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Patent US5409664 - Laminated assay device - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsA laminated assay device for use in determining the presence or amount of an analyte in a sample involving a bibulous assay strip having a sample application zone, a reagent zone and a pair of liquid impervious barriers defining a measurement zone extending from and in fluid communication with the application...http://www.google.com/patents/US5409664?utm_source=gb-gplus-sharePatent US5409664 - Laminated assay deviceAdvanced Patent SearchPublication numberUS5409664 APublication typeGrantApplication numberUS 08/128,373Publication dateApr 25, 1995Filing dateSep 28, 1993Priority dateSep 28, 1993Fee statusPaidAlso published asWO1995009357A1Publication number08128373, 128373, US 5409664 A, US 5409664A, US-A-5409664, US5409664 A, US5409664AInventorsMichael P. AllenOriginal AssigneeChemtrak, Inc.Export CitationBiBTeX, EndNote, RefManPatent Citations (6), Referenced by (43), Classifications (21), Legal Events (4) External Links: USPTO, USPTO Assignment, EspacenetLaminated assay deviceUS 5409664 AAbstract A laminated assay device for use in determining the presence or amount of an analyte in a sample involving a bibulous assay strip having a sample application zone, a reagent zone and a pair of liquid impervious barriers defining a measurement zone extending from and in fluid communication with the application zone. The measurement zone has a volume measuring the amount of sample required for the assay. A substantially nonabsorbent first supporting film extends across and is laminated to the front surface of the assay strip, while a substantially nonabsorbent second supporting film extends across and is laminated to the back surface of the assay strip. The assay strip is impregnated with the members of a signal producing system which, upon reaction with a component in the sample, produce a detectable signal.
What is claimed is: 1. An assay device for performing an assay to determine an analyte in a sample, said device comprising:upper and lower inert supporting films fastened at their edges, said upper film having a sample port and an air vent; positioned between said supporting films at least one bibulous sheet having a width extending substantially the full width of said films; said bibulous sheet comprising an assay strip comprising an application zone for receiving said sample and a separation zone for seperating cells from blood, a reagent zone comprising reagents of a signal producing system for producing a colored product; and a measurement zone comprising reagents of said signal producing system for producing a boundary whose distance along said assay strip is related to the amount of analyte in said sample, wherein at least said measurement zone extends at least a major portion of the length of said bibulous sheet and is defined by liquid impervious barriers and is of substantially narrower width than said bibulous sheet; wherein the absorption capacity of said assay strip determines the amount of sample which is analysed. 2. A device according to claim 1, wherein said at least one bibulous sheet comprises a single sheet comprising said reagent zone and said measurement zone and a second sheet comprising said application zone and said cell separation zone.
TECHNICAL FIELD The field of the subject invention concerns diagnostic assay strips permitting visual measurement of the amount of an analyte in a biological fluid.
BACKGROUND Efficiently and accurately determining the presence or amount of an analyte in a biological sample has become increasingly important. Often, an assay must be performed in a clinical laboratory to obtain an accurate quantitative measurement. When the protocol requires the addition of measured amounts of sample and reagents, a skilled technician must usually perform the assay to guarantee a reliable result. The measurement of an analyte in a biological fluid plays an increasingly important role in the treatment and therapy of numerous medical conditions. The ability to quickly make a qualitative or quantitative determination, in the home or doctor's office, of the presence or amount of an analyte in a sample is of great interest.
Relevant Literature U.S. Pat. Nos. 4,987,085, 4,973,549, 4,999,287, 5,132,086, 5,215,886, 5,234,813 and the references cited therein.
SUMMARY OF THE INVENTION The present invention involves methods and apparatus for use in detecting the amount of an analyte in a biological sample by using a laminated bibulous assay strip impregnated with the members of a signal producing system. The device will have primarily three layers, upper and lower plastic support layers having appropriate openings for sample application, viewing and an air vent and an intermediate bibulous layer with at least one narrow channel defined by liquid impervious borders in the bibulous layer. Usually there will be small additional staggered layers for recieving and processing the sample. The absorption volume of the laminated assay strip determines the amount of sample required for the assay. The assay strip has a continuous sample path which provides a measurement of the analyte in the sample, and desirably a continuous control flow path providing for simultaneous verification of the operability of the device. The sample is applied at one end of the assay strip and moves through the strip by wicking action. The reaction of a component in the sample with members of the signal producing system produces a detectable signal downstream of the sample application site. Improved accuracy and efficiency are obtained by having a simultaneous control, impregnating the assay strip with the reagents needed to produce the detectable signal and by having as the only assay step the application of a minimal amount of sample.
BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a front plan view of an assay device according to this invention;
DESCRIPTION OF SPECIFIC EMBODIMENTS Methods and apparatus are provided for the determination of the amount of an analyte in a sample employing a bibulous assay strip with a continuous sample flow path having a sample application zone, a reagent zone and a measurement zone. The device has three primary layers, a lower plastic support, a main bibulous layer having a defined channel for the measurement region, and an upper plastic support having appropriate openings for sample application, air escape and, as appropriate viewing of the measurement region or other appropriate sites.
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TydingsContainer for urine accumulation; liquid impervious backing; contactor wick; selaing strips; drug screeningUS7060192 *May 9, 2002Jun 13, 2006Lifescan, Inc.Methods of fabricating physiological sample collection devicesUS7195921Apr 1, 2004Mar 27, 2007Cholestech CorporationBioassay for measuring serum cholesterol associated with high-density lipoproteins (HDL) in ablood sample; diagnosing coronary artery diseaseUS7303923Sep 10, 2002Dec 4, 2007Diamatrix LimitedBiochemical and immunochemical assay deviceUS7582063Nov 21, 2001Sep 1, 2009Pelikan Technologies, Inc.Blood testing apparatus having a rotatable cartridge with multiple lancing elements and testing meansUS7582484Apr 18, 2005Sep 1, 2009Cholestech CorporationHigh-density lipoprotein assay device and methodUS7795038 *Apr 8, 2003Sep 14, 2010Cholestech CorporationHigh-density lipoprotein assay device and methodUS7803319Apr 29, 2005Sep 28, 2010Kimberly-Clark Worldwide, Inc.Metering technique for lateral flow assay devicesUS7841992Dec 22, 2005Nov 30, 2010Pelikan Technologies, Inc.Tissue penetration deviceUS7858384Apr 29, 2005Dec 28, 2010Kimberly-Clark Worldwide, Inc.for controlling fluid flow in an assay device that employs a membrane; for determining the presence of an analyte within a test sampleUS7935538Dec 15, 2006May 3, 2011Kimberly-Clark Worldwide, Inc.Indicator immobilization on assay devicesUS8062608May 15, 2008Nov 22, 2011Advance Dx, Inc.separation and drying biological fluid blood; perform three tests on one component; prevent risk of container breakage or leakage; dried sample devices can be transported through the mail system, provide accurate patient cholesterol result, simple to manufacture; polyhexamethylene biguanide hydrochlorideUS8124421Dec 15, 2010Feb 28, 2012Kimberly-Clark Worldwide, Inc.Flow control technique for assay devicesUS8173380Aug 31, 2010May 8, 2012Kimberly-Clark Worldwide, Inc.Metering technique for lateral flow assay devicesUS8206992Mar 27, 2009Jun 26, 2012President And Fellows Of Harvard CollegeCotton thread as a low-cost multi-assay diagnostic platformUS8252139Oct 13, 2011Aug 28, 2012Advance Dx, Inc.Method of making a fluid separator collection cardUS8354245 *Sep 16, 2008Jan 15, 2013Alere Scarborough, Inc.Method of assaying glucose-6-phosphate dehydrogenase on a chromatographic test stripUS8377710Apr 16, 2009Feb 19, 2013President And Fellows Of Harvard CollegeLateral flow and flow-through bioassay devices based on patterned porous media, methods of making same, and methods of using sameUS8383058 *Sep 22, 2009Feb 26, 2013Home Access Health CorporationQuantitative analysis of a biological sample of unknown quantityUS8603832Dec 28, 2012Dec 10, 2013President And Fellows Of Harvard CollegeLateral flow and flow-through bioassay devices based on patterned porous media, methods of making same, and methods of using sameUS8628729Mar 27, 2009Jan 14, 2014President And Fellows Of Harvard CollegeThree-dimensional microfluidic devicesUS8821810Feb 3, 2011Sep 2, 2014President And Fellows Of Harvard CollegeDevices and methods for multiplexed assaysEP1271147A1 *Mar 14, 2001Jan 2, 2003Sanwa Kagaku Kenkyusho Co., Ltd.Test paperEP1875241A1 *Jan 19, 2006Jan 9, 2008Kimberly-Clark Worldwide, Inc.Metering technique for lateral flow assay devicesEP2148743A1 *May 15, 2008Feb 3, 2010Advance DX, INC.Fluid separator collection cardWO1998002249A1 *Jul 16, 1997Jan 22, 1998Robert William CunninghamNew test device for mass screeningWO1999049078A1 *Mar 8, 1999Sep 30, 1999Lever Hindustan LtdEnzyme- and immunoassays in surfactant-containing cosmetic cleansersWO2000029111A1 *Aug 18, 1999May 25, 2000Lee JinDevice and methods for single step collection and assaying of biological fluidsWO2009026394A1 *Aug 20, 2008Feb 26, 2009Vanvisa AttasetBody fluid sampling systemsWO2013033727A1 *Sep 4, 2012Mar 7, 2013Nanodetection Technology, Inc.System for chemiluminescence-based detection* Cited by examinerClassifications U.S. Classification422/424, 436/170, 435/970, 436/810, 435/19, 435/805, 435/11, 436/71, 436/178, 436/805, 435/28International ClassificationG01N33/92, G01N33/52Cooperative ClassificationY10S435/805, Y10S436/805, Y10S435/97, Y10S436/81, G01N33/521, G01N33/92European ClassificationG01N33/52B, G01N33/92Legal EventsDateCodeEventDescriptionSep 26, 2006FPAYFee paymentYear of fee payment: 12Sep 24, 2002FPAYFee paymentYear of fee payment: 8Oct 20, 1998FPAYFee paymentYear of fee payment: 4Dec 20, 1993ASAssignmentOwner name: CHEMTRAK, INC., CALIFORNIAFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:ALLEN, MICHAEL P.;REEL/FRAME:006905/0017Effective date: 19931206RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services©2012 Google


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Best home style TexMex going - Review of El Gallito Restaurant, Cathedral City, CA - TripAdvisor
Best home style TexMex going - El Gallito Restaurant
“Best home style TexMex going”
Review of El Gallito Restaurant - CLOSED
Best home style TexMex going
We visit the Palm Springs area on a regular basis, and never miss a chance to eat at El Gallito. Charming historical environment, personable proprietors and staff, fabulous food. Looking forward to our next visit.
1 Thank Snowtravelers
The restaurant is located in a very plain & older building but has good atmosphere. This was our second visit here and as before we found the food to be very good as was the service. Everything was very fresh and we will be back again on our next trip to Palm Springs.
1 Thank Rayhar
Authentic Mexican Food, lard in everything though
We weren't able to eat here because my partner is vegan, and there was nothing on the menu that didn't have lard in it. Hence vegetarians and vegans are not catered to here. At least they admitted it and we opted to eat elsewhere. Lots of great reviews though, very authentic, and if you don't do eat lard often, or don't have to watch your cholesterol, enjoy! They need to expand their menu if they want more business, especially ours.
1 Thank RFrancis
noroeste62
Excellent!!! ¡Excelente!
El Gallito is a place we must visit when we go to PS. I love the chile verde and when I'm back home and I'm hungry I salivate when I think about it. I trully believe that those few bad reviews are from envious people because the staff at El Gallito are friendly and always ready to service their customers. I've been visiting the place since 2000 and it has never disapppointed me.
1 Thank noroeste62
Great off the beaten path worth a visit
This little hole in the wall just off Palm Canyon in Cathedral City is worth a visit if you like casual home made mexican cuisine for inexpensive prices, along with a cold beer. We ate their tonightt and had enchilados and tacos with guacomole and a corona. The price for two was $34. They only accept cash. It's the perfect spot for a quick tasty bite if you're catching a movie at the Mary Pickford.
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Patent US20070237030 - Systems and methods for determining shooter locations with weak muzzle detection - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inPatentsSystems and methods for locating the shooter of supersonic projectiles are described. The system uses at least five, preferably seven, spaced acoustic sensors. Sensor signals are detected for shockwaves and muzzle blast, wherein muzzle blast detection can be either incomplete coming from less than 4...http://www.google.com/patents/US20070237030?utm_source=gb-gplus-sharePatent US20070237030 - Systems and methods for determining shooter locations with weak muzzle detectionAdvanced Patent SearchPublication numberUS20070237030 A1Publication typeApplicationApplication numberUS 11/210,295Publication dateOct 11, 2007Filing dateAug 23, 2005Priority dateAug 23, 2005Also published asUS7359285, US7710828, US8005631, US20080159078, US20080162089Publication number11210295, 210295, US 2007/0237030 A1, US 2007/237030 A1, US 20070237030 A1, US 20070237030A1, US 2007237030 A1, US 2007237030A1, US-A1-20070237030, US-A1-2007237030, US2007/0237030A1, US2007/237030A1, US20070237030 A1, US20070237030A1, US2007237030 A1, US2007237030A1InventorsJames Barger, Stephen Milligan, Marshall Brinn, Richard MullenOriginal AssigneeBbnt Solutions LlcExport CitationBiBTeX, EndNote, RefManPatent Citations (23), Referenced by (14), Classifications (7), Legal Events (7) External Links: USPTO, USPTO Assignment, EspacenetSystems and methods for determining shooter locations with weak muzzle detection
US 20070237030 A1Abstract
Systems and methods for locating the shooter of supersonic projectiles are described. The system uses at least five, preferably seven, spaced acoustic sensors. Sensor signals are detected for shockwaves and muzzle blast, wherein muzzle blast detection can be either incomplete coming from less than 4 sensor channels, or inconclusive due to lack of signal strength. Shooter range can be determined by an iterative computation and/or a genetic algorithm by minimizing a cost function that includes timing information from both shockwave and muzzle signal channels. Disambiguation is significantly improved over shockwave-only measurements. Images(5) Claims(22)
1. A method for estimating a shooter range by detecting shock wave and muzzle blast, comprising: measuring shockwave-only signals at a plurality of spaced acoustic sensors forming an antenna; measuring a muzzle blast signal at the plurality of acoustic sensors; determining from the measured shock wave and muzzle blast signals an initial estimate of the shooter range; assuming an initial bullet velocity and a bullet drag coefficient; and iteratively computing an instantaneous bullet velocity along a bullet trajectory to obtain an updated shooter range. 2. The method of claim 1, wherein iteratively computing comprises performing a predetermined number of iterations. 3. The method of claim 1, wherein determining the initial shooter range includes computing a time-difference-of-arrival (TDOA) between the shockwave-only signals and the muzzle blast signals, and an arrival angle. 4. The method of claim 1, wherein iteratively computing comprises defining a convergence criterion and accepting the updated shooter range as a final shooter range if a relationship between successively determined updated shooter ranges satisfies the convergence criterion. 5. The method of claim 4, wherein the relationship between successively determined updated shooter ranges is a difference between the successively determined updated shooter ranges. 6. The method of claim 4, wherein the relationship between successively determined updated shooter ranges is a percentage change between the successively determined updated shooter ranges. 7. The method of claim 1, wherein the computed bullet velocity is set to the speed of sound if the computed bullet velocity is less than the speed of sound. 8. The method of claim 1, wherein the updated shooter range is considered invalid if a bullet trajectory angle and an arrival angle are greater than a predetermined value. 9. The method of claim 8, further including, if the updated shooter range is invalid, applying a genetic algorithm (GA) by: defining an initial population of the GA, the population having a predetermined number of individuals, each individual represented by a 3-tupel which includes an assumed shooter range, a missed azimuth (MA) and a missed elevation (ME) of the bullet trajectory; performing the GA for a predefined number of generations; computing residuals for the individuals in each generation; and selecting in each generation the solution having the smallest residual as the individual which survives unmutated. 10. The method of claim 9, and further including the step of selecting, after the predefined number of generations have been performed, the solution having the smallest residual as the updated shooter range. 11. The method of claim 9, further comprising for each 3-tupel in a generation, performing a predetermined number of iterations to compute a revised shooter range, wherein the residuals for the individuals in each generation are computed with the revised shooter range. 12. The method of claim 9, wherein applying the GA comprises applying crossover and mutation operators to the population in a generation. 13. The method of claim 12, wherein applying the crossover operator includes exchanging at least one of missed azimuth and missed elevation between two individuals from the population in a generation. 14. The method of claim 12, wherein the mutation operator comprises field-mutation, incremental mutation, and no mutation. 15. The method of claim 14, wherein the field-mutation operator replaces a value of the 3-tupel with a randomly selected value. 16. The method of claim 14, wherein the incremental mutation operator induces a small mutation in all fields of the 3-tupel. 17. The method of claim 14, wherein the no-mutation operator leaves the individuals in a generation unaltered. 18. A method for disambiguating a projectile trajectory from shockwave signals and a limited number of muzzle blast signals, comprising: measuring shockwave-only signals at five or more spaced acoustic sensors forming an antenna; measuring muzzle blast signals on at most four of the sensors; determining from the shockwave signals Time-Differences-Of-Arrival (TDOA) information for sensor pairs; performing for a predefined number of generations a genetic algorithm with an initial population that includes a predetermined number of individuals, each individual represented by a 4-tupel which includes shooter azimuth, shooter elevation, missed azimuth and missed elevation; computing residuals for the individuals in each generation, said residuals including a least-square fit of a combination of TDOA shockwave and muzzle blast signals; and if a ratio of the solution having the smallest residual and its ambiguous alternate solution is greater than a predefined value, designating the solution having the smallest computed residual as the disambiguated projectile trajectory. 19. A method for extracting a signal from a muzzle wave in the presence of a shockwave signal, comprising: defining a time window having a width corresponding to a time required for a muzzle wave to traverse a sensor array; detecting the shockwave signal; after detection of the shockwave signal, advancing the window and measuring total energy received in the window as a function of time; and associating a maximum of the measured total energy with the muzzle signal. 20. The method of claim 19, wherein measuring the total energy includes integrating the measured energy over the window. 21. The method of claim 19, further including identifying shockwave echoes and disregarding portions in the detected signal caused by the shockwave echoes. 22. The method of claim 19, further including determining a peak signal value in the window producing the maximum total energy and identifying the peak signal value as the muzzle signal, if the peak signal value is greater than the measured total energy in the window by a predefined ratio factor.
BACKGROUND OF THE INVENTION [0001] The present invention relates to law enforcement technologies and security, and more particularly to methods and systems for determining the origin and direction of travel of supersonic projectiles based on shockwave and muzzle sound information. The methods and systems are capable of determining and disambiguating shooter locations even for large distances between shooter and sensor and when the signal from the muzzle sound is weak. [0002] Systems and methods are known that can determine the general direction and trajectory of supersonic projectiles, such as bullets and artillery shells by measuring parameters associated with the shockwave generated by a projectile. One such system, described in U.S. Pat. No. 5,241,518 includes at least three spaced-apart sensors, with each sensor incorporating three acoustic transducers arranged in a plane. The sensors generate signals in response to the shockwave which are related to the azimuth and elevation angle to the origin of the shockwave. However, shock-wave-only measurements are unable to determine the distance between the sensor(s) and the origin of the shockwave. With additional information from the muzzle blast, an accurate location of the origin of the projectile and a line of bearing to the origin of the projectile can be determined. However, when the muzzle blast is masked, shadowed or otherwise distorted, the signal from the muzzle blast may be difficult to discern from spurious signals and noise, so that the derived distance information may become inaccurate. Moreover, even if a clearly discernable muzzle blast signal were received from distant shooter locations, determining the range (distance) of the shooter can still remain a problem. [0003] Conventional systems employ acoustic sensors, e.g., microphones, which can be relatively closely spaced (e.g., 1 meter apart) or widely dispersed (e.g., mounted on a vehicle or carried by soldiers on a battlefield), and measure shockwave pressure omni-directionally at their respective locations. [0004] The azimuth angle, elevation angle, and range of a shooter with reference to the sensor location can be determined by measuring Time-of-Arrival (TOA) information of the muzzle signal and shockwave signal at each sensor. Each of the sensors encounters these signals at a different time and generates an electric signal in response to the shockwave pressure. The signals from the various sensors are processed, and a direction (azimuth and elevation) from the sensor(s) to the origin of the shockwave as well as the range, and hence the trajectory of the projectile can be determined. [0005] Conventional algorithms require at least 4 shockwave and muzzle detections so that a 4�4 matrix can be inverted to map a plane wave on the shockwave TOA. Small errors in shock and muzzle TOA determination can produce substantial errors in the range estimations. Moreover, the conventional algorithms assume a constant bullet speed along the bullet trajectory, which gives inaccurate range estimates for long-range shots being fired from a distance of more than approximately 300 m. [0006] Accordingly, there is a need for rapidly converging algorithms capable of accurately estimating a distant shooter range. [0007] In addition, there is a need to disambiguate shock-wave only solutions for the shooter direction. This is typically accomplished by using the muzzle signal. Disadvantageously, however, less than 4 muzzle sounds may be detected in many situations, for example, due to extraneous noise, reflections, etc., that can mask the muzzle signal. It would therefore be desirable to provide a method for reliably disambiguating shock-wave only solutions even if muzzle blast signals are detected on less than 4, for example 2 or 3, acoustic sensors. [0008] In some situations, an initially detected muzzle signal may be discarded as being unreliable, for example, because the detection level is too low to indicate a muzzle blast signal; or because the muzzle energy is not readily evident in the raw signal; or because echoes from the shockwave are stronger than the muzzle blast and arrive earlier than the actual muzzle blast, causing the detection system to falsely identify shock as muzzle. These uncertain muzzle blast signals, if properly identified and extracted, may still be useful for refining detection of the shooter position, in particular in conjunction with the detection of shock-wave signals. [0009] It would therefore also be desirable to provide a method for extracting muzzle signals that may be obscured by acoustic signatures unrelated to the muzzle blast. SUMMARY OF THE INVENTION [0010] The invention addresses the deficiencies of the prior art by, in various embodiments, providing methods and systems for estimating shooter range for long-range shots, in particular, when muzzle signals are either weak or detected in an insufficient number of detection channels. The disclosed methods and systems also improve disambiguation of shockwave-only shooter trajectory solutions by including detected muzzle sound in the optimization process. [0011] According to one aspect of the invention, in a method for estimating a shooter range by detecting shock wave and muzzle blast, shockwave-only signals as well as muzzle blast signals are measured at a plurality of spaced acoustic sensors forming an antenna. An initial shooter range is estimated from the measured shock wave and muzzle blast signals, assuming an initial bullet velocity and a bullet drag coefficient. The instantaneous bullet velocity along a bullet trajectory is iteratively computed to obtain an updated shooter range. The number of muzzle blast detection channels is usually less than the number of shockwave detection channels. [0012] Advantageous embodiments may include one or more of the following features. A time-difference-of-arrival (TDOA) between the shockwave-only signals and the muzzle blast signals and an arrival angle are computed for determining the initial shooter range. A certain number of iterations may be performed, or the updated shooter range will be considered to be the final shooter range if a relationship between successively determined updated shooter ranges satisfies the convergence criterion. For example, the convergence criterion may be selected so that the difference between the successively determined updated shooter ranges or a percentage change between the successively determined updated shooter ranges is smaller than a predetermined value. To obtain real solutions, the computed bullet velocity is set to always be at least the speed of sound. The solutions are checked for consistency. For example, the updated shooter range is considered invalid if a bullet trajectory angle and an arrival angle are determined to be greater than a predetermined value. [0013] Even if the computed shooter range is determined to be invalid, a solution may still be obtained by applying a genetic algorithm (GA). For example, an initial population of the GA with a predetermined number of individuals can be defined, where each individual is represented by a 3-tupel which includes an assumed shooter range, a missed azimuth (MA) and a missed elevation (ME) of the bullet trajectory. The GA is performed for a predefined number of generations, and residuals for the individuals in each generation are computed. In each generation the solution with the smallest residual is selected as the individual which survives unmutated. The solution having the smallest residual is selected as the updated shooter range. The solution can be refined by performing for each 3-tupel in a generation a predetermined number of iterations to compute a revised shooter range, wherein the residuals for the individuals in each generation are computed with the revised shooter range. [0014] The GA includes crossover and mutation operators. The crossover operator exchanges at least one of missed azimuth and missed elevation between two individuals from the population in a generation, whereas the mutation operator comprises field-mutation (replacing a value of the 3-tupel with a randomly selected value), incremental mutation (inducing a small mutation in all fields of the 3-tupel), and no mutation (leaving the individuals in a generation unaltered). [0015] According to yet another aspect of the invention, a method for disambiguating a projectile trajectory from shockwave signals and from a limited number of muzzle blast signals includes measuring shockwave-only signals at five or more spaced acoustic sensors forming an antenna, measuring muzzle blast signals on at most 4 of the sensors, and determining from the shockwave-only signals Time-Differences-Of-Arrival (TDOA) information for sensor pairs. The method further includes performing for a predefined number of generations a genetic algorithm with an initial population that includes a predetermined number of individuals, each individual represented by a 4-tupel which includes shooter azimuth, shooter elevation, missed azimuth and missed elevation, and computing residuals for the individuals in each generation, with the residuals including a least-square fit of a combination of TDOA shockwave and muzzle blast signals. If a ratio of the solution having the smallest residual and its ambiguous alternate solution is greater than a predefined value, the solution having the smallest computed residual is designated as the disambiguated projectile trajectory. [0016] According to another aspect of the invention, a method for extracting a signal from a muzzle wave in the presence of a shockwave signal includes defining a time window having a width corresponding to a time required for a muzzle wave to traverse a sensor array and detecting the shockwave signal. Following detection of the shockwave signal, the window is advanced in time and the total energy received in the window is measured as a function of advance time. The maximum of the measured total energy is associated with the muzzle signal. [0017] In advantageous embodiments, the total energy can be determined by integrating the measured energy over the window, preferably disregarding portions in the detected signal caused by shockwave echoes. Advantageously, the peak signal value can be determined in the window producing the maximum total energy and if the peak signal value is greater than the measured total energy in the window by a predefined ratio factor, the peak signal value can be identified as being related to the muzzle signal. [0018] Further features and advantages of the invention will be apparent from the following description of illustrative embodiments and from the claims.
BRIEF DESCRIPTION OF THE DRAWINGS [0019] These and other features and advantages of the invention will be more fully understood by the following illustrative description with reference to the appended drawings, in which elements are labeled with like reference designations and which may not be to scale. [0020] FIG. 1 is a schematic diagram of a shockwave Time-of-Arrival (TOA) model; [0021] FIG. 2 shows a schematic process flow diagram for range estimation; [0022] FIG. 3 shows a schematic process flow diagram of a genetic algorithm for range estimation; and [0023] FIG. 4 shows a schematic process flow diagram of a genetic algorithm for disambiguating between shooter trajectories.
DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS [0024] As described above in summary, the invention provides, in various embodiments, methods and systems for shooter range estimation and disambiguation of projectile trajectories. These systems and method are particularly useful and advantageous, when an insufficient number of parameters required for an accurate solution are detected or when such parameters cannot be detected reliably. [0025] FIG. 1 shows schematically a diagram of a Time of Arrival (TOA) model, which is described in more detail in U.S. Pat. No. 6,178,141 (incorporated herein by reference in its entirety). The TOA model can be used to estimate the trajectory of the projectile and the shooter direction relative to the sensor location. The TOA model is based on a ballistic model taking into account certain physical characteristics relating to the projectile's flight path, such as the air density (which is related to temperature); the position {right arrow over (P)} (Px, Py, Pz) of a shooter; the azimuth and elevation angles of the rifle muzzle; the muzzle velocity of the projectile (or equivalent Mach number); and the speed of sound (which varies with temperature/air density). With this ballistic model, it is possible to accurately calculate the time at which the shockwave and muzzle blast reach a particular point in space. [0026] As depicted in the diagram of FIG. 1, the shooter is located at point {right arrow over (P)} (PX, PY, PZ) relative to an origin (0, 0, 0), the various sensors are located at points {right arrow over (S)}j (Sxj, Syj, Szj), and the bullet trajectory is shown as emanating from the shooter in the direction of {right arrow over (A)}. The vector from the shooter to the jth sensor is {right arrow over (D)}, the closest point of approach (CPA) of the bullet to the jth sensor is |{right arrow over (R)}|=|{right arrow over (D)}| sin(β), and the path followed from the point where the shockwave is radiated from the trajectory to the jth sensor is {right arrow over (S)} (the index j of the sensors has been omitted). The Mach angle of the bullet is θ=sin−(1/M), M=V/c0. M is the Mach number of the projectile, V is the supersonic velocity of the projectile, and c0 is the (pressure- and temperature-dependent) speed of sound. The ‘miss-angle’ between trajectory and the jth sensor is β. The trajectory is characterized by its azimuth angle measured counter-clockwise from the x-axis in the x-y plane and by its elevation angle measured upward from the x-y plane. The equations that define the shockwave arrival time tj and unit vector at the jth sensor are written in terms of these geometrical quantities. [0027] The time of arrival is equal to the time  A ->  V it takes for the projectile to travel the distance |{right arrow over (A)}| to the point were sound is radiated toward the jth sensor, plus the time it takes the shockwave to travel the distance |{right arrow over (S)}| from the radiation point to the jth sensor,  S ->  c 0 . t j = t 0 +  A  V +  S  c 0 = t 0 +  D  c 0 sin ( β + θ ) , ( 1 ) [0028] wherein t0 is a time reference (firing time) and c0 is the speed of sound. The Mach angle θ is also indicated in FIG. 1. [0029] It can be safely assumed that the velocity V of the projectile remains constant over a distance corresponding to the sensor spacing, so that there is insignificant loss of speed between the times the projectile radiates to the different sensors. However, over longer distances projectiles are known to slow down due to air resistance. The air resistance can be expressed by a drag coefficient Cb which depends on the bullet shape and bullet caliber. A mathematical ballistics model derived from physical principles can predict the arrival time of a shockwave at any general point in space as a function of a full set of parameters describing the projectile (e.g., by its drag coefficient Cb), its initial velocity, and the density of the surrounding air are known in advance. [0030] The parameters required for an exact calculation are typically not known in a realistic setting, such as a battlefield. However, range estimation can be significant improved by an iterative process shown in form of a process flow diagram 20 in FIG. 2, which takes into account deceleration of the projectile velocity along the trajectory. The process 20 begins at step 202 with the following assumptions: [0031] c0=speed of sound modified for outside temperature/ air pressure (≈340 m/s) [0032] Cb=nominal drag coefficient averaged over anticipated weapons [0033] V0=initial velocity of the projectile, when fired, averaged over anticipated weapons [0034] M0=V0/c=initial Mach number of projectile [0035] A first estimate of the shooter distance D0 is computed in step 204 using the measured time-difference-of-arrival (TDOA) τms and an arrival angle α between shock and muzzle sound at the sensor array and by assuming an initial, constant speed V0 and Mach number M0, according to the equation D 0 = τ ms � c 0 1 - cos ( α ) ( 2 ) [0036] With these assumptions, the projectile's speed at a distance a from the shooter position {right arrow over (P)} can be computed in step 206 from the equation M a = M 0 ( 1 - a C b V 0 ) 2 ( 3 ) so that the time the projectile travels the distance a along the trajectory becomes, step 208, T a = a V 0 - a � V 0 C b ( 4 ) The angle θ is related to the Mach number Ma by the equation sin ( Θ ) = 1 M a ( 5 ) [0037] wherein the Mach number Ma is initially set to M0. It should be noted that the instantaneous bullet velocity is set to the speed of sound (i.e., Ma=1) if the computed bullet velocity becomes less than the speed of sound. The revised distance a=|{right arrow over (A)}| in step 210 then becomes a = D 0 � cos ( β ) � ( 1 - tan ( β ) M a 2 - 1 ) . ( 6 ) [0038] The angles α, β, and θ are related by the equation (α+β+θ)=90�. The process 20 then loops back to step 206 by inserting the computed value for the distance a in equations (3) and (4), yielding an updated Mach number Ma and an updated bullet travel time Ta, respectively, for the traveled distance a. The measured TDOA τms and the computed updated values for Ta and a are then used to successively update the value D for the shooter range: D=c 0�(τms +T α)+s (7) [0039] This process is repeated until either a maximum number of iterations has been reached or the range values D converge, as determined in step 212. [0040] The process 20 also checks in step 214, if the revised range value D=|{right arrow over (D)}| for the distance between the shooter and the sensor array is a “reasonable” value, in which case the process 20 terminates at step 216. For example, the value for D can be considered valid if the distance a traveled by the projectile and the distance s = a � sin ( β ) sin ( α ) between the sensor and the point where the sound wave is radiated from the projectile to the sensor are valid number values, i.e., not a NAN. A NAN is a special floating point value representing the result of a numerical operation which cannot return a valid number value and is typically used to prevent errors from propagating through a calculation. In addition, α and β should both be less than a predetermined threshold value, indicating that the projectile was indeed fired toward the sensor array. [0041] As mentioned above, the number pair (τms, α) is initially used to compute the shooter range D0 in zeroth approximation, neglecting change in the projectile's speed along the trajectory. If the iterative process 20 described above does not return a consistent geometry supporting the number pair (τms, α), then the solution is discarded. [0042] Even if an exact solution may not be obtainable, it is a goal to find values for the shooter range D and the missed azimuth and elevation angles (which are related to β) that most closely match a measured shock TDOA and a measured muzzle TDOA. As already mentioned, the shockwave-only TDOA's between the various sensors can in most situations be reliably measured. The shooter azimuth and shooter elevation, but not the shooter range, can be determined from the shockwave-only TDOA's using the known sensor array coordinates (Sxj, Syj, Szj). It will be assumed that the TDOA τms between the detected shockwave and the muzzle sound can also be measured, whereby the muzzle sound may not be detected by all the sensors. [0043] If it is determined in step 214 that the iterative process 20 does not return a valid result, then the process 20 attempts to compute the shooter range by invoking an evolutionary genetic algorithm (GA) 30. GA's mimic natural evolutionary principles and apply these to search and optimization procedures. A GA begins its search with a random set of solutions, instead of just one solution. Once a random population of solutions is created, each is evaluated in the context of the nonlinear programming problem and a fitness (relative merit) is assigned to each solution. In one embodiment, the fitness can be represented by the Euclidean distance between a calculated solution and the measured solution, for example, by Δ τ min = ∑ j = 1 N ( τ Shock , calc j - τ Shock , meas j ) 2 N + abs ( ∑ i = 1 N ( τ ms , calc i M ) - τ ms , meas ) ( 8 ) [0044] Intuitively, an algorithm producing a smaller value of Δτmin is better. [0045] A schematic flow diagram of the GA process 30 is shown in FIG. 3. The process 30 uses the time-difference-of-arrival (TDOA) τms and the arrival angle α measured previously for process 20, step 302. An exemplary number of 3-tupes having the values {RANGE, MA, ME} is defined as an initial population, step 304, wherein RANGE is the shooter range D=|{right arrow over (D)}| shown in FIG. 1, MA is the missed azimuth, and ME is the missed elevation. The MA and ME values indicate by how much the bullet missed the target in azimuth and elevation space. The target in the illustrate example is assumed to be the sensor array. The initial population in step 304 is created by random selection of the 3-tupel spanning a meaningful and reasonable range of values: RangeShooter={1000, . . . , 3000} [meter], Azimuthmissed={−20, . . . , 20} [degrees], and ElevationMissed={−20, . . . , 20} [degrees]. [0046] The computation essentially follows the same process as outlined above. Initially, for generation Gen=0, step 306, the shooter position vector {right arrow over (P)} (Px, Py, Pz) is computed for each 3-tupel with the previously determined shooter azimuth and elevation, and an assumed RANGE for the particular 3-tupel. Assuming an initial Mach number M0, the vector {right arrow over (A)} (Ax, Ay, Az), i.e. the position from where the shock sound is radiated, is computed with the MA and ME values for each 3-tupel, step 308. The distances {right arrow over (D)}={right arrow over (S)}j−{right arrow over (P)} between the shooter and each sensor j that detects a shockwave are also computed. [0047] For each 3-tupel, the angle β is computed from the equation cos β = A → � ( P → - S → )  A →  �  P → - S →  , wherein the symbol “•” indicates the scalar product between the two vectors. Updated values for the distance a, the travel time Ta of the projectile over the distance a, and the Mach number Ma are computed by inserting the computed value for β and the initially assumed values for Ma=M0 and a into equations (3), (4), (6), and (7), step 312. This process is iterated several times for each of the 3-tupels, for example 3 times, as determined in step 312, whereafter the residual defined in equation (8) is computed for each 3-tupel, step 314. [0048] It is checked in step 316 if a maximum number of iterations for the GA, for example 25 iterations, have been reached. If the maximum number of iterations has been reached, then the process 30 stops at step 320, returning the 3-tupel with the smallest residual. Otherwise, the process 30 creates a new population through a crossover and mutation operation, step 318, and the generation counter is incremented by one, step 322 [0049] In each generation, the “best” individual is allowed to survive unmutated, whereas the top 100 individuals, as judged by their fitness, also survive, but are used to create the next 100 individuals from pairs of these survivors with the crossover/mutation operators listed in Table 1 below. [0050] The following exemplary crossover and mutation operators were used to demonstrate the process 30: TABLE 1 Operator Operator Name Type Probability Description Missed Azimuth- Crossover 0.5 Exchange missed azimuth between two Crossover chromosomes Missed-elevation Crossover 0.5 Exchange missed elevation between Crossover two chromosomes Missed-range Crossover 0.5 Exchange range between two Crossover chromosomes Field-Mutation Mutation 0.3 Replace a given field (with a probability of 0.25 per field) with a randomly selected new value within range Incremental-Mutation Mutation 0.4 Introduce small perturbations in all fields of a chromosome (within �2 meter for shooter range; within �0.1� for missed azimuth and elevation) [0051] The GA process 30 is executed with an initial population of 200 different 3-tupels, with a refill rate of 50, for a total of 25 generations. The GA is run 5 times in parallel with different sets of initial 3-tupels, and the solution with the smallest residual is selected as the final solution for the RANGE, missed azimuth, and missed elevation of the shooter, which allows computation of vector {right arrow over (D)}. [0052] Calculations that do not take into consideration the deceleration of the projectile along its path due to air resistance tend to overestimate range. For certain geometries and sufficiently distant shots, this overestimation may exceed 20%. The aforedescribed process removes this bias from range estimation for long-range shot detections. [0053] Although shock-wave only solutions may be ambiguous, they can frequently be disambiguated by comparing the residuals from two different trajectories and selecting the trajectory with the smaller residual. [0054] The residual of the shockwave-only solution can be defined as Δτ min = ∑ j ( Δτ Shock , calc j - Δτ Shock , meas j ) 2 ( 9 ) [0055] summed over all sensors j. The solution with the smallest value for Δτmin is selected as the most likely solution for the shooter direction. The precision of disambiguation can be improved, for example, by employing a genetic algorithm GA of the type disclosed, for example, in commonly assigned U.S. patent application Ser. No. 10/925,875. [0056] If the muzzle blast signals are detected on 4 or more sensor channels, then the aforedescribed shock-muzzle algorithms can be used to unambiguously determine the shooter location, regardless of the number of shock channels. If the muzzle blast signals are detected in fewer than 4 sensors, but shockwave signals are detected in 5 or more shockwave channels, then the aforementioned GA can be used with a modified cost function or residual, whereby whatever muzzle signals are available are “mixed” into the optimization function to disambiguate the shockwave-only solution and/or refine the estimation of the shooter range. However, if fewer than 3 muzzle channels AND fewer than 5 shockwave channels are detected, then an alert can be activated without attempting to localize the shooter. [0057] The muzzle signal may not be reliably detected on all channels, because: 1. The detection level on one or more channels is too low to detect with confidence. 2. The muzzle energy is not discernable in the raw signal, causing the system to correlate with ‘noise’, giving unreliable TDOA estimates. 3. Echoes from the shockwave can be stronger than the muzzle blast and can arrive earlier than the muzzle blast, causing the system to falsely detect shock as muzzle. [0061] With a muzzle blast signal only detected on some channels, the residual in this situation can be defined as Δ τ min = ∑ i ( Δτ muzzle , calc i - Δτ muzzle , meas i ) 2 + ∑ j ( Δτ Shock , calc j - Δτ Shock , meas j ) 2 , ( 10 ) [0062] wherein the first term for the muzzle blast is summed over the reduced number of sensors (<4) that detect the muzzle blast, and j is summed over the sensors detecting the shockwave (typically all sensors). [0063] When applying the GA to disambiguate the shooter direction and projectile trajectory under these circumstances, the exemplary GA uses as a chromosome an initial population of 200 4-tupels, with each 4-tupel containing the following values: [AzimuthShooter, ElevationShooter, AzimuthMissed, ElevationMissed]. [0064] The values [AzimuthShooter, ElevationShooter] are defined by the angle (90�−(θ+β)), while the values [AzimuthMissed, ElevationMissed] are defined by the angle β (see FIG. 1). An initial range of, for example, 1000 m can be assumed for the shooter range. [0065] The initial population is created by random selection of the 4-tupels spanning a meaningful and reasonable range of values (all values are in degrees): AzimuthShooter={0, . . . , 360}, ElevationShooter={−10, . . . , 30}, AzimuthMissed={−20, . . . , 20}, and ElevationMissed={−20, . . . , 20}. [0066] A schematic flow diagram of the GA process 40 is shown in FIG. 4. The GA process 40 begins its search by initializing a random population of solutions, step 402, and sets a generation counter to zero indicating the initial solution set, step 404. Once a random population of solutions is created, each is evaluated in the context of the nonlinear programming problem, step 406, and a fitness (relative merit) is assigned to each solution, step 408. The fitness can be represented by the residual Δτmin between a calculated solution and the measured solution, as described above. It is checked in step 410 if a maximum number of iterations for the GA, which can be set, for example, to 25, has been reached. If the maximum number of iterations has been reached, the process 40 stops at step 420, and the result can be either accepted or further evaluated. Otherwise, step 412 checks if preset fitness criteria have been satisfied. [0067] Fitness criteria can be, for example, a computed missed azimuth of <15� and/or a ratio of the residuals of two ambiguous solutions. If the fitness criteria are satisfied, the process 40 stops at step 420; otherwise, a new population is created through crossover/mutations, step 414, and the generation counter is incremented by one, step 416. [0068] In each generation, the “best” individual is allowed to survive unmutated, whereas the top 100 individuals, as judged by their fitness, also survive, but are used to create the next 100 individuals from pairs of these survivors with the crossover/mutation operators listed in Table 2. [0069] The following exemplary crossover and mutation operators were used to demonstrate the process 40: TABLE 2 Operator Operator Name Type Probability Description Azimuth-Crossover Crossover 0.5 Exchange shooter/trajectory azimuth between two chromosomes Missed-Crossover Crossover 0.5 Exchange missed azimuth/elevation between two chromosomes Field-Mutation Mutation 0.3 Replace a given field (with a probability of 0.25 per field) with a randomly selected new value within range Incremental-Mutation Mutation 0.4 Introduce small mutations in all fields of a chromosome (within ≦2� for shooter information; within ≦0.5� for missed information Flip-Mutation Mutation 0.1 Change the solution into the ambiguous alternate solution No-Mutation Mutation 0.2 Chromosome remains intact [0070] Recent experimental trials indicated a decrease of ambiguous shots from 95% to 8% on the same data set by using at least one muzzle signal channel in addition to 5 or more shockwave channels. [0071] As demonstrated by the examples described above, the muzzle blast signal provides important information about the shooter azimuth and hence the projectile's trajectory as compared to a shockwave-only solution, so that the computed trajectory solution aligns more closely with one of the ambiguous solutions, i.e., thus disambiguating the solutions. [0072] Without at least some reliable muzzle signals, a significant number of ambiguous shockwave-only solutions may be generated in particular at long shooter distances, which are less desirable than a smaller number of unambiguous, but less precise solutions. [0073] In the event of potentially unreliable muzzle detection, an attempt can still initially be made to detect muzzle signals, e.g., to find a muzzle blast signature in a noisy signal, and to compute the resulting TDOA's. The muzzle detection will be deemed to be reliable if muzzle signals are found on a sufficient number of sensor with sufficient cross-correlation between the channels, and if there is a sufficiently strong correlation between the muzzle signal and the corresponding raw band on each channel (offset by a number of bins to account for filter delays). [0074] Otherwise, at least the muzzle signals that show insufficient correlation are erased, and the following ‘coarse muzzle detection’ logic is invoked: Look for peaks in the shock energy following a shock. Flag these peaks as likely ‘shock echoes’, thereby excluding them as muzzle blasts. Determine a maximum time it would take the muzzle wave to traverse the sensor array and define a “window” having the corresponding duration. Search for muzzle energy peaks by moving this window across substantially all detector channels following the detected shockwave, skipping sections in the detected signal which have been identified as shock echoes. Integrate the energy over the window, i.e., seek the maximum of: f ( i ) = ∑ n = 0 N ∑ j = 0 W ( mb i + j n ) 2 ( 11 ) [0077] wherein the square of mbi+j n represents a measure of energy, e.g., energy of the muzzle blast, measured by the nth sensor. (i+j) indicates the detection channel, with i denoting a discrete time interval between the time the shockwave was detected and the beginning of the window, and j represents a time interval measured from the start of the window. [0078] To discriminate against noise, the peak energy in the window producing the maximum of function fmax(i) in equation 11 is checked to determine if the energy peak at that maximum is greater than the energy across the window by a given ratio factor. If this is the case, then the signal in the window is identified as a muzzle detection, and cross-correlation is performed on all channels in the muzzle blast band mb to determine muzzle TDOA's. [0079] The detected muzzle blast signal can then be used to determine the shooter range and/or disambiguate the shockwave signal, as described above. [0080] While the invention has been disclosed in connection with the preferred embodiments shown and described in detail, various modifications and improvements thereon may be made thereto without departing from the spirit and scope of the invention. By way of example, although the illustrative embodiments are depicted as having acoustic sensors, such as microphones, this need not be the case. Instead, other types of pressure-sensitive mechanical or electrical sensors may be used. Moreover, the values given in Tables 1 and 2 for the various operators are intended to be examples only, and other values may be selected depending on the actual conditions in the field. Accordingly, the spirit and scope of the present invention is to be limited only by the following claims.
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Set travel guestbook and wedding ring.
Set "travel" guestbook and wedding ring.
Wooden box holder, "Voyage" chocolate brown effect aged (damaged).
Old leather strappy faux leather effect Crackle, caramel color.
Travel themed stickers.
Interior faux leather with small beige cord to attach the rings.
Metal embellishment in the shape of airplane.
Possibility to write your names on request.
Album with 25 white leaves, spiral binding, cover in stiff cardboard without window, card stock dimensions: 30 x 21 cm, weight: 128 g/m².
Book is painted with acrylics, way brown leather. Decorated with strips of faux leather, 1.5 cm and "pad travel" stickers. You can read the word "Globe Trotter" painted by hand just underneath with a nice stamp "globe" color gold.
In the Center, a tag made from faux leather can be customized with your names and date of marriage (see photo example).
Poster "Travel"
Postcard "Travel"
Purse-miniklatch "Travel".
Guestbook for wedding anniversary

value: This website is an American e-commerce company focused on handmade or vintage items and craft supplies.


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Revelation Space (Audiobook) by Alastair Reynolds | Audible.com
4 out of 5 stars 3.9 (3,692 ratings)
Good book, but narrator voices all sound the same
The story is good, takes a fair while to get going. I found I really had to pay attention as all the voices sound very similar, which makes it especially hard when the scene changes to a different character during the same chapter. I don't really think all the Russian /French accents are really necessary, I get the idea was to match them to the names, but it didn't work so well in the execution
Confusing reader but good story
The reader made scene and point of view changes confusing, so I was totally lost for the first part of the novel, taking minutes to figure out we had moved to a new character and place.
But his accents were excellent, and otherwise read well.
Story was fascinating
A thoroughly engaging narration with good and seamless voicings. The story, if a bit fantastical for my tastes, is richly scientific. For those who like gothic epic science fictio

value: This website is an American online audiobook and podcast service that allows users to purchase and stream audiobooks and other forms of spoken word content. This content can be purchased individually or under a subscription model where the user receives "credits" that can be redeemed for content monthly and receive access to a curated on-demand library of content.


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P. 1How to Setup Remittance Advice E-mail NotificationHow to Setup Remittance Advice E-mail NotificationRatings: (0)|Views: 4,738|Likes: 16Published by shirin.pathak3362More info:Published by: shirin.pathak3362 on Dec 17, 2011Copyright:Attribution Non-commercialAvailability:Read on Scribd mobile: iPhone, iPad and Android.download as DOCX, PDF, TXT or read online from ScribdFlag for inappropriate content|Add to collectionSee moreSee lesshttps://www.scribd.com/doc/75924360/How-to-Setup-Remittance-Advice-E-mail-Notification03/25/2013pdftextoriginal You're Reading a Free Preview
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Patent US4980793 - Open loop control of solenoid coil driver - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inPatentsAn electronic driver circuit for the open loop control of the energization of a solenoid coil, forming part of an electromagnetic solenoid actuator valve, in response to a control pulse produced by a control circuit and where the predetermined schedules are a function of the inductance and resistance...http://www.google.com/patents/US4980793?utm_source=gb-gplus-sharePatent US4980793 - Open loop control of solenoid coil driverAdvanced Patent SearchPublication numberUS4980793 APublication typeGrantApplication numberUS 07/492,235Publication dateDec 25, 1990Filing dateMar 7, 1990Priority dateApr 29, 1988Fee statusLapsedPublication number07492235, 492235, US 4980793 A, US 4980793A, US-A-4980793, US4980793 A, US4980793AInventorsThomas Glowczewski, Keith B. Carle, Michael R. LindsayOriginal AssigneeChrysler CorporationExport CitationBiBTeX, EndNote, RefManPatent Citations (28), Referenced by (25), Classifications (10), Legal Events (5) External Links: USPTO, USPTO Assignment, EspacenetOpen loop control of solenoid coil driver
US 4980793 AAbstract
1. An electronic driver circuit for open loop control of the energization of a solenoid coil, forming part of an electromagnetic solenoid actuator valve, in response to a control pulse produced by a control circuit, comprising:a microcomputer unit (MCU); a memory to work with the MCU and to store predetermined schedules of solenoid coil energization "ON" time; switching means having a plurality of predetermined states to make or interrupt the current flow to the solenoid coil according to the predetermined schedules an din response to a control pulse; means providing an electrical path for circulating current in the solenoid coil to produce slow decay of the current through the solenoid coil in response to tone of said plurality of predetermined states of said switching means; and means for producing a rapid decay of current through the solenoid coil in response to another of said plurality of predetermined states of said switching means to allow the MCU to rapidly turn off the solenoid coil. 2. The circuit of claim 1 where the predetermined schedules are a function of the inductance and resistance of the coil.
Patent CitationsCited PatentFiling datePublication dateApplicantTitleUS3876028 *Apr 14, 1972Apr 8, 1975Aisin SeikiSystem for controlling automatic transmission of vehicleUS3881368 *Jul 6, 1973May 6, 1975Hitachi LtdControl device for automatic transmission in automobilesUS3882740 *Jun 30, 1972May 13, 1975Daimler Benz AgProcess for controlling the working oil pressure as a function of engine torque for shifting elements of automatically shifted transmissions, especially for motor vehiclesUS3895547 *Jul 25, 1974Jul 22, 1975Aisin SeikiTransmission control systemUS3942393 *May 12, 1972Mar 9, 1976Daimler-Benz AktiengesellschaftDevice for the control of shifting members of automatic change-speed transmissionsUS4044634 *Jul 26, 1974Aug 30, 1977Daimler-Benz AktiengesellschaftInstallation for automatic shifting of change-speed gearsUS4073204 *Nov 7, 1975Feb 14, 1978Voith Getriebe KgTransmission-ratio-changer for multiple-transmission-ratio transmission arrangementUS4082013 *Nov 22, 1974Apr 4, 1978General Motors CorporationHydrostatic transmission controlUS4131036 *Jun 10, 1977Dec 26, 1978Borg-Warner CorporationMethod and apparatus for transmission control systemUS4174645 *Nov 22, 1976Nov 20, 1979The Agency Of Industrial Science And TechnologyAutomatic change-gear control device for use in electromobileUS4208925 *Aug 11, 1977Jun 24, 1980Caterpillar Tractor Co.Electronic transmission control and method thereforUS4220058 *Sep 1, 1978Sep 2, 1980Borg-Warner CorporationElectronic control system for automatic transmissionUS4244244 *Jan 6, 1978Jan 13, 1981Robert Bosch GmbhMethod and apparatus for eliminating gear shifting jolt in motor vehiclesUS4258252 *Jul 19, 1979Mar 24, 1981Simjian Luther GCheck controlled metering deviceUS4258591 *Aug 9, 1978Mar 31, 1981Robert Bosch GmbhApparatus for controlling gear shifts in automatic transmissionsUS4259882 *Jan 3, 1978Apr 7, 1981Borg-Warner CorporationElectronic shift controlUS4283970 *Jul 2, 1979Aug 18, 1981General Motors CorporationAutomatic transmission line pressure controlUS4290322 *May 25, 1979Sep 22, 1981J. I. Case CompanyElectronic transmission controlUS4345489 *Jan 14, 1980Aug 24, 1982Robert Bosch GmbhHydraulic control system for servos in automatic transmissionsUS4485443 *May 27, 1981Nov 27, 1984Zahnradfabrik Friedrichshafen AktiengesellschaftTorque-control system for automatic speed changer shiftable under loadUS4527487 *Jun 18, 1982Jul 9, 1985Creusot-LoireSuspension and coupling device between a bogie frame and an axle boxUS4535412 *Nov 6, 1981Aug 13, 1985Ford Motor CompanyDrivetrain torque determination using torque converter characteristicsUS4631628 *Jun 8, 1983Dec 23, 1986Chrysler Motors CorporationElectronic fuel injector driver circuitUS4656989 *Apr 1, 1986Apr 14, 1987Honda Giken Kogyo Kabushiki KaishaSystem for driving solenoid valve for internal combustion engineUS4667540 *Feb 22, 1985May 26, 1987Nissan Motor Co., Ltd.Shift shock alleviating apparatus and method for automatic transmissionUS4680988 *Nov 21, 1985Jul 21, 1987Nissan Motor Co., Ltd.Control for shock-free shift in an automatic transmissionUS4693142 *Feb 14, 1986Sep 15, 1987Diesel Kiki Co., Ltd.Automatic transmission system for vehiclesUS4724723 *Dec 4, 1986Feb 16, 1988General Motors CorporationClosed loop shift quality control system* Cited by examinerReferenced byCiting PatentFiling datePublication dateApplicantTitleUS5086743 *Dec 20, 1990Feb 11, 1992Ford Motor CompanyIntegrally formed and tuned fuel rail/injectorsUS5134537 *Dec 5, 1991Jul 28, 1992Texas Instruments IncorporatedNegative voltage clamp circuit for controlling currents in inductive loadsUS5621604 *Jun 7, 1995Apr 15, 1997Siliconix, Inc.PWM multiplexed solenoid driverUS5701870 *Apr 15, 1996Dec 30, 1997Caterpillar Inc.Programmable fuel injector current waveform control and method of operating sameUS5796261 *Aug 20, 1996Aug 18, 1998Chrysler CorporationMethod and device for detecting solenoid actuationUS6024071 *Apr 24, 1996Feb 15, 2000Ficht Gmbh & Co. KgProcess for driving the exciting coil of an electromagnetically driven reciprocating piston pumpUS6406102Feb 24, 2000Jun 18, 2002Orscheln Management Co.Electrically operated parking brake control systemUS6545852Oct 6, 1999Apr 8, 2003OrmancoSystem and method for controlling an electromagnetic deviceUS6663195Feb 25, 2002Dec 16, 2003Orscheln Management Co.Electrically operated parking brake control systemsUS7082023 *May 17, 2004Jul 25, 2006Moeller GmbhMethod and circuit arrangement for function monitoring of an electronic-mechanical position switchUS7089736 *Jul 27, 2004Aug 15, 2006General Motors CorporationVariable nozzle turbo (VNT) solenoid temperature estimatorUS7330345May 9, 2005Feb 12, 2008Honeywell International, Inc.Valve control method for circuitry for power generation systemsUS7898788 *May 10, 2007Mar 1, 2011Schneider Electric Industries SasElectronic control device for electromagnetic unitUS8260475Nov 19, 2009Sep 4, 2012Hill-Rom Services, Inc.Constant low-flow air source control system and methodUS8429778Apr 11, 2011Apr 30, 2013Hill-Rom Services, Inc.Low noise linear diaphragm compressor by variable amplitude driverUS8712591Aug 31, 2012Apr 29, 2014Hill-Rom Services, Inc.Constant low-flow air source control system and methodUS20040008002 *May 30, 2003Jan 15, 2004Shigeru KamioMotor control apparatusUS20040228065 *May 17, 2004Nov 18, 2004Moeller GmbhMethod and circuit arrangement for function monitoring of an electronic-mechanical position switchUS20060021345 *Jul 27, 2004Feb 2, 2006Mc Donald Mike MVariable nozzle turbo (VNT) solenoid temperature estimatorUS20060249121 *May 9, 2005Nov 9, 2006Honeywell International, Inc.Valve control method and circuitry for power generation systemsUS20070263337 *May 10, 2007Nov 15, 2007Schneider Electric Industries SasElectronic control device for electromagnetic unitUS20110113560 *May 19, 2011Receveur Timothy JConstant low-flow air source control system and methodDE19715688B4 *Apr 15, 1997Dec 13, 2007Caterpillar Inc., PeoriaProgrammierbare Brennstoffeinspritzvorrichtungs-Stromwellenformsteuerung und Verfahren zum Betrieb davonEP0607030A2 *Jan 12, 1994Jul 20, 1994SILICONIX IncorporatedPWM multiplexed solenoid driverEP1858035A2 *May 4, 2007Nov 21, 2007Schneider Electronic Industries SASElectronic control device for electromagnetic unit* Cited by examinerClassifications U.S. Classification361/154, 318/599, 123/490International ClassificationG05B11/26, F16H61/02Cooperative ClassificationF16H2061/0255, G05B11/26, F16H61/0251European ClassificationG05B11/26, F16H61/02E4Legal EventsDateCodeEventDescriptionJun 20, 1994FPAYFee paymentYear of fee payment: 4May 26, 1998FPAYFee paymentYear of fee payment: 8Jul 9, 2002REMIMaintenance fee reminder mailedDec 26, 2002LAPSLapse for failure to pay maintenance feesFeb 18, 2003FPExpired due to failure to pay maintenance feeEffective date: 20021225RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services


text:
Treadmill training and body weight support for walking after stroke. - PubMed - NCBI
AbstractFormatSummarySummary (text)AbstractAbstract (text)MEDLINEXMLPMID ListApplySend to:Choose DestinationFileClipboardCollectionsE-mailOrderMy BibliographyCitation managerFormatSummary (text)Abstract (text)MEDLINEXMLPMID ListCSVCreate File1 selected item: 24458944FormatSummarySummary (text)AbstractAbstract (text)MEDLINEXMLPMID ListMeSH and Other DataE-mailSubjectAdditional textE-mailDidn't get the message? Find out why...Add to ClipboardAdd to CollectionsOrder articlesAdd to My BibliographyGenerate a file for use with external citation management software.Create File
See comment in PubMed Commons belowCochrane Database Syst Rev. 2014 Jan 23;1:CD002840. doi: 10.1002/14651858.CD002840.pub3.Treadmill training and body weight support for walking after stroke.Mehrholz J1, Pohl M, Elsner B.Author information1Wissenschaftliches Institut, Private Europäische Medizinische Akademie der Klinik Bavaria in Kreischa GmbH, An der Wolfsschlucht 1-2, Kreischa, Germany, 01731.AbstractBACKGROUND: Treadmill training, with or without body weight support using a harness, is used in rehabilitation and might help to improve walking after stroke. This is an update of a Cochrane review first published in 2005.OBJECTIVES: To determine if treadmill training and body weight support, individually or in combination, improve walking ability, quality of life, activities of daily living, dependency or death, and institutionalisation or death, compared with other physiotherapy gait training interventions after stroke. The secondary objective was to determine the safety and acceptability of this method of gait training.SEARCH METHODS: We searched the Cochrane Stroke Group Trials Register (last searched June 2013), the Cochrane Central Register of Controlled Trials (CENTRAL) and the Database of Reviews of Effects (DARE) (The Cochrane Library 2013, Issue 7), MEDLINE (1966 to July 2013), EMBASE (1980 to July 2013), CINAHL (1982 to June 2013), AMED (1985 to July 2013) and SPORTDiscus (1949 to June 2013). We also handsearched relevant conference proceedings and ongoing trials and research registers, screened reference lists and contacted trialists to identify further trials.SELECTION CRITERIA: Randomised or quasi-randomised controlled and cross-over trials of treadmill training and body weight support, individually or in combination, for the treatment of walking after stroke.DATA COLLECTION AND ANALYSIS: Two authors independently selected trials, extracted data and assessed methodological quality. The primary outcomes investigated were walking speed, endurance and dependency.MAIN RESULTS: We included 44 trials with 2658 participants in this updated review. Overall, the use of treadmill training with body weight support did not increase the chances of walking independently compared with other physiotherapy interventions (risk difference (RD) -0.00, 95% confidence interval (CI) -0.02 to 0.02; P = 0.94; I² = 0%). Overall, the use of treadmill training with body weight support in walking rehabilitation for patients after stroke increased the walking velocity and walking endurance significantly. The pooled mean difference (MD) (random-effects model) for walking velocity was 0.07 m/s (95% CI 0.01 to 0.12; P = 0.02; I² = 57%) and the pooled MD for walking endurance was 26.35 metres (95% CI 2.51 to 50.19; P = 0.03; I² = 60%). Overall, the use of treadmill training with body weight support in walking rehabilitation for patients after stroke did not increase the walking velocity and walking endurance at the end of scheduled follow-up significantly. The pooled MD (random-effects model) for walking velocity was 0.04 m/s (95% CI -0.06 to 0.14; P = 0.40; I² = 40%) and the pooled MD for walking endurance was 32.36 metres (95% CI -3.10 to 67.81; P = 0.07; I² = 63%). However, for ambulatory patients improvements in walking endurance lasted until the end of scheduled follow-up (MD 58.88 metres, 95% CI 29.10 to 88.66; P = 0.0001; I² = 0%). Adverse events and drop outs did not occur more frequently in people receiving treadmill training and these were not judged to be clinically serious events.AUTHORS' CONCLUSIONS: Overall, people after stroke who receive treadmill training with or without body weight support are not more likely to improve their ability to walk independently compared with people after stroke not receiving treadmill training, but walking speed and walking endurance may improve. Specifically, stroke patients who are able to walk (but not people who are not able to walk) appear to benefit most from this type of intervention. This review found that improvements in walking endurance in people able to walk may have persisting beneficial effects. Further research should specifically investigate the effects of different frequencies, durations or intensities (in terms of speed increments and inclination) of treadmill training, as well as the use of handrails, in ambulatory patients, but not in dependent walkers.Update ofTreadmill training and body weight support for walking after stroke. [Cochrane Database Syst Rev. 2005]PMID: 24458944 [PubMed - indexed for MEDLINE] SharePublication Types, MeSH TermsPublication TypesMeta-AnalysisResearch Support, Non-U.S. Gov'tReviewMeSH TermsBody WeightExercise Therapy/instrumentationExercise Therapy/methods*HumansOrthotic DevicesRandomized Controlled Trials as TopicStroke/rehabilitation*WalkingWeight-BearingLinkOut - more resourcesFull Text SourcesWileyMedicalClinicalTrials.govStroke - MedlinePlus Health InformationStroke Rehabilitation - MedlinePlus Health InformationMiscellaneousNCI CPTAC Assay PortalPubMed Commons home

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