Suitable signal processing techniques for frequency response functions? Good day everyone
I have recorded experimental frequency response functions (frfs) for a loose bolt monitoring project. Please see figure 1 below for an example of the frf.

Figure 1
The purpose of my project is to determine if loose bolt conditions can be determined using vibration testing. I used a lapped beam made up of two plates, which are joined with 4 bolts in the following configuration (figure 2). The one end, (left hand side in figure 2), of the beam is fixed to a table vice to simulate a fixed boundary condition, while the other end, (Right hand side in figure 2), is free. Therefore, the beam boundary condition is fixed - free in a cantilever orientation. The beam was excited using a modal impulse hammer (instrumented hammer). The resulting vibration was measured using micro accelerometers positioned at different locations on the beam.

Figure 2
The following figure 3 shows the frf results of the loose bolt testing for one of the damage cases. The natural frequencies shift when the bolts become loose. The dashed blue line shows the condition when the bolt is fully loose. (I've focused on the high frequency range since this shows the affect of bolt looseness best).

Figure 3
I've plotted the frfs and plan on using a wavelet transform in the FRF, (using a scaleogram in python). Figure 4 shows my wavelet attempt so far. I'm using python as the program to apply my signal processing methods.

Figure 4
My question is, are there any other signal processing techniques which I could apply to the measured FRF's in order to show a difference from the healthy case, (Fully tightened bolts), to the damaged cases, (loosened bolts)?
In summary I'm asking, what signal processing can I complete on frfs to show possible loose bolt conditions?
I agree with all of what Dan has said, and would add that the method of excitation is probably not the best for reproducibility. Impulse hammer taps can have different frequency content depending on the location of the strike and the angle of strike, not to mention they are slow as compared to shaker excitation or using a loudspeaker (air coupled). If you're going to be amassing statistics you want to make it quick and reproducible. You can get quick FRF's with a logarithmic chirp excitation in this frequency range, I think.