Analysis of vibration signals I have a vibration signal coming from a motor measured from accelerometer (Irregular Time series) and I need to use these signals for analysis purpose. 



I am in need to transform this signal to some form for analysis purpose. I read few blogs and websites containing vibration signal processing technique. The basic thing is to transform the signal from time domain to frequency domain.

So I used the fft function to transform using R 

X.k &lt;- fft(signal)


plot.frequency.spectrum() plot a frequency spectrum of a given fft [Link: here]

plot.frequency.spectrum &lt;- function(X.k, xlimits=c(0,length(X.k))) {
  plot.data  &lt;- cbind(0:(length(X.k)-1), Mod(X.k))


  plot.data[2:length(X.k),2] &lt;- 2*plot.data[2:length(X.k),2] 

  plot(plot.data, t="h", lwd=2, main="", 
       xlab="Frequency (Hz)", ylab="Strength", 
       xlim=xlimits, ylim=c(0,max(Mod(plot.data[,2]))))
}


The frequency spectrum of this fft looks like this


The first peak is extremely high. I don't know why this happens as am new to signal processing techniques. I cannot use this for analysis purpose and do prediction as it will end in bad results. Any other ways to do this method? Or do I need to use other techniques?
The first peak is the DC component of your spectrum which is large compared to the AC components (your signal doesn't have negative value and its always above zero which lead to large DC bias)

Find average of your signal over time and subtract it from your signal to remove the DC component.

Good luck.