Determination of priority among correlated inputs in source identification problems

Abstract Frequency response function technique and partial coherence function technique are two typical approaches in noise source identification of multiple-input/single-output systems. In the second approach, which is used in cases where the inputs are correlated to each other, determining the priority of the input records is a key factor since the priority determines the way in which the results are interpreted. This paper presents a method for determination of priority among inputs when applying the partial coherence function technique to source identification problems. The basic idea is that, if one signal of any two correlated signals causes the other signal, then the causality can be identified by observing two impulse response functions estimated in the negative time region. One impulse response function is obtained by the inverse Fourier transform of the frequency response function, where the first signal is assumed as input and the second signal as output. The other impulse response function is obtained by assuming that the second signal is the input and the first signal is the output. The method was applied to a simulated two-inputs/one-output system in which the inputs were correlated to each other. It is expected that the proposed method will work as a successful means of determining priority among multiple inputs in source identification problems.