Modern society uses a variety of vehicles for transport. While these vehicles are often indispensable to their users, they can also generate unpleasant noise. The field of signal measurements and design of engine sound require that analyzing the correlation of signals among each observation points and extracting the objective components of signal since they cannot be detected with ordinary measuring instruments. In the view of analysis, the frequency analysis is widely used in sound and vibration analysis, but is not always effective in the analysis of non-stationary sounds. Stationary signals can be analyzed the correlation between them using a coherence function, but this method cannot be used for time-varying signals. To solve these problems, we proposed a method that uses an Instantaneous Correlation Function (ICF) that can analyze time-varying signals in time-frequency analysis based on the real-signal wavelet. We also introduced the idea of limiting the bandwidth using filters to improve the precision of our method and applied this method to the running sounds of a motorcycle and the of ship's interior noise to clarify the signal correlation of the components of the engine. As a result, it was possible to observe the running condition relating to the engine sound buried in the noisy environment effectively. This will contribute to the sound design of the engine sounds, separation of sound sources and active noise control.
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