Wavelet transform based signal waveform identification: inspection of rotary compressor

This paper presents a new identification procedure of signal waveforms, based on wavelet theory, for the inspection of rotary compressors. The wavelet transform decomposes signals into time-frequency space, not into mere frequency space, limited by the uncertainty principle. This decomposition enables time-frequency analyses and provides a more flexible means of signal processing than before. To examine a rotary compressor pump, particular waves in the rotational load torque signals that correlate with failure modes are discriminated from one another and evaluated. To extract the focal waves, the signal is decomposed with wavelets and then only the particular waves, such as impulses, are reconstructed from a selected set of wavelet coefficients. This is called time-frequency space filtering. The wavelet local modulus maxims are used to open a time-frequency window through which only the focal waves can pass with high fidelity. The experimental results show the effectiveness of the maneuver