Centrifugal compressor is a piece of key equipment for factories. Among the components of centrifugal compressor, impeller is a pivotal part as it is used to transform kinetic energy to pressure energy. But it usually leads to blade crack or failure as irregular aerodynamic load effect on the blade. Therefore, early crack feature extraction and pattern recognition is important to prevent it from failure. Although time series analysis for monitored signal can be used on feature extraction, incipient weak feature extraction method should be investigated. In this research, pressure pulsation sensors arranged in close vicinity to crack area are used to monitor the blade crack and feature extraction. As there are different kinds of flow interference, the pressure pulsation signal for centrifugal compressor is full of nonlinear characteristics. Therefore, how to obtain the weak information from monitored signal is investigated. Although FFT and envelope analysis have been widely used for rotating equipment, they are not suitable for the determination of incipient crack of a blade as the signal modulation and noise interference. In this research, stochastic resonance is used for the pressure pulsation signal. The results show that it is an effective tool to blade incipient crack classification on centrifugal compressor.

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