A Fault Diagnosis Method Based on Wavelet Approximate Entropy for Fan

The vibration signal of the fan is a typical non-stationary time-varied signal with chaotic characteristic. Approximate entropy is able to take description of disorder or irregularity in the motion systems. This paper introduces approximate entropy as a tool to describing the fan conditions. A threshold filtering algorithm based on the wavelet for reducing noise is introduced. Utilizing the above method, the vibration signals of the fan under different working conditions are analyzed. The result shows that the approximate entropy is able to identify the conditions of the fan with faults compared with the normal condition, thereby providing an effective technology for condition monitoring and fault diagnosis of mechanical equipment.