Rolling Bearing Fault Detection Method Based on Wavelet Packet Energy Spectrum - PLS

For the problem of rolling bearing mechanical fault detection, this paper proposed a fault detection method based on wavelet packet energy spectrum and partial least squares (PLS). Firstly, the collected vibration signal was decomposed by wavelet packet into independent frequency bands. The different frequencies energy spectrum could be collected from the independent frequency bands. That means the energy spectrum feature vectors whose changes reflect the running state could be constructed. Then analyze the energy spectrum feature vector by PLS, and establish the fault detection model. The fault could be detected by the T 2 and SPE statistics. Finally, the experimental results showed that the method is feasible and effective.