HUANG Jing1, GUO Ming yang1, LI Ge2

 

(1. School of Information Science and Technology, Zhejiang Sci Tech University,

 

Hangzhou 310018, China; 2. Faculty of Mechanical Engineering & Automation, Zhejiang Sci Tech University, Hangzhou 310018, China)

 

 

Abstract: Aiming at inspecting the quality of window motor, the motor structure, the cause of the problem, the vibration signal of time domain and frequency domain, time frequency characteristics and energy characteristics were investigated. Common bearing fault frequency were summarized, traditional Fourier transform of frequency domain detecting, Hilbert huang transform time frequency analysis were summed up. Based on the innovative concept combines wavelet transform and energy distribution, a window motor fault detection method was presented to calculate the energy distribution after using eight order wavelet transform. A set of complete collection and detection system was constructed by using the vibration acceleration sensor and the LabView. Vibration signals of the faulted and qualified motors were studied and contrasted through by 8 order wavelet decomposition and the building of energy distribution graph. The results indicate that the system and method can effectively reflect the features of energy distribution of different motors, distinguish faulted and qualified motors very well, and significantly improve the efficiency and accuracy of window motor fault diagnosis.

 

Key words: frequency characteristic; vibration sensors; LabView; wavelet transform (WT); energy distribution