APPROACH TO EXTRACTING GEAR FAULT FEATURE BASED ON MATHEMATICAL MORPHOLOGICAL FILTERING

ZHANG Lijun YANG Debin XU Jinwu CHEN Zhixin

(School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083)

Abstract: To extract fault feature of gear, a novel approach is proposed according to the signal characteristics based on morphological filtering. As a nonlinear filtering algorithm for digital signal processing, morphological filtering is able to identify the feature of fringe and shape of the signal. Lorenz signal is processed by mathematical morphological filtering via various structuring elements, and the effect of noise reduction and non-linear feature reservation of morphological filtering is validated. The vibration signal of gear teeth broken is processed by morphological closing operation via the flat structuring elements, and the length of the structuring elements is 0.6 to 0.8 times to the length of gear impact period. Then, the filtered signal is analyzed by Fourier frequency spectrum. The results show that the impact feature, which can not be identified from noisy data directly, is successfully extracted by morphological filtering.

Key words: Morphological filtering Structuring element Gear Feature extraction

CLC No: TH165.3 TN911.7

高等学校博士学科点专项科研基金(20020008019)和北京市自然科学基金(3062012)资助项目. Received 20060216, received in revised form 20061010