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| Study on Detection Method of Worm Tooth Profile Variation in Worm Reducer Based on Autocorrelation Algorithm |
| ZHANG Rong-fa1,HU Jia-cheng1,LI Dong-sheng1,WANG Jian2,MA Hao1 |
1. China Jiliang University, Hangzhou, Zhejiang 310018, China;
2. Hangzhou Jiacheng Machinery Co. Ltd., Hangzhou, Zhejiang 310018, China |
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Abstract In order to diagnosis the fault of worm reducer caused by worm gear tooth profile changed, a new vibration signal detection method is proposed. The new method was that autocorrelation analysis was referenced to traditional gear fault analysis method which were empirical mode decomposition (EMD) and Hilbert transform. The worm reducer vibration signal were separated to different intrinsic mode functions component in different frequency (IMF). The autocorrelation analysis method is used to select IMF component which containing worm gear fault characteristic signal efficiently. Finally, the fault feature of IMF component is extracted by Hilbert transform. The JD45+ measuring instrument measuring the changed amount of worm gear tooth profile is used to verify the feasibility of this method.
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2014, Vol. 35 
