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| Wind turbine gearbox fault diagnosis based on sound signal and improved MS-LMD |
| LIU Shaokang1, WU Yingjie1,2, AN Weilun1, XIN Hongwei1,2, YANG Yanjun1, WANG Jianguo1,2 |
1.School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China;
2.International Research Center of Precision Drive and Intelligent Control, Jilin 132012, China |
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Abstract Machinery’s fault diagnosis based on sound signal is feasible, but sound signal sensors of wind turbine gearbox can pick up multiple vibration source signals and interference noise in its engine room to affect accurate locating of faults.Here, an improved local mean decomposition (LMD) method was proposed to realize gearbox composite fault diagnosis through separating frequency modulation (FM) and amplitude modulation components of a sound signal.According to the feature of masking signal (MS) being able to suppress mode aliasing, the dichotomy method was used to search MS frequency in the range of 1.0-1.5 times of amplitude weighted average frequency.A cyclic iterative method to combine repeatedly MS and LMD was proposed to judge and suppress multi-group mode aliasing in turn.The effectiveness of the proposed method was verified using two kinds of simulated signals being easy to have modal aliasing.The proposed method was applied in sound signal analysis of an actual wind turbine gearbox to successfully diagnose its composite faults.
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Received: 02 September 2020
Published: 15 June 2021
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