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Enhanced extraction of rolling bearing fault features based on rotary encoder signals |
ZHU Yungui,GUO Yu,ZOU Xiang,TIAN Tian,XU Wantong |
Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China |
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Abstract For the occasion when the fault characteristics of rolling bearings are weak and the installation of vibration sensors is limited, the fault characteristics are not easy to extract. In this paper, combined with the advantages of short signal transmission path and little interference of rotary encoder, this paper proposes a method for enhancing the fault characteristics of rolling bearings based on instantaneous angular speed (IAS) signal of rotary encoder. Firstly, the de-phasing algorithm (DPA) is used to suppress the strict periodic components such as the frequency conversion and its harmonics; secondly, the bearing fault impact component is enhanced by multi-point optimization minimum entropy deconvolution adjusted (MOMEDA); finally, the enhanced signal is analyzed in the spectrum to extract the bearing fault impact characteristics. The effectiveness of the proposed method is verified by simulation and measured data of bearing outer ring.
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Received: 12 April 2022
Published: 28 April 2023
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