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A Gear Fault Detection Method Based on a Fiber Bragg Grating Sensor

CHEN Yong1 CHEN Yawu1 LIU Zhiqiang1 LIU Huanlin2

(1.Key Laboratory of Industrial Internet of Things and Network Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing, China 400065)
(2.Key Laboratory of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing, China 400065)

【Abstract】In this study, we proposed a gear fault identification method based on empirical mode decomposition of adaptive-noise complementary ensemble to solve the problem associated with the identification of gear faults. Initially, we used the fiber Bragg grating to extract the gear vibration signals and uniformized the spectrum of the vibration signal by adaptively adding Gaussian white noise to eliminate the mode mixing caused by the empirical modal algorithm. Subsequently, we used the correlation coefficient and the kurtosis value to obtain comprehensive evaluation indices for selecting the effective components and extracting the features of the effective components. Finally, we used a support vector machine to identify the gear faults. The experimental results denote that the proposed method can be used to effectively identify the states of gears, including normal, mild-wear, severe-wear, pitting, cracks, and broken teeth. Furthermore, the gear state identification accuracy rate is more than 90%.

【Keywords】 fiber optics; gear; fault detection; fiber Bragg grating; empirical mode decomposition; mode mixing;


【Funds】 National Natural Science Foundation of China (51977021)

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This Article


CN: 31-1339/TN

Vol 47, No. 03, Pages 232-241

March 2020


Article Outline


  • 1 Introduction
  • 2 Method of identification of gear faults
  • 3 Simulation verification
  • 4 Experiment and analysis
  • 5 Conclusions
  • References