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Rope Tension Fault Diagnosis in Hoisting Systems Based on Vibration Signals Using EEMD, Improved Permutation Entropy, and PSO-SVM

1
School of Mechanical and Electrical Engineering, Central South University, Changsha 410010, China
2
State Key Laboratory of High Performance and Complex Manufacturing, Changsha 410010, China
*
Author to whom correspondence should be addressed.
Entropy 2020, 22(2), 209; https://doi.org/10.3390/e22020209
Received: 26 December 2019 / Revised: 2 February 2020 / Accepted: 10 February 2020 / Published: 12 February 2020
(This article belongs to the Section Signal and Data Analysis)
Fault diagnosis of rope tension is significantly important for hoisting safety, especially in mine hoists. Conventional diagnosis methods based on force sensors face some challenges regarding sensor installation, data transmission, safety, and reliability in harsh mine environments. In this paper, a novel fault diagnosis method for rope tension based on the vibration signals of head sheaves is proposed. First, the vibration signal is decomposed into some intrinsic mode functions (IMFs) by the ensemble empirical mode decomposition (EEMD) method. Second, a sensitivity index is proposed to extract the main IMFs, then the de-noised signal is obtained by the sum of the main IMFs. Third, the energy and the proposed improved permutation entropy (IPE) values of the main IMFs and the de-noised signal are calculated to create the feature vectors. The IPE is proposed to improve the PE by adding the amplitude information, and it proved to be more sensitive in simulations of impulse detecting and signal segmentation. Fourth, vibration samples in different tension states are used to train a particle swarm optimization–support vector machine (PSO-SVM) model. Lastly, the trained model is implemented to detect tension faults in practice. Two experimental results validated the effectiveness of the proposed method to detect tension faults, such as overload, underload, and imbalance, in both single-rope and multi-rope hoists. This study provides a new perspective for detecting tension faults in hoisting systems.
Keywords: rope tension; fault diagnosis; permutation entropy; EEMD; PSO-SVM rope tension; fault diagnosis; permutation entropy; EEMD; PSO-SVM
MDPI and ACS Style

Xue, S.; Tan, J.; Shi, L.; Deng, J. Rope Tension Fault Diagnosis in Hoisting Systems Based on Vibration Signals Using EEMD, Improved Permutation Entropy, and PSO-SVM. Entropy 2020, 22, 209.

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