Novel Fault Diagnosis of a Conveyor Belt Mis-Tracking via Motor Current Signature Analysis

Author:

Farhat Mohamed Habib1ORCID,Gelman Len1,Abdullahi Abdulmumeen Onimisi1,Ball Andrew1ORCID,Conaghan Gerard2ORCID,Kluis Winston3

Affiliation:

1. School of Computing and Engineering, The University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK

2. Daifuku Airport Technologies, Sutton Road, Hull HU7 0DR, UK

3. Babcock International Group, Schiphol Boulevard 363, 1118 BJ Schiphol, The Netherlands

Abstract

For the first time ever worldwide, this paper proposes, investigates, and validates, by multiple experiments, a new online automatic diagnostic technology for the belt mis-tracking of belt conveyor systems based on motor current signature analysis (MCSA). Three diagnostic technologies were investigated, experimentally evaluated, and compared for conveyor belt mis-tracking diagnosis. The proposed technologies are based on three higher-order spectral diagnostic features: bicoherence, tricoherence, and the cross-correlation of spectral moduli of order 3 (CCSM3). The investigation of the proposed technologies via comprehensive experiments has shown that technology based on the CCSM3 is highly effective for diagnosing a conveyor belt mis-tracking via MCSA.

Funder

Innovate UK

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine Learning Techniques for Improving Multiclass Anomaly Detection on Conveyor Belts;2024 IEEE International Instrumentation and Measurement Technology Conference (I2MTC);2024-05-20

2. Evaluating Conveyor Belt Health With Signal Processing Applied to Inertial Sensing;2023 Symposium on Internet of Things (SIoT);2023-10-25

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