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Machinery Fault Diagnosis in Electric Motors Through Mechanical Vibration Monitoring Using Fiber Bragg Grating-based Accelerometers

2024; IEEE Sensors Council; Volume: 24; Issue: 13 Linguagem: Inglês

10.1109/jsen.2024.3400169

1558-1748

Leandro Macedo, Pablo Louzada, Luis Gustavo Villani, Anselmo Frizera, Carlos Marques, Arnaldo Leal‐Junior,

Gear and Bearing Dynamics Analysis

This paper presents machinery fault diagnosis in electric motors through mechanical vibration monitoring. Using a commercial machinery fault simulator, two Fiber Bragg Gratings accelerometers are evaluated under 1 healthy condition and 9 different fault conditions, including rotors with broken bars, faulted bearings, misalignment, and imbalance. The mechanical vibration spectrum for each fault condition is assessed by analyzing the Bragg wavelength shift modulated by the acceleration. Offline analysis is carried out to identify the mechanical vibration pattern characteristics. In this preliminary analysis, the high-order frequency characteristics of faulted-bearing conditions and the slip frequency characteristics of broken rotor bar conditions were well-identified by both accelerometers. Following this analysis, this paper uses two concurrent approaches to indicate the feasibility of classifying and/or clustering the data from supervised or unsupervised approaches. To that extent, the sensor system is first analyzed using a supervised approach from the k-Nearest Neighbors approach for fault condition classification, where the proposed supervised algorithm resulted in an accuracy of 100% for the fault condition estimation. After the classification analysis, data clustering is also proposed. In the unsupervised approach, the highest score for 7 clusters was observed. Besides in this work 9 fault conditions were studied, there are two fault conditions where the positions of the accelerometers were interchanged for a sensor's acceleration sensitivity evaluation purpose (maintaining the same fault condition). Finally, the results obtained in this work have shown the feasibility of the use of FBG-based accelerometers in different fault conditions under supervised and unsupervised approaches.