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

abstract

This article presents machinery fault diagnosis in electric motors through mechanical vibration monitoring. Using a commercial machinery fault simulator, two fiber Bragg grating (FBG) accelerometers are evaluated under one healthy condition and nine 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 article 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 (kNN) 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 seven clusters was observed. Besides in this work, nine 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.

keywords

BALL-BEARING; SENSORS

subject category

Engineering; Instruments & Instrumentation; Physics

authors

Macedo, L; Louzada, P; Villani, LG; Frizera, A; Marques, C; Leal, A Jr

Groups

G2 - Photonic, Electronic and Magnetic Materials

Projects

CICECO - Aveiro Institute of Materials (UIDB/50011/2020)

CICECO - Aveiro Institute of Materials (UIDP/50011/2020)

acknowledgements

This work was supported in part by Fundacao de Amparo aPesquisa e Inovacao do Espirito Santo (FAPES) under Grant 973/2022, Grant 256/2021, Grant 1004/2022, Grant 2021-07KJ2, Grant 2022-C5K3H, and Grant 459/2021; in part by CNPq under Grant 310709/2021-0, Grant 440064/2022-8, Grant 405336/2022-5, and Grant 304049/2019-0; in part by Ministerio da Ciencia, Tecnologia e Inovac & atilde;o(MCTI)/Fundo Nacional de Desenvolvimento Cientifico e Tecnologico(FNDCT)/Financiadora de Estudos e Projetos (FINEP) under Grant 2784/20 and Grant 0036/21; in part by the Scope of the Projectsi3N under Grant LA/P/0037/2020, Grant UIDB/50025/2020, and Grant UIDP/50025/2020; in part by Centre for Research in Ceramics and Composite Materials (CICECO)-Aveiro Institute of Materials through Portuguese funds under Fundacao para a Ciencia e a Tecnologia(FCT)/Ministerio da Educac & atilde;o (MEC) under Grant UIDB/50011/2020 and Grant UIDP/50011/2020; and in part by European Regional Development Fund (FEDER) through PT2020 Partnership Agreement.