Eccentricity Fault Detection in Industrial Washing Machine by Spectral Analysis

https://doi.org/10.58571/CNCA.AMCA.2025.049

Resumen: Mechanical faults in electrical machines, particularly in industrial washing machines, are a relevant case study, particularly due to the high costs of corrective maintenance performed in the event of a failure. Therefore, the present work aims to detect incipient (small in magnitude) mechanical eccentricity failures by means of a frequency analysis of motor current signals through a programmable logic controller (PLC). Noninvasive signal measurements were performed using Hall effect sensors and signal conditioning for a SIMATIC S7-1200 PLC, obtaining a database during the process of a washing cycle. For data analysis, the Discrete Fourier Transform (FDT) of the Park Instantaneous Space Vector (ISP) was used. For the different eccentricity failures, varying loads in the industrial washing machine basket were considered. The algorithm programmed in the PLC allowed the fault to be detected during a wash cycle, at different operating points of the industrial washing machine and under normal operating environmental conditions; that is, with the noise and vibration of other industrial washing machines. The scope of this work, therefore, allows for early “online" fault detection, avoiding corrective maintenance on industrial washing machines and the generation of other types of mechanical failures, such as bearing failures.

¿Cómo citar?

Maldonado-Ruelas, V. & Ortiz-Medina, R. (2025). Eccentricity Fault Detection in Industrial Washing Machine by Spectral Analysis. Memorias del Congreso Nacional de Control Automático 2025, pp. 286-290. https://doi.org/10.58571/CNCA.AMCA.2025.049

Palabras clave

Fault Detection, Electrical Machines, Frequency Analysis; Programmable Automaton, Washing Machine.

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