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Automatika : časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije, Vol. 63 No. 3, 2022.

Izvorni znanstveni članak

https://doi.org/10.1080/00051144.2022.2052533

Magnetoresistance sensor-based rotor fault detection in induction motor using non-decimated wavelet and streaming data

S. Kavitha ; Electrical and Electronics Engineering, Saveetha Engineering College, Chennai, Tamil Nadu, India
N. S. Bhuvaneswari ; Electrical and Electronics Engineering, GKM College of Engineering and Technology, Chennai, Tamil Nadu, India
R. Senthilkumar ; Electrical and Electronics Engineering, Saveetha Engineering College, Chennai, Tamil Nadu, India
N. R. Shanker ; Computer Science and Engineering, Aalim Muhammed Salegh Engineering College, Chennai, Tamil Nadu, India

Puni tekst: engleski pdf 4.596 Kb

str. 525-541

preuzimanja: 117

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Sažetak

In this paper, the giant magnetoresistance broken rotor (GBR) method is used to diagnose the induction motor (IM) rotor bar fault at an early stage from outward magnetic flux developed by IM.The outward magnetic field signal has anti-clockwise radiation due to broken rotor bar current.In this paper, the outward magnetic signal is acquired using a giant magnetoresistance (GMR) sensor. In the GBR method, IM rotor fault is analysed with a non-decimated wavelet transform (NDWT)-based outward magnetic signal. Experimental result shows the difference in statistical features and energy levels of sub-bands of NDWT for healthy and faulty IM. Least square-support vector machine(LS-SVM)-based classification results are verified by confusion matrix based on 150 outward magnetic signals from a healthy and damaged rotor (broken rotor). The proposed method identifies IM rotor faults with 95% sensitivity, 90% specificity and 92.5% classification accuracy. Furthermore, run-time IM condition monitoring is performed through the ThinkSpeak internet of things (IoT) platform for collecting outer magnetic signal data. ThinkSpeak streaming data of outward magnetic field help detect rotor fault at the initial stage and understand the growth of rotor fault in the motor. The proposed GBR method overcomes sensitivity, translation-invariance limitations of existing IM rotor fault diagnosis methods.

Ključne riječi

Giant magnetoresistance; broken rotor; rotor fault diagnosis; outward magnetic field; NDWT; IoT

Hrčak ID:

287525

URI

https://hrcak.srce.hr/287525

Datum izdavanja:

11.4.2022.

Posjeta: 283 *