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Fault detection and identification in induction motor using weightless neural network.

Anam Abid¹, Zo Afshan²

¹Department of Mechatronics Engineering, University of Engineering and Technology, Peshawar, Pakistan.

The Review of Scientific Instruments

|February 13, 2024

Summary

A new real-valued weightless neural network classifier enhances fault detection in induction motors. This advanced method improves accuracy for both single-phase and three-phase motor fault identification.

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Area of Science:

Electrical Engineering
Artificial Intelligence
Machine Learning

Background:

Fault detection in induction motors is critical for industrial reliability.
Existing weightless neural network variants have limitations in handling real-valued data and multiclass problems.
Accurate fault identification ensures operational efficiency and prevents catastrophic failures.

Purpose of the Study:

To introduce a novel multiclass, multiparameter real-valued weightless neural network (WNN) classifier.
To enhance the recognition and generalization capabilities of WNNs for fault diagnosis.
To apply the developed classifier for fault detection and identification in single-phase and three-phase induction motors.

Main Methods:

Development of an improved input-to-address mapping strategy for discriminator units.
Implementation of an effective memory expansion scheme using similarity metric-based membership values.
Utilization of the WNN classifier for analyzing real-valued input features from induction motors.

Main Results:

The proposed WNN classifier achieved high accuracy in fault identification.
Achieved 99.6% accuracy for single-phase induction motor fault identification.
Achieved 89.25% accuracy for three-phase induction motor fault identification.

Conclusions:

The novel real-valued WNN classifier offers superior performance for multiclass fault detection.
The method demonstrates significant improvements over primitive WNN variants.
The classifier is effective for identifying multiple faults in both single-phase and three-phase induction motors.