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Author

S. Murugan

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Conference Aug 2026

1D-CNN-Based Fault Diagnosis for Traction Motors Using Vibration and Current Signals

Accurate defect detection of traction motors is essential for preserving the performance and safety of electric cars and industrial gear. This research presents a onedimensional convolutional neural network (1D-CNN) architecture for the automated identification of faults using vibration and current information obtained...

M. Indhumathi, R. Deepa, M. Rubinabegam et al. · 0 citations
Conference Aug 2026

Rotatory Machine Fault Detection Using CNNs on Spectrogram Signal Data

Rotary machines are vital in industrial and electrical systems, and prompt defect detection is crucial to prevent operational failures and financial losses. This article presents a framework using a Convolutional Neural Network (CNN) for defect detection via spectrogram images derived from simulated voltage, current, a...

R. M. Vizhi, V. Karthikeyani, L. Sundari et al. · 0 citations

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