Unsupervised Anomaly Detection Method for Electrical Equipment Based on Audio Latent Representation and Parallel Attention Mechanism

Unsupervised Anomaly Detection Method for Electrical Equipment Based on Audio Latent Representation and Parallel Attention Mechanism

The stable operation of electrical equipment is critical for industrial safety, yet traditional anomaly detection methods often suffer from limitations, such as high resource demands, dependency on expert knowledge, and lack of real-world capabilities. To address these challenges, this article propo...

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Bibliographic Details
Main Authors: Wei Zhou, Shaoping Zhou, Yikun Cao, Junkang Yang, Hongqing Liu
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
Subjects:
anomaly detection
mechanical fault diagnosis
unsupervised learning
audio signal analysis
electrical safety
Online Access:https://www.mdpi.com/2076-3417/15/15/8474
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