A zero-fault sample diesel engine early warning and localisation method based on multi-cylinder similarity and memory augmentation

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127948 - 127948

Published: April 1, 2025

Language: Английский

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A convolutional-transformer reinforcement learning agent for rotating machinery fault diagnosis

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: 271, P. 126669 - 126669

Published: Feb. 4, 2025

Language: Английский

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Research on intelligent detection method of high-voltage circuit breaker based on PSO–CNN

International Journal of Low-Carbon Technologies, Journal Year: 2025, Volume and Issue: 20, P. 421 - 427

Published: Jan. 1, 2025

Abstract Through the intelligent detection of high-voltage circuit breakers, equipment faults can be detected and diagnosed in time, which effectively prevent power accidents ensure safe operation grid. In this paper, a method based on particle swarm optimization (PSO) convolutional neural network (CNN) is proposed, parameter setting CNN optimized by PSO. The feature vibration signal extracted sample set constructed. On basis, constructed experiment carried out. experimental results show that proposed has significant advantages precision, recall rate, F1 score compared with traditional method; precision reach 0.926, 0.913, 0.919. Future research could optimize training process to reduce running as well introduce more advanced data preprocessing techniques improve quality.

Language: Английский

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Zero-shot fault diagnosis using soft semantic embedding of diffusion-encoded probability

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103319 - 103319

Published: April 15, 2025

Language: Английский

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A fault diagnosis of high voltage circuit breakers with small samples using a PCA-cascade forest algorithm

Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 6190 - 6200

Published: May 28, 2025

Language: Английский

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