Fault Diagnosis of Wind Turbine Gearbox Based on Improved QPSO Algorithm

Xiong, J.

doi:10.2174/2352096511666180629152127

Cited by 2 publications

(1 citation statement)

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“…BP neural network is a classic and widely used neural network. Cheng et al [142] uses the IQPSO algorithm based on the PSO algorithm to optimize the classic BP neural network, and the IQPSOBP obtained after training has a higher accuracy for gearbox failures than PSOBP. In paper [143], the author compares the fault detection performance of the classic ML algorithms with the proposed 2-D CNN architecture (Fig.…”

Section: B Ai Approaches For Detecting Faults Of Transmissionmentioning

confidence: 99%

Feature Engineering and Artificial Intelligence-Supported Approaches Used for Electric Powertrain Fault Diagnosis: A Review

Zhang

Deng

et al. 2022

IEEE Access

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Electric powertrain is constituted by electric machine transmission unit, inverter and battery packs, etc., is a highly-integrated system. Its reliability and safety are not only related to industrial costs, but more importantly to the safety of human life. This review is the first contribution to comprehensively summarize both the feature engineering methods and artificial intelligence (AI) algorithms (including machine learning, neural networks and deep learning) in electric powertrain condition monitoring and fault diagnosis approaches. Specifically, this paper systematically divides the AI-supported method into two main steps: feature engineering and AI approach. On the one hand, it introduces the data and feature processing in AI-supported methods, and on the other hand it summarizes input signals, feature methods and AI algorithms included in the AI method in cases. Therefore, firstly this review is to guide how to choose the appropriate feature engineering method in further research. Secondly, the up-to-date AI algorithms adopted for powertrain health monitoring are presented in detail. Finally, such current approaches are discussed and future trends are proposed.

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Section: B Ai Approaches For Detecting Faults Of Transmissionmentioning

confidence: 99%

Feature Engineering and Artificial Intelligence-Supported Approaches Used for Electric Powertrain Fault Diagnosis: A Review

Zhang

Deng

et al. 2022

IEEE Access

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Transformer Fault Diagnosis Based on an Improved Sine Cosine Algorithm and BP Neural Network

Cheng

Feng

Xiong

2022

EEENG

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Background: The operation state evaluation and fault location of transformer is one of the technical bottlenecks restricting the safe operation of power grid. Methods: To improve the accuracy of transformer fault diagnosis, a hybrid intelligent method based on the improved sine cosine algorithm and BP neural network (ISCA-BP) is developed. First, the cloud model is introduced into the sine cosine algorithm (SCA) to determine the conversion parameter of each individual, so as to balance the global search and local exploitation capabilities. After that, six popular benchmark functions are used to evaluate the effectiveness of the proposed algorithm. Finally, on the basis of the dissolved gas analysis technology, the improved SCA algorithm is employed to find the optimal weight and threshold parameters of BP neural network, and the transformer fault classification model is established. Results: Simulation results indicate that the improved SCA algorithm exhibits strong competitiveness. Furthermore, compared with the BP neural network optimized by sine cosine algorithm (SCA-BP) and BP neural network, ISCA-BP method can significantly improve the diagnostic accuracy of transformer faults. Conclusion: The proposed intelligent method can provide a valuable reference idea for transformer fault classification.

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Fault Diagnosis of Wind Turbine Gearbox Based on Improved QPSO Algorithm

Cited by 2 publications

References 0 publications

Feature Engineering and Artificial Intelligence-Supported Approaches Used for Electric Powertrain Fault Diagnosis: A Review

Feature Engineering and Artificial Intelligence-Supported Approaches Used for Electric Powertrain Fault Diagnosis: A Review

Transformer Fault Diagnosis Based on an Improved Sine Cosine Algorithm and BP Neural Network

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