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Gear Fault Diagnosis Based on Wavelet Transform
Advanced Materials Research, 2012Gearbox operation conditions have a great effect on the equipment of the whole machine directly; therefore, the gear is the main object in the site monitoring and diagnosis. This paper analysis pitting corrosion signals getting from the test-bed. The signals are analyzed and processed in wavelet and Hilbert transform on Matlab. It is shown that wavelet
Gui Ji Tang, Jiao Wu, Zi Rui Wang
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New Methold on Power Transformer Fault Diagnosis
Applied Mechanics and Materials, 2012This paper improves the simple genetic algorithm and combines genetic algorithm with BP algorithm to the wavelet neural network in the power transformer fault diagnosis by dissolved gas-in-oil analysis, Simulation result shows the problem was solved that wavelet network settles into local small extremum so easily that the network surging will increase ...
Nan Lan Wang, Ming Shan Cai
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Power transformers fault diagnosis using AI techniques
AIP Conference Proceedings, 2020Artificial Intelligence (AI) is a novel branch in science and engineering. AI techniques constitute the most cutting-edge method in Power Transformers Fault Diagnosis. When a transformer fails, some gases are produced and dissolved in the insulating oil, and Gas Chromatography detects them.
V. Rokani, S. D. Kaminaris
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Fuzzy approaches for fault diagnosis of transformers
Fuzzy Sets and Systems, 2001Dissolved gas analysis has been used as a diagnostic method to determine the conditions of transformers for a long time. The criteria used in dissolved gas analysis are based on crisp value norms. Due to the dichotomous nature of crisp criteria, transformers with similar gas-in-oil conditions may lead to very different conclusions of diagnosis ...
An-Pin Chen, Chang-Chun Lin
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SENSOR FAULT DIAGNOSIS COUPLING DEEP LEARNING AND WAVELET TRANSFORMS
Proceedings of the 13th International Workshop on Structural Health Monitoring, 2022Sensor networks facilitate collecting measurement data necessary for decision making regarding structural maintenance and rehabilitation in structural health monitoring (SHM) systems. Nevertheless, the reliability of decision making in SHM systems depends on the proper operation of the sensors.
Peralta Abadia, Jose +3 more
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Transformer Fault Diagnosis Using Deep Neural Network
2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), 2019Analysis of dissolved gases in transformer oil is one of the practical methods for identifying the different types of faults in oil-insulated power transformers. Dissolved gas analysis (DGA) is often exercised as part of the maintenance process, and the Duval Triangle is a commonly applied method for classifying transformer faults.
Hossein MehdipourPicha +5 more
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GRU‐Dual Transformer–BiLSTM Fusion for Transformer Fault Diagnosis
International Journal of Circuit Theory and ApplicationsABSTRACTTo address the shortcomings of conventional dissolved gas in oil analysis technology in transformer fault diagnosis, the GRU‐dual transformer and BiLSTM fusion method for transformer fault diagnosis is proposed. Firstly, the time series waveforms are independently transformed into two different image representations by using the GASF and RP ...
Xin Zhang, Yongxin Zhang, Qi Yang
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Power Transformers Fault Diagnosis Based on DRNN
Advanced Materials Research, 2014In recent years, improved three-ratio is an effective method for transformer fault diagnosis based on Dissolved Gas Analysis (DGA). In this paper, diagonal recurrent neural network (DRNN) is used to resolve the online fault diagnosis problems for oil-filled power transformer based on DGA.
Hui Da Duan, Qiao Song Li
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Transformer Winding Fault Diagnosis by Vibration Monitoring
2018 Condition Monitoring and Diagnosis (CMD), 2018The role of transformer in electricity network reliability and safe operation is quite crucial. Therefore, their monitoring, maintenance and management is vitally important for utility operators. Simpler, non-invasive and online condition monitoring method which is sensitive to incipient faults is in demand for transformer diagnosis. Although vibration
Sai Srinivas Manohar +5 more
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Transformer Fault Diagnosis Based on Elman Network
2019Power transformer fault is characterized by diversity, irregularity and uncertainty. So Elman Network fault diagnosis method is proposed, for the effective realization of transformer fault diagnosis. Key elements are selected from the transformer gas content acquisition parameters as parameters for improved three-ratio method, which is the input of ...
Zhongqiang Liu +4 more
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