Research on Transformer Fault Based on Probabilistic Neural Network

With the development of computer science and technology, and increasingly intelligent industrial production, the application of big data in industry also advances rapidly, and the development of artificial intelligence in the aspect of fault diagnosis is particularly prominent. On the basis of MATLA...

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Main Authors: Li Yingshun, Li Jingjing, Han Junfeng
Format: Article
Language:English
Published: EDP Sciences 2015-01-01
Series:MATEC Web of Conferences
Subjects:
Online Access:http://dx.doi.org/10.1051/matecconf/20152503010
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author Li Yingshun
Li Jingjing
Han Junfeng
author_facet Li Yingshun
Li Jingjing
Han Junfeng
author_sort Li Yingshun
collection DOAJ
description With the development of computer science and technology, and increasingly intelligent industrial production, the application of big data in industry also advances rapidly, and the development of artificial intelligence in the aspect of fault diagnosis is particularly prominent. On the basis of MATLAB platform, this paper constructs a fault diagnosis expert system of artificial intelligence machine based on the probabilistic neural network, and it also carries out a simulation of production process by the use of bionic algorithm. This paper makes a diagnosis of transformer fault by the use of an expert system developed by this paper, and verifies that the probabilistic neural network has a good convergence, fault-tolerant ability and big data handling capability in the fault diagnosis. It is suitable for industrial production, which can provide a reliable mathematical model for the construction of fault diagnosis expert system in the industrial production.
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spelling doaj.art-ffc00c8cdfb745b993b8680cf35ea78b2022-12-21T22:21:00ZengEDP SciencesMATEC Web of Conferences2261-236X2015-01-01250301010.1051/matecconf/20152503010matecconf_emme2015_03010Research on Transformer Fault Based on Probabilistic Neural NetworkLi Yingshun0Li Jingjing1Han Junfeng2Beijing Institute of Petrochemical TechnologyGuangxi University of TechnologyQinzhou UniversityWith the development of computer science and technology, and increasingly intelligent industrial production, the application of big data in industry also advances rapidly, and the development of artificial intelligence in the aspect of fault diagnosis is particularly prominent. On the basis of MATLAB platform, this paper constructs a fault diagnosis expert system of artificial intelligence machine based on the probabilistic neural network, and it also carries out a simulation of production process by the use of bionic algorithm. This paper makes a diagnosis of transformer fault by the use of an expert system developed by this paper, and verifies that the probabilistic neural network has a good convergence, fault-tolerant ability and big data handling capability in the fault diagnosis. It is suitable for industrial production, which can provide a reliable mathematical model for the construction of fault diagnosis expert system in the industrial production.http://dx.doi.org/10.1051/matecconf/20152503010artificial intelligencefault diagnosisexpert systemprobabilistic neural network
spellingShingle Li Yingshun
Li Jingjing
Han Junfeng
Research on Transformer Fault Based on Probabilistic Neural Network
MATEC Web of Conferences
artificial intelligence
fault diagnosis
expert system
probabilistic neural network
title Research on Transformer Fault Based on Probabilistic Neural Network
title_full Research on Transformer Fault Based on Probabilistic Neural Network
title_fullStr Research on Transformer Fault Based on Probabilistic Neural Network
title_full_unstemmed Research on Transformer Fault Based on Probabilistic Neural Network
title_short Research on Transformer Fault Based on Probabilistic Neural Network
title_sort research on transformer fault based on probabilistic neural network
topic artificial intelligence
fault diagnosis
expert system
probabilistic neural network
url http://dx.doi.org/10.1051/matecconf/20152503010
work_keys_str_mv AT liyingshun researchontransformerfaultbasedonprobabilisticneuralnetwork
AT lijingjing researchontransformerfaultbasedonprobabilisticneuralnetwork
AT hanjunfeng researchontransformerfaultbasedonprobabilisticneuralnetwork