Volume 43 Issue 5
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LI Shiguang, XUE Han, LI Zhen, GAO Zhengzhong, LI Ying. Fault diagnosis of mine-used transformer based on optimized fuzzy Petri net[J]. Journal of Mine Automation, 2017, 43(5): 54-57. DOI: 10.13272/j.issn.1671-251x.2017.05.013
Citation: LI Shiguang, XUE Han, LI Zhen, GAO Zhengzhong, LI Ying. Fault diagnosis of mine-used transformer based on optimized fuzzy Petri net[J]. Journal of Mine Automation, 2017, 43(5): 54-57. DOI: 10.13272/j.issn.1671-251x.2017.05.013
shu

Fault diagnosis of mine-used transformer based on optimized fuzzy Petri net

  • 1.

    College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China

  • 2.

    Electromechanical Department, Rizhao Electrical and Mechanical Engineering S

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  • For oil-immer transformer used in places with coal dust and no explosion hazard,an improved fault diagnosis model of mine-used transformer based on fuzzy Petri net was proposed. Fuzzy generation rule was used to establish fault diagnosis model according to relationship between fault symptom and the fault. Self-learning and adaptive ability of Elman network algorithm are used to optimize initial parameters of the model, and the settings of initial parameters of the fuzzy Petri net are more reasonable. Matlab simulation results show that fault diagnosis accuracy of the optimized model and unoptimized model is 87.88% and 75.76% respectively, which verifies effectiveness of the optimized model.
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