Transactions of Materials and Heat Treatment

Title：Fault diagnosis on clutch brake based on firefly optimization BP neural network

Authors： Hu Kai Cao Chunping Sun Yu Wang Yu

Unit： (School of Mechanical Engineering Nanjing University of Science and Technology Nanjing 210094 China)

KeyWords： high-speed press clutch brake BP neural network firefly algorithm fault diagnosis

ClassificationCode：TH165

year,vol(issue):pagenumber：2023,48(6):124-129

Abstract：

In order to solve the fault problem of clutch brake in high speed press, a fault diagnosis algorithm based on firefly optimization BP neural network was proposed, which prevented the problems such as easy entry into local optimum in the traditional BP neural network algorithm. Then, the types and causes of general clutch brake faults were introduced, and the basic theory for fault diagnosis algorithm of firefly optimization BP neural network was analyzed to establish a clutch brake fault diagnosis model based on this algorithm. For the clutch brake in high-speed press, the simulation verification was carried out by Matlab. The results show that the fault diagnosis error of firefly optimization BP neural network is significantly smaller than that of the traditional BP neural network and the genetic algorithm optimization BP neural network, and the correct rate of fault diagnosis reaches 89.167%.

Funds：

江苏省科技成果转化专项资金（BA2021067）

胡凯（1996-），男，硕士研究生

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