Intelligent fault diagnosis of medical equipment based on long short term memory network

In order to solve the current problems in medical equipment maintenance, this study proposed an intelligent fault diagnosis method for medical equipment based on long short term memory network(LSTM). Firstly, in the case of no circuit drawings and unknown circuit board signal direction, the symptom...

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Veröffentlicht in:	Sheng wu yi xue gong cheng xue za zhi 2021-04, Vol.38 (2), p.361-368
Hauptverfasser:	Liu, Xiangjun, Lang, Lang, Zhang, Shihui, Xiao, Jingjing, Fan, Liping, Ma, Jianchuan, Chong, Yinbao
Format:	Artikel
Sprache:	chi
Schlagworte:	Algorithms Artificial neural networks Back propagation Circuits Classification Convolution Electricity Fault diagnosis Long short-term memory Medical equipment Memory, Short-Term Model accuracy Neural networks Neural Networks, Computer Recurrent neural networks Short term
Online-Zugang:	Volltext
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