A Fast and Energy-Saving Neural Network Inference Method for Fault Diagnosis of Industrial Equipment Based on Edge-End Collaboration | |
Wang QZ(王其朝)1,3,4,5; Jin GS(金光淑)2; Li Q(李庆)1,3,4,5; Wang K(王锴)1,4,5; Yang ZY(杨祖业)2; Wang H(王宏)1,4,5 | |
2021 | |
会议日期 | July 27-31, 2021 |
会议地点 | Jiaxing, China |
页码 | 67-72 |
英文摘要 | Data-driven fault diagnosis algorithms represented by deep learning have been widely used in industrial equipment fault diagnosis. However, the lack of real-Time performance has always restricted the development of such methods. With the development of edge computing, many edge and end computing devices are deployed in industrial environments. For this distributed computing environment, we propose a distributed neural network inference method with edge-end collaboration. This method uses an edge server to cooperate with multiple end devices for network inference. In the diagnosis of industrial equipment, it can increase the speed of inference, reduce the traffic of the edge network, and help the application of deep neural networks in industrial environments. |
源文献作者 | IEEE Robotics and Automation Society ; Shenyang Institute of Automation CAS ; Shenzhen Academy of Robotics |
产权排序 | 1 |
会议录 | 2021 IEEE 11th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2021 |
会议录出版者 | IEEE |
会议录出版地 | New York |
语种 | 英语 |
ISSN号 | 2642-6633 |
ISBN号 | 978-1-6654-2527-8 |
内容类型 | 会议论文 |
源URL | [http://ir.sia.cn/handle/173321/29951] |
专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
通讯作者 | Wang QZ(王其朝) |
作者单位 | 1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 2.Microcyber Corporation, Shenyang 110179, China 3.University of Chinese Academy of Sciences, Beijing 100049, China 4.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China 5.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
推荐引用方式 GB/T 7714 | Wang QZ,Jin GS,Li Q,et al. A Fast and Energy-Saving Neural Network Inference Method for Fault Diagnosis of Industrial Equipment Based on Edge-End Collaboration[C]. 见:. Jiaxing, China. July 27-31, 2021. |
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