烟草科技2019，Vol.52Issue(2)：109-114,6.
基于SOM神经网络的制丝生产线设备故障趋势辨识方法
Method for identifying failure trend of equipment in primary processing line based on SOM neural network
雷建生 1李再 2冉宝新 1张建林 1赵伟 1顾农2
作者信息
- 1. 河北白沙烟草有限责任公司,石家庄市珠江大道366号 050001
- 2. 湖南合立拓普科技有限公司,长沙市芙蓉中路513号佳天国际新城1栋1218号 410001
- 折叠
摘要
Abstract
In order to provide an early warning for equipment failures in primary processing line, a method for identifying the failure trend of equipment was proposed based on SOM neural network. The key process variables in primary processing line were categorized and five models were established separately for running status monitoring, including no obvious trend, ascending trend, descending trend, positive step trend and negative step trend. The ascending/descending trend referred to the slow but abnormal variations of equipment running status induced by the ascending/descending of process variables; and the positive/negative step trend referred to the instantaneous and noticeable variations of equipment running status caused by the sudden variations of process variables. The established models were trained by SOM neural network to realize on-line monitoring of equipment running trend. The said method was compared with Shewhart control chart, the results indicated that within 30 working days, the effective abnormal trend detected by the proposed method was 38 times more than that detected by Shewhart control chart, and the accuracy of early warning increased by 33%. The proposed method provides a technical support for the promotion of intelligent failure diagnosis.关键词
卷烟/制丝生产线/设备故障/趋势预警/SOM神经网络/控制图Key words
Cigarette/Primary processing line/Equipment failure/Trend early warning/SOM neural network/Control chart分类
轻工纺织引用本文复制引用
雷建生,李再,冉宝新,张建林,赵伟,顾农..基于SOM神经网络的制丝生产线设备故障趋势辨识方法[J].烟草科技,2019,52(2):109-114,6.
