Mine Gallery Rig Performance Test Based on BP Neural Network and Multi-sensor Data Fusion

被引：0
|
作者：
Zan, Hongyang [1 ]
He, Kaiming [1 ]
Zhu, Yangyang [1 ]
Wang, Mei [1 ]
Dai, Fenlei [2 ]
机构：
[1] Xian Univ Sci & Technol, Sch Elect & Control Engn, Xian, Peoples R China
[2] Xian Res Inst CCTEG, Qual Inspect Ctr, Xian, Peoples R China
来源：
2016 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C) | 2016年
关键词：
multi-sensor; BP neural network; data fusion; Grubbs criterion; gallery rig;
D O I：
10.1109/IS3C.2016.271
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Traditional gallery rig's factory inspection process is complex and the result is not accurate. It is necessary to find a simple way to realize the factory inspection. In this paper multisensor data fusion based on Grubbs criterion is used in gallery rig performance test, and a classification algorithm based on BP neural network is analyzed and simulated. The results showed the validity of the algorithm, and it successfully realized the accurate evaluation of the gallery rig performance. So it has a strong practical value under the premise of both control costs and ensure the evaluation effect.
引用
收藏
页码：1075 / 1079
页数：5
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