工矿自动化2017，Vol.43Issue(9)：102-105,4.DOI:10.13272/j.issn.1671-251x.2017.09.018
基于信息融合和神经网络的煤岩识别方法
Identification method of coal and rock based on information fusion and neural network
摘要
Abstract
In view of problems that coal and rock identification systems use single sensor to monitor data and have low precision,reliability and stability,an identification method of coal and rock based on information fusion and neural network was proposed.A variety of necessary sensors are added to the existing shearer,which are used to collect current,pressure,vibration frequency,acceleration and other signals of the shearer under different situations.Wavelet packet is used for characteristics extraction,and BP neural network is used for data fusion,so as to achieve coal and rock identification.The test results of the real machine show that the identification error of the proposed method is within ±0.5,which verifies its validity.关键词
煤炭开采/煤岩识别/采煤机/多传感器系统/信息融合/神经网络Key words
coal mining/coal and rock identification/shearer/multi-sensor system/information fusion/neural network分类
矿业与冶金引用本文复制引用
雷静,余斌..基于信息融合和神经网络的煤岩识别方法[J].工矿自动化,2017,43(9):102-105,4.基金项目
成都农业科技职业学院科研项目(CNY15-17). （CNY15-17）
