工矿自动化2013，Vol.39Issue(2)：66-71,6.DOI:10.7526/j.issn.1671-251X.2013.02.017
基于Mel频率倒谱系数和遗传算法的煤矸界面识别研究
Research of coal and gangue interface recognition based on Mel frequency cepstrum coefficient and genetic algorithm
摘要
Abstract
In view of problems that y ray method is not suitable for working face with no or little radioactive elements in roof and radar detection method has little detection range and serious signal attenuation which were used in current coal and gangue interface recognition technologies, the paper proposed a coal and gangue interface recognition method based on Mel frequency cepstrum coefficient and genetic algorithm. The method uses feature difference of acoustic signal produced by dropping process of coal and gangue to recognize coal and gangue. It uses Mel frequency cepstrum coefficient to process denoised acoustic signal of coal and gangue in frequency domain to extract 32 dimensions feature parameters of the acoustic signal, uses genetic algorithm to make optimal process for the parameters to get the best parameter combination, and uses support vector machine and BP neural network to recognize the best parameters. The experiment results showed that the method can recognize falling state of coal and gangue accurately.关键词
放顶煤开采/煤矸界面识别/Mel频率倒谱系数/MFCC/遗传算法/支持向量机/BP神经网络Key words
top coal caving/ coal and gangue interface recognition/ Mel frequency cepstrum coefficient/ MFCC/ genetic algorithm/ support vector machine/ BP neural network分类
矿业与冶金引用本文复制引用
何爱香,王平建,魏广芬,张守祥..基于Mel频率倒谱系数和遗传算法的煤矸界面识别研究[J].工矿自动化,2013,39(2):66-71,6.基金项目
国家自然科学基金资助项目(61174007) （61174007）
山东工商学院青年科研基金项目(2011QN078). （2011QN078）
