小波包信号提取算法及其在识别磨煤机煤位敏感声频段中的应用  

Wavelet Packet Signal Extracting Algorithm and its Application in Identification of Sensitive Audio Frequency and Coal Level in Ball Mill

作　　者：曲守平[1] 赵登峰[2] 王国强[2] 宋协春 

机构地区：[1]长春大学,吉林130025 [2]吉林工业大学 [3]沈阳重型机器厂

出　　处：《矿山机械》2001年第1期29-31,共3页Mining & Processing Equipment

摘　　要：利用小波包将信号按任意时频分辨率（满足测不准原理）分解到不同频段的特点，本文提出了基于“能量——频段”的磨煤机煤位敏感声频段的识别方法——小波包信号特征提取算法、通过对不同煤位时磨煤筒体机声辐射信号的小波包分解和各个频段上分解信号的特征量提取，确定了磨煤机简体煤位敏感声频段。An effective method. Wavelet Packet Signal Character Extractiog Algorithm, is proposed in this paper, to identify the sensitive audio frequency band of the coal level of a ball mill, based on the 'energy-frequency band', according to the characters of decomposing signals to any time frequency resolution using wavelet packet. The sensitive audio frequency band is established. through wavelet packet decomposing the sound radiation signals of different coal levels in the mill and the character extraction of the decomposed signals of different frcquency band.

关 键 词：小波变换 信号提取 磨煤机 煤位 声频 识别 

分 类 号：TD45[矿业工程—矿山机电]