基于小波变换去除风机振动信号噪声在煤矿主通风机故障诊断系统的应用
首发时间:2010-07-02
摘要:主通风机是煤矿四大固定设备之一,本文主要对煤矿主通风机故障机理进行了深入分析;鉴于小波变换具有良好的时-频局部化特性和自适应能力,非常适合于机械故障信号分析,论文深入研究了小波分析理论及其应用。论文根据风机振动信号的特点和小波基函数的性质选取了适用于风机故障诊断的小波基函数,在此基础上利用小波变换消除风机振动信号中的噪声,其目的是为了及时掌握风机的运行状态,充分发挥风机的效能、保证矿井通风安全。
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The Application about Removing Noise From Fan Vibrational Signal of Coal Mine Main-Fan Fault Diagnosis system Based on WT
Abstract:Coal mine main-fan is one of the four fixed equipments in coal mine.In view of the wavelet transform has good time-frequency localization characteristic and self-adaptive capability, it is very appropriate for machine failure signal diagnosis. The paper researches the wavelet analysis theory and its application. The thesis chooses wavelet base function which is suitable for coal mine fan according to the character of fan vibration signal and the quality of the wavelet base function. On the basis of this the paper excludes the noise in fan vibration signal by using wavelet transform and constructs fan typical failure character table based on energy analysiss so that we can master its running station in time to express its efficiency sufficiently and ensure the safety of coal mine ventilation .
Keywords: fault diagnosis vibration wavelet transform nosie
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基于小波变换去除风机振动信号噪声在煤矿主通风机故障诊断系统的应用
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