【摘要】 快速傅里叶变换在信号分析中有着十分重要的作用,但传统的快速傅里叶变换无法分析通风机故障存在的趋势突变,故障的开始与结束等特征,而这些特征信号往往包含着故障的重要信息,同时,快速傅里叶变换对故障的局部信号分析也无能为力。为此,文中提出将多尺度小波理论与快速傅里叶变换相结合的方法,利用小波的"数学显微镜"特性,弥补快速傅里叶变换的不足,并将该方法应用于通风机故障诊断中,取得了良好的效果,试验表明,该方法可以有效地提高故障诊断的准确性。更多还原

【Abstract】 The Fast Fournier Transform has a vital role in the signal analysis,but the traditional Fast Fournier Transform is unable to analyze the sudden change of tendency for the ventilator breakdown,breakdown start and stop characteristic.These characteristic signals are often containing important information of the breakdown.At the same time,it’s also helpless for the Fast Fournier Transform to analyze the breakdown’s partial signal.Therefore,the combined method of the multi-scaling wavelet theory and the Fast Fournier Transform is proposed.Using the characteristic of wavelet "mathematics microscope",make up the insufficiency of the Fast Fournier Transform,and apply this method in the ventilator failure diagnosis.The experimental results show the method can improve the accuracy of fault diagnosis.更多还原