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出 处:《机械设计与制造》2006年第9期143-145,共3页Machinery Design & Manufacture
基 金:国家自然科学基金(10402035)资助项目
摘 要:基于小波包分解结果,针对信号在不同频段内能量的变化,进行故障辨识。信号发生故障一般都伴随着能量的变化,而小波包提供了一种将信号划分到不同频段的方法,借助小波包将信号细分到各个频段,分别求出频段内信号的能量,观察能量的变化就可以判断出是否发生了故障以及故障的程度。以一组转子系统正常与故障时的实验数据为例,详细地说明了该方法的可行性,取得了准确的结果。该方法可以被广泛应用于各种平稳信号或非平稳信号的故障监测。Based on the results of wavelet package decomposition and the energy variety in different frequency stage, a method can be adopted to detect the faults between the normal signals and the fault ones. If there occur faults in signals, there must be energy variety in different frequency stages. The signal can be decomposed into different frequency stage by wavelet package, and the energy in different stages can be calculated, With the numerical value, an energy vector can be set up, which can express whether the fault occur or not and how severe the faults are. Taken a series of experimental data as an example, the course of the method is explained in detail. The results show that the method can availably distinguish the fault signal between the normal one. This method can be widely used to detect steady and non - steady signals.
分 类 号:TH165.3[机械工程—机械制造及自动化]
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