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在机械故障智能诊断过程中,提取反映机器状态的有效特征参量时要花费大量的时间和精力,而且这种依靠人的经验来提取特征参量的方法有一定的盲目性。为了解决如何尽可能快而有效地寻找一组特征参量,使诊断对象不同状态之间的可分性为最佳的问题,采用了K—L变换特征提取方法,研制出相应的软件,并已将该方法应用在大庆油田抽油机减速箱智能故障诊断系统中。
In the process of intelligent diagnosis of mechanical faults, it takes a lot of time and energy to extract the effective characteristic parameters that reflect the state of the machine, and the method of extracting the characteristic parameters by using human experience has a certain blindness. In order to solve the problem of how to find a set of characteristic parameters as quickly and effectively as possible and to make the separability between different states of the diagnosis object be the best, K-L transform feature extraction method is used to develop the corresponding software. The method is applied to intelligent fault diagnosis system of gearbox of pumping unit in Daqing Oilfield.