基于剪切力特征的圆盘剪分切机故障监测方法

Condition monitoring method for disc slitting machine based on shearing force characteristics

设计了一种能够实时在线检测金属板材圆盘剪分切的三向力测量系统,提供对金属板材圆盘剪三向分切力特性分析的手段和平台,检测过程和剪切力数据稳定可靠。针对圆盘剪分切力信号特征不显著,以及故障状态难以在线远程识别的问题,提出了一种基于本征模态函数(IMF)能量矩和隐式Markov模型(HMM)相结合的圆盘剪分切机故障诊断方法。使用经验模态分解(EMD)方法将振动信号分解成若干本征模态函数(IMF),计算本征模态函数(IMF)能量矩作为状态特征信息,构造特征向量,建立隐式Markov模型对圆盘剪分切机进行故障监测识别。实验表明,该方法能有效识别圆盘刀周向跳动、机床空转、机床停机3种故障,可用于圆盘剪分切机故障监测。

A three-dimensional force measuring system was designed to test disc slitting of metal plate in real time online and provide a way and platform for analyzing the characteristics of the three-dimensional force of disc slitting for metal plate, and the testing process and the shearing force data were both stable and reliable. Then, for the problem of non-significant signal feature of disc slitting force and the difficulty in long-range online identification under malfunction, the fault diagnosis method on disc slitting machine was proposed based on the intrinsic mode function(IMF) energy moment and the hidden Markov model(HMM), and it used empirical mode decomposition(EMD) method to decompose vibration signals into multiple intrinsic mode functions(IMF), constructed the feature vectors by calculating energy moments of IMF as state feature information, and established a hidden Markov model to monitor and identify the malfunctions of the disc slitting machine. The experiment shows that the above method effectively identify the malfunctions such as circular jumping of disc cutter, machine tool idling and machine tool shutdown, and it detects malfunctions of the disc slitting machine.