Time-Domain Experimental Identification Technique of Rotating Short Systems

随着旋转机械向更高、更轻的方向发展，实现其平稳、安静运行的难度越来越大。为了在这种情况下对机器进行建模，实验识别技术变得更加重要。在本研究中，我们尝试开发一种适用于旋转机械的新的实验识别技术。为了识别旋转机器，我们遇到了一些困难，这在通常的非旋转机器中是没有的。首先，旋转机器在高速运转时通常难以被激励。其次，它们包含诸如不平衡和初始缺陷等参数，这些参数在通常的非旋转机器中并不重要。第三，它们经常成为非线性系统。为了克服这些困难，我们在以前的研究中开发了频域技术。然而，这些技术需要很长时间才能进行识别。为了改善这一缺陷，我们尝试开发一种时域技术。首先，作为基础研究，我们考虑了一个带有圆盘的转轴，并提出了一种使用最小二乘法和拉格朗乘数法的识别技术。通过数值模拟和实验验证了该方法的适用性。然后对该方法进行了推广，使其适用于非线性系统。最后，我们开发了一种连续旋转机器的技术。通过数值模拟和实验验证了该方法的适用性。

As rotating machines becomes higher and lighter, it becomes more difficult to realize their stable and quiet operation. To model machines in this situation, experimental identification techniques become more important. In this research we attempt to develop a new experimental identification technique suitable for rotating machines. To identify rotating machines, we encounter some difficulties which are free in the usual non-rotating machines. First the rotating machines are usually difficult to be excited during their high-speed operation. Second they contain such parameters as unbalances and initial imperfections, which are not important in the usual non-rotating machines. Third they often become nonlinear systems. To overcome these difficulties, we developed, in a former research, frequency-domain techniques. These techniques, however, require long time to conduct identification. To improve this defect, we attempt to develop a time-domain technique. First, as a fundamental study, we consider a rotating shaft with a disc, and propose an identification technique using the least square method and the Lagrane multiplier method. We showed its applicability by numerical simulation and experiment. Then we generalize the technique so that it is applicable to nonlinear systems. Finally, we developed a technique for continuous rotating machines. We also showed its applicability by numerical simulation and experiment.