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Method of machine technical state assessment on the basis of joint signal analysis

机译:基于联合信号分析的机械技术状态评估方法

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Joint analysis of two signals which are observed during machine operation allows us to acquire information on such phenomena occurring within the machine which cannot be obtained as the results of an analysis of single signals. This knowledge makes it purposeful to assume that the joint analysis of a major number of signals allows us also to acquire new information on the machine state. In this paper the concept of joint signal analysis based on a signal analysis in both "micro" and "macro" time domains was described. In order to calculate values of joint features of signals and determine the machine state on the basis of the joint analysis results the generalized data window was introduced. In order to limit a number of simultaneously considered signals and determine a relation between signal feature values and machine states, the procedure based on an application of additional virtual signals was proposed. In order to verify the elaborated method an active diagnostic experiment was carried out. The experiment result was a set of learning data, which enables us to construct a diagnostic classifier. Exemplary results of classification of technical state of a machine were also presented.
机译:在机器运行期间观察到的两个信号的联合分析使我们能够获取有关机器内部发生的此类现象的信息,而这些信息是无法通过单个信号的分析结果获得的。这些知识使我们有目的地假设对大量信号的联合分析可以使我们也获得有关机器状态的新信息。在本文中,描述了基于“微”和“宏”时域中信号分析的联合信号分析的概念。为了计算信号的联合特征值并根据联合分析结果确定机器状态,引入了通用数据窗口。为了限制同时考虑的信号的数量并确定信号特征值与机器状态之间的关系,提出了基于附加虚拟信号的应用的程序。为了验证详细方法,进行了主动诊断实验。实验结果是一组学习数据,这使我们能够构建诊断分类器。还给出了机器技术状态分类的示例性结果。

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