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Research on Fault Diagnosis Method of Thermal Power Generating Units Based on Process

机译:基于过程的火电机组故障诊断方法研究

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At present, in the thermal power generating u-nits, most fault diagnosis methods of rotating machinery rely on extracting eigenvalue from the vibration waveform. The vibration waveform signal is the representation of the condition. If the fault occurs, under certain condition, it is possible that the fault information is not revealed in the vibration waveform, or submerged by other information. Under such circumstance, the fault diagnosis method based on the randomly extractive information of condition can not well differentiate these faults. However, the fault, in any case, is accompanied by some symptoms. Under a condition, the vibration information of the fault may appear decentralized and random, but when the whole process is taken into consideration , the rules stand out. To describe the rule of changes in the vibration process, this paper proposes a new diagnosis method based on the process, with the information entropy (IE) matrix as its identification index.
机译:当前,在火力发电装置中,旋转机械的大多数故障诊断方法都依赖于从振动波形中提取特征值。振动波形信号表示状态。如果在特定条件下发生故障,则故障信息可能不会在振动波形中显示出来,或被其他信息淹没。在这种情况下,基于状态的随机提取信息的故障诊断方法不能很好地区分这些故障。但是,无论如何,该故障都伴随有一些症状。在一定条件下,故障的振动信息可能出现分散,随机的现象,但考虑到整个过程,其规则就显得突出了。为了描述振动过程的变化规律,本文提出了一种基于振动过程的诊断方法,即以信息熵(IE)为识别指标。

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