Signal extraction and fault identification of steam turbine vibration

Junru Gao, Xin Meng, Yajun Sun
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引用次数: 2

Abstract

This paper, the vibration signal of steam turbine which are detected by fault diagnosis are influenced by environmental noise and detecting instrument itself, leading to vibration signal waveform distortion which contains a large number of non-stationary composition, and cannot effectively react turbine fault characteristics, and the coupling among different fault characteristics of unilateral fault features make it difficult to identify fault accurately. Aiming at solving this problem, this paper combine the axis of spectrum analysis with path analysis of vibration signal processing and recognition method, two kinds of detection method in the fault diagnosis process validation to ensure the accuracy of test results.
汽轮机振动信号提取与故障识别
本文研究了汽轮机故障诊断检测到的振动信号受环境噪声和检测仪器本身的影响,导致振动信号波形失真,其中包含大量非平稳成分,不能有效反应汽轮机故障特征,且单侧故障特征的不同故障特征之间存在耦合,难以准确识别故障。针对这一问题,本文将轴向频谱分析与路径分析相结合,对振动信号进行处理和识别方法,在故障诊断过程中对两种检测方法进行验证,保证检测结果的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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