Fault Diagnosis Method of Hydropower Units Based on Integrated Information Fusion Technology

Zhao, Daoli; Liang, Wu; Nan, Haipeng; Luo, Xingqi; Ma, Wei

doi:10.1109/appeec.2009.4918373

Cited by 2 publications

(2 citation statements)

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“…The corresponding failure detection and diagnosis have been the subject of extensive researches. [1][2][3][4] According to statistics, nearly 80% faults of HGU are vibration faults. 1 Therefore, the diagnosis of vibration faults has crucial significance for the safety of HGU operation.…”

Section: Introductionmentioning

confidence: 99%

“…In previous studies, correlation analysis has been used to measure the relationship between vibration and rotating speed, and the correlation coefficient is taken as one of the fault features for diagnosis to improve the accuracy of fault diagnosis. [2][3][4] However, the correlation coefficient is only a measurement of linear relationship and cannot be used to describe the nonlinear relationship, 5 while the relationship between vibration and rotating speed is quite complicated. 6 Therefore, the complex and nonlinear relationship between vibration and rotating speed may not be revealed sufficiently by the correlation analysis, and the vibration-speed curve is proposed, which can be obtained by experimentally measuring the vibration under different speed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of vibration–speed curve for hydroelectric generator unit using statistical fuzzy vector chain code and support vector machine

Xiao

Zhou

Xiao

et al. 2013

Proceedings of the Institution of Mechanical Engineers, Part O:

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The faults of hydroelectric generator unit have many different symptoms, and the relation between vibration amplitude and rotating speed is an important diagnosis criterion. In this article, a novel vibration-speed curve identification approach based on statistical fuzzy vector chain code and support vector machine is proposed and applied to identify the relation between vibration amplitude and rotating speed. In the identification process, the shape features of vibration-speed curve are extracted by statistical fuzzy vector chain code at first and then input to support vector machine to identify the type of vibration-speed curve; furthermore, the fault type of hydroelectric generator unit can be determined. Compared with the previous methods, statistical fuzzy vector chain code shows the advantages of low feature dimension, simple calculation, invariance to scaling and translation, and sensitive variance to rotation. The results of identification and comparative experiments show that the proposed method is more effective and efficient and can identify the vibration-speed curve with satisfactory accuracy.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%