盲源分离技术在振动法检测变压器故障中的应用

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Abstract The vibration signals of transformer oil tank can represent the fault of inner winding and core, which has pretty good application prospect. But the signal measured on the oil tank surface is not only mixture of winding and core vibration but also dependent with each other, therefore, it is difficult to separate with normal BSS arithmetic. As a result, it’s hard to diagnose the fault of winding and core respectively. This paper introduced a method based on Sub-band decomposition independent component analysis(SDICA) arithmetic to separate winding and core vibration signal. First, SDICA arithmetic which can separate the signals with a certain correlation degree was introduced. Then simulated vibration signals were adopted to test and compare the ability of SDICA with fast independent component analysis(fastICA) in separating mixture signals. The results show that SDICA arithmetic is valid to separate transformer vibration signals. Then applied the SDICA arithmetic to the vibration signals measured from a test transformer and discussed the effect of measuring position, voltage and load to the separate result. Finally, applied the SDICA arithmetic to the vibration signals measured from a power transformer which running with a hidden danger. The results show that winding and core vibration signals are separated successfully and the fault signature can be seen clearly from it, which is correspondence to the failure condition. It can be drawn a conclusion that the SDICA arithmetic introduced in this paper is robust in separating the vibration signals measured from transformer oil tank. The results are significant in extending the vibration method to the fault diagnosing in transformer winding and core.

Key words： Power transformer blind source separation SDICA source signals winding core

Received: 25 March 2011 Published: 20 March 2014

PACS:

TM771

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	Articles by authors
	Guo Jun
	Ji Shengchang
	Shen Qi
	Zhu Lingyu
	Ou Xiaobo
	Du Liming

Cite this article:

Guo Jun,Ji Shengchang,Shen Qi等. Blind Source Separation Technology for the Detection of Transformer Fault Based on Vibration Method[J]. Transactions of China Electrotechnical Society, 2012, 27(10): 68-78.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2012/V27/I10/68

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