Transformer winding state diagnosis method based on dynamic nonlinear characteristic sequence

Abstract

The invention discloses a transformer winding state diagnosis method based on a dynamic nonlinear characteristic sequence. The method comprises the following steps: acquiring vibration signals under different load currents by arranging a vibration sensor of an oil tank of a transformer, and acquiring current signals; extracting nonlinear ratio characteristics from a relation between the collectedcurrent and vibration by utilizing a cross recurrence plot analysis method, and computing a nonlinear characteristic sequence changed along with the load current; establishing hidden Markov models corresponding to different states, and training the HMM models by utilizing the nonlinear characteristic sequence; and for the to-be-detected transformer winding, inputting the corresponding nonlinear characteristic sequence into the trained models, comparing the probabilities obtained by different models, thereby acquiring an actual state result of the transformer winding.

Description

technical field [0001] The invention relates to the field of transformer winding fault detection and diagnosis, in particular to a transformer winding state diagnosis method based on a dynamic nonlinear characteristic sequence. Background technique [0002] The power transformer is one of the core equipment of the power grid, and its value is relatively high. For large power transformers, about 41% of faults are caused by on-load tap-changers (OLTCs), and 19% of faults are due to winding faults. But winding faults are far more fatal than faults caused by on-load tap-changers. For transformers without on-load tap-changers, the vast majority of faults (about 26.6%) are caused by winding faults. The winding is the most critical and fragile part inside the transformer, and once the winding fails, the transformer needs to be inspected and further repaired, which will bring huge economic losses. [0003] At present, the off-line detection methods of transformer windings include...

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Problems solved by technology

[0004] Based on this, it is necessary to address the problem of transformer winding state monitoring and diagnosis. In order to solve the problems existing in the background technology, a new transformer winding fault state diagnosis method is proposed, which uses the relationship between dynamic electromagnetic force of winding and nonlinear vibration to detect the state of transformer winding

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