Diagnosis method of power transformer winding on-line monitoring device based on multi-information fusion

Abstract

Multi-information fusion power transformer winding online monitoring device and diagnosis method, the device includes voltage sensor, current sensor, vibration acceleration sensor, phase-shifting amplifier circuit, signal conditioning circuit, A / D conversion control circuit, DSP, dual-port RAM and MCU , the diagnosis method: collect the three-phase primary side voltage signal, three-phase secondary side voltage signal, three-phase primary side current signal and three-phase mechanical vibration signal of the power transformer, process the signal, and pass the mechanical vibration digital signal of each phase through FFT decomposes to obtain the fundamental frequency amplitude of the mechanical vibration signal of each phase, establishes an online short-circuit reactance model, calculates the short-circuit reactance of each phase winding of the power transformer, and uses the short-circuit reactance and current effective value of each phase winding and the corresponding mechanical vibration signal. Fundamental frequency amplitude fitting results are used to diagnose mechanical vibration faults of transformers.

Description

technical field [0001] The invention belongs to the technical field of power transformer fault diagnosis, and in particular relates to an online monitoring device and a diagnosis method for a power transformer winding with multi-information fusion. Background technique [0002] The power transformer is one of the important power transmission and transformation equipment in the power system. It connects multiple voltage levels and plays a pivotal role in the power grid. The safety and reliability of its operation directly affects the operation safety of the power grid, and improving the operation reliability of power transformers is of great significance to the safe and reliable operation of the entire power grid. [0003] Power transformer faults include mechanical faults, insulation faults, overheating faults, etc. Most insulation faults are caused by mechanical faults. More than 60% of the statistical reports on large-scale power transformer faults belong to the internal ...

AI Technical Summary

Problems solved by technology

[0004] The current winding fault diagnosis methods are mainly frequency response analysis method and short-circuit reactance test method. Both methods require offline detection after the transformer is out of operation, and cannot monitor the operation status of the transformer in real time.

Although the vibration analysis method can monitor the transformer online, this method has high requirements on the surrounding environment. Factors such as the operating condition of the transformer and the ambient temperature will have a great impact on the measurement results of the vibration signal of the transformer.

Combining several existing diagnostic methods, it can be seen that the current online fault diagnosis of power transformer windings only uses a single or a few test parameters to obtain diagnostic results.

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