Intelligent trouble diagnosis method for tractive power supply system and system thereof

Abstract

The invention provides an intelligent trouble diagnosis method for a tractive power supply system, which comprises the following steps: firstly establishing a system description library for a system to be diagnosed; then collecting observed value data required by the diagnosis in real time, carrying out pretreatment, acquiring system predicted values in accordance with a system element action description library and the observed value data, and performing a fuzzy consistency check on the predicted values and the observed values to judge the difference, if not, performing a layering consistency diagnosis on the system to generate a fault candidate collection; selecting a fault action model to perform an abductive diagnosis to determine fault reasons and fault positions, thereby predicating relay protection action and breaker action; and finally comparing the consistency of a predicated action result and real action to obtain the fault reasons and the results, and carrying out alarm output. The invention also provides an intelligent trouble diagnosis system for a tractive power supply system. The invention is suitable for the tractive power supply system, can immediately and exactly find out the fault elements and the fault reasons, overcomes computational complexity and realizes real-time monitoring and fault diagnosis for the tractive power supply system.

Description

technical field [0001] The invention relates to a fault diagnosis method and system thereof, in particular to an intelligent fault diagnosis method and system thereof for a power system. Background technique [0002] For the fault diagnosis of the power system, the common method at home and abroad is to use the expert system to develop the intelligent fault diagnosis system of the power grid. Relays and circuit breakers themselves may refuse to operate or malfunction. At the same time, these switching signals are often mistaken or even lost during transmission and collection. The above situations will lead to fault reasoning errors and misunderstandings in the expert system, which cannot be timely and accurate. In addition, due to the defects of the expert system itself, such as relying solely on expert experience and unable to discover unknown faults, the portability of the intelligent fault diagnosis system developed by the expert system is poor, and the diagnosis The res...

AI Technical Summary

Problems solved by technology

[0004] Although the model-based fault diagnosis method avoids the reliance on expert experience and has the advantages of being able to discover unknown faults, it has not yet been applied to successful cases in the field of intelligent fault diagnosis of traction power supply systems. The reasons are: on the one hand, Since the traction power supply system is a high-voltage and large-scale power system, it has the characteristics of dynamic uncertainty. There are many interference factors in the operation of the power supply system, which makes the measurement data of the system have a lot of noise data. At the same time, the measurement data is also scattered and inconsistent. Accuracy, the above characteristics not only cause the complexity of cause and effect in diagnostic reasoning, but also affect the results of diagnosis; on the other hand, the traction power supply system is not static, and there will be more complex systems from time to time - electric locomotives Some traction power supply systems sometimes put in the series compensation device, sometimes do not put in the series compensation device, etc., which cause the structural dynamics of the traction power supply system, and the fault diagnosis method based on the model is generally only for the structural fixed, deterministic system

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