Fault diagnosis device and method based on multi-agent system and wavelet analysis

Abstract

The invention discloses a fault diagnosis device and a fault diagnosis method based on a multi-agent system and wavelet analysis. The device comprises a mutual inductor group, a data acquisition module, a control and man-machine interaction module, a multi-agent system module, and a database module. Active electronic voltage and a current transformer are adopted by the mutual inductor group; and the data acquisition module comprises a follower circuit, an amplification circuit, a biasing circuit and an alternate-current / direct-current (A / D) convertor. The control and man-machine interaction module comprises a protocol conversion module, a 485 bus, an Ethernet network cable, and an upper computer. The multi-agent system module comprises a task decomposition agent, a task distribution agent, a diagnosis agent, an assisting agent and a decision-making agent. The running of the device is controlled by a control program, the running state of a primary side of a power grid is displayed in real time, and historical data is called by a database; and the acquired signal is sent to the task decomposition agent, the fault diagnosis result of the decision-making agent is received for alarming, and a user is assisted in making a final decision.

Description

technical field [0001] The invention belongs to the technical field of power transmission and transformation, in particular to a fault diagnosis device and method based on a multi-agent system and wavelet analysis. Background technique [0002] With the improvement of the voltage level of the power grid and the access of distributed power sources, the fault information of the distribution network is becoming more and more complicated; the uncertain faults of the power grid such as the malfunction and refusal of the circuit breaker increase the difficulty of fault diagnosis of the distribution network. difficulty. This has led to the fact that the traditional diagnostic method based on relay protection action information is increasingly unable to achieve satisfactory results. Currently proposed diagnostic methods mainly include expert system method, Petri net, artificial neural network, fuzzy set theory and so on. [0003] The fault diagnosis method of the expert system use...

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Problems solved by technology

[0003] The fault diagnosis method of the expert system uses computer technology to integrate theoretical knowledge and expert experience in related fields, but obtaining a complete knowledge base is the bottleneck of the fault diagnosis expert system, and incomplete knowledge may lead to the inference of the expert system. The fault diagnosis method based on Petri net has the advantages of graphical structure expression, fast reasoning search and mathematical diagnosis process, but its fault tolerance is poor, and it is difficult to identify wrong alarm information. In the case of multiple faults, the diagnostic performance of the Petri net is not ideal; the fault diagnosis method based on the artificial neural network forms a training sample set for the fault diagnosis neural network model from a large number of sufficient fault examples provided by experts in the field. Certain learning and training enable the neural network to obtain the diagnostic function of power grid faults, but it is very difficult to obtain a complete sample set, and when the system changes, new samples need to be added to re-learn, making its on-site maintenance poor; based on fuzzy sets The theoretical fault diagnosis method is an intelligent technology with a complete reasoning system. However, the establishment of a large-scale complex power grid fuzzy model and the maintenance of the fuzzy model when the power grid topology changes are the bottlenecks of the application.

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