Rail transit line tripping intelligent early warning system based on SCADA (supervisory control and data acquisition)

Abstract

The invention relates to a rail transit line tripping intelligent early warning system based on SCADA, and the system comprises a monitoring control subsystem which is an SCADA system and is used for monitoring and controlling the operation process of a rail transit power supply system and collecting power data; the intelligent prediction subsystem is used for accurately predicting a tripping fault of the rail transit line by constructing a tripping prediction model of the rail transit line and combining the electric power data and the weather data; and the fault early warning subsystem is used for realizing efficient and visual fault early warning according to the prediction result of the intelligent prediction subsystem. Compared with the prior art, the method has the advantages of comprehensive consideration, accuracy, high efficiency, safety, stability and the like.

Description

technical field [0001] The invention relates to the technical field of rail transit power supply system failure early warning technology, in particular to a SCADA-based intelligent rail transit line trip early warning system. Background technique [0002] At present, there is a lack of research on the real-time prediction and judgment of line tripping in rail transit power supply systems. The main method is to predict the probability of line tripping by locating the area and scale of lightning occurrence and predicting lightning weather or mountain fire disasters. [0003] The use of the above method to predict line tripping is mainly based on the fact that weather factors such as lightning or mountain fires are important conditions that affect line tripping. At the same time, this method ignores the importance of the power parameters generated during the line operation, which also leads to the problem of low prediction accuracy. [0004] Existing methods are highly depende...

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Problems solved by technology

[0003] The use of the above method to predict line tripping is mainly based on the fact that weather factors such as lightning or mountain fires are important conditions that affect line tripping. At the same time, this method ignores the important significance of the power parameters generated during the operation of the line, which also leads to the problem of low prediction accuracy.

[0004] Existing methods are highly dependent on equipment, and the prediction of lightning and wildfire disasters requires extremely high precision, which cannot be predicted in real time. The existing method for predicting the probability of line tripping has achieved important research results, but it still has low accuracy. , does not have defects such as generalization, and the existing line trip prediction methods often only predict the probability of extreme and disaster weather, rather than directly predicting the probability of line trips. Although there are short-term and long-term predictions, they cannot be judged in real time.

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