A water supply network pipe explosion risk analysis method

Abstract

The invention relates to a pipe bursting risk analysis method for a water supply pipe network. The pipe bursting rate of different pipe bursting factors is analyzed by establishing a pipe bursting prediction database, and normalization processing is carried out. According to the pipe bursting rate, pipe bursting risk grade division is carried out on different pipe bursting factors, a pipe burstingfactor risk grade division table is obtained and used for judging the risk grade of each pipe bursting factor of all pipe sections in the pipe bursting prediction database, and if at least R-1 (R isthe number of all the pipe explosion factors) pipe explosion factor belongs to the same risk level, the pipe explosion risk of the pipe section belongs to the risk level, and pipelines at different pipe explosion risk levels are divided, so that the efficiency and accuracy of pipe explosion risk analysis are improved. And for the pipelines which cannot be divided and analyzed through the definitions, analyzing the pipelines through a neural network. Sample set data obtained through statistical analysis of the pipeline is used for training the neural network, and the accuracy of the neural network is improved.

Description

technical field [0001] The invention belongs to the pipe burst analysis of a water supply pipe network, and in particular relates to a pipe burst risk analysis method of a water supply pipe network. Background technique [0002] The urban water supply network system is one of the most important infrastructures of the city, known as the "lifeline project". Because the system is distributed throughout the city, the system is huge, highly concealed, has many external interference factors, and the quality of the material and installation quality of the pipeline itself varies greatly, so pipe burst accidents are prone to occur. By analyzing the historical leakage data and establishing an effective pipe burst prediction model, the leakage of the pipeline network can be controlled from the source, so as to achieve early prevention, early detection, scientific and reasonable maintenance, and realize the initiative of leakage. control. [0003] Traditional pipe burst prediction mod...

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Problems solved by technology

[0005] CN103226741B discloses a pipe burst prediction method for urban water supply pipe networks to solve the problem of low prediction accuracy, establish a pipe burst prediction model, and provide a new research basis for urban water supply pipe network burst pipes

[0007] None of the above patent documents involves the risk classification of pipe burst factors

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