Water supply pipe network node water demand checking method based on water demand prior information

Abstract

The invention disclose a node water demand checking method based on water demand prior information and belongs to a water supply pipe network node water demand checking method. The method comprises the following steps of firstly, through information of a user remote-transmitting water meter, a water bill, user distribution and the like, estimating a prior water demand and a covariance matrix; through pipe network pressure and a flow sensor, acquiring the pipe network pressure, flow monitoring data and the covariance matrix; establishing a checking target function, linearizing the target function, acquiring a node water demand iteration step length, and updating the node water demand; and after each iteration is completed, calculating the gradient vector of the target function to the waterdemand, and when the die of the gradient vector is less than 1, terminating the iteration. In the method, through introducing water supply pipe network node water demand prior information, a node algorithm search space is further reduced, the inversion precision of the node water demand is increased, and a scientific basis is provided for water supply pipe network hydraulic modeling.

Description

technical field [0001] The invention belongs to a method for checking the water demand of urban water supply pipe network nodes, in particular to a method for checking the water demand of water supply pipe network nodes based on the prior information of the water demand. Background technique [0002] The water supply network model must be calibrated before it is put into practical use. The purpose is to make the calculated results of the network model consistent with the data monitored by the sensors placed in the network. Model checking is to adjust the model parameters to make the model calculation results consistent with the sensor monitoring results. Pipe roughness and node flow are the main parameters that affect the accuracy of pipe network simulation. Generally, the roughness of the pipe does not change in a large range and is very stable with time, so it does not need to be checked frequently. However, the node traffic varies greatly with time and space. Even after...

AI Technical Summary

Problems solved by technology

In addition, the greater the number of nodes, the greater the complexity and the greater the workload, which often takes several months to complete, requiring a lot of manpower and material resources

Therefore, the problem of water demand calibration has always been the bottleneck of hydraulic modeling of pipe network

However, the current value-based node water demand calibration algorithm generally only considers the monitoring information provided by the node pressure and pipeline flow sensors, and the inversion results tend to deviate from the real results.

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