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Soft measurement method for sewage pumping station flow of urban drainage converged network

A technology for urban drainage and sewage pumping stations, applied in the field of soft measurement

Active Publication Date: 2011-04-27
ZHEJIANG SUPCON INFORMATION TECH CO LTD
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  • Claims
  • Application Information

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Problems solved by technology

Then use the gray relational analysis method to determine the lag time of drainage flow in different upstream pumping stations

Method used

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  • Soft measurement method for sewage pumping station flow of urban drainage converged network
  • Soft measurement method for sewage pumping station flow of urban drainage converged network
  • Soft measurement method for sewage pumping station flow of urban drainage converged network

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Embodiment Construction

[0057] Taking the pipe section of the Wulinmen Pumping Station of the Hangzhou drainage network as an example, the specific implementation of the present invention will be described in detail. There are 3 upstream pumping stations in Wulinmen Pumping Station, which are the Bus Factory Pumping Station, Gudang Pumping Station (leaf node), and Hangda Pumping Station (the upstream pumping station is Gaoxin Pumping Station). The flow soft measurement calculation steps of the confluence node are as follows:

[0058] Step (1) Determine the input variables and output variables of the confluence pipe network model:

[0059] The input variables include the displacement of the pumping station of the passenger car factory, Gudang pumping station and Hangda pumping station, the liquid level change of the forebay of the Wulinmen pumping station and the displacement of the forebay of the Wulinmen pumping station; the output variable is the forebay water level of the Wulinmen pumping station; ...

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Abstract

The invention discloses a soft measurement method for sewage pumping station flow of an urban drainage converged network. The conventional drainage pipe network system has lots of uncertain factors and high measurement hardware cost. The method comprises the following steps of: analyzing main influencing factors of converged node pumping station flow by using mechanism analysis and priori information, and primarily determining influencing factors of a back-propagation (BP) neural network, namely determining input / output variables; determining lag time of different upstream pumping station flows by using a grey correlation analysis method; and establishing a grey neural network model on the basis of pumping station historical operating data, and predicting the converging node pumping station flow. By combining two methods of grey correlation analysis and grey neural network, the method solves the problem of difference of drainage time delay of different upstream pumping stations, well simulates the nonlinear pipe network drainage process, realizes soft measurement of converged node sewage pumping station flow, saves the hardware resources, and is low in cost and high in accuracy.

Description

technical field [0001] The invention belongs to the field of soft measurement, in particular to a method for soft measurement of sewage flow in a drainage pipe network. Background technique [0002] With the rapid development of cities, urban drainage has become one of the bottlenecks restricting the rapid development of cities. However, in the existing urban drainage pipe network system, the flow and water level of sewage flowing through each pipe network and pumping station can only be estimated by manual experience. Due to the lack of detailed measured flow data in the pipe network system, the system cannot predict the flood. generation, pipeline overflow, and it is impossible to achieve the purpose of energy saving of the pump station by scheduling the opening of the pump station unit. [0003] The use of hardware detection devices (including mechanical, turbine, ultrasonic, and electromagnetic) to measure flow requires the transformation of drainage pipes. This process...

Claims

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Application Information

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IPC IPC(8): G01F1/74G06N3/08
Inventor 徐哲左燕薛安克何必仕
Owner ZHEJIANG SUPCON INFORMATION TECH CO LTD
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