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Research On Intelligent Control System Of Airport Water Supply Pipe Network

Posted on:2020-01-31Degree:MasterType:Thesis
Country:ChinaCandidate:H SunFull Text:PDF
GTID:2392330596994317Subject:Control engineering
Abstract/Summary:PDF Full Text Request
In the modern airport water supply pipe network system,the collection of water pressure and energy consumption information still adopts the method of manual meter reading.Due to the backward control measures,in order to protect the user demand,the water supply pipe network often has the situation of overpressure water supply,causing a lot of extra power consumption and energy waste.In order to properly regulate the water supply pressure,the purpose of energy saving and emission reduction is achieved.Taking the partial secondary water supply pipe network system of the West Zone of Tianjin Binhai International Airport as an example,first of all,this paper analyzes the influencing factors of the power consumption of the water supply pipe network system,Through the research on the working characteristics of the main energy-consuming equipment-variable frequency constant pressure water pump unit,the relationship between water supply pressure and power consumption is found.The parper studies the confirmation method of the most unfavorable water distribution point in the water supply pipe network.According to the control scheme of the core of the most unfavorable water distribution point,combined with the water supply pipe network water conservancy model,the energy conservation control strategy of the water supply pipe network system is designed.The RBF neural network intelligent algorithm is introduced to design a self-correcting control pressure supply strategy based on RBF neural network to achieve the minimum water supply pressure and energy consumption of the variable frequency water pump unit under the condition of ensuring the user's water demand.In addition,the particle swarm optimization algorithm is introduced to optimize the parameter selection of RBF neural network to improve the learning efficiency and decision efficiency.Finally,the whole structure of the intelligent control system of the airport water supply pipe network is designed and the remote monitoring function of the pressure of the most unfavorable water distribution point is realized.Through the measured data of the partial secondary water supply pipe network system of the West Zone of Tianjin Binhai International Airport,the pressure regulation experiment is carried out.The experimental results show that there is indeed an overpressure water supply in the water supply pipe network system,andthrough the pressure regulation of the variable frequency constant pressure water pump,under the premise of meeting the pressure demand of the most unfavorable water distribution point,the maximum reduction of the variable frequency water pump pressure is to achieve energy saving,and verify the effectiveness and reliability of the system.
Keywords/Search Tags:Airport water supply network, Energy saving and emission reduction, The most unfavorable water distribution point, RBF neural network, Particle swarm optimization algorithm
PDF Full Text Request
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