| The central heating system is changing so much with the development of urbanization in our country. The automation and intelligent management of central pipeline network is a problem to be solved urgently at this stage. In this paper, the heating pipeline leakage diagnosis system in real time is put forward to differentiate heating pipe network leakage accuratrly. This system is supposed to provide some reference for the central heating intelligent management direction.At first, in order to build central heating pipeline network diagram the graph theory method is introduced in this paper to do scientific and reasonable simplification for the comples central pipeline networks. In a simplified network diagram the matrix representation of central pipeline network is built in this paper. In the other hand, the network hydraulic mathematics calculation model is built whit hydraulic equations and the detailed calculation process has been described in this paper.The second, the change of resistance characteristic coefficient has a great influence on the operation of network from the analysis of data change during central heating pipeline operation. Multiple population hybrid adaptive genetic algorithms are proposed to optimize the resistance characteristic. And the heating pipe netwok operation simulation test bench is introduced in this paper to verify the accuracy of results of standard genetic algorithm, adaptive genetic algorithm optimization and multiple population hybrid adaptive genetic algorithms. The comparison results show that the results of multiple population hybrid adaptive genetic algorithms have the highest precision.In the end, the real-time leakage diagnosis system of heating network is built to judge network running state. The threshold range is determined by the analysis of a large amount of data to reduce the misjudgment rate of this diagnosis system. This system could run reliably and do the accurately determination in the experimental condition. |
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