Optimization Design Of Main Pipe Diameter In Drip Irrigation By Gravity

Xinjiang is situated in northwest, the climate is dry, the annual precipitation is scarce, and such natural environment to the development of Xinjiang is quite disadvantageous. In order to survive, Xinjiang seeks the development unceasingly and takes the hydraulic engineering to be the key point. The fifth division after for 20 years concentrating on study and application practice, has made the concrete analysis and summary to the saving water irrigation technology, and obtained lots of usable experiences. Drip irrigation by gravity is becoming the most esteemed way of irrigation in the fifth division. Through understanding the arrangement way of the drip irrigation by gravity and studying the way of field automation monitor in the fifth division, exploring the optimization design way of main pipe in the drip irrigation by gravity and the influence of cotton growing trend by automated irrigation. Analysis contrast, this article draws the following three conclusions:Firstly, In view of the fifth division ninety-one regiment optimization design of pipeline system is to save the engineering investment. Using Matlab genetic algorithm toolbox for pipe network system for pipe diameter optimization. Group one main reduce investment of more than 400thousand; 91 three main reduce investment of 620 thousand, effect is obvious. In this paper, combining with the characteristics of the network for minimum spanning tree, using single strategy of genetic algorithm, combined with adaptive crossover and mutation probability to solve the figure of the minimum spanning tree, strives for the minimum spanning tree based on the genetic algorithm can satisfy the conditions of solution,comprehensive consideration of the length and the network cost, network with a total investment of the experience method and graph method decreased by 2.8% and 2.8% respectively.Secondly, In code design and pipe network layout, integrated into the design personnel experience,each node is determined according to the experience of the designer’s possible water supply section, design experience into the optimization of initial calculation, effectively reduce the number of optimization calculation insolubility, improve the efficiency of optimization calculation. Is verified by an engineering example, the use of artificial design experience and pipe network layout of the terrain features, using computer technology to determine the minimum investment is closer to the actual engineering requirement tree pipe network design, provides a new way for combination optimization problem of study and the new experience.Thirdly,Pipe diameter and pipe network of synchronous optimization, achieve the global optimal pipe network. This paper, by using integer coding genetic algorithm, in view of tree pipe network layout, a two-level optimization. The first level is to use the principle of tree pipe network of single point water supply have to connect the network in preliminary, meanwhile will effectively in pipe diameter optimization fusion, and USES the integer coded genetic algorithm for pipe network layout optimization,the second level optimization on the basis of the first level optimization using binary encoding, can determine the optimal pipe diameter combination of fast and efficient.Forth,genetic algorithm’s overall situation optimization ability surpasses the traditional optimized method. After analyzed the genetic algorithm development situation profoundly, the practical application as well as the algorithm realization technology, explained this algorithm is more suitable in the middle of the solution misalignment complex problem. We come up with a pipe diameter layout scheme according to Drip irrigation by gravity layout scheme, and then put forward a mathematical model that highly optimized based scheme. By Matlab genetic algorithm toolbox, analyze the choice of parameter in the Genetic algorithm, Selects the biggest iterative algebra 200, overlapping rate 0.7, variations rate 0.1. Through the comparison and analysis we can come out that Genetic algorithm has obvious advantages to traditionalmethod, Genetic algorithm can make up the inherent disadvantages of other traditional methods.