Research On The Intelligent Optimization Design Of Boiler's Heating Surface System Based On GA

Boiler is functional important and widespread utilized in industry. It is a kind of important equipment which is used to supply steam or hot water by changing energy form and energy carrier. The design of a boiler is a big project, which is complex, complicated, time consuming and relies heavily on the experience of the designers. It is a kind of routine design, but strict with economy and reliability requirment. Traditional design method was usually done by changing the parameters and calculating constantly until it reached a satisfactory solution. Heaing surface system is part of the boiler and is very important to the whole boiler. It takes a big proportion in the aspect of steel consumption. So the research of the heaing surface system intelligent optimization design is very meaningful. The optimization could improve design efficiency, quality and diminish the cost of output. In addition, it also could improve the whole design's automatic level.The thesis was in the subsidization of "Project in the National Science & Technology pillar program during the eleven five-year plan period" (2006BAF01A46) and "Zhejiang Technology Plan Program"(200621SA 160008). It researched the boiler intelligent computer aided design, mainly focused on the three key techniques:the performance analysis of the heating surface system; a genetic algorithm based method and it's modified model for searching the design schemes automatically and composing a Pareto solution set; analytic hierarchy process(AHP) based method for comprehensively evaluating all the schemes in Pareto. In the end, an intelligent optimization design model of the heating surface system was created. The main research contents on this subject were explained as follows:(?) Based on the cognition of the research process, analyzed and modeled the boiler heating surface system's thermal calculation. In general sense, rechoned the boiler as a process system which was used to change energy form and energy carrier. In the microscopic point of view, analyzed the structures and the principle of the operation, abstracted the whole thermal calculation system. Reckoned the system was a net work composed of "Generalized Process Cells" in a fixed organizational structure. Took the steady-state simulation theory in the process system "Sequential modular method" as the overall calculation algorithm. Eventually got the whole performance analysis done automatically. It was improved that the method could converge automatically and relied less on the initial values.(?) On the basis of the automatical simulation for the thermal calculation system, used genetic algorithm to optimize the design procedure. The objective of the optimization was to develop and test a model of area estimating for the heating surfaces. Analyzed and modeled both the sole surface and the subsystem which is composed of several surfaces. The estimation was very complex for several performance calculations, including thermal calculation, hydraulic resistance calculation and fuel-gas & air resistance calculation, should all be done. The model of the optimization was developed based on thermal calculation while other performance calculations are simplified as constraints, which were introduced as geometric constraints, velocity constraints and temperature constraints to insure that the candidate design schemes satisfied to all the design specifications. The GA based optimization method could beamly search the whole solution space. At last, a Pareto solution set, which was composed of several optimized schemes, was produced.(?) Modified genetic algorithm models were proposed on the basis of the simple genetic algorithm. Case-based reasoning and randomly generating were combined in initial population generation process, which could help introducing design experience into genetic algorithm effectively and finding the global optimal solution efficiently. Used "Method of Members Grouping", dividing the population into two sub-groups, then the father individual and mother individual were picked from the two sub-groups respectively. Used "Sigmoid Crossover" to generate new individuals. The best two child individuals which won in the "Family Competition" were chosen as new population members. This method could avoid good quality gene of parent individuals being lost in crossover operator. In the section of mutation operation, used an adaptive mutation. The value of adaptive mutation fraction was calculated by a "Sigmoid function". In the early stage of genetic algorithm, a larger mutation fraction was given, and it became smaller gradually with the development of the algorithm, which could also improve the average fitness of the population. Examples were given to prove that these modified methods could promote the genetic algorithm to find better global optimum quickly and effectively, and eventually improve the quality of the Pareto solution set.(?) The design of the heating surface system involves much knowledge in many fields, and it has to meet a series of certain knowledge and fuzzy knowledge, such as design requirements, manufacturing requirements, operational requirements, maintenance requirements and so on. Analytic hierarchy process was used to evaluate the design schemes in Pareto solution set. With the goal of cutting the investment and operating expense, various requirements in design process were classified into two hierarchy and their weight parameters in correspond to their proportion of the cost are given under the guidance of expert experience. In this way, qualitative and quantitative were combined. Finally, the last evaluation values of the whole programs were exported by analyzing each hierarchy, giving the criterion of the best solution selection.(?) The design of boiler heating surface system is a kind of routine design, various values are calculated by theoretical formula. but the actual operation conditions can not be fully consistent with the theoretical calculation. so the boiler products design depends heavily on experience. In this thesis, intelligent optimization design of boiler schemes was proposed based on empirical, in which the design experience was expressed as all kinds of constraints. With GA's ability of creating several design shemes simultaneously, and the AHP's comprehensive evaluation ability, computers could create, analyze, evaluate and export projects intelligently. This method could improve the design quality, reduce the reliance on the experience, shortens the design cycle.