真空断路器弹簧操动机构模糊稳健优化设计的研究
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摘要
高压断路器是电力系统中最主要的控制、保护装置,对电网的安全运行起着关键作用,而高压断路器配用的操动机构的运动特性及其可靠性、稳健性,直接影响着断路器的操作性能及其可靠性。真空断路器弹簧操动机构的模糊稳健优化是工程领域中的前沿性课题,具有良好的应用前景和实用价值。对于它的研究有着重要的理论意义和实际意义。
     本文针对12kV、12.5kA真空断路器弹簧操动机构进行优化设计的研究。在对此机构进行动力学与运动学分析的基础上,建立了计算断路器分、合闸速度的离散关系式;从真空断路器分、合闸功能的基本要求出发,以机构中各杆件的尺寸为设计变量,以真空断路器的分、合闸速度的方差最小化及成本最低为目标,对此机构实施常规优化设计,并对优化结果进行分析,探讨了该方法的缺陷;以机构中各杆件的尺寸和分、合闸弹簧的刚度系数为设计变量,将加工误差等归入设计变量的容差中,以断路器的分、合闸速度的方差最小化且速度最稳健为目标,对此机构实施稳健优化设计,并对优化结果进行分析,探讨了该方法的局限性;将机构中必定存在的运动副间隙、安装水平、材质好坏和设计水平等视作不可控因素,并将其与断路器的分、合闸速度的非线性关系用模糊数学处理,仍以机构中各杆件的尺寸和分、合闸弹簧的刚度系数为设计变量,将零部件的加工误差、老化、疲劳等归入设计变量的容差中,以断路器的分、合闸速度的方差最小化且最稳健为目标,建立了此机构的模糊稳健优化的数学模型,并对优化结果进行分析,比较;以12kV、12.5kA真空断路器弹簧操动机构的模糊稳健优化的结果为技术指标,以弹簧刚度系数误差最小且最稳健为目标,对分、合闸弹簧的动力特性即刚度系数实施模糊稳健优化设计,进一步提高此机构模糊稳健优化结果的稳健性。
     提出了一系列切实可行的优化策略;选取典型多变量多峰值的测试函数进行寻优测试,验证所提出的将随机方向搜索算法与复合型算法相结合的搜索全局最优点的优化算法的可行性;采用模糊推理,结合优化设计技术,应用Matlab软件,求解各个优化数学模型;对各个优化设计结果进行的分析及比较,证明了模糊稳健优化设计的结果性能最佳,最为稳健。
High-voltage circuit breaker is the most important device of control and protection power system. It plays a key role for power systemic safeness. The actuator’s motion characteristics and reliability of high-voltage circuit breaker has a direct impact on the operation performance and reliability of circuit breaker. The issus of fuzzy robust optimization for spring actuator of vacuum circuit breaker, is forwardlooking in engineering, and has a good application prospect and practical value. For its study has a very important theoretical and practical significance.
     The spring actuator of 12kV, 12.5kA vacuum circuit breaker has been as the investigation in here. Based on the dynamics kinematic analysis for this mechanism, the discrete-time formula used to calculate the breaking and cloeing velocity is given. The lengths of the connecting rods of the mechanism are chosen as the optimal variablies, minimizing the variance of the breaking and closing velocity and minimizing the materials costs of those rods compose the objection function. A mathematical model of conventional optimal design for the mechanism is given. The optimal design is carried on by solving this model, ths optimal results are discussed by comparing with present model. The machining error of the mechanism is taken as the tolerance of the mechanism components. The lengths of the rods of the mechanism and stiffness coefficient of the breaking and closing spring are chosen as the optimal variablies. Given the tolerance of variablies, minimizing the variance and fluctuation of the breaking and closing velocity compose the objection function. So a mathematical model of robust optimal design for the mechanism is given, the robustness of robust optimal results is discussed by comparing with present model and conventional optimal design. The kinematic pair clearance, installation level, material grade and design standard are taken as uncontrollable factors. The lengths of the rods of the mechanism and stiffness coefficient of the breaking and closing spring are chosen as the optimal variablies. Given the tolerance of variablies and fuzzy processed the influence carried by those uncontrollable factors, minimizing the variance and fluctuation of the breaking and closing velocity compose the objection function. So a fuzzy robust optimal model for the mechanism is given, the robustness of the fuzzy robust optimal results is discussed. The result of this fuzzy robust optimial design is taken as specification. To minimize the error and fluctuation of stiffness coefficient of the breaking and closing spring are chosen as the objection function, the fuzzy robust optimial design for those springs are given. This work makes fuzzy robust optimial design to be better.
     For solving each optimial model, some optimal strategies are proposed. Secondly carry on the test using some classics standard test functions to the algorithm of merging the random direction search method and the complex algorithm, the simulation result indicated the algorithm has the good optimized effect in the function optimization question. By using fuzzy reasoning theory, combining with optimal design techniques, and adopting Matlab softwork, each optimization model is solved. By analysis and compared to optimal design results, it shows that the result of fuzzy robust optimal design has the optimum performance and is the most robust of these models.
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