用遗传算法进行RFD装置优化设计

免维修流体输送装置RFD由压缩空气做动力,通过气液换能驱动被输送液体间歇性出料。该装置不含运动部件,其优化设计是关系到装置高效稳定运行的关键理论。文中分析了传统枚举法和边际效用法在方案搜索中存在的问题,重点讨论了遗传算法在多目标高维优化问题中的应用,通过计算实例比较了3种方法的计算结果,得出遗传算法在本问题求解中的优势。最后,针对流量和扬程需求,采用遗传算法进行了装置的系列化设计,并分析了有关结构参数和运行参数的变化规律,进一步给出了不同密度和粘度下,RFD装置输送流量的换算关系,为RFD装置的工业设计打下坚实的基础。

Optimization design of RFD set based on genetic algorithm

RFD (reverse flow divert) set is a kind of maintenance-free delivery system driving by compress-air. It intermittently discharges through its delivery pipe. RFD set has no moving part, and its optimized design is critical to efficient and stable operation. The deficiencies in optimization of traditional enumeration algorithm and the marginal utility method were indicated. Then, as a mainly point of the paper, using the genetic algorithm (GA) to solve the multi-objective multidimensional optimization problem was discussed. By comparing the results of the three optimization methods, the superiority of GA can be drawn. Based on the industrial needs for flow and head, a serialization design of RFD was done by using GA and the relationships of the structural parameters and the operational parameters were analyzed. And the conversion relationships of RFD average flow in different densities and viscosities were provided. The promoted approach will be benefit for the RFD set design in industry.