基于PSO-LSSVM和NSGA-Ⅱ的心电记录仪外壳注塑工艺优化

Optimization of injection molding parameters of ECG recorder shell based on PSO-LSSVM and NSGA-Ⅱ

  • 摘要: 心电记录仪是精密的医疗设备,但受注塑工艺的影响,其外壳在注塑生产过程中易产生翘曲和收缩,极大地缩短了使用寿命。针对该问题,提出了一种基于粒子群算法优化的最小二乘支持向量机模型(PSO-LSSVM)和改进的非支配排序遗传算法(NSGA-Ⅱ)相结合的注塑工艺参数多目标优化方法。首先基于正交试验所得样本,利用PSO-LSSVM算法分别了建立翘曲和体积收缩率的预测模型,再结合NSGA-Ⅱ进行全局优化。对优化得到的Pareto最优解集进行CRITIC综合分析,最终得到了最优工艺参数,此时,塑件的翘曲最小为0.438 3 mm,体积收缩率最小为8.729%,比优化前分别降低了6.98%和14.92%。同时,对最优工艺参数进行注塑成型试验,通过测量发现塑件的成型质量较好,达到了实际生产要求。该研究为进一步改善注塑件的质量缺陷提供了理论依据。

     

    Abstract: Electrocardiogram (ECG) recorder is a precision medical equipment, but affected by the injection molding process, its shell is easy to warp and shrink in the injection molding process, which greatly shortens the service life. To solve this problem, a multi-objective optimization method of injection molding process parameters based on particle swarm optimization least squares support vector machine model (PSO-LSSVM) and improved non dominated sorting genetic algorithm (NSGA-Ⅱ) is proposed. Firstly, based on the samples obtained from orthogonal test, the prediction models of warpage and volume shrinkage are established by PSO-LSSVM algorithm, and then combined with NSGA-Ⅱ for global optimization. Through critical comprehensive analysis of the optimized Pareto optimal solution set, the optimal process parameters are finally obtained. At this time, the minimum warpage of plastic parts is 0.438 3mm, and the minimum volume shrinkage is 8.729%, which is 6.98% and 14.92% lower than that before optimization. At the same time, the injection molding test is carried out for the optimal process parameters. Through the measurement, it is found that the molding quality of plastic parts is good and meets the actual production requirements. The research of this paper provides a theoretical basis for further improving the quality defects of injection molded parts.

     

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