基于ISMA-ELM混合模型的选择性激光烧结工艺参数优化

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关键词：选择性激光烧结;黏菌算法;极限学习机；Levy飞行;随机反向学习;高度破坏性多项式变异DOI：10.15938/j. jhust.2025.02.002中图分类号：TP18 文献标志码：A 文章编号：1007-2683（2025）02-0011-11

Abstract：Anew hybrid model is proposed toaddesstheisueofsrinkage inselectivelasersinteringparts，whichcombines the Improved Slime mould Algorithm（ISMA）andExtreme Learning Machine（ELM）to predictthe shrinkagerateofthe partsusing limitedinputdata.Fistly，threeimprovementstrategiessuchasLevyflight，andomopposition-basedleaingandhiglydisuptive polynomialmutationareusedtoimproveteperformanceoftheviscousbacteriaoptimizationalgorithminallaspects.Subsequently， ISMAisusedtooptimizethekeyparametersofELM，andanSMA-ELMmodelisproposedtopredicttheshrinkagerateofSSparts. SimulationresultsdemonstratethattheproposedISMA-ELMobtainsoptimalpredictionresultscompared tothestandardandother algorithm-optiizedELmodels.Finall，theoptimalprocsingparameterspredictedbyteISMA-ELMmodelareusedtoguidethe machining，and the dimensional accuracy of the obtained molded parts is improved by 29.62% compared to the ELM model and 18.02% comparedto the SMA-ELM，which shows thatthe modelcan provideoptimalproess parameters for SLSmolding processing and guide the machining effectively.

Keywords：selective laser sintering；slimemouldalgorithm；extreme learning machine；levy flight；randomopposition-basec learning；highly disruptive polynomial mutation

0 引言

选择性激光烧结（selectivelasersintering，SLS）是一种利用高能量激光束逐层烧结堆积成型的快速成型技术，近些年得到了广泛的关注[1-2]。（剩余12378字）