航空发动机叶片关键检测参数的智能优化研究

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中图分类号：V261.2;TP391.7 文献标识码：A 文章编号：1006-8228（2026）01-34-06

Abstract：Theselectionofinspectionparametersfortraditionalaero-enginebladesreliesheavilyonmanualexperiene，whichoften leadstofluctuationsininspectionqualityToaddressthisisse，thisstudyfocusesonthegrindingprocessofaspecificturbine bladeinanaero-engine.First，anaero-engineblade"inspection-quality"datasetwith5datagroupswasestablishedthroughdata acquistionandaugmentation.Secondanartficialneuralnetwork（AN）-based"ispection-qualt"modelwasdevelopedto characterisethemappingrelationshipbetweenthesevariables.Finally，animprovedHipopotamusOptimisationAgorithm（HOA） incorporatingsixkeyswarmbehaviourswasproposedandapliedtoperformglobaliterativeoptimisationThealgorithmidetfed theoptimalcombinationofinspectionparametersforthebladeExperimentalresultsdemonstratethattheproposedmethodoutperfos existingtechniquesintermsofearly-stageoptimisationcapablityescapefromlocaloptimacapabiltyandglobaloptimisation capabilitypavingteayfoaewaproachtompoweringero-enginebladeinspectionthroughintellgentcomputatioalethods.

Keywords：Aero-EngineBlades;IntelligentComputing;DigitalInspection;NeuralNetwork；SwarmIntellgenceAlgorith

0引言

航空发动机涡轮叶片作为制约发动机性能的关键热端部件，对飞机达到预期动力、寿命及可靠性等各项指标具有重要意义。（剩余7399字）