材料检测智能化转型中人工智能图像识别方法及其标准化路径

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Artificial Intelligence Image Recognition Method and Standardization Path inIntelligent Transformation ofMaterialDetection

WANG MaosenWANG Wangshu SUN HaiyongWU Jiwei （ShandongInstitute for Product Quality Inspection）

Abstract：Aimingatthecorepain pointsof traditional detection methods，suchaslowefciency，highenvironmental sensitivityandpoorcros-materialadaptabilitythisstudyconstructsanintellgentdetectiontechnologyframeworkbased onlightweight modelsand multi-modaldata fusion.Byintroducing sparsityconstraintobjective functionanddynamic interfaceprotocol，thedetectioneficiencyisimproved by24times，whilemaintaining thesurfacedefectrecallrateof aluminum alloy at over 98.2% .More importantly，the paper innovatively proposes the“three-level standard architecture"： atthebasic level， thedefinitionsoftermssuchas 640.1mm2 defectdetectionrate”are solidified;at the technical level， theFl-score≥0.90algorithmevaluationsystemisestablished;attheapplicationlevel，acolortemperaturecompesation standard of 2000～5000K for automotive sheet metal detection is established，forming a standardization chain that runs through technologicalinnovationandindustrialimplementation.Empiricalresearchshows that thesystemincreases the success rate of cross-system data interaction to 93% ，enabling the online detection speed of a German car company to reach2.3timestheindustryaverage，andsuccessfullaligns withthe internationalstandardsframeworkofISO/IECJTC1. Keywords：material testing;artificial intelligence; image recognition method; standardization path

0 引言

在全球制造业智能化浪潮的推动下，材料检测领域正面临前所未有的转型压力。（剩余3703字）