摘要
针对针阀偶件插配智能化加工需求,设计并建设针阀偶件智能化插配加工单元。对加工尺寸的数据进行分析,改进针阀偶件间隙配对加工方法;构建间隙配对问题数学模型,采用改进的遗传算法对其进行求解,实现针阀偶件间隙配对的最优化,现场使用验证,配对成功率85%左右;基于迁移学习训练光学字符识别(OCR)模型,识别针阀体生产顺序号,识别准确率达95%,并将针阀偶件插配过程数据与之关联,实现数据自动记录,便于质量追溯。
Design and construct an intelligent machining unit for needle valve fittings in response to the demand for intelligent machining of needle valve fittings.Analyze the machining dimension data and improve the machining method for matching the clearance between needle valve components;Construct a mathematical model for gap pairing problem and solve it using an improved genetic algorithm to achieve optimal gap pairing of needle valve components.The model has been validated on site with a success rate of approximately 85%;Based on transfer learning,an OCR model is trained to recognize the production sequence number of needle valve bodies with an accuracy rate of 95%.The data of the needle valve fitting process is associated with it to achieve automatic data recording and facilitate quality traceability.
作者
文传奇
杨鑫
罗付强
张云庭
WEN Chuanqi;YANG Xin;LUO Fuqiang;ZHANG Yunting(Chongqing Hongjiang Machinery Co.,Ltd.,Chongqing 402160,China)
出处
《内燃机》
2024年第5期31-37,共7页
Internal Combustion Engines