引用本文:王宏民,王盟.基于磁阻测量的硬质合金锯片焊缝缺陷检测[J].控制与决策,2020,35(9):2292-2298
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基于磁阻测量的硬质合金锯片焊缝缺陷检测
王宏民,王盟
(哈尔滨理工大学自动化学院, 哈尔滨150080)
摘要:
针对硬质合金锯片刀头焊缝体积小、耦合误差干扰较大的问题,提出一种硬质合金锯片磁阻测量的无损检测方法.以锯片基体、刀头和励磁组件所构成的磁阻检测回路构建有限元仿真模型,通过焊缝的性状对磁阻的影响进行缺陷识别;并采用改进的支持向量机,有效削弱磁阻测量回路耦合误差的干扰.测试分析表明,所提出方法可有效降低测量中耦合干扰误差,为小尺寸焊缝质量检测提供解决方法,实验测试正确率达97.25%.
关键词:  磁阻测量  改进的支持向量机  硬质合金锯片  焊缝检测  耦合误差
DOI:10.13195/j.kzyjc.2018.1749
分类号:TP202
基金项目:黑龙江省自然科学基金项目(F201310).
Weld defect detection of carbide saw blade based on reluctance measurement
WANG Hong-min,WANG Meng
(School of Automation,Harbin University of Science and Technology,Harbin150080,China)
Abstract:
A nondestructive testing method for the reluctance measurement of carbide saw blades is proposed, aiming at the problems of small weld volume and large coupling deviation interference of carbide saw blade heads. The finite element simulation model is constructed by reluctance detection circuit composed of saw blade base, cutter head and excitation component. Defect recognition is proceeded by the influence of weld properties on reluctance. And an improved support vector machine is used to effectively reduce the interference of coupling deviation in reluctance measurement circuit. The test results show that this method effectively reduces the coupling interference deviation in the measurement, and provides a solution for the quality detection of small size welds. The accuracy of the experiment is 97.25%.
Key words:  reluctance measurement  improved support vector machine  carbide saw blade  weld detection  coupling deviation

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