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双参数非线性概率模型的板材腐蚀精度估计

Estimation of corrosion accuracy of plates based on two parameter nonlinear probability model
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摘要 针对金属板腐蚀在线超声动态检测时探头抖动致使超声波入射角变化,引起测量精度低的问题,建立双参数超声波水浸检测误差修正的非线性概率模型,结合函数逼近理论补偿超声入射角引入误差。采用基函数加权组合与三阶拉格朗日插值结合方法,同时对超声波入射角、界面声程双参数与工件声程的函数关系进行最小二乘曲线拟合,得出入射角与检测误差的非线性相关关系。通过对误差补偿算法中非线性概率模型入射角与界面声程变量的迭代运算,利用折射角反向求解入射角,解决检测中超声波入射角不确定问题。在水层厚度30~45 mm范围内,对不同厚度铝板进行检测,结果表明,经模型补偿处理,超声波以0°~8°角入射,板材检测精度为1%,为有效提高腐蚀精度估计提供依据。 In view of the change of ultrasonic incidence angle caused by the online ultrasonic dynamic detection and the low measurement accuracy,a nonlinear probability model of two-parameter ultrasonic flooding detection error correction is formulated.The error introduced by ultrasonic incident angle is compensated by the function approximation theory.Using the combination of basis function and third-order Lagrange interpolation,the ultrasonic incidence angle and the nonlinear correlation between the incident angle and the detection error are obtained.The incident angle of the nonlinear probability model and the ultrasonic distance are iteratively calculated.The incidence angle is used to solve the refractive angle in reverse,and the uncertainty of the ultrasonic incidence angle in the detection is resolved.In the range of 30 to 45 mm,the results show that after the model compensation treatment,the ultrasonic wave at 0°~8°angles of the incident,the plate detection accuracy is 1%,which provides a basis for effectively improving the corrosion accuracy estimation.
作者 邢燕好 姜晓霞 张佳 孙盈 赵璐 Xing Yanhao;Jiang Xiaoxia;Zhang Jia;Sun Ying;Zhao Lu(School of Information Science and Engineering,Shenyang University of Technology,Shenyang 110870,China;China North Industries Group Aviation Ammunition Research Institute Co.,Ltd.,Harbin 150030,China)
出处 《仪器仪表学报》 EI CAS CSCD 北大核心 2023年第5期278-287,共10页 Chinese Journal of Scientific Instrument
基金 国家自然科学基金(62241107) 辽宁省自然科学基金(2022-BS-180) 辽宁省教育厅面上项目(LJKMZ20220474,LJKZ0135)资助。
关键词 水浸超声 腐蚀检测 入射角 非线性概率模型 误差补偿 water immersion ultrasound corrosion detection angle of incidence nonlinear probabilistic model error compensation
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