管道机器人微小厚度高精度测量算法
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摘要
针对目前大多磁感应检测数据处理算法用于管道内自动测厚时存在误判率高、精度较低、耗时长等缺点的问题,研究了输油气管道内的微小污垢厚度的高精度校准算法。针对静态校准,提出一种采用数据预处理、基于改进中值滤波器与最小二乘法拟合的综合算法;针对实际应用中温度、湿度、元器件老化等因素引起的测量结果波动,提出了测量中动态校准测量算法。经实际测试,结果表明:所提方法的测量精度达到了±(1+%1)μm,满足高精度测量的要求。
Aiming at problem that at present,most magnetic induction detection data processing algorithms used for automatic thickness measurement in pipelines have disadvantages of high false positive rate,low precision and long time consumption,high-precision calibration algorithm for small dirt thickness in the oil and gas pipeline is studied. For static calibration,a comprehensive algorithm based on data preprocessing,improved median filtering and least squares fitting is proposed. Aiming at fluctuation of measurement results caused by factors such as temperature,humidity and component aging in practical applications,a dynamic calibration algorithm is proposed in measurement. Actual test results validate that the proposed method satisfy the requirements of high-precision measurement with measurement precision of ±( 1 + % 1) μm.
Aiming at problem that at present,most magnetic induction detection data processing algorithms used for automatic thickness measurement in pipelines have disadvantages of high false positive rate,low precision and long time consumption,high-precision calibration algorithm for small dirt thickness in the oil and gas pipeline is studied. For static calibration,a comprehensive algorithm based on data preprocessing,improved median filtering and least squares fitting is proposed. Aiming at fluctuation of measurement results caused by factors such as temperature,humidity and component aging in practical applications,a dynamic calibration algorithm is proposed in measurement. Actual test results validate that the proposed method satisfy the requirements of high-precision measurement with measurement precision of ±( 1 + % 1) μm.
引文
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[2]周卫元,方飞,陈立建,等.面向地下管道的四向行走智能机器人系统[J].传感器与微系统,2017,36(9):73-76.
[3]常玉连,邵守君,高胜.石油工业中管道机器人技术的发展与应用前景[J].石油机械,2006,34(9):122-126.
[4]杨华,董世运,徐滨士.涂镀层厚度检测方法的发展现状及展望[J].材料保护,2008,41(11):34-37.
[5]李旭辉.覆层测厚仪原理及影响测量精度的因素[J].科技创新与应用,2013(29):65.
[6]罗玲,王修信.一种高效去除椒盐噪声的中值滤波方法[J].微电子学与计算机,2011,28(11):118-121.
[7]张开远,周孟然,闫鹏程,等.基于最小二乘法的pH值温度补偿系统设计[J].传感器与微系统,2015,34(5):109-111.
[8]陈良波,郑亚青.基于最小二乘法的曲线拟合研究[J].无锡职业技术学院学报,2012,11(5):52-55.