An error compensation method for on-machine measuring blade with industrial robot

IF 5.2 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Junjie Zhang, Lai Zou, Xinghao Zhang, Ziling Wang, Wenxi Wang
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Abstract

To achieve the seamless integration of precision grinding blade with timely measured data, an on-machine measurement system employing industrial robot is developed. The limitation to its widespread application lies in the accuracy of measurement, prompting the proposal of an error compensation method to address the measurement error within the implemented blade on-machine measurement system. To address the pre-travel error in the measuring device of the on-machine measurement system, an analysis of the factors influencing the pre-travel error of the contact probe is conducted. Subsequently, pre-travel error data is gathered utilizing the experimental calibration method involving a standard ball, and a prediction model employing the bilinear interpolation algorithm is established to facilitate error compensation. Employing pre-travel error compensation for the analysis of the operating body error in the on-machine measurement system, a spherical center distance constraint error model is derived through closed-loop kinematic calibration of the six-degrees-of-freedom industrial robot. Kinematic parameter error identification is conducted using a hybrid algorithm combining the L-M algorithm and the adaptive factor double-variable DE algorithm. This approach diminishes the spherical center distance measurement error, reducing it from 0.081 mm to 0.016 mm. Subsequently, experiment is conducted to measure blade machining allowances using an on-machine robotic measurement system, comparing the obtained data with measurement from a blue light scanner and a coordinate measuring machine (CMM). The results reveal average absolute deviations of 0.020 mm, 0.015 mm, and 0.016 mm in the three blade cross sections for the on-machine robotic measurement system and the blue light scanner, respectively. Correspondingly, the average absolute deviations for the on-machine robotic measurement system and the CMM in the three blade sections are 0.028 mm, 0.029 mm, and 0.029 mm. Moreover, the on-machine measurement system demonstrates commendable measurement repeatability, with a standard deviation of 0.003 mm.
工业机器人机载测量刀片的误差补偿方法
为实现精密磨削刀片与及时测量数据的无缝集成,开发了一种采用工业机器人的机上测量系统。其广泛应用的局限性在于测量精度,因此提出了一种误差补偿方法,以解决已实施的刀片在机测量系统中的测量误差问题。为了解决机上测量系统测量装置的预行程误差问题,对影响接触探头预行程误差的因素进行了分析。随后,利用涉及标准球的实验校准方法收集了预行程误差数据,并建立了采用双线性插值算法的预测模型,以促进误差补偿。利用预行程误差补偿分析机载测量系统中的操作体误差,通过对六自由度工业机器人进行闭环运动学校准,得出球心距约束误差模型。运动参数误差识别采用 L-M 算法和自适应因子双变量 DE 算法相结合的混合算法。这种方法减小了球心距离测量误差,从 0.081 毫米减小到 0.016 毫米。随后,实验使用机上机器人测量系统测量叶片加工余量,并将获得的数据与蓝光扫描仪和坐标测量机(CMM)的测量数据进行比较。结果显示,机载机器人测量系统和蓝光扫描仪在三个叶片横截面上的平均绝对偏差分别为 0.020 毫米、0.015 毫米和 0.016 毫米。相应地,机载机器人测量系统和坐标测量机在三个叶片横截面上的平均绝对偏差分别为 0.028 毫米、0.029 毫米和 0.029 毫米。此外,机载测量系统的测量重复性也值得称赞,标准偏差为 0.003 毫米。
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来源期刊
Measurement
Measurement 工程技术-工程:综合
CiteScore
10.20
自引率
12.50%
发文量
1589
审稿时长
12.1 months
期刊介绍: Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.
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