基于 Jaya 优化标定的高精度数据采集方法

doi:10.12066/j.issn.1007-2861.2372

上海大学学报(自然科学版) ›› 2022, Vol. 28 ›› Issue (3): 361-371.doi: 10.12066/j.issn.1007-2861.2372

• 数据采集、数据库和数据处理 • 上一篇下一篇

基于 Jaya 优化标定的高精度数据采集方法

张合生¹(), 焦鹏¹, 胡琪睿¹, 蔡江乾², 胡顺波³^,⁴, 曹贺⁵, 欧阳求保⁵

1.上海大学机电工程与自动化学院, 上海 200444
2.上海大学计算机工程与科学学院, 上海 200444
3.上海大学材料基因组工程研究院材料信息与数据科学中心, 上海 200444
4.之江实验室, 浙江杭州 311100
5.上海交通大学材料科学与工程学院金属基复合材料国家重点实验室, 上海200240

收稿日期:2022-03-20 出版日期:2022-06-30 发布日期:2022-05-27
通讯作者: 张合生 E-mail:zhs81@shu.edu.cn
作者简介:张合生(1981—), 男, 高级工程师, 博士, 研究方向为精密测量与控制、高可靠嵌入式系统、工业控制系统等. E-mail: zhs81@shu.edu.cn
基金资助:
国家重点研发计划资助项目(2018YFB0704400);云南省重大科技专项资助项目(202002AB080001-2);云南省重大科技专项资助项目(202102AB080019-3);之江实验室科研攻关资助项目(2021PE0AC02);上海张江国家自主创新示范区专项发展资金重大资助项目(ZJ2021-ZD-006)

High-precision data acquisition method based on Jaya optimization and calibration

ZHANG Hesheng¹(), JIAO Peng¹, HU Qirui¹, CAI Jiangqian², HU Shunbo³^,⁴, CAO He⁵, OUYANG Qiubao⁵

1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
2. School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China
3. Center of Materials Informatics and Data Science, Materials Genome Institute, Shanghai University, Shanghai 200444, China
4. Zhejiang Laboratory, Hangzhou 311100, Zhejiang, China
5. State Key Laboratory of Metal Matrix Composites, School of Material Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

Received:2022-03-20 Online:2022-06-30 Published:2022-05-27
Contact: ZHANG Hesheng E-mail:zhs81@shu.edu.cn

摘要/Abstract

摘要：

材料基因组工程融合高通量实验、高通量计算和数据库及人工智能技术, 能加速实现新材料的研发. 然而, 如何快速且可靠地从实验设备中采集数据是材料基因组工程的重要问题. 针对高精度数据采集系统标定数据时间不同步的问题, 以线性模型作为采集数据处理参数的模型, 以设备显示值作为数据采集真实值, 构建数据处理参数寻优的目标函数; 基于 Jaya 优化算法实现了模型参数优化搜索; 最后以设备温度数据采集为例, 构建了高精度数据采集系统并进行实验验证. 实验结果表明, 采用优化后的模型参数, 数据采集平均误差仅为 0.13 ${^\circ}$C, 精度可达 99.89%, 相比于非优化模型参数, 平均误差降低了 63.20%, 显著提高了数据采集精度.

关键词: 时间不同步, 数据采集, Jaya 算法, 数据标定

Abstract:

Materials genome engineering (MGE) integrates high-throughput experiments, high-throughput computations, databases, and artificial intelligence to accelerate the development of advanced materials. However, a reliable and effective method to acquire data from experimental equipment is yet to be identified in MGE. Because the calibration data of high-precision data acquisition systems are not synchronized in terms of time, a linear model is used in this study as a model for data processing parameters, and the value displayed by the device is used as the real value to construct the objective function to optimize the data processing parameters. The Jaya optimization algorithm is used to realize the optimization search of processing parameters. Based on the data acquisition of the equipment temperature as an example, a high-precision data acquisition system is constructed and verified experimentally. The experimental results show that using the optimized model parameters, the average error of data acquisition is only 0.13 $^\circ$C, and the maximum accuracy is 99.89%. Compared with the non-optimized model parameters, the average error reduced by 63.20%, which significantly improves the data acquisition accuracy.

Key words: time out of sync, data acquisition, Jaya algorithm, data calibration

中图分类号:

TP 319

张合生, 焦鹏, 胡琪睿, 蔡江乾, 胡顺波, 曹贺, 欧阳求保. 基于 Jaya 优化标定的高精度数据采集方法[J]. 上海大学学报(自然科学版), 2022, 28(3): 361-371.

ZHANG Hesheng, JIAO Peng, HU Qirui, CAI Jiangqian, HU Shunbo, CAO He, OUYANG Qiubao. High-precision data acquisition method based on Jaya optimization and calibration[J]. Journal of Shanghai University（Natural Science Edition）, 2022, 28(3): 361-371.

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基于 Jaya 优化标定的高精度数据采集方法

High-precision data acquisition method based on Jaya optimization and calibration

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