作者：黄永刚

作者单位：中国铁道科学研究院标准计量研究所, 北京 100015

关键词：机车车辆称重传感器;非线性校正;正交多项式;最小二乘法;曲线拟合

摘要：

因受自身材质、工艺的限制以及外界环境影响，机车车辆称重传感器实际的输入输出关系存在非线性特性，造成测量结果的非线性误差，制约其测量精度。对此，该文采用曲线拟合法、以正交多项式做最小二乘拟合建立非线性校正环节，对机车车辆称重传感器进行非线性校正，来减小非线性特性对测量结果造成的影响，提高测量精度，同时避免正规方程系数矩阵的病态问题。实验结果表明，校正后系统的非线性得到明显改善，测量精度得到显著提高，同时该方法操作简单、校正效率高、结果稳定可靠，具有较好的工程应用价值。

The non-linear correction of the weighing sensor based on orthogonal polynomial fitting method

HUANG Yonggang

Standards & Metrology Research Institute, China Academy of Railway Sciences, Beijing 100015, China

Abstract: Because of the material, process restrictions and external environmental impact, the actual input-output relationship of rolling stock weighing sensor presents non-linear characteristics, which causes non-linear error of measurement results and limits the measurement accuracy, thus non-linear correction is needed. The curve fitting method and least squares method based on orthogonal polynomial are proposed to establish non-linear correction links, so as to achieve non-linear correction for rolling stock weighing sensor and thereby reduce the influence of non-linear characteristics on the measurement results and improve the measurement accuracy, and avoid the ill-posed problem of the matrix of formal equations at the same time. The test results show that the system nonlinearity of corrected system is obviously improved, and the measurement accuracy is greatly improved, and the method has the advantages such as easy operation, high correction efficiency, stable and reliable results and high engineering application value.

Keywords: rolling stock weighing sensor;non-linear correction;orthogonal polynomial;least square method;curve fitting method

2018, 44(4): 91-95  收稿日期: 2017-07-23;收到修改稿日期: 2017-10-13

基金项目: 

作者简介: 黄永刚(1981-),男,湖南常德市人,高级工程师,硕士,主要从事轨道交通机车车辆检测技术的研究。

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