计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (5): 15-18.

• 博士论坛 • 上一篇    下一篇

列车横向加速度传感器的误差补偿

李广军,金炜东   

  1. 西南交通大学 电气学院,成都 610031
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2012-02-11 发布日期:2012-02-11

Error compensation of train’s lateral acceleration sensors

LI Guangjun, JIN Weidong   

  1. School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2012-02-11 Published:2012-02-11

摘要: 提出了一种基于最小二乘法的加速度传感器误差补偿方法,用来提高列车横向加速度的检测精度。利用正弦信号对加速度传感器进行了性能测试,确定了放大器倍数,证实了加速度传感器输出信号在波峰和波谷处误差最大,误差与输入加速度信号的幅值成正比,与输入加速度信号的周期成反比。为了减少误差,对加速度传感器进行了误差补偿,推导了补偿器的数学模型,使用最小二乘法对模型参数进行了辨识,求出该模型最优的待定常量,确定了补偿器模型。针对典型的列车横向加速度检测系统,以采集的列车横向加速度为输入信号,利用实验来验证补偿器的有效性。实验结果表明,经过补偿后,加速度传感器输出信号误差明显减少,均方误差收敛到10-4。传感器的测量精度有了显著提高,完全满足工程要求。

关键词: 列车横向加速度, 传感器, 误差补偿, 最小二乘法

Abstract: An error compensation method of sensors based on the least square algorithm identification is proposed to improve the mearurement accuracy of train’s lateral acceleration. Performance tests are carried out by sinusoidal signal. The multiple of the amplifier is determined. It is confirmed that maximum error of the acceleration sensor’s output signal is in the peaks and troughs, which is proportional to the input signal amplitude and is inversely proportional to the input signal cycle of acceleration. To reduce acceleration error, error compensation is used and the compensator’s mathematical model is derived at the same time. The model parameters are identified to calculate the constants in the compensation model by least square algorithm. The model of the compensator is built in this way. To verify the effectiveness of the compensator, the collected lateral acceleration signals of train are inputted for a typical train’s lateral acceleration detection system in the experiment. Experimental results show that the error of acceleration sensor output signal significantly reduces and the mean square error converges to 10-4 after compensation. The measurement accuracy of sensor is improved significantly and meets the engineering requirements as well.

Key words: train’s lateral acceleration, sensor, error compensation, least square algorithm