Continuous velocity and location detection method of maglev vehicle based on cross inductive loop
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摘要: 分析了交叉回线区域空间磁场分布, 利用磁通密度纵向分布周期性特征, 将车辆位移、速度用感应电压包络信号相位角与角速度来表征; 建立了采用简单交叉回线的车辆测速定位状态空间方程组, 将车辆运行位置和速度作为状态变量在测试过程中连续输出; 考虑实际运行工况下的复杂电磁环境, 引入了噪声自适应算法, 提出了基于新息自适应的磁浮车辆实时连续测速定位计算方法; 在实验室条件下建立了交叉感应回线标定系统, 验证了方法的基本原理; 为了验证方法的有效性和准确性, 进了数值仿真算例分析, 考虑正常噪声和突变噪声工况, 并对比了包含和不包含自适应噪声处理过程的计算结果。试验结果表明: 不同间隔距离条件下, 感应电压包络线都接近于正弦波, 1次谐波是包络信号的主要成分, 相同阶次的谐波幅值与间隔距离成近似线性关系, 与理论分析结果一致; 在正常噪声区段, 速度误差不超过0.03 m·s-1, 定位误差约为3 mm, 在突变噪声区段, 速度误差均值为0.027 m·s-1, 最大值为0.130 m·s-1, 定位误差均值为4.82 mm, 最大值为23.39 mm, 说明测速定位方法可以满足实际应用需求; 数值仿真中突变噪声区段的低信噪比信号在实际应用中是极端情况, 对比正常噪声区段和突变噪声区段的计算结果可知改善输入信号的信噪比可以明显提高测试精度。Abstract: The spatial magnetic field distribution in the cross loop region was analyzed, and the vehicle displacement and velocity were characterized by the phase angle and angular velocity of the induced voltage envelope signal based on the longitudinal distribution and periodicity of magnetic flux density. The state-space equations of vehicle speed and location detection using simple cross loop were established, and the location and speed of the vehicle were taken as state variables outputted continuously during the test. Considering the complicated electromagnetic environment under the actual operating condition, the noise adaptive algorithm was introduced, and the real-time continuous speed and location detection calculation method of maglev vehicle based on the innovation adaption was proposed. The cross induction loop calibration system was established under laboratory condition, and the basic principle of the method was verified. In order to verify the effectiveness and accuracy of the method, numerical simulation analysis was carried out considering the normal and abrupt noise conditions, and the calculation results in the processes with and without adaptive noise were compared. Experimental result shows that at different interval distances, the induced voltage envelopes are close to the sinusoid. The first harmonic is the main component of the envelope signal, and the harmonic amplitude of the same order is approximately linear with the interval distance, which is consistent with the theoretical analysis result. In the normal noise section, the speed error is no more than 0.03 m·s-1, and the location error is about 3 mm. While in the abrupt noise section, the mean value and maximum value of velocity errors are 0.027 and 0.130 m·s-1, respectively, and the mean value and maximum value of location errors are 4.82 and 23.39 mm, respectively. It means that the speed and location detection method can meet the actual application requirement. The low signal-to-noise ratio(SNR) signal in the abrupt noise section in the numerical simulation is an extreme case in the practical application. Comparing the calculation results of normal and abrupt noise sections, improving the SNR of the input signal can obviously improve the measurement accuracy.
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表 1 突变噪声区段计算结果
Table 1. Calculation results of abrupt noise section
计算方法 定位误差/mm 速度误差/(m·s-1) 均值 最大值 均值 最大值 EKF 8.06 39.69 0.046 0.21 IAEKF 4.82 23.39 0.027 0.13 -
[1] LEE H W, KIM K C, LEE J. Review of maglev train technologies[J]. IEEE Transactions on Magnetics, 2006, 42(7): 1917-1925. doi: 10.1109/TMAG.2006.875842 [2] 龙志强, 李晓龙, 周文武, 等. 磁悬浮列车的定位和测速技术研究[J]. 国防科技大学学报, 2003, 25(4): 82-88. doi: 10.3969/j.issn.1001-2486.2003.04.019LONG Zhi-qiang, LI Xiao-long, ZHOU Wen-wu, et al. Study on the techniques of the locating and speed-measuring of the aerotrain[J]. Journal of National University of Defense Technology, 2003, 25(4): 82-88. (in Chinese). doi: 10.3969/j.issn.1001-2486.2003.04.019 [3] 杨建勇, 连级三. 磁悬浮列车定位测速及数据传输方法研究[J]. 铁道学报, 2001, 23(1): 60-65. doi: 10.3321/j.issn:1001-8360.2001.01.013YANG Jian-yong, LIAN Ji-san. Study on the methods of train locating speed measuring and data transmission for maglev train[J]. Journal of the China Railway Society, 2001, 23(1): 60-65. (in Chinese). doi: 10.3321/j.issn:1001-8360.2001.01.013 [4] 张世聪. 适用于磁浮列车的测速定位方法研究综述[J]. 铁道标准设计, 2018, 62(10): 186-191. https://www.cnki.com.cn/Article/CJFDTOTAL-TDBS201810037.htmZHANG Shi-cong. Research review of speed and position detection methods applied to maglev trains[J]. Railway Standard Design, 2018, 62(10): 186-191. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-TDBS201810037.htm [5] 吴峻, 周文武, 李璐. 高速磁浮列车测速定位系统的研究[J]. 国防科技大学学报, 2011, 33(1): 109-114. doi: 10.3969/j.issn.1001-2486.2011.01.023WU Jun, ZHOU Wen-wu, LI Lu. Research on speed and position detection system of high speed maglev train[J]. Journal of National University of Defense Technology, 2011, 33(1): 109-114. (in Chinese). doi: 10.3969/j.issn.1001-2486.2011.01.023 [6] MORISHITA K, KITANO J I, MAEDA T, et al. Novel train position detecting system in the Yamanashi Maglev test line[C]//TRB. 19th International Conference on Magnetically Levitated Systems and Linear Drives. Washington DC: TRB, 2006: 1-4. [7] XUE Song, LONG Zhi-qiang, HE Ning, et al. A high precision position sensor design and its signal processing algorithm for a maglev train[J]. Sensors, 2012, 12: 5225-5245. doi: 10.3390/s120505225 [8] DAI Chun-hui, LONG Zhi-qiang, XIE Yun-de, et al. Research on the filtering algorithm in speed and position detection of maglev trains[J]. Sensors, 2011, 11: 7204-7218. doi: 10.3390/s110707204 [9] XUE Song, DAI Chun-hui, LONG Zhi-qiang. Research on location and speed detection for high speed maglev train based on long stator[C]//IEEE. Proceedings of the 8th World Congress on Intelligent Control and Automation. New York: IEEE, 2010: 6953-6958. [10] 钱存元, 邵德荣, 谢维达, 等. 高速磁悬浮列车测速定位系统的设计与研究[J]. 仪表技术与传感器, 2004(9): 34-36. doi: 10.3969/j.issn.1002-1841.2004.09.015QIAN Cun-yuan, SHAO De-rong, XIE Wei-da, et al. Design and research on speed and position detection system for high-speed maglev train[J]. Instrument Technique and Sensor. 2004(9): 34-36. (in Chinese). doi: 10.3969/j.issn.1002-1841.2004.09.015 [11] 李萌, 曹林, 王东峰. 用于机车测速的雷达传感器算法研究[J]. 传感器与微系统, 2016, 35(12): 69-71. https://www.cnki.com.cn/Article/CJFDTOTAL-CGQJ201612020.htmLI Meng, CAO Lin, WANG Dong-feng. Algorithm study of radar sensor for locomotive speed measuring[J]. Transducer and Microsystem Technologies, 2016, 35(12): 69-71. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CGQJ201612020.htm [12] 姬冰冰, 买培培, 苏涛. 一种基于卡尔曼滤波的机车测速雷达算法[J]. 火控雷达技术, 2009, 38(1): 43-47. doi: 10.3969/j.issn.1008-8652.2009.01.012JI Bing-bing, MAI Pei-pei, SU Tao. An algorithm based on Kalman filter for locomotive speed radar[J]. Fire Control Radar Technology, 2009, 38(1): 43-47. (in Chinese). doi: 10.3969/j.issn.1008-8652.2009.01.012 [13] 郭小舟, 王滢, 王式雄. 高速磁悬浮列车定位测速系统[J]. 西南交通大学学报, 2004, 39(4): 455-459. doi: 10.3969/j.issn.0258-2724.2004.04.009GUO Xiao-zhou, WANG Ying, WANG Shi-xiong. Location and speed detection system for high-speed maglev vehicle[J]. Journal of Southwest Jiaotong University, 2004, 39(4): 455-459. (in Chinese). doi: 10.3969/j.issn.0258-2724.2004.04.009 [14] QIAN Cun-yuan, HAN Zheng-zhi, XIE Wei-da. Research on absolute positioning system for high-speed maglev train[C]//IEEE. Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation. New York: IEEE, 2007: 922-926. [15] ZHANG Da-peng, LONG Zhi-qiang, XUE Song, et al. Optimal design of the absolute positioning sensor for a high-speed maglev train and research on its fault diagnosis[J]. Sensors, 2012, 12: 10621-10638. doi: 10.3390/s120810621 [16] 陈正一, 谢维达, 钱存元. 磁浮列车绝对定位系统[J]. 电力机车与城轨车辆, 2005, 28(6): 8-10. https://www.cnki.com.cn/Article/CJFDTOTAL-DJJI200506002.htmCHEN Zheng-yi, XIE Wei-da, QIAN Cun-yuan. Absolute position detection system for maglev train[J]. Electric Locomotives and Mass Transit Vehicles, 2005, 28(6): 8-10. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-DJJI200506002.htm [17] DAI Chun-hui, DOU Feng-shan, SONG Xiang-lei, et al. Analysis and design of a speed and position system for maglev vehicles[J]. Sensors, 2012, 12: 8526-8543. doi: 10.3390/s120708526 [18] DAI Chun-hui, SONG Xiang-lei, DOU Feng-shan, et al. Study on the speed and location system for low speed maglev vehicle[C]//IEEE. Proceedings of the IEEE International Conference on Automation and Logistics. New York: IEEE, 2011: 220-224. [19] 宋香磊. 基于感应环线的测速定位系统的设计与实现[D]. 长沙: 国防科学技术大学, 2012.SONG Xiang-lei. The design and realization of the speed and location detection system based on the inductive looped-cable[D]. Changsha: National University of Defense Technology, 2012. (in Chinese). [20] 张斌. 基于新型感应环线的磁浮列车定位测速与通信技术研究[D]. 长沙: 国防科学技术大学, 2015.ZHANG Bin. The research of position and speed measurement and communication technology based on the new loop-cable for maglev train[D]. Changsha: National University of Defense Technology, 2015. (in Chinese). [21] DENG Zi-gang, ZHANG Wei-hua, ZHENG Jun, et al. A high-temperature superconducting maglev ring test line developed in Chengdu, China[J]. IEEE Transactions on Applied Superconductivity, 2016, 26(6): 3602408-1-8. [22] QIAN Nan, ZHENG Jun, LEI Wu-yang, et al. Dynamic vibration characteristics of HTS levitation systems operating on a permanent magnet guideway test line[J]. IEEE Transactions on Applied Superconductivity, 2017, 27(4): 3601405-1-5. [23] 勾艳凤. 高温超导磁悬浮车环形线振动特性研究[D]. 成都: 西南交通大学, 2015.GOU Yan-feng. Studies on the vibration characteristics of high-temperature superconducting maglev vehicles on a ring test line[D]. Chengdu: Southwest Jiaotong University, 2015. (in Chinese). [24] JIN Li-an, DENG Zi-gang, LEI Wu-yang, et al. Dynamic characteristics of the HTS maglev vehicle running under a low-pressure environment[J]. IEEE Transactions on Applied Superconductivity, 2019, 29(2): 3601504-1-4. [25] DENG Zi-gang, LI Ji-peng, ZHANG Wei-hua, et al. High-temperature superconducting magnetic levitation vehicles dynamic characteristics while running on a ring test line[J]. IEEE Vehicular Technology Magazine, 2017, 12(3): 95-102. [26] MOHAMED A H, SCHWARZ K P. Adaptive Kalman filtering for INS/GPS[J]. Journal of Geodesy, 1999, 73: 193-203. [27] HIDE C, MOORE T, SMITH M. Adaptive Kalman filtering algorithms for integrating GPS andlow cost INS[C]//IEEE. 2004 Position Location and Navigation Symposium. New York: IEEE, 2004: 227-233. [28] FU Min-yue, DE SOUZA C, LUO Zhi-quan. Finite-horizon robust Kalman filter design[J]. IEEE Transactions on Signal Processing, 2001, 49(9): 2103-2112. [29] 徐定杰, 贺瑞, 沈锋, 等. 基于新息协方差的自适应渐消卡尔曼滤波器[J]. 系统工程与电子技术, 2011, 33(12): 2696-2699. https://www.cnki.com.cn/Article/CJFDTOTAL-XTYD201112025.htmXU Ding-jie, HE Rui, SHEN Feng, et al. Adaptive fading Kalman filter based on innovation covariance[J]. Systems Engineering and Electronics, 2011, 33(12): 2696-2699. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XTYD201112025.htm [30] 岳晓奎, 袁建平. 一种基于极大似然准则的自适应卡尔曼滤波算法[J]. 西北工业大学学报, 2005, 23(4): 469-474. https://www.cnki.com.cn/Article/CJFDTOTAL-XBGD200504014.htmYUE Xiao-kui, YUAN Jian-ping. An adaptive Kalman filtering algorithm based on maximum-likelihood criterion[J]. Journal of Northwestern Polytechnical University, 2005, 23(4): 469-474. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XBGD200504014.htm