• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 57 Issue 4
Jul.  2022
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Article Contents
CHEN Rong, CONG Jianli, GAO Mingyuan, WANG Yuan, WANG Ping. Using Smartphone to Detect Vehicle Running Quality and Its Coordinate Alignment[J]. Journal of Southwest Jiaotong University, 2022, 57(4): 830-839. doi: 10.3969/j.issn.0258-2724.20200756
Citation: CHEN Rong, CONG Jianli, GAO Mingyuan, WANG Yuan, WANG Ping. Using Smartphone to Detect Vehicle Running Quality and Its Coordinate Alignment[J]. Journal of Southwest Jiaotong University, 2022, 57(4): 830-839. doi: 10.3969/j.issn.0258-2724.20200756

Using Smartphone to Detect Vehicle Running Quality and Its Coordinate Alignment

doi: 10.3969/j.issn.0258-2724.20200756
  • Received Date: 09 Nov 2020
  • Rev Recd Date: 17 May 2021
  • Publish Date: 07 Sep 2021
  • As there is angle deviation between the car body coordinate system and smarphone coordinate system, a systematic correction method for the smartphone coordinate alignment is proposed to make smartphone sensor data truly reflect the vibration acceleration of the vehicle body. This method corrects the smartphone vertical acceleration according to gravity direction, and the smartphone horizontal acceleration by means of the orthogonality of the lateral and longitudinal acceleration of the vehicle body. The maximum likelihood principle is used in the estimation of angular deviation to ensure the reliability of smartphone angle correction. Field test results indicate that the detection data of two smartphones obtained a vertical angle deviation of 0.008° and 0.007° relative to gravity direction, the horizontal angle between both smartphones is 29.75°, and the deviation from the test placement angle 30.00° is 0.25°. The amplitude and main frequency of the vehicle body acceleration respectively detected by the smartphone and the high-precision sensor are consistent in time domain and frequency domain.

     

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  • [1]
    WANG Y, CONG J L, WANG P, et al. A data-fusion approach for speed estimation and location calibration of a metro train based on low-cost sensors in smartphones[J]. IEEE Sensors Journal, 2019, 19(22): 10744-10752.
    [2]
    WANG P, WANG Y, WANG L, et al. Measurement of carbody vibration in urban rail tril transtit using smartphones[C]//Transportation Research Board 96th Annual Meeting. Washington D C: [s.n.], 2017: 1-15
    [3]
    JOHANNING E, FISCHER S, CHRIST E, et al. Whole-body vibration exposure study in US railroad locomotives—an ergonomic risk assessment[J]. AIHA Journal, 2002, 63(4): 439-446. doi: 10.1080/15428110208984732
    [4]
    LEE J S, CHOI S, KIM S S, et al. A mixed filtering approach for track condition monitoring using accelerometers on the axle box and bogie[J]. IEEE Transactions on Instrumentation and Measurement, 2012, 61(3): 749-758. doi: 10.1109/TIM.2011.2170377
    [5]
    WANG Y T, QIN Y, WEI X K. Track irregularities estimation based on acceleration measurements[C]//Proceedings of 2012 International Conference on Measurement, Information and Control. Harbin: IEEE, 2012: 83-87.
    [6]
    TSUNASHIMA H, KOJIMA T, MARUMO Y, et al. Condition monitoring of railway track and driver using in-service vehicle[C]//4th IET International Conference on Railway Condition Monitoring. Derby: IEE, 2008: 1-6
    [7]
    LEDERMAN G, CHEN S H, GARRETT J H, et al. Track monitoring from the dynamic response of a passing train:a sparse approach[J]. Mechanical Systems and Signal Processing, 2017, 90: 141-153. doi: 10.1016/j.ymssp.2016.12.009
    [8]
    GAO M Y, CONG J L, XIAO J L, et al. Dynamic modeling and experimental investigation of self-powered sensor nodes for freight rail transport[J]. Applied Energy, 2020, 257: 113969.1-113969.19.
    [9]
    GAO M Y, SU C G, CONG J L, et al. Harvesting thermoelectric energy from railway track[J]. Energy, 2019, 180: 315-329. doi: 10.1016/j.energy.2019.05.087
    [10]
    WANG Y, WANG P, WANG X, et al. Position synchronization for track geometry inspection data via big-data fusion and incremental learning[J]. Transportation Research Part C:Emerging Technologies, 2018, 93: 544-565. doi: 10.1016/j.trc.2018.06.018
    [11]
    SONG C, WU J, LIU M, et al. RESen: sensing and evaluating the riding experience based on crowdsourcing by smartphones[C]//2012 8th International Conference on Mobile Ad-hoc and Sensor Networks. Chengdu: IEEE, 2012: 147-152.
    [12]
    HERRERA J C, WORK D B, HERRING R, et al. Evaluation of traffic data obtained via GPS-nabled mobile phones:the Mobile Century field experi-ment[J]. Transportation Research Part C:Emerging Technologies, 2010, 18(4): 568-583. doi: 10.1016/j.trc.2009.10.006
    [13]
    WANG Y, CHEN Y J, YANG J, et al. Determining driver phone use by exploiting smartphone integrated sensors[J]. IEEE Transactions on Mobile Computing, 2016, 15(8): 1965-1981. doi: 10.1109/TMC.2015.2483501
    [14]
    从建力,王源,杨翠平,等. 智能手机检测车辆振动加速度数据预处理方法[J]. 数据采集与处理,2019,34(2): 349-357.

    CONG Jianli, WANG Yuan, YANG Cuiping, et al. Data preprocessing method of vehicle vibration acceleration by smartphone[J]. Journal of Data Acquisition and Processing, 2019, 34(2): 349-357.
    [15]
    罗林, 张格明, 吴旺青, 等. 轮轨系统轨道平顺状态的控制[M]. 北京: 中国铁道出版社, 2006.
    [16]
    KIM Y G, KWON H B, KIM S W, et al. Correlation of ride comfort evaluation methods for railway vehicles[J]. Proceedings of the Institution of Mechanical Engineers,Part F:Journal of Rail and Rapid Transit, 2003, 217(2): 73-88. doi: 10.1243/095440903765762823
    [17]
    铁道部科学研究院机车车辆研究所. 高速试验列车动力车强度及动力学性能规范: 95J01-L[S]. 北京: 铁道出版社, 2019
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