陈广华, 张金喜, 曹丹丹, 曾靖翔, 吴洋. 智能手机检测的行车振动数据与路面平整度关系[J]. 北京工业大学学报, 2021, 47(10): 1148-1157. DOI: 10.11936/bjutxb2020020007
    引用本文: 陈广华, 张金喜, 曹丹丹, 曾靖翔, 吴洋. 智能手机检测的行车振动数据与路面平整度关系[J]. 北京工业大学学报, 2021, 47(10): 1148-1157. DOI: 10.11936/bjutxb2020020007
    CHEN Guanghua, ZHANG Jinxi, CAO Dandan, ZENG Jingxiang, WU Yang. Relationship Between Pavement Roughness and Vibration Data Measured by Smart Phone[J]. Journal of Beijing University of Technology, 2021, 47(10): 1148-1157. DOI: 10.11936/bjutxb2020020007
    Citation: CHEN Guanghua, ZHANG Jinxi, CAO Dandan, ZENG Jingxiang, WU Yang. Relationship Between Pavement Roughness and Vibration Data Measured by Smart Phone[J]. Journal of Beijing University of Technology, 2021, 47(10): 1148-1157. DOI: 10.11936/bjutxb2020020007

    智能手机检测的行车振动数据与路面平整度关系

    Relationship Between Pavement Roughness and Vibration Data Measured by Smart Phone

    • 摘要: 面向路面平整度的智能化检测目标,采用目前广泛应用的智能手机作为行车振动检测手段,开展了不同平整度路面、不同车辆、不同速度等工况下的行车实验.以车辆行车过程中产生的竖向振动加速度的平均绝对偏差作为行车振动加速度指标,分析了行车振动加速度指标与行车速度和路面平整度之间的关系,提出了行车振动加速度指标的速度敏感度参数.结果表明:路面平整度相同情况下,行车振动加速度指标与行车速度具有显著的线性相关性,可用速度敏感度参数表征,而路面平整度与速度敏感度参数也具有显著的线性相关性,而且当平整度大于2 mm/m时相关性更加显著.建立了路面平整度-速度敏感度参数模型(IRI-SS模型)和基于该模型的路面平整度智能化检测方法.该路面平整度检测方法的平均检测精度大于85%,最高可达93%,具有实际应用的可能性.该检测方法为路面平整度的智能化检测提供了一种途径.

       

      Abstract: Facing the intelligent detection target of pavement roughness, this paper took the widely used smart phone as the vibration detection method of driving vehicle, and carried out a series of driving experiments under different vehicles, different speeds and other conditions. The average absolute deviation of the vertical vibration acceleration produced in the driving process was used as the driving vibration acceleration index (VAI), the relationship between the driving vibration acceleration, the driving speed and the pavement roughness was analyzed, and a parameter called speed sensitivity (SS) was proposed. Results show that the VAI has a significant linear correlation with the driving speed when the pavement roughness is almost the same, which can be characterized by the parameter called speed sensitivity, and the pavement roughness has also a significant linear correlation with the speed sensitivity parameter. When the international roughness index (IRI) is larger than 2 mm/m, the correlation becomes more sensitive. Based on the above analysis, the IRI detection model called IRI-SS model was put forward. The results of preliminary driving test show that the average detection accuracy of IRI by using this method is more than 85% in total, and the highest average detection accuracy reaches up to 93%, which shows the possibility of practical application. This detection method provides a new possible way for the intelligent detection of pavement roughness.

       

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