Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (6): 1765-1772.doi: 10.13229/j.cnki.jdxbgxb.20221508

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Road roughness identification method based on vehicle impulse response

Qing-xia ZHANG1(),Ji-lin HOU2(),Xin-hao AN2,Xiao-yang HU3,Zhong-dong DUAN3   

  1. 1.School of Civil Engineering，Dalian Minzu University，Dalian 116600，China
    2.Department of Construction Engineering，Dalian University of Technology，Dalian 116024，China
    3.School of Civil and Environmental Engineering，Harbin Institute of Technology，Shenzhen 518055，China
  • Received:2022-11-25 Online:2023-06-01 Published:2023-07-23
  • Contact: Ji-lin HOU E-mail:zhangqingxia@dlnu.edu.cn;houjilin@dlut.edu.cn

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Abstract:

Based on the vehicle impulse response， a method of pavement roughness identification using vehicle dynamic response was proposed. First， road roughness was taken as input and the equation of vehicle response computation based on the impulse response function was derived. Then， the impulse response function was discretized into the matrix form and a linear equation for road roughness identification was established based on the impulse response matrix. Furthermore， considering that the front and rear wheels experienced the same road roughness， the correlation matrix of the front and rear wheels was constructed， which can decrease the computational work of road roughness identification. Then， take the advantage of the continuity of the road roughness， the load shape function was used to approximate it and thus not only the unknown identification number was further reduced but also the robustness of method to noise was improved， which achieved the real time identification. At last， the effectiveness of the proposed method was verified by numerical simulation and field test.

Key words: road engineering, impulse response, vehicle dynamic response, road roughness identification, shape function

CLC Number: 

  • U416

Fig.1

Force diagram of a half-vehicle model"

Fig.2

Displacement correlation between front and rear wheels"

Fig.3

Shape function of unevenness curve"

Table 1

Natural frequency of vehicle"

模态阶数1234
频率/Hz1.2812.02812.40214.932

Fig.4

Road roughness curve"

Fig.5

Simulated vehicle acceleration response"

Fig.6

Identified road roughness"

Fig.7

Identification error"

Fig.8

Identification results using theoretical noise free response"

Fig.9

Identification results using noise polluted response"

Fig.10

Road roughness identification using denoised response"

Table 2

Identification errors of different methods"

方法理论响应含噪声响应去噪响应
直接法0.0121.5270.140
形函数法0.0690.1370.139

Table 3

Identification errors using"

噪声水平/%51525355070
误差/cm0.0870.1960.3200.4470.6380.895

Fig.11

Road roughness identification using noise polluted response via shape function method"

Fig.12

On-line identification resuils of road roughness"

Fig.13

Measured vehicle response"

Fig.14

On-line identification results of road roughness in field test"

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