轮廓仪
卡尔曼滤波器
加速度计
表面光洁度
表面粗糙度
国际粗糙度指数
非线性系统
扩展卡尔曼滤波器
功率(物理)
结构工程
计算机科学
控制理论(社会学)
工程类
汽车工程
机械工程
材料科学
物理
人工智能
复合材料
操作系统
控制(管理)
量子力学
作者
Qing Zeng,Xiaoyang Hu,Xiaodong Shi,Yiting Ren,Yuan Li,Zhongdong Duan
标识
DOI:10.1142/s0219455422500730
摘要
The evaluation of road roughness plays a critical role in the life-long maintenance of the highway system. This study proposes a Kalman Filter-based scheme to evaluate the road roughness indirectly from the response of a moving adapted monitoring vehicle. Key feature of the scheme is the use of measurements from dynamic tire pressure of unsprung mass components that directly interact with roads. Combination of ideal gas law and elastic contact model results in a nonlinear relationship between the tire pressure and the contact force, in which the parameters are calibrated by the Extended Kalman Filter. Identification of vehicle’s physical parameters adopts the power spectrum method with a known-size bump test. Subsequently, the road roughness is treated as unknowns in the vehicle’s state-space equation and solved by the Discrete Kalman Filter with unknown inputs. The estimated road roughness profiles are then used to calculate the International Roughness Index and compared with that provided by the standardized laser profilometer, an outer-systematic comparison. On the other hand, available measurements are split into groups that measurements of tire pressure are used to predict the accelerations of the car body and wheels and compared with these accelerations directly measured from accelerometers, an inner-systemic comparison. Field tests are carried out on a 900[Formula: see text]m long standardized road under two scenarios of with and without the bump and four different vehicle running speeds from 20 to 50[Formula: see text]km/h. Consistence of comparison from different perspectives proves the reliability of the proposed scheme. In addition, the results unveil that the scenario with a lower running speed can offer a better estimation of road roughness.
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