Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Inverse Analysis for Road Roughness Profile Identification Utilizing Acceleration of a Moving Vehicle
A road roughness profile of pavement surface is one of the important indicators for status of bridges and roads, and regular pavement monitoring and repairing directly link to the life span of the bridge and road. This research proposes a dynamic regularized least square minimization to identify the road roughness profile directly by regularized least square minimization with dynamic programming. A new discrete-time linear state-space model of a vehicle dynamics which has a road roughness profile as an external input to the system is also proposed. Kalman filter is also a widely researched method of road roughness profile identification. The identification accuracy of dynamic regularized least square minimization was compared to that of Kalman filter. Observations showed that dynamic regularized least square minimization showed a reasonable accuracy and the accuracy was higher than that of Kalman filter in respect of Power Spectral Density (PSD) and International Roughness Index (IRI).
Inverse Analysis for Road Roughness Profile Identification Utilizing Acceleration of a Moving Vehicle
A road roughness profile of pavement surface is one of the important indicators for status of bridges and roads, and regular pavement monitoring and repairing directly link to the life span of the bridge and road. This research proposes a dynamic regularized least square minimization to identify the road roughness profile directly by regularized least square minimization with dynamic programming. A new discrete-time linear state-space model of a vehicle dynamics which has a road roughness profile as an external input to the system is also proposed. Kalman filter is also a widely researched method of road roughness profile identification. The identification accuracy of dynamic regularized least square minimization was compared to that of Kalman filter. Observations showed that dynamic regularized least square minimization showed a reasonable accuracy and the accuracy was higher than that of Kalman filter in respect of Power Spectral Density (PSD) and International Roughness Index (IRI).
Inverse Analysis for Road Roughness Profile Identification Utilizing Acceleration of a Moving Vehicle
Lecture Notes in Civil Engineering
Wu, Zhishen (Herausgeber:in) / Nagayama, Tomonori (Herausgeber:in) / Dang, Ji (Herausgeber:in) / Astroza, Rodrigo (Herausgeber:in) / Hasegawa, Soichiro (Autor:in) / Kim, Chul-Woo (Autor:in) / Toshi, Naoya (Autor:in) / Chang, Kai-Chun (Autor:in)
Experimental Vibration Analysis for Civil Engineering Structures ; Kapitel: 53 ; 643-654
24.08.2022
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Road roughness profile identification , Vehicle acceleration , Inverse analysis , Dynamic regularized least square minimization , Drive-by inspection Engineering , Civil Engineering , Vibration, Dynamical Systems, Control , Mechanical Engineering , Structural Materials , Cyber-physical systems, IoT , Professional Computing
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