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A Novel Method for Pavement Transverse Crack Detection Based on 2D Reconstruction of Vehicle Vibration Signal
Pavement transverse cracks are associated with pavement performance. However, due to low recognition accuracy, the transverse cracking detection through vehicle’s vibration response has hardly been considered. This paper proposes a novel method for pavement transverse cracking detection using reconstructed vehicle vibration signal. An accelerometer installed in the vehicle collects the vibration response between the vehicle and the pavement transverse cracks. A brand-new approach to data processing is suggested that transforms a one-dimensional vibration signal into a two-dimensional vibration image. The two-dimensional vibration image generated can obtain different features effectively from the time domain. Based on Gray Level Concurrence Matrix (GLCM) algorithm, a characteristic index established from the vibration image’s contrast can distinguish transverse cracks from uncracked sections. Then its feasibility was investigated by 410 pavement sections, the accuracy of the index is 93.84%. The transverse crack detection method proposed in this paper seems promising for precisely identifying pavement transverse cracks.
A Novel Method for Pavement Transverse Crack Detection Based on 2D Reconstruction of Vehicle Vibration Signal
Pavement transverse cracks are associated with pavement performance. However, due to low recognition accuracy, the transverse cracking detection through vehicle’s vibration response has hardly been considered. This paper proposes a novel method for pavement transverse cracking detection using reconstructed vehicle vibration signal. An accelerometer installed in the vehicle collects the vibration response between the vehicle and the pavement transverse cracks. A brand-new approach to data processing is suggested that transforms a one-dimensional vibration signal into a two-dimensional vibration image. The two-dimensional vibration image generated can obtain different features effectively from the time domain. Based on Gray Level Concurrence Matrix (GLCM) algorithm, a characteristic index established from the vibration image’s contrast can distinguish transverse cracks from uncracked sections. Then its feasibility was investigated by 410 pavement sections, the accuracy of the index is 93.84%. The transverse crack detection method proposed in this paper seems promising for precisely identifying pavement transverse cracks.
A Novel Method for Pavement Transverse Crack Detection Based on 2D Reconstruction of Vehicle Vibration Signal
KSCE J Civ Eng
Yuan, Wenzhi (author) / Yang, Qun (author)
KSCE Journal of Civil Engineering ; 27 ; 2868-2881
2023-07-01
14 pages
Article (Journal)
Electronic Resource
English
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