An Efficient Method for Detecting Asphalt Pavement Cracks and Sealed Cracks Based on a Deep Data-Driven Model

Thanks to the development of deep learning, the use of data-driven methods to detect pavement distresses has become an active research field. This research makes four contributions to address the problem of efficiently detecting cracks and sealed cracks in asphalt pavements. First, a dataset of pavement cracks and sealed cracks is created, which consists of 10,400 images obtained by a vehicle equipped with a highway condition monitor, with 202,840 labeled distress instances included in these pavement images. Second, we develop a dense and redundant crack annotation method based on the characteristics of the crack images. Compared with traditional annotation, the method we propose generates more object instances, and the localization is more accurate. Next, to achieve efficient crack detection, a semi-automatic crack annotation method is proposed, which reduces the working time by 80% compared with fully manual annotation. Finally, comparative experiments are conducted on our dataset using 13 currently prevailing object detection algorithms. The results show that dense and redundant annotation is effective; moreover, cracks and sealed cracks can be efficiently and accurately detected using the YOLOv5 series model and YOLOv5s is the most balanced model with an F1-score of 86.79% and an inference time of 14.8ms. The pavement crack and sealed crack dataset created in this study is publicly available

An Efficient Method for Detecting Asphalt Pavement Cracks and Sealed Cracks Based on a Deep Data-Driven Model

Thanks to the development of deep learning, the use of data-driven methods to detect pavement distresses has become an active research field. This research makes four contributions to address the problem of efficiently detecting cracks and sealed cracks in asphalt pavements. First, a dataset of pavement cracks and sealed cracks is created, which consists of 10,400 images obtained by a vehicle equipped with a highway condition monitor, with 202,840 labeled distress instances included in these pavement images. Second, we develop a dense and redundant crack annotation method based on the characteristics of the crack images. Compared with traditional annotation, the method we propose generates more object instances, and the localization is more accurate. Next, to achieve efficient crack detection, a semi-automatic crack annotation method is proposed, which reduces the working time by 80% compared with fully manual annotation. Finally, comparative experiments are conducted on our dataset using 13 currently prevailing object detection algorithms. The results show that dense and redundant annotation is effective; moreover, cracks and sealed cracks can be efficiently and accurately detected using the YOLOv5 series model and YOLOv5s is the most balanced model with an F1-score of 86.79% and an inference time of 14.8ms. The pavement crack and sealed crack dataset created in this study is publicly available

Continuous instinct control for powered knee-ankle prostheses

In order to improve the life quality of lower extremity amputees, many researchers have studied the powered knee-ankle prosthesis. Various parameters must necessarily be adjusted for the finite state machine impedance model method. Hybrid zero-dynamic (HZD) assumptions are ideal, and with this method measurement information of existing sensors can be limited. The virtual constraint method offers better comprehensive performance at present and can realize the continuous control for the whole gait cycle. The problem with virtual constraint is mainly the selection of phase variables. The joint trajectory of the virtual constraint is derived from a healthy individual, but the joint trajectory of the amputee’s normal walking is difficult to obtain. In response to the above problems, this paper proposes an instinctive human joint trajectory, selecting the phase variable associated with the hip joint angle and angular velocity. The Fourier transform solves the expression of the joint trajectory, and the virtual constraint unifies the control method of the entire gait cycle. The simulation results prove the feasibility of the scheme

Continuous instinct control for powered knee-ankle prostheses

In order to improve the life quality of lower extremity amputees, many researchers have studied the powered knee-ankle prosthesis. Various parameters must necessarily be adjusted for the finite state machine impedance model method. Hybrid zero-dynamic (HZD) assumptions are ideal, and with this method measurement information of existing sensors can be limited. The virtual constraint method offers better comprehensive performance at present and can realize the continuous control for the whole gait cycle. The problem with virtual constraint is mainly the selection of phase variables. The joint trajectory of the virtual constraint is derived from a healthy individual, but the joint trajectory of the amputee’s normal walking is difficult to obtain. In response to the above problems, this paper proposes an instinctive human joint trajectory, selecting the phase variable associated with the hip joint angle and angular velocity. The Fourier transform solves the expression of the joint trajectory, and the virtual constraint unifies the control method of the entire gait cycle. The simulation results prove the feasibility of the scheme

Experimental Investigation on the Mechanical Behavior of Bovine Bone Using Digital Image Correlation Technique

In order to understand the fracture mechanisms of bone subjected to external force well, an experimental study has been performed on the bovine bone by carrying out the three-point bending test with 3D digital image correlation (DIC) method, which provides a noncontact and full field of displacement measurement. The local strain and damage evolution of the bone has been recorded real time. The results show that the deflection measured by DIC agrees well with that obtained by the displacement sensor of the mechanical testing machine. The relationship between the deflection and the force is nearly linear prior to reaching the peak strength which is about 16 kN for the tested bovine tibia. The full-field strain contours of the bone show that the strain distribution depends on not only the force direction, but also the natural bone shape. The natural arched-shape bovine tibia bone could bear a large force, due to the tissue structure with high strength, and the fracture propagation process of the sample initiates at the inner side of the bone first and propagates along the force direction