Potholes are one type of pavement surface distresses whose assessment is essential for developing road network maintenance strategies. Existing methods for automatic pothole detection either rely on expensive and high‐maintenance equipment or could not segment the pothole accurately. In this paper, an asphalt pavement pothole detection and segmentation method based on energy field is put forward. The proposed method mainly includes two processes. Firstly, the wavelet energy field of the pavement image is constructed to detect the pothole by morphological processing and geometric criterions. Secondly, the detected pothole is segmented by Markov random field model and the pothole edge is extracted accurately. This methodology has been implemented in a MATLAB prototype, trained, and tested on 120 pavement images. The results show that it can effectively distinguish potholes from cracks, patches, greasy dirt, shadows, and manhole covers and accurately segment the pothole. For pothole detection, the method reaches an overall accuracy of 86.7%, with 83.3% precision and 87.5% recall. For pothole segmentation, the overlap degree between the extracted pothole region and the original pothole region is mostly more than 85%, which accounts for 88.6% of the total detected pavement pothole images.

Current pavement pothole repair technology relies heavily on human experience and manual operation. To automate the repair process of pavement pothole spraying repair, a contour-guided zigzag path planning method based on depth image was proposed in this paper, including pothole slicing and slice repair path planning. In the aspect of pothole slicing, a double flood filling method was proposed to ensure the repair strategy from bottom to up under the priority of region by region, while in the aspect of slice path planning, a contour-guided round-trip repair path planning method was proposed to arrange the repair trajectory homogeneously in the pothole without exceeding its irregular boundary. The path planning results showed that the average spacing error of four kinds of common potholes with different shapes was 7.31%, the average time of the whole path planning process was 1.571 s, the average relative difference of the mean square error was only 1.83 mm, which indicated that the proposed method could obtain high path planning accuracy and fast path planning speed. The results demonstrated that the proposed contour-guided zigzag path planning method based on depth image could be applied to the automatic spraying repair of different potholes with convex or concave contours and achieve good pavement repair flatness.

Wear is the main failure type for conical cutters. The main load causing its wear is difficult to measure in the test, and the existing simulation models cannot simulate the wear load. Thus, the three-dimensional dynamic model for conical cutter crushing rock is established based on the SPH-SPH interaction method to analyze the relationship between the cutting performance factors and cutter wear. The factors are taken into account such as the stress distribution of rock, kinetic energy and internal energy and displacement of rock, cutting load of cutter, stress of cutter. Then, it is studied that the effect of cutting angle on the cutting performance parameters such as specific energy consumption, rock avalanching, cutting load, load fluctuation, cutter tip stress and cutter side stress. Finally, the cutting angle selection reference of the cutter is given under different consideration factors.