Dehong Wang

To enhance the anti-overturning performance of poles and prevent tilting or collapse, a prefabricated foundation for distribution lines is developed. Field tests are conducted on five groups of foundations. Based on the test results, finite element analysis (FEA) is employed to investigate the influence of different factors—such as pole embedment depth, foundation locations, soil type, and soil parameters—on the anti-overturning performance of pole prefabricated foundations. The results indicate that under ultimate load conditions, the reaction force distribution at the base of the foundation approximates a triangular pattern, and the lateral earth pressure on the pole follows an approximately quadratic parabolic distribution along the depth. When the foundation size increases from 0.8 m to 0.9 m, the bearing capacity of the prefabricated foundation improves by 8%. Furthermore, when the load direction changes from 0° to 45°, the foundation’s bearing capacity increases by 14%. When the foundation is buried at a depth of 1.0 m, compared with the ground position, the ultimate overturning moment of the prefabricated foundation increases by 10%. Based on field test results, finite element simulation results, and limit equilibrium theory, a calculation method for the anti-overturning bearing capacity of prefabricated pole foundations is developed, which can provide a practical reference for the engineering design of distribution line poles and their prefabricated foundations.

To address the engineering issues of difficult quality control, complex construction processes, and long construction periods in cast-in-place protective walls for manually excavated piles, a prefabricated protective wall structure is proposed. This study aims to investigate its mechanical properties and key influencing parameters through experiments. Six groups of prefabricated wall segment specimens with different wall thicknesses (50 mm, 65 mm) and concrete strengths (C50 concrete, reactive powder concrete RPC) were designed, and two-point bending tests were conducted to systematically analyze their failure characteristics, crack development patterns, and strain distribution laws. The test results show that the peak vertical bending displacements at mid-span of the specimens are 11–18 mm (1.83–2.71% of the radius). The 65-mm-thick specimens exhibit 3–10% higher flexural strength than the 50-mm-thick ones, and reactive powder concrete (RPC) specimens of the same thickness show an 8.3% increase in strength compared to C50 concrete specimens. When the load reaches 80% of the ultimate load, abrupt changes in concrete strain occur at the mid-span and loading points, while the strain at the fixed end is only 15–20% of the mid-span strain. The prefabricated protective wall demonstrates superior deformation resistance, with vertical displacements (3–5% of the radius) significantly lower than those of cast-in-place walls. This research clarifies the influence of wall thickness and concrete strength on the mechanical properties of prefabricated protective walls, providing key mechanical parameters to support their engineering applications.

As a fundamental element of the wind power generation system, the timely detection and rectification of surface cracks and other defects are imperative to ensure the stable function of the entire system. A new wind tower surface crack detection model, You Only Look Once version 5l GhostNetV2-CBAM-BiFPN (YOLOv5l-GCB), is proposed to accomplish the accurate classification of wind tower surface cracks. Ghost Network Version 2 (GhostNetV2) is integrated into the backbone of YOLOv5l to realize lightweighting of the backbone, which simplifies the complexity of the model and enhances the inference speed; the Convolutional Block Attention Module (CBAM) is added to strengthen the attention of the model to the target region; and the bidirectional feature pyramid network (BiFPN) has been developed for the purpose of enhancing the model’s detection accuracy in complex scenes. The proposed improvement strategy is verified through ablation experiments. The experimental results indicate that the precision, recall, F1 score, and mean average precision of YOLOv5l-GCB reach 91.6%, 99.0%, 75.0%, and 84.6%, which are 4.7%, 2%, 1%, and 10.4% higher than that of YOLOv5l, and it can accurately recognize multiple types of cracks, with an average number of 28 images detected per second, which improves the detection speed.

To investigate the influence of repeated loading on the bond behavior between steel bars and reactive powder concrete (RPC), this study conducted repeated loading tests on eight beam specimens and one static loading test as a control. The effects of stress levels and the number of repeated loading cycles on the bond behavior between steel bars and RPC were examined. The results indicate that the static failure mode was characterized by steel bar pull-out accompanied by significant plastic deformation, with no propagation of cracks in the RPC after their initiation, demonstrating the excellent crack control capability of RPC. After 10,000 cycles of repeated loading at a high stress level (Z = 0.9), the ultimate bond strength decreased by only 3.68%, indicating the superior fatigue resistance of the steel–RPC interface. Based on the analysis of slip accumulation effects, a constitutive model considering stress levels and the number of repeated loading cycles was established. This model can serve as a basis for the design of steel anchorage in RPC structures subjected to cyclic loading.