With the explosive development of power edge equipment and the continuous improvement in power inspection performance, the requirements of substations and terminal equipment, such as drones with limited resources, cannot meet the strict delay and energy consumption requirements. This paper proposes an adaptive partitioning strategy for heterogeneous substation inspection systems. First, a layer delay prediction model and layer energy consumption prediction model are established on each heterogeneous node, and nonlinear characteristics related to delay and energy consumption are trained. On this basis, a deep neural network (DNN) hybrid partitioning strategy is proposed. The DNN task is divided into synchronous cooperative reasoning between terminal devices and multi-heterogeneous edge nodes. The experimental results show that the average absolute percentage error (MAPE) of the delay model was reduced by 31.49% on average. On drones and mobile edge nodes, the energy consumption model MAPE reduced the average by 21.92%, and the DNN end-to-end latency was reduced by 31.48%. The total cost of the system was reduced and the efficiency of UAV inspection was improved.

Fringe projection profilometry has been widely adopted in various fields due to its non-contact nature, high accuracy, high speed, and full-field measurement capability. However, when measuring objects with highly reflective surfaces, saturation often occurs due to the limited dynamic range of the camera. To effectively address this issue, this paper proposes a novel adaptive fringe projection method. First, an intensity transfer model is established, which uses uniform grayscale images to compute surface reflectance coefficients and accurately determines the optimal projection intensity in the camera coordinate system. Subsequently, low-intensity orthogonal fringe patterns are employed to compute a smoothed absolute phase in saturated regions, establishing a coordinate mapping. The mapped pixel intensities are diffused into their neighborhoods, and the minimum value is taken in overlapping areas to generate an optimal projection intensity template in the projector coordinate system. Finally, adaptive fringe patterns are generated based on this template. Experimental results demonstrate that the proposed method achieves high-precision and high-completeness 3D measurement for objects with highly reflective surfaces.