To meet the production demand for offline automatic stacking of large transformer cores, this paper researches on the feasibility of the double hole positioning system of the truss type transformer core laminating machine, introduces visual positioning technology and conducts data verification. In the paper, by means of building an actual architecture and combining corresponding control theories and algorithms, the performance, precision, stability and reliability of the system are analyzed and evaluated. The experimental data and analysis results based on practical application scenarios indicate that the system is feasible.

In the context of the global traditional energy crisis and the urgent need to explore green, environmentally friendly, and sustainable new energy, in order to break through the limitations of the understanding of photovoltaic application environment, scope, and carrying capacity, a telescopic and high-efficiency solar roof collector device is developed to address energy challenges and promote energy conservation and emission reduction. This scheme adopts a comparative research and data analysis method to deeply analyze the compatibility between solar energy and automotive characteristics. Through self created design, it integrates efficient photoelectric conversion technology and flexible telescopic structure to ensure maximum collection of solar energy for photoelectric conversion. The experimental results show that the device has high photoelectric conversion efficiency, and numerical examples verify the effectiveness of the proposed scheme and the feasibility of fully utilizing solar energy and extending the service life of automobiles.

Ultra-high voltage AC power system usually uses standard lightning current parameters to calculate external overvoltage, and lightning observation data show that more than 80% of the lightning process is multiple lightning strikes, which is significantly different from the standard recommended waveform. Under the background of frequent multiple lightning accidents in ultra-high voltage AC system, it is urgent to put forward a rigorous and scientific evaluation method of multiple lightning parameters. Therefore, this paper takes a 500kV AC ultra-high voltage transmission system as the object, and proposes a multiple lightning current waveform parameter evaluation method considering the transient characteristics of the line from the extreme lightning conditions and the actual fault recording. The analysis shows that the fault recording inversion method can characterize the real multiple lightning strikes. Extreme multiple lightning strikes method analyzes the lightning current parameters under harsh conditions from the lightning resistance level of the cable. The waveform parameter evaluation method proposed in this paper provides a technical scheme for overvoltage analysis of ultr-high voltage transmission system in lightning-prone areas.

To fully exert the advantages of the convolutional neural network (CNN) in image recognition and classification, a fault diagnosis method for four-quadrant pulse rectifiers based on CNN and Gramian angular difference field (GADF) is proposed. GADF is utilized to transform the one-dimensional time series of rectifier current into a two-dimensional feature map, preserving the temporal dependency of the data and identifying the temporal correlations of the signal over different time intervals. The CNN then extracts and classifies the features of open circuit faults in the rectifier from the generated feature maps. This method is compared with other common fault diagnosis methods. Simulation analysis results indicate that this proposed method achieves higher diagnostic accuracy compared to other fault diagnosis methods.

The grounding wire is an important equipment for ensuring the personal safety of power operators. Traditional grounding wire lacks informationization and intelligent management methods. There is no closed-loop management method for the extraction and return of grounding wire, which can easily lead to misconnection, no connection, and without returning, bringing huge risks to the safe and stable operation of the power grid. This article focuses on the Internet of Things (IoT) and intelligent transformation of grounding wire, grounding wire cabinet, and grounding pile. The design covers the full-process control system architecture covering the “cloud-network-edge-end”, and the full-process control system of grounding wire and intelligent monitoring device are developed. Through the method of edge IoT proxy cross regional collaboration, the consistency of the real-time status of grounding wire, grounding wire cabinet and grounding pile and business data between the security Ⅳ region and the Internet region is achieved. Based on cross regional collaboration of data, cross regional data collection and panoramic monitoring of grounding wire are achieved to ensure accurate grounding connection, improving the safety and work efficiency of on-site operators, and providing guarantees for the safe and stable operation of the power grid.

In order to solve the ground fault in ungrounded systems, this paper applies the differential protection method based on the “external signal generating device and feeder terminal unit” to the external signal ground fault selection technology, proposes differential protection method of ground fault detection criteria and action principles, and achieves segment selection on the basis of ground fault phase selection. Finally, the effectiveness of the method is verified through a case study, and the results show that the proposed fault discrimination method has high accuracy and can minimize the range of ground fault power outages, which can also improve fault handling efficiency and power supply reliability.

The assignment of work orders is an essential part of the power operation and maintenance management system. Timely and accurate assignment methods can effectively improve the efficiency of work order circulation. Based on in-depth analysis of the characteristics of work order management in the field of power operation and maintenance, this article proposes an automatic assignment model for power operation and maintenance work orders based on fit degree. The model adopts criteria importance though intercrieria correlation (CRITIC) weighting method and fuzzy comprehensive evaluation to calculate the compatibility between operation and maintenance personnel and work orders, determine the optimal candidate for work order assignment, and then achieve automatic assignment of work orders. The practical application results show that compared to manual assignment, this automatic assignment model can effectively improve the efficiency and accuracy of work order assignment.