Application Research of Digital Intelligence Technology in Mining Electric Power Equipment Fault Cases: Taking Text Mining Technology as an Example

By using structured, semi-structured, and unstructured data, combined with related algorithms for knowledge extraction, it is one of the current development directions of electric power technology to build a domain knowledge graph. The purpose of this paper is to study entity relation extraction and auxiliary disposal of power equipment fault defect text based on knowledge graph. The construction method of knowledge graph is studied, and the method of constructing a power equipment diagnosis system is used to assist in the disposal of power equipment faults, and the function of the power equipment diagnosis system is analyzed. The system defines 10 entity relationships according to the output of the power equipment fault entity. A method for derivation of power equipment fault entity relationship based on syntactic and semantic features is proposed. Finally, the extraction results of 10 kinds of entity relationships meet the actual use requirements.

Entity relationship extraction and auxiliary disposal of power equipment fault defect text based on knowledge graph

In the current temperature measurement methods of various electrical equipment, such as distributed optical fiber temperature measurement, infrared thermal imager, temperature display wax temperature measurement technology, active wireless temperature measurement technology, etc., these technologies have corresponding bottlenecks restricting them development of. With the development and application of flexible temperature sensors, this paper proposes the application of flexible temperature sensors in the temperature measurement of cable intermediate joints. Due to the characteristics of the flexible sensor itself, it has many advantages in the temperature measurement of cable intermediate joints, such as easy installation and reliable performance. Compared with traditional distributed temperature sensors, the temperature measurement is more accurate and reliable, but considering the complexity and diversity of the environment in which the power grid is located, the universality of flexible temperature sensors needs to be improved in the future.

Application of temperature measurement in cable intermediate joint based on flexible sensor

In order to obtain better monitoring results of the operation status of active distribution networks in mountainous areas, a real-time monitoring method for the operation status of active distribution networks in mountainous areas based on digital twins is designed and proposed in this study. This method first completes the design of the digital twin architecture of the active distribution network from the aspects of physical entities, virtual entities, and data. Then, based on the wavelet coefficient threshold denoising method, signal denoising processing is completed. Finally, combined with attention mechanism, a real-time monitoring model for the operation status of the active distribution network is constructed based on Convolutional Neural Network (CNN) and Deep Bidirectional Gated Recurrent Unit (Bi GRU). The experimental results show that based on the evaluation of the twin device model, it can be concluded that when using the method proposed in this paper, the weighted average accuracy is about 97.80%, and the monitoring speed is about 0.48s. Compared with the comparison methods, both methods have improved performance and the application effect is better.

Real-time monitoring method of mountain active distribution network based on digital twin

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Entity relationship extraction and auxiliary disposal of power equipment fault defect text based on knowledge graph

Application of temperature measurement in cable intermediate joint based on flexible sensor

Real-time monitoring method of mountain active distribution network based on digital twin