Intelligent Processing and Analysis Based on Unstructured Data in the Power Industry

In today’s data-driven power industry, the processing and analysis of unstructured data has become a key technology, including but not limited to maintenance logs, equipment images, and real-time monitoring data streams. This article intends to study a new type of deep learning based unstructured data intelligent processing method, which combines natural language processing and machine vision to achieve intelligent processing of unstructured data. On this basis, this article proposes a new time series analysis method to process and analyze data collected by multiple sensors. In order to verify the effectiveness of the proposed framework, this study conducted application testing in multiple actual power system cases. The response time remains within a short range (1.1 seconds to 1.5 seconds) in various scenarios, indicating that the model performs stably in responding quickly. Research has shown that through intelligent processing and analysis of unstructured data, the power industry can achieve higher levels of automation and informatization, which is of great significance for improving the stability and response speed of the power grid. This study not only expands the theory and practice of unstructured data processing, but also provides a practical and feasible intelligent solution for the power industry.