Establish unified data resource pool
Use distributed storage technology to establish a unified data resource pool that expands data storage capacity to PB level and stores extensive data from production management systems, online monitoring systems of power transmission and transformation, dispatch management systems, and weather forecasting systems. Also provide algorithms for data governance and cleansing, enabling data preprocessing and unified storage.
Build transformer fault library
Build a transformer fault library from years of production data of TBEA. Provide multi-dimensional analyses of fault data, and prior association rules and knowledge about fault prediction and diagnosis of transformers, monetizing the value of professional knowledge and data.
Visualize transformer health status
Build a data portal for the transformer intelligent O&M system, provide visualized analyses of industrial big data to showcase the operational status and health indicators of transformers. Develop functions of fault querying, health assessment, and lifespan prediction, break down barriers of information sharing throughout the transformer lifecycle, and provide a basis for O&M and repair decisions.
Analyze industrial big data intelligently
Provide accurate and efficient industrial big data compute and analysis capabilities, and build algorithm libraries incl. k-means clustering, Apriori association, Naive Bayes, and multivariate linear regression. Offer diagnostic algorithms based on the fault library, case matching, and algorithm validation frameworks, and combine transformer industry knowledge, such as DGA data and oil chromatography, to develop transformer health and lifespan prediction models so as to accurately monitor and analyze transformer health status.
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