Multi-source data integration method and device based on fan data

Abstract

Provided are a multi-source data integration method and device based on fan data. The method includes: designing the table structure of the fan data fact table by analyzing the fan business data and the fan data of each data source; extracting the fan data of each data source into the designed fan data fact table, and extracting the fan data. The data identification in the data identification is converted into a unified data identification; data cleaning is performed on the data of each data source after conversion; data fusion is performed on the data of each data source after cleaning, and a real-time fan data table is generated.

Description

Technical field [0001] The invention involves the field of wind power technology, and more specifically, it involves a multi -source data integration method and device based on fan data. Background technique [0002] In recent years, with the booming development of the wind power industry, the wind power generation units have a large scale. With the development of society and the continuous expansion of the market, in order to regulate the management behavior and customer requirements of the enterprise, it has been established Individual and dimension management system. The implementation of multiple operation and maintenance management systems is conducive to the needs of enterprises to meet different market changes. However, due to different construction periods, different development departments, different development departments, different use equipment, different technological development stages, and capacity levels, data storage management is extremely decentralized, result...

AI Technical Summary

Problems solved by technology

However, due to the different construction periods, different development departments, different equipment used, different technological development stages and different ability levels of rich data resources, data storage management is extremely scattered, resulting in excessive data redundancy and data inconsistency, making data Resources are difficult to query and access, and the management cannot obtain effective decision-making data support

Often managers need to access many different systems to understand the information of different departments under their jurisdiction, and the data cannot be directly compared and analyzed

[0003] The cloud and client systems of the operation and maintenance management system have low integration, poor interconnection, scattered information management, and large gaps in data integrity, accuracy, and timeliness, forming many information islands, lacking shared, networked Wind turbine data system with high availability

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