A method, system and device for industrial data processing

Abstract

The present invention provides an industrial data processing method, system and equipment, which collect industrial data through numbered collectors; perform cluster analysis on industrial data, identify abnormal data in industrial data offline, and obtain normal data samples and abnormal data samples; Perform data sample abnormality analysis on normal data samples and abnormal data samples to obtain abnormal analysis results of data samples; perform abnormal analysis on collectors that collect industrial data according to abnormal analysis results of data samples, and obtain abnormal analysis results of collectors; based on abnormal analysis of collectors As a result, a data collection quality report was generated, and a data collection quality warning was carried out according to the data collection quality report. The invention solves the technical problems of narrow data optimization range and lack of collection quality analysis and early warning in the prior art. Moreover, the present invention also utilizes the abnormal analysis of data to realize the evaluation of collection quality, and then performs instant and periodic early warning for the debugging of the collector.

Description

technical field [0001] The invention relates to the technical field of intelligent manufacturing, in particular to an industrial data processing method, system and equipment. Background technique [0002] As the application of data mining technology in industrial production becomes more and more mature, a large number of data that can express the state of industrial production and reflect the quality of production are widely collected. The collection of a large amount of industrial data has laid an important foundation for data-driven artificial intelligence technology to play a role in industrial production. Under the current production requirements of industrial efficiency and quality, how to check abnormal data of industrial data, improve data credibility, and optimize data classification according to different needs, improve faster follow-up project implementation efficiency, and data collection Quality evaluation and early warning have become the core issues for indust...

AI Technical Summary

Problems solved by technology

[0005] First, in different application objects and application scenarios, the characteristics of required data are different. Specific problems have specific data optimization requirements. Development under customized requirements tends to ignore the invisible logical relationship between data under specific requirements. The constructed algorithm model cannot fully meet the requirements

[0006] Second, the quality of data collection will directly affect the next step of data analysis, processing, and application. However, the existing technical solutions do not analyze, warn and guide the quality of data collection.

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