Industrial data anomaly attribution method, apparatus, device, storage medium, and product

Abstract

The application discloses an industrial data anomaly attribution method and device, equipment, a storage medium and a product, which are applied to a smart power plant data platform, relate to the technical field of anomaly detection, and the method comprises the following steps: acquiring multiple-source industrial data in real time; performing standardization processing on the multiple-source industrial data to generate standardized data streams in a unified format; performing anomaly detection on the standardized data by using a pre-trained ensemble learning model, and identifying an abnormal mode in the data; in response to the detection of the abnormal mode, performing multi-dimensional attribution analysis on the abnormal mode based on an association rule constructed based on a data theme and a data mart, and determining a root cause of the anomaly. Through progressive processing of data integration, intelligent detection and business attribution, the application realizes a complete closed loop from data perception to intelligent decision-making, and converts massive data into high-value decision-making information directly driving business optimization.

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