Method and system for analyzing health degree of equipment running state based on data driving

Abstract

The invention discloses a method and a system for analyzing the health degree of the equipment running state based on data driving. The method comprises the following steps: S1, monitoring equipment in real time, determining suitable equipment according to a PHM principle P-F interval curve, and acquiring suitable equipment measuring point data; S2, processing the acquired measuring point data; S3, establishing an equipment data association model, and establishing an equipment running framework model according to a data characteristic model in the equipment data association model; S4, monitoring according to the equipment running framework model, and performing early warning for a monitored abnormality or fault; and S5, diagnosing and processing according to the early warning result. The method and the system have the beneficial effects that early warning about the abnormality or fault of the equipment can be realized; the time and location of a fault being about to occur are predicted; the equipment maintenance and repair can be carried out pertinently; and the requirement of data integration at the industrial enterprise group level can be met.

Description

technical field [0001] The invention relates to the technical field of boiler production, in particular to a data-driven health analysis method and system for equipment operation status. Background technique [0002] At present, relatively mature equipment anomaly monitoring methods based on big data mainly include mechanism-based models, knowledge-based methods and simple data-based analysis models, among which, [0003] 1) Mechanism-based model: This method is closely combined with control theory, and a mathematical model is established through the operation mechanism of the equipment to predict the system output, and compare it with the actual measurement value to obtain the residual; analyze the residual to determine whether the process occurs Faults, to further identify the types of faults, among them, advantages: combined with physical understanding and monitoring system, fault warning is carried out by analyzing residual errors, which is easy to understand; disadvanta...

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Problems solved by technology

[0007] Aiming at the above-mentioned technical problems in the related art, the present invention proposes a data-driven equipment operation status health analysis method and system, which can solve the problem of untimely and unpredictable abnormalities or fault warnings of industrial enterprises that operate repeatedly or periodically. The time and location of the upcoming failure, the difficulty of targeted equipment maintenance and repair, and the technical problems that cannot meet the data integration requirements of the industrial enterprise group level

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