Fuel cell data analysis system based on data relevance and electronic equipment

Abstract

The invention discloses a fuel cell data analysis system based on data relevance and electronic equipment, and the system comprises a fuel cell big data storage module, an associated information storage module and a data analysis module, the data storage module is used for storing part parameters, research and development data, production data and real-time operation data of the fuel cell; the associated information storage module is used for generating and storing associated information among multiple layers of target data corresponding to the fuel cell according to the data stored by the fuel cell big data storage module, and storing a theoretical model of the fuel cell; and the data analysis module is used for constructing a plurality of neural network models according to the associated information and the theoretical model, and performing data analysis and fault prediction on the fuel cell through the plurality of neural network models. According to the system, the association rules among all levels of data of the fuel cell are defined, corresponding data can be conveniently extracted according to data analysis requirements, and the efficiency and accuracy of data analysis are improved.

Description

technical field [0001] The present application relates to the field of fuel cell technology, in particular to a data correlation-based fuel cell data analysis system and electronic equipment. Background technique [0002] A proton exchange membrane fuel cell (PEMFC) is a device that directly converts the chemical energy of hydrogen fuel into electrical energy. At present, proton exchange membrane fuel cells have been increasingly widely used in many fields such as transportation, distributed power generation and industrial production due to their advantages such as high efficiency, high power density, environmental friendliness, light weight and abundant resources. One of the new power generation devices in the foreground. In the field of fuel cell materials, scientific research on predicting material performance through machine learning has shown great potential, and in order to improve the competitiveness of fuel cells, the use of big data analysis for material screening,...

AI Technical Summary

Problems solved by technology

The system defines the association rules between data at all levels of fuel cells, which facilitates the extraction of corresponding data according to data analysis requirements, improves the efficiency and accuracy of data analysis, and solves the problem of data association items in the application process of big data analysis in the field of fuel cells. unclear question

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