Energy Carbon Emission Detection Cloud Platform Based on Data Mining Technology

In industrial production, agricultural production, scientific experiments and daily life, the measurement of gas concentration is extremely common and extremely important, and its measurement and control are very important. The purpose of this paper is to study the design and implementation of a cloud platform for energy carbon emission detection based on data mining technology. Some theoretical analysis and experimental research are carried out on CO2 concentration inversion algorithm, spectral data optimization processing method, actual influencing factors and temperature correction method. In the platform design, the overall framework, technical framework and modules of data services are designed. Then the energy monitoring analysis and energy management modules are designed in detail, and the database is designed. In the platform test, by simulating the changes of power plant exhaust gas temperature and CO2 concentration, the influence of temperature changes and the application of tunable semiconductor laser absorption spectroscopy in the field of detection are studied. The results confirmed the applicability of the energy carbon emission detection cloud platform in the field of carbon emission detection of coal-fired power plants.