Multi-parameter air quality monitoring system

Abstract

The invention provides a multi-parameter air quality monitoring system. The system is characterized in that a to-be-detected air sample extracted by a sampling pump passes through a constant temperature device, gas concentrations of an SO2 sensor, an NO2 sensor, an O3 sensor and a CO sensor are respectively measured, and the gas concentrations are converted into corresponding digital signals through a conditioning circuit and then are transmitted to a system control module; a to-be-measured air sample collected by the sampling head passes through the heat tracing pipeline, the particulate matter sensor measures the particulate matter concentration, and the measurement result is directly transmitted to the system control module through the data bus; the system control module is used for carrying out concentration prediction on the received digital signal by adopting an established particulate matter concentration prediction model and an established SO2, NO2, CO and O3 gas concentration prediction model to obtain a detection result, and then transmitting the detection result to a local display module, or directly uploading local data to a corresponding platform through a transmission module to carry out data secondary processing and display; and the heat tracing control module and the constant temperature control module are controlled.

Description

technical field [0001] The invention belongs to the field of air quality monitoring, in particular to a multi-parameter air quality monitoring system. Background technique [0002] With the continuous development of my country's national economy and the acceleration of urbanization, a large amount of industrial waste gas, dust from construction sites and pollutants from fossil fuel combustion are discharged into the atmosphere, causing serious air pollution and restricting the sustainable green development of the economy. In recent years, particle pollution and ozone pollution have become one of the key factors affecting the air quality of cities in my country. As air pollution prevention and control work gradually extends to fine scales such as districts, counties, and parks, the demand for grid-based high-density monitoring is gradually increasing. Compared with standard instrument monitoring systems, the low-cost multi-parameter air quality monitoring system has the advan...

AI Technical Summary

Problems solved by technology

At present, the commonly used nonlinear polynomial model compensation technology only studies a single parameter and is not directly applied to multi-parameter monitoring systems; other mainstream modeling methods include neural network methods, such as BP neural network and fuzzy neural network. Good effect, but there are still disadvantages such as slow learning speed, easy to fall into local optimal solution and complicated parameter adjustment in different occasions

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