Design Of Multi-component Gas Detection Systems For Industrial Production Processes

As a result of the rapid growth of our economy and the steady acceleration of industrialization,unsafe industrial production mishaps are prevalent.Monitoring gas concentrations in industrial processes in a timely and efficient manner is essential for the safety and profitability of industrial production.Complex toxic and hazardous gases in the industrial sector must be identified qualitatively and quantitatively.Conventional gas concentration detection methods are mostly based on chemical detection techniques,but require a sample of the gas to be tested for measurement.Even though the principle is simple,easy to operate,and inexpensive,it is susceptible to cross-interference from other gases,and the parameters of measurement accuracy,measurement range,and response time no longer meet the strategic requirements of modern mass production for the industrial and technological revolution.Thus,the purpose of this research is to detect multi-component gas concentrations in industrial processes.Based on the above information,the multi-component gas detection system of industrial production processes can be used for real-time detection and analysis of CO,CO₂,O₂,and H₂gas concentrations.Comparatively,the non-dispersive infrared detection principle was used to detect the concentration of CO and CO₂gas,whilst the paramagnetic method was utilized to measure the concentration of O₂and the thermal conductivity detection principle was used to measure the concentration of H₂.Non-dispersive infrared detection is based primarily on the properties of gas selective absorption of infrared radiation at various wavelengths.The paramagnetic detection principle primarily use oxygen’s paramagnetic properties to assess the gas concentration.In addition,the thermal conductivity measuring method essentially employs the properties of several gases with varying heat conductivity coefficients.The system consists of a gas acquisition and processing component,a circuit control hardware component,and a program software component.The majority of the hardware circuit is comprised of a central processing unit,a gas concentration detection unit,a pressure compensation detection unit,a constant temperature compensation detection unit,a human-computer interface unit,and an output unit.To ensure the accuracy of gas concentration detection of each component during software implementation,IIR digital filtering algorithm and data calibration algorithm are used to collect and process gas concentration data,and are complemented by incremental PID temperature control algorithm to achieve accurate control of the detection environment temperature.A natural selection optimization and adaptive mutation particle swarm optimization support vector machine parameter model is proposed to solve the cross-interference problem of CO and CO₂in the detection process.The comparison with the particle swarm optimization support vector machine parameter shows that the improved algorithm has better performance,which can effectively reduce the problem of easy to reach the local minimum in particle swarm,improve particle performance and accelerate the convergence rate.To achieve accurate and rapid classification regression prediction of CO and CO₂mixed gases.In the industrial production process,a multi-component gas detection system can automatically and precisely complete the detection and analysis of mixed gas,thereby significantly enhancing the work efficiency and ensuring the safety of industrial production.