Research On Air Quality Detection Technology In Aircraft Cabin Environment

The aircraft cabin environment is special,the space is small,the personnel is dense,and the tight seal.During the flight,the crew’s metabolism,equipment operation,material release and introduction from the engine make the air parameters in the cabin very complex,containing a large number of pollutants,which directly affect the air quality in the cabin,and thus pose a great threat to people’s physical and mental health,and even lead to flight accidents.How to better control and improve the cabin air quality,it is necessary to conduct real-time and effective detection of the concentration of each parameter in the cabin,get accurate detection results,and facilitate the later adoption of corresponding measures,which makes the air quality detection and research work become crucial.In particular,the rapidity,accuracy and comprehensiveness of the detection are of great significance to the effective evaluation of air quality and the establishment of the standard system.The main work and results are as follows:1.In order to solve the problem of low detection efficiency and few detection parameters,a multi-sensor composite cabin air quality detection system is designed for integrated optimization of various sensors,which can realize real-time online detection of 7 parameters such as HCHO,CO,CO2,NO2,O3,TVOC and PM2.5,and greatly improve the detection efficiency.2.In order to solve the cabin larger range of pressure change in air quality test results the problem of inaccurate,the special experimental system is designed,a large number positive and negative pressure characteristics of typical experimental research are selected and carried out on HCHO,CO,CO2 and NO2,four typical gas sensors for cabin air quality detection,to collect experimental data and draw characteristic change curves of each gas,and the experiment results are analyzed,it is concluded that the change of air pressure can cause different degree of sensor,the influence of lead to larger test error.3.In order to solve the problem of sensor detection error caused by the change of cabin air pressure,RBF neural network is used to correct and compensate the air pressure,a block diagram of the principle of air pressure error is designed,a three-layer network model is established,and the network parameters are set by MATLAB.Through the algorithm test,the experimental results show that the algorithm can effectively reduce the impact of air pressure on the sensor detection results,the maximum relative error is controlled within12.68%,the compensation effect is better,it has a certain reference value for aircraft cockpit air quality evaluation.4.In order to evaluate the cabin air quality comprehensively and systematically,the fuzzy comprehensive evaluation method is proposed.By using the design of the composite detection system,data acquisition more groups of detection parameters,constitute the evaluation factor set,and then divide the evaluation level and establish the evaluation model,finally using the fuzzy comprehensive evaluation method,established the fine difference four type of subordinate degree function,calculated judgment matrix and the evaluation factors weight proportion and get the final evaluation results,the result shows that evaluation is good,this method can be applied to aircraft cabin air quality evaluation,to the establishment of a national standard evaluation system to provide certain reference basis.