Abstract
A miniaturised bionic electronic nose system was developed to solve the problems of expensive equipment and long response time for soil pesticide residue detection. The structure of the bionic electronic nasal cavity is designed based on the spatial structure and olfactory principle of the sturgeon nasal cavity. Through experimental study, the structure of the nasal cavity of the sturgeon was extracted and analyzed. The 3D model of the bionic electronic nasal cavity was constructed and verified by Computational Fluid Dynamics (CFD) simulation. The results show that the gas flow distribution in the bionic chamber is more uniform than that in the ordinary chamber. The airflow velocity near the sensor in the bionic chamber is lower than in the ordinary chamber. The eddy current intensity near the bionic chamber sensor is 2.29 times that of the ordinary chamber, further increasing the contact intensity between odor molecules and the sensor surface and shortening the response time. The 10-fold cross-validation method of K-Nearest Neighbor (K-NN), Random Forest (RF) and Support Vector Machine (SVM) was used to compare the recognition performance of the bionic electronic nasal cavity with that of the ordinary electronic nasal cavity. The results showed that, when the bionic electronic nose detection system identified the concentration of pesticide residues in soil, the recognition rate of the above three recognition algorithms reached 97.3%, significantly higher than that of the comparison chamber. The bionic chamber electronic nose system can improve the detection performance of electronic noses and has a good application prospect in soil pesticide residue detection.