Research On Multi-parameter Detection System For Stored Grain Biosafety Based On TDLAS Technology

Storage is an important link to ensure grain security,and the grain biosafety problem caused by the occurrence and activities of microorganisms and pests in the storage process has attracted widespread attention all over the world.Therefore,a multi-parameter detection system of stored grain biosafety based on tunable semiconductor laser absorption spectroscopy（TDLAS）technology is developed in this paper,which aims to provide an effective tool for on-site rapid detection and analysis of stored grain biosafety.TDLAS technology is a high-resolution and high-sensitivity gas detection technology,which uses the wavelength tuning characteristics of semiconductor lasers to improve the detection accuracy and stability of CO₂ concentration in granaries,and realize the rapid analysis and judgment of biosafety in granaries.Meanwhile,the detection system designed in this paper can also use relevant models and data processing methods to realize the multi-parameter detection of balanced moisture,water activity,absolute water potential and accumulated temperature and accumulated potential in the granary on the basis of temperature and humidity detection in the granary,intelligently judge the biosafety level of grain storage,generate the multi-parameter cloud map of grain storage,and give ventilation guidance suggestions combined with the analysis of water potential map,so as to effectively detect and guide the biosafety status of grain storage,and reduce losses caused by pests and mildew during grain storage.The main contents of this paper are as follows:（1）Overall solution design of a multi-parameter detection system for stored grain biosafety.Through the analysis of the on-site detection requirements of food security,the function and system structure of the detection system are determined;By analyzing the main factors affecting grain storage,the CO₂ concentration,temperature and humidity in the granary are determined as the basic detection parameters,and the multi-parameter detection of equilibrium moisture,water activity,absolute water potential and accumulated temperature potential in the granary is realized by using relevant models and data processing methods;Based on TDLAS theory,a strategy to improve the accuracy and stability of CO₂ concentration detection in granary is proposed.（2）Hardware design of a multi-parameter detection system for stored grain biosafety.In order to realize the detection of multi-parameters in the granary and improve the accuracy and stability of CO₂ concentration detection,the detection system is composed of three parts:hardware circuit design,basic hardware design and system structure layout and design.The hardware circuit mainly includes main control circuit,laser control circuit,analog-to-digital conversion circuit,preamplifier circuit,power circuit and so on.The control circuit takes the STM32H743VIT6 as the core.When MCU receives the detection command sent by the upper computer,it will drive the air pump,and drive the laser to output a stable 2004nm central wavelength for scanning.After CO₂ gas molecules absorb photons,the light intensity decays,and then the photodetector receives the decaying light intensity and converts it into an electrical signal,which is processed by the later stage circuit and transmitted to MCU for concentration inversion.At the same time,the temperature and humidity will be detected by MCU,and finally the detection data will be transmitted to the upper computer.In addition,in order to adapt to the complex working environment of the granary,this paper uses the industrial tablet computer to realize human-computer interaction,and the shape of the detection system adopts the form of suitcase,and 12V lithium battery is selected as the power supply,which effectively improves the flexibility of the detection system.（3）Software design of a multi-parameter detection system for stored grain biosafety.The upper computer program is designed with Lab VIEW software.Its functions mainly include data storage,remote transmission,grain storage biosafety judgment,multi-parameter cloud map and water potential ventilation.After completing the multi-parameter detection by using the water potential model,CAE and other models and algorithms,the upper computer processes and analyzes the data,and intelligently judges the biological safety of grain storage through the judgment model.Combined with graphical analysis,the system can judge and predict the overall situation of the granary more intuitively.The lower computer program design adopts the modular idea,which is mainly divided into system main program,serial communication subroutine,temperature and humidity acquisition subroutine,concentration inversion subroutine,laser control subroutine and so on.The programs of each part of the software system cooperate with each other to effectively detect and judge the biosafety status of stored grain.（4）Application and verification of a multi-parameter detection system for stored grain biosafety.After completing the calibration experiment,the performance test experiment and application experiment of the detection system are designed respectively.The performance test results show that the detection system can work stably for a long time,and the repeatability of CO₂ concentration detection is 0.4%,the detection accuracy is 5ppm,and the detection range is0～10000ppm.Meanwhile,the parallel control group experiment and the experiment of Longjia direct warehouse of China grain storage are designed respectively,which is to systematically verify the working performance,practicability of the detection system and expand its application scope.Through the analysis of the experimental data,it is concluded that each detection parameter shows good discrimination for corn under different storage conditions,especially with high sensitivity to CO₂ concentration;Secondly,the nonlinear function model between corn moisture content,grain average temperature,storage time and CO₂ concentration was established according to the experimental results,and the fitting index R² was 0.82;In the real warehouse experiment,the detection system can accurately and quickly detect and judge the biological safety status of the stored grain according to the warehousing time,ventilation time and the impact of the environment on the stored grain.Combined with the functions of cloud map analysis and other functions,the detection system can better reflect the biological safety status of the granary.In the meantime,the real warehouse experiment also verifies the practicability of the detection system and the friendliness of human-computer interaction function.