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Design of a peanut moisture detector based on STM32and MATLAB

机译:基于STM32和MATLAB的花生水分检测仪的设计。

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The measurement accuracy and repetition rate of the existing peanut moisture detector are poor. To solve this problem, this paper designs a capacitive peanut moisture detector based on the capacitance method. Firstly, the structure of coaxial cylindrical capacitive moisture sensor is optimized. STM32 chip microcomputer is used in the main control chip, and the change in capacitance is transformed to change in frequency by capacitance detection circuit. The temperature and quality of peanut kernel are measured by DS18B20 temperature sensor and weighing sensor respectively. The influence of particle size, moisture content, temperature and volume density on the output differential frequency of capacitance sensor are studied by using the differential frequency method. In the range of moisture content of 4.3%-19.1% and temperature of 10?°C-40?°C, a mathematical model for the relationship among moisture content, temperature, and differential frequency is established. The prediction test of peanut kernela??s moisture content shows that the measurement error of moisture content is within ?±0.5%, indicating that the instrument has high measurement accuracy and repeatability when it is used to detect the moisture content of peanut kernels, and has a wide application prospect.
机译:现有的花生水分检测仪的测量精度和重复率很差。针对这一问题,本文设计了一种基于电容法的电容式花生水分检测仪。首先,对同轴圆柱电容式湿度传感器的结构进行了优化。主控芯片采用STM32单片机,电容检测电路将电容变化转换为频率变化。 DS18B20温度传感器和称重传感器分别测量花生仁的温度和质量。采用差分频率法研究了粒径,水分,温度和体积密度对电容传感器输出差分频率的影响。在水分含量为4.3%-19.1%且温度为10°C至40°C的范围内,建立了水分含量,温度和差分频率之间关系的数学模型。花生仁水分含量的预测试验表明,该水分含量的测量误差在±0.5%以内,表明该仪器用于检测花生仁的水分含量具有较高的测量精度和重复性。具有广阔的应用前景。

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