3 results about "Moisture ratio" patented technology

1. The name of the design product: detector. 2. The use of the design product: the design product is used for measuring moisture, solid content, temperature and humidity, water activity, dew point temperature, moisture ratio, isothermal adsorption and desorption in any substance. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view.

The application discloses a relative humidity self-adaptive control method and system for hot air drying of fruits and vegetables; the method realizes real-time monitoring of hot air temperature, material surface temperature and material weight loss by arranging multi-modal sensors in a drying cavity; a partial differential equation of moisture diffusion in the thickness direction of the material is taken as a prediction model, and an online weighing signal is taken as an observation quantity, so that the water content distribution of each layer inside the material and the surface moisture gradient are estimated in real time through an extended Kalman filter; in the falling rate drying period, dimensionless moisture ratio and surface moisture gradient are taken as double variables to dynamically generate a relative humidity reference trajectory, and three actuators, i.e., heating power, circulating fan speed and exhaust air valve, are coordinately adjusted to realize precise tracking control of the relative humidity in the cavity; the application can significantly reduce the surface crust phenomenon in the hot air drying process, improve the product quality uniformity of drying, and is suitable for industrialized drying production of apple, carrot, potato and other sliced fruits and vegetables.

The invention discloses a multi-temperature-zone energy-saving control method based on reinforcement learning, and relates to the technical field of automatic control, and the method comprises four steps of clothes state sensing and modeling, multi-temperature-zone adaptive control, process optimization and learning, and later evaluation and learning, and comprises the steps of collecting weight, moisture distribution, surface temperature and material data through multiple sensors; calculating a moisture ratio, drawing a thermodynamic diagram and identifying a high-humidity region; dividing a plurality of independent temperature zones, setting a temperature gradient based on material and moisture distribution, and dynamically adjusting power; energy consumption is monitored in real time, an energy efficiency ratio optimization strategy is calculated, and judgment is completed through the moisture proportion, the weight change rate and the safe temperature; performance is improved through comprehensive scoring, reinforcement learning and knowledge base updating. Through the intelligent control technology, accurate control over the drying process is achieved, the self-learning ability is achieved, the energy utilization efficiency is improved, and on the premise that the drying quality is guaranteed, remarkable economic benefits and environmental benefits are brought to users.