Measurement Of Moisture Content And Flow Characteristics In The Fluidized Bed Using Electrostatic Sensor Arrays And Ultrasonic Sensors

Fluidized bed dryers have been widely applied to dry raw materials due to the advantages of high heat and mass transfer rate and the ability in dealing with a large number of particles.They are the common equipment in the food,pharmaceutical and chemical industries.In order to keep the drying process efficient,economical and safe,it is essential to monitor the moisture content and flow characteristics in the fluidized bed.Particle moisture content directly affects the quality of the product.The drying process without monitoring will cause energy waste and low quality products.In this paper,based on the principles of electrostatic and ultrasonic methods,theoretical and experimental studies on the measurement of particle moisture content and particle flow parameters using a set of arc-shaped electrostatic sensor arrays and a pair of ultrasonic sensors is carried out,during which experimental results have been obtained.The main work of this paper include the following aspects:1.In order to measure the characteristics of the fluidized bed dryer,a laboratory scale bubbling fluidized bed dryer is set up.A series of drying experiments are performed with the purpose of verifying the measurement performance of an arc-shaped electrostatic sensor arrays for the measurement of the particle moisture and flow parameters.The electrostatic sensor arrays are installed on the outer surface of the plexiglass bed wall.The cross-correlation velocity of the particles in the fluidized bed is obtained by using the upstream and downstream electrostatic signals,which indicates the flow behavior of the particles in the fluidized bed.The root mean square value of the electrostatic signal is used to represent the amplitude of signal fluctuation.A model between the root mean square value of the electrostatic signal,particle moisture content and cross-correlation velocity is established.It is found from the experimental results that the particle moisture content in the fluidized bed dryer can be predicted by the electrostatic sensors using the proposed model.The maximum error of the predicted results is less than 15%.2.A NARX neural network is applied for making full use of the electrostatic signals.A more accuracy nonlinear model is established and the measurement error is reduced.Firstly,from the parameters of the six time domain characteristics and three frequency domain characteristics of the electrostatic signal and the temperature and humidity of the air at the outlet of fluidized bed,five inputs are selected using the parameter selection method.Then the model delay order is set to 1 and the number of the elements in the hidden layer is set to 10.7 sets of experimental data are selected as training data,and the remaining 2 sets are used to verify the accuracy of the model.The results show that the model can effectively improve the accuracy of moisture content prediction and the maximum error of the predicted results is less than 10%.3.The ultrasonic sensors are used to measure the air humidity at the outlet of the fluidized bed.Firstly,the system delay and compensation coefficient of sound path in the ultrasonic sensor system are calibrated in a constant temperature and humidity chamber.During the investigation of sound velocity measurement algorithm,it is found that the result from auto-correlation method is closer to the theoretical value than that from threshold method.Then the ultrasonic sensors are installed at the outlet of the fluidized bed to measure the outlet air humidity during the drying process.The results show that the ultrasonic sensor can be used to measure the outlet air humidity.However,further research is needed at lower temperature.Besides,the humidity field reconstruction of the ultrasonic array was simulated using Matlab.The feasibility of reconstructing the air humidity field using ultrasonic sensor array at the outlet of the fluidized bed is verified.