Description
Application
Spray Drying Granulation
Features of Pressure Spray Dryer
Parameters
Model
YPG-25
YPG-50
YPG-100
YPG-150
YPG-200
YPG-300
YPGI-500
YPGI-1000
Evaporated Amount of Moisture (kg/h)
25
50
100
150
200
300
500
1000
Pump Pressure (mpa)
The
pressure is generally between 1 and 3 mpa if the materials are under 0.65 to
5 mpa.
Power (kw)
0.35
4
7.5
11
15
22
30
55
Inlet Air Temperature (℃)
150
to 350
Diameter of Tower Body (mm)
1300
1600
2000
2400
2800
3200
3800
4600
Height of Tower (mm)
7800
8900
11500
13500
14800
15400
18800
22500
As a professional spray drying machine manufacturer and supplier in China, we have obtained the ISO9001 international quality system certificate. In addition to pressure spray dryer, we supply Vacuum Drying Machine, centrifugal spray dryer, belt dryer, flash drying machine, drum dryer and other drying equipment to meet the needs of customers. Yutong consistently commits to provide users with satisfied solutions, high quality products, perfect after-sale service, so as to acquire the satisfaction of each customer.
YPG Pressure Spray Drier Machine Instant Tea Coffee Spray Drying Machine, YPG Vitamin Granulation Dryer, Detergent Pressure Spray Dryer Machine, Tiles Ceramic Spray Drier, Coconut Spray Dryer Jiangsu Yutong Drying Engineering Co.,Ltd , http://www.ytdryer.com
The traditional control system design is based on the known mathematical model of the system. Therefore, the quality of the control system has a lot to do with the accuracy of the mathematical model. However, the actual system is very different and complex, so it is difficult to find a suitable description model. It is even more difficult for nonlinear systems, and sometimes it can't even be done. The neural network is different for the control system design. Instead of the mathematical model of the controlled object, it can train the neural network online or offline, and then use the training results to design. Because neural networks have strong adaptability, parallel processing capability and intrinsic nonlinearity, controllers using neural network design will have stronger adaptability, better real-time performance and robustness for nonlinear and uncertain systems. Sex. There are many design methods for control systems based on neural networks, but no perfect theoretical system and systematic design methods have been formed yet. The proposed neural network controllers mainly include neural network PID control, neural network predictive control, and neural network. Mode control, neural network fuzzy control, etc.
Induction motors are typical multivariable, nonlinear systems, and with the addition of frequency converters, the entire system is more complex. In this paper, the induction motor variable frequency speed control system is selected as the control object, and its mathematical model is reversible. The neural network is used to construct the inverse controller to control the induction motor variable frequency speed control system. The neural network inverse controller combines the inverse system method with the neural network. Liu Guohai, born in 1964, Ph.D., professor and associate dean of the School of Electrical and Information Engineering of Jiangsu University, whose research direction is motor control and complex system control.
The BP network is used to approximate the a-order inverse system of the object, and then connected with the object to form a composite pseudo-linear system, and then the design method of the existing linear system is used to design the control system. The paper uses the neural network inverse system method to carry out the no-load/full load start test, sudden/decrement load test and tracking test verification of the actual induction motor variable frequency speed control system. The first system is formed into a first-order pseudo-linear system before the inverse system is connected in series with the original system, so that the entire composite system is converted into a type 1 pseudo-linear single-input single-output system.
The simulation results of the simulation curve of the unit under variable working conditions show that the control system effectively solves the impact of boiler nonlinearity, large time lag and load disturbance on the unit operation. Not only under normal load stability, the main steam pressure can be kept quite stable, and in the case of peaking of the unit and large change of combustion rate, the control unit can quickly track the load, effectively improving the control quality of the system and satisfying the actual situation. The control requirements have important practical significance for improving the peak shaving performance of the unit.
4 Conclusions The prominent features of cluster adaptive fuzzy control based on neural network prediction model designed in this paper are as follows: () The neural network is used to predict the system, which provides guarantee for the precise control of nonlinear large time-delay systems.
(2) While using fuzzy control to implement fuzzy rules based on expert control strategies and experience, cluster adaptive control is used to compensate for the incompatibility and incompleteness of fuzzy rules. The control method is concise, flexible and fast.
The simulation shows that the control has strong robustness, real-time and anti-interference ability, and even the peak-shaving unit can maintain good control performance and operation effect under variable working conditions (large range of variable load).
YPG pressure spray dryers utilize spray nozzle to atomize the materials to tiny liquid drops, which drop in parallel with the hot air at the top of the tower to finish drying, and transform the materials into powdery or granular products. This pressure spray drying machine is very suitable for drying thermosensitive materials.
YPG pressure spray dryer is broadly used in food, pharmaceutical, chemical, dye, ceramics, biological, pesticide, plastics and other industries. The following are some specific applications:
Chemical industry: organic catalyst, resin, synthetic detergent, oil, thiamine, dye intermediate, white carbon black, graphite and ammonium phosphate.
Food: amino acid, spices, protein, starch, dairy products, coffee extracts, fish meal and so on
Pharmaceuticals: Chinese patent medicine, pesticide, antibiotic and dissolved medicines
Ceramics: magnesium oxide, porcelain clay, all kinds of metal oxide, dolomite, etc.
Spray Granulation
Fertilizers, alumina, ceramic powder, heavy metal, granulous detergent and Chinese patent drug
Spray Cooling Granulation
Aliphatic acid, paraffin, olein and oil
In addition, our spray drying machine can also be used in the fields of spray crystallization, spray concentration and spray reaction.
1.The characteristics of this spray drying machine include fast drying speed, high dust collection rate and energy conservation.
2.The dried products are in the shape of spherical particles, with uniform particle size, good fluidity and solubility, high purity and superior quality.
3.With wide range of applications, this pressure spray dryer can not only implement hot air drying and granulation, but also conduct cooling granulation, spray crystallization and spray reaction.
4.This spray drying machine is easy to operate and maintain. It is also easy to realize automatic operation.
Flow Chart of Pressure Spray Dryer Machine
