A cloud-controlled air source heat pump agricultural product drying system

Abstract

The present invention discloses a cloud-controlled air source heat pump agricultural product drying system, which relates to the field of agricultural processing equipment. The current air source heat pump agricultural product drying system still requires manual setting of operating parameters and manual on-site inspection of operating status in places where multiple systems work simultaneously, and the air source heat pump will not automatically evaluate energy efficiency. The present invention includes a drying room, an air source heat pump dryer, and a centralized control system. The drying room includes a fresh air valve, a return air valve, a condenser, and an agricultural product drying area. The centralized control system includes a temperature and humidity sensor array, a vortex flowmeter, a high-temperature mass sensor, an intelligent circuit breaker, a heat pump field controller, a communication module, cloud application software and database, a mobile terminal and application software. The heat pump field controller is built-in with a fuzzy PID controller that automatically controls the temperature and humidity curve in the drying room and has a two-level energy efficiency evaluation capability, which can eliminate the need for on-site manual modification of operating parameters and inspection work, achieve energy efficiency evaluation, and provide energy efficiency data.

Description

Technical Field

[0001] The present invention relates to the field of agricultural processing equipment, and in particular to a cloud-controlled air source heat pump agricultural product drying system. Background Art

[0002] With the development of economy and the improvement of people's quality of life, the demand for agricultural products such as mushrooms, tea, lotus seeds, etc. is increasing. The most important process in the primary processing of some agricultural products is the drying process, which plays a decisive role in the quality of agricultural products.

[0003] In recent years, with the enhancement of environmental awareness, air source heat pumps have been widely used in the field of agricultural product drying instead of traditional drying equipment. In the context of today's automation and intelligence, the drying systems currently on the market have also kept up with the trend of the times, and drying systems that can automatically control the temperature and humidity during drying have emerged, which has improved the quality of agricultural product drying.

[0004] However, the current agricultural product drying system still has some major problems. First, in places where multiple systems are working simultaneously, the automated drying system still requires manual setting of operating parameters for each system based on experience, and manual on-site inspections of the equipment operating status are required to ensure safe production, which consumes a relatively large amount of manpower. Second, the current air source heat pump does not have a method for automatically evaluating the energy efficiency, and cannot respond to the national dual-carbon target policy needs. Summary of the invention

[0005] The technical problem to be solved and the technical task proposed by the present invention are to improve and perfect the existing technical solutions, and provide a cloud-controlled air source heat pump agricultural product drying system, so as to realize remote modification of equipment operating parameters, remote real-time monitoring of the operating status of the drying equipment and provide system energy efficiency data. To this end, the present invention adopts the following technical solutions.

[0006] A cloud-controlled air source heat pump agricultural product drying system comprises a drying room, an air source heat pump dryer and a centralized control system. The drying room comprises a fresh air valve, a return air valve, a condenser and an agricultural product drying area. The centralized control system comprises a temperature and humidity sensor array, a vortex flowmeter, a high temperature quality sensor, an intelligent circuit breaker, a heat pump field controller, a communication module, cloud application software and a database, a mobile terminal and application software. The heat pump field controller has a built-in fuzzy PID controller capable of automatically controlling the temperature and humidity curve in the drying room. The fuzzy PID controller simultaneously evaluates the system energy efficiency through a two-level energy efficiency evaluation method, collects the operating information of the heat pump dryer through the intelligent circuit breaker, collects the temperature and humidity in the drying room in real time through the temperature and humidity sensor array, collects the loss mass of the agricultural product to be dried through the high temperature quality sensor, collects the air flow at the fresh air valve and the outlet through the vortex flowmeter, and all the information is uploaded to the cloud application software and the database through the communication module. The mobile terminal is connected to the cloud application software and the database through a public network, and the working status of the drying room and the air source heat pump dryer can be remotely monitored on the mobile terminal and the application software. This system uses mobile terminals, cloud application software and databases, and heat pump field controllers to enable users to remotely modify equipment operating parameters and remotely monitor the operating status of drying equipment in real time. The system's built-in fuzzy PID controller can automatically control the temperature and humidity in the drying room, and can display the system energy efficiency in real time on the mobile terminal, which can effectively eliminate the tedious work of manual modification of operating parameters and on-site inspections on site, reducing labor costs. The two-level energy efficiency evaluation method can effectively realize energy efficiency evaluation, provide energy efficiency data, and effectively respond to the needs of the dual-carbon target policy.

[0007] As a preferred technical means: the two-level energy efficiency evaluation method is as follows:

[0008] The first level steps are as follows:

[0009] A101) collecting the temperatures T1 and T2 at the air inlet and outlet of the air source heat pump when it is working through the temperature and humidity sensor array;

[0010] A102) Use vortex flowmeter to detect the air flow Q1, Q2 at the fresh air valve and outlet; working time t;

[0011] A103) Query and obtain the specific heat Ch and density ρ of air at a specific temperature, humidity and air pressure, and calculate the heat loss ΔE in the air. The calculation formula is: ΔE = Ch·p·t(Q2·T-Q1·T);

[0012] A104) The power P measured when the air source heat pump is working is collected by the intelligent circuit breaker, the working efficiency of the air source heat pump is η, the electric heat conversion coefficient k is queried, and the heat energy E generated by the air source heat pump is calculated. x The calculation formula is: x = p·t·η·k;

[0013] A105) then evaluates the first-level energy efficiency ε1, calculated as:

[0014] The second level steps are as follows:

[0015] A201) collecting the mass loss of the crop ΔM at each drying completion by means of the high temperature mass sensor;

[0016] A202) collecting power P and working time t;

[0017] A203) evaluates the second-level energy efficiency ε2, which is used to intuitively express the output of agricultural products per unit of electricity consumption. The specific formula is as follows:

[0018]

[0019] Effectively implement two-level energy efficiency evaluation.

[0020] As a preferred technical means: the control method of the built-in fuzzy PID controller includes the following steps:

[0021] S1) according to the types of agricultural products and expected values ​​of temperature and humidity in the drying room input by the mobile terminal and the application software, the required agricultural product drying data is retrieved from the cloud application software and the database and a corresponding fuzzy inference engine is generated;

[0022] S2) The drying room starts to operate, at this time, the ambient temperature Tc is collected, the temperature X in the drying room is sampled in real time, and the temperature deviation E, the temperature deviation change rate Ec and the temperature difference Te between the drying room and the outside are calculated;

[0023] S3) After the temperature deviation E and the temperature deviation change rate Ec are fuzzified, the fuzzy inference engine generated in S1 generates a control signal uf, which is defuzzified and added to Te to generate a control signal U to control the air source heat pump dryer. Effectively realize the working control of the air source heat pump dryer.

[0024] As a preferred technical means: the temperature deviation E, temperature deviation change rate Ec, and temperature difference Te between indoor and outdoor of the drying room during the control process of the fuzzy PID controller are calculated by the following formula:

[0025]

[0026] Where W is the expected value of the drying room temperature set by the mobile terminal and application software, and K is the proportionality coefficient. The temperature deviation calculation is effectively realized.

[0027] As a preferred technical means: the fuzzy inference engine in step S1) adopts the Madani inference model.

[0028] As the preferred technical means: the intelligent circuit breaker and the heat pump field controller use the field bus for communication, the heat pump field controller and the cloud application software and database are connected through the communication module and use the MQTT protocol for communication, the cloud application software and database use the RDS cloud database for data storage and call, and the cloud application software and database communicate with the mobile terminal using the MQTT protocol. Through various communication protocols, it is convenient to realize the functions of remote parameter modification and real-time monitoring of system operation status.

[0029] Beneficial effects: This system enables users to remotely modify equipment operating parameters and remotely monitor the operating status of drying equipment in real time through mobile terminals, cloud application software and databases, and heat pump field controllers. The system's built-in fuzzy PID controller can automatically control the temperature and humidity in the drying room, and can display the system energy efficiency in real time on the mobile terminal, which can effectively eliminate the tedious work of manual modification of operating parameters and on-site inspections on site, reducing labor costs. The two-level energy efficiency evaluation method can effectively realize energy efficiency evaluation, provide energy efficiency data, and effectively respond to the needs of the dual-carbon target policy. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic diagram of the system composition of the present invention.

[0031] Figure 2 It is a schematic diagram of the two-stage energy efficiency evaluation process in the present invention.

[0032] Figure 3 It is a control flow diagram of the fuzzy PID controller in the present invention.

[0033] Figure 4 It is the principle diagram of the fuzzy PID controller in the present invention.

[0034] In the figure: 1. Drying room; 2. Air source heat pump dryer; 3. Temperature and humidity sensor array; 4. Vortex flowmeter; 5. High temperature quality sensor; 6. Intelligent circuit breaker; 7. Heat pump field controller; 8. Communication module; 9. Cloud application software and database; 10. Mobile terminal and application software. DETAILED DESCRIPTION

[0035] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings.

[0036] like Figure 1As shown, a cloud-controlled air source heat pump agricultural product drying system includes a drying room 1, an air source heat pump dryer 2, and a centralized control system. The drying room 1 includes a fresh air valve, a return air valve, a condenser, and an agricultural product drying area. The centralized control system includes a temperature and humidity sensor array 3, a vortex flowmeter 4, a high-temperature quality sensor 5, an intelligent circuit breaker 6, a heat pump field controller 7, a communication module 8, a cloud application software and a database 9, a mobile terminal and an application software 10. The heat pump field controller 7 has a built-in fuzzy PID controller, which can realize automatic control of the temperature and humidity curve in the drying room 1, and at the same time through two stages The energy efficiency evaluation method evaluates the energy efficiency of the system, collects the operating information of the heat pump dryer through the intelligent circuit breaker 6, collects the temperature and humidity in the drying room 1 through the temperature and humidity sensor array 3, collects the mass loss information of the agricultural products to be dried through the high-temperature mass sensor 5, and collects the air flow at the fresh air valve and the air outlet through the vortex flowmeter 4. All information is uploaded to the cloud application software and database 9 through the communication module 8. The mobile terminal is connected to the cloud application software and database 9 through the public network. The working conditions of the drying room 1 and the air source heat pump dryer 2 can be remotely monitored on the mobile terminal and the application software 10.

[0037] The intelligent circuit breaker 6 integrates the new generation of Internet of Things communication technology to realize intelligent protection connection and disconnection of the circuit, and can connect the voltage, current, power, electric energy metering and fault alarm data on the air source heat pump side with the heat pump field controller 7. The model of the heat pump field controller 7 is the development board EC200U, the communication module 8 is the ESP8266 module, the cloud application software and database 9 is the Alibaba Cloud Internet of Things platform, and the mobile terminal is a mobile phone or tablet with WeChat applet function.

[0038] The intelligent circuit breaker 6 communicates with the heat pump field controller 7 using the field bus. The heat pump field controller 7 is connected to the cloud application software and database 9 through the communication module 8 and communicates using the MQTT protocol. The cloud application software and database 9 use the RDS cloud database to store and call data. The cloud application software and database 9 communicate with the mobile terminal using the MQTT protocol to meet the remote parameter modification and real-time monitoring of the system operation status.

[0039] like Figure 2 As shown, in order to achieve two-level energy efficiency evaluation and provide energy efficiency data to end users, the two-level energy efficiency evaluation method is as follows:

[0040] First level step process:

[0041] A101: collect the temperatures T1 and T2 at the air inlet and outlet of the air source heat pump when it is working through the temperature and humidity sensor array 3;

[0042] A102: Detect the air flow Q1 and Q2 at the fresh air valve and outlet through the vortex flowmeter 4; working time t;

[0043] A103: Query and obtain the specific heat Ch and density ρ of air at a specific temperature, humidity and pressure, and calculate the heat loss ΔE in the air. The calculation formula is: ΔE = Ch·p·t(Q2·T-Q1·T);

[0044] A104: Then collect the power P measured when the air source heat pump is working according to the intelligent circuit breaker 6, query the working efficiency of the air source heat pump as η, the electric heat conversion coefficient k, and calculate the heat energy E generated by the air source heat pump x The calculation formula is: x = p·t·η·k;

[0045] A105: Then evaluate the first-level energy efficiency ε1, calculated as:

[0046] Second level step process:

[0047] A201: collecting the crop mass loss ΔM at each drying completion through the high temperature mass sensor 5;

[0048] A202: collect power P and working time t;

[0049] A203: Evaluate the second-level energy efficiency ε2, which is used to intuitively express the output of agricultural products per unit of electricity consumption. The specific formula is as follows:

[0050]

[0051] Effectively implement two-level energy efficiency evaluation.

[0052] like Figure 3 , 4 As shown, the control process of the built-in fuzzy PID controller includes the following steps:

[0053] S1: According to the agricultural product types and expected values ​​of temperature and humidity in the drying room 1 input by the mobile terminal and the application software 10, the required agricultural product drying data is retrieved from the cloud application software and the database 9 and a corresponding fuzzy inference engine is generated;

[0054] S2: Drying room 1 starts operation. At this time, the ambient temperature Tc is collected, the temperature X in the drying room 1 is sampled in real time, and the temperature deviation E, the temperature deviation change rate Ec and the temperature difference Te between the inside and outside of the drying room 1 are calculated;

[0055] S3: After the temperature deviation E and the temperature deviation change rate Ec are fuzzified, the fuzzy inference engine generated in S1 generates a control signal uf, which is defuzzified and added with Te to generate a control signal U to control the air source heat pump dryer 2. The working control of the air source heat pump dryer 2 is effectively realized.

[0056] During the control process of the fuzzy PID controller, the temperature deviation E, the temperature deviation change rate Ec, and the temperature difference Te between the inside and outside of the drying chamber 1 are calculated by the following formula:

[0057]

[0058] Wherein, W is the expected value of the temperature in the drying chamber 1 set by the mobile terminal and the application software 10, and K is the proportionality coefficient.

[0059] Among them, inside the inference engine in step S1, the range of temperature deviation E is [-10, 10], the range of temperature deviation change rate Ec is [-1, 1], the output Uf is [0, 100], the corresponding quantization factors are: Ke = 0.4, Kec = 4, Ku = 20, and the inference engine adopts the Mamdani inference model.

[0060] When the system is working, the user can access the cloud application software and database from a smart phone or tablet, and remotely access the heat pump field controller 7 through the cloud application software and database to remotely modify the operating parameters of the air source heat pump dryer 2 and remotely monitor the working status of the air source heat pump dryer 2. The intelligent circuit breaker 6 simultaneously collects the sampling data and temperature and humidity data of the air source heat pump dryer 2 and returns them to the heat pump field controller 7. The heat pump field controller 7 performs fuzzy control on the air source heat pump dryer 2 through the temperature and humidity data. When disconnection is required, the heat pump field controller 7 controls the disconnection of the air source heat pump dryer 2 by sending a control signal to the intelligent circuit breaker 6. In addition, the heat pump field controller 7 feeds back the corresponding data to the cloud application software and database after sorting and calculating. The user can access the cloud application software and database from a smart phone or tablet to realize remote monitoring.

[0061] This system uses mobile terminals, cloud application software and database 9, and heat pump field controller 7 to enable users to remotely modify equipment operating parameters and remotely monitor the operating status of drying equipment in real time. The system's built-in fuzzy PID controller can automatically control the temperature and humidity in the drying room 1, and can display the system energy efficiency in real time on the mobile terminal, which can effectively eliminate the tedious work of manual modification of operating parameters and on-site inspections on site, reducing labor costs. The two-level energy efficiency evaluation method can effectively realize energy efficiency evaluation, provide energy efficiency data, and effectively respond to the needs of the dual-carbon target policy.

[0062] above Figure 1-4 The cloud-controlled air source heat pump agricultural product drying system shown is a specific embodiment of the present invention, which has embodied the outstanding substantial features and remarkable progress of the present invention. According to actual use needs and under the guidance of the present invention, equivalent modifications in shape, structure, etc. can be made to it, which are all within the protection scope of this scheme.

Claims

1. A cloud-controlled air source heat pump agricultural product drying system, comprising a drying chamber (1), an air source heat pump dryer (2), and a centralized control system, wherein the drying chamber (1) comprises a fresh air valve, a return air valve, a condenser, and an agricultural product drying area, and is characterized in that: The centralized control system comprises a temperature and humidity sensor array (3), a vortex flowmeter (4), a high-temperature mass sensor (5), an intelligent circuit breaker (6), a heat pump field controller (7), a communication module (8), a cloud application software and a database (9), and a mobile terminal and an application software (10). The heat pump field controller (7) has a built-in fuzzy PID controller capable of automatically controlling the temperature and humidity curve in the drying chamber (1). The fuzzy PID controller simultaneously evaluates the system energy efficiency through a two-level energy efficiency evaluation method. The intelligent circuit breaker (6) collects the operating information of the heat pump dryer. The temperature and humidity in the drying chamber (1) are collected in real time through the temperature and humidity sensor array (3). The loss mass of the agricultural products to be dried is collected through the high-temperature mass sensor (5). The fresh air valve and the air flow at the outlet are collected through the vortex flowmeter (4). All information is connected and uploaded to the cloud application software and the database (9) through the communication module (8). The mobile terminal is connected to the cloud application software and the database (9) through a public network. The working status of the drying chamber (1) and the air source heat pump dryer (2) can be remotely monitored on the mobile terminal and the application software (10). The two-level energy efficiency evaluation method is as follows: The first level steps are as follows: A101) The temperature and humidity sensor array (3) is used to collect the temperature at the air inlet and outlet of the air source heat pump when it is working. , ; A102) Use vortex flowmeter (4) to detect the air flow at the fresh air valve and outlet. , ; Working time t; A103) Query and obtain the specific heat Ch and density of air at a specific temperature, humidity and pressure , calculate the heat loss in the air , the calculation formula is: ; A104) The power P measured when the air source heat pump is working is collected by the intelligent circuit breaker (6), the working efficiency of the air source heat pump is ƞ, the electric heat conversion coefficient k is queried, and the heat energy generated by the air source heat pump is calculated. The calculation formula is: ; A105) and then evaluate the first level energy efficiency , the calculation formula is: ； The second level steps are as follows: A201) The high temperature mass sensor (5) is used to collect the mass loss of the crop at each drying completion. ; A202) collect power P and working time t; A203) Evaluate the second level energy efficiency , which is used to intuitively express the output of agricultural products per unit of electricity consumption. The specific formula is as follows: 。 2. The cloud-controlled air source heat pump agricultural product drying system according to claim 1 is characterized by: The control method of the built-in fuzzy PID controller includes the following steps: S1) according to the agricultural product types and expected values ​​of temperature and humidity in the drying room (1) input by the mobile terminal and the application software (10), the required agricultural product drying data is retrieved from the cloud application software and the database (9) and a corresponding fuzzy inference engine is generated; S2) The drying chamber (1) starts to operate. At this time, the ambient temperature Tc is collected, the temperature X in the drying chamber (1) is sampled in real time, and the temperature deviation E, the temperature deviation change rate Ec and the temperature difference Te between the inside and outside of the drying chamber (1) are calculated; S3) After the temperature deviation E and the temperature deviation change rate Ec are fuzzified, the fuzzy inference engine generated in S1 generates a control signal uf, which is then defuzzified and added to Te to generate a control signal U to control the air source heat pump dryer (2).

3. The cloud-controlled air source heat pump agricultural product drying system according to claim 2 is characterized by: During the control process of the fuzzy PID controller, the temperature deviation E, the temperature deviation change rate Ec, and the temperature difference Te between the inside and outside of the drying chamber (1) are calculated by the following formula: Wherein, W is the expected value of the temperature in the drying room (1) set by the mobile terminal and the application software (10), and K is the proportionality coefficient.

4. The cloud-controlled air source heat pump agricultural product drying system according to claim 2, characterized in that: The fuzzy inference engine in step S1) adopts the Madani inference model.

5. The cloud-controlled air source heat pump agricultural product drying system according to claim 1, characterized in that: The intelligent circuit breaker (6) and the heat pump field controller (7) communicate using a field bus. The heat pump field controller (7) and the cloud application software and database (9) are connected via a communication module (8) and communicate using the MQTT protocol. The cloud application software and database (9) use an RDS cloud database to store and call data. The cloud application software and database (9) and the mobile terminal communicate using the MQTT protocol to meet the functions of remote parameter modification and real-time monitoring of system operation status.

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