Intelligent curing barn temperature control system

Abstract

The invention provides an intelligent curing barn temperature control system, which relates to the technical field of electronic information, and comprises a closed curing barn, a temperature sensor and an intelligent oven arranged in the curing barn, a network transmission module connected with the intelligent oven and the temperature sensor, a data processing platform and terminal control equipment, the intelligent oven comprises a fuel bin, a fuel feeding controller and a calculation processing and control module. According to the method, the data processing platform receives the instruction of the control terminal or the data processing platform automatically adjusts the oven parameters (t, a) according to the preset strategy, so that the manpower consumption for adjusting the parameters is saved to different degrees, and the parameter adjusting efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of electronic information technology, and particularly to an intelligent tobacco barn temperature control system. Background Art

[0002] Tobacco leaf baking is an important part of the tobacco production process, and the control of the baking oven is the key factor for whether the temperature of the tobacco barn can meet the baking requirements. In the existing tobacco leaf baking process, most baking ovens have achieved a semi-automatic working mode. As long as the management personnel regularly replenish sufficient fuel in the fuel bin, the feeding process will occur automatically. The automatic feeding process of the baking oven is controlled by two parameters, namely the amount of each feeding a and the time interval t between two feedings.

[0003] Generally, different parameters (t, a) need to be set, including the oven parameters when maintaining the temperature of the tobacco barn and the adjustment of the oven parameters when raising or lowering the temperature of the tobacco barn to a certain temperature. At the same time, different qualities of fuel determine different amounts of heat released by fuel combustion, and different feeding specifications, that is, different parameters (t, a), need to be set for different fuels.

[0004] Currently, this adjustment is mainly responsible for experienced baking technicians, and may need to be adjusted multiple times according to the fuel combustion situation. This process not only consumes manpower, but also the number of experienced baking technicians is small, the technical levels vary greatly, and there may be mistakes or even errors. Summary of the Invention

[0005] This application provides an intelligent tobacco barn temperature control system to solve or partially solve the problems raised in the above background art.

[0006] This application provides an intelligent tobacco barn temperature control system, including an enclosed tobacco barn, a temperature sensor and an intelligent baking oven arranged in the tobacco barn, a network transmission module connecting the intelligent baking oven and the temperature sensor, a data processing platform, and a terminal control device. The intelligent baking oven includes a fuel bin, a fuel feeding controller, a calculation processing and control module, and is characterized by having the following functions: (1) The data processing platform sets the initial parameters of the feeding time interval and the amount of each feeding of the intelligent baking oven as (t, a) = (t0, a0), which are the temperature maintenance parameters corresponding to the preset first temperature d1 of the tobacco barn. The fuel feeding controller adds fuel with a fixed amount of a = a0 to the furnace every time t = t0. (2) The network transmission module sends the tobacco barn information to the data processing platform and receives the network control instructions from the data processing platform. (3) The calculation processing and control module is used to upload the configuration parameters of the intelligent oven, the temperature information of the baking room, i.e., the baking room information, and update the parameters (t, a) according to the received network control instructions; (4) The user modifies the parameters (t, a) of the intelligent oven through the terminal control device, or the data processing platform and the calculation processing and control module automatically adjust the parameters (t, a) through a preset strategy.

[0007] Preferably, when the temperature of the baking room needs to increase by D degrees within time T, the system performs the following steps: (1) The data processing platform performs the following processing: ① Calculate the total energy E required for the baking room to increase by D degrees; ② Calculate the total amount of fuel W required to generate the energy E; ③ Calculate the feed increase amount w = W * t0 / T / g, where g is the energy conversion rate; ④ Calculate the parameters (t, a) = (t1, a1) of the intelligent oven corresponding to the baking room maintaining the target temperature d2 = d1 + D; ⑤ Send (w, t1, a1) to the calculation processing and control module of the intelligent oven; (2) When the calculation processing and control module of the intelligent oven receives the parameters (w, t1, a1), it performs the following steps: ① Update the parameter a = a0 of the intelligent oven to a = a0 + w; ② After time T, the calculation processing and control module of the intelligent oven updates the parameters of the intelligent oven to (t, a) = (t1, a1).

[0008] Preferably, the calculation processing and control module of the intelligent oven pre-sets the temperature maintenance parameters (t, a) corresponding to different baking room temperatures d; Correspondingly, the data processing platform does not need to calculate and transmit the parameters (t, a) = (t1, a1) of the intelligent oven. After time T, the calculation processing and control module looks up the temperature maintenance parameters (t1, a1) according to the updated baking room target temperature d2, and then controls the intelligent oven with the updated parameters.

[0009] Preferably, it includes the following steps: (1) When the data processing platform detects that the baking room temperature reaches the predetermined target temperature d2 = d1 + D, it sends d2 to the calculation processing and control module of the intelligent oven; (2) The calculation processing and control module of the intelligent oven updates the parameters (t, a) of the intelligent oven to the temperature maintenance parameters (t, a) = (t1, a1) corresponding to the baking room temperature of d2; (3) The data processing platform calculates the time T required for the baking room to heat up to d2, and updates the energy conversion rate g = g * T / T1.

[0010] Preferably, it includes the following steps: (1) Divide the time T into k equal parts, i.e., T = kt d , and whenever the time t has passed d , the system enters a new parameter adjustment time node, and the data processing platform executes the following steps: ① Calculate the expected value d of the baking room temperature at the previous parameter adjustment time node exp1 and the expected value d of the baking room temperature at the current time node exp2 ; ② Detect the current temperature d2 of the baking room and calculate q = (d2 - d exp1 ) / (d exp2 - d exp1 ); ③ If q = 1, keep the value of (t, a) unchanged; if q ≠ 1, calculate a' = a0 + (a - a0) / q, If a' ≤ a max , then send a' to the calculation processing and control module of the baking oven, and the calculation processing and control module updates the value of a to a', keeping the value of t unchanged; If a' > a max , then calculate t' = t * a max / a', and send (t', a') to the calculation processing and control module of the baking oven, and the calculation processing and control module updates (t, a) to (t', a max ), where a max is the maximum single - feed amount of the intelligent baking oven; When a' exceeds a max and t reaches or is less than t min , the calculation processing and control module updates (t, a) to (t min , a max ), where t min is the minimum feeding time interval.

[0011] Preferably, the data processing platform is provided with an energy consumption table corresponding to different fuel materials, including fuel material codes, energy - fuel ratios E / W, energy conversion rates g, and the intelligent baking oven parameters (t, a) corresponding to maintaining different baking room temperatures.

[0012] Preferably, the adjustment range of the baking room temperature is automatically controlled by the data processing platform according to a pre - set baking process curve.

[0013] Compared with the prior art, the beneficial effects of this application are: (1) The present application receives instructions from the control terminal through the data processing platform, or the data processing platform automatically adjusts the oven parameters (t, a) according to preset strategies, saving the labor consumption for parameter adjustment to varying degrees and improving the parameter adjustment efficiency.

[0014] (2) Through the temperature sensor in the baking room, the present application timely grasps the temperature situation in the baking room and the working state of the oven, accurately adjusts the oven feeding parameters, and controls the heat generated by the oven combustion, so as to achieve the expected effect of adjusting the temperature in the baking room.

[0015] (3) By segmenting the temperature adjustment time and adjusting the oven parameters (t, a) according to the actually adjusted temperature values for each period, the present application improves the effect of parameter adjustment and the probability of reaching the target temperature at the target time. Description of the Drawings

[0016] The present application will be further described below in conjunction with the drawings and embodiments.

[0017] Figure 1 It is a schematic diagram of the composition of the intelligent oven of the present application. Figure 2 It is a schematic diagram of the system composition of the present application. Detailed Embodiments

[0018] To make the purpose, technical solutions, and advantages of this specification clearer, the technical solutions of the present application will be described below through a specific embodiment. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present application.

[0019] Several embodiments of the present invention are given below. Those skilled in the art should understand that these embodiments do not limit the technical methods of the present invention.

[0020] Embodiment 1 As Figure 1 and Figure 2 shown, the present application provides an intelligent baking room temperature control system, including an enclosed baking room, a temperature sensor and an intelligent oven arranged in the baking room, a network transmission module connecting the intelligent oven and the temperature sensor, a data processing platform, and a terminal control device. The intelligent oven includes a fuel tank, a fuel feeding controller, a calculation processing and control module, and each module has the following functions: (1) The data processing platform sets the initial parameters of the feeding time interval and the amount of each feed of the intelligent oven as (t, a) = (t0, a0), which are the temperature maintenance parameters corresponding to the case where the temperature of the baking room is the preset first temperature d1. The fuel feeding controller adds fuel with a fixed quantity of a = a0 to the furnace every time t = t0. (2) The network transmission module sends the baking room information to the data processing platform and receives network control instructions from the data processing platform. (3) The calculation processing and control module is used to upload the configuration parameters of the intelligent oven, the temperature information of the baking room, i.e., the baking room information, and update the parameters (t, a) according to the received network control instructions. (4) The user modifies the parameters (t, a) of the intelligent oven through the terminal control device, or the data processing platform and the calculation processing and control module automatically adjust the parameters (t, a) through a preset strategy.

[0021] Regarding the intelligent baking room temperature control system of this application, obviously, the intelligent oven is a key component. As Figure 1 shown, the intelligent oven further includes a hot gas outlet temperature sensor and a furnace blower. The furnace blower helps the fuel burn fully in the furnace. The hot gas outlet temperature sensor is used to detect the temperature at the hot gas outlet of the intelligent oven to determine whether the fuel in the furnace is burned out, so as to control the rotation speed of the blower.

[0022] Specifically, the method for the data processing platform and the calculation processing and control module to automatically adjust the parameters (t, a) through a preset strategy is as follows: When the temperature of the baking room needs to increase by D degrees within time T, the system performs the following steps: (1) The data processing platform performs the following processing: ① Calculate the total energy E required for the baking room to increase by D degrees. This calculation can be obtained based on the recorded historical data. ② Calculate the total amount of fuel W required to generate energy E. This value is related to the fuel variety. ③ Calculate the feed increase amount w = W * t0 / T / g, where g is the energy conversion rate. The energy conversion rate g is an estimated parameter, which is not only related to the fuel variety but also related to factors such as the size, newness, and airtightness of the intelligent oven. ④ Calculate the parameters (t, a) = (t1, a1) of the intelligent oven corresponding to maintaining the target temperature d2 = d1 + D of the baking room. That is, to maintain the baking room at d2 degrees, the intelligent oven needs to feed fuel every time t1, and the amount of each feed is a1. ⑤ Send (w, t1, a1) to the calculation processing and control module of the intelligent oven. (2) When the intelligent oven calculation, processing, and control module receives the parameters (w, t1, a1), the following steps are executed: ① Update the parameter a = a0 of the intelligent oven to a = a0 + w, that is, the amount of fuel advanced each time changes from the current a0 to a0 + w. Here, only the temperature maintenance stage after heating is considered. If cooling is required, only maintain the minimum feed rate of the intelligent oven and cooperate with the furnace blower; ② After a time T, the intelligent oven calculation, processing, and control module updates the parameters of the intelligent oven to (t, a) = (t1, a1). At this time, the baking room should reach the expected temperature and maintain this temperature until the control instruction is sent in the next stage to modify the baking mode and change the baking room environment.

[0023] Preferably, the calculation, processing, and control module of the intelligent oven presets the temperature maintenance parameters (t, a) corresponding to different baking room temperatures d. Correspondingly, the data processing platform does not need to calculate and transmit the intelligent oven parameters (t, a) = (t1, a1). After a time T, the calculation, processing, and control module searches for the temperature maintenance parameters (t1, a1) according to the updated baking room target temperature d2, and then controls the intelligent oven with the updated parameters.

[0024] Furthermore, the intelligent baking room temperature control system as described above can be switched from the temperature change stage to the temperature maintenance stage, including the following steps: (1) When the data processing platform detects that the baking room temperature reaches the predetermined target temperature d2 = d1 + w, send d2 to the calculation and control module of the intelligent oven; (2) The calculation and control module of the intelligent oven updates the intelligent oven parameters (t, a) to the temperature maintenance parameters (t, a) = (t1, a1) corresponding to the baking room temperature d2; (3) The data processing platform calculates the time T1 required for the baking room to heat up to d2 and updates the energy conversion rate g = g * T / T1.

[0025] Even further, the intelligent baking room temperature control system as described above can continuously adjust and optimize the parameters of the intelligent oven during the temperature change stage to make the temperature change in the baking room closer to the expectation, including the following steps: (1) Divide the time T into k equal parts, that is, T = kt d , and every time after a time t d , the system enters a new parameter adjustment time node, and the data processing platform executes the following steps: ① Calculate the expected value d of the baking room temperature at the previous parameter adjustment time node exp1 and the expected value d of the baking room temperature at the current time node exp2 ; ②Detect the current temperature d2 of the baking oven, and calculate q = (d2 - d exp1 ) / (d exp2 - d exp1 ); ③If q = 1, keep the value of (t, a) unchanged; if q ≠ 1, calculate a’ = a0 + (a - a0) / q. If a’ ≤ a max , then send a’ to the calculation processing and control module of the baking oven to update the value of a; If a’ > a max , then calculate t’ = t * a max / a’, and send (t’, a’) to the calculation processing and control module of the baking oven to update the parameters (t, a), where a max is the maximum single - feed amount of the intelligent baking oven; (2) After the data processing platform detects that the temperature of the baking oven reaches the predetermined target temperature d2 = d1 + D / k, send d2 to the calculation processing and control module of the intelligent baking oven; (3) The calculation processing and control module of the intelligent baking oven updates the intelligent baking oven parameters (t, a) to the temperature - maintaining parameters (t, a) = (t1, a1) corresponding to the baking oven temperature d2.

[0026] Further, when a + w exceeds the maximum single - feed amount a of the intelligent baking oven max , update (t, a) = (t * a max / (a + w), a max ) to handle the situation where the expected feed amount exceeds the limit value.

[0027] Further, when a + w exceeds a max and t reaches or is less than t min , execute according to the parameters (t min , a max ), where t min is the minimum feeding interval value.

[0028] Preferably, the data processing platform is provided with an energy consumption table corresponding to different fuel materials, including fuel material coding, energy - fuel ratio E / W, energy conversion rate g, and the intelligent baking oven parameters (t, a) corresponding to maintaining different baking oven temperatures.

[0029] Preferably, in the intelligent baking oven temperature control system as described above, when the temperature of the baking oven cannot reach the preset temperature on time under the set parameters, a feedback iteration algorithm can be used to optimize and update the intelligent baking oven parameters.

[0030] Preferably, the curing barn is provided with multiple intelligent ovens that burn different fuels respectively, and the data processing platform distributes the target temperature increase value to different intelligent ovens proportionally according to the capabilities of different intelligent ovens.

[0031] For example, if oven 1 is three times larger than oven 2, and the capabilities of the two ovens are equivalent to four oven 1s, when the target temperature increase of the curing barn is D degrees, the heating task of 0.25D is assigned to oven 1, and the heating task of 0.75D is assigned to oven 2.

[0032] Preferably, the temperature adjustment range of the curing barn is automatically controlled by the data processing platform according to a pre-set baking process curve.

[0033] Embodiment 2 Based on Embodiment 1, this embodiment illustrates the technical solution of the present application with a specific scenario.

[0034] Suppose there is an intelligent curing barn. When the intelligent oven burns at the minimum scale, it can maintain the room temperature of the curing barn at d1 = 30 degrees, that is, a0 is the minimum single feed amount, and t0 = 30 seconds (0.5 minutes) is the standard time interval between two feeds.

[0035] After the tobacco leaves are loaded and the curing barn is closed, the temperature of the curing barn needs to be raised to 60 degrees within 2 hours and then maintained for a period of time.

[0036] According to these requirements, the data processing platform calculates the total energy E required to raise the temperature of the curing barn by D = 60 - 30 = 30 degrees, calculates the total amount of fuel W (kilograms) required according to the fuel type, and calculates the amount of temperature increase per feed w = W * t0 / T / g, where t0 = 0.5, T = 120 (minutes), and assuming the energy conversion rate is g = 0.8 (the conversion rate is lower at higher temperatures because of heat dissipation).

[0037] If a0 + w does not exceed the maximum single feed amount, then w is sent to the intelligent oven.

[0038] After receiving the instruction, the intelligent oven works with parameters (t0, a1), where a1 = a0 + w. When this working mode lasts for T = 120 minutes, the data processing platform sends the parameters (t1, a1) of the intelligent oven for maintaining the 60-degree curing barn temperature to the intelligent oven, and then the intelligent oven works with parameters (t1, a1), that is, enters a new section of the temperature maintenance mode.

[0039] Under normal circumstances, the time interval between two feeds generally remains unchanged, that is, t1 = t0. But in special cases, such as when rapid temperature increase is required, then t1 < t0.

[0040] It should be noted that if the temperature of the baking room needs to be reduced, the parameters of the intelligent baking oven can be directly adjusted to the parameters corresponding to the temperature of the baking room after cooling, and the specific cooling process is completed by other means, such as opening windows, ventilation, etc.

[0041] Embodiment 3 Based on Embodiments 1 and 2, this embodiment uses a specific scenario to illustrate the technical solution of the present application.

[0042] As in the case of Embodiment 2, if the temperature of the baking room is increased by 30 degrees within T = 120 minutes, the average increase per minute is 30 / 120 = 0.25 degrees. If the time T = 120 minutes is divided into k = 30 parts, then on average every t d = T / k = 4 minutes, the average expected increase in the temperature of the baking room is d2 = d1 + D / k = d1 + 30 / 30 = d1 + 1 degree, that is, every 4 minutes, the expected increase in the temperature of the baking room is 1 degree. However, the actual detected increase is 0.8 degrees, that is, d'2 = d1 + 0.8 degrees. Thus, q = (d'2 - d1) / (d2 - d1) = 0.8 is obtained. Calculate a' = a0 + (a - a0) / q and send a' to the baking oven to update the working parameters of the baking oven. Since q = 0.8 < 1, this means that the previous feeding amount was insufficient and the feeding amount needs to be increased. Assume that in the next time period t d = 4 minutes later, the temperature of the baking room has increased by 1.1 degrees, then calculate q = (d'2 - d1) / (d2 - d1) = 1.1. Similarly, calculate a' = a0 + (a - a0) / q and send a' to the baking oven to update the working parameters of the baking oven. Since q = 1.1 > 1, this means that the previous feeding amount was excessive and the feeding amount needs to be reduced. In this way, after k adjustments, the time required for the baking room to increase the temperature by D degrees is very close to T = 120 minutes.

Claims

1. An intelligent tobacco barn temperature control system, comprising an enclosed tobacco barn, a temperature sensor and an intelligent tobacco oven arranged in the tobacco barn, a network transmission module connecting the intelligent tobacco oven and the temperature sensor, a data processing platform, and a terminal control device. The intelligent tobacco oven includes a fuel bin, a fuel feeding controller, a calculation processing and control module, and is characterized in that, It has the following functions: (1) The data processing platform sets the initial parameters of the feeding time interval and the amount of each feed of the intelligent oven as (t, a) = (t0, a0), which are the temperature maintenance parameters corresponding to the case where the temperature of the baking room is the preset first temperature d1. The fuel feeding controller adds fuel with a fixed quantity of a = a0 into the furnace every t = t0; (2) The network transmission module sends the baking room information to the data processing platform and receives network control instructions from the data processing platform; (3) The calculation processing and control module is used to upload the configuration parameters of the intelligent oven, the temperature information of the baking room, that is, the baking room information, and update the parameters (t, a) according to the received network control instructions; (4) The user modifies the parameters (t, a) of the intelligent oven through the terminal control device, or the data processing platform and the calculation processing and control module automatically adjust the parameters (t, a) through a preset strategy.

2. The intelligent baking room temperature control system according to claim 1, wherein: The method for the data processing platform and the calculation processing and control module to automatically adjust the parameters (t, a) through a preset strategy is as follows: When the temperature of the baking room needs to increase by D degrees within time T, the system performs the following steps: (1) The data processing platform performs the following processing: ① Calculate the total energy E required for the baking room to increase by D degrees; ② Calculate the total amount of fuel W required to generate the energy E; ③ Calculate the feed increase amount w = W * t0 / T / g, where g is the energy conversion rate; ④ Calculate the intelligent oven parameters (t, a) = (t1, a1) corresponding to the baking room maintaining the target temperature d2 = d1 + D; ⑤ Send (w, t1, a1) to the calculation processing and control module of the intelligent oven; (2) When the calculation processing and control module of the intelligent oven receives the parameters (w, t1, a1), it performs the following steps: ① Update the parameter a = a0 of the intelligent oven to a = a0 + w; ② After time T, the calculation processing and control module of the intelligent oven updates the parameters of the intelligent oven to (t, a) = (t1, a1).

3. The intelligent baking room temperature control system according to claim 2, wherein: The calculation processing and control module of the intelligent oven pre-sets the temperature maintenance parameters (t, a) corresponding to different baking room temperatures d; Correspondingly, the data processing platform does not need to calculate and transmit the intelligent oven parameters (t, a) = (t1, a1). After time T, the calculation processing and control module looks up the temperature maintenance parameters (t1, a1) according to the updated baking room target temperature d2, and then controls the intelligent oven with the updated parameters.

4. The intelligent baking room temperature control system according to any one of claims 2 or 3, wherein: It includes the following steps: (1) When the data processing platform detects that the temperature of the baking room reaches the predetermined target temperature d2 = d1 + D, it sends d2 to the calculation processing and control module of the intelligent oven; (2) The calculation, processing, and control module of the intelligent oven updates the intelligent oven parameters (t, a) to the temperature maintenance parameters (t, a) = (t1, a1) corresponding to the curing barn temperature of d2. (3) The data processing platform calculates the time T1 required for the curing barn to heat up to d2 and updates the energy conversion rate g = g * T / T1.

5. An intelligent curing barn temperature control system according to claim 2 or claim 3, characterized in that: It includes the following steps: (1) Divide the time T into k equal parts, i.e., T = kt d , every time after the time t d , the system enters a new parameter adjustment time node, and the data processing platform performs the following steps: ① Calculate the expected value d of the curing barn temperature at the previous parameter adjustment time node exp1 and the expected value d of the curing barn temperature at the current time node exp2 ; ② Detect the current temperature d2 of the curing barn and calculate q=(d2 - d exp1 ) / (d exp2 - d exp1 ); ③ If q = 1, keep the value of (t, a) unchanged; If q ≠ 1, calculate a' = a0 + (a - a0) / q, If a’ ≤ a max , then send a’ to the calculation, processing, and control module of the oven, and the calculation, processing, and control module updates the value of a to a’ while keeping the value of t unchanged; If a’ > a max , then calculate t’ = t * a max / a’, and send (t’, a’) to the calculation processing and control module of the oven. The calculation processing and control module updates (t, a) to (t’, a max ), where a max is the maximum single feeding amount of the intelligent oven.

6. An intelligent curing barn temperature control system according to any one of claim 2 or claim 3, characterized in that: When a' exceeds a max and t reaches or is less than t min then the calculation processing and control module updates (t, a) to (t min , a max ), where t min is the minimum feed time interval.

7. An intelligent curing barn temperature control system according to claim 1, characterized in that: The data processing platform is provided with an energy consumption table corresponding to different fuel materials, including fuel material codes, energy-to-fuel ratios E / W, energy conversion rates g, and intelligent oven parameters (t, a) corresponding to maintaining different curing barn temperatures.

8. An intelligent curing barn temperature control system according to claim 1, characterized in that: The temperature adjustment range of the curing barn is automatically controlled by the data processing platform according to a pre-set baking process curve.

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