CN114967801B - Intelligent production regulation and control curve and big data platform - Google Patents
Intelligent production regulation and control curve and big data platform Download PDFInfo
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- CN114967801B CN114967801B CN202210632351.9A CN202210632351A CN114967801B CN 114967801 B CN114967801 B CN 114967801B CN 202210632351 A CN202210632351 A CN 202210632351A CN 114967801 B CN114967801 B CN 114967801B
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D27/00—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00
- G05D27/02—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00 characterised by the use of electric means
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The application discloses an intelligent production regulation and control curve and big data platform, which comprises an acquisition module, an analysis module, an environment control module, a fusing machine, a fuzzy control module, a central control module, an execution module, a remote control module and a display terminal. According to the application, the acquisition module is used for acquiring the growth environment parameters of each stage of the crops, the analysis module is used for analyzing and processing the acquired growth environment parameters of the crops in combination with the growth environment parameters of the crops in the database, the fusing machine and the fuzzy control module are used for processing the abnormal temperature change rate by applying a fusing mechanism and a fuzzy algorithm, then the central control module is used for sending an instruction to the execution unit according to the analysis result fed back by the analysis unit, the execution unit is used for controlling the operation of the environment control module, changing the growth environment parameters of the crops at the current stage, regulating and controlling the proper temperature and ventilation, ensuring proper relative humidity and illumination, forming closed loop feedback, reasonably enhancing the soil fertility, and thus obtaining the high-yield and high-quality crops.
Description
Technical Field
The application relates to the technical field of intelligent production, in particular to an intelligent production regulation and control curve and a big data platform.
Background
At present, with the gradual improvement of the living standard and scientific diet consciousness of people, the large-scale and industrial production of crop growth has become the necessary trend and means of the high-speed development of the crop industry in the future. The existing crop growth management generally needs to be planted by people according to planting experience and a planting method acquired on books, environmental parameters of each growth stage of crops need to be manually regulated and controlled by experience, and in order to achieve the purpose of high yield and no insect damage of the crops, pesticide spraying and excessive fertilization are often carried out on the crops, and the crop body is rich in various components which are not beneficial to human health although the mode can play a certain role.
Disclosure of Invention
The application aims at: in order to solve the problems, the intelligent production regulation and control curve and a big data platform are provided.
In order to achieve the above purpose, the present application adopts the following technical scheme:
the intelligent production regulation and control curve and big data platform comprises an acquisition module, an analysis module, an environment control module, a fusing machine, a fuzzy control module, a central control module, an execution module, a remote control module and a display terminal;
the acquisition module is connected with the central control module and is used for acquiring the growth environment parameters of each stage of crops and transmitting the acquired environment parameters to the central control module for connection;
the analysis module is connected with the central control module and is used for analyzing the growth environment parameters of crops and feeding back analysis results to the central control module;
the environment control module is connected with the execution module and is used for regulating and controlling the crop growth environment parameters;
the fusing machine is connected with the fuzzy control module and is used for protecting the system when the temperature is abnormal;
the fuzzy control module is connected with the fuse machine and the central control module and is used for processing a fuzzy algorithm of temperature abnormality in closed loop feedback control;
the central control module is connected with the execution module and the remote control module and is used for receiving and storing crop growth environment parameter data and sending an execution instruction to the execution module through the fed back growth environment parameters;
the execution module is used for receiving the instruction of the central control module and controlling the environment control module to execute;
the remote control module is connected with the display terminal in a remote control way, so that the central controller is connected with the display terminal in a remote control way;
and the display terminal is used for displaying the remote received crop growth environment parameter data and the growth curve.
Preferably, the acquisition module comprises an image acquisition unit for acquiring an image of an environmental parameter during the growth of the crop and an environmental factor sensor unit comprising: temperature and humidity sensor, light intensity sensor, oxygen content sensor, temperature and humidity sensor is used for real-time supervision crops growing environment's temperature and humidity, light intensity sensor is used for real-time supervision crops growing environment's illumination intensity, oxygen content sensor is used for the oxygen content of real-time supervision crops growing environment.
Preferably, the environment control module comprises a spraying system, a ventilation system, a light regulation system and a refrigerating and heating system, and is used for controlling the temperature and humidity, the oxygen content and the illumination intensity in the crop growth environment.
Preferably, the fusing machine and the fuzzy control module process the abnormal temperature change rate through a fusing mechanism and a fuzzy algorithm.
Preferably, the central control module further comprises a database, wherein standard growth parameter characteristics corresponding to each growth stage of the crops are recorded in the database.
In summary, due to the adoption of the technical scheme, the beneficial effects of the application are as follows:
1. according to the application, the acquisition module is used for acquiring the growth environment parameters of each stage of the crops, the analysis module is used for analyzing and processing the acquired growth environment parameters of the crops in combination with the growth environment parameters of the crops in the database, then the central control module is used for sending an instruction to the execution unit according to the analysis result fed back by the analysis unit, the execution unit controls the environment control module to work, the current growth environment parameters of the crops are changed, the proper temperature and ventilation are regulated and controlled, the proper relative humidity and illumination are ensured, the closed loop feedback is formed, the environmental conditions which are most suitable for the growth and development of the crops in each stage are created, the use of chemical fertilizers is reduced, the land fertility is reasonably enhanced, and the high-yield and high-quality crops are obtained.
2. In the application, the digital management of crops is realized through the acquisition module, the analysis module, the environment control module, the central control module, the execution module, the remote control module and the display terminal, the growth environment parameters of the crops can be accurately monitored and efficiently controlled, and the management cost and the manpower investment are greatly reduced through a scientific management method combining digitization and agriculture, and the real-time management and the digital monitoring of the crops are facilitated.
3. In the application, the fusing mechanism and the fuzzy control module are used for processing the abnormal temperature change rate by using the fusing mechanism and the fuzzy algorithm, so that the problem of system breakdown when the abnormal temperature change rate occurs in closed loop feedback control is solved, and the system stability is greatly improved.
Drawings
FIG. 1 is a schematic diagram of a system block diagram of an intelligent production control curve and big data platform provided according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an environmental control module system for intelligent production control curves and big data platforms according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1-2, the present application provides a technical solution:
the intelligent production regulation and control curve and big data platform is characterized by comprising an acquisition module, an analysis module, an environment control module, a fusing machine, a fuzzy control module, a central control module, an execution module, a remote control module and a display terminal;
the acquisition module is connected with the central control module and is used for acquiring the growth environment parameters of each stage of crops and transmitting the acquired environment parameters to the central control module for connection;
the analysis module is connected with the central control module and is used for analyzing the growth environment parameters of crops and feeding back analysis results to the central control module;
the environment control module is connected with the execution module and used for regulating and controlling the crop growth environment parameters;
the fusing machine is connected with the fuzzy control module and is used for protecting the system when the temperature is abnormal;
the fuzzy control module is connected with the fusing machine and the central control module and is used for processing a fuzzy algorithm of temperature abnormality in closed-loop feedback control;
the central control module is connected with the execution module and the remote control module and is used for receiving and storing crop growth environment parameter data and sending an execution instruction to the execution module through the fed back growth environment parameters;
the execution module is used for receiving the instruction of the central control module and controlling the environment control module to execute;
the remote control module is connected with the display terminal in a remote control way, so that the central controller is connected with the display terminal in a remote control way;
and the display terminal is used for displaying the remote received crop growth environment parameter data and the growth curve, so that the growth condition of the crops can be conveniently monitored remotely in real time.
Specifically, as shown in fig. 1, the acquisition module includes an image acquisition unit and an environmental factor sensor unit, the image acquisition unit is used for acquiring an image of environmental parameters in the growth process of crops, and the environmental factor sensor unit includes: temperature and humidity sensor, light intensity sensor, oxygen content sensor, temperature and humidity sensor are used for real-time supervision crops growing environment's temperature and humidity, and light intensity sensor is used for real-time supervision crops growing environment's illumination intensity, and oxygen content sensor is used for the oxygen content of real-time supervision crops growing environment.
Specifically, as shown in fig. 1, the specific method of the fuzzy control module is as follows: when the extreme value of the duration t of the change times of the temperature change rate occurs, the extreme value is judged as follows:
complete filtering of extremes of short duration but frequent times of t <2.5S can affect system accuracy and crop quality.
Through fuzzy algorithm analysis, the temperature change rate and the factor alpha have great influence, and the following correlation exists:
>＝2.5S<20S T*α(i,j)
>＝20S<30S 0.95T*α(i,j)
the alpha (i, j) algorithm steps are as follows:
assuming that the state j at the moment t+1 only depends on the state i at the previous moment t after the response action of the executing mechanism, the result accords with the Markov probability prediction, namely the decision-making model probability is p (i, j) =p (j|i);
the smooth distribution is obtained through a limited number of iterations, provided that the extremum does not occur at time t+1.
Introducing a temperature change rate factor alpha, p (i) q (i, j) alpha (i, j) =p (j) q (j, i) alpha (j, i) by a fuzzy algorithm processing mechanism
When the extremum occurs at a (j, i) =1,
α(j,i)＝min{p(j)q(j,i)/p(i)q(i,j)，1}
specifically, as shown in fig. 1, the fuse trigger conditions are: the execution times per minute of the same executing mechanism is set as f m ；
When f m >＝f p +f s 1/2.5, triggering a fusing mechanism, disconnecting the system from the fuzzy control subsystem, storing parameters in a knowledge base, prompting a user to automatically enter a default initial mode, and enabling the user to start manual mode control.
Wherein f p Preset value for response times of each minute of actuating mechanism；f s The trend change factor, namely the change times of the temperature change rate;
specifically, as shown in fig. 2, the environmental control module includes a spraying system, a ventilation system, a light regulation system, and a refrigerating and heating system, and is used for controlling the temperature and humidity, the oxygen content and the illumination intensity in the crop growth environment.
Specifically, as shown in fig. 1, the central control module further includes a database, and standard growth parameter characteristics corresponding to each growth stage of the crops are recorded in the database.
In summary, the intelligent production control curve and the big data platform provided in this embodiment monitor the outline data of each growth stage of the crop and the temperature, humidity, illumination intensity and oxygen content data of each growth stage of the crop through the image acquisition unit, and transmit the partial data to the central control module, the central control module transmits the data to the analysis module for data processing, the analysis module receives and extracts the height and the stem outline characteristics of most similar crops in the image acquisition unit, the environmental factor sensor unit acquires the temperature, humidity, illumination intensity and oxygen content of the growth environment of most similar crops in each growth stage, then extracts the height and the stem outline corresponding to each growth stage of the crop stored in the database as standard features, compares the environmental temperature, humidity, illumination intensity and oxygen content corresponding to each growth stage of the crop in the database with the standard features corresponding to each growth stage of the crop, compares the height and the stem outline features of the crop at the current stage with the standard features corresponding to the crop, if the height and the stem outline features of most similar crops simultaneously satisfy the height and the stem outline features of a certain growth stage, then compares the height and the stem outline features of the crop at the certain growth stage with the current crop corresponding to the moisture and the moisture content of the crop corresponding to the current stage, and performs the control according to the information of the humidity and the moisture content of the crop corresponding to the crop at the growth stage, and the moisture content of the crop corresponding to the moisture and the moisture content of the crop corresponding to the growth stage of the crop in the growth stage and the moisture and the crop corresponding to the moisture and the status of the crop outline, the abnormal temperature change rate is processed by a fusing machine and a fuzzy control module through a fusing mechanism and a fuzzy algorithm; the execution unit receives the instruction and controls any one of the spraying system, the ventilation system, the light regulation and control system and the refrigerating and heating system to work, regulates and controls proper temperature and ventilation, ensures proper relative humidity and illumination at the same time, forms closed-loop feedback, creates the environmental conditions most suitable for the growth and development of each stage of crops, reduces the use of pesticide fertilizers, reasonably enhances the land capability, thereby obtaining high-yield and high-quality crops, simultaneously realizing the scientific management of crops combined with agriculture, greatly reducing the management cost and the labor investment, and facilitating the real-time management and digital monitoring of the crops.
The previous description of the embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (5)
1. The intelligent production regulation and control curve and big data platform is characterized by comprising an acquisition module, an analysis module, an environment control module, a fusing machine, a fuzzy control module, a central control module, an execution module, a remote control module and a display terminal;
the acquisition module is connected with the central control module and is used for acquiring the growth environment parameters of each stage of crops and transmitting the acquired environment parameters to the central control module for connection;
the analysis module is connected with the central control module and is used for analyzing the growth environment parameters of crops and feeding back analysis results to the central control module;
the environment control module is connected with the execution module and is used for regulating and controlling the crop growth environment parameters;
the fusing machine is connected with the fuzzy control module and is used for protecting the system when the temperature is abnormal;
the fuzzy control module is connected with the fuse machine and the central control module and is used for processing a fuzzy algorithm of temperature abnormality in closed loop feedback control;
the central control module is connected with the execution module and the remote control module and is used for receiving and storing crop growth environment parameter data and sending an execution instruction to the execution module through the fed back growth environment parameters;
the execution module is used for receiving the instruction of the central control module and controlling the environment control module to execute;
the remote control module is connected with the display terminal in a remote control way, so that the central controller is connected with the display terminal in a remote control way;
the display terminal is used for displaying the remote received crop growth environment parameter data and the growth curve;
the specific method of the fuzzy control module is as follows: when the extreme value of the duration t of the change times of the temperature change rate occurs, the extreme value is judged as follows:
the extreme value complete filtration with short duration time of t <2.5S and frequent times does not affect the accuracy of the system and the quality of crops;
through fuzzy algorithm analysis, the temperature change rate and the factor alpha have great influence, and the following correlation exists:
t > =2.5s <20s temperature change rate is t×α (i, j)
t > = 20s <30s temperature change rate is 0.95t x α (i, j)
The alpha (i, j) algorithm steps are as follows:
assuming that the state j at the moment t+1 depends on the state i at the previous moment t only after the response action of the executing mechanism, the result accords with the Markov probability prediction, namely the decision-making model probability is p (i, j) =p (j|i);
obtaining stable distribution through limited iterations is premised on that extreme values do not appear at time t+1;
introducing a temperature change rate factor alpha, p (i) p (i, j) alpha (i, j) =p (j) p (j, i) alpha (j, i) by a fuzzy algorithm processing mechanism
When the extremum occurs at a (j, i) =1,
α(i,j)＝min{p(j)p(j,i)/p(i)p(i,j)，1}
specifically, the trigger conditions of the fusing machine are as follows: the execution times per minute of the same executing mechanism is set as f m ；
When f m >＝f p +f s 1/2.5, triggering a fusing mechanism, disconnecting the system from the fuzzy control subsystem, storing parameters into a knowledge base, prompting a user to automatically enter a default initial mode, and enabling the user to start manual mode control;
wherein f p Presetting a value for response times of an executing mechanism per minute; f (f) s Is a trend change factor, i.e., the number of changes in temperature change rate.
2. The intelligent production control curve and big data platform of claim 1, wherein the acquisition module comprises an image acquisition unit for acquiring images of environmental parameters during crop growth and an environmental factor sensor unit comprising: temperature and humidity sensor, light intensity sensor, oxygen content sensor, temperature and humidity sensor is used for real-time supervision crops growing environment's temperature and humidity, light intensity sensor is used for real-time supervision crops growing environment's illumination intensity, oxygen content sensor is used for the oxygen content of real-time supervision crops growing environment.
3. The intelligent production control curve and big data platform according to claim 1, wherein the environment control module comprises a spraying system, a ventilation system, a light control system, a refrigerating and heating system, and is used for controlling the temperature and humidity, the oxygen content and the illumination intensity in the crop growth environment.
4. The intelligent production control curve and big data platform according to claim 1, wherein the fusing machine and the fuzzy control module process the abnormal temperature change rate through a fusing mechanism and a fuzzy algorithm.
5. The intelligent production control curve and big data platform of claim 1, wherein the central control module further comprises a database, wherein standard growth parameter characteristics corresponding to each growth stage of the crops are recorded in the database.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103308199A (en) * | 2013-06-03 | 2013-09-18 | 合肥天海电气技术有限公司 | Wireless temperature detecting monitoring system for grid operation equipment based on fuzzy processing |
| CN103503763A (en) * | 2013-09-30 | 2014-01-15 | 陕西旭田光电农业科技有限公司 | Plant growing box control system and control method thereof |
| CN105050383A (en) * | 2013-03-19 | 2015-11-11 | 青岛裕洋电子有限公司 | Controller apparatus for controlling cultivation environment of cultivation crop in plant factory and method therefor |
| CN108919768A (en) * | 2018-08-31 | 2018-11-30 | 北京唐冠天朗科技开发有限公司 | A kind of agricultural management system and method |
| CN110716598A (en) * | 2019-10-30 | 2020-01-21 | 福建清农智慧农业科技有限公司 | Intelligent greenhouse control and management system based on Internet of things |
| CN111652756A (en) * | 2020-07-03 | 2020-09-11 | 张玉红 | Green wisdom green house planting environment monitoring management system |
| CN215177887U (en) * | 2021-04-30 | 2021-12-14 | 廊坊职业技术学院 | Novel intelligent greenhouse environment monitoring device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10677962B2 (en) * | 2015-03-06 | 2020-06-09 | The Climate Corporation | Estimating temperature values at field level based on less granular data |
-
2022
- 2022-06-07 CN CN202210632351.9A patent/CN114967801B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105050383A (en) * | 2013-03-19 | 2015-11-11 | 青岛裕洋电子有限公司 | Controller apparatus for controlling cultivation environment of cultivation crop in plant factory and method therefor |
| CN103308199A (en) * | 2013-06-03 | 2013-09-18 | 合肥天海电气技术有限公司 | Wireless temperature detecting monitoring system for grid operation equipment based on fuzzy processing |
| CN103503763A (en) * | 2013-09-30 | 2014-01-15 | 陕西旭田光电农业科技有限公司 | Plant growing box control system and control method thereof |
| CN108919768A (en) * | 2018-08-31 | 2018-11-30 | 北京唐冠天朗科技开发有限公司 | A kind of agricultural management system and method |
| CN110716598A (en) * | 2019-10-30 | 2020-01-21 | 福建清农智慧农业科技有限公司 | Intelligent greenhouse control and management system based on Internet of things |
| CN111652756A (en) * | 2020-07-03 | 2020-09-11 | 张玉红 | Green wisdom green house planting environment monitoring management system |
| CN215177887U (en) * | 2021-04-30 | 2021-12-14 | 廊坊职业技术学院 | Novel intelligent greenhouse environment monitoring device |
Non-Patent Citations (1)
| Title |
|---|
| 陈红丽 等.《中南大学学报(自然科学版)》.2011,第42卷全文. * |
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