CN204423100U - Strain growth environmental control system selected by a kind of asparagus - Google Patents
Strain growth environmental control system selected by a kind of asparagus Download PDFInfo
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- CN204423100U CN204423100U CN201420539327.1U CN201420539327U CN204423100U CN 204423100 U CN204423100 U CN 204423100U CN 201420539327 U CN201420539327 U CN 201420539327U CN 204423100 U CN204423100 U CN 204423100U
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Abstract
Strain growth environmental control system selected by a kind of asparagus, comprises Neural Network Data processing unit, genetic algorithm data processing unit, data acquisition unit, performance element, prediction and alarm unit and cloud server.Can detect the carbon dioxide in bacterial strain cultivation place and humiture, assessment IAQ (indoor air quality), by data intelligence processing technology, controls new blower fan start and stop, controls central air conditioner, to ensure IAQ (indoor air quality).Visual monitor can be carried out to bacterial strain, and by Neural Network Data processing unit, Intelligent Recognition be carried out to disease and pest omen, give warning in advance, ensure the normal growth of bacterial strain, facilitate operations staff to manage.By the optimization of genetic algorithm data processing unit, when ensureing bacterial strain normal growth, operation hours can be reduced, reducing equipment energy consumption.
Description
Technical field
The utility model relates to bacterium mushroom production technical field, particularly relates to a kind of asparagus and selects strain growth environmental control system.
Background technology
Asparagus selects the requirement of bacterial strain to environmental parameter higher, and a lot of parameter all needs flexible adjustment, is beneficial to the growth of bacterium mushroom.Major influence factors comprises the factors such as temperature, humidity, illumination.But there is the problems such as management level are low, automaticity is low in existing large-scale planting, cause production cost high, benefit is low.Existing technical scheme does not all consider meteorological condition, equipment energy consumption factor, and does not possess disease and pest early warning and recovery prediction function.
Summary of the invention
In order to improve the automatization level of the environmental management of bacterial strain cultivation place and control, reduce bacterial strain cultivation place equipment energy consumption and disease and pest incidence, increase bacterial strain cultivation field benefit, the utility model provides a kind of asparagus to select strain growth environmental control system.
The technical scheme that the utility model adopts is: strain growth environmental control system selected by a kind of asparagus, it is characterized in that: comprise the Neural Network Data processing unit for setting up early warning and energy consumption model, for the genetic algorithm data processing unit of optimization system parameter, for the data acquisition unit of collection site related data, for the carbon dioxide sensor detected the gas concentration lwevel of bacterial strain cultivation place, for the Temperature Humidity Sensor detected the humiture in place, the air quality that the signal detected according to carbon dioxide sensor and Temperature Humidity Sensor calculates bacterial strain cultivation place air quality calculates unit, to the video monitoring apparatus that described bacterial strain cultivation place disease and pest monitors, the graphics processing unit connected with video monitoring apparatus, for detecting the light sensor of intensity of illumination, for calculating the illumination monitoring means of bacterial strain cultivation place illumination total amount, for the energy consumption monitoring unit of acquisition system total energy consumption, for the performance element of adjusting ambient, for regulating the new blower fan of indoor air quality, for regulating the central air conditioner of indoor temperature, for the solar protection devices of regulating illumination, for conditioning chamber humidity humidifier, for predict and report to the police prediction and alarm unit, for predict yield of flammulina velutipes recovery prediction device, for the disease and pest warning device to disease and pest early warning, for obtaining the cloud server of weather forecast and Optimal Control Strategy.
Neural Network Data processing unit is built-in with Neural Network Data analysis software, the input/output relation between each variable and energy consumption is set up by the historical information of each sensing equipment of data acquisition unit acquires, for genetic algorithm data processing unit provides computation model, by the contrast forecast production with historical data, the abnormal conditions of judgment device, and control forecasting alarm unit, prediction yield of flammulina velutipes, to the disease and pest of disease and pest early warning.
Genetic algorithm data processing unit is built-in with Genetic Algorithm Optimized Software, calculates the optimal operating parameter under current environment, and control performance element by iteration optimizing, and constraint condition and the meteorological forecast data of optimization are given by cloud server.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, described Neural Network Data processing unit has 10 input ports, 10 output ports, and can extend to 50 input ports, 50 output ports.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, described genetic algorithm data processing unit has 10 input ports, 10 output ports, and can extend to 50 input ports, 50 output ports.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, described video monitoring apparatus is for being more than or equal to 4.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, the quantity of described light sensor is for being more than or equal to 10.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, the weather data of described cloud server real-time update various places, and provide suitable parameter range of adjustment.
The utility model compared with prior art has the following advantages:
L, can detect the carbon dioxide in bacterial strain cultivation place and humiture, assessment IAQ (indoor air quality), by data intelligence processing technology, controls new blower fan start and stop, controls central air conditioner, to ensure IAQ (indoor air quality).
2, visual monitor can be carried out to bacterial strain, and by Neural Network Data processing unit, Intelligent Recognition be carried out to disease and pest omen, give warning in advance, ensure the normal growth of bacterial strain, facilitate operations staff to manage.
3, by the optimization of genetic algorithm data processing unit, when ensureing bacterial strain normal growth, operation hours can be reduced, reducing equipment energy consumption.
4, information intelligent process can be carried out to the test signal of multiple sensor, improve data reliability and high efficiency.
In sum, the utility model reasonable in design, good reliability, highly sensitive, parameter acquisition are comprehensive, and efficiently solve existing control system parameter acquisition single, operational efficiency is low, high in cost of production problem.
Accompanying drawing explanation
Fig. 1 is schematic diagram of the present utility model.
In figure, 1 Neural Network Data processing unit; 2 genetic algorithm data processing units; 3 data acquisition units; 3-1 carbon dioxide sensor; 3-2 Temperature Humidity Sensor; 3-3 air quality calculates unit; 3-4 video monitoring apparatus; 3-5 graphics processing unit; 3-6 light sensor; 3-7 illumination monitoring means; 3-8 energy consumption monitoring unit; 4 performance elements; The new blower fan of 4-1; 4-2 central air conditioner; 4-3 solar protection devices; 4-4 humidifier; 5 prediction and alarm unit; 5-1 recovery prediction device; 5-2 disease and pest warning device; 6 cloud servers.
Embodiment
As shown in Figure 1, strain growth environmental control system selected by a kind of asparagus, comprises the Neural Network Data processing unit 1 for setting up early warning and energy consumption model, for the genetic algorithm data processing unit 2 of optimization system parameter, for the data acquisition unit 3 of collection site related data, for the carbon dioxide sensor 3-1 detected the gas concentration lwevel of bacterial strain cultivation place, for the Temperature Humidity Sensor 3-2 detected the humiture in place, the air quality that the signal detected according to carbon dioxide sensor and Temperature Humidity Sensor calculates bacterial strain cultivation place air quality calculates unit 3-3, to the video monitoring apparatus 3-4 that described bacterial strain cultivation place disease and pest monitors, the graphics processing unit 3-5 connected with video monitoring apparatus, for detecting the light sensor 3-6 of intensity of illumination, for calculating the illumination monitoring means 3-7 of bacterial strain cultivation place illumination total amount, for the energy consumption monitoring unit 3-8 of acquisition system total energy consumption, for the performance element 4 of adjusting ambient, for regulating the new blower fan 4-1 of indoor air quality, for regulating the central air conditioner 4-2 of indoor temperature, for the solar protection devices 4-3 of regulating illumination, for conditioning chamber humidity humidifier 4-4, for predict and report to the police prediction and alarm unit 5, for predict yield of flammulina velutipes recovery prediction device 5-1, for the disease and pest warning device 5-2 to disease and pest early warning, for obtaining the cloud server 6 of weather forecast and Optimal Control Strategy.
In the present embodiment, data acquisition unit 3 can Real-time Collection gas concentration lwevel, humiture, and calculates unit 3-3 by air quality and calculate real-time air quality indexes; Can also video monitoring apparatus 3-4 collection site video information be passed through, and by graphics processing unit 3-5, significance map be identified as information, e.g., the form of bacterial strain, the insect pest situation such as size and eye bacterium line, mushroom fly, mite class.Video monitoring apparatus is determined according to bacterial strain cultivation place scale, is at least 4; Can also gather quantity of illumination data by light sensor 3-6, and be obtained the information of illumination total amount by illumination monitoring means 3-7, the quantity of light sensor is determined according to bacterial strain cultivation place scale, is at least more than 10; By the total energy consumption data of energy consumption monitoring unit 3-8 acquisition system, comprise the energy consumption summation of new blower fan, central air conditioner, solar protection devices, humidifier.
Neural Network Data processing unit 1 is built-in with Neural Network Data analysis software, the historical information gathering each sensing equipment by data acquisition unit 3 sets up the input/output relation between each variable and energy consumption, for genetic algorithm data processing unit 2 provides computation model, by the contrast forecast production with historical data, the abnormal conditions of judgment device, and control forecasting alarm unit 5, prediction yield of flammulina velutipes, to disease and pest early warning.
Genetic algorithm data processing unit 2 is built-in with Genetic Algorithm Optimized Software, calculates the optimal operating parameter under current environment by iteration optimizing, and controls performance element 4, and constraint condition and the meteorological forecast data of optimization are given by cloud server 6.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, described Neural Network Data processing unit 1 has 10 input ports, 10 output ports, and can extend to 50 input ports, 50 output ports.Centralizing inspection can be carried out to multiple strain culturing field.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, described genetic algorithm data processing unit 2 has 10 input ports, 10 output ports, and can extend to 50 input ports, 50 output ports.Centralized optimization control can be carried out to multiple strain culturing field.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, described video monitoring apparatus 3-4 is for being more than or equal to 4.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, the quantity of described light sensor 3-6 is for being more than or equal to 10.
Select in strain growth environmental control system at above-mentioned a kind of asparagus, the weather data of described cloud server 6 real-time update various places.And provide suitable parameter range of adjustment by remote control center according to geographic position and seasonal conditions.
Claims (6)
1. a strain growth environmental control system selected by asparagus, comprises the Neural Network Data processing unit for setting up early warning and energy consumption model, for the genetic algorithm data processing unit of optimization system parameter, it is characterized in that: described a kind of asparagus choice strain growth environmental control system also comprises the data acquisition unit for collection site related data, for the carbon dioxide sensor detected the gas concentration lwevel of bacterial strain cultivation place, for the Temperature Humidity Sensor detected the humiture in place, the air quality that the signal detected according to carbon dioxide sensor and Temperature Humidity Sensor calculates bacterial strain cultivation place air quality calculates unit, to the video monitoring apparatus that described bacterial strain cultivation place disease and pest monitors, the graphics processing unit connected with video monitoring apparatus, for detecting the light sensor of intensity of illumination, for calculating the illumination monitoring means of bacterial strain cultivation place illumination total amount, for the energy consumption monitoring unit of acquisition system total energy consumption, for the performance element of adjusting ambient, for regulating the new blower fan of indoor air quality, for regulating the central air conditioner of indoor temperature, for the solar protection devices of regulating illumination, for conditioning chamber humidity humidifier, for predict and report to the police prediction and alarm unit, for predict yield of flammulina velutipes recovery prediction device, for the disease and pest warning device to disease and pest early warning, for obtaining the cloud server of weather forecast and Optimal Control Strategy.
2. strain growth environmental control system selected by a kind of asparagus according to claim 1, it is characterized in that: described Neural Network Data processing unit has 10 input ports, 10 output ports, and 50 input ports can be extended to, 50 output ports.
3. strain growth environmental control system selected by a kind of asparagus according to claim 1, it is characterized in that: described genetic algorithm data processing unit has 10 input ports, 10 output ports, and 50 input ports can be extended to, 50 output ports.
4. strain growth environmental control system selected by a kind of asparagus according to claim 1, it is characterized in that: described video monitoring apparatus is for being more than or equal to 4.
5. strain growth environmental control system selected by a kind of asparagus according to claim 1, it is characterized in that: the quantity of described light sensor is for being more than or equal to 10.
6. strain growth environmental control system selected by a kind of asparagus according to claim 1, it is characterized in that: the weather data of described cloud server real-time update various places, and provides suitable parameter range of adjustment.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201420539327.1U CN204423100U (en) | 2014-09-19 | 2014-09-19 | Strain growth environmental control system selected by a kind of asparagus |
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| CN201420539327.1U CN204423100U (en) | 2014-09-19 | 2014-09-19 | Strain growth environmental control system selected by a kind of asparagus |
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| CN204423100U true CN204423100U (en) | 2015-06-24 |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105676806A (en) * | 2015-07-17 | 2016-06-15 | 山东正晨科技股份有限公司 | Environment control system and method thereof |
| CN107044710A (en) * | 2016-12-26 | 2017-08-15 | 深圳达实智能股份有限公司 | Energy-saving control method for central air conditioner and system based on joint intelligent algorithm |
| CN110109193A (en) * | 2019-04-19 | 2019-08-09 | 淮阴工学院 | A kind of eggplant greenhouse temperature intellectualized detection device based on DRNN neural network |
| CN110150034A (en) * | 2019-06-26 | 2019-08-23 | 山东友和菌业有限公司 | The incubator of acupuncture needle mushroom culture is carried out based on optical flow method |
| CN114901066A (en) * | 2020-01-16 | 2022-08-12 | 横河电机株式会社 | Support system and support method |
-
2014
- 2014-09-19 CN CN201420539327.1U patent/CN204423100U/en not_active Expired - Fee Related
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105676806A (en) * | 2015-07-17 | 2016-06-15 | 山东正晨科技股份有限公司 | Environment control system and method thereof |
| CN107044710A (en) * | 2016-12-26 | 2017-08-15 | 深圳达实智能股份有限公司 | Energy-saving control method for central air conditioner and system based on joint intelligent algorithm |
| CN110109193A (en) * | 2019-04-19 | 2019-08-09 | 淮阴工学院 | A kind of eggplant greenhouse temperature intellectualized detection device based on DRNN neural network |
| CN110109193B (en) * | 2019-04-19 | 2021-01-01 | 淮阴工学院 | Intelligent eggplant greenhouse temperature detection device based on DRNN neural network |
| CN110150034A (en) * | 2019-06-26 | 2019-08-23 | 山东友和菌业有限公司 | The incubator of acupuncture needle mushroom culture is carried out based on optical flow method |
| CN114901066A (en) * | 2020-01-16 | 2022-08-12 | 横河电机株式会社 | Support system and support method |
| CN114901066B (en) * | 2020-01-16 | 2024-03-22 | 横河电机株式会社 | Auxiliary system and auxiliary method |
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Granted publication date: 20150624 Termination date: 20160919 |