CN117348648A - Automatic control method and device for sheep hurdle environment - Google Patents
Automatic control method and device for sheep hurdle environment Download PDFInfo
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- 241001494479 Pecora Species 0.000 title claims abstract description 172
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- 238000010438 heat treatment Methods 0.000 claims description 15
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- 238000009395 breeding Methods 0.000 description 1
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- 239000002274 desiccant Substances 0.000 description 1
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Abstract
The invention relates to the field of sheep hurdle environment control, in particular to an automatic sheep hurdle environment control method and device. The method realizes accurate monitoring and regulation of the internal environment of the sheep hurdle through multidimensional data acquisition and intelligent control strategies. First, temperature, humidity and CO 2 The concentration sensor collects sheep hurdle environmental data. Based on these data, control logic calculates a minimum ventilation to ensure that the minimum respiratory requirements and CO of sheep are met 2 And (5) concentration control. Simultaneously, calculate maximum ventilation volume to satisfy summer ventilation cooling demand. Depending on the temperature setting, ventilation strategies of different ventilation levels are implemented, ensuring that the temperature is within a suitable range. In addition, deep learning algorithms are used to monitor and control temperature, humidity and CO in real time 2 Concentration to further optimize environmental conditions. The invention is beneficial to improving the comfort and the production efficiency of the sheep hurdle environment, reducing the energy consumption and the resource waste and being beneficial to the large-scale and intelligent construction of the sheep raising industry.
Description
Technical Field
The invention relates to the field of sheep hurdle environment control, in particular to an automatic sheep hurdle environment control method and device.
Background
The difficulty in raising sheep in a house is the environmental control of the sheep house. The environmental control is poor in summer, which can cause heat stress and even heatstroke death of sheep; the poor environmental control in winter can cause sheep to be ill and grow slowly, and influence the production benefit. At present, the domestic study on the environmental control of the sheep hurdle is less, basically stays at the theoretical level, and has poor feasibility.
For example: the Chinese patent document CN116256020A discloses a sheep house environment monitoring system and method based on big data, which are characterized in that the environment monitoring data of the sheep house and the activity behavior data of sheep are obtained, the environment monitoring data and the activity behavior data of sheep are preprocessed and fused to generate a data set, the sheep activity behavior data and the environment monitoring data are fitted with the law of the sheep activity behavior along with the change of environmental factors by adopting a difference algorithm, a monitoring model of sheep production environment indexes under the influence of single environmental variables is extracted from the sheep activity data and the environment monitoring model, the comprehensive influence of a plurality of environment variables on the sheep activity behavior is analyzed by adopting a curved surface difference algorithm based on the nonlinear relation between the sheep activity behavior and the environment factors, and the important description in the literature is a sheep house environment control monitoring method without environmental control method.
And the following steps: chinese patent document CN111972304a discloses a sheep pen ventilation system and method, in which the relationship between sheep pen temperature and air exhaust is described, but there is no specific control strategy.
Therefore, it is necessary to provide an automatic control method and device for sheep hurdle environment to solve the above problems.
Disclosure of Invention
In order to solve the problems, the invention provides an automatic control method and device for sheep hurdle environment.
In order to achieve the above purpose, the invention adopts the following technical scheme:
in one aspect, an automatic control method for sheep hurdle environment comprises the following steps:
collecting multi-dimensional data of the sheep hurdle, wherein the multi-dimensional data comprises temperature, humidity and CO 2 Concentration;
configuring a sheep hurdle environment controller, and receiving and processing the multidimensional data according to the sheep hurdle environment controller;
automatically controlling the ventilation, cooling and heating equipment according to preset control logic, wherein the control logic comprises the following steps:
selecting the multidimensional data as sheep hurdle environment control parameters;
calculating the minimum ventilation according to the sheep hurdle environment control parameters;
calculating the maximum ventilation quantity;
setting ventilation levels according to the temperature, and realizing ventilation strategies of different ventilation levels;
the temperature, the humidity and the CO are subjected to deep learning algorithm 2 The concentration is monitored and controlled in real time.
Further, the minimum ventilation volume calculates the minimum ventilation volume required by the sheep hurdle according to the ventilation volume required by the minimum breath of the sheep and the number of sheep raised by the sheep hurdle, and the minimum ventilation volume is not lower than the CO of the sheep hurdle 2 The minimum ventilation volume required by the concentration not exceeding the standard is calculated as follows:
wherein Q is min For the minimum ventilation quantity, N is the number of sheep, Y min The ventilation quantity required by the minimum respiration of sheep in winter only,is CO in sheep hurdle 2 Minimum ventilation calculated without exceeding concentration, +.>
Furthermore, the maximum ventilation volume is calculated according to the ventilation volume required by the ventilation and cooling calculation of sheep in summer, and the calculation formula is as follows:
Q max ＝max{N*Y max ，S*V}
wherein Q is max For maximum ventilation, Y max The maximum ventilation quantity required by sheep in summer is provided, S is the sectional area of the sheep hurdle, and V is the summer ventilation wind speed of the sheep hurdle.
Further, the setting of the ventilation level divides the allowed temperature of the sheep hurdle into a plurality of groups according to the temperature increasing rule, and the higher the temperature is, the higher the ventilation level corresponding to the group is, and the higher the ventilation level is, the larger the corresponding ventilation amount is.
Further, the deep learning algorithm is used for controlling the temperature, the humidity and the CO 2 The concentration real-time monitoring and controlling method comprises the following steps:
acquiring the acquired multidimensional data;
performing data cleaning and preprocessing on the multidimensional data, removing abnormal values and smoothing the data;
training the sheep hurdle environmental controller using a deep learning model, the deep learning model comprising a recurrent neural network and a time-series attention model;
training the deep learning model using the labeled training data set;
the trained deep learning model is embedded into the sheep hurdle environmental controller.
Further, the time sequence attention model construction process comprises the following steps:
acquiring the multidimensional data as time series data;
embedding the time series data into a representation space;
adding a cyclic neural network or long-short-time memory network layer to process time sequence data;
establishing a time sequence attention mechanism, comprising the following steps:
calculating the attention score of each historical time step according to the input of the current time step and the output of the historical time step;
using the calculated attention score to weight and sum the output of the historical time step;
generating a predicted value of the time series data according to a time series attention mechanism;
training the time-lapse attention model using the data in the training set;
evaluating the performance of the model using the validation set;
the trained time sequence attention model is embedded into the sheep hurdle environment controller.
Further, the ventilation strategies with different ventilation levels comprise the following steps:
when the temperature is lower than the normal temperature, the ventilation requirements of corresponding ventilation levels are met by controlling the number of fans, the period opening and closing time and the opening degree of the small ventilation windows;
when the temperature reaches normal temperature and the ventilation requirement cannot be met by fully opening the small ventilation window, the ventilation requirement of the corresponding ventilation level is met by controlling the quantity and the period opening and closing time of the fans and the opening of the small ventilation window and the air inlet; the ventilation requirements of corresponding ventilation levels are met by controlling the number of fans, the period opening and closing time and the opening degree of the air inlet;
when the temperature is higher than normal temperature, the quantity of fans and the period opening and closing time are controlled, and meanwhile, the ventilation opening is set to be the maximum opening, so that the ventilation requirement of the corresponding ventilation level is met.
In another aspect, an automatic sheep hurdle environment control device comprises: temperature sensor, humidity sensor and CO 2 A sensor and sheep hurdle environmental controller;
the temperature sensors are used for collecting the temperature of the sheep hurdle, at least two temperature sensors are configured, and the average value of the two temperature sensors is taken when the controller calculates;
the humidity sensor is used for collecting the humidity of the sheep hurdle;
the CO 2 Sensor for collecting CO of sheep hurdle 2 Concentration;
the sheep hurdle environmental controller is used for collecting a temperature sensor, a humidity sensor and CO 2 And the sheep hurdle environment controller also has an alarm function.
Further, the device also comprises a fan, an air inlet, a small ventilation window, a spraying device and a heating device;
the fans are power components of the sheep house ventilation system, and the number of the fans is configured according to the fact that the total air quantity is higher than the maximum ventilation quantity required by the sheep house;
the air inlet is an air inlet device which is matched with a fan in high temperature and transitional seasons;
the small ventilation window is a ventilation device which is used in cooperation with a fan in low-temperature and transitional seasons and is arranged on the side wall of the sheep hurdle;
the spraying device is a sheep hurdle cooling device in summer and high-temperature seasons, and meanwhile, the humidity of the sheep hurdle is increased for the sheep hurdle;
the heating device is a device for heating the sheep hurdle.
The invention has the beneficial effects that:
the invention collects multidimensional data including temperature, humidity and CO 2 The concentration can accurately monitor the environmental condition of the sheep hurdle, and the climate condition in the sheep hurdle can be known in real time.
According to the invention, the sheep hurdle environment controller is configured, and the multidimensional data can be intelligently received, processed and analyzed by combining with the deep learning algorithm, so that the automatic control of the sheep hurdle environment is realized. This helps to improve the efficiency of the cultivation and the comfort of the animals.
The ventilation strategy in the control logic of the invention is calculated to ensure that the minimum ventilation quantity meets the minimum respiratory requirement and CO of sheep 2 Concentration control while providing adequate aeration and cooling in summer. This helps to save energy costs, reduce unnecessary waste of resources, and maintain the air quality in the sheep hurdle.
According to the invention, through accurate environment monitoring and automatic control, a more suitable breeding environment can be created, and the health level and productivity of sheep can be improved.
Drawings
FIG. 1 is a schematic flow chart of an automatic control method for sheep pen environment.
FIG. 2 is a schematic flow chart of control logic in the present invention.
Fig. 3 is a block diagram of an automatic control device for sheep pen environment according to the present invention.
Fig. 4 is a flow chart of a temperature control strategy according to an embodiment of the present invention.
Fig. 5 is a flow chart of a humidity control strategy according to an embodiment of the present invention.
FIG. 6 is a block diagram of CO provided by an embodiment of the present invention 2 A structural flow chart of the concentration control strategy.
Detailed Description
Referring to fig. 1-6, the present invention relates to a method and an apparatus for automatically controlling sheep pen environment.
Example 1
An automatic control method for sheep hurdle environment comprises the following steps:
s1: collecting multi-dimensional data of the sheep hurdle, wherein the multi-dimensional data comprises temperature, humidity and CO 2 Concentration;
s2: configuring a sheep hurdle environment controller, and receiving and processing the multidimensional data according to the sheep hurdle environment controller;
s3: according to a preset control logic, the ventilation, cooling and heating equipment is automatically controlled, and the control logic comprises the following steps:
s31: selecting the multidimensional data as sheep hurdle environment control parameters;
s32: calculating the minimum ventilation quantity according to the sheep hurdle environment control parameters, and ensuring that the minimum breathing requirement and CO of sheep are met 2 Minimum ventilation for concentration control; the minimum ventilation volume is calculated according to the ventilation volume required by the minimum respiration of sheep and the number of sheep raised in the sheep hurdle, and the minimum ventilation volume is not lower than the CO of the sheep hurdle 2 The minimum ventilation volume required by the concentration not exceeding the standard is calculated as follows:
wherein Q is min For the minimum ventilation quantity, N is the number of sheep, Y min The ventilation quantity required by the minimum respiration of sheep in winter only,is CO in sheep hurdle 2 Minimum ventilation calculated without exceeding concentration, +.>
S33: calculating the maximum ventilation quantity to meet the ventilation and cooling requirements in summer; the maximum ventilation volume is calculated according to the ventilation volume required by the ventilation and cooling calculation of sheep in summer, and the calculation formula is as follows:
Q max ＝max{N*Y max ，S*V}
wherein Q is max For maximum ventilation, Y max The maximum ventilation quantity required by sheep in summer is provided, S is the sectional area of the sheep hurdle, and V is the summer ventilation wind speed of the sheep hurdle.
S34: setting ventilation levels according to the temperature, and realizing ventilation strategies of different ventilation levels; the setting of the ventilation level divides the allowed temperature of the sheep hurdle into a plurality of groups according to the temperature increasing rule, and the higher the temperature is, the higher the ventilation level corresponding to the group is, and the higher the ventilation level is, the larger the ventilation amount is. In the indoor temperature rising stage, when the actual temperature of the sheep pen detected by the temperature sensor reaches a temperature range set corresponding to the ventilation level, starting the group of ventilation; in the indoor temperature falling stage, when the temperature detected by the temperature sensor falls to the temperature range set by the corresponding group, the level ventilation is started. When the temperature exceeds the upper limit of the set temperature, the highest-level ventilation is adopted, and meanwhile, the controller sends out high-temperature alarm information to perform spray cooling. When the temperature in the house is lower than the lower limit of the set temperature, the lowest-level ventilation is adopted, and meanwhile, the controller sends out low-temperature alarm information, and the heating equipment is started to heat.
S35: depth-basedLearning algorithm for the temperature, humidity and CO 2 The concentration is monitored and controlled in real time, and the method comprises the following steps:
acquiring the acquired multidimensional data;
performing data cleaning and preprocessing on the multidimensional data, removing abnormal values and smoothing the data;
training the sheep hurdle environmental controller using a time-series attention model;
training the deep learning model using the labeled training data set;
the trained deep learning model is embedded into the sheep hurdle environmental controller.
The time sequence attention model constructing process comprises the following steps:
acquiring the multidimensional data as time series data;
embedding the time series data into a representation space;
adding a cyclic neural network or long-short-time memory network layer to process time sequence data;
establishing a time sequence attention mechanism, comprising the following steps:
calculating the attention score of each historical time step according to the input of the current time step and the output of the historical time step;
using the calculated attention score to weight and sum the output of the historical time step;
generating a predicted value of the time series data according to a time series attention mechanism;
training the time-lapse attention model using the data in the training set;
evaluating the performance of the model using the validation set;
the trained time sequence attention model is embedded into the sheep hurdle environment controller.
In the embodiment, the sheep hurdle environment automatic control method combines a plurality of key steps such as multidimensional data acquisition, control logic presetting, deep learning algorithm and the like so as to realize intelligent monitoring and automatic regulation and control of the sheep hurdle environment. By collecting temperature and humidityAnd CO 2 Concentration and other multidimensional data, and can monitor the environmental conditions inside the sheep hurdle in real time. The method comprises control logic aiming at different seasons and environmental conditions, and ventilation, cooling, heating equipment and the like can be automatically controlled according to specific conditions so as to maintain a proper sheep hurdle environment. This helps to reduce energy consumption and improve cultivation benefits. The ventilation level is adjusted according to the temperature increment rule, which means that under different temperature conditions, the system can automatically adjust the ventilation strategy to ensure that the temperature in the sheep hurdle is always in a proper range. The method involves steps of data cleansing and outlier removal, which helps to ensure the quality of the acquired data and may detect possible problems in advance.
In the method, a deep learning algorithm is adopted to carry out temperature, humidity and CO 2 The concentration is monitored and controlled in real time, so that the method can better adapt to the environmental requirements of different time points. The use of models can improve the accuracy and stability of environmental control, especially under complex weather conditions. The time sequence attention model is introduced, so that time sequence data can be processed, the capability of learning historical data is provided, and the responsiveness and the accuracy to environmental changes are further improved.
Example 2
The automatic sheep hurdle environment control method according to embodiment 1, wherein the control strategy comprises the following steps:
temperature control strategy:
ventilation strategies corresponding to the lowest ventilation level: the controller adopts the lowest ventilation level according to the collected environmental parameters and a preset control strategy, controls the opening quantity of fans and the opening and closing time of each period, and simultaneously sets the lowest opening of a small ventilation window so as to meet the ventilation requirement of the corresponding ventilation level.
In seasons where the temperature is low: the ventilation window is matched with a ventilation strategy of the fan, the controller calculates corresponding ventilation levels according to collected environmental parameters and a preset control strategy, controls the opening quantity of the fan and the opening and closing time of each period, and simultaneously sets the opening of the ventilation window to meet ventilation requirements of corresponding ventilation levels.
In the transition season: when the ventilation small window is fully opened, the ventilation requirement is not met, the ventilation small window and the air inlet are matched in ventilation mode, the controller calculates corresponding ventilation levels according to collected environmental parameters and a preset control strategy, the opening quantity of fans and the opening and closing time of each period are controlled, and meanwhile the opening degrees of the ventilation small window and the air inlet are set to meet the ventilation requirement of the corresponding ventilation levels.
In the season of higher temperature: the ventilation mode that the air inlet is matched with the fan is adopted, the controller calculates corresponding ventilation levels according to collected environmental parameters and a preset control strategy, controls the opening quantity of the fan and the opening and closing time of each period, and simultaneously controls the opening degree of the air inlet so as to meet the ventilation requirements of the corresponding ventilation levels.
Ventilation strategies corresponding to the highest ventilation level: the controller adopts the highest ventilation level according to the collected environmental parameters and a preset control strategy, controls the opening quantity of the fans and the opening and closing time of each period, and simultaneously sets the ventilation opening to be the maximum opening so as to meet the ventilation requirement of the corresponding ventilation level.
Humidity control strategy:
when the temperature parameter is determined, the controller can determine whether the humidity detected by the humidity sensor is in a set range, and when the humidity is lower than the target humidity, the controller sends out low-humidity alarm information and starts spraying to humidify; when the humidity exceeds the target humidity, a high humidity alarm is sent out, and if spraying is running at the moment, spraying is stopped; if the weather is extremely high in humidity, the desiccant can be sprayed manually to dehumidify until the alarm is eliminated.
When the humidity of the sheep hurdle exceeds the standard, the highest level ventilation is adopted, and spraying is stopped until all parameters are restored to be within the target range, and the situation occurs in extreme weather.
CO 2 Concentration control strategy:
when the temperature and humidity parameters are determined, the controller can determine the CO 2 CO detected by the sensor 2 Whether the concentration is within the set range. When CO 2 When the concentration exceeds the standard, the controller can send out alarm information and simultaneously performAnd judging the ventilation level, wherein when the ventilation level is at the highest ventilation level, the current ventilation level is still adopted, and when the ventilation level is not at the highest ventilation level, the ventilation level is increased by one step until the alarm is eliminated, and the original ventilation level is recovered.
Control strategy with multiple parameters not in target range:
when the temperature and humidity of the sheep hurdle exceed the standard, the highest-level ventilation is adopted, and spraying is stopped until all parameters are restored to be within the target range, and the situation occurs in extreme weather.
When CO 2 When the concentration exceeds the standard, the controller can send out alarm information and judge the ventilation level at the same time, when the ventilation level is at the highest ventilation level, the current ventilation level is still adopted, and when the ventilation level is not at the highest ventilation level, the ventilation level is increased by one level until the alarm is eliminated, and the original ventilation level is recovered.
In this embodiment, the control strategy employs different ventilation strategies according to different seasons and temperature conditions, including a lowest ventilation level, a coordinated use of ventilation windows and air intakes, and a highest ventilation level. The differential control can meet ventilation requirements under different environmental conditions more finely, and provides a more comfortable and suitable living environment. By monitoring humidity, when the humidity exceeds a target range, the system can automatically trigger spraying or dehumidifying operation to maintain a proper humidity level, which is helpful for improving the stability of the cultivation conditions. By monitoring CO 2 And once the concentration exceeds the set range, measures are taken to upgrade the ventilation level so as to ensure that the air quality meets the requirements of sheep. This helps to reduce CO 2 The concentration is a potential hazard to sheep health. Exceeding or CO at the same time of temperature and humidity 2 When the concentration exceeds the standard, the system can take emergency measures, such as adopting the highest ventilation level, and stopping spraying so as to quickly restore the environment parameters to the target range and ensure the safety and comfort of sheep. The system can send out alarm information to prompt an operator that an abnormal situation needs to be processed. This helps to improve the security and monitoring efficiency of the farm, while reducing the need for manual inspection.
Example 3
The automatic sheep hurdle environment control method according to embodiment 1, wherein the automatic sheep hurdle environment control device comprises: temperature sensor, humidity sensor and CO 2 A sensor and sheep hurdle environmental controller;
the temperature sensors are used for collecting the temperature of the sheep hurdle, at least 2 temperature sensors are configured, and the average value of the 2 temperature sensors is taken when the controller calculates;
the humidity sensor is used for collecting the humidity of the sheep hurdle;
the CO 2 Sensor for collecting CO of sheep hurdle 2 Concentration;
the sheep hurdle environment controller is used for collecting a temperature sensor, a humidity sensor and CO 2 The sheep hurdle environmental parameter that the sensor gathered to according to preset control logic automatic control ventilation, cooling, firing equipment, simultaneously sheep hurdle environmental controller still has alarming function.
The device also comprises a fan, an air inlet, a small ventilation window, a spraying device and a heating device;
the fans are power components of the sheep house ventilation system, and the number of the fans is configured according to the fact that the total air quantity is not lower than the maximum ventilation quantity required by the sheep house;
the air inlet is an air inlet device which is higher in temperature and matched with the fan in excessive seasons;
the small ventilation window is a ventilation device which is low in temperature and matched with a fan in excessive seasons and is arranged on the side wall of the sheep hurdle;
the spraying device is a sheep hurdle cooling device in summer in high-temperature seasons, and meanwhile, the humidity of the sheep hurdle can be increased when the humidity of the sheep hurdle is low;
the heating device is used for heating the sheep hurdle in winter when the temperature of the sheep hurdle is low.
In the present embodiment, the apparatus is configured with a temperature sensor, a humidity sensor, and CO 2 The sensor can collect multidimensional environmental data in the sheep hurdle in real time, including temperature, humidity and CO 2 The concentration improves the accuracy of monitoring the environment by comprehensively utilizing the data of a plurality of sensors. The device can monitor not onlyAnd the environmental parameters can be measured, and the fan, the air inlet, the ventilation small window, the spraying device and the heating device can be automatically controlled according to preset control logic. This helps to maintain temperature, humidity and CO within the sheep hurdle 2 The concentration is in a suitable range, providing comfortable living conditions. By configuring the blower, the air inlet and the ventilation window, the device can implement different ventilation strategies under different seasons and temperature conditions, including the lowest ventilation level, the cooperative use of the ventilation window and the air inlet, and the highest ventilation level. Such dynamic ventilation adjustment helps to save energy and provide optimal ventilation. By configuring the blower, the air inlet and the ventilation window, the device can implement different ventilation strategies under different seasons and temperature conditions, including the lowest ventilation level, the cooperative use of the ventilation window and the air inlet, and the highest ventilation level. Such dynamic ventilation adjustment helps to save energy and provide optimal ventilation. Through intelligent control, the device can save energy and water resources, reduce operation cost, improve cultivation efficiency simultaneously, help sustainable cultivation operation.
The above embodiments are merely illustrative of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention, and various modifications and improvements made by those skilled in the art to the technical solution of the present invention should fall within the scope of protection defined by the claims of the present invention without departing from the spirit of the design of the present invention.
Claims (9)
1. An automatic control method for sheep hurdle environment is characterized by comprising the following steps:
collecting multi-dimensional data of the sheep hurdle, wherein the multi-dimensional data comprises temperature, humidity and CO 2 Concentration;
configuring a sheep hurdle environment controller, and receiving and processing the multidimensional data according to the sheep hurdle environment controller;
automatically controlling the ventilation, cooling and heating equipment according to preset control logic, wherein the control logic comprises the following steps:
selecting the multidimensional data as sheep hurdle environment control parameters;
calculating the minimum ventilation according to the sheep hurdle environment control parameters;
calculating the maximum ventilation quantity;
setting ventilation levels according to the temperature, and realizing ventilation strategies of different ventilation levels;
the temperature, the humidity and the CO are subjected to deep learning algorithm 2 The concentration is monitored and controlled in real time.
2. The automatic sheep hurdle environment control method according to claim 1, wherein the minimum ventilation volume is calculated according to the ventilation volume required by the minimum breath of sheep and the number of sheep raised in the sheep hurdle, and the calculation formula is as follows:
Q min ＝min{N*Y min ，Q co2 }
wherein Q is min For the minimum ventilation quantity, N is the number of sheep, Y min The ventilation quantity required by the minimum respiration of sheep in winter only,is CO in sheep hurdle 2 Minimum ventilation calculated without exceeding concentration, +.>
3. The automatic control method for sheep hurdle environment according to claim 1, wherein the maximum ventilation volume is calculated according to the requirement of ventilation and cooling of sheep in summer, and the calculation formula is as follows:
Q max ＝max{N*Y max ，S*V}
wherein Q is max For maximum ventilation, Y max The maximum ventilation quantity required by sheep in summer is provided, S is the sectional area of the sheep hurdle, and V is the summer ventilation wind speed of the sheep hurdle.
4. The automatic control method for the sheep hurdle environment according to claim 1, wherein the setting of the ventilation level divides the allowed temperature of the sheep hurdle into a plurality of groups according to a temperature increasing rule, and the higher the temperature is, the higher the ventilation level is, and the higher the ventilation level is, the larger the ventilation amount is.
5. The method for automatically controlling the environment of a sheep pen according to claim 1, wherein the temperature, humidity and CO are controlled based on a deep learning algorithm 2 The concentration real-time monitoring and controlling method comprises the following steps:
acquiring the acquired multidimensional data;
performing data cleaning and preprocessing on the multidimensional data, removing abnormal values and smoothing the data;
training the sheep hurdle environmental controller using a deep learning model, the deep learning model comprising a recurrent neural network and a time-series attention model;
training the deep learning model using the labeled training data set;
the trained deep learning model is embedded into the sheep hurdle environmental controller.
6. The automatic sheep hurdle environment control method according to claim 5, wherein the time sequence attention model construction process comprises the following steps:
acquiring the multidimensional data as time series data;
embedding the time series data into a representation space;
adding a cyclic neural network or long-short-time memory network layer to process time sequence data;
establishing a time sequence attention mechanism, comprising the following steps:
calculating the attention score of each historical time step according to the input of the current time step and the output of the historical time step;
using the calculated attention score to weight and sum the output of the historical time step;
generating a predicted value of the time series data according to a time series attention mechanism;
training the time-lapse attention model using the data in the training set;
evaluating the performance of the model using the validation set;
the trained time sequence attention model is embedded into the sheep hurdle environment controller.
7. The method for automatically controlling the environment of a sheep pen according to claim 1, wherein the ventilation strategies with different ventilation levels comprise the following steps:
when the temperature is lower than the normal temperature, the ventilation requirements of corresponding ventilation levels are met by controlling the number of fans, the period opening and closing time and the opening degree of the small ventilation windows;
when the temperature reaches normal temperature and the ventilation requirement cannot be met by fully opening the small ventilation window, the ventilation requirement of the corresponding ventilation level is met by controlling the quantity and the period opening and closing time of the fans and the opening of the small ventilation window and the air inlet; the ventilation requirements of corresponding ventilation levels are met by controlling the number of fans, the period opening and closing time and the opening degree of the air inlet;
when the temperature is higher than normal temperature, the quantity of fans and the period opening and closing time are controlled, and meanwhile, the ventilation opening is set to be the maximum opening, so that the ventilation requirement of the corresponding ventilation level is met.
8. An automatic control device for sheep hurdle environment, characterized in that the device is applied to an automatic control method for sheep hurdle environment according to any one of claims 1-7, comprising: temperature sensor, humidity sensor and CO 2 A sensor and sheep hurdle environmental controller;
the temperature sensors are used for collecting the temperature of the sheep hurdle, at least two temperature sensors are configured, and the average value of the two temperature sensors is taken when the controller calculates;
the humidity sensor is used for collecting the humidity of the sheep hurdle;
the CO 2 Sensor for collecting CO of sheep hurdle 2 Concentration;
the sheep hurdle environment controller is used for collecting temperature sensors and humidityDegree sensor and CO 2 And the sheep hurdle environment controller also has an alarm function.
9. The automatic sheep hurdle environment control device of claim 8, further comprising a fan, an air inlet, a ventilation window, a spraying device and a heating device;
the fans are power components of the sheep house ventilation system, and the number of the fans is configured according to the fact that the total air quantity is higher than the maximum ventilation quantity required by the sheep house;
the air inlet is an air inlet device which is matched with a fan in high temperature and transitional seasons;
the small ventilation window is a ventilation device which is used in cooperation with a fan in low-temperature and transitional seasons and is arranged on the side wall of the sheep hurdle;
the spraying device is a sheep hurdle cooling device in summer and high-temperature seasons, and meanwhile, the humidity of the sheep hurdle is increased for the sheep hurdle;
the heating device is a device for heating the sheep hurdle.
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