Environmental parameter control method, system and storage medium for ultra-high double-row rotating rack

Abstract

The present application relates to the technical field of laboratory environmental parameter control, and discloses an environmental parameter control method, system and storage medium for an ultra-high double-row rotating rack. The method collects ammonia concentration data and calculates the average concentration; determines the difference between the average concentration and a preset reference value, and uses a first ventilation algorithm to calculate first ventilation data; collects humidity data and calculates the average humidity; determines the difference between the humidity average and a preset reference value, and uses a second ventilation algorithm to calculate second ventilation data; collects temperature data and calculates the average temperature; determines the difference between the temperature average and a preset reference value, and uses a third ventilation algorithm to calculate third ventilation data; combines the first, second and third ventilation data, and calculates the final fourth ventilation data through a fourth ventilation algorithm; and positively correlates the ventilation fan speed and ventilation duration according to the fourth ventilation data. The present application improves the culture effect of animals in ultra-high double-row rotating racks.

Description

Technical Field

[0001] The present application relates to the technical field of laboratory environmental parameter control, and in particular to an environmental parameter control method, system and storage medium of an ultra-high double-row rotating rack. Background Art

[0002] In some animal laboratories, animals need to be cultured to a certain extent, so special culture tools are needed, such as incubators. The size of the incubator is related to the size of the animal. The larger the animal, the larger the incubator, and the smaller the animal, the smaller the incubator. For small animals, increasing the placement density of incubators is conducive to improving the animal culture efficiency.

[0003] In the prior art, reference Figure 2 There is an ultra-high double-row co-directional cage box rotating device, which includes a main frame, a water supply pipe, a return water pipe, a plurality of cage boxes, and a plurality of horizontal hanging rods; the main frame is provided with two pulley groups arranged symmetrically on the left and right, and each pulley group consists of a transmission belt and two pulleys; the hanging rods are arranged at intervals along the transmission belt, and the left and right ends of each hanging rod are respectively fixed on the transmission belts on the left and right sides, and a cage frame is hung on each hanging rod, and the cage frame is provided with a plurality of cage grids, and the cage boxes are respectively installed on each cage grid; a drinking water manifold is fixed on each cage frame, and a plurality of drinking water nozzles are provided on the drinking water manifold, and the drinking water manifolds on each cage frame are interconnected through hoses, one of the drinking water manifolds is connected to the water supply pipe through a hose, and another drinking water manifold is connected to the return water pipe through a hose.

[0004] However, the existing devices do not control the environmental parameters in the culture room, especially the ventilation and temperature and humidity. Animals will produce some excrement during the culture process, thereby reducing the culture effect of the culture room. Therefore, a method for controlling the environmental parameters in the culture room is needed. Summary of the invention

[0005] In order to improve the effect of animal cultivation in an ultra-high double-row rotating rack, the present application provides an environmental parameter control method, system and storage medium for an ultra-high double-row rotating rack.

[0006] In a first aspect, the present application provides an environmental parameter control method for an ultra-high double-row rotating frame, which adopts the following technical solution:

[0007] A method for controlling environmental parameters of an ultra-high double-row rotating frame comprises the following steps:

[0008] Acquire multiple ammonia concentration data based on multiple ammonia sensors on the rotating frame;

[0009] Calculate the average ammonia data according to the plurality of ammonia concentration data;

[0010] Calculating an ammonia difference between the ammonia average data and a preset ammonia reference data;

[0011] The first ventilation data is calculated by a preset first ventilation algorithm according to the ammonia difference;

[0012] Acquiring a plurality of humidity data based on humidity sensors installed in a plurality of incubators;

[0013] Calculate the average humidity data according to the plurality of humidity data;

[0014] Calculating the humidity difference between the average humidity data and preset humidity reference data;

[0015] The second ventilation data is calculated by a preset second ventilation algorithm according to the humidity difference;

[0016] Acquire a plurality of temperature data based on temperature sensors installed in a plurality of incubators;

[0017] Calculate average temperature data according to the plurality of temperature data;

[0018] Calculating the temperature difference between the average temperature data and the preset temperature reference data;

[0019] Calculating third ventilation data according to the temperature difference using a preset third ventilation algorithm;

[0020] Obtaining fourth ventilation data by using a preset fourth ventilation algorithm according to the first ventilation data, the second ventilation data and the third ventilation data;

[0021] The rotation speed of the ventilation fan is adjusted according to the fourth ventilation data and continued for the set ventilation time. The larger the fourth ventilation data is, the faster the rotation speed is, and the smaller the fourth ventilation data is, the slower the rotation speed is.

[0022] By adopting the above technical solutions, through the comprehensive control of environmental parameters such as ammonia concentration, humidity and temperature, it is possible to ensure that animals grow and reproduce in a good environment. Through the comprehensive use of multiple sensors and algorithms, key environmental parameters such as ammonia concentration, humidity and temperature can be fully and accurately controlled. Using average data and difference calculations, combined with preset reference data, the ventilation volume can be accurately adjusted to meet the needs of animal growth and reproduction. The algorithm automatically calculates ventilation data and adjusts the fan speed, realizing the automatic control of environmental parameters and reducing the complexity and error of manual intervention. By optimizing the algorithm, sensor layout and fan control strategy, the reliability and stability of the system are improved, ensuring the continuous stability of the animal growth environment.

[0023] Optionally, the method further comprises the following steps:

[0024] Calculating first humidification intervention data and first drying intervention data according to the temperature difference;

[0025] Calculating second humidification intervention data and second drying intervention data according to the humidity difference;

[0026] Calculating humidification data according to the first humidification intervention data and the second humidification intervention data;

[0027] Calculate drying data according to the first drying intervention data and the second drying intervention data;

[0028] adjusting the moisture output of the humidifier according to the humidification data, wherein the larger the humidification data is, the larger the moisture output is, and the smaller the humidification data is, the smaller the moisture output is;

[0029] The output power of the dryer is adjusted according to the drying data. The larger the drying data is, the larger the output power is, and the smaller the drying data is, the smaller the output power is.

[0030] By adopting the above technical solutions, by comprehensively considering temperature, humidity and their impact on humidification and drying requirements, it is possible to ensure that animals grow and reproduce in a more suitable environment. By adding humidification and drying intervention steps, this method achieves more comprehensive and precise regulation in environmental parameter control, which helps to improve animal growth quality, enhance system flexibility, save energy and reduce consumption, and improve system reliability.

[0031] Optionally, the method further comprises the following steps:

[0032] Calculating uniformity of the plurality of ammonia concentration data as a first uniformity, the closer the plurality of ammonia concentration data are, the higher the value of the first uniformity is, and the greater the difference between the plurality of ammonia concentration data is, the lower the value of the first uniformity is;

[0033] If the first uniformity is lower than a preset first reference uniformity, extending and updating the ventilation time;

[0034] If the first uniformity is higher than the first reference uniformity, and the ammonia difference is less than a preset ammonia reference difference, the ventilation time is shortened and updated.

[0035] By adopting the above technical solution and adding the steps of calculating the uniformity of ammonia concentration and adjusting the ventilation time according to it, the method achieves more comprehensive and precise regulation in environmental parameter control. It not only helps to improve the stability and uniformity of the animal growth environment, but also significantly reduces operating costs and improves the intelligence level and reliability of the system.

[0036] Optionally, the method further comprises the following steps:

[0037] If the first uniformity is lower than the first reference uniformity, the uneven center positions of the multiple ammonia concentration data on the cage are calculated, and the distance between the uneven center position and the ventilation fan is calculated as the uneven ventilation distance; if the uneven ventilation distance is greater than the preset reference distance value, the extension amplitude of the ventilation time is increased, wherein the larger the uneven ventilation distance, the larger the extension amplitude, and the smaller the uneven ventilation distance, the smaller the extension amplitude.

[0038] By adopting the above technical solution, the uniformity of ammonia concentration in the cage area can be significantly improved, while achieving energy-saving, efficient, automated and intelligent ventilation control.

[0039] Optionally, the method further comprises the following steps:

[0040] Calculating uniformity of the plurality of humidity data as a second uniformity, wherein the closer the plurality of humidity data are, the higher the value of the second uniformity, and the greater the difference between the plurality of humidity data is, the lower the value of the second uniformity;

[0041] If the second uniformity is lower than a preset second reference uniformity, and the humidity difference is less than a preset humidity reference difference, extending and updating the ventilation time;

[0042] If the second uniformity is higher than the second reference uniformity, and the humidity difference is greater than a preset humidity reference difference, the moisture output is reduced and updated, and the ventilation time is extended and updated.

[0043] By adopting the above technical solutions, humidity can be made easier to balance, thereby significantly improving the accuracy of humidity control, optimizing energy utilization, enhancing user experience, and enhancing the intelligence and automation level of the system.

[0044] Optionally, the method further comprises the following steps:

[0045] Calculating uniformity of the plurality of temperature data as a third uniformity, wherein the closer the plurality of temperature data are, the higher the value of the third uniformity, and the greater the difference between the plurality of temperature data is, the lower the value of the third uniformity;

[0046] If the third uniformity is lower than a preset third reference uniformity, and the temperature difference is smaller than a preset temperature reference difference, reducing and updating the output power;

[0047] If the third uniformity is higher than the third reference uniformity, and the temperature difference is greater than a preset temperature reference difference, the output power is amplified and updated, and the ventilation time is extended and updated.

[0048] By adopting the above technical solutions, humidity can be easier to balance, which can significantly improve the accuracy of temperature control, optimize energy efficiency and equipment life, enhance the comprehensive control capabilities of the system, and improve user experience and comfort.

[0049] Optionally, the method further comprises the following steps:

[0050] If the third uniformity is lower than the third reference uniformity, the uneven center positions of the multiple temperature data on the cage are calculated, and the distance between the uneven center position and the ventilation fan is calculated as the uneven ventilation distance; the extension amplitude of the ventilation time is adjusted according to the uneven ventilation distance, wherein the larger the uneven ventilation distance, the larger the extension amplitude, and the smaller the uneven ventilation distance, the smaller the extension amplitude.

[0051] By adopting the above technical solution, when the third uniformity is lower than the third reference uniformity, it indicates that the temperature distribution on the cage is uneven. By calculating the distance between the uneven center position and the ventilation fan (uneven ventilation distance), the system can more accurately identify the specific area with uneven temperature. By adjusting the extension of the ventilation time according to the uneven ventilation distance, targeted regulation of the temperature uneven area can be achieved. This regulation method is more accurate and efficient, and helps to quickly improve the uneven temperature distribution.

[0052] Optionally, the method further comprises the following steps:

[0053] Acquiring distance data between the staff and the cage;

[0054] Adjusting the rotation speed of the cage according to the distance data, wherein the larger the distance data is, the faster the rotation speed is, and the smaller the distance data is, the slower the rotation speed is;

[0055] The fan speed of the ventilation fan is adjusted according to the distance data. The larger the distance data is, the faster the fan speed is, and the smaller the distance data is, the slower the fan speed is.

[0056] By adopting the above technical solution, the distance data between the staff and the cage is obtained, and the rotation speed of the cage and the fan speed of the ventilation fan are adjusted accordingly, so that the system can be dynamically adjusted according to the actual position of the personnel; work efficiency and personnel comfort are improved; the cage rotation speed and fan speed are intelligently adjusted according to the distance data, which helps to avoid unnecessary energy consumption and has energy-saving effects; and the intelligence level of the system and the overall quality of the working environment are improved.

[0057] In the second aspect, the present application provides an environmental parameter control system for an ultra-high double-row rotating frame, which adopts the following technical solution:

[0058] An environmental parameter control system for an ultra-high double-row rotating rack comprises a processor, wherein the processor executes the steps of the environmental parameter control method for an ultra-high double-row rotating rack as described in any one of the above.

[0059] In a third aspect, the present application provides a storage medium, which adopts the following technical solution:

[0060] A storage medium stores a program, and when the program is executed by a processor, the steps of the environmental parameter control method of the ultra-high double-row rotating rack described in any one of the above are implemented.

[0061] In summary, the present application includes at least one of the following beneficial technical effects:

[0062] By comprehensively considering the uniformity of temperature, humidity and ammonia concentration, and intelligently adjusting the rotation speed of the cage, the speed of the ventilation fan and the ventilation time, the present application realizes comprehensive and precise control of the environment inside the cage. It not only improves the stability and comfort of the environment, but also helps to protect the materials from the influence of adverse environmental factors.

[0063] This application achieves the goal of meeting environmental requirements while minimizing energy consumption by intelligently adjusting system parameters such as cage rotation speed, fan speed and ventilation duration. This highly efficient and energy-saving control method helps reduce operating costs and improve overall economic benefits.

[0064] By dynamically adjusting system parameters based on the distance data between the worker and the cage, this application creates a more comfortable, healthy and safe working environment for the worker, which not only improves the user experience, but also helps to improve work efficiency and productivity.

[0065] This application introduces a variety of sensors and intelligent algorithms to achieve real-time monitoring and intelligent control of the environment. It not only improves the accuracy and efficiency of control, but also enhances the adaptability and flexibility of the system, enabling it to better cope with various complex environments and changes in demand. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a step diagram of the environmental parameter control method of the super-high double-row rotating rack.

[0067] Figure 2 It is a structural side view of the super-high double-row rotating frame.

[0068] Figure 3 This is a step chart for adjusting the moisture output of the humidifier and the output power of the dryer.

[0069] Figure 4 It is a step chart for adjusting and updating the ventilation time according to the uniformity of multiple ammonia concentration data.

[0070] Figure 5 It is a method for adjusting the extension range of ventilation time.

[0071] Figure 6 It is a step chart for adjusting the moisture output and ventilation time according to the uniformity of multiple humidity data. DETAILED DESCRIPTION

[0072] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings.

[0073] In the description of this specification, the description with reference to the terms "certain embodiments", "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0074] The present application embodiment discloses an environmental parameter control method for an ultra-high double-row rotating frame, referring to Figure 1 and Figure 2 , including the following steps:

[0075] Acquire multiple ammonia concentration data based on multiple ammonia sensors on the rotating frame;

[0076] Calculate the average ammonia data according to the multiple ammonia concentration data;

[0077] Calculating the ammonia difference between the average ammonia data and the preset ammonia reference data;

[0078] The first ventilation data is calculated according to the ammonia difference through a preset first ventilation algorithm.

[0079] For example, five ammonia sensors are installed on the rotating rack, located in different positions. The data collected by the sensors are: 0.5ppm, 0.6ppm, 0.7ppm, 0.4ppm, 0.6ppm. Then, the average ammonia concentration = (0.5+0.6+0.7+0.4+0.6) / 5=0.56ppm. The preset ammonia reference value is 0.61ppm, and the ammonia difference = 0.61-0.56=0.05ppm. According to the first ventilation algorithm, if the ammonia concentration is higher than the reference value, the ventilation volume needs to be increased. It is assumed that every 0.01ppm difference corresponds to an increase of 2% in ventilation volume; the first ventilation data calculated is an increase of 10% in ventilation volume.

[0080] Acquiring a plurality of humidity data based on humidity sensors installed in a plurality of incubators;

[0081] The average humidity data is calculated based on multiple humidity data;

[0082] Calculate the humidity difference between the average humidity data and the preset humidity reference data;

[0083] The second ventilation data is calculated based on the humidity difference using a preset second ventilation algorithm.

[0084] For example, a humidity sensor is installed in each of the five incubators. The humidity data are: 45%, 50%, 48%, 52%, and 47%. The average humidity value = (45+50+48+52+47) / 5 = 49%. The preset humidity reference value is 50%, and the humidity difference value = 50-49 = 1%. According to the second ventilation algorithm, if the humidity is lower than the reference value, the humidity needs to be increased. Assuming that every 1% difference corresponds to a 2% increase in ventilation volume; the second ventilation data calculated is a 2% increase in ventilation volume.

[0085] Acquire a plurality of temperature data based on temperature sensors installed in a plurality of incubators;

[0086] Calculate the average temperature data based on multiple temperature data;

[0087] Calculate the temperature difference between the average temperature data and the preset temperature reference data;

[0088] The third ventilation data is calculated according to the temperature difference through a preset third ventilation algorithm.

[0089] For example, a temperature sensor is installed in each of the five incubators. The temperature data are: 22°C, 24°C, 23°C, 21°C, and 23°C. The average temperature = (22+24+23+21+23) / 5 = 22.8°C. The preset temperature reference value is 23°C, and the temperature difference = 23-22.8 = 0.2°C. According to the third ventilation algorithm, if the temperature is lower than the reference value, the temperature needs to be increased. Assuming that every 0.1°C difference corresponds to a 2% increase in ventilation volume; the third ventilation data is calculated to be a 4% increase in ventilation volume.

[0090] The fourth ventilation data is obtained by using a preset fourth ventilation algorithm according to the first ventilation data, the second ventilation data and the third ventilation data. The fourth ventilation algorithm is a weighted average algorithm, and assuming that each weight is 1 / 3, the weighted fourth ventilation data is 5.33%.

[0091] The rotation speed of the ventilation fan is adjusted according to the fourth ventilation data and the set ventilation time is continued. The larger the fourth ventilation data is, the faster the rotation speed is, the smaller the fourth ventilation data is, and the slower the rotation speed is.

[0092] Assuming the fan's base speed is 1000 RPM (revolutions per minute), a simple regulation rule can be set, such as:

[0093] For every 1% increase in the fourth ventilation data, the fan speed increases by 50RPM;

[0094] For every 1% decrease in the fourth ventilation data, the fan speed decreases by 50RPM.

[0095] The air delivered by the ventilation fan is clean gas with preset temperature and humidity.

[0096] By comprehensively controlling environmental parameters such as ammonia concentration, humidity and temperature, animals can be ensured to grow and reproduce in a good environment. Through the comprehensive use of multiple sensors and algorithms, key environmental parameters such as ammonia concentration, humidity and temperature can be fully and accurately controlled. Using average data and difference calculations, combined with preset reference data, the ventilation volume can be accurately adjusted to meet the needs of animal growth and reproduction. The algorithm automatically calculates ventilation data and adjusts the fan speed, realizing the automatic control of environmental parameters and reducing the complexity and error of manual intervention. By optimizing the algorithm, sensor layout and fan control strategy, the reliability and stability of the system are improved, ensuring the continuous stability of the animal growth environment.

[0097] Reference Figure 3 , the method further comprises the following steps:

[0098] The first humidification intervention data and the first drying intervention data are calculated based on the temperature difference. Assume that every 0.1°C temperature difference corresponds to: humidification data increases by 1%; drying data decreases by 1%. When the temperature difference = 23-22.8 = 0.2°C, the first humidification intervention data: 0.2×1%=0.2%. The first drying intervention data: -0.2×1%=-0.2%.

[0099] The second humidification intervention data and the second drying intervention data are calculated based on the humidity difference; assuming that every 1% humidity difference corresponds to: humidification data increases by 2%; drying data decreases by 2%. When the humidity difference = 50-49 = 1%, the second humidification intervention data: 1×2%=2%. The second drying intervention data: -1×2%=-2%.

[0100] The humidification data is calculated according to the first humidification intervention data and the second humidification intervention data; the humidification data = the first humidification intervention data + the second humidification intervention data = 0.2% + 2% = 2.2%; the first humidification intervention data + the second humidification intervention data = 0.2% + 2% = 2.2%.

[0101] The drying data is calculated according to the first drying intervention data and the second drying intervention data; the drying data=the first drying intervention data+the second drying intervention data=-0.2%+(-2%)=-2.2%.

[0102] Adjust the moisture output of the humidifier according to the humidification data. The larger the humidification data, the greater the moisture output, and the smaller the humidification data, the smaller the moisture output. Assuming that the basic moisture output of the humidifier is 100 units, the output increases by 5 units for every 1% increase in humidification data. The output of the humidifier after adjustment: 100+(2.2%×5)=100+1.1=101.1 units.

[0103] Adjust the output power of the dryer according to the drying data. The larger the drying data, the larger the output power, and the smaller the drying data, the smaller the output power. Assuming that the basic output power of the dryer is 50 units, the output power increases by 10 units for every 1% reduction in the drying data. The output power of the dryer after adjustment: 50 + (-2.2% × 10) = 47.8 units.

[0104] By comprehensively considering temperature, humidity and their impact on humidification and drying requirements, it is possible to ensure that animals grow and reproduce in a more suitable environment. By adding humidification and drying intervention steps, this method achieves more comprehensive and precise regulation in environmental parameter control, which helps to improve animal growth quality, enhance system flexibility, save energy and reduce consumption, and improve system reliability.

[0105] Reference Figure 4 , the method further comprises the following steps:

[0106] The uniformity of multiple ammonia concentration data is calculated as the first uniformity. The closer the multiple ammonia concentration data are, the higher the value of the first uniformity is. The greater the difference between the multiple ammonia concentration data is, the lower the value of the first uniformity is. Assume that the ammonia sensor data is: 0.5ppm, 0.6ppm, 0.7ppm, 0.4ppm, 0.6ppm. Then, the average ammonia concentration is: 0.56ppm; variance: 0.012; standard deviation ≈ 0.1095.

[0107] The calculation formula of the first uniformity is: first uniformity = 1-standard deviation / (maximum value-minimum value).

[0108] The maximum value is 0.7ppm, the minimum value is 0.4ppm, and the first uniformity is ≈0.635.

[0109] If the first uniformity is lower than the preset first reference uniformity, the ventilation time is extended and updated. Assume that the preset first reference uniformity is 0.8. Because the first uniformity 0.635 is lower than the first reference uniformity 0.8, the difference is 0.8-0.635=0.165, and each 0.01 difference is extended by 1 second, so it is extended by 16.5 seconds, and the ventilation time is updated.

[0110] If the first uniformity is higher than the first reference uniformity, it means that the ammonia concentration is relatively uniform, and the ammonia difference is less than the preset ammonia reference difference, then the ventilation time is shortened and updated. The preset ammonia reference difference is 0.05ppm. Ammonia difference: 0.04ppm

[0111] By adding the steps of calculating the uniformity of ammonia concentration and adjusting the ventilation time accordingly, this method achieves more comprehensive and precise regulation in environmental parameter control. It not only helps to improve the stability and uniformity of the animal growth environment, but also significantly reduces operating costs and improves the intelligence level and reliability of the system.

[0112] For the cage frame, in this embodiment, the ventilation is vertical; in other embodiments, the ventilation can also be horizontal. The positions of the blowing and exhaust devices are adjusted, and the blowing direction is adjusted to horizontal blowing on one side and horizontal exhaust on the other opposite side.

[0113] The method further comprises the steps of:

[0114] If the first uniformity is lower than the first reference uniformity, the uneven center positions of the multiple ammonia concentration data on the cage are calculated, and the distance between the uneven center position and the ventilation fan is calculated as the uneven ventilation distance. If the uneven ventilation distance is greater than the preset reference distance value, the extension amplitude of the extended ventilation time is increased, wherein the larger the uneven ventilation distance, the larger the extension amplitude, and the smaller the uneven ventilation distance, the smaller the extension amplitude.

[0115] According to the assumed ammonia sensor data: 0.5ppm, 0.6ppm, 0.7ppm, 0.4ppm, 0.6ppm; then, the average ammonia concentration is 0.56ppm.

[0116] Calculate the difference between each sensor data and the average value: 0.5-0.56=-0.06, 0.6-0.56=0.04, 0.7-0.56=0.14, 0.4-0.56=-0.16, 0.6-0.56=0.04.

[0117] From the above differences, it can be seen that the position corresponding to the maximum value of the sum of the absolute values ​​of two or more adjacent differences is the position of the point where the data is most uneven, that is, the difference between 0.7ppm and 0.4ppm is the largest, indicating that the most uneven point is between 0.7ppm and 0.4ppm.

[0118] Assume that the positions of the sensors are: 1, 2, 3, 4, 5.

[0119] That is, the uneven center position is 3.5.

[0120] Due to the horizontal blowing, the position of the ventilation fan is 0; then the uneven ventilation distance is 3.5.

[0121] Assume that the preset reference distance value is 3, which corresponds to the middle position. Because the uneven ventilation distance of 3.5 is greater than the reference distance value of 3, the extension of the ventilation time is increased, that is, it takes longer to blow away the ammonia at the uneven center position farther away from the ventilation fan. Assume that the calculation formula for the extension range is: extension range = uneven ventilation distance - reference distance value.

[0122] Extension range: 3.5-3=0.5.

[0123] The above solution can significantly improve the uniformity of ammonia concentration in the cage area, while achieving energy-saving, efficient, automated and intelligent ventilation control.

[0124] Reference Figure 5 , the method further comprises the following steps:

[0125] The uniformity of the plurality of humidity data is calculated as the second uniformity. The closer the plurality of humidity data are, the higher the value of the second uniformity is. The greater the difference between the plurality of humidity data is, the lower the value of the second uniformity is.

[0126] According to the assumed humidity sensor data: 45%, 50%, 48%, 52%, 47%. The average humidity is 49%;

[0127] The calculated standard deviation is 2.45.

[0128] The calculation formula for uniformity is: uniformity = 1-standard deviation / (maximum value-minimum value);

[0129] The maximum value is 52% and the minimum value is 45%, so the uniformity is ≈ 0.85.

[0130] If the second uniformity is lower than the preset second reference uniformity, and the humidity difference is less than the preset humidity reference difference, the ventilation time is reduced and updated. This indicates that the humidity distribution is uneven, and the humidity data is close to the standard humidity after averaging. At this time, too much humidification operation is not required, and the overall humidity uniformity needs to be improved.

[0131] Assume that the preset second reference uniformity is 0.9 and the preset humidity reference difference is 5%.

[0132] Humidity difference 1%.

[0133] Assuming the basic ventilation time is 30 minutes, the ventilation time should be increased by 5 minutes for every 0.01 decrease in uniformity.

[0134] The additional ventilation time required is: 5×5=25 minutes.

[0135] Updated ventilation time: 30+25=55 minutes.

[0136] If the second uniformity is higher than the second reference uniformity, and the humidity difference is greater than the preset humidity reference difference, the moisture output is amplified and updated, and the moisture output is extended and updated, indicating that the data is relatively uniform at this time, and the overall humidity is higher than the reference value.

[0137] Assume that in another scenario, the uniformity calculation result of humidity data is 0.94, and the humidity difference is 6%.

[0138] Because the second uniformity of 0.94 is higher than the second reference uniformity of 0.9, and the humidity difference of 6% is higher than the preset humidity reference difference of 5%, the moisture output is reduced and updated, and the ventilation time is extended and updated.

[0139] Assume that for every 1% increase in humidity difference, the moisture output is reduced by 10 units. Among them, the humidity difference is 6%, and the humidity difference is increased by 1%.

[0140] Moisture output to be reduced: 10 units.

[0141] Updated moisture output: 100-10=90 units.

[0142] Assuming the basic ventilation time is 30 minutes, increase the ventilation time by 5 minutes for every 1% increase in humidity difference.

[0143] The additional ventilation time required is: 1×5=5 minutes.

[0144] Updated ventilation time: 30+5=35 minutes.

[0145] It can make humidity easier to balance, which can significantly improve the accuracy of humidity control, optimize energy utilization, enhance user experience, and enhance the intelligence and automation level of the system.

[0146] Reference Figure 6 , the method further comprises the following steps:

[0147] The uniformity of the multiple temperature data is calculated as the third uniformity. The closer the multiple temperature data are, the higher the value of the third uniformity is. The greater the difference between the multiple temperature data is, the lower the value of the third uniformity is.

[0148] Assume that the temperature sensor data is: 22℃, 24℃, 23℃, 21℃, 23℃. The average temperature is 22.8℃. The calculated standard deviation is 1.02. The calculation formula for uniformity is: uniformity = 1-standard deviation / (maximum value-minimum value); the maximum value is 24℃, the minimum value is 21℃, so the uniformity is 0.673.

[0149] If the third uniformity is lower than a preset third reference uniformity and the temperature difference is smaller than a preset temperature reference difference, the output power is reduced and updated.

[0150] Assume that the preset third reference uniformity is 0.7 and the preset temperature reference difference is 1°C.

[0151] Temperature difference: 23-22.8=0.2℃.

[0152] Because the third uniformity of 0.673 is lower than the third reference uniformity of 0.7, and the temperature difference of 0.2° C. is lower than the preset temperature reference difference of 1° C., the output power amount is reduced and updated.

[0153] Assuming that the base value of the output power is 100 units, the output power will decrease by 5 units for every 0.1 decrease in uniformity.

[0154] The output power that needs to be reduced is: (0.7-0.673)×50=1.3 units.

[0155] Updated output power: 100-1.3=98.7 units.

[0156] If the third uniformity is higher than the third reference uniformity, and the temperature difference is greater than a preset temperature reference difference, the output power is amplified and updated, and the ventilation time is extended and updated.

[0157] Assume that in another scenario, the uniformity calculation result of the temperature data is 0.8 and the temperature difference is 2°C.

[0158] Because the third uniformity of 0.8 is higher than the third reference uniformity of 0.7, and the temperature difference of 2° C. is greater than the preset temperature reference difference of 1° C., the output power is amplified and updated, and the ventilation time is extended and updated.

[0159] Assume that for every 0.1 increase in uniformity, the output power increases by 10 units.

[0160] The output power that needs to be increased is: (0.8-0.7)×100=10 units.

[0161] Updated output power: 100+10=110 units.

[0162] Assuming the basic ventilation time is 30 minutes, increase the ventilation time by 10 minutes for every 1°C increase in temperature difference.

[0163] The additional ventilation time required is: 2×10=20 minutes.

[0164] Updated ventilation time: 30+20=50 minutes.

[0165] It can make humidity easier to balance, significantly improve the accuracy of temperature control, optimize energy efficiency and equipment life, enhance the system's comprehensive regulation capabilities, and improve user experience and comfort.

[0166] The method further comprises the steps of:

[0167] If the third uniformity is lower than the third reference uniformity, it means that the data is not uniform enough and the degree of dispersion is large. The uneven center position of multiple temperature data on the cage is calculated, and the distance between the uneven center position and the ventilation fan is calculated as the uneven ventilation distance. The extension amplitude of the ventilation time is adjusted according to the uneven ventilation distance. The larger the uneven ventilation distance, the greater the extension amplitude, and the smaller the uneven ventilation distance, the smaller the extension amplitude.

[0168] Assume that the temperature sensor data is: 22℃, 23℃, 23℃, 20℃, 23℃. The average temperature is 22.2℃.

[0169] Calculate the difference between each sensor data and the average value: 22-22.2=-0.2, 23-22.2=0.8, 23-22.2=0.8, 20-22.2=-2.2, 23-22.2=0.8.

[0170] From the above differences, it can be seen that the position corresponding to the maximum value of the sum of the absolute values ​​of two or more adjacent differences is the position of the point where the data is most uneven, that is, the difference between 23°C, 20°C, and 23°C is the largest, indicating that the most uneven point is at 20°C.

[0171] Assume that the positions of the sensors are: 1, 2, 3, 4, 5.

[0172] That is, the uneven center position is 4.

[0173] The position of the ventilation fan is 0. Due to the horizontal blowing, the position of the ventilation fan is 0; then the uneven ventilation distance is 4.

[0174] Assuming the base extension is 0 minutes, the extension increases by 1 minute for every 1 unit increase in uneven ventilation distance.

[0175] Extension: 4 minutes. For example, the farther the ventilation fan is, the longer the ventilation time is needed, which is conducive to improving the uniformity of temperature data. On the contrary, the closer the uneven point is to the ventilation fan, the shorter the time it takes for the ventilation fan to diffuse the temperature and improve the uniformity of temperature.

[0176] When the third uniformity is lower than the third reference uniformity, it indicates that the temperature distribution on the cage is uneven. By calculating the distance between the uneven center and the ventilation fan (uneven ventilation distance), the system can more accurately identify the specific area with uneven temperature. By adjusting the extension of the ventilation time according to the uneven ventilation distance, targeted regulation of the temperature uneven area can be achieved. This regulation method has a rapid heat dissipation effect, is more accurate and efficient, and helps to quickly improve the uneven temperature distribution.

[0177] The method further comprises the steps of:

[0178] Get the distance data between the staff and the cage.

[0179] The rotation speed of the cage is adjusted according to the distance data. The larger the distance data, the faster the rotation speed, and the smaller the distance data, the slower the rotation speed.

[0180] For example, when the worker is 5 meters away from the cage, assuming the maximum distance, the cage rotates at a basic speed, such as 10 revolutions per minute.

[0181] If the staff is 2.5 meters away from the cage, the rotation speed of the cage will be halved, that is, 5 revolutions per minute.

[0182] If the worker is 10 meters away from the cage, the cage's rotation speed will double, that is, 20 revolutions per minute.

[0183] The fan speed of the ventilation fan is adjusted according to the distance data. The larger the distance data, the faster the fan speed, and the smaller the distance data, the slower the fan speed.

[0184] For example, when the worker is 5 meters away from the cage, the fan runs at a basic speed, such as 1000 revolutions per minute.

[0185] If the worker is 2.5 meters away from the cage, the fan speed will be halved to 500 revolutions per minute.

[0186] If the worker is 10 meters away from the cage, the fan speed will double to 2000 revolutions per minute.

[0187] The distance data between the staff and the cage is obtained, and the rotation speed of the cage and the fan speed of the ventilation fan are adjusted accordingly, so that the system can be dynamically adjusted according to the actual position of the personnel; work efficiency and personnel comfort are improved; the cage rotation speed and fan speed are intelligently adjusted according to the distance data, which helps to avoid unnecessary energy consumption and has energy-saving effects; and the intelligence level of the system and the overall quality of the working environment are improved.

[0188] The embodiment of the present application also discloses an environmental parameter control system for an ultra-high double-row rotating rack, including a processor, wherein the processor executes the steps of the environmental parameter control method for an ultra-high double-row rotating rack as described in any one of the above.

[0189] The embodiment of the present application further discloses a storage medium, wherein a program is stored in the storage medium, and when the program is executed by a processor, the steps of the environmental parameter control method of the ultra-high double-row rotating rack described in any one of the above are implemented.

[0190] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for controlling environmental parameters of an ultra-high double-row rotating frame, characterized in that: The steps include: Acquire multiple ammonia concentration data based on multiple ammonia sensors on the rotating frame; Calculate the average ammonia data according to the plurality of ammonia concentration data; Calculating an ammonia difference between the ammonia average data and a preset ammonia reference data; The first ventilation data is calculated by a preset first ventilation algorithm according to the ammonia difference; Acquiring a plurality of humidity data based on humidity sensors installed in a plurality of incubators; Calculate the average humidity data according to the plurality of humidity data; Calculating the humidity difference between the average humidity data and preset humidity reference data; The second ventilation data is calculated by a preset second ventilation algorithm according to the humidity difference; Acquire a plurality of temperature data based on temperature sensors installed in a plurality of incubators; Calculate average temperature data according to the plurality of temperature data; Calculating the temperature difference between the average temperature data and the preset temperature reference data; Calculating third ventilation data according to the temperature difference using a preset third ventilation algorithm; Obtaining fourth ventilation data by using a preset fourth ventilation algorithm according to the first ventilation data, the second ventilation data and the third ventilation data; The rotation speed of the ventilation fan is adjusted according to the fourth ventilation data and the ventilation time is continued for the set time. The larger the fourth ventilation data is, the faster the rotation speed is, and the smaller the fourth ventilation data is, the slower the rotation speed is. The wind delivered by the ventilation fan is clean gas with preset temperature and humidity.

2. The environmental parameter control method of the ultra-high double-row rotating frame according to claim 1 is characterized in that: The method further comprises the steps of: Calculating first humidification intervention data and first drying intervention data according to the temperature difference; Calculating second humidification intervention data and second drying intervention data according to the humidity difference; Calculating humidification data according to the first humidification intervention data and the second humidification intervention data; Calculate drying data according to the first drying intervention data and the second drying intervention data; adjusting the moisture output of the humidifier according to the humidification data, wherein the larger the humidification data is, the larger the moisture output is, and the smaller the humidification data is, the smaller the moisture output is; The output power of the dryer is adjusted according to the drying data. The larger the drying data is, the larger the output power is, and the smaller the drying data is, the smaller the output power is.

3. The environmental parameter control method of the ultra-high double-row rotating frame according to claim 1 is characterized in that: The method further comprises the steps of: Calculating uniformity of the plurality of ammonia concentration data as a first uniformity, the closer the plurality of ammonia concentration data are, the higher the value of the first uniformity is, and the greater the difference between the plurality of ammonia concentration data is, the lower the value of the first uniformity is; If the first uniformity is lower than a preset first reference uniformity, extending and updating the ventilation time; If the first uniformity is higher than the first reference uniformity, and the ammonia difference is less than a preset ammonia reference difference, the ventilation time is shortened and updated.

4. The environmental parameter control method of the ultra-high double-row rotating frame according to claim 3 is characterized in that: The method further comprises the steps of: If the first uniformity is lower than the first reference uniformity, the uneven center positions of the multiple ammonia concentration data on the cage are calculated, and the distance between the uneven center position and the ventilation fan is calculated as the uneven ventilation distance; if the uneven ventilation distance is greater than the preset reference distance value, the extension amplitude of the ventilation time is increased, wherein the larger the uneven ventilation distance, the larger the extension amplitude, and the smaller the uneven ventilation distance, the smaller the extension amplitude.

5. The environmental parameter control method of the ultra-high double-row rotating frame according to claim 2 is characterized in that: The method further comprises the steps of: Calculating uniformity of the plurality of humidity data as a second uniformity, wherein the closer the plurality of humidity data are, the higher the value of the second uniformity, and the greater the difference between the plurality of humidity data is, the lower the value of the second uniformity; If the second uniformity is lower than a preset second reference uniformity, and the humidity difference is less than a preset humidity reference difference, extending and updating the ventilation time; If the second uniformity is higher than the second reference uniformity, and the humidity difference is greater than a preset humidity reference difference, the moisture output is reduced and updated, and the ventilation time is extended and updated.

6. The environmental parameter control method of the ultra-high double-row rotating frame according to claim 2 is characterized in that: The method further comprises the steps of: Calculating uniformity of the plurality of temperature data as a third uniformity, wherein the closer the plurality of temperature data are, the higher the value of the third uniformity, and the greater the difference between the plurality of temperature data is, the lower the value of the third uniformity; If the third uniformity is lower than a preset third reference uniformity, and the temperature difference is smaller than a preset temperature reference difference, reducing and updating the output power; If the third uniformity is higher than the third reference uniformity, and the temperature difference is greater than a preset temperature reference difference, the output power is amplified and updated, and the ventilation time is extended and updated.

7. The environmental parameter control method of the ultra-high double-row rotating frame according to claim 6 is characterized in that: The method further comprises the steps of: If the third uniformity is lower than the third reference uniformity, the uneven center positions of the multiple temperature data on the cage are calculated, and the distance between the uneven center position and the ventilation fan is calculated as the uneven ventilation distance; the extension amplitude of the ventilation time is adjusted according to the uneven ventilation distance, wherein the larger the uneven ventilation distance, the larger the extension amplitude, and the smaller the uneven ventilation distance, the smaller the extension amplitude.

8. The environmental parameter control method of the ultra-high double-row rotating frame according to claim 1 is characterized in that: The method further comprises the steps of: Obtain the distance data between the staff and the cage; Adjusting the rotation speed of the cage according to the distance data, wherein the larger the distance data is, the faster the rotation speed is, and the smaller the distance data is, the slower the rotation speed is; The fan speed of the ventilation fan is adjusted according to the distance data. The larger the distance data is, the faster the fan speed is, and the smaller the distance data is, the slower the fan speed is.

9. An environmental parameter control system for an ultra-high double-row rotating frame, characterized in that: It comprises a processor, in which the steps of the environmental parameter control method of the ultra-high double-row rotating frame as described in any one of claims 1-8 are executed.

10. A storage medium, characterized in that: The medium stores a program, and when the program is executed by the processor, the steps of the environmental parameter control method of the ultra-high double-row rotating rack described in any one of claims 1 to 8 are implemented.

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