Prefabricated cabin adaptive environment adjusting method and system based on AI prediction

Abstract

This invention relates to the field of environmental control technology, and discloses an AI-based predictive adaptive environmental regulation method and system for prefabricated cabins. The method includes calculating the equivalent temperature and humidity within the prefabricated cabin; acquiring predicted temperature and humidity sequences over a time range t; determining the start-up and shutdown timing of the equipment based on a comparison of the predicted temperature and humidity sequences with environmental parameter limits; and continuing to acquire predicted data after the equipment completes the start-up and shutdown commands. This invention avoids conflicting operation and ineffective start-up and shutdown by constructing a dynamic control mechanism for the equipment; simultaneously, it achieves predictive proactive control to prevent environmental parameters within the prefabricated cabin from exceeding safety thresholds. Combined with dual operating modes, it flexibly switches control strategies according to the type of equipment within the prefabricated cabin, effectively reducing environmental fluctuations and suppressing condensation within the cabin, thereby reducing the equipment failure rate.

Description

Technical Field

[0001] This invention relates to the field of environmental control technology, specifically to a method and system for adaptive environmental regulation of prefabricated cabins based on AI prediction. Background Technology

[0002] Prefabricated substations are used across the country, covering a wide range of complex and harsh operating conditions, including high salt spray, high humidity and heat, and extreme cold. The stability of the internal environment of the prefabricated substation directly affects the reliability and safety of the internal electrical equipment. Drastic changes in the external environment often cause fluctuations in the internal environment, leading to problems such as moisture absorption and condensation in the insulating medium. This, in turn, increases the probability of partial discharge, induces electrochemical corrosion, increases operation and maintenance costs, and affects the safe operation of the power grid.

[0003] Currently, prefabricated substations rely solely on their HVAC equipment, using simple threshold triggers for basic control. This results in a simplistic control strategy lacking necessary coordination, often leading to control lag and regulation delays. Furthermore, the slow response to dynamic disturbances such as heat transfer within the cabin and equipment start-up and shutdown further exacerbates the risks of severe environmental fluctuations and surface condensation within the prefabricated cabin.

[0004] In summary, there is a need to design an AI-based predictive method and system for adaptive environmental adjustment of prefabricated cabins to address the aforementioned problems in existing technologies. Summary of the Invention

[0005] This invention provides an AI-based adaptive environmental adjustment method and system for prefabricated cabins, which solves problems such as significant environmental fluctuations, easy condensation, isolated operation of existing HVAC equipment, single control strategy, and lagging control effect in conventional prefabricated cabins.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The AI-based predictive method for adaptive environmental adjustment of prefabricated cabins includes the following steps:

[0008] S1. Calculate the equivalent temperature and equivalent humidity inside the prefabricated cabin based on the location of the temperature and humidity sensors inside the cabin and the collected temperature and humidity data.

[0009] S2. Obtain the predicted temperature and humidity sequences within the time range t;

[0010] S3. Determine the start-up and shutdown timing of the equipment based on the comparison results between the predicted temperature sequence and the predicted humidity sequence and the environmental parameter limits; the environmental parameter limits include temperature limits, humidity limits, and dew point temperature limits; the equipment includes air conditioners, electric heaters, and dehumidifiers; the determination process includes the following steps:

[0011] S31. Compare the predicted temperature sequence with the temperature limit, and output the start / stop timing of the air conditioner or electric heater based on the comparison result;

[0012] S32. Determine the moment when the humidity limit is first met in the predicted humidity sequence, and calculate the dehumidification time required for the predicted humidity to reach the set humidity at that moment, and record it as the first dehumidification time.

[0013] Calculate the predicted dew point temperature sequence, determine the moment when the dew point temperature limit is first met in the predicted dew point temperature sequence, and calculate the dehumidification time required for the predicted humidity to reach the target humidity at that moment, which is denoted as the second dehumidification time.

[0014] If the above-mentioned time exists, the larger value between the first dehumidification time and the second dehumidification time is selected as the dehumidifier's operating time; otherwise, the dehumidifier's shutdown time is determined based on the surface temperature and dew point temperature of the prefabricated compartment.

[0015] S4. After the device completes the start / stop command, return to step S2.

[0016] In some embodiments of the present invention, the calculation process for the first dehumidification time is as follows:

[0017] The moment when the humidity limit is first met in the predicted humidity sequence is determined and denoted as the first moment; the predicted humidity corresponding to the first moment is denoted as the first predicted humidity.

[0018] Calculate the amount of dehumidification required for the first predicted humidity to reach the set humidity, and record it as the first dehumidification amount;

[0019] The first dehumidification time is calculated based on the number of dehumidifiers and their rated dehumidification capacity, using the following formula:

[0020] First dehumidification time = First dehumidification capacity / (Number of dehumidifiers × Rated dehumidification capacity).

[0021] In some embodiments of the present invention, the calculation process for the second dehumidification time is as follows:

[0022] Calculate and predict the dew point temperature series;

[0023] The moment when the dew point temperature limit is first met in the predicted dew point temperature sequence is denoted as the second moment; the predicted humidity corresponding to the second moment in the predicted humidity sequence is denoted as the second predicted humidity; and the predicted temperature corresponding to the second moment in the predicted temperature sequence is denoted as the second predicted temperature.

[0024] Calculate the target humidity based on the second predicted temperature and the set dew point temperature;

[0025] Calculate the amount of dehumidification required for the second predicted humidity to reach the target humidity, and denot it as the second dehumidification amount;

[0026] The second dehumidification time is calculated based on the number of dehumidifiers and their rated dehumidification capacity, using the following formula:

[0027] Second dehumidification time = Second dehumidification capacity / (Number of dehumidifiers × Rated dehumidification capacity).

[0028] In some embodiments of the present invention, step S3 further includes: when the dehumidifier is started, a timer is started synchronously; when the timer ends, if the dehumidifier is still on, the start / stop judgment program of the air conditioner is started.

[0029] In some embodiments of the present invention, the start / stop determination procedure of the air conditioner includes: determining whether the equivalent temperature meets T. max -15℃ <T<T max -10℃, T max This is the upper limit of the temperature; if this limit is met, the air conditioner will be turned on for cooling, and the cooling value T will be set. set Otherwise, the judgment process ends.

[0030] During air conditioner operation, determine whether the equivalent temperature satisfies T < T max If the temperature is -15℃, turn off the air conditioner and end the judgment process.

[0031] Otherwise, determine the dew point temperature T. d and the surface temperature T of the prefabricated cabin b Does T satisfy? d <T b -5℃ and T d <T dmax -5℃, T dmax The dew point temperature limit is set; if the limit is met, the air conditioner is turned off and the judgment procedure ends; otherwise, the process returns to the previous judgment step.

[0032] In some embodiments of the present invention, determining the shutdown timing of the dehumidifier based on the surface temperature and dew point temperature of the prefabricated compartment in step S32 includes:

[0033] When the dew point temperature and the surface temperature of the prefabricated compartment meet the condition that the dew point temperature is less than the surface temperature -5°C, the dehumidifier stops and the timer is reset.

[0034] In some embodiments of the present invention, the parameters required for the acquisition process of the predicted temperature sequence and predicted humidity sequence in step S2 include: air conditioning power P. L Electric heater power P d Dehumidifier dehumidification capacity C, equivalent temperature T inside the prefabricated compartment, equivalent humidity H, and external temperature T outside the prefabricated compartment. w External humidity H w The opening and closing status of the prefabricated cabin doors.

[0035] In some embodiments of the present invention, an AI-predictive prefabricated cabin adaptive environment adjustment system is provided to implement the above-mentioned prefabricated cabin adaptive environment adjustment method, including:

[0036] The data acquisition module is used to collect cabin data, real-time environmental data and real-time operation data of the prefabricated cabin, and also to calculate the equivalent temperature and equivalent humidity inside the prefabricated cabin;

[0037] The prediction module is used to output predicted temperature and predicted humidity sequences based on the data from the data acquisition module.

[0038] The data processing module is used to determine the start-up and shutdown timing of the equipment based on the comparison results between the predicted temperature sequence and the predicted humidity sequence and the environmental parameter limits;

[0039] The equipment execution module is used to control the equipment to complete parameter adjustment and start / stop actions according to the start / stop timing.

[0040] The technical solution of the present invention has the following technical effects compared with the prior art:

[0041] This invention avoids conflicting operation and ineffective start-stop by constructing a dynamic control mechanism for the equipment; at the same time, it achieves predictive active control to prevent environmental parameters in the prefabricated cabin from exceeding safety thresholds. With dual working modes, it flexibly switches control strategies according to the type of equipment in the prefabricated cabin, effectively reducing environmental fluctuations and suppressing the generation of condensation in the cabin, thereby reducing the incidence of equipment failure. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a schematic flowchart illustrating the adjustment method of the present invention.

[0044] Figure 2 This is a flowchart illustrating the adjustment method shown in Embodiment 1 of the present invention. Figure 1 .

[0045] Figure 3 This is a flowchart illustrating the adjustment method shown in Embodiment 1 of the present invention. Figure 2 .

[0046] Figure 4 This is a sub-process of the adjustment method shown in Embodiment 1 of the present invention.

[0047] Figure 5This is a schematic flowchart of the adjustment method shown in Embodiment 2 of the present invention. Figure 1 .

[0048] Figure 6 This is a schematic flowchart of the adjustment method shown in Embodiment 2 of the present invention. Figure 2 .

[0049] Figure 7 This is a schematic diagram of the regulating system shown in this invention.

[0050] Figure 8 This is a schematic diagram of the electronic device.

[0051] Reference numerals: 100, regulation system; 110, data acquisition module; 120, prediction module; 130, data processing module; 140, equipment execution module; 200, electronic device; 210, processor; 220, memory; 230, transceiver. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0054] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0055] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0056] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0057] The following disclosure provides many different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the invention. Furthermore, reference numerals and / or letters may be repeated in different examples; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. In addition, examples of various specific processes and materials are provided in this invention, but those skilled in the art will recognize the application of other processes and / or the use of other materials.

[0058] In order to overcome the problems in the existing technology, referring to Figure 1 As shown, this invention provides a prefabricated cabin adaptive environment adjustment method based on AI prediction, including the following steps:

[0059] S1. Calculate the equivalent temperature and equivalent humidity inside the prefabricated cabin based on the location of the temperature and humidity sensors inside the cabin and the collected temperature and humidity data.

[0060] S2. Obtain the predicted temperature and humidity sequences within the time range t;

[0061] S3. Determine the start-up and shutdown timing of the equipment based on the comparison results between the predicted temperature sequence and the predicted humidity sequence and the environmental parameter limits;

[0062] S4. After the device completes the start / stop command, return to step S2.

[0063] This invention avoids conflicting operation and ineffective start-stop by constructing a dynamic control mechanism for the equipment; at the same time, it achieves predictive active control to prevent environmental parameters in the prefabricated cabin from exceeding safety thresholds. With dual working modes, it flexibly switches control strategies according to the type of equipment in the prefabricated cabin, effectively reducing environmental fluctuations and suppressing the generation of condensation in the cabin, thereby reducing the incidence of equipment failure.

[0064] The adjustment method provided by this invention supports two working modes:

[0065] In the standard environmental protection mode, the lower temperature threshold is T. min The upper limit threshold is T max The upper limit threshold for humidity is H max The upper limit threshold for dew point temperature is T. dmax ;

[0066] Constant temperature environment protection mode, with a constant temperature target T c (Temperature fluctuation ≤2℃), upper limit threshold for humidity is H max The upper limit threshold for dew point temperature is T. dmax .

[0067] Select the corresponding operating mode based on the operational requirements of the equipment inside the prefabricated cabin:

[0068] When the prefabricated compartment contains conventional power equipment such as transformers and switchgear, the conventional environmental protection mode should be selected.

[0069] When the prefabricated cabin contains precision equipment such as switches, protection devices, and fault recorders, a constant temperature environment protection mode should be selected.

[0070] The following descriptions are provided using Examples 1 and 2, respectively.

[0071] Example 1: Under conventional environmental protection mode, the prefabricated cabin adaptive environmental adjustment method based on AI prediction includes the following steps:

[0072] S1. Obtain the equivalent temperature T and equivalent humidity H; that is, calculate the equivalent temperature T and equivalent humidity H in the prefabricated cabin based on the location of the temperature and humidity sensors in the prefabricated cabin and the collected temperature and humidity data.

[0073] n temperature and humidity sensors are evenly distributed inside the prefabricated cabin to collect temperature T data at different locations within the cabin. i (i=1,2,3,...,n), humidity H i (i=1,2,3,...,n).

[0074] A three-dimensional coordinate system is established with the lower left corner of the prefabricated cabin as the origin O (0,0,0), and the spatial coordinates of each sensor are (x... i ,y i,z i The target point for calculating the equivalent temperature T and equivalent humidity H is the geometric center of the cabin, with the coordinates preset as (x0, y0, z0). The three-dimensional distance d between each sensor and the target point is calculated. i The formula is as follows:

[0075] .

[0076] Calculate the weighting coefficient W for each sensor data. i The weight is inversely proportional to the p-th power of the distance; the closer the distance, the greater the weight.

[0077] .

[0078] The equivalent temperature T and equivalent humidity H are calculated using a weighted average formula, taking into account the weighting coefficients of each sensor.

[0079] ;

[0080] .

[0081] S2. Obtain the predicted temperature sequence {T'} and predicted humidity sequence {H'} within the time range t.

[0082] The parameters required for obtaining the predicted temperature series {T'} and the predicted humidity series {H'} include: air conditioning power P. L Electric heater power P d Dehumidifier dehumidification capacity C, equivalent temperature T inside the prefabricated compartment, equivalent humidity H, and external temperature T outside the prefabricated compartment. w External humidity H w The opening and closing status of the prefabricated cabin doors.

[0083] External temperature T w External humidity H w Micro-meteorological sensors can be used to collect data; the opening and closing status of refrigeration equipment, heating equipment, and prefabricated doors can be collected and monitored through signal acquisition modules.

[0084] S3. Determine the start-up and shutdown timing of the equipment based on the comparison results between the predicted temperature sequence {T'} and the predicted humidity sequence {H'} and the environmental parameter limits; the environmental parameter limits include temperature limits, humidity limits, and dew point temperature limits; the equipment includes air conditioners, electric heaters, and dehumidifiers; the determination process includes the following steps:

[0085] S31, Reference Figure 2As shown in the figure, this process illustrates the adjustment of the temperature inside the prefabricated cabin. It involves comparing the predicted temperature sequence {T'} with the temperature limits and outputting the start / stop timing for the air conditioner or electric heater based on the comparison result. The temperature limits involved in this step include the upper temperature limit T. max Temperature limit T min Specifically, it includes the following steps:

[0086] Based on the predicted temperature sequence {T'}={T'1,T''} of the prefabricated cabin equivalent temperature obtained in step S2 for the next 30 minutes. 2, T' 3, T' 4, T' 5, T'6} contains a total of 6 temperature data points.

[0087] S311. The process for determining the start and stop timing of the air conditioner: When there is a T'>T in the predicted temperature sequence {T'}. max (e.g., at 35℃) obtain the latest operating status of the electric heater, determine whether the electric heater is on, if so, turn off the electric heater and then turn on all air conditioners for cooling; otherwise, directly turn on all air conditioners for cooling; and set the cooling value T of the air conditioners. set =T max -15℃.

[0088] During the continuous operation of the air conditioner, the forecast data is updated every 5 minutes. A judgment is made based on the latest forecast data, specifically, if all data in the forecast temperature sequence {T'} satisfy T' < T... max If the temperature drops to -10℃ (e.g., 25℃), the air conditioner will be turned off. Otherwise, return to the previous step to continue updating the forecast data, and the air conditioner will continue to run.

[0089] S312. The process for determining the start-stop timing of an electric heater: When there is a T' in the predicted temperature sequence {T'}. <T min (e.g., at 5℃) obtain the latest operating status of the air conditioner, determine whether the air conditioner is cooling on, if so, turn off the air conditioner and turn on all electric heaters for heating, otherwise turn on all electric heaters for heating directly.

[0090] During the continuous operation of the electric heater, the prediction data is updated every 5 minutes. The latest prediction data is then used to make a judgment, namely, if all the data in the predicted temperature sequence {T'} satisfy T'>T min If the temperature rises by 10℃ (e.g., 15℃), the electric heater will be turned off; otherwise, return to the previous step to continue updating the prediction data; the electric heater will continue to run.

[0091] S32. Reference Figure 3As shown in the figure, this illustrates the process of adjusting the humidity inside the prefabricated cabin. Specifically, it involves determining the start and stop times of the dehumidifier and air conditioner based on the predicted temperature sequence {T'} and the predicted humidity sequence {H'}. The humidity limit involved in this step is the upper humidity limit H. max upper limit of dew point temperature T dmax Specifically, it includes the following steps:

[0092] Based on the predicted temperature sequence {T'}={T'1,T''} of the prefabricated cabin equivalent temperature obtained in step S2, the temperature over the next 6 hours is calculated as follows: 2, T' 3,..., T' 72 Predicted humidity sequence {H'} = {H'1, H' 2, H' 3,..., H' 72}

[0093] S321. Determine the moment when the humidity limit is first met in the predicted humidity sequence, and calculate the dehumidification time required for the predicted humidity to reach the set humidity at that moment, denoted as the first dehumidification time.

[0094] S3211. Extract the first humidity sequence {H'} that satisfies the predicted humidity H' > H. max The moment when the humidity reaches 60% is denoted as the first moment t1, and the predicted humidity corresponding to the first moment t1 is denoted as the first predicted humidity H1'; the predicted temperature corresponding to the first moment t1 is denoted as the first predicted temperature T1'.

[0095] S3212, Calculate the first predicted humidity H1' to reach the set humidity H s The required dehumidification capacity is denoted as the first dehumidification capacity W1.

[0096] The formula for calculating the first dehumidification capacity W1 is:

[0097] ;

[0098] Where V is the volume of the prefabricated cabin; D2 is the set humidity H. s The corresponding target moisture content; D1 is the initial moisture content corresponding to the first predicted humidity H1'.

[0099] The formula for calculating the target moisture content D2 is:

[0100] ;

[0101] The formula for calculating the initial moisture content D1 is:

[0102] ;

[0103] E in the above formula WFor saturated water vapor pressure, via logE W The formula is derived by reverse calculation, where T is the first predicted temperature T1', and logE W The formula is as follows:

[0104] .

[0105] S3213. Calculate the first dehumidification time Δt1 based on the number of dehumidifiers n and the rated dehumidification capacity C. The calculation formula is as follows:

[0106] Δt1 = W1 / (n × C).

[0107] S322. Calculate the predicted dew point temperature sequence, determine the moment when the dew point temperature limit is first met in the predicted dew point temperature sequence, and calculate the dehumidification time required for the predicted humidity to reach the target humidity at that moment, denoted as the second dehumidification time.

[0108] S3221. Calculate the corresponding future predicted dew point temperature sequence {T} d '}={T d '1,T d ' 2, T d ' 3,..., T d ' 72};

[0109] Among them, the dew point temperature T d The calculation formula is:

[0110] Where e is the water vapor pressure.

[0111] The formula for calculating water vapor pressure e is: H represents the equivalent humidity; E represents the equivalent humidity. W For saturated water vapor pressure, via the above logE W The formula is obtained, where T is the corresponding predicted temperature.

[0112] S3222, From the predicted dew point temperature sequence {T d Extract the first temperature T that satisfies the predicted dew point temperature. d >T dmax The time (e.g., 15℃) is denoted as the second time t2; in the predicted temperature sequence {T'}, the predicted temperature corresponding to the second time t2 is denoted as the second predicted temperature T2'; in the predicted humidity sequence {H'}, the predicted humidity corresponding to the second time t2 is denoted as the second predicted humidity H2'.

[0113] S3223, Based on the second predicted temperature T2' and the set dew point temperature T ds Calculate the target humidity H gThe specific calculation formula is as follows:

[0114] ;

[0115] Among them, the water vapor pressure e is related to the dew point temperature T. d The calculation formula is derived by reverse calculation, where the dew point temperature T in the formula is... d Replace with setting the dew point temperature T ds ; Saturated vapor pressure E W From the above logE W The formula is obtained, where T refers to the second predicted temperature T2'.

[0116] S3224. Calculate the target humidity H when the second predicted humidity H2' reaches the target humidity H. g The required dehumidification capacity is denoted as the second dehumidification capacity W2.

[0117] The formula for calculating the second dehumidification capacity W2 is:

[0118] ;

[0119] Where V is the volume of the prefabricated cabin; D2 is the target humidity H. g The corresponding target moisture content; D1 is the initial moisture content corresponding to the second predicted humidity H2'.

[0120] The formula for calculating the target moisture content D2 is:

[0121] ;

[0122] The formula for calculating the initial moisture content D1 is:

[0123] ;

[0124] E in the above formula W For saturated water vapor pressure, via logE W By reversing the formula, we can find that T in the formula is the second predicted temperature T2'.

[0125] S3225. Calculate the second dehumidification time Δt2 based on the number of dehumidifiers n and the rated dehumidification capacity C. The calculation formula is as follows:

[0126] Δt2 = W2 / (n × C).

[0127] S323. Determine whether the first time t1 and the second time t2 do not exist. If they do, it means that the system has no dehumidification requirement, and proceed to step S327. Otherwise, proceed to step S324.

[0128] S324. Select the larger value between the first dehumidification time Δt1 and the second dehumidification time Δt2 as the dehumidifier's operating time Δt.

[0129] S325. Turn on the dehumidifier and simultaneously start the timer, for example, a countdown of 5 hours.

[0130] S326. After the timer countdown ends, determine whether the dehumidifier is still on. If so, start the subroutine, i.e., start the air conditioner start / stop determination program; otherwise, return to step S2, re-obtain the latest prediction data, and complete the subsequent judgment and related calculations.

[0131] S327, Based on the surface temperature T of the prefabricated cabin b and dew point temperature T d Determine when to stop the dehumidifier;

[0132] Specifically, when the dew point temperature T d and the surface temperature T of the prefabricated cabin b Satisfy T d <T b When the temperature reaches -5℃, the dehumidifier stops and the timer is reset.

[0133] The formula for calculating the surface temperature of the prefabricated cabin is as follows:

[0134] ;

[0135] Where T is the equivalent temperature, T w R represents the external temperature. i R0 is the heat transfer resistance of the inner surface of the prefabricated cabin, and R0 is the heat transfer resistance of the cabin body.

[0136] The subroutine reference Figure 4 As shown:

[0137] Determine whether the equivalent temperature T satisfies T max -15℃ <T<T max -10℃ (e.g., 20℃ < T < 25℃), T max This is the upper limit of the temperature; if this limit is met, the air conditioner will be turned on for cooling, and the cooling value T will be set. set ;

[0138] During air conditioner operation, determine whether the equivalent temperature T satisfies T < T max If the temperature is -15℃ (e.g., 20℃), turn off the air conditioner and end the subroutine; return to step S2, retrieve the latest prediction data again, and complete the subsequent judgment and related calculations.

[0139] Otherwise, determine the dew point temperature T. d and the surface temperature T of the prefabricated cabin b Does T satisfy? d <T b -5℃ and T d <T dmax-5℃ (e.g., 10℃), T dmax The upper limit of the dew point temperature is set; if this limit is met, the air conditioner is turned off, the subroutine is terminated, and the process returns to step S2 to retrieve the latest prediction data and complete subsequent judgments and related calculations; otherwise, the process returns to the previous judgment step.

[0140] S4. After the device completes the start / stop command, it returns to step S2. That is, after the air conditioner, electric heater, or dehumidifier completes the start or stop command and the running time is completed, it returns to step S2 to obtain the latest prediction data again and complete subsequent judgments and related calculations.

[0141] Example 2: In the constant temperature environment protection mode, the preset constant temperature T in this example c The maximum dew point temperature is 25℃, with an allowable fluctuation of 2℃. dmax The temperature is 15℃.

[0142] The AI-based predictive method for adaptive environmental adjustment of prefabricated cabins includes the following steps: (Refer to...) Figure 5 and Figure 6 As shown.

[0143] S1. Calculate the equivalent temperature and equivalent humidity inside the prefabricated cabin based on the location of the temperature and humidity sensors inside the cabin and the collected temperature and humidity data.

[0144] n temperature and humidity sensors are evenly distributed inside the prefabricated cabin to collect temperature T data at different locations within the cabin. i (i=1,2,3,...,n), humidity H i (i=1,2,3,...,n).

[0145] A three-dimensional coordinate system is established with the lower left corner of the prefabricated cabin as the origin O (0,0,0), and the spatial coordinates of each sensor are (x... i ,y i ,z i The target point for calculating the equivalent temperature T and equivalent humidity H is the geometric center of the cabin, with the coordinates preset as (x0, y0, z0). The three-dimensional distance d between each sensor and the target point is calculated. i The formula is as follows:

[0146] .

[0147] Calculate the weighting coefficient W for each sensor data. i The weight is inversely proportional to the p-th power of the distance; the closer the distance, the greater the weight.

[0148] .

[0149] The equivalent temperature T and equivalent humidity H are calculated using a weighted average formula, taking into account the weighting coefficients of each sensor.

[0150] ;

[0151] .

[0152] S2. Obtain the predicted temperature sequence {T'} and predicted humidity sequence {H'} within the time range t.

[0153] The parameters required for obtaining the predicted temperature series {T'} and the predicted humidity series {H'} include: air conditioning power P. L Electric heater power P d Dehumidifier dehumidification capacity C, equivalent temperature T inside the prefabricated compartment, equivalent humidity H, and external temperature T outside the prefabricated compartment. w External humidity H w The opening and closing status of the prefabricated cabin doors.

[0154] External temperature T w External humidity H w Micro-meteorological sensors can be used to collect data; the opening and closing status of refrigeration equipment, heating equipment, and prefabricated doors can be collected and monitored through signal acquisition modules.

[0155] S3. Determine the start-up and shutdown timing of the equipment based on the comparison results between the predicted temperature sequence {T'} and the predicted humidity sequence {H'} and the environmental parameter limits; the environmental parameter limits include temperature limits, humidity limits, and dew point temperature limits; the equipment includes air conditioners, electric heaters, and dehumidifiers; the determination process includes the following steps:

[0156] S31, Reference Figure 5 As shown in the figure, this illustrates the process of adjusting the temperature inside the prefabricated cabin, specifically based on the predicted temperature sequence {T'} and the preset constant temperature T. c The comparison is performed, and the start / stop timing of the air conditioner or electric heater is output based on the comparison result. Specifically, this includes the following steps:

[0157] According to step S2, the predicted temperature sequence {T'}={T'1,T''} of the equivalent temperature of the prefabricated cabin for the next 30 minutes is obtained at an update frequency of 5 minutes. 2, T' 3, T' 4, T' 5, T'6}.

[0158] S311. The process for determining the start and stop timing of the air conditioner: When there exists a T'≥T in the predicted temperature sequence {T'}. c When the temperature is +2℃ (e.g., 27℃), ensure that the electric heater is turned off; otherwise, return to step S311.

[0159] Calculate the heat transfer Q between the inside and outside of the prefabricated cabin, based on the cooling power P of the air conditioner. LMatch the corresponding number of air conditioners n = Q / P L Turn on the air conditioner and set its cooling temperature (T). set =T c That is, T set= 25℃.

[0160] The formula for calculating the heat transfer Q is: ;T w Where is the external temperature, and T is the equivalent temperature.

[0161] During continuous operation of the air conditioner, the equivalent temperature T of the prefabricated cabin is monitored in real time. When the equivalent temperature T satisfies the condition T≤T c At +2℃ (e.g., 27℃), a secondary judgment is made based on the latest predicted temperature sequence {T'}:

[0162] If all data in {T'} satisfy T'≤T c If the temperature drops to -2℃ (e.g., 23℃), all air conditioning will be turned off; otherwise, the air conditioning will continue to run until the next round of forecast data is updated and a new assessment is made.

[0163] S312. The process for determining the start and stop timing of an electric heater: When any data in the predicted temperature sequence {T'} satisfies T'≤T c At -2℃ (e.g., 23℃), ensure the air conditioner is turned off;

[0164] Calculate the heat transfer Q between the inside and outside of the prefabricated cabin, based on the heating power P of the electric heater. d The number of matching electric heaters is n = Q / P. d Turn on the electric heater to heat it up;

[0165] While the electric heater is running continuously, the equivalent temperature T of the prefabricated cabin is monitored in real time. When the equivalent temperature T satisfies the condition T≥T c At -2℃, a secondary judgment is made based on the latest predicted temperature sequence {T'}:

[0166] If all data in {T'} satisfy T'≥T c If the temperature increases by 2°C (e.g., 27°C), all electric heaters will be turned off; otherwise, the heaters will continue to run until the next round of forecast data is updated and a new assessment is made.

[0167] S32. Reference Figure 6 As shown in the figure, this illustrates the process of adjusting the humidity inside the prefabricated cabin. Specifically, it involves determining the start and stop times of the dehumidifier and air conditioner based on the predicted temperature sequence {T'} and the predicted humidity sequence {H'}. The humidity limit involved in this step is the upper humidity limit H. max upper limit of dew point temperature T dmax Specifically, it includes the following steps:

[0168] According to step S2, obtain the predicted temperature sequence {T'}={T'1,T''} of the equivalent temperature of the prefabricated cabin in the future t=6h. 2, T' 3,..., T' 72 Predicted humidity sequence {H'} = {H'1, H' 2, H' 3,..., H' 72}

[0169] S321. Determine the moment when the humidity limit is first met in the predicted humidity sequence, and calculate the dehumidification time required for the predicted humidity to reach the set humidity at that moment, denoted as the first dehumidification time.

[0170] S3211. Extract the first variable whose predicted humidity H' satisfies H' > H from the predicted humidity sequence {H'}. max The moment when the humidity reaches 60% is denoted as the first moment t1, and the predicted humidity corresponding to the first moment t1 is denoted as the first predicted humidity H1'; the predicted temperature corresponding to the first moment t1 is denoted as the first predicted temperature T1'.

[0171] S3212, Calculate the first predicted humidity H1' to reach the set humidity H s The required dehumidification capacity is denoted as the first dehumidification capacity W1.

[0172] The formula for calculating the first dehumidification capacity W1 is:

[0173] ;

[0174] Where V is the volume of the prefabricated cabin; D2 is the set humidity H. s The corresponding target moisture content; D1 is the initial moisture content corresponding to the first predicted humidity H1'.

[0175] The formula for calculating the target moisture content D2 is:

[0176] ;

[0177] The formula for calculating the initial moisture content D1 is:

[0178] ;

[0179] E in the above formula W For saturated water vapor pressure, via logE W The formula is derived by reverse calculation, where T is the first predicted temperature T1', and logE W The formula is as follows:

[0180] .

[0181] S3213. Calculate the first dehumidification time Δt1 based on the number of dehumidifiers n and the rated dehumidification capacity C. The calculation formula is as follows:

[0182] Δt1 = W1 / (n × C).

[0183] S322. Calculate the predicted dew point temperature sequence, determine the moment when the dew point temperature limit is first met in the predicted dew point temperature sequence, and calculate the dehumidification time required for the predicted humidity to reach the target humidity at that moment, denoted as the second dehumidification time.

[0184] S3221. Calculate the corresponding future predicted dew point temperature sequence {T} d '}={T d '1,T d ' 2, T d ' 3,..., T d ' 72};

[0185] Among them, the dew point temperature T d The calculation formula is:

[0186] Where e is the water vapor pressure.

[0187] The formula for calculating water vapor pressure e is: H represents the equivalent humidity; E represents the equivalent humidity. W For saturated water vapor pressure, via the above logE W The formula is obtained, where T is the corresponding predicted temperature.

[0188] S3222, From the predicted dew point temperature sequence {T d Extract the first temperature T that satisfies the predicted dew point temperature. d >T dmax The time (e.g., 15℃) is denoted as the second time t2; in the predicted temperature sequence {T'}, the predicted temperature corresponding to the second time t2 is denoted as the second predicted temperature T2'; in the predicted humidity sequence {H'}, the predicted humidity corresponding to the second time t2 is denoted as the second predicted humidity H2'.

[0189] S3223, Based on the second predicted temperature T2' and the set dew point temperature T ds Calculate the target humidity H g The specific calculation formula is as follows:

[0190] ;

[0191] Among them, the water vapor pressure e is related to the dew point temperature T. d The calculation formula is derived by reverse calculation, where the dew point temperature T in the formula is... dReplace with setting the dew point temperature T ds ; Saturated vapor pressure E W The above logE W The formula is obtained, where T refers to the second predicted temperature T2'.

[0192] S3224. Calculate the target humidity H when the second predicted humidity H2' reaches the target humidity H. g The required dehumidification capacity is denoted as the second dehumidification capacity W2.

[0193] The formula for calculating the second dehumidification capacity W2 is:

[0194] ;

[0195] Where V is the volume of the prefabricated cabin; D2 is the target humidity H. g The corresponding target moisture content; D1 is the initial moisture content corresponding to the second predicted humidity H2'.

[0196] The formula for calculating the target moisture content D2 is:

[0197] ;

[0198] The formula for calculating the initial moisture content D1 is:

[0199] ;

[0200] E in the above formula W For saturated water vapor pressure, via logE W By reversing the formula, we can find that T in the formula is the second predicted temperature T2'.

[0201] S3225. Calculate the second dehumidification time Δt2 based on the number of dehumidifiers n and the rated dehumidification capacity C. The calculation formula is as follows:

[0202] Δt2 = W2 / (n × C).

[0203] S323. Determine whether the first time t1 and the second time t2 do not exist. If they do, it means that the system has no dehumidification requirement, and proceed to step S326. Otherwise, proceed to step S324.

[0204] S324. Select the larger value between the first dehumidification time Δt1 and the second dehumidification time Δt2 as the dehumidifier's operating time Δt.

[0205] S325. Turn on the dehumidifier and run for Δt.

[0206] S326, Based on the surface temperature T of the prefabricated cabin b and dew point temperature T d Determine when to stop the dehumidifier;

[0207] Specifically, determining the dew point temperature T d and the surface temperature T of the prefabricated cabin b Does T satisfy? d <T b If the temperature is -5℃, the dehumidifier will stop; otherwise, return to step S2.

[0208] The formula for calculating the surface temperature of the prefabricated cabin is as follows:

[0209] ;

[0210] Where T is the equivalent temperature, T w R represents the external temperature. i R0 is the heat transfer resistance of the inner surface of the prefabricated cabin, and R0 is the heat transfer resistance of the cabin body.

[0211] S4. After the device completes the start / stop command, it returns to step S2. That is, after the air conditioner, electric heater, or dehumidifier completes the start or stop command and the running time is completed, it returns to step S2 to obtain the latest prediction data again and complete subsequent judgments and related calculations.

[0212] Example 3, this example will be based on Figure 7 and Figure 8 Describes an AI-predictive prefabricated cabin adaptive environmental conditioning system 100 and electronic equipment 200.

[0213] Reference Figure 7 As shown, the prefabricated cabin adaptive environment control system 100 based on AI prediction includes:

[0214] The data acquisition module 110 is used to collect the cabin data, real-time environmental data and real-time operation data of the prefabricated cabin, and is also used to calculate the equivalent temperature and equivalent humidity inside the prefabricated cabin.

[0215] Prediction module 120 is used to output predicted temperature sequence and predicted humidity sequence based on the data in the data acquisition module;

[0216] Data processing module 130 is used to determine the start-up and shutdown timing of the equipment based on the comparison results between the predicted temperature sequence and the predicted humidity sequence and the environmental parameter limits;

[0217] The equipment execution module 140 is used to control the equipment to complete parameter adjustment and start / stop actions according to the start / stop timing.

[0218] The system adopts a parametric design, and all key parameters can be set according to actual usage needs, which has good adaptability and high flexibility. By defining general parameters, the system can be applied to prefabricated cabins of different specifications and different environmental control requirements.

[0219] It should be understood that the regulation system 100 here is embodied in the form of functional modules. The term "module" here can refer to application-specific integrated circuits (ASICs), electronic circuits, processors (e.g., shared processors, proprietary processors, or group processors, etc.) and memories for executing one or more software or firmware programs, integrated logic circuits, and / or other suitable components supporting the described functions. In an alternative example, those skilled in the art will understand that the regulation system 100 may be specifically the electronic device 200 in the above embodiments, or the functions of the electronic device 200 in the above embodiments may be integrated into the regulation system 100. The regulation system 100 may be used to execute the various processes and / or steps corresponding to the electronic device 200 in the above method embodiments; to avoid repetition, these will not be described again here.

[0220] The aforementioned adjustment system 100 has the function of implementing the corresponding steps performed by the electronic device 200 of the adjustment method in Embodiment 1; the aforementioned function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the aforementioned function. For example, the aforementioned acquisition module can be a communication interface, such as a transceiver interface.

[0221] In the embodiments of this application, Figure 7 The regulation system 100 can also be a chip or a chip system, such as a system on chip (SoC).

[0222] Reference Figure 8 As shown, in this embodiment, an electronic device 200 is provided, including:

[0223] Processor 210, and memory 220 and transceiver 230 communicatively connected to said processor;

[0224] The memory 220 stores computer-executed instructions; the transceiver 230 is used for sending and receiving data.

[0225] The processor 210 executes the computer execution instructions stored in the memory 220 to implement the adjustment method in Embodiment 1.

[0226] It should be understood that the electronic device 200 can be used to perform the corresponding steps and / or processes in the above method embodiments. Optionally, the memory 220 may include read-only memory and random access memory, and provide instructions and data to the processor. A portion of the memory 220 may also include non-volatile random access memory. For example, the memory 220 may also store device type information. The processor 210 can be used to execute instructions stored in the memory 220, and when the processor 210 executes the instructions, the processor 210 can perform the corresponding steps and / or processes in the above method embodiments.

[0227] It should be understood that, in the embodiments of this application, the processor 210 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0228] In implementation, each step of the above method can be completed by the integrated logic circuitry of the hardware in the processor 210 or by instructions in software form. The steps of the method disclosed in the embodiments of this application can be directly embodied in the execution by the hardware processor, or by a combination of hardware and software modules in the processor 210. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor executes the instructions in the memory, combining them with its hardware to complete the steps of the above method. To avoid repetition, detailed descriptions are not provided here.

[0229] Example 4: In this example, a computer-readable storage medium is provided, which stores computer-executable instructions. When executed by a processor, the computer-executable instructions are used to implement the adjustment method in Example 1.

[0230] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0231] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0232] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0233] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0234] In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0235] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A prefabricated cabin adaptive environmental regulation method based on AI prediction, characterized in that, Includes the following steps: S1. Calculate the equivalent temperature and equivalent humidity inside the prefabricated cabin based on the location of the temperature and humidity sensors inside the cabin and the collected temperature and humidity data. S2. Obtain the predicted temperature and humidity sequences within the time range t; S3. Determine the start-up and shutdown timing of the equipment based on the comparison results between the predicted temperature sequence and the predicted humidity sequence and the environmental parameter limits; the environmental parameter limits include temperature limits, humidity limits, and dew point temperature limits; the equipment includes air conditioners, electric heaters, and dehumidifiers; the determination process includes the following steps: S31. Compare the predicted temperature sequence with the temperature limit, and output the start / stop timing of the air conditioner or electric heater based on the comparison result; S32. Determine the moment when the humidity limit is first met in the predicted humidity sequence, and record it as the first moment. Calculate the dehumidification time required for the predicted humidity to reach the set humidity at the first moment, and record it as the first dehumidification time. Calculate the predicted dew point temperature sequence, determine the moment when the dew point temperature limit is first met in the predicted dew point temperature sequence, and record it as the second moment. Calculate the dehumidification time required for the predicted humidity to reach the target humidity at the second moment, and record it as the second dehumidification time. If neither the first nor the second time point exists, the dehumidifier's shutdown time is determined based on the surface temperature and dew point temperature of the prefabricated compartment; otherwise, the larger of the first and second dehumidification times is selected as the dehumidifier's operating time. S4. After the device completes the start / stop command, return to step S2. 2.The AI prediction based prefabricated cabin adaptive environmental regulation method according to claim 1, characterized in that, The calculation process for the first dehumidification time is as follows: The moment when the humidity limit is first met in the predicted humidity sequence is determined and denoted as the first moment; the predicted humidity corresponding to the first moment is denoted as the first predicted humidity. Calculate the amount of dehumidification required for the first predicted humidity to reach the set humidity, and record it as the first dehumidification amount; The first dehumidification time is calculated based on the number of dehumidifiers and their rated dehumidification capacity, using the following formula: First dehumidification time = First dehumidification capacity / (Number of dehumidifiers × Rated dehumidification capacity). 3.The AI prediction based prefabricated cabin adaptive environmental regulation method according to claim 1, characterized in that, The calculation process for the second dehumidification time is as follows: Calculate and predict the dew point temperature series; The moment when the dew point temperature limit is first met in the predicted dew point temperature sequence is denoted as the second moment; the predicted humidity corresponding to the second moment in the predicted humidity sequence is denoted as the second predicted humidity; and the predicted temperature corresponding to the second moment in the predicted temperature sequence is denoted as the second predicted temperature. Calculate the target humidity based on the second predicted temperature and the set dew point temperature; Calculate the amount of dehumidification required for the second predicted humidity to reach the target humidity, and denot it as the second dehumidification amount; The second dehumidification time is calculated based on the number of dehumidifiers and their rated dehumidification capacity, using the following formula: Second dehumidification time = Second dehumidification capacity / (Number of dehumidifiers × Rated dehumidification capacity). 4.The AI prediction based prefabricated cabin adaptive environmental regulation method according to claim 1, wherein, Step S3 further includes: when the dehumidifier starts, a timer is started synchronously; when the timer ends, if the dehumidifier is still on, the start / stop judgment program of the air conditioner is started. The start-stop judging program of the air conditioner comprises: judging whether the equivalent temperature T max -15℃ < T < T max -10℃, T max is a temperature upper limit value; if yes, the air conditioner is started to cool, and a cooling value T set is set; otherwise, the judging program is ended.

5. The AI-predictive-based adaptive environment adjustment method for prefabricated cabins according to claim 1, characterized in that, During the operation of the air conditioner, it is judged whether the equivalent temperature satisfies T < T max -15℃, if yes, the air conditioner is turned off, and the judgment program is ended. Otherwise, judge the dew point temperature T d and the surface temperature T of the prefabricated cabin b whether T d <T b -5℃ and T d <T dmax -5℃, T dmax is the dew point temperature limit value; if it is satisfied, the air conditioner is turned off, and the judgment program is ended; otherwise, return to the previous step of judgment. 6.The AI prediction based prefabricated cabin adaptive environmental regulation method according to claim 4, characterized in that, The step S32, which determines when to stop the dehumidifier based on the surface temperature and dew point temperature of the prefabricated compartment, includes: When the dew point temperature and the surface temperature of the prefabricated compartment meet the condition that the dew point temperature is less than the surface temperature -5°C, the dehumidifier stops and the timer is reset. 7.The AI prediction based prefabricated cabin adaptive environmental regulation method according to claim 1, wherein, The parameters required in the acquisition process of the predicted temperature sequence and the predicted humidity sequence in the step S2 include: air conditioner power P L , electric heater power P d , dehumidifier dehumidification capacity C, equivalent temperature T in the prefabricated cabin, equivalent humidity H, external temperature T w outside the prefabricated cabin, external humidity H w , and opening and closing state of the prefabricated cabin door.

8. A prefabricated cabin adaptive environmental control system based on AI prediction, characterized by, To achieve the AI-predictive-based adaptive environment adjustment method for prefabricated cabins as described in any one of claims 1-7, the method includes: The data acquisition module is used to collect cabin data, real-time environmental data and real-time operation data of the prefabricated cabin, and also to calculate the equivalent temperature and equivalent humidity inside the prefabricated cabin; The prediction module is used to output predicted temperature and predicted humidity sequences based on the data from the data acquisition module. The data processing module is used to determine the start-up and shutdown timing of the equipment based on the comparison results between the predicted temperature sequence and the predicted humidity sequence and the environmental parameter limits; The equipment execution module is used to control the equipment to complete parameter adjustment and start / stop actions according to the start / stop timing.

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