Ventilation control method, device, system and equipment and storage medium

Abstract

The invention provides a ventilation control method, device, system and equipment and a storage medium, and relates to the technical field of rail transit. The method comprises the following steps: acquiring respective environment data of a plurality of region blocks in a target region within a preset time period; based on the respective environment data of the plurality of region blocks, determining respective region block statistical indexes of the plurality of region blocks and a region statistical index of the target region; predicting predicted environment data at a future moment based on the region block statistical indexes of the plurality of region blocks, the region statistical index of the target region and an environment data prediction model; therefore, the environmental data prediction at the future moment is performed by means of the environmental data prediction model, and the predicted environmental data and the target environmental data at the future moment are taken as the basis of ventilation control to perform ventilation control on the ventilation equipment in the target area in advance, so that the environmental change at the future moment can be better coped with; the defect of lag control in the prior art is overcome, and the accuracy of ventilation control is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of rail transit technology, and in particular to a ventilation control method, device, system, equipment and storage medium. Background Art

[0002] The subway ventilation and air-conditioning system is controlled and monitored by the subway environment and equipment monitoring system (Building Automation System, BAS), which is used to adjust the environmental data of the station area to improve the riding comfort of passengers.

[0003] At present, BAS mainly uses proportional-integral-derivative (PID) controller or fuzzy PID controller to control ventilation equipment in the station area, such as air conditioning units and fresh air fans, to adjust the environmental data of the station area. Among them, when using PID controller to control ventilation equipment in the station area, it is mainly to compare the collected return air temperature with the given temperature value, and ventilate according to the temperature deviation; when using fuzzy PID controller to control ventilation equipment in the station area, it is mainly to compare the collected carbon dioxide concentration with the given carbon dioxide concentration, and control ventilation according to the deviation and the deviation change.

[0004] However, the above two control methods cannot perform ventilation control on the heat generated in the future in advance. The heat is collected and ventilation control is performed in real time after the heat is generated. There is a problem of lagging control, which leads to low accuracy of ventilation control. Summary of the invention

[0005] The present application provides a ventilation control method, device, system, equipment and storage medium to solve the defects of the hysteresis control problem existing in the prior art, thereby improving the accuracy of ventilation control.

[0006] The present application provides a ventilation control method, which is applied to a programmable logic controller (PLC) device, and the method comprises: Collecting environmental data of each of a plurality of area blocks in a target area within a preset time period, wherein the environmental data includes at least two of temperature, humidity and carbon dioxide concentration; Determining the regional block statistical indicators of the respective regional blocks and the regional statistical indicators of the target area based on the environmental data of the respective regional blocks; Based on the regional block statistical indicators of each of the multiple regional blocks, the regional statistical indicators of the target area and the environmental data prediction model, predict the predicted environmental data at a future time; wherein the environmental data prediction model is trained based on the regional block statistical indicators of each of the multiple sample regional blocks, the regional statistical indicators of the sample areas to which the multiple sample regional blocks belong and the corresponding environmental data labels; Based on the predicted environmental data and the target environmental data at the future moment, ventilation control is performed on the ventilation equipment in the target area.

[0007] According to a ventilation control method provided by the present application, the environmental data prediction model includes a plurality of LSTM units; The predicting of the predicted environmental data at a future time based on the regional block statistical indicators of each of the plurality of regional blocks, the regional statistical indicators of the target area and the environmental data prediction model includes: Normalizing the respective regional block statistical indicators of the plurality of regional blocks and the regional statistical indicator of the target area to obtain the respective target regional block statistical indicators of the plurality of regional blocks and the target area statistical indicator of the target area; Inputting the target area block statistical indicators of each of the multiple area blocks and the target area statistical indicators of the target area into each of the LSTM units, respectively, to obtain the predicted sub-environment data of the corresponding time series output by each of the LSTM units; wherein the time series corresponding to the multiple LSTM units constitute the preset time period; Integrate the predicted sub-environmental data of the corresponding time series output by each of the LSTM units to obtain the initial environmental data at the future moment; The initial environmental data is denormalized to obtain the predicted environmental data at the future moment.

[0008] According to a ventilation control method provided by the present application, determining the respective regional block statistical indicators of the plurality of regional blocks and the regional statistical indicators of the target area based on the respective environmental data of the plurality of regional blocks includes: Preprocessing the environmental data of each of the plurality of area blocks to obtain the preprocessed environmental data of each of the plurality of area blocks; For each of the area blocks, extracting key environmental features corresponding to the area block from the preprocessed environmental data of the area block, wherein the key environmental features are used to characterize changes in the environmental data of the area block; Based on the key environmental features corresponding to the respective area blocks, area block statistical indicators of the plurality of area blocks and area statistical indicators of the target area are determined.

[0009] According to a ventilation control method provided by the present application, the determining of the regional block statistical indicators of each of the plurality of regional blocks and the regional statistical indicators of the target area based on the key environmental features corresponding to each of the regional blocks includes: Aggregating the key environmental features corresponding to each of the area blocks to obtain the overall environmental data of the target area; For each of the area blocks, based on the key environmental features corresponding to the area block, determine the area block statistical index of the area block; According to the overall environmental data of the target area, regional statistical indicators of the target area are determined.

[0010] According to a ventilation control method provided by the present application, the ventilation control of the ventilation equipment in the target area based on the predicted environment data and the target environment data at the future moment includes: Determining difference data between the predicted environment data and the target environment data at the future moment; Based on the difference data, determining the ventilation control amount corresponding to the ventilation equipment; A control instruction is sent to the ventilation device, where the control instruction is used to control the ventilation device to perform ventilation control based on the ventilation control amount.

[0011] The present application also provides a ventilation control device, which is applied to a programmable logic controller (PLC) device, and the device comprises: A collection unit, used to collect environmental data of each of a plurality of area blocks in a target area within a preset time period, wherein the environmental data includes at least two of temperature, humidity and carbon dioxide concentration; A processing unit, configured to determine the regional block statistical indicators of each of the plurality of regional blocks and the regional statistical indicator of the target area based on the environmental data of each of the plurality of regional blocks; A prediction unit, configured to predict predicted environmental data at a future time based on the respective regional block statistical indicators of the plurality of regional blocks, the regional statistical indicators of the target area, and an environmental data prediction model; wherein the environmental data prediction model is obtained by training based on the respective regional block statistical indicators of the plurality of sample regional blocks, the regional statistical indicators of the sample areas to which the plurality of sample regional blocks belong, and the corresponding environmental data labels; A control unit is used to perform ventilation control on the ventilation equipment in the target area based on the predicted environmental data and the target environmental data at the future moment.

[0012] The present application also provides a ventilation control system, including a programmable logic controller PLC device and a ventilation device; The PLC device is used to collect environmental data of each of a plurality of area blocks in a target area within a preset time period, wherein the environmental data includes at least two of temperature, humidity and carbon dioxide concentration; The PLC device is further used to determine the regional block statistical indicators of each of the plurality of regional blocks and the regional statistical indicators of the target area based on the environmental data of each of the plurality of regional blocks; The PLC device is further used to predict the predicted environmental data at a future time based on the regional block statistical indicators of each of the multiple regional blocks, the regional statistical indicators of the target area and the environmental data prediction model; wherein the environmental data prediction model is trained based on the regional block statistical indicators of each of the multiple sample regional blocks, the regional statistical indicators of the sample areas to which the multiple sample regional blocks belong and the corresponding environmental data labels; The PLC device is also used to perform ventilation control on the ventilation equipment in the target area based on the predicted environmental data and the target environmental data at the future moment.

[0013] The present application also provides a programmable logic controller (PLC) device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a ventilation control method as described above is implemented.

[0014] The present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the ventilation control method as described in any one of the above is implemented.

[0015] The present application also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the ventilation control method as described above is implemented.

[0016] The ventilation control method, device, system, equipment and storage medium provided by the present application can first collect the environmental data of each of the multiple area blocks in the target area within a preset time period when performing ventilation control; and determine the area block statistical indicators of each of the multiple area blocks and the area statistical indicators of the target area based on the environmental data of each of the multiple area blocks; and then predict the predicted environmental data at future times based on the area block statistical indicators of each of the multiple area blocks, the area statistical indicators of the target area and the environmental data prediction model; in this way, the environmental data at future times are predicted with the help of the environmental data prediction model, and the obtained predicted environmental data and the target environmental data at future times are used as the basis for ventilation control, and the ventilation equipment in the target area is controlled in advance, which can better cope with environmental changes at future times, not only improve the response speed and control accuracy, but also improve the energy utilization rate, solve the defects of the problem of lag control in the prior art, and thus effectively improve the accuracy of ventilation control. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 A flow chart of a ventilation control method provided in an embodiment of the present application.

[0019] Figure 2 A schematic diagram of a flow chart for determining regional block statistical indicators of a plurality of regional blocks and regional statistical indicators of a target area provided in an embodiment of the present application.

[0020] Figure 3 A schematic diagram of the structure of an environmental data prediction model provided in an embodiment of the present application.

[0021] Figure 4 A schematic structural diagram of a ventilation control device provided in an embodiment of the present application.

[0022] Figure 5 A schematic diagram of the physical structure of a programmable logic controller (PLC) device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0024] In the embodiments of the present application, "at least one" means one or more, and "more" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In the text description of the present application, the character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0025] The technical solution provided by the embodiment of the present application can be adapted to ventilation control scenarios. Taking the subway ventilation and air-conditioning system as an example, the subway environment and equipment monitoring system BAS mainly uses a PID controller or a fuzzy PID controller to control ventilation equipment in the station area, such as air-conditioning units and fresh air fans, to adjust the environmental data of the station area.

[0026] Among them, when using PID controller to control ventilation equipment in the station area, it is mainly to build a fixed value closed-loop negative feedback regulation system, send the return air temperature measured by the temperature sensor to the PLC controller for comparison with the given temperature value, and adjust the opening of the chilled return water regulating valve according to the PID law based on the temperature deviation to control the chilled water return volume, thereby controlling the ventilation equipment in the station area.

[0027] When the fuzzy PID controller is used to control the ventilation equipment in the station area, a dual-input and three-output structure mode is mainly adopted. 800ppm is used as the given carbon dioxide concentration, and the actual collected carbon dioxide concentration is compared with the given carbon dioxide concentration. The deviation and the deviation change rate are calculated as the input of the fuzzy PID control, and then the operating speed of the ventilation equipment is controlled by fuzzy calculation to change the air supply volume, thereby controlling the ventilation equipment in the station area.

[0028] However, the control method using PID controller cannot adapt to the changes in temperature, humidity and passenger flow in the subway environment; the control method using fuzzy PID controller only considers the impact of carbon dioxide concentration, and does not consider the impact of temperature and humidity on the environment in the station at the same time. Moreover, it is impossible to control the ventilation in advance for the heat generated in the future. The heat is collected and controlled in real time after it is generated, which has the problem of lagging control, resulting in low accuracy of ventilation control.

[0029] In order to solve the problem of lagging control and thus improve the accuracy of ventilation control, an embodiment of the present application provides a ventilation control method that can be applied to a PLC controller. The difference is that the PLC controller is a controller with stronger computing power, for example, a controller based on the IEC 61499 standard, which can better serve as a hardware platform for ventilation control, better support the implementation of intelligent control, and enable the subway environment and equipment monitoring system BAS to have good scalability and adaptability, facilitating subsequent maintenance and upgrades.

[0030] In addition, the ventilation control method provided in the embodiment of the present application has strong portability, reusability and improves the dynamic reconstruction capability of the ventilation control system, making it easier to develop, deploy, maintain and upgrade.

[0031] The ventilation control method provided by the present application will be described in detail below through the following specific embodiments. It is understandable that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0032] Figure 1 A flow chart of a ventilation control method provided in an embodiment of the present application is applied to a programmable logic controller (PLC) device. For example, see Figure 1 As shown, the ventilation control method may include: S101 , collecting environmental data of a plurality of area blocks in a target area within a preset time period, where the environmental data includes at least two of temperature, humidity and carbon dioxide concentration.

[0033] The value of the preset time period can be set according to actual needs.

[0034] For example, the target area may be a public area of ​​a subway station, or a public area of ​​a movie theater, etc., and may be specifically set according to actual needs.

[0035] Taking the collected environmental data of an area block including temperature, humidity and carbon dioxide concentration as an example, for example, when collecting the temperature, humidity and carbon dioxide concentration of a certain area block, the temperature in the area block can be collected by a temperature sensor set in the area block, the humidity in the area block can be collected by a humidity sensor set in the area block, and the carbon dioxide concentration in the area block can be collected by a carbon dioxide concentration sensor set in the area block, thereby collecting the environmental data of the area block.

[0036] After collecting the environmental data of the plurality of area blocks, the area block statistical indicators of the plurality of area blocks and the area statistical indicators of the target area can be determined based on the environmental data of the plurality of area blocks, that is, the following S102 is performed: S102: Determine the regional block statistical indicators of the plurality of regional blocks and the regional statistical indicators of the target area based on the environmental data of the plurality of regional blocks.

[0037] For example, the statistical indicators may include mean, variance, maximum value, minimum value, etc., which may be set according to actual needs.

[0038] Taking the environmental data of the area block including temperature, humidity and carbon dioxide concentration as an example, the area block statistical indicators of the area block may include the mean, variance, maximum value, minimum value, etc. corresponding to the temperature, humidity and carbon dioxide concentration respectively.

[0039] Similarly, taking the environmental data of the target area including temperature, humidity and carbon dioxide concentration as an example, the regional statistical indicators of the target area may include the mean, variance, maximum value, minimum value, etc. corresponding to the temperature, humidity and carbon dioxide concentration respectively.

[0040] After calculating and obtaining the regional block statistical indicators of the multiple regional blocks and the regional statistical indicators of the target area, the predicted environmental data at the future moment can be predicted by means of the environmental data prediction model based on deep learning, that is, the following S103 is executed: S103: predicting environmental data at a future time based on the regional block statistical indicators of each of the plurality of regional blocks, the regional statistical indicators of the target area and the environmental data prediction model.

[0041] The environmental data prediction model is obtained by training based on the regional block statistical indicators of each of the multiple sample regional blocks, the regional statistical indicators of the sample areas to which the multiple sample regional blocks belong, and the corresponding environmental data labels.

[0042] For example, in an embodiment of the present application, the environmental data prediction model may be a deep learning model based on long short-term memory networks (Long Short-Term Memory networks), which may be specifically set according to actual needs.

[0043] In an embodiment of the present application, after determining the regional block statistical indicators of the multiple regional blocks and the regional statistical indicators of the target area based on the environmental data of each of the multiple regional blocks, the environmental data prediction model is used to jointly predict the environmental data at future times, and the obtained predicted environmental data is used as the basis for ventilation control so that ventilation control can be performed in advance. This can better cope with environmental changes at future times, not only improve the response speed and control accuracy, but also improve the energy utilization rate, so that the ventilation control system can operate stably for a long time, thereby reducing operating costs.

[0044] S104: Based on the predicted environmental data and the target environmental data at a future moment, ventilation control is performed on the ventilation equipment in the target area.

[0045] Among them, the target environmental data at the future moment can be understood as the environmental data expected at the future moment.

[0046] Taking the collected environmental data of the regional block including temperature, humidity and carbon dioxide concentration as an example, the target environmental data at the future moment includes the target temperature, target humidity and target carbon dioxide concentration expected at the future moment.

[0047] It can be seen that in the embodiment of the present application, when performing ventilation control, the environmental data of each of the multiple area blocks in the target area within a preset time period can be first collected; and based on the environmental data of each of the multiple area blocks, the area block statistical indicators of each of the multiple area blocks and the area statistical indicators of the target area are determined; and then based on the area block statistical indicators of each of the multiple area blocks, the area statistical indicators of the target area and the environmental data prediction model, the predicted environmental data at future times are predicted; in this way, the environmental data prediction model is used to predict the environmental data at future times, and the obtained predicted environmental data and the target environmental data at future times are used as the basis for ventilation control, and the ventilation equipment in the target area is controlled in advance, which can better cope with environmental changes at future times, not only improve the response speed and control accuracy, but also improve the energy utilization rate, solve the defects of the problem of lag control in the prior art, thereby effectively improving the accuracy of ventilation control.

[0048] Based on the above Figure 1 In the embodiment shown, for example, in the above S102, based on the environmental data of each of the multiple regional blocks, when determining the regional block statistical indicators of the multiple regional blocks and the regional statistical indicators of the target area, please refer to the following for details. Figure 2 The embodiment shown.

[0049] Figure 2 A flow chart of determining regional block statistical indicators of a plurality of regional blocks and regional statistical indicators of a target area provided in an embodiment of the present application, the method may include: S201 , preprocessing the environmental data of each of the plurality of area blocks to obtain the preprocessed environmental data of each of the plurality of area blocks.

[0050] For example, in an embodiment of the present application, when preprocessing the environmental data of each of the multiple regional blocks, the preprocessing operation may include data cleaning, data smoothing or time synchronization operation, etc., which can be specifically set according to actual needs.

[0051] Taking the preprocessing operations including data cleaning, data smoothing and time synchronization as an example, a moving average algorithm or a Kalman filter algorithm can be first used to clean the environmental data of multiple regional blocks to obtain cleaned environmental data; and a filter can be used to smooth the cleaned environmental data to obtain smoothed environmental data; and a time synchronization algorithm can be used to synchronize the smoothed environmental data to obtain preprocessed environmental data.

[0052] By way of example, in an embodiment of the present application, after the time synchronization algorithm is used to time synchronize the environmental data after smoothing, the 3sigma criterion can be further used to perform anomaly detection on the environmental data after time synchronization to obtain abnormal environmental data, and the abnormal environmental data can be eliminated from the environmental data after time synchronization to obtain preprocessed environmental data. The specific settings can be made according to actual needs.

[0053] S202 . For each area block, extract key environmental features corresponding to the area block from the pre-processed environmental data of the area block, where the key environmental features are used to characterize changes in the environmental data of the area block.

[0054] For example, the key environmental characteristics may include a change rate, a moving average, a peak value, etc., which may be set according to actual needs.

[0055] Taking the environmental data after preprocessing of the regional block including temperature, humidity and carbon dioxide concentration as an example, the key environmental features extracted may include the change rate, moving average, peak value, etc. corresponding to the temperature, humidity and carbon dioxide concentration.

[0056] After extracting the key environmental features corresponding to each area block, the following S203 can be further performed: S203: Determine the regional block statistical indicators of the plurality of regional blocks and the regional statistical indicators of the target area based on the key environmental features corresponding to the respective regional blocks.

[0057] By way of example, in an embodiment of the present application, when determining the regional block statistical indicators of multiple regional blocks and the regional statistical indicators of the target area based on the key environmental features corresponding to each regional block, the key environmental features corresponding to each regional block can be first aggregated to obtain the overall environmental data of the target area; for each regional block, the regional block statistical indicators of the regional block can be determined based on the key environmental features corresponding to the regional block; and the regional statistical indicators of the target area can be determined based on the overall environmental data of the target area.

[0058] In combination with the description in S202 above, taking the key environmental characteristics including the change rate, moving average and peak value corresponding to the temperature, humidity and carbon dioxide concentration as an example, the key environmental characteristics corresponding to each area block are aggregated, and the obtained overall environmental data may include the average temperature, average humidity and average carbon dioxide concentration of the target area as a whole, so as to perform overall analysis and decision-making control on the target area.

[0059] By way of example, in an embodiment of the present application, after obtaining the regional block statistical indicators of each of the multiple regional blocks and the regional statistical indicators of the target area, anomaly detection can be further performed on the regional block statistical indicators of each of the multiple regional blocks and the regional statistical indicators of the target area to obtain abnormal statistical indicators; and the abnormal statistical indicators can be eliminated to obtain statistical indicators of better quality, and on the basis of these statistical indicators of better quality, the predicted environmental data at future times can be jointly predicted in combination with the environmental data prediction model.

[0060] For example, in the embodiment of the present application, the environmental data prediction model includes multiple LSTM units, which can be seen in Figure 3 As shown, Figure 3 A structural schematic diagram of an environmental data prediction model provided for an embodiment of the present application, based on the regional block statistical indicators of each of the multiple regional blocks, the regional statistical indicators of the target area and the environmental data prediction model, when predicting the predicted environmental data at a future time, the regional block statistical indicators of each of the multiple regional blocks and the regional statistical indicators of the target area can be first normalized to obtain the target regional block statistical indicators of each of the multiple regional blocks and the target area statistical indicators of the target area; and the target regional block statistical indicators of each of the multiple regional blocks and the target area statistical indicators of the target area are respectively input into each LSTM unit to obtain the predicted sub-environmental data of the corresponding time series output by each LSTM unit; wherein the time series corresponding to the multiple LSTM units constitute a preset time period; the predicted sub-environmental data of the corresponding time series output by each LSTM unit are integrated to obtain the initial environmental data at a future time; and the initial environmental data are then denormalized to obtain the predicted environmental data at a future time.

[0061] In this way, the environmental data prediction model is used to predict the environmental data at future moments, and the predicted environmental data and the target environmental data at future moments are used as the basis for ventilation control. The ventilation equipment in the target area can be controlled in advance, which can better cope with environmental changes at future moments. It not only improves the response speed and control accuracy, but also improves energy utilization, solves the defects of the lag control problem in the prior art, and thus effectively improves the accuracy of ventilation control.

[0062] Based on any of the above embodiments, after the predicted environmental data at a future moment is predicted through the environmental data prediction model, the above S104 can be executed, and ventilation control can be performed on the ventilation equipment in the target area based on the predicted environmental data and the target environmental data at the future moment. For example, in an embodiment of the present application, the difference data between the predicted environmental data and the target environmental data at the future moment can be first determined; based on the difference data, the ventilation control amount corresponding to the ventilation equipment can be determined; a control instruction is sent to the ventilation equipment, and the control instruction may include the ventilation control amount, so that the control instruction is used to control the ventilation equipment to perform ventilation control based on the ventilation control amount, so that the ventilation control of the ventilation equipment in the target area can be performed in advance, and the environmental changes at the future moment can be better coped with, and the defects of the problem of lagging control existing in the prior art are solved, thereby effectively improving the accuracy of ventilation control.

[0063] For example, the ventilation control quantity may include the wind speed of the fresh air fan, the air volume of the fresh air fan, the output temperature of the air-conditioning unit, the switching of the air-conditioning unit mode, etc., which can be set according to actual needs.

[0064] After sending the control instruction to the ventilation device, the ventilation device may first parse the received control instruction and perform ventilation control according to the ventilation control amount included in the parsed control instruction.

[0065] For example, after the ventilation control is performed based on the ventilation control amount, the entire execution process of the ventilation control can also be monitored, and corresponding execution feedback information can be generated to ensure the correctness of the execution and provide a reference for subsequent ventilation control.

[0066] The ventilation control device provided in the present application is described below. The ventilation control device described below and the ventilation control method described above can be referenced to each other.

[0067] Figure 4 A schematic diagram of the structure of a ventilation control device provided in an embodiment of the present application is applied to a programmable logic controller PLC device. For example, see Figure 4 As shown, the ventilation control device 40 may include: A collection unit 401 is used to collect environmental data of each of a plurality of area blocks in a target area within a preset time period, wherein the environmental data includes at least two of temperature, humidity and carbon dioxide concentration; The processing unit 402 is configured to determine the regional block statistical indicators of each of the plurality of regional blocks and the regional statistical indicator of the target area based on the environmental data of each of the plurality of regional blocks; A prediction unit 403 is used to predict the predicted environmental data at a future time based on the regional block statistical indicators of each of the multiple regional blocks, the regional statistical indicators of the target area, and an environmental data prediction model; wherein the environmental data prediction model is trained based on the regional block statistical indicators of each of the multiple sample regional blocks, the regional statistical indicators of the sample areas to which the multiple sample regional blocks belong, and the corresponding environmental data labels; The control unit 404 is used to perform ventilation control on the ventilation equipment in the target area based on the predicted environmental data and the target environmental data at the future moment.

[0068] For example, in an embodiment of the present application, the environmental data prediction model includes a plurality of LSTM units; The prediction unit 403 is used to predict the predicted environmental data at a future time based on the regional block statistical indicators of each of the multiple regional blocks, the regional statistical indicators of the target area and the environmental data prediction model, including: Normalizing the respective regional block statistical indicators of the plurality of regional blocks and the regional statistical indicator of the target area to obtain the respective target regional block statistical indicators of the plurality of regional blocks and the target area statistical indicator of the target area; Inputting the target area block statistical indicators of each of the multiple area blocks and the target area statistical indicators of the target area into each of the LSTM units, respectively, to obtain the predicted sub-environment data of the corresponding time series output by each of the LSTM units; wherein the time series corresponding to the multiple LSTM units constitute the preset time period; Integrate the predicted sub-environmental data of the corresponding time series output by each of the LSTM units to obtain the initial environmental data at the future moment; The initial environmental data is denormalized to obtain the predicted environmental data at the future moment.

[0069] For example, in the embodiment of the present application, the processing unit 402 is used to determine the regional block statistical indicators of each of the multiple regional blocks and the regional statistical indicators of the target area based on the environmental data of each of the multiple regional blocks, including: Preprocessing the environmental data of each of the plurality of area blocks to obtain the preprocessed environmental data of each of the plurality of area blocks; For each of the area blocks, extracting key environmental features corresponding to the area block from the preprocessed environmental data of the area block, wherein the key environmental features are used to characterize changes in the environmental data of the area block; Based on the key environmental features corresponding to the respective area blocks, area block statistical indicators of the plurality of area blocks and area statistical indicators of the target area are determined.

[0070] For example, in the embodiment of the present application, the processing unit 402 is used to determine the regional block statistical indicators of each of the multiple regional blocks and the regional statistical indicators of the target area based on the key environmental features corresponding to each of the regional blocks, including: Aggregating the key environmental features corresponding to each of the area blocks to obtain the overall environmental data of the target area; For each of the area blocks, based on the key environmental features corresponding to the area block, determine the area block statistical index of the area block; According to the overall environmental data of the target area, regional statistical indicators of the target area are determined.

[0071] For example, in the embodiment of the present application, the control unit 404 is used to perform ventilation control on the ventilation equipment in the target area based on the predicted environment data and the target environment data at the future moment, including: Determining difference data between the predicted environment data and the target environment data at the future moment; Based on the difference data, determining the ventilation control amount corresponding to the ventilation equipment; A control instruction is sent to the ventilation device, where the control instruction is used to control the ventilation device to perform ventilation control based on the ventilation control amount.

[0072] The ventilation control device 40 provided in the embodiment of the present application can execute the technical solution of the ventilation control method in any of the above-mentioned embodiments. Its implementation principle and beneficial effects are similar to the implementation principle and beneficial effects of the ventilation control method. Please refer to the implementation principle and beneficial effects of the ventilation control method, and no further details will be given here.

[0073] Figure 5 A schematic diagram of the physical structure of a programmable logic controller (PLC) device provided in an embodiment of the present application is shown in FIG. Figure 5As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 430 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute the ventilation control method, which includes: collecting environmental data of each of the multiple area blocks in the target area within a preset time period, wherein the environmental data includes at least two of temperature, humidity and carbon dioxide concentration; based on the environmental data of each of the multiple area blocks, determining the area block statistical indicators of each of the multiple area blocks and the regional statistical indicators of the target area; based on the area block statistical indicators of each of the multiple area blocks, the regional statistical indicators of the target area and the environmental data prediction model, predicting the predicted environmental data at a future moment; wherein the environmental data prediction model is obtained by training based on the area block statistical indicators of each of the multiple sample area blocks, the regional statistical indicators of the sample areas to which the multiple sample area blocks belong and the corresponding environmental data labels; based on the predicted environmental data and the target environmental data at the future moment, performing ventilation control on the ventilation equipment in the target area.

[0074] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0075] On the other hand, the present application also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the ventilation control method provided by the above-mentioned methods, which includes: collecting environmental data of each of multiple area blocks in a target area within a preset time period, and the environmental data includes at least two of temperature, humidity and carbon dioxide concentration; based on the environmental data of each of the multiple area blocks, determining the area block statistical indicators of each of the multiple area blocks and the regional statistical indicators of the target area; based on the area block statistical indicators of each of the multiple area blocks, the regional statistical indicators of the target area and the environmental data prediction model, predicting the predicted environmental data at a future time; wherein the environmental data prediction model is trained based on the area block statistical indicators of each of the multiple sample area blocks, the regional statistical indicators of the sample areas to which the multiple sample area blocks belong and the corresponding environmental data labels; based on the predicted environmental data and the target environmental data at the future time, ventilation control is performed on the ventilation equipment in the target area.

[0076] On the other hand, the present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented by a processor to execute the ventilation control method provided by the above-mentioned methods when the computer program is executed, the method comprising: collecting environmental data of each of a plurality of area blocks in a target area within a preset time period, the environmental data comprising at least two of temperature, humidity and carbon dioxide concentration; determining the area block statistical indicators of each of the plurality of area blocks and the regional statistical indicators of the target area based on the environmental data of each of the plurality of area blocks; predicting the predicted environmental data at a future moment based on the area block statistical indicators of each of the plurality of area blocks, the regional statistical indicators of the target area and an environmental data prediction model; wherein the environmental data prediction model is obtained by training based on the area block statistical indicators of each of a plurality of sample area blocks, the regional statistical indicators of the sample areas to which the plurality of sample area blocks belong and the corresponding environmental data labels; and performing ventilation control on the ventilation equipment in the target area based on the predicted environmental data and the target environmental data at the future moment.

[0077] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0078] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A ventilation control method, characterized in that: Applied to a programmable logic controller (PLC) device, the method comprises: Collecting environmental data of each of a plurality of area blocks in a target area within a preset time period, wherein the environmental data includes at least two of temperature, humidity and carbon dioxide concentration; Determining the regional block statistical indicators of the respective regional blocks and the regional statistical indicators of the target area based on the environmental data of the respective regional blocks; Based on the regional block statistical indicators of each of the multiple regional blocks, the regional statistical indicators of the target area and the environmental data prediction model, predict the predicted environmental data at a future time; wherein the environmental data prediction model is trained based on the regional block statistical indicators of each of the multiple sample regional blocks, the regional statistical indicators of the sample areas to which the multiple sample regional blocks belong and the corresponding environmental data labels; Based on the predicted environmental data and the target environmental data at the future moment, ventilation control is performed on the ventilation equipment in the target area.

2. The ventilation control method according to claim 1, characterized in that: The environmental data prediction model includes multiple LSTM units; The predicting of the predicted environmental data at a future time based on the regional block statistical indicators of each of the plurality of regional blocks, the regional statistical indicators of the target area and the environmental data prediction model includes: Normalizing the respective regional block statistical indicators of the plurality of regional blocks and the regional statistical indicator of the target area to obtain the respective target regional block statistical indicators of the plurality of regional blocks and the target area statistical indicator of the target area; Inputting the target area block statistical indicators of each of the multiple area blocks and the target area statistical indicators of the target area into each of the LSTM units, respectively, to obtain the predicted sub-environment data of the corresponding time series output by each of the LSTM units; wherein the time series corresponding to the multiple LSTM units constitute the preset time period; Integrate the predicted sub-environmental data of the corresponding time series output by each of the LSTM units to obtain the initial environmental data at the future moment; The initial environmental data is denormalized to obtain the predicted environmental data at the future moment.

3. The ventilation control method according to claim 1 or 2, characterized in that: The determining, based on the respective environmental data of the plurality of area blocks, the respective area block statistical indicators of the plurality of area blocks and the area statistical indicator of the target area comprises: Preprocessing the environmental data of each of the plurality of area blocks to obtain the preprocessed environmental data of each of the plurality of area blocks; For each of the area blocks, extracting key environmental features corresponding to the area block from the preprocessed environmental data of the area block, wherein the key environmental features are used to characterize changes in the environmental data of the area block; Based on the key environmental features corresponding to the respective area blocks, area block statistical indicators of the plurality of area blocks and area statistical indicators of the target area are determined.

4. The ventilation control method according to claim 3, characterized in that: The determining of the regional block statistical indicators of each of the plurality of regional blocks and the regional statistical indicators of the target area based on the key environmental features corresponding to each of the regional blocks includes: Aggregating the key environmental features corresponding to each of the area blocks to obtain the overall environmental data of the target area; For each of the area blocks, based on the key environmental features corresponding to the area block, determine the area block statistical index of the area block; According to the overall environmental data of the target area, regional statistical indicators of the target area are determined.

5. The ventilation control method according to claim 1, characterized in that: The step of controlling ventilation equipment in the target area based on the predicted environmental data and the target environmental data at the future time includes: Determining difference data between the predicted environment data and the target environment data at the future moment; Based on the difference data, determining the ventilation control amount corresponding to the ventilation equipment; A control instruction is sent to the ventilation device, where the control instruction is used to control the ventilation device to perform ventilation control based on the ventilation control amount.

6. A ventilation control device, characterized in that: Applied to a programmable logic controller (PLC) device, the device comprises: A collection unit, used to collect environmental data of each of a plurality of area blocks in a target area within a preset time period, wherein the environmental data includes at least two of temperature, humidity and carbon dioxide concentration; A processing unit, configured to determine the regional block statistical indicators of each of the plurality of regional blocks and the regional statistical indicator of the target area based on the environmental data of each of the plurality of regional blocks; A prediction unit, configured to predict predicted environmental data at a future time based on the respective regional block statistical indicators of the plurality of regional blocks, the regional statistical indicators of the target area, and an environmental data prediction model; wherein the environmental data prediction model is obtained by training based on the respective regional block statistical indicators of the plurality of sample regional blocks, the regional statistical indicators of the sample areas to which the plurality of sample regional blocks belong, and the corresponding environmental data labels; A control unit is used to perform ventilation control on the ventilation equipment in the target area based on the predicted environmental data and the target environmental data at the future moment.

7. A ventilation control system, characterized in that: Including programmable logic controller PLC equipment and ventilation equipment; The PLC device is used to collect environmental data of each of a plurality of area blocks in a target area within a preset time period, wherein the environmental data includes at least two of temperature, humidity and carbon dioxide concentration; The PLC device is further used to determine the regional block statistical indicators of each of the plurality of regional blocks and the regional statistical indicators of the target area based on the environmental data of each of the plurality of regional blocks; The PLC device is further used to predict the predicted environmental data at a future time based on the regional block statistical indicators of each of the multiple regional blocks, the regional statistical indicators of the target area and the environmental data prediction model; wherein the environmental data prediction model is trained based on the regional block statistical indicators of each of the multiple sample regional blocks, the regional statistical indicators of the sample areas to which the multiple sample regional blocks belong and the corresponding environmental data labels; The PLC device is also used to perform ventilation control on the ventilation equipment in the target area based on the predicted environmental data and the target environmental data at the future moment.

8. A programmable logic controller (PLC) device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the ventilation control method according to any one of claims 1 to 5 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the ventilation control method according to any one of claims 1 to 5 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the ventilation control method according to any one of claims 1 to 5 is implemented.

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