Subway air valve control method, device and equipment and storage medium

Abstract

The invention provides a subway air valve control method, device and equipment and a storage medium, relates to the technical field of air valve control, and solves the problem that energy waste is easily caused due to the fact that an air valve control mode in the related technology cannot adapt to the current environment. Real-time detection of the environment and the operation state is achieved, so that the control strategy is adjusted in time, the operation state of the air valve is effectively and accurately controlled, meanwhile, energy consumption generated when the target control strategy is operated is detected, feedback adjustment is achieved through detection of the energy consumption, then the energy consumption brought by the operation process is better controlled, and the control efficiency of the air valve is improved. And the situation of energy waste can be reduced.

Description

Technical Field

[0001] The present application relates to the field of air valve control technology, and in particular to a subway air valve control method, device, equipment and storage medium. Background Art

[0002] In modern subway systems, energy management and operational safety have always been of vital concern. Traditional subway air valve control methods are often relatively simple, and the control of air valve parameters such as wind speed and frequency is usually based on a preset fixed mode, which cannot be flexibly adjusted according to the real-time environment and operating conditions.

[0003] Moreover, because it is difficult to accurately control the operating status of the air valve according to the real-time environment and operating status, the traditional subway air valve control method will lead to serious energy waste. In addition, when an emergency occurs, such as a fire or smoke, the traditional subway air valve control method cannot enable the air valve to respond quickly, and then adjust the wind speed and direction in time to effectively exhaust the smoke or provide fresh air, which is very likely to cause safety problems. Summary of the invention

[0004] The present application provides a subway air valve control method, device, equipment and storage medium, which solves the problem that the air valve control method in the related technology cannot adapt to the current environment and easily causes energy waste. The present solution can detect the environment and operating status in real time, so as to adjust the control strategy and corresponding energy consumption in time, so as to achieve precise control of the operating status of the air valve while reducing energy consumption.

[0005] In a first aspect, the present application provides a subway air valve control method, which is applied to an edge computing module in a control system. The control system includes an edge sensing module, an edge computing module, and a cloud collaboration module. The edge sensing module is used for data collection. The edge sensing module is connected to the edge computing module for data transmission. The edge computing module is connected to the cloud collaboration module. The cloud collaboration module is used for energy consumption calculation. The method includes: Receive the fire sensing data, passenger flow data and temperature data acquired by the edge sensing module in real time, and perform data preprocessing on the received data to determine the corresponding smoke concentration, carbon monoxide concentration, carbon dioxide concentration, passenger flow density and temperature change rate; Determine fire characteristic values ​​based on smoke density, carbon monoxide concentration and temperature change rate; Determine the target control strategy based on fire characteristic values, carbon dioxide concentration, crowd density and temperature change rate; Send target control strategies to execution devices and receive operation data; The operation data is pre-processed in turn and then uploaded to the cloud collaboration module, so that the cloud collaboration module can determine the energy consumption value corresponding to the target control strategy; In response to the feedback signal of the cloud collaboration module on the energy consumption value, the operating parameters in the target control strategy are readjusted.

[0006] In the second aspect, the present application also provides a subway air valve control device, which is applied to an edge computing module in a control system. The control system includes an edge sensing module, an edge computing module and a cloud collaboration module. The edge sensing module is used for data collection. The edge sensing module is connected to the edge computing module for data transmission. The edge computing module is connected to the cloud collaboration module. The cloud collaboration module is used for energy consumption calculation. The device includes: A data preprocessing module is configured to receive in real time the fire sensing data, passenger flow data and temperature data acquired by the edge sensing module, and perform data preprocessing on the received data to determine the corresponding smoke concentration, carbon monoxide concentration, carbon dioxide concentration, passenger flow density and temperature change rate; a feature extraction module configured to determine a fire feature value based on smoke density, carbon monoxide concentration, and temperature change rate; A strategy selection module is configured to determine a target control strategy based on fire characteristic values, carbon dioxide concentration, crowd density, and temperature change rate; The device control module is configured to send target control strategies to the execution devices and receive operation data; A data reprocessing module is configured to perform data preprocessing on the operation data in sequence and then upload the data to the cloud collaboration module, so that the cloud collaboration module can determine the energy consumption value corresponding to the target control strategy; The strategy reset module is configured to readjust the operating parameters in the target control strategy in response to the feedback signal of the cloud collaboration module on the energy consumption value.

[0007] In a third aspect, the present application further provides an electronic device, including: one or more processors; The storage device is used to store one or more programs. When the one or more programs are executed by one or more processors, the one or more processors implement the subway air valve control method of the present application.

[0008] In a fourth aspect, the present application also provides a storage medium storing computer executable instructions, which, when executed by a processor, are used to execute the subway air valve control method of the present application.

[0009] The present application scheme can collect fire perception data, passenger flow data and temperature data through the edge perception module to realize real-time detection of the environment and operating status, so as to adjust the control strategy in time and effectively realize precise control of the operating status of the air valve. At the same time, it also detects the energy consumption generated when the target control strategy is operated, so as to realize feedback adjustment through the detection of energy consumption, thereby better controlling the energy consumption brought about by the operation process, which helps to reduce energy waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A schematic diagram of the structure of a control system provided in one embodiment of the present application.

[0011] Figure 2 A schematic diagram of the steps of a subway air valve control method provided in one embodiment of the present application.

[0012] Figure 3 A schematic diagram of the structure of a subway air valve control device provided in one embodiment of the present application.

[0013] Figure 4 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0014] The embodiments of the present application are further described in detail below in conjunction with the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are only used to explain the embodiments of the present application, rather than to limit the embodiments of the present application. It should also be noted that, for ease of description, only the parts related to the embodiments of the present application rather than all structures are shown in the accompanying drawings, and those skilled in the art should be able to think of it after reading the specification of this application that as long as the technical features do not contradict each other, any combination of the technical features can constitute an optional implementation method.

[0015] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable when appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally a class, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally represents that the objects associated before and after are in an "or" relationship. In the description of the present application, "multiple" means two or more, and "several" means one or more.

[0016] In the current subway system, the air valve system is used to adjust the air flow to ensure the comfort and safety of the subway environment. It at least includes an air valve, an actuator, a fan and a controller, so that the fan is controlled by the controller, and the actuator is controlled by the controller to drive the air valve to achieve the adjustment of the air valve. It can be imagined that the number of air valves in the air valve system can be multiple, so as to be distributed in the subway venue, and each air valve can play a different role, such as including an air valve as a smoke exhaust valve, an air valve for adjusting the air volume, and a fire damper for fire prevention.

[0017] Moreover, energy management and operational safety are crucial in subway systems. The energy consumption caused by the air valve system in subway systems is relatively large. This is because the control method of the air valve system in related technologies is often relatively simple, lacking refined adjustment means, and it is difficult to accurately control the operating state of the air valve according to the real-time environment and operating status. Instead, the wind speed, frequency and other parameters are adjusted according to preset fixed values. For example, when the passenger flow is small, the air valve system still operates at a higher wind speed and frequency, thereby increasing unnecessary energy consumption.

[0018] In this regard, the present application provides a subway air valve control method, which is applied to the edge computing module in the control system. Figure 1 A structural diagram of a control system provided for an embodiment of the present application, wherein the control system includes an edge perception module 101, an edge computing module 102 and a cloud collaboration module 103. It can be understood that the control system is implemented based on edge computing. Edge computing is a distributed computing paradigm whose core idea is to transfer data processing, storage and analysis from the traditional centralized cloud (such as a data center) to a local device or server close to the source of data generation (ie, the "edge").

[0019] For example, in the control system, data is collected through the edge perception module 101, and the data collected by the edge perception module 101 is processed through the edge computing module 102, and then the data is transmitted to the cloud collaboration module 103, so that the cloud collaboration module 103 can calculate energy consumption. It is conceivable that the edge perception module 101 includes sensors (such as temperature sensors, gas sensors, smoke sensors, etc.) and radars (such as millimeter wave radars, ultrasonic radars, etc.) for data collection. It is conceivable that the edge computing module 102 can be deployed on the controller side to connect with the edge perception module 101, so as to receive corresponding data and perform data processing; the cloud collaboration module 103 can be deployed on the cloud server, and the edge computing module 102 is also connected to the cloud collaboration module 103, such as the two are connected through a network to communicate and transmit corresponding data, so that the cloud collaboration module 103 can calculate energy consumption.

[0020] Figure 2A schematic diagram of the steps of a subway air valve control method provided in an embodiment of the present application is shown in the figure. After the corresponding data is collected, it is processed to determine the target control strategy for adjusting the air valve system, and then the air valve system is feedback-adjusted according to the calculated energy consumption, so that the air valve system can be better adjusted in combination with the actual environment and operating status, while reducing the energy consumption caused by the air valve system, and realizing efficient and energy-saving air valve control. The specific steps include steps S110-S160: Step S110, receiving the fire sensing data, passenger flow data and temperature data acquired by the edge sensing module in real time, and performing data preprocessing on the received data to determine the corresponding smoke concentration, carbon monoxide concentration, carbon dioxide concentration, passenger flow density and temperature change rate.

[0021] The control system collects data based on the edge perception module, such as fire perception data, passenger flow data and temperature data. It can be imagined that the edge perception module includes but is not limited to temperature sensors, gas sensors, and smoke sensors to obtain temperature data, carbon monoxide data, carbon dioxide data, and smoke data. The edge perception module also includes a millimeter-wave radar to collect passenger flow data through the point cloud data collected by the millimeter-wave radar. After completing the data collection, the edge perception module transmits the corresponding collected data to the edge computing module for data preprocessing by the edge computing module.

[0022] It can be imagined that the edge perception module uses the collected point cloud data as passenger flow data and transmits it to the edge computing module. In this regard, the edge computing module can filter the point cloud data during data preprocessing (such as using Kalman filtering) to remove noise in the data, and then complete the matching calculation of the point cloud data and the skeleton template through the Hungarian algorithm to achieve the positioning of multiple human targets, thereby constructing a grid heat map for density calculation, and thus calculating the corresponding passenger flow density.

[0023] In addition, the gas concentration can be detected correspondingly in the gas sensor. The specific detection principle can refer to the relevant technology and will not be elaborated here. The gas sensor in the edge sensing module can detect the carbon monoxide concentration and carbon dioxide concentration accordingly. Similarly, the smoke sensor in the edge sensing module can determine the corresponding smoke concentration by detecting smoke particles. Moreover, the calculation of the temperature change rate can be determined by the collected temperature data, such as based on the temperature data collected at multiple sampling times, so that the temperature change rate within the period of time can be determined.

[0024] Step S120: Determine fire characteristic values ​​according to smoke density, carbon monoxide concentration and temperature change rate.

[0025] The fire characteristic value is used to characterize whether there is a fire in the current environment. For this purpose, after preprocessing the data collected by the edge sensing module, the fire characteristic value is further determined based on the preprocessed data (such as the smoke concentration, carbon monoxide concentration and temperature change rate mentioned above). Optionally, in one embodiment, in the process of calculating the fire characteristic value, the weight values ​​configured for the corresponding carbon monoxide concentration, temperature change rate and smoke concentration are determined. It can be imagined that corresponding weight values ​​are configured for different parameters, wherein the weight value corresponding to the temperature change rate is higher than the weight value corresponding to the smoke concentration, and lower than the weight value corresponding to the carbon monoxide concentration.

[0026] Then, according to the configured weight value, the carbon monoxide concentration, temperature change rate, smoke concentration and the weight corresponding to each parameter are weighted to determine the corresponding cumulative sum, and the cumulative sum is used as the fire characteristic value. The corresponding calculation formula is as follows:

[0027] Among them, F fire is the fire characteristic value, CO norm is the carbon monoxide concentration, T grad is the temperature change rate, Smoke clean is the smoke concentration, W1, W2, and W3 are the weight values ​​corresponding to the carbon monoxide concentration, temperature change rate, and smoke concentration, respectively, and the sum is 1. For example, W1, W2, and W3 are 0.6, 0.3, and 0.1, respectively. It can be imagined that carbon monoxide concentration, as an important indicator in a fire scene, can be assigned a higher weight; the temperature change rate is used to reflect the speed of fire spread, and the smoke concentration can be used to determine the combustion situation. Smaller weights can be set for each of them. Therefore, the weight values ​​are W1, W2, and W3 from high to low. It should be noted that in some embodiments, the fire characteristic value can also be determined by calculating the weighted sum of squares.

[0028] Step S130: Determine the target control strategy according to the fire characteristic value, carbon dioxide concentration, crowd density and temperature change rate.

[0029] After determining the fire characteristic value, the target control strategy is selected. It can be imagined that the preset local decision database includes multiple control strategies, and an adaptive control strategy is selected as the target control strategy according to the fire characteristic value, carbon dioxide concentration, crowd density and temperature change rate. That is, the control strategies are screened based on the above-mentioned fire characteristic value, carbon dioxide concentration, crowd density and temperature change rate, and then the target control strategy is determined.

[0030] Step S140: Send the target control strategy to the execution device and receive the operation data.

[0031] A communication channel is provided between the control system and the execution device to enable data exchange between the control system and the execution device. In some embodiments, a dual redundant communication channel is provided between the control system and the execution device to enable data exchange through the dual redundant communication channel. It is conceivable that the dual redundant communication channel can play a role of redundant communication to improve the reliability and stability of the system. For example, the dual redundant communication channel includes multiple communication channels, one of which is used as the main communication channel during communication, and the other communication channels are used as backup communication channels. When the main communication channel fails, the backup communication channel is used for communication, thereby ensuring that the control system and the execution device can still communicate normally.

[0032] Based on this, the control system sends the target control strategy to the execution device, so that the execution device can control the fans, air valves and other devices in the air valve system according to the target control strategy. In addition, the control system also receives operating data, such as the operating parameters of fans, air valves and other devices collected by the execution device, the temperature data collected by the edge sensing module, the passenger flow data, etc. It can be imagined that the target control strategy and the operating parameters collected by the execution device can also be sent to the control system through the dual redundant communication channel.

[0033] Step S150: pre-process the operation data in sequence and upload them to the cloud collaboration module, so that the cloud collaboration module can determine the energy consumption value corresponding to the target control strategy.

[0034] The cloud collaboration module can be used to calculate energy consumption. For this, the edge computing module obtains the corresponding operating data, performs data preprocessing and data feature extraction, and then uploads it to the cloud collaboration module, so that the cloud collaboration module can judge the energy consumption value brought about by the target control strategy based on the processed operating data. It is conceivable that the cloud collaboration module can be deployed with a trained neural network model, so that the neural network model outputs the corresponding energy consumption value by inputting the operating data, thereby serving as the energy consumption value brought about under the target control strategy. Of course, in some embodiments, the currently acquired operating data can also be calculated based on the corresponding algorithm to obtain the corresponding energy consumption value.

[0035] Step S160: Responding to the feedback signal of the cloud collaboration module on the energy consumption value, readjusting the operating parameters in the target control strategy.

[0036] After the cloud collaboration module calculates the corresponding energy consumption value, it can output a feedback signal to the edge computing module by judging the energy consumption value, and the edge computing module calculates and readjusts the operating parameters in the target control strategy according to the feedback signal. That is, for different feedback signals, the edge computing module can determine that the energy consumption brought by the control strategy adopted by the current target mode does not meet the requirements, and then readjust the relevant operating parameters to adjust the energy consumption.

[0037] It can be understood that the control system can collect fire perception data, passenger flow data and temperature data through the edge perception module, so that the edge computing module can select the corresponding target control strategy based on the processed data after processing the data, so that the damper system can operate according to the target control strategy. Moreover, after the acquired data changes, the edge computing module will also detect the changed data to determine whether the current target control strategy matches the changed data, so as to adjust the control strategy in time when there is a mismatch; and the cloud collaboration module also calculates the energy consumption value brought about by operating according to the target control strategy based on the operating data, so as to realize feedback adjustment of the damper system through the detection of the energy consumption value, that is, readjust the operating parameters to complete the regulation of energy consumption.

[0038] It can be seen from the above scheme that the present application scheme can collect fire perception data, passenger flow data and temperature data through the edge perception module, realize real-time detection of the environment and operating status, so as to adjust the control strategy in time, effectively realize precise control of the operating status of the air valve, and at the same time, detect the energy consumption generated when the target control strategy is operated, so as to realize feedback adjustment through the detection of energy consumption, thereby better controlling the energy consumption brought by the operation process, which helps to reduce energy waste.

[0039] In some embodiments, the target control strategy is sent to the execution device through a dual redundant communication channel, and the dual redundant communication channel includes a CAN bus channel and a Lora wireless channel, that is, the control system sends the target control strategy to the execution device through the dual redundant communication channel, and also receives the operation data through the dual redundant communication channel. For example, when sending the target control strategy, the target control strategy is sent through the CAN bus channel and the Lora wireless channel respectively, so that the execution device can receive the target control strategy; similarly, when the execution device feeds back the operation data, it also sends the operation data through the CAN bus channel and the Lora wireless channel. In this regard, after sending the target control strategy, the control system monitors the CAN bus channel and the Lora wireless channel to receive the operation data. Therefore, by sending and receiving data through the dual redundant communication channels, the control system and the execution device can ensure that the corresponding data is received, which helps to ensure that the adjustment of the air valve system can be carried out stably and improve the stability of the system.

[0040] Optionally, in one embodiment, different control strategies correspond to different modes, and are also associated with the above-mentioned fire characteristic value, carbon dioxide concentration, crowd density and temperature change rate, so as to determine the target mode according to the above-mentioned parameters. Exemplarily, when the fire characteristic value is greater than the preset threshold, the target mode is determined to be the first mode, and the corresponding target control strategy is to control the smoke exhaust valve to be fully opened and lock the fan frequency at the first preset frequency. At this time, it can be considered that there is a fire risk, and then it is necessary to control the air valve system to open the air valve as the smoke exhaust valve and drive the fan to open at the corresponding frequency to exhaust the smoke.

[0041] When the carbon dioxide concentration is greater than the first concentration and the passenger density is greater than the first density, the target mode is determined to be the second mode, and the corresponding target control strategy is to control the air valve to be fully opened and control the fan frequency within the first frequency range. It can be determined that the current subway is in the peak operation stage, and then the air valve is controlled to be fully opened and the fan frequency of the fan is controlled within the first frequency range to speed up the speed of air supply and exhaust, and improve the air circulation speed in the venue. It can be imagined that the fan frequency can be set according to dynamic adjustment within the first frequency range, such as PID adjustment, so that the fan with dynamically adjusted fan frequency can adapt to changes in passenger flow.

[0042] When the carbon dioxide concentration is less than the second concentration, the crowd density is less than the second density, and the temperature change rate is less than the first set value, wherein the second concentration is less than the first concentration, and the second density is less than the first density, the target mode is determined to be the third mode, and the corresponding target control strategy is to control the air valve opening to be dynamically adjusted within the first opening range, and to control the fan frequency to be maintained above the second preset frequency. That is, in this case, it can be determined that the current energy-saving operation stage is in progress, and accordingly, the air valve opening is dynamically adjusted within the first opening range, such as the first opening range is 30%-70%, and the air valve opening can be dynamically adjusted within this range based on the change of crowd density, such as positively correlating the air valve opening with the crowd density, that is, as the crowd density increases, the air valve opening also increases accordingly.

[0043] Therefore, based on the data collected in real time, the mode and control strategy are selected after data processing, so that the target control strategy configured for the air valve system can adapt to the current environment and operating status, which helps to achieve more accurate air valve control.

[0044] In some embodiments, when the crowd density is greater than the second density and less than the first density, and the temperature change rate is less than the second set value, the target mode is determined to be the fourth mode, and the corresponding target control strategy is to control the opening of the air valve to maintain the preset opening value, and control the fan frequency to maintain the preset frequency value. In this regard, it can be determined that the current stage is in the transition adjustment stage, and the opening of the air valve is maintained at the preset opening value and the fan frequency is maintained at the preset frequency value accordingly. Optionally, in one embodiment, the preset opening value can be set with a corresponding weight coefficient according to the crowd density, and then the product of the weight coefficient and the initially set opening value is used as the preset opening value. The preset frequency value can be a corresponding frequency set according to the crowd density (such as the product value of the crowd density and the preset coefficient as the frequency), and then the sum of the frequency and the initially set frequency value is used as the preset frequency value. That is, a corresponding threshold is set for the transition adjustment stage. When the crowd density and the temperature change rate meet the corresponding conditions, it is determined that the current stage is in the transition adjustment stage, so that the air valve and the fan are adjusted through the corresponding control strategy, so as to adapt to the current environment and operating state, so as to achieve precise air valve control.

[0045] In one embodiment, corresponding to the received feedback data, the edge computing module responds to different feedback signals and changes the operating parameters accordingly to adjust the control strategy in the current mode, thereby regulating energy consumption. Exemplarily, when the target mode is the first mode, in response to the feedback signal, the edge computing module releases the restriction on the fan and deletes the limit value of the fan frequency, that is, the fan is not restricted during operation, and the fan frequency is increased, thereby reducing the risk of fire.

[0046] When the target mode is the second mode, in response to the feedback signal, the edge computing module reduces the upper limit value of the corresponding fan frequency within the first frequency range, that is, adjusts the maximum value of the first frequency range to reduce the first frequency range. For example, the initial first frequency range is 30%-70%, and the adjusted first frequency range is 30%-60%, thereby reducing the upper limit value of the fan frequency in the second mode to achieve the purpose of frequency reduction, thereby reducing energy consumption.

[0047] When the target mode is the third mode, in response to the feedback signal, the edge computing module controls the air valve to increase its opening. Similarly, the third module corresponds to the energy-saving operation stage. Optionally, in one embodiment, when the cloud-based collaborative module determines that the energy consumption value is low after calculation, it can output a feedback signal to the edge computing module to trigger the edge computing module to adjust the operating parameters. In response to this, the edge computing module increases the opening of the air valve, thereby better exhausting and supplying air with less energy consumption. Therefore, the control system flexibly adjusts the control strategy through feedback adjustment of the operating parameters, so that the control of the air valve system can adapt to the current environment and operating status, thereby reducing energy waste.

[0048] In one embodiment, the feedback signal is determined by the cloud-based collaborative module based on the real-time energy consumption value, the historical energy consumption baseline value, and the predicted energy consumption value. That is, for the cloud-based collaborative module, it calculates and determines the real-time energy consumption value and the predicted energy consumption value after obtaining the operating data. If the operating data includes flow, pressure difference, current, motor efficiency factor, and air valve opening, as well as historical data including historical energy consumption values ​​obtained from the database, when calculating the real-time energy consumption value, the product of the ratio of fluid power to motor efficiency factor and air valve opening can be calculated, and the calculation result is used as the real-time energy consumption value. The specific calculation formula is as follows:

[0049] in, is the real-time energy consumption value, is the air valve opening, Q is the flow rate, is the pressure difference, is the fluid power, is the motor efficiency factor.

[0050] In addition, the historical energy consumption benchmark value is the cumulative average of the product of the historical energy consumption value and the correction coefficient. The specific calculation formula is as follows:

[0051] in, is the historical energy consumption benchmark value, is the historical energy consumption value, is the current time, This corresponds to the reference peak moment of energy consumption on that day in the historical data.

[0052] The predicted energy consumption value is determined based on the real-time energy consumption value and the historical energy consumption benchmark value. For example, the weighted sum of the real-time energy consumption value and the historical energy consumption benchmark value multiplied by the environmental compensation coefficient is used as the predicted energy consumption value. The specific calculation formula is as follows:

[0053] in, To predict the energy consumption value, is the environmental compensation coefficient.

[0054] Therefore, based on the calculation of energy consumption by the cloud collaborative module, the control system can monitor the energy consumption of the executed control strategy and then adjust the operating parameters, which helps to make the air valve system better match the current application environment.

[0055] In one embodiment, for the output of the feedback signal, if the target mode is the second mode, the feedback signal received by the edge computing module is output by the cloud collaboration module when the real-time energy consumption value is less than 0.8 times the historical energy consumption benchmark value, that is, in the process of calculating the energy consumption value, the cloud collaboration module also compares the real-time energy consumption value with the comparison value, and the comparison value is 0.8 times the historical energy consumption benchmark value, and then when the real-time energy consumption value is greater than the comparison value, the feedback signal is output to the edge computing module.

[0056] When the target mode is the third mode, the feedback signal received by the edge computing module is output by the cloud collaboration module when the predicted energy consumption value is less than the historical energy consumption benchmark value. That is, in the process of calculating the energy consumption value, the cloud collaboration module also compares the predicted energy consumption value with the comparison value, and the comparison value is taken as the historical energy consumption benchmark value. Then, when the predicted energy consumption value is greater than the comparison value, a feedback signal is output to the edge computing module.

[0057] Therefore, energy consumption is calculated through the cloud collaboration module to determine the energy consumption situation by comparing the calculation results with historical data, so that the control system can achieve feedback adjustment, thereby flexibly adjusting the operating parameters, so that the control of the air valve system can adapt to the current environment and operating status, thereby reducing energy waste.

[0058] Figure 3 The schematic diagram of the structure of the subway air valve control device provided in one embodiment of the present application is used to execute the subway air valve control method provided in the above embodiment, and has the functional modules and beneficial effects corresponding to the execution method. The device is applied to the edge computing module in the control system, and the control system includes an edge perception module, an edge computing module and a cloud collaboration module. The edge perception module is used for data collection, the edge perception module is connected to the edge computing module for data transmission, the edge computing module is connected to the cloud collaboration module, and the cloud collaboration module is used for energy consumption calculation. The device includes a data preprocessing module 301, a feature extraction module 302, a strategy selection module 303, a device control module 304, a data reprocessing module 305 and a strategy reset module 306.

[0059] Specifically, the data preprocessing module 301 is configured to receive the fire sensing data, passenger flow data and temperature data acquired by the edge sensing module in real time, and perform data preprocessing on the received data to determine the corresponding smoke concentration, carbon monoxide concentration, carbon dioxide concentration, passenger flow density and temperature change rate; The feature extraction module 302 is configured to determine a fire feature value based on smoke concentration, carbon monoxide concentration, and temperature change rate; The strategy selection module 303 is configured to determine the target control strategy according to the fire characteristic value, carbon dioxide concentration, crowd density and temperature change rate; The device control module 304 is configured to send target control strategies to the execution devices and receive operation data; The data reprocessing module 305 is configured to perform data preprocessing on the operation data in sequence and then upload the data to the cloud collaboration module, so that the cloud collaboration module can determine the energy consumption value corresponding to the target control strategy; The strategy reset module 306 is configured to readjust the operating parameters in the target control strategy in response to the feedback signal of the cloud collaboration module on the energy consumption value.

[0060] Based on the above embodiment, the feature extraction module 302 is specifically configured as follows: Determine the weight values ​​corresponding to the carbon monoxide concentration, temperature change rate and smoke concentration; According to the configured weight value, the cumulative sum of carbon monoxide concentration, temperature change rate and smoke concentration is weighted and calculated as the fire characteristic value; Among them, the weight value corresponding to the temperature change rate is higher than the weight value corresponding to the smoke concentration, and lower than the weight value corresponding to the carbon monoxide concentration.

[0061] On the basis of the above embodiment, the target control strategy is sent to the execution device through the dual redundant communication channel, the dual redundant communication channel includes a CAN bus channel and a Lora wireless channel, and the device control module 304 is specifically configured as follows: The target control strategy is issued through the CAN bus channel and the Lora wireless channel respectively, and the CAN bus channel and the Lora wireless channel are monitored to receive the operation data.

[0062] Based on the above embodiment, the strategy selection module 303 is specifically configured as follows: When the fire characteristic value is greater than the preset threshold, the target mode is determined to be the first mode, and the corresponding target control strategy is to control the smoke exhaust valve to be fully opened and lock the fan frequency to the first preset frequency; When the carbon dioxide concentration is greater than the first concentration and the crowd density is greater than the first density, the target mode is determined to be the second mode, and the corresponding target control strategy is to control the air valve to be fully opened and control the fan frequency within the first frequency range; When the carbon dioxide concentration is lower than the second concentration, the crowd density is lower than the second density and the temperature change rate is lower than the first set value, the target mode is determined to be the third mode, and the corresponding target control strategy is to control the air valve opening to dynamically adjust within the first opening range, and control the fan frequency to maintain above the second preset frequency.

[0063] Based on the above embodiment, the strategy selection module 303 is further configured as follows: When the crowd density is greater than the second density and less than the first density, and the temperature change rate is less than the second set value, the target mode is determined to be the fourth mode, and the corresponding target control strategy is to control the opening of the air valve to maintain at the preset opening value, and to control the fan frequency to maintain at the preset frequency value.

[0064] Based on the above embodiment, the policy resetting module 306 is specifically configured as follows: When the target mode is the first mode, in response to the feedback signal, the limit value of the fan frequency is deleted, and the fan frequency is increased; When the target mode is the second mode, in response to the feedback signal, lowering the upper limit value of the corresponding fan frequency within the first frequency range; When the target mode is the third mode, the air valve is controlled to increase its opening degree in response to the feedback signal.

[0065] On the basis of the above embodiment, the feedback signal is determined by the cloud-based collaborative module based on the real-time energy consumption value, the historical energy consumption benchmark value and the predicted energy consumption value to determine whether to output. The real-time energy consumption value is the product of the ratio of fluid power to motor efficiency factor and the air valve opening. The historical energy consumption benchmark value is the cumulative average of the product of the historical energy consumption value and the correction coefficient. The predicted energy consumption value is the weighted sum of the real-time energy consumption value and the historical energy consumption benchmark value and the environmental compensation coefficient.

[0066] Based on the above embodiment, the device is further configured as: The feedback signal received when the target mode is the second mode is output by the cloud collaboration module when the real-time energy consumption value is less than 0.8 times the historical energy consumption reference value; The feedback signal received when the target mode is the third mode is output by the cloud collaboration module when the predicted energy consumption value is less than the historical energy consumption benchmark value.

[0067] It is worth noting that in the embodiment of the above-mentioned device, the modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the modules are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the embodiments of the present application.

[0068] Figure 4The schematic diagram of the structure of an electronic device provided in an embodiment of the present application is used to execute the subway air valve control method provided in the above embodiment, and has the functional modules and beneficial effects corresponding to the execution method. As shown in the figure, the device includes a processor 401, a memory 402, an input device 403 and an output device 404. The number of processors 401 can be one or more, and one processor 401 is taken as an example in the figure; the processor 401, the memory 402, the input device 403 and the output device 404 can be connected by a bus or other means, and the figure takes the connection through a bus as an example. The memory 402, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as the program instructions / modules corresponding to the subway air valve control method in the embodiment of the present application. The processor 401 executes the corresponding various functional applications and data processing by running the software programs, instructions and modules stored in the memory 402, that is, the above-mentioned subway air valve control method is realized.

[0069] The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data recorded or created during use, etc. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 402 may further include a memory remotely arranged relative to the processor 401, and these remotely arranged memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0070] The input device 403 can be used to input corresponding digital or character information to the processor 401, and to generate key signal input related to the user settings and function control of the device; the output device 404 can be used to send or display key signal output related to the user settings and function control of the device.

[0071] An embodiment of the present application also provides a storage medium storing computer executable instructions, which, when executed by a processor, are used to perform relevant operations in the subway air valve control method provided in any embodiment of the present application.

[0072] Computer-readable storage media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0073] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0074] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A subway air valve control method, characterized in that: An edge computing module applied to a control system, the control system comprising an edge perception module, an edge computing module and a cloud collaboration module, the edge perception module is used for data collection, the edge perception module is connected to the edge computing module for data transmission, the edge computing module is connected to the cloud collaboration module, the cloud collaboration module is used for energy consumption calculation, the method comprises: Receive the fire sensing data, passenger flow data and temperature data acquired by the edge sensing module in real time, and perform data preprocessing on the received data to determine the corresponding smoke concentration, carbon monoxide concentration, carbon dioxide concentration, passenger flow density and temperature change rate; Determining a fire characteristic value according to the smoke concentration, the carbon monoxide concentration and the temperature change rate; Determining a target control strategy according to the fire characteristic value, the carbon dioxide concentration, the crowd density and the temperature change rate; Sending the target control strategy to the execution device and receiving operation data; Preprocessing the operation data in turn and uploading them to the cloud collaboration module, so that the cloud collaboration module can determine the energy consumption value corresponding to the target control strategy; In response to the feedback signal of the cloud collaboration module to the energy consumption value, the operating parameters in the target control strategy are readjusted.

2. The subway air valve control method according to claim 1, characterized in that: The determining of the fire characteristic value according to the smoke concentration, the carbon monoxide concentration and the temperature change rate comprises: Determining weight values ​​configured corresponding to the carbon monoxide concentration, the temperature change rate, and the smoke concentration; According to the configured weight value, weighted calculation is performed on the cumulative sum of the carbon monoxide concentration, the temperature change rate and the smoke concentration to serve as the fire characteristic value; The weight value corresponding to the temperature change rate is higher than the weight value corresponding to the smoke concentration, and lower than the weight value corresponding to the carbon monoxide concentration.

3. The subway air valve control method according to claim 1, characterized in that: The target control strategy is sent to the execution device through a dual redundant communication channel, wherein the dual redundant communication channel includes a CAN bus channel and a Lora wireless channel. The target control strategy is sent to the execution device and the operation data is received, including: The target control strategy is respectively issued through the CAN bus channel and the Lora wireless channel, and the CAN bus channel and the Lora wireless channel are monitored to receive the operation data.

4. The subway air valve control method according to any one of claims 1 to 3, characterized in that: The determining of the target control strategy according to the fire characteristic value, the carbon dioxide concentration, the crowd density and the temperature change rate includes: When the fire characteristic value is greater than a preset threshold, the target mode is determined to be the first mode, and the corresponding target control strategy is to control the smoke exhaust valve to be fully opened and lock the fan frequency to the first preset frequency; When the carbon dioxide concentration is greater than the first concentration and the crowd density is greater than the first density, the target mode is determined to be the second mode, and the corresponding target control strategy is to control the air valve to be fully opened and control the fan frequency within the first frequency range; When the carbon dioxide concentration is lower than the second concentration, the crowd density is lower than the second density, and the temperature change rate is lower than the first set value, the target mode is determined to be the third mode, and the corresponding target control strategy is to control the air valve opening to dynamically adjust within the first opening range, and control the fan frequency to maintain above the second preset frequency.

5. The subway air valve control method according to claim 4, characterized in that: The step of re-adjusting the operating parameters in the target control strategy in response to the feedback signal of the cloud collaboration module to the energy consumption value includes: When the target mode is the first mode, in response to the feedback signal, the limit value of the fan frequency is deleted, and the fan frequency is increased; When the target mode is the second mode, in response to the feedback signal, lowering the upper limit value of the corresponding fan frequency within the first frequency range; When the target mode is the third mode, the air valve is controlled to increase its opening degree in response to the feedback signal.

6. The subway air valve control method according to claim 5, characterized in that: The feedback signal is determined by the cloud-based collaborative module based on the real-time energy consumption value, the historical energy consumption benchmark value and the predicted energy consumption value. The real-time energy consumption value is the product of the ratio of fluid power to motor efficiency factor and the air valve opening. The historical energy consumption benchmark value is the cumulative average of the products of the historical energy consumption value and the correction coefficient. The predicted energy consumption value is the weighted sum of the real-time energy consumption value and the historical energy consumption benchmark value and the environmental compensation coefficient.

7. The subway air valve control method according to claim 4, characterized in that: The determining of the target control strategy according to the fire characteristic value, the carbon dioxide concentration, the crowd density and the temperature change rate also includes: When the crowd density is greater than the second density and less than the first density and the temperature change rate is less than the second set value, the target mode is determined to be the fourth mode, and the corresponding target control strategy is to control the opening of the air valve to maintain at a preset opening value, and to control the fan frequency to maintain at a preset frequency value.

8. The subway air valve control method according to claim 6, characterized in that: The method further comprises: The feedback signal received when the target mode is the second mode is output by the cloud collaboration module when the real-time energy consumption value is less than 0.8 times the historical energy consumption reference value; The feedback signal received when the target mode is the third mode is output by the cloud collaboration module when the predicted energy consumption value is less than the historical energy consumption reference value.

9. A subway air valve control device, characterized in that: An edge computing module applied to a control system, the control system includes an edge perception module, an edge computing module and a cloud collaboration module, the edge perception module is used for data collection, the edge perception module is connected to the edge computing module for data transmission, the edge computing module is connected to the cloud collaboration module, the cloud collaboration module is used for energy consumption calculation, the device includes: A data preprocessing module is configured to receive the fire sensing data, passenger flow data and temperature data acquired by the edge sensing module in real time, and perform data preprocessing on the received data to determine the corresponding smoke concentration, carbon monoxide concentration, carbon dioxide concentration, passenger flow density and temperature change rate; a feature extraction module configured to determine a fire feature value according to the smoke concentration, the carbon monoxide concentration and the temperature change rate; A strategy selection module is configured to determine a target control strategy according to the fire characteristic value, the carbon dioxide concentration, the crowd density and the temperature change rate; The device control module is configured to send the target control strategy to the execution device and receive operation data; A data reprocessing module, configured to perform data preprocessing on the operation data in sequence and then upload the data to the cloud collaboration module, so that the cloud collaboration module can determine the energy consumption value corresponding to the target control strategy; The strategy reset module is configured to readjust the operating parameters in the target control strategy in response to the feedback signal of the cloud collaboration module to the energy consumption value.

10. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the subway air valve control method as described in any one of claims 1-8.

11. A storage medium storing computer executable instructions, characterized in that: The computer executable instructions are used to execute the subway air valve control method according to any one of claims 1 to 8 when executed by a processor.

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