Control method and device of system and storage medium

Abstract

The application discloses a system control method and device and a storage medium. The method comprises the following steps: acquiring the current user load of a service area of a target system and monitoring images of each sub-area in the service area; in the case that the recognition result obtained by an artificial intelligence model according to the monitoring images of each sub-area indicates that all components in the service area are operating normally, controlling each component to work according to the current user load, wherein the artificial intelligence model is obtained by pre-training using image pairs (i.e. images with different resolutions); in the case that the recognition result obtained by the artificial intelligence model according to the monitoring images of each sub-area indicates that there is a first component operating abnormally in the service area, controlling a second component in the target system to operate according to a specified working mode, so as to eliminate the influence caused by the failure of the first component, the load supply can be adjusted according to the load demand, and the technical problem that a building equipment automatic control system is not energy-saving enough during operation can be solved.

Description

Technical Field

[0001] This application relates to the field of building automation technology, and more specifically, to a system control method, device, and storage medium. Background Technology

[0002] This section is intended to provide background or context for the content set forth in the claims or specification, and the content described herein is not acknowledged as prior art simply because it is included in this section.

[0003] BA system, short for Building Automation System-RTU, is a professional building automation control system that uses a microcomputer as its core and connects to regional intelligent substations (i.e., DDCs) distributed in the monitoring site via an industrial standard network. Through specific terminal devices, it realizes centralized monitoring and management of building electromechanical equipment.

[0004] It is a distributed system designed based on distributed control theory in modern cybernetics. It is a comprehensive monitoring system with centralized operation, management, and decentralized control functions. The goal of the system is to use modern computer technology to comprehensively and effectively monitor and manage most of the electromechanical equipment in a building, ensuring that all equipment in the building is in an efficient and reasonable operating state.

[0005] Building automation systems (RAS) primarily monitor and measure the operation of building equipment such as power distribution equipment, emergency backup power supplies, batteries, and uninterruptible power supplies (UPS). They also monitor lighting equipment, water supply and drainage systems (including drinking water and sewage treatment equipment), secondary heat source equipment, air conditioning equipment, ventilation equipment, and environmental monitoring equipment in air conditioning systems, as well as the operation of heat source equipment in heating systems. Furthermore, they monitor the operation of elevators and escalators. By using RTUs to monitor and manage these mechanical and electrical devices within the building, human resources can be saved, creating a more comfortable and safer environment for users.

[0006] Current building automation systems operate at full load, which is not energy-efficient, and no effective solution has yet been proposed to address this issue. Summary of the Invention

[0007] This application provides a system control method, device, and storage medium to at least solve the technical problem of insufficient energy efficiency in building equipment automatic control systems during operation.

[0008] According to one aspect of the embodiments of this application, a system control method is provided, comprising: acquiring the current user load of a service area of ​​a target system and monitoring images of each sub-area within the service area, the target system including multiple components located in each sub-area, the multiple components being used to provide services to the service area, and the user load being the load demand of users within the service area; when the identification results obtained by an artificial intelligence model based on the monitoring images of each sub-area indicate that all components within the service area are operating normally, controlling each component in the target system to operate according to the current user load, the artificial intelligence model being pre-trained using image pairs, the image pairs including a first image of a first resolution and a second image of a second resolution taken from the same sub-area, the resolution of the monitoring image being the first resolution, and the second resolution being an integer multiple of the first resolution; when the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that a first component is operating abnormally within the service area, controlling a second component in the target system to operate according to a specified working mode to eliminate the impact of the failure of the first component, the second component being different from the first component.

[0009] Optionally, the multiple components include N load providing devices, M load switching devices, and M load delivery devices. The control system operates each component according to the current user load, including: acquiring the user load provided by the currently operating load providing devices, load switching devices, and load delivery devices, wherein the number of currently operating load providing devices is less than or equal to an integer N, and the number of currently operating load switching devices is the same as and less than an integer M; and controlling the operating status of the N load providing devices, M load switching devices, and M load delivery devices to meet the current user load when the provided user load does not match the current user load, wherein the number of load switching devices in operation is the same as the number of load delivery devices in operation.

[0010] Optionally, when the provided user load does not match the current user load, the operating status of the M load exchange devices and M load delivery devices is controlled, including: when the provided user load is less than the current user load, opening the electric valves on the inlet and outlet water pipes of the first load delivery device which is in a closed state; after the electric valves have been open for a first period of time, starting the first load exchange device and the first load delivery device which are in a closed state; and after the first load exchange device and the first load delivery device have been running for a second period of time, starting the first load delivery device, where the first period of time is 2-3 minutes and the second period of time is twice the first period of time.

[0011] Optionally, when the provided user load does not match the current user load, controlling the operating status of the M load exchange devices and M load delivery devices further includes: shutting down the second load supply device that is in the open state when the provided user load is greater than the current user load; shutting down the second load exchange device and the second load delivery device that are in the open state after the shutdown time of the second load supply device reaches a first duration; and closing the electric valves on the inlet and outlet water pipes of the second load supply device after the shutdown time of the second load exchange device and the second load delivery device reaches a second duration.

[0012] Optionally, the target system includes N load-providing devices, M load delivery devices, P indoor devices, P circulating devices, and P outdoor devices. Controlling each component in the target system to operate according to the current user load includes: acquiring the user load provided by the currently operating devices, which include multiple load-providing devices; and controlling the operating status of the M load delivery devices, P indoor devices, P circulating devices, and P outdoor devices to meet the current user load when the provided user load does not match the current user load, with the number of indoor devices in operation being the same as the number of outdoor devices in operation.

[0013] Optionally, when the provided user load does not match the current user load, the operating status of M load delivery devices, P indoor devices, P circulation devices, and P outdoor devices is controlled, including: when the provided user load is less than the current user load, opening the electric valves on the inlet and outlet water pipes of the first indoor device which is in a closed state; after the electric valves have been open for a third time, starting the first circulation device and the third load delivery device which are in a closed state; after the first circulation device and the third load delivery device have been running for a fourth time, starting the first outdoor device which is in a closed state; after the first outdoor device has been running for a fifth time, starting the first indoor device, where the third time is longer than the fourth time and shorter than the fifth time.

[0014] Optionally, when the provided user load does not match the current user load, controlling the operating status of the M load delivery devices, P indoor devices, P circulation devices, and P outdoor devices further includes: shutting down the second indoor device when the provided user load is greater than the current user load; shutting down the second circulation device and the fourth load delivery device when the second indoor device has been shut down for a period of six hours; shutting down the electric valves on the inlet and outlet water pipes of the second indoor device when the second circulation device and the fourth load delivery device have been shut down for a period of seven hours; and shutting down the second outdoor device when the second circulation device and the fourth load delivery device have been shut down for a period of eight hours.

[0015] According to another aspect of the embodiments of this application, a system control device is also provided, comprising: an acquisition unit, configured to acquire the current user load of a service area of ​​a target system and monitoring images of each sub-area within the service area, wherein the target system includes multiple components located in each sub-area, the multiple components being used to provide services to the service area, and the user load being the load demand of users within the service area; a first control unit, configured to control each component of the target system to operate according to the current user load when the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that all components within the service area are operating normally, wherein the artificial intelligence model is obtained through pre-training using image pairs, the image pairs including a first image of a first resolution and a second image of a second resolution taken from the same sub-area, the resolution of the monitoring image being the first resolution, and the second resolution being an integer multiple of the first resolution; and a second control unit, configured to control a second component in the target system to operate according to a specified working mode when the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that a first component is operating abnormally within the service area, in order to eliminate the impact of the failure of the first component, wherein the second component is different from the first component.

[0016] According to another aspect of the embodiments of this application, a computer-readable storage medium (such as an optical disc, a USB flash drive, a hard disk, etc.) is also provided, the storage medium including a stored program, which executes the above-described method when the program is run.

[0017] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor performs the above-described method through the computer program.

[0018] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps of any of the embodiments of the methods described above.

[0019] In this embodiment, the current user load of the service area of ​​the target system and monitoring images of each sub-area within the service area are acquired. The target system includes multiple components located in each sub-area, which provide services to the service area. The user load is the load demand of users within the service area. When the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that all components within the service area are operating normally, the components in the target system are controlled to operate according to the current user load. The artificial intelligence model is obtained through pre-training using image pairs. Each image pair includes a first image at a first resolution and a second image at a second resolution, both captured from the same sub-area. The resolution of the monitoring image is the first resolution, and the second resolution is an integer multiple of the first resolution. When the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that a first component is operating abnormally within the service area, the second component in the target system is controlled to operate according to a specified working mode to eliminate the impact of the first component's failure. The second component differs from the first component and can adjust the load supply according to the load demand, thus solving the technical problem of insufficient energy efficiency in building equipment automatic control systems during operation. Attached Figure Description

[0020] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0021] Figure 1 This is a flowchart of an optional system control method according to an embodiment of this application;

[0022] Figure 2 This is a schematic diagram of a control device for an optional system according to an embodiment of this application;

[0023] Figure 3 This is a structural block diagram of a terminal according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] According to one aspect of the embodiments of this application, a method embodiment of a system control method is provided.

[0027] Figure 1 This is a flowchart of an optional system control method according to an embodiment of this application, such as... Figure 1 As shown, the method may include the following steps:

[0028] Step S1: Obtain the current user load of the service area of ​​the target system and the monitoring images of each sub-area in the service area. The target system includes multiple components located in each sub-area. These components are used to provide services to the service area. The user load is the load demand of users in the service area.

[0029] The target system described above can be a Building Automation (BA) system, where the user load is the demand for cooling or heating from residents within the service area. The aforementioned components can be some or all of the following: load supply equipment (such as ground source heat pump units), load exchange equipment (such as ground source side circulation pumps), load delivery equipment (such as air conditioning primary side circulation pumps), indoor equipment (such as chillers), circulation equipment (such as cooling water circulation pumps), and outdoor equipment (such as cooling towers).

[0030] Step S2: If the recognition results obtained by the artificial intelligence model based on the monitoring images of each sub-region indicate that all components in the service area are operating normally, control each component in the target system to work according to the current user load. The artificial intelligence model is obtained by pre-training using image pairs. The image pair includes a first image with a first resolution and a second image with a second resolution taken from the same sub-region. The resolution of the monitoring image is the first resolution, and the second resolution is an integer multiple of the first resolution.

[0031] In an optional embodiment, the multiple components in the above system can be N ground source heat pump units, M ground source side circulation pumps, and M air conditioning primary side circulation pumps. Controlling each component in the target system to operate according to the current user load includes: acquiring the user load provided by the multiple currently operating ground source heat pump units, multiple ground source side circulation pumps, and multiple air conditioning primary side circulation pumps, wherein the number of currently operating ground source heat pump units is less than or equal to an integer N, and the number of currently operating ground source side circulation pumps is the same as the number of currently operating air conditioning primary side circulation pumps and less than an integer M; when the provided user load does not match the current user load, controlling the operating status of the N ground source heat pump units, M ground source side circulation pumps, and M air conditioning primary side circulation pumps to meet the current user load, wherein the number of ground source side circulation pumps in operation is the same as the number of air conditioning primary side circulation pumps in operation.

[0032] For example, when the provided user load is less than the current user load, the electric valves on the inlet and outlet water pipes of the first ground source heat pump unit, which is in a closed state, are opened; after the electric valves have been open for a first period of time, the first ground source side circulation pump and the first air conditioning primary side circulation pump, which are in a closed state, are started; after the first ground source side circulation pump and the first air conditioning primary side circulation pump have been running for a second period of time, the first ground source heat pump unit is started. The first period of time is 2-3 minutes, and the second period of time is twice the first period of time.

[0033] For example, if the provided user load is greater than the current user load, the second ground source heat pump unit that is in the on state is shut down; after the shutdown time of the second ground source heat pump unit reaches the first duration, the second ground source side circulation pump and the second air conditioning primary side circulation pump that are in the on state are shut down; after the shutdown time of the second ground source side circulation pump and the second air conditioning primary side circulation pump reaches the second duration, the electric valves on the inlet and outlet water pipes of the second ground source heat pump unit are closed.

[0034] In another optional embodiment, the multiple components in the above system can be N ground source heat pump units, M air conditioning primary-side circulation pumps, P chillers, P cooling water circulation pumps, and P cooling towers. Controlling each component in the BA system to operate according to the current user load includes: acquiring the user load provided by the currently operating equipment, which includes at least multiple ground source heat pump units; and controlling the operating status of the M air conditioning primary-side circulation pumps, P chillers, P cooling water circulation pumps, and P cooling towers to meet the current user load when the provided user load does not match the current user load, wherein the number of chillers in operation is the same as the number of cooling towers in operation.

[0035] For example, when the provided user load is less than the current user load, the electric valves on the inlet and outlet water pipes of the first chiller unit, which is in a closed state, are opened; after the electric valves have been open for a third time, the first cooling water circulation pump and the third air conditioning primary side circulation pump, which are in a closed state, are started; after the first cooling water circulation pump and the third air conditioning primary side circulation pump have been running for a fourth time, the first cooling tower, which is in a closed state, is started; after the first cooling tower has been running for a fifth time, the first chiller unit is started, where the third time is greater than the fourth time and less than the fifth time.

[0036] For example, if the provided user load is greater than the current user load, the second chiller unit, which is in the on state, is shut down; after the second chiller unit has been shut down for six hours, the second cooling water circulation pump and the fourth air conditioning primary side circulation pump, which are in the on state, are shut down; after the second cooling water circulation pump and the fourth air conditioning primary side circulation pump have been shut down for seven hours, the electric valves on the inlet and outlet water pipes of the second chiller unit are closed; after the second cooling water circulation pump and the fourth air conditioning primary side circulation pump have been shut down for eight hours, the second cooling tower, which is in the on state, is shut down.

[0037] In one optional implementation, there are four ground source heat pump units (CH1-CH4), four ground source side circulation pumps (DYP1-DYP1), four air conditioning circulation pumps (CHP1-CHP4), and auxiliary systems such as corresponding plate heat exchangers and water replenishment devices.

[0038] The control strategy for the power data center is as follows:

[0039] 1) Utilizing heat pump units, chiller units, and water pump systems for cooling and heating.

[0040] 1.1) Heating and cooling by ground source heat pump units

[0041] After the ground source heat pump equipment is put into operation, if the load still cannot meet the user's demand after testing and calculation, then another air conditioning primary-side circulation pump will be started. The number of air conditioning primary-side circulation pumps started is also determined according to the load determination method: if starting one air conditioning primary-side circulation pump cannot meet the user's load, then a second air conditioning primary-side circulation pump will be started. The starting sequence of the ground source circulation pumps is determined according to the number of ground source heat pump units started. When the load decreases, the corresponding equipment will stop operating. The starting sequence of a single ground source heat pump unit is as follows:

[0042] The startup sequence for a single ground source heat pump unit is as follows: Open the electric valves on the inlet and outlet water pipes of the ground source heat pump unit; after the electric valves are opened, start one ground source side circulation pump and one air conditioning side circulation pump after a delay of 2-3 minutes (i.e., the first time interval); after the water pumps are running, start one ground source heat pump unit after a delay of 5-6 minutes (i.e., the second time interval).

[0043] The shutdown sequence for a single ground source heat pump unit is as follows: shut down the ground source heat pump unit; after shutting down the ground source heat pump unit, delay for 2-3 minutes to shut down the ground source side circulation pump and the air conditioning side circulation pump; after the water pump stops, delay for 5-6 minutes to close the electric valves on the inlet and outlet water pipes of the ground source heat pump unit.

[0044] 1.2) Cooling provided by chiller units

[0045] During the day, prioritize the use of ground source heat pump units CH1-CH4. When the ground source heat pump units cannot meet the user's required load, turn on the chiller units C1-C2 and the cooling tower. At night, when the outdoor temperature is low, the chiller units and cooling tower system can be turned on to restore the ground source heat exchange capacity.

[0046] If the local source heat pump equipment is still insufficient to meet system requirements after commissioning, the chiller unit needs to be started. If, after testing and calculation, the summer load still cannot meet user demand, one air conditioning primary-side circulation pump is started. The number of air conditioning primary-side circulation pumps started is determined according to the load determination method: if starting one air conditioning primary-side circulation pump is insufficient to meet user load, a second air conditioning primary-side circulation pump is started. After the chiller unit starts, the corresponding cooling tower is put into operation, with each cooling tower and chiller unit operating in a one-to-one correspondence. The number of cooling circulation pumps started is determined based on the number of chiller units started. When the load decreases, the corresponding equipment stops operating.

[0047] The startup sequence for a single chiller unit is as follows: Open the electric valves on the inlet and outlet water pipes of one chiller unit; after the electric valves are opened, start one cooling circulation pump and one air conditioning side circulation pump after a 2-3 minute delay (i.e., the third time interval); after the water pumps are running, start one cooling tower after a 1-2 minute delay (i.e., the fourth time interval); after the water pumps and cooling towers are running, start one chiller unit after a 5-6 minute delay (i.e., the fifth time interval).

[0048] The shutdown sequence for a single chiller unit is as follows: shut down one chiller unit; after the unit is shut down, delay for 10-15 minutes (i.e., the sixth hour) to shut down one cooling water circulation pump and one air conditioning side circulation pump; after the pumps are shut down, delay for 2-3 minutes (i.e., the seventh hour) to close the electric valves on the inlet and outlet water pipes of the chiller unit; after the pumps and unit are shut down, delay for 5-6 minutes (i.e., the eighth hour) to shut down one cooling tower.

[0049] 1.3) Water pump and cooling tower operation control strategy

[0050] The air conditioning-side circulating pump and cooling water pump are energy transfer devices in the system. The start and stop of these pumps are controlled according to different system settings. After receiving start / stop signals from the unit, the pump set will be uniformly regulated using frequency converter control. The specific pump to start and stop is determined according to the principle of equipment start-stop first and then stop later. The ground source side pump and air conditioning-side pump use frequency converter control, with multiple pumps operating simultaneously when adjusting the frequency. The ground source side pump uses frequency converter control, monitoring the temperature difference between the ground source supply and return water, and adjusting the pump speed through the frequency converter to achieve energy-saving control. However, the operating frequency of the ground source side pump must be set to a minimum frequency to ensure the normal operation of the unit (higher than the unit's minimum operating flow rate).

[0051] The air conditioning side water pump uses variable frequency control and needs to be controlled through the following three monitoring points:

[0052] a) The minimum operating frequency of the water pumps to ensure the normal operation of the unit;

[0053] b) Pressure difference between supply and return water at the most unfavorable end of the air conditioning side (pressure difference between supply and return water at the very end of the water transport system);

[0054] c) Temperature difference between supply and return water.

[0055] The air conditioning side water pump adopts variable frequency control. Under the premise of ensuring the lowest operating frequency and the most unfavorable pressure difference of the water pump, the frequency of the inverter is adjusted by the temperature difference between the supply and return water at the terminal, thereby adjusting the water pump speed and achieving the purpose of energy-saving control.

[0056] 2) Cooling water pump control

[0057] The cooling water pump uses variable frequency control, monitoring the temperature difference between the supply and return water on the cooling water side. The pump speed is adjusted via the frequency converter to achieve energy-saving control. However, the operating frequency of the cooling water pump must be set to a minimum frequency to ensure the normal operation of the chiller unit (higher than the unit's minimum operating flow rate).

[0058] 3) Cooling tower fan control strategy

[0059] The number of cooling tower fans in operation is controlled by temperature sensors installed on the return water pipeline. Real-time monitoring of the return water temperature allows for tiered control of the cooling tower's operation. When the actual return water temperature exceeds the set temperature (approximately 32°C), the cooling tower is loaded, increasing the number of operating fans. Conversely, when the actual return water temperature falls below the set temperature (approximately 32°C), the load is reduced, decreasing the number of operating fans.

[0060] The closed-circuit cooling tower comes with its own spray pump, which is controlled and protected by a float switch installed inside the tower. Each pump group has a backup pump, which is automatically activated in case of a malfunction, ensuring the safe and reliable operation of the system.

[0061] Step S3: If the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-region indicate that there is a first component with abnormal operation in the service area, the second component in the target system is controlled to operate in a specified working mode to eliminate the impact of the first component's failure. The second component is different from the first component. Here, eliminating the impact can be to directly eliminate the failure of the first component (such as clearing blocked inlets, outlets, pipes, etc.) or to replace the function of the first component (such as increasing the power of other identical components or starting a new component with the same function).

[0062] In the technical solution of this application, in order to diagnose faults in various parts of the Building Automation (BA) system (such as ground source heat pump units, ground source side circulation pumps, air conditioning primary side circulation pumps, fresh air units, capillary networks, etc.), this application adopts image-related artificial intelligence algorithms (i.e., artificial intelligence models). The images of each part of the BA system collected can serve as the basis and foundation for diagnosis. For accurate identification, high-definition images are required. However, to avoid additional costs (not purchasing dedicated image acquisition equipment), images need to be acquired using existing image acquisition equipment. This is clearly contradictory, as existing image acquisition equipment is not dedicated (generally monitoring equipment), and its images do not include complex details. Therefore, deep learning technology can be used to process these simple images, obtaining more detailed information through super-resolution processing. This information is crucial for fault diagnosis. The specific implementation method of fault diagnosis is as follows:

[0063] Step S31: Acquire image pairs of the target part to be monitored in the BA system (the target part can be any part, including ordinary color image pairs or infrared image pairs).

[0064] The tasks are predefined (such as internal malfunctions or inlet / outlet blockages of heat pumps in the energy room, internal malfunctions or inlet / outlet blockages of boilers in the energy room, etc.). For each task, for each part of the BA system related to the task, image acquisition device 1 (with the first resolution) is called to take m images from multiple angles at a fixed distance (such as 8 meters, 12 meters, 20 meters, etc.). (For example, taking a 90° angle as a reference, images are taken at 10° increments to both sides, forming images with 17 angles, i.e., images from 10° to 170°). These images are denoted as LP. Then, image acquisition device 2 (with a resolution that is an integer multiple of the resolution of image acquisition device 1, such as 2 times, 5 times, etc.) is called to take m images from multiple angles at the same distance. These images are denoted as HP. LP and HP at the same angle are recorded as an image pair.

[0065] Step S32: Preprocess the acquired image pairs to obtain more training image pairs and enrich the training data.

[0066] Step S321, Image Splitting: Image splitting includes cropping, angle transformation, and color space transformation. Each transformation randomly generates a triplet [crop coordinates, transformation angle, color space transformation matrix] (crop coordinates and transformation angle are randomly generated in the triplet, while the color space transformation matrix is ​​randomly selected from multiple candidate color space transformation matrices). It should be noted that the value of the color space transformation matrix in the infrared image pair is always 0. The element value in the array is 0 to indicate no corresponding operation or a non-zero value to indicate corresponding operation. For example, the crop coordinates are the coordinates of the two diagonals (which determine the rectangle to be cropped). The transformation angle includes the rotation angles in the x, y, and z directions. It should be noted that for the same image pair, cropping needs to be aligned with the real world position (i.e., each image corresponds to the same area in the real world).

[0067] Step S322, Image Anti-interference Enhancement: This includes Laplacian Transform, Histogram Equalization, and Gradient Operator Sharpening. During each enhancement, a ternary array [Laplacian Transform, Histogram Equalization, Gradient Operator Sharpening] is randomly obtained (multiple Laplacian Transform operators, histogram equalization operators, and gradient operators are pre-configured; each time, one is randomly selected from multiple Laplacian Transform operators, one from multiple candidate histogram equalization operators, and one from multiple candidate gradient operators). The element values ​​in the array are either 0 (indicating no corresponding operation) or non-zero values ​​representing the selected operator (e.g., 1 represents the first operator, 2 represents the second operator, and so on; of course, the operator itself can also be used directly).

[0068] For each image pair, p1 random image splits can be performed. After each split, p2 random image anti-interference enhancements are performed on each image pair. The final number of image pairs is m*p1*p2.

[0069] Step S33: Construct an artificial intelligence model (including two parts: a generative model and a classification model).

[0070] This scheme employs a generative model based on variational inference, where the latent variables are of the same dimension as the original data, and the inference process is often fixed, giving it powerful capabilities in generative tasks. The inference process consists of: denoising autoencoders (encoding the original image into a latent representation and decoding the noisy data from it), uniform sampling, and layer-by-layer generation.

[0071] Step S331: Encode the original image (i.e., the image in the image pair) into a latent representation.

[0072] Transform the distribution q(u0) of the known low-resolution image u0 into a latent variable distribution q(u T The noise is then fixed to a Markov chain, which gradually adds Gaussian noise to the image data according to the timestamp. This can be represented as:

[0073]

[0074]

[0075] In the above formula, q(u1,…,u) T |u0) represents the conditional probability distribution of a given low-resolution image u0 (i.e., the image LP acquired in the first round) after T-step diffusion, where q(u t |u t-1 Let u represent the conditional probability distribution of the diffusion process from time t-1 to t. t This represents the image data obtained by adding noise at timestamp t, u1,…,u T This represents a latent variable with the same data dimension as u0. T Let I represent the final generated noise image with an approximate standard Gaussian distribution, where the timestamp t∈{1,2,…,T}, and I is a matrix containing only 1s. Representing a Gaussian distribution, β1,β1,…,β t The noise level parameter representing the diffusion process has the following variance:

[0076] α t :=1-β t ,

[0077]

[0078] The values ​​of α and β can be obtained by looking up a table (pre-set). According to Markov chain theory, this process allows sampling of u at any time step t. t :

[0079]

[0080] u at any time t The relationship with the initial value can be expressed as:

[0081]

[0082] Where ∈ represents real Gaussian noise generated using a Gaussian distribution.

[0083] Step S332, convert the variable distribution of the latent representation into the actual data distribution (i.e., uniform sampling and layer-by-layer generation).

[0084] Transforming the potential variable distribution into the actual data distribution can be understood as supplementing high-frequency data. This process can be illustrated by the following formula:

[0085]

[0086]

[0087] The above formula can be understood as the process of the sampling model generating an image, and the corresponding joint distribution is p. θ (u0,…,u T-1 |u T ), is a Markov chain, the difference being that the final output is u0, and the input is Distribution μ θ (u t ,t) represents the mean, σ θ (u t ,t) represents the variance, and θ represents the parameters of the simulated noise generation model.

[0088] Step S34: Train the constructed artificial intelligence model.

[0089] Step S341, Initialize parameters: Initialize the artificial intelligence model (denoted as the original model), i.e., hyperparameters, such as network structure, parameter initialization, optimizer selection, etc.

[0090] Step S342: The image pairs obtained after expansion in step S32 are divided into multiple subsets according to the task (each subset is used for training of a batch, a subset includes image pairs of at least one task, and the tasks included in any two subsets do not overlap), and split into training set 1 and training set 2 (e.g., divided in a 3:1 ratio).

[0091] Step S343: Copy an original model as intermediate model 1 to be trained, input the training set 1 and the corresponding task from a batch into the model for training, and obtain the target model 1 after training is completed.

[0092] Step S344: For target model 1, calculate the generalization loss using training set 2:

[0093] L1 = u HP -(up(u LP )+∈ θ (u t ,u LP ,t)),

[0094] u HP Represents a high-resolution image, up(u LP ) represents a low-resolution image u LP Upsampled image, ∈ θ (u t ,u LP ,t) represents simulated Gaussian noise generated using the network.

[0095] Step S345: Update the parameters and hyperparameters in the original model using the calculated generalization loss.

[0096] Then, for the training of the i-th batch (where i is greater than 1 and the upper limit is the maximum number of batches), repeat steps S342 and S343 to train the intermediate model i to obtain the target model i used to identify the corresponding task. Then, based on the generalization loss of the target model i, continue to update the original model until the training of all batches is completed.

[0097] The steps S342-S343 above improve the model's ability to distinguish a single batch, i.e., one or more specific tasks. The subsequent steps S344-S344 improve the generalization ability of the original model.

[0098] For example, Task 1 is apple classification, and an apple classification model can be obtained using the corresponding training set. Task 2 is pear classification, and a pear classification model can be obtained using the corresponding training set. Task 3 is cherry classification, and a cherry classification model can be obtained using the corresponding training set. Since the original model is back-optimized after Task 1 is completed, the model for Task 2 already has a certain recognition ability before training. Theoretically, Task 2 can be trained with less data than Task 1. Since the original model is also back-optimized after Task 2 is completed, the model for Task 3 already has a stronger recognition ability before training. Theoretically, Task 3 can be trained with less data than Task 2. And so on, the generalization ability of the original model will become stronger and stronger, while the amount of training data required will become less and less.

[0099] Through the above process, a correlation is established between low-resolution images and high-resolution images. In the subsequent fault identification process, only low-resolution images need to be collected, and the generative model can be used to generate high-resolution images. Then, the classification model can be used to identify faults using high-resolution images.

[0100] Step S35: Use the trained model to identify faults.

[0101] The technical solution adopted in this application has the following advantages: 1) No high-definition equipment needs to be installed; image acquisition and fault identification can be achieved based on existing equipment. 2) Since each round of model training will generate positive feedback to the original model (i.e., improve the generalization ability of the original model across different tasks), it is possible to train a model with good recognition performance with only a small amount of data when using the original model in the future, without having to provide a large number of training samples, and significantly reducing training time. 3) For complex classification and image acquisition, it can significantly reduce the data labeling for new tasks, and greatly improve the robustness and adaptability of the model. 4) For new scenarios (such as new fault tasks), no complex fine-tuning is required; simply adding a fully connected (FC) layer can achieve good training results without changing the information of other branches in the existing model.

[0102] Taking the unblocking of equipment inlets and outlets as an example, the specific methods for troubleshooting are as follows:

[0103] The equipment is generally equipped with valves at the inlet and outlet, and flow sensors and pressure sensors are installed before and after the valves.

[0104] 1) If the artificial intelligence model identifies a valve malfunction using the collected infrared images, it will prompt the valve to be replaced.

[0105] 2) If the artificial intelligence model identifies the blockage as being caused by inlet / outlet obstruction (such as blockage due to rust or fallen parts) using the collected infrared images, it will clear the blockage as follows:

[0106] First, determine the blockage level, obtain the pressure value 1 at the valve (outflow) before the blockage location, the pressure value 2 at the valve (inflow) before the blockage location, and the current blockage level. Mathematical symbols Indicates rounding down;

[0107] Then, pressurization is carried out according to the determined blockage level p (the higher the blockage level, the greater the pressure) so that the blockage can be dispersed and washed away by the high-pressure water flow, and the inlet and outlet can be restored to normal.

[0108] It should be noted that if the above-mentioned unblocking methods fail (e.g., maintaining pressure for a specific duration without successful unblocking), the open and closed states of the inlet and outlet will continue to be maintained. Pulse opening and closing control will be applied to the target valve (i.e., the valve in front of the blockage). During the i-th unblocking attempt, the target valve will be opened at the following frequency f(i): f(i) = 5*i. For example, when i = 1, the target valve will open 5 times per minute, each time for 6 seconds and then closed for 6 seconds. When i = 2, the target valve will open 10 times per minute, each time for 3 seconds and then closed for 3 seconds, and so on, until i reaches the value of 6. Every 6 times is considered one round of unblocking. After each round, the pressure change before and after the blockage is compared. If there is a change, pulse unblocking will continue. If the pressure before and after the blockage does not change for several consecutive rounds (e.g., 6 rounds), pulse unblocking will stop.

[0109] It can also identify blockages in pipes between equipment rooms, and then perform unblocking or replacement in a similar manner as described above.

[0110] Through the above steps, the current user load of the target system's service area and monitoring images of each sub-area within the service area are obtained. The target system includes multiple components located in each sub-area, which provide services to the service area. The user load is the load demand of users within the service area. If the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that all components within the service area are operating normally, the components in the target system are controlled to operate according to the current user load. The artificial intelligence model is pre-trained using image pairs, which include a first image at a first resolution and a second image at a second resolution taken from the same sub-area. The resolution of the monitoring image is the first resolution, and the second resolution is an integer multiple of the first resolution. If the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that a first component is malfunctioning within the service area, the second component in the target system is controlled to operate according to a specified working mode to eliminate the impact of the first component's failure. Unlike the first component, the second component can adjust the load supply according to load demand, thus solving the technical problem of insufficient energy efficiency in building automation systems.

[0111] Alternatively, the boiler can be designed with two spaces (specifically, through two partitions: partition A and the lower partition B, with water passage holes at the same positions on both. Partition A can rotate, allowing the water passage holes on partition B to be opened, partially closed, or completely closed). The lower space of the boiler is directly heated, while the upper space is indirectly heated, and the water in both spaces can be mixed for heating. This design offers the following advantages in terms of energy saving and flexibility: 1) Layered heating improves thermal efficiency and enables tiered utilization of thermal energy: The water in the lower space directly contacts the heat source, obtaining a higher temperature and achieving efficient utilization of thermal energy; the water in the upper space absorbs heat from the lower space through heat conduction, forming a temperature gradient and achieving secondary utilization of thermal energy. This design reduces heat loss and improves the overall thermal efficiency of the boiler. 2) Precise temperature control to meet diverse needs, flexible mixing ratio to adapt to various loads: By controlling the mixing ratio of water in the upper and lower spaces, suitable water temperatures can be provided according to the different heating temperature requirements of different floors or residents. For areas with regular heating needs, mixed water can be supplied; for floors with higher heating needs or residents who urgently need higher temperatures, high-temperature water from the lower space can be supplied separately. This refined heating method can better match actual needs and avoid overheating waste or insufficient heating. 3) Energy-saving operation, reduced energy consumption, and energy-saving mode switching: When the overall heating demand is low or some areas only require regular heating, mixed water is mainly used for heating, reducing the use of high-temperature water and reducing energy consumption. Only when rapid heating is needed or to meet special high-temperature requirements is the high-temperature water from the lower space used, achieving on-demand heating and avoiding excessive energy consumption. Reduced heat loss: The design of separating the upper and lower spaces helps reduce heat transfer between the heat source and the boiler shell, especially since the water temperature in the upper space is relatively lower, reducing radiation and convection heat loss to the external environment and further improving the overall thermal efficiency of the boiler. 4) Dynamic adjustment, rapid response, and real-time mixing ratio adjustment: By controlling the valve opening for mixing water in the upper and lower spaces, the water supply temperature can be quickly adjusted according to changes in external temperature and user demand, enhancing the response speed and adaptability of the heating system. Emergency heating guarantee: In extreme weather or sudden increases in heating demand, high-temperature water from the lower space can be directly drawn to provide emergency or additional heating support, ensuring the stability and reliability of the heating system. 5) Extended equipment life, reduced maintenance costs, and reduced thermal stress: By mixing low-temperature and high-temperature water, the thermal stress on pipes, radiators, and other equipment in the entire system can be effectively reduced, slowing down material aging and extending equipment life, thereby reducing maintenance and replacement costs during long-term operation.

[0112] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0113] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0114] According to another aspect of the embodiments of this application, a control device for a system implementing the control method of the above-described system is also provided. Figure 2 This is a schematic diagram of a control device for an optional system according to an embodiment of this application, such as... Figure 2 As shown, the device may include:

[0115] The acquisition unit 21 is used to acquire the current user load of the service area of ​​the target system and the monitoring images of each sub-area in the service area. The target system includes multiple components located in each sub-area. The multiple components are used to provide services to the service area. The user load is the load demand of users in the service area.

[0116] The first control unit 22 is used to control each component in the target system to work according to the current user load when the recognition results obtained by the artificial intelligence model based on the monitoring images of each sub-region indicate that the components in the service area are all operating normally. The artificial intelligence model is obtained by pre-training using image pairs. The image pairs include a first image with a first resolution and a second image with a second resolution taken from the same sub-region. The resolution of the monitoring image is the first resolution, and the second resolution is an integer multiple of the first resolution.

[0117] The second control unit 23 is used to control the second component in the target system to operate in a specified working mode when the identification result obtained by the artificial intelligence model based on the monitoring images of each sub-region indicates that there is a first component with abnormal operation in the service area, so as to eliminate the impact of the failure of the first component. The second component is different from the first component.

[0118] Through the aforementioned modules, the current user load of the target system's service area and monitoring images of each sub-area within the service area are obtained. The target system includes multiple components located in each sub-area, which provide services to the service area. The user load is the load demand of users within the service area. If the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that all components within the service area are operating normally, the system controls each component in the target system to operate according to the current user load. The artificial intelligence model is pre-trained using image pairs, which include a first image at a first resolution and a second image at a second resolution taken from the same sub-area. The resolution of the monitoring image is the first resolution, and the second resolution is an integer multiple of the first resolution. If the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that a first component in the service area is malfunctioning, the system controls the second component in the target system to operate according to a specified working mode to eliminate the impact of the first component's failure. Unlike the first component, the second component can adjust the load supply according to load demand, thus solving the technical problem of insufficient energy efficiency in building automation systems.

[0119] It should be noted that the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should also be noted that the above modules, as part of the device, can run in a corresponding hardware environment, and can be implemented through software or hardware, wherein the hardware environment includes a network environment.

[0120] According to another aspect of the embodiments of this application, a server or terminal for implementing the control method of the above-described system is also provided.

[0121] Figure 3 This is a structural block diagram of a terminal according to an embodiment of this application, such as... Figure 3 As shown, the terminal may include: one or more (only one is shown in the figure) processors 301, memory 303, and transmission devices 305, such as... Figure 3 As shown, the terminal may also include input / output devices 307.

[0122] The memory 303 can be used to store software programs and modules, such as the program instructions / modules corresponding to the control method and apparatus of the system in this embodiment. The processor 301 executes various functional applications and data processing by running the software programs and modules stored in the memory 303, thereby realizing the control method of the system described above. The memory 303 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 303 may further include memory remotely located relative to the processor 301, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0123] The aforementioned transmission device 305 is used to receive or send data via a network, and can also be used for data transfer between the processor and memory. Specific examples of the network described above may include wired networks and wireless networks. In one example, the transmission device 305 includes a Network Interface Controller (NIC), which can be connected to other network devices and routers via a network cable to communicate with the Internet or a local area network. In another example, the transmission device 305 is a radio frequency (RF) module used for wireless communication with the Internet.

[0124] Specifically, memory 303 is used to store application programs.

[0125] The processor 301 can invoke the application program stored in the memory 303 via the transmission device 305 to perform the following steps:

[0126] The system acquires the current user load of the service area of ​​the target system and monitoring images of each sub-area within the service area. The target system includes multiple components located in each sub-area, which provide services to the service area. The user load is the load demand of users within the service area. If the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that all components within the service area are operating normally, the system controls each component of the target system to operate according to the current user load. The artificial intelligence model is pre-trained using image pairs, which include a first image at a first resolution and a second image at a second resolution taken from the same sub-area. The resolution of the monitoring images is the first resolution, and the second resolution is an integer multiple of the first resolution. If the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that a first component is malfunctioning within the service area, the system controls the second component in the target system to operate according to a specified working mode to eliminate the impact of the first component's failure. The second component is different from the first component.

[0127] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated here.

[0128] Those skilled in the art will understand that Figure 3 The structure shown is for illustrative purposes only. The terminal can be a smartphone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile internet device (MID), a PAD, or other terminal devices. Figure 3 This does not limit the structure of the aforementioned electronic device. For example, the terminal may also include components that are more... Figure 3 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 3 The different configurations shown.

[0129] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0130] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to execute program code for a system control method.

[0131] Optionally, in this embodiment, the storage medium may be located on at least one of the network devices in the network shown in the above embodiment.

[0132] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps:

[0133] The system acquires the current user load of the service area of ​​the target system and monitoring images of each sub-area within the service area. The target system includes multiple components located in each sub-area, which provide services to the service area. The user load is the load demand of users within the service area. If the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that all components within the service area are operating normally, the system controls each component of the target system to operate according to the current user load. The artificial intelligence model is pre-trained using image pairs, which include a first image at a first resolution and a second image at a second resolution taken from the same sub-area. The resolution of the monitoring images is the first resolution, and the second resolution is an integer multiple of the first resolution. If the identification results obtained by the artificial intelligence model based on the monitoring images of each sub-area indicate that a first component is malfunctioning within the service area, the system controls the second component in the target system to operate according to a specified working mode to eliminate the impact of the first component's failure. The second component is different from the first component.

[0134] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated here.

[0135] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0136] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0137] If the integrated units in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0138] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0139] In the several embodiments provided in this application, it should be understood that the disclosed client can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0140] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0141] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0142] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A system control method, characterized in that, include: The current user load of the service area of ​​the target system and the monitoring images of each sub-area in the service area are obtained. The target system includes multiple components located in each sub-area. The multiple components are used to provide services to the service area. The user load is the load demand of users in the service area. If the recognition results obtained by the artificial intelligence model based on the monitoring images of each sub-region indicate that all components in the service area are operating normally, the system controls each component in the target system to work according to the current user load. The artificial intelligence model is obtained by pre-training with image pairs, which include a first image of a first resolution and a second image of a second resolution taken from the same sub-region. The resolution of the monitoring image is the first resolution, and the second resolution is an integer multiple of the first resolution. If the identification result obtained by the artificial intelligence model based on the monitoring images of each sub-region indicates that there is a first component with abnormal operation in the service area, the second component in the target system is controlled to operate in a specified working mode to eliminate the impact of the failure of the first component. The second component is different from the first component. The plurality of components includes N load providing devices, M load switching devices, and M load delivery devices, wherein controlling each component in the target system to operate according to the current user load includes: Get the user load provided by multiple currently running load providing devices, multiple load switching devices, and multiple load delivery devices, wherein the number of currently running load providing devices is less than or equal to an integer N, and the number of currently running load switching devices is the same as the number of currently running load delivery devices and is less than an integer M; If the provided user load does not match the current user load, the operating status of the N load providing devices, the M load switching devices, and the M load delivery devices is controlled to meet the current user load. The number of load switching devices in operation is the same as the number of load delivery devices in operation.

2. The method according to claim 1, characterized in that, Before acquiring the current user load of the service area of ​​the target system and the monitoring images of each sub-area within the service area, the method further includes: The first image acquisition device and the second image acquisition device are respectively invoked to acquire image pairs of the target part to be monitored in the target system at a fixed distance. The resolution of the first image acquisition device is a first resolution, and the resolution of the second image acquisition device is a second resolution. The acquired image pairs are preprocessed to obtain training image pairs. The preprocessing includes image splitting and image anti-interference enhancement. The image splitting includes cropping, angle transformation and color space transformation. The image anti-interference enhancement includes Laplacian transform, histogram equalization and gradient operator sharpening. An artificial intelligence model is constructed, which includes a generative model and a classification model, and the artificial intelligence model is trained using training images.

3. The method according to claim 1, characterized in that, When the provided user load does not match the current user load, the operating status of the M load switching devices and the M load delivery devices is controlled, including: When the provided user load is less than the current user load, the electric valves on the inlet and outlet water pipes of the first load providing device, which is in a closed state, are opened; after the electric valves have been open for a first period of time, the first load exchange device and the first load delivery device, which are in a closed state, are started; when the first load exchange device and the first load delivery device have been running for a second period of time, the first load providing device is started, wherein the first period of time is 2-3 minutes, and the second period of time is twice the first period of time; If the provided user load is greater than the current user load, shut down the second load providing device that is in the open state; after the shutdown time of the second load providing device reaches the first time, shut down the second load switching device and the second load delivery device that are in the open state; after the shutdown time of the second load switching device and the second load delivery device reaches the second time, close the electric valves on the inlet and outlet water pipes of the second load providing device.

4. The method according to claim 1, characterized in that, The target system includes N load providing devices, M load delivery devices, P indoor devices, P circulating devices, and P outdoor devices. Controlling each component of the target system to operate according to the current user load includes: Obtain the user load provided by the currently running devices, wherein the currently running devices include multiple load-providing devices; If the provided user load does not match the current user load, the operating status of the M load delivery devices, the P indoor devices, the P circulating devices, and the P outdoor devices are controlled to meet the current user load, wherein the number of indoor devices in operation is the same as the number of outdoor devices in operation.

5. The method according to claim 4, characterized in that, When the provided user load does not match the current user load, the operating status of the M load delivery devices, the P indoor devices, the P circulating devices, and the P outdoor devices is controlled, including: If the provided user load is less than the current user load, open the electric valves on the inlet and outlet water pipes of the first indoor device, which is in a closed state; after the electric valves have been open for a third period of time, start the first circulation device and the third load delivery device, which are in a closed state; after the first circulation device and the third load delivery device have been running for a fourth period of time, start the first outdoor device, which is in a closed state; after the first outdoor device has been running for a fifth period of time, start the first indoor device, wherein the third period of time is greater than the fourth period of time and less than the fifth period of time.

6. The method according to claim 5, characterized in that, In the event that the provided user load does not match the current user load, controlling the operating status of the M load delivery devices, the P indoor devices, the P circulating devices, and the P outdoor devices further includes: If the provided user load exceeds the current user load, shut down the second indoor device that is in the open state; after the second indoor device has been closed for a period of six hours, shut down the second circulation device and the fourth load delivery device that are in the open state; after the second circulation device and the fourth load delivery device have been closed for a period of seven hours, close the electric valves on the inlet and outlet water pipes of the second indoor device; after the second circulation device and the fourth load delivery device have been closed for a period of eight hours, shut down the second outdoor device that is in the open state.

7. A control device for a target system, characterized in that, include: The acquisition unit is used to acquire the current user load of the service area of ​​the target system and the monitoring images of each sub-area in the service area. The target system includes multiple components located in each sub-area. The multiple components are used to provide services to the service area. The user load is the load demand of users in the service area. The first control unit is configured to control each component in the target system to operate according to the current user load when the recognition results obtained by the artificial intelligence model based on the monitoring images of each sub-region indicate that all components in the service area are operating normally. The artificial intelligence model is obtained by pre-training using image pairs, and the image pairs include a first image of a first resolution and a second image of a second resolution taken from the same sub-region. The resolution of the monitoring image is the first resolution, and the second resolution is an integer multiple of the first resolution. The second control unit is used to control the second component in the target system to operate in a specified working mode when the identification result obtained by the artificial intelligence model based on the monitoring images of the various sub-regions indicates that there is a first component with abnormal operation in the service area, so as to eliminate the impact of the failure of the first component. The second component is different from the first component. The plurality of components includes N load providing devices, M load switching devices, and M load delivery devices. In the first control unit, the various components of the target system are controlled to operate according to the current user load, including: Get the user load provided by multiple currently running load providing devices, multiple load switching devices, and multiple load delivery devices, wherein the number of currently running load providing devices is less than or equal to an integer N, and the number of currently running load switching devices is the same as the number of currently running load delivery devices and is less than an integer M; If the provided user load does not match the current user load, the operating status of the N load providing devices, the M load switching devices, and the M load delivery devices is controlled to meet the current user load. The number of load switching devices in operation is the same as the number of load delivery devices in operation.

8. A computer-readable storage medium, characterized in that, The storage medium includes a stored program, wherein the program executes the method described in any one of claims 1 to 6 when it is run.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the method described in any one of claims 1 to 6 via the computer program.

Images