Intelligent operation and maintenance method and system for central air conditioner

Abstract

The invention discloses an intelligent operation and maintenance method and system of a central air conditioner, and relates to the technical field of intelligent operation and maintenance methods, and the intelligent operation and maintenance system of the central air conditioner is determined according to a cold supply mode of each cold supply area, external weather information and indoor temperature loss of a plurality of cold supply areas. And the accuracy of the intelligent operation and maintenance system of the central air conditioner is ensured. A plurality of temperature regulation paths are determined based on the current temperature of each cold supply area, the personnel activity event of each cold supply area and the relative position of each cold supply area, so that the accuracy of the plurality of temperature regulation paths is ensured. Autonomous regulation and control of the multiple cooling areas are triggered on the basis of the multiple temperature regulation and control paths, the current time and the indoor states of the cooling areas, the working duration of the central air conditioner is regulated and controlled on the basis of the standby air conditioner, at the moment, autonomous regulation and control of the multiple cooling areas are achieved, dynamic management and control of the central air conditioner on the cooling areas are fully utilized, and meanwhile the cooling efficiency is improved. And the working time of the central air conditioner is regulated.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent operation and maintenance methods, and in particular to an intelligent operation and maintenance method and system for a central air conditioner. Background Art

[0002] With the development of science and technology, central air-conditioning is applied to people's lives. As one of the refrigeration equipment in buildings, central air-conditioning is open to various spaces in the building. There are various floors in the building with different functional areas. In the existing technology, the central air-conditioning provides cooling to each cooling area and provides cooling according to the preset cooling mode. It is not compatible with the indoor temperature loss of multiple cooling areas, which affects the accuracy of the intelligent operation and maintenance system of the central air-conditioning. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art, and the present invention provides an intelligent operation and maintenance method and system for a central air conditioner.

[0004] An embodiment of the present invention provides an intelligent operation and maintenance method for a central air conditioner, comprising: determining each cooling space in a building based on a cooling path of the central air conditioner and a three-dimensional model of the building; determining multiple cooling areas according to each cooling space, the corresponding floor position of the building and the corresponding indoor area; determining a cooling mode of the cooling area based on the multiple cooling areas, the corresponding area functions and the number of people in the cooling area; determining an intelligent operation and maintenance system for the central air conditioner according to the cooling mode of each cooling area, external weather information and the indoor temperature loss of the multiple cooling areas; in the intelligent operation and maintenance system of the central air conditioner, determining multiple temperature control paths based on the current temperature of each cooling area, personnel activity events in each cooling area and the relative position of each cooling area; triggering autonomous control of multiple cooling areas based on the multiple temperature control paths, the current time and the indoor status of each cooling area, and controlling the working time of the central air conditioner based on the standby air conditioner.

[0005] An embodiment of the present invention provides a central air conditioner intelligent operation and maintenance system, the central air conditioner intelligent operation and maintenance system is applied to the above-mentioned central air conditioner intelligent operation and maintenance method, the central air conditioner intelligent operation and maintenance system includes:

[0006] A cooling space module is used to determine each cooling space in the building based on the cooling path of the central air conditioner and the three-dimensional model of the building;

[0007] A cooling zone module, for determining a plurality of cooling zones according to each cooling space, the floor position of the corresponding building and the corresponding indoor area;

[0008] A cooling mode module, used to determine a cooling mode for a cooling area based on multiple cooling areas, corresponding area functions, and the number of people in the cooling area;

[0009] The intelligent operation and maintenance system module is used to determine the intelligent operation and maintenance system of the central air conditioner according to the cooling mode of each cooling area, external weather information, and indoor temperature loss of multiple cooling areas;

[0010] The temperature control module is used to determine multiple temperature control paths in the intelligent operation and maintenance system of the central air conditioner based on the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area;

[0011] The autonomous control module is used to trigger the autonomous control of multiple cooling areas based on multiple temperature control paths, the current time and the indoor status of each cooling area, and the standby air conditioner controls the working time of the central air conditioner.

[0012] The present invention has the following beneficial effects:

[0013] (1) Based on the cooling path of the central air conditioner and the three-dimensional model of the building, the various cooling spaces in the building are determined; multiple cooling areas are determined according to the various cooling spaces, the corresponding floor locations of the building, and the corresponding indoor areas; the cooling modes of the cooling areas are determined based on the multiple cooling areas, the corresponding regional functions, and the number of people in the cooling areas; the intelligent operation and maintenance system of the central air conditioner is determined according to the cooling modes of the cooling areas, the external weather information, and the indoor temperature losses of the multiple cooling areas, which is compatible with the overall consideration of the cooling modes of the cooling areas, the external weather information, and the indoor temperature losses of the multiple cooling areas, thereby ensuring the accuracy of the intelligent operation and maintenance system of the central air conditioner and improving the adaptability of the intelligent operation and maintenance system of the central air conditioner to the building.

[0014] (2) In the intelligent operation and maintenance system of central air conditioning, multiple temperature control paths are determined based on the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative position of each cooling area. Multiple interactions of the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative position of each cooling area are realized, ensuring the accuracy of multiple temperature control paths.

[0015] (3) Based on multiple temperature control paths, the current time and the indoor status of each cooling area, autonomous control of multiple cooling areas is triggered, and the working hours of the central air conditioner are regulated based on the standby air conditioner. At this time, autonomous control of multiple cooling areas is achieved, and the dynamic control of each cooling area by the central air conditioner is fully utilized. At the same time, the assistance ability of the standby air conditioner to the standby air conditioner is improved, and the working hours of the central air conditioner are regulated. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of an application scenario of a smart operation and maintenance method for a central air conditioner in an embodiment;

[0017] Figure 2 It is a flowchart of the intelligent operation and maintenance method of the central air conditioner in the embodiment of the present invention;

[0018] Figure 3 It is a schematic diagram of the structural composition of the intelligent operation and maintenance system of the central air conditioner in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0020] Embodiment 1

[0021] The intelligent operation and maintenance method of central air conditioner provided in this application is applied to Figure 1 In the application environment shown, the computer 102 communicates with the server 104 through the network. The computer 102 is not limited to various personal computers, servers, and intelligent operation and maintenance methods, and the server 104 is implemented by an independent server or a server cluster composed of servers.

[0022] Embodiment 2

[0023] See also Figures 1 to 3 , a central air conditioner intelligent operation and maintenance method, applied to the central air conditioner intelligent operation and maintenance scenario; the central air conditioner intelligent operation and maintenance method includes:

[0024] Step S11: determining each cooling space in the building based on the cooling path of the central air conditioner and the three-dimensional model of the building;

[0025] Step S12: determining a plurality of cooling areas according to each cooling space, the corresponding floor position of the building and the corresponding indoor area;

[0026] Step S13: determining a cooling mode of the cooling area based on the plurality of cooling areas, corresponding area functions and the number of people in the cooling area;

[0027] Step S14: determining the intelligent operation and maintenance system of the central air conditioner according to the cooling mode of each cooling area, external weather information, and indoor temperature losses of multiple cooling areas;

[0028] Step S15: In the intelligent operation and maintenance system of the central air conditioner, multiple temperature control paths are determined based on the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area;

[0029] Step S16: triggering autonomous regulation of multiple cooling areas based on multiple temperature control paths, current time, and indoor status of each cooling area, and using the standby air conditioner to regulate the working time of the central air conditioner.

[0030] In step S11, each cooling space in the building is determined based on the cooling path of the central air conditioner and the three-dimensional model of the building;

[0031] In the specific implementation process of the present invention, the specific steps are:

[0032] S111: collecting the location of the building, and determining a three-dimensional model of the building according to the location of the building, the architectural information of the building, and the town database;

[0033] S112: Determine a pipeline layout diagram of the building according to the traversal of the three-dimensional model of the building;

[0034] S113: determining a cooling path of the central air conditioner according to a spatial position of the central air conditioner relative to the building and a pipeline layout diagram of the building;

[0035] S114: Determine each cooling space in the building based on the cooling path of the central air conditioner, the three-dimensional model of the building, and the rental and sale status of each indoor space in the building.

[0036] In an embodiment of the present application, the location of the building is collected, and the three-dimensional model of the building is determined based on the location of the building, the building's architectural information and the town database, which is compatible with the overall consideration of the location of the building, the building's architectural information and the town database, and ensures the accuracy of the three-dimensional model of the building.

[0037] At this time, use GPS or other geo-positioning technologies to obtain the precise latitude and longitude coordinates of the building; record the street address, city, postal code and other geographic location information of the building; at the same time, obtain detailed design drawings, building specifications, floor heights, room layouts and other information of the building from the architectural design company, property management party or relevant government departments; this information exists in the form of paper drawings, electronic documents (such as CAD files) or databases.

[0038] Access town planning databases or geographic information systems (GIS) to obtain urban planning information, building standards, land use planning, etc. of the area where the building is located; this information helps to verify and supplement the accuracy of the building's architectural information, especially when the building information is incomplete or updated; combine the building's location information, architectural information and town database, and use 3D modeling software (such as AutoCAD, SketchUp, Revit, etc.) or GIS tools to build a three-dimensional model of the building; the three-dimensional model should be able to reflect the building's geometric shape, floor distribution, room layout, and obstacles (such as columns, walls) and pipeline locations.

[0039] Furthermore, the pipeline layout diagram of the building is determined according to the traversal of the three-dimensional model of the building, thereby realizing the traversal of the three-dimensional model of the building and ensuring the accuracy of the pipeline layout diagram of the building.

[0040] At this time, in the three-dimensional model of the building, traversal means checking each space in the model one by one according to floors, rooms or specific paths to identify and record the location, type and connection relationship of the pipes; in the traversal process, identifying the pipe components in the model is a key step; this involves distinguishing different types of pipes (such as water supply pipes and drainage pipes), determining the size and material of the pipes, and recording the connection points and directions of the pipes; optionally, the pipe components exist in the three-dimensional model in the form of prefabricated three-dimensional models, and are also provided in the form of two-dimensional drawings or data tables, and are marked and matched in the three-dimensional model.

[0041] After traversing and identifying the pipeline components, record detailed pipeline layout information; this includes the location of the pipeline (such as the specific location on the floor, room, wall or under the ground), the direction of the pipeline (such as horizontal or vertical), the connection relationship of the pipeline (such as branch points, confluence points), and parameters such as the size, material and flow of the pipeline; based on the recorded pipeline layout information, use CAD software or other drawing tools to generate a pipeline layout diagram; the pipeline layout diagram usually includes multiple views such as plan views, cross-section views, elevation views, etc. to fully display the layout of the pipeline.

[0042] Further, determining a cooling path of the central air conditioner according to the spatial position of the central air conditioner relative to the building and the pipeline layout diagram of the building;

[0043] At this time, the spatial position of the central air-conditioning relative to the building and the pipe layout diagram of the building are introduced. At the same time, the specific location of the central air-conditioning equipment (such as chillers, cooling towers, chilled water pumps, cooling water pumps, fan coil units, etc.) in the building is clarified; the spatial location information of the central air-conditioning equipment should include the specific location on the floor, room, wall or under the ground, as well as the relative position relationship between the equipment.

[0044] Analyze the building's piping layout to understand information such as pipe type, size, material and connection relationship; this helps to identify the pipe connection paths between central air conditioning equipment and each cooling zone; the piping layout diagram usually includes multiple views such as plan, section and elevation to fully display the layout of the pipes.

[0045] After clarifying the spatial location of the central air-conditioning equipment and analyzing the building's piping layout, the cooling path of the central air-conditioning begins to be determined; this involves identifying the complete path from the chiller, through the chilled water pump, cooling pipes, fan coil units and other components, and finally reaching each cooling area; the determination of the cooling path takes into account factors such as the connection sequence, direction, branch points and confluence points of the pipes to ensure that the cooling medium (such as cold water) can flow smoothly to each cooling area.

[0046] Therefore, each cooling space in the building is determined based on the cooling path of the central air-conditioning, the three-dimensional model of the building, and the rental and sale status of each indoor space in the building, which is compatible with the overall consideration of the cooling path of the central air-conditioning, the three-dimensional model of the building, and the rental and sale status of each indoor space in the building, ensuring the accuracy of each cooling space in the building.

[0047] At this point, the central air conditioning cooling path determined in step S113 is reviewed and analyzed; this includes the specific path of cold water starting from the chiller, passing through pipes, branch points, and confluence points, and finally reaching each cooling area; it is particularly noted that the cooling path contains multiple branches, each of which serves a specific cooling area or indoor space.

[0048] Next, refer to the 3D model of the building to understand the specific location, size, layout and relative position of each indoor space to the cooling path; the 3D model provides an intuitive 3D view to help accurately identify which spaces are cooled and how they are connected to the cooling pipes.

[0049] When determining the cooling space, the rental and sale status of each indoor space in the building is also considered; for example, if a room has been rented or sold, and the tenant or owner provides cooling services, then the room should be included in the cooling space range. Based on the above information, determine the various cooling spaces in the building; this includes rooms or areas that are directly connected to the cooling pipes and cooled, as well as the cooling range adjusted according to the rental and sale status and demand; after determining the cooling space, further formulate a cooling plan and adjust the cooling parameters (such as temperature, humidity, etc.) to meet the specific needs of different spaces.

[0050] In step S12, a plurality of cooling areas are determined according to each cooling space, the corresponding floor position of the building, and the corresponding indoor area;

[0051] In the specific implementation process of the present invention, the specific steps are:

[0052] S121: Obtain each cooling space;

[0053] S122: Determine the spatial position of each cooling space based on each cooling space and the three-dimensional model of the building;

[0054] S123: determining the floor position of the corresponding building according to the spatial position of each cooling space and the house number information of each cooling space;

[0055] S124: Determine the corresponding indoor area based on the traversal of each cooling space;

[0056] S125: interacting with each cooling space, the floor position of the corresponding building, and the corresponding indoor area;

[0057] S126: determining a first zone parameter according to each cooling space and a corresponding floor position of the building, and determining a second zone parameter according to each cooling space and a corresponding indoor area;

[0058] S127: Determine a plurality of cooling areas according to the three-dimensional model of the building, the first area parameter, and the second area parameter.

[0059] In an embodiment of the present application, each cooling space is obtained; the spatial position of each cooling space is determined based on the three-dimensional model of each cooling space and the building, which is compatible with the overall consideration of the three-dimensional model of each cooling space and the building, and ensures the accuracy of the spatial position of each cooling space.

[0060] At this time, each cooling space is obtained and managed. At the same time, a three-dimensional model of each cooling space and building is introduced, and the previously identified cooling space (as obtained in step S121) is matched with the three-dimensional model; this usually involves matching the space name, number or other identifier with the corresponding element in the model.

[0061] In the three-dimensional model of the building, accurately locate each cooling space; this includes determining the floor, zone, relative position to adjacent spaces, and relationship to other important structural elements (such as stairs, elevators, corridors) of the space in the building; record the location information of each cooling space in a database, management system, or visualization interface; this includes the floor, zone, coordinates (if available), and relative position description to other spaces.

[0062] Furthermore, the floor position of the corresponding building is determined according to the spatial position of each cooling space and the house number information of each cooling space, thereby realizing the interaction of the spatial position of each cooling space and the house number information of each cooling space, ensuring the accuracy of the floor position of the building and being compatible with the consideration of the floor position of the building.

[0063] At this time, the house number information of each cooling space is collected; the house number information usually includes the floor number, room number, area identification, etc., which helps to determine the specific location of the space in the building; the cooling space location previously determined by a three-dimensional model or other means (as obtained in step S122) is matched with the collected house number information; this usually involves matching the space name, number or other identifier with the corresponding element in the house number information.

[0064] Record the floor location information of each cooled space in a database, management system or visual interface; this includes the floor number, zone identification and a description of the relative location to other floors or spaces.

[0065] Furthermore, the corresponding indoor area is determined based on the traversal of each cooling space, thereby achieving the traversal of each cooling space and ensuring the accuracy of the indoor area.

[0066] At this time, each cooling space is traversed, and each cooling space identified previously (as obtained in step S121) is traversed one by one; this includes entering the interior of the space and observing its layout, shape and size; using a measuring tool to measure or estimate the indoor area of ​​the cooling space; for spaces of regular shapes (such as rectangles and squares), directly measure the length and width and calculate the area; for spaces of irregular shapes, use segmentation method, approximation method or area measurement software to estimate the area.

[0067] Record the indoor area information of each cooled space in a database, management system or visual interface; this includes the space name, floor location, area value, and the date and method of measurement or estimation; verify the accuracy of the measured or estimated area information by communicating with the building manager, tenants or professional measurement team; and perform calibration and adjustments when necessary to ensure the reliability of the area data.

[0068] Furthermore, each cooling space, the corresponding floor position of the building, and the corresponding indoor area are interacted; the first area parameter is determined according to the floor position of each cooling space and the corresponding building, and the second area parameter is determined according to each cooling space and the corresponding indoor area; multiple cooling areas are determined according to the three-dimensional model of the building, the first area parameter, and the second area parameter, which is compatible with the overall consideration of the three-dimensional model of the building, the first area parameter, and the second area parameter, and ensures the accuracy and rationality of multiple cooling areas.

[0069] At this point, the information of each cooling space (such as space name, location identifier, etc.), the corresponding floor location information (such as floor number, room number, etc.), and the indoor area information collected in the previous steps are integrated and interacted. This usually involves a data management system or platform that can receive, store and process this information and ensure the accuracy and consistency of the data. The interaction process includes operations such as importing, cleaning, matching and formatting data to facilitate subsequent analysis and processing.

[0070] Based on the integrated information, two key regional parameters are determined: the first regional parameter and the second regional parameter. The first regional parameter is usually related to the floor location, regional division, etc., and is used to group the cooling space by floor or area. The second regional parameter is related to the indoor area, space type, etc., and is used to evaluate the cooling demand and energy efficiency. The determination of these parameters will help the subsequent intelligent operation and maintenance work, such as formulating targeted cooling strategies and optimizing energy efficiency.

[0071] Specifically, the first area parameter is defined as the floor number, that is, the cooling space is divided into different areas according to the floor. For example, "1st floor area", "2nd floor area", etc. At the same time, the second area parameter is defined as the area interval, that is, the cooling space is divided into different groups according to the indoor area. For example, "less than 30 square meters group", "30-50 square meters group", etc. In this way, the cooling space can be classified and managed more finely according to the floor and area information.

[0072] At the same time, multiple cooling zones are determined by combining the three-dimensional model of the building, the first zone parameters and the second zone parameters. This usually involves a spatial analysis and division process, aiming to divide the cooling space into multiple zones with relatively independent cooling needs and control strategies. The division of these zones should take into account factors such as floor location, area size, space type, occupancy density and frequency of use to ensure the accuracy and energy efficiency of the cooling service.

[0073] Specifically, the cooling space is divided into multiple specific cooling areas according to the floor number (first area parameter) and area range (second area parameter). For example, the rooms in the "less than 30 square meters group" in the "first floor area" are divided into one cooling area, and the rooms in the "30-50 square meters group" in the "third floor area" are divided into another cooling area. In this way, a targeted cooling strategy is formulated for each cooling area, a suitable temperature range is set, and energy efficiency is optimized. The division of these cooling areas will help improve the energy efficiency management level of the building, reduce operating costs, and improve user satisfaction and comfort.

[0074] In step S13, a cooling mode of the cooling area is determined based on the plurality of cooling areas, the corresponding area functions and the number of people in the cooling area;

[0075] In the specific implementation process of the present invention, the specific steps are:

[0076] S131: Acquire multiple cooling areas;

[0077] S132: determining a first function parameter based on function detection of the plurality of cooling areas, and determining a second function parameter according to past business hours of the plurality of cooling areas;

[0078] S133: Determine a corresponding regional function according to the first functional parameter, the second functional parameter and the regional function matching table;

[0079] S134: Determine the number of people in each cooling area based on real-time monitoring of each cooling area;

[0080] S135: Interacting with multiple cooling areas, corresponding area functions, and the number of people in the cooling areas to determine cooling modes for the cooling areas;

[0081] S136: Determine the cooling mode of each cooling area by interacting the cooling modes of the cooling areas according to the plurality of cooling areas, the corresponding area functions and the number of people in the cooling areas.

[0082] In an embodiment of the present application, multiple cooling areas are obtained; a first functional parameter is determined based on functional detection of the multiple cooling areas, and a second functional parameter is determined according to previous business hours of the multiple cooling areas, thereby introducing the first functional parameter and the second functional parameter.

[0083] At this time, multiple cooling areas are obtained. At the same time, functional tests of multiple cooling areas are introduced. Functional tests are performed on each cooling area to understand its main purpose, personnel density, equipment configuration and other information; based on the functional test results, the first functional parameters are set for each cooling area; these parameters include personnel density level, equipment heating level, sensitivity to temperature and humidity, etc.

[0084] Furthermore, the historical usage data of each cooling area is collected and analyzed, especially the business hours (i.e. the time period when the area is actually used); based on the business time analysis results, the second functional parameters are set for each cooling area; these parameters include peak usage periods, idle periods, weekend usage, etc.

[0085] Specifically, let’s continue with the example of a five-story office building.

[0086] First functional parameter: Reception area: high population density, medium sensitivity to temperature and humidity, and low equipment heat; Office areas A to E: medium population density, high sensitivity to temperature and humidity, and medium equipment heat (due to heat generated by computers and other equipment); Conference rooms A to E: variable population density (depending on the scale of the meeting), high sensitivity to temperature and humidity, and low equipment heat (unless projectors and other equipment are used); Restrooms and rest areas: low population density, medium sensitivity to temperature and humidity, and low equipment heat.

[0087] Second functional parameter: Reception area: used during peak hours throughout the day and remains open on weekends; Office areas A to E: Peak usage hours on weekdays are from 9 a.m. to 6 p.m. and are basically idle on weekends; Meeting rooms A to E: Usage hours are not fixed, but are usually more frequent between 10 a.m. and 4 p.m. on weekdays; Restrooms and rest areas: used throughout the day, but the frequency of use is higher between 9 a.m. and 6 p.m. on weekdays.

[0088] Furthermore, the corresponding regional function is determined according to the first functional parameter, the second functional parameter and the regional function matching table, which is compatible with the overall consideration of the first functional parameter, the second functional parameter and the regional function matching table, and ensures the accuracy of the regional function.

[0089] At this time, the first function parameter, the second function parameter and the regional function matching table are introduced to formulate a detailed regional function matching table; this table should include all cooling area functions (such as office, meeting, reception, rest, etc.), as well as the thresholds or ranges of the first function parameters and the second function parameters corresponding to each function.

[0090] For example, for office areas, the first functional parameters include medium population density, medium equipment heat generation, and high sensitivity to temperature and humidity; the second functional parameters include clear peak usage hours on weekdays and basically idle time on weekends.

[0091] The first function parameter and the second function parameter of each cooling area are compared with the area function matching table; and the function of the cooling area is determined according to whether the parameter value is within the threshold or range of the corresponding function in the matching table.

[0092] If the first function parameter and the second function parameter of a cooling area completely match a function in the matching table, the function is directly determined as the function of the cooling area; if there are multiple function matches, other factors (such as the actual use of the area, building structure design, etc.) are further considered to make a final judgment.

[0093] Specifically, taking the previous five-story office building as an example, there is a preset regional function matching table, which contains the following functions and their corresponding parameter ranges:

[0094] Office area: medium population density (5-15 people / 100 square meters), medium equipment heat generation (about 100W of heat per person on average), high sensitivity to temperature and humidity, clear peak usage hours on weekdays (such as 9 am to 6 pm), and basically idle on weekends.

[0095] Meeting area: variable density of people (depending on the size of the meeting), low heat generation of equipment (unless using equipment such as projectors), high sensitivity to temperature and humidity, and irregular usage hours but usually within specific time periods on weekdays.

[0096] Reception area: high population density (more than 15 people / 100 square meters), moderate sensitivity to temperature and humidity, low equipment heat generation, peak usage throughout the day, and open on weekends.

[0097] Rest / restroom area: low density of people, moderate sensitivity to temperature and humidity, low heat generation from equipment, used throughout the day but with higher frequency of use during specific time periods on weekdays.

[0098] Now, the function of each cooling zone is determined based on the first function parameter and the second function parameter collected previously:

[0099] Reception area: The first functional parameter shows that the population density is high, the sensitivity to temperature and humidity is medium, and the equipment heat generation is low; the second functional parameter shows that it is used at peak times throughout the day and remains open on weekends; this matches the function of the reception area.

[0100] Office areas A to E: The first functional parameter shows that the population density is medium, the sensitivity to temperature and humidity is high, and the equipment heat generation is medium; the second functional parameter shows that the peak usage period on weekdays is clear and the weekends are basically idle; this matches the function of the office area.

[0101] Meeting Rooms A to E: The first functional parameter shows that the density of people is variable (but usually not high), the sensitivity to temperature and humidity is high, and the equipment heat generation is low (unless specific equipment is used); the second functional parameter shows that the usage period is not fixed but is usually within a specific time period on weekdays; this matches the function of the meeting area.

[0102] Restrooms and rest areas: The first functional parameter shows low occupancy density, medium sensitivity to temperature and humidity, and low equipment heat generation; the second functional parameter shows that it is used throughout the day but the frequency of use is higher during specific time periods on weekdays; this matches the function of the restroom / restroom area (although in actual applications, restrooms and rest areas would be considered different functional areas, in this example, they are classified as one for simplicity).

[0103] Furthermore, the number of people in each cooling area is determined based on real-time monitoring of each cooling area, thereby achieving real-time monitoring of each cooling area, ensuring the accuracy of the number of people in each cooling area, and taking into account the consideration of the number of people in each cooling area.

[0104] At this time, each cooling area is monitored in real time, and appropriate monitoring technology is selected to track the number of people in each cooling area in real time. This includes infrared sensors, cameras with people recognition software, Wi-Fi hotspot tracking (estimates the number of people by analyzing the number of devices connected to Wi-Fi), Bluetooth beacons and other technologies.

[0105] At the same time, the monitoring system will collect data on the number of people in each area in real time and store it in a database; use data analysis tools to process and analyze the collected data to generate useful reports and charts; and ensure compliance with relevant privacy protection regulations and standards when implementing monitoring.

[0106] Specifically, taking the previous five-story office building as an example, it was decided to install infrared sensors at the entrance of each cooling area to track the number of people in real time; after evaluation, infrared sensors were selected as the monitoring technology; this technology has the advantages of moderate cost, easy installation and high accuracy.

[0107] All infrared sensors are connected to the central monitoring system, and the data update frequency is configured to be once a minute. An alarm threshold is set, and when the number of people in a certain area exceeds the preset capacity, the system will automatically issue an alarm prompt. The monitoring system collects the number of people in each area in real time and stores it in the database. The collected data is processed and analyzed using data analysis tools to generate real-time number of people reports and trend charts for each area.

[0108] Furthermore, the cooling modes of the cooling areas are determined interactively among multiple cooling areas, corresponding area functions and the number of people in the cooling areas; the cooling modes of each cooling area are determined interactively among multiple cooling areas, corresponding area functions and the number of people in the cooling areas, thereby realizing the interaction of cooling modes of the cooling areas determined by multiple cooling areas, corresponding area functions and the number of people in the cooling areas, and ensuring the accuracy of the cooling modes of each cooling area.

[0109] At this point, the interaction of multiple cooling zones, corresponding zone functions and the number of people in the cooling zone to determine the cooling mode of the cooling zone is realized. At the same time, data on the functions of the cooling zones, the real-time number of people and other relevant factors are collected from the previous steps; these data are analyzed to understand the actual needs and potential changing trends of each zone; based on the results of the data analysis, a suitable cooling strategy is formulated for each cooling zone; this includes setting specific parameters such as temperature, humidity, wind speed, and determining when to turn the cooling system on or off; considering the mutual influence between different zones to ensure that the cooling system of the entire building can operate in a coordinated manner.

[0110] Input the developed cooling strategies into the control interface of the cooling system; ensure that the cooling system can accurately receive and execute these strategies, and monitor the operating status of the system to ensure its normal operation; adjust the cooling strategy in real time according to changes in the real-time number of people and other factors.

[0111] Furthermore, based on the specific information of multiple cooling areas (including area functions, real-time number of people, etc.), the most appropriate cooling mode is determined for each cooling area through a series of logical judgments and optimization formulas.

[0112] Integrate all key data obtained from the previous steps, including functional classification of cooling areas, real-time population statistics, outdoor climate conditions (such as temperature and humidity), indoor environmental requirements (such as ideal temperature and humidity, air quality), etc.; based on the data analysis results, formulate a preliminary cooling strategy for each cooling area; this usually involves setting expected values ​​for key parameters such as temperature, humidity, air flow rate, and determining the start time and operating intensity of the cooling system; optionally, the formulation of the preliminary strategy should fully consider factors such as regional function, population density, activity level, etc., to ensure that energy efficiency is maximized while meeting comfort requirements.

[0113] Optimize the initial strategy; this includes predictive adjustments based on historical data, economic optimization considering energy costs, and dynamic adjustments based on real-time changes in the number of people; ensure that the optimized cooling mode can both meet the needs of personnel comfort and effectively save energy consumption; communicate the optimized cooling mode to the control center of the cooling system to ensure its accurate execution; monitor the operating status and key parameters of the cooling system in real time, and promptly detect and handle any abnormal situations.

[0114] Specifically, the optimized cooling mode is communicated to the control center of the cooling system to ensure its accurate execution; the operating status and key parameters of the cooling system are monitored in real time to promptly detect and handle any abnormal situations.

[0115] The system integrates functional information of the office area (such as high population density and sensitivity to temperature and humidity), real-time headcount (such as there are currently 200 people in the office area), outdoor climate conditions (such as the current outdoor temperature is 32°C and the humidity is 60%) and other data; analysis shows that due to the high population density and sensitivity to temperature and humidity, the office area maintains a low indoor temperature and suitable humidity.

[0116] Based on the analysis results, a preliminary cooling strategy was set for the office area: the indoor temperature was 24°C, the humidity was 50%, and the cooling system operated all day, but was dynamically adjusted according to the real-time number of people and outdoor climate conditions; the preliminary strategy was optimized; for example, when it was predicted that the outdoor temperature would rise to 35°C in the afternoon, the formula would automatically adjust the operating intensity of the cooling system to ensure that the indoor temperature remained at 24°C; at the same time, when it was detected that the number of people in the office area decreased, the formula would reduce the cooling intensity to save energy.

[0117] In another embodiment of the present application, the cooling mode matching table is:

[0118]

[0119] Assuming that there are 150 people in the current office area and the outdoor temperature is 30°C, according to the matching table, the cooling mode of the office area should be that the indoor temperature is set to 24°C, the humidity is set to 50%, and the cooling system runs all day.

[0120] In step S14, the intelligent operation and maintenance system of the central air conditioner is determined according to the cooling mode of each cooling area, the external weather information, and the indoor temperature loss of multiple cooling areas;

[0121] In the specific implementation process of the present invention, the specific steps are:

[0122] S141: Determine external weather information based on the location of the building, the corresponding weather system, and external temperature detection parameters of the building;

[0123] S142: monitoring multiple cooling areas in real time, and collecting indoor temperature data sets of the multiple cooling areas at different times;

[0124] S143: determining indoor temperature losses of the plurality of cooling areas according to the indoor temperature data sets of the plurality of cooling areas at different times and the length of the cooling path of the central air conditioner;

[0125] S144: performing multiple interactions on the cooling mode of each cooling area, external weather information, and indoor temperature losses of multiple cooling areas, so as to train the cooling mode of each cooling area, external weather information, and indoor temperature losses of multiple cooling areas in different dimensions;

[0126] S145: Determine the intelligent operation and maintenance system of the central air conditioner based on the cooling mode of each cooling area, external weather information, and training of indoor temperature losses in multiple cooling areas.

[0127] In an embodiment of the present application, external weather information is determined based on the location of the building, the corresponding weather system and the external temperature detection parameters of the building, which is compatible with the overall consideration of the location of the building, the corresponding weather system and the external temperature detection parameters of the building, thereby ensuring the accuracy of the external weather information.

[0128] At this point, the location of the building, the corresponding weather system, and the building's external temperature detection parameters are introduced; according to the location of the building, a weather system that can provide accurate weather information is selected; these systems are official data provided by the National Meteorological Administration and local weather stations, as well as data from third-party weather service providers; real-time weather data is obtained from the selected weather system through API interfaces, data push services, or manual queries.

[0129] Temperature sensors and other temperature detection equipment are installed on the outside of the building to measure ambient temperature, humidity and other parameters in real time; these measurement data are compared with the data obtained from the weather system to calibrate and verify the accuracy of the weather data. The data obtained from the weather system and the temperature detection parameters outside the building are integrated to form a comprehensive weather information report; the weather information is analyzed to identify the trends and patterns of weather changes, and provide decision support for the building's cooling, heating, ventilation and other systems.

[0130] Furthermore, multiple cooling areas are monitored in real time, and indoor temperature data sets of the multiple cooling areas at different times are collected; the indoor temperature losses of the multiple cooling areas are determined according to the indoor temperature data sets of the multiple cooling areas at different times and the length of the cooling path of the central air-conditioning, which is compatible with the overall consideration of the indoor temperature data sets of the multiple cooling areas at different times and the length of the cooling path of the central air-conditioning, thereby ensuring the accuracy of the indoor temperature losses of the multiple cooling areas.

[0131] At this time, multiple cooling areas are monitored in real time, and a data acquisition platform or system is built to receive data from various temperature sensors in real time; the collection frequency of temperature data is set according to actual needs, such as once every minute, every five minutes or every hour; the collection frequency of temperature data is set according to actual needs, such as once every minute, every five minutes or every hour; a data management mechanism is established to ensure the security and integrity of the data.

[0132] Conduct statistical analysis on the collected indoor temperature data and calculate the average temperature of each cooling area at different time points; identify the fluctuation trend and abnormal values ​​of the temperature data to provide a basis for subsequent temperature loss calculations; at the same time, draw a cooling path diagram for the central air-conditioning system to clarify the pipe length between each cooling area and the cooling host.

[0133] A temperature loss calculation model is established based on indoor temperature data and the length of the cooling path. The model should comprehensively consider factors such as the attenuation of cooling during transmission, the impact of ambient temperature on pipelines, and indoor temperature fluctuations. The temperature loss value of each cooling area is calculated through the model, and its impact on the cooling effect is evaluated.

[0134] Specifically, in the office building, by analyzing the indoor temperature data of the office area, conference room and rest area, it was found that the temperature in the conference room fluctuated greatly and the average temperature was higher; at the same time, according to the cooling path diagram of the central air-conditioning system, it was found that the conference room was far away from the cooling host and the cooling path was relatively long.

[0135] Based on this information, a temperature loss calculation model was established, taking into account factors such as pipe material, diameter and thermal insulation performance; through model calculation, it was found that the temperature loss value in the conference room was relatively high, which explains why the temperature fluctuations in the conference room were large and the average temperature was high.

[0136] To improve this situation, the following recommendations are made:

[0137] Optimize the cooling path of the central air-conditioning system and shorten the distance between the conference room and the cooling host; strengthen the thermal insulation performance of the pipeline to reduce the attenuation of cold air during transmission; adjust the cooling strategy of the conference room, such as increasing the cooling intensity or adjusting the cooling time, to improve the indoor temperature conditions.

[0138] Therefore, multiple interactions are performed on the cooling mode of each cooling area, the external weather information, and the indoor temperature loss of multiple cooling areas, so as to train the cooling mode of each cooling area, the external weather information, and the indoor temperature loss of multiple cooling areas in different dimensions; based on the training of the cooling mode of each cooling area, the external weather information, and the indoor temperature loss of multiple cooling areas, the intelligent operation and maintenance system of the central air-conditioning is determined, and the training of the cooling mode of each cooling area, the external weather information, and the indoor temperature loss of multiple cooling areas is realized, thereby ensuring the accuracy of the intelligent operation and maintenance system of the central air-conditioning.

[0139] At this point, data from different sources are collected and integrated; this includes real-time cooling mode data (such as temperature setting, wind speed, humidity, etc.) of the cooling area, real-time weather data (such as temperature, humidity, wind speed, wind direction, rainfall, etc.) of the external weather system, and indoor temperature loss data collected by temperature sensors; multiple interactive analyses are performed on these data; this includes exploring the correlation between cooling mode and external weather, analyzing the correlation between indoor temperature loss and cooling mode and weather factors, and identifying the changing trends of these variables at different time scales (such as day, week, month).

[0140] Based on the above analysis, one or more machine learning models are constructed to predict and optimize cooling strategies. These models are trained based on historical data to learn the complex relationship between different cooling modes, weather conditions, and indoor temperature losses. During the training process, techniques such as cross-validation are used to evaluate the performance of the model, and the model parameters are adjusted to improve the prediction accuracy.

[0141] At the same time, a smart operation and maintenance system is further built to realize the automated and intelligent management of the central air-conditioning system. At this time, an intelligent control system is designed, which can receive and process data from the cooling area, weather system and temperature sensor in real time. The system should also have the functions of early warning, scheduling and automatic adjustment of cooling strategy. The trained machine learning models are integrated into the intelligent control system. These models will serve as decision support tools to help the system automatically adjust the cooling strategy according to real-time data. In addition, the system is continuously optimized to improve its performance, reduce energy consumption and enhance user experience.

[0142] The smart operation and maintenance system should also include a monitoring and feedback mechanism to track the system's operating status and performance in real time; this includes monitoring key indicators such as cooling effect, energy consumption, equipment failure, and providing timely feedback and suggestions to managers.

[0143] Specifically, suppose there is an office building with five cooling areas, each with different cooling needs and external weather influences; through multiple interactive analyses, it was found that when the external temperature exceeds 30°C and the humidity is high, the indoor temperature loss in cooling area A increases significantly; at the same time, it was also found that cooling mode B (i.e., higher wind speed and lower humidity settings) can effectively reduce indoor temperature loss in hot weather; based on these findings, a machine learning model was trained, which can automatically adjust the cooling mode of cooling area A to B according to real-time data of external weather and indoor temperature loss.

[0144] A smart operation and maintenance system was designed for the office building; the system can receive and process data from five cooling zones, weather systems and temperature sensors in real time; when the outside temperature exceeds 30°C and the humidity is high, the intelligent control system will automatically adjust the cooling mode of cooling zone A to B (higher wind speed and lower humidity settings); at the same time, the system will also monitor the cooling effect and energy consumption in real time, and send warnings or adjustment suggestions to managers when necessary; in this way, the automatic and intelligent management of the central air-conditioning system is realized, which effectively reduces energy consumption and improves user experience.

[0145] In another embodiment of the present application, the intelligent operation and maintenance system matches an example:

[0146] External weather conditions Cooling zone status Indoor temperature loss range Cooling strategy / mode High temperature and humidity High demand high Enhanced cooling mode High temperature and humidity Medium demand medium Standard cooling mode High temperature and humidity Low demand Low Energy-saving cooling mode medium temperature medium humidity High demand high Standard cooling mode + wind speed adjustment medium temperature medium humidity Medium demand medium Mild cooling mode medium temperature medium humidity Low demand Low Natural ventilation mode Low temperature and low humidity Any needs any Stop cooling / maintain minimum operation

[0147] In this smart operation and maintenance system matching table, the appropriate cooling strategy or mode is selected based on external weather conditions (such as temperature and humidity), the status of the cooling area (such as high demand, medium demand, and low demand, which is determined by factors such as the number of people in the area and the activity level), and the indoor temperature loss range (such as high, medium, and low).

[0148] Assume that the current external weather conditions are high temperature and high humidity, cooling area A is in high demand (for example, there are a lot of people in the area), and the indoor temperature loss is high. According to the matching table, the intelligent operation and maintenance system will automatically select "enhanced cooling mode" to ensure the comfort of the area.

[0149] In step S15, in the intelligent operation and maintenance system of the central air conditioner, multiple temperature control paths are determined based on the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area;

[0150] In the specific implementation process of the present invention, the specific steps are:

[0151] S151: Collecting the intelligent operation and maintenance system of central air conditioners;

[0152] S152: In the intelligent operation and maintenance system of the central air conditioner, real-time temperature control is performed on each cooling area, and the current temperature of each cooling area is collected;

[0153] S153: determining the personnel activity events of each cooling area according to the multiple internal images of each cooling area, the area functions corresponding to each cooling area, and the places where personnel gather in each cooling area;

[0154] S154: Determining the relative positions of the cooling areas based on the position comparison of the cooling areas;

[0155] S155: interacting with the current temperature of each cooling area, the personnel activity events of each cooling area, and the relative positions of each cooling area;

[0156] S156: Determine a plurality of temperature control paths according to the current temperature of each cooling area, the personnel activity events in each cooling area, and the interaction of the relative positions of each cooling area.

[0157] In an embodiment of the present application, an intelligent operation and maintenance system of a central air conditioner is collected; in the intelligent operation and maintenance system of the central air conditioner, real-time temperature control is performed on each cooling area, and the current temperature of each cooling area is collected; personnel activity events in each cooling area are determined based on multiple internal images of each cooling area, the area functions corresponding to each cooling area, and the places where people gather in each cooling area, thereby ensuring the accuracy of personnel activity events in each cooling area.

[0158] At this time, the intelligent operation and maintenance system of central air conditioning is introduced to control the intelligent operation and maintenance system of central air conditioning. At the same time, real-time temperature control is carried out on each cooling area, and the current temperature of each cooling area is collected; temperature sensors are deployed in each cooling area to collect current temperature data in real time; temperature control strategies are formulated according to the functional requirements of each cooling area, personnel activities and other factors; for example, for areas with dense personnel and high temperature requirements (such as conference rooms, offices, etc.), a lower temperature threshold is set; for areas with less personnel activities and low temperature requirements (such as corridors, storage rooms, etc.), a higher temperature threshold is set; the temperature control strategy is integrated with the control terminal of the central air-conditioning system to realize automatic temperature control; when the temperature of a cooling area exceeds the preset threshold, the system automatically adjusts the cooling intensity of the area to ensure that the temperature is maintained within a comfortable range.

[0159] According to the internal images, regional functions and places where people gather in each cooling area, the personnel activity events in each cooling area are determined, and the temperature control strategy is adjusted accordingly. At the same time, high-definition surveillance cameras are deployed in each cooling area to capture internal images in real time. The captured images are identified and analyzed to determine the personnel activity events. For example, by identifying the number of people, action characteristics, etc., it can be judged whether there are people gathering in a certain area, whether there is a meeting in progress, etc.

[0160] Adjust the temperature control strategy in time according to the identified human activity events; for example, when people gather in a conference room and the meeting is about to begin, appropriately lower the temperature setting value of the area; when there are fewer people and less activity in a certain office area, appropriately increase the temperature setting value of the area to save energy.

[0161] Furthermore, the relative positions of the cooling areas are determined based on the position comparison of the cooling areas, thereby achieving the position comparison of the cooling areas and ensuring the accuracy of the relative positions of the cooling areas.

[0162] At this point, obtain a building plan that includes all cooling areas; this plan should detail the location and layout of each room, corridor, staircase and other spaces; on the building plan, mark the location of each cooling area one by one according to the actual cooling area layout; this is achieved by drawing a bounding box, filling color or using text annotations on the plan; by comparing the positions of each cooling area on the building plan, determine the relative position relationship between them; this includes adjacent relationships, upper and lower floor relationships, and distance relationships.

[0163] The determined relative position information is organized into a database format to facilitate subsequent data analysis and application; this database contains fields such as the name of the cooling area, location coordinates, and adjacent area information.

[0164] Therefore, the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area are interacted; multiple temperature control paths are determined according to the interaction of the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area, thereby ensuring the accuracy of multiple temperature control paths.

[0165] At this time, the interaction of the current temperature, personnel activity events and relative positions of each cooling area is realized, and the current temperature, personnel activity events and relative positions of each cooling area are fully considered.

[0166] Establish a dedicated information interaction platform that can receive and display the temperature data, personnel activity event data and relative position data of each cooling area in real time; integrate the various types of data received and display them in an intuitive manner on the information interaction platform; for example, use temperature distribution maps to display the current temperature conditions of each cooling area, use personnel activity heat maps to display personnel activities, and use floor plans or three-dimensional models to display the relative position relationship of cooling areas.

[0167] On the information interaction platform, the interactive function between various types of data is realized; for example, when clicking on a cooling area, the current temperature of the area, personnel activities and information of adjacent areas can be displayed.

[0168] Based on the information interacted and integrated in step S155, multiple temperature control paths are determined; these paths should comprehensively consider the current temperature, personnel activities and relative position relationships of each cooling area to ensure that energy efficiency is maximized while meeting personnel comfort.

[0169] Conduct in-depth analysis on the data interacted and integrated in step S155; this includes analyzing the temperature change trends of each cooling area, the patterns of personnel activities, and the mutual influence between adjacent areas; based on the results of data analysis, formulate multiple temperature control strategies; these strategies should be able to be flexibly adjusted according to different situations to meet different needs; use simulation software to simulate and evaluate the formulated control strategies; this includes simulating energy consumption and changes in personnel comfort under different temperature settings; select the optimal control strategy through simulation evaluation; determine multiple temperature control paths based on the results of simulation evaluation; these paths should be able to comprehensively consider temperature, personnel activities and location information to achieve the best balance between energy efficiency and comfort.

[0170] Specifically, taking a large office building as an example, in step S156, based on the information interacted and integrated in step S155, the following multiple temperature control paths are determined:

[0171] Path 1: When the temperature in a cooling area is high and there are dense human activities, the temperature setting value of this area is lowered first, and the cooling intensity of adjacent areas is appropriately increased to ensure a balance between human comfort and energy efficiency;

[0172] Path 2: When the temperature in a cooling area is moderate and there is less human activity, the temperature setting value of the area is appropriately increased, and the cooling intensity of adjacent areas is reduced to save energy and reduce energy consumption;

[0173] Path 3: When the overall temperature of the office building is high and the activities of personnel are generally intensive, adopt an overall cooling strategy and optimize the temperature setting value and cooling intensity distribution of each cooling area to achieve the best balance between energy efficiency and comfort;

[0174] Path 4: When the overall temperature of the office building is moderate and there is generally less human activity, adopt an overall insulation strategy and appropriately reduce the temperature setting value and cooling intensity distribution of each cooling area to further save energy and reduce energy consumption.

[0175] In another embodiment of the present application, the temperature control path matching table is:

[0176]

[0177] Assume that the current temperature of a cooling area is 27°C, the human activity events are high-density, and the area is adjacent to the adjacent area. According to the temperature control path table, it is determined that the temperature setting value of the area should be adjusted down by 2°C and the cooling intensity should be increased by 10%.

[0178] In step S16, autonomous regulation of multiple cooling areas is triggered based on multiple temperature control paths, current time, and indoor status of each cooling area, and the standby air conditioner regulates the working time of the central air conditioner;

[0179] In the specific implementation process of the present invention, the specific steps are:

[0180] S161: Acquire multiple temperature control paths;

[0181] S162: Determine the current time based on the time data of the central air conditioner;

[0182] S163: Determine the indoor state of each cooling area according to the personnel information of each cooling space, the indoor image of each cooling space, and the appliance usage data of each cooling space;

[0183] S164: associating multiple temperature control paths, current time, and indoor states of each cooling area, determining an optimization event of the central air conditioner according to the multiple temperature control paths, current time, and indoor states of each cooling area, and triggering autonomous control of the multiple cooling areas according to the optimization time of the central air conditioner;

[0184] S165: Determine a standby air conditioner based on the building detection, and associate the standby air conditioner with the central air conditioner;

[0185] S166: Collect the pipeline layout diagram of the building, and determine the cooling area of ​​the standby air conditioner based on the location of the standby air conditioner, the power information of the standby air conditioner, and the pipeline layout diagram of the building;

[0186] S167: estimating cooling energy according to the current time, the number of people staying in each cooling area, and external weather information; at this time, each cooling area is included in the cooling area of ​​the standby air conditioner;

[0187] S168: If the cooling energy is lower than the lower limit cooling energy of the central air conditioner, the central air conditioner is kept in a shutdown state, and the standby air conditioner is triggered to operate, so as to adjust the working time of the central air conditioner.

[0188] In an embodiment of the present application, multiple temperature control paths are obtained; the current time is determined based on the time data of the central air conditioner, thereby ensuring the accuracy of the current time.

[0189] At this point, multiple temperature control paths are obtained, and the time data of the central air conditioner is introduced to obtain the time data of the central air conditioning system and determine the current accurate time based on it. This is crucial for time-sensitive decisions in subsequent steps, such as adjusting the cooling strategy according to working hours and non-working hours, triggering scheduled tasks, etc.

[0190] Directly read the system clock built into the central air-conditioning system; synchronize the system time with the Internet standard time server through the network time protocol; specifically, the system determines that the current time is 14:00 p.m. on a weekday by reading the system clock built into the central air-conditioning system or synchronizing the time through the network time protocol; based on this time information, the system can automatically select and execute a temperature control path that matches the current time period (such as the active cooling strategy in path one) to ensure that the temperature in each cooling area in the office building is comfortable and the energy efficiency is optimal.

[0191] Furthermore, the indoor state of each cooling area is determined based on the personnel information of each cooling space, the indoor image of each cooling space, and the appliance usage data of each cooling space, thereby ensuring the accuracy of the indoor state of each cooling area.

[0192] At this point, information from multiple data sources is comprehensively analyzed to determine the indoor status of each cooling zone; this information includes personnel information, indoor images, and appliance usage data; by analyzing this data, the system can more accurately understand the actual usage of each cooling zone, thereby providing a key basis for subsequent temperature control strategies.

[0193] For personnel information, data sources include access control systems, personnel positioning systems, or manually entered personnel lists; analysis content includes the number of personnel, distribution, activity level, etc. For indoor images, data sources include camera monitoring systems; analysis content includes personnel behavior, lighting conditions, window status (whether open), etc. For electrical appliance usage data, data sources include smart meters, equipment sensors, etc.; analysis content includes energy consumption of electrical equipment, switch status, etc.

[0194] Information from different data sources is integrated to form a more comprehensive description of the indoor state. Advanced formulas (such as machine learning models) are used to process and analyze these data to automatically identify changes in the indoor state. The system updates these data in real time to ensure an accurate description of the indoor state.

[0195] Specifically, suppose there is a large shopping mall whose cooling system covers multiple floors and areas; in step S163, the system performs the following analysis:

[0196] Personnel information: By analyzing the data from the access control system and the personnel positioning system, the system found that the food court on the first floor and the clothing store on the second floor were densely populated, while the cinema on the third floor was relatively deserted; Indoor images: Camera monitoring showed that the food court on the first floor had a high temperature in some areas due to direct sunlight; the clothing store on the second floor had moderate lighting, but several windows were open, resulting in loss of cool air; the cinema on the third floor had dim lighting and the windows were closed; Electrical appliance usage data: The smart meter showed that the food court on the first floor had a large number of kitchen equipment and lighting equipment in operation, with high energy consumption; the clothing store on the second floor used relatively few electrical appliances; although the cinema on the third floor did not use many electrical appliances, its projection equipment and sound system continued to operate.

[0197] Based on the above information, the system determines the following indoor status:

[0198] Food court on the first floor: crowded and high temperature, so increase cooling and consider closing some windows to reduce the influx of hot air; clothing store on the second floor: moderate density of people, but open windows lead to loss of cold air, so adjust the air supply and window status appropriately; cinema on the third floor: sparsely populated and moderate temperature, so reduce cooling appropriately to save energy; through these specific analyses, the system can more accurately understand the indoor status of each cooling area and provide key basis for subsequent temperature control strategies.

[0199] Furthermore, multiple temperature control paths, the current time and the indoor status of each cooling area are associated, and the optimization event of the central air-conditioning is determined according to the multiple temperature control paths, the current time and the indoor status of each cooling area. The autonomous control of multiple cooling areas is triggered according to the optimization time of the central air-conditioning, thereby realizing autonomous control of multiple cooling areas.

[0200] At this time, multiple temperature control paths, current timestamps, and indoor status data of each cooling area are integrated into a unified data platform or database; the current time is matched with the preset time period (such as weekdays, weekends, holidays, etc.), while considering the indoor status (such as population density, appliance usage, and environmental conditions reflected by indoor images) and the temperature control path. Based on the above analysis, the system develops one or more optimized temperature control strategies, which aim to maximize energy efficiency and reduce energy consumption while meeting comfort requirements.

[0201] Optimization events include adjusting cooling intensity, changing temperature set points, starting / stopping cooling in specific areas, adjusting air volume or wind speed, etc.; optimizing events are prioritized based on factors such as urgency, energy consumption impact, and comfort requirements; the system automatically executes optimization events based on preset optimization times (either real-time triggers or timed triggers based on a schedule); each cooling area autonomously adjusts the operating status of its cooling system (such as fan coil units, VAV boxes, etc.) based on the instructions received to achieve the optimization goal.

[0202] Specifically, assuming that there is a large commercial complex, including multiple cooling areas with different functions, such as office areas, retail areas, dining areas, and entertainment areas; in step S164, the system will perform the following operations:

[0203] The system has obtained that the current time is 15:00 p.m. on a weekday, and the indoor status data of each cooling area has also been collected; for example, the office area has a high density of people and electrical appliances are frequently used, the retail area attracts a large number of customers due to promotional activities, and the dining area and entertainment area have a relatively low density of people; the system correlates this information with multiple preset temperature control paths for analysis;

[0204] Based on the above analysis, the system formulates a series of optimization events; for example, for the office area, the system decides to lower the temperature set point and increase the air supply to improve comfort; for the retail area, although the density of people is high, considering the customer experience, the system decides to maintain the current temperature but optimize the air supply mode to reduce energy consumption; for the dining area and entertainment area, the cooling intensity is appropriately adjusted according to the actual situation;

[0205] The system sends corresponding control instructions to each cooling zone according to the preset optimization time (real-time trigger in this case); the fan coil units in the office area automatically adjust the air supply volume and temperature set point, the VAV box in the retail area optimizes the air supply mode, and the cooling system in the dining area and entertainment area is also adjusted accordingly according to the instructions.

[0206] Furthermore, the standby air conditioner is determined based on the detection of the building, and the standby air conditioner and the central air conditioner are associated; the pipeline layout diagram of the building is collected, and the cooling area of ​​the standby air conditioner is determined based on the location of the standby air conditioner, the power information of the standby air conditioner and the pipeline layout diagram of the building, thereby ensuring the accuracy of the cooling area of ​​the standby air conditioner.

[0207] At this time, the building was inspected and a backup air conditioner was introduced. The status and location of the backup air conditioner were identified through building inspection methods and associated with the central air conditioning system. This step is critical to ensure that when the central air conditioning system fails or is under maintenance, it can quickly switch to the backup air conditioner to maintain normal cooling in the building.

[0208] Collect the building's piping layout diagram and combine it with the location and power information of the backup air conditioner and the actual layout of the building to determine the cooling area that the backup air conditioner can cover; this step is crucial for formulating an effective switching strategy and ensuring the cooling effect after switching.

[0209] Obtain the building's piping layout diagram, including air conditioning ducts, supply and return air ducts, etc., through the building management system or on-site inspection; evaluate the range of cooling demand that the standby air conditioner can meet based on its power, cooling capacity and other parameters; determine the cooling area that the standby air conditioner can cover based on the piping layout diagram and the performance analysis of the standby air conditioner, and mark it on the building plan; formulate a switching strategy for the standby air conditioner based on the cooling area and actual needs, including switching sequence, time nodes, etc.

[0210] Specifically, the system obtained the building's pipeline layout diagram through the building management system, and confirmed the actual direction and connection of the pipeline in combination with on-site inspections; at the same time, the system analyzed the power and cooling capacity of the backup air conditioner and evaluated the range of cooling demand it can meet; based on this information, the system determined the cooling areas that the backup air conditioner can cover, mainly including the lower floors and some middle floors of the office building; the system marked this information on the building floor plan and formulated corresponding switching strategies; when the main system fails, the system will automatically or manually switch to the backup air conditioner according to the switching strategy to ensure normal cooling of these areas; at the same time, the system will also monitor the cooling effect after the switch and make necessary adjustments based on actual conditions.

[0211] Therefore, the cooling energy is estimated according to the current time, the number of people staying in each cooling area and the external weather information; at this time, each cooling area is included in the cooling area of ​​the standby air conditioner; if the cooling energy is lower than the lower limit cooling energy of the central air conditioner, the central air conditioner is maintained in the shutdown state, and the standby air conditioner is triggered to adjust the working time of the central air conditioner, and at the same time, the assistance ability of the standby air conditioner to the standby air conditioner is improved.

[0212] At this time, the current time, the number of people staying in each cooling area and the external weather information are introduced to estimate the cooling energy, thereby realizing the estimation of cooling energy. At the same time, according to the current time (such as weekdays, weekends, holidays or different times of the day), the system can adjust the estimation of cooling energy, because the activities of people and the external temperature will be different in different time periods; through the access control system, face recognition or other personnel tracking technology, the system can obtain the number of people in each cooling area in real time; this information is crucial for evaluating heat load and cooling demand.

[0213] The system obtains external weather information, including temperature, humidity, wind speed, etc., through meteorological services or internal sensors. This information directly affects the heat dissipation and cooling needs of the building. Based on the above data, the system uses a heat load calculation model or empirical formula to estimate the cooling energy required for each cooling area.

[0214] Determine whether the estimated cooling energy is lower than the lower limit cooling energy of the central air-conditioning system; if so, the system will maintain the central air-conditioning in the shutdown state and trigger the standby air-conditioning to start working, so as to adjust the working time of the central air-conditioning, thereby improving energy efficiency and extending the life of the equipment.

[0215] The system pre-sets a lower limit cooling energy value based on the performance parameters and energy efficiency standards of the central air-conditioning system; this value represents the minimum cooling energy that the central air-conditioning system can provide under efficient operation; the system compares the estimated cooling energy with the lower limit cooling energy; if the estimated value is lower than the lower limit, it means that the central air-conditioning system is not operating efficiently or cannot meet the demand under the current conditions; when the estimated cooling energy is lower than the lower limit, the system will automatically or manually trigger the standby air conditioner to start working to supplement the cooling energy; at the same time, the system will record this event and monitor the operating status and effect of the standby air conditioner.

[0216] In another embodiment of the present application, the standby air conditioner matching table is as follows:

[0217]

[0218]

[0219] In this example, X represents the lower limit of the cooling energy value of the central air conditioning system. When the cooling energy estimated by the system is lower than X, the matching table indicates to maintain the shutdown state of the central air conditioning and trigger the backup air conditioning to start working; on the contrary, if the estimated cooling energy is higher than or equal to X, the system will choose to start or maintain the operation of the central air conditioning;

[0220] Assume that the lower limit cooling energy of the central air conditioner in an office building is 500kW; during an event on the weekend, the system estimates that the cooling energy demand of a cooling area on a certain floor is 400kW (due to the increase in personnel density, but not reaching the efficient operating range of the central air conditioner); according to the backup air conditioner matching table, this estimated value is lower than the lower limit cooling energy, so the system will maintain the central air conditioner in the shutdown state and trigger the backup air conditioner to start working to meet the cooling demand of this floor.

[0221] Embodiment 3

[0222] See also Figure 3 , Figure 31 is a schematic diagram of the structure of the intelligent operation and maintenance system of the central air conditioner in an embodiment of the present invention, a smart operation and maintenance system of the central air conditioner, the smart operation and maintenance system of the central air conditioner includes:

[0223] A cooling space module 21 is used to determine each cooling space in the building based on the cooling path of the central air conditioner and the three-dimensional model of the building;

[0224] A cooling area module 22, for determining a plurality of cooling areas according to each cooling space, the floor position of the corresponding building and the corresponding indoor area;

[0225] A cooling mode module 23, for determining a cooling mode for a cooling area based on a plurality of cooling areas, corresponding area functions and the number of people in the cooling area;

[0226] The intelligent operation and maintenance system module 24 is used to determine the intelligent operation and maintenance system of the central air conditioner according to the cooling mode of each cooling area, external weather information and indoor temperature loss of multiple cooling areas;

[0227] The temperature control module 25 is used to determine multiple temperature control paths based on the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area in the intelligent operation and maintenance system of the central air conditioner;

[0228] The autonomous control module 26 is used to trigger the autonomous control of multiple cooling areas based on multiple temperature control paths, the current time and the indoor status of each cooling area, and to control the working time of the central air conditioner by the standby air conditioner.

[0229] The technical features of the above embodiments are arbitrarily combined. In order to make the description concise, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A smart operation and maintenance method for a central air conditioner, characterized in that: include: Determine each cooling space in the building based on the cooling path of the central air conditioner and the three-dimensional model of the building; Determine multiple cooling zones according to each cooling space, the corresponding floor location of the building, and the corresponding indoor area; Determining a cooling mode for a cooling area based on a plurality of cooling areas, corresponding area functions, and the number of people in the cooling area; Determine the intelligent operation and maintenance system of the central air conditioner based on the cooling mode of each cooling area, external weather information, and indoor temperature loss of multiple cooling areas; In the intelligent operation and maintenance system of central air conditioning, multiple temperature control paths are determined based on the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area; Based on multiple temperature control paths, the current time and the indoor status of each cooling area, autonomous control of multiple cooling areas is triggered, and the working time of the central air conditioner is controlled based on the standby air conditioner.

2. The intelligent operation and maintenance method of central air conditioning according to claim 1, characterized in that: The method of determining each cooling space in the building based on the cooling path of the central air conditioner and the three-dimensional model of the building includes: Collect the location of the building, and determine the three-dimensional model of the building according to the location of the building, the architectural information of the building and the town database; Determine the building's piping layout diagram based on the traversal of the building's three-dimensional model; Determine the cooling path of the central air conditioner based on the spatial location of the central air conditioner relative to the building and the building's piping layout; Each cooling space in the building is determined based on the cooling path of the central air conditioner, the three-dimensional model of the building, and the rental and sale status of each indoor space in the building.

3. The intelligent operation and maintenance method of central air conditioning according to claim 2, characterized in that: Determining a plurality of cooling areas according to each cooling space, the corresponding floor position of the building and the corresponding indoor area includes: Get each cooling space; Determine the spatial position of each cooling space based on the three-dimensional model of each cooling space and the building; Determine the floor position of the corresponding building according to the spatial position of each cooling space and the house number information of each cooling space; Determine the corresponding indoor area based on the traversal of each cooling space; Interact with each cooling space, the corresponding building floor location and the corresponding indoor area; Determine the first zone parameter according to each cooling space and the corresponding floor position of the building, and determine the second zone parameter according to each cooling space and the corresponding indoor area; A plurality of cooling zones are determined according to the three-dimensional model of the building, the first zone parameter and the second zone parameter.

4. The intelligent operation and maintenance method of central air conditioning according to claim 3, characterized in that: The method of determining the cooling mode of the cooling area based on the plurality of cooling areas, the corresponding area functions and the number of people in the cooling area includes: Get multiple cooling zones; Determine a first function parameter based on function detection of the plurality of cooling areas, and determine a second function parameter based on past business hours of the plurality of cooling areas; Determine a corresponding regional function according to the first functional parameter, the second functional parameter and the regional function matching table; Determine the number of people in each cooling area based on real-time monitoring of each cooling area; Interacting with multiple cooling zones, corresponding zone functions, and the number of people in the cooling zones to determine cooling modes for the cooling zones; The cooling mode of each cooling area is determined by interaction of the cooling modes of the cooling areas according to the plurality of cooling areas, the corresponding area functions and the number of people in the cooling areas.

5. The intelligent operation and maintenance method of a central air conditioner according to any one of claims 1 to 4, characterized in that: The intelligent operation and maintenance system of the central air conditioner is determined according to the cooling mode of each cooling area, external weather information, and indoor temperature loss of multiple cooling areas, including: Determine external weather information based on the location of the building, the corresponding weather system, and the external temperature detection parameters of the building; Monitor multiple cooling areas in real time and collect indoor temperature data sets of multiple cooling areas at different times; Determine the indoor temperature loss of the multiple cooling areas according to the indoor temperature data sets of the multiple cooling areas at different times and the length of the cooling path of the central air conditioner; Multiple interactions are performed on the cooling mode of each cooling area, external weather information, and indoor temperature loss of multiple cooling areas to train the cooling mode of each cooling area, external weather information, and indoor temperature loss of multiple cooling areas in different dimensions; The intelligent operation and maintenance system of the central air conditioner is determined based on the cooling mode of each cooling area, external weather information and training of indoor temperature losses in multiple cooling areas.

6. The intelligent operation and maintenance method of a central air conditioner according to any one of claims 1 to 4, characterized in that: In the intelligent operation and maintenance system of the central air conditioner, multiple temperature control paths are determined based on the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area, including: Collect the intelligent operation and maintenance system of central air conditioning; In the intelligent operation and maintenance system of central air conditioning, real-time temperature control is performed on each cooling area, and the current temperature of each cooling area is collected; Determine the personnel activity events in each cooling area according to the multiple internal images of each cooling area, the regional functions corresponding to each cooling area, and the personnel gathering places in each cooling area; The relative positions of the cooling zones are determined based on the position comparison of the cooling zones.

7. The intelligent operation and maintenance method of central air conditioner according to claim 6, characterized in that: In the intelligent operation and maintenance system of the central air conditioner, multiple temperature control paths are determined based on the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area, and further include: Interact with the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area; A plurality of temperature control paths are determined according to the interaction of the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area.

8. The intelligent operation and maintenance method of a central air conditioner according to any one of claims 1 to 4, characterized in that: The method of triggering the autonomous regulation of multiple cooling areas based on multiple temperature control paths, the current time, and the indoor status of each cooling area, and regulating the working time of the central air conditioner by the standby air conditioner, includes: Obtain multiple temperature control paths; Determine the current time based on the time data of the central air conditioner; Determine the indoor status of each cooling area based on the personnel information of each cooling space, the indoor image of each cooling space, and the appliance usage data of each cooling space Multiple temperature control paths, current time and indoor status of each cooling area are associated, and optimization events of the central air conditioner are determined according to the multiple temperature control paths, current time and indoor status of each cooling area, and autonomous control of multiple cooling areas is triggered according to the optimization time of the central air conditioner.

9. The intelligent operation and maintenance method of central air conditioning according to claim 8, characterized in that: The method of triggering the autonomous regulation of multiple cooling areas based on multiple temperature regulation paths, the current time and the indoor status of each cooling area, and regulating the working time of the central air conditioner by the standby air conditioner, further includes: Determine the standby air conditioner based on the building detection, and associate the standby air conditioner with the central air conditioner; Collect the pipeline layout diagram of the building, and determine the cooling area of ​​the standby air conditioner based on the location of the standby air conditioner, the power information of the standby air conditioner and the pipeline layout diagram of the building; The cooling energy is estimated according to the current time, the number of people staying in each cooling area and the external weather information; at this time, each cooling area is included in the cooling area of ​​the standby air conditioner; If the cooling energy is lower than the lower limit cooling energy of the central air conditioner, the central air conditioner is kept in the shutdown state and the standby air conditioner is triggered to adjust the working time of the central air conditioner.

10. A central air-conditioning intelligent operation and maintenance system, characterized in that: The intelligent operation and maintenance system of the central air conditioner is applied to the intelligent operation and maintenance method of the central air conditioner as claimed in any one of claims 1 to 9, and the intelligent operation and maintenance system of the central air conditioner comprises: A cooling space module is used to determine each cooling space in the building based on the cooling path of the central air conditioner and the three-dimensional model of the building; A cooling zone module, for determining a plurality of cooling zones according to each cooling space, the floor position of the corresponding building and the corresponding indoor area; A cooling mode module, used to determine a cooling mode for a cooling area based on multiple cooling areas, corresponding area functions, and the number of people in the cooling area; The intelligent operation and maintenance system module is used to determine the intelligent operation and maintenance system of the central air conditioner according to the cooling mode of each cooling area, external weather information, and indoor temperature loss of multiple cooling areas; The temperature control module is used to determine multiple temperature control paths in the intelligent operation and maintenance system of the central air conditioner based on the current temperature of each cooling area, the personnel activity events in each cooling area, and the relative positions of each cooling area; The autonomous control module is used to trigger the autonomous control of multiple cooling areas based on multiple temperature control paths, the current time and the indoor status of each cooling area, and the standby air conditioner controls the working time of the central air conditioner.

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