A protective device and control method for improving heat pump energy efficiency

Abstract

The present invention provides a protective device and control method for improving the energy efficiency of a heat pump. The method includes obtaining real-time monitoring of the heat pump operating status, including monitoring data such as operating temperature, fan status, and defrost conditions, through devices such as temperature sensors, pressure sensors, and airflow sensors; feeding the monitoring data back to the heat pump controller to determine whether the heat pump is in normal operation, shut down, or requires defrosting; adjusting the opening angle of the blinds when the heat pump is in normal operation; issuing a command to automatically close the protective device when the heat pump is shut down, powered off, or enters the defrost phase; automatically closing the blinds when the heat pump reaches the defrost conditions; and reopening the blinds to the fully open state when the heat pump completes defrosting and detects the conditions for exiting defrost, allowing the heat pump to operate normally. The device includes a data acquisition module, a status judgment module, and a result output module. The present invention maximizes the efficiency of the heat pump system and reduces unnecessary energy consumption.

Description

Technical Field

[0001] The present invention relates to the technical field of air energy heat pumps, and in particular to a protection device and a control method for improving the energy efficiency of a heat pump. Background Art

[0002] An air source heat pump is a device that uses the thermal energy in the air for heating or cooling. Through a refrigeration cycle, the heat in the air is transferred to water or air, thereby achieving indoor temperature control. Existing low-temperature air source heat pumps have relatively simple protective screens and cannot achieve air volume adjustment. The entire heat pump system generally has uneven air volume, which affects the energy efficiency of the heat pump. Existing low-temperature air source heat pumps have varying defrosting technologies, and defrosting energy consumption has become the most important factor affecting heat pumps under low-temperature conditions. Currently, mainstream heat pumps dissipate a large amount of heat to the low-temperature environment when defrosting under low-temperature conditions, resulting in very high defrosting energy consumption.

[0003] Prior art 1, application number: CN202311421658.5 discloses a control method, device, and air source heat pump system for an air source heat pump system. By obtaining the current status of each group of air source heat pump units and detecting the inlet and outlet water temperature difference, load rate, cooling capacity, and heating capacity of the system, different control strategies are adopted for each group of air source heat pump units that are turned on in different working modes. Furthermore, through a dynamic grouping control method, although the water mixing problem caused by the asynchronous start and stop frequencies of each group of air source heat pump units in the traditional system is solved, the operating energy efficiency of the system is improved. However, its structure is relatively complex and the operation is cumbersome, which increases the use and manufacturing costs of the air source heat pump.

[0004] Prior art 2, application number: CN202410496501.7 discloses an air source heat pump control method, system, and heat pump, including data processing of the historical operating data of the air source heat pump to obtain a performance loss characterization value of the air source heat pump, and at the same time, combined with monitoring of the subordinate operating area of ​​the air source heat pump, to obtain the temperature adjustment reference rate of the air source heat pump during actual operation, and to analyze and obtain the target execution adjustment speed of the compressor of the air source heat pump, and finally to achieve precise control of the compressor speed of the air source heat pump, so that the air source heat pump can dynamically adjust the compressor of the air source heat pump according to real-time demand, which can improve the energy efficiency of the air source heat pump and reduce energy consumption. Although it provides effective support for the control effect and operating efficiency of the air source heat pump, it can effectively optimize the operating efficiency and overall control coordination of the air source heat pump. However, the protective net structure is relatively simple and cannot achieve air volume adjustment, which affects the energy efficiency of the heat pump.

[0005] Prior art three, application number: CN 202310930326.3 discloses a design and selection method for frost-suppressing air source heat pumps suitable for different regions, including the following steps: a conventional air source heat pump temperature drop ΔTa < 6°C to achieve frost suppression energy efficiency; when ΔTa is greater than 6°C, a frost suppression heat pump needs to be selected; when 6 < ΔTa ≤ 8, a frost suppression heat pump with CICO = 8 is selected, when 8 < ΔTa ≤ 10, a frost suppression heat pump with CICO = 10 is selected, and when 10 < ΔTa, a frost suppression heat pump with CICO = 12 is selected; calculate the defrosting equivalent temperature drop ΔTa` of the frost suppression air source heat pump under the CICO; verify whether the selected frost suppression air source heat pump meets the frost suppression energy efficiency, if it does not meet ΔTa` < 6°C, reselect the air source heat pump CICO; until the corresponding region meets the frost suppression energy efficiency, the design and selection of the frost suppression air source heat pump is completed; although it is suitable for different climatic conditions in different regions. However, the amount of heat dissipated in a low-temperature environment during defrosting is very large, resulting in very high defrosting energy consumption.

[0006] Currently, the existing technologies 1, 2, and 3 have the problem that the protective net structure is simple and cannot achieve air volume adjustment, which affects the energy efficiency of the heat pump; the heat dissipation in the low-temperature environment during defrosting is large, resulting in high energy consumption for defrosting. Therefore, the present invention provides a protective device and control method for improving the energy efficiency of the heat pump, which is installed at the air inlet position of the heat pump fin heat exchanger and adopts an electric openable and closable shutter design. The shutter can be adjusted to a full opening angle according to the height of the fin and the air volume of the fan to achieve uniform air volume above and below the fin heat exchanger. At the same time, it can be closed when the heat pump is not in use or when defrosting, thereby protecting the heat pump fin heat exchanger and reducing defrosting energy consumption. Summary of the Invention

[0007] In order to solve the above technical problems, the present invention provides a protection device and a control method for improving the energy efficiency of a heat pump, comprising the following steps:

[0008] Obtain real-time monitoring of heat pump operating status;

[0009] Feedback the monitoring data to the heat pump controller to determine whether the heat pump is in normal operation, shut down, or needs to be defrosted;

[0010] When the heat pump is in normal operation, the shutters will be adjusted to open at an angle; when the heat pump is shut down, powered off, or enters the defrost stage, a command will be issued to automatically close the protective device; when the heat pump reaches the defrost conditions, the shutters will be automatically closed; when the heat pump completes defrosting and detects the conditions to exit defrosting, the shutters will be reopened to the fully open state, and the heat pump will operate normally.

[0011] Optionally, the monitoring data acquisition process includes the following steps:

[0012] Obtain the target requirements of the monitoring data, analyze the target requirements, and obtain the specific types of content corresponding to the target requirements; perform three-dimensional modeling on the heat pump, obtain the result position coordinates corresponding to the target requirements based on the three-dimensional modeling, and map the position coordinates with the target requirements to form a relationship mapping table;

[0013] According to the relationship mapping table, the database searches for the device corresponding to the specific type and obtains the performance parameters of the device; the location coordinates are used as the unique identifier to distinguish the location of the device, and the performance parameters and coordinates of the device are added to the relationship mapping table to correspond to the target requirements;

[0014] All devices are linked to form a monitoring data acquisition network to summarize the content of the monitoring data; the monitoring data acquisition network issues a startup instruction according to the preset acquisition cycle of the monitoring data, all devices begin to initialize and collect the corresponding monitoring data, and the location coordinates and monitoring data are packaged and sent to the heat pump, and the controller determines the status of the heat pump.

[0015] Optionally, the process of determining the state of the heat pump includes the following steps:

[0016] The controller receives real-time data from temperature sensors, pressure sensors, and airflow sensors, forming a multi-dimensional data packet containing key information such as operating temperature, fan status, ambient temperature, and compressor pressure. It also obtains multiple sets of thresholds set for the heat pump, which are used to define normal operation, shutdown, and defrost conditions.

[0017] According to the key information of the data packet, a comparison is performed with one of the items corresponding to the multiple sets of thresholds, and the status of the heat pump is obtained according to the comparison result;

[0018] The judgment results are fed back to the heat pump controller, and the corresponding actions are executed according to the program set inside the controller; after each data collection, the controller cross-verifies the operating status and obtains the reliability of the operating status through data trend analysis.

[0019] The optional multi-threshold process includes the following steps:

[0020] The insulation performance and usage pattern history information of the user is collected; historical information is analyzed to obtain the user's past usage habits, and personalized demand forecasts are made based on seasonal changes and energy consumption patterns;

[0021] Establish a rule engine between historical data and operating conditions, and automatically generate a dynamic combination of operating thresholds by analyzing historical data. After the heat pump has been running for a certain period of time according to the set threshold, the current energy efficiency and operating status are evaluated. If the operating efficiency or energy consumption in the evaluation results exceeds the corresponding evaluation threshold, the threshold configuration is automatically optimized and the evaluation result is adjusted to within the evaluation threshold.

[0022] The operating temperature, fan status, ambient temperature and compressor pressure thresholds are set up into independent threshold groups according to the usage environment, grouped and managed, and the priority of each threshold is defined.

[0023] Optionally, the priority of setting each threshold value includes that under extremely low temperature conditions, the threshold setting of the ambient temperature takes precedence over the setting of the operating pressure.

[0024] Optionally, the process of processing real-time monitoring data includes the following steps:

[0025] Utilize data streams to continuously acquire new data and match it with the rules in the database; compare the environmental conditions captured in the real-time data stream with the conditions in the rule base; determine the rules that meet the conditions and form a dynamic threshold combination;

[0026] Compare real-time environmental parameters with the conditions in the rule base, combine all rules that meet the conditions to form a new dynamic threshold set; use the currently collected real-time data to determine the current status;

[0027] Leverage feedback to generate adjustment suggestions based on real-time status.

[0028] Optionally, the switching control process of the blinds includes the following steps:

[0029] Obtain the target state of the heat pump in normal operation, shutdown, or needing to defrost. According to the target state, call the corresponding shutter control program, which is closed and opened.

[0030] When the instruction is for normal operation, the PWM signal controls the servo motor to drive the shutters to adjust the opening angle to 60 degrees. When the instruction is for shutdown or defrosting, the controller sends a shutter closing instruction, and the servo motor closes the shutters. In the shutdown state, the shutters are completely closed, that is, 0 degrees. When defrosting is required, the shutters close quickly.

[0031] Regularly check the temperature and humidity to confirm whether the defrost operation is complete; the controller sends a reopening instruction to the blinds, and adjusts the blinds through the servo motor; the blinds opening angle is automatically adjusted according to the wind speed and outside temperature.

[0032] Optionally, the opening angle of the shutters is adjusted to 60°.

[0033] Optionally, the process of automatically adjusting the blinds' opening angle according to wind speed and outside temperature includes the following steps:

[0034] Through the logic judgment model, determine the impact of the current external environment on the shutter opening angle according to the combination of wind speed and temperature;

[0035] After calculating the required opening angle, the controller sends a control signal to the servo motor. The position sensor continuously monitors the actual opening angle of the blinds. If any deviation is found, the controller automatically sends a correction command to adjust the blinds to the ideal state.

[0036] The controller continuously monitors the external environment and internal status, re-evaluating whether the shutter opening angle needs to be adjusted every time the wind speed or temperature changes, and re-evaluating and confirming the status after each adjustment; storing environmental data and corresponding opening angle settings to optimize control strategies.

[0037] The present invention provides a protective device for improving the energy efficiency of a heat pump, comprising:

[0038] The data acquisition module is responsible for obtaining the real-time monitoring of the heat pump operating status;

[0039] The status judgment module is responsible for feeding back the monitoring data to the heat pump controller to determine whether the heat pump is in normal operation, shut down, or needs to be defrosted;

[0040] The result output module is responsible for adjusting the opening angle of the blinds when the heat pump is in normal operation; when the heat pump is shut down, powered off, or enters the defrost stage, it will issue a command to automatically close the protective device; when the heat pump reaches the defrost conditions, the blinds will automatically close; when the heat pump completes defrosting and detects the conditions for exiting defrost, the blinds will reopen and return to the fully open state, and the heat pump will operate normally.

[0041] The present invention obtains real-time monitoring data, utilizing devices such as temperature sensors, pressure sensors, and airflow sensors to monitor the operating status of the heat pump in real time and obtain key data (such as operating temperature, fan status, and defrost conditions). This data is fed back to the heat pump control system to help determine the current status (normal operation, shutdown, or defrosting required). Significance: Dynamic monitoring of the heat pump system is achieved, enabling it to respond promptly to different operating conditions and ensure that the equipment operates at optimal performance. The system's intelligence level is improved, providing accurate basic data for subsequent decision-making and avoiding suboptimal operation due to changes in the external environment. Adjusting the shutter opening angle: When the heat pump is operating normally, the shutter opening angle is automatically adjusted to optimize the way air flows into the heat exchanger and enhance heat exchange efficiency. When the heat pump is shut down, powered off, or enters the defrost state, a command is issued to automatically shut down the protective device to protect the heat pump and save energy. Significance: Adjusting the air volume according to the specific operating conditions ensures the effective utilization of heat and prevents heat energy loss, thereby improving the overall energy efficiency of the heat pump. The automatic shutdown device avoids unnecessary energy consumption, protects the equipment, and extends its service life. Automatically close and reopen the blinds. When the heat pump reaches defrost conditions, the blinds automatically close to prevent cold outside air from coming into direct contact with the heat exchanger, significantly reducing heat loss during defrost. After defrost is complete, if the relevant conditions are detected, the blinds reopen to resume normal operation. Significance: This improves the efficiency of the heat pump during the defrost process, ensuring heat retention, reducing energy consumption, and improving the overall energy efficiency of the system. Through intelligent control, it prevents the impact of human factors on equipment efficiency and ensures the efficient and stable operation of the heat pump under different operating conditions.

[0042] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0043] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0045] Figure 1 This is a flow chart of a control method for a protective device for improving the energy efficiency of a heat pump in Example 1 of the present invention;

[0046] Figure 2 This is a diagram of the monitoring data acquisition process in Example 2 of the present invention;

[0047] Figure 3 This is a process diagram for determining the state of a heat pump in Example 3 of the present invention;

[0048] Figure 4 This is a process diagram of multiple sets of thresholds in Example 4 of the present invention;

[0049] Figure 5 A process diagram for automatically generating a dynamic combination of operating thresholds in Example 5 of the present invention;

[0050] Figure 6 A process diagram for establishing a comprehensive heat pump operation rule base in Example 6 of the present invention;

[0051] Figure 7 This is a process diagram for processing real-time monitoring data in Example 7 of the present invention;

[0052] Figure 8 1 is a diagram of the switching control process of the blinds in Example 8 of the present invention;

[0053] Figure 9 This is a diagram showing the process of automatically adjusting the shutter opening angle according to wind speed and external temperature in Example 9 of the present invention;

[0054] Figure 10 This is a block diagram of a protective device for improving the energy efficiency of a heat pump in Example 10 of the present invention. DETAILED DESCRIPTION

[0055] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0056] The terms used in the embodiments of the present application are for the purpose of describing specific embodiments only and are not intended to limit the embodiments of the present application. The singular forms "a", "the" and "the" used in the embodiments of the present application are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0057] When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0058] Example 1: Figure 1 As shown, an embodiment of the present invention provides a control method for a protective device for improving the energy efficiency of a heat pump, comprising the following steps:

[0059] S100: Obtain real-time monitoring of the heat pump operating status, including operating temperature, fan status, and defrost conditions, through devices such as temperature sensors, pressure sensors, and air flow sensors;

[0060] S200: Feedback the monitoring data to the heat pump controller to determine whether the heat pump is in normal operation, shut down, or needs to be defrosted;

[0061] S300: When the heat pump is in normal operation, the shutters will be adjusted to open at an angle; when the heat pump is shut down, powered off, or enters the defrost stage, a command will be issued to automatically close the protective device; when the heat pump reaches the defrost conditions, the shutters will be automatically closed; when the heat pump completes defrosting and detects the conditions to exit defrosting, the shutters will be reopened to the fully open state, and the heat pump will operate normally.

[0062] The working principle and beneficial effects of the above technical solution are as follows: First, this embodiment obtains real-time monitoring of the heat pump operating status, including monitoring data such as operating temperature, fan status, and defrost conditions, through devices such as temperature sensors, pressure sensors, and airflow sensors; secondly, the monitoring data is fed back to the heat pump controller to determine whether the heat pump is in normal operation, shut down, or requires defrosting; finally, when the heat pump is in normal operation, the blinds are adjusted to the opening angle; when the heat pump is shut down, powered off, or enters the defrost phase, a command is issued to automatically close the protective device; finally, when the heat pump reaches the defrost condition, the blinds are automatically closed; when the heat pump completes defrosting and detects the conditions for exiting defrost, the blinds are reopened and restored to the fully open state, and the heat pump operates normally. Step S100 of the above solution obtains real-time monitoring data, using devices such as temperature sensors, pressure sensors, and airflow sensors to monitor the operating status of the heat pump in real time and obtain key data (such as operating temperature, fan status, and defrost conditions); step S200 feeds the data back to the heat pump control system to help determine the current state (normal operation, shut down, or requiring defrost). Significance: Dynamic monitoring of the heat pump system is achieved, enabling it to respond promptly to varying operating conditions and ensuring optimal performance. The system's intelligence is enhanced, providing accurate data for subsequent decision-making and preventing suboptimal operation due to environmental changes. Step S300: Adjusting the shutter angle. During normal heat pump operation, the shutter angle is automatically adjusted to optimize air flow into the heat exchanger, enhancing heat exchange efficiency. When the heat pump is shut down, loses power, or enters defrost mode, a command is issued to automatically close the protective device to protect the heat pump and save energy. Significance: Adjusting air volume based on specific operating conditions ensures efficient heat utilization and prevents heat loss, thereby improving the overall energy efficiency of the heat pump. Automatically closing the device avoids unnecessary energy consumption, protecting the equipment and extending its service life. Automatically closing and reopening the shutters: When the heat pump reaches defrost conditions, the shutters automatically close to prevent direct contact between low-temperature outside air and the heat exchanger, significantly reducing heat loss during defrost. After defrost is complete, the shutters reopen when relevant conditions are detected, resuming normal operation. Significance: It improves the efficiency of the heat pump during the defrosting process, ensures heat retention, reduces energy consumption, and improves the overall energy efficiency of the system; through intelligent control, it avoids the impact of human factors on the operating efficiency of the equipment, and ensures the efficient and stable operation of the heat pump under different working conditions.

[0063] In this embodiment, when the heat pump is operating normally, the protective device is fully open to the optimal opening angle originally designed. When the heat pump is shut down or loses power, the protective device automatically closes. When the heat pump reaches defrost conditions and shuts down the fan, the protective device is no longer required to close. In this closed state, the heat pump defrosts. Because the protective device isolates the heat exchanger from the cold air flowing outside, it avoids excessive heat loss during defrosting and significantly improves defrost efficiency. When the heat pump reaches defrost exit conditions and the fan is turned on again, the protective device returns to its fully open state and continues normal operation.

[0064] Compared with existing technologies, this embodiment reduces heat loss during defrosting, improves defrosting efficiency, and reduces system energy consumption. It also shortens defrosting time and reduces defrosting power consumption. It also improves defrosting effectiveness, resulting in a more effective and thorough defrosting process due to reduced heat loss, thus enhancing the unit's reliability under harsh operating conditions. It also improves the uniformity of air volume during normal heat pump operation, improving heat pump efficiency and reducing uneven frosting. Compared with existing technologies, this embodiment not only improves the operating efficiency of the heat pump but also significantly reduces heat loss during the defrosting process, thereby improving the overall operating efficiency of the heat pump.

[0065] In summary, the three steps of this embodiment maximize the efficiency of the heat pump system and reduce unnecessary energy consumption through precise monitoring, intelligent control, and optimized management mechanisms. Furthermore, by strengthening the equipment's self-regulation capabilities, the overall system's operational reliability and economic benefits are improved, achieving the goal of enhancing heat pump energy efficiency.

[0066] Example 2: Figure 2 As shown, based on Example 1, the monitoring data acquisition process provided by the embodiment of the present invention includes the following steps:

[0067] S101: Obtain target requirements from monitoring data, analyze the target requirements, and obtain specific types of content corresponding to the target requirements; perform three-dimensional modeling on the heat pump, obtain result location coordinates corresponding to the target requirements based on the three-dimensional modeling, and map the location coordinates to the target requirements to form a relationship mapping table;

[0068] S102: Searching for a device corresponding to a specific type in a database according to a relationship mapping table to obtain performance parameters of the device; using the location coordinates as a unique identifier to distinguish the location of the device, adding the performance parameters and coordinates of the device to the relationship mapping table to correspond to the target requirements;

[0069] S103: All devices are associated to form a monitoring data acquisition network to summarize the content of the monitoring data; the monitoring data acquisition network issues a startup instruction according to the preset acquisition cycle of the monitoring data, all devices begin to initialize and collect the corresponding monitoring data, and the location coordinates and monitoring data are packaged and sent to the heat pump, and the controller determines the status of the heat pump.

[0070] The working principle and beneficial effects of the above technical solution are as follows: this embodiment first obtains the target demand of the monitoring data, parses the target demand, and obtains the specific type of content corresponding to the target demand; performs three-dimensional modeling on the heat pump, obtains the result position coordinates corresponding to the target demand based on the three-dimensional modeling, maps the position coordinates with the target demand, and forms a relationship mapping table; secondly, searches the database for the device corresponding to the specific type according to the relationship mapping table to obtain the performance parameters of the device; uses the position coordinates as a unique identifier to distinguish the position of the device, adds the performance parameters and coordinates of the device to the relationship mapping table, corresponding to the target demand; finally, all devices are associated to form a monitoring data acquisition network to summarize the content of the monitoring data; the monitoring data acquisition network issues a start-up instruction according to the preset acquisition cycle of the monitoring data, all devices start to initialize, and collect corresponding monitoring data, and packages the position coordinates and monitoring data and sends them to the heat pump, and the controller determines the status of the heat pump. Step S101 of the above scheme obtains the target requirements for monitoring data. By analyzing the monitoring target requirements, the data types required for different monitoring tasks (such as temperature, pressure, airflow, etc.) are clarified; a three-dimensional model of the heat pump is established to provide basic support for the positioning and spatial identification of subsequent monitoring data; the target requirements are mapped with the corresponding monitoring result location coordinates to generate a relationship mapping table, forming a clear data processing framework. Significance: It provides a systematic method to clarify the monitoring content and target requirements, laying the foundation for subsequent data acquisition; the three-dimensional modeling provides an intuitive view, which helps to efficiently identify the required monitoring locations and ensure the accuracy of monitoring data; the relationship mapping table effectively connects the relationship between the target requirements and the actual monitoring equipment, enhancing the maintainability and scalability of the system. Step S102 searches for devices and performance parameters. Using the relationship mapping table, the database is quickly searched for monitoring devices and their performance parameters that match the specific type of requirements; the location coordinates are used as a unique identifier to distinguish the location of the device, making the monitoring device clear in the network; the performance parameters of the device and its coordinates are associated with the target requirements to enhance the relevance and accuracy of the data. Significance: It realizes the dynamic identification and data integration of devices, ensuring the effective utilization and information update of each device in the monitoring system; it clarifies the geographical location of the device, realizes accurate data collection, and provides a basis for subsequent data analysis; it integrates the performance parameters of the device in the relationship mapping table, provides data support for the optimization of system operation, and helps the decision-making and control of the entire system. Step S103 forms a monitoring data acquisition network. By associating all monitoring devices, a complete monitoring data acquisition network is formed, which enhances the coordination and data sharing capabilities of the system; it issues a startup instruction according to the set time period to ensure that all devices initialize and collect data at the appropriate time node; the collected monitoring data and its location coordinates are packaged and sent to the heat pump. The controller can immediately judge the status of the heat pump based on the received data and make corresponding adjustments.Significance: An efficient monitoring network has been built, enhancing the real-time performance and responsiveness of the system while ensuring comprehensive collection of monitoring data. Regular data collection ensures that the operating status of the heat pump is always under monitoring, expanding preventive maintenance management capabilities. The real-time feedback mechanism provides effective data support for the optimized control of the heat pump, enabling the system to maintain optimal performance under different operating conditions.

[0071] In summary, the monitoring data acquisition process in this embodiment forms a complete closed loop, from demand analysis to device search, data collection, and transmission. This ensures real-time, accurate, and comprehensive monitoring of the heat pump system. This effectively improves the system's intelligence and operational efficiency, laying a solid foundation for subsequent control and optimization.

[0072] Example 3: Figure 3 As shown, based on Example 1, the process of determining the state of the heat pump provided by the embodiment of the present invention includes the following steps:

[0073] S201: Implementing a controller to receive real-time data from temperature sensors, pressure sensors, and airflow sensors to form a multi-dimensional data packet; the data packet includes key information such as operating temperature, fan status, ambient temperature, and compressor pressure; obtaining multiple sets of thresholds set for the heat pump, which are used to define normal operation, shutdown, and defrost conditions;

[0074] S202: comparing the key information of the data packet with an item corresponding to the multiple sets of thresholds, and obtaining the status of the heat pump according to the comparison result;

[0075] Among them, the normal operating state is judged. When the monitored temperature, pressure and air flow are all within the threshold range and the fan is operating normally (for example, the fan operating frequency is within the set range), the controller determines that the heat pump is in a normal operating state;

[0076] Shutdown status recognition: When the monitored temperature is lower than the set minimum threshold, the compressor pressure falls back to a safe range (for example, lower than the static pressure threshold), or the fan status is detected as abnormal (such as stalled), the controller immediately determines that the heat pump is in shutdown state;

[0077] Defrost condition detection: When the temperature sensor detects frost on the evaporator surface and records a specific temperature (for example, below 0°C), and the air flow sensor detects that the air flow rate has dropped to a too low range (which may indicate frost causing air flow obstruction), the controller will make a real-time judgment and issue a command to enter the defrost state;

[0078] S203: Feedback the judgment result to the heat pump controller, and execute the corresponding action according to the program set in the controller; after each data collection, the controller cross-verifies the operating status and obtains the reliability of the operating status through data trend analysis.

[0079] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first realizes that the controller receives real-time data from temperature sensors, pressure sensors and air flow sensors to form a multi-dimensional data packet; the data packet contains key information such as operating temperature, fan status, ambient temperature and compressor pressure; multiple sets of thresholds set by the heat pump are obtained, and the thresholds are used to define normal operation, shutdown and defrost conditions; secondly, according to the key information of the data packet, a comparison is performed with one of the items corresponding to the multiple sets of thresholds, and the status content of the heat pump is obtained according to the comparison results; among them, the normal operating state is judged, when the monitored temperature, pressure and air flow are all within the threshold range, and the fan is operating normally (for example, the fan operating frequency is within the set range), the controller determines that the heat pump is in normal operating state; shutdown state Identification: When the monitored temperature is lower than the set minimum threshold, the compressor pressure drops back to a safe range (for example, lower than the static pressure threshold), or the fan status is detected as abnormal (such as stalled), the controller immediately determines that the heat pump is in a shutdown state; defrost condition detection: when the temperature sensor detects frost on the evaporator surface and records a specific temperature (for example, lower than 0°C), and the air flow sensor detects that the air flow rate drops to a too low range (which may indicate that frost causes poor airflow), the controller makes a real-time judgment and issues an instruction to enter the defrost state; finally, the judgment result is fed back to the heat pump controller, and the corresponding action is executed according to the program set inside the controller; after each data collection, the controller cross-verifies the operating status and obtains the reliability of the operating status through data trend analysis. Step S201 of the above scheme enables the controller to receive sensor data. The controller can simultaneously receive real-time data information from temperature sensors, pressure sensors, and airflow sensors to form a complete multi-dimensional data packet. Integration makes the monitoring information more comprehensive, covering all key factors affecting the operating status of the heat pump. The data packet contains key parameters such as operating temperature, fan status, ambient temperature, and compressor pressure, providing the necessary basis for status judgment. Multiple sets of thresholds set by the heat pump are obtained. The thresholds are an important basis for judging the operating status of the system and define the operating conditions for normal operation, shutdown, and defrosting. Significance: Through comprehensive data collection, a panoramic view of the operating status of the heat pump is provided, providing a reliable basis for subsequent judgments; ensuring that the controller can use information from multiple parameters when making decisions to improve the accuracy and rationality of judgments. In step S202, performance comparison and status judgment, the controller compares the key information in the data packet with the set threshold value, which can clearly judge the operating status of the heat pump; the comparison mechanism can evaluate different operating parameters, improving the efficiency of data use; by confirming that all monitoring parameters are within the set range, the conclusion of normal operation is drawn to ensure efficient operation of the system; shutdown conditions are identified in time to avoid energy waste and loss due to system failures; the necessity of defrosting is judged by monitoring the evaporator temperature and air flow rate, and instructions are issued in time to solve the frosting problem, ensuring the normal operation of the heat pump in a cold environment.Significance: Through real-time status judgment, early warning can be given before problems occur, thus avoiding more serious failures; ensuring that the heat pump can operate effectively under various environmental conditions, improving the reliability of the system and user experience. Step S203 feedback and cross-validation, the judgment results are fed back to the heat pump controller in a timely manner. The controller can quickly perform corresponding operations (such as adjusting the fan speed, starting defrost, etc.) according to the judgment results to achieve real-time control; after each data collection, the controller confirms the operating status through a cross-validation mechanism, and combined with trend analysis, it can identify potential problems that may arise during long-term operation. Significance: An efficient feedback mechanism can ensure that the heat pump automatically adjusts during operation, reduces human intervention, and improves the system's adaptability and operational safety; through cross-validation and trend analysis, the system's ability to identify different failure modes is enhanced, providing a guarantee for the long-term stable operation of the equipment, reducing maintenance costs, and extending the service life of the equipment.

[0080] In summary, this embodiment forms a closed-loop control system for determining heat pump status through precise data collection, detailed comparison, and effective feedback. This not only improves the heat pump's operating efficiency and safety, but also enhances the system's intelligence, providing users with a more efficient and reliable temperature control solution.

[0081] Example 4: Figure 4 As shown, based on Example 3, the process of multiple sets of thresholds provided in this embodiment of the present invention includes the following steps:

[0082] S2011: Through a user-friendly interface, users can input historical information such as the location of the location, expected season of use, insulation performance of the building or facility, and usage patterns (e.g., continuous or intermittent use). This historical information is analyzed to determine the user's past usage habits and provide personalized demand forecasts based on seasonal changes and energy consumption patterns.

[0083] S2012: Establish a rule engine between historical data and operating conditions. By analyzing historical data, a dynamic combination of operating thresholds is automatically generated. After the heat pump has been operating for a certain period of time according to the set thresholds, the current energy efficiency and operating status are evaluated. If the operating efficiency or energy consumption in the evaluation results exceeds the corresponding evaluation thresholds, the threshold configuration is automatically optimized to adjust the evaluation results to within the evaluation thresholds.

[0084] S2013: The operating temperature, fan status, ambient temperature, and compressor pressure thresholds are organized into independent threshold groups based on the usage environment. These groups are managed and the priority of each threshold is defined. Usage environments include home heating, commercial heating, and swimming pool heating. The priority of each threshold is set so that under extreme low temperature conditions, the ambient temperature threshold setting takes precedence over the operating pressure setting.

[0085] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first uses a user-friendly interface to input historical information such as the geographic location of the location, the expected season of use, the insulation performance of the building or facility, and usage patterns (such as continuous use or intermittent use). This historical information is analyzed to obtain the user's past usage habits and perform personalized demand forecasts based on seasonal changes and energy consumption patterns. Secondly, a rule engine is established to link historical data with operating conditions. By analyzing historical data, a dynamic combination of operating thresholds is automatically generated. After the heat pump has operated for a certain period of time according to the set thresholds, the current energy efficiency and operating status are evaluated. If the operating efficiency or energy consumption in the evaluation results exceeds the corresponding evaluation thresholds, the threshold configuration is automatically optimized and the evaluation results are adjusted to within the evaluation thresholds. Finally, the operating temperature, fan status, ambient temperature, and compressor pressure thresholds are established into independent threshold groups based on the usage environment for group management and definition of the priority of each threshold. The usage environments include home heating, commercial heating, and pool heating. The priority of each threshold is set, including in extreme low temperature conditions, where the ambient temperature threshold setting takes precedence over the operating pressure setting. In step S2011 of the above scheme, user input and personalized demand prediction are performed. Information such as the location of the user, seasonal variations, building insulation performance, and usage patterns are collected through a user-friendly interface. The user's historical usage habits are analyzed, and data analysis techniques are used to identify factors influencing energy consumption patterns and seasonal variations. Based on the analysis results, a personalized demand forecast is generated, providing data support for subsequent threshold setting. Significance: Personalized information collection and analysis enables user participation in system configuration, improving system friendliness and interactivity. By understanding the user's specific needs and usage environment, the heat pump's operating hours and operating modes are ensured to match actual usage needs, thereby reducing resource waste. This lays a solid data foundation for threshold setting, making subsequent operational optimization more accurate. Step S2012 establishes a rule engine and dynamic threshold combination. The established rule engine generates a dynamic threshold combination based on historical data analysis. Real-time monitoring is implemented, and operational efficiency and energy consumption data are regularly evaluated. The current operating status is determined by comparing the calculated data with pre-set assessment thresholds. When operating efficiency or energy consumption exceeds the assessment threshold, the system automatically optimizes the operating threshold configuration to restore it to a reasonable range. Significance: Through real-time data input and analysis, the system has the ability to intelligently, dynamically adjust and optimize, allowing the heat pump to adaptively adjust according to environmental changes and actual load; precise threshold combination and real-time optimization can significantly improve the operating efficiency and energy utilization of the heat pump, reduce energy consumption and extend the service life of the equipment; the automatic optimization mechanism helps to promptly detect operating anomalies, reduce the risk of system failure, and improve the reliability of the heat pump system.Step S2013 is group management and priority setting, which classifies and manages the thresholds under different usage environments (such as home heating, commercial heating, and swimming pool heating) to ensure that the operations in each environment are relatively independent but have the integrity of the system; clarify the priorities of different threshold settings. For example, under extremely low temperature conditions, the threshold of ambient temperature takes precedence over the threshold setting of operating pressure, and determine the priority processing rules for potential conflicts through logical relationships. Significance: Group management and priority setting can enable the system to best match the needs of different industries, improve the flexibility and applicability of the system, and better serve user-specific scenarios; by pre-setting priorities, it can quickly respond to critical situations facing the system and adopt the most appropriate control strategy to ensure safe and efficient operation; ensure that the thresholds of different application scenarios can cooperate with each other, standardize the operation of the heat pump, reduce cross-interference, and improve the overall operational stability of the equipment.

[0086] In summary, this embodiment achieves personalized, intelligent, safe, and efficient operation of the heat pump system through user input, dynamic adjustment of the rule engine, and group management. Each step not only achieves technical innovation in safety and management, but also meets the diverse needs of users at the application level, greatly improving the operating efficiency and energy utilization of the heat pump, and providing users with a better experience and value.

[0087] Example 5: Figure 5 As shown, based on Example 4, the process of automatically generating a dynamic combination of operating thresholds provided by the embodiment of the present invention includes the following steps:

[0088] S20121: Integrate real-time data sources to build a comprehensive database and establish a comprehensive heat pump operation rule base. The heat pump operation rule base defines different operating threshold combinations under various conditions. The rules set logical relationships between different parameters such as ambient temperature and usage mode. For example, when the outside temperature falls below a certain threshold, the indoor environment target temperature is automatically adjusted and the operation mode is optimized accordingly.

[0089] S20122: Based on the collected real-time data stream and user input, the current environmental conditions are matched with the heat pump operation rule library for analysis to determine the threshold combination; the real-time monitoring data is processed to obtain the operation mode and optimization suggestions;

[0090] S20123: Continuously monitor and collect energy efficiency data and user feedback, and evaluate the current operating status by comparing the actual operating efficiency with the preset evaluation threshold. If the evaluation result shows that it exceeds the set evaluation threshold, the rule engine will add, modify or discard operating rules based on the feedback information, and naturally generate a new dynamic threshold combination.

[0091] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first integrates real-time data sources, builds a comprehensive database, and establishes a comprehensive heat pump operation rule base. The heat pump operation rule base defines different operation threshold combinations under various conditions; the logical relationship between different parameters such as ambient temperature and usage mode is set in the rules; for example, when the outside temperature is lower than a specific threshold, the indoor environment target temperature is automatically adjusted and the operation mode is optimized accordingly; secondly, based on the collected real-time data stream and the information input by the user, the current environmental conditions are matched with the heat pump operation rule base for analysis to determine the threshold combination; the real-time monitoring data is processed to obtain the operation mode and optimization suggestions; finally, energy efficiency data and user feedback are continuously monitored and collected, and the current operation status is evaluated by comparing the actual operation efficiency with the preset evaluation threshold; if the evaluation result shows that the set evaluation threshold is exceeded, the rule engine will add, modify or discard the operation rules based on the feedback information, and naturally generate a new dynamic threshold combination. Step S20121 of the above solution integrates real-time data sources with the establishment of a heat pump operation rule library, creating a comprehensive database that integrates real-time data from various sources, including ambient temperature, humidity, and user behavior. This ensures timely data updates and accuracy to support subsequent decision-making processes. It also defines operating threshold combinations under various conditions and creates a set of logical rules for automatically adjusting operating states. It also sets relationships between parameters such as ambient temperature and usage patterns to provide a basis for intelligent decision-making. By setting logical relationships, for example, automatically adjusting the indoor temperature when the outside temperature falls below a certain threshold, a preset decision-making mechanism is formed. Significance: This ensures that intelligent decisions are made based on real-time and historical data, enhancing the intelligence level of the system. Through preset rules, the system can automatically adapt to changing environmental conditions and optimize resource utilization efficiency. It adjusts indoor conditions based on real-time environmental changes to ensure that the user's comfort experience is not affected by the external environment. Step S20122 matches data with threshold combinations. Based on the real-time data stream and user input, the heat pump operation rule library analyzes the current environmental conditions and determines an appropriate threshold combination. The monitoring data is processed using a heuristic algorithm to discover the optimal operating mode and feasible optimization suggestions. The real-time monitoring data is analyzed to provide practical optimization suggestions, enabling the heat pump system to select the optimal operating strategy under different environmental conditions. Significance: Combining real-time data with the heat pump operation rule library enables the system to make fast and flexible decisions under different conditions, demonstrating the intelligent nature of the technology. By optimizing the threshold combination, the system achieves high efficiency and energy conservation, helping users reduce energy costs. The system ensures dynamic adjustments based on real-time data feedback and user preferences, improving user satisfaction and user experience.Step S20123 involves continuous monitoring and feedback optimization, continuously tracking and collecting energy efficiency data and user feedback, comparing actual operating efficiency with preset assessment thresholds, and determining the current system status. Through monitoring, abnormalities in operation are promptly detected to ensure healthy system operation. If the operating results exceed the set assessment threshold, the rule engine will update the operating rules based on the feedback information, enabling dynamic adjustment of the financing portfolio. Certain operating rules can be automatically added, modified, or discarded to generate new dynamic operating thresholds. Significance: With data feedback, the system can continuously adjust and optimize operating parameters to ensure sustained high efficiency and stable operation. Through real-time monitoring and feedback mechanisms, potential problems can be identified earlier, reducing the probability of system failures and improving system reliability. Users' participation in system management is enhanced, making their feedback an important basis for system optimization and fostering a positive interaction between users and the system.

[0092] In summary, this embodiment achieves dynamic threshold combination for a heat pump system through real-time data collection, rule definition, continuous monitoring, and self-optimization. This improves the system's intelligence, adaptability, and operational efficiency; it not only enhances user experience and satisfaction, but also ensures the system's long-term operation and reliability. Through this dynamic and flexible management mechanism, the heat pump system can better adapt to changing environmental conditions and user needs, making positive contributions to smart buildings and energy conservation and environmental protection.

[0093] Example 6: Figure 6 As shown, based on Example 5, the process of establishing a comprehensive heat pump operation rule base provided by the embodiment of the present invention includes the following steps:

[0094] S201211: Determine the data source for all heat pump operations, establish a JSON or XML data format standard, and standardize data units; categorize rules by usage scenario, environmental conditions, and operating mode, and prioritize each rule based on its actual impact;

[0095] S201212: Create an object for each rule in the rule library, including the rule ID, description, trigger condition, and execution action. In rule implementation, use a programming interface to extract data related to key information from the database. Use database views to integrate all relevant data into a single view. When the trigger condition is met, the relevant data is automatically pulled from the database and the relevant rule is executed.

[0096] S201213: After each rule execution, a feedback program is designed to write the execution results into the database, including timestamp, operation results, energy efficiency, and user feedback; a data record table is constructed to save the execution history; when multiple rules can be triggered under the same conditions, the effective rule is determined based on the set priority.

[0097] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first determines the data source of all heat pump operations, establishes the data format JSON or XML standard, and unifies the data units; classifies the rules according to the usage scenario, environmental conditions and operation mode, and sets the priority for each rule according to the actual impact; secondly, creates an object for each rule in the rule library, which includes the rule ID, description, and trigger condition (Example 1 Rule description is "When the indoor temperature is lower than 20℃, start the heating mode", and the trigger condition is "Indoor temperature < 20℃"; Rule description is "When the external humidity is greater than 60%, enable the dehumidification mode", and the trigger condition is "External humidity > 60%"; Rule description is "If the device If the cumulative operating time exceeds 500 hours, a maintenance reminder will be issued (the trigger condition is "equipment operating time > 500 hours") and an action will be executed. In rule implementation, a programming interface is used to extract data related to key information from the database, and a database view is used to integrate all relevant data into a single view. When the trigger condition is met, the relevant data will be automatically pulled from the database and the relevant rules will be executed. Finally, after each rule execution, a feedback program is designed to write the execution results to the database, including timestamps, operation results, energy efficiency, and user feedback. A data record table is constructed to save the execution history. When multiple rules can be triggered under the same condition, the effective rule is determined based on the set priority. Step S201211 of the above solution determines the data source and establishes standards to fully identify the various data sources required for heat pump operation (such as environmental sensors, user behavior, and meteorological data), ensuring the comprehensiveness and diversity of data collection. A unified JSON or XML format is used to enable seamless data transmission and use between different systems. The unified format reduces the complexity of data parsing and processing; the unification of all data units (for example, temperature is in degrees Celsius, humidity is in percentage, etc.) avoids errors caused by inconsistent units in calculations and rule applications, improving data consistency and reliability; rules are classified according to usage scenarios and conditions, making the rule base more organized; in addition, by setting priorities for rules, it ensures that the system can promptly select the optimal rule in complex situations and optimize the decision-making process. Significance: By clarifying the data source and establishing unified standards, data quality is guaranteed and the maintainability and reliability of the system are improved; the classification and priority setting of rules lay the foundation for subsequent automated decision-making, allowing the system to flexibly respond to complex scenarios, ensuring efficient operation and user comfort.Step S201212 creates rule objects and a data extraction mechanism. An object is created for each rule (including the rule ID, description, trigger conditions, and execution actions), forming a clear rule base structure that facilitates management, search, and execution. Dynamic data extraction is achieved through a database programming interface (API), enabling real-time data updates and application to rule execution, improving the system's flexibility and responsiveness. Database views are used to integrate related data, enabling one-stop data access, reducing repeated queries and data redundancy, and making rule execution more efficient. A trigger mechanism is established to automatically pull data from the database and execute the corresponding rules when conditions are met, ensuring timely and accurate rule execution. Significance: By creating rule objects and an efficient data extraction mechanism, the system is able to achieve real-time monitoring and intelligent decision-making. This not only improves the efficiency of heat pump operation, but also optimizes energy management, reduces the user's operational burden, and improves the user experience. Step S201213: Feedback mechanism and conflict management. After each rule is executed, the execution results (including timestamp, operation results, energy efficiency, and user feedback) are written to the database through a feedback program, forming a closed data loop and enabling real-time monitoring. A data record table is constructed to store the execution history, providing a basis for subsequent data analysis and rule optimization, enhancing the traceability of the system. When multiple rules can be triggered simultaneously, the effective rule is determined based on the set priority to avoid conflicts and make the system operation more stable. Significance: The implementation of the feedback mechanism enables the system to continuously learn and optimize, adjusting rules based on actual operating results. The adaptability enables the system to maintain excellent performance in a constantly changing environment and user needs. At the same time, the accumulation of execution history records provides data support for future optimization decisions.

[0098] In summary, this embodiment, through systematic data management, standardized rule base construction, and real-time data extraction and feedback mechanisms, enables a heat pump operation rule base to achieve more intelligent, efficient, and adaptive operation management. This not only improves the energy efficiency and user experience of the heat pump, but also lays a solid foundation for future system optimization and intelligent development.

[0099] Example 7: Figure 7 As shown, based on Example 5, the process of processing real-time monitoring data provided by the embodiment of the present invention includes the following steps:

[0100] S201221: Utilize data streams to continuously acquire new data and match it with the rules in the database; use fuzzy logic matching to compare the environmental conditions captured in the real-time data stream with the conditions in the rule base; determine the rules that meet the conditions and form a dynamic threshold combination;

[0101] S201222: Compare real-time environmental parameters (such as current indoor temperature, external temperature, humidity, etc.) with the conditions in the rule base, combine all rules that meet the conditions to form a new dynamic threshold set; use the currently collected real-time data to determine the current status, including key indicators such as energy consumption and indoor environmental comfort;

[0102] S201223: Generate adjustment suggestions based on real-time status using feedback information. If the outside temperature drops suddenly, it is recommended to increase the indoor target temperature by 1-2°C. Compare real-time monitoring data with the historical highest / lowest energy consumption data to assess whether the current operating efficiency is within an acceptable range. If deviations are found, determine whether the operating mode needs to be changed, and recommend that users make certain settings during a certain period of time.

[0103] The working principle and beneficial effects of the above technical solution are as follows: this embodiment first uses the data stream to continuously obtain new data and matches it with the rules in the database; according to the environmental conditions captured in the real-time data stream, fuzzy logic matching is used to compare with the conditions in the rule base; the rules that meet the conditions are determined and form a dynamic threshold combination; secondly, the real-time environmental parameters (such as the current indoor temperature, external temperature, humidity, etc.) are compared with the conditions in the rule base, and all the rules that meet the conditions are combined to form a new dynamic threshold set; the current state is determined using the currently collected real-time data, including key indicators such as energy consumption and indoor environmental comfort; finally, adjustment suggestions are generated based on the real-time state using feedback information. If the external temperature drops sharply, it is recommended to increase the indoor target temperature by 1-2°C; the real-time monitoring data is compared with the historical highest / lowest energy consumption data to evaluate whether the current operating efficiency is within an acceptable range. If deviation is found, it is determined whether the operating mode needs to be changed, and the user is advised to make certain settings during a certain period of time. Step S201221 of the above scheme involves real-time data acquisition and rule matching. New data is continuously acquired through data streams to ensure the system's responsiveness and adaptability, enabling it to promptly reflect environmental changes. Data is analyzed to enable the system to process imprecise or ambiguous inputs and dynamically determine applicable rules. The implications are: Rapid adaptation to environmental changes, such as timely adjustment of operating modes when external temperatures rise or fall; ensuring that suitable operating solutions can be found under different environmental conditions, optimizing heat pump performance through dynamic threshold combinations, and effectively improving equipment operating accuracy and efficiency. Step S201222 involves dynamic threshold combination formation and status evaluation. Real-time environmental parameters are compared with rule base conditions, enabling the system to obtain comprehensive operating status, such as energy consumption levels and indoor comfort levels. Rules that meet the conditions are integrated to generate a personalized dynamic threshold set that better suits the current environment and user needs. Significance Achieved: By comprehensively evaluating the current state, the system can more accurately understand the actual operating conditions of the device and subsequently formulate appropriate operating thresholds, further improving operational efficiency. Users can maintain extremely low energy consumption in a more comfortable environment. For example, at low external temperatures, the system can self-adjust to maintain the indoor temperature without requiring frequent manual adjustments by the user. Step S201223: Feedback information generation and user setting recommendations. Based on a comparison of real-time data and historical energy consumption data, the system can generate scientific adjustment recommendations, such as raising the indoor target temperature by 1-2°C. The system also uses historical data to evaluate current operating efficiency and, if deviations are detected, can make appropriate adjustments to the operating mode. Significance Achieved: Not only can the system respond to the external environment in real time, but it can also continuously evaluate and adjust operating modes to ensure that the device operates at the highest energy efficiency, directly saving users energy costs. Through intelligent recommendations, users can enjoy a comfortable indoor environment without excessive intervention. The system proactively adjusts to suit different usage scenarios, significantly improving user convenience and satisfaction.

[0104] In summary, this embodiment possesses efficient adaptive capabilities and intelligent decision-making capabilities. It can continuously optimize the heat pump's operating mode based on comprehensive analysis of real-time and historical data. This not only improves system efficiency, reduces energy consumption and user management costs, but also enhances user comfort, promoting the development of smart homes and environmental protection.

[0105] Example 8: Figure 8 As shown, based on Example 1, the switching control process of the blinds provided by the embodiment of the present invention includes the following steps:

[0106] S301: Obtaining a target state of the heat pump, whether it is in normal operation, shutdown, or in need of defrosting. Based on the target state, calling a corresponding blind control program. The blind control program can be closed or opened. Opening means adjusting the blind opening angle to 60°.

[0107] S302: When the instruction is for normal operation, the servo motor is controlled by the PWM signal to drive the shutter to adjust the opening angle to 60°. When the instruction is for shutdown or defrosting, the controller issues a shutter closing instruction, and the servo motor closes the shutter. In the shutdown state, the shutter is fully closed (0 degrees), and when defrosting is required, the shutter closes quickly.

[0108] S303: Regularly check the temperature and humidity to confirm whether the defrost operation is completed. When the temperature returns to the normal range (>5°C) and the humidity is lower than 50%, it is marked as defrost completion; the controller sends a reopening instruction to the blinds and adjusts the blinds through the servo motor; the blinds opening angle is automatically adjusted according to the wind speed and external temperature.

[0109] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first obtains the target state of the heat pump in normal operation, shutdown, or requiring defrost. According to the target state, the corresponding shutter control program is called. The shutter control program has closing and opening functions, and opening adjusts the shutter opening angle to 60°. Secondly, when the instruction is for adjustment during normal operation, the servo motor is controlled by a PWM signal to drive the shutter opening angle to 60°. When the instruction content is shutdown or defrost is required, the controller issues a shutter closing instruction, and the servo motor closes the shutter. In the shutdown state, the shutter is fully closed (0 degrees). When defrost is required, the shutter closes quickly. Finally, the temperature and humidity are regularly checked to confirm whether the defrost operation is complete. When the temperature returns to the normal range (>5°C) and the humidity is below 50%, it is marked as defrost completion. The controller issues a reopening instruction to the shutter, and the servo motor adjusts the shutter. The shutter opening angle is automatically adjusted according to the wind speed and the outside temperature. If the outside temperature rises rapidly or the wind speed is too high, the opening angle is reduced. In step S301 of the above scheme, the target state of the heat pump is obtained and the corresponding blind control program is called. By monitoring the operating state of the heat pump (normal, shutdown, defrost), the system ensures that it can accurately understand the current requirements. Based on different target states, the system can call the corresponding control program, laying the foundation for subsequent operations. Significance: It can flexibly adapt to different working conditions and adjust the blind state according to needs, enhancing the intelligence level of the system. By timely adjusting the blind opening and closing state, the heat pump can achieve optimal energy efficiency, ensure maximum performance, and reduce energy consumption. In step S302, the PWM signal controls the servo motor to open and close the blinds. The PWM (pulse width modulation) signal can precisely control the movement of the servo motor, adjusting the blind opening angle to the set 60° or fully closed (0°). When stopping or defrosting is required, the servo motor can quickly respond to the control command to ensure that the blinds close quickly, improving the system's ability to respond to changes. Significance: In the shutdown or defrosting state, quickly closing the shutters can protect the heat pump equipment and prevent the negative impact of external cold air on the system, thereby extending the service life of the equipment; by reasonably adjusting the shutter opening angle, the indoor temperature can be effectively managed, the comfort of the indoor environment can be guaranteed, and user needs can be met. Step S303 confirms whether the defrosting operation is completed and adjusts the shutters, regularly checks the temperature and humidity, and realizes real-time monitoring of the defrosting operation process to ensure timely judgment of whether the defrosting is completed under appropriate environmental conditions; dynamically adjusts the shutter opening angle according to the external environment (such as wind speed and temperature) to adapt to environmental changes and optimize the heat exchange effect. Significance: By monitoring the temperature and humidity status, the efficiency of the defrosting operation is ensured, and the normal operation of the heat pump is restored in time, thereby improving the operating efficiency of the entire system; dynamically adjusting the system status reflects the system's ability to adapt to environmental changes and improves the intelligence level of the heat pump system under different weather and load conditions.

[0110] In summary, this embodiment is used for regulating and controlling the heat pump and blinds, ensuring the safety, flexibility and energy efficiency of the system; it not only improves the operational stability of the equipment, but also creates a good environmental comfort for users, while enabling the system to achieve intelligent self-regulation under different environmental conditions.

[0111] Example 9: Figure 9 As shown, based on Example 8, the process of automatically adjusting the shutter angle according to wind speed and external temperature provided by the embodiment of the present invention includes the following steps:

[0112] S3031: Determine the impact of the current external environment on the shutter opening angle through a logical judgment model, and set a corresponding response strategy based on the combination of wind speed and temperature, including:

[0113] High temperature and low wind speed (temperature > 25℃ and wind speed < 1m / s): Set the blinds to 80° to encourage cool air to enter the room.

[0114] High temperature and high wind speed (temperature > 25°C and wind speed > 3m / s): Adjust the blinds to 30° to reduce the direct impact of external wind speed and maintain indoor comfort.

[0115] Low temperature, any wind speed (temperature < 5°C): shutters closed to 0° to prevent cold air from penetrating and retain warm air;

[0116] Moderate temperature (5°C to 25°C): Dynamically adjusts the opening angle (ranging from 30° to 60°) based on wind speed to optimize indoor temperature and air circulation;

[0117] S3032: After calculating the desired opening angle, the controller sends a control signal to the servo motor. The position sensor continuously monitors the actual opening angle of the blinds. If a deviation is detected, the controller automatically sends a correction command to adjust the blinds to the ideal state.

[0118] S3033: The controller continuously monitors the external environment and internal status, re-evaluating whether the blinds' opening angle needs to be adjusted each time the wind speed or temperature changes, and re-evaluating and confirming the status after each adjustment; it stores environmental data and corresponding opening angle settings to optimize the control strategy.

[0119] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first determines the impact of the current external environment on the opening angle of the blinds through a logical judgment model, and sets the corresponding response strategy according to the combination of wind speed and temperature, including: high temperature and low wind speed (temperature>25℃&wind speed<1m / s): set the blinds opening angle to 80° to promote the entry of cold air into the room; high temperature and high wind speed (temperature>25℃&wind speed>3m / s): adjust the blinds opening angle to 30° to reduce the direct impact of external wind speed and maintain indoor comfort; low temperature and any wind speed (temperature<5℃): close the blinds to 0° to prevent cold air from penetrating and keep warm air Moderate temperature (5°C to 25°C): Dynamically adjust the opening angle (ranging from 30° to 60°) according to the wind speed to optimize indoor temperature and air circulation; secondly, after calculating the required opening angle, the controller sends a control signal to the servo motor; the position sensor continuously monitors the actual opening angle of the blinds. If a deviation is found, the controller automatically sends a correction instruction to adjust the blinds to the ideal state; finally, the controller continuously monitors the external environment and internal status, and re-evaluates whether the opening angle of the blinds needs to be adjusted every time the wind speed or temperature changes, and performs status evaluation and confirmation after each adjustment; stores environmental data and corresponding opening angle settings to optimize the control strategy. Step S3031 of the above scheme sets the logical judgment model and response strategy. Through the logical judgment model, the system can evaluate the impact of external environmental factors (wind speed and temperature) on the adjustment of the blinds in real time, and thus adopt corresponding opening angle adjustment strategies; according to different temperature and wind speed combinations, set targeted opening angles to fine-tune the management of the indoor climate and avoid a "one-size-fits-all" control method. Significance achieved: By adjusting the opening angle of the blinds, the indoor temperature and air circulation can be effectively managed, the comfort of the living environment can be improved, and the needs of users can be met; ensuring effective isolation from external environmental influences under extreme climate conditions (such as high temperature and strong wind or low temperature) helps reduce the burden on the heating or cooling system, thereby achieving energy conservation and improved utilization efficiency. Step S3032: The control signal is sent to the servo motor and corrected in real time. The controller will generate a control signal based on the calculated ideal opening angle to ensure that the servo motor can accurately adjust the opening angle of the blinds; the actual opening angle is monitored by the position sensor. If a deviation from the set angle is found, the correction instruction can be automatically issued to make timely adjustments to ensure that the opening angle always remains within the desired range. Significance achieved: The automatic correction mechanism enhances the reliability and stability of the system, reduces control errors caused by mechanical errors, external force interference, etc., and ensures that the blinds perform consistently in different scenarios; under rapidly changing climate conditions, it can ensure the stability of the indoor environment and improve user comfort and satisfaction. Step S3033: Continuous monitoring and strategy optimization. The controller continuously monitors the external environment and internal status. When the wind speed or temperature fluctuates, it promptly re-evaluates the need to adjust the opening angle to achieve dynamic self-adaptation of the system. It stores environmental data and response strategies, and uses historical data to gradually optimize the control algorithm to improve response efficiency and adaptability.Significance achieved: It realizes intelligent environmental monitoring and can implement automatic and intelligent management based on real-time data, demonstrating a high level of technological innovation and smart home concept; by continuously optimizing the control strategy, the system can gradually improve energy efficiency and comfort, reduce energy waste, and at the same time improve the overall operating efficiency of the system to achieve long-term sustainability; it has the ability to optimize for different seasons, time or specific climatic conditions, making the system more adaptable and more in line with the laws of nature, and realizing a benign interaction between the environment and equipment.

[0120] In summary, the implementation of this embodiment forms a closed-loop control system, seamlessly integrating environmental perception, decision execution, feedback correction, and optimization. This demonstrates the combined effects of maintaining indoor comfort, energy conservation, and automated intelligent control. This demonstrates superior performance and user experience in practical applications.

[0121] Example 10: Figure 10 As shown, based on Examples 1 to 9, the protective device for improving the energy efficiency of a heat pump provided by the embodiments of the present invention includes:

[0122] The data acquisition module is responsible for obtaining real-time monitoring of the heat pump operating status through devices such as temperature sensors, pressure sensors, and air flow sensors, including monitoring data such as operating temperature, fan status, and defrost conditions;

[0123] The status judgment module is responsible for feeding back the monitoring data to the heat pump controller to determine whether the heat pump is in normal operation, shut down, or needs to be defrosted;

[0124] The result output module is responsible for adjusting the opening angle of the blinds when the heat pump is in normal operation; when the heat pump is shut down, powered off, or enters the defrost stage, it will issue a command to automatically close the protective device; when the heat pump reaches the defrost conditions, the blinds will automatically close; when the heat pump completes defrosting and detects the conditions for exiting defrost, the blinds will reopen and return to the fully open state, and the heat pump will operate normally.

[0125] The working principle and beneficial effects of the above technical solution are as follows: the data acquisition module of this embodiment obtains real-time monitoring of the heat pump operating status, including monitoring data such as operating temperature, fan status, and defrost conditions, through devices such as temperature sensors, pressure sensors, and airflow sensors; the status judgment module feeds the monitoring data back to the heat pump controller to determine whether the heat pump is in normal operation, shut down, or needs defrosting; the result output module adjusts the opening angle of the blinds when the heat pump is in normal operation; when the heat pump is shut down, powered off, or enters the defrost phase, it issues a command to automatically close the protective device; when the heat pump reaches the defrost conditions, the blinds are automatically closed; when the heat pump completes defrosting and detects the conditions for exiting defrost, the blinds are reopened to the fully open state, and the heat pump operates normally. The data acquisition module of the above solution obtains key parameters of the heat pump during operation (such as operating temperature, fan status, and defrost conditions) through devices such as temperature sensors, pressure sensors, and airflow sensors, realizing real-time monitoring of the heat pump performance; it can comprehensively collect and integrate different data required for heat pump operation, providing sufficient information support for the status judgment module. Significance achieved: Through accurate data collection, the controller can make more reasonable decisions based on the actual operating status, improving the operating efficiency and responsiveness of the heat pump; timely acquisition of operating data can warn of potential faults, ensure that the heat pump system operates in the best condition, and reduce maintenance costs and downtime. The status judgment module will analyze the monitoring data obtained from the data acquisition module to determine the current status of the heat pump (normal operation, shutdown, or need for defrosting); it can dynamically adjust the response strategy and issue corresponding instructions for different states to ensure the stable operation of the heat pump. Significance achieved: Through the status judgment module, the system can adapt to different operating environments and needs in real time to achieve intelligent control; accurately judging the operating status of the heat pump can avoid unnecessary operating losses, ensure that it works in the best condition, and thus improve overall energy efficiency. When the heat pump is operating normally, the output module adjusts the shutter angle in real time to optimize indoor ventilation and heat exchange. When the heat pump enters shutdown, power outage, or defrosting mode, it automatically issues a command to close protective devices, ensuring equipment safety and reducing energy consumption. When the heat pump completes defrosting and meets the conditions for resuming operation, it automatically opens the shutters to their fully open state, ensuring a quick and smooth return to normal operation. Significance: Adjusting the shutter angle effectively manages indoor temperature and humidity, improving user comfort. Proper shutter angle adjustment avoids energy waste, improves the heat pump's energy efficiency through optimal heat exchange, and effectively reduces energy consumption during defrosting. This reduces manual intervention, improves the system's intelligence and automation, and makes the heat pump more flexible and efficient in different operating states.

[0126] In the specific application of this embodiment, a control signal is sent to the servo motor, and the position sensor continuously monitors the actual opening angle of the blinds. The servo motor drives the opening angle of the blinds; the protective device for improving the energy efficiency of the heat pump is installed at the air inlet position of the heat pump fin heat exchanger, and adopts an electric openable and closable blind design. The blinds can be adjusted to a full opening angle according to the height of the fins and the air volume of the fan, so as to achieve uniform air volume above and below the fin heat exchanger. At the same time, it can be closed when the heat pump is not in use or defrosting, so as to protect the heat pump fin heat exchanger and reduce defrosting energy consumption; the protective device is installed on the sheet metal outside the heat exchanger and fixed with bolts or clamps to ensure stability. The device is opened and closed and the maximum full opening angle is determined by the control system of the heat pump; the protective device is installed on the sheet metal outside the heat exchanger and fixed with bolts or clamps to ensure stability; the opening and closing control and the maximum full opening angle are determined by the control system of the heat pump;

[0127] In summary, this embodiment achieves comprehensive monitoring and intelligent control of the heat pump system, ensuring the heat pump operates at peak efficiency. This not only improves the heat pump's energy efficiency and reduces operating costs, but also enhances user experience and satisfaction. This system lays the foundation for widespread application in building thermal management, smart homes, energy conservation, and emission reduction, and possesses significant practical application value and potential market prospects.

[0128] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention's equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A control method for a protective device for improving the energy efficiency of a heat pump, characterized in that: The following steps are involved: Obtain real-time monitoring of heat pump operating status; Feedback the monitoring data to the heat pump controller to determine whether the heat pump is in normal operation, shut down, or needs to be defrosted; When the heat pump is in normal operation, the shutters are adjusted to open at different angles. When the heat pump is shut down, powered off, or enters the defrost phase, a command is issued to automatically close the protective device. When the heat pump reaches the defrost condition, the shutters are automatically closed. When the heat pump completes defrosting and detects the conditions for exiting defrost, the shutters are reopened to return to the fully open state, and the heat pump operates normally. The process of acquiring monitoring data includes the following steps: Obtain the target requirements of the monitoring data, analyze the target requirements, and obtain the specific types of content corresponding to the target requirements; perform three-dimensional modeling on the heat pump, obtain the result position coordinates corresponding to the target requirements based on the three-dimensional modeling, and map the position coordinates with the target requirements to form a relationship mapping table; According to the relationship mapping table, the database searches for the device corresponding to the specific type and obtains the performance parameters of the device; the location coordinates are used as the unique identifier to distinguish the location of the device, and the performance parameters and coordinates of the device are added to the relationship mapping table to correspond to the target requirements; All devices are linked to form a monitoring data collection network to summarize the content of the monitoring data; The monitoring data acquisition network issues a startup command according to the preset collection cycle of the monitoring data. All devices start to initialize and collect the corresponding monitoring data. The location coordinates and monitoring data are packaged and sent to the heat pump. The controller determines the status of the heat pump.

2. The control method for the protective device for improving the energy efficiency of a heat pump according to claim 1, characterized in that: The process of determining the status of the heat pump includes the following steps: The controller receives real-time data from temperature sensors, pressure sensors, and airflow sensors, forming a multi-dimensional data packet containing key information such as operating temperature, fan status, ambient temperature, and compressor pressure. It also obtains multiple sets of thresholds set for the heat pump, which are used to define normal operation, shutdown, and defrost conditions. According to the key information of the data packet, a comparison is performed with one of the items corresponding to the multiple sets of thresholds, and the status of the heat pump is obtained according to the comparison result; Feedback the judgment result to the heat pump controller, and execute the corresponding action according to the program set in the controller; After each data collection, the controller cross-verifies the operating status and obtains the reliability of the operating status through data trend analysis.

3. The control method of the protective device for improving the energy efficiency of a heat pump according to claim 2, characterized in that: The process of obtaining multiple sets of thresholds for heat pump settings includes the following steps: Through a user-friendly interface, users can input the geographic location of the location, the expected season of use, the insulation performance of the building or facility, and historical usage patterns. This historical information is analyzed to determine the user's past usage habits and provide personalized demand forecasts based on seasonal changes and energy consumption patterns. Establish a rule engine between historical data and operating conditions, and automatically generate a dynamic combination of operating thresholds by analyzing historical data. After the heat pump has been running for a certain period of time according to the set threshold, the current energy efficiency and operating status are evaluated. If the operating efficiency or energy consumption in the evaluation results exceeds the corresponding evaluation threshold, the threshold configuration is automatically optimized and the evaluation result is adjusted to within the evaluation threshold. The operating temperature, fan status, ambient temperature and compressor pressure thresholds are set up into independent threshold groups according to the usage environment, grouped and managed, and the priority of each threshold is defined.

4. The control method for a protective device for improving heat pump energy efficiency according to claim 3, wherein: The priority of setting each threshold value includes that under extremely low temperature conditions, the threshold setting of ambient temperature takes precedence over the setting of operating pressure.

5. The control method of the protective device for improving the energy efficiency of a heat pump according to claim 1, characterized in that: The process of processing real-time monitoring data includes the following steps: Utilize data streams to continuously acquire new data and match it with the rules in the database; compare the environmental conditions captured in the real-time data stream with the conditions in the rule base; determine the rules that meet the conditions and form a dynamic threshold combination; Compare real-time environmental parameters with the conditions in the rule base, combine all rules that meet the conditions to form a new dynamic threshold set; use the currently collected real-time data to determine the current status; Leverage feedback to generate adjustment suggestions based on real-time status.

6. The control method for a protective device for improving heat pump energy efficiency according to claim 1, wherein: The switching control process of the blinds includes the following steps: Obtain the target state of the heat pump in normal operation, shutdown, or needing to defrost. According to the target state, call the corresponding shutter control program, which is closed and opened. When the instruction is for normal operation, the PWM signal controls the servo motor to drive the shutters to adjust the opening angle to 60 degrees. When the instruction is for shutdown or defrosting, the controller sends a shutter closing instruction, and the servo motor closes the shutters. In the shutdown state, the shutters are completely closed, that is, 0 degrees. When defrosting is required, the shutters close quickly. Regularly check the temperature and humidity to confirm whether the defrost operation is complete; the controller sends a reopening instruction to the blinds, and adjusts the blinds through the servo motor; the blinds opening angle is automatically adjusted according to the wind speed and outside temperature.

7. The control method of the protective device for improving the energy efficiency of a heat pump according to claim 6, characterized in that: When opening, the shutters are adjusted to an opening angle of 60°.

8. The control method for a protective device for improving heat pump energy efficiency according to claim 6, wherein: The process of automatically adjusting the blinds' opening angle based on wind speed and outside temperature includes the following steps: Through the logic judgment model, determine the impact of the current external environment on the shutter opening angle according to the combination of wind speed and temperature; After calculating the required opening angle, the controller sends a control signal to the servo motor. The position sensor continuously monitors the actual opening angle of the blinds. If any deviation is found, the controller automatically sends a correction command to adjust the blinds to the ideal state. The controller continuously monitors the external environment and internal status, re-evaluating whether the shutter opening angle needs to be adjusted every time the wind speed or temperature changes, and re-evaluating and confirming the status after each adjustment; storing environmental data and corresponding opening angle settings to optimize control strategies.

9. A protective device for improving the energy efficiency of a heat pump, wherein the control method for the protective device for improving the energy efficiency of a heat pump according to any one of claims 1 to 8 is implemented, characterized in that: Include: The data acquisition module is responsible for obtaining the real-time monitoring of the heat pump operating status; The status judgment module is responsible for feeding back the monitoring data to the heat pump controller to determine whether the heat pump is in normal operation, shut down, or needs to be defrosted; The result output module is responsible for adjusting the opening angle of the blinds when the heat pump is in normal operation; when the heat pump is shut down, powered off, or enters the defrost stage, it will issue a command to automatically close the protective device; when the heat pump reaches the defrost conditions, the blinds will automatically close; when the heat pump completes defrosting and detects the conditions for exiting defrost, the blinds will reopen and return to the fully open state, and the heat pump will operate normally.

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