Intelligent monitoring and automatic repair system for refrigeration equipment

Abstract

The invention discloses an intelligent monitoring and automatic repair system for refrigeration equipment, which belongs to the technical field of control systems and comprises an intelligent monitoring subsystem and an automatic repair subsystem for the refrigeration equipment. The refrigeration equipment intelligent monitoring subsystem comprises a real-time data acquisition module which acquires data in real time through sensors installed on all operation units of refrigeration equipment, and the data comprises at least one of temperature, pressure, humidity, current, voltage, water flow and electricity consumption. The multi-operation-unit data association module is used for integrating the real-time data of the real-time data acquisition module, mining and analyzing the relationship among the data, carrying out logic association and comparison on parameters of a plurality of operation units, identifying the potential dependency relationship and mutual influence among the operation units, and sending the potential dependency relationship and the mutual influence to the real-time data acquisition module; and associated faults are screened out through the potential dependency relationship and the mutual influence between the operation units. The method has the advantages of judging the damage type and complementing the monitoring vulnerability through the association between the data.

Description

Technical Field

[0001] The invention belongs to the technical field of control systems, and in particular relates to an intelligent monitoring and automatic repair reporting system for refrigeration equipment. Background Art

[0002] The intelligent monitoring and automatic repair system of refrigeration equipment is an indispensable part of the modern industrial and commercial environment. By integrating sensors, data analysis technology and automated processes, it ensures the continuous and stable operation of refrigeration equipment and responds quickly when equipment fails, reducing maintenance costs and downtime. It can not only improve the reliability and stability of equipment and reduce maintenance costs, but also optimize energy use and improve customer satisfaction.

[0003] Refrigeration equipment usually consists of multiple operating units working together to achieve its functions. These operating units play different roles in the refrigeration process. For example: Compressor unit: The compressor is the core component of the refrigeration system, responsible for compressing the low-temperature and low-pressure refrigerant gas into high-temperature and high-pressure gas, and promoting the circulation of the refrigerant in the system.

[0004] Condenser unit: The condenser is a device in the refrigeration system that cools and condenses the high-temperature and high-pressure refrigerant gas discharged from the compressor into liquid. The condenser usually dissipates heat through a cooling medium such as air or water to ensure that the refrigerant gas can be smoothly condensed into liquid.

[0005] Evaporator unit: The evaporator is the place in the refrigeration system where the refrigerant liquid evaporates and absorbs heat, reducing the temperature of the object being cooled by evaporation. In the evaporator, the refrigerant liquid exchanges heat with the medium to be cooled (such as air, water, etc.), and the refrigerant liquid evaporates into gas while absorbing heat.

[0006] Expansion valve (or throttle valve) unit: The expansion valve is a key component used to control the refrigerant flow and pressure in the refrigeration system. It reduces the cross-sectional area of ​​the refrigerant flow channel, causing the refrigerant to reduce pressure and flow when it flows from the high-pressure side to the low-pressure side, thereby achieving the evaporation and heat absorption process of the refrigerant.

[0007] Control system unit: The control system is the "brain" of the refrigeration equipment, responsible for monitoring and controlling the operating status of the refrigeration system. It can automatically adjust the working status of the compressor, expansion valve and other operating units according to the set temperature, humidity and other parameters to ensure the efficient and stable operation of the refrigeration system.

[0008] Other auxiliary units: In addition to the core operating units mentioned above, refrigeration equipment may also include some auxiliary units, such as liquid receivers, dry filters, oil separators, etc. These auxiliary units play the role of storage, filtration, separation, etc. in the refrigeration system to ensure the smooth and efficient circulation of refrigerant in the system.

[0009] The above operating units work together to realize the basic function of refrigeration equipment - transferring heat from low-temperature objects to high-temperature objects, thereby cooling the cooled objects.

[0010] However, when monitoring multiple operating units, there are the following problems: First, if a monitoring component (sensor) is damaged, it will lead to monitoring loopholes; Second, there are many types of damage to operating units (temperature, pressure, humidity, current, voltage, water flow, power consumption, etc. may all fail or be abnormal). If a monitoring element is configured for each type of damage, the cost will be high. However, if the configuration is not accurate, it will be difficult to accurately determine the type of damage. Summary of the invention

[0011] In view of the problems existing in the prior art, the present invention provides an intelligent monitoring and automatic repair reporting system for refrigeration equipment, which has the advantages of judging the damage type and filling the monitoring loopholes through the association between data, thereby solving the problems of the prior art.

[0012] The present invention is implemented in this way: a refrigeration equipment intelligent monitoring and automatic repair reporting system includes a central management subsystem, and the central management subsystem is signal-connected to the refrigeration equipment intelligent monitoring subsystem and the automatic repair reporting subsystem.

[0013] The refrigeration equipment intelligent monitoring subsystem includes: Real-time data acquisition module: collects data in real time through sensors installed on each operating unit of the refrigeration equipment, and the data includes at least one of temperature, pressure, humidity, current, voltage, water flow, and power consumption; Multi-operation unit data association module: Integrate the real-time data of the real-time data acquisition module, mine and analyze the relationship between each data, logically associate and compare the parameters of multiple operation units, identify the potential dependencies and mutual influences between the operation units, and screen out related faults through the potential dependencies and mutual influences between the operation units; The central management subsystem includes: Data analysis module: receiving data from the real-time data acquisition module and / or the multi-operation unit data association module, and determining whether the data exceeds a preset range. If the data exceeds the preset range, determining that a fault has occurred; Fault confirmation module: compares the associated faults of the multi-operation unit data association module with the results of the data analysis module to further confirm the fault type and cause of the refrigeration equipment; The automatic repair reporting subsystem comprises: Repair process automation module: Once a fault is identified, an early warning notification is issued and the repair process is automatically triggered, including sending a notification to the designated maintenance personnel, providing fault details and alternative solutions, and tracking the repair progress; Maintenance report module: Generates a detailed maintenance report after the maintenance is completed, including the cause of the failure, repair measures, maintenance time and cost.

[0014] As a preferred embodiment of the present invention, the multi-operation unit data association module includes: Real-time data collection and integration unit: Receives real-time data streams from the real-time data collection module and integrates them into a unified data warehouse or data lake. During the integration process, cleans and standardizes the data to ensure its quality and consistency. Data Relationship Mining Unit: Uses data mining and machine learning techniques to deeply explore potential associations and patterns in integrated real-time data, and identifies direct and indirect relationships between different equipment parameters through algorithm analysis; Logical association and comparison unit: After determining the potential relationships between data, these relationships are logically associated and compared. By comparing the parameter changes of different operating units, logical links between them are established, and potential dependencies and mutual influences are identified; Potential dependency identification unit: Based on the results of logical association and comparison, the potential dependencies between devices are identified. These dependencies are based on a certain parameter change pattern or behavior pattern, including how the parameter change of one device affects the operation of another device. Damage impact analysis unit: Analyze the specific impact of different types of damage to a certain operating unit on other related operating units. By comparing and analyzing the changes in related parameters before and after the damage, the potential impact of the damage on the overall performance of the system can be obtained; Intrinsic connection mining unit: Based on the results of damage impact analysis, the intrinsic connections between the operating units are further mined, including physical connections, logical dependencies, and operational collaboration.

[0015] As a preferred embodiment of the present invention, the multi-operation unit data association module includes a data verification and validation unit: using the identified data association relationship, the data verification and validation unit mutually verifies the data from different operation units.

[0016] As a preferred embodiment of the present invention, the intelligent monitoring and automatic repair reporting system for refrigeration equipment also includes a multi-operating unit fault sorting module, and the multi-operating unit fault sorting module signal is connected to the multi-operating unit data association module and the data analysis module. After receiving the fault data, the multi-operating unit fault sorting module sorts the fault data according to preset sorting rules, and then preferentially transmits high-priority faults to the data analysis module.

[0017] As a preferred embodiment of the present invention, the multi-operation unit fault sorting module is also signal-connected to the repair process automation module, and when a preset condition is triggered, the multi-operation unit fault sorting module directly instructs the repair process automation module to perform maintenance.

[0018] As a preferred embodiment of the present invention, the intelligent monitoring and automatic repair reporting system for refrigeration equipment also includes a maintenance effect feedback module, and the maintenance effect feedback module signal is connected to the multi-operation unit data association module and the data analysis module; the data of the multi-operation unit data association module is first sent to the maintenance effect feedback module to determine whether other faults associated with it are eliminated by repairing one fault, and then the data analysis module is notified.

[0019] As a preferred embodiment of the present invention, the maintenance effect feedback module is signal-connected to the repair process automation module; the signal of the repair process automation module is sent to the maintenance effect feedback module, and then to the data analysis module.

[0020] As a preferred embodiment of the present invention, the maintenance effect feedback module is connected to the multi-operation unit fault sorting module by signal, and the sorting of faults in the multi-operation unit fault sorting module can be adjusted in time according to the feedback of the maintenance effect feedback module. Compared with the prior art, the present invention has the following beneficial effects: The present invention sets up a multi-operation unit data association module, which has the following functions: For example, there are multiple damage modes for operating unit A, such as first-type damage, second-type damage, third-type damage, etc. Among them, the first-type damage will affect the parameters of operating units B and C, causing them to also display faults; the second-type damage will affect the parameters of operating units B and D, causing them to also display faults; by associating the parameters of operating units A, B, C, and D, the internal connection can be excavated.

[0021] If the parameters of operating unit B and operating unit C are monitored to be abnormal, even if the parameters of operating unit A are not monitored to be abnormal (it may be that the monitoring sensor of operating unit A is damaged), it is preliminarily inferred that it is caused by the first type of damage of operating unit A. Without this function, two maintenance personnel need to be dispatched to repair operating unit B and operating unit C respectively, which is difficult to achieve maintenance results on the one hand, and on the other hand, two maintenance personnel need to be occupied at the same time.

[0022] If it is monitored that operating units A, B, and C are damaged at the same time, it can be preliminarily determined that the first type of damage is caused by operating unit A, so that the location and cause of the damage can be quickly obtained, so as to carry out more targeted maintenance.

[0023] When a monitoring element (sensor) is damaged, the monitoring effect can still be achieved by checking whether other associated data is abnormal. Moreover, even if sensors are not installed in some parts, the monitoring effect can still be achieved through data association. If the number of monitoring elements is not reduced, the effect of data monitoring can be improved through data association. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The structure frame of the intelligent monitoring and automatic repair system for refrigeration equipment provided by the embodiment of the present invention is Figure 1 ; Figure 2 It is a structural frame of the multi-operation unit data association module provided by the embodiment of the present invention. Figure 1 ; Figure 3 It is a structural frame of the multi-operation unit data association module provided by the embodiment of the present invention. Figure 2 ; Figure 4 The structure frame of the intelligent monitoring and automatic repair system for refrigeration equipment provided by the embodiment of the present invention is Figure 2 ; Figure 5 The structure frame of the intelligent monitoring and automatic repair system for refrigeration equipment provided by the embodiment of the present invention is Figure 3 ; Figure 6 The structure frame of the intelligent monitoring and automatic repair system for refrigeration equipment provided by the embodiment of the present invention is Figure 4 ; Figure 7 The structure frame of the intelligent monitoring and automatic repair system for refrigeration equipment provided by the embodiment of the present invention is Figure 5 . DETAILED DESCRIPTION

[0025] In order to further understand the content, features and effects of the present invention, the following embodiments are given as examples and described in detail with reference to the accompanying drawings.

[0026] The structure of the present invention is described in detail below in conjunction with the accompanying drawings.

[0027] See also Figure 1 The embodiment of the present invention provides a refrigeration equipment intelligent monitoring and automatic repair system, including a central management subsystem, the central management subsystem is signal-connected to the refrigeration equipment intelligent monitoring subsystem and the automatic repair subsystem, and the refrigeration equipment intelligent monitoring subsystem includes: Real-time data acquisition module: collects data in real time through sensors installed on each operating unit of the refrigeration equipment, and the data includes at least one of temperature, pressure, humidity, current, voltage, water flow, and power consumption; Multi-operation unit data association module: Integrate the real-time data of the real-time data acquisition module, mine and analyze the relationship between each data, logically associate and compare the parameters of multiple operation units, identify the potential dependencies and mutual influences between the operation units, and screen out related faults through the potential dependencies and mutual influences between the operation units; The central management subsystem includes: Data analysis module: receiving data from the real-time data acquisition module and / or the multi-operation unit data association module, and determining whether the data exceeds a preset range. If the data exceeds the preset range, determining that a fault has occurred; Fault confirmation module: compares the associated faults of the multi-operation unit data association module with the results of the data analysis module to further confirm the fault type and cause of the refrigeration equipment; The automatic repair reporting subsystem comprises: Repair process automation module: Once a fault is identified, an early warning notification is issued and the repair process is automatically triggered, including sending a notification to the designated maintenance personnel, providing fault details and alternative solutions, and tracking the repair progress; Maintenance report module: Generates a detailed maintenance report after the maintenance is completed, including the cause of the failure, repair measures, maintenance time and cost.

[0028] The intelligent monitoring and automatic repair reporting system for refrigeration equipment connects the intelligent monitoring subsystem and the automatic repair reporting subsystem of refrigeration equipment through the central management subsystem to realize intelligent management. In the intelligent monitoring subsystem of refrigeration equipment, the real-time data acquisition module uses sensors to collect data of each operating unit of the refrigeration equipment in real time, such as temperature, pressure, etc. The multi-operating unit data association module integrates these data, analyzes the relationship between each data, identifies potential dependencies and mutual influences, and thus predicts possible faults. The data analysis module of the central management subsystem receives these data and determines whether they exceed the preset range. If they exceed the range, it is judged as a fault. The fault confirmation module further compares the associated faults of the multi-operating unit data association module and the results of the data analysis module to confirm the type and cause of the fault.

[0029] In the above settings, through real-time data collection and multi-operation unit data correlation analysis, the system can promptly detect and predict potential failures of refrigeration equipment, thereby avoiding losses caused by sudden equipment shutdown. At the same time, the automatic repair subsystem can quickly trigger the repair process after identifying the fault, promptly notify maintenance personnel and provide detailed fault information and alternative solutions, thereby improving maintenance efficiency and response speed. In addition, the detailed maintenance report generated after the maintenance is completed not only provides a reference for equipment maintenance, but also provides data support for subsequent fault prediction and prevention.

[0030] See also Figure 2, the multi-operation unit data association module includes: Real-time data collection and integration unit: Receives real-time data streams from the real-time data collection module and integrates them into a unified data warehouse or data lake. During the integration process, cleans and standardizes the data to ensure its quality and consistency. Data Relationship Mining Unit: Uses data mining and machine learning techniques to deeply explore potential associations and patterns in integrated real-time data, and identifies direct and indirect relationships between different equipment parameters through algorithm analysis; Logical association and comparison unit: After determining the potential relationships between data, these relationships are logically associated and compared. By comparing the parameter changes of different operating units, logical links between them are established, and potential dependencies and mutual influences are identified; Potential dependency identification unit: Based on the results of logical association and comparison, the potential dependencies between devices are identified. These dependencies are based on a certain parameter change pattern or behavior pattern, including how the parameter change of one device affects the operation of another device. Damage impact analysis unit (taking A operating unit as an example): Analyze the specific impact of different types of damage (such as first-type damage, second-type damage, etc.) of a certain operating unit (such as A) on other related operating units (such as B, C, D). By comparing and analyzing the changes in related parameters before and after the damage, the potential impact of the damage on the overall performance of the system is obtained; Intrinsic connection mining unit: Based on the results of damage impact analysis, the intrinsic connections between the operating units are further mined, including physical connections, logical dependencies, and operational collaboration.

[0031] Through the collaborative work of the above six units, the multi-operation unit data association module can comprehensively and deeply analyze the data relationship between multiple devices, providing strong support for system optimization and maintenance.

[0032] Exemplarily, the operation mode of the multi-operation unit data association module is as follows: For example, there are multiple damage modes for operating unit A, such as first-type damage, second-type damage, third-type damage, etc. Among them, the first-type damage will affect the parameters of operating units B and C, causing them to also display faults; the second-type damage will affect the parameters of operating units B and D, causing them to also display faults; by associating the parameters of operating units A, B, C, and D, the internal connection can be excavated.

[0033] There are many benefits: First, if the parameters of operating unit B and operating unit C are monitored to be abnormal, even if the parameters of operating unit A are not monitored to be abnormal (it may be that the monitoring sensor of operating unit A is damaged), it is preliminarily inferred that it is caused by the first type of damage to operating unit A. If this function is not available, two maintenance personnel need to be dispatched to repair operating unit B and operating unit C respectively. However, this method is difficult to achieve maintenance results on the one hand, and on the other hand, it requires two maintenance personnel to be occupied at the same time.

[0034] Second, if it is monitored that operating units A, B, and C are damaged at the same time, it can be preliminarily determined that the first type of damage is caused by operating unit A, so that the location and cause of the damage can be quickly obtained, so that more targeted maintenance can be carried out.

[0035] Third, when a monitoring element (sensor) is damaged, the monitoring effect can still be achieved by checking whether other associated data is abnormal. Moreover, even if sensors are not installed in some parts, the monitoring effect can still be achieved through data association. If the number of monitoring elements is not reduced, the effect of data monitoring can be improved through data association.

[0036] See also Figure 3 , the multi-operation unit data association module includes a data verification and validation unit: using the identified data association relationship, the data verification and validation unit mutually verifies the data from different operation units. For example, if two operation units should logically have a certain correspondence, but the actual data does not correspond, then this may indicate that one or both of the data are wrong. Data verification may also involve checking the integrity, consistency, accuracy and rationality of the data to ensure the reliability and validity of the data. For example, when the A1 parameter decreases, the A2, A3, and A4 parameters will inevitably decrease. If the A1 parameter decreases, the A2, A3, and A4 parameters remain unchanged, then it is preliminarily judged that an error occurred during the A1 parameter data processing or transmission. If one of the A2, A3, and A4 parameters decreases, it is preliminarily judged as a potential fault.

[0037] See also Figure 4 The intelligent monitoring and automatic repair reporting system for refrigeration equipment also includes a multi-operating unit fault sorting module, and the multi-operating unit fault sorting module signal is connected to the multi-operating unit data association module and the data analysis module. After receiving the fault data, the multi-operating unit fault sorting module sorts the fault data according to a preset sorting rule, and then transmits the high-priority faults to the data analysis module first.

[0038] These sorting rules may include multi-operation unit data relevance (e.g., giving priority to source faults among interrelated faults), fault severity, impact range, and fault frequency. The multi-operation unit fault sorting module provides efficient and accurate fault handling support for the refrigeration system monitoring and automatic repair system by collecting, sorting, and outputting fault data. For example, multiple interrelated faults are divided into a whole, and the sources of multiple faults, or possible sources, are analyzed. For example, fault 1, fault 2, fault 3, fault 4, and fault 5 are a group of interrelated faults. Among them, fault 1 will cause fault 2, fault 3, fault 4, and fault 5, so fault 1 is a possible source fault. When sorting, fault 1 is prioritized, and then fault 6, fault 7, etc. are sorted. After fault 1 is repaired, it is determined again whether the faults that cause fault 2, fault 3, fault 4, and fault 5 still exist. If they still exist or partially exist, the relevance of the remaining faults is continued to be matched (including the faults that still exist in fault 2, fault 3, fault 4, and fault 5), and then the source faults are continued to be prioritized. Specifically, a fault association database may be set up to store associated faults and corresponding source fault models. The remaining faults are matched with the associated faults and corresponding source fault models in the fault association database, so as to quickly determine the source fault.

[0039] Preferably, the multi-operating unit data association module sends the associated data to the multi-operating unit fault sorting module, and then the multi-operating unit fault sorting module sends the sorted data to the data analysis module, and then the data analysis module sends the analyzed data to the multi-operating unit data association module, and performs multiple cycles.

[0040] This cycle has the following effects: 1. Real-time fault identification and response: Through the multi-operation unit data association module, the system can integrate data from different operation units in real time and mine the potential dependencies and mutual influences between them. This enables the system to quickly identify other related operation units when a fault occurs and take corresponding measures.

[0041] The multi-operation unit fault sorting module prioritizes faults according to preset sorting rules to ensure that important and urgent faults are handled first, thereby improving the timeliness and accuracy of fault response.

[0042] 2. Fault prevention and prediction: By correlating and comparing real-time data, the system can identify potential failure modes between operating units, so as to take preventive measures in advance and avoid failures.

[0043] During the data loop processing, the data analysis module can continuously learn and optimize the logic and scope of fault judgment, further improving the accuracy of fault prediction.

[0044] 3. System optimization and decision support: Through multiple cycles of data processing, the system can accumulate a large amount of fault data and operation data, which can be used to optimize and improve the system and improve its stability and efficiency. The analysis results of the data analysis module can provide decision support for system managers, helping them better understand the operating status of the system and formulate more effective management strategies.

[0045] 4. Improve system maintainability: By sorting and analyzing fault data, the system can simplify complex fault problems into a series of orderly processing steps, reducing the difficulty and complexity of fault processing and improving the maintainability of the system.

[0046] During the fault handling process, the system can automatically generate fault reports and handling suggestions, reducing the need for manual intervention and improving the efficiency of fault handling.

[0047] See also Figure 5 Preferably, the multi-operation unit fault sorting module is also signal-connected to the repair process automation module. When a preset condition is triggered, the multi-operation unit fault sorting module directly instructs the repair process automation module to perform maintenance. For example, the preset condition may be that the central management subsystem (data analysis module and fault confirmation module) is paralyzed, or the connection between the multi-operation unit fault sorting module and the data analysis module is interrupted. With this setting, even if the central processing subsystem is damaged, orderly monitoring and fault repair can be performed.

[0048] See also Figure 6 The intelligent monitoring and automatic repair reporting system for refrigeration equipment also includes a maintenance effect feedback module, and the maintenance effect feedback module signal is connected to the multi-operation unit data association module and the data analysis module; the data of the multi-operation unit data association module is first sent to the maintenance effect feedback module to determine whether other faults associated with it are eliminated by repairing one fault, and then the data analysis module is notified.

[0049] Through this setting, a maintenance effect feedback module is set up, and this link is introduced between the multi-operation unit data association module and the data analysis module, which has the following effects: 1. Improve maintenance efficiency: The maintenance effect feedback module can quickly evaluate the effect of maintenance actions after maintenance, and determine whether the problems of other related devices have been successfully eliminated by solving the problem of one device. This timely feedback can help maintenance personnel adjust maintenance strategies more quickly and reduce the time and resources wasted due to multiple maintenance attempts.

[0050] 2. Enhanced system reliability: By confirming that the repair has actually solved the problem and eliminating potential related problems, the overall reliability of the system is enhanced. This helps prevent cascading failures caused by unresolved related problems, thereby ensuring stable operation of the refrigeration system.

[0051] 3. Optimize data analysis: After receiving notifications from the maintenance effect feedback module, the data analysis module can update its preset range and fault judgment logic based on more accurate maintenance results, which helps the data analysis module to more accurately identify potential problems in the future and improve the accuracy of fault prediction.

[0052] 4. Reduce maintenance costs: By promptly confirming the effectiveness of maintenance and eliminating related problems, additional costs caused by multiple repairs, downtime or equipment replacement can be reduced. In addition, optimized data analysis can also help predict and prevent potential failures, further reducing maintenance costs.

[0053] 5. Improve user experience: By improving system reliability and reducing failure rates, users will enjoy more stable and reliable cooling services. In addition, fast and effective maintenance response can also improve user satisfaction with maintenance services.

[0054] In summary, setting up a maintenance effect feedback module and introducing this link between the multi-operation unit data association module and the data analysis module can significantly improve the maintenance efficiency, reliability and user experience of the refrigeration system, while reducing maintenance costs and providing strong decision support for management. If the problem is not solved, the automatic repair subsystem will be notified for further maintenance.

[0055] See also Figure 7 The maintenance effect feedback module is signal-connected to the repair process automation module; the signal of the repair process automation module is sent to the maintenance effect feedback module, and then to the data analysis module.

[0056] Has the following effects: 1. Real-time monitoring and evaluation of maintenance results: The maintenance effect feedback module can monitor the results of the maintenance process in real time and evaluate whether the maintenance operation has effectively solved the equipment failure. This real-time monitoring and evaluation ensures the timeliness and accuracy of maintenance work and improves the maintenance efficiency of refrigeration equipment.

[0057] 2. Closed-loop management of data flow: From fault identification to maintenance notification, to maintenance effect feedback, and finally back to the data analysis module, a complete data flow closed loop is formed. This closed-loop management makes the maintenance process of the entire refrigeration equipment more systematic and standardized, ensuring the comprehensiveness and consistency of fault handling.

[0058] 3. Fault prevention and early warning: Through the maintenance effect feedback module, the operation data of the equipment after maintenance can be analyzed to determine whether there is a potential fault risk. If there is a risk, the data analysis module can issue a warning in time to avoid the recurrence of the fault and achieve early prevention of the fault.

[0059] 4. Scientific maintenance decision-making: The data provided by the maintenance effect feedback module can be used as input to the data analysis module to further analyze the causes and patterns of equipment failures. This data-based decision support makes maintenance decisions more scientific and reasonable, and improves the pertinence and effectiveness of maintenance work.

[0060] 5. Automation and intelligence of maintenance process: The coordinated use of the repair process automation module and the maintenance effect feedback module realizes the automation and intelligence of the refrigeration equipment maintenance process. This not only improves work efficiency and reduces labor costs, but also reduces the possibility of human errors and improves the quality and reliability of maintenance work.

[0061] Preferably, the maintenance effect feedback module is signal-connected to the multi-operation unit fault ranking module, and the ranking of faults in the multi-operation unit fault ranking module can be adjusted in a timely manner according to the feedback from the maintenance effect feedback module.

[0062] Working principle of the present invention: The multi-operation unit data association module integrates the real-time data of the real-time data acquisition module, mines and analyzes the relationship between each data, logically associates and compares the parameters of multiple operation units, identifies the potential dependencies and mutual influences between the operation units, and screens out related faults through the potential dependencies and mutual influences between the operation units. This system determines the damage type and fills the monitoring loopholes through the association between data.

[0063] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0064] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A refrigeration equipment intelligent monitoring and automatic repair reporting system, comprising a central management subsystem, wherein the central management subsystem is signal-connected to a refrigeration equipment intelligent monitoring subsystem and an automatic repair reporting subsystem, and characterized in that: The refrigeration equipment intelligent monitoring subsystem includes: Real-time data acquisition module: collects data in real time through sensors installed on each operating unit of the refrigeration equipment, and the data includes at least one of temperature, pressure, humidity, current, voltage, water flow, and power consumption; Multi-operation unit data association module: Integrate the real-time data of the real-time data acquisition module, mine and analyze the relationship between each data, logically associate and compare the parameters of multiple operation units, identify the potential dependencies and mutual influences between the operation units, and screen out related faults through the potential dependencies and mutual influences between the operation units; The central management subsystem includes: Data analysis module: receiving data from the real-time data acquisition module and / or the multi-operation unit data association module, and determining whether the data exceeds a preset range. If the data exceeds the preset range, determining that a fault has occurred; Fault confirmation module: compares the associated faults of the multi-operation unit data association module with the results of the data analysis module to further confirm the fault type and cause of the refrigeration equipment; The automatic repair reporting subsystem comprises: Repair process automation module: Once a fault is identified, an early warning notification is issued and the repair process is automatically triggered, including sending a notification to the designated maintenance personnel, providing fault details and alternative solutions, and tracking the repair progress; Maintenance report module: Generates a detailed maintenance report after the maintenance is completed, including the cause of the failure, repair measures, maintenance time and cost.

2. The intelligent monitoring and automatic repair system for refrigeration equipment according to claim 1, characterized in that: The multi-operation unit data association module includes: Real-time data collection and integration unit: Receives real-time data streams from the real-time data collection module and integrates them into a unified data warehouse or data lake. During the integration process, cleans and standardizes the data to ensure its quality and consistency. Data Relationship Mining Unit: Uses data mining and machine learning techniques to deeply explore potential associations and patterns in integrated real-time data, and identifies direct and indirect relationships between different equipment parameters through algorithm analysis; Logical association and comparison unit: After determining the potential relationships between data, these relationships are logically associated and compared. By comparing the parameter changes of different operating units, logical links between them are established, and potential dependencies and mutual influences are identified; Potential dependency identification unit: Based on the results of logical association and comparison, the potential dependencies between devices are identified. These dependencies are based on a certain parameter change pattern or behavior pattern, including how the parameter change of one device affects the operation of another device. Damage impact analysis unit: Analyze the specific impact of different types of damage to a certain operating unit on other related operating units. By comparing and analyzing the changes in related parameters before and after the damage, the potential impact of the damage on the overall performance of the system can be obtained; Intrinsic connection mining unit: Based on the results of damage impact analysis, the intrinsic connections between the operating units are further mined, including physical connections, logical dependencies, and operational collaboration.

3. The intelligent monitoring and automatic repair system for refrigeration equipment according to claim 2, characterized in that: The multi-operation unit data association module includes a data verification and validation unit: using the identified data association relationship, the data verification and validation unit mutually verifies the data from different operation units.

4. The intelligent monitoring and automatic repair system for refrigeration equipment according to claim 1, characterized in that: The intelligent monitoring and automatic repair reporting system for refrigeration equipment also includes a multi-operating unit fault sorting module, and the multi-operating unit fault sorting module signal is connected to the multi-operating unit data association module and the data analysis module. After receiving the fault data, the multi-operating unit fault sorting module sorts the fault data according to preset sorting rules, and then transmits high-priority faults to the data analysis module in priority.

5. The intelligent monitoring and automatic repair system for refrigeration equipment according to claim 4, characterized in that: The multi-operation unit fault sorting module is also signal-connected to the repair process automation module. When a preset condition is triggered, the multi-operation unit fault sorting module directly instructs the repair process automation module to perform maintenance.

6. The intelligent monitoring and automatic repair system for refrigeration equipment according to claim 5, characterized in that: The intelligent monitoring and automatic repair reporting system for refrigeration equipment also includes a maintenance effect feedback module, and the maintenance effect feedback module signal is connected to the multi-operation unit data association module and the data analysis module; the data of the multi-operation unit data association module is first sent to the maintenance effect feedback module to determine whether other faults associated with it are eliminated by repairing one fault, and then the data analysis module is notified.

7. The intelligent monitoring and automatic repair system for refrigeration equipment according to claim 6, characterized in that: The maintenance effect feedback module is signal-connected to the repair process automation module; the signal of the repair process automation module is sent to the maintenance effect feedback module, and then sent to the data analysis module.

8. The intelligent monitoring and automatic repair system for refrigeration equipment according to claim 7, characterized in that: The maintenance effect feedback module is signal-connected to the multi-operation unit fault sorting module, and can timely adjust the sorting of faults in the multi-operation unit fault sorting module according to the feedback of the maintenance effect feedback module.

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