Intelligent repair-requesting maintenance system based on equipment operation and maintenance knowledge graph

Abstract

The invention relates to the technical field of equipment repair and maintenance, in particular to an intelligent repair and maintenance system based on an equipment operation and maintenance knowledge graph, which comprises a data acquisition module, a data analysis module, a repair and maintenance module, a data storage module and a centralized management module, according to the method, remote control of workers is facilitated, the field workers carry out operation and maintenance according to the optimal maintenance solution in a mode of replacing operation codes or sending the optimal maintenance solution given by a model to the field workers, so that the equipment recovers to the operation state as soon as possible and carries out short-term normal work; by detecting and analyzing the operation data, the appearance data and the operation temperature and combining the knowledge graph and the fault false alarm unit, the analysis precision is improved, dust in the equipment is cleaned in the detection process, and the influence of the dust on electrical components is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment repair and maintenance, and in particular to an intelligent repair and maintenance system based on an equipment operation and maintenance knowledge graph. Background Art

[0002] Equipment repair reports are generally notified to maintenance personnel by phone or WeChat, informing them of the equipment failure and briefly describing the symptoms of the failure. This requires a high level of professional knowledge from the staff, and this type of communication makes it difficult to clearly describe the fault point and cause.

[0003] Therefore, there have emerged equipment repair methods, systems and storage media disclosed in the invention patent with publication number CN118710246A and an intelligent industrial equipment repair management system disclosed in the invention patent with publication number CN106502187B, which improve the accuracy of repair reports by combining detection and repair reports.

[0004] However, during use, it was found that the accuracy of determining the fault point and cause of the fault was poor only by analyzing and processing the operating data, and the analysis accuracy was also poor when the data was analyzed and processed only by the model. In addition, it was inconvenient to clean the dust on the circuits and electrical components during the detection process, resulting in poor practicality. Therefore, there is an urgent need for an intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph to improve the above problems. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention provides a method that is convenient for staff to remotely control the equipment. By replacing the operating code or sending the optimal maintenance solution given by the model to the on-site staff, the on-site staff performs maintenance operations according to the optimal maintenance solution, so that the equipment can be restored to operation as soon as possible and perform normal work in the short term; by detecting and analyzing the operating data, appearance data and operating temperature, and combining the knowledge graph and the fault false alarm unit, the analysis accuracy is improved, the dust in the equipment is cleaned during the detection process, and the impact of dust on electrical components is reduced. An intelligent repair and maintenance system based on the equipment operation and maintenance knowledge graph is provided.

[0006] The present invention provides an intelligent repair and maintenance system based on an equipment operation and maintenance knowledge graph, comprising:

[0007] Data acquisition module: acquires the equipment's operating data, appearance data, and temperature data;

[0008] Data analysis module: Analyzes and processes the acquired data to determine the equipment's fault points and causes, or predicts the equipment's operating status in the future based on the acquired data;

[0009] Repair and maintenance module: Report repairs to the staff and assist them in adjusting the equipment system to ensure normal operation of the equipment in the short term and ensure normal production;

[0010] Data storage module: Classify and store acquired data, analysis results, maintenance records, and system operation records;

[0011] Centralized management module: Centrally control and manage the data acquisition module, data analysis module, repair and maintenance module, and data storage module. When the staff logs into the system, their identity information is verified. During the operation of the system, the operation process of the system is recorded, which makes it easy to trace the problem when a problem occurs in the system.

[0012] Preferably, the data acquisition module includes:

[0013] Operation data acquisition unit: acquires the operation data of the equipment in real time;

[0014] Inspection data acquisition unit: acquires appearance data and temperature data of the equipment;

[0015] Preferably, the data analysis module includes:

[0016] Data preprocessing unit: adjusts the format of received data, cleans the data, identifies missing values ​​and outliers, adjusts the size and clarity of image data, and processes data redundancy;

[0017] AI Analysis Unit: This unit uses the PyTorch framework and convolutional neural networks to analyze and process acquired data using a trained model to determine the equipment's fault point and cause. It then combines the equipment's operation and maintenance knowledge graph to provide the optimal repair solution for the identified fault point or cause, or predict the equipment's operating status over the next period of time based on the acquired data.

[0018] Equipment operation and maintenance knowledge graph: This integrates operation and maintenance experience and prior knowledge to assist the AI ​​analysis unit in analyzing and processing acquired data. It also assists the fault false alarm unit in determining the accuracy of the analysis results, performing matching and proofreading, and providing the optimal maintenance solution.

[0019] Fault false alarm unit: compares the analyzed fault point and fault cause with the real-time operating status of the equipment to determine whether it is a fault false alarm. If so, it re-acquires the data, re-analyzes and processes the data, and notifies the staff through the repair and maintenance module;

[0020] Database: stores the training data of the model;

[0021] Preferably, the warranty maintenance module includes:

[0022] Data transmission unit: transmits the fault point and cause to the staff, and sends the optimal maintenance solution given by the model to the staff for confirmation, or receives data and commands from the staff. After the staff confirms the optimal maintenance solution, it can also send the optimal maintenance solution to the central control system of the faulty equipment, so that the on-site personnel can operate according to the optimal maintenance solution;

[0023] Independent data storage unit: backs up and stores the equipment's operating code. When a system failure occurs, the staff can edit and modify the backup code based on the fault point and cause, and then run the backup code to keep the equipment running normally in the short term, making it easier for staff to prepare maintenance tools and materials and rush to the site.

[0024] Preferably, the data storage module includes:

[0025] Data management unit: classifies and marks received data, and deletes data that exceeds the storage period;

[0026] Data storage unit: stores the separated and marked data for a limited time;

[0027] Preferably, the centralized management module includes:

[0028] Centralized management unit: Centralized control and management of data acquisition module, data analysis module, repair and maintenance module and data storage module;

[0029] Identity verification unit: When a staff member logs into the system, the identity information of the staff member is verified;

[0030] Operation recording unit: records the system operation process during system operation, which facilitates tracing the source of the problem when the system encounters a problem;

[0031] Preferably, the inspection data acquisition unit includes an inspection mechanism and a cleaning mechanism, and the cleaning mechanism is installed on the inspection mechanism; the appearance data and operating temperature data of multiple devices on the production line are acquired through the inspection mechanism, and the dust in the equipment is cleaned through the cleaning mechanism.

[0032] Preferably, the inspection mechanism includes a support arm, a guide rail, a baffle, an electric slider, a high-definition camera and a far-infrared sensor. The electric slider is interactively installed on the guide rail. The baffle protects the electric slider to reduce the contact between the staff and the electric slider. The support arm is installed on the electric slider, and the high-definition camera and the far-infrared sensor are both installed on the support arm. The position of the support arm is adjusted by sliding the electric slider on the guide rail, and then the position of the high-definition camera and the far-infrared sensor is adjusted by bending or stretching the support arm, so that the high-definition camera can take pictures of the appearance of the equipment, or extend into the interior of the equipment through the ventilation hole or reserved hole of the equipment through the support arm, and the operating temperature of the circuits and electrical components in the equipment is detected by the far-infrared sensor.

[0033] Preferably, the support arm includes multiple sets of universal joints, support seats, exhaust equipment, multiple sets of telescopic tubes, multiple sets of electric control valves and multiple sets of connecting pipes. Adjacent universal joints are rotatably connected to form a support structure. The support seat is rotatably mounted on the top of the top universal joint. The exhaust equipment is mounted on the electric slider. Multiple sets of telescopic tubes are respectively mounted on multiple universal joints, and the multiple sets of telescopic tubes are respectively located between the multiple sets of universal joints and between the support seat and the universal joint. Multiple sets of electric control valves are respectively mounted on the multiple sets of telescopic tubes. Multiple sets of connecting pipes are respectively mounted on On multiple sets of electric-controlled valves, and the bottoms of multiple sets of connecting pipes are connected to a set of exhaust ports of the exhaust equipment; air is discharged into the multiple sets of connecting pipes through the exhaust equipment, so that the air passes through the multiple sets of electric-controlled valves and enters the multiple sets of telescopic pipes respectively, and then the multiple sets of telescopic pipes are extended to keep the support mechanism upright, and then by closing the multiple sets of electric-controlled valves and opening one or more sets of electric-controlled valves, the air in one or more sets of electric-controlled valves is discharged through the exhaust equipment, so that one or more sets of electric-controlled valves are contracted, and then the support mechanism is bent, so that the support arm can be easily extended into the narrow position in the equipment.

[0034] Preferably, the cleaning mechanism includes a crushing box, a sealing cover, a driving motor, a gear, a scraper, a gear ring, an extrusion ring and a spring. The crushing box is installed at the bottom of the electric slider, the sealing cover is installed at the bottom of the crushing box, the driving motor is fixedly installed at the bottom of the sealing cover, the gear is installed on the output shaft of the driving motor, the scraper is rotatably installed on the sealing cover, and the top of the scraper extends to the inside of the crushing box, the top of the scraper is provided with multiple groups of air jet holes, the interior of the scraper is provided with an exhaust passage, the bottom end of the scraper is rotatably connected to another group of exhaust holes of the exhaust device, the gear ring is sleeved on the scraper, the side end of the gear ring is meshed with the side end of the gear, the extrusion ring is installed on the top of the crushing box through a spring, and the The interiors of multiple sets of universal joints and support seats are all provided with perforations, and the interior of the crushing box is communicated with the interior of the bottom universal joint; the sealing cover is opened to put dry ice into the crushing box, and the sealing cover is reset. The elasticity of the spring causes the extrusion ring to squeeze the dry ice downward, and at the same time, the drive motor is turned on, and the gear and gear ring are engaged to drive the scraper to rotate, scraping and crushing the dry ice to form dry ice particles. At the same time, the exhaust device discharges air into the scraper, and the air jet hole of the scraper discharges air into the crushing box. After that, the dry ice particles are mixed with the air and pass through the perforations of multiple sets of universal joints and support seats into the interior of the device. The dust on the circuit and electrical components is cleaned by the blown air and dry ice particles.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. By replacing the running code, it is convenient for staff to remotely control the equipment and restore it to running state as soon as possible for short-term work;

[0037] 2. Improve analysis accuracy by detecting and analyzing operating data, appearance data, and operating temperature, combined with knowledge graphs and fault false alarm units;

[0038] 3. Clean the dust inside the equipment during the testing process to reduce the impact of dust on electrical components. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a structural diagram of the intelligent repair and maintenance system based on the equipment operation and maintenance knowledge graph of the present invention;

[0040] Figure 2 It is a structural diagram of the data acquisition module of the present invention;

[0041] Figure 3 It is a structural diagram of the data analysis module of the present invention;

[0042] Figure 4 It is a structural diagram of the repair and maintenance module of the present invention;

[0043] Figure 5It is a structural diagram of the data storage module of the present invention;

[0044] Figure 6 It is a structural diagram of the centralized management module of the present invention;

[0045] Figure 7 This is a schematic diagram of the first axonometric structure of the inspection data acquisition unit of the present invention;

[0046] Figure 8 This is a second isometric structural diagram of the inspection data acquisition unit of the present invention;

[0047] Figure 9 This invention Figure 8 A schematic diagram of the enlarged structure of part A in FIG;

[0048] Figure 10 1 is a front view structural diagram of the inspection data acquisition unit of the present invention;

[0049] Figure 11 It is an enlarged right side cross-sectional schematic diagram of the crushing box and sealing cover structure of the present invention.

[0050] Markings in the accompanying drawings: 1. Guide rail; 2. Baffle; 3. Electric slider; 4. High-definition camera; 5. Far-infrared sensor; 6. Universal joint; 7. Support seat; 8. Exhaust equipment; 9. Telescopic tube; 10. Electric control valve; 11. Connecting pipe; 12. Crushing box; 13. Sealing cover; 14. Drive motor; 15. Gear; 16. Scraper; 17. Gear ring; 18. Extrusion ring; 19. Spring. DETAILED DESCRIPTION

[0051] To facilitate understanding of the present invention, the present invention will be described more fully below with reference to the accompanying drawings. The present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0052] Example 1

[0053] like Figures 1 to 11 As shown, an intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph includes:

[0054] Data acquisition module: acquires the equipment's operating data, appearance data, and temperature data;

[0055] Data analysis module: Analyzes and processes the acquired data to determine the equipment's fault points and causes, or predicts the equipment's operating status in the future based on the acquired data;

[0056] Repair and maintenance module: Report repairs to the staff and assist them in adjusting the equipment system to ensure normal operation of the equipment in the short term and ensure normal production;

[0057] Data storage module: Classify and store acquired data, analysis results, maintenance records, and system operation records;

[0058] Centralized management module: Centrally control and manage the data acquisition module, data analysis module, repair and maintenance module, and data storage module. When staff log in to the system, their identity information is verified. During the system operation, the system operation process is recorded, which facilitates tracing the source of the problem when the system has problems.

[0059] The data acquisition module includes:

[0060] Operation data acquisition unit: acquires the operation data of the equipment in real time;

[0061] Inspection data acquisition unit: acquires appearance data and temperature data of the equipment;

[0062] The data analysis module includes:

[0063] Data preprocessing unit: adjusts the format of received data, cleans the data, identifies missing values ​​and outliers, adjusts the size and clarity of image data, and processes data redundancy;

[0064] AI Analysis Unit: This unit uses the PyTorch framework and convolutional neural networks to analyze and process acquired data using a trained model to determine the equipment's fault point and cause. It then combines the equipment's operation and maintenance knowledge graph to provide the optimal repair solution for the identified fault point or cause, or predict the equipment's operating status over the next period of time based on the acquired data.

[0065] Equipment operation and maintenance knowledge graph: This integrates operation and maintenance experience and prior knowledge to assist the AI ​​analysis unit in analyzing and processing acquired data. It also assists the fault false alarm unit in determining the accuracy of the analysis results, performing matching and proofreading, and providing the optimal maintenance solution.

[0066] Fault false alarm unit: compares the analyzed fault point and fault cause with the real-time operating status of the equipment to determine whether it is a fault false alarm. If so, it re-acquires the data, re-analyzes and processes the data, and notifies the staff through the repair and maintenance module;

[0067] Database: stores the training data of the model;

[0068] The warranty maintenance module includes:

[0069] Data transmission unit: transmits the fault point and cause to the staff, and sends the optimal maintenance solution given by the model to the staff for confirmation, or receives data and commands from the staff. After the staff confirms the optimal maintenance solution, it can also send the optimal maintenance solution to the central control system of the faulty equipment, so that the on-site personnel can operate according to the optimal maintenance solution;

[0070] Independent data storage unit: backs up and stores the equipment's operating code. When a system failure occurs, the staff can edit and modify the backup code based on the fault point and cause, and then run the backup code to keep the equipment running normally in the short term, making it easier for staff to prepare maintenance tools and materials and rush to the site.

[0071] The data storage module includes:

[0072] Data management unit: classifies and marks received data, and deletes data that exceeds the storage period;

[0073] Data storage unit: stores the separated and marked data for a limited time;

[0074] The centralized management module includes:

[0075] Centralized management unit: Centralized control and management of data acquisition module, data analysis module, repair and maintenance module and data storage module;

[0076] Identity verification unit: When a staff member logs into the system, the identity information of the staff member is verified;

[0077] Operation recording unit: records the system operation process during system operation, which facilitates tracing the source of the problem when the system encounters a problem;

[0078] The inspection data acquisition unit includes an inspection mechanism and a cleaning mechanism, and the cleaning mechanism is installed on the inspection mechanism;

[0079] The inspection mechanism includes a support arm, a guide rail 1, a baffle 2, an electric slider 3, a high-definition camera 4 and a far-infrared sensor 5. The electric slider 3 is interactively installed on the guide rail 1. The baffle 2 protects the electric slider 3 to reduce the contact between the staff and the electric slider 3. The support arm is installed on the electric slider 3. The high-definition camera 4 and the far-infrared sensor 5 are both installed on the support arm;

[0080] The support arm includes multiple groups of universal joints 6, a support seat 7, an exhaust device 8, multiple groups of telescopic tubes 9, multiple groups of electric control valves 10 and multiple groups of connecting tubes 11. Adjacent universal joints 6 are rotatably connected to form a support structure. The support seat 7 is rotatably mounted on the top of the top universal joint 6. The exhaust device 8 is mounted on the electric slider 3. Multiple groups of telescopic tubes 9 are respectively mounted on the multiple universal joints 6, and the multiple groups of telescopic tubes 9 are respectively located between the multiple groups of universal joints 6 and between the support seat 7 and the universal joint 6. Multiple groups of electric control valves 10 are respectively mounted on the multiple groups of telescopic tubes 9. Multiple groups of connecting tubes 11 are respectively mounted on the multiple groups of electric control valves 10, and the bottoms of the multiple groups of connecting tubes 11 are all connected to a group of exhaust ports of the exhaust device 8.

[0081] The cleaning mechanism includes a crushing box 12, a sealing cover 13, a driving motor 14, a gear 15, a scraper 16, a gear ring 17, an extrusion ring 18 and a spring 19. The crushing box 12 is installed at the bottom of the electric slider 3, the sealing cover 13 is installed at the bottom of the crushing box 12, the driving motor 14 is fixedly installed at the bottom of the sealing cover 13, the gear 15 is installed on the output shaft of the driving motor 14, the scraper 16 is rotatably installed on the sealing cover 13, and the top end of the scraper 16 extends into the interior of the crushing box 12, the top of the scraper 16 is provided with multiple groups of air injection holes, the interior of the scraper 16 is provided with an exhaust passage, the bottom end of the scraper 16 is rotatably connected to another group of exhaust holes of the exhaust device 8, the gear ring 17 is sleeved on the scraper 16, the side end of the gear ring 17 is meshed and connected with the side end of the gear 15, the extrusion ring 18 is installed at the top of the crushing box 12 by the spring 19, the interiors of the multiple groups of universal joints 6 and the support seat 7 are all provided with through holes, and the interior of the crushing box 12 is communicated with the interior of the bottom universal joint 6;

[0082] The operation data of the equipment is acquired in real time through the operation data acquisition unit, and the air is discharged into multiple groups of connecting pipes 11 through the exhaust device 8, so that the air passes through multiple groups of electric-controlled valves 10 and enters multiple groups of telescopic tubes 9 respectively. Then, the multiple groups of telescopic tubes 9 are extended to keep the support mechanism upright, and then the multiple groups of electric-controlled valves 10 are closed and one or more groups of electric-controlled valves 10 are opened, and the air in one or more groups of electric-controlled valves 10 is discharged through the exhaust device 8, so that one or more groups of electric-controlled valves 10 are contracted, and then the support mechanism is bent, so that the support arm can be easily extended into the narrow position in the equipment, so that the high-definition camera 4 can shoot the appearance of the equipment, and the operating temperature of the circuits and electrical components in the equipment can be detected by the far-infrared sensor 5 to obtain the appearance data and operating temperature data of the equipment. Then, the format of the received data is adjusted by the data preprocessing unit, and the data is cleaned, missing values ​​and abnormal values ​​are identified, and the size and clarity of the image data are adjusted. The degree is adjusted, and then the data redundancy is processed. The AI ​​analysis unit adopts the PyTorch framework and convolutional neural network, and analyzes and processes the acquired data with a qualified trained model in conjunction with the equipment operation and maintenance knowledge graph to determine the equipment's fault point and fault cause, or predict the equipment's operating status in the future based on the acquired data. The fault false alarm unit compares the analyzed fault point and fault cause with the equipment's real-time operating status to determine whether it is a fault false alarm. If so, the data is acquired again and re-analyzed and processed. If so, the staff is notified through the repair and maintenance module. Then, when the fault is a device system fault, the staff edits and modifies the backup stored code according to the fault point and fault cause, and then enables the device to run the backup stored code, so that the equipment can operate normally in the short term, making it convenient for the staff to prepare maintenance tools and materials to rush to the site, thereby improving the convenience of repair and maintenance, and reducing equipment downtime.

[0083] Example 2

[0084] like Figures 1 to 11 As shown, an intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph, based on Example 1, further includes:

[0085] The cleaning mechanism includes a crushing box 12, a sealing cover 13, a driving motor 14, a gear 15, a scraper 16, a gear ring 17, an extrusion ring 18 and a spring 19. The crushing box 12 is installed at the bottom of the electric slider 3, the sealing cover 13 is installed at the bottom of the crushing box 12, the driving motor 14 is fixedly installed at the bottom of the sealing cover 13, the gear 15 is installed on the output shaft of the driving motor 14, the scraper 16 is rotatably installed on the sealing cover 13, and the top end of the scraper 16 extends into the interior of the crushing box 12, the top of the scraper 16 is provided with multiple groups of air injection holes, the interior of the scraper 16 is provided with an exhaust passage, the bottom end of the scraper 16 is rotatably connected to another group of exhaust holes of the exhaust device 8, the gear ring 17 is sleeved on the scraper 16, the side end of the gear ring 17 is meshed and connected with the side end of the gear 15, the extrusion ring 18 is installed at the top of the crushing box 12 by the spring 19, the interiors of the multiple groups of universal joints 6 and the support seat 7 are all provided with through holes, and the interior of the crushing box 12 is communicated with the interior of the bottom universal joint 6;

[0086] The operation data of the equipment is acquired in real time through the operation data acquisition unit, and the air is discharged into the multiple groups of connecting pipes 11 through the exhaust device 8, so that the air passes through the multiple groups of electric control valves 10 and enters the multiple groups of telescopic tubes 9 respectively. Then the multiple groups of telescopic tubes 9 are stretched to keep the support mechanism upright, and then the multiple groups of electric control valves 10 are closed and one or more groups of electric control valves 10 are opened, and the air in one or more groups of electric control valves 10 is discharged through the exhaust device 8, so that one or more groups of electric control valves 10 are contracted, and then the support mechanism is bent, so that the support arm can be extended into the narrow position in the equipment to make the high-definition camera 4 takes a picture of the appearance of the device, and uses the far-infrared sensor 5 to detect the operating temperature of the circuits and electrical components in the device, and obtains the appearance data and operating temperature data of the device. At the same time, the drive motor 14 is turned on, and the gear 15 is engaged with the gear ring 17 to drive the scraper 16 to rotate, and the dry ice is scraped into pieces to form dry ice particles. At the same time, the exhaust device 8 discharges air into the scraper 16, and the air jet hole of the scraper 16 discharges the air into the crushing box 12. After that, the dry ice particles are mixed with the air and pass through the perforations of the multiple sets of universal joints 6 and the support seat 7 into the interior of the device, and are blown out by the blown air and Dry ice particles clean dust from circuits and electrical components. The data preprocessing unit then adjusts the format of the received data, cleans the data, identifies missing values ​​and outliers, adjusts the size and clarity of the image data, and processes data redundancy. The AI ​​analysis unit uses the PyTorch framework and convolutional neural network to analyze and process the acquired data using a trained model in conjunction with the equipment operation and maintenance knowledge graph. This analysis identifies the equipment's fault point and cause, or predicts the equipment's operating status for a period of time based on the acquired data. The false alarm unit compares the analyzed fault point and cause with the equipment's real-time operating status to determine whether it is a false alarm. If so, the data is retrieved and re-analyzed. If so, the repair and maintenance module notifies personnel. If the fault is a system fault, personnel edit and modify the backup stored code based on the fault point and cause, then enable the equipment to run the backup stored code, ensuring normal operation in the short term. This allows personnel to prepare repair tools and materials and rush to the site, thereby improving the convenience of repair reporting and maintenance and reducing equipment downtime.

[0087] The intelligent repair and maintenance system based on the equipment operation and maintenance knowledge graph of the present invention has common mechanical installation, connection or setting methods, which can be implemented as long as they can achieve their beneficial effects; the exhaust equipment 8 is composed of an exhaust pump and a vacuum pump; the electric slider 3, high-definition camera 4, far-infrared sensor 5, exhaust equipment 8 and drive motor 14 of the intelligent repair and maintenance system based on the equipment operation and maintenance knowledge graph of the present invention are purchased on the market, and technicians in this industry only need to install and operate them according to the accompanying instruction manual, without the need for technical personnel in this field to pay creative labor.

[0088] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph, characterized in that: include: Data acquisition module: acquires the operation data, appearance data and temperature data of the equipment; Data analysis module: Analyze and process the acquired data to determine the equipment's fault point and cause, or predict the equipment's operating status in the future based on the acquired data; Repair and maintenance module: report repairs to the staff and assist the staff to adjust the equipment system to ensure normal operation of the equipment in the short term and normal production; Data storage module: Classify and store the acquired data, analysis results, maintenance records, and system operation records; Centralized management module: Centrally control and manage the data acquisition module, data analysis module, repair and maintenance module, and data storage module. When the staff logs into the system, their identity information is verified. During the operation of the system, the operation process of the system is recorded. When problems occur in the system, it is convenient to trace the source of the problem.

2. The intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph according to claim 1, characterized in that: The data acquisition module comprises: Operation data acquisition unit: acquire the operation data of the equipment in real time; Inspection data acquisition unit: acquires the appearance data and temperature data of the equipment.

3. The intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph according to claim 1, characterized in that: The data analysis module includes: Data preprocessing unit: adjusts the format of received data, cleans the data, identifies missing values ​​and outliers, adjusts the size and clarity of image data, and processes data redundancy; AI analysis unit: Using the PyTorch framework and convolutional neural network, the acquired data is analyzed and processed with a qualified training model to determine the equipment's fault point and cause. In addition, the optimal maintenance solution is given for the confirmed fault point or fault principle in combination with the equipment operation and maintenance knowledge graph, or the operating status of the equipment in the future is predicted based on the acquired data. Equipment operation and maintenance knowledge graph: Integrates operation and maintenance experience and prior knowledge, assists the AI ​​analysis unit to analyze and process the acquired data, assists the fault false alarm unit to judge the accuracy of the analysis results, and performs matching and proofreading to provide the optimal maintenance solution; Fault false alarm unit: compares the analyzed fault point and fault cause with the real-time operating status of the equipment to determine whether it is a fault false alarm. If so, reacquire the data, re-analyze and process the data, and notify the staff through the repair and maintenance module; Database: Stores the training data of the model.

4. The intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph according to claim 1, characterized in that: The warranty maintenance module includes: Data transmission unit: transmits the fault point and fault cause to the staff, and sends the optimal maintenance solution given by the model to the staff for confirmation, or receives data and commands issued by the staff. After the staff confirms the optimal maintenance solution, the optimal maintenance solution can be sent to the central control of the faulty equipment, so that the on-site personnel can operate according to the optimal maintenance solution; Independent data storage unit: backs up and stores the equipment's operating code. When the equipment's system fails, the staff edits and modifies the backup stored code according to the fault point and cause, and then makes the equipment run the backup stored code, so that the equipment can operate normally in a short period of time, making it convenient for the staff to prepare maintenance tools and materials and rush to the site.

5. The intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph according to claim 1, characterized in that: The data storage module comprises: Data management unit: classifies and marks the received data, and deletes the data that exceeds the storage period; Data storage unit: stores the separated and marked data for a limited time.

6. The intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph according to claim 1, characterized in that: The centralized management module includes: Centralized management unit: Centralized control and management of data acquisition module, data analysis module, repair and maintenance module and data storage module; Identity verification unit: When a staff member logs into the system, the staff member's identity information is verified; Operation recording unit: During the operation of the system, the operation process of the system is recorded, which facilitates tracing the source of the problem when a problem occurs in the system.

7. The intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph as claimed in claim 2, characterized in that: The inspection data acquisition unit comprises an inspection mechanism and a cleaning mechanism, and the cleaning mechanism is installed on the inspection mechanism.

8. The intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph as claimed in claim 7, characterized in that: The inspection mechanism comprises a support arm, a guide rail (1), a baffle (2), an electric slider (3), a high-definition camera (4) and a far-infrared sensor (5); the electric slider (3) is interactively mounted on the guide rail (1); the baffle (2) protects the electric slider (3) to reduce contact between the staff and the electric slider (3); the support arm is mounted on the electric slider (3); and the high-definition camera (4) and the far-infrared sensor (5) are both mounted on the support arm.

9. The intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph as claimed in claim 8, characterized in that: The support arm comprises a plurality of sets of universal joints (6), a support seat (7), an exhaust device (8), a plurality of sets of telescopic tubes (9), a plurality of sets of electric control valves (10) and a plurality of sets of connecting tubes (11). Adjacent universal joints (6) are rotatably connected to form a support structure. The support seat (7) is rotatably mounted on the top of the top universal joint (6). The exhaust device (8) is mounted on the electric slider (3). The plurality of sets of telescopic tubes (9) are respectively mounted on the plurality of universal joints (6). The plurality of sets of telescopic tubes (9) are respectively located between the plurality of sets of universal joints (6) and between the support seat (7) and the universal joint (6). The plurality of sets of electric control valves (10) are respectively mounted on the plurality of sets of telescopic tubes (9). The plurality of connecting tubes (11) are respectively mounted on the plurality of sets of electric control valves (10). The bottoms of the plurality of connecting tubes (11) are respectively connected to a set of exhaust ports of the exhaust device (8).

10. The intelligent repair and maintenance system based on equipment operation and maintenance knowledge graph according to claim 9, characterized in that: The cleaning mechanism comprises a crushing box (12), a sealing cover (13), a driving motor (14), a gear (15), a scraper (16), a gear ring (17), an extrusion ring (18) and a spring (19); the crushing box (12) is mounted on the bottom of the electric slider (3); the sealing cover (13) is mounted on the bottom of the crushing box (12); the driving motor (14) is fixedly mounted on the bottom of the sealing cover (13); the gear (15) is mounted on the output shaft of the driving motor (14); the scraper (16) is rotatably mounted on the sealing cover (13); and the top end of the scraper (16) extends to the crushing box (12). ), a plurality of groups of air jet holes are arranged on the top of the scraper (16), an exhaust passage is arranged inside the scraper (16), the bottom end of the scraper (16) is rotatably connected to another group of exhaust holes of the exhaust device (8), a gear ring (17) is mounted on the scraper (16), the side end of the gear ring (17) is meshedly connected to the side end of the gear (15), an extrusion ring (18) is installed on the top of the crushing box (12) through a spring (19), the insides of the plurality of groups of universal joints (6) and the support seat (7) are all provided with perforations, and the inside of the crushing box (12) is communicated with the inside of the bottom universal joint (6).

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