Data center power distribution machine room inspection system based on inspection robot

Abstract

The invention discloses a data center power distribution machine room inspection system based on an inspection robot, and relates to the technical field of automation control, the system realizes accurate management of a power distribution room through area division and serial number labeling, and operation data of power distribution equipment is collected in real time through a sensor group in the inspection robot. The data is transmitted to the terminal processing module through a wireless network for preprocessing and storage, and the state of the power distribution equipment is analyzed based on the health data set. And calculating a task priority coefficient Rwh according to the health index Sjk of the power distribution equipment and the travel distance jl of the inspection robot, and in combination with a robot optimization scheduling strategy, avoiding path conflicts and ensuring priority inspection of the power distribution equipment. The system also has a robot electric quantity optimization function, can plan a charging path according to the electric quantity condition, and carries out charging monitoring and strategy adjustment. According to the system, the automation and intelligence level of data center power distribution machine room inspection is improved, and the reliability and safety of power distribution equipment operation are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of automation control technology, and in particular to a data center power distribution room inspection system based on an inspection robot. Background Art

[0002] In today's rapidly developing society, the application of intelligent and automated technologies is increasingly penetrating into various industries, especially in the fields of energy management and equipment monitoring. With the continuous advancement of industrialization and digitalization, the safety and stability of the distribution room, as an important hub for power distribution, are crucial to the operation of the entire power system. The traditional manual inspection method has gradually revealed its limitations due to its high labor intensity, low efficiency and susceptibility to human factors. Therefore, enterprises are in urgent need of introducing emerging technologies to improve inspection efficiency and the accuracy of equipment monitoring.

[0003] Although the inspection robot system provides many conveniences in the inspection work of the distribution room, there are still some shortcomings in the current inspection path planning and conflict scheduling. First, the traditional inspection system often relies on manual scheduling, which leads to uneven task distribution, which can easily cause excessive inspections in some areas and insufficient inspections in other areas. In addition, in emergency situations, the existing system may not judge the priority of tasks quickly and accurately, resulting in delayed detection of important equipment, making it difficult to detect potential faults and hidden dangers in a timely manner. Finally, if the inspection robot fails to fully consider dynamic environmental factors when planning its path, it may cause deviations and collisions in the inspection route, further reducing the efficiency and safety of the inspection. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a data center power distribution room inspection system based on an inspection robot, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a data center power distribution room inspection system based on an inspection robot, comprising an area division module, a data acquisition module, a terminal processing module, an inspection analysis module, a robot scheduling module and a robot power optimization module;

[0006] The area division module is used to divide the power distribution room into n areas, deploy inspection robots in each area, and mark each area and the inspection robots in the area with serial numbers, so that the sensors installed on the inspection robots can perceive the surrounding environment and power distribution equipment in real time;

[0007] The data acquisition module monitors the operating data of the power distribution equipment on the inspection path in real time through the integrated sensors and acquisition devices installed inside the inspection robot, and transmits the operating data to the terminal processing module in real time;

[0008] The terminal processing module is used to receive the operation data in real time, perform preprocessing, obtain the operation health data group, and then store the operation data group in real time in the relational database MySQL;

[0009] The inspection analysis module is used to perform summary calculations based on the acquired operation health data group to obtain the health index Sjk of the power distribution equipment. When the operation of the power distribution equipment is abnormal, the power distribution equipment is marked as the first priority detection, and then the health index Sjk of the power distribution equipment and the distance jl that the inspection robot should travel are combined for summary calculation to obtain the task priority coefficient Rwh, and a preliminary evaluation is performed with the preset task priority threshold M, and then a secondary evaluation mechanism is triggered based on the evaluation results;

[0010] The robot scheduling module is used to summarize and calculate the inspection path conflict coefficient Lct when the inspection robot needs to be scheduled according to the initial assessment, and summarize and calculate it with the obtained task priority coefficient Rwh to obtain the comprehensive scheduling optimization coefficient DUY, and perform a secondary assessment with the preset scheduling conflict threshold A, and generate a scheduling signal according to the assessment result;

[0011] The robot power optimization module is used to automatically plan a route to return to the charging station for charging when the patrol robot is low on power, monitor the hardware status of the patrol robot, and perform self-diagnosis and maintenance regularly.

[0012] Preferably, the area division module includes an area division unit and a robot operation unit;

[0013] The area division unit is used to divide the power distribution room into n areas according to the spatial layout and the type of power distribution equipment, reserve n inspection channels between the power distribution equipment in each area, deploy an inspection robot, and then mark each area and the inspection robot in the area with serial numbers;

[0014] The robot operation unit scans the environment in real time through the laser radar sensors and ultrasonic sensors installed at the front end, top end, left end, right end and rear end of the robot, senses the positions of obstacles, walls and power distribution equipment, and inspects pre-set inspection tasks and routes through crawler drive. When a dynamic obstacle is sensed, the dynamic window method DWA is used to adjust the path in real time, continuously correct the motion trajectory, and avoid collision and deviation from the route.

[0015] Preferably, the data acquisition module includes a data acquisition unit and a data transmission unit;

[0016] The data acquisition unit monitors the operating data of the power distribution equipment on the inspection path in real time through the integrated sensor group and acquisition equipment installed in the inspection robot;

[0017] The integrated sensor group includes a piezoelectric vibration sensor, a humidity sensor, a current sensor, a voltage sensor, a power sensor, a temperature sensor, a flow sensor and a pressure sensor;

[0018] The acquisition equipment includes an insulation resistance tester;

[0019] The vibration frequency zd is directly collected by a vibration sensor;

[0020] The cable insulation resistance dz is directly collected by an insulation resistance tester;

[0021] The environmental humidity change rate sd is directly collected by a humidity sensor;

[0022] The equipment load fluctuation rate fz is obtained by monitoring the current, voltage and power changes through a current sensor, a voltage sensor and a power sensor, and calculating the ratio of the standard deviation of the power to the average power;

[0023] The data transmission unit is used to transmit the operation data collected by the inspection robot to the terminal processing module through the wireless network. If the data is not successfully transmitted, the inspection robot automatically resends the data.

[0024] Preferably, the terminal processing module includes a data preprocessing unit and a data storage unit;

[0025] The preprocessing unit is used to receive the operation data in real time, and perform data filtering, abnormal data cleaning, noise removal and normalization processing to obtain the operation health data group;

[0026] The operation health data group includes equipment vibration frequency zd, cable insulation resistance dz, environmental humidity change rate sd and equipment load fluctuation rate fz;

[0027] The data storage unit is used to store the acquired operation health data group in the relational database MySQL through the API interface, adopt incremental backup and differential backup strategies, combine the cloud backup service to back up the operation health data group for long-term storage, and extract the operation health data group in the relational database MySQL in real time through the database port.

[0028] Preferably, the inspection and analysis module includes a power distribution equipment health analysis unit, a task priority analysis unit and a task priority evaluation unit;

[0029] The power distribution equipment health analysis unit is used to perform summary calculation based on the acquired operation health data group to obtain the power distribution equipment health index Sjk;

[0030] The power distribution equipment health index Sjk is calculated by the following formula:

[0031]

[0032] In the formula, ln represents the logarithmic function;

[0033] The task priority analysis unit determines the normal and abnormal operation of the distribution equipment according to the health index Sjk of the distribution equipment through the abnormal operation data of the relay distribution equipment in the relational database MySQL. When the distribution equipment operates abnormally, the distribution equipment is marked as the first priority detection distribution equipment, and data detection of the distribution equipment is required immediately. At this time, the terminal control system displays the position of the inspection robot and the position of the distribution equipment in the spatial map data of the distribution room, and then calculates the required travel distance jl from the inspection robot to the distribution equipment in combination with the inspection path, and summarizes and calculates the required travel distance jl and the obtained health index Sjk of the distribution equipment to obtain the task priority coefficient Rwh;

[0034] The task priority coefficient Rwh is calculated by the following formula:

[0035]

[0036] In the formula, Sjk j Indicates the health index of the jth power distribution device. The jth power distribution device is the first priority detection power distribution device. i，j represents the required travel distance from the i-th inspection robot to the j-th power distribution equipment, jl i+1，j represents the required travel distance from the i+1th inspection robot to the jth power distribution equipment, (jl i，j -jl i+1，j ) represents the difference in required distances between the ith inspection robot and the i+1th inspection robot, Ww represents the wth weight coefficient of the health index Sjk of the jth distribution device, Qq represents the qth weight coefficient of the difference in required distances between the ith inspection robot and the i+1th inspection robot to the jth distribution device, and c represents the correction constant.

[0037] Preferably, the task priority evaluation unit is used to evaluate the difference in task urgency scheduling between the first priority power distribution equipment j and the inspection robot with sequence number i in the area n and the inspection robot with sequence number i+1 in the area n+1, and to preset the task priority threshold M based on the average value of the historical power distribution equipment health data, and to make a preliminary comparative evaluation with the obtained task priority coefficient Rwh, and to generate a secondary evaluation mechanism based on the evaluation results. The specific evaluation scheme is as follows;

[0038] When the task priority coefficient Rwh≤task priority threshold M, it means that the distance jl from the inspection robot i in area n to the power distribution equipment j is less than the distance jl from the inspection robot i+1 in area n+1 to the power distribution equipment j. At this time, there is no need to mobilize other robots for inspection, and the inspection robot in the current area will perform the inspection;

[0039] When the task priority coefficient Rwh>task ​​priority threshold M, the distance jl between the inspection robot i in area n and the distribution equipment j is greater than the distance jl between the inspection robot i+1 in area n+1 and the distribution equipment j. At this time, a first scheduling signal is generated and sent to the inspection robot scheduling control system. After a comprehensive analysis by the task priority evaluation unit on the detection status of all robots around the first-priority distribution equipment in their current nth area and the distance to this distribution equipment, the robots are mobilized to inspect the first-priority distribution equipment and the second evaluation mechanism is triggered.

[0040] Preferably, the robot scheduling module includes a path analysis unit and a comprehensive scheduling analysis unit;

[0041] The path analysis unit is used to analyze the distance between the inspection robot and the power distribution equipment and the distance between the inspection robot i and the inspection robot n through the spatial map data when the inspection robot needs to be dispatched according to the initial assessment, and summarize and calculate the inspection path conflict coefficient Lct;

[0042] The inspection path conflict coefficient Lct is calculated by the following formula:

[0043]

[0044] Where, T i and T n They represent the time it takes for inspection robot i and inspection robot n to reach the power distribution equipment in the target area, T diff Indicates the time difference peak value set by the system, D i，n represents the distance between inspection robot i and inspection robot n, D min Indicates the safety distance valley value set between inspection robots, O i，n represents the overlap between the inspection areas of robot i and robot n, and 0≤O i，n ≤1,O i，n When it is equal to 0, it means there is no overlap. i，n When equal to 1, it indicates complete overlap.

[0045] Preferably, the comprehensive scheduling analysis unit includes a scheduling optimization calculation unit and a comprehensive scheduling evaluation unit;

[0046] The scheduling optimization calculation unit is used to perform summary calculation based on the acquired task priority coefficient Rwh and inspection path conflict coefficient Lct to obtain a comprehensive scheduling optimization coefficient DUY;

[0047] The comprehensive scheduling optimization coefficient DUY is calculated by the following formula:

[0048]

[0049] Wherein, k1 and k2 are weight coefficients of the task priority coefficient Rwh and the inspection path conflict coefficient Lct respectively, and k1+k2=1, and the specific values ​​are set by the user according to the actual situation.

[0050] Preferably, the comprehensive scheduling evaluation unit is used to perform a secondary comparative evaluation of the preset scheduling conflict threshold A and the obtained comprehensive scheduling optimization coefficient DUY, perform an in-depth evaluation of the inspection robot path after the inspection scheduling, and generate relevant scheduling information based on the evaluation results. The specific evaluation scheme is as follows;

[0051] When the comprehensive scheduling optimization coefficient DUY is less than the scheduling conflict threshold A, it means that there are one or more robots that detect the power distribution equipment at the same time. At this time, a second scheduling signal is generated and transmitted to the inspection robot scheduling control system. The inspection robot that performs repeated inspections is obtained according to the inspection record of the power distribution equipment, and the inspection path of each inspection robot is transmitted to the inspection analysis module for iterative evaluation to re-optimize the inspection path.

[0052] When the comprehensive scheduling optimization coefficient DUY ≥ the scheduling conflict threshold A, it means that the robot inspection path is normal, and normal monitoring is maintained at this time.

[0053] Preferably, the robot power optimization module is used to continuously monitor the power of the inspection robot, record the current power consumption rate and the progress of the inspection task. When the power is lower than the 20% alarm value, the inspection robot will automatically trigger a low-power alarm, calculate the remaining drivable distance of the inspection robot based on the remaining power, and initiate the instruction to return to the charging pile. Combined with the planned inspection path and the current distance between the inspection robot and the charging pile, a safe and optimized charging path for the inspection robot is automatically planned. During the charging process, the charging progress and battery temperature are dynamically monitored. When charging abnormalities are found, the charging strategy is automatically adjusted to avoid battery damage.

[0054] The present invention provides a data center power distribution room inspection system based on an inspection robot. It has the following beneficial effects:

[0055] (1) The system's area division module effectively divides the power distribution room into multiple inspection areas, deploys inspection robots in each area, and labels each area and robot with a serial number. This method not only optimizes the layout of the inspection area, but also ensures that the inspection robot can flexibly avoid obstacles according to the preset inspection path. When the inspection robot is working, the lidar sensor and ultrasonic sensor scan the surrounding environment in real time, can promptly identify obstacles, walls and the location of distribution equipment, and adjust the path through the crawler drive system to avoid collisions and deviations from the established route. This efficient inspection mechanism greatly improves the coverage and response speed of distribution equipment monitoring, and effectively reduces the risk of human errors and accidents during the inspection process.

[0056] (2) The system uses the terminal processing module to filter, clean up abnormal data and normalize the real-time collected operation data, obtain the operation health data group, and store it in the relational database MySQL, which provides a reliable basis for subsequent data analysis. The inspection analysis module uses these health data to calculate the health index Sjk and task priority coefficient Rwh of the distribution equipment, so that the system can automatically adjust the inspection strategy according to the health status and distance of the distribution equipment. When the distribution equipment operates abnormally, it will immediately mark the distribution equipment as the first priority detection distribution equipment to ensure timely data detection. This intelligent analysis and processing mechanism significantly improves the accuracy and timeliness of the distribution equipment operation status monitoring and reduces the risks caused by potential failures.

[0057] (3) The design of the robot scheduling module and power optimization module of the system further enhances the intelligence and autonomy of the system. The robot scheduling module realizes efficient scheduling of the inspection robot by analyzing the task priority coefficient Rwh and the inspection path conflict coefficient Lct. When the robot needs to be scheduled, the system can calculate the distance from each robot to the target power distribution equipment and generate a scheduling signal to ensure the timely completion of the task. In addition, the power optimization module can monitor the power status of the inspection robot in real time and record the power consumption rate. When the power is lower than 20%, the system automatically triggers an alarm and plans a safe charging path to ensure that the robot can safely return to the charging pile for charging. The intelligent management mechanism not only improves the inspection efficiency and the safety of the distribution equipment operation, but also provides a strong guarantee for the long-term stable operation of the data center. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The present invention is a schematic diagram of the process flow of a data center power distribution room inspection system based on an inspection robot. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] Example 1

[0061] See also Figure 1 The present invention provides a data center power distribution room inspection system based on an inspection robot. To achieve the above purpose, the present invention is implemented through the following technical solutions: including a region division module, a data acquisition module, a terminal processing module, an inspection analysis module, a robot scheduling module and a robot power optimization module;

[0062] The area division module is used to divide the power distribution room into n areas, deploy inspection robots in each area, and mark each area and the inspection robots in the area with serial numbers, so that the sensors installed on the inspection robots can perceive the surrounding environment and power distribution equipment in real time;

[0063] The data acquisition module monitors the operating data of the power distribution equipment on the inspection path in real time through the integrated sensors and acquisition devices installed inside the inspection robot, and transmits the operating data to the terminal processing module in real time;

[0064] The terminal processing module is used to receive the operation data in real time, perform preprocessing, obtain the operation health data group, and then store the operation data group in real time in the relational database MySQL;

[0065] The inspection analysis module is used to perform summary calculations based on the acquired operation health data group to obtain the health index Sjk of the power distribution equipment. When the operation of the power distribution equipment is abnormal, the power distribution equipment is marked as the first priority detection, and then the health index Sjk of the power distribution equipment and the distance jl that the inspection robot should travel are combined for summary calculation to obtain the task priority coefficient Rwh, and a preliminary evaluation is performed with the preset task priority threshold M, and then a secondary evaluation mechanism is triggered based on the evaluation results;

[0066] The robot scheduling module is used to summarize and calculate the inspection path conflict coefficient Lct when the inspection robot needs to be scheduled according to the initial assessment, and summarize and calculate it with the obtained task priority coefficient Rwh to obtain the comprehensive scheduling optimization coefficient DUY, and perform a secondary assessment with the preset scheduling conflict threshold A, and generate a scheduling signal according to the assessment result;

[0067] The robot power optimization module is used to automatically plan a route to return to the charging station for charging when the patrol robot is low on power, monitor the hardware status of the patrol robot, and perform self-diagnosis and maintenance regularly.

[0068] In this embodiment, the distribution room is divided into multiple inspection areas through the area division module, ensuring that each area has a dedicated inspection robot responsible for inspection, which significantly improves the coverage and accuracy of distribution equipment monitoring. With the help of sensors, the inspection robot can perceive the environment and the status of the distribution equipment in real time, providing reliable real-time data support for the data acquisition module, ensuring the comprehensiveness and real-time nature of data acquisition. The terminal processing module can pre-process the operating data received in real time, and store the processed data in the relational database MySQL, providing efficient data storage and retrieval functions. At the same time, the inspection analysis module can perform intelligent scheduling according to the health status and inspection requirements of the distribution equipment by summarizing and calculating the health index Sjk and task priority coefficient Rwh of the distribution equipment. When the distribution equipment is operating abnormally, it is automatically marked as the first priority detection object to ensure timely response. This data-driven analysis capability makes the inspection work more intelligent and can effectively reduce the failure rate and downtime of the distribution equipment. The robot scheduling module can intelligently optimize the scheduling strategy of the inspection robot according to the task priority coefficient Rwh and the inspection path conflict coefficient Lct, ensuring that each robot works efficiently and collaboratively, reducing inspection conflicts and resource waste. At the same time, the power optimization module monitors the power status of the inspection robot and automatically plans the charging path when the power is low to ensure that the robot is always available. These improvements not only improve the inspection efficiency and the safety of power distribution equipment, but also provide important guarantees for the long-term stable operation of the data center. Compared with traditional manual inspections or simple automatic inspections, the intelligence level of distribution equipment management and the overall operation and maintenance efficiency have been significantly improved.

[0069] Example 2

[0070] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the area division module includes an area division unit and a robot operation unit;

[0071] The area division unit is used to divide the power distribution room into n areas according to the spatial layout and the type of power distribution equipment, reserve n inspection channels between the power distribution equipment in each area, deploy an inspection robot, and then mark each area and the inspection robot in the area with serial numbers;

[0072] The robot operation unit scans the environment in real time through the laser radar sensors and ultrasonic sensors installed at the front end, top end, left end, right end and rear end of the robot, senses the positions of obstacles, walls and power distribution equipment, and inspects pre-set inspection tasks and routes through crawler drive. When a dynamic obstacle is sensed, the dynamic window method DWA is used to adjust the path in real time, continuously correct the motion trajectory, and avoid collision and deviation from the route.

[0073] In this embodiment, a scientific division is made based on the spatial layout of the distribution room and the type of distribution equipment, ensuring that each area is managed by a dedicated inspection robot. The reserved inspection channel optimizes the inspection path and reduces interference and obstruction during the inspection process. At the same time, the inspection robot can scan the surrounding environment in real time and accurately identify obstacles, walls and the location of distribution equipment through the integrated laser radar and ultrasonic sensors. This real-time perception capability enables the inspection robot to have flexible dynamic obstacle avoidance capabilities when performing tasks, and can adjust the path through the dynamic window method DWA to ensure stable operation in complex environments. This series of designs not only improves the inspection efficiency, but also ensures the safety of distribution equipment, significantly reduces the risk of collision and the probability of damage to distribution equipment during the inspection process, thereby effectively improving the overall operation and maintenance level and the degree of intelligence in the management of distribution equipment.

[0074] Example 3

[0075] This embodiment is explained in Example 2. Please refer to Figure 1 ,Specifically: the data acquisition module includes a data acquisition unit and a data transmission unit;

[0076] The data acquisition unit monitors the operating data of the power distribution equipment on the inspection path in real time through the integrated sensor group and acquisition equipment installed in the inspection robot;

[0077] The integrated sensor group includes a piezoelectric vibration sensor, a humidity sensor, a current sensor, a voltage sensor, a power sensor, a temperature sensor, a flow sensor and a pressure sensor;

[0078] The acquisition equipment includes an insulation resistance tester;

[0079] The data transmission unit is used to transmit the operation data collected by the inspection robot to the terminal processing module through the wireless network. If the data is not successfully transmitted, the inspection robot automatically resends the data.

[0080] In this embodiment, by installing an integrated sensor group on the inspection robot, the operating status of the power distribution equipment can be fully monitored, and a comprehensive health assessment of the power distribution equipment can be achieved. This multi-parameter monitoring capability not only improves the richness of the data, but also can promptly detect potential problems and prevent the occurrence of power distribution equipment failures. Secondly, the collected real-time data is transmitted to the terminal processing module via a wireless network to ensure that the data can quickly enter the analysis and processing links. When data transmission fails, the inspection robot will automatically resend the data to ensure the integrity and reliability of the data. This intelligent data collection and transmission mechanism not only improves the inspection efficiency, but also provides a solid foundation for subsequent health analysis of power distribution equipment, thereby ensuring efficient operation and maintenance and safe management of the data center.

[0081] Example 4

[0082] This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically: the terminal processing module includes a data preprocessing unit and a data storage unit;

[0083] The preprocessing unit is used to receive the operation data in real time, and perform data filtering, abnormal data cleaning, noise removal and normalization processing to obtain the operation health data group;

[0084] The operation health data group includes equipment vibration frequency zd, cable insulation resistance dz, environmental humidity change rate sd and equipment load fluctuation rate fz;

[0085] The data storage unit is used to store the acquired operation health data group in the relational database MySQL through the API interface, adopt incremental backup and differential backup strategies, combine the cloud backup service to back up the operation health data group for long-term storage, and extract the operation health data group in the relational database MySQL in real time through the database port.

[0086] In this embodiment, the accuracy and reliability of the acquired operation health data group are ensured by real-time data reception, data filtering, exception cleaning, noise removal and normalization. This process not only improves the data quality, but also provides a solid foundation for subsequent analysis. The indicators contained in the operation health data group reflect the operating status of the distribution equipment. The data storage unit realizes efficient connection with the relational database MySQL through the API interface, adopts incremental and differential backup strategies, and combines cloud backup services to ensure the security and traceability of the data. Such a design not only realizes the convenience of long-term storage and real-time extraction, but also ensures the persistence and security of the data, thereby providing strong data support for health monitoring and fault warning of distribution equipment, and ultimately improving the level of intelligent management and operation and maintenance efficiency.

[0087] Example 5

[0088] This embodiment is explained in Example 4. Please refer to Figure 1 ,Specifically: the inspection and analysis module includes a power distribution equipment health analysis unit, a task priority analysis unit and a task priority evaluation unit;

[0089] The power distribution equipment health analysis unit is used to perform summary calculation based on the acquired operation health data group to obtain the power distribution equipment health index Sjk;

[0090] The power distribution equipment health index Sjk is calculated by the following formula:

[0091]

[0092] In the formula, ln represents the logarithmic function;

[0093] The task priority analysis unit determines the normal and abnormal operation of the distribution equipment according to the health index Sjk of the distribution equipment through the abnormal operation data of the relay distribution equipment in the relational database MySQL. When the distribution equipment operates abnormally, the distribution equipment is marked as the first priority detection distribution equipment, and data detection of the distribution equipment is required immediately. At this time, the terminal control system displays the position of the inspection robot and the position of the distribution equipment in the spatial map data of the distribution room, and then calculates the required travel distance jl from the inspection robot to the distribution equipment in combination with the inspection path, and summarizes and calculates the required travel distance jl and the obtained health index Sjk of the distribution equipment to obtain the task priority coefficient Rwh;

[0094] The task priority coefficient Rwh is calculated by the following formula:

[0095]

[0096] In the formula, Sjk j Indicates the health index of the jth power distribution device. The jth power distribution device is the first priority detection power distribution device. i，j represents the required travel distance from the i-th inspection robot to the j-th power distribution equipment, jl i+1，j represents the required travel distance from the i+1th inspection robot to the jth power distribution equipment, (jl i，j -jl i+1，j ) represents the difference in required distances between the ith inspection robot and the i+1th inspection robot, Ww represents the wth weight coefficient of the health index Sjk of the jth distribution device, Qq represents the qth weight coefficient of the difference in required distances between the ith inspection robot and the i+1th inspection robot to the jth distribution device, and c represents the correction constant.

[0097] The task priority evaluation unit is used to evaluate the difference in task urgency scheduling between the first priority power distribution equipment j and the inspection robot with sequence number i in the area n and the inspection robot with sequence number i+1 in the area n+1, and to preset the task priority threshold M based on the average value of the historical power distribution equipment health data, and to make a preliminary comparative evaluation with the obtained task priority coefficient Rwh, and to generate a secondary evaluation mechanism based on the evaluation results. The specific evaluation scheme is as follows;

[0098] When the task priority coefficient Rwh≤task priority threshold M, it means that the distance jl from the inspection robot i in area n to the power distribution equipment j is less than the distance jl from the inspection robot i+1 in area n+1 to the power distribution equipment j. At this time, there is no need to mobilize other robots for inspection, and the inspection robot in the current area will perform the inspection;

[0099] When the task priority coefficient Rwh>task ​​priority threshold M, the distance jl between the inspection robot i in area n and the distribution equipment j is greater than the distance jl between the inspection robot i+1 in area n+1 and the distribution equipment j. At this time, a first scheduling signal is generated and sent to the inspection robot scheduling control system. After a comprehensive analysis by the task priority evaluation unit on the detection status of all robots around the first-priority distribution equipment in their current nth area and the distance to this distribution equipment, the robots are mobilized to inspect the first-priority distribution equipment and the second evaluation mechanism is triggered.

[0100] In this embodiment, the health analysis unit of the power distribution equipment can calculate and monitor the health index Sjk of the power distribution equipment in real time, providing a scientific basis for timely discovery of potential problems. When the power distribution equipment is operating abnormally, the task priority analysis unit quickly marks the problem power distribution equipment as the first priority detection object, and calculates the distance jl that the inspection robot should travel to the power distribution equipment, thereby obtaining the task priority coefficient Rwh. This method ensures the efficiency of task scheduling and avoids unnecessary waste of inspection resources. The task priority evaluation unit further enhances the decision-making ability, and performs preliminary comparative evaluation by presetting the task priority threshold M to ensure that under the condition of distance differences between different inspection robots, it can accurately determine whether other robots need to be mobilized for inspection. Overall, the implementation of this module not only improves the detection rate and response speed of power distribution equipment failures, but also optimizes resource allocation, effectively reduces operating costs, and provides strong support for the safe and stable operation of data centers. This systematic and intelligent inspection strategy ensures the reliability of power distribution equipment, while saving a lot of manpower and material resources for enterprises, giving them a clear competitive advantage in modern management.

[0101] Example 6

[0102] This embodiment is explained in Example 5. Please refer to Figure 1 ,Specifically: the robot scheduling module includes a path analysis unit and a comprehensive scheduling analysis unit;

[0103] The path analysis unit is used to analyze the distance between the inspection robot and the power distribution equipment and the distance between the inspection robot i and the inspection robot n through the spatial map data when the inspection robot needs to be dispatched according to the initial assessment, and summarize and calculate the inspection path conflict coefficient Lct;

[0104] The inspection path conflict coefficient Lct is calculated by the following formula:

[0105]

[0106] Where, T i and T n They represent the time it takes for inspection robot i and inspection robot n to reach the power distribution equipment in the target area, T diff Indicates the time difference peak value set by the system, D i，n represents the distance between inspection robot i and inspection robot n, D min Indicates the safety distance valley value set between inspection robots, O i，n Indicates the degree of overlap between the inspection areas of robot i and robot n.

[0107] The comprehensive scheduling analysis unit includes a scheduling optimization calculation unit and a comprehensive scheduling evaluation unit;

[0108] The scheduling optimization calculation unit is used to perform summary calculation based on the acquired task priority coefficient Rwh and inspection path conflict coefficient Lct to obtain a comprehensive scheduling optimization coefficient DUY;

[0109] The comprehensive scheduling optimization coefficient DUY is calculated by the following formula:

[0110]

[0111] Wherein, k1 and k2 are weight coefficients of the task priority coefficient Rwh and the inspection path conflict coefficient Lct respectively, and k1+k2=1, and the specific values ​​are set by the user according to the actual situation.

[0112] The comprehensive scheduling evaluation unit is used to perform a secondary comparative evaluation of the preset scheduling conflict threshold A and the obtained comprehensive scheduling optimization coefficient DUY, perform a deep evaluation of the inspection robot path after the inspection scheduling, and generate relevant scheduling information based on the evaluation results. The specific evaluation scheme is as follows;

[0113] When the comprehensive scheduling optimization coefficient DUY is less than the scheduling conflict threshold A, it means that there are one or more robots that detect the power distribution equipment at the same time. At this time, a second scheduling signal is generated and transmitted to the inspection robot scheduling control system. The inspection robot that performs repeated inspections is obtained according to the inspection record of the power distribution equipment, and the inspection path of each inspection robot is transmitted to the inspection analysis module for iterative evaluation to re-optimize the inspection path.

[0114] When the comprehensive scheduling optimization coefficient DUY ≥ the scheduling conflict threshold A, it means that the robot inspection path is normal, and normal monitoring is maintained at this time.

[0115] In this embodiment, the path analysis unit can calculate the travel path of each inspection robot and the time to reach the target distribution equipment in real time based on the spatial map data, identify potential path conflicts, and effectively avoid them, ensuring efficient collaborative operation of multiple robots in the same area. The comprehensive scheduling analysis unit generates a comprehensive scheduling optimization coefficient by summarizing the task priority coefficient and the path conflict coefficient, thereby dynamically adjusting the scheduling strategy. When the scheduling conflict threshold is not touched, normal monitoring can be maintained to avoid unnecessary interference and repeated inspections, thereby improving the consistency and stability of the overall inspection process. This intelligent scheduling mechanism not only reduces manual intervention and scheduling errors, but also improves the real-time and accuracy of distribution equipment detection, making inspection work more efficient and providing a solid guarantee for the reliable operation of the data center.

[0116] Example 7

[0117] This embodiment is explained in Example 1, please refer to Figure 1 Specifically: the robot power optimization module is used to continuously monitor the power of the inspection robot, record the current power consumption rate and the progress of the inspection task. When the power is lower than the 20% alarm value, the inspection robot will automatically trigger the low power alarm, calculate the remaining driving distance of the inspection robot according to the remaining power, and start the instruction to return to the charging pile. Combined with the planned inspection path and the current distance between the inspection robot and the charging pile, it automatically plans a safe and optimized charging path for the inspection robot. During the charging process, it dynamically monitors the charging progress and battery temperature. When charging abnormalities are found, the charging strategy will be automatically adjusted to avoid battery damage.

[0118] In this embodiment, by continuously monitoring the power consumption rate and the progress of the inspection task, the module can automatically trigger an alarm when the power is less than 20%, ensuring timely response and preventing inspection interruptions due to insufficient power. In addition, the drivable distance of the inspection robot is calculated based on the remaining power, and the optimal path to return to the charging pile is intelligently planned, which not only ensures the normal operation of the robot, but also improves the safety and efficiency of the charging process. During the charging process, the charging progress and battery temperature can be dynamically monitored, and the charging strategy can be automatically adjusted when an abnormality is found, thereby effectively preventing battery damage. This power management strategy not only improves the availability and reliability of the inspection robot, but also ensures the efficient operation of the inspection system, providing a solid foundation for the management of power distribution equipment in the data center.

[0119] 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 data center power distribution room inspection system based on an inspection robot, characterized in that: It includes area division module, data acquisition module, terminal processing module, inspection analysis module, robot scheduling module and robot power optimization module; The area division module is used to divide the power distribution room into n areas, deploy inspection robots in each area, and mark each area and the inspection robots in the area with serial numbers, so that the sensors installed on the inspection robots can perceive the surrounding environment and power distribution equipment in real time; The data acquisition module monitors the operating data of the power distribution equipment on the inspection path in real time through the integrated sensors and acquisition devices installed inside the inspection robot, and transmits the operating data to the terminal processing module in real time; The terminal processing module is used to receive the operation data in real time, perform preprocessing, obtain the operation health data group, and then store the operation data group in real time in the relational database MySQL; The inspection analysis module is used to perform summary calculations based on the acquired operation health data group to obtain the health index Sjk of the power distribution equipment. When the operation of the power distribution equipment is abnormal, the power distribution equipment is marked as the first priority detection, and then the health index Sjk of the power distribution equipment and the distance jl that the inspection robot should travel are combined for summary calculation to obtain the task priority coefficient Rwh, and a preliminary evaluation is performed with the preset task priority threshold M, and then a secondary evaluation mechanism is triggered based on the evaluation results; The robot scheduling module is used to summarize and calculate the inspection path conflict coefficient Lct when the inspection robot needs to be scheduled according to the initial assessment, and summarize and calculate it with the obtained task priority coefficient Rwh to obtain the comprehensive scheduling optimization coefficient DUY, and perform a secondary assessment with the preset scheduling conflict threshold A, and generate a scheduling signal according to the assessment result; The robot power optimization module is used to automatically plan a route to return to the charging station for charging when the patrol robot is low on power, monitor the hardware status of the patrol robot, and perform self-diagnosis and maintenance regularly.

2. According to claim 1, a data center power distribution room inspection system based on an inspection robot is characterized in that: The area division module includes an area division unit and a robot operation unit; The area division unit is used to divide the power distribution room into n areas according to the spatial layout and the type of power distribution equipment, reserve n inspection channels between the power distribution equipment in each area, deploy an inspection robot, and then mark each area and the inspection robot in the area with serial numbers; The robot operation unit scans the environment in real time through the laser radar sensors and ultrasonic sensors installed at the front end, top end, left end, right end and rear end of the robot, senses the positions of obstacles, walls and power distribution equipment, and inspects pre-set inspection tasks and routes through crawler drive. When a dynamic obstacle is sensed, the dynamic window method DWA is used to adjust the path in real time, continuously correct the motion trajectory, and avoid collision and deviation from the route.

3. According to claim 2, a data center power distribution room inspection system based on an inspection robot is characterized in that: The data acquisition module includes a data acquisition unit and a data transmission unit; The data acquisition unit monitors the operating data of the power distribution equipment on the inspection path in real time through the integrated sensor group and acquisition equipment installed in the inspection robot; The integrated sensor group includes a piezoelectric vibration sensor, a humidity sensor, a current sensor, a voltage sensor, a power sensor, a temperature sensor, a flow sensor and a pressure sensor; The acquisition equipment includes an insulation resistance tester; The data transmission unit is used to transmit the operation data collected by the inspection robot to the terminal processing module through the wireless network. If the data is not successfully transmitted, the inspection robot automatically resends the data.

4. According to claim 3, a data center power distribution room inspection system based on an inspection robot is characterized in that: The terminal processing module includes a data preprocessing unit and a data storage unit; The preprocessing unit is used to receive the operation data in real time, and perform data filtering, abnormal data cleaning, noise removal and normalization processing to obtain the operation health data group; The operation health data group includes equipment vibration frequency zd, cable insulation resistance dz, environmental humidity change rate sd and equipment load fluctuation rate fz; The data storage unit is used to store the acquired operation health data group in the relational database MySQL through the API interface, adopt incremental backup and differential backup strategies, combine the cloud backup service to back up the operation health data group for long-term storage, and extract the operation health data group in the relational database MySQL in real time through the database port.

5. According to claim 4, a data center power distribution room inspection system based on an inspection robot is characterized in that: The inspection and analysis module includes a power distribution equipment health analysis unit, a task priority analysis unit and a task priority evaluation unit; The power distribution equipment health analysis unit is used to perform summary calculation based on the acquired operation health data group to obtain the power distribution equipment health index Sjk; The power distribution equipment health index Sjk is calculated by the following formula: In the formula, ln represents the logarithmic function; The task priority analysis unit determines the normal and abnormal operation of the distribution equipment according to the health index Sjk of the distribution equipment through the abnormal operation data of the relay distribution equipment in the relational database MySQL. When the distribution equipment operates abnormally, the distribution equipment is marked as the first priority detection distribution equipment, and data detection of the distribution equipment is required immediately. At this time, the terminal control system displays the position of the inspection robot and the position of the distribution equipment in the spatial map data of the distribution room, and then calculates the required travel distance jl from the inspection robot to the distribution equipment in combination with the inspection path, and summarizes and calculates the required travel distance jl and the obtained health index Sjk of the distribution equipment to obtain the task priority coefficient Rwh; The task priority coefficient Rwh is calculated by the following formula: In the formula, Sjk j Indicates the health index of the jth power distribution device. The jth power distribution device is the first priority detection power distribution device. i，j represents the required travel distance from the i-th inspection robot to the j-th power distribution equipment, jl i+1，j represents the required travel distance from the i+1th inspection robot to the jth power distribution equipment, (jl i，j -jl i+1，j ) represents the difference in required distances between the ith inspection robot and the i+1th inspection robot, Ww represents the wth weight coefficient of the health index Sjk of the jth distribution device, Qq represents the qth weight coefficient of the difference in required distances between the ith inspection robot and the i+1th inspection robot to the jth distribution device, and c represents the correction constant.

6. According to claim 5, a data center power distribution room inspection system based on an inspection robot is characterized in that: The task priority evaluation unit is used to evaluate the difference in task urgency scheduling between the first priority power distribution equipment j and the inspection robot with sequence number i in the area n and the inspection robot with sequence number i+1 in the area n+1, and to preset the task priority threshold M based on the average value of the historical power distribution equipment health data, and to make a preliminary comparative evaluation with the obtained task priority coefficient Rwh, and to generate a secondary evaluation mechanism based on the evaluation results. The specific evaluation scheme is as follows; When the task priority coefficient Rwh≤task priority threshold M, it means that the distance jl from the inspection robot i in area n to the power distribution equipment j is less than the distance jl from the inspection robot i+1 in area n+1 to the power distribution equipment j. At this time, there is no need to mobilize other robots for inspection, and the inspection robot in the current area will perform the inspection; When the task priority coefficient Rwh>task ​​priority threshold M, the distance jl between the inspection robot i in area n and the distribution equipment j is greater than the distance jl between the inspection robot i+1 in area n+1 and the distribution equipment j. At this time, a first scheduling signal is generated and sent to the inspection robot scheduling control system. After a comprehensive analysis by the task priority evaluation unit on the detection status of all robots around the first-priority distribution equipment in their current nth area and the distance to this distribution equipment, the robots are mobilized to inspect the first-priority distribution equipment and the second evaluation mechanism is triggered.

7. The data center power distribution room inspection system based on the inspection robot according to claim 6 is characterized by: The robot scheduling module includes a path analysis unit and a comprehensive scheduling analysis unit; The path analysis unit is used to analyze the distance between the inspection robot and the power distribution equipment and the distance between the inspection robot i and the inspection robot n through the spatial map data when the inspection robot needs to be dispatched according to the initial assessment, and summarize and calculate the inspection path conflict coefficient Lct; The inspection path conflict coefficient Lct is calculated by the following formula: Where, T i and T n They represent the time it takes for inspection robot i and inspection robot n to reach the power distribution equipment in the target area, T diff Indicates the time difference peak value set by the system, D i，n represents the distance between inspection robot i and inspection robot n, D min Indicates the safety distance valley value set between inspection robots, O i，n Indicates the degree of overlap between the inspection areas of robot i and robot n.

8. The data center power distribution room inspection system based on the inspection robot according to claim 7 is characterized by: The comprehensive scheduling analysis unit includes a scheduling optimization calculation unit and a comprehensive scheduling evaluation unit; The scheduling optimization calculation unit is used to perform summary calculation based on the acquired task priority coefficient Rwh and inspection path conflict coefficient Lct to obtain a comprehensive scheduling optimization coefficient DUY; The comprehensive scheduling optimization coefficient DUY is calculated by the following formula: Wherein, k1 and k2 are weight coefficients of the task priority coefficient Rwh and the inspection path conflict coefficient Lct respectively, and k1+k2=1, and the specific values ​​are set by the user according to the actual situation.

9. The data center power distribution room inspection system based on the inspection robot according to claim 8, characterized in that: The comprehensive scheduling evaluation unit is used to perform a secondary comparative evaluation of the preset scheduling conflict threshold A and the obtained comprehensive scheduling optimization coefficient DUY, perform a deep evaluation of the inspection robot path after the inspection scheduling, and generate relevant scheduling information based on the evaluation results. The specific evaluation scheme is as follows; When the comprehensive scheduling optimization coefficient DUY is less than the scheduling conflict threshold A, it means that there are one or more robots that detect the power distribution equipment at the same time. At this time, a second scheduling signal is generated and transmitted to the inspection robot scheduling control system. The inspection robot that performs repeated inspections is obtained according to the inspection record of the power distribution equipment, and the inspection path of each inspection robot is transmitted to the inspection analysis module for iterative evaluation to re-optimize the inspection path. When the comprehensive scheduling optimization coefficient DUY ≥ the scheduling conflict threshold A, it means that the robot inspection path is normal, and normal monitoring is maintained at this time.

10. The data center power distribution room inspection system based on the inspection robot according to claim 1, characterized in that: The robot power optimization module is used to continuously monitor the power of the inspection robot, record the current power consumption rate and the progress of the inspection task. When the power is lower than the 20% alarm value, the inspection robot will automatically trigger a low-power alarm, calculate the remaining drivable distance of the inspection robot based on the remaining power, and start the instruction to return to the charging pile. Combined with the planned inspection path and the current distance between the inspection robot and the charging pile, a safe and optimized charging path for the inspection robot is automatically planned. During the charging process, the charging progress and battery temperature are dynamically monitored. When charging abnormalities are found, the charging strategy is automatically adjusted to avoid battery damage.

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