Personnel planning method, system and equipment for routing inspection of intelligent calculation center

Abstract

The invention relates to the technical field of intelligent calculation center operation and maintenance management, and discloses a personnel planning method, system and equipment for an intelligent calculation center routing inspection line. The personnel planning method for the inspection line of the intelligent calculation center is applied to the intelligent calculation inspection equipment, and specifically comprises the following steps: S101, obtaining feature information of equipment points to be inspected of the intelligent calculation center, configuring inspection times of each equipment every day according to the operation characteristics and the importance degree of the equipment of the intelligent calculation center, and providing a planning basis of time dimension for an inspection plan; according to the method, the problems of line optimization, personnel quantity distribution and the like in routing inspection line planning of the intelligent calculation center are solved, the routing inspection efficiency and the management scientificity are improved while stable operation of equipment of the intelligent calculation center is ensured, the routing inspection time is calculated strictly according to a standard operation process corresponding to the equipment type and the number of required inspection items, and the routing inspection efficiency is improved. And the calculation result can accurately reflect the time required by the actual inspection work.

Description

Technical Field

[0001] The present invention relates to the technical field of operation and maintenance management of an intelligent computing center, and in particular to a personnel planning method, system and equipment for inspection routes of an intelligent computing center. Background Art

[0002] The Intelligent Computing Center is a new type of public computing infrastructure based on the latest artificial intelligence theory and the leading artificial intelligence computing architecture. It provides artificial intelligence computing institutions and computing services, data services and algorithm services required for artificial intelligence applications. It plays a significant role in promoting the industrialization of AI, enabling the AIization of industries, helping intelligent governance, and promoting industrial clustering.

[0003] The normal operation of the equipment in the intelligent computing center is crucial to its stable service, and inspection is a key measure to ensure the stable operation of equipment. Traditional inspection planning lacks systematicity and scientificity, and often ignores key factors such as inspection route optimization, inspection time and cycle. This may not only lead to inefficient inspections and waste of human resources, but also fail to detect equipment problems in time due to untimely inspections, thus affecting the normal operation of the intelligent computing center. Summary of the invention

[0004] The purpose of the present invention is to provide a personnel planning method, system and equipment for the inspection routes of the intelligent computing center, which solves the problems of route optimization, personnel number allocation and so on in the inspection route planning of the intelligent computing center, and aims to ensure the stable operation of the equipment of the intelligent computing center while improving the inspection efficiency and scientific management. It aims to solve the problem that traditional inspection planning in the prior art lacks systematicity and scientificity, and often ignores key factors such as inspection route optimization, inspection time and cycle, which may not only lead to low inspection efficiency, but also cause waste of human resources.

[0005] The present invention is implemented in this way: a personnel planning method for an intelligent computing center inspection line is applied to an intelligent computing inspection device, specifically comprising the following steps:

[0006] S101: Acquire characteristic information of the equipment points to be inspected in the intelligent computing center, configure the number of inspections per day for each equipment point according to the operating characteristics and importance of the equipment in the intelligent computing center, and provide a planning basis for the time dimension of the inspection plan;

[0007] S102: Using the Dijkstra algorithm based on graph theory, starting from the ECC duty room, by constructing a network graph and calculating the weight of each edge, the shortest or most time-saving path is determined as the optimal inspection route, and the optimal inspection path is planned for each inspection equipment point;

[0008] S103: The number of TSP loops required to depart from the ECC duty room within the specified time is obtained by dividing the total time of the optimal inspection route by the inspection cycle set by the basic information module;

[0009] S104: Accurately calculate the number of inspection personnel required based on the workload and safety regulations of the number of TSP loops to ensure that there is sufficient manpower support for the inspection tasks.

[0010] Furthermore, in S101, characteristic information of the equipment points to be inspected in the intelligent computing center is obtained, including:

[0011] The characteristic information includes basic characteristic information of the equipment point to be inspected;

[0012] The basic characteristic information of the equipment point to be inspected includes basic equipment information of the equipment point to be inspected, estimated inspection time, location coordinates, inspection cycle, and inspection shift;

[0013] The basic characteristic information of the equipment points to be inspected is stored in the system database to provide basic data support for subsequent planning.

[0014] Further, in S102, the Dijkstra algorithm based on the graph theory algorithm is used, starting from the ECC duty room, by constructing a network graph and calculating the weight of each edge, to determine the shortest or most time-saving path, that is, the optimal inspection route, including:

[0015] Taking the ECC duty room as the starting point of inspection route planning, the Dijkstra algorithm is started in the inspection route planning module;

[0016] Dijkstra algorithm constructs a network graph G = (V, E) containing all equipment points, where the equipment point set V = {v 0 ,v 1 ,...,v n}, edge e=(v i ,v j )’s weight w(v i ,v j )=d(v i ,v j )+t(v i ), the algorithm starts to iterate, each time selecting the node u with the smallest d(u) from the node set U whose shortest path has not been determined, removing it from U and determining the node whose shortest path has been found as the optimal inspection route;

[0017] According to the determined optimal inspection route, calculate the total time T required to complete an inspection task total , according to the formula The travel time between each equipment point and the inspection time d(v i-1 ,v i ), where v o For ECC duty room, n For the last inspection equipment point, calculate the inspection time t(vi ).

[0018] Furthermore, the Dijkstra algorithm first initializes the data, setting the starting point v o The distance to itself d(v 0 )=0, to other device point v i (i≠0) the distance d(v i )=∞, and to the previous node prev(v i )=null.

[0019] Furthermore, each time, a node u with the smallest d(u) is selected from the node set U whose shortest path has not been determined, and it is removed from U and determined as the node whose shortest path has been found as the optimal inspection route, including:

[0020] For u and its adjacent node v, if d(v)>d(u)+w(u,v), then update d(v)=d(u)+w(u,v), prev(v)=u, and continue to repeat this selection and update operation until U is an empty set. At this time, by backtracking prev(v i ) to obtain the optimal path from the ECC duty room to each equipment point, which is the optimal inspection route.

[0021] Further, in S103, by dividing the total time of the optimal inspection route by the inspection cycle set by the basic information module, the number of TSP loops required to depart from the ECC duty room within the specified time is obtained, including:

[0022] Extract the calculated optimal inspection route total time T from the inspection loop and personnel calculation module total , and the inspection cycle T obtained in the basic information configuration phase cycle ;

[0023] T total Divide by T cycle , and use the formula to calculate Get the number k of TSP loops required to depart from the ECC duty room within the specified time.

[0024] Furthermore, in S104, the number of required inspection personnel is accurately calculated based on the work intensity and safety regulation factors of the number of TSP loops, including:

[0025] According to the calculated number of TSP loops k, combined with the preset work intensity I of each loop and the additional personnel coefficient α required by safety regulations;

[0026] Substitute into the formula That is, calculate the number of inspection personnel N required.

[0027] Furthermore, combined with the preset work intensity I of each circuit, the work intensity I is comprehensively determined according to the complexity of the actual inspection task, the equipment distribution density and the physical exertion factors of the personnel;

[0028] The personnel coefficient α is a specific value set according to safety management regulations and personnel fatigue recovery requirements.

[0029] Compared with the prior art, the personnel planning method, system and device for the inspection line of the intelligent computing center provided by the present invention have the following beneficial effects:

[0030] 1. It solves the problems of route optimization and personnel allocation in the inspection route planning of the intelligent computing center, aiming to ensure the stable operation of the equipment in the intelligent computing center while improving the inspection efficiency and scientific management. When calculating the inspection time, it is strictly determined according to the standard operating procedures corresponding to the equipment type and the number of inspection items required to ensure that the calculation results accurately reflect the time required for the actual inspection work;

[0031] 2. Calculation of total inspection time Calculate the total time required to complete the inspection task based on the optimal path T total , the calculation formula is (where v 0 For ECC duty room, n is the last inspection equipment point), the duration is the sum of the inspection time at each equipment point and the travel time between equipment points. The inspection time is calculated based on the equipment type and inspection standard. The inspection loop calculation is based on the total time T of the optimal inspection route. total Divide by the inspection cycle T set in the basic information module cycle , we can get the number of TSP (travel salesman problem) circuits k required to depart from the ECC duty room within the specified time. The calculation formula is: ( Indicates rounding up), and then accurately calculate the number of inspection personnel N required through factors such as the number of circuits, the work intensity of each circuit, and safety regulations, thereby ensuring the high efficiency of the inspection, enabling human resources to be matched in all aspects and avoiding waste of human resources.

[0032] The personnel planning system of the inspection line of the intelligent computing center is executed in the above-mentioned personnel planning method, and the personnel planning system includes:

[0033] The basic information module is used to obtain the characteristic information of the equipment points to be inspected in the intelligent computing center, configure the number of inspections for each point per day, and provide a planning basis for the time dimension of the inspection plan;

[0034] The inspection route planning module is used to use the Dijkstra algorithm based on graph theory, starting from the ECC duty room, to plan the optimal inspection route for each inspection equipment point by constructing a network graph and calculating the weight of each edge;

[0035] The inspection loop calculation module is used to calculate the number of TSP loops required to depart from the ECC duty room within the specified time by dividing the total time of the optimal inspection route by the inspection cycle set by the basic information module;

[0036] The personnel calculation module is used to accurately calculate the number of inspection personnel required based on the work intensity and safety regulation factors of the number of TSP loops.

[0037] The personnel planning device of the inspection line of the intelligent computing center includes a storage device and a processor, wherein the storage device is used to store a computer program, and the processor runs the computer program to enable the personnel planning device to execute the above-mentioned personnel planning method. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a schematic flow chart of the personnel planning method for the inspection route of the intelligent computing center proposed by the present invention;

[0039] Figure 2 This is a structural diagram of the personnel planning system for the inspection route of the intelligent computing center proposed by the present invention;

[0040] Figure 3 This is a structural schematic diagram of the personnel planning equipment for the inspection line of the intelligent computing center proposed in the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0042] The implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0043] The same or similar numbers in the drawings of this embodiment correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right" and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, it is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and cannot be understood as limitations on the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0044] Reference Figure 1 As shown in the figure, the personnel planning method of the intelligent computing center inspection route is applied to the intelligent computing inspection equipment, which specifically includes the following steps:

[0045] S101: Acquire characteristic information of the equipment points to be inspected in the intelligent computing center, configure the number of inspections per day for each equipment point according to the operating characteristics and importance of the equipment in the intelligent computing center, and provide a planning basis for the time dimension of the inspection plan;

[0046] Among them, the basic information such as the equipment points to be inspected, inspection cycles, and inspection shifts of the intelligent computing center is obtained, including detailed information of the equipment points (basic equipment information, estimated inspection time, location coordinates, etc.), inspection cycles (for example, setting an inspection once every hour), and inspection shifts (two shifts per day, such as day shift (08:00-20:00) and night shift (20:00-08:00)), and stored in the system database to provide basic data support for subsequent planning;

[0047] S102: Using the Dijkstra algorithm based on graph theory, starting from the ECC duty room, by constructing a network graph and calculating the weight of each edge, the shortest or most time-saving path is determined as the optimal inspection route, and the optimal inspection path is planned for each inspection equipment point;

[0048] Specifically, the Dijkstra algorithm is used, and according to the algorithm formula in the inspection route planning module, the optimal inspection path to each inspection equipment point is calculated with the ECC duty room as the starting point. Assume that the intelligent computing center has n inspection equipment points, and the equipment point set is V = {v 0 ,v 1 ,...,v n}(where v o is the ECC duty room), the distance between the two points is d(v i ,v j ), the equipment inspection duration is t(v i ); construct a network graph G = (V, E), where edge e = (v i ,v j )’s weight w(v i ,v j )=d(v i ,v j )+t(v i )(Indicates from v i Device point to v j The cost, including the distance and the cost of v i The Dijkstra algorithm finds the optimal path by continuously updating the shortest path estimate from the starting point to other points. The steps are as follows:

[0049] Initialization: d(v 0 )=0,d(v i )=∞(i≠0),prev(v i )=null(prev(v i ) indicates vi to the previous node);

[0050] For the node set U (initially V-{v 0}), select the node u with the smallest d(u), remove it from U and determine it as the node for which the shortest path has been found;

[0051] For u and the adjacent node v, if d(v)>d(u)+w(u,v), then update d(v)=d(u)+w(u,v), prev(v)=u;

[0052] Repeat steps 2 and 3 until U is empty;

[0053] Finally, the optimal path from the ECC duty room to each equipment point is obtained, which is the optimal inspection route;

[0054] S103: The number of TSP loops required to depart from the ECC duty room within the specified time is obtained by dividing the total time of the optimal inspection route by the inspection cycle set by the basic information module;

[0055] Among them, by dividing the total time of the optimal inspection route by the inspection cycle set by the basic information module, the number of TSP loops required to depart from the ECC duty room within the specified time is obtained, including:

[0056] Extract the calculated optimal inspection route total time T from the inspection loop and personnel calculation module total , and the inspection cycle T obtained in the basic information configuration phase cycle ;

[0057] The operation and maintenance management experts of the intelligent computing center determine the reasonable number of inspections per day for each device based on the historical failure data of the equipment, the impact on the overall business, and the aging of the equipment, thereby setting the inspection cycle T. cycle For example, for core critical equipment and equipment with high failure rate, it is set to inspect once every hour (i.e. T cycle = 1 hour), for relatively minor and more stable equipment, it can be set to be inspected every two hours or longer. Accurately enter the set inspection cycle into the system;

[0058] T total Divide by T cycle , and use the formula to calculate Get the number of TSP loops k required to depart from the ECC duty room within the specified time;

[0059] For example, if T total = 5.5 hours, T cycle = 1 hour, then, that is That is, 6 circuits are needed to complete all inspection tasks within the specified time;

[0060] S104: Accurately calculate the number of inspection personnel required based on the work intensity and safety regulation factors of the number of TSP loops to ensure that there is sufficient manpower support for the inspection task;

[0061] Among them, the number of inspection personnel required is accurately calculated based on the work intensity and safety regulation factors of the number of TSP loops, including:

[0062] According to the calculated number of TSP loops k, combined with the preset work intensity I of each loop and the additional personnel coefficient α required by safety regulations;

[0063] Substitute into the formula That is, calculate the number of inspection personnel N required;

[0064] Combined with the preset work intensity I of each circuit, the work intensity I is determined comprehensively according to the complexity of the actual inspection task, the density of equipment distribution and the physical exertion of personnel;

[0065] The personnel coefficient α is a specific value set according to safety management regulations and personnel fatigue recovery requirements;

[0066] For example, combined with the preset work intensity I of each circuit (this value can be determined comprehensively according to factors such as the complexity of the actual inspection task, the density of equipment distribution, and the physical exertion of personnel, for example, it is set to 0.8, indicating that the average work intensity of each circuit is 80% of the full load), and the additional personnel coefficient α required by safety regulations (assuming that according to safety management regulations and personnel fatigue recovery requirements, α is set to 1.2);

[0067] Use the formula Calculate the number of patrol personnel required, N. For example, when k = 6, I = 0.8, α = 1.2, that is, That is, 6 inspection personnel are needed to complete the inspection task to ensure that the inspection task has sufficient manpower support. At the same time, the work intensity and safety factors of the personnel are also taken into consideration. This technical solution solves the problems of route optimization and personnel allocation in the inspection route planning of the intelligent computing center. It aims to ensure the stable operation of the equipment in the intelligent computing center while improving the inspection efficiency and scientific management.

[0068] In S101 of this embodiment, the characteristic information of the equipment point to be inspected in the intelligent computing center is obtained, including:

[0069] The characteristic information includes the basic characteristic information of the equipment points to be inspected, specifically the basic information such as the equipment points to be inspected, inspection cycles, and inspection shifts of the intelligent computing center, including detailed information of the equipment points (basic equipment information, estimated inspection time, location coordinates, etc.), inspection cycles (for example, setting an inspection once every hour), and inspection shifts (2 shifts per day, such as day shift (08:00-20:00) and night shift (20:00-08:00)). The basic characteristic information of the equipment points to be inspected includes the basic information of the equipment points to be inspected, estimated inspection time, location coordinates, inspection cycles, and inspection shifts; the basic characteristic information of the equipment points to be inspected is stored in the system database to provide basic data support for subsequent planning.

[0070] In S102 of this embodiment, the Dijkstra algorithm based on the graph theory algorithm is used, starting from the ECC duty room, by constructing a network graph and calculating the weight of each edge, to determine the shortest or most time-saving path, that is, the optimal inspection route, including:

[0071] Taking the ECC duty room as the starting point of inspection route planning, the Dijkstra algorithm is started in the inspection route planning module;

[0072] Dijkstra algorithm constructs a network graph G = (V, E) containing all equipment points, where the equipment point set V = {v 0 ,v 1 ,...,v n}, edge e=(v i ,v j )’s weight w(v i ,v j )=d(v i ,v j )+t(v i ), the algorithm starts to iterate, each time selecting the node u with the smallest d(u) from the node set U whose shortest path has not been determined, removing it from U and determining the node whose shortest path has been found as the optimal inspection route;

[0073] According to the determined optimal inspection route, calculate the total time T required to complete an inspection task total , according to the formula The travel time between each equipment point and the inspection time d(v i-1 ,v i ), where v o For ECC duty room, n For the last inspection equipment point, calculate the inspection time t(v i ).

[0074] Furthermore, the Dijkstra algorithm first initializes the data and sets the starting point v oThe distance to itself d(v 0 )=0, to other device point v i (i≠0) the distance d(v i )=∞, and to the previous node prev(v i )=null.

[0075] Furthermore, each time, a node u with the smallest d(u) is selected from the node set U whose shortest path has not been determined, and it is removed from U and determined as the node whose shortest path has been found as the optimal inspection route, including:

[0076] For u and its adjacent node v, if d(v)>d(u)+w(u,v), then update d(v)=d(u)+w(u,v), prev(v)=u, and continue to repeat this selection and update operation until U is an empty set. At this time, by backtracking prev(v i ) to obtain the optimal path from the ECC duty room to each equipment point, which is the optimal inspection route.

[0077] This technical solution solves the problems of route optimization and personnel allocation in the inspection route planning of the intelligent computing center. It aims to ensure the stable operation of the equipment in the intelligent computing center while improving the inspection efficiency and scientific management. When calculating the inspection time, it is strictly determined according to the standard operating procedures corresponding to the equipment type and the number of inspection items required to ensure that the calculation results accurately reflect the time required for the actual inspection work.

[0078] Reference Figure 2 As shown in the figure, the personnel planning system of the inspection line of the intelligent computing center is executed in the above-mentioned personnel planning method. The personnel planning system includes: a basic information module, which is used to obtain the characteristic information of the equipment points to be inspected in the intelligent computing center, configure the number of inspections for each point per day, and provide a planning basis for the time dimension of the inspection plan; an inspection line planning module, which is used to use the Dijkstra algorithm based on the graph theory algorithm, take the ECC duty room as the starting point, and plan the optimal inspection path for each inspection equipment point by constructing a network diagram and calculating the weight of each edge; an inspection loop calculation module, which is used to divide the total time of the optimal inspection route by the inspection cycle set by the basic information module, and obtain the number of TSP loops required to start from the ECC duty room within the specified time; a personnel calculation module, which is used to accurately calculate the number of inspection personnel required through the work intensity and safety specification factors of the number of TSP loops, and the total inspection time calculation is based on the optimal path to calculate the total time T required to complete the inspection task. total , the calculation formula is (where v 0 For ECC duty room, nis the last inspection equipment point), the duration is the sum of the inspection time at each equipment point and the travel time between equipment points. The inspection time is calculated based on the equipment type and inspection standard. The inspection loop calculation is based on the total time T of the optimal inspection route. total Divide by the inspection cycle T set in the basic information module cycle , we can get the number of TSP (travel salesman problem) circuits k required to depart from the ECC duty room within the specified time. The calculation formula is: ( Indicates rounding up), and then accurately calculate the number of inspection personnel N required through factors such as the number of circuits, the work intensity of each circuit, and safety regulations, thereby ensuring the high efficiency of the inspection, enabling human resources to be matched in all aspects and avoiding waste of human resources.

[0079] Reference Figure 3 As shown, the personnel planning device of the inspection line of the intelligent computing center includes a storage device and a processor. The storage device is used to store computer programs. The processor runs the computer program to enable the personnel planning device to execute the above-mentioned personnel planning method, which solves the problems of line optimization and personnel quantity allocation in the inspection line planning of the intelligent computing center, and aims to ensure the stable operation of the equipment of the intelligent computing center while improving the inspection efficiency and scientific management. When calculating the inspection time, it is strictly determined according to the standard operating procedures corresponding to the equipment type and the number of inspection items required to ensure that the calculation result accurately reflects the time required for the actual inspection work. The total inspection time is calculated according to the optimal path to calculate the total time T required to complete the inspection task. total , the inspection loop is calculated by taking the total time T of the optimal inspection route total Divide by the inspection cycle T set in the basic information module cycle , the number of TSP (travelling salesman problem) loops k required to depart from the ECC duty room within the specified time is obtained, and then the number of inspection personnel N required is accurately calculated through factors such as the number of loops, the work intensity of each loop, and safety regulations, ensuring the efficiency of the inspection, so that human resources can be matched in all aspects and avoid waste of human resources.

[0080] In this embodiment, ECC=Enterprise Control Center;

[0081] TSP = Traveling Salesman Problem, which is described as: given a series of cities and the distance between each pair of cities, find the shortest way to visit each city once and return to the starting city.

[0082] In this embodiment, the entire operation process can be controlled by a computer, and in each operation link, sensors can be set to provide signal feedback to achieve sequential execution of steps. These are all common knowledge of current automated control and will not be described in detail in this embodiment.

[0083] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A personnel planning method for inspection routes of an intelligent computing center is characterized by: Applied to intelligent inspection equipment, specifically including the following steps: S101: Acquire characteristic information of the equipment points to be inspected in the intelligent computing center, configure the number of inspections per day for each equipment point according to the operating characteristics and importance of the equipment in the intelligent computing center, and provide a planning basis for the time dimension of the inspection plan; S102: Using the Dijkstra algorithm based on graph theory, starting from the ECC duty room, by constructing a network graph and calculating the weight of each edge, the shortest or most time-saving path is determined as the optimal inspection route, and the optimal inspection path is planned for each inspection equipment point; S103: The number of TSP loops required to depart from the ECC duty room within the specified time is obtained by dividing the total time of the optimal inspection route by the inspection cycle set by the basic information module; S104: Accurately calculate the number of inspection personnel required based on the workload and safety regulations of the number of TSP loops to ensure that there is sufficient manpower support for the inspection tasks.

2. The method for planning personnel for inspection routes of an intelligent computing center according to claim 1, characterized in that: In S101, characteristic information of the equipment points to be inspected in the intelligent computing center is obtained, including: The characteristic information includes basic characteristic information of the equipment point to be inspected; The basic characteristic information of the equipment point to be inspected includes basic equipment information of the equipment point to be inspected, estimated inspection time, location coordinates, inspection cycle, and inspection shift; The basic characteristic information of the equipment points to be inspected is stored in the system database to provide basic data support for subsequent planning.

3. The method for planning personnel for inspection routes of an intelligent computing center as claimed in claim 2, characterized in that: In S102, the Dijkstra algorithm based on graph theory is used, starting from the ECC duty room, to construct a network graph and calculate the weight of each edge to determine the shortest or most time-saving path, which is the optimal inspection route, including: Taking the ECC duty room as the starting point of inspection route planning, the Dijkstra algorithm is started in the inspection route planning module; Dijkstra algorithm constructs a network graph G = (V, E) containing all device points, where the device point set V = {v0, v1, ..., v n }, edge e=(v i ,v j )’s weight w(v i ,v j )=d(v i ,v j )+t(v i ), the algorithm starts to iterate, each time selecting the node u with the smallest d(u) from the node set U whose shortest path has not been determined, removing it from U and determining the node whose shortest path has been found as the optimal inspection route; According to the determined optimal inspection route, calculate the total time T required to complete an inspection task total , according to the formula The travel time between each equipment point and the inspection time d(v i-1 ,v i ), where v o is the ECC duty room, vn is the last inspection equipment point, and the inspection time t(v i ).

4. The method for planning personnel for inspection routes of an intelligent computing center as claimed in claim 3, characterized in that: The Dijkstra algorithm first initializes the data, setting the starting point v o The distance to itself is d(v0) = 0, and the distance to other devices is v i (i≠0) the distance d(v i )=∞, and to the previous node prev(v i )=null.

5. The method for planning personnel for inspection routes of an intelligent computing center as claimed in claim 4, characterized in that: Each time, a node u with the smallest d(u) is selected from the node set U whose shortest path has not been determined, and it is removed from U and determined as the node whose shortest path has been found as the optimal inspection route, including: For u and its adjacent node v, if d(v)>d(u)+w(u,v), then update d(v)=d(u)+w(u,v), prev(v)=u, and continue to repeat this selection and update operation until U is an empty set. At this time, by backtracking prev(v i ) to obtain the optimal path from the ECC duty room to each equipment point, which is the optimal inspection route.

6. The method for planning personnel for inspection routes of an intelligent computing center as claimed in claim 5, characterized in that: In S103, the number of TSP loops required to depart from the ECC duty room within the specified time is obtained by dividing the total time of the optimal inspection route by the inspection cycle set by the basic information module, including: Extract the calculated optimal inspection route total time T from the inspection loop and personnel calculation module total , and the inspection cycle T obtained in the basic information configuration phase cycle ; T total Divide by T cycle , and use the formula to calculate Get the number k of TSP loops required to depart from the ECC duty room within the specified time.

7. The method for planning personnel for inspection routes of an intelligent computing center as claimed in claim 6, characterized in that: In S104, the number of inspection personnel required is accurately calculated based on the work intensity and safety regulation factors of the number of TSP loops, including: According to the calculated number of TSP loops k, combined with the preset work intensity I of each loop and the additional personnel coefficient α required by safety regulations; Substitute into the formula That is, calculate the number of inspection personnel N required.

8. The method for planning personnel for inspection routes of an intelligent computing center as claimed in claim 7, characterized in that: Combined with the preset work intensity I of each circuit, the work intensity I is comprehensively determined according to the complexity of the actual inspection task, the equipment distribution density and the physical exertion factors of the personnel; The personnel coefficient α is a specific value set according to safety management regulations and personnel fatigue recovery requirements.

9. The personnel planning system for the inspection route of the intelligent computing center is characterized by: The personnel planning method according to any one of claims 1 to 8 is implemented, wherein the personnel planning system comprises: The basic information module is used to obtain the characteristic information of the equipment points to be inspected in the intelligent computing center, configure the number of inspections for each point per day, and provide a planning basis for the time dimension of the inspection plan; The inspection route planning module is used to use the Dijkstra algorithm based on graph theory, starting from the ECC duty room, to plan the optimal inspection route for each inspection equipment point by constructing a network graph and calculating the weight of each edge; The inspection loop calculation module is used to calculate the number of TSP loops required to depart from the ECC duty room within the specified time by dividing the total time of the optimal inspection route by the inspection cycle set by the basic information module; The personnel calculation module is used to accurately calculate the number of inspection personnel required based on the work intensity and safety regulation factors of the number of TSP loops.

10. The personnel planning equipment of the intelligent computing center inspection line is characterized by: It comprises a storage device and a processor, wherein the storage device is used to store a computer program, and the processor runs the computer program to enable the personnel planning device to execute the personnel planning method according to any one of claims 1 to 8.

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