Substitute maintenance routing inspection path planning method

Abstract

The invention relates to the technical field of commission maintenance routing inspection, and discloses a commission maintenance routing inspection path planning method, which comprises the following steps of: acquiring positioning data of all routing inspection resources and fault alarm resources in real time, classifying the positioning data into a routing inspection data set and a fault data set, and accurately positioning and optimizing a routing inspection path; the method comprises the following steps: collecting a historical data set, performing centesimal scoring on various data of inspection equipment, dividing the inspection equipment into three grades after scoring, and dynamically making a maintenance-for-another inspection plan; according to the fault data set and the historical data set, correspondingly collecting the alarm level of the equipment, and then performing centesimal scoring on the potential hidden danger of the inspection equipment; according to the hidden danger scoring result of the inspection equipment, the priority of path planning is judged, the optimal commissioning maintenance inspection path is planned by adopting a Dijksta algorithm and an ant colony optimization algorithm, the task execution efficiency is high, and the network quality is good.

Description

Technical Field

[0001] The present invention relates to the technical field of maintenance and inspection services, and in particular to a maintenance and inspection route planning method. Background Art

[0002] With the continuous development of mobile networks, the number of network equipment in mobile companies continues to increase, and the scale is getting larger and larger, making equipment maintenance and management more and more complicated, and putting forward higher requirements for the accuracy, efficiency and quality of maintenance and inspection work. The maintenance and inspection service covers a full range of work from daily inspections to troubleshooting, from preventive maintenance to emergency repairs. Professional technicians will regularly conduct comprehensive inspections of customers' equipment, including but not limited to the physical state of hardware, software updates and configurations, system operating efficiency and safety performance, etc. Professional technicians can quickly and accurately identify the problem and take appropriate measures to repair or optimize it. The main purpose of maintenance and inspection is to reduce the occurrence of equipment failures, extend the service life of equipment, and improve the overall performance of the system. Through regular inspections and maintenance, potential problems can be discovered and resolved in a timely manner to avoid serious consequences such as production stagnation or data loss caused by equipment failure. In the maintenance management of mobile communications, maintenance and inspection tasks will be classified according to the equipment coverage scenario to formulate inspection plans, which are divided into the following 4 levels:

[0003] Class A equipment is the most important. For example, for base station equipment, it includes key support stations in disaster areas (super base stations), VIP and VVIP base stations, stations where local emergency command and dispatch agencies are located, important business stations, high-value base stations, base stations where local agencies are located, transmission nodes (with more than 10 stations connected), stations where important group dedicated lines are located, and ultra-short wave stations;

[0004] Class B equipment refers to ordinary equipment with a general degree of importance. For example, for base station equipment, it includes most base stations except support stations and important stations. This type of equipment accounts for more than 60% of all inspection equipment;

[0005] Class C equipment is relatively rarely used inspection equipment, such as base station equipment, including equipment with very little traffic, high altitude or remote areas, the end of the transmission branch chain, and only non-important base stations that solve local basic communications;

[0006] Class D base stations are located in urban-rural fringe areas, remote locations and are easily stolen.

[0007] The current inspection rules are that Class A equipment is inspected once a month, Class B equipment is inspected once every two months, Class C equipment is inspected once a quarter, and Class D equipment is inspected once a quarter and needs to be inspected once a month. After the inspection plan is formulated, the maintenance target inspection resources will be fixed, and the maintenance personnel can carry out the inspection. However, the maintenance staff is also responsible for communication equipment alarm processing and fault handling (such as dynamic power generation). In this way, if the maintenance inspection is not combined with equipment alarms and faults for real-time status update path planning, it will consume a lot of time and energy of the maintenance personnel on the inspection route, and the network quality cannot be effectively improved, and the maintenance inspection efficiency is greatly reduced.

[0008] With the extension of the network, the area covered by maintenance work is getting larger and larger, and the distribution areas are diversified. Due to the limitations of GPS technology, the traditional maintenance inspection path planning algorithm cannot meet the requirements of precise positioning in special locations such as mountainous areas. There is no rating mechanism between inspection resource equipment, and no appropriate inspection method is selected for various resources. Maintenance personnel often conduct inspection and maintenance work in a disorderly manner among the complex resources and equipment. At the same time, maintenance personnel also undertake troubleshooting and other tasks. There is no reasonable planning of inspection tasks, low execution efficiency and poor network quality. Summary of the invention

[0009] (-) Technical issues solved

[0010] In view of the shortcomings of the existing technology, the present invention provides a maintenance inspection path planning method, which has the advantages of accurately locating and optimizing the inspection path, high task execution efficiency and good network quality. It solves the problem that the maintenance inspection path planning algorithm cannot accurately locate and optimize the inspection path, and the task execution efficiency is low and the network quality is poor.

[0011] (II) Technical solution

[0012] To achieve the above object, the present invention provides the following technical solutions:

[0013] According to a first aspect of the present invention, a maintenance inspection path planning method is provided, the method comprising:

[0014] The positioning data of all inspection resources and fault alarm resources are collected in real time through GPS devices and GIS geographic information devices. The positioning data includes the latitude and longitude data collected by the GPS device and the map data collected by the GIS geographic information device, and all positioning data are classified into inspection data sets and fault data sets; among them, the inspection data set includes the grouped positioning data of all personnel and vehicles involved in the maintenance inspection task. The inspection data set expression is c represents the positioning data of the inspection vehicle involved in the maintenance inspection task, r represents the positioning data of the inspection personnel involved in the maintenance inspection task, to The longitude and latitude data and map data corresponding to each group of maintenance inspection personnel and vehicles in turn; the fault data set includes the location data of equipment fault alarm points in all level coverage scenarios, and the fault data set expression is: d represents the level data of the coverage scenario to which the equipment fault alarm point belongs. to Corresponding to the latitude and longitude data and map data of the equipment fault alarm point in each level coverage scenario;

[0015] According to the coverage scenario level of the equipment in the fault data set, the corresponding historical data set is collected. The historical data set includes the power outage duration, fault frequency and alarm frequency of the equipment. Then, the data of the inspection equipment is scored on a percentage basis. After scoring, the inspection equipment is divided into three levels: excellent, qualified and poor, and a maintenance inspection plan is dynamically formulated;

[0016] According to the coverage scenario level of the equipment in the fault data set and the power outage duration of the equipment in the historical data set, the corresponding collection equipment alarm level is used, and then the potential hidden dangers of the inspection equipment are scored on a percentage basis;

[0017] According to the hidden danger scoring results of the inspection equipment, the priority of path planning is determined, and the Dijksta algorithm and ant colony optimization algorithm are used to plan the optimal maintenance inspection path based on the inspection data set and fault data set.

[0018] Furthermore, according to the coverage scenario level of the equipment in the fault data set, a corresponding historical data set is collected, and the historical data set includes the power outage duration, fault frequency and alarm frequency of the equipment, and then the data of the inspection equipment are scored in percentage, including:

[0019] The equipment coverage scenario level score accounts for 25% of the total score, the equipment power outage duration score accounts for 20% of the total score, the equipment failure frequency score accounts for 45% of the total score, and the equipment alarm frequency score accounts for 10% of the total score;

[0020] There are four levels of equipment coverage scenario level settings, each level corresponds to a different score, the four levels are computer room level A, computer room level B, computer room level C and computer room level D, from computer room level A to computer room level A correspond to 5 points, 15 points, 20 points and 25 points respectively;

[0021] The equipment outage duration scoring is set with a fixed duration standard. First, the actual equipment outage duration is automatically calculated through a linear score. If the actual equipment outage duration exceeds the fixed duration standard, 5 points are awarded. If the actual equipment outage duration is equal to the fixed duration standard, 15 points are awarded. If the actual equipment outage duration is less than the fixed duration standard, 20 points are awarded.

[0022] Equipment failure frequency scoring is divided into stages according to the number of monthly failures. In the first stage, if the number of monthly failures is 0, 45 points are awarded. In the second stage, if the number of monthly failures is less than 3, 25 points are awarded. In the third stage, if the number of monthly failures is 3-10, 10 points are awarded. In the fourth stage, if the number of monthly failures is more than 10, 5 points are awarded.

[0023] The device alarm frequency scoring is set with a fixed frequency standard. If the device has an abnormal alarm, 5 points will be awarded. If the device alarm frequency does not exceed the fixed frequency standard, 10 points will be awarded.

[0024] Furthermore, after scoring, the inspection equipment is divided into three levels: excellent, qualified and poor, including:

[0025] Excellent: Scores above 85 points. No inspection plan is made for the month. If such equipment fails, a maintenance inspection work order is issued at the same time as the fault work order is generated. A maintenance inspection work order is only issued once a month for a network device. When the maintenance personnel handle the fault, they will inspect the base station simultaneously.

[0026] Pass: Scores are between 60-85 points. Inspection tasks are formulated according to the original plan. If such equipment fails, the inspection tasks are completed simultaneously with the fault handling. Inspections are conducted once a month at most.

[0027] Poor: The score is below 60 points. The inspection tasks are formulated according to the original plan and are arranged at the beginning of the month in priority. If there is no inspection task for this type of equipment, the equipment fails and the inspection task is completed simultaneously with the fault handling.

[0028] Furthermore, according to the coverage scenario level of the equipment in the fault data set and the power outage duration of the equipment in the historical data set, the corresponding collection equipment alarm level is scored on a percentage basis for the potential hidden dangers of the inspection equipment, including:

[0029] The equipment coverage scenario level score accounts for 30% of the total score, the equipment alarm level score accounts for 50% of the total score, and the equipment power outage duration score accounts for 20% of the total score;

[0030] There are four levels of equipment coverage scenario level, each level corresponds to a different score, the four levels are computer room level A, computer room level B, computer room level C and computer room level D, from computer room level A to computer room level A correspond to 30 points, 15 points, 10 points and 5 points respectively;

[0031] There are four levels of equipment alarm levels, each corresponding to different points. The four levels are level 1 alarm, level 2 alarm, level 3 alarm and level 4 alarm. Level 1 alarm to level 4 alarm correspond to 50 points, 30 points, 10 points and 5 points respectively.

[0032] The equipment power outage duration is set with three priority levels. Each priority level corresponds to a different score. The three priority levels are high priority, medium priority, and low priority, with scores of 20 points, 10 points, and 5 points respectively from high priority to low priority.

[0033] Further: in the inspection equipment hidden danger scoring result, for the equipment power outage duration item, if the equipment power outage duration score is 20 points, the inspection equipment hidden danger scoring result will note that the equipment is high priority power generation; if the equipment power outage duration score is 10 points, the inspection equipment hidden danger scoring result will note that the equipment is medium priority power generation; if the equipment power outage duration score is 5 points, the inspection equipment hidden danger scoring result will note that the equipment is low priority power generation.

[0034] Furthermore: according to the hidden danger scoring results of the inspection equipment, the priority of path planning is determined, and the inspection equipment with high scores takes precedence over the inspection equipment with low scores. If the hidden danger scoring results of multiple inspection equipment are equal, the Dijksta algorithm and ant colony optimization algorithm are used to plan the best maintenance inspection path.

[0035] Furthermore, the use of the Dijksta algorithm and the ant colony optimization algorithm to plan the optimal maintenance inspection path includes:

[0036] Inspection personnel based on inspection data set Establish an adjacency matrix to obtain the first path calculation information of other resources closest to the resource in the current area;

[0037] Determine the sameness of the first path calculation information and the second path calculation information in all the maintenance inspection task path calculation information;

[0038] If the first path calculation information and the second path calculation information are the same in all the maintenance inspection task path calculation information, the planned path corresponding to the second path calculation information is directly read;

[0039] When the same first path calculation information and second path calculation information do not exist in all the maintenance inspection task path calculation information, the best path of the first path calculation information is calculated in combination with the ant colony optimization algorithm.

[0040] Furthermore, the use of the Dijksta algorithm and the ant colony optimization algorithm to plan the optimal maintenance inspection path includes:

[0041] A Φmax is set in each path planning information, and the information content on the path is set to two extreme values ​​to meet the conditions of Φ:

[0042] Φmin when Φ≤Φmin

[0043] Φ when Φ∈[Φmin,Φmax]

[0044] Φmax when Φ≤Φmin

[0045] After each cycle, the best maintenance inspection path is updated, and other path planning information is not updated.

[0046] According to a second aspect of the present invention, an electronic device is provided, comprising a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the maintenance inspection path planning method is executed.

[0047] According to a third aspect of the present invention, a storage medium is provided, which stores a computer program that can be executed by one or more processors and can be used to implement the maintenance inspection path planning method.

[0048] Compared with the prior art, the present invention provides a maintenance inspection path planning method, which has the following features:

[0049] Beneficial effects:

[0050] 1. The present invention collects the positioning data of all inspection resources and fault alarm resources in real time through GPS devices and GIS geographic information devices. The positioning data includes the latitude and longitude data collected by the GPS device and the map data collected by the GIS geographic information device, and classifies all positioning data into inspection data sets and fault data sets. Accurate positioning helps to optimize the inspection path. According to the coverage scenario level of the equipment in the fault data set, a historical data set is collected accordingly. The historical data set includes the power outage duration of the equipment, the fault frequency and the alarm frequency. Then, each data of the inspection equipment is scored on a percentage basis. After scoring, the inspection equipment is divided into three levels: excellent, qualified and poor. A maintenance inspection plan is dynamically formulated. By establishing a corresponding relationship between inspection tasks and equipment alarm resources, the inspection task work order information, fault work order information and historical data are used to realize the association between the work order and the resource and the basic information of the resource.

[0051] 2. The present invention collects equipment alarm levels according to the coverage scenario levels of equipment in the fault data set and the power outage duration of equipment in the historical data set, and then scores the potential hidden dangers of the inspection equipment on a percentage basis, thereby realizing dynamic setting of special inspection methods for special geographical locations and real-time status information update between maintenance tasks. According to the hidden danger scoring results of the inspection equipment, the priority of path planning is determined, and according to the inspection data set and the fault data set, the Dijksta algorithm and the ant colony optimization algorithm are used to plan the best maintenance inspection path, with high task execution efficiency and good network quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The above and other features, advantages and aspects of the embodiments of the present invention will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are used to better understand the present invention and do not constitute a limitation of the present invention. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0053] Figure 1 A schematic diagram of a process flow of a maintenance inspection path planning method according to an embodiment of the present invention is shown;

[0054] Figure 2 A block diagram of an exemplary electronic device capable of implementing embodiments of the present invention is shown. DETAILED DESCRIPTION

[0055] 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.

[0056] Figure 1 A schematic diagram of a process flow of a maintenance inspection path planning method according to an embodiment of the present invention is shown, and the method includes:

[0057] S101, collect the positioning data of all inspection resources and fault alarm resources in real time through GPS devices and GIS geographic information devices, the positioning data includes the latitude and longitude data collected by the GPS devices and the map data collected by the GIS geographic information devices, and classify all positioning data into inspection data sets and fault data sets. Accurate positioning helps optimize the inspection path;

[0058] The inspection data set includes the grouped positioning data of all personnel and vehicles involved in the maintenance inspection task. The inspection data set expression is c represents the positioning data of the inspection vehicle involved in the maintenance inspection task, r represents the positioning data of the inspection personnel involved in the maintenance inspection task, to The latitude and longitude data and map data of each group of maintenance inspection personnel and vehicles are sequentially matched to accurately obtain the positioning data of the current inspection human resources and material resources, effectively solving the problem of being unable to accurately locate resources and the current inspection personnel in a large area, providing reliable data support for subsequent route planning, and achieving a positioning success rate of more than 99% for maintenance inspections;

[0059] The fault data set includes the location data of equipment fault alarm points in all level coverage scenarios. The fault data set expression is: d represents the level data of the coverage scenario to which the equipment fault alarm point belongs. to The latitude and longitude data and map data of the equipment fault alarm points in each level coverage scenario are sequentially provided to facilitate the subsequent association of network equipment fault handling tasks with daily maintenance inspection tasks;

[0060] S102, according to the coverage scenario level of the equipment in the fault data set, the corresponding historical data set is collected, and the historical data set includes the power outage duration of the equipment, the fault frequency and the alarm frequency, and then the data of the inspection equipment are scored in percentage. After scoring, the inspection equipment is divided into three levels: excellent, qualified and poor, and a maintenance inspection plan is dynamically formulated. By establishing a corresponding relationship between the inspection task and the equipment alarm resource, the inspection task work order information, the fault work order information and the historical data are used to realize the association between the work order and the resource and the basic information of the resource;

[0061] According to the fault data set and historical data set, the data of the inspection equipment are scored on a percentage basis. The percentage scoring rules are as follows:

[0062] The equipment coverage scenario level score accounts for 25% of the total score, the equipment power outage duration score accounts for 20% of the total score, the equipment failure frequency score accounts for 45% of the total score, and the equipment alarm frequency score accounts for 10% of the total score;

[0063] There are four levels of equipment coverage scenario level settings, each level corresponds to a different score, the four levels are computer room level A, computer room level B, computer room level C and computer room level D, from computer room level A to computer room level A correspond to 5 points, 15 points, 20 points and 25 points respectively;

[0064] The equipment outage duration scoring is set with a fixed duration standard. First, the actual equipment outage duration is automatically calculated through a linear score. If the actual equipment outage duration exceeds the fixed duration standard, 5 points are awarded. If the actual equipment outage duration is equal to the fixed duration standard, 15 points are awarded. If the actual equipment outage duration is less than the fixed duration standard, 20 points are awarded.

[0065] Equipment failure frequency scoring is divided into stages according to the number of monthly failures. In the first stage, if the number of monthly failures is 0, 45 points are awarded. In the second stage, if the number of monthly failures is less than 3, 25 points are awarded. In the third stage, if the number of monthly failures is 3-10, 10 points are awarded. In the fourth stage, if the number of monthly failures is more than 10, 5 points are awarded.

[0066] The device alarm frequency scoring is set with a fixed frequency standard. If the device has an abnormal alarm, 5 points will be awarded. If the device alarm frequency does not exceed the fixed frequency standard, 10 points will be awarded.

[0067] According to the scoring results, the inspection equipment is divided into the following three levels:

[0068] Excellent: Scores above 85 points. No inspection plan is made for the month. If such equipment fails, a maintenance inspection work order is issued at the same time as the fault work order is generated. A maintenance inspection work order is only issued once a month for a network device. When the maintenance personnel handle the fault, they will inspect the base station simultaneously.

[0069] Pass: Scores are between 60-85 points. Inspection tasks are formulated according to the original plan. If such equipment fails, the inspection tasks are completed simultaneously with the fault handling. Inspections are conducted once a month at most.

[0070] Poor: The score is below 60 points. Inspection tasks are formulated according to the original plan and are arranged at the beginning of the month first. If there is no inspection task for this type of equipment, and the equipment fails, the inspection task is completed simultaneously with the fault handling;

[0071] In the process of path planning, reasonable planning is carried out according to the task level instead of resource planning, which effectively speeds up the efficiency of inspection path planning and reduces the difficulty of algorithm and program development;

[0072] S103, according to the coverage scenario level of the equipment in the fault data set and the power outage duration of the equipment in the historical data set, the corresponding equipment alarm level is collected, and then the potential hidden dangers of the inspection equipment are scored on a percentage basis, so as to realize the dynamic setting of special inspection methods for special geographical locations and the real-time status information update between the maintenance tasks;

[0073] Based on the fault data set, historical data set and equipment alarm level, the potential hidden dangers of the inspection equipment are scored on a percentage basis. The scoring rules are as follows:

[0074] The equipment coverage scenario level score accounts for 30% of the total score, the equipment alarm level score accounts for 50% of the total score, and the equipment power outage duration score accounts for 20% of the total score;

[0075] There are four levels of equipment coverage scenario level, each level corresponds to a different score, the four levels are computer room level A, computer room level B, computer room level C and computer room level D, from computer room level A to computer room level A correspond to 30 points, 15 points, 10 points and 5 points respectively;

[0076] There are four levels of equipment alarm levels, each corresponding to different points. The four levels are level 1 alarm, level 2 alarm, level 3 alarm and level 4 alarm. Level 1 alarm to level 4 alarm correspond to 50 points, 30 points, 10 points and 5 points respectively.

[0077] The power outage duration of the equipment is set with three priority levels. Each priority level corresponds to a different score. The three priority levels are high priority, medium priority, and low priority. The scores from high priority to low priority are 20 points, 10 points, and 5 points respectively.

[0078] S104: Determine the priority of path planning based on the hidden danger scoring results of the inspection equipment, and use the Dijksta algorithm and ant colony optimization algorithm to plan the best maintenance inspection path based on the inspection data set and the fault data set, so that the task execution efficiency is high and the network quality is good;

[0079] In the inspection equipment hidden danger scoring result, if the equipment power outage duration score is 20 points, the inspection equipment hidden danger scoring result will note that the equipment is a high-priority power generation device; if the equipment power outage duration score is 10 points, the inspection equipment hidden danger scoring result will note that the equipment is a medium-priority power generation device; if the equipment power outage duration score is 5 points, the inspection equipment hidden danger scoring result will note that the equipment is a low-priority power generation device;

[0080] According to the hidden danger scoring results of the inspection equipment, the priority of the path planning is determined. The inspection equipment with high scores takes precedence over the inspection equipment with low scores. If the hidden danger scoring results of multiple inspection equipment are equal, the Dijksta algorithm and ant colony optimization algorithm are used to plan the best maintenance inspection path;

[0081] The hidden danger risk value is also the main factor affecting route planning. The larger the hidden danger risk value, the more optimal processing is required during route planning. For example, the real-time alarm status updates of three network inspection devices A, B, and C are all new states:

[0082]

[0083] According to the principle of priority processing, when the real-time road conditions and other conditions are good, the route planning will prioritize the processing of inspection equipment C, then the inspection equipment B, and finally the inspection equipment A;

[0084] The Dijksta algorithm is used to plan the optimal maintenance inspection route. The planning process is as follows:

[0085] Inspection personnel based on inspection data set Establish an adjacency matrix to obtain the first path calculation information of other resources closest to the resource in the current area;

[0086] Determine the sameness of the first path calculation information and the second path calculation information in all the maintenance inspection task path calculation information;

[0087] If the first path calculation information and the second path calculation information are the same in all the maintenance inspection task path calculation information, the planned path corresponding to the second path calculation information is directly read;

[0088] When the same first path calculation information and second path calculation information do not exist in all maintenance inspection task path calculation information, the best path of the first path calculation information is calculated by combining the ant colony optimization algorithm. This path planning method makes the optimization faster and can meet the high real-time requirements in the planning process. In addition, the path planning file can be continuously updated so that the used path is continuously optimized.

[0089] Optimal path model establishment:

[0090] The communication network inspection path is a traffic path from the road intersection closest to the current resource point to the road intersection closest to the next inspection task point. The weight of the path line will be determined by the length of the road, real-time traffic conditions and other information. Therefore, the road can be abstracted as a weighted directed graph. A weighted directed graph is given as a binary tuple G = (V, {E}), where V is a set of n nodes, E is a set of h edges, (i, j) is the edge from node i to node j in E, if there is a direct edge from vertex i to vertex j, then X& = 1, otherwise X& = 0, ω& represents the non-negative weight of (i, j), let S and T be the starting point and target node in V respectively, then the optimal path is to search for a path from S to T in the weighted directed graph, and the path weight is the smallest, so the shortest path formula for the inspection task is:

[0091]

[0092] The ant colony optimization algorithm is used to plan the best maintenance inspection route. The planning process is as follows:

[0093] A Φmax is set in each path planning information. The update of each path information does not have a particularly obvious impact on the path refinement system. In this way, the algorithm will have a larger operation space, effectively preventing the local optimal solution problem caused by the accumulation of a large amount of path information. The information content on the path is set to two extreme values ​​to meet the conditions of Φ:

[0094] Φmin when Φ≤Φmin

[0095] Φ when Φ∈[Φmin,Φmax]

[0096] Φmax when Φ≤Φmin

[0097] After each cycle, the best maintenance inspection path is updated, and other path planning information is not updated, so the task execution efficiency is high and the network quality is good;

[0098] The optimized algorithm is different from the traditional programming mode, avoiding lengthy programming and planning. The program itself is based on certain rules, such as random operation of base station level, type, inspection task information, and timestamp information to find the best configuration. When the program first finds the target, the path is almost impossible to be optimal, and it may even contain countless wrong choices and be extremely lengthy. However, the program can continuously correct the original route based on the information of multiple searches to make the entire route shorter and shorter. In other words, the more times the program is executed, the more likely the obtained path is to be close to the optimal path. Through the algorithm, the path information of each site can be recorded after multiple inspections to provide basic data for other subsequent inspection paths, which mainly includes the following information:

[0099] Selection mechanism: The more information a path has, the greater the probability of being selected. The more information a path has, the more times it will be selected.

[0100] Update mechanism: The information on the path will increase as the number of searches increases. After the search, the search information will be recorded as a basis for future searches.

[0101] According to an embodiment of the present invention, the present invention also provides an electronic device and a readable storage medium.

[0102] Figure 2 A schematic block diagram of an electronic device that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0103] The electronic device includes a computing unit 201, which can perform various appropriate actions and processes according to a computer program stored in ROM 202 or a computer program loaded from a storage unit 208 into RAM 203. In RAM 203, various programs and data required for the operation of the electronic device can also be stored. The computing unit 201, ROM 202, and RAM 203 are connected to each other via a bus 204. An I / O interface 205 is also connected to the bus 204.

[0104] A number of components in the electronic device are connected to the I / O interface 205, including: an input unit 206, such as a keyboard, a mouse, etc.; an output unit 207, such as various types of displays, speakers, etc.; a storage unit 208, such as a disk, an optical disk, etc.; and a communication unit 209, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 209 allows the electronic device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0105] The computing unit 201 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 201 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 201 performs the various methods and processes described above. For example, in some embodiments, the maintenance inspection path planning method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 208. In some embodiments, part or all of the computer program may be loaded and / or installed on an electronic device via ROM 202 and / or a communication unit 209. When the computer program is loaded into RAM 203 and executed by the computing unit 201, one or more steps of the maintenance inspection path planning method described above may be performed. Alternatively, in other embodiments, the computing unit 201 may be configured to perform the maintenance inspection path planning method in any other appropriate manner (e.g., by means of firmware).

[0106] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0107] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0108] In the context of the present invention, a readable storage medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A readable storage medium may be a machine-readable signal medium or a machine-readable storage medium. A readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. More specific examples of readable storage media may include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0109] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0110] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communications network). Examples of communications networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0111] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0112] 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 maintenance inspection route planning method, characterized in that: include: The positioning data of all inspection resources and fault alarm resources are collected in real time through GPS devices and GIS geographic information devices. The positioning data includes the latitude and longitude data collected by the GPS device and the map data collected by the GIS geographic information device, and all positioning data are classified into inspection data sets and fault data sets; among them, the inspection data set includes the grouped positioning data of all personnel and vehicles involved in the maintenance inspection task. The inspection data set expression is c represents the positioning data of the inspection vehicle involved in the maintenance inspection task, r represents the positioning data of the inspection personnel involved in the maintenance inspection task, to The longitude and latitude data and map data corresponding to each group of maintenance inspection personnel and vehicles in turn; the fault data set includes the location data of equipment fault alarm points in all level coverage scenarios, and the fault data set expression is: d represents the level data of the coverage scenario to which the equipment fault alarm point belongs. to Corresponding to the latitude and longitude data and map data of the equipment fault alarm point in each level coverage scenario; According to the coverage scenario level of the equipment in the fault data set, the corresponding historical data set is collected. The historical data set includes the power outage duration, fault frequency and alarm frequency of the equipment. Then, the data of the inspection equipment is scored on a percentage basis. After scoring, the inspection equipment is divided into three levels: excellent, qualified and poor, and a maintenance inspection plan is dynamically formulated; According to the coverage scenario level of the equipment in the fault data set and the power outage duration of the equipment in the historical data set, the corresponding collection equipment alarm level is used, and then the potential hidden dangers of the inspection equipment are scored on a percentage basis; According to the hidden danger scoring results of the inspection equipment, the priority of path planning is determined, and the Dijksta algorithm and ant colony optimization algorithm are used to plan the optimal maintenance inspection path based on the inspection data set and fault data set.

2. The method for planning a maintenance inspection path according to claim 1, characterized in that: According to the coverage scenario level of the equipment in the fault data set, the historical data set is collected accordingly. The historical data set includes the power outage duration, fault frequency and alarm frequency of the equipment, and then the data of the inspection equipment are scored in percentage, including: The equipment coverage scenario level score accounts for 25% of the total score, the equipment power outage duration score accounts for 20% of the total score, the equipment failure frequency score accounts for 45% of the total score, and the equipment alarm frequency score accounts for 10% of the total score; There are four levels of equipment coverage scenario level settings, each level corresponds to a different score, the four levels are computer room level A, computer room level B, computer room level C and computer room level D, from computer room level A to computer room level A correspond to 5 points, 15 points, 20 points and 25 points respectively; The equipment outage duration scoring is set with a fixed duration standard. First, the actual equipment outage duration is automatically calculated through a linear score. If the actual equipment outage duration exceeds the fixed duration standard, 5 points are awarded. If the actual equipment outage duration is equal to the fixed duration standard, 15 points are awarded. If the actual equipment outage duration is less than the fixed duration standard, 20 points are awarded. Equipment failure frequency scoring is divided into stages according to the number of monthly failures. In the first stage, if the number of monthly failures is 0, 45 points are awarded. In the second stage, if the number of monthly failures is less than 3, 25 points are awarded. In the third stage, if the number of monthly failures is 3-10, 10 points are awarded. In the fourth stage, if the number of monthly failures is more than 10, 5 points are awarded. The device alarm frequency scoring is set with a fixed frequency standard. If the device has an abnormal alarm, 5 points will be awarded. If the device alarm frequency does not exceed the fixed frequency standard, 10 points will be awarded.

3. The method for planning a maintenance inspection path according to claim 2, characterized in that: After the scoring, the inspection equipment is divided into three levels: excellent, qualified and poor, including: Excellent: Scores above 85 points. No inspection plan is made for the month. If such equipment fails, a maintenance inspection work order is issued at the same time as the fault work order is generated. A maintenance inspection work order is only issued once a month for a network device. When the maintenance personnel handle the fault, they will inspect the base station simultaneously. Pass: Scores are between 60-85 points. Inspection tasks are formulated according to the original plan. If such equipment fails, the inspection tasks are completed simultaneously with the fault handling. Inspections are conducted once a month at most. Poor: The score is below 60 points. The inspection tasks are formulated according to the original plan and are arranged at the beginning of the month in priority. If there is no inspection task for this type of equipment, the equipment fails and the inspection task is completed simultaneously with the fault handling.

4. The method for planning a maintenance inspection path according to claim 3, characterized in that: According to the coverage scenario level of the equipment in the fault data set and the power outage duration of the equipment in the historical data set, the corresponding collection equipment alarm level is scored on a percentage basis for the potential hidden dangers of the inspection equipment, including: The equipment coverage scenario level score accounts for 30% of the total score, the equipment alarm level score accounts for 50% of the total score, and the equipment power outage duration score accounts for 20% of the total score; There are four levels of equipment coverage scenario level, each level corresponds to a different score, the four levels are computer room level A, computer room level B, computer room level C and computer room level D, from computer room level A to computer room level A correspond to 30 points, 15 points, 10 points and 5 points respectively; There are four levels of equipment alarm levels, each corresponding to different points. The four levels are level 1 alarm, level 2 alarm, level 3 alarm and level 4 alarm. Level 1 alarm to level 4 alarm correspond to 50 points, 30 points, 10 points and 5 points respectively. The equipment power outage duration is set with three priority levels. Each priority level corresponds to a different score. The three priority levels are high priority, medium priority, and low priority, with scores of 20 points, 10 points, and 5 points respectively from high priority to low priority.

5. The method for planning a maintenance inspection path according to claim 4, characterized in that: In the inspection equipment hidden danger scoring result, for the equipment power outage duration item, if the equipment power outage duration score is 20 points, the inspection equipment hidden danger scoring result will note that the equipment is high priority power generation; if the equipment power outage duration score is 10 points, the inspection equipment hidden danger scoring result will note that the equipment is medium priority power generation; if the equipment power outage duration score is 5 points, the inspection equipment hidden danger scoring result will note that the equipment is low priority power generation.

6. The method for planning a maintenance inspection path according to claim 5, characterized in that: According to the hidden danger scoring results of the inspection equipment, the priority of path planning is determined. Inspection equipment with high scores takes precedence over those with low scores. If the hidden danger scoring results of multiple inspection equipment are equal, the Dijksta algorithm and ant colony optimization algorithm are used to plan the optimal maintenance inspection path.

7. The method for planning a maintenance inspection path according to claim 6, characterized in that: The Dijksta algorithm and ant colony optimization algorithm are used to plan the best maintenance inspection path, including: Inspection personnel based on inspection data set Establish an adjacency matrix to obtain the first path calculation information of other resources closest to the resource in the current area; Determine the sameness of the first path calculation information and the second path calculation information in all the maintenance inspection task path calculation information; If the first path calculation information and the second path calculation information are the same in all the maintenance inspection task path calculation information, the planned path corresponding to the second path calculation information is directly read; When the same first path calculation information and second path calculation information do not exist in all the maintenance inspection task path calculation information, the best path of the first path calculation information is calculated in combination with the ant colony optimization algorithm.

8. The method for planning a maintenance inspection path according to claim 7, characterized in that: The Dijksta algorithm and ant colony optimization algorithm are used to plan the best maintenance inspection path, including: A Φmax is set in each path planning information, and the information content on the path is set to two extreme values ​​to meet the conditions of Φ: Φmin when Φ≤Φmin Φ when Φ∈[Φmin,Φmax] Φmax when Φ≤Φmin After each cycle, the best maintenance inspection path is updated, and other path planning information is not updated.

9. An electronic device, characterized in that: It includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the maintenance inspection path planning method as described in any one of claims 1 to 8 is executed.

10. A storage medium, characterized in that: The computer program stored in the storage medium can be executed by one or more processors and can be used to implement the maintenance inspection path planning method as described in any one of claims 1 to 8.

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