CN115938009B - Intelligent electronic inspection positioning method and system - Google Patents
Intelligent electronic inspection positioning method and system Download PDFInfo
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- CN115938009B CN115938009B CN202310209145.1A CN202310209145A CN115938009B CN 115938009 B CN115938009 B CN 115938009B CN 202310209145 A CN202310209145 A CN 202310209145A CN 115938009 B CN115938009 B CN 115938009B
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Abstract
The invention provides an intelligent electronic inspection positioning method, which comprises the steps of obtaining a target area containing an importance level; the target area is represented by a three-dimensional coordinate set; determining a limit track according to the target area, and determining a speed function of the patrol inspector according to the importance level; receiving an inspection requirement input by a user, and determining the types and the number of the inspection devices according to the inspection requirement; and acquiring a patrol image fed back by the patrol device in real time, identifying the patrol image, and generating a patrol report. The invention also provides an intelligent electronic inspection positioning system. According to the invention, a limit track is determined according to a target area input by a management party, a preset number of patrol detectors with the same movement condition are arranged in the limit track, and all-round timing patrol is carried out on staff; in addition, the work flow of the patrol inspector can be easily changed, the regularity is weak, the evasive response is difficult to be made by staff, and the comprehensive patrol inspection is greatly improved.
Description
Technical Field
The invention relates to the technical field of regional inspection, in particular to an intelligent electronic inspection positioning method and system.
Background
With the improvement of productivity, production activities are more and more, and inspection links exist in the production activities, so that the safety of the production activities is ensured, and illegal operations of workers are prevented.
The existing inspection mode mostly relies on manual regular inspection, the inspection by inspection personnel is regular, because the inspection work is repeated and boring, many inspection personnel can be idle in work, and some detail problems are difficult to find, in practice, after the working habit of the inspection personnel is mastered by the staff, the inspection by the inspection personnel is easy to avoid, and therefore, the inspection by the inspection personnel mostly only has a frightening effect. How to ensure the comprehensiveness and the easy fatigue degree of the inspection work is a technical problem to be solved by the technical scheme of the invention.
Disclosure of Invention
The invention aims to provide an intelligent electronic inspection positioning method and system, which are used for solving the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions:
an intelligent electronic patrol positioning method, the method comprising:
acquiring a target area containing an importance level; the target area is represented by a three-dimensional coordinate set;
determining a limit track according to the target area, and determining a speed function of the patrol inspector according to the importance level;
receiving an inspection requirement input by a user, and determining the types and the number of the inspection devices according to the inspection requirement;
and acquiring a patrol image fed back by the patrol device in real time, identifying the patrol image, and generating a patrol report.
As a further scheme of the invention: the step of acquiring the target area containing the importance level includes:
receiving boundary information input by a user, and constructing a global scene containing a preset scale according to the boundary information;
receiving a target area selected by a user based on the global scene, and determining an observation area of the target area;
determining an observation point in the observation area, and acquiring an actual scene of the target area at the observation point;
identifying the actual scene according to the recorded facility database, and correcting the global scene according to the identification result; in the correction process of the global scene, the target area is regulated in real time according to the correction process of the global scene;
and displaying the corrected global scene containing the target areas, and receiving confirmation information sent by the user and the importance levels of the target areas.
As a further scheme of the invention: the step of determining a limit track according to the target area and determining a speed function of the patrol inspector according to the importance level comprises the following steps:
reading an observation area of a target area, and acquiring the height span of the observation area;
selecting a track surface in the height span;
projecting the target area on the track surface to obtain an area distribution map;
determining a limit track based on the regional distribution map;
determining a sampling point in the limit track according to a preset sampling frequency, inquiring an importance level of a nearest target area corresponding to the sampling point, and determining a movement speed according to the importance level;
counting all the motion speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limit track, and the dependent variable is the speed.
As a further scheme of the invention: the step of receiving the inspection requirement input by the user and determining the type and the number of the inspection devices according to the inspection requirement comprises the following steps:
inquiring definition requirements of all target areas, and determining the type of the patrol inspector according to the definition requirements;
and receiving a patrol period input by a user, and determining the number of patrol detectors according to the patrol period.
As a further scheme of the invention: the step of acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image and generating an inspection report comprises the following steps:
acquiring a patrol image containing a position tag fed back by a patrol device in real time; the position is a distance relative to the starting point of the limit track;
inquiring a target area corresponding to the inspection image according to the position, and storing the target area into a database corresponding to the target area; wherein the image storage order in the database is determined by the image acquisition time;
identifying different databases based on preset threads, and determining risk characteristics and probability of different target areas according to identification results;
and counting all risk characteristics and probability thereof to obtain a patrol report.
As a further scheme of the invention: the step of identifying different databases based on preset threads and determining risk characteristics and probability of different target areas according to the identification result comprises the following steps:
sequentially identifying inspection images within a preset time period range in a database based on a preset neural network model, and acquiring equipment information and personnel information;
inquiring personnel requirements according to the equipment information, verifying personnel information according to the personnel requirements, and determining the abnormal degree corresponding to each inspection image;
counting the degree of abnormality, fitting an abnormal curve and calculating a derivative curve of a preset order of the abnormal curve;
and inputting the abnormal curve and the derivative curve thereof into a trained curve analysis model to obtain risk characteristics and probability thereof.
The technical scheme of the invention also provides an intelligent electronic inspection position system, which comprises:
the target area acquisition module is used for acquiring a target area containing an important level; the target area is represented by a three-dimensional coordinate set;
the path setting module is used for determining a limit track according to the target area and determining a speed function of the patrol inspector according to the importance level;
the inspection device selecting module is used for receiving the inspection requirement input by a user and determining the types and the quantity of the inspection devices according to the inspection requirement;
and the report generation module is used for acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image and generating an inspection report.
As a further scheme of the invention: the target area acquisition module includes:
the global building unit is used for receiving boundary information input by a user and building a global scene containing a preset scale according to the boundary information;
an observation area determining unit, configured to receive a target area selected by a user based on the global scene, and determine an observation area of the target area;
the actual scene acquisition unit is used for determining an observation point position in the observation area and acquiring an actual scene of the target area at the observation point position;
the global scene correction unit is used for identifying the actual scene according to the recorded facility database and correcting the global scene according to the identification result; in the correction process of the global scene, the target area is regulated in real time according to the correction process of the global scene;
and the level receiving unit is used for displaying the corrected global scene containing the target areas and receiving confirmation information sent by the user and the importance level of each target area.
As a further scheme of the invention: the path setting module includes:
the span acquisition unit is used for reading the observation area of the target area and acquiring the height span of the observation area;
a track surface selecting unit, configured to select a track surface in the height span;
the distribution map determining unit is used for projecting the target area on the track surface to obtain an area distribution map;
the track determining unit is used for determining a limit track based on the regional distribution map;
the speed determining unit is used for determining sampling points in the limiting track according to preset sampling frequency, inquiring importance levels of the nearest target areas corresponding to the sampling points and determining movement speed according to the importance levels;
the speed statistics unit is used for counting all the movement speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limit track, and the dependent variable is the speed.
As a further scheme of the invention: the patrol inspection device selection module comprises:
the type selection unit is used for inquiring the definition requirements of all the target areas and determining the type of the patrol inspector according to the definition requirements;
the quantity selecting unit is used for receiving the inspection period input by the user and determining the quantity of the inspection devices according to the inspection period.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, a limit track is determined according to a target area input by a management party, a preset number of patrol detectors with the same movement condition are arranged in the limit track, and all-round timing patrol is carried out on staff; in addition, the work flow of the patrol inspector can be easily changed, the regularity is weak, the evasive response is difficult to be made by staff, and the comprehensive patrol inspection is greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following description will briefly introduce the drawings that are needed in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
FIG. 1 is a block flow diagram of an intelligent electronic patrol positioning method.
Fig. 2 is a first sub-flowchart of the intelligent electronic patrol positioning method.
FIG. 3 is a second sub-flow diagram of an intelligent electronic patrol positioning method.
Fig. 4 is a third sub-flowchart of the intelligent electronic patrol positioning method.
Fig. 5 is a fourth sub-flowchart of the intelligent electronic patrol positioning method.
Fig. 6 is a block diagram of the composition and structure of the intelligent electronic inspection positioning system.
Description of the embodiments
In order to make the technical problems, technical schemes and beneficial effects to be solved more clear, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Example 1
Fig. 1 is a flow chart of an intelligent electronic inspection positioning method, in an embodiment of the invention, an intelligent electronic inspection positioning method includes:
step S100: acquiring a target area containing an importance level; the target area is represented by a three-dimensional coordinate set;
the target area is an area needing to be inspected, and in a workshop or a work area, the area needing to be inspected is predetermined by a worker; the area to be inspected is a range, which is a three-dimensional range, and the three-dimensional range is determined by three-dimensional coordinates, which point to points on the boundary of the three-dimensional range.
Step S200: determining a limit track according to the target area, and determining a speed function of the patrol inspector according to the importance level;
after the target area is determined, a limit track can be determined according to the position of the target area, and the limit track is used for limiting the patrol inspector; in the hardware architecture, the limit track may be a track on which the patrol inspector moves; when the patrol inspector moves on the track and moves to different target areas, the movement speed of the patrol inspector is determined according to the corresponding importance level, and the higher the importance level is, the lower the speed of the patrol inspector is.
Step S300: receiving an inspection requirement input by a user, and determining the types and the number of the inspection devices according to the inspection requirement;
the inspection requirements are input by a user, the user determines how long to inspect once and how much definition is needed for each target area at least according to the actual condition of a working area, how long to inspect once represents how many inspection devices are placed, and the movement process of each inspection device is the same; the required resolution determines the type of patrol.
Step S400: acquiring a patrol image fed back by a patrol device in real time, identifying the patrol image, and generating a patrol report;
and acquiring the inspection data fed back by the inspection device in real time, wherein the inspection data is image data, identifying the image data, so that the analysis result of each target area can be obtained, and counting the analysis result of each target area, thereby obtaining the whole inspection report.
FIG. 2 is a first sub-flowchart of an intelligent electronic patrol positioning method, wherein the step of obtaining a target area containing importance levels comprises:
step S101: receiving boundary information input by a user, and constructing a global scene containing a preset scale according to the boundary information;
the boundary information is input by a user, and a global scene corresponding to the whole working area to be analyzed can be determined by the boundary information; typically, the global scene is a cube.
Step S102: receiving a target area selected by a user based on the global scene, and determining an observation area of the target area;
after the global scene is built, the user inputs selection information, and a target area is determined according to the selection information, wherein the target area can be a three-dimensional curved surface or a plane, and in the global scene, an observation area of the target area can be determined according to a sight rule.
Step S103: determining an observation point in the observation area, and acquiring an actual scene of the target area at the observation point;
determining an observation point in the observation area, and acquiring an actual scene of the target area at the observation point; in colloquial terms, an actual image of the target area is taken at each observation point as an actual scene.
Step S104: identifying the actual scene according to the recorded facility database, and correcting the global scene according to the identification result; in the correction process of the global scene, the target area is regulated in real time according to the correction process of the global scene;
the comparison type identification is carried out on the actual scene, and because the facilities in one working area are limited, the comparison type identification process is very simple and easy to complete; according to the identification result, which facilities are in each position in the global scene can be queried, and then the global scene is adjusted, so that the global scene which is more in line with reality is obtained.
Step S105: displaying the corrected global scene containing the target areas, and receiving confirmation information sent by a user and the importance level of each target area;
displaying the corrected global scene containing the target area, judging by a user, and if the user considers that the problem does not exist, sending confirmation information and the importance level thereof; the importance level is used to characterize the importance level of each target area.
FIG. 3 is a second sub-flowchart of the intelligent electronic inspection positioning method, wherein the steps of determining a limit track according to the target area and determining a speed function of the inspection device according to the importance level include:
step S201: reading an observation area of a target area, and acquiring the height span of the observation area;
reading the observation areas of all the target areas, and acquiring the height span of the observation areas;
step S202: selecting a track surface in the height span;
comparing all height spans, a detection height, namely the track surface, can be determined; the types of the track surfaces are many, and one track surface is selected randomly.
Step S203: projecting the target area on the track surface to obtain an area distribution map;
the target area is a three-dimensional area, and the three-dimensional area is projected to obtain an area distribution map.
Step S204: determining a limit track based on the regional distribution map;
and determining a limit track in the regional distribution diagram, wherein the limit track is required to acquire information of all target regions in the movement process of the limit track by the patrol inspector.
Step S205: determining a sampling point in the limit track according to a preset sampling frequency, inquiring an importance level of a nearest target area corresponding to the sampling point, and determining a movement speed according to the importance level;
and cutting the limit track to obtain sampling points, inquiring the nearest target area at each sampling point, and determining the current movement speed according to the importance level of the nearest target area.
Step S206: counting all the motion speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limit track, and the dependent variable is the speed;
counting all the motion speeds to obtain a speed function; the independent variable of the speed function is not time, but is a distance from the start point of the limit track.
FIG. 4 is a third sub-flowchart of the intelligent electronic inspection positioning method, wherein the steps of receiving an inspection requirement input by a user and determining the type and the number of the inspection devices according to the inspection requirement comprise:
step S301: inquiring definition requirements of all target areas, and determining the type of the patrol inspector according to the definition requirements;
step S302: and receiving a patrol period input by a user, and determining the number of patrol detectors according to the patrol period.
The process of determining the type and number of patrol machines is not difficult, the type is determined by the cleaning demand, and the number is determined by the patrol cycle.
FIG. 5 is a fourth sub-flowchart of the intelligent electronic inspection positioning method, wherein the steps of acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image, and generating an inspection report include:
step S401: acquiring a patrol image containing a position tag fed back by a patrol device in real time; the position is a distance relative to the starting point of the limit track;
and establishing a connection channel between the inspection device and the inspection device, and acquiring an inspection image based on the connection channel.
Step S402: inquiring a target area corresponding to the inspection image according to the position, and storing the target area into a database corresponding to the target area; wherein the image storage order in the database is determined by the image acquisition time;
the position of the patrol inspector corresponds to the target area, and the target area corresponding to the patrol image is inquired by the position, namely the target area corresponding to the patrol image; each target area is provided with a database belonging to the target area, and the inspection images are stored in the corresponding database; the elements in the database are ordered by time.
Step S403: identifying different databases based on preset threads, and determining risk characteristics and probability of different target areas according to identification results;
and identifying databases of different target areas to obtain risk characteristics of each target area and probability of occurrence of the risk characteristics.
Step S404: counting all risk characteristics and probability thereof to obtain a patrol report;
and counting risk characteristics of all target areas and probability of occurrence of the risk characteristics, and generating a patrol report.
As a preferred embodiment of the present invention, the step of identifying different databases based on the preset threads, and determining risk features and probabilities thereof of different target areas according to the identification result includes:
sequentially identifying inspection images within a preset time period range in a database based on a preset neural network model, and acquiring equipment information and personnel information;
the inspection image belongs to an image in a global scene, the types of the inspection image are limited, and equipment information and personnel information can be obtained by only training a neural network model according to a pre-acquired sample and then identifying the inspection image based on the neural network model when a new inspection image is received; the equipment information comprises equipment types and the levels and the numbers of staff needed by the equipment; the personnel information includes the level and number of personnel already present in the current target area.
Inquiring personnel requirements according to the equipment information, verifying personnel information according to the personnel requirements, and determining the abnormal degree corresponding to each inspection image;
inquiring personnel requirements according to the equipment information, verifying whether personnel information has problems according to the personnel requirements, and determining the abnormality degree of each inspection image; for example, where two technicians are required, only one technician may have a degree of anomaly; if there is no technician, the degree of anomaly is high.
Counting the degree of abnormality, fitting an abnormal curve and calculating a derivative curve of a preset order of the abnormal curve;
counting the abnormal degree of the inspection images at different times, obtaining an abnormal curve, and conducting derivation on the abnormal curve for multiple times to obtain derivative curves with different orders.
Inputting the abnormal curve and the guide curve thereof into a trained curve analysis model to obtain risk characteristics and probability thereof;
the mapping relation exists between the abnormal curve and the guide curve thereof and the risk characteristics and the probability thereof, and the mapping relation is autonomously determined by staff according to the sample and the actual situation, and the invention is not repeated.
Wherein the risk features include at least this type:
risk characteristics: the equipment management personnel are not enough; probability: 80%.
It should be noted that under the architecture of the technical scheme of the invention, other recognition algorithms can be introduced, so as to determine different risk characteristics and occurrence probabilities of the equipment.
Example 2
Fig. 6 is a block diagram of the composition and structure of an intelligent electronic inspection and verification system, in which, in an embodiment of the present invention, the system 10 includes:
a target region acquisition module 11 for acquiring a target region containing an importance level; the target area is represented by a three-dimensional coordinate set;
the path setting module 12 is configured to determine a limit track according to the target area, and determine a speed function of the patrol instrument according to the importance level;
the patrol device selecting module 13 is used for receiving the patrol requirement input by a user and determining the types and the number of the patrol devices according to the patrol requirement;
and the report generation module 14 is used for acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image and generating an inspection report.
The target area acquisition module 11 includes:
the global building unit is used for receiving boundary information input by a user and building a global scene containing a preset scale according to the boundary information;
an observation area determining unit, configured to receive a target area selected by a user based on the global scene, and determine an observation area of the target area;
the actual scene acquisition unit is used for determining an observation point position in the observation area and acquiring an actual scene of the target area at the observation point position;
the global scene correction unit is used for identifying the actual scene according to the recorded facility database and correcting the global scene according to the identification result; in the correction process of the global scene, the target area is regulated in real time according to the correction process of the global scene;
and the level receiving unit is used for displaying the corrected global scene containing the target areas and receiving confirmation information sent by the user and the importance level of each target area.
The path setting module 12 includes:
the span acquisition unit is used for reading the observation area of the target area and acquiring the height span of the observation area;
a track surface selecting unit, configured to select a track surface in the height span;
the distribution map determining unit is used for projecting the target area on the track surface to obtain an area distribution map;
the track determining unit is used for determining a limit track based on the regional distribution map;
the speed determining unit is used for determining sampling points in the limiting track according to preset sampling frequency, inquiring importance levels of the nearest target areas corresponding to the sampling points and determining movement speed according to the importance levels;
the speed statistics unit is used for counting all the movement speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limit track, and the dependent variable is the speed.
The patrol selecting module 13 includes:
the type selection unit is used for inquiring the definition requirements of all the target areas and determining the type of the patrol inspector according to the definition requirements;
the quantity selecting unit is used for receiving the inspection period input by the user and determining the quantity of the inspection devices according to the inspection period.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (8)
1. An intelligent electronic inspection positioning method, which is characterized by comprising the following steps:
acquiring a target area containing an importance level; the target area is represented by a three-dimensional coordinate set;
determining a limit track according to the target area, and determining a speed function of the patrol inspector according to the importance level;
receiving an inspection requirement input by a user, and determining the types and the number of the inspection devices according to the inspection requirement;
acquiring a patrol image fed back by a patrol device in real time, identifying the patrol image, and generating a patrol report;
the step of determining a limit track according to the target area and determining a speed function of the patrol inspector according to the importance level comprises the following steps:
reading an observation area of a target area, and acquiring the height span of the observation area;
selecting a track surface in the height span;
projecting the target area on the track surface to obtain an area distribution map;
determining a limit track based on the regional distribution map;
determining a sampling point in the limit track according to a preset sampling frequency, inquiring an importance level of a nearest target area corresponding to the sampling point, and determining a movement speed according to the importance level;
counting all the motion speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limit track, and the dependent variable is the speed.
2. The intelligent electronic patrol positioning method according to claim 1, wherein said step of obtaining a target area containing a level of importance comprises:
receiving boundary information input by a user, and constructing a global scene containing a preset scale according to the boundary information;
receiving a target area selected by a user based on the global scene, and determining an observation area of the target area;
determining an observation point in the observation area, and acquiring an actual scene of the target area at the observation point;
identifying the actual scene according to the recorded facility database, and correcting the global scene according to the identification result; in the correction process of the global scene, the target area is regulated in real time according to the correction process of the global scene;
and displaying the corrected global scene containing the target areas, and receiving confirmation information sent by the user and the importance levels of the target areas.
3. The intelligent electronic inspection location method according to claim 1, wherein the step of receiving the user input of the inspection requirement and determining the type and number of the inspection devices according to the inspection requirement comprises:
inquiring definition requirements of all target areas, and determining the type of the patrol inspector according to the definition requirements;
and receiving a patrol period input by a user, and determining the number of patrol detectors according to the patrol period.
4. The intelligent electronic inspection positioning method according to claim 1, wherein the step of acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image, and generating the inspection report comprises:
acquiring a patrol image containing a position tag fed back by a patrol device in real time; the position is a distance relative to the starting point of the limit track;
inquiring a target area corresponding to the inspection image according to the position, and storing the target area into a database corresponding to the target area; wherein the image storage order in the database is determined by the image acquisition time;
identifying different databases based on preset threads, and determining risk characteristics and probability of different target areas according to identification results;
and counting all risk characteristics and probability thereof to obtain a patrol report.
5. The intelligent electronic inspection positioning method according to claim 4, wherein the step of identifying different databases based on preset threads and determining risk characteristics and probabilities thereof of different target areas according to the identification result comprises:
sequentially identifying inspection images within a preset time period range in a database based on a preset neural network model, and acquiring equipment information and personnel information;
inquiring personnel requirements according to the equipment information, verifying personnel information according to the personnel requirements, and determining the abnormal degree corresponding to each inspection image;
counting the degree of abnormality, fitting an abnormal curve and calculating a derivative curve of a preset order of the abnormal curve;
and inputting the abnormal curve and the derivative curve thereof into a trained curve analysis model to obtain risk characteristics and probability thereof.
6. An intelligent electronic patrol positioning system, the system comprising:
the target area acquisition module is used for acquiring a target area containing an important level; the target area is represented by a three-dimensional coordinate set;
the path setting module is used for determining a limit track according to the target area and determining a speed function of the patrol inspector according to the importance level;
the inspection device selecting module is used for receiving the inspection requirement input by a user and determining the types and the quantity of the inspection devices according to the inspection requirement;
the report generation module is used for acquiring the inspection image fed back by the inspection device in real time, identifying the inspection image and generating an inspection report;
wherein, the path setting module includes:
the span acquisition unit is used for reading the observation area of the target area and acquiring the height span of the observation area;
a track surface selecting unit, configured to select a track surface in the height span;
the distribution map determining unit is used for projecting the target area on the track surface to obtain an area distribution map;
the track determining unit is used for determining a limit track based on the regional distribution map;
the speed determining unit is used for determining sampling points in the limiting track according to preset sampling frequency, inquiring importance levels of the nearest target areas corresponding to the sampling points and determining movement speed according to the importance levels;
the speed statistics unit is used for counting all the movement speeds to obtain a speed function; the independent variable of the speed function is the distance relative to the starting point of the limit track, and the dependent variable is the speed.
7. The intelligent electronic patrol positioning system according to claim 6, wherein said target area acquisition module comprises:
the global building unit is used for receiving boundary information input by a user and building a global scene containing a preset scale according to the boundary information;
an observation area determining unit, configured to receive a target area selected by a user based on the global scene, and determine an observation area of the target area;
the actual scene acquisition unit is used for determining an observation point position in the observation area and acquiring an actual scene of the target area at the observation point position;
the global scene correction unit is used for identifying the actual scene according to the recorded facility database and correcting the global scene according to the identification result; in the correction process of the global scene, the target area is regulated in real time according to the correction process of the global scene;
and the level receiving unit is used for displaying the corrected global scene containing the target areas and receiving confirmation information sent by the user and the importance level of each target area.
8. The intelligent electronic patrol positioning system according to claim 6, wherein said patrol pick module comprises:
the type selection unit is used for inquiring the definition requirements of all the target areas and determining the type of the patrol inspector according to the definition requirements;
the quantity selecting unit is used for receiving the inspection period input by the user and determining the quantity of the inspection devices according to the inspection period.
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| CN106506955A (en) * | 2016-11-10 | 2017-03-15 | 国网江苏省电力公司南京供电公司 | A kind of transformer substation video polling path planing method based on GIS map |
| CN111787189A (en) * | 2020-07-17 | 2020-10-16 | 塔盾信息技术(上海)有限公司 | Gridding automatic monitoring system for integration of augmented reality and geographic information |
| CN111968713B (en) * | 2020-08-05 | 2023-10-27 | 七海行(深圳)科技有限公司 | Data acquisition method and inspection device |
| CN112148034A (en) * | 2020-10-30 | 2020-12-29 | 重庆电子工程职业学院 | Hydrogen fuel cell oil field inspection unmanned aerial vehicle and inspection method |
| CN114237466B (en) * | 2021-12-15 | 2023-06-30 | 文思海辉智科科技有限公司 | Inspection point configuration method and device |
| CN115225859A (en) * | 2022-07-04 | 2022-10-21 | 中国铁道科学研究院集团有限公司 | Station safety inspection method, device and equipment based on video fusion |
| CN115272944A (en) * | 2022-07-07 | 2022-11-01 | 上海发电设备成套设计研究院有限责任公司 | Inspection system and method based on three-dimensional live-action |
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