CN115563341A - Spatial video field for electric power operation violation identification and intelligent data processing system and method thereof - Google Patents
Spatial video field for electric power operation violation identification and intelligent data processing system and method thereof Download PDFInfo
- Publication number
- CN115563341A CN115563341A CN202211240618.6A CN202211240618A CN115563341A CN 115563341 A CN115563341 A CN 115563341A CN 202211240618 A CN202211240618 A CN 202211240618A CN 115563341 A CN115563341 A CN 115563341A
- Authority
- CN
- China
- Prior art keywords
- data
- violation
- vector
- video
- field
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012545 processing Methods 0.000 title claims abstract description 76
- 238000000034 method Methods 0.000 title claims abstract description 53
- 238000012544 monitoring process Methods 0.000 claims abstract description 21
- 238000010276 construction Methods 0.000 claims description 78
- 230000006870 function Effects 0.000 claims description 40
- 230000008569 process Effects 0.000 claims description 25
- 238000013519 translation Methods 0.000 claims description 17
- 238000007781 pre-processing Methods 0.000 claims description 13
- 230000005484 gravity Effects 0.000 claims description 12
- 238000013499 data model Methods 0.000 claims description 11
- 230000010354 integration Effects 0.000 claims description 10
- 238000013459 approach Methods 0.000 claims description 9
- 230000002265 prevention Effects 0.000 claims description 9
- 230000003068 static effect Effects 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000012800 visualization Methods 0.000 claims description 7
- 238000004458 analytical method Methods 0.000 claims description 6
- 238000009826 distribution Methods 0.000 claims description 6
- 230000002452 interceptive effect Effects 0.000 claims description 6
- 238000013507 mapping Methods 0.000 claims description 4
- 208000027418 Wounds and injury Diseases 0.000 claims description 3
- 238000004422 calculation algorithm Methods 0.000 claims description 3
- 230000006378 damage Effects 0.000 claims description 3
- 230000001419 dependent effect Effects 0.000 claims description 3
- 238000005538 encapsulation Methods 0.000 claims description 3
- 208000014674 injury Diseases 0.000 claims description 3
- 238000011895 specific detection Methods 0.000 claims description 3
- 238000012790 confirmation Methods 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 abstract description 30
- 238000005516 engineering process Methods 0.000 abstract description 18
- 230000000694 effects Effects 0.000 abstract description 5
- 238000007726 management method Methods 0.000 description 35
- 238000004891 communication Methods 0.000 description 17
- 238000012954 risk control Methods 0.000 description 12
- 230000005540 biological transmission Effects 0.000 description 8
- 238000011161 development Methods 0.000 description 8
- 238000004590 computer program Methods 0.000 description 7
- 238000007619 statistical method Methods 0.000 description 6
- 239000000383 hazardous chemical Substances 0.000 description 5
- 238000003860 storage Methods 0.000 description 5
- 230000008447 perception Effects 0.000 description 4
- 230000004044 response Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 230000003203 everyday effect Effects 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000002354 daily effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003032 molecular docking Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012946 outsourcing Methods 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
- 210000000707 wrist Anatomy 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/71—Indexing; Data structures therefor; Storage structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/94—Hardware or software architectures specially adapted for image or video understanding
- G06V10/95—Hardware or software architectures specially adapted for image or video understanding structured as a network, e.g. client-server architectures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Multimedia (AREA)
- Entrepreneurship & Innovation (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Data Mining & Analysis (AREA)
- Game Theory and Decision Science (AREA)
- General Engineering & Computer Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Educational Administration (AREA)
- Databases & Information Systems (AREA)
- Development Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a space video field for electric power operation violation identification and an intelligent data processing system and method thereof, which are used for carrying out vector field data processing on a video data stream of an electric power operation field acquired by a video monitoring network of a power grid system and comprise the following steps: the method comprises the steps of constructing a standard space dynamic video vector field database, constructing a power operation field space dynamic video vector field database, collecting and constructing the power operation field space dynamic video vector field database, pre-optimizing double-layer data, comparing and processing the data and the like, and intelligently identifying the violation operation risks. The invention develops the data processing technology related to intelligent identification of electric power operation violation, and provides a fundamental and core support effect for improving and optimizing informatization and intelligent levels of a power grid safety production risk platform.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a data processing technology for electric power operation field violation identification.
Background
The safety and supervision of the power grid are the guarantee of national power grid construction and operation, a series of unstable factors are brought by complex power system industrial structure adjustment while the national power grid construction is developed at a high speed, and a series of transformation also puts higher requirements on power safety. The safety and supervision of the power grid become the heaviest in the construction and operation of the power grid, and the rapid development of social economy can be adapted more favorably only by ensuring the safe operation of the power grid and reducing the accidents of the power grid.
At present, based on the safety production requirements of national grid companies, hebei company combines the safety production practice to strengthen 'science and technology Xingan', and develops active exploration and research in the aspects of informatization and safety production fusion. Through construction for many years, certain safety control effects are achieved in aspects of risk early warning management and control, operation plan management and control, field supervision, field operator management, enterprise personnel safety access, hazardous chemical risk management, information system safety time early warning, safety tool and instrument full-process management and the like. The national grid company has pointed out that safety is the basis of all works and is the life line of the works of the company in the security committee of 2021. The safety of grasping iron wrists deeply, the technical security, the strong management safety, the reform and the promotion of safety are required, the safety production management system and the management capability modernization of a company are promoted, and the safe and reliable power guarantee is provided for starting the new journey of the socialist modernization country of the comprehensive construction society. The system and the method have the advantages that personal accidents are firmly avoided, the requirements of four control are met, the management and control of various operations are enhanced, the serious and extra-large equipment accidents are firmly avoided, the master control of the equipment is realized, and the equipment state sensing and diagnosis capacity is improved. The integration of science and technology and production business is accelerated, the falling of technologies such as 'big cloud thing moving intelligent chain' and the like in the safety production field is promoted, the integration of science and technology and safety supervision is accelerated, the safety management and control of full coverage, full time and full process is promoted, and the safety and technical prevention capability is improved. According to the file requirements of 'notice about issue of 2021-year digital safety control key tasks' of the State grid Security administration ', the national grid company four-time employment and 2021-year job meeting spirit are deeply penetrated, the company's '2021-year safety production work opinion' is strictly implemented, the application of a safety production risk control platform is deepened, a digital safety control terminal is popularized, the operation of a safety control center is standardized, a three-in-one digital safety control system is comprehensively promoted to be deeply developed and efficiently operated, the execution of four governance sites is supported in a full force mode, and the promotion of field safety control is upgraded to digital and intelligent conversion.
However, in the aspect of application of the intelligent violation identification technology, technical means such as violation behavior identification, violation type judgment, violation photo recording and the like of a job site are not widely applied through the intelligent technology, a large amount of terminal image monitoring data are still monitored manually, the labor cost required to be invested is high, and the timeliness of violation and construction potential safety hazard discovery cannot be met. Therefore, it is urgently needed to expand the development work of intelligent identification related application on the basis of a safety production risk control platform constructed and completed by electric power companies in the state network, hebei province and the China network.
Disclosure of Invention
The invention aims to overcome various defects in the prior art and provides a space video field for electric power operation violation identification and an intelligent data processing system and method thereof.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows.
An intelligent data processing system for recognizing a space video field violating electric power operation carries out vector field data processing on a video data stream of the electric power operation field acquired by a video monitoring network of a power grid system, and carries out intelligent recognition of the risks of the violating operation.
As a preferred technical solution of the present invention, the execution process of the system includes:
A. and (2) a standard space dynamic video vector field database and construction thereof: constructing a standard database into a dynamic atypical vector field data model;
the vector field correspondingly constructs a monitoring target of the power operation as a vector function relative to a specified data zero point, and the data expression of the vector allows the spatial position of the monitoring target to be subjected to data representation in a planar mode, namely by a double data set (m, n), or in a spatial mode, namely by a three data set (l, m, n);
the atypical corresponding vector function original image is not typical space data points, namely a double data set or a three data set corresponding to the double data set (m, n) or the three data set (l, m, n), the data configuration of the original image is a double parameter model, the first parameter is a time parameter t, and the second parameter is the number (alpha, beta, gamma, 8230;,/8230;); the first parameter t is dynamic independent variable data, the second parameter (alpha, beta, gamma, \8230;) is static marking data, and the static marking data is used for summarizing vector field functions corresponding to specific detection objects so as to realize the encapsulation of a plurality of groups of proper function values, and the encapsulated combined data is processed conveniently in the follow-up process, so that the calculation power resource of the system is saved; the vector function is used as a dependent variable of a first parameter, namely dynamic independent variable data t;
the vector field configuration of the dynamic corresponding database is a dynamic vector field, and compatible data changes along with time;
B. the electric power operation site space dynamic video vector field database and the acquisition and construction thereof are as follows:
objects of a power construction operation site are grouped and numbered, a grouping rule is determined according to the physical and engineering relations of the power operation objects, and the numbering rule is consistent with a second parameter, namely static marking data (alpha, beta, gamma, \8230; 8230) in a standard space dynamic video vector field database or is kept in a fixed single mapping relation although the numbering rule is inconsistent; recording dynamic independent variable data of a space dynamic video vector field of the power operation field as t';
the violation monitoring is realized on the basis that the standard data is compared with the field data, so that the configuration of the space dynamic video vector field database of the power operation field is consistent with that of the standard space dynamic video vector field database; specifically, the video vector field database comprises three elements of a vector field, an atypical feature and a dynamic feature, and the content of the three elements of the vector field, the atypical feature and the dynamic feature is consistent with the standard spatial dynamic video vector field database;
finally, the construction of a space dynamic video vector field database of the electric power operation field is completed through a data acquisition way; different from various optional construction approaches of a standard space dynamic video vector field database, the data source of the space dynamic video vector field database of the electric power operation site is a single approach, namely the filling construction of the database is completed by carrying out video data acquisition on the electric power construction operation site;
C. and carrying out data preprocessing and data comparison on the standard space dynamic video vector field database and the electric power operation field space dynamic video vector field database to identify the violation risks of the electric power construction operation field.
As a preferred technical solution of the present invention, in step a, a construction approach of the standard spatial dynamic video vector field database includes: constructing by carrying out field video data acquisition on calibrated standardized electric power construction operation; constructing through data input according to a standardized electric power construction operation model; based on a normalized electric power construction operation model, formulating through a data rule, and automatically generating a standard dynamic atypical vector database through the data rule; other standardized construction approaches; selecting one of the ways to construct a standard space dynamic video vector field database;
as a preferred technical solution of the present invention, in step a, for the original image data and the vector function data in the standard spatial dynamic video vector field database, because a certain range of operation flexibility is allowed based on the normalized operation model, the original image data and the vector function data in the database are correspondingly represented as range values; or calibrating the original image data t and setting the vector function data as a range numerical value.
As a preferred technical solution of the present invention, in step C, the data preprocessing includes data translation processing: the dynamic independent variable data t 'of the power operation field space dynamic video vector field database is obtained based on field video acquisition and is naturally inconsistent with the dynamic independent variable data t of the standard space dynamic video vector field database, so that the dynamic independent variable data t' and the standard space dynamic video vector field database are kept consistent through data translation processing; the data translation operation may be selected from one of the following paradigms: simultaneously carrying out zeroing treatment on the dynamic independent variable data t' and t in the two databases according to the event starting point; translating any t' to a position coincident with t;
as a preferred technical solution of the present invention, in step C, the data preprocessing includes data scaling and interactive processing with data translation: on one hand, calibrating key nodes of the electric power construction process to be used as conservative data points, and carrying out segmented zooming processing on the whole electric power construction operation process according to the calibrated conservative data points, or using the conservative data points as data comparison central points; on the other hand, the electric power construction operation process is subjected to subsection translation processing according to the distribution of the conservative data points; the comparison value coefficients of the two groups of databases are improved through the interactive processing of zooming and translation, and particularly the data comparison value coefficients near the conservative data points are improved;
as a preferred technical solution of the present invention, in the step C, the data preprocessing includes: constructing a double-layer vector field data model, and obtaining inner layer comparison data serving as an auxiliary comparison parameter for violation identification; specifically, vector function data of different power operation objects packaged into the same group, namely real-time space vector data of the power operation objects with the labels of alpha, beta, gamma, \8230, is subjected to finite difference data processing to obtain a vector data group serving as a difference data group in the box; on the other hand, a gravity center vector of the whole encapsulated data set is obtained through a gravity center algorithm of space vector data, and the gravity center vector is expressed as single space vector data; and taking the difference data group in the box and the gravity center vector as inner layer comparison data to be used as an auxiliary comparison parameter for violation identification.
As a preferred technical scheme of the invention, the system is also compatible with developing the following data identification subassemblies in a function guidance mode: the device comprises an aerial falling prevention type identification subassembly, an electric shock prevention type identification subassembly, an anti-broken rod type identification subassembly, a deep foundation pit operation violation type identification subassembly, an aerial falling object injury human identification subassembly, a crane operation violation type identification subassembly and other violation identification subassemblies.
As a preferred technical scheme of the invention, the system is also compatible with the following parallel subsystems: an intelligent anti-violation subsystem; the method comprises the following steps: (1) and (3) real-time reminding of violation alarm information: the real-time violation alarm notification based on operation field monitoring is realized through hanging and integrating with an external information sending platform; (2) automatic violation generation and information pre-filling: by additionally hanging and integrating with a data port or a data platform, the information such as the name of an operation plan, the operation type, the construction unit, the business unit to which the construction unit belongs, the operation risk level and the like is back-checked according to the equipment ID fed back by the analysis result and is automatically filled into the violation alarm; (3) intelligently analyzing violation identification and secondarily confirming: the existing regulation and regulation violation rectifying process is reformed, the regulation and regulation violation information discovered through intelligent analysis is specially marked, and a manual confirmation link is added before the regulation and regulation violation process is processed; and (3) controlling the authority of the violation data: through data authority control, only the port with authority before exposure allows viewing of data.
As a preferred technical scheme of the invention, the system is also compatible with the following parallel subsystems: an intelligent anti-violation information visualization subsystem; the method comprises the following steps: (1) intelligent identification data overview: the inquiry of real-time and historical data and the violation detail display are supported; the retrieval is supported through the operation name, the violation type, the violation unit and the violation location; (2) counting intelligent identification data: through summarizing and integrating data of historical violation processing conditions, violation types, violation units, violation places and the like, dynamic statistics and display are carried out according to the violation quantity, the violation quantity of each type, the violation processing efficiency and the violation distribution area.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in: the invention develops the data processing technology related to intelligent identification of electric power operation violation, and provides a fundamental and core support effect for improving and optimizing informatization and intelligent levels of a power grid safety production risk platform.
The invention is developed based on a related platform of a national network company, and the adopted video field data model has direct compatibility, saving property of storage and rapidity of calculation for data transmitted and displayed by the existing video monitoring platform, and has higher data hierarchy or data containment and higher logic intuition compared with a calculation model based on single byte summary analysis.
The standardized data model constructed by the invention has comprehensive configuration of vector containment, dynamic and atypical, and is compatible with construction, storage and processing of two-dimensional data or three-dimensional data, the vector containment naturally encapsulates video related source data, the data coverage of the data model is improved, the logic efficiency of system data processing is simplified, and the atypical data structure artificially encapsulates other essential compact data dimensions except video data stream information, so that the data configuration is used as a processing carrier to carry out global association and expression on dynamic electric power operation field information, and the apparent introduction degree of the system is greatly improved.
The data construction and processing model ensures that the configuration of the space dynamic video vector field database of the power operation site is consistent with that of the standard space dynamic video vector field database; the vector field, the atypical and the dynamic elements are included, and the content of the vector field, the atypical and the dynamic elements is consistent with the standard space dynamic video vector field database.
The invention constructs a plurality of preprocessing models, and simultaneously constructs a double-layer data processing and optimizing comparison mode, which have uniqueness and originality.
The invention also has good monitoring performance and expansibility, and is convenient for docking with a system platform and carrying out subsequent function development of the similarity data model.
Detailed Description
In the following description of embodiments, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail. It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]". Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing a relative importance or importance.
Example 1 bottom technical framework and specification
The national grid company releases a basic version of a safety production risk control platform, carries out deployment implementation work of the safety production risk control platform, and has the functions of home page, operation safety intelligent control, enterprise personnel safety access, safety statistics and analysis, accident potential troubleshooting and management, safety control center duty management, information system safety event early warning, power grid risk early warning control, risk panoramic perception and statistical analysis, field safety supervision visualization, safety tool and instrument full-flow management, hazardous chemical product risk management and the like. Wherein, the items of the primary function point 11, the items of the secondary function point 34 and the items of the tertiary function point 22. Since the safety production risk control platform is put into operation, the national grid, hebei province and electric power limited company, city level, county level, work area team and the like are commonly applied, the number of registered users of the system is nearly 3000, the system visits users nearly 300 times every day, about 70 construction operation sites are controlled in real time through the platform every day, the safety production risk control platform is used regularly in each company unit through functional modules such as operation safety intelligent control, enterprise personnel safety admission, safety event statistical analysis, accident hidden danger investigation and management, safety control center duty management, information system safety event early warning, power grid risk early warning control, risk panoramic perception and statistical analysis, field safety supervision visualization, safety tool and appliance full-flow management, hazardous chemical product risk management and the like, certain safety control effect is obtained in the aspect of site control of each type of construction operation, and daily management, emergency handling, risk control, admission enterprise management and control, personnel management and control, industrial and appliance management, hazardous chemical product and the like are supported. The safety production risk management and control platform is expanded in function, breaks rules and regulations are identified and developed, an intelligent identification technology is further fused and applied, and the intelligent and informatization level of management and control of a construction operation field is improved.
The safety production risk platform is provided with the following primary sub-platforms: the system comprises an operation safety intelligent management and control sub-platform, an enterprise personnel safety access sub-platform, a safety event data statistical analysis sub-platform, an accident potential hazard investigation data sub-platform, a safety management and control central value inquiry sub-platform, an information system safety event early warning sub-platform, a risk early warning mechanism sub-platform, a risk panoramic perception and statistical analysis sub-platform, a field safety supervision visualization sub-platform, a safety tool full-flow sub-platform and a hazardous chemical risk sub-platform. Wherein, the intelligent management and control sub-platform of operation safety sets up: the system comprises a power grid infrastructure and construction operation planning secondary sub-platform, a power grid infrastructure and construction inspection secondary sub-platform and a power grid infrastructure and construction violation safety risk secondary sub-platform. Furthermore, a third-level sub-platform for recognizing the violation in the electric power working site and a third-level sub-platform for visualizing the violation information in the electric power working site are expanded and arranged under a second-level sub-platform for establishing the violation safety risk in the electric power grid; and distributing the calculation capacity of the server, the storage capacity of the server, a data communication protocol, a data security protocol and a data communication port according to the actual capacity constructed by the system.
And finally, synchronously mapping the two groups of expansion platforms into the following two groups of secondary sub-platforms under a safety production risk platform by adopting a shortcut type data model for the three-level sub-platform for electric power operation field violation identification and the three-level sub-platform for electric power operation field violation information visualization: a risk panoramic perception and statistical analysis sub-platform and a field safety supervision visualization sub-platform.
The technical basis and the specification related to the new technology development comprise: the technical proposal comprises the following steps of comments on accelerating the construction of novel digital infrastructures by national grid company (national grid interconnection [ 2020 ] 260), 'notices of the State grid safety supervision department on issuing safety production risk control platform functions and practical laboratory acceptance standards (trial implementation)' safety production risk control platform interfaces and data specifications (trial implementation) '(Security supervision II [ 2020 ] 15),' notices of the State grid safety supervision department on issuing key tasks of the safety production risk control platform 2020 (Security supervision II [ 2020 ] 3), 'notices of the State grid safety supervision department on issuing safety production risk control platform functional key points (Security supervision II [ 2019 ]),' notices of the State grid safety supervision department on issuing safety production risk control platform construction and application project '(Security supervision II [ 2019 ] 25)' method for managing and managing potential safety hazard of national grid company (national grid Security administration [ 2014 ] 481), safety accident survey procedure of national grid company (2017 revision), working specification for early warning and management of grid operation risk (QGDW 11711-2017), standard working specification (trial implementation) for production operation safety management and management of standard production line (national grid Security administration [ 2016 ] 356), standard working specification (trial implementation) for early warning and management of construction safety risk of power transmission and transformation project of national grid company (national grid Security administration [ 2015 ] 972), method for managing anti-violation working of safety production of national grid company (national grid Security administration [ 2014 ] 156), and method for managing service outsourcing safety supervision of national grid company (national grid (Security administration/4) 853-2017) National grid company electric safety tools and appliances management regulations (national grid (safety supervision/4) 289-2014), and grid video monitoring system and interface (Q/GDW 1517.1-2014); other applicable specifications.
Example 2 technical integration
The data information of a comprehensive digital management platform, PMS2.0, OMS, S6000, I6000 and the like in the whole process of capital construction is obtained by integrating the prior art, and the specific integrated information is shown in the following table. The deployment environment is a cloud mode on the micro-service, and the platform is integrally deployed in the management information large area. Subsequent development may continue its architecture.
Example 3 development guidance
Carrying out video information flow expansion construction on a safety production risk platform based on a power grid system so as to identify safety production risks of electric power infrastructure and operation sites and carry out informatization transmission and processing on risk operations; the method comprises the following steps: (1) performing cooperative integration on the existing software and hardware facilities of the power grid system; (2) and newly building a hardware facility component and an executable data component for electric power operation site violation identification, and carrying the hardware facility component and the executable data component on the existing software and hardware facility platform of the power grid system after cooperative integration in a coordinated manner to perform platform expansion of the system.
Embodiment 4 cooperative integration of software and hardware facilities of a power grid system
Cooperative integration includes: carrying out networking communication integration construction on the existing software and hardware facilities of the power grid system; networked communications include: the method comprises the following steps of constructing a power grid internal network wired communication protocol and port, and/or constructing a power grid internal network wireless communication protocol and port, and/or constructing a power grid internal-external network wired communication protocol and port, and/or constructing a power grid internal-external network wireless communication protocol and port; the communication protocol comprises a data transmission protocol and a data safety protocol meeting the internal requirements of the power grid system; performing data communication integration construction on the existing software and hardware facilities of the power grid system; data opening comprises data format consistency and/or data interface consistency.
Example 5 hardware facility Components
The newly-built hardware facility component is subjected to additional configuration according to project requirements of electric power operation risk violation identification, and the additional configuration comprises the additional configuration of video monitoring facilities, the additional laying of communication lines, the additional arrangement of risk identification and processing stations, the capacity increase of a data processing server and the additional arrangement of other facilities, and the additional arrangement can be carried out according to requirements according to the existing framework of a power grid system safety production risk platform;
embodiment 6 video data processing
The video data processing belongs to a newly-built executable data assembly, and is used for processing the video data stream of the electric power operation field acquired by a power grid system video monitoring network, intelligently identifying the violation operation risk, acquiring and recording a risk node data array after the violation risk is identified, wherein the risk node data array is constructed into a risk node database; specifically, the risk node database is structured by the following parallel data sets: the system comprises a violation site space-time node data column, a violation site image intercepting data column, a violation site video recording data column, a violation site construction project bibliographic data column, a violation site operator information and contact information data column and a higher-level returning responsibility department data column of the violation site construction project; other columns of data; blank data columns may be expanded.
The video data processing assembly processes the video data stream of the electric power operation site acquired by the video monitoring network of the power grid system, and intelligently identifies the violation operation risk; the data processing process comprises the following steps:
A. and (5) constructing a standard space dynamic video vector field database.
The standard database is constructed as a dynamic atypical vector field data model. The vector field is that a monitoring target of the power operation is constructed as a vector function relative to a designated data zero point, and the data expression of the vector allows the spatial position of the monitoring target to be expressed by adopting a plane mode, namely a double data set (m, n), or a spatial mode, namely a triple data set (l, m, n). Atypical means a spatial data point of the vector function whose original image is atypical, i.e. a double data set or a triple data set corresponding to the above-mentioned double data set (m, n) or triple data set (l, m, n), the data configuration of the original image is a double parameter model, the first parameter is a time parameter t, and the second parameter is the number (α, β, γ, 8230; \8230;); the first parameter t is dynamic independent variable data, the second parameter (alpha, beta, gamma, \8230;) is static marking data, and the static marking data is used for summarizing vector field functions corresponding to specific detection objects so as to realize the encapsulation of a plurality of groups of proper function values, and the encapsulated combined data is processed conveniently in the follow-up process, so that the calculation power resource of the system is saved; the vector function is used as a dependent variable of the first parameter, i.e. the dynamic independent variable data t. Dynamic means that the vector field is a dynamic vector field, which varies with time.
The standard space dynamic video vector field database construction method comprises the following steps: delta, constructing by carrying out field video data acquisition on the calibrated standardized electric power construction operation; epsilon, constructing through data input according to a normalized electric power construction operation model; zeta, based on normalized electric power construction operation model, formulating through data rule, and automatically generating standard dynamic atypical vector database by data rule; eta, other standardized construction approaches; and selecting one of the ways to construct a standard space dynamic video vector field database.
For original image data and vector function data in a standard space dynamic video vector field database, because certain range operation flexibility is allowed by taking a standardized operation model as a reference, the original image data and the vector function data in the database are correspondingly expressed as range values; or calibrating the original image data t and setting the vector function data as a range numerical value.
B. And (3) acquiring and constructing a space dynamic video vector field database of the electric power operation field.
Objects of a power construction operation site are grouped and numbered, a grouping rule is determined according to the physical and engineering relations of the power operation objects, and the numbering rule is consistent with a second parameter, namely static marking data (alpha, beta, gamma, \8230; 8230) in a standard space dynamic video vector field database or is inconsistent but is kept in a fixed single mapping relation; recording dynamic independent variable data of a space dynamic video vector field of the power operation field as t';
the violation monitoring is realized on the basis that the standard data is compared with the field data, so that the configuration of the space dynamic video vector field database of the power operation field is consistent with that of the standard space dynamic video vector field database; specifically, the video vector field database comprises three elements of a vector field, an atypical feature and a dynamic feature, and the content of the three elements of the vector field, the atypical feature and the dynamic feature is consistent with the standard spatial dynamic video vector field database; finally, the construction of a space dynamic video vector field database of the electric power operation field is completed through a data acquisition way; different from various optional construction ways of a standard space dynamic video vector field database, the data source of the space dynamic video vector field database of the electric power construction site is a single way, namely the filling construction of the database is completed by carrying out video data acquisition on the electric power construction site.
C. And carrying out data preprocessing and data comparison on the standard space dynamic video vector field database and the power operation site space dynamic video vector field database to identify the violation risk of the power construction operation site. The data preprocessing comprises data translation processing: the dynamic independent variable data t 'of the power operation field space dynamic video vector field database is obtained based on field video acquisition and is naturally inconsistent with the dynamic independent variable data t of the standard space dynamic video vector field database, so that the dynamic independent variable data t' and the standard space dynamic video vector field database are kept consistent through data translation processing; the data shifting operation may be selected from one of the following paradigms: simultaneously carrying out zeroing processing on dynamic independent variable data t' and t in the two databases according to the event starting point; translating any t' to a position coincident with t; the data preprocessing comprises data scaling and interactive processing with data translation: on one hand, calibrating key nodes of the electric power construction process to be used as conservative data points, and carrying out segmented zooming processing on the whole electric power construction operation process according to the calibrated conservative data points, or using the conservative data points as data comparison central points; on the other hand, the power construction operation process is subjected to subsection translation processing according to the distribution of the conservative data points; the comparison value coefficients of the two groups of databases are improved through the interactive processing of zooming and translation, and particularly the data comparison value coefficients near the conservative data points are improved; the data preprocessing comprises the following steps: constructing a double-layer vector field data model, and obtaining inner layer comparison data as an auxiliary comparison parameter for violation identification; specifically, vector function data of different power operation objects packaged into the same group, namely real-time space vector data of the power operation objects with the labels of alpha, beta, gamma, 8230\8230, is subjected to finite difference data processing to obtain a vector data group serving as a box internal difference data group; on the other hand, a gravity center vector of the whole encapsulated data set is obtained through a gravity center algorithm of space vector data, and the gravity center vector is expressed as single space vector data; and taking the difference data group and the gravity vector in the box as inner layer comparison data to be used as an auxiliary comparison parameter for violation identification.
The video data processing component can also develop the following data identification sub-components in a function-guided manner: the high-altitude falling prevention identification subassembly, the electric shock prevention identification subassembly, the breakage prevention rod identification subassembly, the deep foundation pit operation violation identification subassembly, the high-altitude falling object injury human identification subassembly, the crane operation violation identification subassembly and other violation identification subassemblies.
Embodiment 7 information transfer processing of job Risk
The information transmission processing of the operation risk belongs to a newly-built executable data assembly, the information transmission processing belongs to an integrated functional assembly, firstly, violation information identified by a video data processing assembly is sent to a safety production risk platform through a violation information sending module, further, data interaction is carried out with a risk node data array through a data authority approach, and the data interaction with the risk node data array through the data authority approach means that: the information transmission processing component of the operation risk carries out bidirectional data communication with 'information and contact information data of operating personnel at the violation site' and 'data of superior entry responsibility department of construction project' in the risk node database through a data authority way while or after sending the risk violation information, thereby butting and meeting the subsequent risk data processing requirement and further generating a related database; the method is characterized in that the method is used for realizing alarming, inquiring, key attention, risk processing feedback, risk processing supervision, risk processing effect evaluation and other functions of violation risk supervision facing to two directions of a multi-level management department and an operation site, and meanwhile, violation risk identification and generation construction of a processing process database are carried out, wherein the generation construction specifically comprises the following steps: and the information transmission processing component of the operation risk carries out system log recording and backup on related data in a transmission link of the risk information and a link of carrying out data interaction with the risk node data array.
Embodiment 8, correlation technique type selection and technique platform
And (4) associating the technology type selection path. Interface display technology: and (3) using mature interface presentation technologies, including related technologies such as HTML, CSS, ajax, JSP and the like. Selecting a server development technology: and selecting a technical route for mixed development of Python, C + +, java EE and servlet. And (3) encoding specification: and UTF-8 encoding is adopted for codes, components, data serialization and other related files and data uniformly. Open source software: ECharts, jQuery, VUE, redis. A middleware: message middleware kafka, distributed cache redis. A database: mySQL level, fastDFS (cloud platform based). A container engine: docker. Inteli-rec: docker, python, pyTorch.
A technology platform path is associated. SG-UAP3.0, flash, spring bound frame, pyTorch
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
In various embodiments, the hardware implementation of the technology may directly employ existing intelligent devices, including but not limited to industrial personal computers, PCs, smart phones, handheld stand-alone machines, floor stand-alone machines, and the like. The input device preferably adopts a screen keyboard, the data storage and calculation module adopts the existing memory, calculator and controller, the internal communication module adopts the existing communication port and protocol, and the remote communication adopts the existing gprs network, the web and the like. It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules, so as to perform all or part of the functions described above. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, a module or a unit may be divided into only one logical function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in an electrical, mechanical or other form. The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Each functional unit in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit. The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method according to the embodiments of the present invention may also be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of the embodiments of the method. . Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, and software distribution media, etc. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, in accordance with legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunications signals.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. The utility model provides an intelligent data processing system based on electric power operation identification space video field violating regulations which characterized in that: and carrying out vector field data processing on the power operation field video data stream acquired by the power grid system video monitoring network, and carrying out intelligent identification on the violation operation risk.
2. The intelligent data processing system based on electric power operation violation identification space video field according to claim 1, characterized in that: the system executes the process that:
A. a standard space dynamic video vector field database and construction thereof: constructing a standard database into a dynamic atypical vector field data model;
the vector field correspondingly constructs a monitoring target of the power operation as a vector function relative to a specified data zero point, and the data expression of the vector allows the spatial position of the monitoring target to be subjected to data representation in a planar mode, namely by a double data set (m, n), or in a spatial mode, namely by a three data set (l, m, n);
the atypical corresponding vector function original image is not typical space data points, namely a double data set or a three data set corresponding to the double data set (m, n) or the three data set (l, m, n), the data configuration of the original image is a double parameter model, the first parameter is a time parameter t, and the second parameter is the number (alpha, beta, gamma, 8230;,/8230;); the first parameter t is dynamic independent variable data, the second parameter (alpha, beta, gamma, \8230;) is static marking data, and the static marking data is used for summarizing vector field functions corresponding to specific detection objects so as to realize the encapsulation of a plurality of groups of proper function values, and the encapsulated combined data is processed conveniently in the follow-up process, so that the calculation power resource of the system is saved; the vector function is used as a dependent variable of a first parameter, namely dynamic independent variable data t;
the vector field configuration of the dynamic corresponding database is a dynamic vector field, and compatible data changes along with time;
B. the electric power operation site space dynamic video vector field database and the acquisition and construction thereof are as follows:
objects of the power construction operation site are grouped and numbered, a grouping rule is determined according to the physical and engineering relations of the power operation objects, and the numbering rule is consistent with a second parameter, namely static marking data (alpha, beta, gamma, \8230; 8230), in a standard space dynamic video vector field database or is in a fixed single mapping relation although the numbering rule is inconsistent; recording the dynamic independent variable data of the space dynamic video vector field of the power operation field as t';
the violation monitoring is realized on the basis that the standard data is compared with the field data, so that the configuration of the space dynamic video vector field database of the power operation field is consistent with that of the standard space dynamic video vector field database; specifically, the method comprises three elements of vector field, atypical type and dynamic type, and the content of the three elements of vector field, atypical type and dynamic type is consistent with the vector field database of the standard space dynamic video;
finally, the construction of a space dynamic video vector field database of the electric power operation field is completed through a data acquisition way; different from various optional construction ways of a standard space dynamic video vector field database, the data source of the space dynamic video vector field database of the electric power construction site is a single way, namely the filling construction of the database is completed by carrying out video data acquisition on the electric power construction site;
C. and carrying out data preprocessing and data comparison on the standard space dynamic video vector field database and the power operation site space dynamic video vector field database to identify the violation risk of the power construction operation site.
3. The intelligent data processing system based on electric power operation violation identification space video field according to claim 1, characterized in that: in step a, the construction approach of the standard spatial dynamic video vector field database includes: constructing by carrying out field video data acquisition on calibrated standardized electric power construction operation; constructing through data input according to a standardized electric power construction operation model; based on a normalized electric power construction operation model, formulating through a data rule, and automatically generating a standard dynamic atypical vector database through the data rule; other standardized construction approaches; and selecting one of the ways to construct a standard space dynamic video vector field database.
4. The intelligent data processing system based on electric power operation violation identification space video field according to claim 1, characterized in that: in the step A, for original image data and vector function data in a standard space dynamic video vector field database, because certain range operation flexibility is allowed to exist by taking a standardized operation model as a reference, the original image data and the vector function data in the database are correspondingly represented as range values; or calibrating the original image data t and setting the vector function data as a range numerical value.
5. The intelligent data processing system based on electric power operation violation identification space video field according to claim 1, characterized in that: in step C, the data preprocessing includes data translation processing: the dynamic independent variable data t 'of the power operation field space dynamic video vector field database is obtained based on field video acquisition and is naturally inconsistent with the dynamic independent variable data t of the standard space dynamic video vector field database, so that the dynamic independent variable data t' and the standard space dynamic video vector field database are kept consistent through data translation processing; the data translation operation may be selected from one of the following paradigms: simultaneously carrying out zeroing processing on dynamic independent variable data t' and t in the two databases according to the event starting point; any t' is translated to a position coincident with t.
6. The intelligent data processing system based on electric power operation violation identification space video field according to claim 1, characterized in that: in step C, the data preprocessing includes data scaling and interactive processing with data translation: on one hand, calibrating key nodes of the power construction process to serve as conservative data points, and carrying out segmented scaling processing on the whole power construction operation process according to the calibrated conservative data points, or taking the conservative data points as data comparison center points; on the other hand, the power construction operation process is subjected to subsection translation processing according to the distribution of the conservative data points; and the comparison value coefficients of the two groups of databases are improved through interactive processing of scaling and translation, and particularly the data comparison value coefficients near the conservative data points are improved.
7. The intelligent data processing system based on electric power operation violation identification space video field according to claim 1, characterized in that: in step C, the data preprocessing includes: constructing a double-layer vector field data model, and obtaining inner layer comparison data as an auxiliary comparison parameter for violation identification; specifically, vector function data of different power operation objects packaged into the same group, namely real-time space vector data of the power operation objects with the labels of alpha, beta, gamma, 8230\8230, is subjected to finite difference data processing to obtain a vector data group serving as a box internal difference data group; on the other hand, a gravity center vector of the whole encapsulated data set is obtained through a gravity center algorithm of space vector data, and the gravity center vector is expressed as single space vector data; and taking the difference data group in the box and the gravity vector as inner layer comparison data to be used as an auxiliary comparison parameter for violation identification.
8. The intelligent data processing system based on electric power operation violation identification space video field according to claim 1, characterized in that: the system is also compatible with the following data identification subcomponents developed and developed in a function guidance mode: the high-altitude falling prevention identification subassembly, the electric shock prevention identification subassembly, the breakage prevention rod identification subassembly, the deep foundation pit operation violation identification subassembly, the high-altitude falling object injury human identification subassembly, the crane operation violation identification subassembly and other violation identification subassemblies.
9. The intelligent data processing system based on electric power operation violation identification space video field according to claim 1, characterized in that: the system is also compatible with the following parallel subsystems: an intelligent anti-violation subsystem; the method comprises the following steps: (1) and (3) carrying out real-time reminding on violation alarm information: the real-time violation alarm notification based on operation field monitoring is realized by hanging and integrating with an external information sending platform; (2) automatic violation generation and information pre-filling: through the hanging integration with a data port or a data platform, the information such as the name of an operation plan, the operation type, the construction unit, the business and opportunity unit of the construction unit, the operation risk level and the like is back-checked according to the equipment ID fed back by the analysis result and is automatically filled into the violation alarm; (3) intelligently analyzing violation identification and secondarily confirming: the existing regulation and regulation violation rectifying process is reformed, the regulation and regulation violation information discovered through intelligent analysis is specially marked, and a manual confirmation link is added before the regulation and regulation violation process is processed; and (3) controlling the authority of the violation data: through data authority control, only the port with authority before exposure allows viewing of data.
10. The intelligent data processing system based on electric power operation violation identification space video field according to claim 1, characterized in that: the system is also compatible with the following parallel subsystems: an intelligent anti-violation information visualization subsystem; the method comprises the following steps: (1) intelligent identification data overview: the inquiry of real-time and historical data and the violation detail display are supported; the retrieval is carried out according to the operation name, the violation type, the violation unit and the violation location; (2) counting intelligent identification data: through summarizing and integrating data of historical violation processing conditions, violation types, violation units, violation places and the like, dynamic statistics and display are carried out according to the violation quantity, the violation quantity of each type, the violation processing efficiency and the violation distribution area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211240618.6A CN115563341A (en) | 2022-10-11 | 2022-10-11 | Spatial video field for electric power operation violation identification and intelligent data processing system and method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211240618.6A CN115563341A (en) | 2022-10-11 | 2022-10-11 | Spatial video field for electric power operation violation identification and intelligent data processing system and method thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115563341A true CN115563341A (en) | 2023-01-03 |
Family
ID=84744137
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211240618.6A Pending CN115563341A (en) | 2022-10-11 | 2022-10-11 | Spatial video field for electric power operation violation identification and intelligent data processing system and method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115563341A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116126961A (en) * | 2023-04-04 | 2023-05-16 | 河北中废通网络技术有限公司 | Tamper-proof unattended weighing data system of regeneration circulation internet of things information system |
-
2022
- 2022-10-11 CN CN202211240618.6A patent/CN115563341A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116126961A (en) * | 2023-04-04 | 2023-05-16 | 河北中废通网络技术有限公司 | Tamper-proof unattended weighing data system of regeneration circulation internet of things information system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105022769B (en) | A kind of City Underground Pipeline interactive system and its method | |
| CN111552995B (en) | BIM-3DGIS and data automatic analysis technology-based rail transit construction visual monitoring management system | |
| CN107194588A (en) | A kind of bridge construction management system and method based on Quick Response Code and BIM technology | |
| CN112651126B (en) | BIM-based construction engineering construction optimization system, method, terminal and storage medium | |
| CN105550758A (en) | GIS-based underground pipeline operation and maintenance system | |
| CN106850666A (en) | The shared cloud platform of Forestry Information and monitoring operation system | |
| CN112966903A (en) | Dangerous chemical safety production risk monitoring and early warning system and method | |
| CN111176642B (en) | Interactive visualization processing system based on plane graph and application method | |
| CN101931648A (en) | Chemical industrial park environment risk source monitoring platform | |
| CN102801805A (en) | Field data acquisition system and method based on mobile internet technology | |
| CN114968984A (en) | Digital twin full life cycle management platform | |
| CN104778551A (en) | Designing and analyzing method of visualization grid | |
| CN115563341A (en) | Spatial video field for electric power operation violation identification and intelligent data processing system and method thereof | |
| CN114092648A (en) | Digital twin application framework and method for application scene of station equipment | |
| CN112559351A (en) | CFD software verification and confirmation database platform | |
| CN115424212B (en) | Electric power operation site violation identification system and application thereof | |
| CN115457211A (en) | Transformer substation management method and system based on digital twins | |
| Yu et al. | [Retracted] Construction and Evaluation of Construction Safety Management System Based on BIM and Internet of Things | |
| Cao et al. | A digital twin (DT) framework at design and construction phases | |
| CN116739496A (en) | Intelligent management system for coal mine production | |
| CN111368450A (en) | BIM-based GIM digital model modeling method for power transmission and transformation project | |
| CN117112702A (en) | Service rapid processing system for long and large bridge tunneling scene | |
| CN111784189A (en) | Power communication dispatching intelligent command platform | |
| CN111882177A (en) | Pressure drainage system fault maintenance method, server, user terminal and medium | |
| CN108491530B (en) | Space geographic information system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |