CN108228900A - Power equipment multispectral data center model method for building up based on layered structure - Google Patents
Power equipment multispectral data center model method for building up based on layered structure Download PDFInfo
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Abstract
The present invention provides the power equipment multispectral data center model method for building up based on layered structure, including：Carry out the analysis based on power equipment multispectral data structure, build power equipment multispectral data center model, build image discriminance analysis model, it carries out image discriminance analysis model and relationship analysis is applied for multispectral data center model, and build power equipment information connection proxy construction, computer is relied on individually to model the unit in each model system, generate hierarchical control unit, and the network for forming distributed frame is connected according to practical topology relationship, so as to fulfill the AUTOMATIC ZONING for power equipment multispectral data and operation.The present invention proposes the layered structure technology that can adaptively adjust, and adapts to the demand that power equipment image data frequently changes, and further to analyze electric power image comprehensively, judges that power equipment operating status provides powerful support.
Description
Technical field
The present invention relates to power equipment data management and applied technical field more particularly to the electric power based on layered structure is set
Standby multispectral data center model method for building up.
Background technology
Some substations are mounted with video monitoring system, it can be achieved that field device monitoring, control remote camera fortune at present
The functions such as dynamic, digital video recorder.But only function for monitoring does not have image identification function, lack to transformer device of transformer substation from
Dynamic identification and analytic function.Operator on duty is still relied on to go to observe and analyze the image of acquisition, so as to judge the fortune of transformer equipment
Row state, system lack the automatic identification and analytic function to transformer equipment image.It is the substation to background complexity at all
The analysis of image and the research of the method for discrimination of transformer equipment operation troubles are not mature enough, and improve image analysis capabilities conscientiously,
As it is in the urgent need to address the problem of.
The disclosure of the invention of Patent No. 201510412958.6 is a kind of based on multispectral composite insulator detection method,
Including：Detection device is selected, under identical operating condition, visible ray inspection is carried out using detection device to same composite insulator
Survey, infrared detection and ultraviolet detection obtain the detection image of the composite insulator；It shines to the shelf depreciation of visible images
The corona point of point, the local hot spot of infrared image and ultraviolet image is compared；To same under identical operating condition
Visible images, infrared image and the ultraviolet image of the different composite insulator of the same base shaft tower of circuit are compared；For every
A composite insulator establishes multispectral Test database, and according to the data of the detection of some cycles, data are compared, are looked for
Go out existing data difference.The invention will be seen that light, infrared, ultraviolet three kinds of detection means organically combine, and have complementary advantages,
Live detection easily is carried out to insulator, can find composite insulator defect in time, convenient for carrying out the inspection of large area.
The invention of Patent No. 201110419576.8 provides a kind of method for detecting high optical spectrum of composite insulator, including following
Step：1）Composite insulator is imaged using hyperspectral imager, obtains the Hyperspectral imaging of composite insulator；2）To compound exhausted
The Hyperspectral imaging of edge is pre-processed, including geometric correction, radiant correction to obtain more accurate spectral information；3）With
Specialty analysis platform carries out processing analysis, determines the operating status of composite insulator, and judgement result output/display judges whether
Need replacing composite insulator.The invention method for detecting high optical spectrum of composite insulator can carry out contactless inspection to composite insulator
It surveys, is not required to worker Deng Ta；And it is short the time required to execute-in-place, when obtaining data with hyperspectral imager, it can obtain simultaneously more
The information of a composite insulator carries out processing analysis to multiple composite insulators simultaneously convenient for the later stage, reaches the mesh of batch detection
, meet the needs of China's composite insulator state-detection.
It, can be from by the multispectral detection and analysis such as visible ray, infrared, ultraviolet and identification technology however, in practical applications
Fundamentally solve the problems, such as some present in current transformer equipment on-line monitoring：The operating parameter of important equipment needs prison in real time
It surveys, is difficult to meet requirement of real-time using manual patrol, sense of responsibility, working attitude and the mental status of floor manager seriously affect
The result of detection；The operating status of many high-tension apparatuses is difficult to be converted into electric signal, in signal conversion and transmission process easily by
Strong-electromagnetic field interferes and influences diagnosis；Equipment is detected still in the simple application level to thermograph using infrared,
It is not associated with equipment state, historical data is also difficult to memory scan；In addition, the gray scale that human eye is difficult to differentiate fine image becomes
Change, it is difficult to the objective degree for judging transformer equipment surface defect.Therefore, utilization and mould of the multispectral image analysis with identification technology
The foundation of type can promote the intelligence of on-line monitoring system, automation, improve the working efficiency of work of transformer substation personnel, obtain more
High economic benefit, will be with larger practical value and application prospect.
Invention content
Present invention aims at the power equipment multispectral data center model method for building up based on layered structure is provided, carry
The layered structure technology that can adaptively adjust is gone out, has adapted to the demand that power equipment image data frequently changes, be further
Analysis electric power image comprehensively, judges that power equipment operating status provides powerful support.
To achieve the above object, the technical solution adopted by the present invention is：The multispectral number of power equipment based on layered structure
According to center model method for building up, include the following steps：
1）The analysis based on power equipment multispectral data structure is carried out, including the analysis to data center services frame and to shadow
As the analysis of discriminance analysis algorithm；
2）According to the analysis to data center services frame, power equipment multispectral data center model is built, including mutually interconnecting
Connect and carry out application layer, dispatch layer, operation layer and the data Layer of data transfer；
3）According to the analysis to image discriminance analysis algorithm, image discriminance analysis model is built, including image information acquisition and in advance
Processing, image characteristics extraction and reconstruct, image judgement and identification；
4）It carries out image discriminance analysis model and relationship analysis is applied, and build power equipment for multispectral data center model
Information connects proxy construction；
5）By the way that power equipment multispectral data center model, image discriminance analysis algorithm is called to connect generation with power equipment information
Structure is managed, computer is relied on individually to model the unit in each model system, generates hierarchical control unit, and according to practical topology
Relationship is connected the network for forming distributed frame, so as to fulfill the AUTOMATIC ZONING for power equipment multispectral data
And operation.
Further, the power equipment information connection proxy construction includes service agent and application proxy, the business
Agency includes control agent, distributed agent and user agent, and the application proxy includes data service and acts on behalf of and visualize mould
Block.
Further, the hierarchical control unit is multilayer nest structure, including central agency unit connected in sequence, is imitated
True process unit, emulation sequential hierarchical control unit, object broker unit, condition monitoring unit and external interface unit.
Further, the external interface unit includes EMS external data bases, described outer for obtaining initialization data
Portion's interface unit by high-performance messaging bus respectively with the simulation process unit, the emulation sequential hierarchical control unit,
The object broker unit, the condition monitoring unit realize two-way interconnection.
Further, the data Layer is power equipment physical layer, passes through visualization model, measuring apparatus, proxy for equipment
Power equipment spectral information is obtained, inquire power equipment image data result or deposits the image data that operation layer transmits
Storage.
Further, the dispatch layer is information security layer, and the fire wall as whole system is not only to System Back-end
Request carries out authentication, while completes the encryption protection work in service forwarding.
Further, the operation layer by multiple subsystems and is adapted to the service in market and forms, and can not only call
Internal services may call upon other external services, and carry out information exchange with other agencies, collect and send from business generation
The control signal of reason and application proxy.
Further, the application layer makes user be directly facing terminal user and mobile terminal application, passes through application
Software moves device A PP programs to access status of electric power.
The beneficial effects of the present invention are：
Multispectral detection and analysis and key technology involved in identification the present invention provides transformer equipment operating status, are established
The multispectral data center model of transformer equipment operating status builds distributed power grid equipment image data processing center technology frame
Frame, the analyzing and processing of acquisition, image data including Multiple Source Sensor image, mobile terminal interaction and the contents such as builds, by more
Kind of sensor and other modes obtain multi-source image and power equipment relevant information, electric power facility data are detected point
Analysis, data processing centre builds data center's storing framework, by file system, Computational frame and database, further improves
Many bottlenecks in terms of storage.Data processing centre and mobile terminal are realized finally by data processing centre's technological frame is built
Technology interconnection, so as to fulfill interconnecting for detection platform and expert's platform, and finally utilize mobile-terminal platform further
Instruct field operation.This project can be not only solved in the analysis of transformer equipment multispectral image, how to be established in multispectral data
Heart model simultaneously efficiently utilizes image data problem, provides data basis for transformer equipment fault detection and diagnosis, has played shifting
The advantage of dynamic terminal ensures grid equipment safe and reliable operation, has higher theoretical and practical significance, and have with very strong
Effect property and practicability, should be widely promoted and use.
Description of the drawings
Fig. 1 is the system assumption diagram of power equipment multispectral data center model of the present invention.
Fig. 2 is the structural relation figure of image discriminance analysis model of the present invention.
Fig. 3 is the composition structure diagram of hierarchical control unit of the present invention.
Fig. 4 is the component relationship figure of power equipment information connection proxy construction of the present invention.
Specific embodiment
Embodiment
As shown in Figures 1 to 4, the power equipment multispectral data center model method for building up based on layered structure, including
Following steps：1）The analysis based on power equipment multispectral data structure is carried out, including the analysis to data center services frame
With the analysis to image discriminance analysis algorithm；2）According to the analysis to data center services frame, structure power equipment is multispectral
Data center model, application layer, dispatch layer, operation layer and data Layer including being connected with each other and carrying out data transfer；3）According to
Analysis to image discriminance analysis algorithm builds image discriminance analysis model, including image information acquisition and pretreatment, image spy
Sign extraction and reconstruct, image judgement and identification；4）Carry out image discriminance analysis model answering for multispectral data center model
With relationship analysis, and build power equipment information connection proxy construction；5）By calling power equipment multispectral data center die
Type, image discriminance analysis algorithm and power equipment information connect proxy construction, rely on computer by the unit in each model system
Individually modeling generates hierarchical control unit, and the network for forming distributed frame is connected according to practical topology relationship,
So as to fulfill the AUTOMATIC ZONING for power equipment multispectral data and operation.
In specific application, power equipment multispectral data center model is broadly divided into four levels, and 1）Application layer, i.e., directly
Junction is applied to terminal user and mobile terminal；2）Dispatch layer, such as fire wall；3）Operation layer；4）Data Layer.It is applying
In layer, user accesses target device state using application software or mobile device A PP programs.Request is entered by dispatch layer
Operation layer, the fire wall as whole system not only carry out authentication to the request of System Back-end, while complete service forwarding
Work.System business layer is by multiple subsystems and is adapted to the service in market and forms, and can not only call internal services, may be used also
To call other external services.Final data accumulation layer is responsible for what is inquired power equipment image data result or transmit operation layer
Image data is stored.
Grid equipment image discriminance analysis model in the present invention, as shown in Fig. 2,：Image information acquisition and pretreatment, image
Feature extraction and reconstruct, image judgement and identification, equipment feature extraction will consider equipment color characteristic, textural characteristics, shape
Shape（Contour feature）With scale space information；Exemplary apparatus feature in the computer vision based on geometric properties is studied, uses for reference figure
As the experience that processing is applied successfully with identification technology in other fields, image procossing and the algorithm of pattern-recognition are applied into electricity
The identification of power equipment can find target by certain algorithm in figure, determine its coordinate position, identify power equipment
Type, this is further to analyze electric power image prerequisite comprehensively, is the basis for judging power equipment operating status.
For the characteristic of grid equipment image, the reconstruct of equipment image is carried out, and then promote obtained equipment image
Quality.Image enhancement technique protrudes area-of-interest in grid equipment image for the preprocessing process in image analysis identification
Information, it is the image for being more suitable for man-machine identification to convert former grid equipment image.Study common equipment image enhancement processing side
Formula：Greyscale transformation, histogram modification, image sharpening, noise remove, geometric distortion correction, frequency domain filtering and colored enhancing etc.；It grinds
Study carefully the algorithm for image enhancement based on spatial domain and the algorithm for image enhancement based on transform domain, it will targeted, the various applications of adaptation
The algorithm for image enhancement of occasion is applied in the processing of equipment image.
For the hotter image reconstructing method based on rarefaction representation of present image reconstruction field, research is based on compression sense
Know theoretical and rarefaction representation the quality of device images Enhancement Method.Grid equipment image generally all has abundant texture, is based on
The details such as texture of the image rebuilding method of rarefaction representation to restoring natural image have good effect, without notable noise shadow
Under the premise of sound and fuzzy core are known, performance is more outstanding.In addition to this, the dictionary atom number of the method structure of rarefaction representation
Less, efficient, this has reserved space further to design more complicated, the better algorithm of image reconstruction effect.
The High level feature extraction model based on deep learning is studied, is built from image bottom visual signature to advanced language
Adopted feature successively iteration, successively abstract depth network mapping model, it is intended to reduce semantic gap, obtain image, semantic feature,
Good basis is provided for large-scale image automatic marking
For the problem that the equipment image based on deep learning identifies, most basic i.e. stronger feature is researched and solved, using more
Good network training model can greatly improve the accuracy rate of identification.Research directly predicts that each position may using global characteristics
Device target, be constantly iterated recurrence adjustment, obtain final recognition result.Research is by defining recurrence mode, network
And model, original recognition result is returned and then is identified again, promotes effect.
The basis of the method for the present invention is the analysis of progress demixing technology, and technology is a kind of information processing technology, by multiple
Agency completes a certain target by cooperating, and agency can be with environment where it into row information and the interaction of behavior.At this
Agent unit is corresponded to containing distributed distribution sub-district in method.Layering is a kind of its advanced existence form, will by certain rule
Agent unit merges, and realizes the advanced interaction function of group.It " is layered " and is embodied in the method：According to the algorithm rule proposed
Then, the division on effectively " space " scale is carried out to power equipment region, is acted on behalf of by the agent group forming region in region.Its skill
Art feature is between regional agency and regional agency that the information and behavior between regional agency and upper-level system agency are interactive.
Its core value be the self study of agent group, self-coordinating, Self management, from the function of performing, inherently " parallel processing " and
The ability of " batch processing ".
Power equipment information connection proxy construction include service agent and application proxy, service agent include control agent,
Distributed agent and user agent, application proxy include data service agency and visualization model.It is made of four kinds of agencies, respectively
It is control agent, distributed agent, user agent and application proxy, and application proxy includes data service and acts on behalf of and visualize
Module.Within the system, each agency has respective target and responsibility.The function of control agent includes surveillance and monitoring accident.When
During faulty generation, control agent sends signal and forms isolation.Distributed agent is responsible for storing correlation distribution information, can also supervise
Control distributed power and connection status.Distributed information includes number of devices, type, rated power, utilization rate etc..User's generation
Manage the channel for user being supplied to understand relevant information as intelligent micro-grid.User agent provides each entity of intelligence system for client
Real time information.User agent can also monitor the channel of important and insignificant information, and finally, application proxy is responsible for storage system letter
Information sharing between breath, record information and each agency, application proxy also serves as the data access of each agency and user shows
Module, as shown in Figure 4.
Traditional model cootrol, modeling agent are the fixed cells by initial setting, it is impossible to adapt to the variation of scene
And make adaptive adjustment.The agency that the present invention designs is not changeless, with the variation of scene, can be done between agency
Go out adaptive adjustment, i.e. " nesting "." nesting " is a kind of concrete methods of realizing of " layering " information model of the present invention, first
First the distribution network systems studied are carried out with the identification and search of fragility critical path, determines basis agent unit, then root again
According to distributed frame access information, operation rules is formed according to distributed access point and equipment key factor, to agent unit into
Row repeatedly " merging " operation, i.e., so-called " nesting ".
The layered model of the present invention includes two aspects, and a kind of is the functionalization layering as multispectral data center, i.e.,
Function from top to bottom is transmitted, wherein, data Layer is power equipment physical layer, passes through visualization model, measuring apparatus, equipment generation
Reason obtains power equipment spectral information, inquires power equipment image data result or deposits the image data that operation layer transmits
Storage.Dispatch layer is information security layer, and the fire wall as whole system not only carries out authentication to the request of System Back-end, together
When complete service forwarding in encryption protection work.Operation layer is by multiple subsystems and is adapted to the service in market and forms, no
But internal services can be called, other external services is may call upon, and information exchange is carried out with other agencies, collects and send
Control signal from service agent and application proxy.Application layer makes user be directly facing terminal user and mobile terminal should
With accessing status of electric power by application software or mobile device A PP programs.
On the other hand, it is by simulating control planning, with the concept of global coordination, carries out the layering of network classification formula,
That is hierarchical control unit is multilayer nest structure, including central agency unit connected in sequence, simulation process unit, emulation
Sequential hierarchical control unit, object broker unit, condition monitoring unit and external interface unit.
External interface unit includes EMS external data bases, and for obtaining initialization data, external interface unit passes through high property
Energy messaging bus is real with simulation process unit, emulation sequential hierarchical control unit, object broker unit, condition monitoring unit respectively
Existing two-way interconnection.
The hierarchical control unit of the present invention is that computing unit is then constituted to multiple Central co-ordination generations with cascade connection
Unit is managed, the control planning being responsible between simulation multistage network, and respectively plan as a whole internal multiple object brokers and collectively form one
Using " orderly access and network fluctuation are minimum for distribution " as the image discriminance analysis algorithm of " global coordination target ", what is given
After input parameter, constraints, the distributed node inside analog network orderly accesses and the energy balance process of network internal,
Cyberrelationship figure is as shown in figure 3, each section, that is, opposite outer is independent, and can be carried out by central agency unit arbitrary external
It expands, generates with the multistage multi-region network model of different power equipment types and region division, in different levels, different zones
It realizes the superior and the subordinate and interregional coordinated management, is only contacted by central agency unit between the superior and the subordinate and sane level, do not done mutually
Relate to internal operation.
In practical applications, hierarchical control unit is multilayer nest structure, and every grade of structure is similar.By taking level-one as an example, such as
Shown in Fig. 3, mainly include central agency unit, simulation process, emulation timing control, object broker unit, Stateful Inspection and outer
The parts such as portion's interface, Each part and concrete function are as follows：
Central agency is responsible for coordinating the simulation process between the superior and the subordinate and subregion, and make overall plans and coordinate this grade of inside.It is each
A central agency, which is all only responsible for this grade or one's respective area, upper network or undernet, respectively has independent central agency to be responsible for.In
Another important function of centre agency is to be responsible for calling backstage simulation calculation program to this grade of network internal state analysis meter
It calculates, and result of calculation is broadcasted to its administrative all object broker；
In simulation process, since artificial network is multilevel hierarchy, in order to realize that the parallelization in region calculates, drawn per sub-regions
A simulation calculation process is separated, so as to fulfill multizone concurrent operation.In addition when local area coordination strategy can not restrain, pass through
The central agency progress on upper strata is transregional to make overall plans and coordinate task；Emulation scene refers under sometime section, by central agency and
The global state for the artificial network that the current information of object broker is formed.
It is by the simulation process whole sequential inside all levels and subregion to emulate timing control, is triggered by event
Mode carry out the simulation of continuous time section and calculate, the calculation process in each area is relatively independent, therefore central agency will be closed especially
Note synchronization of the event in sequential in its subregion.According to central agency " Stateful Inspection ", " simulation analysis ", " overall planning ",
The definition of " tasks carrying " Simulation Control ring, to central agency, complete function is defined as follows shown in figure：Central agency according to when
Between stamp constantly update current network state, and by result to own net broadcast, obtained by port snoop to affiliated object
The status information of agency.Central agency needs global coordination strategy to support, applicable coordination is calculated under current constraints
Strategy.When calculating coordination strategy result and not restraining, show inside present networks can not self-coordinating, can superior application.Similarly,
The request that central agency should send undernet responds.
Object broker unit is by the object of central location management, is the most basic constructing module of artificial network, each region
In all comprising multiple object broker examples, for describing and the essential attribute of constructive simulation object model, its own has knowledge
Method base and logic rules algorithm, for changing from main response oneself state.
Central agency or object broker are all a kind of computing units, and artificial network is exactly to be made of these computing units.
In software systems, if the resource that computing unit has under its command has been specifically directed towards certain class specific simulation model, external manifestation is
Object broker, if computing unit, which has under its command, further includes other computing units in resource, external manifestation is central agency.Artificial network
Autonomized conclusion for be exactly to realize autonomous management mechanism of the computing unit to itself administrative resource, for replace those originally
Need the management work manually carried out.In addition, initialization data, distributed file system are obtained by EMS external data bases
Each region topology model file data are then provided.
Distributed collaborative modeling method under hierarchical control unit structure is that lower control unit is individually encapsulated, and is only focused on interior
Portion defines and the exciter response strategy to main hierarchical control unit, its own data and resource are limited, and nonintervention or influence are external
Network structure and other targets.Main hierarchical control unit no longer serves as the calculating each intra-node process of the task, it is only necessary to root
Carry out requirement according to whole control targe formulation pumping signal to response to which, feedback result is verified, the inside of lower control unit
Analysis, adjustment and optimization process hide it.And the master administrator of real application systems is also not intended to excessively pay close attention to each subordinate's
Whether internal procedure, assessment system have reached overall operation target, significantly reduce the burden of central task in this mode.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, the general technology people of this field
Member using the solution of the present invention it will be recognized that can also realize many optional embodiments.It is all in the spirit and principles in the present invention
Within all any modification, equivalent and improvement made etc., should all be included in the protection scope of the present invention.
Claims (8)
1. the power equipment multispectral data center model method for building up based on layered structure, which is characterized in that including walking as follows
Suddenly：
1）The analysis based on power equipment multispectral data structure is carried out, including the analysis to data center services frame and to shadow
As the analysis of discriminance analysis algorithm；
2）According to the analysis to data center services frame, power equipment multispectral data center model is built, including mutually interconnecting
Connect and carry out application layer, dispatch layer, operation layer and the data Layer of data transfer；
3）According to the analysis to image discriminance analysis algorithm, image discriminance analysis model is built, including image information acquisition and in advance
Processing, image characteristics extraction and reconstruct, image judgement and identification；
4）It carries out image discriminance analysis model and relationship analysis is applied, and build power equipment for multispectral data center model
Information connects proxy construction；
5）By the way that power equipment multispectral data center model, image discriminance analysis algorithm is called to connect generation with power equipment information
Structure is managed, computer is relied on individually to model the unit in each model system, generates hierarchical control unit, and according to practical topology
Relationship is connected the network for forming distributed frame, so as to fulfill the AUTOMATIC ZONING for power equipment multispectral data
And operation.
2. the power equipment multispectral data center model method for building up based on layered structure as described in claim 1, special
Sign is：The power equipment information connection proxy construction includes service agent and application proxy, and the service agent includes control
System agency, distributed agent and user agent, the application proxy include data service agency and visualization model.
3. the power equipment multispectral data center model method for building up based on layered structure as described in claim 1, special
Sign is：The hierarchical control unit is multilayer nest structure, including central agency unit connected in sequence, simulation process list
Member, emulation sequential hierarchical control unit, object broker unit, condition monitoring unit and external interface unit.
4. the power equipment multispectral data center model method for building up based on layered structure as claimed in claim 3, special
Sign is：The external interface unit includes EMS external data bases, for obtaining initialization data, the external interface unit
By high-performance messaging bus respectively with the simulation process unit, the emulation sequential hierarchical control unit, the object generation
Manage unit, the condition monitoring unit realizes two-way interconnection.
5. the power equipment multispectral data center model method for building up based on layered structure as described in claim 1, special
Sign is：The data Layer is power equipment physical layer, obtains electric power by visualization model, measuring apparatus, proxy for equipment and sets
Standby spectral information inquires power equipment image data result or stores the image data that operation layer transmits.
6. the power equipment multispectral data center model method for building up based on layered structure as described in claim 1, special
Sign is：The dispatch layer is information security layer, and the fire wall as whole system not only carries out body to the request of System Back-end
Part verification, while complete the encryption protection work in service forwarding.
7. the power equipment multispectral data center model method for building up based on layered structure as described in claim 1, special
Sign is：The operation layer is by multiple subsystems and is adapted to the service in market and forms, and can not only call internal services, also
Other external services can be called, and information exchange is carried out with other agencies, collects and sends from service agent and using generation
The control signal of reason.
8. the power equipment multispectral data center model method for building up based on layered structure as described in claim 1, special
Sign is：The application layer makes user be directly facing terminal user and mobile terminal application, passes through application software or shifting
Device A PP programs are moved to access status of electric power.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109272232A (en) * | 2018-09-21 | 2019-01-25 | 国家电网有限公司 | Visualized data management method based on substation's fining inspection business |
| CN109546684A (en) * | 2018-12-18 | 2019-03-29 | 辽宁恒顺新能源科技有限公司 | Micro-capacitance sensor power supply system |
| CN113222211A (en) * | 2021-03-31 | 2021-08-06 | 中国科学技术大学先进技术研究院 | Multi-region diesel vehicle pollutant emission factor prediction method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102968620A (en) * | 2012-11-16 | 2013-03-13 | 华中科技大学 | Scene recognition method based on layered Gaussian hybrid model |
| CN103218796A (en) * | 2013-05-14 | 2013-07-24 | 中国科学院自动化研究所 | Fusion method of full color-multispectral remote sensing images |
| CN104573654A (en) * | 2015-01-08 | 2015-04-29 | 中国林业科学研究院资源信息研究所 | Mangrove extraction method based on hierarchical decision tree |
| US20170262984A1 (en) * | 2014-12-03 | 2017-09-14 | Ventana Medical Systems, Inc. | Methods, Systems, and Apparatuses for Quantitative Analysis of Heterogeneous Biomarker Distribution |
| CN107248149A (en) * | 2017-05-31 | 2017-10-13 | 浙江国遥地理信息技术有限公司 | Methods on Multi-Sensors RS Image fusion method |
-
2018
- 2018-02-06 CN CN201810119273.6A patent/CN108228900B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102968620A (en) * | 2012-11-16 | 2013-03-13 | 华中科技大学 | Scene recognition method based on layered Gaussian hybrid model |
| CN103218796A (en) * | 2013-05-14 | 2013-07-24 | 中国科学院自动化研究所 | Fusion method of full color-multispectral remote sensing images |
| US20170262984A1 (en) * | 2014-12-03 | 2017-09-14 | Ventana Medical Systems, Inc. | Methods, Systems, and Apparatuses for Quantitative Analysis of Heterogeneous Biomarker Distribution |
| CN104573654A (en) * | 2015-01-08 | 2015-04-29 | 中国林业科学研究院资源信息研究所 | Mangrove extraction method based on hierarchical decision tree |
| CN107248149A (en) * | 2017-05-31 | 2017-10-13 | 浙江国遥地理信息技术有限公司 | Methods on Multi-Sensors RS Image fusion method |
Non-Patent Citations (2)
| Title |
|---|
| XIMING CHEN ET AL.: ""Optimal coinfection control of competitive epidemics in multi-layer networks"", 《IEEE CONFERENCE ON DECISION AND CONTROL》 * |
| 宋文洋: ""应用多光谱图像融合的电力设备故障点检测方法"", 《万方数据知识服务平台》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109272232A (en) * | 2018-09-21 | 2019-01-25 | 国家电网有限公司 | Visualized data management method based on substation's fining inspection business |
| CN109546684A (en) * | 2018-12-18 | 2019-03-29 | 辽宁恒顺新能源科技有限公司 | Micro-capacitance sensor power supply system |
| CN109546684B (en) * | 2018-12-18 | 2024-04-02 | 辽宁恒顺新能源科技有限公司 | Micro-grid power supply system |
| CN113222211A (en) * | 2021-03-31 | 2021-08-06 | 中国科学技术大学先进技术研究院 | Multi-region diesel vehicle pollutant emission factor prediction method and system |
| CN113222211B (en) * | 2021-03-31 | 2023-12-12 | 中国科学技术大学先进技术研究院 | Method and system for predicting pollutant emission factors of multi-region diesel vehicle |
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