CN109190716A - Processing method, device and the electronic equipment of low-voltage collecting meter reading failure - Google Patents
Processing method, device and the electronic equipment of low-voltage collecting meter reading failure Download PDFInfo
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- CN109190716A CN109190716A CN201811238707.0A CN201811238707A CN109190716A CN 109190716 A CN109190716 A CN 109190716A CN 201811238707 A CN201811238707 A CN 201811238707A CN 109190716 A CN109190716 A CN 109190716A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- 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
- G06Q10/20—Administration of product repair or maintenance
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- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
Present invention discloses processing method, device and the electronic equipments of a kind of low-voltage collecting meter reading failure, belong to computer application technology.The described method includes: fault signature when obtaining low-voltage collecting meter reading；Similar historical fault signature is searched from the accident analysis library constructed in advance according to the fault signature；The failure cause for generating the fault signature is determined according to the corresponding failure cause of the similar historical fault signature.Fault signature when processing method, device and the electronic equipment of above-mentioned low-voltage collecting meter reading failure can be according to low-voltage collecting meter readings automatically determines failure cause, provides preferable convenience for the troubleshooting of low-voltage collecting meter reading, substantially increases the efficiency for solving failure.
Description
Technical field
The present invention relates to computer application technology, in particular to a kind of processing method of low-voltage collecting meter reading failure, device
And electronic equipment.
Background technique
Low-voltage collecting meter reading is the proper noun of a power industry, is construed to " low pressure kilowatt-hour meter centralized automatic meter-reading ", refers to automatic survey
Amount and acquisition resident's electric energy meter degree monthly arrive user house without meter reader and are copied one by one by using low-voltage collecting meter reading
By network manual metering cost can be greatly saved in the electricity consumption of backstage real time inspection each household resident in table, grid company
And efficiency is significantly improved, low-voltage collecting meter reading system has covered most of residents at present.
However, current low-voltage collecting meter reading system usually will appear failure, cause grid company that can not accurately acquire resident's
Electricity consumption.Currently, needing service personnel to check failure one by one to multiple places, ability when low-voltage collecting meter reading system breaks down
Determine fault point.Such as: if grid company can not collect ammeter reading by network, service personnel needs to arrive first to work as platform
Transformer where area check concentrator whether failure, if the collector arrived again by resident family's inspection electric energy meter without failure is
No failure, if still fault-free to check again resident electric energy meter whether failure, if again without failure cause is found,
There are also check whether communication network is abnormal.Service work is very cumbersome, and low efficiency, and service personnel is needed to have stronger skill
Can, to propose higher requirement to service personnel.
Summary of the invention
For the technical problem that cost of overhaul when solving low-voltage collecting meter reading failure in the related technology is higher, efficiency is lower, originally
Invention provides processing method, device and the electronic equipment of a kind of low-voltage collecting meter reading failure.
In a first aspect, providing a kind of processing method of low-voltage collecting meter reading failure, comprising:
Obtain fault signature when low-voltage collecting meter reading；
Similar historical fault signature is searched from the accident analysis library constructed in advance according to the fault signature；
The failure cause for generating the fault signature is determined according to the corresponding failure cause of the similar historical fault signature.
Optionally, the construction method in the accident analysis library includes:
Operation/maintenance data when low-voltage collecting meter reading is excavated by big data；
Fault signature when low-voltage collecting meter reading breaks down and corresponding failure cause are extracted from the operation/maintenance data；
The fault signature and corresponding failure cause are subjected to corresponding storage and form the accident analysis library.
Optionally, the method also includes:
When being searched from the accident analysis library constructed in advance less than similar historical fault signature according to the fault signature,
Carry out the insufficient prompt of breakdown judge；
The prompt is responded, acquisition low-voltage collecting meter reading generates O&M image when failure；
The O&M image is subjected to deep learning in the accident analysis library, identifies the equipment in the O&M image
Title and abort situation；
The failure cause for generating the fault signature is determined by the fault signature, device name and abort situation.
Optionally, the construction method in the accident analysis library further include:
The image of involved equipment during collection low-voltage collecting meter reading；
Described image is marked according to the model of each equipment and failure cause；
Deep learning is carried out to by the described image of label, forms the accident analysis library.
Optionally, described that the O&M image is subjected to deep learning in the accident analysis library, identify the O&M
The step of device name and abort situation in image includes:
The O&M image is carried out by matching operation in accident analysis library using deep learning algorithm, identifies the O&M
Device name in image；
The image that different zones are intercepted from the O&M image, obtains area image；
Matching degree between fault picture in the area image and accident analysis library is calculated using deep learning algorithm；
The abort situation in the O&M image is identified according to the matching degree.
Optionally, the method also includes:
Corresponding troubleshooting measure is searched in the accident analysis library according to the failure cause；
It is instructed to carry out troubleshooting according to the troubleshooting measure.
Second aspect provides a kind of processing unit of low-voltage collecting meter reading failure, comprising:
Speech data collection module, for obtaining fault signature when low-voltage collecting meter reading；
Similar features searching module, it is similar for being searched from the accident analysis library constructed in advance according to the fault signature
Historical failure feature；
Failure cause determining module generates institute for determining according to the corresponding failure cause of the similar historical fault signature
State the failure cause of fault signature.
Optionally, described device further include:
Cue module, for being gone through less than similar being searched from the accident analysis library constructed in advance according to the fault signature
When history fault signature, the insufficient prompt of breakdown judge is carried out；
O&M image capture module, for responding the prompt, acquisition low-voltage collecting meter reading generates O&M image when failure；
Deep learning module identifies institute for the O&M image to be carried out deep learning in the accident analysis library
State the device name and abort situation in O&M image；
Failure cause depth determining module is generated for being determined by the fault signature, device name and abort situation
The failure cause of the fault signature.
The third aspect provides a kind of electronic equipment, which is characterized in that the electronic equipment includes:
At least one processor；And
The memory being connect at least one described processor communication；Wherein,
The memory is stored with the instruction that can be executed by least one described processor, and described instruction is by described at least one
A processor executes, so that at least one described processor is able to carry out method as described in relation to the first aspect.
Fourth aspect provides a kind of computer readable storage medium, for storing program, which is characterized in that the journey
Sequence makes terminal execute the method such as first aspect when executed.
The technical solution that embodiment through the invention provides can obtain it is following the utility model has the advantages that
When low-voltage collecting meter reading breaks down, phase is searched from the accident analysis library constructed in advance according to the fault signature of acquisition
After historical failure feature, failure cause can be automatically determined, provides preferable convenience for the troubleshooting of low-voltage collecting meter reading,
Substantially increase the efficiency for solving failure.
It should be understood that the above general description and the following detailed description are merely exemplary, the present invention not by
Limitation.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows and meets implementation of the invention
Example, and be used to explain the principle of the present invention together with specification.
Fig. 1 is a kind of processing method flow chart of low-voltage collecting meter reading failure shown according to an exemplary embodiment.
The interface schematic diagram of fault signature shown according to an exemplary embodiment input when Fig. 2.
Fig. 3 is accident analysis library building side in the processing method according to the low-voltage collecting meter reading failure shown in Fig. 1 corresponding embodiment
A kind of specific implementation flow chart of method.
Fig. 4 is the flow chart in the processing method of another low-voltage collecting meter reading failure shown according to Fig. 1 corresponding embodiment.
Fig. 5 is accident analysis library building side in the processing method according to the low-voltage collecting meter reading failure shown in Fig. 4 corresponding embodiment
A kind of specific implementation flow chart of method.
Fig. 6 is a kind of tool of step S230 in the processing method according to the low-voltage collecting meter reading failure shown in Fig. 4 corresponding embodiment
Body implementation flow chart.
Fig. 7 is the processing method of another low-voltage collecting meter reading failure shown according to Fig. 1 or Fig. 3 corresponding embodiment.
Fig. 8 is a kind of block diagram of the processing unit of low-voltage collecting meter reading failure shown according to an exemplary embodiment.
Fig. 9 is the block diagram of the processing unit of another low-voltage collecting meter reading failure shown according to Fig. 8 corresponding embodiment.
The block diagram of Figure 10 a kind of electronic equipment 100 shown according to an exemplary embodiment.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following exemplary is implemented
Embodiment described in example does not represent all embodiments consistented with the present invention.On the contrary, they are only and such as institute
The example of device and method documented in attached claims, some aspects of the invention are consistent.
Fig. 1 is a kind of processing method flow chart of low-voltage collecting meter reading failure shown according to an exemplary embodiment, is applied to
In the electronic equipments such as AR glasses, mobile phone, computer.If Fig. 1 shows, the processing method of the low-voltage collecting meter reading failure may include following step
Suddenly.
Step S110 obtains fault signature when low-voltage collecting meter reading.
It is understood that in low-voltage collecting meter reading, when be in the presence of can not meter reading or when inaccurate meter reading, it will usually table
Reveal some from different feature under normal circumstances, and these features are fault signature.
Fault signature can be what low-voltage collecting meter reading system obtained in real time, is also possible to user and is judging corresponding fault signature
When and input, fault signature, which can also be, to be obtained by other forms.
For example, when Fig. 2 fault signature shown according to an exemplary embodiment input interface schematic diagram.Existed by user
The check box that interactive interface carries out fault signature is chosen, and fault signature when low-voltage collecting meter reading is obtained.
Step S120 searches similar historical fault signature according to fault signature from the accident analysis library constructed in advance.
Historical failure feature and corresponding failure cause are stored in the accident analysis library constructed in advance.
In exemplary embodiment in the specific implementation, the historical failure feature that is stored in accident analysis library and corresponding
Failure cause, can be the fault signature collected in advance and with the matched failure cause of the fault signature, being also possible to will be each
Instant fault signature and immediately determining failure cause are as history data store.
The accident analysis library constructed in advance can be stored in the database in terminal device, be stored in server
In database.
It should be noted that each historical failure feature in the accident analysis library constructed in advance includes the shapes such as text, image
Formula.
Break down in current low-voltage collecting meter reading and after obtaining fault signature, by the historical failure feature in accident analysis library
Current fault signature compares with instant medical record information, searches historical failure feature similar with current fault signature.
Optionally, as shown in figure 3, the construction method in accident analysis library may include step S121, S122, S123:
Step S121 excavates operation/maintenance data when low-voltage collecting meter reading by big data.
When low-voltage collecting meter reading, it will a large amount of operation/maintenance data is generated, after operation/maintenance data is uploaded to background service, operation/maintenance data packet
The text information generated during O&M and image information are contained.
Step S122 extracts failure cause when low-voltage collecting meter reading breaks down and corresponding failure spy from operation/maintenance data
Sign.
After determining failure cause according to fault signature each time, when extraction low-voltage collecting meter reading breaks down from operation/maintenance data
Fault signature and corresponding failure cause, and corresponding storage, form accident analysis library.
Failure cause and corresponding fault signature are carried out corresponding storage and form accident analysis library by step S123.
Similar historical fault signature can be a historical failure feature identical with the text of current failure feature；It can also
To be a historical failure feature identical with the image of current failure feature；Can also be with the image of current failure feature or
The combination of the identical multiple historical failure features of text.
Step S130 determines that the failure for generating fault signature is former according to the corresponding failure cause of similar historical fault signature
Cause.
Failure cause is failure cause corresponding with similar historical fault signature in the database constructed in advance.
When finding similar historical fault signature, if the quantity of similar historical fault signature be it is multiple, need to be more according to this
The feature of a similar historical fault signature combines, and searches in accident analysis library and combines corresponding failure cause with this feature.
In one exemplary embodiment, can the electronic equipments such as AR terminal be carried out with the typing of fault signature, it is a certain in discovery
When the similar low-voltage collecting meter reading equipment fault in platform area, according to the promotion of AR terminal, maintenance task according to system suggestion typing/click
Corresponding failure is similar.Because AR terminal has very strong number by network and accident analysis library real time link, accident analysis library
According to storage and query capability.And means are excavated by the big data of depth learning technology, accident analysis library can be with O&M number
According to be continuously increased, data volume is also more and more.After service personnel carries out the typing of fault signature by AR terminal, by wireless
Network passes to accident analysis library, after accident analysis library is connected to fault signature, in such a way that database list is inquired, looks in real time
Similar fault signature and corresponding failure cause and AR terminal is returned into accident analysis library.
Using method as described above, when low-voltage collecting meter reading breaks down, constructed according to the fault signature of acquisition from preparatory
Accident analysis library in search similar historical fault signature after, failure cause can be automatically determined, be low-voltage collecting meter reading failure at
Reason provides preferable convenience, substantially increases the efficiency for solving failure.
Fig. 4 is the flow chart in the processing method of another low-voltage collecting meter reading failure shown according to Fig. 1 corresponding embodiment, such as
Shown in Fig. 4, the processing method of the low-voltage collecting meter reading failure can also include the following steps S210, step S220, step S230, step
S240。
Step S210, it is special less than similar historical failure being searched from the accident analysis library constructed in advance according to fault signature
When sign, the insufficient prompt of breakdown judge is carried out.
It is understood that the data volume for the accident analysis library storage that ought be constructed in advance is less, it can not be in accident analysis library
In when finding with similar historical fault signature, then need to further determine that failure cause by other means.
Therefore, it is being searched from the accident analysis library constructed in advance less than similar historical fault signature according to fault signature
When, the insufficient prompt of breakdown judge is carried out, to inform that user further provides for dependent failure information.
Step S220, response prompt, acquisition low-voltage collecting meter reading generate O&M image when failure.
It is installed with the image capture devices such as camera on electronic equipment, failure is generated by image capture device low-voltage collecting meter reading
When O&M image.
Optionally, when carrying out O&M Image Acquisition, the preliminary judgement of failure cause is carried out according to existing fault signature,
Analyze possible failure cause and other there may be location of faults, and then there may be location of faults for these
The acquisition for carrying out O&M image, to further increase the accuracy and efficiency of breakdown judge.
O&M image is carried out in accident analysis library deep learning, identifies the implementor name in O&M image by step S230
Title and abort situation.
Carrying out image recognition using deep learning is realized based on the prior sample for marking and training.
Optionally, as shown in figure 5, the construction method in accident analysis library may include step S310, step S320, step
S330:
Step S310 collects the image of involved equipment during low-voltage collecting meter reading.
All devices image involved in low-voltage collecting meter reading system is collected (comprising equipment appearance, nameplate, LED status, to press
Button state etc.),
Step S320 is marked image according to the model of each equipment and failure cause.
Step S330 carries out deep learning to by the image of label, forms accident analysis library.
The a large amount of pictures being collected into are subjected to unified classified finishing, different equipment is marked as according to different device models
It encodes (each equipment code value is unique).Then these samples are carried out to the training of deep learning, adjusted after the completion of training
It can be achieved with computer with sample pattern and export different device codings according to distinct device image classification.Furthermore in back-end data
In library, by way of data form in advance by each device coding and facility information (model, title, electrical characteristic,
Fault category etc.) it corresponds.Therefore it is just tender to inquire after computer gets the unique encodings value of equipment by image recognition
Corresponding device model.
In one exemplary embodiment, O&M image is subjected to depth in accident analysis library using convolutional neural networks
It practises, identifies the device name and abort situation in O&M image.
After the training by deep learning, forming accident analysis library is a convolutional neural networks.
Convolutional neural networks (CNN, Convolutional Neural Network) are a kind of multilayer neural networks, are good at
Processing image is especially the correlation machine problem concerning study of big image.Convolutional network is by serial of methods, successfully by data volume Pang
The continuous dimensionality reduction of big problem of image recognition, can finally be trained to.CNN is proposed by Yann LeCun earliest and is applied in hand
(MINST) is write in Character Font Recognition.
Convolutional neural networks are made of convolutional layer, pond layer, full articulamentum.Wherein convolutional layer and pond layer cooperate, composition
Multiple convolution groups, successively extract feature, complete classification eventually by several full articulamentums.The operation that convolutional layer is completed, can be with
It is considered the inspiration by local receptor field concept, and pond layer, primarily to reducing data dimension.
It integrates, CNN is distinguished by convolution come simulation feature, and the weight for passing through convolution is shared and pond, comes
The order of magnitude for reducing network parameter forms accident analysis library finally by traditional neural network.
Optionally, as shown in fig. 6, step S230 may include step S231, step S232, step S233, step S234.
O&M image is carried out matching operation, identification fortune using deep learning algorithm by step S231 in accident analysis library
Tie up the device name in image.
As previously described, there are a large amount of fault pictures in accident analysis library, therefore, using deep learning algorithm by O&M
Image is identified in accident analysis library, that is, can determine the device name in O&M image.
Step S232 intercepts the image of different zones from O&M image, obtains area image.
Intercept different zones image when, can according to different area size from O&M image interception area image.
Step S233 is matched using between deep learning algorithm zoning image and the fault picture in accident analysis library
Degree.
The matching degree between fault picture and area image is calculated by using deep learning algorithm, and then according to matching degree
Identify O&M image.
Optionally, it begins through the biggish area image of area and fault picture carries out matching operation, and then according to matching
Degree intercepts the smaller area image of area in the biggish area image of the area, then carries out matching operation, to pass through a step
The matching operation of one step finally determines the abort situation to break down in O&M image more accurately, substantially increases determination
The accuracy of abort situation.
Step S234 identifies the abort situation in O&M image according to matching degree.
For example, when judging that failure has occurred in an electric energy meter in certain area, but it can not determine and (can not be determined when failure cause
It is wireless transport module failure or metering module failure), AR terminal opens camera in a manner of AR, it is desirable that service personnel couple
The status indicator lamp of the quasi- electric energy meter, obtains judging result to analyze LED status.Service personnel mentions according to AR terminal
Show, after turn electric energy meter indicator light, for system by detection instruction lamp on/off gap periods, determining is that metering module has event
Barrier.
Step S240 determines the failure cause for generating fault signature by fault signature, device name and abort situation.
After determining the device name and abort situation that break down, sufficient fault signature is obtained, by combining root
Searched from the accident analysis library constructed in advance according to fault signature less than similar historical fault signature and pass through deep learning
Identified device name and abort situation can determine the failure cause for generating failure.
Using method as described above, when according to existing fault signature failure cause cannot be able adequately determines, by into
The acquisition of one step generates O&M image when failure, and then the identification of deep learning is carried out to the O&M image, determines and breaks down
Device name and abort situation, and then combine before existing fault signature determine failure cause, avoiding the occurrence of can not determine
The case where failure cause, effectively increases the accuracy of determining failure cause.
Fig. 7 is the processing method of another low-voltage collecting meter reading failure shown according to Fig. 1 or Fig. 3 corresponding embodiment, such as Fig. 7 institute
Show, the processing method of the low-voltage collecting meter reading failure can also include the following steps.
Step S410 searches corresponding troubleshooting measure according to failure cause in accident analysis library.
Each user is when clear failure reason uses measure to carry out troubleshooting, at the failure cause and corresponding failure
Reason measure will be uploaded, and be corresponded to and be stored in accident analysis library as historical data.Therefore, it is stored in accident analysis library
Historical failure reason and its corresponding troubleshooting measure.
After determining failure cause, it will be searched one by one in accident analysis library according to the failure cause.
Optionally, can previously according to failure cause to the historical failure reason and its failure being stored in accident analysis library at
Reason measure carries out Classification Management and greatly improves to can find identical historical failure reason rapidly according to failure cause
Search efficiency.
For example, can be classified according to the device name of failure to historical failure reason.
Step S420 instructs to carry out troubleshooting according to troubleshooting measure.
For example, can instruct to carry out troubleshooting by AR visualized operation.Pass through the language by " AR intelligent mobile terminal "
The modules such as sound, camera, touch screen, display and service personnel carry out visualization human-computer interaction.The guidance of AR visualized operation is inclined
Overweight by camera collection site real-time pictures, then on real-time video picture overlap-add operation text tutorial message.Pass through
The operation such as voice, text prompt, prompting service personnel's next step, how this does.
It by network connection, is communicated in real time with background server, existing fault message is informed into background server,
The previous troubleshooting measure of background server real-time searching, then troubleshooting measure is pushed to AR equipment, AR equipment passes through
Opening system camera, in equipment components color marks such as display facility switching, button, the conducting wires to be operated this step
(these components have done model training in system development to note, and camera sees some component just and can know that its name out
Title and attribute).By the real-time AR color mark to operating member, then it is superimposed corresponding text and speech explanation.Even literary
The not high maintenance personal of change degree can also complete task with following the prescribed order, and greatly reduce troubleshooting difficulty, and it is accurate to improve
Property.
Following is present system embodiment, can be used for executing the processing method embodiment of above-mentioned low-voltage collecting meter reading failure.
For undisclosed details in present system embodiment, the processing method embodiment of low-voltage collecting meter reading failure of the present invention is please referred to.
Fig. 8 is a kind of block diagram of the processing unit of low-voltage collecting meter reading failure shown according to an exemplary embodiment, the system
Including but not limited to: fault signature obtains module 110, similar features searching module 120 and failure cause determining module 130.
Fault signature obtains module 110, for obtaining fault signature when low-voltage collecting meter reading；
Similar features searching module 120, for being searched from the accident analysis library constructed in advance according to the fault signature
Similar historical fault signature；
Failure cause determining module 130 is produced for being determined according to the corresponding failure cause of the similar historical fault signature
The failure cause of the raw fault signature.
The function of modules and the realization process of effect are specifically detailed in the place of above-mentioned low-voltage collecting meter reading failure in above-mentioned apparatus
The realization process of step is corresponded in reason method, details are not described herein.
Optionally, as shown in figure 9, the processing unit of the low-voltage collecting meter reading failure shown in Fig. 8 corresponding embodiment further includes but not
It is limited to: cue module 210, O&M image capture module 220, deep learning module 230 and failure cause depth determining module
240。
Cue module 210, for being searched from the accident analysis library constructed in advance less than phase according to the fault signature
When like historical failure feature, the insufficient prompt of breakdown judge is carried out；
O&M image capture module 220, for responding the prompt, acquisition low-voltage collecting meter reading generates O&M figure when failure
Picture；
Deep learning module 230 is identified for the O&M image to be carried out deep learning in the accident analysis library
Device name and abort situation in the O&M image；
Failure cause depth determining module 240 is produced for being determined by the fault signature, device name and abort situation
The failure cause of the raw fault signature.
The block diagram of Figure 10 a kind of electronic equipment 100 shown according to an exemplary embodiment.With reference to Figure 10, electronic equipment
100 may include one or more following component: processing component 101, memory 102, power supply module 103, multimedia component
104, audio component 105, sensor module 107 and communication component 108.Wherein, said modules and it is not all necessary, electronics
Equipment 100 can increase other assemblies according to itself functional requirement or reduce certain components, and this embodiment is not limited.
The integrated operation of the usual controlling electronic devices 100 of processing component 101, such as with display, call, data are logical
Letter, camera operation and the associated operation of record operation etc..Processing component 101 may include one or more processors 109
It executes instruction, to complete all or part of the steps of aforesaid operations.In addition, processing component 101 may include one or more
Module, convenient for the interaction between processing component 101 and other assemblies.For example, processing component 101 may include multi-media module,
To facilitate the interaction between multimedia component 104 and processing component 101.
Memory 102 is configured as storing various types of data to support the operation in electronic equipment 100.These data
Example include any application or method for being operated on electronic equipment 100 instruction.Memory 102 can be by appointing
The volatibility or non-volatile memory device or their combination of what type are realized, such as SRAM (Static Random
Access Memory, static random access memory), EEPROM (Electrically Erasable Programmable
Read-Only Memory, electrically erasable programmable read-only memory), EPROM (Erasable Programmable Read
Only Memory, Erasable Programmable Read Only Memory EPROM), (Programmable Read-Only Memory may be programmed PROM
Read-only memory), ROM (Read-Only Memory, read-only memory), magnetic memory, flash memory, disk or CD.
One or more modules are also stored in memory 102, which is configured to be handled by the one or more
Device 109 executes, to complete all or part of step in any shown method of the present invention.
Power supply module 103 provides electric power for the various assemblies of electronic equipment 100.Power supply module 103 may include power supply pipe
Reason system, one or more power supplys and other with for electronic equipment 100 generate, manage, and distribute the associated component of electric power.
Multimedia component 104 includes the screen of one output interface of offer between the electronic equipment 100 and user.
In some embodiments, screen may include LCD (Liquid Crystal Display, liquid crystal display) and TP (Touch
Panel, touch panel).If screen includes touch panel, screen may be implemented as touch screen, from the user to receive
Input signal.Touch panel includes one or more touch sensors to sense the gesture on touch, slide, and touch panel.Institute
The boundary of a touch or slide action can not only be sensed by stating touch sensor, but also be detected and the touch or slide phase
The duration and pressure of pass.
Audio component 105 is configured as output and/or input audio signal.For example, audio component 105 includes a Mike
Wind, when electronic equipment 100 is in operation mode, when such as call mode, recording mode, and voice recognition mode, microphone is configured
To receive external audio signal.The received audio signal can be further stored in memory 102 or via communication component
108 send.In some embodiments, audio component 105 further includes a loudspeaker, is used for output audio signal.
Sensor module 107 includes one or more sensors, for providing the state of various aspects for electronic equipment 100
Assessment.For example, sensor module 107 can detecte the state that opens/closes of electronic equipment 100, the relative positioning of component is passed
The coordinate that sensor component 107 can also detect 100 1 components of electronic equipment 100 or electronic equipment changes and electronic equipment
100 temperature change.In some embodiments, which can also include optical sensor or temperature sensor.
Communication component 108 is configured to facilitate the communication of wired or wireless way between electronic equipment 100 and other equipment.
Electronic equipment 100 can access the wireless network based on communication standard, such as WiFi (Wireless-Fidelity, wireless network),
2G or 3G or their combination.In one exemplary embodiment, communication component 108 is received via broadcast channel from outside
The broadcast singal or broadcast related information of broadcasting management systems.In one exemplary embodiment, the communication component 108 also wraps
NFC (Near Field Communication, near-field communication) module is included, to promote short range communication.For example, NFC module can
Based on RFID (Radio Frequency Identification, radio frequency identification) technology, IrDA (Infrared Data
Association, Infrared Data Association) technology, UWB (Ultra-Wideband, ultra wide band) technology, BT (Bluetooth, it is blue
Tooth) technology and other technologies realize.
In the exemplary embodiment, electronic equipment 100 can be by one or more ASIC (Application Specific
Integrated Circuit, application specific integrated circuit), DSP (Digital Signal Processing, at digital signal
Manage device), PLD (Programmable Logic Device, programmable logic device), FPGA (Field-Programmable
Gate Array, field programmable gate array), controller, microcontroller, microprocessor or other electronic components realize, be used for
Execute the above method.
Processor executes the concrete mode of operation in related low-voltage collecting meter reading event in electronic equipment in the embodiment
Detailed description is performed in the embodiment of the processing method of barrier, will no longer elaborate explanation herein.
Optionally, it the present invention also provides a kind of electronic equipment (can be AR glasses, mobile phone, computer etc.), executes any of the above-described
Shown in low-voltage collecting meter reading failure processing method all or part of step.The electronic equipment includes:
At least one processor；And
The memory being connect at least one described processor communication；Wherein,
The memory is stored with the instruction that can be executed by least one described processor, and described instruction is by described at least one
A processor executes, so that at least one described processor is able to carry out the method as described in any of the above-described exemplary embodiments.
Processor executes the concrete mode of operation in the related low-voltage collecting meter reading failure in terminal in the embodiment
Detailed description is performed in the embodiment of processing method, no detailed explanation will be given here.
In the exemplary embodiment, a kind of storage medium is additionally provided, which is computer readable storage medium,
It such as can be the provisional and non-transitorycomputer readable storage medium for including instruction.The storage medium is for example including instruction
Memory 102, above-metioned instruction can executes by the processor 109 of terminal 100 to complete the processing side of above-mentioned low-voltage collecting meter reading failure
Method.
It should be understood that the present invention is not limited to the precise structure already described above and shown in the accompanying drawings, this
Field technical staff can execute without departing from the scope various modifications and change.The scope of the present invention is only wanted by appended right
It asks to limit.
Claims (10)
1. a kind of processing method of low-voltage collecting meter reading failure, which is characterized in that the described method includes:
Obtain fault signature when low-voltage collecting meter reading；
Similar historical fault signature is searched from the accident analysis library constructed in advance according to the fault signature；
The failure cause for generating the fault signature is determined according to the corresponding failure cause of the similar historical fault signature.
2. the method according to claim 1, wherein the construction method in the accident analysis library includes:
Operation/maintenance data when low-voltage collecting meter reading is excavated by big data；
Fault signature when low-voltage collecting meter reading breaks down and corresponding failure cause are extracted from the operation/maintenance data；
The fault signature and corresponding failure cause are subjected to corresponding storage and form the accident analysis library.
3. the method according to claim 1, wherein the method also includes:
When being searched from the accident analysis library constructed in advance less than similar historical fault signature according to the fault signature, carry out
The insufficient prompt of breakdown judge；
The prompt is responded, acquisition low-voltage collecting meter reading generates O&M image when failure；
The O&M image is subjected to deep learning in the accident analysis library, identifies the device name in the O&M image
And abort situation；
The failure cause for generating the fault signature is determined by the fault signature, device name and abort situation.
4. according to the method described in claim 3, it is characterized in that, the construction method in the accident analysis library further include:
The image of involved equipment during collection low-voltage collecting meter reading；
Described image is marked according to the model of each equipment and failure cause；
Deep learning is carried out to by the described image of label, forms the accident analysis library.
5. according to the method described in claim 3, it is characterized in that, it is described by the O&M image in the accident analysis library
Deep learning is carried out, the step of identifying the device name and abort situation in the O&M image includes:
The O&M image is carried out by matching operation in accident analysis library using deep learning algorithm, identifies the O&M image
In device name；
The image that different zones are intercepted from the O&M image, obtains area image；
Matching degree between fault picture in the area image and accident analysis library is calculated using deep learning algorithm；
The abort situation in the O&M image is identified according to the matching degree.
6. method according to claim 1 or 3, which is characterized in that the method also includes:
Corresponding troubleshooting measure is searched in the accident analysis library according to the failure cause；
It is instructed to carry out troubleshooting according to the troubleshooting measure.
7. a kind of processing unit of low-voltage collecting meter reading failure characterized by comprising
Fault signature obtains module, for obtaining fault signature when low-voltage collecting meter reading；
Similar features searching module, for searching similar historical from the accident analysis library constructed in advance according to the fault signature
Fault signature；
Failure cause determining module generates the event for determining according to the corresponding failure cause of the similar historical fault signature
Hinder the failure cause of feature.
8. device according to claim 7, which is characterized in that described device further include:
Cue module, for being searched from the accident analysis library constructed in advance according to the fault signature less than similar historical event
When hindering feature, the insufficient prompt of breakdown judge is carried out；
O&M image capture module, for responding the prompt, acquisition low-voltage collecting meter reading generates O&M image when failure；
Deep learning module identifies the fortune for the O&M image to be carried out deep learning in the accident analysis library
Tie up the device name and abort situation in image；
Failure cause depth determining module, for being determined described in generation by the fault signature, device name and abort situation
The failure cause of fault signature.
9. a kind of electronic equipment, which is characterized in that the electronic equipment glasses include:
At least one processor；And
The memory being connect at least one described processor communication；Wherein,
The memory is stored with the instruction that can be executed by least one described processor, and described instruction is by described at least one
It manages device to execute, so that at least one described processor is able to carry out the method as described in claim 1-6 mono-.
10. a kind of computer readable storage medium, for storing program, which is characterized in that described program makes when executed
Terminal executes the method as described in claim 1-6 mono-.
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