CN106341248A - Fault processing method and device based on cloud platform - Google Patents
Fault processing method and device based on cloud platform Download PDFInfo
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- CN106341248A CN106341248A CN201510401576.3A CN201510401576A CN106341248A CN 106341248 A CN106341248 A CN 106341248A CN 201510401576 A CN201510401576 A CN 201510401576A CN 106341248 A CN106341248 A CN 106341248A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0654—Management of faults, events, alarms or notifications using network fault recovery
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0677—Localisation of faults
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
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Abstract
The embodiment of the application provides a fault processing method and device based on a cloud platform. The method comprises the steps that when the fault processing request of a target object is received, the first target data of the terminal of the target object and/or the second target data of the server are acquired; the first target data and/or the second object data match a preset fault model, wherein the fault model is associated with one or more fault solutions; if the matching is successful, a target fault solution is selected from one or more fault resolutions; and the target fault solution is output. According to the embodiment provided by the invention, the detection coverage is improved; a user is prevented from directly describing a problem; the detection efficiency is improved; the fault detection using the fault model is simple, which greatly reduces the frequency of manual participation and reduces the consumption of the user's energy.
Description
Technical field
The application is related to field of computer technology, more particularly to a kind of troubleshooting side based on cloud platform
Method and a kind of fault treating apparatus based on cloud platform.
Background technology
With scientific and technological fast development, based on the various products of cloud platform, such as fictitious host computer, cloud storage etc.,
The extensively field such as the life of entrance people, study, work.
Standard Question Log system is used to support the troubleshooting service of product in current cloud platform.
Specifically, the problem during product is used by user by modes such as word, picture, sound is carried out
Abstract describes, and customer service carries out malfunction elimination according to the description of these abstracts.
But, this kind of being described on visible physical property product is easier to realize, and the product of cloud platform
For user be by one kind invisible presented in.
The feature of the product of cloud platform is in remote service, also need to enter with client using these products
Row connects.The difference of FTP client FTP and environment is larger, describes extremely difficult, customer service indigestion, especially
It is clear for the very difficult description of the weak user of technology foundation, and causing trouble treatment effeciency is relatively low.
And if, clearly describe problem, need there is accumulation to the knowledge in field, technical threshold is higher,
Solving problems by themselves is difficult to for the weak user of technology foundation or customer service, causing trouble processing cost is higher.
Content of the invention
In view of the above problems it is proposed that the embodiment of the present application is to provide one kind to overcome the problems referred to above or extremely
A kind of fault handling method based on cloud platform of partially solving the above problems and accordingly a kind of base
Fault treating apparatus in cloud platform.
In order to solve the above problems, the embodiment of the present application discloses a kind of troubleshooting side based on cloud platform
Method, comprising:
When the troubleshooting receiving destination object is asked, gather the of terminal residing for described destination object
One target data and/or the second target data of residing service end；
Using described first object data and/or described second target data, carry out with default fault model
Coupling, described fault model is associated with one or more fault settling modes；
When the match is successful, choose target faults solution party from one or more of fault settling modes
Formula；
Export described target faults settling mode.
Preferably, described first object data includes terminal environments data and/or destination object test data；
Described gather the of the first object data of terminal residing for described destination object and/or residing service end
The step of two target datas includes:
Inquire about the type information of described destination object；
Search the corresponding harvester of described type information；
Terminal residing for described harvester is sent to described destination object；
Receive what described harvester returned, described terminal is carried out detect the terminal environments data obtaining and
/ or, described destination object is carried out detection obtain destination object test data.
Preferably, described second target data includes destination object status data and/or service end monitoring number
According to；
Described gather the of the first object data of terminal residing for described destination object and/or residing service end
The step of two target datas includes:
Inquire about the example information of described destination object；
Search the corresponding user profile of described example information；
Inquire about described user profile corresponding destination object status data；
And/or,
Extract service end monitoring data service end residing for described destination object being monitored obtain.
Preferably, described fault model include one or more with reference to detection datas and, one or more
Reference portfolios relation；
Described using described first object data and/or described second target data, with default fault model
The step mated includes:
Judge that described first object data and/or described second target data with described with reference to detection data are
No coupling；
Described first object data and/or described second target that judgement is mated with described reference detection data
The syntagmatic of data, if with one or more of reference portfolios relationship match；If so, then judge
Described first object data and/or described second target data are mated with default fault model.
Preferably, described first object data includes terminal detection and the first numerical value, described second target
Data includes service detection item and second value, and described reference detection data is included with reference to detection and reference
Numerical range；
The described first object data of described judgement and/or described second target data and described reference detection number
Include according to the step whether mated:
Search the reference detection mating with described terminal detection and/or described service detection item；
Judge described first numerical value or described second value whether in the range of described referential data；
If so, described first object data and/or described second target data and described reference detection are then judged
Data Matching；
If it is not, then judging described first object data and/or described second target data and described reference detection
Data mismatches.
Preferably, also include:
Fault model is trained using first object data and/or the second target data；
Effectiveness screening is carried out to one or more fault settling modes of described fault model association.
Preferably, the step of described employing first object data and/or the second target data training fault model
Including:
Search the first object data mated with reference to detection and/or the second target data；
Filter off noise data from the first object data and/or the second target data of coupling；
Using the first object data filtering off noise data and/or the adjustment of the second target data with reference to detection
Referential data scope.
Preferably, filter off noise data the described first object data from coupling and/or the second target data
Step include:
Calculate the first object data of coupling and/or the meansigma methodss of the second target data；
Using first object data described in described mean value calculation and/or described second target data first
Variance；
Difference with described meansigma methodss is more than first object data and/or second mesh of described first variance
Mark data filters off.
Preferably, the described first object data using elimination noise data and/or the adjustment of the second target data
Step with reference to the referential data scope of detection includes:
Calculate and filter off the first object data of noise data and/or the second variance of the second target data；
Adjust the referential data scope with reference to detection according to described second variance.
Preferably, described one or more fault settling modes to the association of described fault model are carried out effectively
Property screening step include:
Obtain the number of applications of one or more fault settling modes and/or the use of described fault model association
Family feedback information；
Effective fault settling mode is filtered out using described number of applications and/or field feedback.
The embodiment of the present application also discloses a kind of fault treating apparatus based on cloud platform, comprising:
Data acquisition module, during for asking in the troubleshooting receiving destination object, gathers described mesh
The first object data of terminal and/or the second target data of residing service end residing for mark object；
Fault model matching module, for using described first object data and/or described second number of targets
According to being mated with default fault model, described fault model is associated with one or more faults and solves
Mode；
Target faults settling mode chooses module, for when the match is successful, from one or more of events
Target faults settling mode is chosen in barrier settling mode；
Target faults settling mode output module, for exporting described target faults settling mode.
Preferably, described first object data includes terminal environments data and/or destination object test data；
Described data acquisition module includes:
Type information inquires about submodule, for inquiring about the type information of described destination object；
Submodule searched by harvester, for searching the corresponding harvester of described type information；
Harvester sending submodule, for the end residing for sending described harvester to described destination object
End；
Data receiver submodule, for receiving what described harvester returned, carries out detection to described terminal and obtains
Terminal environments data and/or, described destination object is carried out detection obtain destination object test data.
Preferably, described second target data includes destination object status data and/or service end monitoring number
According to；
Described data acquisition module includes:
Example information inquires about submodule, for inquiring about the example information of described destination object；
User profile searches submodule, for searching the corresponding user profile of described example information；
State-data queries submodule, for inquiring about described user profile corresponding destination object status number
According to；
And/or,
Service end monitoring data extracting sub-module, is carried out to service end residing for described destination object for extracting
The service end monitoring data that monitoring obtains.
Preferably, described fault model include one or more with reference to detection datas and, one or more
Reference portfolios relation；
Described fault model matching module includes:
With reference to detection data matched sub-block, for judging described first object data and/or described second mesh
Whether mark data is mated with reference to detection data with described；
Syntagmatic matched sub-block, for judging and described described first mesh mating with reference to detection data
Mark data and/or the syntagmatic of described second target data, if with one or more of reference portfolios
Relationship match；If so, then call matching judgment submodule；
Matching judgment submodule, for judge described first object data and/or described second target data with
Default fault model coupling.
Preferably, described first object data includes terminal detection and the first numerical value, described second target
Data includes service detection item and second value, and described reference detection data is included with reference to detection and reference
Numerical range；
Described reference detection data matched sub-block includes:
With reference to detection searching unit, search and mate with described terminal detection and/or described service detection item
Reference detection；
Whether referential data range judging unit, judge described first numerical value or described second value described
In the range of referential data；If so, then call the first judging unit, if it is not, then calling the second judging unit；
First judging unit, for judging described first object data and/or described second target data and institute
State with reference to detection data coupling；
Second judging unit, for judging described first object data and/or described second target data and institute
State and mismatch with reference to detection data.
Preferably, also include:
Fault model training module, for training fault using first object data and/or the second target data
Model；
Effectiveness screening module, for one or more fault settling modes that described fault model is associated
Carry out effectiveness screening.
Preferably, described fault model training module includes:
Matched data searches submodule, for search with the reference first object data mated of detection and/
Or second target data；
Noise data filters off submodule, for from the first object data and/or the second target data of coupling
Filter off noise data；
Referential data scope adjust submodule, for using filter off noise data first object data and/
Or second target data adjustment with reference to detection referential data scope.
Preferably, described noise data filters off submodule and includes:
Average calculation unit, for calculating the first object data of coupling and/or the flat of the second target data
Average；
First variance computing unit, for using first object data described in described mean value calculation and/or institute
State the first variance of the second target data；
Data filters off unit, for the difference with described meansigma methodss is more than the first mesh of described first variance
Mark data and/or the second target data filter off.
Preferably, described referential data scope adjustment submodule includes:
Second variance computing unit, for calculating the first object data filtering off noise data and/or the second mesh
The second variance of mark data；
Variance adjustment unit, for adjusting the referential data model with reference to detection according to described second variance
Enclose.
Preferably, described effectiveness screening module includes:
Acquisition submodule, for obtaining one or more fault settling modes that described fault model associates
Number of applications and/or field feedback；
Screening submodule, for filtering out effective event using described number of applications and/or field feedback
Barrier settling mode.
The embodiment of the present application includes advantages below:
The embodiment of the present application adopts the first object data of terminal residing for destination object and/or residing service end
The second target data, mated with default fault model, output fault model association target therefore
Barrier settling mode, improves the coverage rate of detection, avoids user and directly describe problem, improve detection
Efficiency, meanwhile, the failure detection operations of application and trouble model are simple, greatly reduce the frequency of artificial participation
Secondary, reduce the consuming of user's energy, meanwhile, using in the fault model that the work order data of magnanimity is formed
Knowledge point handling failure, greatly reduce technical threshold, facilitate the weak user of technology foundation or customer service only
From solve problem, substantially increase troubleshooting efficiency, greatly reduce the cost of troubleshooting.
The embodiment of the present application by the training to fault model, and, fault settling mode is carried out effectively
Property screening, further improve fault model, the degree of accuracy of fault settling mode, thus further increasing
The efficiency of troubleshooting.
Brief description
Fig. 1 is a kind of flow chart of steps of fault handling method embodiment based on cloud platform of the application；
Fig. 2 is a kind of structured flowchart of fault treating apparatus embodiment based on cloud platform of the application.
Specific embodiment
Understandable for enabling the above-mentioned purpose of the application, feature and advantage to become apparent from, below in conjunction with the accompanying drawings
With specific embodiment, the application is described in further detail.
One of core idea of the embodiment of the present application is to propose digitalized fault processing scheme, by product
Information is described as numerical index, is mated with fault model by digitized information, identifies rapidly
Fault, and then corresponding solution is provided.
With reference to Fig. 1, show a kind of step of fault handling method embodiment based on cloud platform of the application
Rapid flow chart, specifically may include steps of:
Step 101, when the troubleshooting receiving destination object is asked, gathers described destination object institute
Place's first object data of terminal and/or the second target data of residing service end；
Cloud platform (cloud platforms), is a kind of meter of application cloud computing (cloud computing)
Calculation machine cluster, such as distributed system, cloud computing service is provided, such as ecs (elastic compute service,
Cloud Server) virtual machine, rds ((relational database service, relevant database service)
Data base, oss (open storage service, open storage service) storage, etc..
In cloud platform, user the program finished writing can be placed in cloud platform and run, it is possible to use cloud
The service providing in platform, the program finished writing can also be placed in cloud platform and run simultaneously using cloud platform
The service providing.
Huge calculating processing routine is split into numerous less sub- journey through network by cloud platform automatically
Sequence, then transfer to bulky systems that multi-section server formed through searching result, calculating after analysis
Return to user.
, oss is certain cloud platform externally magnanimity of offer, safety, low cost, height taking oss as a example
Reliable cloud storage service.
User can pass through simple rest (representational state transfer, declarative state
Transfer) interface upload and downloading data, it is possible to use web page is managed to data.
Based on oss, user can build various multimedia sharing websites, Dropbox, individual enterprise's data
The service based on large-scale data such as backup.
When certain object (as product or service) that carrying point calculates service breaks down, user is permissible
Work order is filled in by client (as browser), sends troubleshooting request, request cloud platform is right to this
As carrying out troubleshooting, and this object can be referred to as destination object.
If cloud platform receives the troubleshooting request of destination object, the shape of two kinds of data can be gathered
State: the first object data of terminal residing for this destination object, i.e. user's private data, and, this target
Second target data of service end residing for object, i.e. cloud platform private data.
Digitalized fault process can improve existing troubleshooting service system in terms of two and ask
With answer.
Problem description (detection) of destination object (as product or service) is converted to numerical index
(key).
For example:
Whether ecs server state is normal: ecs_server_status；
Whether ecs Server remote connects normal: ecs_server_remote_status；
Ecs pressure condition: ecs_server_load_status.
By the reply translation bit automatic detection of user, the reply of problem is converted into numerical value (value), needs
Illustrate, numerical value can be digital numerical value or logic value.
For example:
Service is normal to be run: ecs_server_status:1；
Server can not be normally long-range: ecs_server_remote_status:0；
Server is very slow: ecs_server_load_status:60.
In a preferred embodiment of the present application, first object data can include terminal environments data and
/ or destination object test data, then in the embodiment of the present application, step 101 can include following sub-step:
Sub-step s11, inquires about the type information of described destination object；
Sub-step s12, searches the corresponding harvester of described type information；
Sub-step s13, described harvester is sent to described destination object residing for terminal；
Sub-step s14, receives what described harvester returned, described terminal is carried out detect the terminal obtaining
Environmental data and/or, described destination object is carried out detection obtain destination object test data.
In the embodiment of the present application, after user submits to work order to send fault detect request, work order can be passed through
System judges the type information (as product type or COS) of destination object, and by this destination object
(as product or service) corresponding harvester is issued user and is downloaded.
Harvester can be by the client-side program of the language developments such as java, for collecting residing for destination object eventually
The environmental data at end, and, destination object is detected.
Client-side program due to java can be cross-platform, it is possible to reduce the use difficulty of user.
In actual applications, harvester, by detecting to preset terminal detection, obtains corresponding
First numerical value, forms first object data.And terminal detection with the type information of destination object can be
Corresponding, certain difference can be had because of the difference of its type information:
First, terminal environments data；
Terminal environments data can be for characterizing terminal (as mobile phone, panel computer etc.) residing for destination object
The information of environment.
The example of terminal detection is as follows:
Operating system version, development environment version, the network information, machine configuration information, loading condition etc.
Deng.
2nd, destination object test data；
Functional test that cloud platform can be carried out according to the service that destination object (as product or service) provides,
Performance test, obtains destination object test data.
The example of the terminal detection of functional test is as follows:
Ecs: control station api (application programming interface, application programming
Interface) call test, long-range connecting test, ecs information, cloud monitors ecs monitoring information；
Oss: upload, download, how concurrently to upload, delete test；
Rds: control station api test, rds database manipulation is tested；
The example of the terminal detection of performance test is as follows:
Method call response time；
Method call responsive state；
The id calling every time.
It should be noted that for the right of privacy and the right to know that ensure user, this first object can be directed to
Whether data genaration mandate information, such as " upload first object data？", if user selects really
Recognize upload, then confirm that user is authorized to the collection of first object data, terminal can continue executing with
The upload flow process of first object data, if user selects refusal to upload, confirms user not to the first mesh
The collection of mark data is authorized, and terminal terminates the upload flow process of execution first object data.
In another preferred embodiment of the present application, described first object data includes terminal environments data
And/or destination object test data.Furthermore, can be by examining to preset service detection item
Survey, obtain corresponding second value, form the second target data.
Then in the embodiment of the present application, step 101 can include following sub-step:
Sub-step s21, inquires about the example information of described destination object；
Sub-step s22, searches the corresponding user profile of described example information；
Sub-step s23, inquires about described user profile corresponding destination object status data；
In implementing, in work order, user understands the reality of typing destination object (as product or service)
Example information, such as example id, user profile can be inquired by example id, such as user id, exabyte
Claim etc..
Backstage corresponding destination object status data can be inquired about by user profile, such as punishment, finance,
The status datas such as safety.
With financial situation data instance, if the account balance ratio of user is relatively low, destination object may be caused
(as product or service) locking.
, possibility is because putting on record, (green net is used for checking in user website green net taking safe state data as a example
Invalid information) etc. during reason leads to website to be punished, do not open in the website (destination object) of user.
And/or,
Sub-step s24, extracts service end prison service end residing for described destination object being monitored obtain
Control data.
In implementing, basis can be carried out to service end residing for destination object (as product or service)
The monitoring of the O＆M layer such as the machine room of O＆M layer, network, obtains service end monitoring data.
For example, computer room temperature, rack power supplies state, disk space, cpu utilization rate, memory usage
Etc..
Backstage physical equipment is problematic to lead to destination object (as product or service) to produce fault, for example,
If cpu utilization rate, memory usage are too high, destination object (as product or service) may be led to
Access slow.
It should be noted that user's private data and cloud platform private data can be passed through to order by cloud platform
Relation and O＆M Back ground Information relation merge series winding, and (user that will belong to same user is privately owned
Data and cloud platform private data are combined into data acquisition system), to carry out the judgement of fault.
For example, user → user profile (contact method, work order id) → terminal environments data → target
Object test data → destination object status data → service end monitoring data, wherein, " → " represent string
Connection.
Step 102, using described first object data and/or described second target data, with default event
Barrier model is mated；
Fault model can be that fault is simplified, and with the suitable form of expression or rule fault
Principal character is described.
When obtaining computer discernible first object data, after the second target data, then can enter
Row fault model coupling and the work choosing target faults settling mode, realize the cloud of digitadiagnosis system
The troubleshooting of platform product.
In a preferred embodiment of the present application, described fault model can include one or more references
Detection data and, one or more reference portfolios relation, then in the embodiment of the present application, step 102
Can include following sub-step:
Sub-step s31, judges described first object data and/or described second target data and described reference
Whether detection data mates；
Sub-step s32, judges described first object data and/or the institute mated with described reference detection data
State the syntagmatic of the second target data, if with one or more of reference portfolios relationship match；If
It is then to execute sub-step s33,
Sub-step s33, judges described first object data and/or described second target data and default event
Barrier Model Matching.
In the embodiment of the present application, can be for describing the number of certain attribute of certain fault with reference to detection data
According to, this reference detection data by reference to syntagmatic (as with or wait) characterization failure.
For example, as follows in the reference detection data of fault model:
Case1=ecs_server_status 1；Case1 characterizes the normal operation of service；
Case2=ecs_server_remote_status 0；Case2 characterizes and remotely cannot log in；
Case3=ecs_server_load_status > 10；It is big that case3 characterizes server stress；
If meeting reference portfolios relation case1＆case2, case1＆case2＆case3, case1＆
Case2 | | case3, then this fault model can characterize remote service fault.
If first object data, the syntagmatic of the second target data and the ginseng mated with reference to detection data
Examine syntagmatic coupling, then can confirm that the fault detecting that this fault model characterizes.
It should be noted that some faults are complex, its performance is closer to, for example, network congestion,
The big performance of database loads can be slow for accessing database access, therefore, when mating fault model,
Multiple fault models may be matched.
In a kind of preferred exemplary of the embodiment of the present application, described first object data can include terminal inspection
Survey item and the first numerical value, described second target data can include service detection item and second value, described
Include with reference to detection and referential data scope, then in this example, sub-step s31 with reference to detection data
Can include following sub-step:
Sub-step s311, searches the reference mated with described terminal detection and/or described service detection item
Detection；
Whether sub-step s312, judge described first numerical value and/or described second value in described reference number
In the range of value；If so, then execute sub-step s313, if it is not, then executing sub-step s314；
Sub-step s313, judges described first object data and/or described second target data and described ginseng
Examine detection data coupling；
Sub-step s314, judges described first object data and/or described second target data and described ginseng
Examine detection data to mismatch.
In failure definition model, the reference detection (key) that fault model needs can be selected, and its
Referential data scope (limit).
If first numerical value (value) of the corresponding terminal detection (key) of reference detection (key),
The second value (value) of service detection item (key) in referential data scope (limit), then may be used
To think that first object data, the second target data mate with reference to detection data, otherwise it is assumed that mismatch.
For example, reference detection (key) is ping, and referential data scope (limit) is less than 10,
I.e. ping < 10.If service detection item (key) is ping, its second value (value) is 5,
Then it is assumed that the second target data is mated with reference to detection data in referential data scope (limit).
Step 103, when the match is successful, chooses target from one or more of fault settling modes
Fault settling mode；
In implementing, described fault model can be associated with one or more fault settling modes, should
Fault settling mode describes the scheme of the fault how solving this fault model sign.
For example, if certain fault model meets following reference portfolios relation:
Case1=ecs_server_status 1＆＆case2=ecs_server_remote_status 0
Then this fault model characterizes remote service fault, and its fault settling mode can be remote for checking ecs
Journey services.
Again for example, certain fault model meets following reference portfolios relation:
Ossdel:function_runtime>5＆＆ping<10＆＆osslog=
networktimeout,rpc retry&&net_tcp_error>0
Then this fault model characterizes cloud platform network failure, and its fault settling mode can be examined for feedback net work
The company of looking into exchanges, that is, after choosing, the data of end switch monitoring judges switch whether fault, this number evidence
Net work can be seen simultaneously, if it is determined that being exchange fault, then the fault detecting and work order can be turned net
Work confirms.
In actual applications, by those skilled in the art, suitable solution party can be chosen according to practical situation
Formula is as target faults settling mode.
Certainly, other selection rules can also be adopted in the embodiment of the present application, such as randomly choose, choose mesh
Mark fault settling mode, the embodiment of the present application is not any limitation as to this.
Step 104, exports described target faults settling mode.
Cloud platform sends the target faults settling mode of selection to client, feeds back to user, Yong Huke
To process to fault according to this target faults settling mode.
Fault settling mode is often chosen as target faults settling mode once, or, often export once,
Number of applications once all can be recorded.
If current troubleshooting finishes, user can be carried out to this fault treating procedure by client
Scoring, such as 1-100 divides, and fraction is higher, represents that the quality of troubleshooting is better, fuller to troubleshooting
Meaning, generates field feedback, feeds back to cloud platform, to generate troubleshooting report further.
The embodiment of the present application adopts the first object data of terminal residing for destination object and/or residing service end
The second target data, mated with default fault model, output fault model association target therefore
Barrier settling mode, improves the coverage rate of detection, avoids user and directly describe problem, improve detection
Efficiency, meanwhile, the failure detection operations of application and trouble model are simple, greatly reduce the frequency of artificial participation
Secondary, reduce the consuming of user's energy, meanwhile, using in the fault model that the work order data of magnanimity is formed
Knowledge point handling failure, greatly reduce technical threshold, facilitate the weak user of technology foundation or customer service only
From solve problem, substantially increase troubleshooting efficiency, greatly reduce the cost of troubleshooting.
In a preferred embodiment of the present application, the method can also comprise the steps:
Step 105, trains fault model using first object data and/or the second target data；
In implementing, can be by the first object data in troubleshooting audit report and/or the second mesh
Mark data setting is the sample vector of fault model, and fault model is trained, to improve event further
The degree of accuracy of barrier model.
It should be noted that this first object data, the second target data can be the first of current collection
The first object data of target data, the second target data or history, the second target data,
I.e. after step 104, the current first object data gathering, the second target data can be applied again
Train fault model it is also possible to before step 101, using the first object data of history, the second mesh
Mark data training fault model.
In a preferred embodiment of the present application, step 105 can include following sub-step:
Sub-step s41, searches the first object data mated with reference to detection and/or the second number of targets
According to；
Sub-step s42, filters off noise number from the first object data and/or the second target data of coupling
According to；
Noise data can refer to the random error of measured first object data or the second target data,
Filtering off noise data, improving first object data, the reasonability of the second target data, thus improving training
The accuracy of fault model.
In a kind of preferred exemplary of the embodiment of the present application, sub-step s42 can include following sub-step:
Sub-step s421, calculates the first object data of coupling and/or the meansigma methodss of the second target data；
Sub-step s422, using first object data described in described mean value calculation and/or described second mesh
The first variance of mark data；
First variance, can refer to the expected value of the difference square of actual value and expected value, i.e. each data (the
One target data and/or the second target data) with the difference of meansigma methodss square average.
Sub-step s423, the difference with described meansigma methodss is more than the first object number of described first variance
According to and/or the second target data filter off.
If being more than first variance with the difference of meansigma methodss, can represent this data (first object data and
/ or the second target data) be not inconsistent with expectation, can filter off.
Sub-step s43, using the first object data filtering off noise data and/or the adjustment of the second target data
Referential data scope with reference to detection.
In implementing, the first object data filtering off noise data and/or the second number of targets can be calculated
According to second variance, adjust the referential data scope with reference to detection according to second variance, such as in reference number
The higher limit of value scope adds this second variance, deducts this second party in the lower limit of referential data scope
Difference.
One or more fault settling modes of described fault model association are carried out effectiveness by step 106
Screening.
In implementing, can be ranked up according to Usefulness Pair fault settling mode, effectiveness is minimum
N (n is positive integer, such as 20) fault settling mode can put into garbage warehouse, if a timing
Between (within half a year) no longer choose these fault settling modes, these fault settling modes can be eliminated,
No longer carry out the inspection of fault settling mode.
In a preferred embodiment of the present application, step 106 can include following sub-step:
Sub-step s51, obtains the application of one or more fault settling modes of described fault model association
Number of times and/or field feedback；
Sub-step s52, filters out effective fault solution using described number of applications and/or field feedback
Certainly mode.
In the embodiment of the present application, linear regression can be carried out using number of applications, field feedback,
Scored according to the effectiveness that it occurs simultaneously to fault settling mode.
In general, choosing the fault solution that number of applications is more, user has higher rating (as higher in scoring)
Certainly mode, the fraction of effectiveness is also higher.
The embodiment of the present application by the training to fault model, and, fault settling mode is carried out effectively
Property screening, further improve fault model, the degree of accuracy of fault settling mode, thus further increasing
The efficiency of troubleshooting.
It should be noted that for embodiment of the method, in order to be briefly described, therefore it is all expressed as one and be
The combination of actions of row, but those skilled in the art should know, and the embodiment of the present application is not subject to described
Sequence of movement restriction because according to the embodiment of the present application, some steps can using other orders or
Person is carried out simultaneously.Secondly, those skilled in the art also should know, embodiment described in this description
Belong to preferred embodiment, necessary to involved action not necessarily the embodiment of the present application.
With reference to Fig. 2, show a kind of knot of fault treating apparatus embodiment based on cloud platform of the application
Structure block diagram, specifically can include as lower module:
Data acquisition module 201, during for asking in the troubleshooting receiving destination object, gathers institute
State the first object data of terminal residing for destination object and/or the second target data of residing service end；
Fault model matching module 202, for using described first object data and/or described second target
Data, is mated with default fault model, and described fault model is associated with one or more fault solutions
Certainly mode；
Target faults settling mode chooses module 203, for when the match is successful, from one or many
Target faults settling mode is chosen in individual fault settling mode；
Target faults settling mode output module 204, for exporting described target faults settling mode.
In a preferred embodiment of the present application, described first object data can include terminal environments number
According to and/or destination object test data；
Described data acquisition module 201 can include following submodule:
Type information inquires about submodule, for inquiring about the type information of described destination object；
Submodule searched by harvester, for searching the corresponding harvester of described type information；
Harvester sending submodule, for the end residing for sending described harvester to described destination object
End；
Data receiver submodule, for receiving what described harvester returned, carries out detection to described terminal and obtains
Terminal environments data and/or, described destination object is carried out detection obtain destination object test data.
In another preferred embodiment of the present application, described second target data can include destination object
Status data and/or service end monitoring data；
Described data acquisition module 201 can include following submodule:
Example information inquires about submodule, for inquiring about the example information of described destination object；
User profile searches submodule, for searching the corresponding user profile of described example information；
State-data queries submodule, for inquiring about described user profile corresponding destination object status number
According to；
And/or,
Service end monitoring data extracting sub-module, is carried out to service end residing for described destination object for extracting
The service end monitoring data that monitoring obtains.
In another preferred embodiment of the present application, described fault model can include one or more ginsengs
Examine detection data and, one or more reference portfolios relation；
Described fault model matching module 202 can include following submodule:
With reference to detection data matched sub-block, for judging described first object data and/or described second mesh
Whether mark data is mated with reference to detection data with described；
Syntagmatic matched sub-block, for judging and described described first mesh mating with reference to detection data
Mark data and/or the syntagmatic of described second target data, if with one or more of reference portfolios
Relationship match；If so, then call matching judgment submodule；
Matching judgment submodule, for judge described first object data and/or described second target data with
Default fault model coupling.
In a preferred embodiment of the present application, described first object data can include terminal detection
With the first numerical value, described second target data can include service detection item and second value, described reference
Detection data can be included with reference to detection and referential data scope；
Described reference detection data matched sub-block can be included as lower unit:
With reference to detection searching unit, search and mate with described terminal detection and/or described service detection item
Reference detection；
Whether referential data range judging unit, judge described first numerical value or described second value described
In the range of referential data；If so, then call the first judging unit, if it is not, then calling the second judging unit；
First judging unit, for judging described first object data and/or described second target data and institute
State with reference to detection data coupling；
Second judging unit, for judging described first object data and/or described second target data and institute
State and mismatch with reference to detection data.
In a preferred embodiment of the present application, this device can also be included as lower module:
Fault model training module, for training fault using first object data and/or the second target data
Model；
Effectiveness screening module, for one or more fault settling modes that described fault model is associated
Carry out effectiveness screening.
In a preferred embodiment of the present application, described fault model training module can include following son
Module:
Matched data searches submodule, for search with the reference first object data mated of detection and/
Or second target data；
Noise data filters off submodule, for from the first object data and/or the second target data of coupling
Filter off noise data；
Referential data scope adjust submodule, for using filter off noise data first object data and/
Or second target data adjustment with reference to detection referential data scope.
In a kind of preferred exemplary of the embodiment of the present application, described noise data filters off submodule and can include
As lower unit:
Average calculation unit, for calculating the first object data of coupling and/or the flat of the second target data
Average；
First variance computing unit, for using first object data described in described mean value calculation and/or institute
State the first variance of the second target data；
Data filters off unit, for the difference with described meansigma methodss is more than the first mesh of described first variance
Mark data and/or the second target data filter off.
In a kind of preferred exemplary of the embodiment of the present application, described referential data scope adjustment submodule is permissible
Including such as lower unit:
Second variance computing unit, for calculating the first object data filtering off noise data and/or the second mesh
The second variance of mark data；
Variance adjustment unit, for adjusting the referential data model with reference to detection according to described second variance
Enclose.
In a preferred embodiment of the present application, described effectiveness screening module can include following submodule
Block:
Acquisition submodule, for obtaining one or more fault settling modes that described fault model associates
Number of applications and/or field feedback；
Screening submodule, for filtering out effective event using described number of applications and/or field feedback
Barrier settling mode.
For device embodiment, due to itself and embodiment of the method basic simlarity, so the comparison of description
Simply, in place of correlation, the part referring to embodiment of the method illustrates.
Each embodiment in this specification is all described by the way of going forward one by one, and each embodiment stresses
Be all difference with other embodiment, between each embodiment identical similar partly mutually referring to
?.
Those skilled in the art are it should be appreciated that the embodiment of the embodiment of the present application can be provided as method, dress
Put or computer program.Therefore, the embodiment of the present application can be using complete hardware embodiment, completely
Software implementation or the form of the embodiment with reference to software and hardware aspect.And, the embodiment of the present application
Storage can be can use to be situated between using in one or more computers wherein including computer usable program code
The upper computer journey implemented of matter (including but not limited to disk memory, cd-rom, optical memory etc.)
The form of sequence product.
In a typical configuration, described computer equipment includes one or more processors
(cpu), input/output interface, network interface and internal memory.Internal memory potentially includes computer-readable medium
In volatile memory, the shape such as random access memory (ram) and/or Nonvolatile memory
Formula, such as read only memory (rom) or flash memory (flash ram).Internal memory is computer-readable medium
Example.Computer-readable medium includes permanent and non-permanent, removable and non-removable media
Information Store can be realized by any method or technique.Information can be computer-readable instruction,
Data structure, the module of program or other data.The example of the storage medium of computer includes, but
It is not limited to phase transition internal memory (pram), static RAM (sram), dynamic random are deposited
Access to memory (dram), other kinds of random access memory (ram), read only memory
(rom), Electrically Erasable Read Only Memory (eeprom), fast flash memory bank or other in
Deposit technology, read-only optical disc read only memory (cd-rom), digital versatile disc (dvd) or other
Optical storage, magnetic cassette tape, tape magnetic rigid disk storage other magnetic storage apparatus or any its
His non-transmission medium, can be used for storing the information that can be accessed by a computing device.According to herein
Define, computer-readable medium does not include the computer readable media (transitory media) of non-standing,
Data signal and carrier wave as modulation.
The embodiment of the present application is with reference to according to the method for the embodiment of the present application, terminal unit (system) and meter
The flow chart of calculation machine program product and/or block diagram are describing.It should be understood that can be by computer program instructions
Each flow process in flowchart and/or block diagram and/or square frame and flow chart and/or square frame
The flow process of in figure and/or the combination of square frame.Can provide these computer program instructions to general purpose computer,
The processor of special-purpose computer, Embedded Processor or other programmable data processing terminal equipments is to produce
One machine is so that pass through the computing device of computer or other programmable data processing terminal equipments
Instruction produce for realizing in one flow process of flow chart or multiple flow process and/or one square frame of block diagram or
The device of the function of specifying in multiple square frames.
These computer program instructions may be alternatively stored in and computer or other programmable datas can be guided to process
So that being stored in this computer-readable in the computer-readable memory that terminal unit works in a specific way
Instruction in memorizer produces and includes the manufacture of command device, and the realization of this command device is in flow chart one
The function of specifying in flow process or multiple flow process and/or one square frame of block diagram or multiple square frame.
These computer program instructions also can be loaded into computer or other programmable data processing terminals set
For upper so that execution series of operation steps is in terms of producing on computer or other programmable terminal equipments
The process that calculation machine is realized, thus the instruction of execution provides use on computer or other programmable terminal equipments
In realization in one flow process of flow chart or multiple flow process and/or one square frame of block diagram or multiple square frame
The step of the function of specifying.
Although having been described for the preferred embodiment of the embodiment of the present application, those skilled in the art are once
Know basic creative concept, then these embodiments can be made with other change and modification.So,
The institute that claims are intended to be construed to including preferred embodiment and fall into the embodiment of the present application scope
Have altered and change.
Finally in addition it is also necessary to illustrate, herein, such as first and second or the like relational terms
It is used merely to make a distinction an entity or operation with another entity or operation, and not necessarily require
Or imply between these entities or operation, there is any this actual relation or order.And, art
Language " inclusion ", "comprising" or its any other variant are intended to comprising of nonexcludability, so that
Not only include those key elements including a series of process of key elements, method, article or terminal unit, and
Also include other key elements being not expressly set out, or also include for this process, method, article or
The intrinsic key element of person's terminal unit.In the absence of more restrictions, " include one by sentence
Individual ... " key element that limits is it is not excluded that at process, method, article or the end including described key element
Also there is other identical element in end equipment.
Above cloud is based on to a kind of fault handling method based on cloud platform provided herein and one kind
The fault treating apparatus of platform, are described in detail, and specific case used herein is to the application's
Principle and embodiment are set forth, and the explanation of above example is only intended to help understand the application's
Method and its core concept；Simultaneously for one of ordinary skill in the art, according to the thought of the application,
All will change in specific embodiments and applications, in sum, this specification content is not
It is interpreted as the restriction to the application.
Claims (20)
1. a kind of fault handling method based on cloud platform is it is characterised in that include:
When the troubleshooting receiving destination object is asked, gather the of terminal residing for described destination object
One target data and/or the second target data of residing service end；
Using described first object data and/or described second target data, carry out with default fault model
Coupling, described fault model is associated with one or more fault settling modes；
When the match is successful, choose target faults solution party from one or more of fault settling modes
Formula；
Export described target faults settling mode.
2. method according to claim 1 is it is characterised in that described first object data includes
Terminal environments data and/or destination object test data；
Described gather the of the first object data of terminal residing for described destination object and/or residing service end
The step of two target datas includes:
Inquire about the type information of described destination object；
Search the corresponding harvester of described type information；
Terminal residing for described harvester is sent to described destination object；
Receive what described harvester returned, described terminal is carried out detect the terminal environments data obtaining and
/ or, described destination object is carried out detection obtain destination object test data.
3. method according to claim 1 is it is characterised in that described second target data includes
Destination object status data and/or service end monitoring data；
Described gather the of the first object data of terminal residing for described destination object and/or residing service end
The step of two target datas includes:
Inquire about the example information of described destination object；
Search the corresponding user profile of described example information；
Inquire about described user profile corresponding destination object status data；
And/or,
Extract service end monitoring data service end residing for described destination object being monitored obtain.
4. the method according to claim 1 or 2 or 3 is it is characterised in that described fault model
Including one or more with reference to detection datas and, one or more reference portfolios relation；
Described using described first object data and/or described second target data, with default fault model
The step mated includes:
Judge that described first object data and/or described second target data with described with reference to detection data are
No coupling；
Described first object data and/or described second target that judgement is mated with described reference detection data
The syntagmatic of data, if with one or more of reference portfolios relationship match；If so, then judge
Described first object data and/or described second target data are mated with default fault model.
5. method according to claim 4 is it is characterised in that described first object data includes
Terminal detection and the first numerical value, described second target data includes service detection item and second value, institute
State and include with reference to detection and referential data scope with reference to detection data；
The described first object data of described judgement and/or described second target data and described reference detection number
Include according to the step whether mated:
Search the reference detection mating with described terminal detection and/or described service detection item；
Judge described first numerical value or described second value whether in the range of described referential data；
If so, described first object data and/or described second target data and described reference detection are then judged
Data Matching；
If it is not, then judging described first object data and/or described second target data and described reference detection
Data mismatches.
6. the method according to claim 1 or 2 or 3 or 4 or 5 is it is characterised in that also wrap
Include:
Fault model is trained using first object data and/or the second target data；
Effectiveness screening is carried out to one or more fault settling modes of described fault model association.
7. method according to claim 6 is it is characterised in that described employing first object data
And/or second target data train fault model step include:
Search the first object data mated with reference to detection and/or the second target data；
Filter off noise data from the first object data and/or the second target data of coupling；
Using the first object data filtering off noise data and/or the adjustment of the second target data with reference to detection
Referential data scope.
8. method according to claim 7 it is characterised in that described from coupling first object
The step filtering off noise data in data and/or the second target data includes:
Calculate the first object data of coupling and/or the meansigma methodss of the second target data；
Using first object data described in described mean value calculation and/or described second target data first
Variance；
Difference with described meansigma methodss is more than first object data and/or second mesh of described first variance
Mark data filters off.
9. method according to claim 7 is it is characterised in that described employing filters off noise data
First object data and/or the second target data adjustment with reference to detection referential data scope step
Including:
Calculate and filter off the first object data of noise data and/or the second variance of the second target data；
Adjust the referential data scope with reference to detection according to described second variance.
10. method according to claim 6 is it is characterised in that described close to described fault model
The step that one or more fault settling modes of connection carry out effectiveness screening includes:
Obtain the number of applications of one or more fault settling modes and/or the use of described fault model association
Family feedback information；
Effective fault settling mode is filtered out using described number of applications and/or field feedback.
A kind of 11. fault treating apparatus based on cloud platform are it is characterised in that include:
Data acquisition module, during for asking in the troubleshooting receiving destination object, gathers described mesh
The first object data of terminal and/or the second target data of residing service end residing for mark object；
Fault model matching module, for using described first object data and/or described second number of targets
According to being mated with default fault model, described fault model is associated with one or more faults and solves
Mode；
Target faults settling mode chooses module, for when the match is successful, from one or more of events
Target faults settling mode is chosen in barrier settling mode；
Target faults settling mode output module, for exporting described target faults settling mode.
12. devices according to claim 11 are it is characterised in that described first object packet
Include terminal environments data and/or destination object test data；
Described data acquisition module includes:
Type information inquires about submodule, for inquiring about the type information of described destination object；
Submodule searched by harvester, for searching the corresponding harvester of described type information；
Harvester sending submodule, for the end residing for sending described harvester to described destination object
End；
Data receiver submodule, for receiving what described harvester returned, carries out detection to described terminal and obtains
Terminal environments data and/or, described destination object is carried out detection obtain destination object test data.
13. devices according to claim 11 are it is characterised in that described second target data bag
Include destination object status data and/or service end monitoring data；
Described data acquisition module includes:
Example information inquires about submodule, for inquiring about the example information of described destination object；
User profile searches submodule, for searching the corresponding user profile of described example information；
State-data queries submodule, for inquiring about described user profile corresponding destination object status number
According to；
And/or,
Service end monitoring data extracting sub-module, is carried out to service end residing for described destination object for extracting
The service end monitoring data that monitoring obtains.
14. devices according to claim 11 or 12 or 13 are it is characterised in that described fault
Model include one or more with reference to detection datas and, one or more reference portfolios relation；
Described fault model matching module includes:
With reference to detection data matched sub-block, for judging described first object data and/or described second mesh
Whether mark data is mated with reference to detection data with described；
Syntagmatic matched sub-block, for judging and described described first mesh mating with reference to detection data
Mark data and/or the syntagmatic of described second target data, if with one or more of reference portfolios
Relationship match；If so, then call matching judgment submodule；
Matching judgment submodule, for judge described first object data and/or described second target data with
Default fault model coupling.
15. methods according to claim 14 are it is characterised in that described first object packet
Include terminal detection and the first numerical value, described second target data includes service detection item and second value,
Described reference detection data is included with reference to detection and referential data scope；
Described reference detection data matched sub-block includes:
With reference to detection searching unit, search and mate with described terminal detection and/or described service detection item
Reference detection；
Whether referential data range judging unit, judge described first numerical value or described second value described
In the range of referential data；If so, then call the first judging unit, if it is not, then calling the second judging unit；
First judging unit, for judging described first object data and/or described second target data and institute
State with reference to detection data coupling；
Second judging unit, for judging described first object data and/or described second target data and institute
State and mismatch with reference to detection data.
16. devices according to claim 11 or 12 or 13 or 14 or 15 it is characterised in that
Also include:
Fault model training module, for training fault using first object data and/or the second target data
Model；
Effectiveness screening module, for one or more fault settling modes that described fault model is associated
Carry out effectiveness screening.
17. devices according to claim 16 are it is characterised in that described fault model trains mould
Block includes:
Matched data searches submodule, for search with the reference first object data mated of detection and/
Or second target data；
Noise data filters off submodule, for from the first object data and/or the second target data of coupling
Filter off noise data；
Referential data scope adjust submodule, for using filter off noise data first object data and/
Or second target data adjustment with reference to detection referential data scope.
18. devices according to claim 17 are it is characterised in that described noise data filters off son
Module includes:
Average calculation unit, for calculating the first object data of coupling and/or the flat of the second target data
Average；
First variance computing unit, for using first object data described in described mean value calculation and/or institute
State the first variance of the second target data；
Data filters off unit, for the difference with described meansigma methodss is more than the first mesh of described first variance
Mark data and/or the second target data filter off.
19. devices according to claim 17 are it is characterised in that described referential data scope is adjusted
Whole submodule includes:
Second variance computing unit, for calculating the first object data filtering off noise data and/or the second mesh
The second variance of mark data；
Variance adjustment unit, for adjusting the referential data model with reference to detection according to described second variance
Enclose.
20. devices according to claim 16 are it is characterised in that described effectiveness screening module
Including:
Acquisition submodule, for obtaining one or more fault settling modes that described fault model associates
Number of applications and/or field feedback；
Screening submodule, for filtering out effective event using described number of applications and/or field feedback
Barrier settling mode.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201510401576.3A CN106341248B (en) | 2015-07-09 | 2015-07-09 | Fault processing method and device based on cloud platform |
| PCT/CN2016/087463 WO2017005117A1 (en) | 2015-07-09 | 2016-06-28 | Cloud platform-based fault handling method and device |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201510401576.3A CN106341248B (en) | 2015-07-09 | 2015-07-09 | Fault processing method and device based on cloud platform |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108763039A (en) * | 2018-04-02 | 2018-11-06 | 阿里巴巴集团控股有限公司 | A kind of traffic failure analogy method, device and equipment |
| CN108965049A (en) * | 2018-06-28 | 2018-12-07 | 深信服科技股份有限公司 | Method, equipment, system and the storage medium of cluster exception solution are provided |
| CN109284200A (en) * | 2018-09-04 | 2019-01-29 | 深圳市宝德计算机***有限公司 | Server exception processing method, equipment and processor |
| CN109976318A (en) * | 2019-04-28 | 2019-07-05 | 郑州万特电气股份有限公司 | Electrical energy measurement fault diagnosis Internet-based checks expert system |
| WO2019232964A1 (en) * | 2018-06-07 | 2019-12-12 | 平安科技（深圳）有限公司 | Risk management data processing method and apparatus, computer device, and storage medium |
| CN110704225A (en) * | 2019-09-18 | 2020-01-17 | 平安科技（深圳）有限公司 | Monitoring method, monitoring device, electronic equipment and computer readable storage medium |
| CN111859047A (en) * | 2019-04-23 | 2020-10-30 | 华为技术有限公司 | Fault solving method and device |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108769047A (en) * | 2018-06-06 | 2018-11-06 | 厦门华厦学院 | A kind of big data risk monitoring system |
| CN111431733B (en) * | 2020-02-20 | 2021-06-22 | 拉扎斯网络科技（上海）有限公司 | Service alarm coverage information evaluation method and device |
| CN112383435B (en) * | 2020-11-17 | 2022-03-29 | 珠海大横琴科技发展有限公司 | Fault processing method and device |
| CN113411204B (en) * | 2021-05-17 | 2023-05-02 | 吴志伟 | Method and device for detecting facility fault of telecommunication access network and computer storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103062862A (en) * | 2012-12-05 | 2013-04-24 | 四川长虹电器股份有限公司 | Remote fault processing method for intelligent air conditioner |
| CN103514079A (en) * | 2012-06-15 | 2014-01-15 | 波音公司 | Failure analysis validation and visualization |
| US20140189702A1 (en) * | 2012-12-28 | 2014-07-03 | General Electric Company | System and method for automatic model identification and creation with high scalability |
| CN103957116A (en) * | 2014-03-31 | 2014-07-30 | 昆明理工大学 | Decision-making method and system of cloud failure data |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102055604B (en) * | 2009-11-05 | 2012-12-05 | ***通信集团山东有限公司 | Fault location method and system thereof |
| WO2015080705A1 (en) * | 2013-11-26 | 2015-06-04 | Hewlett-Packard Development Company, L.P. | Fault management service in a cloud |
-
2015
- 2015-07-09 CN CN201510401576.3A patent/CN106341248B/en active Active
-
2016
- 2016-06-28 WO PCT/CN2016/087463 patent/WO2017005117A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103514079A (en) * | 2012-06-15 | 2014-01-15 | 波音公司 | Failure analysis validation and visualization |
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