CN106372785A - System fault data processing method based on characteristic index - Google Patents
System fault data processing method based on characteristic index Download PDFInfo
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- CN106372785A CN106372785A CN201610755384.7A CN201610755384A CN106372785A CN 106372785 A CN106372785 A CN 106372785A CN 201610755384 A CN201610755384 A CN 201610755384A CN 106372785 A CN106372785 A CN 106372785A
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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
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
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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
- G06Q10/10—Office automation; Time management
- G06Q10/109—Time management, e.g. calendars, reminders, meetings or time accounting
- G06Q10/1093—Calendar-based scheduling for persons or groups
- G06Q10/1097—Task assignment
Abstract
The invention discloses a system fault data processing method based on a characteristic index. The method comprises the following steps: 1) fault tree analysis, which is responsible for simulation, determination and verification of a target system fault mode, and is arranged on the upper layer of the whole data processing process; 2) constructing the characteristic index, which is used for realizing specific measurement of a fault tree bottom event, and is arranged on the lower layer of the whole data processing process; and 3) data processing, which comprises configuration, adjustment and calibration, identification and improvement. The system fault data processing method has a wide industry application prospect, can be applied to system fault monitoring and management in the IT industry, and can also be applied to the aspects of disease intelligent diagnosis and enterprise quality process control and the like in the medical industry.
Description
Technical field
The present invention relates to a kind of method of system failure data processing, specifically a kind of system failure of feature based index
The method of data processing, belongs to data analysis and process technical field.
Background technology
With country two change depth integration levels raisings further, Chinese manufacturing informationization welcome one brand-new
Developmental stage.Erp, mes, dnc, mdc, pdm, tracker etc. are advanced, and KXG obtains in manufacturing enterprise
Extensively apply, further speeded up manufacturing enterprise and realized transition and upgrade.Also bring stability, the reliability of information system simultaneously
Concern enterprise and whether be capable of the new problem of normal production and operation and be derived from the risk of information system and grow with each passing day.
Characteristic refers to that all can be detected eigenvalue during the processed system operation of measurement.As cpu averagely accounts for
Rate, internal memory average occupancy, current process number, service alert event, network present flow rate, current thread number, data base is had to work as
Front connection number and disk i/o queue length etc..
Characteristic index, also referred to as problem characteristic, are built upon the characteristic combination related to problem on time shafts.
Each characteristic can be regarded as simplest problem characteristic；Each problem characteristic is by the least unit of data processing.
Problem characteristic is the Data Representation of processed system operation situation, has variability, and variability has statistics
Regular.
So-called variability refers to the fluctuation that the operation conditions of processed system under different space-times exists.Even identical
Equipment, identical environment, are also such.This fluctuation is unavoidable.However, the factor of impact fluctuation has a lot, such as cpu
Occupation rate, internal memory occupation rate etc..Any or several factor all may not this fluctuation of directviewing description true feelings
Condition.It is therefore desirable to being combined to these factors and changing.
So-called statistical regularity refers to that the frequency that a random event occurs often is waved near certain definite value, Er Qieshi
Test number of times more, swing fewer.After characteristic combination related for problem, according still further to statistical analysis it finds that difference is asked
Topic feature and its between there is statistical law.
The syntagmatic of problem characteristic is built upon, on the field scientific basic of processed system, meeting processed system
Field universal rule.Well appropriate problem characteristic is the concrete summary of long-term field practical experience；Correct problem is special
Levy the cause that apparent can faster disclose processed system operation fluctuation.
The failure accident of system can lead to the economic loss of enterprise, brand image to glide, and enterprises consumption and client flow
Lose.Therefore, it is necessary to invent a kind of method of the system failure data processing of feature based index.
Content of the invention
For above-mentioned prior art existing problems, the present invention provides a kind of system failure data processing of feature based index
Method, the method be capable of feature based data composition problem characteristic, efficiently intactly complete the fault data of appointing system
Processing procedure.
The present invention is achieved through the following technical solutions above-mentioned purpose: at a kind of system failure data of feature based index
The method of reason, the method comprises the steps:
1) fault tree analysiss, the simulation of responsible goal systems fault mode, determination and checking, positioned at whole data processing
Top section；
2) construction feature index, realizes the concrete measurement of bottom event of fault tree；Underclad portion positioned at whole data processing；
3) data processing, including configuration, adjustment, identification and improvement.
Further, described fault tree analysiss include qualitative analyses and quantitative analyses.
Further, described characteristic index is and the combining of described bottom event of fault tree correlated characteristic data.
Further, described construction feature index includes:
A) setting of characteristic index is carried out according to analysis different target；
B) carry out the screening combination of correlated characteristic data by understanding target；
C) select to combine with the analysis the most direct characteristic of goal systems.
Further, described step 3) in configuration comprise the steps:
A) investigation and the system mode understanding goal systems and parameter, draw out Organization Chart, data flow figure and deployment diagram；
B) collect existing event of failure case, carry out accident statistics, and the accident that anticipation system can occur；
C) it is directed to the accident that can occur and gathers the principle of its generation, configure corresponding fault tree example；
D) it is the reason each fault tree example arranges config failure parameter；
E) it is every kind of possible configuration automatic interventional operations step in each fault tree example；
F) fault tree example is adjusted according to system principle inspection, and it is real to carry out tentative calculation validation fault tree with reference to historical data
Example.
Further, described step 3) in adjustment comprise the steps:
) for the bottom event in fault tree example specific requirement, select characteristic combination, construction feature refers to one by one
Number；
) according to bottom event of fault tree, specify suitable characteristic index or characteristic index set for it；
) collect or transfer the historical data related to fault mode and constantly fault mode example is calculated.
Further, described step 3) in identification be to close according to single failure schema instance or fault mode example cluster
Applicable border, screens the real time data collecting in bounds, and temporally fragment is input to corresponding event in batches incessantly
Calculated in barrier schema instance, and shown by service chart.
Further, described step 3) in identification be will the result of calculation of real time data and historical data result of calculation with
When show.
Further, described step 4) in improvement include:
) process of hand inspection alarm transactions, analyze process data, eliminate system failure hidden danger；
) irregularly carry out the regression analyses of history feature data, find and find new fault mode, or adjustment is original
Every configuration of fault diagnosis example；
) statistical analysiss are carried out to the generation account of the history of fault mode example, participate in the aid decision of system.
Beneficial effects of the present invention: 1) method of this system failure data processing has wide sector application prospect, energy
Enough it is applied to the system failure monitoring management of it industry moreover it is possible to be applied to the disease intelligent diagnostics of medical industry, enterprise-quality mistake
The directions such as process control.
2) method of this system failure data processing has stronger autgmentability.The fault mode of different field can be directed to
Analysis requires, and increases the species to fault tree affair logic relation, such as: logic XOR, logic voting, logic are forbidden.Acceptable
Increase computation rule of combination of characteristic index etc..
3) method of this system failure data processing is workable.The overall process of data processing can patterned way
Carry out dynamic configuration, operation is intuitively convenient, the analysis of the expert with Professional knowledge background, the needs excavating can not only be met,
Also the requirement that the simple data of general operation employee is extracted, changed can be suitable for.
Specific embodiment
Below in conjunction with the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described,
Obviously, described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.Based in the present invention
Embodiment, the every other embodiment that those of ordinary skill in the art are obtained under the premise of not making creative work, all
Belong to the scope of protection of the invention.
A kind of method of the system failure data processing of feature based index, the method comprises the steps:
1) fault tree analysiss, the simulation of responsible goal systems fault mode, determination and checking, positioned at whole data processing
Top section；
2) construction feature index, realizes the concrete measurement of bottom event of fault tree；Underclad portion positioned at whole data processing；
3) data processing, including configuration, adjustment, identification and improvement.
Wherein, fault tree includes all critical eventss related to fault mode, and also remote-effects and guide feature to refer to
The structure of number.Fault tree analysiss (fault tree analysis, abbreviation fta) are also referred to as event tree analysis, are security systems
Most important analysis method in engineering.Event tree analysis from the beginning of a possible accident, from top to bottom, searching top from level to level
The immediate cause of event and remote cause event, until fundamental cause event (also referred to as bottom event), and use logic chart handle
Logical relation between these events is expressed.
Described fault tree analysiss include qualitative analyses and quantitative analyses.Qualitative analyses: find out and lead to all of event generation
Possible fault mode, that is, ask out of order all minimal cut sets (mcs).Quantitative analyses: one is by input system each unit (bottom
Event) failure probability obtain the probability of failure of system；Two is that to obtain the structure importance of each unit (bottom event), probability important
Degree and criticality importance, finally according to criticality importance size sort out optimal fault diagnosis and repairing order, also may be used simultaneously
Improve relatively less reliable cell data as primary.
Described characteristic index is and the combining of described bottom event of fault tree correlated characteristic data.Computation rule bag in combination
Contain codomain and the detailed rules and regulations such as divide conversion, note power, priority, added up.In general, the characteristic of combination calculation can be used to
Enable the continuous measurement of instrument or the basic data of collection, and every kind of characteristic can not only be according to time shafts horizontal spreading
Reviewing moreover it is possible to unique point to specifically tested source entity.Such as: be the data throughout of any platform equipment, be which application
Cpu occupancy of example etc..Analyzed system can also be divided into some subsystems by us, and direct construction is directed to subsystem
Irrespective of size another characteristic index, such as: the data throughout of system front end server zone, the average cpu of certain web service interface
Occupancy etc..In a word, characteristic index is exactly by the collocation to separate sources, characteristic of different nature, then through closing
The combination configuration of reason specification, establishment has played the completely automatic of the calculating from the fault tree analysiss of Domain Theory to real application data
Change process.
Build effective characteristic index, comprising: 1) setting of characteristic index is carried out according to the difference analyzing target.Example
As, mutually same server, on the one hand it is intended to carry out the day-to-day operation monitoring of hardware, on the one hand will be to the application system running thereon
System carries out Performance Evaluation.Here it is two kinds of analysis purposes correspond to therewith it is necessary at least set up two stack features indexes, otherwise just hold
The phenomenon easily cause wrong report, failing to report occurs.2) carry out the screening combination of related validity feature data according to understanding target.Example
As a server, if be only intended to carry out the day-to-day operation monitoring of hardware, then only need to be by normal for impact server operation
Hardware characteristics data (such as: the average occupancy of cpu, memory usage etc.) is chosen just.As for current process number, current thread
Number just belongs to redundant term, if the redundant term participating in excessively will occur failing to report phenomenon.3) under same target, if there is because
Two category feature data of fruit relation, then should not exist under same characteristic features index.In other words, select with to analyze target the most direct
Characteristic be combined.For example, a server, if be only intended to carry out the day-to-day operation monitoring of hardware, then permissible
Average for cpu occupancy, memory usage are combined, is present under a characteristic index, and should not be by disk i/o queue
Length, disk i/o speed are also selected under same characteristic features index, because disk ruuning situation has one with cpu, internal memory ruuning situation
Determine the cause effect relation of degree, if being disposed at together, can occur operation troubles problem positioning forbidden situations such as.
The work of configuration phase is the basis of whole analytical technology, is also the concrete manifestation of mode fault principle.Described bag
Include following steps:
A) investigation and the system mode understanding goal systems and parameter, draw out Organization Chart, data flow figure and deployment diagram；
B) collect existing event of failure case, carry out accident statistics, and the accident that anticipation system can occur；For instance that being
System disconnection fault, grid link failure, system overload fault etc.；
C) it is directed to the accident that can occur and gathers the principle of its generation, configure corresponding fault tree example；
First, after simple for the accident occurring name, determine that it is fault tree top event；
Second, investigate all reason events related to top event and various factors, find out downwards immediate cause step by step
Event, until all of bottom event can be measured, then by its logical relation (logical AND, logic or wait), constructs fault tree
Example.
D) it is the reason each fault tree example arranges config failure parameter, so that guide field observation personnel are met an urgent need
Response is processed；
E) it is every kind of possible configuration automatic interventional operations step in each fault tree example, for example: report to the police, remotely control
Instruction etc.；
F) fault tree example is adjusted according to system principle inspection, and it is real to carry out tentative calculation validation fault tree with reference to historical data
Example, for example: system cut-off fault (top event), can be made up of two bottom events and relation, a, the terminal meeting ups there are
Effect data feedback；B, do not connect ups terminal do not have valid data feed back.
To build a kind of fault mode example with good practicality, not only to accomplish good accuracy, also will
There is good accurateness.Briefly, to show, on appropriate opportunity, the complete overall picture that event of failure occurs, can neither have leakage
Report, nor have wrong report.So, the process of instruction is extremely important.Described step 3) in adjustment comprise the steps:
) for the bottom event in fault tree example specific requirement, select characteristic combination, construction feature refers to one by one
Number；
) according to bottom event of fault tree, specify suitable characteristic index or characteristic index set for it, for example: data base
There is access resource anxiety (bottom event) in server, can be by cpu health index, internal memory health index, database access manifold
It is combined, jointly point to bottom event；
) collect or transfer the historical data related to fault mode and constantly fault mode example is calculated.Observe
Occur with the presence or absence of situation about reporting by mistake or fail to report, if it is present being carried by adjusting the rule of combination of correlated characteristic index again
The accuracy of high fault mode example and accurateness.
If if there is the rule of combination adjusting characteristic index anyway during instruction, all cannot prevent all the time
Wrong report and situation about failing to report occur, then will consider that the domain expert contacting previous stage re-starts the tune of fault mode
Whole.
Fault mode example after adjustment just can put into actual observation identification application.If automaticdata can be used in combination
Acquisition system and remote control and regulation system can be achieved with a set of more powerful big system of system failure data intelligence processing.
Identification can be the applicable border closed according to single failure schema instance or fault mode example cluster, screens border
In the range of the real time data that collects, temporally fragment be input to incessantly in corresponding fault mode example in batches and counted
Calculate, and shown by service chart.Identification can also be by the result of calculation of the result of calculation of real time data and historical data
Show simultaneously.
If finding new wrong report, failing to report problem in cognitive phase, can pass through to contact the staff of earlier stage,
Carry out appropriately configured or adjustment again.
Due to the correct efficient operation of cognitive phase, computer can help us to complete substantial amounts of real-time calculating and control
Work, it is achieved thereby that process to the quick positioning of the system failure, quick identification, quick response.But we also should be following
Several aspects are further improved.
Described improvement includes:
) process of hand inspection alarm transactions, analyze process data, eliminate system failure hidden danger；
) irregularly carry out the regression analyses of history feature data, find and find new fault mode, or adjustment is original
Every configuration of fault diagnosis example；
) statistical analysiss are carried out to the generation account of the history of fault mode example, participate in the aid decision of system.
The organizing and implementing of data processing activity are the important leverages of system failure data processing platform (DPP) continuous service.Particularly
In the face of increasingly complicated integrated system, the management of data processing activity will not be single role or institute of department is competent.
The system failure data processing technique of feature based index is respectively domain expert and technical specialist is supplied to different analysis sides
Method and instrument.
Around the management of fault mode, domain expert can carry out the structure of fault mode according to the method for oneself area research
Build, tentative calculation, configuration, classification, the activity such as optimization.Around the management of characteristic index, technical specialist then can be by characteristic
The understanding of relation, carries out the activities such as the structure of characteristic index, adjustment, identification, improvement.The tissue of the two activity can be unified to assist
Adjust, and can independent work.Individually implement to run or implement characteristic index part, the result of data processing is exactly processed system fortune
The Data Representation of row situation, and individually implement or operation troubles pattern part, achievement is exactly a whole set of valuable system failure pipe
Reason knowledge base.
Embodiment:
The information system operation management current condition of certain hospital of city and problem are: for the stable operation of guarantee information system,
Information centre needs allotment personnel to carry out 3 × 8 hours, and class Three is on duty in turn, leads to human cost to be inversely proportional to efficiency；
All kinds of problems that each information centre personnel are intended to be capable of independent process business department declare phone, and look in time
Test, diagnose, process, lead to person works' pressure big, staff wastage proportional imbalance；
A large amount of problems, such as system operation are slow, program disposes upgrading, system in case of system halt etc., can irregularly repeat to occur, lead to
Work is dull, and operational error risk increases；
With the substantial increase of the increasingly complicated of information system and information data, the problem of information system, fault occur
Risk is also being continuously increased, and depends merely on simply newly-increased manpower and is not enough to deal with the trend in future.
Information centre, by original three-shift system, is changed to double shift, and night shift has product (ias) to be responsible for unmanned, and manpower becomes
This is obvious with the ratio improvement of efficiency；
Each problem is declared first after the preliminary analyses of information centre personnel, has been diverted to product (ias) or people
Work is processed, and operating pressure substantially weakens；
After regular problem occurs first in a large number, as slow in system operation, program disposes upgrading, system in case of system halt etc., meeting
Adjusted, be configured to different problem identification patterns or Fault Diagnosis Strategy by information centre personnel, product (ias) is once detect
Will voluntarily process to matching problem or fault, greatly reduce the workload of manual intervention；
Problem identification pattern with product (ias) and increasingly perfect, the problem of information system, the event of Fault Diagnosis Strategy
Barrier effectively automatically processes rate and is also being continuously increased when occurring, rely on the optimum way to manage of information system management information system progressively
Formed；
Embodiment provided above is the better embodiment of the present invention, is only used for the convenient explanation present invention, not to this
Bright make any pro forma restriction, any those of ordinary skill in the art, if without departing from the carried skill of the present invention
In the range of art feature, made, using disclosed technology contents, the Equivalent embodiments that local is changed or modified, and
Without departing from the technical characteristic content of the present invention, all still fall within the technology of the present invention feature.
Claims (8)
1. a kind of method of the system failure data processing of feature based index is it is characterised in that the method comprises the steps:
1) fault tree analysiss, the simulation of responsible goal systems fault mode, determination and checking, positioned at the upper strata of whole data processing
Part；
2) construction feature index, realizes the concrete measurement of bottom event of fault tree；Underclad portion positioned at whole data processing；
3) data processing, including configuration, adjustment, identification and improvement.
2. the system failure data processing of feature based index according to claim 1 method it is characterised in that: described
Characteristic index is, with described bottom event of fault tree, combining of the correlated characteristic data associating occurs.
3. the method for the system failure data processing of feature based index according to claim 1 is it is characterised in that described
Construction feature index comprises the steps:
A) setting of characteristic index is carried out according to analysis different target；
B) carry out the screening combination of correlated characteristic data by understanding target；
C) select to be combined with the analysis the most direct characteristic of target.
4. the system failure data processing of feature based index according to claim 1 method it is characterised in that: described
Step 3) in configuration process comprise the steps:
A) investigation and the system mode understanding goal systems and parameter, draw out Organization Chart, data flow figure and deployment diagram；
B) collect existing event of failure case, carry out accident statistics, and the accident that anticipation system can occur；
C) it is directed to the accident that can occur and combines the principle of its generation, configure corresponding fault tree example；
D) it is the reason each fault tree example arranges config failure parameter；
E) it is every kind of possible configuration automatic interventional operations step in each fault tree example；
F) fault tree example is adjusted according to system principle inspection, and carry out tentative calculation validation fault tree example with reference to historical data.
5. the system failure data processing of feature based index according to claim 4 method it is characterised in that: described
Step 3) in calibration procedures comprise the steps:
) for the bottom event in fault tree example specific requirement, select characteristic combination, construction feature index one by one；
) according to bottom event of fault tree, specify suitable characteristic index or characteristic index set for it；
) collect or transfer the historical data related to fault mode fault mode example is checked.
6. the system failure data processing of feature based index according to claim 5 method it is characterised in that: described
Step 3) in identification be the applicable border closed according to single failure schema instance or fault mode example cluster, screening border model
The real time data collecting in enclosing, temporally fragment be input to incessantly in corresponding fault mode example in batches and counted
Calculate, and shown by service chart.
7. the system failure data processing of feature based index according to claim 6 method it is characterised in that: described
Step 3) in identification be that the result of calculation of the result of calculation of real time data and historical data is shown simultaneously.
8. the system failure data processing of feature based index according to claim 7 method it is characterised in that: described
Step 4) in development include:
) process of hand inspection alarm transactions, analyze process data, eliminate system failure hidden danger；
) irregularly carry out the regression analyses of history feature data, find and find new fault mode, or adjust original fault
Every configuration of example；
) statistical analysiss are carried out to the generation account of the history of fault mode example, participate in the aid decision of system.
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| CN109104304A (en) * | 2018-07-24 | 2018-12-28 | 国网山东省电力公司电力科学研究院 | A kind of distribution real time fail processing method |
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Application publication date: 20170201 |