CN106533754A - Fault diagnosis method and expert system for college teaching servers - Google Patents
Fault diagnosis method and expert system for college teaching servers Download PDFInfo
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- CN106533754A CN106533754A CN201610979319.2A CN201610979319A CN106533754A CN 106533754 A CN106533754 A CN 106533754A CN 201610979319 A CN201610979319 A CN 201610979319A CN 106533754 A CN106533754 A CN 106533754A
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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
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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
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
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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
- H04L41/069—Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
-
- 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
- H04L41/142—Network analysis or design using statistical or mathematical methods
Abstract
The invention discloses a fault diagnosis method and expert system for college teaching servers. The method comprises the following steps: acquiring expert knowledge; establishing a fault tree based on the expert knowledge; storing the fault tree in a knowledge base; acquiring fault information a teaching server cluster; storing the fault information in an auxiliary memory pool; comparing the fault tree with the fault information to acquire a server fault processing method; interpreting the fault processing method; and outputting the interpreted fault processing method. The expert system comprises a human-computer interaction module, a fault tree establishment module, a knowledge base, a fault information acquisition module, an auxiliary memory pool, an inference engine and an interpreter. According to the fault diagnosis method and expert system disclosed by the invention, the fault reasons of the servers are accurately discovered by a fault tree analysis method, and an overhaul scheme is provided, thereby overcoming the original inconvenience that restoration cannot be performed in time due to the shortage of IT service personal, greatly reducing the operation costs and the maintenance fees of the college teaching servers and greatly improving the stability and the reliability of the servers.
Description
Technical field
The present invention relates to college teaching server system field.It is used for college teaching server more particularly, to a kind of
The method of fault diagnosis and specialist system.
Background technology
With the continuous expansion of colleges and universities' size of the student body and being continuously increased for student's quantity, the teaching method of modernization from
The auxiliary of educational server is not opened.Although cloud computing technology quickly grows in the last few years, cloud resource can be rented as religion by colleges and universities
Server is learned, but most colleges and universities still select deployment server nearby in the machine room of each subunit, single for meeting different sons
The teaching of position and regulatory requirement.
Being continuously increased for number of servers, brings greatly not to school's IT service personals regular maintenance and malfunction elimination
Just, it is mainly reflected in：
(1) IT service personals due to not knowing the questions and prospect of educational server for breaking down, Jing will often go live row
Look into, substantially prolongs maintenance time；
(2) as the quantity of server is likely to very many, its geographical position disperses, and needs many IT service personals common
Cooperation completes maintenance, considerably increases cost of human resources；
(3) for some failures are difficult to determine reason, for low-level IT service personals at all cannot failure judgement original
Because being located, processing method cannot be also given, and the limited amount of expert, cause some failures to be difficult to be solved in the very first time
Certainly, teaching is affected to need.
Regular maintenance being carried out directly from existing IT service personals and malfunction elimination being different, specialist system is that an intelligence is counted
Calculation machine programming system, its internal knowledge containing substantial amounts of certain domain expert's level and experience, can be using human expert's
The method of knowledge and solve problem is processing the field question.Therefore, specialist system is one with a large amount of expertises and Jing
The programming system tested, using artificial intelligence technology and computer technology, according to the knowledge that one or more experts of certain field provide
And experience, make inferences and judge, simulate the decision making process of human expert, answering for human expert's process is needed to solve those
Miscellaneous problem.In brief, specialist system is the computer programming system that a kind of simulation human expert solves field question.
Accordingly, it is desirable to provide a kind of method and specialist system for the diagnosis of college teaching server failure, for solving
Above-mentioned inconvenience, provides failure cause and the solution of failed server in time, reduces cost of human resources, improves college teaching
The regular maintenance and fault diagnosis efficiency of server, meets teaching and regulatory requirement.
The content of the invention
It is an object of the present invention to provide a kind of method for the diagnosis of college teaching server failure, for colleges and universities
Fault diagnosis detection and the diagnosis of educational server.
Fault information acquisition and arrangement of the present invention based on educational server cluster, analyze and set up Fault diagnosis expert system
System, on the basis of to educational server cluster daily record fault information analysis, design generates fault tree, further by fault tree
Knowledge sets up the knowledge base of specialist system, and carries out fault diagnosis according to the knowledge base, for the daily of college teaching server
Safeguard and fault diagnosis, realize the function of educational server fault diagnosis expert system.
For reaching above-mentioned purpose, the present invention adopts following technical proposals：
A kind of method for diagnosing faults for college teaching server, the method are comprised the following steps：
Obtain expertise；
Fault tree is set up based on expertise；
Fault tree is stored in knowledge base；
Obtain the fault message of educational server cluster；
Fault message is stored in auxiliary storage storehouse；
Fault tree is compared with fault message, server failure treating method is obtained；
Troubleshooting method is explained；
The explained troubleshooting method of output.
Preferably, logical table of the fault tree also including each failure, condition table, conclusion table and data set table, wherein
Logical table, including logical reasoning code field, logical name field, logical description field and logical division field；
Condition table, for storage and the conditional information of the logical reasoning code match；
Conclusion table, for depositing decision information；
Data set table, for preserving reasoning process conditional Value Types, scope and acquiescence value information.
It is further preferred that step " fault tree being compared with fault message, obtain server failure treating method "
Specifically include：
Inference machine is from read failure information in auxiliary storage storehouse, and extracts fault message and describe key word；
Calculate matching similarity to distinguish fault message classification by fuzzy matching algorithm, and it is excellent fault category to be set up with this
First level sequence；
The fault tree rule of logical table highest priority in knowledge base is read one by one；
By the condition value provided in the condition table and data set table of reading associated, corresponding ginseng when occurring with failure
Numerical value is contrasted, if condition meets, chooses the fault tree rule；It is if condition is unsatisfactory for, excellent into next low level
In first level fault category；
Repeat the above steps are until find matching fault tree rule；
Reading is associated the decision information in conclusion table with the fault tree, completes this reasoning and works.
Preferably, expertise is obtained by human-computer interaction module, including based on to educational server Trouble cause
The fault tree logic that analysis draws.
Preferably, knowledge base includes that each rule is by multiple IF for preserving the rule in fault tree<Condition>With
Then<Conclusion>Composition.
Preferably, fault message acquisition module obtains the fault message of each educational server cluster in real time.
Preferably, auxiliary storage storehouse is used for preserving fault message, and concrete time, position, performance, preferential occurs including failure
Level, and related information.
Preferably, knowledge base is MySQL relevant databases with auxiliary storage storehouse.
Further object is that providing a kind of educational server fault diagnosis using above-mentioned specialist system
Specialist system.
It is a kind of for college teaching server failure diagnosis specialist system, the specialist system include human-computer interaction module,
Construction of Fault Tree module, knowledge base, fault message acquisition module, auxiliary storage storehouse, inference machine and interpreter；Construction of Fault Tree mould
Block is set up fault tree based on the expert info obtained by human-computer interaction module and is stored in knowledge base, and fault message obtains mould
Block be used for obtain educational server cluster fault message and be stored in auxiliary storage storehouse, interpreter by by fault message with
Fault tree is compared and draws troubleshooting method, and troubleshooting method is explained and passes through human-computer interaction module by interpreter
Output.
Beneficial effects of the present invention are as follows：
The present invention takes Fault Tree Analysis accurately to find out server fail reason and provide maintenance solution, can use
In college teaching server fault diagnosis and safeguard use, overcome it is original face IT service personals shortage and cannot be timely
The inconvenience of reparation is made, college teaching server operating cost and maintenance cost is greatly lowered, significantly improve the steady of server
Qualitative and reliability.
Description of the drawings
Below in conjunction with the accompanying drawings the specific embodiment of the present invention is described in further detail.
Fig. 1 illustrates the composition schematic diagram of the specialist system for the diagnosis of college teaching server failure.
Fig. 2 illustrates the method for diagnosing faults block diagram for college teaching server.
During Fig. 3 illustrates embodiment, fault message describes table.
Specific embodiment
In order to be illustrated more clearly that the present invention, the present invention is done further with reference to preferred embodiments and drawings
It is bright.In accompanying drawing, similar part is indicated with identical reference.It will be appreciated by those skilled in the art that institute is concrete below
The content of description is illustrative and be not restrictive, and should not be limited the scope of the invention with this.
Fault information acquisition and arrangement of the present invention based on educational server cluster, analyze and set up Fault diagnosis expert system
System, on the basis of to educational server cluster daily record fault information analysis, design generates fault tree, further by fault tree
Knowledge sets up the knowledge base of specialist system, and carries out fault diagnosis according to the knowledge base, for the daily of college teaching server
Safeguard and fault diagnosis, realize the function of educational server fault diagnosis expert system.
In the present invention, a kind of specialist system for the diagnosis of college teaching server failure, the specialist system includes man-machine
Interactive module, Construction of Fault Tree module, knowledge base, fault message acquisition module, auxiliary storage storehouse, inference machine and interpreter；Therefore
Barrier tree is set up module and sets up fault tree based on the expert info obtained by human-computer interaction module and be stored in knowledge base, failure
Data obtaining module is used for obtaining the fault message of educational server cluster and being stored in auxiliary storage storehouse, and interpreter passes through will
Fault message is compared with fault tree and draws troubleshooting method, and troubleshooting method is explained and passes through people by interpreter
Machine interactive module is exported.
Below to the present invention in each module be further explained：Human-computer interaction module refers to man-machine interface, man-machine interface
The interface for setting up the input-output apparatus for contacting, exchanging information between people and computer is referred to, these equipment include keyboard, show
Show device, printer, Genius mouse etc.；Knowledge base is structuring, comprehensively utilization easy to operate, easy, organized knowledge cluster, is to be directed to
College teaching server failure diagnosis need, using storage, tissue, management and using the knowledge piece set for interkniting；It is auxiliary
Thesauruss are helped to be a kind of data base, data base (Database) is come the storehouse organized, store and manage data according to data structure
Storehouse；Inference machine (Inference Engine) is the part for realizing knowledge-based inference in specialist system, is that Knowledge based engineering is pushed away
Reason realization in a computer, mainly includes two aspects of reasoning and control, is indispensable important composition in knowledge system
Part；Interpreter (Interpreter), is translated into Command Interpreter again, is a kind of computer program, inference machine in the present invention can be produced
Raw decision information is directly translated into the text message that user can recognize line by line.
In the present invention, a kind of method for diagnosing faults for college teaching server, the method are comprised the following steps：
Step one：Expertise is obtained, expertise is obtained by human-computer interaction module, including based on to educational server
The fault tree logic that Trouble cause analysis draws.
Step 2：Fault tree, logical table of the fault tree also including each failure, condition table, knot are set up based on expertise
By table and data set table, wherein logical table, including logical reasoning code field, logical name field, logical description field and patrol
Collect sorting field；Condition table, for storage and the conditional information of the logical reasoning code match；Conclusion table, determines for storage
Plan information；Data set table, for preserving reasoning process conditional Value Types, scope and acquiescence value information.
Step 3：Fault tree is stored in knowledge base, knowledge base is included for preserving the rule in fault tree, each
Rule is by multiple IF<Condition>With Then<Conclusion>Composition.
Step 4：The fault message of educational server cluster is obtained, fault message acquisition module obtains each teaching in real time
The fault message of server cluster.
Step 5：Fault message is stored in auxiliary storage storehouse, auxiliary storage storehouse is used for preserving fault message, including event
There is concrete time, position, performance, priority and related information in barrier.
In the present invention, knowledge base is MySQL relevant databases with auxiliary storage storehouse.
Step 6：Fault tree is compared with fault message, is obtained server failure treating method, is specifically included following
Step：Inference machine is from read failure information in auxiliary storage storehouse, and extracts fault message and describe key word；By fuzzy matching side
Method calculates matching similarity to distinguish fault message classification, and sets up fault category prioritization with this；Knowledge is read one by one
The fault tree rule of logical table highest priority in storehouse；By the bar provided in the condition table and data set table of reading associated
Part value, corresponding parameter value when being occurred with failure are contrasted, if condition meets, choose the fault tree rule；If condition is not
Meet, then in next low level priority fault category；Repeat the above steps are until find matching fault tree
Rule；Reading is associated the decision information in conclusion table with the fault tree, completes this reasoning and works.
Step 7：Troubleshooting method is explained, interpreter is translated into the text that user can recognize by treating method
Word information.
Step 8：Explained troubleshooting method is exported by human-computer interaction module, front end IT service people are used to help
Member's settlement server failure.
In the present invention, the method and specialist system for the diagnosis of college teaching server failure, its working method are as follows：
(1), the failure cause of expert or IT service personal's Analysis servers, and consider possible failure factor, design and generate failure
Tree；(2) fault tree, is preserved to knowledge base；(3), the fault message of each server cluster of fault message acquisition module Real-time Collection；
(4), call inference machine to combine knowledge base according to the fault message for collecting and judge the reason for producing failure；(5), generate failure solution
Certainly to man machine interface, for front end, IT service personals are used for settlement server failure to scheme.
Illustrate with reference to a specific embodiment
As shown in figure 1, a kind of specialist system for the diagnosis of college teaching server failure, the specialist system includes man-machine
Interactive module, Construction of Fault Tree module, knowledge base, fault message acquisition module, auxiliary storage storehouse, inference machine and interpreter；Therefore
Barrier tree is set up module and sets up fault tree based on the expert info obtained by human-computer interaction module and be stored in knowledge base, failure
Data obtaining module is used for obtaining the fault message of educational server cluster and being stored in auxiliary storage storehouse, and interpreter passes through will
Fault message is compared with fault tree and draws troubleshooting method, and troubleshooting method is explained and passes through people by interpreter
Machine interactive module is exported.Above-mentioned specialist system supports Window, (SuSE) Linux OS, by Ethernet and educational server phase
Connection.
As shown in Fig. 2 a kind of method for diagnosing faults for college teaching server, the method is comprised the following steps：
Expert or IT service personals provide fault tree logic by analytic instruction server failure producing cause first, lead to
Cross Construction of Fault Tree module initialized data base and preserve fault tree；Fault message acquisition module Real-time Collection educational server cluster
Middle fault message, and preserve to auxiliary storage storehouse；Exist in the fault message that inference machine is returned by auxiliary storage, with knowledge base
Fault tree compare, obtain server failure treating method, treating method is translated into user by interpreter module can
With the Word message for recognizing；During reasoning, if a certain loss of learning in running into fault tree, the information can be by asking
Ask that user mode is obtained.
In the present embodiment, it is as shown in Figure 3 that specific fault message describes table.
In inference machine, fault tree is described as follows with fault message alignment algorithm：1) inference machine is read from auxiliary storage data base
A fault message is taken, and extracts fault message and describe key word, calculate matching similarity to distinguish by Method of Fuzzy Matching
Fault message classification, and fault category prioritization, such as W are set up with this1->W2->W3；2) examined according to the failure for pre-setting
Disconnected program, reads in knowledge base logical table (LogicTable) in the high fault category of priority fault tree in W classifications one by one
Rule, by the middle offer of the condition table (ConditionTable) and data set table (DatasetTable) that read associated
Condition value, and corresponding parameter value when being occurred with failure contrasted, if condition meets, chooses fault tree rule；If condition
It is unsatisfactory for, in next low level priority fault category, repeats 2) until finding matching fault tree rule；3)
Reading is associated the decision information in conclusion table (ConclusionTable) with the fault tree, completes this reasoning and works.
The specialist system of the fault diagnosis, individually can be deployed on the server of, by LAN and Teaching Service
Device cluster is attached, it is adaptable at present main flow operating system (as Windows, Linux it is serial), realize cross-platform connection.
Knowledge base and auxiliary storage all adopt MySQL relevant databases.Knowledge base is used for preserving the strictly all rules in fault tree, each
Rule is by some IF<Condition>With Then<Conclusion>Composition.Auxiliary storage is used for preserving fault message, and tool occurs including failure
Body time, position, performance, priority and related information (including the auxiliary equipment situation such as power supply, cooling air conditioner).
Fault tree rule design is the basic table knot of present invention design four based on processing the inference logic of strategy
Structure, be respectively：1) logical table (LogicTable), wherein comprising logical reasoning code field (LogicID), logical name field
(LogicName), logical description field (LogicDescription), logical division field (LogicClassification)；
2) conditional information of condition table (ConditionTable) storage and the logical reasoning code match；3) conclusion table
(ConclusionTable) the relevant information of storage decision-making in；4) data set table (DatasetTable) is used for preserving reasoning
Journey conditional Value Types, scope, acquiescence value information.LogicID fields are all included in four tables as unique major key, realize each table
Association between structure.In implementation process, a fault tree rule is broken down into above-mentioned 4 category information, deposits in respectively above-mentioned
In four tables.Such as change server power supply rule storage to be expressed as follows：LogicTable tables deposit ReplacePower
(LogicID fields), changes server power supply (LogicName fields)；In condition table, storage condition title is (such as the failed services
The downtime t of devicestop, interval machine stop times ninterval)；Power down mode lower downtime value is provided in data dictionary table
tz1With interval machine stop times value nz1；It is used for depositing power supply status conclusion power work exception p in conclusion tablefaultAnd process strategy
Recommended replacement power policies tr1.The foundation of college teaching server failure diagnostician's knowledge base is serviced with experienced IT
The knowledge that personnel provide is foundation, is extracted according to Construction of Fault Tree module, is subdivided into logical description, corresponds to above-mentioned four respectively
In individual table, knowledge base is formed.
Logic is changed with power supply in fault tree rule to be exemplified below：
In the present invention, the method for college teaching server failure diagnosis and specialist system, can realize remote diagnosis college teaching
Server failure, is easy to IT service personals to be accurately positioned the position of fault in real time, provides failure cause and maintenance method, has saved dimension
Repair time and cost.
Obviously, the above embodiment of the present invention is only intended to clearly illustrate example of the present invention, and is not right
The restriction of embodiments of the present invention, for those of ordinary skill in the field, may be used also on the basis of the above description
To make other changes in different forms, all of embodiment cannot be exhaustive here, it is every to belong to this
Bright technical scheme it is extended obvious change or change still in protection scope of the present invention row.
Claims (9)
1. a kind of method for the diagnosis of college teaching server failure, the method comprising the steps of：
Obtain expertise；
Fault tree is set up based on the expertise；
The fault tree is stored in knowledge base；
Obtain the fault message of educational server cluster；
The fault message is stored in auxiliary storage storehouse；
The fault tree and fault message are compared, server failure treating method is obtained；
The troubleshooting method is explained；
The explained troubleshooting method of output.
2. specialist system according to claim 1, it is characterised in that logic of the fault tree also including each failure
Table, condition table, conclusion table and data set table, wherein
Logical table, including logical reasoning code field, logical name field, logical description field and logical division field；
Condition table, for storage and the conditional information of the logical reasoning code match；
Conclusion table, for depositing decision information；
Data set table, for preserving reasoning process conditional Value Types, scope and acquiescence value information.
3. specialist system according to claim 2, it is characterised in that described " fault tree to be carried out with fault message
Compare, obtain server failure treating method " specifically include：
Inference machine is from read failure information in auxiliary storage storehouse, and extracts fault message and describe key word；
Calculate matching similarity to distinguish fault message classification by fuzzy matching algorithm, and fault category priority is set up with this
Sequence；
The fault tree rule of logical table highest priority in knowledge base is read one by one；
By the condition value provided in the condition table and data set table of reading associated, corresponding parameter value when occurring with failure
Contrasted, if condition meets, chosen the fault tree rule；If condition is unsatisfactory for, into next low level priority
In fault category；
Repeat the above steps are until find matching fault tree rule；
Reading is associated the decision information in conclusion table with the fault tree, completes this reasoning and works.
4. specialist system according to claim 1, it is characterised in that the expertise is obtained by human-computer interaction module
, including based on the fault tree logic drawn to the analysis of educational server Trouble cause.
5. specialist system according to claim 1, it is characterised in that the knowledge base is included for preserving in fault tree
Rule, each rule is by multiple IF<Condition>With Then<Conclusion>Composition.
6. specialist system according to claim 1, it is characterised in that fault message acquisition module obtains each teaching in real time
The fault message of server cluster.
7. specialist system according to claim 1, it is characterised in that the auxiliary storage storehouse is used for preserving fault message,
There is concrete time, position, performance, priority and related information including failure.
8. specialist system according to claim 1, it is characterised in that the knowledge base is MySQL passes with auxiliary storage storehouse
It is type data base.
9. it is a kind of for college teaching server failure diagnosis specialist system, it is characterised in that the specialist system includes people
Machine interactive module, Construction of Fault Tree module, knowledge base, fault message acquisition module, auxiliary storage storehouse, inference machine and interpreter；
The Construction of Fault Tree module is set up fault tree based on the expert info obtained by the human-computer interaction module and is stored in institute
State in knowledge base, the fault message acquisition module is used for obtaining the fault message of educational server cluster and being stored in described auxiliary
Help in thesauruss, the interpreter draws troubleshooting method by the fault message and fault tree are compared, described
The troubleshooting method is explained and passes through the human-computer interaction module and exported by interpreter.
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| CN108416443A (en) * | 2018-03-29 | 2018-08-17 | 北京润科通用技术有限公司 | A kind of method for diagnosing faults and device |
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