CN109933049A - A kind of power scheduling log Fault Classification and system - Google Patents
A kind of power scheduling log Fault Classification and system Download PDFInfo
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Abstract
Present disclose provides a kind of power scheduling log Fault Classification and systems.Wherein, a kind of power scheduling log Fault Classification, comprising: normalize the format of power scheduling log and template；Content of constructing is inquired in power scheduling log, extracts construction location information as characteristic value information；The characteristic value information of extraction is input in the classifier trained and completed, exports failure modes result；The classifier is generated based on decision tree learning algorithm, training process are as follows: the characteristic value information of the power scheduling log of the normalized known fault type of extraction is divided into training set and test set；Classifier is trained using training set, until the classification results precision that test set tests out classifier reaches preset requirement.
Description
Technical field
The disclosure belongs to power scheduling log failure modes field more particularly to a kind of power scheduling log failure modes side
Method and system.
Background technique
Only there is provided background technical informations relevant to the disclosure for the statement of this part, it is not necessary to so constitute first skill
Art.
Inventors have found that the template style and template of the log of power scheduling at present are various, and for different electric power
The fault type recorded in dispatching log is also different, big using manual sort's task amount, and existing classification method is due to lattice
Formula disunity causes classification speed slow, or even omits key message, the problem of classification inaccuracy occurs.
Summary of the invention
To solve the above-mentioned problems, the first aspect of the disclosure provides a kind of power scheduling log Fault Classification,
It carries out failure modes to power scheduling log using the classifier generated based on decision tree learning algorithm, can be improved classification effect
Rate and accuracy.
To achieve the goals above, the disclosure adopts the following technical scheme that
A kind of power scheduling log Fault Classification, comprising:
The format of power scheduling log and template are normalized；
Content of constructing is inquired in power scheduling log, extracts construction location information therein as characteristic value information；
The characteristic value information of extraction is input in the classifier trained and completed, exports failure modes result；
The classifier is generated based on decision tree learning algorithm, training process are as follows:
The characteristic value information of the power scheduling log of the normalized known fault type of extraction is divided into training set and survey
Examination collection；
Classifier is trained using training set, is wanted until the classification results precision that test set tests out classifier reaches default
It asks.
To solve the above-mentioned problems, the second aspect of the disclosure provides a kind of power scheduling log failure modes system,
It carries out failure modes to power scheduling log using the classifier generated based on decision tree learning algorithm, can be improved classification effect
Rate and accuracy.
To achieve the goals above, the disclosure adopts the following technical scheme that
A kind of power scheduling log failure modes system, comprising:
Module is normalized, is used to normalize the format of power scheduling log and template；
Characteristic extracting module is used to inquire content of constructing in power scheduling log, extracts construction location information therein
As characteristic value information；
Failure modes module is used to for the characteristic value information of extraction being input in the classifier trained and completed, output
Failure modes result；
The failure modes module further include: classifier training module is used for:
The classifier is generated based on decision tree learning algorithm；
The characteristic value information of the power scheduling log of the normalized known fault type of extraction is divided into training set and survey
Examination collection；
Classifier is trained using training set, is wanted until the classification results precision that test set tests out classifier reaches default
It asks.
To solve the above-mentioned problems, a kind of computer readable storage medium is provided in terms of the third of the disclosure, utilized
Failure modes are carried out to power scheduling log based on the classifier that decision tree learning algorithm generates, can be improved classification effectiveness and standard
True property.
To achieve the goals above, the disclosure adopts the following technical scheme that
A kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor
The step in power scheduling log Fault Classification described above is realized when execution.
To solve the above-mentioned problems, the 4th aspect of the disclosure provides a kind of computer equipment, using based on decision
It sets the classifier that learning algorithm generates and failure modes is carried out to power scheduling log, can be improved classification effectiveness and accuracy.
To achieve the goals above, the disclosure adopts the following technical scheme that
A kind of computer equipment can be run on a memory and on a processor including memory, processor and storage
Computer program, the processor are realized in power scheduling log Fault Classification described above when executing described program
Step.
The beneficial effect of the disclosure is:
The power scheduling log Fault Classification and system of the disclosure, by the format of power scheduling log and template normalizing
Change；Content of constructing is inquired in power scheduling log, extracts construction location information therein as characteristic value information；By the spy of extraction
Value indicative information input exports failure modes result to having trained in the classifier completed；Wherein, classifier, which utilizes, is based on decision tree
Learning algorithm generates, and carries out failure modes to power scheduling log using classifier, improves point of power scheduling log failure
Class efficiency and accuracy.
Detailed description of the invention
The Figure of description for constituting a part of this disclosure is used to provide further understanding of the disclosure, and the disclosure is shown
Meaning property embodiment and its explanation do not constitute the improper restriction to the disclosure for explaining the disclosure.
Fig. 1 is a kind of power scheduling log Fault Classification flow chart that the embodiment of the present disclosure provides.
Fig. 2 is a kind of power scheduling log failure modes system structure diagram that the embodiment of the present disclosure provides.
Specific embodiment
The disclosure is described further with embodiment with reference to the accompanying drawing.
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the disclosure.Unless another
It indicates, all technical and scientific terms used herein has usual with disclosure person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the disclosure.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
Fig. 1 is a kind of power scheduling log Fault Classification flow chart that the embodiment of the present disclosure provides.
As shown in Figure 1, a kind of power scheduling log Fault Classification of the present embodiment, comprising:
S101: the format of power scheduling log and template are normalized.
In specific implementation, step S101 is by the format of power scheduling log and the normalization process of template are as follows:
S1011: the format and template of normalized power scheduling log are set；Wherein, normalized power scheduling log
Template include command context and record information, the record information includes scope of power outage and construction content；
S1012: the format conversion of power scheduling log；
Using setting normalized power scheduling journal format as excel format.
The format of current power scheduling log is word format, extracts the key character and related statement word of word format
Symbol, filling to excel format corresponding position.
The efficiency and accuracy of later period failure modes can be improved in this way.
S1013: command context, scope of power outage and the construction content of identification power scheduling log fill out corresponding contents correspondence
It is charged in normalized template.
It should be noted that the template of normalized power scheduling log in addition to include command context and record information it
Outside, it can also include command number, the time that says the word, the time of annotation, require the deadline, report the time and made us.
Power scheduling log is normalized the present embodiment, so that power scheduling journal format is consistent with template,
It can be improved the efficiency for content of constructing in inquiry power scheduling log, additionally it is possible to it is accurate to extract construction location information, it avoids constructing
The omission of location information guarantees the accuracy of final failure modes.
S102: content of constructing in inquiry power scheduling log extracts construction location information therein as characteristic value information.
In specific implementation, step S102 inquires in power scheduling log content of constructing, and extracts the conduct of construction location information
The process of characteristic value information are as follows:
S1021: it is character by Content Transformation of constructing in power scheduling log, and screens out punctuation mark；
S1022: information associated with construction location is proposed in the character for screen out punctuation mark as characteristic value information.
The processing time for saving redundancy in this way, improve the efficiency of power scheduling log failure modes.
S103: the characteristic value information of extraction being input in the classifier trained and completed, and exports failure modes result.
Wherein, the classifier is generated based on decision tree learning algorithm, training process are as follows:
The characteristic value information of the power scheduling log of the normalized known fault type of extraction is divided into training set and survey
Examination collection；
Classifier is trained using training set, is wanted until the classification results precision that test set tests out classifier reaches default
It asks.
Specifically, the fault type of power scheduling log, comprising:
Line fault, transformer fault, bus-bar fault and other failures.
The power scheduling log Fault Classification of the present embodiment normalizes the format of power scheduling log and template；
Content of constructing is inquired in power scheduling log, extracts construction location information therein as characteristic value information；By the feature of extraction
Value information is input in the classifier trained and completed, and exports failure modes result；Wherein, classifier is utilized is learned based on decision tree
It practises algorithm to generate, failure modes is carried out to power scheduling log using classifier, improve the classification of power scheduling log failure
Efficiency and accuracy.
Fig. 2 is a kind of power scheduling log failure modes system structure diagram that the embodiment of the present disclosure provides.
As shown in Fig. 2, a kind of power scheduling log failure modes system of the present embodiment, comprising:
(1) module is normalized, is used to normalize the format of power scheduling log and template.
In specific implementation, the normalization module, further includes:
Setting module is normalized, is used to set the format and template of normalized power scheduling log；Wherein, it normalizes
The template of power scheduling log include command context and record information, the record information includes in scope of power outage and construction
Hold；
Format converts cover half block, is used for the format conversion of power scheduling log；
Template switch module, for identification the command context, scope of power outage of power scheduling log and construction content, by phase
Answer the corresponding filling of content into normalized template.
(2) characteristic extracting module is used to inquire content of constructing in power scheduling log, extracts construction location letter therein
Breath is used as characteristic value information.
In specific implementation, the characteristic extracting module, is used for:
It is character by Content Transformation of constructing in power scheduling log, and screens out punctuation mark；
Information associated with construction location is proposed in the character for screen out punctuation mark as characteristic value information.
(3) failure modes module is used to for the characteristic value information of extraction being input in the classifier trained and completed, defeated
Be out of order classification results；
The failure modes module further include: classifier training module is used for:
The classifier is generated based on decision tree learning algorithm；
The characteristic value information of the power scheduling log of the normalized known fault type of extraction is divided into training set and survey
Examination collection；
Classifier is trained using training set, is wanted until the classification results precision that test set tests out classifier reaches default
It asks.
Wherein, the fault type of power scheduling log, comprising:
Line fault, transformer fault, bus-bar fault and other failures.
The power scheduling log failure modes system of the present embodiment normalizes the format of power scheduling log and template；
Content of constructing is inquired in power scheduling log, extracts construction location information therein as characteristic value information；By the feature of extraction
Value information is input in the classifier trained and completed, and exports failure modes result；Wherein, classifier is utilized is learned based on decision tree
It practises algorithm to generate, failure modes is carried out to power scheduling log using classifier, improve the classification of power scheduling log failure
Efficiency and accuracy.
In another embodiment, a kind of computer readable storage medium is additionally provided, computer program is stored thereon with, it should
The step in power scheduling log Fault Classification as shown in Figure 1 is realized when program is executed by processor.
In another embodiment, it additionally provides a kind of computer equipment, including memory, processor and is stored in memory
Computer program that is upper and can running on a processor, the processor realize electric power as shown in Figure 1 when executing described program
Step in dispatching log Fault Classification.
It should be understood by those skilled in the art that, embodiment of the disclosure can provide as method, system or computer program
Product.Therefore, the shape of hardware embodiment, software implementation or embodiment combining software and hardware aspects can be used in the disclosure
Formula.Moreover, the disclosure, which can be used, can use storage in the computer that one or more wherein includes computer usable program code
The form for the computer program product implemented on medium (including but not limited to magnetic disk storage and optical memory etc.).
The disclosure is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present disclosure
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the program can be stored in a computer-readable storage medium
In, the program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (Random
AccessMemory, RAM) etc..
The foregoing is merely preferred embodiment of the present disclosure, are not limited to the disclosure, for the skill of this field
For art personnel, the disclosure can have various modifications and variations.It is all within the spirit and principle of the disclosure, it is made any to repair
Change, equivalent replacement, improvement etc., should be included within the protection scope of the disclosure.
Claims (10)
1. a kind of power scheduling log Fault Classification characterized by comprising
The format of power scheduling log and template are normalized；
Content of constructing is inquired in power scheduling log, extracts construction location information therein as characteristic value information；
The characteristic value information of extraction is input in the classifier trained and completed, exports failure modes result；
The classifier is generated based on decision tree learning algorithm, training process are as follows:
The characteristic value information of the power scheduling log of the normalized known fault type of extraction is divided into training set and test set；
Classifier is trained using training set, until the classification results precision that test set tests out classifier reaches preset requirement.
2. a kind of power scheduling log Fault Classification as described in claim 1, which is characterized in that by power scheduling log
Format and template normalization process are as follows:
Set the format and template of normalized power scheduling log；Wherein, the template of normalized power scheduling log includes
Command context and record information, the record information include scope of power outage and construction content；
The format of power scheduling log is converted；
The command context, scope of power outage and construction content for identifying power scheduling log, the corresponding filling of corresponding contents is extremely normalized
Template in.
3. a kind of power scheduling log Fault Classification as described in claim 1, which is characterized in that inquiry power scheduling day
It constructs in will content, extracts process of the construction location information as characteristic value information are as follows:
It is character by Content Transformation of constructing in power scheduling log, and screens out punctuation mark；
Information associated with construction location is proposed in the character for screen out punctuation mark as characteristic value information.
4. a kind of power scheduling log Fault Classification as described in claim 1, which is characterized in that power scheduling log
Fault type, comprising:
Line fault, transformer fault, bus-bar fault and other failures.
5. a kind of power scheduling log failure modes system characterized by comprising
Module is normalized, is used to normalize the format of power scheduling log and template；
Characteristic extracting module is used to inquire content of constructing in power scheduling log, extracts construction location information conduct therein
Characteristic value information；
Failure modes module is used to for the characteristic value information of extraction being input in the classifier trained and completed, exports failure
Classification results；
The failure modes module further include: classifier training module is used for:
The classifier is generated based on decision tree learning algorithm；
The characteristic value information of the power scheduling log of the normalized known fault type of extraction is divided into training set and test set；
Classifier is trained using training set, until the classification results precision that test set tests out classifier reaches preset requirement.
6. a kind of power scheduling log failure modes system as claimed in claim 5, which is characterized in that the normalization mould
Block, further includes:
Setting module is normalized, is used to set the format and template of normalized power scheduling log；Wherein, normalized electricity
The template of power dispatching log includes command context and record information, and the record information includes scope of power outage and construction content；
Format converts cover half block, is used for the format conversion of power scheduling log；
Template switch module, the command context, scope of power outage of power scheduling log and construction content, are incited somebody to action in corresponding for identification
Hold corresponding filling into normalized template.
7. a kind of power scheduling log failure modes system as claimed in claim 5, which is characterized in that the feature extraction mould
Block is used for:
It is character by Content Transformation of constructing in power scheduling log, and screens out punctuation mark；
Information associated with construction location is proposed in the character for screen out punctuation mark as characteristic value information.
8. a kind of power scheduling log failure modes system as claimed in claim 5, which is characterized in that power scheduling log
Fault type, comprising:
Line fault, transformer fault, bus-bar fault and other failures.
9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor
It realizes when row such as the step in power scheduling log Fault Classification of any of claims 1-4.
10. a kind of computer equipment including memory, processor and stores the meter that can be run on a memory and on a processor
Calculation machine program, which is characterized in that the processor realizes such as electricity of any of claims 1-4 when executing described program
Step in power dispatching log Fault Classification.
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