CN112463929A - Automatic classification method of fault information - Google Patents

Automatic classification method of fault information Download PDF

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CN112463929A
CN112463929A CN202011445862.7A CN202011445862A CN112463929A CN 112463929 A CN112463929 A CN 112463929A CN 202011445862 A CN202011445862 A CN 202011445862A CN 112463929 A CN112463929 A CN 112463929A
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凌忠标
郑楚韬
张耀宇
王洪帅
钟嘉瑜
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Foshan Power Supply Bureau of Guangdong Power Grid Corp
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Abstract

The invention provides an automatic classification method of fault information, which comprises the following steps: s1: reading any fault information X to be classified from a fault information database to be classified; s2: read the classification reference library LiObtaining a classification reference library LiKey word L ofi‑jCalculating each keyword Li‑jIs given a priority value Pi‑j(ii) a S3: traverse the classification reference library LiAll keywords L ofi‑jCalculating a classification reference library LiTotal priority score Pi(ii) a S4: setting an initial priority score PaCompare P with 0iAnd PaIf P isi>PaThen let Pa＝PiA is i, howeverThen S5 is carried out; otherwise, directly performing S5; s5: traverse all the classification reference libraries LiObtaining the final total priority value PmaxMax ═ i; according to the final total priority value PmaxAnd classifying the fault information X to be classified. The invention has more accurate classification result and more efficient classification process.

Description

Automatic classification method of fault information
Technical Field
The invention relates to the technical field of operation and maintenance, in particular to an automatic classification method for fault information.
Background
In current power grid enterprises, in order to analyze the operation condition and the management condition of a power grid, historical fault first-aid repair information needs to be classified and counted so as to formulate a corresponding operation and maintenance management strategy. When fault information is filled in, due to the fact that operation and maintenance personnel are different, filling classification standards are different and other actual factors, the same fault is described in different modes, and the same fault is recorded for multiple times, the fault information is difficult to classify accurately under the conditions, manual checking and classification are needed one by one, the work is complicated and time-consuming, the efficiency is low, and missing items and errors are easy to occur.
Chinese patent CN106960274A published in 2017, 7, month and 18 provides a fault work order processing system and method, including: the work order scheduling module receives a work order from the outside of the system, and the analysis module extracts keywords of fault description in the work order; the analysis module searches a fault case list with the same keyword in the case storage module according to the extracted keyword, and finds out the fault reason with the most keywords as the fault reason of the work order; according to the found fault reason, all solutions for solving the fault reason are found in the fault case, and the same solution with the largest quantity is used as the optimal solution for the fault of the work order; and feeding back the found fault reason and the optimal solution to the corresponding origin of the work order. The patent only searches the fault reason containing the most keywords in the case storage module, and the processing result is not accurate.
Disclosure of Invention
The invention provides an automatic classification method of fault information, aiming at overcoming the defect that the classification processing result of the fault information in the prior art is inaccurate.
The technical scheme of the invention is as follows:
the invention provides an automatic classification method of fault information, which comprises the following steps:
s1: reading any fault information X to be classified from a fault information database to be classified;
s2: read the classification reference library Li，Lie.L, i is 1, 2, …, n, L is total classification reference library, and a classification reference library L is obtainediKey word L ofi-j J 1, 2, …, i, each keyword L is calculatedi-jIs given a priority value Pi-j；
S3: traverse the classification reference library LiAll keywords L ofi-jCalculating a classification reference library LiTotal priority score Pi；
S4: setting initial priority score to Pa；
Comparison PiAnd PaIf P isi>PaThen let Pa＝PiAnd a ═ i, then S5; otherwise, directly performing S5;
s5: traverse all the classification reference libraries LiTo obtain the final total priority value PmaxMax ═ i; according to the final total priority value PmaxAnd classifying the fault information X to be classified.
Preferably, the fault information X to be classified in S1 includes a faulty device, a fault cause description, a fault handling condition, and a fault key information remark.
Preferably, the keyword L in S2i-jComprising determining the direction alphai-jContaining a coefficient of betai-jAnd a decision weight Qi-j。
Preferably, the keyword L is calculatedi-jIs given a priority value Pi-jBefore, the keyword L is judgedi-jWhether or not to be included in the fault information X to be classified to determine the inclusion coefficient betai-jThe value of (a).
Preferably, the inclusion coefficient β is determinedi-jThe value taking method comprises the following specific steps:
when the key word Li-jWhen included in the fault information X to be classified, includes a coefficient β i-j1 is ═ 1; when in useKeyword Li-jWhen not included in the failure information X to be classified, the coefficient β is includedi-j＝0。
Preferably, the keyword L in S2i-jIs given a priority value Pi-jCalculated by the following formula:
Pi-j＝αi-j*βi-j*Qi-j
wherein alpha isi-jIndicates the determination direction, betai-jThe representation contains coefficients and Qi-jIndicating the decision weight.
Preferably, the classification reference library L in S3iTotal priority score PiCalculated by the following formula:
Figure BDA0002831159390000021
wherein, Pi-jRepresents a keyword Li-jThe priority score of (1).
Preferably, the final total priority value P in S5maxCalculated by the following formula:
Figure BDA0002831159390000022
wherein, PiRepresents a library of classification references LiTotal priority score of.
Preferably, in the step S5, the final total priority value P is usedmaxThe specific method for classifying the fault information X to be classified is as follows:
if the final total priority score Pmax>0, the corresponding classification reference library is the classification reference library to which the fault information X to be classified belongs, LX＝Lmax，max＝i；
If the final total priority score PmaxIf the fault information X to be classified is less than or equal to 0, judging that the fault information X to be classified does not have a classification reference library to which the fault information X belongs to LX"tentatively undefined classification".
Preferably, if the fault information to be classified is judged to be 'temporarily undefined classification', the fault information is fed back to operation and maintenance personnel for manual classification.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention determines each final total priority value based on judging whether the keywords in the classification reference library are contained in the fault information to be classified, and calculates the priority value of each keyword, and classifies the fault information to be classified according to the final total priority values. The method can comprehensively carry out discrimination and grading on the fault information, and finally determines the classification reference library to which the fault information belongs, so that the classification result is more accurate, and the classification process is more efficient.
Drawings
FIG. 1 is a diagram illustrating the structure of a total classification reference library according to example 1;
fig. 2 is a flowchart of a method for automatically classifying fault information according to embodiment 1.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
The present embodiment provides an automatic classification method of fault information, as shown in fig. 2, the method includes the following steps:
s1: reading any fault information X to be classified from a fault information database to be classified;
s2: as shown in FIG. 1, a library L of classification references is readi，Lie.L, i is 1, 2, …, n, L is total classification reference library, and a classification reference library L is obtainediKey word L ofi-j J 1, 2, …, i, each keyword L is calculatedi-jIs given a priority value Pi-j；
S3: traverse the classification reference library LiAll keywords L ofi-jCalculating a classification reference library LiTotal priority score Pi；
S4: setting initial priority score to Pa；
Comparison PiAnd PaIf P isi>PaThen let Pa＝PiAnd a ═ i, then S5; otherwise, directly performing S5;
s5: traverse all the classification reference libraries LiTo obtain the final total priority value PmaxMax ═ i; according to the final total priority value PmaxAnd classifying the fault information X to be classified.
The fault information X to be classified in S1 includes the device with fault, the description of the fault cause, the fault handling condition, and the remark of the fault key information.
The keyword L in S2i-jComprising determining the direction alphai-jContaining a coefficient of betai-jAnd a decision weight Qi-j。
In calculating the keyword Li-jIs given a priority value Pi-jBefore, the keyword L is judgedi-jWhether or not to be included in the fault information X to be classified to determine the inclusion coefficient betai-jThe value of (a).
Determining the inclusion coefficient betai-jThe value taking method comprises the following specific steps:
when the key word Li-jWhen included in the fault information X to be classified, includes a coefficient β i-j1 is ═ 1; when the key word Li-jWhen not included in the failure information X to be classified, the coefficient β is includedi-j＝0。
The keyword L in S2i-jIs given a priority value Pi-jCalculated by the following formula:
Pi-j＝αi-j*βi-j*Qi-j
wherein alpha isi-jIndicates the determination direction, betai-jThe representation contains coefficients and Qi-jIndicating the decision weight.
Figure BDA0002831159390000041
Wherein, Pi-jRepresents a keyword Li-jThe priority score of (1).
The final total priority value P in S5maxCalculated by the following formula:
Figure BDA0002831159390000042
wherein, PiRepresents a library of classification references LiTotal priority score of.
In the step S5, the final total priority value P is obtainedmaxThe specific method for classifying the fault information X to be classified is as follows:
if the final total priority score Pmax>0, the corresponding classification reference library is the classification reference library to which the fault information X to be classified belongs, LX＝Lmax，max＝i；
If the final total priority score PmaxIf the fault information X to be classified is less than or equal to 0, judging that the fault information X to be classified does not have a classification reference library to which the fault information X belongs to LX"tentatively undefined classification".
And if the fault information to be classified is judged to be 'temporarily without definition classification', feeding the fault information to the operation and maintenance personnel for manual classification.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.

Claims (10)

1. A method for automatically classifying fault information, the method comprising the steps of:
s1: reading any fault information X to be classified from a fault information database to be classified;
s2: read the classification reference library Li，Lie.L, i is 1, 2, …, n, L is total classification reference library, and a classification reference library L is obtainediKey word L ofi-jJ 1, 2, …, i, each keyword L is calculatedi-jIs given a priority value Pi-j；
S3: traverse the classification reference library LiAll keywords L ofi-jCalculating a classification reference library LiTotal priority score Pi；
S4: setting initial priority score to Pa；
Comparison PiAnd PaIf P isi＞PaThen let Pa＝PiAnd a ═ i, then S5; otherwise, directly performing S5;
s5: traverse all the classification reference libraries LiTo obtain the final total priority value PmaxMax ═ i; according to the final total priority value PmaxAnd classifying the fault information X to be classified.
2. The method according to claim 1, wherein the fault information X to be classified in S1 includes a faulty device, a fault cause description, a fault handling condition and a fault key information remark.
3. The method according to claim 2, wherein the keyword L in S2 is a keyword Li-jComprising determining the direction alphai-jContaining a coefficient of betai-jAnd a decision weight Qi-j。
4. The method of claim 3, wherein the keyword L is calculatedi-jIs given a priority value Pi-jBefore, the keyword L is judgedi-jWhether or not to be included in the fault information X to be classified to determine the packetContaining the coefficient betai-jThe value of (a).
5. The method according to claim 4, wherein the inclusion coefficient β is determinedi-jThe value taking method comprises the following specific steps:
when the key word Li-jWhen included in the fault information X to be classified, includes a coefficient βi-j1 is ═ 1; when the key word Li-jWhen not included in the failure information X to be classified, the coefficient β is includedi-j＝0。
6. The method for automatically classifying fault information according to claim 5, wherein the keyword L in S2i-jIs given a priority value Pi-jCalculated by the following formula:
Pi-j＝αi-j*βi-j*Qi-j
wherein alpha isi-jIndicates the determination direction, betai-jThe representation contains coefficients and Qi-jIndicating the decision weight.
7. The method according to claim 6, wherein the classification reference library L in S3 is a classification reference library LiTotal priority score PiCalculated by the following formula:
Figure FDA0002831159380000021
wherein, Pi-jRepresents a keyword Li-jThe priority score of (1).
8. The method according to claim 7, wherein the final total priority value P in S5 ismaxCalculated by the following formula:
Figure FDA0002831159380000022
wherein, PiRepresents a library of classification references LiTotal priority score of.
9. The method according to claim 8, wherein in step S5, the fault information is classified according to a final total priority value PmaxThe specific method for classifying the fault information X to be classified is as follows:
if the final total priority score PmaxIf the fault information X is more than 0, the corresponding classification reference library is the classification reference library to which the fault information X to be classified belongs, and LX＝Lmax，max＝i；
If the final total priority score PmaxIf the fault information X to be classified is less than or equal to 0, judging that the fault information X to be classified does not have a classification reference library to which the fault information X belongs to LX"tentatively undefined classification".
10. The method according to claim 9, wherein if the fault information to be classified is determined as "tentative definitional classification", the fault information is fed back to operation and maintenance personnel for manual classification.
CN202011445862.7A 2020-12-11 2020-12-11 Automatic classification method of fault information Pending CN112463929A (en)

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* Cited by examiner, † Cited by third party
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KR20110016593A (en) * 2009-08-12 2011-02-18 주식회사 나스미디어 A method for analyzing reactions of advertizing object using internet
CN107679153A (en) * 2017-09-27 2018-02-09 国家电网公司信息通信分公司 A kind of patent classification method and device
CN107844559A (en) * 2017-10-31 2018-03-27 国信优易数据有限公司 A kind of file classifying method, device and electronic equipment
CN108256090A (en) * 2018-01-25 2018-07-06 成都贝发信息技术有限公司 APP divides class method for distinguishing automatically based on keyword
CN108509482A (en) * 2018-01-23 2018-09-07 深圳市阿西莫夫科技有限公司 Question classification method, device, computer equipment and storage medium
CN108664612A (en) * 2018-05-11 2018-10-16 广东电网有限责任公司 Intelligent long text data classification method based on keyword scoring
CN110634017A (en) * 2019-08-23 2019-12-31 深圳市新系区块链技术有限公司 Information classification method, device and equipment

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20110016593A (en) * 2009-08-12 2011-02-18 주식회사 나스미디어 A method for analyzing reactions of advertizing object using internet
CN107679153A (en) * 2017-09-27 2018-02-09 国家电网公司信息通信分公司 A kind of patent classification method and device
CN107844559A (en) * 2017-10-31 2018-03-27 国信优易数据有限公司 A kind of file classifying method, device and electronic equipment
CN108509482A (en) * 2018-01-23 2018-09-07 深圳市阿西莫夫科技有限公司 Question classification method, device, computer equipment and storage medium
CN108256090A (en) * 2018-01-25 2018-07-06 成都贝发信息技术有限公司 APP divides class method for distinguishing automatically based on keyword
CN108664612A (en) * 2018-05-11 2018-10-16 广东电网有限责任公司 Intelligent long text data classification method based on keyword scoring
CN110634017A (en) * 2019-08-23 2019-12-31 深圳市新系区块链技术有限公司 Information classification method, device and equipment

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