CN102248955B - Automatic alarm receiving method - Google Patents
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Abstract
The invention provides an automatic alarm receiving method, which comprises the following steps of: 1, matching a subject field in alarm information with a failure name in a history library and acquiring a successful matching plan; 2, recording information corresponding to the successful matching plan in the history library and starting the plan; and 3, recording an execution result of the plan in a status bar corresponding to the plan in the history library. In the method, the subject field in the alarm information transmitted by a locomotive and the failure name in the history library are matched to obtain the successful matching plan for realizing automatic selection and starting of the plan when the locomotive transmits the alarm information, and a reliable plan is adopted in a short period of time, so that a failure can be eliminated immediately, and safe running of the locomotive can be recovered.
Description
Technical field
The present invention relates to the locomotive failure control technology, relate in particular to the method for automatically receiving a crime report that the automatic prediction scheme of alarm message is selected and started.
Background technology
Along with the lasting acceleration of national economy development and city, Development of China's Urbanization, Chinese Railway also in without a stop development to adapt to more passenger flow, faster speed and safer running.
Because it is various and affect greatly affect factor that the locomotive on the railway normally moves, locomotive often breaks down.When locomotive breaks down, at first need the staff to carry out specialty analysis and draw prediction scheme; then eliminate fault through staff's rigorous operation, can not more in time eliminate fault although the prediction scheme that staff's specialty analysis draws can be guaranteed the safe operation of locomotive.
Summary of the invention
For defects, the invention provides a kind of method of automatically receiving a crime report.
Automatically the method for receiving a crime report provided by the invention comprises:
Step 1: the subject field in the alarm message and the fault title in the history library mated and obtain the prediction scheme that the match is successful;
Step 2: information recording/corresponding to prediction scheme that will the match is successful and starts described prediction scheme in described history library;
Step 3: the execution result of described prediction scheme is recorded to status bar corresponding with described prediction scheme in the described history library.
Automatic selection and the startup of prediction scheme when obtaining the prediction scheme that the match is successful and realizing that locomotive sends alarm message mated in the present invention by the subject field in the alarm message that locomotive is sent and the fault title in the history library, adopt at short notice the failure-free prediction scheme, thereby can eliminate in time fault, recover the safe operation of locomotive.
Description of drawings
Fig. 1 is automatically the receive a crime report diagram of circuit of method of the present invention;
Fig. 2 is the constructional drawing of forecast model decision tree of the present invention.
The specific embodiment
Further specify the technical scheme of the embodiment of the invention below in conjunction with the drawings and specific embodiments.
Fig. 1 is automatically the receive a crime report diagram of circuit of method of the present invention, and as shown in Figure 1, the method mainly may further comprise the steps:
Step 1: the subject field in the alarm message and the fault title in the history library mated and obtain the prediction scheme that the match is successful;
Step 2: information recording/corresponding to prediction scheme that will the match is successful and starts described prediction scheme in described history library;
Step 3: the execution result of described prediction scheme is recorded to status bar corresponding with described prediction scheme in the described history library.
The information recording/that the prediction scheme that the match is successful is corresponding is in described history library, and start described prediction scheme, particularly, with the fault title of the prediction scheme that the match is successful, use the fault title of prediction scheme number record in history library, use in the prediction scheme numbered bin, and prediction scheme that will the match is successful is presented on the display terminal, checks for the staff; The execution result of described prediction scheme is recorded to status bar corresponding with described prediction scheme in the described prediction scheme storehouse, particularly, the execution result of the prediction scheme that the match is successful comprises " success ", " unsuccessful ", if execution result is " success ", then will " finish " and add in the status bar corresponding with described prediction scheme in the history library, if execution result is " unsuccessful ", then will " finish " and add in the status bar corresponding with described prediction scheme in the history library.In step 2, also can with the fault number record in the fault numbered bin of history library, in step 3, can be added in the dateline corresponding with this prediction scheme in the history library execution date of prediction scheme.
The startup of the automatic selection of prediction scheme when obtaining the prediction scheme that the match is successful and realizing that locomotive sends alarm message is mated in the present invention by the subject field in the alarm message that locomotive is sent and the fault title in the history library, adopt at short notice the failure-free prediction scheme, thereby can eliminate in time fault, recover the safe operation of locomotive.
Step 1 can specifically comprise the steps:
Step 11: go out the historical operation record that conforms to subject field in the alarm message according to fault title exact-match lookup from history library, and the record that obtains the historical operation number counts Rs, if Rs=1, then the match is successful, execution in step 2; If Rs＞1, then execution in step 12; If Rs=0, then execution in step 13.
From history library, go out the historical operation record that conforms to subject field in the alarm message according to fault title exact-match lookup, belong to the exact matching process, in history library, search the situation of in historical operation, eliminating this fault by this exact matching process, the prediction scheme that comprises use is used implementation status of prediction scheme etc.
Historical operation in the history library has recorded historical failure and has eliminated process, and this also is the main authority of real-time fault analysis.The content of historical operation record includes but not limited in the history library: fault numbering, fault title, use prediction scheme numbering, date and state, and as shown in table 1, certainly comprise the fault title in the history library, use prediction scheme numbering, state to get final product.
Table 1
| The fault numbering | The fault title | Use prediction scheme numbering | Date | State |
| SysA-P0-9878 | Be subjected to the electric work fault | EQ-P0-23554 | 2010-9-12 | Finish |
| SysB-Win-0980 | The strong wind early warning | Sec-Win-98778 | 2010-11-21 | Finish |
Step 12: the content in the described alarm message is added that adeditive attribute and content summary carry out fuzzy matching in text library, wherein, described content summary is present in the prediction scheme storehouse, and prediction scheme numbering corresponding to described content summary is same as use prediction scheme numbering corresponding to the fault title corresponding with described subject field, if the match is successful, then execution in step 2;
Hypernym, hyponym, polysemant are recorded in the text library.Hypernym refers to the descriptor that conceptive extension is wider, and for example the vehicle are exactly the hypernym of train; Hyponym refers to the descriptor that conceptive intension is narrower, and for example motor-car is exactly the hyponym of train; Polysemant is the word with several meanings that differ from one another and be mutually related.
Comprise the descriptor of describing content summary in the text library.When the distance between the common hypernym refers to find the common hypernym of two words, find each word this common hypernym desired seek number of times and, even the hypernym of A is a, the hypernym of B is b, the hypernym of a is d, the hypernym of b is a, then a is the common hypernym of A and B, the number of times that finds this common hypernym to search from A is 1, and the number of times that finds this common hypernym to search from B is 2, and then the distance between the common hypernym of A and B is 1+2=3, also as: car is the hypernym of train, distance between them is 1, and train is the hypernym of motor-car, and the distance between car and the motor-car is 2 so.In fact, in text library, search the hypernym that content summary and content add adeditive attribute, when in text library, finding content summary and content to add the common hypernym of adeditive attribute, from content add adeditive attribute find number of times that this common hypernym need to search and from content summary find number of times that this common hypernym need to search and be exactly C2.
Have mapping relations between alarm message and the prediction scheme storehouse, alarm message represents with C, and the prediction scheme storehouse represents with D.Alarm message is sent by peripheral system, and alarm message includes but not limited to: message subject, message content, type of message and adeditive attribute etc., wherein message subject belongs to subject field, type of message belongs to the type of alarm field, adeditive attribute belongs to the adeditive attribute field, and message content belongs to content field; The prediction scheme storehouse includes but not limited to: content summary field, prediction scheme number field, header field.
The adeditive attribute field of content field+C of C and the content summary field of D form corresponding relation.
Step 13: described content is added the above adeditive attribute mate in described text library, if the match is successful, then execution in step 2.
Need to prove, Rs=1 means two kinds of situations: only have one with the fault title in the history library that subject field in the alarm message conforms to; With more than one of fault title in the history library that subject field in the alarm message conforms to, but be the same with use prediction scheme numbering corresponding to each fault title.
When Rs＞1, the detailed process of execution in step 12 can be described below:
Step 121: for each content summary, search the common hypernym that described content adds the above adeditive attribute and described content summary in described text library, and obtain the number C3 of described common hypernym, if C3=0, then it fails to match; If C3＞0, then execution in step 122;
Because Rs＞1 o'clock, the number of the content summary that the fault title that conforms to subject field in the history library is corresponding is greater than 1, so need to will add that adeditive attribute carries out fuzzy matching in text library with content for each content summary.
Step 122: obtain the distance C 2 between the described common hypernym, if C2 is not more than the 3rd threshold value, then calculate the prediction scheme reference value of prediction scheme corresponding to qualified described content summary; If C2 is greater than the 3rd threshold value, then execution in step 123;
Step 123: in described text library, search described content and add respectively corresponding polysemant of the above adeditive attribute and described content summary, and obtain the summation C4 of described polysemant, if C4 greater than first threshold, then it fails to match; If C4 is not more than first threshold, then execution in step 124;
Step 124: for each content summary corresponding with described polysemant in the described prediction scheme storehouse, in described text library, search the common hypernym that described content adds the above adeditive attribute and described content summary, and obtain distance C 2 between the described common hypernym, if C2 is greater than Second Threshold, then it fails to match; If C2 is not more than Second Threshold, then execution in step 125;
Step 125: the prediction scheme reference value of calculating prediction scheme corresponding to qualified content summary;
Wherein, step 121-step 125 belongs to the process of fuzzy matching, and the algorithm that fuzzy matching is adopted is: (Latent Semantic Analysis is called for short: LSA), can find out a plurality of prediction schemes by this fuzzy matching latent semantic analysis.
Step 126: the described prediction scheme reference value of all that will calculate compares and selects prediction scheme corresponding to maximum prediction scheme reference value as the prediction scheme that the match is successful, and the match is successful, execution in step 2.
Step 126 belongs to the exact matching process, selects a prediction scheme conduct prediction scheme that the match is successful in this exact matching process from a plurality of prediction schemes that find out by fuzzy matching.
Be accurate to by employing and fuzzy arrive again accurate matching way, guaranteeing to mate under the prerequisite of particularity, can improve the speed of coupling.
It should be noted that, content summary and content add that the common hypernym of adeditive attribute in text library might be for a plurality of, at this moment, the value of the distance between the common hypernym is a plurality of certainly, and this will select the distance between the minimum common hypernym to compare with the 3rd threshold value or Second Threshold.
Can be to show error message at display terminal to mentioning the processing mode that it fails to match in the literary composition among the present invention, remind the staff that it fails to match, thereby the alarm message that the manual analysis locomotive sends is formulated prediction scheme, to eliminate fault, guarantee the safe operation of locomotive.
First threshold, Second Threshold and the 3rd threshold value all are that the staff sets according to the experience of oneself, first threshold is between 6 and 10, Second Threshold is between 3 and 6, when content summary and content add that adeditive attribute is totally 148 pairs the time, the first threshold preferred value is 8, the Second Threshold preferred value is 5, and in addition, the preferred value of the 3rd threshold value is 2.
Wherein, calculate prediction scheme reference value: RV=0.4*UR+0.6*PR according to following rule, wherein, RV is the prediction scheme reference value, UR is the prediction scheme frequency of utilization, PR is the accurate implementation rate of prediction scheme, UR=(summation of these prediction scheme access times/the type warning frequency) * 100%, PR=(this prediction scheme successful execution number of times/these prediction scheme access times) * 100%.By qualified content summary, can be in the prediction scheme storehouse correspondence go out the prediction scheme numbering, the number of times of the use prediction scheme numbering generation that statistics is consistent with this corresponding prediction scheme numbering that goes out in history library can be learnt this prediction scheme access times; By qualified content summary, can in the prediction scheme storehouse, correspondence go out the prediction scheme numbering, this prediction scheme numbering that goes out according to the correspondence title that can correspondence in history library be out of order, can correspondence go out type of alarm in alarm message according to the fault title, the number of this fault title of statistics can be learnt the summation of the warning frequency of the type in history library; Can in the prediction scheme storehouse, correspondence go out the prediction scheme numbering by qualified content summary, the prediction scheme numbering that goes out according to this correspondence is the corresponding state that goes out this prediction scheme in history library, and the number of times that statistics " finishing " state occurs in history library can be learnt this prediction scheme successful execution number of times.Need to prove, drawing the weight ratio of UR and PR according to experiment and business diagnosis should be between 0.60-0.75, and it is comparatively accurate being preferably the result who drew at 4: 6 o'clock.
When Rs=0, the detailed process of execution in step 13 can be described below:
Step 131: search in described text library with described content and add descriptor corresponding to the above adeditive attribute, obtain the number R of the described descriptor that finds, if R=0, then it fails to match; If R=1, then the match is successful; If R＞1, then execution in step 132;
Step 132: for each content summary in the described prediction scheme storehouse, in described text library, search the common hypernym that described content summary and described content add the above adeditive attribute, and obtain the number C3 of described common hypernym, if C3=0, then it fails to match; If C3＞0, then execution in step 133;
Step 133: obtain the distance C 2 between the described common hypernym, if C2 is not more than the 3rd threshold value, then calculate the prediction scheme reference value of prediction scheme corresponding to qualified described content summary; If C2 is greater than the 3rd threshold value, then execution in step 134;
Step 134: in described text library, search described content and add respectively corresponding polysemant of the above adeditive attribute and described content summary, and obtain the summation C4 of described polysemant, if C4 greater than first threshold, then it fails to match; If C4 is not more than first threshold, then execution in step 135;
Step 135: for each content summary corresponding with described polysemant in the described prediction scheme storehouse, in described text library, search the common hypernym that described content summary and described content add the above adeditive attribute, and obtain distance C 2 between the described common hypernym, if C2 is greater than Second Threshold, then it fails to match; If C2 is not more than Second Threshold, then execution in step 136;
Step 136: the prediction scheme reference value of calculating prediction scheme corresponding to qualified content summary;
Step 131-step 136 belongs to the fuzzy matching process, and the LSA algorithm is adopted in fuzzy matching, finds out a plurality of prediction schemes by this fuzzy matching process.
Step 137: the described prediction scheme reference value of all that will calculate compares and selects prediction scheme corresponding to maximum prediction scheme reference value as the prediction scheme that the match is successful, and the match is successful, execution in step 2.
Step 137 belongs to the exact matching process, selects a prediction scheme conduct prediction scheme that the match is successful in this exact matching process from a plurality of prediction schemes that find out by the fuzzy matching process.
Equally, it should be noted that more than one situation of common hypernym that adds adeditive attribute and content summary for content, select the distance between the minimum common hypernym to compare with the 3rd threshold value or Second Threshold.
The method of wherein calculating the prediction scheme reference value can with reference to aforementioned, repeat no more herein.
Used the forecast model decision tree structure when adopting the LSA algorithm, specifically referring to Fig. 2, decision tree has been explained a kind of tree, and each decision tree can rely on carrying out data test cutting apart of source database.This process can recursion tree is pruned, when the class that can not cut apart again or one is independent can be applied to a certain branch, recursive procedure had just been finished, and adopted prediction model decision tree to mate rapidly.
It should be noted that at last: above embodiment only in order to technical scheme of the present invention to be described, is not intended to limit; Although with reference to previous embodiment the present invention is had been described in detail, those of ordinary skill in the art is to be understood that: it still can be made amendment to the technical scheme that aforementioned each embodiment puts down in writing, and perhaps part technical characterictic wherein is equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution break away from the spirit and scope of various embodiments of the present invention technical scheme.
Claims (7)
1. the method for automatically receiving a crime report of a locomotive failure is characterized in that, comprising:
Step 1: the subject field in the alarm message and the fault title in the history library are mated, and obtain the prediction scheme that the match is successful;
Described step 1 comprises:
Step 11: go out the historical operation record that conforms to described subject field according to described fault title exact-match lookup from described history library, and obtain the number Rs of described historical operation record, if Rs=1, then the match is successful, execution in step 2; If Rs〉1, then execution in step 12; If Rs=0, then execution in step 13;
Step 12: the content in content summary and the described alarm message is added that adeditive attribute carries out fuzzy matching in text library, wherein, described content summary is present in the prediction scheme storehouse, and prediction scheme numbering corresponding to described content summary is same as use prediction scheme numbering corresponding to the fault title corresponding with described subject field, if the match is successful, then execution in step 2;
Step 13: described content is added the above adeditive attribute mate in described text library, if the match is successful, then execution in step 2;
Step 2: information recording/corresponding to prediction scheme that will the match is successful and carried out described prediction scheme in described history library;
Step 3: the execution result of described prediction scheme is recorded to status bar corresponding with described prediction scheme in the described history library.
2. the method for automatically receiving a crime report according to claim 1 is characterized in that, described step 12 comprises:
Step 121: for each content summary, search the common hypernym that described content adds the above adeditive attribute and described content summary in described text library, and obtain the number C3 of described common hypernym, if C3=0, then it fails to match; If C3〉0, then execution in step 122;
Step 122: obtain the distance C 2 between the described common hypernym, if C2 is not more than the 3rd threshold value, then calculate the prediction scheme reference value of prediction scheme corresponding to qualified described content summary; If C2 is greater than the 3rd threshold value, then execution in step 123;
Step 123: in described text library, search described content and add respectively corresponding polysemant of the above adeditive attribute and described content summary, and obtain the summation C4 of described polysemant, if C4 greater than first threshold, then it fails to match; If C4 is not more than first threshold, then execution in step 124;
Step 124: for each content summary corresponding with described polysemant in the described prediction scheme storehouse, in described text library, search the common hypernym that described content adds the above adeditive attribute and described content summary, and obtain distance C 2 between the described common hypernym, if C2 is greater than Second Threshold, then it fails to match; If C2 is not more than Second Threshold, then execution in step 125;
Step 125: the prediction scheme reference value of calculating prediction scheme corresponding to qualified content summary;
Step 126: the described prediction scheme reference value of all that will calculate compares and selects prediction scheme corresponding to maximum prediction scheme reference value as the prediction scheme that the match is successful, and the match is successful, execution in step 2.
3. the method for automatically receiving a crime report according to claim 1 is characterized in that, described step 13 comprises:
Step 131: search in described text library with described content and add descriptor corresponding to the above adeditive attribute, obtain the number R of the described descriptor that finds, if R=0, then it fails to match; If R=1, then the match is successful; If R〉1, then execution in step 132;
Step 132: for each content summary in the described prediction scheme storehouse, search the common hypernym that described content summary and described content add the above adeditive attribute in described text library, and obtain the number C3 of described common hypernym, if C3=0, then it fails to match; If C3〉0, then execution in step 133;
Step 133: obtain the distance C 2 between the described common hypernym, if C2 is not more than the 3rd threshold value, then calculate the prediction scheme reference value of prediction scheme corresponding to qualified described content summary; If C2 is greater than the 3rd threshold value, then execution in step 134;
Step 134: in described text library, search described content and add respectively corresponding polysemant of the above adeditive attribute and described content summary, and obtain the summation C4 of described polysemant, if C4 greater than first threshold, then it fails to match; If C4 is not more than first threshold, then execution in step 135;
Step 135: for each content summary corresponding with described polysemant in the described prediction scheme storehouse, in described text library, search the common hypernym that described content summary and described content add the above adeditive attribute, and obtain distance C 2 between the described common hypernym, if C2 is greater than Second Threshold, then it fails to match; If C2 is not more than Second Threshold, then execution in step 136;
Step 136: the prediction scheme reference value of calculating prediction scheme corresponding to qualified content summary;
Step 137: the described prediction scheme reference value of all that will calculate compares and selects prediction scheme corresponding to maximum prediction scheme reference value as the prediction scheme that the match is successful, and the match is successful, execution in step 2.
4. according to claim 2 or the 3 described methods of automatically receiving a crime report, it is characterized in that, calculate described prediction scheme reference value: RV=0.4*UR+0.6*PR according to following rule, wherein, RV is described prediction scheme reference value, and UR is the prediction scheme frequency of utilization, and PR is the accurate implementation rate of prediction scheme, UR=(summation of these prediction scheme access times/the type warning frequency) * 100%, PR=(this prediction scheme successful execution number of times/these prediction scheme access times) * 100%.
5. according to claim 2 or the 3 described methods of automatically receiving a crime report, it is characterized in that, described first threshold is 8.
6. according to claim 2 or the 3 described methods of automatically receiving a crime report, it is characterized in that, described Second Threshold is 5.
7. according to claim 2 or the 3 described methods of automatically receiving a crime report, it is characterized in that, described the 3rd threshold value is 2.
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| CN106274991A (en) * | 2016-08-23 | 2017-01-04 | 四川网达科技有限公司 | Railway fail analysis device and method |
| CN110275992B (en) * | 2019-05-17 | 2023-08-29 | 创新先进技术有限公司 | Emergency processing method, device, server and computer readable storage medium |
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