CN109558590A - A kind of critical failure device localization method based on spacecraft telemetry parameter participle - Google Patents

A kind of critical failure device localization method based on spacecraft telemetry parameter participle Download PDF

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CN109558590A
CN109558590A CN201811405302.1A CN201811405302A CN109558590A CN 109558590 A CN109558590 A CN 109558590A CN 201811405302 A CN201811405302 A CN 201811405302A CN 109558590 A CN109558590 A CN 109558590A
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parameter
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telemetry parameter
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CN109558590B (en
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付枫
李卫平
李涵秋
高宇
李辉
郭小红
袁线
秦勃
程富强
白大明
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63789 Army Of Chinese People's Liberation Army
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G06F40/284—Lexical analysis, e.g. tokenisation or collocates
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y04S10/52—Outage or fault management, e.g. fault detection or location

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Abstract

The present invention provides a kind of critical failure device localization methods based on spacecraft telemetry parameter participle, each abnormal telemetry parameter is segmented as device name, four device description, detection type and additional notes parts, the device name of all abnormal telemetry parameters and detection type part are subjected to class statistic again, frequent item set is obtained, as critical failure device.This method only needs to define the detection type keyword of few quantity, improves personnel for the analysis efficiency and accuracy of spacecraft warning message, the personnel that not only improve describe abnormal phenomenon clearly, and are advantageously implemented the analyzing and positioning of critical failure device.

Description

A kind of critical failure device localization method based on spacecraft telemetry parameter participle
Technical field
The present invention relates to a kind of spacecraft critical failure device localization methods, belong to spacecraft fault diagnosis analysis field.
Background technique
With the continuous development of space technology, the function of spacecraft is increasingly sophisticated, and new device is increasing, and needs simultaneously Corresponding monitoring point is set, and collection analysis judges device state, could find device exception in time, and effective guarantee spacecraft is in-orbit The smooth development of safe and stable operation and task.The telemetry parameter quantity of spacecraft is up to ten thousand grades, and the degree of coupling is high between device, in appearance When state or the energy are abnormal, the warning message for generating dozens or even hundreds of related telemetry parameter can frequently result in.
The analyzing and positioning failure Primary Component in a large amount of warning messages at present, manually completes by systems analyst, exists It takes a long time, rely on the problem of experience, be unable to satisfy the timeliness and accuracy requirement of Spacecraft anomaly positioning disposition.
Summary of the invention
For overcome the deficiencies in the prior art, the present invention provides a kind of critical failure based on spacecraft telemetry parameter participle Abnormal telemetry parameter is carried out word segmentation processing, then all telemetry parameter word segmentation results is carried out cluster system by device localization method Meter obtains the frequent abnormal device in warning message, completes the positioning of critical failure device, improve defective device positioning Accuracy and efficiency.
The technical solution adopted by the present invention to solve the technical problems includes the following steps:
Step 1, fault alarm information is acquired, single fault alarm information is { paraName:msg }, wherein paraName For the parameter name of failure telemetry parameter, msg is type of alarm, and value is the super upper limit or super lower limit；All warning message compositions Set detectionSet={ paraName1:msg1,paraName2:msg2,…,paraNamen:msgn, total n alarm signal Breath；
Step 2, the detection type paid close attention to will be needed to be defined as dictionary sequence dict=[type1,type2,…,typem], Total m kind detection type；
Step 3, using alarm telemetry parameter information and detection type dictionary, to each telemetry parameter according to " device name, Device description, detection type, additional notes " carries out participle cutting, and each telemetry parameter includes at least device name, first distinguishes Then detection type and additional notes distinguish device name and device description；
Step 4, word segmentation result is counted and is sorted, determine frequent defective device and frequent fault type.
The detection type of the telemetry parameter includes but is not limited to power, temperature, voltage, electric current, error, number and shape State.
The dictionary sequence dict=[type1,type2,…,typem] in each detection type according to string length Descending arrangement.
In the step 3, the character string of single telemetry parameter title is paraNamei=[a1,a2,..,apL], 1≤i ≤ n, pL are string length；Search for paraNameiIn whether a certain item in containing type dictionary, if containing type typej, 1≤j≤m, in paraNameiIn starting position be stypej, end position etypej, then parameter paraNamei's Detection type segments part typeParti=typej, parameter paraNameiDevice name and device description participle part elementParti=paraNamei[1:stypej], parameter paraNameiAdditional notes segment part detailParti= paraNamei[etypej:pL]；If not including any type in dictionary, typeParti=" ", elementParti= paraNamei, detailParti=" ".
In the step 3,1) the participle cutting of device name and device description is the following steps are included: be arranged current cutting Starting position cutStartPos=0, current cutting end position cutEndPos=cutStartPos+1；2) segmenting word is defined Variable 1 is cutWord1=elementParti[cutStartPos:cutEndPos -1], segmenting word variable 2 are cutWord2= elementParti[cutStartPos:cutEndPos]；3) searchResult is defined1For ginsengs all in detectionSet Several titles search cutWord1The sequence vector that starting position is formed, if cutWord does not occur in certain parameter1The value is -1；4) Define searchResult2CutWord is searched for parameter names all in detectionSet2The vector sequence that starting position is formed Column, if cutWord does not occur in certain parameter2The value is -1；If 5) searchResult1With searchResult2Complete phase Together, then it updates cutEndPos value and adds 1,2) return repeats the above process until cutEndPos is greater than stypej；If 6) searchResult1Not equal to searchResult2, obtain parameter paraNameiDevice name word segmentation result elementNameParti=elementParti[cutStartPos:cutEndPos-1], parameter paraNameiDevice retouch State word segmentation result elementDetailParti=elementParti[cutEndPos:stypej]。
In the step 3, telemetry parameter paraNameiWord segmentation result be [elementNameParti, elementDetailParti,typeParti,detailParti], all telemetry parameters in detectionSet are all carried out Cutting is segmented, word segmentation result sequence partsResult=[[elementNamePart is obtained1,…,elementNamePartn], [elementDetailPart1,…,elementDetailPartn],[typePart1,…,typePartn], [detailPart1,…,detailPartn]]。
In the step 4, by [elementNamePart in word segmentation result sequence partsResult1,…, elementNamePartn] all progresss counting statistics occurring, and descending arrangement is carried out according to count number, it obtains frequent Defective device statistics set partsSet={ elementNamePart1:eCount1,…,elementNamePartp: eCountp}；By [typePart in partsResult1,…,typePartn] all progress counting statistics occurring, and it presses Descending arrangement is carried out according to count number, obtains frequent fault type statistics set typesSet={ typePart1: tCount1,…,typePartq:tCountq}。
The beneficial effects of the present invention are: overcome it is existing based on probability Chinese word cutting method cutting telemetry parameter when effect according to It is poor to everyday words accuracy of identification in the merging of design parameter collection to rely, and needs when the Chinese word cutting method cutting telemetry parameter based on dictionary The shortcomings that defining a large amount of keywords, by by each telemetry parameter according to " device name, [device description], [detection type], [additional notes] " carry out participle cutting, it is only necessary to define the detection type keyword of few quantity, and by first distinguishing " [inspection Survey type], [additional notes] ", the secondary participle process of " device name, [device description] " is then distinguished, telemetry parameter is completed Participle.It is handled simultaneously by participle to a large amount of fault alarm telemetry parameters and statistic of classification, improves personnel for space flight The analysis efficiency and accuracy of device warning message.The frequent defective device collection and frequent fault type collection listed, can help desk personnel Effective position critical failure device improves fault location ability.
Detailed description of the invention
Fig. 1 is flow chart of the invention；
Fig. 2 is the schematic diagram of application case of the present invention.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples, and the present invention includes but are not limited to following implementations Example.
The present invention provides a kind of critical failure device localization methods based on spacecraft telemetry parameter participle, will be each different Normal telemetry parameter participle is device name, four device description, detection type and additional notes parts, then by all abnormal telemeterings The device name of parameter and detection type part carry out class statistic, frequent item set are obtained, as critical failure device.This method It not only improves personnel and describes abnormal phenomenon clearly, and be advantageously implemented the analyzing and positioning of critical failure device.
As shown in Figure 1, the method specifically includes following steps:
Step 1: the definition of fault alarm information acquisition and detection type dictionary；
Step 2: the participle cutting of failure telemetry parameter；
Step 3: the statistical analysis of critical failure device.
The first step as described above specifically comprises the following steps:
Step 1.1: fault alarm information is collected.Single warning message is { paraName:msg }, and wherein paraName is The parameter name of failure telemetry parameter, msg are type of alarm, and value is the super upper limit or super lower limit.All warning message composition collection Close detectionSet={ paraName1:msg1,paraName2:msg2,…,paraNamen:msgn, total n alarm signal Breath.
Step 1.2: the definition of detection type dictionary.The detection class of the telemetry parameter can be indicated in telemetry parameter title Type, including " power ", " temperature ", " voltage ", " electric current ", " error ", " number ", " state ", the detection type that needs are paid close attention to It is defined as dictionary sequence dict=[type1,type2,…,typem], total m kind detection type, and by items therein according to word Accord with the descending arrangement of string length.
Second step as described above includes the following steps:
Using alarm telemetry parameter information and detection type dictionary, participle cutting is carried out to each telemetry parameter.Each is distant It surveys parameter and carries out participle cutting according to " device name, [device description], [detection type], [additional notes] ", rear three parts are all It is option, both each telemetry parameter centainly included device name, and selection includes latter three.Specific step is as follows:
Step 2.1: the participle cutting of detection type and additional notes part in individual event telemetry parameter.Single telemetry parameter name Character string be referred to as paraNamei=[a1,a2,..,apL], 1≤i≤n, pL are string length.Search for paraNameiIn be A certain item in no containing type dictionary, if containing type typej, 1≤j≤m, in paraNameiIn starting position be stypej, end position etypej, then parameter paraNameiDetection type segment part typeParti=typej, parameter paraNameiDevice name and device description participle part elementParti=paraNamei[1:stypej], parameter paraNameiAdditional notes segment part detailParti=paraNamei[etypej:pL]；If do not included in dictionary Any type, then typeParti=" ", elementParti=paraNamei, detailParti=" ".
Step 2.2: the participle cutting of device name and device description section in individual event telemetry parameter.1) current cutting is set Starting position cutStartPos=0, current cutting end position cutEndPos=cutStartPos+1；2) segmenting word variable 1 For cutWord1=elementParti[cutStartPos:cutEndPos -1], segmenting word variable 2 are cutWord2= elementParti[cutStartPos:cutEndPos]；3)searchResult1For parameter names all in detectionSet Claim to search cutWord1The sequence vector that starting position is formed, if cutWord does not occur in certain parameter1The value is -1；4) searchResult2CutWord is searched for parameter names all in detectionSet2The sequence vector that starting position is formed, such as There is not cutWord in fruit parameter2The value is -1；If 5) searchResult1With searchResult2It is identical, then CutEndPos=cutEndPos+1 is updated, 2) return repeats the above process until cutEndPos is greater than stypej；If 6) searchResult1Not equal to searchResult2, obtain parameter paraNameiDevice name word segmentation result elementNameParti=elementParti[cutStartPos:cutEndPos-1], parameter paraNameiDevice retouch State word segmentation result elementDetailParti=elementParti[cutEndPos:stypej]。
Step 2.3: the collection of telemetry parameter word segmentation result.Telemetry parameter paraNameiWord segmentation result be [elementNameParti,elementDetailParti,typeParti,detailParti], in detectionSet All telemetry parameters all carry out participle cutting, obtain word segmentation result sequence partsResult= [[elementNamePart1,…,elementNamePartn],[elementDetailPart1,…, elementDetailPartn],[typePart1,…,typePartn],[detailPart1,…,detailPartn]]。
Third step as described above includes the following steps:
The statistical analysis of frequent alarm appliance is carried out using the calculated word segmentation result of previous step, the specific steps are as follows:
Step 3.1: frequent defective device statistics.It will be in word segmentation result sequence partsResult [elementNamePart1,…,elementNamePartn] all progress counting statistics occurring, and according to count number Descending arrangement is carried out, set partsSet={ elementNamePart is obtained1:eCount1,…,elementNamePartp: eCountp}。
Step 3.2: frequent fault type statistics.By [typePart in partsResult1,…,typePartn] occur All progress counting statistics, and descending arrangement is carried out according to count number, obtain detection type participle set typesSet= {typePart1:tCount1,…,typePartq:tCountq}。
Referring to Fig. 2, application case of the present invention is divided into three key steps:
1) definition of fault alarm information acquisition and detection type dictionary.8 fault alarm letters are listed in Fig. 2 first step Breath, quantity of alarming in practical applications are far longer than the quantity, this example is only used as method flow to illustrate.The first step needs simultaneously User defined type dictionary defines the typical telemetry parameter type such as temperature, voltage, electric current in Fig. 2.
2) the participle cutting of failure telemetry parameter.Completed first by type dictionary in telemetry parameter title detection type and Then the participle of additional notes part completes the participle of device name and device description section.The participle of 8 alarm telemetry parameters As a result as shown in second step in Fig. 2, each segment uses between part ", " separate.
3) statistical analysis of critical failure device.Respectively to device name and detection type in faulty telemetry parameter Part is counted, and frequent defective device set and frequent fault type set are obtained, as shown in third step in Fig. 2,8 alarms The Primary Component of information is " southern battery group " and " UHF power amplifier ", and major failure type is " temperature ".
In conclusion the present invention provides a kind of critical failure device positioning sides based on spacecraft telemetry parameter participle Method.Solve it is existing in a large amount of fault alarm informations, it is inefficient caused by personnel's manual analyzing critical failure device, The technical issues of accuracy is difficult to ensure.

Claims (7)

1. a kind of critical failure device localization method based on spacecraft telemetry parameter participle, it is characterised in that including following steps It is rapid:
Step 1, fault alarm information is acquired, single fault alarm information is { paraName:msg }, and wherein paraName is event Hinder the parameter name of telemetry parameter, msg is type of alarm, and value is the super upper limit or super lower limit；All warning message composition set DetectionSet={ paraName1:msg1,paraName2:msg2,…,paraNamen:msgn, total n warning message；
Step 2, the detection type paid close attention to will be needed to be defined as dictionary sequence dict=[type1,type2,…,typem], total m kind Detection type；
Step 3, using alarm telemetry parameter information and detection type dictionary, to each telemetry parameter according to " device name, device Description, detection type, additional notes " carries out participle cutting, and each telemetry parameter includes at least device name, first distinguishes detection Then type and additional notes distinguish device name and device description；
Step 4, word segmentation result is counted and is sorted, determine frequent defective device and frequent fault type.
2. the critical failure device localization method according to claim 1 based on spacecraft telemetry parameter participle, feature Be: the detection type of the telemetry parameter includes but is not limited to power, temperature, voltage, electric current, error, number and state.
3. the critical failure device localization method according to claim 1 based on spacecraft telemetry parameter participle, feature It is: the dictionary sequence dict=[type1,type2,…,typem] in each detection type according to string length drop Sequence arrangement.
4. the critical failure device localization method according to claim 1 based on spacecraft telemetry parameter participle, feature Be: in the step 3, the character string of single telemetry parameter title is paraNamei=[a1,a2,..,apL], 1≤i≤n, PL is string length；Search for paraNameiIn whether a certain item in containing type dictionary, if containing type typej, 1≤ J≤m, in paraNameiIn starting position be stypej, end position etypej, then parameter paraNameiDetection type point Word part typeParti=typej, parameter paraNameiDevice name and device description participle part elementParti= paraNamei[1:stypej], parameter paraNameiAdditional notes segment part detailParti=paraNamei[etypej: pL]；If not including any type in dictionary, typeParti=" ", elementParti=paraNamei, detailParti=" ".
5. the critical failure device localization method according to claim 1 based on spacecraft telemetry parameter participle, feature Be: in the step 3, the participle cutting of device name and device description is opened the following steps are included: current cutting 1) is arranged Beginning position cutStartPos=0, current cutting end position cutEndPos=cutStartPos+1；2) segmenting word is defined to become Amount 1 is cutWord1=elementParti[cutStartPos:cutEndPos -1], segmenting word variable 2 are cutWord2= elementParti[cutStartPos:cutEndPos]；3) searchResult is defined1For ginsengs all in detectionSet Several titles search cutWord1The sequence vector that starting position is formed, if cutWord does not occur in certain parameter1The value is -1；4) Define searchResult2CutWord is searched for parameter names all in detectionSet2The vector sequence that starting position is formed Column, if cutWord does not occur in certain parameter2The value is -1；If 5) searchResult1With searchResult2Complete phase Together, then it updates cutEndPos value and adds 1,2) return repeats the above process until cutEndPos is greater than stypej；If 6) searchResult1Not equal to searchResult2, obtain parameter paraNameiDevice name word segmentation result elementNameParti=elementParti[cutStartPos:cutEndPos-1], parameter paraNameiDevice retouch State word segmentation result elementDetailParti=elementParti[cutEndPos:stypej]。
6. the critical failure device localization method according to claim 1 based on spacecraft telemetry parameter participle, feature It is: in the step 3, telemetry parameter paraNameiWord segmentation result be [elementNameParti, elementDetailParti,typeParti,detailParti], all telemetry parameters in detectionSet are all carried out Cutting is segmented, word segmentation result sequence partsResult=[[elementNamePart is obtained1,…,elementNamePartn], [elementDetailPart1,…,elementDetailPartn],[typePart1,…,typePartn], [detailPart1,…,detailPartn]]。
7. the critical failure device localization method according to claim 1 based on spacecraft telemetry parameter participle, feature It is: in the step 4, by [elementNamePart in word segmentation result sequence partsResult1,…, elementNamePartn] all progresss counting statistics occurring, and descending arrangement is carried out according to count number, it obtains frequent Defective device statistics set partsSet={ elementNamePart1:eCount1,…,elementNamePartp: eCountp}；By [typePart in partsResult1,…,typePartn] all progress counting statistics occurring, and it presses Descending arrangement is carried out according to count number, obtains frequent fault type statistics set typesSet={ typePart1: tCount1,…,typePartq:tCountq}。
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CN108478926A (en) * 2018-05-02 2018-09-04 清华大学深圳研究生院 The method that the wearable device of body temperature can be automatically adjusted and adjust body temperature
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1601969A (en) * 2003-09-24 2005-03-30 华为技术有限公司 Information analytical method for facility configuration
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