CN110276509A - Subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity - Google Patents
Subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity Download PDFInfo
- Publication number
- CN110276509A CN110276509A CN201910164981.6A CN201910164981A CN110276509A CN 110276509 A CN110276509 A CN 110276509A CN 201910164981 A CN201910164981 A CN 201910164981A CN 110276509 A CN110276509 A CN 110276509A
- Authority
- CN
- China
- Prior art keywords
- risk
- probability
- traction
- subway train
- assessment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000012502 risk assessment Methods 0.000 title claims abstract description 44
- 239000003990 capacitor Substances 0.000 claims abstract description 38
- 238000004458 analytical method Methods 0.000 claims abstract description 20
- 230000008859 change Effects 0.000 claims abstract description 14
- 238000012544 monitoring process Methods 0.000 claims abstract description 8
- 238000010586 diagram Methods 0.000 claims abstract description 7
- 230000006378 damage Effects 0.000 claims description 30
- 239000011159 matrix material Substances 0.000 claims description 18
- 238000012423 maintenance Methods 0.000 claims description 16
- 238000011156 evaluation Methods 0.000 claims description 13
- 238000004364 calculation method Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 8
- 208000027418 Wounds and injury Diseases 0.000 claims description 6
- 230000005611 electricity Effects 0.000 claims description 6
- 230000008439 repair process Effects 0.000 claims description 6
- 230000002159 abnormal effect Effects 0.000 claims description 5
- 230000015556 catabolic process Effects 0.000 claims description 5
- 230000007257 malfunction Effects 0.000 claims description 5
- 238000011835 investigation Methods 0.000 claims description 4
- 230000007774 longterm Effects 0.000 claims description 4
- 238000011158 quantitative evaluation Methods 0.000 claims description 4
- 230000008929 regeneration Effects 0.000 claims description 4
- 238000011069 regeneration method Methods 0.000 claims description 4
- 208000037974 severe injury Diseases 0.000 claims description 4
- 230000015572 biosynthetic process Effects 0.000 claims description 3
- 238000003786 synthesis reaction Methods 0.000 claims description 3
- 238000012512 characterization method Methods 0.000 claims description 2
- 238000007689 inspection Methods 0.000 claims description 2
- 238000013139 quantization Methods 0.000 claims description 2
- 238000000926 separation method Methods 0.000 claims description 2
- 230000009528 severe injury Effects 0.000 claims description 2
- 230000003862 health status Effects 0.000 abstract description 2
- 238000004891 communication Methods 0.000 description 9
- 230000000875 corresponding effect Effects 0.000 description 9
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 6
- 230000000694 effects Effects 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 229910052742 iron Inorganic materials 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 208000014674 injury Diseases 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 208000019901 Anxiety disease Diseases 0.000 description 1
- 241000208340 Araliaceae Species 0.000 description 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000036506 anxiety Effects 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 235000008434 ginseng Nutrition 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002401 inhibitory effect Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000644 propagated effect Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000012955 system risk analysis Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Databases & Information Systems (AREA)
- Entrepreneurship & Innovation (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Algebra (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
- Development Economics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Probability & Statistics with Applications (AREA)
- Computing Systems (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Educational Administration (AREA)
Abstract
The subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity that the present invention relates to a kind of, includes at least: S1, the monitoring of subway train trailer system acquire the data of each vehicle and equipment in real time；S2, the data based on acquisition establish metro traction system typical case's risk chain, establish capacitive faults rate with capacitor equivalent series resistance variation diagram and traction motor failure rate with motor oscillating change curve；The data that S3, foundation detect, the equivalent series resistance R of dynamic statistics t moment traction invertorESR, motor oscillating earthquake intensity L calculate capacitor real time fail probability P and according to capacitive faults rate with capacitor equivalent series resistance modified-imaget1；According to traction motor failure rate with motor oscillating change curve, electrical fault probability P is calculatedt2；S4, t moment is acquired because of risk chain probability of happening P typical under inverter Support Capacitor fault conditiont.This method can make the analysis assessment of real-time quantitative to trailer system health status, find the running safe weak link of system in time.
Description
Technical field
The present invention relates to the risk analysis technologies of electric power supply system for subway, and in particular to a kind of subway train based on characteristic quantity
Trailer system dynamic risk analysis appraisal procedure.
Background technique
With the rapid development of Regional Rail Transit, a large amount of railcar route constantly puts into effect, subway circulation
Potential risk hazards identification also constantly increasing.Traction inversion system in electric power supply system for subway is the safe and stable fortune of train
Capable key, traction inversion system once break down, it is possible to cause car crash, lead to huge life, property loss.
Therefore, the risk assessment for drawing inversion system finds the weak link of operating system as early as possible, and then ties up to the maintenance for instructing train
It repairs and is of great significance.The technology content and complexity of railcar are higher and higher simultaneously, keep the failure risk of trailer system special
Property presents the kinds of risks feature such as obvious hierarchy, propagated, non-linear, ambiguity, and traditional risk analysis has been difficult to
Meet reality to the needs of railcar trailer system security evaluation.
The premise of risk assessment is the accurate understanding to risk intension, it is considered that risk assessment is built upon Risk Identification
On the basis of, by analyzing, both the uncertain probability for damaging state of affairs generation and corresponding severity degree are comprehensive to complete relevant risk
Assessment.Lot of domestic and foreign scholar has done considerable degree of research about system risk analysis, but is based on relevant device mostly
Historical data carry out traditional risk analysis assessment.Mature method is less in terms of system dynamic risk analysis, at present base
It is deep not enough in the risk assessment correlative study of characteristic quantity.
Subway train trailer system fault type is various and interrelated, and different faults will cause along Risk of Communication chain
Different failure effect, the extent of injury may also differ widely, and risk analysis and assessment are more and more difficult.In addition, failure shadow
It rings since directly affecting to subsequent indirect influence, is the process gradually changed.If lacking the detailed of failure impact evaluation
Thin scene is ignored the propagation change procedure that analysis causes failure, is then just lacked to the severity evaluation result that failure impacts
Systematicness, it is difficult to which it is objective, accurate to accomplish.Corresponding with above-mentioned traditional static risk analysis, applicant puts forth effort on risk analysis
Dynamic studies, due to the dynamic risk analysis based on Risk Chain it is emphasised that risk probability state becomes with spatial variations at any time
The feature of change, therefore the analysis assessment of real-time quantitative can be made to trailer system health status, it is found in system operation in time
Safe weak link block risk and subsequent rationally risk blocked to pass using engineering measure to be optimal control risk source
It broadcasts chain and lays theoretical basis, the safe and efficient operation of rail traffic, which has, to be guaranteed to the failure accident that reduction causes by railcar
Significance.
Summary of the invention
The purpose of the present invention metro traction system risk assess there are aiming at the problem that, propose a kind of ground based on characteristic quantity
Iron train traction system dynamic risk analysis appraisal procedure, this method selection typical fault establish Risk of Communication chain, pass through event
Hinder the dynamic CALCULATION OF FAILURE PROBABILITY for determining Risk of Communication chain of analysis of mechanism, and combines the specific feelings of metro accidents O&M
Condition sets reasonable maintenance and loss index by clustering and completes failure effect analysis of severity, finally combines the two
Complete the dynamic risk analysis assessment based on risk chain.
To achieve the above object, the technical scheme adopted by the invention is that a kind of subway train based on characteristic quantity draws system
System dynamic risk analysis appraisal procedure, includes at least:
S1, the monitoring of subway train trailer system acquire the data of the acquisition of each vehicle and equipment in real time, including draw inverse
Become condenser voltage, inverter output current, DC loop current, braking resistor chopper current and the motor oscillating of device front end
Earthquake intensity, and the data of acquisition are uploaded to assessment system；
S2, system establish metro traction system typical case's risk chain based on the data of acquisition, while establishing capacitive faults rate
With capacitor equivalent series resistance variation diagram and traction motor failure rate with motor oscillating change curve；
The data that S3, foundation detect, the equivalent series resistance R of dynamic statistics t moment traction invertorESR, motor oscillating it is strong
L is spent, and calculates capacitor real time fail probability P with capacitor equivalent series resistance modified-image according to capacitive faults ratet1；According to leading
Draw electrical fault rate with motor oscillating change curve, calculates electrical fault probability Pt2；
S4, t moment is acquired according to formula 1 because of risk chain probability of happening typical under inverter Support Capacitor fault condition
Pt, that is, complete the probability of malfunction dynamic analysis of typical risk chain；
Wherein, formula (1) are as follows: Pt=Pt1×Pt2。
Further, the particular content of metro traction system typical case's risk chain in the S2 are as follows:
1) long-term temperature it is excessively high and it is filthy cause traction invertor front support capacitance to become smaller, capacitor equivalent series electricity
Resistance value increases, and regeneration brake system front end inverter voltage increases when emergency braking, the breakdown short circuit of traction invertor charging capacitor；
2) a large amount of higher hamonic waves that traction invertor outlet side voltage waveform contains make output waveform distortion degree become larger, with
The abnormal raising of its connected traction electric machine torque unstability, asynchronous machine running temperature, motor oscillating earthquake intensity L are excessive, make asynchronous
Traction motor failure probability increases.
The present invention is based on the subway train trailer system dynamic risk analysis appraisal procedures of characteristic quantity on the other hand also to assess
Damage sequence severity obtains risk class to combine above scheme to carry out comprehensive assessment.Specifically, the method also includes
S5, the event that traction electric machine when burning fault occurs for subway train traction electric machine burns consequence is established according to investigation
Tree, the probability and consequence that various accidents caused by the event tree characterization electric driving machinery of subway is burnt occur；
S6, establish subway train damage sequence severity assessment indicator system, the system include capacity loss, repair at
Sheet, social influence, each index value of human loss；Capacity loss, maintenance are obtained with analytic hierarchy process (AHP) by expert estimation simultaneously
The weight that cost, social influence, each factor of human loss influence damage sequence severity；
S7, the m kind accident in event tree is calculated by clustering method for the grey power assessment square of each index value
Battle array, the grey power evaluating matrix is multiplied with index weights obtains sequence severity comprehensive assessment vector, then passes through the consequence
Comprehensive damage sequence caused by severity grey evaluation vector calculation risk chain is seriously worth；
S8, quantitative evaluation is seriously worth according to the typical risk chain probability of happening of S4 and the synthesis damage sequence of S7, obtained
Risk class.
The method of the present invention has analysed in depth subway train trailer system failure machine, and selects typical fault event establishment related
Risk of Communication chain calculates typical case's risk chain probability of malfunction value by the Fault Mechanism Analysis of dynamic risk chain.Its
It is secondary to establish index of security assessment with event tree and the method for clustering, before completing because of subway train trailer system inverter
The dynamic risk chain of traction electric machine burning fault is caused to cause the accident sequence severity under the conditions of the Support Capacitor puncture short of end
Analysis.And example risk assessment has been carried out by taking Type B subway train as an example, then provide corresponding subway train maintenance suggestion.
The analysis assessment of the dynamic risk level to break down by subway train trailer system internal structure may be implemented in the method, and is
The timely blocking of relevant risk chain is provided fundamental basis.
Detailed description of the invention
To describe the technical solutions in the embodiments of the present invention more clearly, make required in being described below to embodiment
Attached drawing is briefly introduced, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this
For the those of ordinary skill in field, without creative efforts, others can be also obtained according to these attached drawings
Attached drawing.
Fig. 1 is train traction system main circuit structure figure；
Fig. 2 is the main circuit topological structure that subway train draws inversion unit；
Fig. 3 is a kind of embodiment schematic diagram of the method for the present invention；
Fig. 4 is metro traction system typical case risk chain schematic diagram of the present invention；
Fig. 5 is trend chart of the electrolytic capacitor under harsh environments in damage process with capacitive faults rate；
Fig. 6 is traction motor failure rate with motor oscillating variation relation figure；
Fig. 7 is the another embodiment schematic diagram of the method for the present invention；
Fig. 8 is the event tree graph that traction electric machine burns consequence；
Fig. 9 is subway train damage sequence severity assessment indicator system structure chart.
Specific embodiment
In order to which the purpose, technical solution and beneficial effect of the application is more clearly understood, below in conjunction with attached drawing and implementation
The application is further described in example.It should be appreciated that specific embodiment described herein is only used to explain the application,
It is not used to limit the application.
Before understanding the present application main points, the trailer system overall structure of subway train need to be first understood.Common subway
Train generally uses the power decentralized type of six make-up type 4M2T to configure, and DC1500V standard overhead contact line pantograph is flowed
Mode.Railcar traction drive constitutes alternating-current actuating system against device-asynchronous traction motor using VVVF, and the traction is inverse
Change system generally uses the structure of 3 electrical level inverters to carry out variable voltage variable frequency.Train traction system main circuit as shown in Figure 1,
The DC1500V voltage of its contact net flows through pantograph and is sent to VVVF using high-voltage electrical box, preliminary filling resistance, feed(er) reactor
Inverter, copped wave unit and inversion unit output voltage and the adjustable three-phase alternating current of frequency by three-phase inverter, with this
Drive the operating of asynchronous traction motor (M01-M04), the power of traction electric machine output is transmitted to wheel to driving train operation.Ground
It placed the state of many voltage-current sensor moment monitoring railcar electrical systems in iron car traction drive,
Middle voltage sensor VH1 detects direct current network pressure, and voltage sensor VH2 detects condenser voltage on inverter, current sensor
LH1 and LH2 detection DC loop current, current sensor LH3 and LH4 detection inverter output current, current sensor LH5,
LH6 detects braking resistor chopper current.The monitoring to metro traction system running state in real time is completed by detection system, entirely
Electric energy transmitting transformation system is the overall structure of subway train trailer system.
Dynamic risk analysis research based on metro traction system finds the traction inversion unit of metro traction system and leads
Drawing electric motor units is main failure risk, chooses inversion unit failure and establishes reasonable Risk of Communication chain.With Fig. 2 shows ground
For the main circuit topological structure of iron train traction inversion unit, three level voltage types are used directly to hand over inverter circuit, subway is led
Draw inverter to be in for a long time in severe working environment, inverter Support Capacitor in hot environment and is easy to be covered with big
The greasy dirt of amount.Long-term temperature is excessively high and filthy is easy to cause traction invertor front support capacitance to become smaller then to show as capacitor
Device equivalent series impedance increases, and regeneration brake system front end inverter voltage increases when emergency braking, traction invertor occurs and fills
The breakdown short circuit condition of capacitor.At this moment its traction invertor outlet side voltage waveform, which contains a large amount of higher hamonic waves, makes output waveform
Distortion degree becomes larger, and leads to the abnormal raising of coupled traction electric machine torque unstability, asynchronous machine running temperature, motor vibration
Dynamic earthquake intensity L is excessive, significantly increases asynchronous traction motor probability of malfunction.It causes subway late when serious or stops transport, to entire area
Domain rail traffic safe operation has an adverse effect.
Based on above-mentioned analysis, the present invention proposes the subway train trailer system dynamic risk analysis assessment side based on characteristic quantity
Method, this method metro traction system risk assess there are aiming at the problem that, select typical fault establish Risk of Communication chain, pass through
The dynamic analysis that failure mechanism extracts correlated characteristic amount determine the CALCULATION OF FAILURE PROBABILITY of Risk of Communication chain.It is specific as shown in figure 3,
The method includes the following steps:
S1, the monitoring of subway train trailer system acquire the data of the acquisition of each vehicle and equipment in real time, including draw inverse
Become condenser voltage, inverter output current, DC loop current, braking resistor chopper current and the motor oscillating of device front end
Earthquake intensity, and the data of acquisition are uploaded to assessment system；
S2, system establish metro traction system typical case's risk chain based on the data of acquisition, while establishing capacitive faults rate
With capacitor equivalent series resistance variation diagram and traction motor failure rate with motor oscillating change curve；
Wherein, as shown in figure 4, the particular content of the metro traction system typical case risk chain are as follows:
1) long-term temperature it is excessively high and it is filthy cause traction invertor front support capacitance to become smaller, capacitor equivalent series electricity
Resistance value increases, and regeneration brake system front end inverter voltage increases when emergency braking, the breakdown short circuit of traction invertor charging capacitor；
2) a large amount of higher hamonic waves that traction invertor outlet side voltage waveform contains make output waveform distortion degree become larger, with
The abnormal raising of its connected traction electric machine torque unstability, asynchronous machine running temperature, motor oscillating earthquake intensity L are excessive, make asynchronous
Traction motor failure probability increases.
Accordingly it is found that there are two entire risk chain Observable failure operation characteristic quantities, observable feature amount 1 is reaction
The capacitor series impedance R of capacitor breakdown fault rateESR, observable feature amount 2 is the motor oscillating for reacting motor burning fault rate
Earthquake intensity.
Document " the electrolytic capacitor reliability assessment based on Markov model " (Meng Linghui, Liu Zhigang, Wang Lei, the north et al.
Capital university of communications journal, 2014,38 (2)) to electrolytic capacitor fault condition in different equivalent series resistance RESRRelated reality is done
It tests, has obtained electrolytic capacitor series resistance RESRWith the data of electrolytic capacitor failure rate, show that electrolytic capacitor exists according to related data
R in damage process under harsh environmentsESRWith the trend chart of capacitive faults rate, as shown in Figure 5.
The traction motor failure rate is according to ISO23732 motor device vibration separation with motor oscillating change curve
Standard, it is specified that motor under kilter according to electric driving machinery of subway belong to III class medium-sized machine fitting traction motor failure rate with
The Drawing of Curve of vibration severity variation.ISO23732 motor device vibration standard grading regulation motor oscillating and motor operation
The relevant industries standard of state, as shown in table 1:
The classification of 1 ISO23732 motor device vibration standard of table
1: I class of note is micro-machine (power is less than 15KW)；II class is middle size motor (power 15KW-75KW)；III class is
Large-size machine.
According to professional standard, failure rate only has 2.13 × 10 under kilter-7, belong to III class according to electric driving machinery of subway
The curve P that medium-sized machine fitting traction motor failure rate changes with vibration severity2(L) as shown in fig. 6, wherein drawing the curve
According to being
As seen from the figure, (1) when motor oscillating earthquake intensity is in " good ", " satisfaction " section, traction electric machine operation conditions is good
Good, electrical fault rate is lower.
(2) when motor oscillating earthquake intensity is in " dissatisfied " section, the operation conditions of traction electric machine has caused anxiety, motor event
Barrier probability significantly increases, and needs to take timely measure the irregular operating for inhibiting motor.
(3) when motor oscillating earthquake intensity is in " not allowing " section, traction motor failure rate is excessively high, has been difficult to adapt to electricity
The operation of machine.
S3, the data according to the real-time acquisition characteristics amount of subway train monitoring system, dynamic statistics t moment traction invertor
Equivalent series resistance RESR, motor oscillating earthquake intensity L calculates and according to capacitive faults rate with capacitor equivalent series resistance modified-image
Capacitor real time fail probability Pt1；According to traction motor failure rate with motor oscillating change curve, electrical fault probability is calculated
Pt2；
S4, t moment is acquired according to formula 1 because of risk chain probability of happening typical under inverter Support Capacitor fault condition
Pt, that is, complete the probability of malfunction dynamic analysis of typical risk chain；
Wherein, formula (1) are as follows: Pt=Pt1×Pt2。
Shown in Fig. 7, the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity further includes following steps
It is rapid:
S5, the event that traction electric machine when burning fault occurs for subway train traction electric machine burns consequence is established according to investigation
Tree；
During establishing event tree, some event chains are not developed to finally, having terminated.Therefore event tree
Simplification follows following two points principle:
(1) it can not be included in successor when a certain abnormal event probability of happening is extremely low；
(2) after a certain successor occurs, other events thereafter cannot slow down the event chain whether no matter generation
Consequence when, which has terminated.
When burning fault occurs for subway train traction motor, traction electric machine is established according to the empirical data that investigation obtains and is burnt
The event tree of consequence is ruined, as shown in Figure 8.Not motor (the N event for shocking by electricity on fire) probability on fire is 0.4, consequence at this time
Event is C5Fall-back；Because the motor Y probability of happening on fire is 0.6, into next event chain link -- whether can find in time,
Discovery (failing the N event found in time) probability is 0.85 in time, and consequential event at this time is C4Maintenance parking；Fail and
The Y probability of happening of Shi Faxian is 0.15, into next event chain link -- whether can put out a fire, fire extinguishing (fails the N event of fire extinguishing)
Probability is 0.5, and consequential event at this time is C3Overhaul disastershutdown；The Y probability of happening for failing fire extinguishing is 0.5, into next thing
Whether part chain link -- personnel withdraw, and it is 0.75 that personnel, which can withdraw (i.e. personnel do not withdraw N event) probability, consequence thing at this time
Part is C2Fire incident parking；It is 0.25 that personnel, which fail the Y probability of happening withdrawn, and consequential event at this time is C1Personnel's accident is stopped
Vehicle.
S6, establish subway train damage sequence severity assessment indicator system, the system include capacity loss, repair at
Sheet, social influence, each index value u of human lossj；Capacity loss, dimension are obtained with analytic hierarchy process (AHP) by expert estimation simultaneously
Accomplish sheet, the weight W that social influence, each factor of human loss influence damage sequence severity；
The Consequential Loss of subway train risk accidents generally comprises capacity loss, maintenance cost, social influence, human loss
Etc. many aspects.According to the phases such as " metro operation accident treatment rule ", " rail transportation operation accident treatment is regular (2018 editions) "
Pass standard analyzes damage sequence seriousness, subway train damage sequence severity assessment indicator system such as Fig. 9 institute
Show.
Each index value u in figurejCalculation are as follows:
(1) capacity loss=parking vehicle transport power × idle time
(2) maintenance cost=car inspection and repair expense+line maintenance expense
(3) casualties=slight wound number × slight wound grading-severe injury number × severe injury grading+death toll × death is commented
Grade
(4) social influence=influence number × duration
With analytic hierarchy process (AHP) and meet consistency check according to expert opinion, obtains capacity loss, maintenance cost, society
It influences, the weight that each factor of human loss influences damage sequence severity is respectively
W=(w1, w2, w3, w4)
S7, the m kind accident in event tree is calculated for each index value u by clustering methodjGrey weigh assessment
Matrix, the grey power evaluating matrix is multiplied with index weights W obtains sequence severity comprehensive assessment vector Ω, then by described
Damage sequence seriously value η is integrated caused by sequence severity grey evaluation vector Ω calculation risk chain.
Specifically, the appraisal procedure based on metro traction systematic failures sequence severity is as follows:
S70, the Risk Chain known to the event tree analysis in S5 may cause m kind accident, remember i-th kind of accident for ujFinger
Scale value is xij, then sample matrix is constituted are as follows:
S71, the actual conditions assessed according to damage sequence severity, k=4 grey class is arranged in the present invention, since consequence is tight
Weight its higher loss of degree is bigger, and its increase tendency is exponential, therefore indicates that 1,10,40,100 successively indicate to refer to variable u
4 grades from light to heavy of severity degree corresponding to scale value size, and determine the k whitened weight function f for assessing grey classk(xij),
fk(xij) it is the power for belonging to kth class evaluation criteria.According to the typical whitened weight function of the following table 2, it is moderate estimate whitened weight function, under
Limit estimates whitened weight function, the corresponding gray scale of upper measure whitened weight function and mathematic(al) representation, empirically obtains function ginseng
Number A, B, C, D.
2 four class whitened weight function of table
S72, by sample and related weight function, comprehensive m kind accident calculates k class Grey Statistical to each evaluation index value
Number pijAnd use kth class assessment level grey weight rij, it may be assumed that
pij=fk(xij) (j=1,2 ..., 5) (2)
The assessment weight matrix being made of grey weight are as follows:
S73, damage sequence severity comprehensive assessment vector can be obtained by index weights vector sum grey power evaluating matrix, expressed
Formula are as follows: Ω=(σ1, σ2..., σi)=WR (4)
S74, seriously it is worth by comprehensive damage sequence caused by sequence severity grey evaluation vector calculation risk chain, is expressed
Formula are as follows:
S8, quantitative evaluation is seriously worth according to the typical risk chain probability of happening of S4 and the synthesis damage sequence of S7, obtained
Risk class.
The uncertainty and damage sequence severity of risk are combined analysis by risk assessment, i.e. risk occurs general
The safe coefficient of both rate and sequence severity measurement event.Integrated risk is expressed as R (risk), contingency occurrence probability P
(Probability), sequence severity S (Severity) is i.e.:
R=P × S.
For leaving for certain subway train of dragon's fountain post by Xi Pu by Metro Line 2 of Chengdu below, the method for the present invention is carried out
Description.0.9 Ω of equivalent series impedance of trailer system Support Capacitor, corresponding Support Capacitor puncture short are detected in t moment
Probability is.The vibration severity 3.1mm/s of this conditional event a situation arises lower traction electric machine corresponds to electrical fault conditional probability.Root
Cause to draw through Risk of Communication under a situation arises when inverter Support Capacitor puncture short according to the dynamic probability analysis of risk chain
The probability that the risk chain that motor is burnt occurs are as follows:
P=P1×P2
The probability for bringing the generation of its risk chain of related data into is 1.74 × 10-6。
When Chengdu metro operation company occurs to burn because of traction electric machine, caused various causality losses rule of thumb data knot
Fruit is as shown in table 3 below.
3 Metro Line 2 of Chengdu traction electric machine burnout failure of table causes damages situation
According to the calculation of each first class index, table 4 is calculated in data substitution in table 3
4 Metro Line 2 of Chengdu traction electric machine burnout failure sequence severity index table of table
According to rail traffic concerned countries standard and the actual conditions of risk assessment, step analysis is used by expert estimation
It is respectively (0.2,0.2,0.15,0.15) W=that method, which obtains each index weights,.
The grey class of setting herein 4, successively indicates degree of risk corresponding to index value size by light with 1,10,40,100
To weight be it is not serious, general it is serious, than more serious, very serious.Selection in general grey classification about clustering function
Interior element reflection is the bigger the better, it is contemplated that uses upper measure whitened weight function；If the smaller the better, lower limit is selected to estimate white
Change weight function；If surrounding some point, moderate whitened weight function, i.e. triangle whitened weight function are selected.According to the above principle and warp
The whitened weight function for testing to obtain each index is as shown in table 5 below:
Each index of table 5 corresponds to whitened weight function parameter value
Sample matrix is obtained according to the index parameter of 4 damage sequence severity of table
X is obtained by whitened weight functionijBelong to the power f of kth class evaluation criteriak(xij), and then calculate Grey System count and
Total Grey System counts, therefore evaluating matrix is
It normalizes:
Bring Ω=(σ into1, σ2..., σi)=WR, obtains: Ω=(0.298 0.214 0.291 0.297).
By formula (5) draw because of the Risk Chain of traction electric machine burning fault caused by under the conditions of inverter front support capacitive faults
Play the sequence severity value of train accident are as follows: η=65.8.
Because degree of risk corresponding to 1,10,40,100 successively expression index value size is not serious, general from light to heavy
Seriously, than more serious, very serious, so damage sequence severity caused by the Risk Chain once occurs is than more serious.
It is divided into 1-10-3 with typical risk chain probability of happening, 10-3-10-6,10-6-10-9, < 10-9 level Four are vertical
To parameter, with severity degree it is not serious, general it is serious, be lateral quantization parameter than more serious, very serious level Four, comment
Determine the accident risk grade of parameter intersection, that is, establishes typical risk assessment matrix, as shown in table 6.According to above analysis integrated right
Risk assessment matrix is answered to carry out assessment accident risk grade.
6 subway train failure typical case's risk assessment matrix of table
To because causing traction electric machine to burn under the conditions of subway train trailer system inverter front support capacitor puncture short
The dynamic risk chain of failure is analyzed and corresponding consequence severity of injuries quantitative evaluation, it is known that caused by the dynamic risk chain
Subsequent possibility accident belongs to the grade for comparing risk, and subway circulation maintenance personnel is needed to reinforce maintenance and monitoring work.
Embodiments described above does not constitute the restriction to the technical solution protection scope.It is any in above-mentioned implementation
Made modifications, equivalent substitutions and improvements etc., should be included in the protection model of the technical solution within the spirit and principle of mode
Within enclosing.
Claims (10)
1. a kind of subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity, includes at least:
S1, the monitoring of subway train trailer system acquire the data of each vehicle and equipment in real time, including traction invertor front end
Condenser voltage, inverter output current, DC loop current, braking resistor chopper current and motor oscillating earthquake intensity, and will
The data of acquisition are uploaded to assessment system；
S2, the data based on acquisition establish metro traction system typical case's risk chain, while establishing capacitive faults rate with capacitor etc.
Series resistance variation diagram and traction motor failure rate are imitated with motor oscillating change curve；
The data that S3, foundation detect, the equivalent series resistance R of dynamic statistics t moment traction invertorESR, motor oscillating earthquake intensity L,
And capacitor real time fail probability P is calculated with capacitor equivalent series resistance modified-image according to capacitive faults ratet1；According to traction electricity
Machine failure rate calculates electrical fault probability P with motor oscillating change curvet2；
S4, t moment is acquired according to formula 1 because of risk chain probability of happening P typical under inverter Support Capacitor fault conditiont, i.e., complete
At the probability of malfunction dynamic analysis of typical risk chain；
Wherein, formula (1) are as follows: Pt=Pt1×Pt2。
2. the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity as described in claim 1, special
Sign is, the particular content of metro traction system typical case's risk chain in the S2 are as follows:
1) long-term temperature it is excessively high and it is filthy cause traction invertor front support capacitance to become smaller, capacitor equivalent series resistance value
RESRIncrease, regeneration brake system front end inverter voltage increases when emergency braking, the breakdown short circuit of traction invertor charging capacitor；
2) a large amount of higher hamonic waves that traction invertor outlet side voltage waveform contains make output waveform distortion degree become larger, with its phase
The abnormal raising of traction electric machine torque unstability even, asynchronous machine running temperature, motor oscillating earthquake intensity L are excessive, make asynchronous traction
Electrical fault probability increases.
3. the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity as described in claim 1, special
Sign is that the traction motor failure rate is according to ISO23732 motor device vibration separation mark with motor oscillating change curve
Standard is, it is specified that motor failure rate under kilter only has 2.13 × 10-7, and belong to the medium-sized machine of III class according to electric driving machinery of subway
The Drawing of Curve that fitting traction motor failure rate changes with vibration severity.
4. the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity as described in claim 1, special
Sign is, the method also includes
S5, the event tree that traction electric machine when burning fault occurs for subway train traction electric machine burns consequence is established according to investigation,
The probability and consequence that various accidents caused by the event tree characterization electric driving machinery of subway is burnt occur；
S6, subway train damage sequence severity assessment indicator system is established, which includes capacity loss, maintenance cost, society
It will affect, each index value u of human lossj；Simultaneously by expert estimation with analytic hierarchy process (AHP) obtain capacity loss, repair at
Weight W=(the w that sheet, social influence, each factor of human loss influence damage sequence severity1, w2, w3, w4)；
S7, the m kind accident in event tree is calculated for each index value u by clustering methodjGrey weigh evaluating matrix,
The grey power evaluating matrix is multiplied with index weights W obtains sequence severity comprehensive assessment vector Ω, then passes through the consequence
Damage sequence seriously value η is integrated caused by severity grey evaluation vector Ω calculation risk chain；
S8, quantitative evaluation is seriously worth according to the typical risk chain probability of happening of S4 and the synthesis damage sequence of S7, obtains risk
Grade.
5. the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity as claimed in claim 4, special
Sign is, in the event tree of the S5, the electric driving machinery of subway probability that various accidents occur caused by burning and consequence description are as follows:
The N probability of happening for shocking by electricity on fire is 0.4, and consequential event at this time is fall-back；Because the motor Y probability of happening on fire is
0.6, into next event chain link -- whether can find in time；
Failing the N probability of happening found in time is 0.85, and consequential event at this time is maintenance parking；Fail the Y thing found in time
Part probability is 0.15, into next event chain link -- whether can put out a fire；
The N probability of happening for failing fire extinguishing is 0.5, and consequential event at this time is maintenance disastershutdown；Fail the Y probability of happening of fire extinguishing
It is 0.5, into next event chain link -- whether personnel withdraw；
The N probability of happening that i.e. personnel do not withdraw is 0.75, and consequential event at this time is fire incident parking；What personnel failed to withdraw
The Y probability of happening is 0.25, and consequential event at this time is personnel's disastershutdown.
6. the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity as claimed in claim 4, special
Sign is, each index value u in the S6jCalculation are as follows:
1) capacity loss=parking vehicle transport power × idle time
2) maintenance cost=car inspection and repair expense+line maintenance expense
3) casualties=slight wound number × slight wound grading-severe injury number × severe injury grading+death toll × death grading
4) social influence=influence number × duration.
7. the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity as claimed in claim 4, special
Sign is that each index weights are according to rail traffic concerned countries standard and the actual conditions of risk assessment in the S6, by special
Family's marking obtains W=(0.2,0.2,0.15,0.15) with analytic hierarchy process (AHP).
8. the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity as claimed in claim 4, special
Sign is, includes in the S7
S70, the Risk Chain known to the event tree analysis in S5 may cause m kind accident, remember i-th kind of accident for ujIndex value
For xij, then sample matrix is constituted are as follows:
S71, setting k=4 grey class, variable u indicate that 1,10,40,100 successively indicate that consequence corresponding to index value size is serious
4 grades from light to heavy of degree, and determine the k whitened weight function f for assessing grey classk(xij), fk(xij) it is to belong to kth class evaluation criteria
Power；
S72, by sample and related weight function, comprehensive m kind accident calculates k class Grey System and counts p to each evaluation index valueij
And use kth class assessment level grey weight rij, the assessment weight matrix that is made of grey weight are as follows:
S73, damage sequence severity comprehensive assessment vector can be obtained by index weights vector sum grey power evaluating matrix, expression formula is
Ω=(σ1, σ2..., σi)=WR；
S74, seriously it is worth by comprehensive damage sequence caused by sequence severity grey evaluation vector calculation risk chain, expression formula
Are as follows:
9. the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity as claimed in claim 8, special
Sign is that the variable u indicates that 1,10,40,100 successively indicate not serious, generally serious, than more serious, very serious.
10. the subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity as claimed in claim 9, special
Sign is, specifically includes in the S8:
It is divided into 1-10 with typical risk chain probability of happening-3、10-3-10-6、10-6-10-9, < 10-9 level Four be longitudinal parameter, with
Severity degree it is not serious, general it is serious, be lateral quantization parameter, assessment parameters phase than more serious, very serious level Four
The accident risk grade of friendship establishes typical risk assessment matrix；
Risk assessment matrix assessment accident risk grade is corresponded to according to the analysis integrated result of step S1-S7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910164981.6A CN110276509A (en) | 2019-03-05 | 2019-03-05 | Subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910164981.6A CN110276509A (en) | 2019-03-05 | 2019-03-05 | Subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110276509A true CN110276509A (en) | 2019-09-24 |
Family
ID=67959014
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910164981.6A Pending CN110276509A (en) | 2019-03-05 | 2019-03-05 | Subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110276509A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112231623A (en) * | 2020-10-13 | 2021-01-15 | 广州市扬新技术研究有限责任公司 | Contact network parameter calculation method of rail transit traction power supply system |
| CN112434955A (en) * | 2020-11-27 | 2021-03-02 | 广东电网有限责任公司肇庆供电局 | Distribution network line operation risk sensing method based on multi-data fusion |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10236165A1 (en) * | 2002-08-07 | 2004-02-19 | Siemens Ag | Capacitor balancing method for a capacitor battery/bank of capacitors monitors the charging status of capacitors by applying three voltage levels available through a source of reference voltage |
| CN104236933A (en) * | 2013-06-13 | 2014-12-24 | 同济大学 | Hidden fault danger warning method for train hauling system |
| CN104569819A (en) * | 2015-01-12 | 2015-04-29 | 清华大学 | Fault detection method for asynchronous traction motor |
| CN105301470A (en) * | 2015-08-12 | 2016-02-03 | 南京航空航天大学 | IGBT fault diagnosis method for traction drive system of CRH5 type high-speed train |
| CN205540889U (en) * | 2016-03-18 | 2016-08-31 | 中国铁道科学研学院东郊分院 | Pull power supply risk feature data storehouse system based on risk assessment |
| CN107632531A (en) * | 2017-09-14 | 2018-01-26 | 南京航空航天大学 | A kind of method for building up of model for the bullet train lengthwise movement containing interference |
| CN108537002A (en) * | 2018-06-29 | 2018-09-14 | 中车成都机车车辆有限公司 | A kind of rail traffic tractive power supply system reliability estimation method |
-
2019
- 2019-03-05 CN CN201910164981.6A patent/CN110276509A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10236165A1 (en) * | 2002-08-07 | 2004-02-19 | Siemens Ag | Capacitor balancing method for a capacitor battery/bank of capacitors monitors the charging status of capacitors by applying three voltage levels available through a source of reference voltage |
| CN104236933A (en) * | 2013-06-13 | 2014-12-24 | 同济大学 | Hidden fault danger warning method for train hauling system |
| CN104569819A (en) * | 2015-01-12 | 2015-04-29 | 清华大学 | Fault detection method for asynchronous traction motor |
| CN105301470A (en) * | 2015-08-12 | 2016-02-03 | 南京航空航天大学 | IGBT fault diagnosis method for traction drive system of CRH5 type high-speed train |
| CN205540889U (en) * | 2016-03-18 | 2016-08-31 | 中国铁道科学研学院东郊分院 | Pull power supply risk feature data storehouse system based on risk assessment |
| CN107632531A (en) * | 2017-09-14 | 2018-01-26 | 南京航空航天大学 | A kind of method for building up of model for the bullet train lengthwise movement containing interference |
| CN108537002A (en) * | 2018-06-29 | 2018-09-14 | 中车成都机车车辆有限公司 | A kind of rail traffic tractive power supply system reliability estimation method |
Non-Patent Citations (2)
| Title |
|---|
| 孟苓辉: "城轨列车牵引逆变系统可靠性评估", 《铁道学报》 * |
| 殷俊 等: "高铁牵引系统三相逆变器IGBT和电机速度传感器的复合故障诊断", 《机械设计与制造工程》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112231623A (en) * | 2020-10-13 | 2021-01-15 | 广州市扬新技术研究有限责任公司 | Contact network parameter calculation method of rail transit traction power supply system |
| CN112434955A (en) * | 2020-11-27 | 2021-03-02 | 广东电网有限责任公司肇庆供电局 | Distribution network line operation risk sensing method based on multi-data fusion |
| CN112434955B (en) * | 2020-11-27 | 2023-01-24 | 广东电网有限责任公司肇庆供电局 | Distribution network line operation risk sensing method based on multi-data fusion |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103400310B (en) | Method for evaluating power distribution network electrical equipment state based on historical data trend prediction | |
| CN105035902B (en) | A kind of elevator safety condition evaluation method | |
| CN105196877B (en) | Electric automobile high-voltage electric system health status diagnoses early warning circuit and method | |
| CN103324992B (en) | Transformer risk prediction method based on markov and entropy weight fuzzy comprehensive evaluation | |
| CN102510125B (en) | Method and device for monitoring operation conditions of power primary equipment | |
| CN102289731B (en) | Method for maintaining state of power transmission equipment based on system risk | |
| CN103926491B (en) | A kind of Transformer condition evaluation taking into account DC magnetic biasing impact | |
| CN103150633B (en) | Power equipment state real-time evaluation and auxiliary decision-making system | |
| CN106384210A (en) | Power transmission and transformation equipment maintenance priority ordering method based on maintenance risk premium | |
| CN203497948U (en) | Fuzzy neural network fault diagnosis device of auto crane | |
| CN103235991A (en) | Condition evaluation method of distribution network transformer based on fuzzy theory | |
| CN103177186B (en) | A kind of electric loop probability of malfunction Forecasting Methodology | |
| CN107145675A (en) | Diagnosing fault of power transformer device and method based on BP neural network algorithm | |
| CN110276509A (en) | Subway train trailer system dynamic risk analysis appraisal procedure based on characteristic quantity | |
| CN105354768A (en) | Assessment method and system for electric transmission and transformation equipment states | |
| CN107392324A (en) | The specialized maintenance total management system of transformer | |
| CN105260861A (en) | Comprehensive risk assessment method for electric vehicle battery replacement station | |
| CN104991549A (en) | Track circuit red-light strip default diagnosis method based on FTA and multilevel fuzzy-neural sub-networks | |
| CN113466597A (en) | Intelligent detection method for equipment state of rail transit power supply system | |
| CN103678924A (en) | Method for determining failure mode risk priority numbers of key component of rail transit vehicle | |
| CN107239652A (en) | A kind of charging station running status methods of risk assessment | |
| CN106802599A (en) | A kind of diagnosing fault of power transformer system based on expert database | |
| CN104236933B (en) | A kind of potential faults method for early warning for train traction system | |
| CN107451744A (en) | A kind of substation grounding unit state appraisal procedure based on fuzzy overall evaluation | |
| CN107832984A (en) | Consider the tractive power supply system methods of risk assessment of reliability of relay protection |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| AD01 | Patent right deemed abandoned |
Effective date of abandoning: 20211029 |
|
| AD01 | Patent right deemed abandoned |