CN110135040A - 3K planetary reduction gear reliability estimation method neural network based - Google Patents
3K planetary reduction gear reliability estimation method neural network based Download PDFInfo
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Abstract
The invention proposes a kind of 3K planetary reduction gear reliability estimation methods neural network based.This method is from the angle of Monte Carlo emulation mode, it is defined based on failure properties of the neuronal structure to 3K planetary reduction gear system parts, the system reliability layered network model simplified without components is established based on neural network structure on this basis, then consider that common cause failure determines Reliability evaluation strategy, finally establishes the Monte Carlo emulation mode to match with reliability layered network model.The present invention is slowed down using convectional reliability appraisal procedure to bring error simplified in 3K planetary reduction gear Reliability modeling, total probability model method is avoided to occur multiple integral when calculating and there are problems that the mechanical system reliability of common cause failure and be difficult to solve, it is designer assessment amount of parts is big, structure is complicated, and system reliability provides foundation, and improves the accuracy of Reliability evaluation.
Description
Technical field
The present invention relates to engineering transmission system reliability assessment field, specifically a kind of 3K planet neural network based subtracts
Fast device reliability estimation method can be applied to the occasion of the application 3K planetary reduction gear such as aerospace.
Background technique
In recent years, 3K planetary reduction gear (K: centre wheel) is compact-sized with its, light-weight, transmission ratio is big, high-efficient etc.
Advantage is continually applied to the every field of machinery industry further.Especially aerospace field, 3K planetary reduction gear are extensive
Flap slat, raising lift are opened when taking off with landing applied to aircraft in the flap slat of aircraft, is responsible for；In high-altitude normal flight
When withdraw flap slat, to reduce resistance.And components are numerous, structure is complicated in aircraft flap slat 3K planetary reduction gear, system is lost
Effect factor is more, and requirement the considerations of in terms of safety to its reliability is very high.Therefore correct assessment 3K planet subtracts
The reliability of fast device smoothly takes off to guarantee aircraft safety, cruises, landing plays a crucial role.
Currently, the reliability estimation method of complicated transmission system more to this number of parts of 3K planetary reduction gear
There are mainly two types of, one is based on reliability test, counting to obtain reliability value by a large number of experiments, another kind is to answer
Classical Reliability of Mechanical System appraisal procedure based on power strength Interference theory and the series-parallel theory of components is strong by stress
Degree interference calculates Reliability of Parts, then passes through series-parallel theoretical calculation system dependability.First method is due to 3K planet
Retarder production and processing is complicated, at high cost, test period is long, carries out the big test of sample size, is all difficult on time and financial resources
It realizes.It needs largely to simplify system in implementation process for second, only retains the main parts size for causing thrashing,
And this inevitably results in reliability calculating value and is overestimated, and then exists to the high authenticity product such as aerospace equipment or precision machinery
Certain risk, furthermore series and parallel model method assumes that components failure is independent mutually, and actually using load as representative it is total because
Failure is widely present and reliability calculating value can be made error occur.Therefore, system parts are carried out without letter to 3K planetary reduction gear
Change Reliability modeling, and consider to carry out reliability assessment under the conditions of common cause failure, for preferably analysis and research and improves 3K row
The reliability of star retarder, it is ensured that the reliable and stable work of precision mechanical transmission system has important theory and realistic meaning.
Summary of the invention
For defect existing for existing reliability estimation method, the present invention provides a kind of 3K planet neural network based and subtracts
Fast device reliability estimation method, the failure mode based on system carry out components failure definition using neural network structure, establish
The system layer reliability model that no components simplify, common cause failure existing for consideration system, emulates angle from Monte Carlo
It sets out and has worked out the Reliablility simulation strategy of 3K planetary reduction gear to predict the reliability of system, in favor of pacifying in next step
O&M maintenance is arranged, system reliability of operation is improved.
The technical solution of the present invention is as follows:
A kind of 3K planetary reduction gear reliability estimation method neural network based, it is characterised in that: including following
Step:
Step 1: failure definition, the failure definition are carried out to each components of 3K planetary reduction gear based on neuronal structure
Including three attributes, respectively input attribute, failure trigger attribute and output attribute；The failure trigger attribute includes external loses
Imitate trigger condition and internal failure trigger condition；
Step 2: after carrying out failure definition to each part, determining internal failure mechanism, the External Failure machine of each part
System and failure mechanism of transmission；
Step 3: neural network Earthquake response is based on, according to the assembly relation between components and in power transmission process
In different degree reliability layered modeling is carried out to 3K planetary reduction gear, obtain reliability network figure, in reliability network figure altogether
Have Z layers: wherein the 1st layer of core component for 3K planetary reduction gear, the 2nd layer is the secondary components for directly affecting core component,
3rd layer is the components for directly affecting secondary components, and so on, determine the affiliated of each components in 3K planetary reduction gear
Layering；Direction sequence is established according to power direction of transfer to each layer of components；
Step 4: using the failure rate of 3K planetary reduction gear as evaluation index, initializing simulation times N=1, and initialize
System adds up Safe Times n=0；
Step 5: failure being transmitted to often because carrying out unified sample again altogether according to common cause failure Monte Carlo Simulation Strategy
In one components, to non-failed altogether because parameter is respectively according to parameter distribution independent sampling；
Step 6: according to the triggering of the internal failure of each components and External Failure trigger condition, according to Z layers, Z-1
Layer, Z-2 layers ... the 2nd layer, the 1st layer of sequence successively updates each layer of spare parts logistics Ti；Spare parts logistics are divided into safety
With failure two states；
Step 7: judging whether the last one components of direction sequence in the 1st layer of reliability network figure fail, if not having
There is failure then to set system state variables k=1, indicates system safety, otherwise k=0, indicate thrashing；
Step 8: updating simulation times N=N+1 and system adds up Safe Times n=n+k；
Step 9: judging whether simulation times meet N < Num, Num indicates total simulation times of setting, returns if meeting
Step 5 continues iteration, and otherwise terminator and statistical system accumulate Safe Times n, calculating reliability R=n/Num, crash rate Y
Crash rate is compared by=1-R with the probability of malfunction of formulation, according to result judgement 3K planetary reduction gear operating status.
Further preferred embodiment, a kind of 3K planetary reduction gear reliability estimation method neural network based,
Be characterized in that: in step 1, input attribute includes state input k, load F, the vibration x, torque T of components；Output attribute refers to defeated
It does well；External Failure trigger condition indicate to be connected with the components and be in system dynamic transmit upper level another zero
Component failure and cause the components that can not receive the condition of system dynamic；Internal failure trigger condition indicates the components itself
Each failure mode.
Beneficial effect
1. relationship is complicated between huge, components for amount of parts, it is difficult to the machine driving modeled with series-parallel connection method
System, the Complex System Reliability modeling method that without components simplifies of the creation based on neural network structure, so that established
Reliability model accuracy with higher.
2. being based on reliability total probability model from Monte Carlo method, establishing common cause failure Monte
Carlo Simulation Strategy is slowed down using convectional reliability appraisal procedure to band simplified in 3K planetary reduction gear Reliability modeling
The error come, avoiding total probability model method, there are multiple integral occur when the mechanical system reliability of common cause failure in calculating
It is difficult to the problem of solving, so that system dependability calculating is more efficiently and accurate.
Additional aspect and advantage of the invention will be set forth in part in the description, and will partially become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
Above-mentioned and/or additional aspect of the invention and advantage will become from the description of the embodiment in conjunction with the following figures
Obviously and it is readily appreciated that, in which:
Fig. 1 is the method for the present invention flow chart.
Fig. 2 is components failure definition figure.
Fig. 3 is 3K planetary reduction gear drive mechanism schematic diagram.
Fig. 4 is 3K planetary reduction gear components installation diagram.
Fig. 5 is to include kernel component reliability network figure.
Fig. 6 is the reliability network figure comprising secondary components.
Fig. 7 is the reliability network figure comprising all components.
Specific embodiment
The embodiment of the present invention is described below in detail, the present embodiment illustrates 3K by taking big aircraft slat 3K planetary reduction gear as an example
The embodiment of the specific embodiment of planetary reduction gear reliability estimation method, description is intended to be used to explain the present invention, Bu Nengli
Solution is limitation of the present invention.
It is as shown in Figure 1 the flow chart of the method for the present invention, the transmission knot of this selected big aircraft slat 3K planetary reduction gear
Structure schematic diagram such as Fig. 3 is inputted from N3, N4 output, main shaft input speed nN3=1500r/min, output torque Te=94.26N
M, projected life 2000h.In the present embodiment, its structure is analyzed, determine the revolving speeds of the components such as major gear, axis with
Bear load.Slat 3K retarder basic parameter such as table 1.
1 slat 3K planetary reduction gear basic parameter introduction of table
Known resultant gear ratioInput speed nN3=1500r/min can calculate input in conjunction with attached drawing 3 and turn
Square, each gear rotational speed and engagement force.(the present embodiment focuses on explanation the method for the present invention, herein input torque, each gear rotational speed
It is omitted with the calculating process of engagement force.) wherein nN4=17.86r/min, nN5=1155.77r/min.
Input torque:
Then:
Te=TN4=58.5Ta
The engagement place N3 and N2 normal direction shearing stress:
The engagement place N1 and N2 normal direction shearing stress:
The engagement place N4 and N5 normal direction shearing stress:
Wherein np is planetary gear number 3.
Step 1: failure definition, the failure definition are carried out to each components of 3K planetary reduction gear based on neuronal structure
Including three attributes, respectively input attribute, failure trigger attribute and output attribute；The failure trigger attribute includes external loses
Imitate trigger condition and internal failure trigger condition；, components failure definition schematic diagram such as Fig. 2.
Input attribute includes state input k, load F, the vibration x, torque T of components；Output attribute refers to output state；Outside
Portion's failure trigger condition is indicated to be connected with the components and be failed in another components of system dynamic transmitting upper level
And cause the components that can not receive the condition of system dynamic；Internal failure trigger condition indicates each mistake of the components itself
Effect mode.
In the present embodiment, input attribute is selected as load, and output attribute is components safety and failure two states.
Step 2: after carrying out failure definition to each part, determining internal failure mechanism, the External Failure machine of each part
System and failure mechanism of transmission.
According to the components (table 2) of 3K planetary reduction gear and attached drawing 4 to the internal failure machine of each part in the present embodiment
System, External Failure mechanism and failure mechanism of transmission are analyzed.
2 slat 3K planetary reduction gear components inventory of table
(1) No. 10 (axis 2, material 40CrNiMoA): axis 2 is power input axis, by analysis only by shearing stress in torsion power shadow
It rings.
External Failure trigger mechanism: the failure of part 9,18,37 will lead to its failure；
Internal failure trigger mechanism: shearing stress in torsion power is greater than torsional strength and causes to fail；
Failure mechanism of transmission: the failure of part 10 will lead to the failure of part 31.
Internal failure is assessed according to input load TaIt is distributed sampling and the value of diameter D, calculate Dangerous Place maximum stress and is resisted
Intensity is turned round, whether determines axis failure after comparing size.Wherein:
Dangerous Place maximum stress
Torsional strength στIt can be consulted according to " mechanical design handbook " related Sections and obtain its distribution, obtained: στ~N (576.34,
86.452)。
(2) No. 31 (gear N3, material 38CrMoAl), gear 31 is the centre wheel in Gear Planet Transmission.
External Failure trigger mechanism: the failure of part 10,16 will lead to its failure；
Internal failure trigger mechanism: it fails including face fatigue failure and tooth root flexural fatigue；
Failure mechanism of transmission: the failure of part 31 will lead to the failure of part 33.
Internal failure assessment is compared by calculating separately contact stress, bending stress, then with contact strength, bending strength
Compared with, gear safety is determined when the two intensity is both greater than stress, it is on the contrary to determine gear as long as one of stress is greater than intensity
Failure.Wherein:
Contact Stress of Gear
Contact strength of tooth surface
σHG=σH limZNTZLZVZRZWZX
Dedenda's bending stress
Teeth bending strength
σFG=σFlimYSTYNTYδrelTYRrelTYX
The above tangential force FtIt is known that Contact Stress of Gear, Strength co-mputation parameter, Contact Stress of Gear, Strength co-mputation ginseng
Number can be consulted according to " mechanical design handbook " related Sections and obtain its distribution.
(3) No. 33 (planet axis N2, N5), No. 33 parts are planet wheel spindle, are integrated with gear N2, N5, therefore it fails
It include the failure of two gears.Again because the 3K planet actuator includes three planetary gears, from the angle of closing to reality
Using three planetary gears as two-out-of-three voting system processing.
External Failure trigger mechanism: the failure of part 31,46 will lead to voting system failure, and the failure of part 29,30 will lead to
Planetary gear fails and carries out 2/3 voting；
Internal failure trigger mechanism: face fatigue failure and the failure of tooth root flexural fatigue including gear N2, N5；
Failure mechanism of transmission: voting system failure will lead to the failure of part 47.
The assessment of planetary gear N2, N5 internal failure by calculating separately contact stress, bending stress, then with contact strength, curved
Qu Qiangdu is compared, and gear safety is determined when the two intensity is both greater than stress, as long as one of stress on the contrary is greater than by force
Degree then determines gear failure.The contact stress of planetary gear N2, N5, contact strength, bending stress, bending strength calculating process and 31
Number part (gear N3) is similar, herein not reinflated explanation.
(4) No. 47 (gear N1), the ring gear in gear N1 Gear Planet Transmission.
External Failure trigger mechanism: the failure of planet wheel spindle two-out-of-three voting system will lead to its failure；
Internal failure trigger mechanism: it fails including face fatigue failure and tooth root flexural fatigue；
Failure mechanism of transmission: the failure of part 47 will lead to the failure of part 11.
Internal failure assessment is compared by calculating separately contact stress, bending stress, then with contact strength, bending strength
Compared with, gear safety is determined when the two intensity is both greater than stress, it is on the contrary to determine gear as long as one of stress is greater than intensity
Failure.Contact stress, contact strength, bending stress, bending strength calculating process and No. 31 part (gear N3) classes of gear N1
Seemingly, not reinflated explanation herein.
(5) No. 11 (gear N4).
External Failure trigger mechanism: No. 47 and No. 34 failures of part will lead to its failure；
Internal failure trigger mechanism: it fails including face fatigue failure and tooth root flexural fatigue.
Failure mechanism of transmission: the failure of part 11 will lead to the failure of part 4.
Internal failure assessment is compared by calculating separately contact stress, bending stress, then with contact strength, bending strength
Compared with, gear safety is determined when the two intensity is both greater than stress, it is on the contrary to determine gear as long as one of stress is greater than intensity
Failure.Contact stress, contact strength, bending stress, bending strength calculating process and No. 31 part (gear N3) classes of gear 11
Seemingly, not reinflated explanation herein.
(6) No. 4 (No. 1 output shaft): part 4 is No. 1 output shaft axis, is only influenced by analysis by shearing stress in torsion power.
External Failure trigger mechanism: the failure of part 7,11 will lead to its failure；
Internal failure trigger mechanism: shearing stress in torsion power is greater than torsional strength and causes to fail；
Failure mechanism of transmission: the failure of part 4 will lead to the failure of part 1.
4 internal failure evaluation process of part is similar with part 10 (axis 2), herein not reinflated explanation.
(7) No. 1 (No. 2 output shafts): part 1 is No. 2 output shaft axis, is only influenced by analysis by shearing stress in torsion power.
External Failure trigger mechanism: the failure of part 4,5,43,45 will lead to its failure；
Internal failure trigger mechanism: shearing stress in torsion power is greater than torsional strength and causes to fail；
Failure mechanism of transmission: the failure of part 1 will lead to entire actuator failure.
1 internal failure evaluation process of part is similar with part 10 (axis 2), herein not reinflated explanation.
(8) No. 9, No. 37 (bearing): bearing is standard component.
External Failure trigger mechanism: the failure of part 36,38,39 will lead to its failure；
Internal failure trigger mechanism: bearing is standard component and is assembly, this, which calculates its reliability, can pass through volume
Determine service life reliability (factory is known and is 0.9) and the relationship between actuator projected life calculates, therefore its internal failure is
It is no to be directly sampled according to reliability；
Failure mechanism of transmission: part 9, the failure of part 37 will lead to the failure of part 10.
Bearing inner Failure Assessment process is as follows:
Formula of reliability:
It can be counted according to the projected life of 3K planetary reduction gear and bearing relevant parameter (can be obtained by " mechanical design handbook ")
It calculates.
(9) No. 18 (bearing): bearing is standard component.
External Failure trigger mechanism: the failure of part 19,20,22,24,26 will lead to its failure；
Internal failure trigger mechanism: bearing is standard component and is assembly, and failure cause is complex, and reliability can
To be calculated by rated life time reliability (factory is known and for 0.9) and the relationship between actuator projected life, therefore in it
Whether portion's failure can directly be sampled according to reliability；
Failure mechanism of transmission: the failure of part 18 will lead to the failure of part 10.
18 internal failure evaluation process of part is similar with part 9 (bearing), herein not reinflated explanation.
(10) No. 16 (circlip): circlip is standard component.
External Failure trigger mechanism: nothing；
Internal failure trigger mechanism: circlip is a standard component, is mainly used for the axial float of limiting gear, in tooth
Reliability is not very high in the case where by axial force for wheel, and reliability can be set as 0.999, then determine it according to the method for random sampling
State at any time.
Failure mechanism of transmission: the failure of part 16 will lead to the failure of part 31.
(11) No. 29 (bearing): bearing is standard component.
External Failure trigger mechanism: nothing；
Internal failure trigger mechanism: bearing is standard component and is assembly, and failure cause is complex, and reliability can
To be calculated by rated life time reliability (factory is known and for 0.9) and the relationship between actuator projected life, therefore in it
Whether portion's failure can directly be sampled according to reliability；
Failure mechanism of transmission: the failure of part 29 will lead to the failure of part 33.
29 internal failure evaluation process of part is similar with part 9 (bearing), herein not reinflated explanation.
(12) No. 30 (copper sheathing), No. 34 (oval styletable holding screw M5 × 6 of slotting): can be considered standard component.
External Failure trigger mechanism: nothing；
Internal failure trigger mechanism: copper sheathing, screw reliability are very high, and reliability can be set as 0.999, then take out according to random
The method of sample determines its state at any time；
Failure mechanism of transmission: the failure of part 30 will lead to the failure of part 33, and the failure of part 34 will lead to the failure of part 11.
(13) No. 46 (planet carrier)
External Failure trigger mechanism: the failure of part 12,13,14,15,17,32 will lead to the failure of part 46；
Internal failure trigger mechanism: planet carrier reliability itself is very high, and reliability can be set as 0.999；Then according to random
The method of sampling determines its state at any time；
Failure mechanism of transmission: the failure of part 46 will lead to the failure of part 33.
(14) No. 7 (bearing): bearing is standard component.
External Failure trigger mechanism: the failure of part 8,40 will lead to its failure；
Internal failure trigger mechanism: bearing is standard component and is assembly, and failure cause is complex, and reliability can
To be calculated by rated life time reliability (factory is known and for 0.9) and the relationship between actuator projected life, therefore in it
Whether portion's failure can directly be sampled according to reliability；
Failure mechanism of transmission: the failure of part 7 will lead to the failure of part 4.
7 internal failure evaluation process of part is similar with part 9 (bearing), herein not reinflated explanation.
(15) No. 5 (spline housing), No. 45 (gasket)
External Failure trigger mechanism: nothing；
Internal failure trigger mechanism: spline housing, gasket itself reliability are very high, its reliability can be set as 0.999；Then
Its state at any time is determined according to the method for random sampling；
Failure mechanism of transmission: part 5, the failure of part 45 will lead to the failure of part 1.
(16) No. 43 (bearing): bearing is standard component.
External Failure trigger mechanism: the failure of part 2,3,41,42,44 will lead to its failure；
Internal failure trigger mechanism: bearing is standard component and is assembly, and failure cause is complex, and reliability can
To be calculated by rated life time reliability (factory is known and for 0.9) and the relationship between actuator projected life, therefore in it
Whether portion's failure can directly be sampled according to reliability；
Failure mechanism of transmission: the failure of part 43 will lead to the failure of part 1.
43 internal failure evaluation process of part is similar with part 9 (bearing), herein not reinflated explanation.
Show only the key components and parts for directly affecting power transfer above, and act on key components and parts assist into
The components (herein become second level components) of row power transfer, the failure trigger mechanism and failure mechanism of transmission of remaining parts and
It analyzes above similar.
Step 3: neural network Earthquake response is based on, according to the assembly relation between components and in power transmission process
In different degree reliability layered modeling is carried out to 3K planetary reduction gear, obtain reliability network figure, in reliability network figure altogether
There are Z layers: wherein the 1st layer of core component for 3K planetary reduction gear, such as input shaft, output shaft, intermediate propeller shaft, sun gear, row
Star-wheel, ring gear etc., the 2nd layer is the secondary components for directly affecting core component, such as bearing, shell, retaining ring, sleeve, spline
Set etc., the 3rd layer is the components for directly affecting secondary components, such as planet carrier, screw, nut, washer, end cap, successively class
It pushes away, determines the affiliated layering of each components in 3K planetary reduction gear.Each layer of components are built according to power direction of transfer
Vertical direction sequence；It is same to represent power direction of transfer for arrow in the 1st layer of core component reliability neural network diagram of 3K planetary reduction gear
When be also the failure direction of propagation, according to the state representation system mode of the last one components of arrow direction sequence, i.e., if the 1st
The failure of the last one components does not trigger in layer, illustrates that system dynamic transmitting is normal, system safety, if instead the last one
Components failure, which is triggered, illustrates system dynamic transmitting failure, thrashing；2nd layer, the 3rd layer ..., arrow is directed toward in Z layers
The components being directed toward according to failure propagation effect characteristic in upper one layer respective.
For the present embodiment, from the angle of power transfer, the main power transfer components of slat 3K planetary reduction gear
Including transmission shaft and gear, slat 3K planetary reduction gear kernel component reliability network figure (the 1st layer) as shown in Fig. 5,
10 be transmission shaft, and 31 be gear N3, and 33 be planetary gear, that is, includes gear N2 and gear N5, and 47 be gear N1, and 11 be gear N4,4
It is No. 2 output shafts for No. 1 output shaft, 1.
It acts directly on the secondary components that auxiliary carries out power transfer on key components and parts and belongs to slat 3K planetary reduction gear
The second layer of device reliability network figure, it includes the reliability network figure of secondary components is as shown in Fig. 6, wherein 7,9,18,
29,37,43 be bearing, and 16 be retaining ring, and 30 be copper sheathing, and 46 be planet carrier, and 34 be screw, and 5 be spline housing, and 45 be gasket, and 35 are
Shell.
Being divided into modeling method to establish according to above-mentioned reliable network includes the reliable of all components of slat 3K planetary reduction gear
Property network it is as shown in Fig. 7, parts title that specific each serial number represents, quantity such as table 2.
Step 4: using the failure rate Y=0.0600 of slat 3K planetary reduction gear as evaluation index, setting emulation total degree
Num is 105 times, initializes simulation times N=1, and system adds up Safe Times n=0.
Step 5: failure being transmitted to often because carrying out unified sample again altogether according to common cause failure Monte Carlo Simulation Strategy
In one components, to non-failed altogether because parameter is respectively according to parameter distribution independent sampling.
The formulation of common cause failure Monte Carlo Simulation Strategy utilizes common cause failure system dependability total probability model；
For there are the train of common cause failure, reliability total probability model can be indicated are as follows:
For there are the parallel system of common cause failure, reliability total probability model can be indicated are as follows:
Obtain full reliability total probability model when handling common cause failure problem to generate failure altogether because stress only carry out
Primary integral, R represent system dependability, and f (σ) represents generalized stress distribution density function, and it is close that f (S) represents GENERALIZED STRENGTH distribution
Function is spent, p represents series connection parts count, and q represents parts count in parallel.Common cause failure Monte Carlo Simulation Strategy is using entirely
The characteristics of reliability total probability model is when handling common cause failure problem, emulation when, to generate failure altogether because stress only take out
Sample is primary.
According to the common cause failure Monte Carlo Simulation Strategy of formulation in the present embodiment, input load TaAs failure
Altogether because, it is distributed and carries out Monte Carlo random sampling, secondly on by failure altogether because the components such as the gear, the axis that influence by
Carry out stress and intensity random sampling in a program according to evaluation method for failure in the above failure analysis, it is non-failed altogether because parameter according to
Evaluation method for failure in the above failure analysis carries out distribution independent sampling in a program.
Step 6: according to the triggering of the internal failure of each components and External Failure trigger condition, according to Z layers, Z-1
Layer, Z-2 layers ... the 2nd layer, the 1st layer of sequence successively updates each layer of spare parts logistics Ti；Spare parts logistics are divided into safety
With failure two states.
According to the triggering of the internal failure of each components and External Failure trigger condition in the present embodiment, according in attached drawing 7
4th layer, the 3rd layer, the 2nd layer, the 1st layer successively updates spare parts logistics Ti each time in attached drawing 7, and Ti=1 indicates i-th of components
Safety, Ti=0 indicates i-th of components failure.
Step 7: judging whether the last one components of arrow direction sequence fail in the 1st layer of attached drawing 7, i.e. the shape of part 1
State TiIt whether is 1；System state variables k=1 is set if part 1 does not fail, and is indicated system safety, otherwise k=0, is indicated system
System failure.
Step 8: updating simulation times N=N+1 and system adds up Safe Times n=n+k.
Step 9: judging whether simulation times meet N < Num, Num indicates total simulation times of setting, returns if meeting
Step 5 continues iteration, and otherwise terminator and statistical system accumulate Safe Times n, calculating reliability R=n/Num, crash rate Y
Crash rate is compared by=1-R with the probability of malfunction of formulation, according to result judgement 3K planetary reduction gear operating status, rationally
Arrange O&M maintenance.
The system dependability R=0.9526, crash rate Y=for the slat 3K planetary reduction gear that this time embodiment calculates
0.0474.The crash rate of gained slat 3K planetary reduction gear is less than required failure rate, illustrates this stage slat 3K planet
Retarder is in a safe condition.
Although the embodiments of the present invention has been shown and described above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art are not departing from the principle of the present invention and objective
In the case where can make changes, modifications, alterations, and variations to the above described embodiments within the scope of the invention.
Claims (2)
1. a kind of 3K planetary reduction gear reliability estimation method neural network based, it is characterised in that: the following steps are included:
Step 1: failure definition being carried out to each components of 3K planetary reduction gear based on neuronal structure, the failure definition includes
Three attributes, respectively input attribute, failure trigger attribute and output attribute；The failure trigger attribute includes External Failure touching
Clockwork spring part and internal failure trigger condition；
Step 2: after carrying out failure definition to each part, determine the internal failure mechanism of each part, External Failure mechanism and
Fail mechanism of transmission；
Step 3: neural network Earthquake response is based on, according to the assembly relation between components and in power transmission process
Different degree carries out reliability layered modeling to 3K planetary reduction gear, obtains reliability network figure, shares Z in reliability network figure
Layer: wherein the 1st layer be 3K planetary reduction gear core component, the 2nd layer is the secondary components for directly affecting core component, the 3rd
Layer is the components for directly affecting secondary components, and so on, determine affiliated point of each components in 3K planetary reduction gear
Layer；Direction sequence is established according to power direction of transfer to each layer of components；
Step 4: using the failure rate of 3K planetary reduction gear as evaluation index, initializing simulation times N=1, and initialize system
Accumulative Safe Times n=0；
Step 5: each is transmitted to because carrying out unified sample altogether to failure according to common cause failure Monte Carlo Simulation Strategy again
In components, to non-failed altogether because parameter is respectively according to parameter distribution independent sampling；
Step 6: according to the triggering of the internal failure of each components and External Failure trigger condition, according to Z layers, Z-1 layers, the
Z-2 layers ... the 2nd layer, the 1st layer of sequence successively updates each layer of spare parts logistics Ti；Spare parts logistics are divided into safety and lose
Imitate two states；
Step 7: judging whether the last one components of direction sequence in the 1st layer of reliability network figure fail, if not losing
Effect then sets system state variables k=1, indicates system safety, otherwise k=0, indicates thrashing；
Step 8: updating simulation times N=N+1 and system adds up Safe Times n=n+k；
Step 9: judging whether simulation times meet N < Num, Num indicates total simulation times of setting, the return step 5 if meeting
Continue iteration, otherwise terminator and statistical system accumulate Safe Times n, calculating reliability R=n/Num, crash rate Y=1-R,
Crash rate is compared with the probability of malfunction of formulation, according to result judgement 3K planetary reduction gear operating status.
2. a kind of 3K planetary reduction gear reliability estimation method neural network based, feature exist according to claim 1
In: in step 1, input attribute includes state input k, load F, the vibration x, torque T of components；Output attribute refers to output shape
State；External Failure trigger condition indicates another components for being connected and transmitting in system dynamic upper level with the components
The condition for failing and causing the components that can not receive system dynamic；Internal failure trigger condition indicates each of the components itself
A failure mode.
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