CN108182306A - Power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method - Google Patents
Power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method Download PDFInfo
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Abstract
The invention belongs to power train for vehicle studying technological domains, and in particular to a kind of power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method.Compared with prior art, the present invention rubs secondary geometrical characteristic parameter failure threshold as foundation using power train for vehicle key, it is equal for principle with the Reliability assessment result based on abrasive grain characteristic parameter degraded data and geometrical characteristic parameter degraded data, the reasonable estimation of abrasive grain characteristic parameter degradation failure threshold value is realized, is provided the foundation for the high-precision failure analysis of power train for vehicle, status assessment and fault detect.
Description
Technical field
The invention belongs to power train for vehicle studying technological domains, and in particular to a kind of power train for vehicle mill
The determining method of grain character parameter degradation failure threshold.
Background technology
Abrasive grain characteristic parameter degradation failure threshold value is that pair is rubbed in power train for vehicle by stablizing wear stage entrance
The value of abrasive grain characteristic parameter during the accelerated wear test stage, when certain abrasive grain characteristic parameter reaches its failure threshold, vehicle power passes
The failure rate of dynamic device will significantly increase or will be rapidly reached the durability limit, should not be continuing with.Abrasive grain characteristic parameter is degenerated
Failure threshold is to carry out the important evidence of power train for vehicle failure analysis and power train for vehicle status assessment
With the key criterion of fault detect.
Carrying out actuating unit status assessment needs to provide the degraded data of characteristic parameter and the failure of this feature parameter
Threshold value carries out status assessment to power train for vehicle at present and mainly takes two ways with fault detect：It is rubbed using key
The degraded data and failure threshold and the degraded data using oil liquid abrasive grain characteristic parameter of the secondary geometrical characteristic parameter of wiping and the threshold that fails
Value.
The degraded data of the secondary geometrical characteristic parameter of key friction can be by carrying out actuating unit to disassemble inspection
Measurement obtains, failure threshold can be analyzed according to design value and be obtained, but disassembles inspection and need actuating unit hanging out vehicle
Body, and it is decomposed, the secondary geometrical characteristic parameter changing value of crucial friction, this process need inside measuring device one by one
A large amount of human and material resources, financial resources are spent, usually carries out after vehicle travels 6000km once disassemble inspection at present, be not suitable for out
Open up the assessment of actuating unit real-time status.
The degraded data of oil liquid abrasive grain characteristic parameter can be examined by the fluid sample that actuating unit oil transportation mouth acquires
It measures out, collecting and analyzing for the data is more convenient, can carry out the assessment of actuating unit real-time status, but oil liquid abrasive grain is special
The failure threshold of parameter is levied, can refer to there is no specific design value, at present metallic element concentration, abrasion in determining lubricating oil
Earthquake intensity relies primarily on the engineering experience of designer, but the vehicle of different model moves when the failure threshold of abrasive grains characteristic parameter
For force actuators other than friction means difference in itself, lubricating oil systematic parameter and state also tend to difference, oily filters at different levels
Influence it is sufficiently complex, therefore, only carry out failure analysis, status assessment or fault detect with empirical failure threshold, it is impossible to
Fully consider the influence of the factors such as architectural difference, oily filter, working environment, the accuracy and confidence level of analysis result are relatively low.
For this purpose, a kind of power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method how is designed,
To improve the confidence level of the work such as power train for vehicle failure analysis, status assessment, fault detect and accuracy, become
The technical issues of urgently to be resolved hurrily.
Invention content
(1) technical problems to be solved
The technical problem to be solved by the present invention is to：For the defects in the prior art, a kind of vehicle power how is provided to pass
Dynamic device abrasive grain characteristic parameter degradation failure threshold value determination method, to realize the high-precision failure point of power train for vehicle
Analysis, status assessment and fault detect provide foundation.
(2) technical solution
In order to solve the above technical problems, the present invention provides a kind of power train for vehicle abrasive grain characteristic parameter degradation failure
Threshold value determination method the described method comprises the following steps：
Step S1, it analyzes and determines abrasive grain characteristic parameter and the secondary geometrical characteristic parameter of crucial friction in power train for vehicle
Correspondence；
Step S2, carry out power train for vehicle bench test；
Step S3, in collection step S2 the time-series rules data of power train for vehicle abrasive grain characteristic parameter and with its phase
The time-series rules data of the corresponding secondary geometrical characteristic parameter of crucial friction；
Step S4, the time-series rules data of the secondary geometrical characteristic parameter of crucial friction of each test sample are fitted, obtained
To the secondary abrasion timing variations curve of crucial friction using geometrical characteristic parameter as variable, with reference to geometrical characteristic parameter failure threshold,
Build the Reliability assessment function based on the crucial secondary geometrical characteristic parameter that rubs；
Step S5, the time-series rules data of the abrasive grain characteristic parameter of each test sample are fitted, obtained with abrasive grain spy
The abrasive grain characteristic parameter timing variations curve that parameter is variable is levied, it is assumed that in the case of failure threshold, structure is special based on abrasive grain
Levy the Reliability assessment function of parameter；
Step S6, various faults characteristic parameter can be utilized to carry out reliability assessment identical product, identical product
State of the art, use condition are all identical, in the case where not considering analytical error, are joined in synchronization using different faults feature
The result that number carries out reliability assessment is also identical, for this purpose, with " in identical product of the particular moment based on different faults characteristic parameter
Reliability assessment result is equal " it is principle, it builds the friction plate reliability based on geometrical characteristic parameter and abrasive grain characteristic parameter and comments
Estimate equation group, simultaneous solution abrasive grain characteristic parameter failure threshold.
Wherein, in the step S2, test sample amount is not less than 4.
Wherein, in the step S2, test period is not less than the half of projected life.
Wherein, in the step S3, abrasive grain characteristic parameter data acquisition time is acquired not less than geometrical characteristic parameter data
/ 3rd of time.
Wherein, it in the step S1, according to material composition, abrasion mechanism, abrasive grain topographical information, analyzes and determines vehicle power
The correspondence of abrasive grain characteristic parameter and the secondary geometrical characteristic parameter of crucial friction in transmission device.
Wherein, in the step S4, the sequential inspection for rejecting the geometrical characteristic parameter being collected into step S3 first is further included
Abnormal data in measured data.
Wherein, the abnormal data is and the deviation of average value is more than the measured value of twice of standard deviation.
Wherein, actuating unit abrasive grain characteristic parameter degradation failure threshold value determination method, which is characterized in that the step
In rapid S5, the abnormal data in the abrasive grain characteristic parameter time-series rules data rejected be collected into S3 first, abnormal number are further included
According to for and average value deviation be more than twice standard deviation measured value.
Wherein, the abnormal data is and the deviation of average value is more than the measured value of twice of standard deviation.
Wherein, in the step S3, experiment carries out power train for vehicle to disassemble detection, recording step S1 when completing
The middle secondary geometrical characteristic parameter degraded data of friction, disassembles detection number and is no less than 1 time.
(3) advantageous effect
Compared with prior art, the present invention is with the secondary geometrical characteristic parameter failure threshold of power train for vehicle key friction
It is worth for foundation, it is equal with the Reliability assessment result based on abrasive grain characteristic parameter degraded data and geometrical characteristic parameter degraded data
For principle, the reasonable estimation of abrasive grain characteristic parameter degradation failure threshold value is realized, is the high-precision mistake of power train for vehicle
Effect analysis, status assessment and fault detect provide the foundation.
The present invention has carried out application verification work in the actuating unit of certain type vehicle, ensure that power transmission fills
The precision of status assessment is put, will be ground using the degraded data of the secondary geometrical characteristic parameter of crucial friction and failure threshold and using fluid
Two methods of the degraded data and failure threshold of grain character parameter combine, and carrying out failure threshold for designer determines
Provide a kind of new idea and method.
Description of the drawings
Fig. 1 is technical solution of the present invention flow chart.
Specific embodiment
To make the purpose of the present invention, content and advantage clearer, with reference to the accompanying drawings and examples, to the present invention's
Specific embodiment is described in further detail.
The present invention is based on the secondary geometrical characteristic parameter actual measurement degraded data of power train for vehicle key friction, abrasive grain features
Parameter surveys the abrasive grain characteristic parameter degradation failure threshold value of degraded data and geometrical characteristic parameter failure threshold.
Specifically, the present invention provides a kind of determining for power train for vehicle abrasive grain characteristic parameter degradation failure threshold value
Method, as shown in Figure 1, the described method comprises the following steps：
Step S1, it analyzes and determines abrasive grain characteristic parameter and the secondary geometrical characteristic parameter of crucial friction in power train for vehicle
Correspondence；
Step S2, carry out power train for vehicle bench test；
Step S3, in collection step S2 the time-series rules data of power train for vehicle abrasive grain characteristic parameter and with its phase
The time-series rules data of the corresponding secondary geometrical characteristic parameter of crucial friction；
Step S4, the time-series rules data of the secondary geometrical characteristic parameter of crucial friction of each test sample are fitted, obtained
To the secondary abrasion timing variations curve of crucial friction using geometrical characteristic parameter as variable, with reference to geometrical characteristic parameter failure threshold,
Build the Reliability assessment function based on the crucial secondary geometrical characteristic parameter that rubs；
Step S5, the time-series rules data of the abrasive grain characteristic parameter of each test sample are fitted, obtained with abrasive grain spy
The abrasive grain characteristic parameter timing variations curve that parameter is variable is levied, it is assumed that in the case of failure threshold, structure is special based on abrasive grain
Levy the Reliability assessment function of parameter；
Step S6, various faults characteristic parameter can be utilized to carry out reliability assessment identical product, identical product
State of the art, use condition are all identical, in the case where not considering analytical error, are joined in synchronization using different faults feature
The result that number carries out reliability assessment is also identical, for this purpose, with " in identical product of the particular moment based on different faults characteristic parameter
Reliability assessment result is equal " it is principle, it builds the friction plate reliability based on geometrical characteristic parameter and abrasive grain characteristic parameter and comments
Estimate equation group, simultaneous solution abrasive grain characteristic parameter failure threshold.
Wherein, in the step S2, test sample amount is not less than 4.
Wherein, in the step S2, test period is not less than the half of projected life.
Wherein, in the step S3, abrasive grain characteristic parameter data acquisition time is acquired not less than geometrical characteristic parameter data
/ 3rd of time.
Wherein, it in the step S1, according to material composition, abrasion mechanism, abrasive grain topographical information, analyzes and determines vehicle power
The correspondence of abrasive grain characteristic parameter and the secondary geometrical characteristic parameter of crucial friction in transmission device.
Wherein, in the step S4, the sequential inspection for rejecting the geometrical characteristic parameter being collected into step S3 first is further included
Abnormal data in measured data.
Wherein, the abnormal data is and the deviation of average value is more than the measured value of twice of standard deviation.
Wherein, in the step S5, the abrasive grain characteristic parameter time-series rules data rejected be collected into S3 first are further included
In abnormal data, abnormal data is and the deviation of average value is more than the measured value of twice standard deviation.
Wherein, the abnormal data is and the deviation of average value is more than the measured value of twice of standard deviation.
Wherein, in the step S3, experiment carries out power train for vehicle to disassemble detection, recording step S1 when completing
The middle secondary geometrical characteristic parameter degraded data of friction, disassembles detection number and is no less than 1 time.
Embodiment 1
As shown in Figure 1, the present embodiment provides a kind of geometrical characteristic parameter degraded data secondary based on crucial friction, abrasive grain are special
Levy the power train for vehicle abrasive grain characteristic parameter degradation failure of parameter degradation data and geometrical characteristic parameter failure threshold
Threshold includes the following steps：
The information such as S1, foundation material composition, abrasion mechanism, abrasive grain pattern, analyze and determine to grind in power train for vehicle
Grain character parameter and the correspondence of the secondary geometrical characteristic parameter of crucial friction；
S2, carry out power train for vehicle bench test, test sample amount is not less than 4, and test period, which is not less than, to be set
Count the half in service life；
Power train for vehicle is carried out when S3, experiment are completed to disassemble detection, records the secondary geometric properties ginseng that rubs in S1
Number degraded data is disassembled detection number and is no less than 1 time, and timing acquiring lubricating oil sample is analyzed during experiment, record
Abrasive grain characteristic parameter degraded data corresponding with geometrical characteristic parameter, fluid sampling detection number are no less than 20, abrasive grain feature
Parameter acquisition time is not less than 1/3rd of the secondary geometrical characteristic parameter acquisition time of friction；
S4, reject the abnormal data in the geometrical characteristic parameter time-series rules data that are collected into S3, abnormal data be with
The deviation of average value is more than the measured value of twice of standard deviation, obtains one group of detection array [tj,xi(tj)], wherein tjRepresent jth time
At the time of carrying out disassembling detection to power train for vehicle, xi(tj) represent the secondary geometry that rubs during i-th of sample jth time detection
The detected value of characteristic parameter.
The secondary degree of wear of key friction can be characterized by the variation of relative dimensions, in the implementation case, be set in stabilization
Wear stage geometrical characteristic parameter linearly successively decreases relationship, and the function that critical size changes over time is X (t), then X (t)=X
(0)+Vt, wherein X (0) represent the initial value of the secondary geometric dimension of friction, have certain discreteness, according to central-limit theorem, recognize
It is the stochastic variable of Normal Distribution for product initial value, i.e.,Its mean value can be by product design with variance
Value is obtained with tolerance；V represents friction auxiliary scale cun rate of depreciation, and decisions such as friction subtask stress, material property, even
Similarly hereinafter a collection of product, rate of depreciation, according to central-limit theorem, can also be set same operating mode there are certain discreteness
For the stochastic variable of Normal Distribution, i.e.,According to detection array [tj,xi(tj)] a period of time can be obtained
(tj-1,tj) in rate of depreciation vij=(xi(tj-1)-xi(tj))/(tj-1-tj), further obtain the mean μ of rate of depreciationvWith
Variance
Key friction pair geometrical characteristic parameter X (t) for linear stochastic process model, for it is any given at the time of t, X (t)
For normally distributed random variable, and
E (X (t))=E (X (0)+Vt)=μ0+μvt
The Reliability assessment function based on the crucial secondary geometrical characteristic parameter time-series rules data that rub is built, key friction is secondary
Geometrical characteristic parameter it is less and less with the working time, it is believed that monotonic decreasing function, when size characteristic parameter be less than or equal to its
Failure threshold DxWhen, it is believed that it fails, and Reliability Function is at this time
Wherein Ψ represents Standard Normal Distribution, that is, obeys the normal distyribution function of N (0,1).
S5, reject the abnormal data in the abrasive grain characteristic parameter time-series rules data that are collected into S3, abnormal data be with
The deviation of average value is more than the measured value of twice of standard deviation, obtains one group of detection array [tk,yi(tk)], wherein tkRepresent kth time
At the time of fluid samples, yi(tk) represent the detected value of abrasive grain characteristic parameter during i-th of sample kth time fluid sampling.
This group of detection data is used and is modeled based on the method that performance degradation amount is distributed into row degradation.In the implementation case,
Abrasive grain characteristic parameter Normal Distribution at any one time, is stablizing wear stage, abrasive grain characteristic parameter linearly increases at any time
Long relationship, sequential change curve equation are Y (t)=at+b, and wherein Y (t) represents the abrasive grain feature in lubricating oil in moment t
The timing values of parameter, a, b are undetermined coefficient, according to detection array [tk,yi(tk)] can obtain in tkAbrasive grain characteristic parameter it is equal
Value μykAnd varianceThe situation that changed with time using least square method to mean value and standard deviation carries out parameter Estimation, obtains
The function of value and standard deviation；
The Reliability assessment function based on abrasive grain characteristic parameter time-series rules data is built, when abrasive grain characteristic parameter is with work
Between gradually increase, it is believed that monotonically increasing function, when abrasive grain characteristic parameter be more than or equal to its failure threshold DyWhen, it is believed that it occurs
Failure, Reliability Function is at this time
S6, utilization " equal in identical product Reliability assessment result of the particular moment based on various faults characteristic parameter "
Principle in the case of given time T, builds the friction plate Reliability assessment based on geometrical characteristic parameter and abrasive grain characteristic parameter
As a result equal equation, Rx(T)=Ry(T), i.e.,
The secondary geometrical characteristic parameter failure threshold D of crucial friction is given by designerx, abrasive grain characteristic parameter in prediction on such basis
Degradation failure threshold value Dy。
Embodiment 2
Below by taking certain type actuating unit as an example, the solution of the present invention is further described.
S1, certain type vehicle drive-train transposition internal toothed friction plate be the key components and parts for limiting its reliability, in clutch
In the device course of work, sliding friction occurs for internal toothed friction plate and external tooth friction plate, generates a large amount of wear debris and enters lubricating oil and follows
Loop system finds that only internal toothed friction plate contains Cu elements by the material composition analysis of movement parts each in actuating unit,
And lot of experimental data analysis shows in abrasive grain the abrasion of Cu constituent contents and actuating unit internal toothed friction plate have significantly
Correspondence, when shift clutch friction plate accelerated wear test, Cu contents significantly rise, therefore when in geometrical characteristic parameter selection
Tooth friction plate thickness variable quantity when abrasive grain characteristic parameter chooses Cu constituent contents, can pass through the abrasion of internal toothed friction plate thickness
The degradation failure threshold value of Cu concentration of element in detection data estimation fluid.
S2, carry out the type power train for vehicle bench test, test sample amount is 6, and projected life is small for 600
When, test period is 400 hours；
Timing acquiring lubricating oil sample carries out spectrum analysis during S3, experiment, records 6 actuating unit abrasive grains
The detection data of middle Cu constituent contents carries out actuating unit after the completion of experiment to disassemble detection, every actuating unit
Internal toothed friction plate amounts of thickness variation takes multiple measurements and records.
S4, the multiple measured value for collecting every actuating unit internal toothed friction plate amounts of thickness variation in S3, rejecting abnormalities
It is averaged after data, obtains amounts of thickness variation number of 6 actuating unit internal toothed friction plate samples after experiment in 400 hours
According to being shown in Table 1.
1.400 hours friction plates of table disassemble detection amounts of thickness variation data (unit：mm)
| Actuating unit serial number | Amounts of thickness variation |
| 1 | 0.084 |
| 2 | 0.078 |
| 3 | 0.066 |
| 4 | 0.111 |
| 5 | 0.072 |
| 6 | 0.057 |
According to central-limit theorem, friction disc wear rate V Normal Distributions, distribution function is：
μv=1.95e-4
σv=4.672e-4
The design size of this type of actuating unit friction plate is 3.2 ± 0.03mm, according to 3 σ principles, determines that it is distributed letter
Number is：
μ0=3.2
σ0=0.01
Its friction plate thickness wear out failure threshold value DxFor 3mm, in t moment, its reliability is：
S5,6 actuating unit abrasive grain Cu detection of content of element data in S3 are collected, one is obtained after rejecting abnormalities data
Group Cu constituent content System reliabilities, are shown in Table 2.
2. fluid Cu constituent content System reliability (units of table：10-6ppm)
Cu concentration of element is linearly incremented by relationship at any time in the type actuating unit abrasive grain, and degenrate function was fitted
Cheng Wei：
The mean value and standard deviation of table 3.Cu concentration of element at a time
The situation that changed with time using least square method to mean value and variance carries out parameter Estimation, obtains mean value and variance
Function；
μy(t)=0.5242t+34.817
σy(t)=0.1489t-0.7084
Since the degradation failure threshold value of Cu constituent contents in abrasive grain is difficult to provide by design, D is used hereinyIt represents, at this time
Reliability Function is：
S6, with it is " equal in identical product Reliability assessment result of the particular moment based on various faults characteristic parameter " for original
Then, it is contemplated that be within 600 hours the projected life of the type actuating unit, take T=600 hours, make R at this timex(T)=Ry(T),
I.e.
Fluid Cu element degradation failure threshold values D can be provided by above formulayFor 596.6 × 10-6ppm.
As can be seen from the above embodiments, the secondary geometrical characteristic parameter failure threshold of the crucial friction of the present invention is foundation, with base
Equal in the Reliability assessment result of abrasive grain characteristic parameter degraded data and geometrical characteristic parameter degraded data is principle, is realized
The reasonable estimation of abrasive grain characteristic parameter degradation failure threshold value is commented for the high-precision failure analysis of power train for vehicle, state
Estimate and provide the foundation with fault detect, and information utilization is high, there is preferable practicability.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, without departing from the technical principles of the invention, several improvement and deformation can also be made, these are improved and deformation
Also it should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method, which is characterized in that described
Method includes the following steps：
Step S1, pair for determining abrasive grain characteristic parameter and the secondary geometrical characteristic parameter of crucial friction in power train for vehicle is analyzed
It should be related to；
Step S2, carry out power train for vehicle bench test；
Step S3, time-series rules data of power train for vehicle abrasive grain characteristic parameter and corresponding thereto in collection step S2
The secondary geometrical characteristic parameter of crucial friction time-series rules data；
Step S4, the time-series rules data of the secondary geometrical characteristic parameter of crucial friction of each test sample are fitted, obtain with
Crucial friction secondary abrasion timing variations curve of the geometrical characteristic parameter for variable, with reference to geometrical characteristic parameter failure threshold, structure
Reliability assessment function based on the crucial secondary geometrical characteristic parameter that rubs；
Step S5, the time-series rules data of the abrasive grain characteristic parameter of each test sample are fitted, obtain joining with abrasive grain feature
Abrasive grain characteristic parameter timing variations curve of the number for variable, it is assumed that in the case of failure threshold, structure is joined based on abrasive grain feature
Several Reliability assessment functions；
Step S6, various faults characteristic parameter can be utilized to carry out reliability assessment, the technology of identical product identical product
State, use condition are all identical, in the case where not considering analytical error, are opened in synchronization using different faults characteristic parameter
The result for opening up reliability assessment is also identical, for this purpose, with " reliable in identical product of the particular moment based on different faults characteristic parameter
It is equal to spend assessment result " it is principle, build the friction plate Reliability assessment side based on geometrical characteristic parameter and abrasive grain characteristic parameter
Journey group, simultaneous solution abrasive grain characteristic parameter failure threshold.
2. power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method as described in claim 1,
It is characterized in that, in the step S2, test sample amount is not less than 4.
3. power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method as described in claim 1,
It is characterized in that, in the step S2, test period is not less than the half of projected life.
4. power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method as described in claim 1,
It is characterized in that, in the step S3, abrasive grain characteristic parameter data acquisition time is not less than geometrical characteristic parameter data acquisition time
1/3rd.
5. power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method as described in claim 1,
It is characterized in that, in the step S1, according to material composition, abrasion mechanism, abrasive grain topographical information, analyzes and determine vehicle drive-train
The correspondence of abrasive grain characteristic parameter and the secondary geometrical characteristic parameter of crucial friction in device.
6. power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method as described in claim 1,
It is characterized in that, in the step S4, further includes the time-series rules number of geometrical characteristic parameter rejected be collected into step S3 first
Abnormal data in.
7. power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method as claimed in claim 6,
It is characterized in that, the abnormal data is and the deviation of average value is more than the measured value of twice of standard deviation.
8. power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method as described in claim 1,
It is characterized in that, in the step S5, further includes in the abrasive grain characteristic parameter time-series rules data rejected be collected into S3 first
Abnormal data, abnormal data is and the deviation of average value is more than the measured value of twice of standard deviation.
9. power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method as claimed in claim 8,
It is characterized in that, the abnormal data is and the deviation of average value is more than the measured value of twice of standard deviation.
10. power train for vehicle abrasive grain characteristic parameter degradation failure threshold value determination method as described in claim 1,
It is characterized in that, in the step S3, experiment carries out power train for vehicle to disassemble detection when completing, and rubs in recording step S1
Secondary geometrical characteristic parameter degraded data is wiped, detection number is disassembled and is no less than 1 time.
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