CN107025345A - A kind of Forecasting Methodology of engineering machinery vehicle failure time - Google Patents
A kind of Forecasting Methodology of engineering machinery vehicle failure time Download PDFInfo
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- CN107025345A CN107025345A CN201710215882.7A CN201710215882A CN107025345A CN 107025345 A CN107025345 A CN 107025345A CN 201710215882 A CN201710215882 A CN 201710215882A CN 107025345 A CN107025345 A CN 107025345A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
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Abstract
A kind of Forecasting Methodology of engineering machinery vehicle failure time, comprises the following steps：System of vehicle transmission shaft universal-joint fit clearance sample data is obtained, including：Different type vehicle uses the sample data of different time；Engineering machinery vehicle is set up using abrasion finite element prediction model according to the sample data of acquisition, and passes through finite element analysis and optimizes the wear model；Wherein optimization uses Bayesian model, adds the posterior infromation and vehicle actual useful year of expert；According to the wear model of gained in above-mentioned steps, the universal joint fit clearance to input is judged use time；The time limit according to as defined in forcing to scrap subtracts the failure time that use time is predicted.There are reliable assessment means for the remaining use time of vehicle, so that greatling save vehicle vehicle condition assesses time and cost.
Description
Technical field
The present invention relates to vehicle scrapping method of testing, more particularly to a kind of engineering machinery vehicle tested based on power transmission shaft
The method of testing of finite element analysis.
Background technology
The automobile industry of China is developed rapidly in recent decades, and the use of automobile has its specific time limit, especially
It is that there is pressure to scrap the time limit for country, this is many users and supervision department problem of concern.Engineering machinery vehicle is used
Environment is generally relatively more severe, and the more severe vehicle of vehicle condition would generally cause very big accident to safety, and personal owner is usual
It is unwilling actively to go to scrap and repair, often results in very big danger, administrative department needs a kind of simple and reliable appraisal procedure pair
Engineering machinery vehicle carries out accurate assessment to supervise.And the rapid second-hand automobile market of latest developments is even more to need one kind just
The method for really precisely evaluating vehicle behaviour in service, to ensure that vehicle safety is reliably used, so that convenient appraisal.It is above-mentioned in order to solve
Problem, it is necessary to study vehicle assess use time method, failure time is predicted.At present, exist in the prior art logical
The methods such as tire are crossed to be estimated, but equipment of the tire as often changing, unless used present tire always, otherwise pass through
Tire is estimated extremely unreliable.
The content of the invention
The technical problems to be solved by the invention are to provide a kind of Forecasting Methodology of engineering machinery vehicle failure time, can
It is convenient to obtain vehicle condition, effectively vehicle vehicle condition is judged, so that solving the accurate judgement that is difficult to of existing method presence makes
With situation and estimate and scrap time limit problem.
The technical solution adopted for the present invention to solve the technical problems is：A kind of engineering machinery vehicle failure time is provided
Forecasting Methodology, comprises the following steps：
(a) system of vehicle transmission shaft universal-joint fit clearance sample data is obtained, including：Different type vehicle uses different time
Sample data；
(b) engineering machinery vehicle is set up using abrasion finite element prediction model according to the sample data of acquisition, and passed through
Finite element analysis optimizes the wear model；Wherein optimization uses Bayesian model, and the posterior infromation and vehicle for adding expert are actual
Service life；
(c) according to the wear model of gained in step (b), when being judged to have used to the universal joint fit clearance of input
Between；
(d) time limit according to as defined in forcing to scrap subtracts the failure time that use time is predicted.
Described sample data carries out classification input according to different vehicle and the time time limit and collected, such as with certain brand type
Number excavator service life is arranged with excel forms.
The Bayesian model that Optimized model is used in described step (b) is analyzed time series, and to future
The performance time carries out quantitative forecast, and the actual correct result after expert judgments obtained is further used as into sample progress
Training.
Force to scrap the defined time limit in described step (d) using national standard as foundation.
Technique effect
As a result of above-mentioned technical scheme, the present invention compared with prior art, has the following advantages that and actively imitated
Really：Universal joint gap sample data of the invention based on bearing, establishes finite element analysis model, with relatively accurate technology
Effect, can facilitate test, fast and effectively feature.There are reliable assessment means for remaining use time, so as to save significantly
Save vehicle vehicle condition and assess time and cost.
Brief description of the drawings
Fig. 1 is the flow chart of the present invention；
Embodiment
With reference to specific embodiment, the present invention is expanded on further.It should be understood that these embodiments are merely to illustrate the present invention
Rather than limitation the scope of the present invention.In addition, it is to be understood that after the content of the invention lectured has been read, people in the art
Member can make various changes or modifications to the present invention, and these equivalent form of values equally fall within the application appended claims and limited
Scope.
A kind of Forecasting Methodology of engineering machinery vehicle failure time, comprises the following steps：
(a) system of vehicle transmission shaft universal-joint fit clearance sample data is obtained, including：Different type vehicle uses different time
Sample data；
(b) engineering machinery vehicle is set up using abrasion finite element prediction model according to the sample data of acquisition, and passed through
Finite element analysis optimizes the wear model；Wherein optimization uses Bayesian model, and the posterior infromation and vehicle for adding expert are actual
Service life；
(c) according to the wear model of gained in step (b), when being judged to have used to the universal joint fit clearance of input
Between；
(d) time limit according to as defined in forcing to scrap subtracts the failure time that use time is predicted.
Below by certain brand need to assess used the haulage truck of 9 months 4 years exemplified by further illustrate the present invention.
1. the universal joint gap data of the same brand haulage truck of collection, FEM model is set up according to simulation algorithm；
2. inputting the universal joint gap data for the haulage truck that need to be assessed, current clearance reaches 0.5mm, is calculated analytically
Use time 5 years are obtained, national regulation forces failure time to be 15 years, and therefore, prediction obtains it is also possible to use 10 years.
3. result of calculation and actual result comparative analysis, it is contemplated that the engineering truck use environment is severe, wear and tear larger, by mistake
Difference is relatively accurate at 3 months.
The foregoing is only a preferred embodiment of the present invention, but protection scope of the present invention be not limited thereto,
Any one skilled in the art the invention discloses technical scope in, the change or replacement that can be readily occurred in,
It should all be included within the scope of the present invention.
Claims (1)
1. a kind of Forecasting Methodology of engineering machinery vehicle failure time, comprises the following steps：
A) system of vehicle transmission shaft universal-joint fit clearance sample data is obtained, including：Different type vehicle uses the sample of different time
Notebook data；
B) engineering machinery vehicle is set up using abrasion finite element prediction model according to the sample data of acquisition, and passes through finite element
The analysis optimization wear model；Wherein optimization uses Bayesian model, adds posterior infromation and the vehicle Shi Jishiyong year of expert
Limit；
C) according to the wear model of gained in step (b), the universal joint fit clearance to input is judged use time；
D) time limit according to as defined in forcing to scrap subtracts the failure time that use time is predicted.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710215882.7A CN107025345A (en) | 2017-03-31 | 2017-03-31 | A kind of Forecasting Methodology of engineering machinery vehicle failure time |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710215882.7A CN107025345A (en) | 2017-03-31 | 2017-03-31 | A kind of Forecasting Methodology of engineering machinery vehicle failure time |
Publications (1)
| Publication Number | Publication Date |
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| CN107025345A true CN107025345A (en) | 2017-08-08 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN201710215882.7A Pending CN107025345A (en) | 2017-03-31 | 2017-03-31 | A kind of Forecasting Methodology of engineering machinery vehicle failure time |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108053075A (en) * | 2017-12-27 | 2018-05-18 | 北京中交兴路车联网科技有限公司 | A kind of scrap-car Forecasting Methodology and system |
| CN109635965A (en) * | 2018-12-24 | 2019-04-16 | 成都四方伟业软件股份有限公司 | Bus scraps decision-making technique, device and readable storage medium storing program for executing |
| CN112036694A (en) * | 2020-10-27 | 2020-12-04 | 重庆首讯科技股份有限公司 | Expressway electromechanical equipment life cycle prediction method and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101984333A (en) * | 2010-09-16 | 2011-03-09 | 齐晓杰 | Method for forecasting remaining service life of retreaded tire body of heavy-duty vehicle |
| CN102402727A (en) * | 2011-11-10 | 2012-04-04 | 中联重科股份有限公司 | System and method for predicting residual life of part of engineering machine |
| CN103279627A (en) * | 2013-06-17 | 2013-09-04 | 清华大学 | Heat-machinery-abrasion coupling analysis numerical simulation method based on finite element |
| CN103838931A (en) * | 2014-03-10 | 2014-06-04 | 太原科技大学 | Method for evaluating remanufacturing access period of engineering mechanical arm rest class structure |
-
2017
- 2017-03-31 CN CN201710215882.7A patent/CN107025345A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101984333A (en) * | 2010-09-16 | 2011-03-09 | 齐晓杰 | Method for forecasting remaining service life of retreaded tire body of heavy-duty vehicle |
| CN102402727A (en) * | 2011-11-10 | 2012-04-04 | 中联重科股份有限公司 | System and method for predicting residual life of part of engineering machine |
| CN103279627A (en) * | 2013-06-17 | 2013-09-04 | 清华大学 | Heat-machinery-abrasion coupling analysis numerical simulation method based on finite element |
| CN103838931A (en) * | 2014-03-10 | 2014-06-04 | 太原科技大学 | Method for evaluating remanufacturing access period of engineering mechanical arm rest class structure |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108053075A (en) * | 2017-12-27 | 2018-05-18 | 北京中交兴路车联网科技有限公司 | A kind of scrap-car Forecasting Methodology and system |
| CN108053075B (en) * | 2017-12-27 | 2021-03-26 | 北京中交兴路车联网科技有限公司 | Scrapped vehicle prediction method and system |
| CN109635965A (en) * | 2018-12-24 | 2019-04-16 | 成都四方伟业软件股份有限公司 | Bus scraps decision-making technique, device and readable storage medium storing program for executing |
| CN112036694A (en) * | 2020-10-27 | 2020-12-04 | 重庆首讯科技股份有限公司 | Expressway electromechanical equipment life cycle prediction method and system |
| CN112036694B (en) * | 2020-10-27 | 2024-02-23 | 重庆首讯科技股份有限公司 | Highway electromechanical equipment life cycle prediction method and system |
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Application publication date: 20170808 |