CN106441851A - Method for detecting fatigue life of mechanical part - Google Patents
Method for detecting fatigue life of mechanical part Download PDFInfo
- Publication number
- CN106441851A CN106441851A CN201610948649.5A CN201610948649A CN106441851A CN 106441851 A CN106441851 A CN 106441851A CN 201610948649 A CN201610948649 A CN 201610948649A CN 106441851 A CN106441851 A CN 106441851A
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- Prior art keywords
- machine components
- measured
- fatigue
- fatigue life
- strain
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
- G01M13/04—Bearings
Abstract
An embodiment of the invention discloses a method for detecting the fatigue life of a mechanical part. The method includes: acquiring the load of a to-be-detected mechanical part in real time, and generating load spectrum; detecting the fatigue parameters of the to-be-detected mechanical part; identifying the weak node of the to-be-detected mechanical part and the corresponding stress or strain of the weak node according to the generated load spectrum of the to-be-detected mechanical part and the detected fatigue parameters; determining the fatigue life of the to-be-detected mechanical part according to the identified weak node of the to-be-detected part and the corresponding stress of strain of the weak node. The method has the advantages that the fatigue life of the mechanical part can be estimated in advance, the method is high in universality, applicable to mechanical parts such as rolling bearings and accurate in detecting result, and the method has an important reference value to mechanical part design and an actual production process.
Description
Technical field
The present invention relates to machine components detection technique field, more particularly, it relates to a kind of machine components are tired
The detection method in life-span.
Background technology
Generally, machine components such as rolling bearing, which is good in lubrication, and under conditions of entering without impurity, fatigue rupture is
Its main cause that damages.It is true that as most machine components are all operated under the load of circulation change, fatigue rupture
The main damage form of rolling bearing is not only, fatigue rupture is also actually the main damage form of universal machine parts.
According to external statistics, the 50%-90% that machine components are destroyed is fatigue rupture, and as machinery is to high temperature, at a high speed and large-scale
Change and develop, machine work stress more and more higher, working condition is more and more severe, and fatigue failure accident also emerges in an endless stream.
In general, when machine components occur fatigue rupture, stress level is often much smaller than the yield stress of material itself
And strength degree.The fatigue rupture of machine components often occurs suddenly, causes catastrophic failure, and industry is highly desirable can be to machine
The fatigue life of tool part is detected.
Content of the invention
In view of the above problems, it is tired that a kind of machine components for partly or entirely solving the above problems are embodiments provided
The detection method in labor life-span, to estimate machine components fatigue life in advance.
In order to solve above-mentioned technical problem, the application is adopted the following technical scheme that：
A kind of detection method of machine components fatigue life according to embodiments of the present invention, which includes：
Obtain the load of machine components to be measured in real time and generate loading spectrum；
Detect the damage parameters of machine components to be measured；
The damage parameters identification to be measured mechanical zero that loading spectrum according to the machine components to be measured of above-mentioned generation is obtained with detection
The weak node of part and the corresponding stress of weak node or strain；
The weak node of the machine components to be measured for being obtained according to above-mentioned identification and the corresponding stress of weak node or strain,
Determine the fatigue life of machine components to be measured.
Wherein, the load for obtaining machine components to be measured in real time generate loading spectrum and specifically include：
Detect and record the load history of machine components to be measured, the load history according to machine components to be measured reflects
Penetrate the loading spectrum for obtaining machine components to be measured.
Wherein, the loading spectrum tool for obtaining machine components to be measured according to the mapping of the load history of machine components to be measured
Body includes：
Using cycle counting method, sliding-model control is carried out to the load history of machine components to be measured, obtain discrete change
Amplitude loading spectrum.
Wherein, the loading spectrum for obtaining machine components to be measured according to the mapping of the load history of machine components to be measured
Specifically include：
By the Fourier transformation of time domain/frequency domain, and in frequency domain through vibration synthesis real load time history, the company of being formed
Continuous stochastic process loading spectrum.
Wherein, the damage parameters of the machine components to be measured include：
Pulsating stress and corresponding strain, load and corresponding life-span, and fatigue limit.
Wherein, the damage parameters identification that the loading spectrum of the machine components to be measured according to above-mentioned generation and detection are obtained is treated
The weak node of survey machine components and the corresponding stress of weak node or strain are specifically included：
Using Neuber method the cyclic stress-strain curve with reference to machine components to be measured is revised, machine components to be measured are entered
Row elastoplasticity is solved, and is obtained the strain history at each position of UUT, and is compared according to the strain threshold for setting, the weak section of identification
Point, and the corresponding stress of weak node or strain.
Wherein, the fatigue life of machine components to be measured is determined using the accumulative rule of fatigue damage.
Wherein, the accumulative rule of the fatigue damage is specifically included：
The damage that one Cyclic Stress is caused：D=1/N, wherein N are the fatigue life under current load level；
Under variable amplitude loading, the damage that n Cyclic Stress is caused：Wherein NiFor corresponding different loads level
Fatigue life；
Critical fatigue damage value is Dc=1.
Wherein, when fatigue damage reaches critical fatigue damage value DcWhen, the most short node of the mechanical part life of detection, then treat
Survey the fatigue life N of machine componentsx=t*n/525600, unit is year；
Wherein, n is the stress-number of cycles of the node, and t is the duration of each Cyclic Stress of node, and unit is for dividing
Clock.
A kind of detection method of machine components fatigue life according to embodiments of the present invention, by obtaining machinery to be measured in real time
The load of part simultaneously generates loading spectrum；Detect the damage parameters of machine components to be measured；Machine components to be measured according to above-mentioned generation
Loading spectrum and the damage parameters that obtain of detection recognize weak node and the corresponding stress of weak node of machine components to be measured
Or strain；The weak node of the machine components to be measured for being obtained according to above-mentioned identification and the corresponding stress of weak node or strain,
Determine the fatigue life of machine components to be measured, so as to realize estimating in advance machine components fatigue life, highly versatile, it is applicable to
The machine components such as rolling bearing, testing result is accurate, and the design to machine components and actual production process have important reference
It is worth.
Description of the drawings
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
Accompanying drawing to be used needed for technology description is had to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments described in invention, for those of ordinary skill in the art, can also obtain other according to these accompanying drawings
Accompanying drawing.
Fig. 1 is that a kind of specific embodiment flow process of the detection method of the machine components fatigue life according to the present invention is illustrated
Figure.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, the every other embodiment obtained by those of ordinary skill in the art, belong to present invention protection
Scope.
With reference to shown in Fig. 1, the figure is being embodied as according to a kind of detection method of machine components fatigue life of the present invention
Example schematic flow sheet.
As shown, the detection method of the machine components fatigue life of the present embodiment mainly comprises the steps：
Step S1：Obtain the load of machine components to be measured in real time, generate loading spectrum；
When implementing, the load history of to be measured machine components can be detected and be recorded first, according to be measured mechanical zero
The load history mapping of part obtains the loading spectrum of machine components to be measured.By the loading spectrum, can be with clear mathematics shape
Formula is described and being capable of load condition, the weak node being easy to subsequently to machine components to be measured suffered by constitutionally reflection parts
It is identified, also allows for computer and read and process.
As an optional embodiment, above-mentioned obtained according to the mapping of the load history of machine components to be measured to be measured
Implementing for the loading spectrum of machine components can in the following way, i.e.,：Using load of the cycle counting method to machine components to be measured
Lotus time history carries out sliding-model control, obtains discrete Variable Amplitude loading spectrum.
In addition, as another optional embodiment, above-mentioned according to the mapping of the load history of machine components to be measured
The implementing for loading spectrum for obtaining machine components to be measured can also in the following way, i.e.,：Fourier by time domain/frequency domain
Conversion, and in frequency domain through vibration synthesis real load time history, form continuous stochastic process loading spectrum.
Step S2：Detect the damage parameters of machine components to be measured；
When implementing, in the present embodiment the damage parameters of machine components to be measured may include pulsating stress and corresponding should
Change, load and corresponding life-span, and fatigue limit etc., other damage parameters can also be determined according to practical situation in practice,
Here it is not specifically limited.
Step S3：According to the loading spectrum of machine components to be measured and the weak node of damage parameters identification machine components to be measured,
And the corresponding stress of weak node or strain；
When implementing, can be identified using such as various modes in the present embodiment, for example using correction Neuber method simultaneously
In conjunction with the cyclic stress-strain curve of machine components to be measured, elastoplasticity solution is carried out to machine components to be measured, obtain UUT
The strain history at each position, and compared according to the strain threshold for setting, recognize weak node, and the corresponding stress of weak node
Or strain.As the weak node of machine components to be measured is the essential intrinsic factor of its fatigue life of impact, to be measured by recognizing
The weak node of machine components, can be that the fatigue life of subsequent calculations machine components to be measured provides foundation, improve result of calculation
Accuracy.
Step S4：According to the weak node of machine components to be measured, and the corresponding stress of weak node or strain, using tired
The accumulative rule of strain wound, calculates the fatigue life of machine components to be measured.
When implementing, the accumulative rule of following fatigue damages can be adopted in the present embodiment, i.e.,：
The damage that one Cyclic Stress is caused：D=1/N, wherein N are the fatigue life under current load level；
Under variable amplitude loading, the damage that n Cyclic Stress is caused：Wherein NiFor corresponding different loads level
Fatigue life；
Critical fatigue damage value is Dc=1.
By the accumulative rule of fatigue damage, the damage for singly eating that Cyclic Stress is caused, and repeatedly Cyclic Stress can be calculated
The progressive damage for causing, and the fatigue life of machine components to be measured can be calculated with reference to critical fatigue data.
Explanation is needed, in this step S4, when fatigue damage reaches critical fatigue damage value DcWhen, detect the machine components longevity
Most short node is ordered, then the fatigue life N of machine components to be measuredx=t*n/525600, unit is year；
Wherein, n is the stress-number of cycles of the node, and t is the duration of each Cyclic Stress of node, and unit is for dividing
Clock.
To sum up, according to the detection method of the machine components fatigue life of above-described embodiment, by obtaining machinery to be measured in real time
The load of part simultaneously generates loading spectrum；Detect the damage parameters of machine components to be measured；Machine components to be measured according to above-mentioned generation
Loading spectrum and the damage parameters that obtain of detection recognize weak node and the corresponding stress of weak node of machine components to be measured
Or strain；The weak node of the machine components to be measured for being obtained according to above-mentioned identification and the corresponding stress of weak node or strain,
Determine the fatigue life of machine components to be measured, so as to realize estimating in advance machine components fatigue life, highly versatile, it is applicable to
The machine components such as rolling bearing, testing result is accurate, and the design to machine components and actual production process have important reference
It is worth.
The technical scheme for above embodiment of the present invention being provided is described in detail, specific case used herein
The principle and embodiment of the embodiment of the present invention is set forth, the explanation of above example is only applicable to help and understands this
The principle of inventive embodiments；Simultaneously for one of ordinary skill in the art, according to the embodiment of the present invention, in specific embodiment party
All will change in formula and range of application, i.e., it should be noted that above-described embodiment the present invention will be described rather than
Limit the invention, and those skilled in the art can design without departing from the scope of the appended claims
Alternative embodiment.
Claims (9)
1. a kind of detection method of machine components fatigue life, it is characterised in that include：
Obtain the load of machine components to be measured in real time and generate loading spectrum；
Detect the damage parameters of machine components to be measured；
The damage parameters that loading spectrum according to the machine components to be measured of above-mentioned generation is obtained with detection recognize machine components to be measured
Weak node and the corresponding stress of weak node or strain；
The weak node of the machine components to be measured for being obtained according to above-mentioned identification and the corresponding stress of weak node or strain, determine
The fatigue life of machine components to be measured.
2. the detection method of machine components fatigue life according to claim 1, it is characterised in that the real-time acquisition is treated
Survey the load of machine components and generate loading spectrum and specifically include：
Detect and record the load history of machine components to be measured, the load history according to machine components to be measured maps
Loading spectrum to machine components to be measured.
3. the detection method of machine components fatigue life according to claim 2, it is characterised in that described according to machine to be measured
The load history mapping of tool part obtains the loading spectrum of machine components to be measured and specifically includes：
Using cycle counting method, sliding-model control is carried out to the load history of machine components to be measured, obtain discrete Variable Amplitude
Loading spectrum.
4. the detection method of machine components fatigue life according to claim 2, it is characterised in that described according to machine to be measured
The load history mapping of tool part obtains specifically including for the loading spectrum of machine components to be measured：
By the Fourier transformation of time domain/frequency domain, and in frequency domain through vibration synthesis real load time history, formed continuous
Stochastic process loading spectrum.
5. the detection method of machine components fatigue life according to claim 1, it is characterised in that described to be measured mechanical zero
The damage parameters of part include：
Pulsating stress and corresponding strain, load and corresponding life-span, and fatigue limit.
6. the detection method of machine components fatigue life according to claim 5, it is characterised in that described according to above-mentioned life
The loading spectrum of the machine components to be measured for becoming and the damage parameters that obtain of detection recognize the weak node of machine components to be measured and thin
The corresponding stress of weak bus or strain are specifically included：
Using revising the Neuber method cyclic stress-strain curve with reference to machine components to be measured carries out bullet to machine components to be measured
Plasticity is solved, and is obtained the strain history at each position of UUT, and is compared according to the strain threshold for setting, recognizes weak node,
And the corresponding stress of weak node or strain.
7. the detection method of machine components fatigue life according to claim 1, it is characterised in that tired using fatigue damage
Meter rule determines the fatigue life of machine components to be measured.
8. the detection method of machine components fatigue life according to claim 7, it is characterised in that the fatigue damage is tired out
Meter rule is specifically included：
The damage that one Cyclic Stress is caused：D=1/N, wherein N are the fatigue life under current load level；
Under variable amplitude loading, the damage that n Cyclic Stress is caused：Wherein NiFatigue for corresponding different loads level
Life-span；
Critical fatigue damage value is Dc=1.
9. the detection method of machine components fatigue life according to claim 8, it is characterised in that when fatigue damage reaches
Critical fatigue damage value DcWhen, the most short node of mechanical part life is detected, then the fatigue life N of machine components to be measuredx=t*n/
525600, unit is year；
Wherein, n is the stress-number of cycles of the node, and t is the duration of each Cyclic Stress of node, and unit is minute.
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Cited By (7)
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| CN107907314A (en) * | 2017-10-22 | 2018-04-13 | 成都具鑫机械设备有限公司 | The fatigue test device and test method of a kind of machine components |
| CN109201884A (en) * | 2017-06-30 | 2019-01-15 | 株式会社日立制作所 | Die life decision maker, press forming die assembly and stamping object autofrettage |
| CN109708882A (en) * | 2019-02-27 | 2019-05-03 | 上海大制科技有限公司 | Horizontal feed device drives axis fatigue failure prediction technique and device |
| CN110702410A (en) * | 2019-10-15 | 2020-01-17 | 中国直升机设计研究所 | Method for acquiring fatigue limit of joint bearing connection structure |
| CN111931297A (en) * | 2020-09-24 | 2020-11-13 | 西门子交通技术(北京)有限公司 | Method and device for determining fatigue degree and method and device for determining maintenance plan |
| CN112585444A (en) * | 2018-08-21 | 2021-03-30 | 采埃孚股份公司 | Method and system for directly acquiring theoretical damage of at least one component of equipment |
| TWI794052B (en) * | 2022-03-14 | 2023-02-21 | 中國鋼鐵股份有限公司 | Abrasion evaluation method for grooves of grooved roller |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109201884A (en) * | 2017-06-30 | 2019-01-15 | 株式会社日立制作所 | Die life decision maker, press forming die assembly and stamping object autofrettage |
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| CN110702410A (en) * | 2019-10-15 | 2020-01-17 | 中国直升机设计研究所 | Method for acquiring fatigue limit of joint bearing connection structure |
| CN110702410B (en) * | 2019-10-15 | 2021-08-13 | 中国直升机设计研究所 | Method for acquiring fatigue limit of joint bearing connection structure |
| CN111931297A (en) * | 2020-09-24 | 2020-11-13 | 西门子交通技术(北京)有限公司 | Method and device for determining fatigue degree and method and device for determining maintenance plan |
| TWI794052B (en) * | 2022-03-14 | 2023-02-21 | 中國鋼鐵股份有限公司 | Abrasion evaluation method for grooves of grooved roller |
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Application publication date: 20170222 |