CN107255549A - A kind of rotor multiple spot amount of unbalance recognition methods - Google Patents
A kind of rotor multiple spot amount of unbalance recognition methods Download PDFInfo
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- G—PHYSICS
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M1/00—Testing static or dynamic balance of machines or structures
- G01M1/14—Determining imbalance
- G01M1/16—Determining imbalance by oscillating or rotating the body to be tested
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Abstract
The invention discloses a kind of rotor multiple spot amount of unbalance recognition methods, have the advantages that global optimizing ability and particle cluster algorithm local optimal searching ability are stronger using genetic algorithm, be applied to rotor multiple spot amount of unbalance identification process.The present invention is based on rotor-support-foundation system structural information, sets up rotor-support-foundation system lumped-mass model, obtains the theoretical response of rotor-support-foundation system；Then in conjunction with vibration signals measured, introduce regularization thought and determine object function, carrying out rotor-support-foundation system amount of unbalance number using genetic algorithm recognizes；On this basis amount of unbalance position and size identification are carried out using particle cluster algorithm.Vibration information of the present invention only by obtaining limited sensing station under certain fixed rotating speed, rotor unbalance position and size can be obtained, the deficiency that start and stop car adds test mass need to repeatedly be carried out by solving traditional amount of unbalance identification, and guidance is provided for follow-up accurately dynamic balancing.
Description
Technical field
The invention belongs to rotating machinery dynamic balancing technique field, and in particular to a kind of rotor multiple spot amount of unbalance identification side
Method.
Background technology
In modern society, rotating machinery is using quite varied, in the large-scale production enterprise such as steel, petrochemical industry, Aero-Space
In industry, include the key equipments such as blower fan, steam turbine, motor, gas turbine, compressor, air blower, aero-engine, pump, its
The quality of operation conditions directly affects the production of enterprise, once because of disorderly closedown, huge economic loss will be caused and serious
Consequence.Therefore, enterprise pays special attention to the situation of this kind equipment.
The problem of maximum that large rotating machinery faces is vibration problem, causes mechanical performance to damage due to vibration
Occupy very big ratio.In a variety of causes for producing vibration, most importantly rotor unbalance.According to statistics, rotating machinery
In various vibration faults, uneven caused vibration accounts for 60% or so.Therefore, dynamic balancing technique seems outstanding to large rotating machinery
To be important.
Conventional rotors dynamic balance method, such as influence coefficient method and modal balance method, have had considerable hair so far from proposition
Exhibition, but still come with some shortcomings.Influence coefficient method needs multiple start and stop rotor to obtain the influence coefficient matrix of system, and mode is put down
The rule that weighs need to carry out accurately model analysis to rotor-support-foundation system, and Project Realization difficulty is larger.Therefore, if rotor can be understood in advance
Imbalance distribution is estimated to it with certain, i.e., carry out amount of unbalance identification to rotor, then can greatly speed up dynamic balancing
Efficiency.Rotating machinery constantly develops towards high speed, complication direction, if only carrying out single-point amount of unbalance identification, it is impossible to be applicable
In industry spot complicated and changeable.Therefore, seeking that a kind of rotor multiple spot amount of unbalance recognition methods has very much to spot dynamic balance must
Will.
The content of the invention
It is an object of the invention to overcome the shortcomings of that traditional amount of unbalance recognition methods needs multiple start and stop car addition test mass,
There is provided a kind of rotor multiple spot amount of unbalance recognition methods, this method is according to rotor inherent structure and actual measurement vibration information, identification
Rotor unbalance value.
To reach above-mentioned purpose, the present invention is adopted the following technical scheme that：
A kind of rotor multiple spot amount of unbalance recognition methods, comprises the following steps：
1) the intrinsic structure of rotor-support-foundation system and modal information are obtained：Rotor length l, diameter d, density p, elastic modulus E, turn
Disk diameter D, thickness t and position, bearing rigidity K, damping C and bearing position；
2) node division is carried out to rotor-support-foundation system, sets up rotor-support-foundation system lumped-mass model；
3) Riccati transfer matrixes are used, with reference to step 2) in lumped-mass model, obtain rotor-support-foundation system theoretical uneven
Response；
4) vibration signal of rotor-support-foundation system actual motion is gathered；
5) rotor-support-foundation system theoretical response and vibration signals measured are combined, amount of unbalance number knowledge is carried out using genetic algorithm
Not；
6) in step 5) on the basis of gained amount of unbalance number, amount of unbalance position is carried out and big using particle cluster algorithm
Small identification.
Of the invention further improve be, step 2) in set up rotor lumped-mass model, detailed process is as follows：
Rotor-support-foundation system is separated into disk, shaft part and supporting elementary cell, the quality and rotary inertia collection of each shaft part
On the rigid Thin Disk always constituted to left and right ends, shaft part is then simplified to the elastic shaft of massless in itself；The wherein attribute of disk
Including lumped mass Mi, collection overall diameter rotary inertia JdiWith lump polar moment of inertia Jpi；
Lumped mass：
Lump polar moment of inertia：
Collect overall diameter rotary inertia：
Node aggregated parameter：
In formula,WithThe quality of rotating disk, diameter rotary inertia and polar moment of inertia at respectively origin node i；
Node equivalent rigidity is at bearing：
Ksi=Ki+iω·Ci (5)
If there is uneven, the node amount of unbalance in the i-th node：
Ui=mie(cosα+isinα) (6)
In formula, miFor unbalance mass, e, α are the amplitude and phase of amount of unbalance.
The present invention, which is further improved, to be, step 3) it is middle using Riccati transfer matrix methods calculating unbalance response, have
Body step is as follows：
If the state vector in i-th of section isWherein MxAnd MyFor section
Moment of flexure, QxAnd QyFor section shear, X and Y are section amount of deflection, and A and B are section slope, and this vector is designated as into zi, by each disk
A component is constituted with shaft part, then the section vector at component two ends is designated as z respectivelyiAnd zi+1, external force suffered by component is designated as Fi, component
The vector correlation at two ends is：
zi+1=Tizi+Fi (7)
In formula, TiIt is the transfer matrix of i-th of component；
Element in state vector is divided into two groups of { f }, { e }, preceding four elements and remaining are represented in state vector respectively
Element, introduces Riccati conversion, then：
{f}i={ S }i{e}i+{P}i (8)
According to left cross sectional boundary condition fi=0, ei=0 and right interface boundary condition fi=0, recursion obtains each section state
Vector ei, i.e., the plural form that rotor unbalance is responded.
Of the invention further improve be, step 4) in unbalance vibration signal under setting fixed rotating speed, limited biography
Vibration signal at sensor position.
Of the invention further improve be, step 5) in genetic algorithm object function, regularization thought is introduced, in tradition
Increase L1 regularization terms on the basis of object function, form new object function, obtain the openness result of amount of unbalance, target
Function is as follows：
In formula：
U- rotor unbalance values vector；
xr- rotor-support-foundation system vibration signals measured；
The theoretical unbalance response of f (U)-rotor-support-foundation system；
λ-regularization factors；
Uneven number identification is carried out using genetic algorithm to comprise the following steps that：
A. initialize, randomly generate one group of initial individuals and constitute initial population P (t), and each individual is evaluated by formula (9)
Fitness value；
B. whether evaluation algorithm meets whether end condition, i.e. error are less than setting value or reach setting iterations, if
End condition then output result is met, computing is terminated；Otherwise following steps are performed；
C. Selecting operation, according to fitness size, the generation gap value set using user is select probability, if being selected from population
Dry individual；
D. crossing operation, the crossover probability set according to user, are randomly assigned one or more crosspoints, to random selection
Two individuals exchange the unilateral or middle genes in crosspoints, form two new individuals；
E. mutation operator, the mutation probability set according to user, the upper randomly selected portion gene of genes of individuals seat is used
Other genes are replaced, and form new individual；
F. colony P (t+1) of future generation, return to step b are obtained by aforesaid operations.
Of the invention further improve is, in step 6) in particle cluster algorithm used, it is when initial value is chosen and indirect
The gamut of optimized variable, but the characteristics of recognized according to amount of unbalance, it is appropriate to reduce initial value selection range, improve identification accurate
True rate, is comprised the following steps that：
A. initialize, randomly generate one group of initial individuals and constitute initial population P (t), calculate each particle fitness value；
B. whether evaluation algorithm meets end condition, i.e., whether error is less than setting value or reaches setting iterations, if
End condition then output result is met, computing is terminated；Otherwise following steps are performed；
C. current particle movement velocity of future generation is calculated：
In formula, w is the inertia weight factor；C1, c2 are Studying factors；R1, r2 are equally distributed random to obey [0,1]
Number；It is current particle kth for stop place；For current particle history desired positions；For the best position of colony's history
Put；
D. particle position is updated according to Particles Moving speed：
E. particle fitness value of new generation, return to step b are calculated.
Further improve of the invention is that Studying factors c1, c2 are 2.
Compared with prior art, the invention has the advantages that：
Of the present invention is a kind of rotor multiple spot amount of unbalance recognition methods, by carrying out lumped mass to rotor-support-foundation system
Modeling, obtains Systems Theory unbalance response, and is compared with actual measurement unbalance vibration signal, passes through genetic algorithm and particle
Rotor unbalance value is identified group's algorithm.Whole identification process need not add test mass, it is to avoid repeatedly open car, when shortening maintenance
Between, the cost of repairs is reduced, downtime is reduced, and the present invention only need to gather vibration information under certain fixed rotating speed, it is many without rotor
Secondary rotational speed regulation, you can identify rotor unbalance value number, position, quality and phase information, substantially increase balance efficiency,
And guidance can be provided for follow-up accurately dynamic balancing.
Further, present invention introduces regularization thought, the uneven number of rotor multiple spot is accurately identified by genetic algorithm, can
Priori is provided for other amount of unbalance recognition methods.
Further, the present invention, can be to amount of unbalance position distribution by suitably reducing particle cluster algorithm initial value selection range
Good estimation is carried out, is that live rotor maintenance and rotor dynamic balancing provide reference.
Brief description of the drawings
Fig. 1 is basic flow sheet of the invention.
Fig. 2 is rotor-support-foundation system node division schematic diagram.
Fig. 3 is each nodal information of rotor-support-foundation system lumped-mass model.
Fig. 4 is two first order modes before rotor-support-foundation system model.
Fig. 5 is the block diagram of genetic algorithm in identification amount of unbalance number.
Fig. 6 is penalty h (N) schematic diagram in regularization factors.
Embodiment
In order to verify the superiority of rotor multiple spot amount of unbalance recognition methods of the invention, below in conjunction with drawings and examples
The present invention is described in further detail.
Rotor multiple spot imbalance identification method is described in detail below：
1) the intrinsic structure of rotor-support-foundation system and modal information are obtained：Rotor length l, diameter d, density p, elastic modulus E, turn
Disk diameter D, thickness t and position, bearing rigidity K, damping C and bearing position；
2) node division is carried out to rotor-support-foundation system, sets up rotor-support-foundation system lumped-mass model；
3) Riccati transfer matrixes are used, with reference to step 2) in lumped-mass model, obtain rotor-support-foundation system theoretical uneven
Response；
4) vibration signal of rotor-support-foundation system actual motion is gathered；
5) rotor-support-foundation system theoretical response and vibration signals measured are combined, amount of unbalance number knowledge is carried out using genetic algorithm
Not；
6) in step 5) on the basis of gained amount of unbalance number, amount of unbalance position is carried out and big using particle cluster algorithm
Small identification.
In order to examine the accuracy and practicality of the inventive method, following instance has been done.Know refering to amount of unbalance shown in Fig. 1
Other flow, i.e., modeled by rotor first, obtains the theoretical unbalance response of rotor, secondly collection rotor actual vibration signal, is carried
Power frequency component amplitude and phase are taken, is compared with theoretical value, amount of unbalance identification is carried out finally by intelligent optimization algorithm.Cause
Rotor unbalance information includes number, position, four aspects of quality and phase, and Direct Recognition parameter is more, therefore is classified as not
Balance number is recognized and other information recognizes two parts, is identified successively.
1) a certain rotor-support-foundation system is directed to, its intrinsic structure is obtained and modal information is as shown in table 1.
The rotor-support-foundation system structural information of table 1
2) obtain after structural information, it is as shown in Figure 2 to carry out node division to rotor.Rotor is divided into 13 shaft parts, altogether
Count 14 nodes；Disk position is node 6 and node 9, and sensing station is node 3 and node 12, and bearing bearing position is section
Point 1 and node 14.
3) according to the node of division, rotor-support-foundation system lumped-mass model is set up, each nodal analysis method parameter, rotor-support-foundation system is calculated
Each nodal information of lumped-mass model as shown in figure 3, mainly include each node quality, it is polar moment of inertia, diameter rotary inertia, outer
Footpath, equivalent bending stiffness, shaft part length, support stiffness.
Rotor-support-foundation system unbalance response is calculated using Riccati transfer matrixes, selection balancing speed is 1020rpm, is calculated
Two first order modes are as shown in Figure 4 before rotor-support-foundation system.As can be seen that a first order mode has 0 node；Second_mode has 1 node,
And node both sides particle synchronization vibration phase is on the contrary, vibration shape situation is with being actually consistent.
4) rotor oscillation signal is gathered, and by accurate FFT to the signal amplitude phase of power frequency component, i.e. frequency for 17Hz
Extracted.
5) amount of unbalance number identification is carried out using genetic algorithm, flow is as shown in Figure 5.Will be per generation genetic algorithm optimization
Unbalance response obtained by parameter is contrasted with actual unbalance response, and fitness value is calculated by object function, until reaching convergence
Criterion.Because sensor is located at node 3 and node 12, setting genetic algorithm object function is as follows：
In formula：
U- rotors amount of unbalance vector to be optimized；
xr3,xr12- rotor-support-foundation system node 3,12 vibration signals measureds；
F3,F12The theoretical unbalance response of-rotor-support-foundation system node 3,12；
λ-regularization factors.
Object function Part I is rotor residual oscillation quadratic sum, and Part II is regularization term.According to this rotor system
Actual vibration of uniting response, regularization factors setting is as follows：
λ=107/(2.0503*10-4*xr 2-0.0468*xr+2.320)/h(N) (13)
In formula：
xr- rotor node 3 and the actual measurement unbalance vibration amplitude sum of node 12；
N- node locations；
H (N)-node location N function；
H (N) function can regard penalty as, as shown in fig. 6, for same amount of unbalance, if its positional distance bearing is got over
Closely, h (N) value is bigger, and target function value is then smaller, so as to avoid recognition result from concentrating on the rotor node position farthest apart from bearing
Put.
Genetic algorithm uses binary coding, and maximum iteration is 50, and identification range is [0,100] g.mm, this step
It is middle to assume that all amount of unbalance phase informations are all 0 °.
6) after the completion of the identification of amount of unbalance number, non-equilibrium site size identification is carried out using particle cluster algorithm.It is uneven
Mass range is [0,100] g.mm, and primary scope is set to [0,45] g.mm.Unbalance phase scope is [0,360], initially
The same identification range of particle range.It fact proved, this primary scope can obtain higher accuracy of identification.
This rotor-support-foundation system carries out single-point and 2 amount of unbalance identifications respectively provided with two exacerbation disks.
This rotor-support-foundation system single-point amount of unbalance recognition result as shown in table 2, unbalance mass, is represented in table respectively before and after "@"
And phase.The amount of unbalance of different quality and out of phase is identified respectively, as a result shown, recognition effect is preferable.
The single-point amount of unbalance recognition result of table 2
| Amount of unbalance is set | Recognize number | Recognize position | Recognize size |
| The 0.8g@0 of node 6 | 1 | 6 | [email protected] |
| The 1.6g@- 45 of node 6 | 1 | 6 | [email protected] |
| The 1.2g@0 of node 6 | 1 | 6 | [email protected] |
| The 1.2g@45 of node 6 | 1 | 6 | [email protected] |
| The 1.2g@90 of node 6 | 1 | 6 | [email protected] |
| The 1.2g@135 of node 6 | 1 | 6 | [email protected] |
| The 1.2g@180 of node 6 | 1 | 6 | [email protected] |
| The 1.2g@225 of node 6 | 1 | 6 | [email protected] |
| The 1.2g@270 of node 6 | 1 | 6 | [email protected] |
| The 1.2g@315 of node 6 | 1 | 6 | [email protected] |
2 amount of unbalance recognition results of this rotor-support-foundation system as shown in table 3, unbalance mass, are represented in table respectively before and after "@"
And phase.The amount of unbalance of different quality and out of phase is identified respectively, as a result shown, amount of unbalance number has been recognized
Total correctness, uneven size has certain recognition effect.
3 two amount of unbalance recognition results of table
Claims (7)
1. a kind of rotor multiple spot amount of unbalance recognition methods, it is characterised in that comprise the following steps：
1) the intrinsic structure of rotor-support-foundation system and modal information are obtained：Rotor length l, diameter d, density p, elastic modulus E, rotating disk are straight
Footpath D, thickness t and position, bearing rigidity K, damping C and bearing position；
2) node division is carried out to rotor-support-foundation system, sets up rotor-support-foundation system lumped-mass model；
3) Riccati transfer matrixes are used, with reference to step 2) in lumped-mass model, obtain that rotor-support-foundation system is theoretical uneven to be rung
Should；
4) vibration signal of rotor-support-foundation system actual motion is gathered；
5) rotor-support-foundation system theoretical response and vibration signals measured are combined, amount of unbalance number identification is carried out using genetic algorithm；
6) in step 5) on the basis of gained amount of unbalance number, use particle cluster algorithm to carry out amount of unbalance position and size and know
Not.
2. a kind of rotor multiple spot amount of unbalance recognition methods according to claim 1, it is characterised in that step 2) middle foundation turn
Sub- lumped-mass model, detailed process is as follows：
Rotor-support-foundation system is separated into disk, shaft part and supporting elementary cell, the quality of each shaft part and rotary inertia lump are arrived
On the rigid Thin Disk that left and right ends are constituted, shaft part is then simplified to the elastic shaft of massless in itself；The attribute of wherein disk includes
Lumped mass Mi, collection overall diameter rotary inertia JdiWith lump polar moment of inertia Jpi；
Lumped mass：
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In formula,WithThe quality of rotating disk, diameter rotary inertia and polar moment of inertia at respectively origin node i；
Node equivalent rigidity is at bearing：
Ksi=Ki+iω·Ci (5)
If there is uneven, the node amount of unbalance in the i-th node：
Ui=mie(cosα+isinα) (6)
In formula, miFor unbalance mass, e, α are the amplitude and phase of amount of unbalance.
3. a kind of rotor multiple spot amount of unbalance recognition methods according to claim 2, it is characterised in that step 3) middle use
Riccati transfer matrix methods calculate unbalance response, comprise the following steps that：
If the state vector in i-th of section isWherein MxAnd MyFor section turn moment,
QxAnd QyFor section shear, X and Y are section amount of deflection, and A and B are section slope, and this vector is designated as into zi, by each disk and shaft part
A component is constituted, then the section vector at component two ends is designated as z respectivelyiAnd zi+1, external force suffered by component is designated as Fi, component two ends
Vector correlation is：
zi+1=Tizi+Fi (7)
In formula, TiIt is the transfer matrix of i-th of component；
Element in state vector is divided into two groups of { f }, { e }, preceding four elements and remaining element in state vector are represented respectively,
Riccati conversion is introduced, then：
{f}i={ S }i{e}i+{P}i (8)
According to left cross sectional boundary condition fi=0, ei=0 and right interface boundary condition fi=0, recursion obtains each section state vector
ei, i.e., the plural form that rotor unbalance is responded.
4. a kind of rotor multiple spot amount of unbalance recognition methods according to claim 1, it is characterised in that step 4) in it is uneven
Vibration signal is sets under fixed rotating speed, vibration signal at limited sensing station.
5. a kind of rotor multiple spot amount of unbalance recognition methods according to claim 4, it is characterised in that step 5) in heredity calculate
Method object function, introduces regularization thought, increases L1 regularization terms on the basis of traditional objective function, forms new target letter
Number, obtains the openness result of amount of unbalance, object function is as follows：
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<mi>n</mi>
<mrow>
<mo>(</mo>
<mo>|</mo>
<mo>|</mo>
<msub>
<mi>x</mi>
<mi>r</mi>
</msub>
<mo>-</mo>
<mi>f</mi>
<mo>(</mo>
<mi>U</mi>
<mo>)</mo>
<mo>|</mo>
<msubsup>
<mo>|</mo>
<mn>2</mn>
<mn>2</mn>
</msubsup>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mi>&lambda;</mi>
<mo>|</mo>
<mo>|</mo>
<mi>U</mi>
<mo>|</mo>
<msub>
<mo>|</mo>
<mn>1</mn>
</msub>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>9</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula：
U- rotor unbalance values vector；
xr- rotor-support-foundation system vibration signals measured；
The theoretical unbalance response of f (U)-rotor-support-foundation system；
λ-regularization factors；
Uneven number identification is carried out using genetic algorithm to comprise the following steps that：
A. initialize, randomly generate one group of initial individuals and constitute initial population P (t), and the suitable of each individual is evaluated by formula (9)
Answer angle value；
B. whether evaluation algorithm meets whether end condition, i.e. error are less than setting value or reach setting iterations, if meeting
End condition then output result, terminates computing；Otherwise following steps are performed；
C. Selecting operation, according to fitness size, the generation gap value set using user selects several as select probability from population
Body；
D. crossing operation, the crossover probability set according to user, are randomly assigned one or more crosspoints, to randomly selected two
Individual exchanges the unilateral or middle gene in crosspoint, forms two new individuals；
E. mutation operator, the mutation probability set according to user, other are used by the upper randomly selected portion gene of genes of individuals seat
Gene is replaced, and forms new individual；
F. colony P (t+1) of future generation, return to step b are obtained by aforesaid operations.
6. a kind of rotor multiple spot amount of unbalance recognition methods according to claim 5, it is characterised in that in step 6) in it is used
Particle cluster algorithm, when initial value is chosen and indirect optimized variable gamut, but the characteristics of recognized according to amount of unbalance,
It is appropriate to reduce initial value selection range, recognition accuracy is improved, is comprised the following steps that：
A. initialize, randomly generate one group of initial individuals and constitute initial population P (t), calculate each particle fitness value；
B. whether evaluation algorithm meets end condition, i.e., whether error is less than setting value or reaches setting iterations, if meeting
End condition then output result, terminates computing；Otherwise following steps are performed；
C. current particle movement velocity of future generation is calculated：
<mrow>
<msubsup>
<mi>V</mi>
<mi>j</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</msubsup>
<mo>=</mo>
<msubsup>
<mi>wV</mi>
<mi>j</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>+</mo>
<mi>c</mi>
<mn>1</mn>
<mi>r</mi>
<mn>1</mn>
<mrow>
<mo>(</mo>
<msubsup>
<mi>pb</mi>
<mi>j</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>I</mi>
<mi>j</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mi>c</mi>
<mn>2</mn>
<mi>r</mi>
<mn>2</mn>
<mrow>
<mo>(</mo>
<msubsup>
<mi>gb</mi>
<mi>j</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>I</mi>
<mi>j</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>10</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula, w is the inertia weight factor；C1, c2 are Studying factors；R1, r2 are obedience [0,1] equally distributed random number；
It is current particle kth for stop place；For current particle history desired positions；For colony's history desired positions；
D. particle position is updated according to Particles Moving speed：
<mrow>
<msubsup>
<mi>I</mi>
<mi>j</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</msubsup>
<mo>=</mo>
<msubsup>
<mi>I</mi>
<mi>j</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>V</mi>
<mi>j</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</msubsup>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>11</mn>
<mo>)</mo>
</mrow>
</mrow>
E. particle fitness value of new generation, return to step b are calculated.
7. a kind of rotor multiple spot amount of unbalance recognition methods according to claim 6, it is characterised in that Studying factors c1, c2
It is 2.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108694417A (en) * | 2018-08-16 | 2018-10-23 | 湖南工程学院 | A kind of sliding bearing-rotor system amount of unbalance recognition methods |
| CN109029689A (en) * | 2018-08-08 | 2018-12-18 | 中国大唐集团科学技术研究院有限公司华中分公司 | A kind of rotating machinery vibration analysis method based on two ends of rotor motion profile |
| CN110276164A (en) * | 2019-07-10 | 2019-09-24 | 湖南科技大学 | Annular components gusset welding magnitude of misalignment causes rotor structure amount of unbalance analytic approach |
| CN110377995A (en) * | 2019-07-10 | 2019-10-25 | 湖南科技大学 | Permanent magnet mounting groove radial position symmetry generates rotor structure imbalance analysis method |
| CN110877751A (en) * | 2019-12-04 | 2020-03-13 | 哈尔滨工业大学 | Large-scale high-speed rotation equipment rotational inertia stacking method based on vector projection |
| CN111639386A (en) * | 2020-04-17 | 2020-09-08 | 北京化工大学 | Keyless phase virtual dynamic balance method for aircraft engine |
| CN112556931A (en) * | 2020-11-23 | 2021-03-26 | 沈阳建筑大学 | Particle swarm algorithm-based modal dynamic balance method for high-speed bearing rotor system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4033042A (en) * | 1974-10-10 | 1977-07-05 | Bently Nevada Corporation | Shaft alignment apparatus and method |
| JP2003019997A (en) * | 2001-05-01 | 2003-01-21 | Hitachi Zosen Corp | Position detecting method and position detecting device of driving shaft system in marine propulsion device and position detecting program |
| CN101178335A (en) * | 2007-11-29 | 2008-05-14 | 浙江大学 | Synchronized dual rotors system inside and outside rotor unbalance value quick recognizing methods |
| CN101387567A (en) * | 2008-10-29 | 2009-03-18 | 西北工业大学 | Double surface transient equilibration method for flexible rotor |
| CN103076163A (en) * | 2011-12-06 | 2013-05-01 | 西安交通大学 | Online test method for characteristic parameter of bearing-rotor system |
-
2017
- 2017-06-14 CN CN201710449072.8A patent/CN107255549B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4033042A (en) * | 1974-10-10 | 1977-07-05 | Bently Nevada Corporation | Shaft alignment apparatus and method |
| JP2003019997A (en) * | 2001-05-01 | 2003-01-21 | Hitachi Zosen Corp | Position detecting method and position detecting device of driving shaft system in marine propulsion device and position detecting program |
| CN101178335A (en) * | 2007-11-29 | 2008-05-14 | 浙江大学 | Synchronized dual rotors system inside and outside rotor unbalance value quick recognizing methods |
| CN101387567A (en) * | 2008-10-29 | 2009-03-18 | 西北工业大学 | Double surface transient equilibration method for flexible rotor |
| CN103076163A (en) * | 2011-12-06 | 2013-05-01 | 西安交通大学 | Online test method for characteristic parameter of bearing-rotor system |
Non-Patent Citations (4)
| Title |
|---|
| 李立新等: "基于遗传算法的多级盘转子平衡方案优化设计", 《振动、测试与诊断》 * |
| 王俊爵: "基于遗传算法的1000ＭＷ核电套装转子动平衡优化", 《传动技术》 * |
| 虞烈: "《可控磁悬浮转子***》", 31 August 2003, 科学出版社 * |
| 邱海: "遗传算法在柔性转子动平衡中的应用", 《中国机械工程》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109029689A (en) * | 2018-08-08 | 2018-12-18 | 中国大唐集团科学技术研究院有限公司华中分公司 | A kind of rotating machinery vibration analysis method based on two ends of rotor motion profile |
| CN109029689B (en) * | 2018-08-08 | 2020-05-22 | 中国大唐集团科学技术研究院有限公司华中分公司 | Rotary mechanical vibration analysis method based on movement tracks of two ends of rotor |
| CN108694417A (en) * | 2018-08-16 | 2018-10-23 | 湖南工程学院 | A kind of sliding bearing-rotor system amount of unbalance recognition methods |
| CN110276164A (en) * | 2019-07-10 | 2019-09-24 | 湖南科技大学 | Annular components gusset welding magnitude of misalignment causes rotor structure amount of unbalance analytic approach |
| CN110377995A (en) * | 2019-07-10 | 2019-10-25 | 湖南科技大学 | Permanent magnet mounting groove radial position symmetry generates rotor structure imbalance analysis method |
| CN110877751A (en) * | 2019-12-04 | 2020-03-13 | 哈尔滨工业大学 | Large-scale high-speed rotation equipment rotational inertia stacking method based on vector projection |
| CN110877751B (en) * | 2019-12-04 | 2021-04-30 | 哈尔滨工业大学 | Large-scale high-speed rotation equipment rotational inertia stacking method based on vector projection |
| CN111639386A (en) * | 2020-04-17 | 2020-09-08 | 北京化工大学 | Keyless phase virtual dynamic balance method for aircraft engine |
| CN112556931A (en) * | 2020-11-23 | 2021-03-26 | 沈阳建筑大学 | Particle swarm algorithm-based modal dynamic balance method for high-speed bearing rotor system |
| CN112556931B (en) * | 2020-11-23 | 2022-09-06 | 沈阳建筑大学 | Particle swarm algorithm-based modal dynamic balance method for high-speed bearing rotor system |
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