CN103258096A - Contactor bouncing time qualified rate prediction method based on Monte Carlo simulation - Google Patents
Contactor bouncing time qualified rate prediction method based on Monte Carlo simulation Download PDFInfo
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Abstract
The invention discloses a contactor bouncing time qualified rate prediction method based on Monte Carlo simulation, and belongs to the technical field of contactor detection. The contactor bouncing time qualified rate prediction method based on the Monte Carlo simulation solves the problems of high designing and testing cost and a long designing period caused by the fact that in a method for testing bouncing time parameters in the contactor designing process, a sample needs to be manufactured. The method comprises the following steps that three parameter designing values and top and bottom limitation all of which have an effect on the bouncing time are determined according to a contactor designing file, and N groups of parameter combinations are produced by adopting the independent identically distributed central limit theorem and utilizing the MATLAB; N groups of bouncing time characteristic parameters are obtained according to the N groups of parameter combinations; then, the distribution character of the bouncing time parameters are obtained; a contactor bouncing time qualified rate is obtained by utilizing the Simpson principle and according to the distribution character and the contactor bouncing time designing parameters. The contactor bouncing time qualified rate prediction method is suitable for predicating and analyzing the contactor bouncing time qualified rate in the designing link of a contactor, and a basis for revising designing parameters is provided for a designer of the contactor.
Description
Technical field
The invention belongs to the contactor field, relate to a kind of bounce time qualification rate computing method, just be based on the contactor bounce time yield analysis method of Monte Carlo simulation specifically.
Background technology
Bounce time is the most important basic parameter of contactor, is the key factor that determines contactor electric current of make-and-break ability, can directly determine according to this parameter whether contactor is qualified." when any open-circuit voltage of 90% that is equal to or greater than occurring, and the phenomenon that pulse width is equal to or greater than 10 μ s is then thought contact bounce for GJB2228 4.8.8.5.1 bar regulation." contact bounce time can not be long, otherwise the rebound electric arc to contact for a long time ablation the contactor life-span is descended rapidly.But in the product development of reality, because the complicacy of real mechanism, various parameters comprise dimensional parameters, design parameter and adjustment parameter all can produce certain influence to bounce time, therefore need determine to influence the principal element of this parameter in the design phase, and can be by certain methods qualification rate with regard to its bounce time of analog computation before actual product is produced, thereby control the qualification rate of bounce time by the range of tolerable variance that changes the part factor, make the productivity effect of contactor reach maximum, will have great value in theory and productivity effect so invent a kind of contactor bounce time yield analysis method.
In the design process of existing contactor, be after the design drawing of contactor is handled, go out a plurality of samples according to the design drawing processing and fabricating, adopt testing apparatus to carry out the test of bounce time to a plurality of samples of making then, and then whether the parameter that can verify design is reasonable, if unreasonable, just needs revisions on drawings, then again the processing and fabricating sample, do experiment again, this has just caused design cycle prolongation and design and testing cost than higher.
Summary of the invention
The objective of the invention is to solve in the design process of existing contactor, need come out to exist the method that the parameter of bounce time is tested design cycle length and processing and fabricating sample to cause designing the problem high with testing cost sample making according to design drawing, the invention provides a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation.
The step of the contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation of the present invention is as follows:
Step 1: obtain dimensional parameters design load, the design parameter design load of contactor and adjust the range of tolerable variance of parameter designing value and each parameter according to design document and art work sheet, utilize MATLAB to produce the N group changes and meet normal distribution in range of tolerable variance dimensional parameters, design parameter and adjustment parameter three class parameter combinations according to independent identically distributed central limit theorem, Parameter N is the integer more than or equal to 1000;
Step 2: above N is organized three class parameter combinations successively as the input parameter of contactor bounce time acquisition module, obtain N group bounce time characterisitic parameter;
Step 3: the N group bounce time parameter that obtains is analyzed, calculated and obtain probability density function, parameter expectation and mean square deviation, and then obtain N group bounce time parameter distributions characteristic;
Step 4: require to determine bounce time differentiation boundary according to the performance index in the design parameter of contactor, the N group bounce time parameter distributions property calculation contactor bounce time qualification rate of utilizing the Simpson rule to obtain according to step 3.
Described contactor bounce time acquisition module adopts software engineering to realize, the course of work of this module comprises and the following is step:
Steps A, contactor model calculating parameter initialization characterisitic parameter is set;
Step B, obtain the current time magnetic linkage by previous moment coil voltage, electric current and magnetic linkage integration;
Step C, obtain coil current by coil flux linkage, armature displacement check table;
Step D, the coil current, the armature displacement check table that are obtained by step C obtain electromagnetic attraction;
Step e, calculate the mechanical spring counter-force by the armature displacement
f=k·x+c
d·v
K, c in the formula
dRepresent spring rate and spring damping respectively, x, v represent armature displacement and the armature speed of spring respectively;
Step F, employing fourth-order Runge-Kutta method are found the solution the mechanical motion differential equation group, and described mechanical motion differential equation group is:
Described Y represents armature displacement, speed column vector, expression formula be Y=(x, v)
TFollowing footnote n represents sampling instant; t
nExpression n is time corresponding constantly;
G represents armature speed, acceleration column vector, and expression formula is
V represents armature speed, and F represents electromagnetic attraction; F represents counter-force; M represents the armature quality;
G (t
n, Y
n) middle t
nAnd Y
nIndependent variable for above-mentioned expression formula;
H represents step-length computing time;
The calculation result data of step G, preservation step F is also extracted the bounce time characterisitic parameter, and obtain the bounce time qualification rate according to the allowed band of the bounce time in the design document from described calculation result data.
The described table of comparisons be the coil flux linkage of contactor about the bivariate table of coil current and armature displacement, this table of comparisons obtains by following step:
Step H, in UG software, set up the electromagnetic mechanism three-dimensional model according to the design drawing of the electromagnetic mechanism of contactor;
Step I, by software finite element software FLUX according to the three-dimensional model of electromagnetic mechanism, calculate the coil current, armature displacement, electromagnetic attraction and the magnetic linkage that obtain many windings tentaculum;
Step J, the coil current, armature displacement, electromagnetic attraction and the magnetic linkage parameter that obtain many windings tentaculum according to step I make up the table of comparisons.
Step I is described by the three-dimensional model of software finite element software FLUX according to electromagnetic mechanism, and the process of calculating the coil flux linkage, coil current and the armature displacement that obtain many windings tentaculum is:
Step I1, employing finite element software FLUX set up geometric model according to the three-dimensional model of electromagnetic mechanism, and this geometric model are divided finite element grid;
Step I2, the physical attribute of each finite element grid among the step I1 is set according to the real physical characteristics of electromagnetic mechanism;
Step I3, the geometric model that sets up physical attribute is carried out static characteristics emulation, the coil current values of the many groups of input and corresponding dimensional parameters during emulation, described current value is obtained divided by the coil resistance in the design parameter of contactor by voltage; Obtain armature displacement, electromagnetic attraction and the magnetic linkage of every group of coil current value and dimensional parameters correspondence by emulation.
The process that the N that utilizes the Simpson rule to obtain according to step 3 described in the step 4 organizes bounce time parameter distributions property calculation contactor bounce time qualification rate is: the expectation and the variance that at first calculate N group bounce time data, determine that according to existing bounce time acceptability limit the Simpson rule calculates required upper lower limit value then, adopt described rule to divide in the upper lower limit value inner product at last and obtain contactor bounce time qualification rate.
Method of the present invention is applied to the design link of contactor, can just carry out quantitative assessment and judgement to the rationality of its parameter in the design link, when shortening trial-produce period, reducing testing cost, improves reliability of products.
Method of the present invention was applicable in the contactor design phase carries out forecast analysis to the qualification rate of contactor bounce time, and then the foundation of correction design parameter is provided for the deviser of contactor.
This method is based on Monte Carlo simulation and proposes, and Monte Carlo (Monte Carlo) simulation is a kind of by setting stochastic process, rise time sequence repeatedly, and the calculating parameter estimator, and then study the method for its distribution characteristics.The principle of Monte Carlo simulation method is when problem or object itself have probability characteristics, can produce sampling results with the method for computer simulation, according to the value of sample calculation statistic or parameter; Along with increasing of simulation number of times, the method that can be averaging by the estimated value to each time statistic or parameter obtains stablizing conclusion.
When each parameter of contactor known, owing to relate to machine,, finding the solution of magnetic coupling equation, be difficult to directly set up according to the tolerance of each parameter the mathematical models of contactor batch products bounce time qualification rate, but can (comprise dimensional parameters at each parameter of contactor, design parameter, tuning parameter) produces N numerical value that in range of tolerable variance, changes and meet normal distribution at random, from these parameters, extract a numerical value then at every turn and be used for calculating bounce time, so carry out obtaining for N time the bounce time of N contactor, be equivalent to produce and assembled N contactor and recorded bounce time, then this N bounce time is carried out statistical study, obtain its regularity of distribution and parameter, calculate its bounce time qualification rate according to discrimination standard at last, N is more big, and its qualification rate that calculates more approaches with actual conditions.This computation process has been used the thought of Monte Carlo simulation.
The present invention is in the design phase of contactor, the dimensional parameters, design parameter and the adjustment parameter tolerances scope that provide according to art work sheet, utilize the approximate contactor bounce time qualification rate that obtains of thought of Monte Carlo Analogue Method, can allow manufacturing enterprise that the manufacturing of contactor is had the assurance of an overall situation, lay the foundation for further improving the contactor qualification rate simultaneously.
Description of drawings
Fig. 1 is the schematic diagram of the method for the invention; Fig. 2 is the fundamental diagram of contactor bounce time acquisition module; Fig. 3 is certain model contactor construction synoptic diagram, and wherein 1 is shell, and 2 is connecting rod, and 3 is coil, and 4 is armature, and 5 is reaction spring, and 6 is iron core, and 7 is yoke, and 8 is rebound spring, and 9 is moving contact, and 10 is static contact; Fig. 4 is certain model contactor moving contact bounce time distribution curve and differentiates boundary that wherein the vertical line perpendicular to horizontal ordinate is the differentiation boundary.Fig. 5 is that the present invention calculates the schematic diagram that obtains the bounce time qualification rate.
Embodiment
Embodiment one, referring to Fig. 1 present embodiment is described.The described a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation of present embodiment, this method comprises the steps:
Step 1: obtain dimensional parameters design load, the design parameter design load of contactor and adjust the range of tolerable variance of parameter designing value and each parameter according to design document and art work sheet, utilize MATLAB to produce the N group changes and meet normal distribution in range of tolerable variance dimensional parameters, design parameter and adjustment parameter three class parameter combinations according to independent identically distributed central limit theorem, Parameter N is the integer more than or equal to 1000;
Step 2: above N is organized three class parameter combinations successively as the input parameter of contactor bounce time acquisition module, obtain N group bounce time characterisitic parameter;
Step 3: the N group bounce time parameter that obtains is analyzed, calculated and obtain probability density function, parameter expectation and mean square deviation, and then obtain N group bounce time parameter distributions characteristic;
Step 4: require to determine bounce time differentiation boundary according to the performance index in the design parameter of contactor, the N group bounce time parameter distributions property calculation contactor bounce time qualification rate of utilizing the Simpson rule to obtain according to step 3.
The described independent identically distributed central limit theorem of step 1, namely row dimension one Edward Lindberg theorem is a kind of special shape of the central limit theorem in the statistics, has than widespread use in practice.
The specific implementation method of above-mentioned independent identically distributed central limit theorem in MATLAB is in MATLAB, by limiting the mode of expectation value and variance, adopt function of random variable Random to generate N group number, then this N group numerical value directly satisfies row dimension one Edward Lindberg theorem.Wherein, expectation value is the design centre value, and variance is then determined by the range of tolerable variance of design.
Embodiment two, referring to Fig. 2 present embodiment is described.The difference of the described a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation of present embodiment and embodiment one is, described contactor bounce time acquisition module adopts software engineering to realize, the course of work of this module comprises and the following is step:
Steps A, contactor model calculating parameter initialization characterisitic parameter is set;
Step B, ask the current time magnetic linkage by previous moment coil voltage, electric current and magnetic linkage integration;
Step C, obtain coil current by coil flux linkage, armature displacement check table;
Step D, the coil current, the armature displacement check table that are obtained by step C obtain electromagnetic attraction;
Step e, calculate the mechanical spring counter-force by the armature displacement
f=k·x+c
d·v
K, c in the formula
dRepresent spring rate and spring damping respectively, x, v represent armature displacement and the armature speed of spring respectively;
Step F, employing fourth-order Runge-Kutta method are found the solution the mechanical motion differential equation group, and described mechanical motion differential equation group is:
Described Y represents armature displacement, speed column vector, expression formula be Y=(x, v)
TFollowing footnote n represents sampling instant; t
nExpression n is time corresponding constantly;
G represents armature speed, acceleration column vector, and expression formula is
V represents armature speed, and F represents electromagnetic attraction; F represents counter-force; M represents the armature quality;
G (t
n, Y
n) middle t
nAnd Y
nIndependent variable for above-mentioned expression formula;
H represents step-length computing time;
The calculation result data of step G, preservation step F is also extracted the bounce time characterisitic parameter, and obtain the bounce time qualification rate according to the allowed band of the bounce time in the design document from described calculation result data.
The difference of the described a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation of embodiment three, present embodiment and embodiment two is, the described table of comparisons be the coil flux linkage of contactor about the bivariate table of coil current and armature displacement, this table of comparisons obtains by following step:
Step H, in UG software, set up the electromagnetic mechanism three-dimensional model according to the design drawing of the electromagnetic mechanism of contactor;
Step I, by software finite element software FLUX according to the three-dimensional model of electromagnetic mechanism, calculate the coil current, armature displacement, electromagnetic attraction and the magnetic linkage that obtain many windings tentaculum;
Step J, the coil current, armature displacement, electromagnetic attraction and the magnetic linkage parameter that obtain many windings tentaculum according to step I make up the table of comparisons.
The difference of the described a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation of embodiment four, present embodiment and embodiment three is, step I is described by the three-dimensional model of software finite element software FLUX according to electromagnetic mechanism, and the process of calculating the coil flux linkage, coil current and the armature displacement that obtain many windings tentaculum is:
Step I1, employing finite element software FLUX set up geometric model according to the three-dimensional model of electromagnetic mechanism, and this geometric model are divided finite element grid;
Step I2, the physical attribute of each finite element grid among the step I1 is set according to the real physical characteristics of electromagnetic mechanism;
Step I3, the geometric model that sets up physical attribute is carried out static characteristics emulation, the coil current values of the many groups of input and corresponding dimensional parameters during emulation, described current value is obtained divided by the coil resistance in the design parameter of contactor by voltage; Obtain armature displacement, electromagnetic attraction and the magnetic linkage of every group of coil current value and dimensional parameters correspondence by emulation.
Embodiment five, the difference of the described a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation of present embodiment and embodiment one is, the process that the N that utilizes the Simpson rule to obtain according to step 3 described in the step 4 organizes bounce time parameter distributions property calculation contactor bounce time qualification rate is: the expectation and the variance that at first calculate N group bounce time data, determine that according to existing bounce time acceptability limit the Simpson rule calculates required upper lower limit value then, adopt described rule to divide in the upper lower limit value inner product at last and obtain contactor bounce time qualification rate.
Illustrate that referring to Fig. 5 present embodiment calculating obtains the principle of bounce time qualification rate, among Fig. 5, curve is represented the bounce time family curve, and horizontal ordinate is represented bounce time, and ordinate is represented probability density, and vertical curve is represented boundary, then according to formula
Can obtain the probability of bounce time.
Embodiment six, present embodiment are concrete cases of a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation of the present invention, and in the present case, described step is as follows:
Step 1: the parameter ginseng that obtains dimensional parameters design load, the design parameter design load of contactor and adjust the range of tolerable variance of parameter designing value and each parameter according to the design document of certain model contactor construction shown in Figure 3 and art work sheet is shown in Table 1:
Table 1
| Code name | Meaning | Scope | Design load |
| x1 | Coil resistance (Ω) | 5.50±0.55 | 5.50 |
| x2 | Clearance between open contacts (mm) | 1.30±0.13 | 1.3 |
| x3 | Armature travel (mm) | 2.20±0.06 | 2.20 |
| x4 | Rebound spring decrement (mm) | 0.45±0.03 | 0.45 |
| x5 | Reaction spring decrement (mm) | 8.54±0.10 | 8.54 |
| x6 | Rebound spring rigidity (kN/m) | 16.27±0.30 | 16.27 |
| x7 | Reaction spring rigidity (kN/m) | 0.250±0.019 | 0.250 |
| x8 | Moving contact quality (g) | 7.74±0.74 | 7.74 |
| x9 | Armature quality (g) | 8.88±0.18 | 8.88 |
| x10 | Contact colliding stiffness (10 9N/m） | 4.20±0.84 | 4.20 |
| x11 | The contact collision punishment degree of depth (mm) | 0.10±0.01 | 0.10 |
| x12 | Contact collisional damping (10 4Ns/m） | 3.5±0.7 | 3.5 |
Utilize MATLAB to produce the N group changes and meet normal distribution in range of tolerable variance dimensional parameters, design parameter and adjustment parameter three class parameter combinations according to independent identically distributed central limit theorem, Parameter N is the integer more than or equal to 1000;
Step 2: above N is organized three class parameter combinations successively as the input parameter of contactor bounce time acquisition module, obtain N group bounce time characterisitic parameter;
Step 3: the N group bounce time parameter to acquisition is analyzed, and calculate and obtain probability density function, parameter expectation and mean square deviation, and then acquisition N group moving contact bounce time parameter distributions characteristic is N (0.0002412,3.3094 * 10
-9);
Step 4: require to determine that according to the performance index in the design parameter of contactor bounce time differentiates boundary for being specification product less than 0.32ms, the N group bounce time parameter distributions property calculation contactor bounce time qualification rate of utilizing the Simpson rule to obtain according to step 3, as shown in Figure 4, curve is that contact is inhaled and time distribution curve among the figure, the vertical line vertical with horizontal ordinate is to be the differentiation boundary of 0.32ms the time, and utilizing the Simpson rule to calculate contactor bounce time qualification rate is 91.46%.
Claims (5)
1. the contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation is characterized in that this method comprises the steps:
Step 1: obtain the influential dimensional parameters design load of the bounce time of contactor, design parameter design load and adjust the range of tolerable variance of parameter designing value and each parameter according to design document and art work sheet, utilize MATLAB to produce the N group changes and meet normal distribution in range of tolerable variance dimensional parameters, design parameter and adjustment parameter three class parameter combinations according to independent identically distributed central limit theorem, Parameter N is the integer more than or equal to 1000;
Step 2: above N is organized three class parameter combinations successively as the input parameter of contactor bounce time acquisition module, obtain N group bounce time characterisitic parameter;
Step 3: the N group bounce time parameter that obtains is analyzed, calculated and obtain probability density function, parameter expectation and mean square deviation, and then obtain N group moving contact bounce time parameter distributions characteristic;
Step 4: require to determine bounce time differentiation boundary according to the performance index in the design parameter of contactor, the N group bounce time parameter distributions property calculation contactor bounce time qualification rate of utilizing the Simpson rule to obtain according to step 3.
2. a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation according to claim 1 is characterized in that, described contactor bounce time acquisition module adopts software engineering to realize, the course of work of this module comprises and the following is step:
Steps A, contactor model calculating parameter initialization characterisitic parameter is set;
Step B, ask the current time magnetic linkage by previous moment coil voltage, electric current and magnetic linkage integration;
Step C, obtain coil current by coil flux linkage, armature displacement check table;
Step D, the coil current, the armature displacement check table that are obtained by step C obtain electromagnetic attraction;
Step e, calculate the mechanical spring counter-force by the armature displacement
f=k·x+c
d·v
K, c in the formula
dRepresent spring rate and spring damping respectively, x, v represent armature displacement and the armature speed of spring respectively;
Step F, employing fourth-order Runge-Kutta method are found the solution the mechanical motion differential equation group, and described mechanical motion differential equation group is:
Described Y represents armature displacement, speed column vector, and expression formula is
Following footnote n represents sampling instant; t
nExpression n is time corresponding constantly;
G represents armature speed, acceleration column vector, and expression formula is
F represents electromagnetic attraction; M represents the armature quality;
G (t
n, Y
n) middle t
nAnd Y
nIndependent variable for above-mentioned expression formula;
H represents step-length computing time;
The calculation result data of step G, preservation step F is also extracted the bounce time characterisitic parameter from described calculation result data, finish obtaining of bounce time characterisitic parameter.
3. a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation according to claim 2, it is characterized in that, the described table of comparisons be the coil flux linkage of contactor about the bivariate table of coil current and armature displacement, this table of comparisons obtains by following step:
Step H, in UG software, set up the electromagnetic mechanism three-dimensional model according to the design drawing of the electromagnetic mechanism of contactor;
Step I, by software finite element software FLUX according to the three-dimensional model of electromagnetic mechanism, calculate the coil current, armature displacement, electromagnetic attraction and the magnetic linkage that obtain many windings tentaculum;
Step J, the coil current, armature displacement, electromagnetic attraction and the magnetic linkage parameter that obtain many windings tentaculum according to step I make up the table of comparisons.
4. a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation according to claim 3, it is characterized in that, step I is described by the three-dimensional model of software finite element software FLUX according to electromagnetic mechanism, and the process of calculating the coil flux linkage, coil current and the armature displacement that obtain many windings tentaculum is:
Step I1, employing finite element software FLUX set up geometric model according to the three-dimensional model of electromagnetic mechanism, and this geometric model are divided finite element grid;
Step I2, the physical attribute of each finite element grid among the step I1 is set according to the real physical characteristics of electromagnetic mechanism;
Step I3, the geometric model that sets up physical attribute is carried out static characteristics emulation, the coil current values of the many groups of input and corresponding dimensional parameters during emulation, described current value is obtained divided by the coil resistance in the design parameter of contactor by voltage; Obtain armature displacement, electromagnetic attraction and the magnetic linkage of every group of coil current value and dimensional parameters correspondence by emulation.
5. a kind of contactor bounce time qualification rate Forecasting Methodology based on Monte Carlo simulation according to claim 1, it is characterized in that the process that the N that utilizes the Simpson rule to obtain according to step 3 described in the step 4 organizes bounce time parameter distributions property calculation contactor bounce time qualification rate is:
At first calculate expectation and the variance of N group bounce time data, determine that according to existing bounce time acceptability limit the Simpson rule calculates required upper lower limit value then, adopt described rule to divide in the upper lower limit value inner product at last and obtain contactor bounce time qualification rate.
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Owner name: GUIZHOU ZHENHUA QUNYING ELECTRICAL APPLIANCES CO., Effective date: 20131107 |
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Effective date of registration: 20131107 Address after: 150001 Harbin, Nangang, West District, large straight street, No. 92 Applicant after: Harbin Institute of Technology Applicant after: Guizhou Zhenhua Qunying Electrical Appliances Co.,Ltd. Address before: 150001 Harbin, Nangang, West District, large straight street, No. 92 Applicant before: Harbin Institute of Technology |
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