CN105512496B - Tie up cable beam geometry characteristic method for automatic measurement at random - Google Patents
Tie up cable beam geometry characteristic method for automatic measurement at random Download PDFInfo
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Abstract
Cable beam geometry characteristic method for automatic measurement is tied up at random, belongs to electromagnetic measurement field.In order to solve the problems, such as that existing cable bundle geometrical property parameter acquiring method model applicable elements are harsh.The present invention establishes the inverse estimation model of Bayes of the random certainty forward model for tying up cable bundle model, the cable bundle external characteristics parameter set based on fractal coefficient, description fractal coefficient and impedance operator relationship and forward model based on fractal theory respectively, in conjunction with Markov chain Monte-Carlo algorithm, utilize cable bundle external impedance characteristic measured data, the inverse estimation model of Bayes is solved, the optimal estimation of fractal coefficient is calculated, and then the distribution character of geometric parameter between cable bunch is tied up in acquisition at random.This method is suitable for all kinds of random measurements for tying up cable beam geometry characteristic.
Description
Technical field
The invention belongs to electromagnetic measurement fields.
Background technology
The coupled problem of cable bundle is the typical problem faced in Aeronautics and Astronautics device EMC Design, and this problem
Also it just receives more and more attention.And at EMC Design initial stage, the geometrical property for determining cable bundle is first had to, it could be right
Its Electro Magnetic Compatibility is studied.Uniform transmission line model is used for tying up the approximate description of cable bundle at random at present,
Assume that cable bundle cross section geometry does not change in an axial direction between transmission circuit network node.This scheme is in mould
A kind of compromise processing made between type complexity and accuracy.And actual conditions are, due to the limitation of cable bundle technique, i.e.,
The same type produced using same process is with batch cable bundle, and there is also prodigious randomnesss for geometric cross-section.In addition, line
During the use of cable beam due to vibration cause cable and fixed frame rubs mutually, temperature change cause insulating layer aging etc. because
Element so that cable structure parameter and medium parameter change a lot, and then influence Distribution electric parameter and the electricity to cable bundle
Magneto-coupling effect has an impact.Traditional uniform transmission line model is not enough to describe the variation of these geometrical properties, it is therefore necessary to
Using the method for measurement, quantify the randomness of these geometrical property parameters, preferably to study the coupling effect of cable bundle.
The method for obtaining cable bundle external characteristics existing at present is mainly to be obtained by the method for numerical simulation, mainly have with
Lower three kinds of methods：
(1) the uniform transmission line Cascade of Segment equivalent is used, and the cross section geometric structure of adjacent transmission lines becomes at random
Change, the distribution character of result can be obtained by carrying out Multi simulation running using monte carlo method.The advantages of such method is to realize letter
It is single, but the computing resource consumed is more, and arbitrary structures cascade easily causes that cable is discontinuous, influences the accuracy of high frequency piecewise analysis.
(2) random midpoint set method：The randomness that one group of fractal curve comes analog cable position is generated, and uses FRACTAL DIMENSION
The axially varying degree of degree characterization cable location.Based on RDSI algorithms, using spline interpolation techniques keep the continuous of cable and
Smoothly, the randomness of cable location is characterized using the Gaussian Distribution Parameters of set-point and cable segments.This method can be with
Calculation amount is saved, but the premise used is the conducting wire for only including same model in cable bundle, does not consider the feelings of a variety of cable bundles
Condition.
(3) WH (Wire-Hole) modelling：By controlling every cable (Wire) in predefined cable bundle location hole
(Hole) the random transmission in characterizes the randomness of cable structure.This model is still only applicable to the cable being made of single cable
The modeling of beam.
Invention content
The purpose of the present invention is to solve existing cable bundle geometrical property parameter acquiring method model applicable elements harshnesses
The problem of, the present invention provides one kind and tying up cable beam geometry characteristic method for automatic measurement at random.
The random of the present invention ties up cable beam geometry characteristic method for automatic measurement, and described method includes following steps：
Step 1：Measure one group of random external impedance characteristic for tying up cable bundle to be measured, including open-circuit impedance characteristic and short
Road impedance operator obtains the random impedance for tying up cable bundle to be measured according to the distribution situation for tying up cable beam impedance characteristic at random
Performance data；
Step 2：Cable bundle is tied up at random according to be measured, establishes and cable beam geometry mould is tied up based on fractal theory at random
Type；
Step 3：According to the random cable type tied up in cable bundle to be measured, the description based on cable fractal coefficient is established
The parameter set of cable bundle geometrical property；
Step 4：Cable beam geometry model, structure cable point are tied up at random according to what transmission line theory and step 2 were established
The mapping relations of shape coefficient and impedance operator obtain certainty forward model；
Step 5：The certainty forward model of impedance operator data and the step 4 structure obtained according to step 1, is established
The inverse estimation model of Bayes；
Step 6：The inverse estimation model of Bayes obtained to step 5 using Markov chain Monte-Carlo algorithm is asked
Solution, obtains the optimal estimation of fractal coefficient；
Step 7：The optimal estimation for the fractal coefficient that step 6 obtains is substituted into the parameter set that step 3 obtains, is obtained
The parameter of the geometrical property of cable bundle is described.
The step 1, the method for measuring the random external impedance characteristic for tying up cable bundle to be measured：
The random both ends for tying up cable bundle to be measured pass sequentially through an air plug, an interconnecting device and a cubicle switchboard respectively
Battle array is connected with vector network analyzer simultaneously；Cable is tied up using the measurement of PC control vector network analyzer is to be measured at random
The open-circuit impedance characteristic and short-circuit impedance characteristic of beam.
The parameter set of the step 3, the description cable bundle geometrical property based on cable fractal coefficient is：
X={ x1(θ),x2(θ),...,xn(θ)}；
Wherein, θ={ θ1,θ2,...,θm}∈RmFor cable fractal coefficient；
Wherein, θiIt is i-th kind of random cable fractal coefficient for tying up cable bundle, m is the number for tying up cable bundle type at random
Amount, RmReal number space is tieed up for m.
In the step 4, certainty forward model is：Y=F (θ)+v, this model are established based on transmission line theory；
Wherein, y ∈ RdTo tie up the impedance operator data of cable bundle at random, d is the dimension of impedance operator data, v ∈ RdIt is
The random error introduced when by measuring, F (θ) are the forward model for not considering random error, indicate cable fractal coefficient to impedance
The mapping function of characteristic.
Wherein, Prob (θ) is the prior estimate of the cable fractal coefficient provided based on background knowledge；Prob (y | θ) be by
The probability distribution that one group of impedance operator data for tying up cable bundle at random obtains；Prob (θ | y) it is a likelihood distribution, it is to combine
Certainty forward model and the Posterior probability distribution after the impedance operator data of cable bundle is tied up at random.
In the step 6, the optimal estimation θ of fractal coefficient*=maximizeProb (θ | y)；
The beneficial effects of the present invention are, can to a variety of cables constitute complicated cable bundle model geometric characterisitic parameter with
Machine is quantified, strong applicability, and measuring system is easy to operate, stablizes and has high performance reproducibility so that measurement result has
There are very high stability and accuracy.
Description of the drawings
Fig. 1 is to measure the principle signal for tying up cable beam geometry characteristic at random in specific implementation mode using measuring table
Figure.
Fig. 2 is the left view of cable support 1 in Fig. 1.
Fig. 3 is the random T shape equivalent circuits for tying up cable bundle to be measured in specific implementation mode.
Fig. 4 is the random impedance measurement principle schematic diagram for tying up cable bundle to be measured in specific implementation mode.
Fig. 5 is the principle schematic for the cross-sectional model for tying up cable bundle at random.
Specific implementation mode
Present embodiment is illustrated in conjunction with Fig. 1 to Fig. 5, cable beam geometry characteristic is tied up at random described in present embodiment
Method for automatic measurement is realized based on test system, and the test system includes the switching of the air plug 2, two of cable support 1, two
Box 3,50 Europe resistance of SMA interfaces, 4, two switch matrix 5, vector network analyzer 6, host computer 7 and general purpose interface bus 8.
It is to be measured that random to tie up cable bundle can be the cable bundle or be different type that same type cable is tied up at random
The cable bundle that cable is tied up at random.In present embodiment, by taking the cable bundle of three same type cable bundles as an example；
The one random both ends for tying up cable bundle to be measured connect two interconnecting devices 3, one of interconnecting device by air plug 2 respectively
3 are connected by 50 Europe resistance 4 of SMA interfaces with a switch matrix 5, another interconnecting device 3 directly with another 5 phase of switch matrix
Even, two switch matrix 5 are connected by bnc interface connected vector Network Analyzer, while by USB interface with host computer, such as
Shown in Fig. 1.
The measurement method includes the following steps：
Step 1: by host computer 7 control two switch matrix 5, using vector network analyzer 6 measure one group it is to be measured with
Machine ties up the external impedance characteristic of cable bundle, according to the impedance operator distribution situation for tying up cable bundle at random, obtains to be measured random
Tie up the impedance operator data of cable bundle；
In present embodiment, the high-frequency transmission line model of three conductor cables is established, considers that cable kelvin effect is damaged with dielectric
Effect is consumed, the T shape equivalent circuits as shown in Figure 3 of the RLCG parameters in basic transmission line model are substituted.According to the impedance of Fig. 4
Measuring principle schematic diagram measures the external impedance characteristic for tying up cable bundle at random, can respectively obtain open-circuit impedance curve and short circuit
Impedance curve, the impedance operator measured Z ∈ RdIt indicates.
Present embodiment needs to measure one group of random external impedance characteristic for tying up cable bundle to be measured, in this way it is multiple it is to be measured with
The impedance operator that machine ties up cable bundle will present out certain probability distribution rule, and then determines and to be measured tie up cable bundle at random
Impedance operator data improve accuracy.
Step 2: tying up cable bundle at random according to be measured, establishes and cable beam geometry mould is tied up based on fractal theory at random
Type；
In order to accurately describe to tie up the randomness in cable bundle external characteristics at random, using the neutral displacement in fractal theory
Method models harness Linear Segments.Fractal theory has followed cable bundle and is continuous this brass tacks, and can ensure pair
The description of cable bundle randomness ensures the smooth of cable bundle structure using the spline interpolation used in RDSI methods simultaneously in modeling
Property.
Step 3: according to the random cable type tied up in cable bundle to be measured, the description based on cable fractal coefficient is established
The parameter set of cable bundle geometrical property；
As shown in Figure 5 ties up in cable bundle cross-sectional model at random, describes the parameter master of cable bundle external characteristics randomness
Have：
Cable centerline position coordinates (xi,yi), Cable radius ri, cable insulating layer thickness △ ri, the distance between two cables
si,j。
In addition to parameter described in cross-sectional model, also cable bundle length l.
Therefore the parameter set of the description cable bundle external characteristics randomness based on fractal coefficient is：
{(xi(θ),yi(θ)),ri(θ),△ri(θ),si,j(θ),l(θ)}。
Step 4: tying up cable beam geometry model, structure cable point at random according to what transmission line theory and step 2 were established
The mapping relations of shape coefficient and impedance operator obtain certainty forward model：：
Y=F (θ)+v (5)
Wherein, y ∈ RdTo tie up the impedance operator data of cable bundle at random, d is the dimension of impedance operator data, v ∈ RdIt is
The random error introduced when by measuring, for example, BNC connector influence etc..F (θ) is the forward model for not considering random error, table
Mapping function of the timberline cable fractal coefficient to impedance operator.
Step 5: the certainty forward model of the impedance operator data and step 4 structure obtained according to step 1, is established
The inverse estimation model of Bayes：
Wherein, Prob (θ) is the prior estimate of the cable fractal coefficient provided based on background knowledge；Prob (y | θ) be by
The probability distribution that one group of impedance operator data for tying up cable bundle at random obtains；Prob (θ | y) it is a likelihood distribution, it is to combine
Certainty forward model and the Posterior probability distribution after the impedance operator data of cable bundle is tied up at random.
Step 6: being asked using the inverse estimation model of Bayes that Markov chain Monte-Carlo algorithm obtains step 5
Solution, obtains the optimal estimation of fractal coefficient：
θ *=maximize Prob (θ | y) (7)
Step 7: the optimal estimation for the fractal coefficient that step 6 obtains is substituted into the parameter set that step 3 obtains, obtain
The parameter of the geometrical property of cable bundle is described：
{(xi(θ*),yi(θ*)),ri(θ*),△ri(θ*),si,j(θ*),l(θ*)}。
Claims (4)
1. one kind tying up cable beam geometry characteristic method for automatic measurement at random, which is characterized in that described method includes following steps：
Step 1：One group of random external impedance characteristic for tying up cable bundle to be measured is measured, including open-circuit impedance characteristic and short circuit hinder
Anti- characteristic obtains the random impedance operator for tying up cable bundle to be measured according to the distribution situation for tying up cable beam impedance characteristic at random
Data；
Step 2：Cable bundle is tied up at random according to be measured, establishes and cable beam geometry model is tied up based on fractal theory at random；
Step 3：According to the random cable type tied up in cable bundle to be measured, the description cable based on cable fractal coefficient is established
The parameter set of beam geometry characteristic；
Step 4：Cable beam geometry model is tied up at random according to what transmission line theory and step 2 were established, and structure cable divides shape system
The mapping relations of number and impedance operator obtain certainty forward model；
Step 5：The certainty forward model of impedance operator data and the step 4 structure obtained according to step 1, establishes pattra leaves
This inverse estimation model；
Step 6：The inverse estimation model of Bayes obtained to step 5 using Markov chain Monte-Carlo algorithm is solved,
Obtain the optimal estimation of fractal coefficient；
Step 7：The optimal estimation for the fractal coefficient that step 6 obtains is substituted into the parameter set that step 3 obtains, is described
The parameter of the geometrical property of cable bundle.
2. according to claim 1 tie up cable beam geometry characteristic method for automatic measurement at random, which is characterized in that the step
Rapid one, the method for measuring the random external impedance characteristic for tying up cable bundle to be measured：
It is same that the random both ends for tying up cable bundle to be measured pass sequentially through an air plug, an interconnecting device and a switch matrix respectively
When be connected with vector network analyzer；It is measured using PC control vector network analyzer and to be measured ties up cable bundle at random
Open-circuit impedance characteristic and short-circuit impedance characteristic.
3. according to claim 1 or 2 tie up cable beam geometry characteristic method for automatic measurement at random, which is characterized in that institute
Step 3 is stated, the parameter set of the description cable bundle geometrical property based on cable fractal coefficient is：
X={ x1(θ),x2(θ),...,xn(θ)}；
Wherein, θ={ θ1,θ2,...,θm}∈RmFor cable fractal coefficient；
Wherein, θiIt is i-th kind of random cable fractal coefficient for tying up cable bundle, m is the quantity for tying up cable bundle type at random, Rm
Real number space is tieed up for m.
4. according to claim 3 tie up cable beam geometry characteristic method for automatic measurement at random, which is characterized in that the step
In rapid four, certainty forward model is：Y=F (θ)+v, this model are established based on transmission line theory；
Wherein, y ∈ RdTo tie up the impedance operator data of cable bundle at random, d is the dimension of impedance operator data, v ∈ RdIt is by surveying
The random error introduced when amount, F (θ) are the forward model for not considering random error, indicate cable fractal coefficient to impedance operator
Mapping function.
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| CN101071450A (en) * | 2007-06-08 | 2007-11-14 | 桂林电子科技大学 | Electronic machine three-dimensional automatic routing system |
| CN104007326A (en) * | 2014-06-16 | 2014-08-27 | 吉林大学 | Method for quickly predicting crosstalk frequency domain dynamic characteristics of vehicle harness |
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| CN101071450A (en) * | 2007-06-08 | 2007-11-14 | 桂林电子科技大学 | Electronic machine three-dimensional automatic routing system |
| CN104007326A (en) * | 2014-06-16 | 2014-08-27 | 吉林大学 | Method for quickly predicting crosstalk frequency domain dynamic characteristics of vehicle harness |
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