CN104749251B - A kind of rejecting crystallite dimension ultrasonic evaluation method of the underwater sound away from influence - Google Patents
A kind of rejecting crystallite dimension ultrasonic evaluation method of the underwater sound away from influence Download PDFInfo
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Abstract
The invention discloses a kind of rejecting crystallite dimension ultrasonic evaluation method of the underwater sound away from influence, methods described to demarcation metal coupons by carrying out data acquisition, initial analysis determines to reject the iotave evaluation model structure of crystallite dimension of the underwater sound away from influence, again the pivot that each variable dimensionality reduction is combined in iotave evaluation model is calculated with PCA methods, by the parameter of each pivot regression estimates model so as to set up rejecting crystallite dimension implicit rating model of the underwater sound away from influence, crystallite dimension evaluation is carried out to the test test block for having neither part nor lot in model calculating.This method can reduce the systematic error of average grain size evaluation, for the test metal coupons that Metallography method determination average grain size is 105.57 μm, and the model evaluation result is 106.74 μm, and error is only 1.1%.It can be seen that, the adverse effect that the method that the present invention is provided inhibits the underwater sound to be evaluated away from Adjustment precision crystallite dimension improves the reliability of metal grain size Nondestructive Evaluation.
Description
Technical field
The present invention relates to metal average grain size field of measuring technique, more particularly to a kind of rejecting crystalline substance of the underwater sound away from influence
Particle size ultrasonic evaluation method.
Background technology
Crystallite dimension be characterize metal material microscopic characteristics an important parameter, it affect material fatigue strength,
The mechanical performance such as yield strength, toughness and plasticity, creep resistance and antifatigue extended capability.Therefore accurate measuring metallic materials
Crystallite dimension is significant to studying its mechanical performance.The measuring method of metal material crystallite dimension, which is divided into, to be damaged and nothing
Two kinds are damaged, there is that damage method such as metallographic method has visual result and accuracy of detection high, but material need to be destroyed, and point
Analysis program is cumbersome, detection efficiency bottom.Ultrasonic nonodestruction evaluation method has penetration capacity strong, and sensitivity is high, harmless etc. excellent
Point, is to carry out one of commonly used method of micro structure testing to material both at home and abroad at present.
The crystallite dimension of Polycrystalline Metals material has been largely fixed the decay of acoustic energy, therefore can determine ultrasonic attenuation system
The crystallite dimension of number Indirect evaluation material.However, accurate detection attenuation coefficient is by by a series of harsh in engineering practice
Experiment condition is constrained.For example in the different underwater sounds away under the conditions of, the attenuation coefficient detected to same material not definite value, and it is existing
Detection model, away from considering as influence factor, must take a significant amount of time the adjustment underwater sound away from general not using the underwater sound in actually detected
Sound beam focusing is in the middle part of measurand, and degree of regulation is difficult to ensure that.Therefore, the underwater sound how is rejected away between other empirical factors
Linear dependence, reduce the interference of experimental error, and therefrom excavate the underwater sound away from the affecting laws to attenuation measurement, be to improve brilliant
Particle size ultrasonic attenuation evaluates the key of validity.Based on above present Research, the present invention establishes one kind using PCA methods and picked
Remove water the metal average grain size evaluation model of throw influence.
The content of the invention
(1) technical problem to be solved
The technical problem to be solved in the present invention be without accurately adjustment the underwater sound away from the case of, how accurately, reliably, nothing
Loss measurement crystallite dimension.
(2) technical scheme
In order to solve the above-mentioned technical problem, the invention provides a kind of rejecting crystallite dimension ultrasound Evaluation of the underwater sound away from influence
Method, the described method comprises the following steps：
S1, by setting different heat treatment conditions to prepare test blocks, make it have grain size gradient, fixed probe master
Frequently, collection calculates corresponding put down in ultrasound echo signal of the different underwater sounds away from lower demarcation test block using ultrasound echo signal
Equal attenuation coefficient, using Metallography method determination and records the average grain size of each demarcation test block；
S2, using described mean attenuation coefficient, and its corresponding underwater sound away from and demarcation test block average grain size,
Based on the fitting of a polynomial for limiting correlation coefficient threshold, set up and reject average grain size initial evaluation model of the underwater sound away from influence
Structure；
S3, the pivot that each variable dimensionality reduction in the initial evaluation model structure is combined into is calculated using PCA methods,
With the parameter of each pivot regression estimates model, so as to set up rejecting average grain size implicit rating mould of the underwater sound away from influence
Type；
S4, average grain size implicit rating model of the rejecting underwater sound away from influence obtained using the step S3 are to demarcation
Test block carries out crystallite dimension evaluation, and contrast metallographic method surveys crystallite dimension and verifies the accurate of the average grain size evaluation model
Property；Then to test test block progress attenuation coefficient prediction and evaluation, put down described in contrast echo die-away test survey calculation result verification
The predictive ability of equal crystallite dimension evaluation model.
2nd, preferably, in the step S2, fitting of a polynomial correlation coefficient threshold is [0.95,1], and selects to meet threshold value
The minimum number of times of standard is used as multinomial highest number of times；Setting measurement probe dominant frequency is f0When, based on above-mentioned calculated rejecting
Crystallite dimension initial evaluation model of the underwater sound away from influence be
In formula, C1For with f0Related model constants, D is test block average grain size, aiFor the coefficient of D ith side,
m0For average grain size D highest time number formulary, W is the measurement underwater sound away from bi is the coefficient of W ith side, m1It is the underwater sound away from W's
Highest time number formulary, α (D, W) is the function on attenuation coefficient α of the underwater sound away from W and average grain size D；
3rd, preferably, the step S3 is specially：
S31, the measured variable by the multifactor evaluation model of initial average grain size in the step 2It is denoted asEach measured variable has n
Observation sample, thus can build linearized data matrixMeasured variable is standardized simultaneously, i.e.,：
In formula, LnUnit column vector is tieed up for n,
Measured variable matrix after standardization is denoted asxiFor the i-th of measured variable matrix X
Row data；
Standardization measured variable matrix X measured variable pivot score matrixes in S32 and then solution procedure S31Calculation formula is
In formula,X model value is represented, E is modeling error, and Z is measured variable pivot score matrix, and P is measured variable
Pivot matrix of loadings, Z*It is measured variable residual error score matrix, P*It is measured variable residual error matrix of loadings, tiObtained for measured variable
Resolute, piIt is measured variable load vector, l is pivot quantity；
S33, handled using PCA after data, multivariate linear equation is carried out to the measured variable pivot score matrix of gained,
Obtaining rejecting crystallite dimension implicit rating model of the underwater sound away from influence is
In formula, B=[b1,b2……bl]TFor measured variable principal component regression model coefficient matrix, C2To return computational constant, Y
For the attenuation coefficient matrix of crystallite dimension implicit rating model.
(3) beneficial effect
The invention provides a kind of rejecting crystallite dimension ultrasonic evaluation method of the underwater sound away from influence, eliminated by PCA methods
The underwater sound reduces the interference of experimental error away from the linear dependence between other empirical factors, and therefrom excavates the underwater sound away to decay
The affecting laws of measurement, set up and reject crystallite dimension implicit rating model of the underwater sound away from influence.For the average crystalline substance of Metallography method determination
Particle size is 105.57 μm of test metal coupons, and the model evaluation result is 106.74 μm, and error is only 1.1%, it is seen then that logical
The adverse effect for rejecting measurement process reclaimed water throw Adjustment precision to average grain size evaluation result is crossed, metal material is improved and puts down
The practicality and reliability of equal crystallite dimension ultrasonic nonodestruction evaluation method.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the accompanying drawing used required in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can be with
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is a kind of flow chart of crystallite dimension ultrasonic evaluation method of rejecting underwater sound away from influence of the present invention；
Fig. 2 is ultrasonic signal acquisition system structural representation in the present invention；
Fig. 3 is the physical dimension figure of test block in the present invention；
Fig. 4 a-4i are the metallograph of each test block in the present invention；
Fig. 5 for the present invention in test block survey calculation the underwater sound away from attenuation relation figure；
Fig. 6 is the result figure of the multifactor evaluation model of average grain size in the present invention；
Embodiment
The present invention is described in further detail with reference to the accompanying drawings and examples.Following examples are used to illustrate this hair
It is bright, but can not be used for limiting the scope of the present invention.
Embodiment is the 304 stainless steels preparation test block for 06Cr19Ni10 from the trade mark, and the underwater sound is rejected to set up
Crystallite dimension implicit rating model away from influence using test block known to average grain size, it is necessary to be used as reference.Using ultrasonic arteries and veins
Rush signal generation/receiver and transmitting-receiving into line-pulse signal is connected with focusing probe；Using motion control card and motion platform, adjust
Whole control probe vertical moves up and down in measured surface, and is obtained with the high-speed data acquisition card on computer and store Ultrasound Instrument
The raw ultrasound A ripple signals of output, are finally further analyzed and model on computers.
Fig. 1 for the present invention a kind of crystallite dimension ultrasonic evaluation method of rejecting underwater sound away from influence flow chart, modeling with
The step of evaluation, is as follows：
S1, by setting different heat treatment conditions to prepare test blocks, make it have grain size gradient, pass through such as Fig. 2 institutes
The ultrasonic testing system shown.Fixed probe dominant frequency, gathers in ultrasound echo signal of the different underwater sounds away from lower demarcation test block, utilizes
Ultrasound echo signal calculates corresponding mean attenuation coefficient, using Metallography method determination and records the average crystal grain of each demarcation test block
Size；
S11, to make not produce side-wall interference during ultrasound detection, physical dimension such as Fig. 3 institutes of design demarcation and test test block
Show；
S12, adjustment control probe vertical are in the position of measured surface, to k1Individual various grain sizes test block takes k successively2Group
The underwater sound away from；Echo-signal is gathered using high-speed data acquisition card, using VC++ and Matlab hybrid programmings to the data that collect
Handled, obtain A wave number evidences, and thus calculate the underwater sound away from and attenuation coefficient；
S13, using Metallography method determination and the average grain size of each demarcation test block is recorded, specific method is：Use high temperature
Stove is to crowd k prepared1Individual test block carries out the heat treatment of different temperatures and soaking time, makes it have the same of grain size gradient
When keep essentially identical diffusion rate and cyrystal boundary segregation, a stress relief annealing then is carried out to all test blocks, then use metallographic
Method measures average grain size：Grind away and polishing are carried out to the test block after heat treatment；Corrosive liquid is prepared to be corroded；It is aobvious in metallographic
The observation and pattern collection of metallographic are carried out in micro-system, each test block metallographic is as shown in Fig. 4 a-4i；According to GB-6394-2002《Gold
Belong to mean grain size assay method》Calculate each average grain size and be denoted as
S2, using described mean attenuation coefficient, and its corresponding underwater sound away from and demarcation test block average grain size,
Based on the fitting of a polynomial for limiting correlation coefficient threshold, set up and reject average grain size initial evaluation model of the underwater sound away from influence
Structure；
S21, by the k described in step 11Individual various grain sizes, k2The group underwater sound away from and the attenuation coefficient that is calculated as model
The reference sample set up and verified, the sample size is k1·k2, according to the data of the sample determine the underwater sound away from attenuation coefficient
Relation curve, the tentatively selected underwater sound is away from decaying to high-order moment functional relation；
S22, selected fitting of a polynomial correlation coefficient threshold are [0.95,1], and select to meet the minimum number of times of threshold value standard
For multinomial highest number of times, the phase relation is met away from being fitted determination with attenuation relation curve to every underwater sound using enumerative technique
The m of number threshold1；According to classical ultrasonic scattering formula, the m corresponding to this experimental condition is selected0；Initially put down based on above-mentioned calculated
The multifactor evaluation model of equal crystallite dimension is
In formula, C1For with f0Related model constants, D is test block average grain size, aiFor the coefficient of D ith side,
m0For average grain size D highest time number formulary, W is the measurement underwater sound away from bi is the coefficient of W ith side, m1It is the underwater sound away from W's
Highest time number formulary, α (D, W) is the function on attenuation coefficient α of the underwater sound away from W and average grain size D；
S3, the pivot that each variable dimensionality reduction in the initial evaluation model structure is combined into is calculated using PCA methods,
With the parameter of each pivot regression estimates model, so as to set up rejecting average grain size implicit rating mould of the underwater sound away from influence
Type；
S31, the measured variable by the multifactor evaluation model of initial average grain size in the step 2It is denoted asEach measured variable has n
Observation sample, thus can build linearized data matrixMeasured variable is standardized simultaneously, i.e.,：
In formula, LnUnit column vector is tieed up for n,
Measured variable matrix after standardization is denoted asxiFor the i-th of measured variable matrix X
Row data；
The measured variable pivot score matrix of standardization measured variable matrix X in S32 and then solution procedure S31Calculation formula is
In formula,X model value is represented, E is modeling error, and Z is measured variable pivot score matrix, and P is measured variable
Pivot matrix of loadings, Z*It is measured variable residual error score matrix, P*It is measured variable residual error matrix of loadings, tiObtained for measured variable
Resolute, piIt is measured variable load vector, l is pivot quantity；
S33, handled using PCA after data, multivariate linear equation is carried out to the measured variable pivot score matrix of gained,
Obtaining rejecting crystallite dimension implicit rating model of the underwater sound away from influence is
In formula, B=[b1,b2……bl]TFor measured variable principal component regression model coefficient matrix, C2To return computational constant, Y
For the attenuation coefficient matrix of crystallite dimension implicit rating model.
S4, average grain size implicit rating model of the rejecting underwater sound away from influence obtained using the step S3 are to demarcation
Test block carries out crystallite dimension evaluation, and contrast metallographic method surveys crystallite dimension and verifies the accurate of the average grain size evaluation model
Property；Then to test test block progress attenuation coefficient prediction and evaluation, put down described in contrast echo die-away test survey calculation result verification
The predictive ability of equal crystallite dimension evaluation model.
Fig. 2 is ultrasonic signal acquisition system structural representation in the present invention, and the ultrasonic signal acquisition system includes being used for
Control bottom hardware and the industrial computer 1 of computing, the high-speed data acquisition card 2 for gathering ultrasonic a-signal, for encouraging and receiving
Ultrasonic pulse generation/receiver 3 of ultrasonic probe signal, tank 4, as the pure water 5 of the couplant of ultrasonic propagation, is used for
Connect the probe holder 6 of motion platform and ultrasonic probe, 6-dof motion platform 7, the ultrasound for launching and receiving ultrasonic wave
Longitudinal wave probe 8,304 tested stainless steel test blocks 9, the switch board 10 for manipulating motion platform, for passing through PC control
Motion platform controls the motion control card 11 of circuit.
Present embodiment is prepared demarcation test block 6, is designated as # from 304 stainless steels that the trade mark is 06Cr19Ni10
0、#1、#3、#4、#5、#8；Test block 3 is tested, #2, #6, #7 is designated as.The heat treatment of test block uses CM companies 1610BL type high temperature
The corrosive liquid chemical composition used in stove, Metallographic Analysis is 20%HF+10%HNO3+ 70%H2O, etching time is 20min, is connect
And grind away, polishing are carried out to test block, using Leica companies DM4000M type metallography microscope sem observation metallographic structures.At the heat of test block
Manage bar part and metallographic method crystallite dimension are as shown in table 1.
The test block heat treatment condition of table 1 and metallographic method crystallite dimension
Six used in the collection of A ripple signals, this example are carried out to test block using the ultrasonic signal acquisition system shown in Fig. 2
Free degree motion platform is the CYS-1100 type 6-dof motion platforms that Shanghai Cytrix Electrical Technology Co., Ltd. produces, high
Fast data collecting card uses ADLINKPCIe-9852 Data Acquisition Cards, and its sampling interval is set to 5ns, ultrasonic pulse generation/reception
Device uses Olympus 5072PR types ultrasonic pulses generation/receiver, and ultrasonic longitudinal wave probe is from model GE-IAP10.6.3
Probe, its centre frequency be 10MHz, motion control card use the axle control card of DMC2610PCI buses 6.
The underwater sound is observed away from the relation with attenuation coefficient as shown in figure 5, being clear to the underwater sound away from there is significant shadow to pad value by Fig. 5
Ring；The underwater sound is away from a timing, and attenuation coefficient and crystallite dimension are 82.51~105.57 μ in crystallite dimension on the whole into positive correlation
The positive correlation reduces and attenuation coefficient distribution Relatively centralized during m and 124.43~135.44 μm of interval；It is also shown simultaneously by Fig. 5
Decay with the underwater sound away from change meet tentatively select high-order moment function fluctuation tendency, every curve in Fig. 5 is all adopted
When being fitted with 4 times, coefficient correlation is all higher than 0.95 first, i.e., just enough using the multinomial nonlinear regression model (NLRM) of highest 4 times
Fitting, therefore m can be obtained1=4, and because experiment condition meets Rayleigh scattering, therefore take m0=3.
With reference to the data gathered, by formula (2-6) can with the underwater sound away from and the average crystalline substance of the related metal of attenuation coefficient
Particle size implicit rating model：
When solving crystallite dimension by the way that upper crystallite dimension implicit rating model is counter, it can be calculated by formula (8), wherein C3=
1.654
F (D)=α-h (W)-C3=g (α, W) (8)
With rejecting average grain size implicit rating model of the underwater sound away from influence to participating in #0, #1, # that model is calculated
3rd, six demarcation test blocks of #4, #5, #8 carry out crystallite dimension evaluation, and contrast metallographic method surveys crystallite dimension and verifies the average crystal grain
The accuracy of Size Evaluation model.Table 2 and Fig. 6 illustrate evaluation result and metallographic of the method for the invention provided to demarcation test block
Result and their error analysis that method is determined.
The evaluation result of 2 pairs of demarcation test blocks of table and error analysis
Crystallite dimension is surveyed with reference to metallographic method, with rejecting average grain size implicit rating model pair of the underwater sound away from influence
The tri- test test blocks of #2, #6, #7 for having neither part nor lot in model calculating carry out ultrasonic attenuation coefficient prediction, contrast test survey calculation gained
Attenuation coefficient verifies the predictive ability of the average grain size evaluation model.Table 3 illustrates the method prediction that the present invention is provided
Test the attenuation coefficient of test block and the result of ultrasonic attenuation experiment calculation and their error analysis.
The evaluation result of 3 pairs of test test blocks of table and error analysis
The method of the present invention eliminates the underwater sound away between other empirical factors according to PCA data space dimensionality reduction projection property
Linear dependence, reduce the interference of experimental error, and therefrom excavate the underwater sound away from the affecting laws to attenuation measurement, set up and reject
Crystallite dimension implicit rating model of the underwater sound away from influence, can reduce the systematic error of average grain size evaluation, for metallographic method
The test metal coupons that average grain size is 105.57 μm are determined, the model evaluation result is 106.74 μm, and error is only
1.1%, it is seen then that by rejecting adverse effect of the measurement process reclaimed water throw Adjustment precision to average grain size evaluation result,
Improve the practicality and reliability of metal material average grain size ultrasonic nonodestruction evaluation method.
Embodiment of above is merely to illustrate the present invention, rather than limitation of the present invention.Although with reference to embodiment to this hair
It is bright to be described in detail, it will be understood by those within the art that, to technical scheme carry out it is various combination,
Modification or equivalent substitution, without departure from the spirit and scope of technical solution of the present invention, the right that all should cover in the present invention is wanted
Ask among scope.
Claims (3)
1. a kind of rejecting crystallite dimension ultrasonic evaluation method of the underwater sound away from influence, it is characterised in that methods described includes following step
Suddenly：
S1, by setting different heat treatment conditions to prepare test blocks, make it have grain size gradient, fixed probe dominant frequency is adopted
Collect in ultrasound echo signal of the different underwater sounds away from lower demarcation test block, corresponding average attenuation is calculated using ultrasound echo signal
Coefficient, using Metallography method determination and record it is each demarcation test block average grain size；
S2, using described mean attenuation coefficient, and its corresponding underwater sound away from and demarcation test block average grain size, be based on
The fitting of a polynomial of correlation coefficient threshold is limited, sets up and rejects average grain size initial evaluation model knot of the underwater sound away from influence
Structure；
S3, using PCA methods the pivot that each variable dimensionality reduction in the initial evaluation model structure is combined into is calculated, used
The parameter of each pivot regression estimates model, so as to set up rejecting average grain size implicit rating model of the underwater sound away from influence；
S4, average grain size implicit rating model of the rejecting underwater sound away from influence obtained using the step S3 are to demarcation test block
Crystallite dimension evaluation is carried out, contrast metallographic method surveys the accuracy that crystallite dimension verifies the average grain size evaluation model；
Then attenuation coefficient prediction and evaluation, average crystalline substance described in contrast echo die-away test survey calculation result verification are carried out to test test block
The predictive ability of particle size evaluation model.
2. according to the method described in claim 1, it is characterised in that in the step S2, fitting of a polynomial correlation coefficient threshold
For [0.95,1], and the minimum number of times for meeting threshold value standard is selected as multinomial highest number of times；Setting measurement probe dominant frequency be
f0When, it is based on above-mentioned calculated crystallite dimension initial evaluation model of the rejecting underwater sound away from influence
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In formula, C1For with f0Related model constants, D is test block average grain size, aiFor the coefficient of D ith side, m0It is flat
Equal crystallite dimension D highest time number formulary, W is the measurement underwater sound away from bi is the coefficient of W ith side, m1For highest of the underwater sound away from W
Secondary number formulary, α (D, W) is the function on attenuation coefficient α of the underwater sound away from W and average grain size D；
3. according to the method described in claim 1, it is characterised in that the step S3 is specially：
S31, the measured variable by the multifactor evaluation model of initial average grain size in the step 2It is denoted asEach measured variable has n
Observation sample, thus can build linearized data matrixMeasured variable is standardized simultaneously, i.e.,：
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Matrix of loadings, Z*It is measured variable residual error score matrix, P*It is measured variable residual error matrix of loadings, tiSweared for measured variable score
Amount, piIt is measured variable load vector, l is pivot quantity；
S33, handled using PCA after data, multivariate linear equation is carried out to the measured variable pivot score matrix of gained, obtained
Rejecting crystallite dimension implicit rating model of the underwater sound away from influence is
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In formula, B=[b1,b2……bl]TFor measured variable principal component regression model coefficient matrix, C2To return computational constant, Y is crystalline substance
The attenuation coefficient matrix of particle size implicit rating model.
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| CN106483198B (en) * | 2015-10-21 | 2019-03-19 | 中南大学 | A kind of metal grain size ultrasonic attenuation evaluation method rejecting curved surface and extending influence |
| CN105954360A (en) * | 2016-06-03 | 2016-09-21 | 河北省电力建设调整试验所 | Ultrasonic testing method for coarse grain of 20 CrlMolVNbTiB high-temperature bolt |
| CN107037131B (en) * | 2017-05-04 | 2019-09-06 | 中南大学 | A kind of tiny flaw supersonic detection method based on the extreme value distribution theory |
| CN109033586B (en) * | 2018-07-13 | 2022-08-12 | 南昌航空大学 | Method and system for determining alloy grain size based on mapping monotonicity |
| CN111044614B (en) * | 2019-12-16 | 2022-03-29 | 南昌航空大学 | High-temperature alloy grain size circle-like mapping ultrasonic evaluation method |
| CN112328972B (en) * | 2020-11-11 | 2022-03-29 | 南昌航空大学 | Method and system for evaluating crystal grain structure |
| CN113804591B (en) * | 2021-09-03 | 2023-05-12 | 南昌航空大学 | High-dimensional ultrasonic evaluation method for nickel-based alloy grain size |
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