CN106932416B - Gas turbine blades internal flaw three-dimensional parameter extracting method based on digital radial - Google Patents
Gas turbine blades internal flaw three-dimensional parameter extracting method based on digital radial Download PDFInfo
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- CN106932416B CN106932416B CN201710084115.7A CN201710084115A CN106932416B CN 106932416 B CN106932416 B CN 106932416B CN 201710084115 A CN201710084115 A CN 201710084115A CN 106932416 B CN106932416 B CN 106932416B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
- G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
- G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2223/00—Investigating materials by wave or particle radiation
- G01N2223/40—Imaging
- G01N2223/401—Imaging image processing
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2223/00—Investigating materials by wave or particle radiation
- G01N2223/60—Specific applications or type of materials
- G01N2223/646—Specific applications or type of materials flaws, defects
Abstract
The two-dimensional detection image of defect is carried out a finite element according to pixel arrangement first and divided by the gas turbine blades internal flaw three-dimensional parameter extracting method based on digital radial that the invention discloses a kind of；Then discrete quantized is carried out according to gray value to the thickness at each pixel, determines the corresponding relationship of gray scale and thickness；Finally all pixels finite element is accumulated, extracts the three-dimensional parameter of defect area.The two-dimensional detection image of defect is carried out a finite element according to pixel arrangement and divided by thought of this method based on finite element, carries out discrete quantized according to gray value to the thickness at each pixel, and then determine the corresponding relationship of gray scale and thickness.By adding up to all pixels finite element region, extraction obtains the three-dimensional parameter of defect, deficiency of the traditional radiographic detection method in the extraction of defect three-dimensional parameter can be effectively made up, can realize the extraction to gas turbine blades internal flaw three-dimensional parameter with lower cost with higher efficiency.
Description
[technical field]
The invention belongs to industrial x-ray field of non destructive testing, it is related to inside a kind of gas turbine blades based on digital radial
Defect three-dimensional parameter extracting method.
[background technique]
Gas turbine is in the widely applied a kind of rotary vane type dynamic power machine in the fields such as electric power, navigation.Currently, China
In the key technology for not yet grasping the manufacture of gas turbine kernel component completely, Related product also relies primarily on external import.Leaf
Piece is the core pneumatic zero for interacting and realizing energy conversion with the working media of high temperature high pressure and hig flow speed on gas turbine
Part, manufacture generally use hot investment casting moulding process, and need to bear huge work under high temperature and pressure and carry
Lotus.Since no matter blade is manufacturing or be on active service the stage, it may all be formed in the interior thereof shrinkage cavity and porosity, crackle, be mingled with
The defect of form will seriously affect the working performance, service life and the security reliability of operation of gas turbine complete machine.Cause
This, studies the detection technique of gas turbine blades defect, to the skill for improving China's gas turbine manufacture level, breaking through developed country
Art block has important and far-reaching strategic importance.
Since gas turbine blades belong to complex free curved surface class part, and usually by the nickel-base high-temperature with greater density
Alloy material is constituted, therefore generallys use the method based on ray to its non-destructive testing.Traditional method uses industrial x-ray pair
Blade carries out transillumination, and the detection to blade interior defect is realized by film imaging.This method has imaging resolution high, clever
The advantages that sensitivity is high, intuitive and reliable, plays an important role in industrial nondestructive testing field.Due to the method be substantially by
Blade projection imaging on film along transillumination direction, therefore only can clearly show the two-dimensional silhouette of defect, for defect saturating
It can not but be shown according to the three-dimensional feature information on direction.Even veteran professional technician is also difficult accurately to estimate this
Information on dimension.And Industrial Computed Tomography is due to can accurate, clear, intuitively obtain testee internal structure composition and lack
Sunken three-dimensional information, so that it has a degree of application in blade interior defects detection.But also there is both sides
Limitation: on the one hand, due to blade composition material nickel base superalloy for ray have biggish attenuation coefficient, power compared with
Small CT completely can not effectively penetrate blade realization.Therefore the industrial CT system with larger transillumination power can only be used,
Such system fancy price has directly raised the cost of crop leaf measuring.It on the other hand, is smaller ruler inside precise detection of blade
The defect of degree need to also largely be sliced blade with lesser interval.In view of gas turbine blades are usually required full inspection,
Huge number of slice of data acquisition requires the efficiency that detection can not only be greatly reduced, and can also bring huge operating cost.Cause
This, just because of the high testing cost of industry CT and extremely low detection efficiency, so that it is difficult in the actual combustion gas wheel of engineering
It is widely used in machine crop leaf measuring.
[summary of the invention]
In view of the above-mentioned deficiencies in the prior art, the technical problem to be solved by the present invention is that the invention discloses one kind
Large high-temperature blade interior defect three-dimensional parameter extracting method based on digital radial, by scheming the thickness at each pixel
The gray scale of picture carries out discrete quantized, so that each gray value corresponds to a thickness, acquires the thickness at each pixel, simultaneously based on this
The quantitative detection to defect three-dimensional parameter can be realized in conjunction with the size of pixel.
The invention adopts the following technical scheme:
Gas turbine blades internal flaw three-dimensional parameter extracting method based on digital radial first examines the two dimension of defect
Altimetric image carries out a finite element according to pixel arrangement and divides；Then the thickness at each pixel is carried out according to gray value discrete
Quantization, determines the corresponding relationship of gray scale G Yu thickness T；Finally all pixels finite element is accumulated, extracts the three of defect area
Tie up parameter.
Further, comprising the following steps:
S1, the linear response range for determining digital radial detection system；
S2, two-dimensional detection image is obtained to blade progress transillumination using digital radial detection system, and obtains the two of defect
Tie up profile；
S3, by test voussoir transillumination, obtain under specific transmitting illumination parameter image grayscale and material thickness relationship
Curve；
S4, by the simulation background gray scale of defect and original image defect gradation conversion at thickness, two thickness subtract each other acquisition defect
Thickness.
S5, it adds up to thickness information at each defect pixel, the three-dimensional parameter of defect can be obtained.
Further, in step S1, the digital radial detection system includes that the support of radiographic source, the tested blade of placement is put down
Platform, flat panel detector and imaging and control system, the radiographic source are connected to the imaging and control by radiographic source controller
System processed, control system is connect the support platform with the imaging and control system after testing, the flat panel detector warp
Detector controller is crossed to connect with the imaging and control system.
Further, in step S1, center is set on the flat panel detector and opens foraminate stereotype, the aperture passes through
The stereotype is worn, the diameter of the aperture is 1mm or more, is less than 10mm, increases the transillumination ginseng of the digital radial detection system
Number obtains different light exposures, and the flat panel detector is changed into highlighted complete white, acquisition by completely black at image in collimating eyelet place
The digital radial detection system corresponds to the imaging gray scale of different light exposures in orifice region, draws the sound of the flat panel detector
Curve is answered, determines the linear response regions of digital radial detection system.
Further, the linear response relationship of the digital radial detection system are as follows:
G=α H+b
Wherein: G-imaging gray value, H-light exposure, α-linear response regions slope, b-imaging gray scale linear deflection
Amount.
Further, in step S2, obtain the two-dimensional silhouette of the defect specifically includes the following steps:
S21, it transillumination is carried out to blade using digital radial detection system obtains gray scale and is in system linear regional scope
Two-dimensional detection image；
S22, crop leaf measuring image zooming-out defect boundary, the preliminary two-dimensional silhouette for obtaining defect are based on；
S23, morphological dilations are carried out to the defect two-dimensional silhouette that step S22 is tentatively obtained, expands defect area to ensure
All defect profile is entirely included in the region after morphological dilations；
S24, bicubic interpolation is carried out to expansion area, calculates the simulation background of defect area；
S25, simulation background image and original image are made the difference, and the two dimension that binary conversion treatment obtains defect is done to error image
Precise boundary.
Further, in step S3, the same material test identical with subregion thickness change range of processing thickness change range
With voussoir, each voussoir uses exposure parameter identical with corresponding region, using subregion arrangement, by each region
Thickness is limited in certain range, and carries out a transillumination, the transmitting illumination parameter packet using one group of specific exposure parameter
Include tube voltage, tube current and time for exposure.
Further, during a transillumination, as the increase of scanning thickness reaches the flat panel detector
Effective light exposure reduces, and is determined between imaging gray value G and scanning thickness T according to light exposure H and the linear relationship that gray scale G is imaged
Functional relation it is as follows:
G=f (T).
Further, in step S5, the body of each pixel region in defect two-dimensional silhouette region is sought according to thickness information
Product is as follows:
V=a2×(T0-T1)
Wherein: V-single pixel Domain Volume, a-pixel side length, T0- single pixel Region Theory thickness, T1- single
Pixel region actual (real) thickness.
Further, the three-dimensional parameter of the defect area calculates as follows:
Wherein: Vall- defect area total volume, n-defect area sum of all pixels, Ti0- defect area ith pixel area
Domain theory thickness, Ti1- defect area ith pixel region actual (real) thickness.
Compared with prior art, the present invention at least has the advantages that
The present invention is based on the gas turbine blades internal flaw three-dimensional parameter extracting methods of digital radial, based on finite element
The two-dimensional detection image of defect is carried out a finite element according to pixel arrangement and divided, pressed to the thickness at each pixel by thought
Discrete quantized is carried out according to gray value, and then determines the corresponding relationship of gray scale and thickness.By to all pixels finite element region into
Row is cumulative, and extraction obtains the three-dimensional parameter of defect, can effectively make up traditional radiographic detection method in the extraction of defect three-dimensional parameter
Deficiency can realize with higher efficiency with lower cost to gas turbine blades internal flaw compared to industrial CT system
The extraction of three-dimensional parameter.
Further, this method first determines the linear response range of digital radial detection system, and digital radial is recycled to visit
Examining system carries out transillumination to blade and obtains two-dimensional detection image, and obtains the two-dimensional silhouette of defect, then uses bicubic interpolation
The background in method simulated defect region, then by obtaining image grayscale and material under specific transmitting illumination parameter to test voussoir transillumination
The relation curve for expecting thickness, then by the simulation background gray scale of defect and original image defect gradation conversion at thickness, two thickness phases
Subtract and obtain defect thickness, finally adds up to thickness information at each defect pixel, the three-dimensional parameter of defect can be obtained.
Further, digital radial detection system by radiographic source, the support platform for placing tested blade, flat panel detector with
And imaging and control system form, the center that is provided on flat panel detector is provided with the stereotype of a grade through-hole, passes through it
Reduce the scattering of ray to the collimating effect of ray, effectively avoiding ray, there are scattering phenomenons in transillumination object.
Further, crop leaf measuring image zooming-out defect boundary, the preliminary two-dimensional silhouette for obtaining defect, then to first are based on
The defect two-dimensional silhouette that step obtains carries out morphological dilations, expands defect area to ensure that all defect profile is entirely included
In region after morphological dilations, then bicubic interpolation is carried out to expansion area, calculates the simulation background of defect area, finally
Simulation background image is made the difference with original image, and the two-dimentional precise boundary that binary conversion treatment obtains defect is done to error image, no
It is only capable of accurately obtaining defect two-dimensional silhouette reduction error, moreover it is possible to pass through simulated defect background and obtain original thickness.
Further, processing thickness change range same material test voussoir identical with subregion thickness change range, often
A voussoir passes through the test to known dimensions using subregion arrangement using exposure parameter identical with corresponding region
Voussoir carries out transillumination, can quantitatively quantify scanning thickness representated by each gray value of transillumination image.
Below by drawings and examples, technical scheme of the present invention will be described in further detail.
[Detailed description of the invention]
Fig. 1 is digital radial detection system schematic diagram of the present invention；
Fig. 2 is the method for the present invention flow diagram；
Fig. 3 is digital radial detection system test schematic of the present invention；
Fig. 4 is the response pattern curve graph of flat panel detector of the present invention；
Fig. 5 is that the method for the present invention obtains defect two-dimensional silhouette flow diagram；
Fig. 6 is blade subregion transillumination schematic diagram of the present invention；
Fig. 7 is present invention test voussoir transillumination schematic diagram；
Fig. 8 is gray scale of the present invention-thickness relationship curve graph；
Fig. 9 is the present invention by image grayscale acquisition material thickness schematic diagram；
Figure 10 is the volume schematic diagram of defect pixel of the present invention.
[specific embodiment]
Refering to Figure 1, the invention discloses a kind of digital radial detection system, and the combustion gas based on digital radial
Turbine blade internal flaw three-dimensional parameter quantifies extracting method.By by the gray scale of the image of the thickness at each pixel carry out from
Quantization is dissipated, so that (flat panel detector dynamic range reaches sixteen bit, the discrete thickness of acquisition to the corresponding thickness of each gray value
Three orders of magnitude smaller than Pixel Dimensions).Thus the thickness at each pixel is acquired, based on this and combines the size of pixel can be real
Now to the quantitative detection of defect three-dimensional parameter.
It please refers to shown in Fig. 2, the present invention is based on the gas turbine blades internal flaw three-dimensional parameters of digital radial quantitatively to mention
Taking method includes following six step:
S1, the linear response range for determining digital radial detection system；
Please refer to shown in Fig. 3, the digital radial detection system include radiographic source, the support platform for placing tested blade,
Flat panel detector and imaging and control system, the radiographic source are connected to the imaging and control system by radiographic source controller
System, control system is connect the support platform with the imaging and control system after testing, and the flat panel detector is by visiting
It surveys device controller to connect with the imaging and control system, since there are scattering phenomenons in transillumination object for ray, in stereotype
The heart processes a millimetre-sized small through hole, and the diameter of aperture is 1mm or more, is less than 10mm, passes through its collimating effect to ray
Reduce the scattering of ray, and stereotype is close to the flat panel detector and is placed.
The digital radial detection system course of work is as follows: by radiographic source controller be arranged every transmitting illumination parameter (tube voltage,
Tube current, time for exposure) control radiographic source transmitting X-ray；The X-ray of radiographic source transmitting passes through tested blade and is detected by plate
Device is received；X-ray is converted into electric signal by flat panel detector, is finally shown in imaging and control system by analog-to-digital conversion
Detection image.
Each system function:
Radiographic source controller: setting radiographic source transmitting illumination parameter, triggering radiographic source；
Detecting and controlling system: tested leaf position is adjusted；
Detector controller: triggering flat panel detector；
Imaging and control system: each system trigger and display image are controlled.
It please refers to shown in Fig. 4, constantly increases the transmitting illumination parameter of digital radial detection system (when tube voltage, tube current, exposure
Between) obtain different light exposures, until flat panel detector collimating eyelet place at image by it is completely black be changed into it is highlighted complete white.It obtains
Digital radial detection system corresponds to the imaging gray scale of different light exposures in orifice region, bent with the response that this draws flat panel detector
Line, and then determine the linear response regions of digital radial detection system.In conjunction with imaging gray scale and exposure data, formula (1) is determined
In two parameters of α, b, obtain digital radial detection system linear response relationship it is as follows:
G=α H+b (1)
Wherein:
G-imaging gray value
H-light exposure
α-linear response regions slope
B-linear the offset of imaging gray scale.
For the digital radial transillumination process of any workpiece, it is necessary to adjust exposure parameter, make at a transillumination image gray scale
In linear region range, otherwise quantitative analysis can not be carried out to image.
S2, two-dimensional detection image is obtained to blade progress transillumination using digital radial detection system；
It please refers to shown in Fig. 5, obtains defect two-dimensional silhouette, simulated defect regional background includes following five steps:
S21, it transillumination is carried out to blade using digital radial detection system obtains gray scale and is in system linear regional scope
Two-dimensional detection image；
S22, crop leaf measuring image zooming-out defect boundary, the preliminary two-dimensional silhouette for obtaining defect are based on；
S23, morphological dilations are carried out to the defect two-dimensional silhouette that step S22 is tentatively obtained, expands defect area to ensure
All defect profile is entirely included in the region after morphological dilations；
S24, bicubic interpolation is carried out to expansion area, calculates the simulation background of defect area；
S25, simulation background image and original image are made the difference, and the two dimension that binary conversion treatment obtains defect is done to error image
Precise boundary.
S3, by test voussoir transillumination, obtain under specific transmitting illumination parameter (tube voltage, tube current, time for exposure)
The relation curve of image grayscale and material thickness；
It please refers to shown in Fig. 6, due to the special structure of blade, subregion arrangement is used to its detection.By tested leaf
Piece is divided into six regions, and the thickness in each region is limited in certain range, and using one group of specific exposure parameter into
Transillumination of row.
It please refers to shown in Fig. 7, wedge is used in the same material test identical with subregion thickness change range of processing thickness change range
Block, each voussoir uses exposure parameter identical with corresponding region, using subregion arrangement, by the thickness in each region
It is limited in certain range, and a transillumination is carried out using one group of specific exposure parameter, the transmitting illumination parameter includes pipe
Voltage, tube current and time for exposure.
To a certain subregion, processes thickness change range same material identical with the subregion thickness change range and test wedge
Block, each voussoir carry out a transillumination using exposure parameter identical with corresponding region.During a transillumination, with transillumination
Effective light exposure that the increase of thickness reaches detector reduces (the two is in one-to-one relationship).Due to light exposure H and imaging ash
Spending G has linear relationship described in formula (1), and the functional relation between imaging gray value G and scanning thickness T can be determined with this:
G=f (T) (2)
It please refers to shown in Fig. 8, each voussoir carries out a transillumination using exposure parameter identical with corresponding region, and record connects
Gray value of image under continuous thickness change, determines the relation curve of image grayscale and material thickness.
S4, by the simulation background gray scale of defect and original image defect gradation conversion at thickness, two thickness subtract each other acquisition defect
Thickness.
Please refer to shown in Fig. 9, by the relation curve of image grayscale and material thickness, can respectively by simulation background image and
Actually detected image obtains theoretic throat and actual (real) thickness of the blade on each pixel, and two values, which are subtracted each other, can be obtained blade
Defect area and each of which pixel thickness.For single pixel point, G0For bicubic interpolation background gray scale, G1For reality
Pixel grey scale, then defect thickness can be obtained by formula:
T=T0-T1 (3)
Wherein,
T-defect thickness
T0- pixel region interpolation theory thickness
T1- pixel region actual (real) thickness.
S5, it adds up to thickness information at each defect pixel, the three-dimensional parameter of defect can be obtained.
It please refers to shown in Figure 10, is based on finite element theory, seeks defect two-dimensional silhouette respectively in conjunction with corresponding thickness information
The volume of each pixel region in region can acquire the volume of entire defect area adding up to all pixels volume.
The defect volume in single pixel region can be calculated by formula (4):
V=a2×(T0-T1) (4)
Wherein:
V-single pixel Domain Volume
A-pixel side length
T0- single pixel Region Theory thickness
T1- single pixel region actual (real) thickness.
Defect area total volume is calculated by formula (5) again:
Wherein:
Vall- defect area total volume
N-defect area sum of all pixels
Ti0- defect area ith pixel Region Theory thickness
Ti1- defect area ith pixel region actual (real) thickness.
The present invention is based on the large high-temperature blade interior defect three-dimensional parameter extracting methods of digital radial, based on finite element
The two-dimensional detection image of defect is carried out a finite element according to pixel arrangement first and divided by thought；Then to each pixel at
Thickness according to gray value carry out discrete quantized, determine the corresponding relationship of gray scale and thickness；Finally to all pixels finite element into
The three-dimensional parameter of the i.e. extractable defect of row accumulation, on the one hand, can effectively make up traditional radiographic detection method in defect three-dimensional parameter
Deficiency in extraction；On the other hand, it compared to industrial CT system, can realize with higher efficiency with lower cost to combustion gas wheel
The extraction of machine blade interior defect three-dimensional parameter.
Claims (7)
1. the gas turbine blades internal flaw three-dimensional parameter extracting method based on digital radial, which is characterized in that will lack first
Sunken two-dimensional detection image carries out a finite element according to pixel arrangement and divides；Then to the thickness at each pixel according to gray scale
Value carries out discrete quantized, determines the corresponding relationship of gray scale G Yu thickness T；Finally all pixels finite element is accumulated, extracts and lacks
Fall into the three-dimensional parameter in region, comprising the following steps:
S1, the linear response range for determining digital radial detection system, the digital radial detection system include radiographic source, place
Support platform, flat panel detector and the imaging and control system of tested blade, the radiographic source connect by radiographic source controller
It is connected to the imaging and control system, control system is connect the support platform with the imaging and control system after testing,
The flat panel detector is connect by detector controller with the imaging and control system；
S2, two-dimensional detection image is obtained to blade progress transillumination using digital radial detection system, and obtains the two dimension wheel of defect
Exterior feature, obtain the two-dimensional silhouette of the defect specifically includes the following steps:
S21, the two dimension that gray scale is in system linear regional scope is obtained to blade progress transillumination using digital radial detection system
Detection image；
S22, crop leaf measuring image zooming-out defect boundary, the preliminary two-dimensional silhouette for obtaining defect are based on；
S23, morphological dilations are carried out to the defect two-dimensional silhouette that step S22 is tentatively obtained, expands defect area to ensure to own
Defect profile is entirely included in the region after morphological dilations；
S24, bicubic interpolation is carried out to expansion area, calculates the simulation background of defect area；
S25, simulation background image and original image are made the difference, and binary conversion treatment is done to error image and obtains the two dimension of defect accurately
Profile；
S3, by test voussoir transillumination, obtain under specific transmitting illumination parameter image grayscale and material thickness relation curve；
S4, by the simulation background gray scale of defect and original image defect gradation conversion at thickness, two thickness subtract each other obtain defect thickness；
S5, it adds up to thickness information at each defect pixel, the three-dimensional parameter of defect can be obtained.
2. a kind of gas turbine blades internal flaw three-dimensional parameter extraction side based on digital radial according to claim 1
Method, it is characterised in that: in step S1, center is set on the flat panel detector and opens foraminate stereotype, the aperture runs through
The stereotype, the diameter of the aperture are 1mm or more, are less than 10mm, increase the transmitting illumination parameter of the digital radial detection system
Different light exposures are obtained, the flat panel detector is changed into highlighted complete white, acquisition institute by completely black at image in collimating eyelet place
The imaging gray scale that digital radial detection system corresponds to different light exposures in orifice region is stated, the response of the flat panel detector is drawn
Curve determines the linear response regions of digital radial detection system.
3. a kind of gas turbine blades internal flaw three-dimensional parameter extraction side based on digital radial according to claim 2
Method, it is characterised in that: the linear response relationship of the digital radial detection system are as follows:
G=α H+b
Wherein: G-imaging gray value, H-light exposure, α-linear response regions slope, b-linear offset of imaging gray scale.
4. a kind of gas turbine blades internal flaw three-dimensional parameter extraction side based on digital radial according to claim 1
Method, it is characterised in that: in step S3, wedge is used in the same material test identical with subregion thickness change range of processing thickness change range
Block, each voussoir uses exposure parameter identical with corresponding region, using subregion arrangement, by the thickness in each region
It is limited in certain range, and a transillumination is carried out using one group of specific exposure parameter, the transmitting illumination parameter includes pipe
Voltage, tube current and time for exposure.
5. a kind of gas turbine blades internal flaw three-dimensional parameter extraction side based on digital radial according to claim 4
Method a, it is characterised in that: during transillumination, as the increase of scanning thickness reaches the effective of the flat panel detector
Light exposure reduces, and determines the letter being imaged between gray value G and scanning thickness T according to light exposure H and the linear relationship that gray scale G is imaged
Number relationship is as follows:
G=f (T).
6. a kind of gas turbine blades internal flaw three-dimensional parameter extraction side based on digital radial according to claim 1
Method, it is characterised in that: in step S5, the volume of each pixel region in defect two-dimensional silhouette region is sought such as according to thickness information
Under:
V=a2×(T0-T1)
Wherein: V-single pixel Domain Volume, a-pixel side length, T0- single pixel Region Theory thickness, T1- single pixel
Region actual (real) thickness.
7. a kind of gas turbine blades internal flaw three-dimensional parameter extraction side based on digital radial according to claim 6
Method, it is characterised in that: the three-dimensional parameter of the defect area calculates as follows:
Wherein: Vall- defect area total volume, n-defect area sum of all pixels, Ti0- defect area ith pixel region reason
By thickness, Ti1- defect area ith pixel region actual (real) thickness.
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| CN108072674B (en) * | 2018-02-07 | 2019-07-23 | 西安交通大学 | A kind of gas turbine blades defect three dimension location method based on digital radial |
| CN108229080B (en) * | 2018-03-26 | 2020-06-19 | 西安交通大学 | Optimization method for model unknown gas turbine blade digital ray subarea transillumination direction |
| CN109636800B (en) * | 2019-01-28 | 2022-10-14 | 中国科学院上海硅酸盐研究所 | Method for measuring size of internal defect of object |
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| CN104655658A (en) * | 2015-02-10 | 2015-05-27 | 西安交通大学 | Large-sized high-temperature blade internal defect three-dimensional nondestructive detection method |
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| CN106370678A (en) * | 2016-08-23 | 2017-02-01 | 中国工程物理研究院激光聚变研究中心 | X-ray equivalence absorption method for measuring concentration of element doped in material |
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| CN101556147A (en) * | 2009-05-19 | 2009-10-14 | 西北工业大学 | Method for measuring defect thickness in carbon/silicon carbide composite material |
| CN104655658A (en) * | 2015-02-10 | 2015-05-27 | 西安交通大学 | Large-sized high-temperature blade internal defect three-dimensional nondestructive detection method |
| CN104730091A (en) * | 2015-02-10 | 2015-06-24 | 西安交通大学 | Gas turbine blade defects extraction and analysis method based on region segmenting detection |
| CN106353828A (en) * | 2015-07-22 | 2017-01-25 | 清华大学 | Method and device for estimating weight of inspected object in security inspection system |
| CN105158280A (en) * | 2015-08-03 | 2015-12-16 | 赵建江 | Method for accurate detection of material defect and thickness by using digital radiography transillumination technology |
| CN205655808U (en) * | 2015-12-20 | 2016-10-19 | 赵建江 | Device of material thickness and defect height is measured with gasket and digital ray |
| CN106093080A (en) * | 2016-01-14 | 2016-11-09 | 南昌航空大学 | A kind of metal alloy compositions scattering ratio measuring method based on digital radial imaging technology explorer response curve |
| CN106370678A (en) * | 2016-08-23 | 2017-02-01 | 中国工程物理研究院激光聚变研究中心 | X-ray equivalence absorption method for measuring concentration of element doped in material |
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