CN114034405A - Non-contact temperature measurement method and system - Google Patents
Non-contact temperature measurement method and system Download PDFInfo
- Publication number
- CN114034405A CN114034405A CN202111311954.0A CN202111311954A CN114034405A CN 114034405 A CN114034405 A CN 114034405A CN 202111311954 A CN202111311954 A CN 202111311954A CN 114034405 A CN114034405 A CN 114034405A
- Authority
- CN
- China
- Prior art keywords
- images
- temperature measurement
- temperature
- background
- light intensity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000009529 body temperature measurement Methods 0.000 title claims abstract description 138
- 238000000034 method Methods 0.000 title claims abstract description 76
- 238000012937 correction Methods 0.000 claims abstract description 29
- 238000012545 processing Methods 0.000 claims abstract description 29
- 239000011248 coating agent Substances 0.000 claims abstract description 24
- 238000000576 coating method Methods 0.000 claims abstract description 24
- 230000005855 radiation Effects 0.000 claims abstract description 22
- 238000004422 calculation algorithm Methods 0.000 claims description 32
- 238000003705 background correction Methods 0.000 claims description 12
- 238000001914 filtration Methods 0.000 claims description 10
- 238000004861 thermometry Methods 0.000 claims description 9
- 238000000295 emission spectrum Methods 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 5
- 230000007613 environmental effect Effects 0.000 abstract description 3
- 238000004364 calculation method Methods 0.000 description 5
- 230000009467 reduction Effects 0.000 description 5
- 238000006243 chemical reaction Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 239000011159 matrix material Substances 0.000 description 4
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000013507 mapping Methods 0.000 description 3
- 239000012720 thermal barrier coating Substances 0.000 description 3
- 235000002566 Capsicum Nutrition 0.000 description 2
- 239000006002 Pepper Substances 0.000 description 2
- 241000722363 Piper Species 0.000 description 2
- 235000016761 Piper aduncum Nutrition 0.000 description 2
- 235000017804 Piper guineense Nutrition 0.000 description 2
- 235000008184 Piper nigrum Nutrition 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 230000001419 dependent effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000005286 illumination Methods 0.000 description 2
- 230000008676 import Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 239000003973 paint Substances 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 150000003839 salts Chemical class 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 239000000919 ceramic Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000003708 edge detection Methods 0.000 description 1
- 230000005281 excited state Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000011056 performance test Methods 0.000 description 1
- 229910052698 phosphorus Inorganic materials 0.000 description 1
- 239000011574 phosphorus Substances 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 229910052761 rare earth metal Inorganic materials 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 239000000758 substrate Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K11/00—Measuring temperature based upon physical or chemical changes not covered by groups G01K3/00, G01K5/00, G01K7/00 or G01K9/00
- G01K11/006—Measuring temperature based upon physical or chemical changes not covered by groups G01K3/00, G01K5/00, G01K7/00 or G01K9/00 using measurement of the effect of a material on microwaves or longer electromagnetic waves, e.g. measuring temperature via microwaves emitted by the object
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration by the use of local operators
-
- G06T5/70—
-
- G06T5/77—
-
- G06T5/80—
-
- G06T5/90—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Electromagnetism (AREA)
- Radiation Pyrometers (AREA)
Abstract
The invention relates to a non-contact temperature measurement method and a non-contact temperature measurement system, wherein two images at two wave crests of a set part are obtained respectively; and carrying out background radiation correction, edge recognition and feature point recognition on the two images, finally carrying out ratio processing on temperature measuring areas in the two images to obtain a light intensity ratio result, and finally corresponding the result with a calibration result calibrated in advance to obtain the temperature distribution of the temperature measuring surface, thereby obtaining the real-time temperature distribution of the surface to be measured by shooting and signal processing phosphorescent coating samples under different environmental temperatures, and greatly improving the precision of phosphorescence temperature measurement by a ratio light intensity method and improving the upper limit of temperature measurement by using the measures of background radiation correction, temperature measuring area recognition, high-precision alignment processing of the two images, temperature-position accurate matching and the like. According to the invention, accurate temperature measurement can be realized without mastering the surface emissivity characteristics, and the problem of inaccurate temperature measurement of the interior of the aero-engine at present is effectively solved.
Description
Technical Field
The invention relates to the field of non-contact solid surface temperature measurement, in particular to a non-contact temperature measurement method and system.
Background
The engine is used as a core system of the airplane and has very important influence on various performances of the airplane. The development of the turbine mainly has the characteristics of continuously increasing the pressure increase ratio, continuously increasing the temperature in front of the turbine, continuously increasing the bypass ratio and the like. In order to meet the comprehensive requirements of the aero-engine on reliability and durability, a more comprehensive structural strength and working performance test is required in the process of developing the aero-engine. The measurement of temperature is particularly important in the need to rely on reliable testing techniques to provide useful information data, particularly techniques for measuring key parameters of hot end components of the engine.
For the interior of an aircraft engine, particularly a rotating blade, due to the severe operating environments of high temperature, fast temperature change, fast rotating speed and the like, a temperature measurement mode is required to be capable of not damaging the internal structure of the rotating blade and recording the temperature change of a two-dimensional surface in real time. However, most non-contact temperature measurement methods need to accurately know the emissivity of the surface when the temperature measurement is carried out with high precision, and the emissivity depends on the wavelength, the detection angle and the surface characteristics of the device to be measured, which may change during the operation process, so that the temperature measurement is inaccurate.
Therefore, a technical scheme for accurately measuring the internal temperature of the aircraft engine in a non-contact manner is needed in the field.
Disclosure of Invention
The invention aims to provide a non-contact temperature measurement method and a non-contact temperature measurement system, which can realize accurate temperature measurement by utilizing a phosphorescence temperature measurement method without mastering surface emissivity characteristics and effectively solve the problem of inaccurate temperature measurement of the interior of an aircraft engine at present.
In order to achieve the purpose, the invention provides the following scheme:
a method of non-contact thermometry, the method comprising:
obtaining a calibration result of the corresponding relation between the light intensity ratio at the two wave crests and the temperature;
respectively acquiring two images at two wave crests of a set part; the set part is provided with a phosphorescent coating, the image is a phosphorescent image excited after the set part is irradiated by laser, and the peak is the peak of an emission spectrum of the phosphorescent coating;
removing the background except the phosphorescence from the two images by using a background radiation correction method to obtain two background-removed images;
respectively identifying temperature measuring areas in the two background-removed images by using an edge identification algorithm to obtain two temperature measuring images;
aligning the two temperature measurement images by using a characteristic point identification algorithm;
carrying out ratio processing on the gray values of the pixel points of the temperature measurement areas in the two temperature measurement images to obtain a light intensity ratio result;
and corresponding the light intensity ratio result with the corresponding relation calibration result to obtain the temperature distribution of the temperature measurement surface.
In some embodiments, before the method using background radiation correction respectively removes the background except for the phosphor in the two images to obtain two background-removed images, the method further includes:
the calibration results under different powers are corresponding to the feedback readings of the power meter; the power is the power of the irradiation laser.
In some embodiments, the method for correcting with background radiation respectively removes the background except for the phosphor in the two images to obtain the two background-removed images, specifically including:
acquiring a background picture; the background picture is taken before laser irradiation;
and subtracting the two images at the two wave crests from the background picture respectively to obtain two background-removed images.
In some embodiments, after the aligning the two thermometric images by using the feature point identification algorithm, the method further includes:
performing feature point detection and matching on the two aligned temperature measurement images, and finishing primary alignment if the coordinate difference of all matched points is smaller than a single pixel;
and merging 9 multiplied by 9 pixels of the two temperature measurement images after the preliminary alignment is finished, calculating the matching error of the temperature measurement area, and finishing the alignment if the matching errors of all the pixels in the temperature measurement area are smaller than the allowable matching error.
In some embodiments, after the aligning the two thermometric images by using the feature point identification algorithm, the method further includes:
acquiring a bad point index of a camera;
marking the dead pixel by utilizing cut-off filtering;
and removing noise by using average filtering, and compensating the data at the dead point.
In some embodiments, after the ratio processing is performed on the gray values of the pixel points in the temperature measurement areas in the two temperature measurement images to obtain the light intensity ratio result, the method further includes:
the method of flat field correction is used to compensate the nonuniform light splitting phenomenon of the stereoscope.
In another aspect of the present invention, there is also provided a non-contact thermometry system, the system comprising:
the calibration result module is used for importing calibrated calibration results of the corresponding relation between the light intensity ratio at the two wave crests and the temperature;
a temperature distribution module to:
respectively acquiring two images at two wave crests of a set part; the set part is provided with a phosphorescent coating, the image is a phosphorescent image excited after the set part is irradiated by laser, and the peak is the peak of an emission spectrum of the phosphorescent coating;
removing the background except the phosphorescence from the two images by using a background radiation correction method to obtain two background-removed images;
respectively identifying temperature measuring areas in the two background-removed images by using an edge identification algorithm to obtain two temperature measuring images;
aligning the two temperature measurement images by using a characteristic point identification algorithm;
carrying out ratio processing on the gray values of the pixel points of the temperature measurement areas in the two temperature measurement images to obtain a light intensity ratio result;
and corresponding the light intensity ratio result with the corresponding relation calibration result to obtain the temperature distribution of the temperature measurement surface.
In some embodiments, further comprising:
and the personal information module is used for verifying the identity of the user and registering and modifying the account password for the user.
In some embodiments, further comprising:
and the device control module is used for controlling the switch of the camera and the laser device and setting the parameters of the camera.
In some embodiments, further comprising:
the temperature determining module is used for integrating the display position and the temperature;
and the distribution result module is used for displaying each process in the temperature distribution module step by step.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the invention, accurate temperature measurement can be realized by using a phosphorescence temperature measurement method without mastering the surface emissivity characteristics, so that the problem of inaccurate temperature measurement of the interior of the aero-engine at present is effectively solved, and two images at two wave crests of a set part are respectively obtained; and carrying out background radiation correction, edge recognition and feature point recognition on the two images, finally carrying out ratio processing on temperature measuring areas in the two images to obtain a light intensity ratio result, and finally corresponding the result with a calibration result calibrated in advance to obtain the temperature distribution of the temperature measuring surface, thereby obtaining the real-time temperature distribution of the surface to be measured by shooting and signal processing phosphorescent coating samples under different environmental temperatures, and greatly improving the precision of phosphorescence temperature measurement by a ratio light intensity method and improving the upper limit of temperature measurement by using the measures of background radiation correction, temperature measuring area recognition, high-precision alignment processing of the two images, temperature-position accurate matching and the like.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic diagram of a shooting process according to an embodiment of the present invention.
Fig. 2 is a flowchart of a non-contact temperature measuring method according to an embodiment of the present invention.
Fig. 3 is a block diagram of a non-contact temperature measurement system according to a second embodiment of the present invention.
Fig. 4 is a simplified system diagram of non-contact temperature measurement software according to a third embodiment of the present invention.
Fig. 5 is a detailed block diagram of non-contact temperature measurement software provided in the third embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a non-contact temperature measurement method and a non-contact temperature measurement system, which can realize accurate temperature measurement by utilizing a phosphorescence temperature measurement method without mastering surface emissivity characteristics and effectively solve the problem of inaccurate temperature measurement of the interior of an aircraft engine at present.
Phosphorescence temperature measurement is based on the temperature characteristics of light generated in the process that a phosphorescent paint returns to an excited state after being excited to undergo energy level transition. Phosphorescent paint is a luminescent material sintered together from a ceramic substrate and up to 10% of rare earth elements, which luminesces upon exposure to external stimuli such as ultraviolet radiation, and certain properties of the light are temperature dependent. The temperature sensitivity is high, the response speed is fast, the high temperature resistance is realized, the interference of high temperature heat radiation such as flame and the like is avoided, the non-contact measurement is realized, the method is very suitable for the use environment of the thermal barrier coating of the aeroengine, and the method has very wide application prospect.
In actual temperature measurement, firstly, exciting light is emitted by a laser, the exciting light is expanded into a circle with the diameter of 2cm, the exciting light reaches the surface of a phosphorescent coating of the turbine blade after passing through a transmission light path and excites a phosphorescent signal with the area of the circle with the diameter of 2cm, the phosphorescent signal enters a camera lens after passing through the light path, and then the phosphorescent signal is received by a camera and is converted and transmitted through a signal, and finally, an image is formed at a computer terminal.
The specific light intensity method provided by the invention is a phosphorescence temperature measurement method, and has good two-dimensional temperature measurement accuracy and higher data processing speed in a high-temperature environment. The basic principle of the specific intensity method is that the phosphorescent coating can generate phosphorescence when being excited, the light intensity of the phosphorescence has a certain dependent relation with the temperature, in which there is a one-to-one functional relationship between the intensity ratio at two peaks and the temperature, as shown in figure 1, the method comprises the steps of shooting two images of two peaks corresponding to the same area (the two peaks can be obtained through spectral analysis, the two peaks are determined and cannot be changed, and therefore, the images under the two peaks can be obtained by adopting corresponding filter plates aiming at the two determined peaks. The part of specific shooting is the phosphorescence coating of the turbine blade of laser irradiation, and the light that sends out the phosphorescence coating passes through the dichroic mirror and divides into two bundles of light, and the dichroic mirror can see through the light of the wavelength that one of them crest corresponds, reflects the light of another crest corresponding wavelength, and a beam of light gets into a camera lens after the filter that the bandwidth is 10nm with this crest as the center, and another beam of light gets into another camera lens through the filter that the bandwidth is 10nm with another crest as the center after the speculum reflection.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The first embodiment is as follows:
as shown in fig. 2, the present embodiment provides a non-contact temperature measurement method, including:
and S1, acquiring a calibration result of the corresponding relation between the light intensity ratio at the two wave crests and the temperature, and taking the calibration result as a standard of temperature conversion.
S2, respectively acquiring two images at two wave crests of the set part; the set part is provided with a phosphorescent coating, the image is a phosphorescent image excited after the set part is irradiated by laser, and the peak is the peak of an emission spectrum of the phosphorescent coating. The setting position can be selected according to the needs of the user, and the setting position in the embodiment is a turbine blade in the aircraft engine.
The emission spectrum of the phosphorescent material has wave crests at certain wavelengths, the wave crests are wavelengths corresponding to thermal coupling energy levels, the relative population of particles on the two thermal coupling energy levels obeys Boltzmann distribution, and therefore the light intensity ratio at the two wave crests has a one-to-one correspondence relationship with the temperature. The determination of the wave peak needs to obtain the spectrum under different temperatures, the wavelength which is convex and meets the Boltzmann law is searched in the spectrum to be used as the wave peak, and the image at the wave peak can be directly obtained by directly utilizing a specific filter in practical application. The laser irradiation direction is vertical to the surface irradiation of the phosphorescent coating.
As some optional embodiments, in order to improve the accuracy of temperature measurement after two images are acquired, a power meter is further used to feed back calibration results corresponding to readings at different powers, so as to eliminate the influence of power fluctuation on temperature measurement; the power is the power of the irradiation laser.
S3, removing the background except the phosphorescence from the two images by using a background radiation correction method to obtain two background-removed images;
specifically, the method comprises the following steps: and acquiring a background picture shot before laser irradiation, and subtracting the two images at the two wave crests from the background picture to obtain two background-removed images.
S4, identifying temperature measurement areas in the two background-removed images respectively by using an edge identification algorithm to obtain two temperature measurement images, and setting the gray value of the non-temperature measurement area to be 0 to avoid the influence on temperature measurement caused by the fact that the non-temperature measurement area obtains specific light intensity data when the two images are subjected to specific light intensity.
The specific method for identification is as follows: the proportion of the phosphorescent coating area in the imaging picture can be determined by the known focal length of the camera, the object distance and the laser spot diameter, the number of pixel points of the phosphorescent coating area can be obtained by multiplying the proportion by the total number of the image pixel points, because the gray value of the phosphorescent coating area in the image is larger, and the gray value of the non-phosphorescent area is smaller, the image is subjected to binarization processing by taking the gray value as a threshold value, and performing circular edge detection on the obtained binary image, wherein the circle with the largest diameter can be regarded as the boundary of the phosphorescent coating area, calculating the distance between a pixel point in the image and the obtained boundary, wherein the distance is larger than zero and is a pixel point outside the boundary, the distance is smaller than zero and is a pixel point inside the boundary, setting the gray value of the point inside the boundary as the original gray value of the obtained image, and setting the gray value of the point outside the boundary as 0, so that the temperature measuring area identification function can be realized.
And S5, aligning the two temperature measurement images by using a characteristic point recognition algorithm.
The feature point recognition algorithm uses an SURF algorithm and improves the SURF algorithm, because the two images of the embodiment mainly have optical path difference errors and tangential distortion errors, the total error of the coincidence degree of the two images is about 2%, aiming at the characteristic, matching conditions can be constrained, firstly, the opencv self-contained findContours algorithm is used for recognizing the positions of the edges and the circle centers of the images, the constraint condition 1 is dimensionless length constraint, namely the ratio of the distance from a feature point to the circle center to the distance from the circle center to the edge of the image, and the dimensionless length difference of the two images is set to be matched within 5%; the constraint condition 2 is angle constraint, included angles between two image feature points and the horizontal direction are respectively obtained, the angle difference between the two images is set to be within 5% so that the two images can be matched, correct matching points can be obtained through the constraint condition, and then image distortion correction is carried out through an RANSAC algorithm so that image alignment can be realized. Wherein a feature point is a point with a characteristic property that can represent an image or object in an identical or at least very similar invariant form in other similar images containing the same scene or object.
After the two temperature measurement images are aligned by using the feature point identification algorithm, the two temperature measurement images need to be checked to see whether the two temperature measurement images are actually aligned.
And (3) performing feature point detection and matching on the two aligned temperature measurement images by adopting the improved SURF algorithm, and finishing primary alignment if the coordinate difference of all matched points is less than a single pixel (the feature point positions of the corrected images are identified and matched, and the coordinate difference of the matched points is less than 1).
And merging 9 multiplied by 9 pixels of the two temperature measurement images after the preliminary alignment is finished, calculating the matching error of the temperature measurement area, and finishing the alignment if the matching errors of all the pixels in the temperature measurement area are smaller than the allowable matching error.
Merging the 9 multiplied by 9 pixels of the image, and calculating the matching error delta x of the temperature measurement area, wherein the calculation formula is as follows:
wherein, Δ xmThe difference between the gray values of the pixels of the two temperature measurement images, namely the alignment error,
xitaking each pixel point of a 9 x 9 pixel merging area for the first temperature measurement image; x is the number ofmiThe top points or the middle points of the edges with the side lengths of 5 pixel points of the outermost 4 of the regions with the side lengths of 5 pixels contained in the 9-by-9 pixel combination region taken for the first temperature measurement image are 8 in total; y isiTaking each pixel point of the 9 x 9 pixel merging area for the second temperature measurement image; y ismiAnd taking 8 vertexes or midpoints of the edges with the side lengths of 5 pixels of the outermost 4 of the regions with the side lengths of 5 pixels contained in the 9-by-9 pixel merging region for the second temperature measurement image.
And if the matching errors of all pixels in the temperature measuring area are smaller than the allowable matching errors, namely the proportion of the pixel points meeting the temperature measuring precision requirement to the pixel points of the image in the temperature measuring area is 1, the two images are successfully aligned with high precision.
As an alternative embodiment, after the two thermometric images are aligned, the method further comprises the steps of compensating for camera dead pixel and removing noise.
The method specifically comprises the following steps:
acquiring a camera dead pixel index, and marking the dead pixels by utilizing cut-off filtering; and removing Gaussian noise and salt and pepper noise in the temperature measurement image by using mean filtering, compensating the data at the dead pixel, and selecting 9 multiplied by 9 mean filtering for processing.
S6, carrying out ratio processing on the gray values of the pixel points of the temperature measurement areas in the two temperature measurement images to obtain the light intensity ratio of the two temperature measurement images, namely the light intensity ratio result.
Then, the method of flat field correction is used to compensate the nonuniform light splitting phenomenon of the stereoscope.
And S7, corresponding the light intensity ratio result with the corresponding relation calibration result to obtain the temperature distribution of the temperature measurement surface.
The non-contact temperature measurement method provided by the embodiment of the invention utilizes a phosphorescence temperature measurement method, can accurately obtain the temperature distribution of the surface to be measured under the condition of not contacting the surface of the detected object, and can be applied to different working conditions of an aeroengine to obtain the two-dimensional temperature distribution of the part of the surface of the aeroengine coated with the thermal barrier coating under different working conditions in real time. The method can measure the phosphorescence intensity ratio corresponding to two wave crests radiated by a sample to be measured so as to obtain the temperature distribution of the surface of the sample to be measured, and can be applied to different working conditions of an aeroengine to obtain the temperature distribution rule of the surface of the aeroengine so as to better predict the service life of the thermal barrier coating.
The temperature measurement technology provided by the embodiment has the advantages of wide temperature measurement range, high temperature measurement precision, small influence of heat radiation and gas absorption, capability of carrying out two-dimensional temperature measurement and the like, can acquire the temperature distribution of a high-speed rotating part in real time, and is superior to other temperature measurement methods in two-dimensional temperature measurement under the harsh environment conditions. And the precision of phosphorescence temperature measurement by a specific light intensity method is greatly improved and the upper limit of temperature measurement is improved by the measures of background radiation correction, temperature measurement area identification, high-precision alignment processing of two images, image noise reduction, accurate temperature-position matching and the like.
Example two:
as shown in fig. 3, the present embodiment provides a non-contact temperature measurement system, which includes:
the calibration result module M1 is used for introducing calibration results of the corresponding relation between the light intensity ratio and the temperature at the two calibrated wave crests;
a temperature distribution module M2 for:
respectively acquiring two images at two wave crests of a set part; the set part is provided with a phosphorescent coating, the image is a phosphorescent image excited after the set part is irradiated by laser, and the peak is the peak of an emission spectrum of the phosphorescent coating;
removing the background except the phosphorescence from the two images by using a background radiation correction method to obtain two background-removed images;
respectively identifying temperature measuring areas in the two background-removed images by using an edge identification algorithm to obtain two temperature measuring images;
aligning the two temperature measurement images by using a characteristic point identification algorithm;
carrying out ratio processing on the gray values of the pixel points of the temperature measurement areas in the two temperature measurement images to obtain a light intensity ratio result;
and corresponding the light intensity ratio result with the corresponding relation calibration result to obtain the temperature distribution of the temperature measurement surface.
As some optional embodiments, the method may further include:
and the personal information module is used for verifying the identity of the user and registering and modifying the account password for the user.
And the device control module is used for controlling the switch of the camera and the laser device and setting the parameters of the camera.
The temperature determining module is used for integrating the display position and the temperature;
and the distribution result module is used for displaying each process in the temperature distribution module step by step.
Example three:
as shown in fig. 4, an embodiment of the present invention provides a non-contact temperature measurement system, where the system is temperature measurement software, and the system includes: the device comprises a personal information module 2, an equipment control module 3, a calibration result module 4, a temperature distribution module 5, a position determination module 6 and a step result module 7.
The personal information module 2, the equipment control module 3 and the calibration result module 4 form a preprocessing system, and the temperature distribution module 5, the position determination module 6 and the step result module 7 form a data processing system.
The personal information module 2 can verify the identity of the user, the user needs to input an account and a password to use the program, and the user can register and modify the account and the password through the module.
The device control module 3 can control the opening and closing of devices such as a camera shutter and a laser and set parameters of the camera.
The calibration result module 4 can import the calibration result of the corresponding relationship between the light intensity ratio at the two wave crests and the temperature calibrated in advance, and the calibration result is used as a reference for the temperature field calculation part in the temperature distribution module 5.
The temperature distribution module 5 can perform image acquisition, background radiation correction, temperature measurement area identification, high-precision alignment processing of two images, image noise reduction, specific light intensity, flat field correction and temperature field calculation on the images corresponding to the two wavelengths input by the camera, so that the effects of temperature conversion and temperature measurement precision improvement on a temperature measurement area are achieved, and the part is a program core.
The position determination module 6 is able to locate the respective temperature as a result of the temperature distribution module 5.
The step result module 7 can display partial results of image acquisition, background correction, temperature measurement area identification, high-precision alignment processing of two images, image noise reduction, specific light intensity, flat field correction and temperature field calculation in the temperature distribution module step by step
Referring to fig. 5, the software includes an image data processing module 8, a temperature equalization image 9, an image acquisition 10, a background image 11, a corrected image 12, a power correction 13, a pixel correction 14, a corrected image 15, a background correction 16, an edge enhancement 17, a region identification 18, a distortion correction 19, an image mapping 20, an image alignment 21, an alignment precision 22, a cut-off filter 23, a mean filter 24, a specific light intensity 25, an import database 26, a flat field correction 27, a calibration result 28, a temperature conversion 29, a temperature field 30, a temperature field acquisition 31, a position acquisition 32, an experimental segment 33, a rotating turbine 34, a temperature-position matching 35, and a temperature-position matching 36.
The power correction 13, the pixel correction 14 and the background correction 16 form an image preprocessing system, the edge enhancement 17 and the area identification 18 form a temperature measurement area identification system, the distortion correction 19, the image mapping 20, the image alignment 21 and the alignment precision 22 form a two-image high-precision alignment processing system, the cut-off filter 23 and the mean filter 24 form an image noise reduction system, and the temperature-position matching 35 and the temperature-position matching 36 form a temperature-position precision matching system.
The power correction 13 can correspond to the calibration results under different powers by feeding back the readings from the power meter, so as to eliminate the influence of power fluctuation on the temperature measurement.
The pixel correction 14 can perform light-wall ratio by using a pixel mean value through calibration experimental data processing, and correct the problems of uneven light intensity response of pixels and pixel dead pixel by using a pixel combination and filtering method during actual temperature measurement.
The background correction 16 can be performed by capturing an image before laser irradiation to obtain background radiation, capturing an image after laser irradiation to obtain a phosphorescence signal and background radiation when the phosphorescence signal is generated, and subtracting the first image from the second image to remove background noise.
The edge enhancement 17 can enhance the border portion of the temperature measurement area. Amplifying the part with larger gray value difference at the boundary, and adopting a convolution algorithm: the pixel value of a certain point is equal to the pixel value of the point multiplied by 4, and then the four surrounding pixel values are subtracted, so that the part with large gray value difference is amplified, and the boundary enhancement is realized.
The area identification 18 can identify the temperature measuring area through an edge identification algorithm, and set the gray value of the non-temperature measuring area to 0, so that the influence of the non-phosphorus light area on temperature measurement caused by obtaining specific light intensity data when the specific light intensity of two pictures is carried out is avoided.
The image mapping 20 can identify and match the feature points of the two images, the feature point identification method uses a SURF algorithm and improves the SURF algorithm, because the two images mainly have optical path difference errors and tangential distortion errors in the experiment, the total error of the contact ratio of the two images is about 2%, the matching condition can be restricted aiming at the characteristic, firstly, the edge and circle center positions of the images are identified, the restriction condition 1 is dimensionless length restriction, namely, the distance between the feature point and the circle center is only compared with the distance between the circle center and the edge of the image, and the dimensionless length difference of the two images is set to be within 5% so as to match; the constraint condition 2 is angle constraint, the included angles between the characteristic points of the two images and the horizontal direction are respectively obtained, the angle difference between the two images is set to be within 5 percent so as to be matched, the correct matching points can be obtained through the constraint condition, and the distortion correction 19 can realize image alignment 21 by carrying out image distortion correction through RANSAC algorithm.
The alignment precision 22 can obtain the proportion of the pixel points of the temperature measurement area image which meet the temperature measurement precision requirement after the two images are aligned in high precision, firstly, the two aligned temperature measurement images are subjected to feature point detection and matching by adopting the improved SURF algorithm, and if the coordinate difference of all the matching points is smaller than a single pixel (the feature point positions of the corrected images are identified and matched, and the coordinate difference of the matching points is smaller than 1), the preliminary alignment is completed.
And merging 9 multiplied by 9 pixels of the two temperature measurement images after the preliminary alignment is finished, calculating the matching error of the temperature measurement area, and finishing the alignment if the matching errors of all the pixels in the temperature measurement area are smaller than the allowable matching error.
Merging the 9 multiplied by 9 pixels of the image, and calculating the matching error delta x of the temperature measurement area, wherein the calculation formula is as follows:
wherein, Δ xmThe difference between the gray values of the pixels of the two temperature measurement images, namely the alignment error,
xitaking each pixel point of a 9 x 9 pixel merging area for the first temperature measurement image; x is the number ofmiThe top points or the middle points of the edges with the side lengths of 5 pixel points of the outermost 4 of the regions with the side lengths of 5 pixels contained in the 9-by-9 pixel combination region taken for the first temperature measurement image are 8 in total; y isiTaking each pixel point of the 9 x 9 pixel merging area for the second temperature measurement image; y ismiAnd taking 8 vertexes or midpoints of the edges with the side lengths of 5 pixels of the outermost 4 of the regions with the side lengths of 5 pixels contained in the 9-by-9 pixel merging region for the second temperature measurement image.
And if the matching errors of all pixels in the temperature measuring area are smaller than the allowable matching errors, namely the proportion of the pixel points meeting the temperature measuring precision requirement to the pixel points of the image in the temperature measuring area is 1, the two images are successfully aligned with high precision.
The cut-off filter 23 can find the wrong temperature measuring point in the temperature measuring area by combining the bad point index of the camera through a gray scale statistical method, mark the bad points by cutting off the filter, and then compensate the bad points by processing measures.
The mean filtering 24 can remove gaussian noise and salt and pepper noise in the image and compensate temperature measurement dead point data so as to improve the temperature measurement precision, and 9 × 9 mean filtering is selected for processing.
The ratio light intensity 25 can perform ratio processing on the gray values of the pixel points of the two processed images corresponding to the temperature measurement area to obtain the light intensity ratio of the two images.
The flat field correction 27 can compensate the nonuniform light splitting phenomenon of the stereoscope so as to achieve accurate temperature measurement.
The method adopts a flat field correction method, the gray values of the images presented by the two lenses under uniform illumination are equal, but the dichroic mirror has the phenomenon of nonuniform light splitting, so that deviation exists, the correction method is to shoot the images under uniform illumination, obtain the gray value matrix of the images, use the matrix as a correction coefficient, and actually measure the gray value matrix to divide the matrix into the corrected images to realize compensation.
The temperature conversion 29 can correspond the light intensity ratio of the flat field corrected image to the calibration result 28 processed in advance, and finally obtain the temperature field 30.
The temperature-position matching 35 can determine the position of the temperature measuring region of the laboratory stationary sample by determining the position of the sample and the focal length of the camera, and the temperature-position matching 36 can determine the position of the temperature measuring region in the turbine rotating environment by a characteristic point identification and matching algorithm. Firstly, traversing and shooting the whole to-be-detected area under the same focal length to obtain a panoramic image, setting the distance as the minimum distance of a matching point to obtain an optimal matching point by using a SURF algorithm and a distance constraint method for shot partial images and the panoramic image, obtaining the relative position of two images according to the matching point, matching the two images by using the SURF algorithm again, setting the distance of the matching point to be less than one pixel according to the relative position of the two images in the matching, obtaining correct matching points at the moment, and considering that correct position matching is realized if the number of the correct matching points is approximately equal to the number of all the matching points.
The embodiment provides high-precision intelligent specific light intensity phosphorescence temperature measurement signal processing software suitable for the high-speed rotating part dynamics for the phosphorescence temperature measurement technology, and real-time temperature distribution of the surface to be measured can be obtained by shooting and processing signals of phosphorescence coating samples at different environmental temperatures. And the precision of phosphorescence temperature measurement by a specific light intensity method is greatly improved and the upper limit of temperature measurement is improved by the measures of background radiation correction, temperature measurement area identification, high-precision alignment processing of two images, image noise reduction, accurate temperature-position matching and the like.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (10)
1. A method of non-contact thermometry, the method comprising:
obtaining a calibration result of the corresponding relation between the light intensity ratio at the two wave crests and the temperature;
respectively acquiring two images at two wave crests of a set part; the set part is provided with a phosphorescent coating, the image is a phosphorescent image excited after the set part is irradiated by laser, and the peak is the peak of an emission spectrum of the phosphorescent coating;
removing the background except the phosphorescence from the two images by using a background radiation correction method to obtain two background-removed images;
respectively identifying temperature measuring areas in the two background-removed images by using an edge identification algorithm to obtain two temperature measuring images;
aligning the two temperature measurement images by using a characteristic point identification algorithm;
carrying out ratio processing on the gray values of the pixel points of the temperature measurement areas in the two temperature measurement images to obtain a light intensity ratio result;
and corresponding the light intensity ratio result with the corresponding relation calibration result to obtain the temperature distribution of the temperature measurement surface.
2. The method of claim 1, wherein before the background radiation correction is used to remove the background except for the phosphorescence from the two images to obtain two background-removed images, the method further comprises:
the calibration results under different powers are corresponding to the feedback readings of the power meter; the power is the power of the irradiation laser.
3. The non-contact temperature measurement method according to claim 1, wherein the background radiation correction method is used to remove the background except for the phosphorescence from the two images to obtain two background-removed images, and specifically comprises:
acquiring a background picture; the background picture is taken before laser irradiation;
and subtracting the two images at the two wave crests from the background picture respectively to obtain two background-removed images.
4. The method of claim 1, wherein after aligning the two thermometry images using the feature point recognition algorithm, further comprising:
performing feature point detection and matching on the two aligned temperature measurement images, and finishing primary alignment if the coordinate difference of all matched points is smaller than a single pixel;
and merging 9 multiplied by 9 pixels of the two temperature measurement images after the preliminary alignment is finished, calculating the matching error of the temperature measurement area, and finishing the alignment if the matching errors of all the pixels in the temperature measurement area are smaller than the allowable matching error.
5. The method of claim 1, wherein after aligning the two thermometry images using the feature point recognition algorithm, further comprising:
acquiring a bad point index of a camera;
marking the dead pixel by utilizing cut-off filtering;
and removing noise by using average filtering, and compensating the data at the dead point.
6. The non-contact temperature measurement method according to claim 1, wherein after the ratio processing is performed on the gray values of the pixel points in the temperature measurement areas in the two temperature measurement images to obtain the light intensity ratio result, the method further comprises:
the method of flat field correction is used to compensate the nonuniform light splitting phenomenon of the stereoscope.
7. A non-contact thermometry system, the system comprising:
the calibration result module is used for importing calibrated calibration results of the corresponding relation between the light intensity ratio at the two wave crests and the temperature;
a temperature distribution module to:
respectively acquiring two images at two wave crests of a set part; the set part is provided with a phosphorescent coating, the image is a phosphorescent image excited after the set part is irradiated by laser, and the peak is the peak of an emission spectrum of the phosphorescent coating;
removing the background except the phosphorescence from the two images by using a background radiation correction method to obtain two background-removed images;
respectively identifying temperature measuring areas in the two background-removed images by using an edge identification algorithm to obtain two temperature measuring images;
aligning the two temperature measurement images by using a characteristic point identification algorithm;
carrying out ratio processing on the gray values of the pixel points of the temperature measurement areas in the two temperature measurement images to obtain a light intensity ratio result;
and corresponding the light intensity ratio result with the corresponding relation calibration result to obtain the temperature distribution of the temperature measurement surface.
8. The non-contact thermometry system of claim 7, further comprising:
and the personal information module is used for verifying the identity of the user and registering and modifying the account password for the user.
9. The non-contact thermometry system of claim 7, further comprising:
and the device control module is used for controlling the switch of the camera and the laser device and setting the parameters of the camera.
10. The non-contact thermometry system of claim 7, further comprising:
the temperature determining module is used for integrating the display position and the temperature;
and the distribution result module is used for displaying each process in the temperature distribution module step by step.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111311954.0A CN114034405A (en) | 2021-11-08 | 2021-11-08 | Non-contact temperature measurement method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111311954.0A CN114034405A (en) | 2021-11-08 | 2021-11-08 | Non-contact temperature measurement method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114034405A true CN114034405A (en) | 2022-02-11 |
Family
ID=80143322
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111311954.0A Pending CN114034405A (en) | 2021-11-08 | 2021-11-08 | Non-contact temperature measurement method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114034405A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114964374A (en) * | 2022-05-30 | 2022-08-30 | 中国航空发动机研究院 | Non-contact strain field and temperature field synchronous testing system and testing method thereof |
-
2021
- 2021-11-08 CN CN202111311954.0A patent/CN114034405A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114964374A (en) * | 2022-05-30 | 2022-08-30 | 中国航空发动机研究院 | Non-contact strain field and temperature field synchronous testing system and testing method thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108362469B (en) | Size and surface pressure measurement method and apparatus based on pressure sensitive paint and light-field camera | |
| CN110146259A (en) | A kind of reflective multi-light axis consistency quantitative test of large-caliber off-axis and calibrating installation | |
| CN109559348A (en) | A kind of contactless deformation measurement method of bridge based on tracing characteristic points | |
| CN109813435B (en) | Static light reflection micro thermal imaging method and device and terminal equipment | |
| CN110411346B (en) | Method for quickly positioning surface micro-defects of aspheric fused quartz element | |
| López et al. | LED near-field goniophotometer at PTB | |
| EP0947813A1 (en) | Interpretation of thermal paint | |
| CN109655161B (en) | Target infrared integral radiation intensity testing method and device based on thermal infrared imager | |
| CN107727616A (en) | A kind of auxilary focusing method and device | |
| CN106706132B (en) | Infrared detection device and method for identifying targets in sea surface sun bright band | |
| CN108955555B (en) | High-precision high-temperature deformation measuring method | |
| CN111707382B (en) | Dynamic optical compensation method and device for synchronous measurement of temperature deformation | |
| CN114034405A (en) | Non-contact temperature measurement method and system | |
| CN106500843A (en) | A kind of imaging spectrometer optimum image plane calibration method and device | |
| WO2016020826A1 (en) | Method and relevant device for measuring distance with auto-calibration and temperature compensation | |
| CN110836634A (en) | Four-quadrant detector calibration method capable of adapting to various light beams | |
| CN112200788B (en) | High-temperature deformation measuring device and method | |
| CN108827915A (en) | A kind of sub-pixel location acquisition methods based on photoelectric sensing array measurement refractive index | |
| CN110567920B (en) | Detection system for haze of transparent or semitransparent glass | |
| CN112053341A (en) | Surface temperature measurement method of alloy material based on light reflectivity and artificial intelligence | |
| CN108132197B (en) | Uncertainty analysis and calculation method for impact temperature of transparent material | |
| CN207515908U (en) | A kind of multi-pass self calibration polarization detecting device and system | |
| CN114659455A (en) | Diffraction stripe recognition processing method for measuring diameter of filament | |
| CN114235149A (en) | Laser measurement system and method based on CCD reflection imaging method | |
| KR100983877B1 (en) | System and method for measuring reflectance of an object |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |