CN117405732A - Combined scanning laser thermal imaging detection system, sampling method and device - Google Patents
Combined scanning laser thermal imaging detection system, sampling method and device Download PDFInfo
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Abstract
The invention discloses a combined scanning laser thermal imaging detection system, a sampling method and a device, which belong to the technical field of thermal imaging, wherein the combined scanning laser thermal imaging detection system comprises a thermal infrared imager, an optical platform, a clamp and a laser, wherein a moving platform is arranged on the moving platform, the optical ends of the thermal infrared imager and the laser are arranged on the moving platform, the moving platform is arranged on the optical platform, the moving platform is movable relative to the optical platform, the clamp is arranged on the optical platform, the height of the clamp relative to the optical platform is adjustable, the clamp is used for clamping an aluminum alloy test piece, the surface of the aluminum alloy test piece is not subjected to black paint spraying treatment, laser emitted by the laser is transmitted to the surface of the aluminum alloy test piece, the thermal infrared imager is used for collecting temperature data in a sampling area of the surface of the aluminum alloy test piece, and the sampling area is a front area of a laser heat affected zone in the laser moving direction.
Description
Technical Field
The invention belongs to the technical field of thermal imaging, and particularly relates to a combined scanning laser thermal imaging detection system, a sampling method and a device.
Background
Aluminum alloys are widely used materials for aircraft, and fatigue cracks are the most dangerous surface defects for them. The early surface microcrack of the aluminum alloy component of the aircraft is found in time to be an important nondestructive testing task.
Laser infrared thermal imaging is an emerging nondestructive testing technology which does not need to be in contact, is rapid to detect and has high sensitivity. The laser infrared thermal imaging technology has good suitability and application potential for detecting surface cracks of the metal material, and can meet the requirements of non-contact, high-efficiency, high-precision and pollution-free surface crack detection.
The aluminum alloy has the characteristics of high heat conductivity, low emissivity and high reflectivity. The high thermal conductivity characteristics allow for enhanced heat dissipation effects, and when cracks exist in the surface, heat is rapidly conducted to non-crack areas. This results in a reduced surface temperature difference between the crack and non-crack areas, thereby reducing the thermal signal contrast of the crack and the response characteristics of the crack location are reduced. When the motion scanning laser irradiates the surface of the untreated aluminum alloy, adverse effects such as light spot diffusion, energy distortion, shape distortion and the like can be generated, so that serious noise interference is caused, and the detection precision of surface microcracks is seriously affected. Therefore, in order to eliminate the influence of the surface condition on the detection result, the conventional crack detection method is used for preprocessing the surface, such as black paint spraying and the like, as a precondition for laser infrared thermal imaging detection.
Disclosure of Invention
The embodiment of the invention aims to provide a combined scanning laser thermal imaging detection system, a sampling method and a device, which are used for solving the technical problems that the noise interference is large, the micro-crack signal on the surface of an untreated aluminum alloy is easily submerged by surface noise, the characteristic signal is fuzzy and the positioning robustness is poor in the existing crack positioning detection method.
In order to solve the technical problems, the invention is realized as follows:
in a first aspect, an embodiment of the present invention provides a combined scanning laser thermal imaging detection system, including a thermal infrared imager, an optical platform, a fixture, a laser, and a motion platform;
the infrared thermal imager and the light emitting end of the laser are arranged on the moving platform, the moving platform is arranged on the optical platform, and the moving platform can move relative to the optical platform;
the clamp is arranged on the optical platform, the height of the clamp relative to the optical platform is adjustable, the clamp is used for clamping an aluminum alloy test piece, and the surface of the aluminum alloy test piece is not subjected to black paint spraying treatment;
the laser emitted by the laser is transmitted to the surface of the aluminum alloy test piece, the thermal infrared imager is used for collecting temperature data in a sampling area on the surface of the aluminum alloy test piece, and the sampling area is a front side area of a laser heat affected zone in the laser movement direction.
Optionally, the system further comprises: the light emitting end of the laser is connected with the collimator through an optical fiber, the collimator is arranged on the motion platform, laser emitted by the laser is transmitted to the surface of the aluminum alloy test piece after being collimated by the collimator so as to form a spot light on the surface of the aluminum alloy test piece, and the distance between the collimator and the aluminum alloy test piece is the focal length of the collimator.
In a second aspect, an embodiment of the present invention provides a sampling method based on LROI-Dmin, which is applied to the joint scanning laser thermal imaging detection system according to any one of the first aspect, where the method includes:
under the condition that an aluminum alloy test piece is placed in a clamp and the clamp is positioned in the visual angle of the thermal infrared imager, controlling the laser to emit light, and driving the laser to move through a moving platform so as to enable laser emitted by the laser to move on the surface of the aluminum alloy test piece;
determining a sampling area, wherein the sampling area is a front side area of a laser heat affected zone in the laser movement direction;
acquiring temperature data of a sampling area on the surface of the aluminum alloy test piece through a thermal infrared imager;
And determining the position of the crack of the aluminum alloy test piece according to the minimum value characteristic in the temperature data.
Optionally, after the acquiring, by the thermal infrared imager, temperature data of a sampling area of the surface of the aluminum alloy test piece, the method further includes:
performing wavelet three-layer decomposition on the temperature data based on Haar wavelet to obtain a detail coefficient after the wavelet three-layer decomposition;
the determining the position of the crack of the aluminum alloy test piece according to the minimum value characteristic in the temperature data comprises the following steps:
and determining the position of the crack of the aluminum alloy test piece according to the detail coefficient.
Optionally, after the wavelet tri-layer decomposition of the temperature data based on Haar wavelet, the method further comprises:
taking a signal obtained by carrying out wavelet three-layer decomposition on the temperature data as an input signal;
continuously performing wavelet transformation on the input signal to obtain a correlation coefficient between the input signal and a wavelet function after each wavelet transformation;
and determining the position of the maximum value of the correlation coefficient as the position of the crack of the aluminum alloy test piece.
Optionally, the area of the laser heat affected zone is a first area, and determining the sampling area further includes:
A region of the front side region of the laser heat affected zone having an area of one-half of the first area is determined to be a sampling region.
In a third aspect, an embodiment of the present invention provides a sampling device based on LROI-Dmin, applied to the joint scanning laser thermal imaging detection system according to any one of the first aspect, where the device includes:
the control module is used for controlling the laser to emit light under the condition that an aluminum alloy test piece is placed in the clamp and the clamp is positioned in the visual angle of the thermal infrared imager, and driving the laser to move through the moving platform so as to enable the laser emitted by the laser to move on the surface of the aluminum alloy test piece;
the first determining module is used for determining a sampling area, wherein the sampling area is a front side area of a laser heat affected zone in the laser movement direction;
the acquisition module is used for acquiring temperature data of a sampling area on the surface of the aluminum alloy test piece through the thermal infrared imager;
and the second determining module is used for determining the position of the crack of the aluminum alloy test piece according to the minimum value characteristic in the temperature data.
Optionally, the sampling device further includes:
the decomposition module is used for carrying out wavelet three-layer decomposition on the temperature data based on Haar wavelet to obtain a detail coefficient after wavelet three-layer decomposition;
The second determining module is specifically used for determining the position of the crack of the aluminum alloy test piece according to the detail coefficient.
Optionally, the sampling device further includes:
the third determining module is used for taking the signal obtained by carrying out wavelet three-layer decomposition on the temperature data as an input signal;
the transformation module is used for carrying out continuous wavelet transformation on the input signal to obtain the correlation coefficient between the input signal and a wavelet function after each wavelet transformation;
and the fourth determining module is used for determining that the position of the maximum value of the correlation coefficient is the position of the crack of the aluminum alloy test piece.
Optionally, the area of the laser heat affected zone is a first area, and the first determining module is specifically configured to determine that a region of the front side area of the laser heat affected zone, which is one half of the first area, is a sampling region.
The embodiment of the invention provides a combined scanning laser thermal imaging detection system, which comprises a thermal infrared imager, an optical platform, a clamp, a laser and a moving platform, wherein the thermal infrared imager and the light emitting end of the laser are arranged on the moving platform, the moving platform is arranged on the optical platform, and the moving platform can move relative to the optical platform; the clamp is arranged on the optical platform, the height of the clamp relative to the optical platform is adjustable, the clamp is used for clamping an aluminum alloy test piece, and the surface of the aluminum alloy test piece is not subjected to black paint spraying treatment; the laser emitted by the laser is transmitted to the surface of the aluminum alloy test piece, the thermal infrared imager is used for collecting temperature data in a sampling area on the surface of the aluminum alloy test piece, and the sampling area is a front side area of a laser heat affected zone in the laser movement direction. According to the embodiment of the invention, the aluminum alloy test piece is not required to be treated by black paint spraying, the traditional surface pretreatment methods such as black paint spraying and the like are overcome, the front side area of the laser heat affected zone in the laser movement direction is selected as the sampling area of the thermal infrared imager, the noise influence caused by the characteristics of low emissivity and high reflectivity of the untreated aluminum alloy surface is obviously weakened, and the quick and automatic positioning characterization of microcracks on the untreated aluminum alloy surface is realized.
Drawings
FIG. 1 is a block diagram of a joint scanning laser thermal imaging detection system provided by an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a sample 1 and a microscopic image of a crack in the top view of the surface of the sample 1 according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a sample 2 and a microscopic image of a top view of a surface and a crack of the sample 2 according to an embodiment of the present invention;
fig. 4 is a schematic view of a surface scanning path of a sample 1 and a schematic view of a surface scanning path of a sample 2 according to an embodiment of the present invention;
FIG. 5 is a microscopic image of surface scratches and surface pits of sample 1 provided in an embodiment of the present invention;
FIG. 6 is a diagram of a numerical grid consisting of 194610 elements provided by an embodiment of the present invention;
FIG. 7 is a schematic diagram of three stages of movement of a laser spot into a crack provided by an embodiment of the present invention;
FIG. 8 is a diagram showing the numerical simulation result point probe position and the numerical simulation temperature curve characteristics of surface microcracks provided by the embodiment of the invention;
FIG. 9 is a partial enlarged view of a feature at a crack of a Point 2 at a sampling Point and a schematic diagram of analysis results of signal to noise ratios of different sampling points according to an embodiment of the present invention;
FIG. 10 is a schematic diagram of a point sampling method and an SROI sampling region according to an embodiment of the present invention;
FIG. 11 is a schematic diagram showing temperature curve results of a sample 1 scan path A and a sample 2 scan path 1 point sampling and SROI-mean sampling method according to an embodiment of the present invention;
FIG. 12 is a schematic diagram of a surface scratch defect and a surface pit defect with enhanced thermal radiation of non-crack defects on the surface of a sample 1 after laser excitation according to an embodiment of the present invention;
fig. 13 is a flowchart of a sampling method based on LROI-Dmin according to an embodiment of the present invention;
FIG. 14 is a schematic diagram of a dynamic minimum feature point location in a sampling region according to an embodiment of the present invention;
FIG. 15 is a schematic diagram of sampling positions of feature points of dynamic minima when cracks provided by an embodiment of the present invention are located in different regions of LROI;
fig. 16 is a schematic diagram showing comparison of temperature curve results of a point sampling and SROI-mean sampling method and an LROI-Dmin sampling method according to an embodiment of the present invention;
fig. 17 is a schematic diagram of a temperature distribution curve of a scan path a result and a scan path B result in a sample 1 based on an LROI-Dmin sampling method according to an embodiment of the present invention;
fig. 18 is a schematic diagram of a temperature distribution curve of a scan path 1 result and a scan path 2 result in a sample 2 based on an LROI-Dmin sampling method according to an embodiment of the present invention;
FIG. 19 is a graph of signal characteristics at a crack and a Haar wavelet schematic provided by an embodiment of the present invention;
Fig. 20 is a schematic diagram of an LROI-Dmin original temperature curve and a temperature curve after wavelet decomposition treatment provided in an embodiment of the present invention;
FIG. 21 is a three-dimensional curved surface diagram of the distribution of wavelet correlation coefficients on different scales and wavelet phase relation numbers provided by the embodiment of the invention;
fig. 22 is a schematic diagram showing the distribution of LROI-Dmin original temperature curves and wavelet correlation coefficients on different scales in a scan path B of a sample 1 according to an embodiment of the present invention;
FIG. 23 is a schematic view of a laser heat affected zone range provided by an embodiment of the present invention;
fig. 24 is a schematic diagram of different LROI diagrams and a schematic diagram of temperature curves of dynamic minimum feature sampling results in different LROI domains according to an embodiment of the present invention;
FIG. 25 is a graph showing signal-to-noise ratios of temperature curves of sampling regions at different laser powers and scan speeds according to an embodiment of the present invention;
fig. 26 is a schematic structural diagram of a sampling device based on LROI-Dmin according to an embodiment of the present invention.
The achievement of the object, functional features and advantages of the present invention will be further described with reference to the embodiments, referring to the accompanying drawings.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms first, second and the like in the description and in the claims, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present invention may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type, and are not limited to the number of objects, such as the first object may be one or more.
The joint scanning laser thermal imaging detection system provided by the embodiment of the invention is described in detail below through specific embodiments and application scenes thereof with reference to the accompanying drawings.
Example 1
Referring to fig. 1, a block diagram of a joint scanning laser thermal imaging detection system according to an embodiment of the present invention is shown.
The invention provides a combined scanning laser thermal imaging detection system which comprises a thermal infrared imager, an optical platform, a clamp, a laser and a motion platform, wherein the optical platform is arranged on the thermal infrared imager;
the infrared thermal imager and the light emitting end of the laser are arranged on the moving platform, the moving platform is arranged on the optical platform, and the moving platform can move relative to the optical platform;
The clamp is arranged on the optical platform, the height of the clamp relative to the optical platform is adjustable, the clamp is used for clamping an aluminum alloy test piece, and the surface of the aluminum alloy test piece is not subjected to black paint spraying treatment;
the laser emitted by the laser is transmitted to the surface of the aluminum alloy test piece, the thermal infrared imager is used for collecting temperature data in a sampling area on the surface of the aluminum alloy test piece, and the sampling area is a front side area of a laser heat affected zone in the laser movement direction.
In the embodiment of the invention, the combined scanning laser thermal imaging is to scan the surface of the aluminum alloy test piece along a scanning path by utilizing a laser point. In the scanning process, the thermal infrared imager and the laser collimator are arranged on a moving platform to form a combined scanning unit, and the static sample is synchronously scanned. The infrared thermal imager and the aluminum alloy test piece move relatively, so that the aluminum alloy test piece moves in the visual field of the infrared thermal imager, and the thermal image sequence acquired by the infrared thermal imager records the temperature data on the surface of the aluminum alloy test piece.
In one possible embodiment, the joint-scan laser thermal imaging detection system may further include: the light emitting end of the laser is connected with the collimator through an optical fiber, the collimator is arranged on the motion platform, laser emitted by the laser is transmitted to the surface of the aluminum alloy test piece after being collimated by the collimator so as to form a spot light on the surface of the aluminum alloy test piece, and the distance between the collimator and the aluminum alloy test piece is the focal length of the collimator.
In the experimental setup shown in fig. 1, a thermal infrared imager was fixed on an optical stage against an aluminum alloy test piece. The aluminum alloy test piece is arranged on the aluminum alloy test piece clamp, and the height of the clamp can be manually adjusted to enable the aluminum alloy test piece to be positioned in the center of the field of view of the thermal infrared imager. The laser generated by the laser is transmitted to the laser collimator through the optical fiber, and then is shaped into spot light spots through the light beam and irradiated to the surface of the aluminum alloy test piece. The thermal infrared imager and the laser collimator are arranged on the electric control motion platform, and parameters such as an incident angle, laser power, a scanning path, scanning speed and the like of laser can be adjusted according to experimental requirements. The thermal infrared imager, the laser and the electric control desk controller are controlled by a terminal control computer to start and stop. The thermal infrared imager and the laser collimator are arranged on the motion platform to form a combined scanning unit, and the stationary sample is synchronously scanned along the direction parallel to the surface of the aluminum alloy sample. And recording temperature data information of the surface of the aluminum alloy test piece in the scanning process by the thermal infrared imager.
Optionally, in order to realize heat input with high energy density to the surface of the aluminum alloy test piece, the distance between the laser collimator and the aluminum alloy test piece is the focal length of the collimator, that is, the optimal focusing position of the spot light, so as to ensure the high focusing of the spot light of the laser spot.
In the embodiment of the invention, in order to verify that the detection of the combined scanning laser thermal imaging detection system on the non-processed aluminum alloy test piece with the surface sprayed with black paint and the like can obviously weaken the noise influence generated by the characteristics of low emissivity and high reflectivity of the non-processed aluminum alloy surface, the quick and automatic positioning characterization of microcracks on the non-processed aluminum alloy surface is realized, and the embodiment of the invention designs two types of test pieces and carries out numerical simulation.
As shown in fig. 2 (a) and fig. 2 (b), the structural schematic diagram, the top plan view and the microscopic images of the crack of the sample 1 provided by the embodiment of the invention, the sample 1 has real fatigue crack, crack tortuosity and gradual change of opening width. Meanwhile, the surface integrity is weaker, and the defects of pits, scratches and the like exist. The aluminum alloy material 6061 is adopted, the thermal conductivity is 180W/(m.K), and the specific heat is 896J/(kg.K). Firstly, prefabricating an artificial incision in the middle of a sample, and then preparing a real fatigue crack at the tip of the artificial incision through a fatigue experiment. The sample 1 had a size as shown in FIG. 2 (a), and the fatigue crack generated on the surface of the sample 1 had a length of 14.5mm, and an average width of 4.51. Mu.m, as shown in FIG. 2 (b).
As shown in fig. 3 (a) and fig. 3 (b), the structural schematic diagram, the top plan view and the microscopic image of the crack of the sample 2 provided by the embodiment of the invention, the sample 2 is a manually simulated crack, the crack is flat, and the opening width is relatively uniform. Sample 2 has good surface integrity and high smoothness. The two block-shaped aluminum alloys are tightly attached, and microcracks are simulated by utilizing gaps of attaching surfaces. Sample 2 is also made of 6061 aluminum alloy, the size is shown in fig. 3, the joint surfaces of the two aluminum alloy blocks are polished and ground, the two aluminum alloy blocks are fixed through positioning pins, and tight joint is achieved through screws. The top view of sample 2, shown in fig. 3 (a), and the surface microscopic image shown in fig. 3 (b), can obtain a simulated crack characterization with a surface average width of 4.42 μm. However, because the two aluminum alloy blocks are tightly attached, the actual crack gap is not completely separated, so that partial thermal contact conduction exists between the two surfaces in the heat transfer process, the temperature characteristic of the crack is weakened, and crack detection is more difficult.
It should be noted that, the surface of the sample piece detected in the embodiment of the invention is not subjected to pretreatment such as black paint spraying.
The schematic diagrams of the combined scanning laser thermal imaging scanning path are shown in fig. 4 (a) and fig. 4 (b), and the laser point moves from left to right along the scanning path. The crack widths of the two sample pieces designed and processed by the embodiment of the invention are relatively uniform. In the embodiment of the invention, the surface of the sample 1 has shallow surface scratches, pits and other interference factors as shown in fig. 5 (a) and 5 (b), so that the complexity of the surface condition is increased, the real detection environment is simulated, and the robustness of the crack positioning method is tested. The thermal phenomena of the shallow scratches and pits were subsequently studied and analyzed for their effect on detection. To test the stability of the detection method herein, two scan paths are provided on the surface of sample 1, as shown in fig. 4 (a), designated by uppercase letters. The sample piece 2 maintains a high finish surface to analyze the thermal response law of the laser on the low-emissivity, high-reflectivity surface and to analyze the influence of different process parameters. Two scan paths are provided on the surface of the sample 2, as shown in fig. 4 (b), designated by numerals.
In the embodiment of the invention, COMSOL finite element analysis software is initially used for carrying out numerical simulation analysis on the combined scanning laser thermal imaging. In the process of jointly scanning laser, the power density of the laser on the surface of the sample can be expressed as:
Wherein D represents power density, A is material surface absorption coefficient, P is laser power, x 0 And y 0 The origin of the beam on the x and y axes, v is the speed of movement of the laser spot heat source on the sample surface, and R represents the sample surface laser spot radius. The three-dimensional heat conduction equation in a solid can be written as:
wherein Q is a heat source, i.e. heat generated or absorbed in the volume of solid per unit time, ρ is the density of solid, C p Specific heat capacity, k, of a solid x 、k y 、k z For directional thermal conductivity, T is temperature and T is time.
A numerical grid of crack sample modeling was created using COMSOL finite element analysis software, as in fig. 6. The simulated sample material was 6061 aluminum alloy, and the crack area was considered as air. The thermophysical properties and numerical simulation parameters of the specific materials are shown in tables 1 and 2.
TABLE 1 Thermophysical Properties of materials in numerical simulations
Table 2 detailed numerical simulation parameters
Fig. 7 shows images of three stages of laser spot movement to the front, middle and rear of a crack during laser movement. In the process of joint scanning laser thermal imaging, the laser moves at a constant speed on the surface of a test piece, and constant heat is input to the surface of the test piece per unit time. When the laser excitation point approaches to the crack, the crack on the surface of the metal material blocks the propagation of heat flow, heat is accumulated on the left side of the crack on the surface of the material to form heat blockage, and the heat blocking effect causes the temperature on the excitation side of the laser. Meanwhile, the right side of the crack shows a low temperature area, and a significant temperature difference is formed between the left side and the right side of the crack. Because the crack detection targets are all in a narrow scale, the temperature rise phenomenon caused by the thermal trapping effect of the crack is negligible. The heat blocking effect becomes a main influencing factor for the formation of micro-crack characteristics on the surface of the aluminum alloy.
The above temperature variations indicate that the temperature profile of the sample area near the laser spot is very sensitive to microcrack defects, and that the crack location is expected to exhibit a characteristic of a particular temperature fluctuation that is different from that of the non-crack area, and can be used to detect and identify the characteristic microcracks.
And setting an equidistant point probe near the laser spot to analyze the temperature curve sampling result. The positions of equidistant sampling points with respect to the laser light are shown in fig. 8 (a) with reference to the radius of the laser spot. Even if the surface crack width is only 5 mu m, the crack is blocked by an air interlayer in the crack in the heat conduction process, and the crack positions of the temperature curves of all sampling points show obvious special fluctuation characteristics. As shown in fig. 8 (b), point 1 and Point 2 are located at the front side in the laser motion direction, and the heat accumulation at the left side of the crack causes a first peak value of the fluctuation feature, so that the heat is difficult to transfer to the right side of the crack, and the fluctuation feature valley phenomenon is caused. As the laser is excited to the right of the crack, the temperature rises rapidly and the temperature profile at the final crack location exhibits a peak-valley bipolar characteristic. The laser center sampling Point 3 is characterized by a single-pole peak at the crack because the laser center energy is highest, the temperature is rapidly increased when the laser Point moves to the right side of the crack, and the thermal barrier effect of the crack is not obvious. And the Point 4 and Point 5 sampling points are positioned at the rear side of the laser movement direction, and when the laser Point moves to the right side of the crack, heat formed at the right side of the crack is accumulated, so that the peak-valley tripolar characteristic is presented. Therefore, the peak-to-valley multi-level feature described above can be considered as a microcrack defect feature.
In the non-destructive detection process, signal-to-Noise Ratio (SNR) is one of the important indicators for measuring Signal quality. In the crack detection process of the combined scanning laser thermal imaging, a thermal signal of a crack defect area contains useful information, which is defined as a signal. The thermal signal around the defective area is a disturbance existing in the detection process, defined as noise. Taking the crack fluctuation feature of Point 2 as an example, the temperature signal amplitude at the crack is defined herein as a useful signal, as in fig. 9 (a), and the average value of the temperature signal amplitudes in the intact area (i.e., the crack defect free area) is defined as noise disturbance. A is that s Characteristic peaks Gu Chazhi of the crack region are represented, and τ represents the time difference between the peak and the valley.
The temperature curve is expressed as T (x), and the peak-valley bipolar characteristic peak corresponding position at the crack is assumed to be x 0 We define the amplitude of the temperature signal as:
A s ＝max(T(x))-min(T(x)),x∈[x 0 ,x 0 +τ]
the average value of the amplitude of noise is defined as:
the signal-to-noise ratio is defined as:
the higher the signal-to-noise ratio is, the more obvious the signal characteristics are at the crack, the smaller the influence of noise on the signal is, and the signal-to-noise ratio analysis results of different sampling points are shown in fig. 17 (b). In contrast, the fluctuation characteristics of the crack positions of the sampling points Point1 and Point 2 at the front side in the laser movement direction are stronger, and the signal to noise ratio is higher. Although the crack characteristic amplitudes of Point 2 and Point4 are stronger, because they are interfered by noise generated by laser motion, the signal-to-noise ratio is lower than that of the sampling points Point1 and Point 5 located outside the laser heat affected zone. Notably, the numerically simulated sample surface is ideal, producing a noiseless thermal response. The weak fluctuation interference can be further amplified in the actual detection process, and the influence of the non-processed surface can be stronger. The sampling location should be set away from the laser heat affected zone. And then preliminarily establishing an optimal sampling area as a front side area of a laser heat affected zone along the laser movement direction, so that the thermal infrared imager is used for acquiring temperature data in the sampling area on the surface of the aluminum alloy test piece in the embodiment of the application, and the sampling area is the front side area of the laser heat affected zone in the laser movement direction.
The embodiment of the invention provides a combined scanning laser thermal imaging detection system, which comprises a thermal infrared imager, an optical platform, a clamp, a laser and a moving platform, wherein the thermal infrared imager and the light emitting end of the laser are arranged on the moving platform, the moving platform is arranged on the optical platform, and the moving platform can move relative to the optical platform; the clamp is arranged on the optical platform, the height of the clamp relative to the optical platform is adjustable, the clamp is used for clamping an aluminum alloy test piece, and the surface of the aluminum alloy test piece is not subjected to black paint spraying treatment; the laser emitted by the laser is transmitted to the surface of the aluminum alloy test piece, the thermal infrared imager is used for collecting temperature data in a sampling area on the surface of the aluminum alloy test piece, and the sampling area is a front side area of a laser heat affected zone in the laser movement direction. According to the embodiment of the invention, the aluminum alloy test piece is not required to be treated by black paint spraying, the traditional surface pretreatment methods such as black paint spraying and the like are overcome, after simulation verification, the front side area of the laser heat affected zone in the laser movement direction is selected as the sampling area of the thermal infrared imager, the noise influence caused by the characteristics of low emissivity and high reflectivity of the untreated aluminum alloy surface is obviously weakened, and the quick and automatic positioning characterization of microcracks on the untreated aluminum alloy surface is realized.
Example two
The existing combined scanning laser thermal imaging technology requires that a test piece is subjected to surface pretreatment, and the surface pretreatment can remarkably weaken noise of acquired signals, so that a temperature sampling area can be far smaller than a heat affected zone of a laser excitation point, and point sampling or average temperature sampling of a small-range area (Small Region of Interest, SROI) can be performed, as shown in fig. 10 (a) and 10 (b). However, when the surface of the aluminum alloy sample is not treated, the surface state of the material, such as scratches, pits and other interference factors, can seriously interfere with crack characteristic signals, so that the existing combined scanning laser thermal imaging sampling method cannot accurately position micro cracks.
Among the conventional temperature signal sampling methods, the point sampling and SROI averaging (Mean values in the SROI, SROI-mean) fixed area sampling method is very sensitive to no-process surface conditions. As shown in FIG. 11, in sample 1 scan path A and sample 2 scan path 1, the laser power was 90W, the scanning speed was 5.86mm/s, and the temperature profile of the conventional sampling result was analyzed.
In the sample 1 scanning path a, as shown in fig. 11 (a), defects such as scratches and pits have large width dimensions, laser light acts on the inside of the shallow defects, and the temperature of the defects rapidly increases, which is manifested as abrupt temperature peak changes in local areas. Causing a bright spot as in fig. 12, the scratch and pit locations are marked in the figure with a dashed box. Both point sampling and SROI-mean collect local temperature abrupt changes of the surface, and temperature peak phenomena at 12mm and 25mm positions correspond to scratches and pit defects, respectively. The temperature curve shows strong fluctuation, and the surface conditions such as non-crack defects and the like generate serious noise interference. In the scan path 1 of the sample 2, as shown in fig. 11 (b), the sample surface condition is relatively flat, and no other non-crack defects interfere. Noise mainly comes from temperature fluctuation caused by thermal diffusion, surface unevenness and the like when a laser spot moves on the surface of a sample piece, and a spot sampling temperature curve has obvious jitter nonlinear variation. The SROI-mean temperature curve is more prone to have some suppression effect on noise for the overall temperature change acquisition in the region. In sample 2, it is difficult for conventional sampling methods to capture and analyze crack signal characteristics.
Compared with the sample 1, the conventional sampling method of the sample 2 has the advantages that the overall noise interference of the temperature curve is less, the stability is better, and the overall fluctuation range is narrower. Because the quality of the signal is relatively higher, the change trend information of the temperature curve can be primarily identified. Therefore, a surface with a high finish is more advantageous for the detection and characterization of microcracks. However, in both samples, the crack waveform is submerged and the features are lost due to noise interference, and neither the point sampling nor the SROI-mean sampling method can effectively extract features of microcracks on the surface of the untreated aluminum alloy.
The temperature rise caused by non-crack defects is much greater than the temperature fluctuations caused by microcrack defects, which makes the traditional sampling method unable to accurately locate and characterize untreated surface microcrack defects, and these effects are mainly due to the temperature rise phenomenon caused by thermal radiation enhancement. The thermal barrier effect is a main influencing factor of the formation of micro-crack characteristics on the surface of the aluminum alloy, and obvious temperature difference is formed at two sides of the micro-crack, so that the temperature drop characteristics in the sampling area are more worth focusing.
Referring to fig. 13, a flowchart of a sampling method based on LROI-Dmin according to an embodiment of the present invention is shown.
An LROI-Dmin based sampling method applied to the joint scanning laser thermal imaging detection device according to the first embodiment, the method includes:
s1301: under the condition that an aluminum alloy test piece is placed in a clamp and the clamp is positioned in the visual angle of the thermal infrared imager, controlling the laser to emit light, and driving the laser to move through a moving platform so as to enable laser emitted by the laser to move on the surface of the aluminum alloy test piece;
s1302: determining a sampling area, wherein the sampling area is a front side area of a laser heat affected zone in the laser movement direction;
s1303: acquiring temperature data of a sampling area on the surface of the aluminum alloy test piece through a thermal infrared imager;
s1304: and determining the position of the crack of the aluminum alloy test piece according to the minimum value characteristic in the temperature data.
By further suppressing noise using a large-scale sampling region (Large Region of Interest, LROI), temperature signal acquisition is performed on dynamic minima features (Dynamic minimum features in the LROI, LROI-Dmin) in the large-scale sampling region, and as shown in fig. 14, pentagonal star points represent dynamic minima feature point positions based on the frame heat map. The low-temperature signal change in the sampling area is not affected by the local temperature rise phenomenon in the area, the signal is more stable, and the noise interference is less. Meanwhile, the LROI-Dmin keeps good sensitivity on low-temperature phenomenon caused by crack blocking, and further extracts the crack singularity fluctuation characteristic.
The LROI-Dmin-based sampling method can effectively extract the feature of microcrack on the surface without treatment. The method can collect continuously-changing dynamic characteristic temperature information frame by frame. In the process of joint scanning laser thermal imaging, the laser spot heat source scans from left to right. When the sampling area is in front of the crack defect, as shown in fig. 15 (a), the pentagram points represent the positions of the dynamic minimum feature points in the domain, and the LROI-Dmin dynamic points are mainly distributed at the positions farthest from the laser center. The acquisition temperature shows a tendency to rise slowly. With the action of the laser heat affected zone, the LROI approaches the crack defect, and the LROI-Dmin acquisition temperature continuously and slowly rises. When LROI crosses a crack defect as in fig. 15 (b), 15 (c), LROI-Dmin acquires a low temperature region on the right side of the crack due to thermal barrier effect of the crack. And further, the characteristic of significant temperature drop is presented, and the peak-valley bipolar characteristic of the acquisition temperature at the crack is caused. After the LROI passes through the crack region, as shown in fig. 15 (d), the dynamic sampling point is mainly concentrated at the farthest point from the center, and the collected temperature continues to show a steady slow rising trend. The LROI-Dmin can effectively collect a low-temperature area caused by crack thermal barrier, and has good suitability and robustness in positioning characterization of microcracks on the surface of the untreated aluminum alloy.
In comparison with the temperature curve results of the traditional sampling method, the LROI-Dmin sampling method has higher signal to noise ratio, and the crack position of the temperature curve shows obvious peak-valley bipolar characteristics. In sample 1 scan path A and sample 2 scan path 1, the laser power was 90W and the scan speed was 5.86mm/s. As shown in fig. 16 (a), in the sample 1, the LROI-Dmin sampling method effectively suppresses noise interference generated in the non-crack area, does not collect temperature peak abrupt change in the area, and significantly reduces the influence of interference factors such as surface scratches, pits, and the like. In sample 2, as shown in fig. 16 (b), the LROI-Dmin sampling method can significantly reduce noise interference caused by laser spot movement because the surface is relatively flat, so that the obtained temperature profile is smoother than that of sample 1. The LROI-Dmin sampling method is capable of detecting 5 μm wide microcracks in both samples and exhibits significant peak-to-valley bipolar characteristic volatility at the cracks. The method has good sensitivity to crack characteristics, can amplify the crack characteristic amplitude, improves the thermal contrast of crack areas and non-crack areas, and clearly shows the overall heating trend of a temperature curve.
Based on the LROI-Dmin sampling method, the characteristics of microcracks on the surface of the untreated aluminum alloy can be stably extracted and characterized. At a scanning speed of 5.86mm/s, a laser power of 90W, a process parameter setting of the sampling region LROI 1. As shown in fig. 17, the LROI-Dmin sampling temperature curves of the 2 scan paths in the sample 1, as shown in fig. 18, and the crack areas are indicated by black dashed boxes. The LROI-Dmin sampling method successfully and stably characterizes crack location peak-valley bipolar characteristics in sample 1 and sample 2 scan path 1. In sample 2 scan path 2, the evolution of the crack waveform is caused by the presence of thermal contact conduction. The left side of the crack is insufficient in heat accumulation, the heat is rapidly dissipated due to the high heat conductivity of the aluminum alloy, when the laser point moves to the right side of the crack, the LROI-Dmin sampling temperature is rapidly raised, the waveform shape of the crack position changes, and the waveform shows similar fluctuation of the monopole valley characteristic, but is still quite obvious. Thermal contact conduction of sample 2 will lead to a weakening of the amplitude of the crack signature, amplitude a of sample 1 s Stronger, but because its surface condition is more complex, the signal-to-noise ratio of the temperature profile is not much different from that of the sample 2.
In summary, the LROI-Dmin based sampling method presented herein has a high degree of sensitivity and accuracy, and is capable of effectively detecting the presence of microcracks. It shows good universality in different samples and can stably represent the positions of cracks and peak-valley bipolar characteristics.
In signal processing, it is often necessary to consider how to suppress noise to improve the quality and reliability of the signal. So to further amplify the characteristics at the crack of the temperature signal, noise interference at the non-crack location is reduced. Although the LROI-Dmin sampling method can effectively reduce noise interference for a surface without treatment, compared with signals collected on the surface of black paint by the traditional method, the noise interference on the signals is stronger, and the signal-to-noise ratio is relatively lower.
Analysis of crack signatures based on LROI-Dmin sampling methods is performed herein, taking sample 2 scan path 1 as an example, because of the thermal barrier effect of the crack, the temperature signal continues to rise to the left of the crack. As the acquisition region traverses the crack, a significant peak-to-valley bipolar characteristic of the temperature signal is formed as shown in fig. 19 (a) because the blocking causes the temperature to be lower to the right of the crack than to the left. This feature is very similar to Haar wavelet as in fig. 19 (b). Haar wavelet signals are characterized by rising and then suddenly falling. Shows consistency with the peak-to-valley bipolar characteristics at the crack.
In a possible embodiment, after step S1303, the method further includes:
s1305: performing wavelet three-layer decomposition on the temperature data based on Haar wavelet to obtain a detail coefficient after the wavelet three-layer decomposition;
step S1304 may be specifically performed by step S13041:
s13041: and determining the position of the crack of the aluminum alloy test piece according to the detail coefficient.
Wavelet decomposition has wide application in the field of signal denoising. The input signal can be subjected to multi-level wavelet transformation through wavelet decomposition, and the approximation coefficients and detail coefficients of various scales are returned. The original temperature signal is subjected to wavelet 3-layer decomposition based on Haar wavelet, and the detailed coefficient result of the third-layer decomposition is selected as an output signal. As shown in fig. 20, the crack signal characteristics are further amplified by wavelet decomposition. Noise removal of the temperature signal and enhancement of the useful signal characteristics are achieved. Compared with the original temperature signal, the signal to noise ratio of the processed signal is obviously increased from the original 16.02 to 27.25. The processed temperature signal oscillates around 0K, and the rising trend of the signal is eliminated, so that the singularity of the crack position characteristic of the temperature curve is further enhanced.
The wavelet analysis is a time-frequency analysis method, can decompose time series signals into subcomponents with different scales and frequencies, and shows good suitability in defect feature extraction. Based on the LROI-Dmin thermal signal sampling method, the temperature signal peak-valley bipolar characteristic corresponding to the microcrack of the non-processing surface is established. Based on waveform characteristic analysis, the embodiment of the application provides a method for automatically positioning crack positions by Haar wavelet transformation correlation coefficient analysis.
After step S1305, the method further includes:
s1306: taking a signal obtained by carrying out wavelet three-layer decomposition on the temperature data as an input signal;
s1307: continuously performing wavelet transformation on the input signal to obtain a correlation coefficient between the input signal and a wavelet function after each wavelet transformation;
s1308: and determining the position of the maximum value of the correlation coefficient as the position of the crack of the aluminum alloy test piece.
Specifically, the output signal processed in step S1305 is taken as the input signal in the embodiment of the present application. The correlation coefficient between a series of signals and the wavelet function is calculated by wavelet analysis of wavelet changes. The one-dimensional continuous wavelet transform is an integral form wavelet transform that is continuous for both scale scaling and panning of the parent wavelet, so the result of the transform is a binary function consisting of scaling and displacement. The one-dimensional continuous wavelet transformation can perform time-frequency analysis on given data, so as to obtain wavelet correlation coefficients of the input temperature signal f (x) under different displacement and scale:
Where W (s, p) represents a one-dimensional continuous wavelet correlation coefficient, x represents a spatial displacement, s represents a scale transform coefficient, and p represents a translational transform coefficient. Haar wavelet is selected as a wavelet generation function ψ (t):
the Haar wavelet is an orthogonal basis, can keep the energy of the signal unchanged, and has simple realization and high calculation speed. For signals with hopping properties, the continuous Haar wavelet transform may better reflect the locations of the hopping points, i.e., the locations of the crack peak-valley bipolar features.
As shown in fig. 21 (a), the wavelet correlation coefficient varies between-1 and 1, and is 1 if and only if the temperature profile is exactly equal to the input wavelet function. In fig. 21, the correlation coefficient is large as the peak is located closer to the bottom surface, and is small as the horizontal axis represents the displacement axis, and the vertical axis represents the scale axis. This way the distribution of the correlation coefficient over the displacement-scale plane can be understood from fig. 21. To get a more visual representation of the results, we plot the results in a three-dimensional surface as in fig. 21 (b).
In signal analysis, wavelet correlation coefficients are a statistic that characterizes signal singularities in an indirect way. Singularities can be used to measure how abnormal a signal is at certain points. For the peak-to-valley bipolar feature of the crack region, it has a significant singularity that is clearly distinct from other regions. Therefore, the position of the maximum value of the wavelet phase relation number can be confirmed as a singular point characterizing the crack position. By locking the position of the singular point using the correlation coefficient analysis method, the crack position can be positioned quickly and efficiently. In fig. 21, crack locations are indicated by five-pointed star symbols. As shown in fig. 22, in the scanning path B of the sample 1, the method still shows good suitability.
In a possible embodiment, the area of the heat affected zone of the laser is the first area, and step S1302 is specifically performed by step S13021:
s13021: and determining that a region of which the area is one half of the first area in the front side region of the laser heat affected zone in the laser movement direction is a sampling region.
The LROI sampling area size is an important factor affecting the temperature profile results. In the actual detection process, the diffusion effect of the laser spot can be generated by the non-treatment of the aluminum alloy surface, and the area of the laser heat affected zone is enlarged, as shown in fig. 23. The LROI is provided on the front side in the laser movement direction, and three LROI regions of 0.5S, S and 1.5S are provided with reference to the heat affected zone area S of the laser spot, as shown in fig. 24 (a). In sample 2 scan path 1, the laser power 90W, scan speed 5.86mm/s, as shown in FIG. 24 (b), the crack area has been marked with a black frame line, showing the temperature profile of dynamic minimum feature samples in the field of different LROIs. As the sampling area is enlarged, the farther the sampling position of the LROI-Dmin dynamic characteristic point is away from the laser center, the peak-valley bipolar characteristic of the crack position is correspondingly weakened, and the overall noise interference of the signal is weakened. The LROI is gradually enlarged, so that the dynamic sampling point is farther from the laser center, the temperature drop phenomenon is collected earlier, and the positions of peak-valley bipolar characteristics at the crack position correspondingly move forward. LROI1 shows a slow temperature rise trend, and as the sampling area expands, the LROI3 temperature rise trend becomes less obvious and tends to be quasi-steady. The LROI1 shows the most pronounced peak-to-valley bipolar characteristics with the strongest amplitude characteristics. LROI3 shows the weakest peak-to-valley bipolar characteristics, which have not been able to locate crack locations accurately, and signal characteristics are prone to be swamped by noise. If the sampling area is further expanded, the wave characteristics at the crack are more unextractable.
As shown in fig. 25, the effect of LROI size on detection results at different scan speeds and laser power parameters was studied herein in scan path 1 by analysis of signal-to-noise ratio. Region selection of LROI is the most dominant contributor to signal-to-noise ratio impact compared to laser power and scan speed. By using different LROI sampling areas, effective extraction can be performed for the peak-valley bipolar characteristics at the crack. Although the signal-to-noise ratio fluctuates, the signal-to-noise ratio of the LROI-Dmin temperature curve at the front side of the laser motion direction keeps a relatively stable level. The sampling result of LROI1 has larger amplitude, stronger anti-interference capability to noise and higher signal-to-noise ratio than the other two areas. This is because the closer to the laser excitation center point, the higher the power density of the laser, with better sensitivity. LROI1 is ultimately selected as the optimal sampling region.
Example III
Referring to fig. 26, a schematic structural diagram of a sampling device based on LROI-Dmin according to an embodiment of the present invention is shown.
An LROI-Dmin based sampling device 260 for use in a joint scanning laser thermal imaging detection system according to any of the embodiments, said device 260 comprising:
The control module 2601 is used for controlling the laser to emit light under the condition that an aluminum alloy test piece is placed in a clamp and the clamp is located in the visual angle of the thermal infrared imager, and driving the laser to move through a moving platform so as to enable laser emitted by the laser to move on the surface of the aluminum alloy test piece;
a first determining module 2602, configured to determine a sampling area, where the sampling area is a front area of a laser heat affected zone in a laser motion direction;
an acquisition module 2603, configured to acquire temperature data of a sampling area on the surface of the aluminum alloy test piece through a thermal infrared imager;
and a second determining module 2604, configured to determine a location of a crack of the aluminum alloy test piece according to the minimum feature in the temperature data.
Optionally, the sampling device 260 further includes:
the decomposition module 2605 is configured to perform wavelet three-layer decomposition on the temperature data based on Haar wavelet, so as to obtain a detail coefficient after the wavelet three-layer decomposition;
the second determining module 2604 is specifically configured to determine a location of a crack of the aluminum alloy test piece according to the detail coefficient.
Optionally, the sampling device 260 further includes:
a third determining module 2606, configured to take a signal obtained by performing wavelet three-layer decomposition on the temperature data as an input signal;
A transformation module 2607, configured to perform continuous wavelet transformation on the input signal, so as to obtain a correlation coefficient between the input signal and a wavelet function after each wavelet transformation;
and a fourth determining module 2608, configured to determine a position of the maximum value of the correlation coefficient as a position of the crack of the aluminum alloy test piece.
Optionally, the area of the laser heat affected zone is a first area, and the first determining module 2602 is specifically configured to determine that a region of the front side area of the laser heat affected zone that is one half of the first area is a sampling region.
The sampling device 260 provided in the embodiment of the present invention can implement each process implemented in the above method embodiment, and in order to avoid repetition, a description is omitted here.
In the embodiment of the invention, the control module is used for controlling the laser to emit light under the condition that the aluminum alloy test piece is placed in the clamp and the clamp is positioned in the visual angle of the thermal infrared imager, the laser is driven to move through the moving platform, so that laser emitted by the laser moves on the surface of the aluminum alloy test piece, the first determining module is used for determining a sampling area, the sampling area is a front side area of a laser heat affected zone in the laser movement direction, the acquiring module is used for acquiring temperature data of the sampling area on the surface of the aluminum alloy test piece through the thermal infrared imager, and the second determining module is used for determining the position of a crack of the aluminum alloy test piece according to the minimum value characteristic in the temperature data. The sampling device based on the LROI-Dmin provided by the embodiment of the invention has high sensitivity and accuracy, and can effectively detect the existence of micro cracks. It shows good universality in different samples and can stably represent the positions of cracks and peak-valley bipolar characteristics.
The virtual system in the embodiment of the invention can be a device, a component in a terminal, an integrated circuit or a chip.
In addition, it should be noted that the above embodiment of the apparatus is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select some or all modules according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details not described in detail in this embodiment may refer to the intelligent cognitive method and system provided in any embodiment of the present invention, which are not described herein.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. The combined scanning laser thermal imaging detection system is characterized by comprising a thermal infrared imager, an optical platform, a clamp, a laser and a motion platform;
the infrared thermal imager and the light emitting end of the laser are arranged on the moving platform, the moving platform is arranged on the optical platform, and the moving platform can move relative to the optical platform;
The clamp is arranged on the optical platform, the height of the clamp relative to the optical platform is adjustable, the clamp is used for clamping an aluminum alloy test piece, and the surface of the aluminum alloy test piece is not subjected to black paint spraying treatment;
the laser emitted by the laser is transmitted to the surface of the aluminum alloy test piece, the thermal infrared imager is used for collecting temperature data in a sampling area on the surface of the aluminum alloy test piece, and the sampling area is a front side area of a laser heat affected zone in the laser movement direction.
2. The system of claim 1, wherein the system further comprises:
the light emitting end of the laser is connected with the collimator through an optical fiber, the collimator is arranged on the motion platform, laser emitted by the laser is transmitted to the surface of the aluminum alloy test piece after being collimated by the collimator so as to form a spot light on the surface of the aluminum alloy test piece, and the distance between the collimator and the aluminum alloy test piece is the focal length of the collimator.
3. A sampling method based on LROI-Dmin, applied to the joint scanning laser thermal imaging detection system according to any one of claims 1-2, wherein the method comprises:
Under the condition that an aluminum alloy test piece is placed in a clamp and the clamp is positioned in the visual angle of the thermal infrared imager, controlling the laser to emit light, and driving the laser to move through a moving platform so as to enable laser emitted by the laser to move on the surface of the aluminum alloy test piece;
determining a sampling area, wherein the sampling area is a front side area of a laser heat affected zone in the laser movement direction;
acquiring temperature data of a sampling area on the surface of the aluminum alloy test piece through a thermal infrared imager;
and determining the position of the crack of the aluminum alloy test piece according to the minimum value characteristic in the temperature data.
4. A sampling method according to claim 3, wherein after the obtaining of the temperature data of the sampling area of the surface of the aluminum alloy test piece by the thermal infrared imager, the method further comprises:
performing wavelet three-layer decomposition on the temperature data based on Haar wavelet to obtain a detail coefficient after the wavelet three-layer decomposition;
the determining the position of the crack of the aluminum alloy test piece according to the minimum value characteristic in the temperature data comprises the following steps:
and determining the position of the crack of the aluminum alloy test piece according to the detail coefficient.
5. The sampling method according to claim 4, wherein after the wavelet tri-layer decomposition of the temperature data based on Haar wavelets, the method further comprises:
Taking a signal obtained by carrying out wavelet three-layer decomposition on the temperature data as an input signal;
continuously performing wavelet transformation on the input signal to obtain a correlation coefficient between the input signal and a wavelet function after each wavelet transformation;
and determining the position of the maximum value of the correlation coefficient as the position of the crack of the aluminum alloy test piece.
6. The sampling method of claim 3, wherein the area of the laser heat affected zone is a first area, the determining the sampling area further comprising:
a region of the front side region of the laser heat affected zone having an area of one-half of the first area is determined to be a sampling region.
7. A sampling device based on LROI-Dmin for use in a joint scanning laser thermal imaging detection system according to any one of claims 1-2, said device comprising:
the control module is used for controlling the laser to emit light under the condition that an aluminum alloy test piece is placed in the clamp and the clamp is positioned in the visual angle of the thermal infrared imager, and driving the laser to move through the moving platform so as to enable the laser emitted by the laser to move on the surface of the aluminum alloy test piece;
the first determining module is used for determining a sampling area, wherein the sampling area is a front side area of a laser heat affected zone in the laser movement direction;
The acquisition module is used for acquiring temperature data of a sampling area on the surface of the aluminum alloy test piece through the thermal infrared imager;
and the second determining module is used for determining the position of the crack of the aluminum alloy test piece according to the minimum value characteristic in the temperature data.
8. The sampling device of claim 7, further comprising:
the decomposition module is used for carrying out wavelet three-layer decomposition on the temperature data based on Haar wavelet to obtain a detail coefficient after wavelet three-layer decomposition;
the second determining module is specifically used for determining the position of the crack of the aluminum alloy test piece according to the detail coefficient.
9. The sampling device of claim 8, further comprising:
the third determining module is used for taking the signal obtained by carrying out wavelet three-layer decomposition on the temperature data as an input signal;
the transformation module is used for carrying out continuous wavelet transformation on the input signal to obtain the correlation coefficient between the input signal and a wavelet function after each wavelet transformation;
and the fourth determining module is used for determining that the position of the maximum value of the correlation coefficient is the position of the crack of the aluminum alloy test piece.
10. The sampling device of claim 7, wherein the area of the laser heat affected zone is a first area, and the first determining module is specifically configured to determine that a region of the front region of the laser heat affected zone that is one half of the first area is a sampling region.
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