EP4584584A2 - Thermographical component testing - Google Patents

Abstract

The invention relates to a device and a method for thermographically testing a component, comprising an excitation source for generating a transient heat flow in a test sample, an infrared detector array for detecting thermal radiation emitted from a surface of the test sample, a surface scanner, a control device and an evaluation device, wherein the device comprises an inertial measuring unit for detecting movements of the device.

Description

THERMQGRAPHIC COMPONENT TESTING

The invention relates to a device and a method for non-destructive component testing.

Active thermography is known from the prior art as a non-destructive and imaging testing method for material and component characterization. This is based on the thermal excitation of the test body by means of absorption of optical radiation, induction of eddy currents, coupling of mechanical waves or other forms of energy that lead to a time-dependent temperature change in the test body. Infrared sensors - designed as point, line or area detectors - can detect the heat radiation from the test body without contact. Based on the measured temperature field on the component surface, the time-varying heat diffusion process is analyzed and component features can be detected and identified. Well-known technical implementations of active thermography include, for example, laboratory setups on fixed stands or mobile, hand-held or robot-guided testing systems.

It is the object of the present invention to create a device and a method for non-destructive component testing with which deep component features or defects can be assigned to the three-dimensional component geometry with greater reliability. Furthermore, it is an object of the invention to create a device with which non-destructive component testing can be used in a larger field of applications and can be used with improved user-friendliness.

This task is solved by a device and a method according to the claims.

The device according to the invention for thermographic component testing comprises an excitation source for generating an unsteady heat flow in a test object, an infrared detector array for detecting thermal radiation emitted by a surface of the test object, a surface scanner, a control device and an evaluation device, the device having an inertial measuring unit for the detection of Movements included in this device. The device also includes a physical unit for user authentication. What is particularly advantageous is the further development of the device, according to which the evaluation device comprises a geometry detection system for calculating spatial coordinates of the surface of the test object.

According to an advantageous embodiment of the device, it is provided that the geometry detection system is designed to calculate a relative spatial position between the device and the test object.

A further development of the device provides that the infrared detector array of the surface scanner and the inertial measuring unit are arranged relative to one another at defined distances and defined orientations in the device. This has the advantage that flexible and user-friendly applicability of the device can be achieved.

The design of the device is also advantageous, according to which the evaluation device is designed for the program-controlled reconstruction of defects in a test specimen or of material differences or material properties of a test specimen, with the evaluation device generating a time- and location-dependent surface temperature signal Tmess from data from infrared images from the infrared detector array is calculated, and wherein the surface temperature signal Tmess is transformed into a mirror source representation Tsq using a regularization method. This has the advantage that reconstructed component features can be assigned to the true component features (defects, interfaces, etc.) with greater reliability.

The object of the invention is also achieved independently by a method for thermographic component testing of a test object with a device comprising an excitation source, an infrared detector array, a surface scanner, a physical unit for user authentication, a control device and an evaluation device, with the following method steps: authenticating a user, detecting a spatial position and orientation of the device relative to the test object and detecting a surface of the test object with the surface scanner; Generating a transient heat flow in the test specimen through the excitation source; Recording infrared images of the surface of the test specimen with the infrared detector array during a preselected measurement period; Reconstruction of a spatial position of a defect from recorded data from the infrared images by the evaluation device, with the reconstruction of the defect being carried out by the Evaluation device calculates a surface temperature signal Tmess from the data of the infrared images, and the surface temperature signal Tmess is transformed into a mirror source representation Ts _q using a regularization method.

It also proves to be advantageous if a Green's function based on the heat conduction equation is used in the regularization process.

An advantage is the procedure according to which, when reconstructing the spatial position of the defect, additional information from a group comprising a dimensionality of the heat flow, a number of boundary layers in the test specimen, a position of boundary layers in the test specimen, thermophysical material properties or boundary conditions is used .

According to an advantageous development of the method, it is provided that component identification is carried out by the device. This makes a priori information about the test subject available as additional information.

According to an advantageous development of the method, it is provided that user authentication is carried out by the device. This makes the additional information dependent on the device user.

For component identification and user authentication, technologies such as a contactless transmitter-receiver system (radio-frequency identification technologies), optoelectronically detectable fonts, bar codes or multi-dimensional codes (using a camera or scanner), biometric authentication, among others through face, Fingerprint, eye iris or voice recognition, manual authentication using a user interface or card reader, or digital authentication based on cryptographic handshake procedures can be used.

According to an advantageous development of the method, it is provided that an inertial measuring unit is arranged in the device, the infrared detector array of the surface scanners and the inertial measuring unit being arranged relative to one another at defined distances and defined orientations in the device.

The procedure in which the spatial level and orientation of the device relative to the test specimen is measured by the inertial measuring unit is also advantageous. This enables the image sequence to be corrected and stabilized using the inertial measuring unit.

According to an alternative procedure, it is provided that external data sources are taken into account for detecting the spatial position and orientation of the device and for detecting the surface of the test object.

An advantageous embodiment of the method provides that additional information about the component geometry and the material properties of the test specimen are used for optimized discretization of the reconstruction space.

The procedure, according to which the method steps are repeated one or more times, from a different spatial position and orientation of the device relative to the test specimen and results of reconstructions of the spatial position of the defect are superpositioned, provides the advantage of even greater accuracy and reliability Assignment of defects or component features to the three-dimensional geometry of the test specimen is achieved.

The further development of the method, according to which temperature and location-calibrated image data are calculated from the infrared images, also proves to be advantageous.

According to a likewise advantageous procedure, it is provided that the extracted features of the defects can be used for data compression.

For a better understanding of the invention, it will be explained in more detail using the following figures.

They show in a highly simplified, schematic representation:

Fig. 1 shows a device for non-destructive component testing of a test specimen;

Fig. 2 is a view of the device according to Fig. 1, corresponding to a viewing direction towards its sensors or towards its infrared detector array;

3 shows a flowchart of the method for thermographic component testing;

Fig. 4 details of the regularization process according to the “Regularization and Reconstruction” process step in Fig. 3; 5 shows the device when carrying out the thermographic test of the test specimen;

6 shows an illustration of evaluation steps of the measured surface temperature signals carried out using the regularization method based on temporal and spatial temperature profiles;

Fig. 7 evaluation steps of the regularization method of a further application, illustrated by temporal and spatial temperature profiles;

Fig. 8 shows a further exemplary embodiment of a device for non-destructive component testing.

As an introduction, it should be noted that in the differently described embodiments, the same parts are provided with the same reference numbers or the same component names, whereby the disclosures contained in the entire description can be transferred analogously to the same parts with the same reference numbers or the same component names. The position information selected in the description, such as top, bottom, side, etc., is also related to the figure directly described and shown and, in the event of a change in position, these position information must be transferred accordingly to the new position.

1 shows a device 1 for non-destructive component testing of a component or test object 2. The device 1 is suitable for carrying out a method for component testing using active thermography and includes an excitation source 3 and an infrared detector array 4. In addition to an electrical Supply unit 5 is further provided with a control device 6 or a processor unit for controlling the test process and controlling or regulating the components of the device 1 necessary for this. Part of the control device 6 is formed by an evaluation device 7 for program-controlled processing of the measurement signals detected by the infrared detector array 4 or by other sensors. Furthermore, the device 1 comprises a surface scanner 8 for recording the geometric data or the geometric features of the test object 2. Finally, the device 1 is also designed with an inertial measuring unit 9 for detecting the movement of the device 1. Furthermore, the device 1 also includes an operating terminal 10, which also has at least one digital, bidirectional communication interface for providing data or for retrieving additional information from external Data sources included. Optionally, the device 1 can also be equipped with an optical camera or with an optical imaging system 11 (a so-called RGB camera) for the visible wavelength range.

2 shows a view of the device 1 according to FIG. 1, corresponding to a viewing direction of the infrared detector array 4 or a viewing direction corresponding to an optical axis 12 of the infrared detector array 4.

As shown in FIG. 1, the test specimen 2 has an inhomogeneity below a surface 13 in its interior - referred to in simple terms as a defect 14.

Fig. 3 shows, using a flow chart, the process of the thermographic component testing on the test object 2 (Fig. 1). This is a multi-stage signal processing process. In the course of an initial measurement, the surface 13 of the test object 2 is first optically recorded and the initial pose (position and orientation) of the device 1 relative to the test object 2 or its surface 13 is determined. Before the test object 2 is thermally excited with the excitation source 3, one or more static (passive) infrared images of the test object 2 are captured with the infrared detector array 4.

By determining transformation parameters, an image point I(u,v) can be assigned to one or more coordinate points p (Fig. 5). Since there is no movement of the device 1 between the determination of the position of the device 1, the thermal excitation by means of the excitation source 3 and the recording of the thermal response by the infrared detector array 4, this assignment also applies to the temporally dynamic part of the infrared radiation emitted by the test object 2 and therefore does not necessarily have to be carried out during the measurement of thermal excitation and response. The coordinate transformation can be determined by a previously carried out calibration of the infrared detector array 4 and the surface scanner 8 or by image registration methods based on characteristic image features, such as edges or differences in emissivity.

To reduce artifacts in the reconstruction and registration step, the scanner data is consolidated (if necessary, removal of outliers, noise filtering, reduction of image size, reduction of local resolution). Furthermore, a normal vector n _p is created for all relevant coordinate points on the surface 13 of the test object 2 certainly. The normal vectors n _p are always oriented towards the interior of the component (Fig. 5).

After the thermal excitation with the excitation source 3, the thermal response of the test object 2 is recorded for a sufficiently long time by recording infrared images with the infrared detector array 4. The measurement duration and form of excitation determine the desired penetration depth into the test object 2. The image repetition rate when the infrared images are recorded by the infrared detector array 4 determines the resolution in the axial direction of the device 1, that is, in the depth direction of the test object 2.

With the help of the evaluation device 7, the thermal response for each pixel is inversely transformed into a mirror source representation using a so-called regularization. In this illustration, subsurface structures, such as defect 14, are shown as pulse-shaped features in a discrete, equidistant signal I(u,v,w).

3 gives an overview of the measures to be carried out in the thermographic testing procedures as well as their chronological sequence. After the device 1 has been put into operation, the spatial position and the orientation of the device 1 are determined with the help of the inertial measuring unit (IMU). On the other hand, the external geometry of the test object 2 is measured with the help of the surface scanner 8. As measure 100, the measurement data obtained thereby provide information about the geometry as well as the spatial relative arrangement of device 1 and test object 2. The measurements according to measure 100 are preferably carried out permanently, that is to say continuously over the entire time course of the component testing of test object 2. This is particularly advantageous in the event that the device 1 is designed as a hand-held device. Section 101 includes measurements or detections that take place before the thermal excitation of the test object 2. From the thermal excitation with the infrared detector array 4, one or more static (passive) infrared images of the test object 1 are recorded and transformation parameters for the assignment of coordinate points p to respective image points I (u, v) of the infrared images are determined. In a subsequent section 102, the thermal excitation takes place with the aid of the excitation source 3 and at the same time the thermal response is recorded by recording a sequence of infrared images by the infrared detector array 4. The images recorded in the process by the infrared detector array 4 represent surface temperature data Tmess(p) from Points p on the surface 13 of the test specimen 2 as well as the time course of surface temperatures. The surface temperature signals obtained in this way are subjected to an evaluation procedure using the evaluation device 7 in a final section 103. For this purpose, the surface temperature signals Tmess are subjected to a so-called regularization process. This enables a reconstruction of the defect 14 in the test specimen 2.

4 shows a detail of FIG. 3 corresponding to the “Regularization and Reconstruction” process step, further specified in section 103. Following the recording of the thermal response from the surface 13 of the test object 2 with the aid of the infrared detector array 4, a transformation into the mentioned mirror source representation takes place. In order to reconstruct defects 14 that lie on the surface 13 or below the surface 13 or to determine material parameters, the measured surface temperature signal Tmess 6 IR ^A (Nt x Nu * N _v ) is converted into the corresponding mirror source representation Ts _q G IR ^A (N _W x N _u * N _v ) transformed (IR, set of real numbers). Here, N _u and N _v describe the number of pixels of the area detector of the infrared detector array 4 in the u and v directions. The number of time steps for the measurement is represented by Nt and the number of coordinate points in the depth direction is represented by _Nw . In the simplest case, the transformation matrix KG IR ^A (Nt x N _w ) can be represented by a Green's function with the thermal diffusivity oi33 in the following form.

This function corresponds to the fundamental solution of the heat conduction equation. It should also be mentioned at this point that other Green "see functions can also be used based on existing component characteristics and test environment characteristics. With the thermal diffusivity in the depth direction 0133 and with the discrete numerical steps ti = 1 A _t and tj = j A _z and under the use the run variables 1 = {0, 1, 2, ..., Nt-1 } and j = {0, 1, 2, ..., Nw-1 }, the elements of the transformation matrix K, using the ones given above Green's function can be written as follows: Equation 6 (2) ' The term 77 = describes a dimensionless number, where f is a dimensionless number

Scaling parameter for optimizing the quality of the inverse solution and A _t represents the temporal resolution of the surface temperature signal and A _w represents the depth resolution for the mirror source representation.

By mathematically folding the transformation kernel or the transformation matrix K with respect to time and location, possible temporal and spatial excitation patterns can be taken into account. Since the diffusion processes and thus the heat conduction equation are considered on a macroscopic level, the discrete form results in a linear matrix equation Tmess = K Ts _q and therefore a linear inverse problem. It can also be noted that equation (2) has no dependence on the transversal coordinates u and v. Solving the matrix equation Tmess = K Tsq therefore represents a local inverse problem. This means that the measured temperature signal can be transformed locally (pixel by pixel) into the corresponding mirror source representation.

For the transformation, a very ill-posed inverse problem must be solved due to the entropy production during heat diffusion. Different regularization methods can be used for this. It should also be noted that the inverse problem can also be solved using machine learning approaches.

In the present case, the inverse problem is solved in the evaluation process using additional information, such as positivity or sparsity (solution matrix is sparse). The calculated mirror source distribution as a function of depth reveals the characteristics of the measured surface temperature signal with respect to identical interfaces (surface 13) and defect interfaces in the form of sources (positive amplitude) and sinks (negative amplitude). The sources and sinks can arise, for example, from defects or the prevailing boundary conditions, whereby features due to defects can be clearly distinguished from features due to the boundary conditions. The boundary conditions or test environment characteristics can be described by thermal conduction, thermal radiation or convection or a mixture of these effects. In addition, adiabatic boundary conditions only provide positive mirror source amplitudes. Thermal radiation and convection can provide both negative and positive mirror source amplitudes (Figs. 6, 7). Based on the defect characteristics, the depth of the defect 14 can only be roughly estimated. In addition, due to the boundary conditions and the observation surface, the amplitudes do not provide any relevant information regarding the defect 14 and the position of the rear wall. Therefore, the amplitudes due to the defect 14 and the back wall are extracted. A noise-free defect temperature signal is then calculated from the resulting signal. By eliminating the noise signal, the depth of the defect can now be determined more precisely by evaluating the maximum defect temperature signal.

From the calculated defect depth, a replacement mirror source signal I 6 IR ^A (N _U x N _v x N _w ) can then be determined for each pixel of the infrared detector array 4 and each defect signal for a multi-dimensional defect representation (see Fig. 6f and Fig. 6h).

Furthermore, if the thermal effusivity of the base material e2 is greater than the thermal effusivity of the defect material ei, then on the depth scale of the mirror source distribution the positive amplitude (source) can be seen before the negative amplitude (sink) (Fig. 6c, 6d). If ei is greater than e2, then on the depth scale there is first a sink and then a source (Fig. 7).

The described transformation of the measured temperature signal into the corresponding mirror source representation does not take into account transverse diffusion processes or geometric information of the possibly anisotropic and complex shaped test specimen 2.

In a further evaluation step and with the help of the geometric information of the test specimen 2 recorded by the surface scanner 8 in conjunction with a known thermal diffusivity tensor a, local filtering can be carried out. This enables a more accurate reconstruction of the true interface dimensions. This local filtering can also be performed by solving an inverse problem. This further and optional evaluation step is particularly recommended for defects 14 that lie deep below the surface 13 of the test specimen 2 and when the ratio of the thermal conductivities in the transverse direction and depth direction is large.

As shown in FIG. 4, the surface temperature signals go through a sequence of several steps for their evaluation, regularization and defect reconstruction. A first step 111 corresponds to the detection of the surface temperature signal _Tme ss. In the subsequent step 112, the measured value is transformed Surface temperature signal Tmess into the corresponding mirror source distribution according to the linear matrix equation Tmess = K Ts _q . In a subsequent step 113, defect features are extracted. In step 114, the defect temperature signal is calculated based on the extracted defect features. The following step 115 corresponds to determining the real defect depth from the calculated defect temperature signal. The real defect depth is used in a subsequent step 116 to calculate a replacement mirror source signal. In a final step 117, local filtering takes place based on the measured geometric information of the test object 2 and information about the known thermal diffusivity tensor. Based on the results obtained, the size determination of the defect 14 in the test specimen 2 can be improved or optimized.

5 shows the device 1 carrying out the thermographic test of the test specimen 2.

With the help of the excitation source 3, the test object 2 has already been thermally excited and the thermal response of the component is detected by the infrared detector array 4 of the device 1 over a predetermined measuring period and the geometry information is recorded with the help of the surface scanner 8 of the device 1 (Fig. 1, 2). This means that a sequence of thermal images is recorded by the infrared detector array 4. Based on this, a 3D depth signal Ik(u,v,w) is reconstructed from the at least one spatial level k of the device 1. As a prerequisite, there must be at least one image position (u _p *, v _p *) for a surface point pi and an associated, normalized normal vector n _Pi . Relevant replacement feature positions from the depth signal Ik(u _p *,v _p *,w) are projected into a global coordinate system.

With known material parameters (for example in the form of a thermal conductivity sensor) and with normal vectors implicitly known or manually defined from the surface 13, a relevant substitute feature P in the global coordinate system is composed of its position and its intensity. According to FIG. 5, the projection of replacement feature positions of one or more data sets I(u,v,w) into the global coordinate system leads to an aggregation of replacement features at or near the position of the physical component feature, provided that the replacement features belong to the same component feature (defect 14). . This is the case, for example, with adjacent surface points from one measurement or congruent or adjacent surface points from several measurements (i.e. a multiple implementation of steps 101, 102 and 103 like. Fig. 3) from congruent or different spatial positions of the device 1. Such an aggregation of replacement features is also the case if surface points from several measurements (i.e. a multiple implementation of steps 101, 102, 103 like. Fig. 3) from opposite spatial positions of the device 1, if the component to be tested or the test object 2 is sufficiently thin or the measurement of the temperature response is sufficiently long. In such a case, the opposite, invisible component surface is visible as a substitute feature in every measurement.

The thermographic measurements to be superimposed may differ from each other with regard to all common measurement parameters, since these can be taken into account as preliminary information when reconstructing and positioning the replacement features. These measurement parameters can be: the temporal and spatial form of excitation by the excitation source 3; the measurement frequency (corresponding to the recording of thermal images by the infrared detector array 4); the spatial resolution and the distance of the surface 13 of the test object 2 or the spatial position of the device 1.

When the transformed data is stored in the form of a point cloud (ie the coordinates are explicitly available), the depth resolution can be defined independently of the resolution of the geometry detection by the surface scanner 8. In addition to the replacement feature position, the replacement feature intensity can also be assigned to a data point. This enables improved visualization of the features of the test specimen 2, for example by texturing point clouds or rendered surfaces of the features or defect 14. This also enables intensity values to be specified if the result data is in a three-dimensional, Cartesian grid with implicit coordinates ( Volume pixels, or “voxels” for short, should be present. Here, the replacement feature positions of relevant data points are transferred to the grid by interpolation. By systematically positioning the replacement features in the global coordinate system, further reconstruction and segmentation methods can be used in a subsequent step, which enable more precise localization and visualization of the component features. The introduction of geometric (surface points, normal directions, preliminary information on the characteristics of test specimen 2 such as orientation, size and shape) and material-specific additional information also makes it possible to use known methods based on superposition, triangulation, lateration, regression and machine learning.

The method for the thermographic reconstruction of the defect 14 will be explained in more detail below with reference to FIGS. 6 and 7.

6 illustrates the evaluation procedure for reconstructing a defect 14 and for determining material parameters of the test specimen 2. The illustration a) shows an example of a defective test specimen 2, where the thermal efficiency of the base material e2 is greater than the thermal efficiency of the defect material ei. Diagram b) shows a characteristic temperature signal for a measurement in reflection mode in the defect area. Diagram d) shows the mirror source distribution calculated from this. Diagram c) shows the extracted defect and component features, diagram e) the defect temperature signal calculated from this and diagram f) the corrected depth distribution of the mirror sources. Illustrations g) and h) show a 2D visualization of the extracted defect and component features and the corrected depth distribution of the mirror sources.

The method steps described correspond to the measures already presented in FIG. 4. The expression of component features of the test specimen 2 depends on the thermal impedances of the base material and the defect material, the thermal impedances being formed by the respective effusivities, which in turn depend on the thermal conductivity k, the specific heat capacity c _p and the material density p (Fig. 6a). The greater the difference in thermal impedances, the more clearly the characteristic component features of the test object 2 are displayed. Since the position of the image points in space is known, the individual feature intensities and positions can be used for more precise feature localization and quantification through appropriate overlay. Component features under the surface 13 of the test specimen 2, which are imaged, for example, by a defect interface, can be due to their spatial expansion occurs in several adjacent pixels, whereby at the same time a distortion of the spatial expansion occurs due to heat diffusion. 6b shows an example of a measured surface temperature signal as a function of time for the reflection (pulse-echo) configuration (excitation source 3 and infrared detector array 4 on the same side) based on a very short excitation pulse in the form of a Dirac delta distribution regarding time.

However, the described procedure for thermographic defect reconstruction is applicable to all temporal and local thermal excitation functions, as well as in the case of a transmission configuration (excitation source 3 and infrared detector array 4 on opposite sides).

To ensure that all relevant component features are recorded, a test measurement can be carried out. With a test measurement, the thermal diffusion time td and thus the measurement time _tme ss can be determined.

The temperature signal measured after thermal excitation can be transformed locally, i.e. pixel by pixel, into a corresponding mirror source representation. The diagram, shown in Fig. 6d, illustrates the calculated mirror source distribution as a function of depth and reveals the characteristics of the measured surface temperature signal related to component interfaces and defect interfaces in the form of sources (detected by positive amplitudes) and sinks (detected by negative amplitudes). By extracting the amplitudes due to the defect 14 and the back wall, the diagram as shown in Fig. 6c is finally obtained.

A noise-free defect temperature signal is then calculated from the resulting signal. By evaluating the maximum defect temperature signal of the filtered defect temperature signal, the defect depth can then be determined more precisely. This is explained by the representations in FIGS. 6e and 6g, with the diagram in FIG. 6g showing a cross section through the surface 13 of the test object 2 with the corresponding mirror source distribution.

From the calculated defect depth, a replacement mirror source signal IE IR ^A (N _U x N - x N _w ) can then be determined for each camera pixel and defect signal for a multi-dimensional defect representation, as illustrated by the representations in FIGS. 6f and 6h. At 6, the thermal effusivity of the base material e2 is greater than the thermal effusivity of the defect material ei.

7 illustrates the evaluation procedure for reconstructing defects 14 and determining material parameters. In contrast to the case discussed in FIG. 6, the thermal efficiency of the base material e2 is smaller than the thermal efficiency of the defect material ei. The temperature signal was recorded in reflection mode. Diagram a) shows the corresponding mirror source distribution in the defect area. Diagram b) shows the extracted defect and component features and diagram d) shows the defect temperature signal calculated from them. Diagram c) shows the corrected depth distribution of the mirror sources. 7 therefore shows an example of the thermographic defect reconstruction for a case when the effusivity of the defect material el is greater than the effusivity of the base material e2. In this case, there is first a sink and then a source on the depth scale (Fig. 7a and 7b).

For a consistent registration of new thermography data and the reconstruction of component features of the test object 2 from this data, the geometric features recorded by the surface scanner 8 (for example by TOF camera, profile scanner, using the device itself by overlaying image data from different poses) and the position estimates from the inertial measurement unit are used. The position estimation of the sensor in the original coordinate system occurs continuously.

A preferred embodiment of the device 1 is that of a hand-held device on which all required components are positioned at defined, relative distances from one another.

In an alternative embodiment variant of the device 1, the spatial position relative to the component surface or the surface 13 of the test object 2 is provided by external data sources, for example by a single- or multi-axis robot that moves the device 1.

In a further alternative embodiment of the device 1, the surface 13 of the test object 2 and the inertial position of the device 1 relative to the surface 13 are provided by external data sources, for example by a CAD model of the test object 2. In a likewise alternative embodiment, the device remains 1 at rest and the Examinee 2 is moved using suitable facilities. The relative position of the device 1 is determined by the manipulation device of the test object 2 and made available to the device 1 for evaluation.

A further possible application or embodiment of the device for thermal component testing will be described below with renewed reference to the representation of the device 1 according to FIG. 1. In this case - preceding the process steps already described - an identification of the test object 2 is carried out at the beginning. This means that the control device 6 or the evaluation device 7 is designed to detect or automatically read an identifier 15 that is coded in some form and is attached to the surface 13 of the test object 2. This enables a later clear assignment of the results of the thermographic component test carried out to the respective test object 2. Images that were preferably taken by the infrared camera or by the infrared detector array 4 from the identifier 15 serve as the basis for this. Alternatively, it is also possible to record the images required for component identification using the optical camera 11. The control device 6 or the evaluation device 7 is designed for program-controlled decoding of the image information data and identification of the identifier 15. In this embodiment variant of the device 1, the identifier 15 can be formed by optoelectronically detectable fonts or one- or multi-dimensional codes (such as a bar code or a QR code).

In a preferred embodiment of the device 1, a program-controlled user test 16 is provided in the control device 6. With this design variant of the device 1, it is therefore possible to restrict its commissioning to a group of people authorized to do so. For example, user authentication can take place by checking a password entered by the user via the operating terminal 10. Alternatively, user authentication can also be based on technologies such as facial recognition or eye-iris recognition. Alternatively, the infrared camera or the infrared detector array 4 or the optical camera 11 of the device 1 are available to record corresponding images. The program-controlled user check 16 of the device 1 could alternatively also be based on other technologies such as reading an RFID element with appropriate readers or scanners as well as the recognition of fingerprints. The user test 16 of the device 1 for image recognition corresponds to the technology used or designed to decode corresponding detection signals from a corresponding reading device. A further exemplary embodiment of user identification could also provide for two- or multi-factor authentication.

A further embodiment variant of a device 1 for thermographic component testing will be described below with reference to FIG. 8 shows a device 1 for the non-destructive component testing of a test object 2, which also includes two excitation sources 3 for generating a heat flow in the test object 2 and a control device 6 with an evaluation device 7. In this example of the device 1, two infrared detector arrays 4 are provided for detecting or recording the thermal radiation emitted by the surface 13 of the test object 2. This allows a combined evaluation of the surface temperature signals obtained from the respective infrared images of the two infrared detector arrays 4, whereby a greater spatial or temporal resolution can subsequently be achieved.

On the other hand, the type of thermal excitation of the surface 13 of the test object 2 caused by the excitation sources 3 can also achieve an improvement in the quality of the component testing results determined using the method. One possibility for this is to provide a filter 17 in the respective beam path of the two excitation sources 3. The two filters 17 select a narrower spectral range from the infrared radiation generated by the two excitation sources 3.

Another embodiment variant provides for a focusing device or a focusing lens 18 to be provided in the beam path of the respective excitation source 3. The focusing lenses 18 allow the component testing method to be carried out in such a way that the thermal excitation with the infrared radiation can be carried out in a locally concentrated manner on the surface 13 of the test object 2. By appropriately designing or adjusting the focusing lenses 18, the heat input can, for example, be concentrated on a surface area that is as point-shaped or linear or stretch-shaped as possible. This is advantageous for the evaluation method to be used in that the initial conditions of the heat flow generated in the test object 2 can be determined or specified more precisely.

The exemplary embodiments show possible embodiment variants, although it should be noted at this point that the invention does not apply to the specifically illustrated embodiment variants of the same is limited, but rather various combinations of the individual design variants with one another are possible and this possibility of variation lies within the ability of the person skilled in the art working in this technical field due to the teaching on technical action through the subject invention.

The scope of protection is determined by the claims. However, the description and drawings must be used to interpret the claims. Individual features or combinations of features from the different exemplary embodiments shown and described can represent independent inventive solutions in their own right. The task underlying the independent inventive solutions can be found in the description.

All information on value ranges in this description should be understood to include any and all sub-ranges, e.g. the information 1 to 10 should be understood to include all sub-ranges, starting from the lower limit 1 and the upper limit 10 , i.e. all subranges start with a lower limit of 1 or greater and end with an upper limit of 10 or less, e.g. 1 to 1.7, or 3.2 to 8.1, or 5.5 to 10.

For the sake of order, it should finally be pointed out that in order to better understand the structure, elements have sometimes been shown out of scale and/or enlarged and/or reduced in size.

List of reference symbols

Device 100 Measure test object 101 Excitation source section 102 Infrared detector array section 103 Supply unit section 111 Step control device 112 Step evaluation device 113 Step surface scanner 114 Step inertial measuring unit 115 Step operating terminal 116 Step camera 117 Step optical axis Surface defect identifier

User review filtering

Focusing lens

Claims

P atent claims 1. Device (1) for thermographic component testing, - comprising an excitation source (3) for generating a transient heat flow in a test specimen (2), - an infrared detector array (4) for detecting one of a surface (13) of the test specimen (2) emitted thermal radiation, - a surface scanner (8), - a control device (6) and an evaluation device (7), characterized in that the device (1) comprises an inertial measuring unit (9) for detecting movements of the device (1). 2. Device (1) according to claim 1, characterized in that a geometry detection system is designed to calculate spatial coordinates of the surface (13) of the test specimen (2). 3. Device (1) according to claim 2, characterized in that the geometry detection system is designed to calculate a relative spatial position between the device (1) and the test specimen (2). 4. Device (1) according to one of the preceding claims, characterized in that the infrared detector array (4), the surface scanner (8) and the inertial measuring unit (9) are arranged relative to one another at defined distances and defined orientations in the device (1). are. 5. Device (1) according to one of the preceding claims, characterized in that two infrared detector arrays (4) are designed to detect the thermal radiation emitted by a surface (13) of the test object (2). 6. Device (1) according to one of the preceding claims, characterized in that two excitation sources (3) are formed. 7. Device (1) according to one of the preceding claims, characterized in that the excitation source (3) comprises a filter (17) for selecting a part of a spectral range of the infrared radiation. 8. Device (1) according to one of the preceding claims, characterized in that the excitation source (3) comprises a focusing lens (18). 9. Device (1) according to one of the preceding claims, characterized in that the control device (6) and / or the evaluation device (7) for program-controlled identification of the test object (2) by decoding a on the surface (13) of the test object (2 ) attached identifier (15) is formed. 10. Device (1) according to one of the preceding claims, characterized in that a user check (16) is included and the user check (16) is designed for program-controlled authentication of a user, wherein a method for authenticating the user is used, which consists of a Group comprising entering a password, performing facial recognition or eye-iris recognition, detecting a fingerprint, reading an RFID element, or reading a user card provided with a magnetic stripe is selected. 11. Device (1) according to one of the preceding claims, characterized in that the evaluation device (7) is designed for the program-controlled reconstruction of a defect (14) in a test specimen (2), wherein the evaluation device (7) uses data from infrared images of a surface temperature signal Tmess is calculated in the infrared detector array (4), and the surface temperature signal Tmess is transformed into a mirror source representation Ts _q using a regularization method. 12. Method for thermographic component testing of a test object (2) with a device (1) comprising an excitation source (3), an infrared detector array (4), a surface scanner (8), a control device (6) and an evaluation device (7), with the following procedural steps: - Detecting a spatial position and orientation of the device (1) relative to the test specimen (2) and detecting a surface (13) of the test specimen (2) with the surface scanner (8); - Generating a transient heat flow in the test specimen (2) through the excitation source (3); - Recording infrared images of the surface (13) of the test specimen (2) with the infrared detector array (4) during a preselected measurement period; - Reconstruction of a spatial position of a defect (14) from recorded data of the infrared images by the evaluation device (7), - characterized in that in order to reconstruct the defect (14), a surface temperature signal Tmess is calculated by the evaluation device (7) from the data of the infrared images, - and that the surface temperature signal Tmess is transformed into a mirror source representation Ts _q , where Tmess = K Tsq, and where K is a transformation matrix. 13. The method according to claim 12, characterized in that substitute mirror sources and/or substitute features are calculated from the mirror source representation Tsq. 14. The method according to claim 13, characterized in that a regularization method or a machine leaming approach is used to calculate the replacement mirror sources and / or replacement features. 15. The method according to claim 14, characterized in that Green's functions based on the heat conduction equation are used in the regularization process. 16. The method according to any one of claims 12 to 15, characterized in that when reconstructing the spatial position of the defect (14), additional information from a group comprising a dimensionality of the heat flow, a number of boundary layers in the test specimen (2), a Position of boundary layers in the test specimen (2), thermophysical material properties or boundary conditions, is used. 17. The method according to any one of claims 12 to 16, characterized in that an inertial measuring unit (9) is arranged in the device (1), the infrared detector array (4) being the surface scanner (8) and the inertial measuring unit ( 9) are arranged relative to each other at defined distances and defined orientations in the device (1). 18. The method according to one of claims 12 to 17, characterized in that the spatial position and the orientation of the device (1) and test object (2) relative to one another is measured by the inertial measuring unit (9). 19. Method according to one of claims 12 to 18, characterized in that external data sources are taken into account for detecting the spatial position and orientation of the device (1) and for detecting the surface (13) of the test object (2). 20. The method according to one of claims 12 to 19, characterized in that in the step of recording the infrared images of the surface (13) of the test object (2), the infrared images are recorded by two infrared detector array cameras (4). 21. The method according to any one of claims 12 to 20, characterized in that in the method step of generating a heat flow in the test object (2) through the excitation source (3), infrared radiation emitted by the excitation source (3) is reduced through a filter (17). Spectral range of the infrared radiation is selected. 22. The method according to any one of claims 12 to 21, characterized in that in the method step of generating a heat flow in the test object (2) through the excitation source (3), infrared radiation emitted by the excitation source (3) is passed through a focusing device or a focusing lens ( 18) acts on the surface (13) of the test specimen (2) in a manner that is as concentrated as possible in points and/or lines or stretches. 23. Method according to one of claims 12 to 22, characterized in that additional information about the component geometry and the material properties of the test specimen (2) are used for optimized discretization of the reconstruction space. 24. The method according to one of claims 12 to 23, characterized in that the method steps are repeated one or more times, from a different spatial position and orientation of the device (1) relative to the test specimen (2) and results of reconstructions of the spatial position of the defect (14) can be superpositioned. 25. Method according to one of claims 12 to 24, characterized in that temperature- and location-calibrated image data are calculated from the infrared images. 26. Method according to one of claims 12 to 25, characterized in that the extracted features of the defects (14) or boundary layers are used for data compression. 27. The method according to one of claims 12 to 26, characterized in that the method step of detecting the spatial position and orientation of the device (1) relative to the test object (2) is preceded by a component identification by detecting an identifier attached to the test object (2). (15) is carried out. 28. The method according to one of claims 12 to 27, characterized in that the method step of detecting the spatial position and orientation of the device (1) relative to the test object (2) is preceded by user authentication, the user authentication comprising a method that is selected from a group comprising entering a password, performing facial recognition or eye-iris recognition, detecting a fingerprint, reading an RFID element, or reading a user card provided with a magnetic stripe.