JP5574261B2 - Flaw detection method and flaw detection apparatus - Google Patents

Description

  The present invention relates to a nondestructive material flaw detection technique for detecting defects in an inspection object by measuring the temperature of the inspection object.

  An infrared thermography method is known as one of methods for detecting defects in an inspection object by nondestructive inspection. Among them, the pulse thermography method is the most frequently used method. In the pulse thermography method, the surface of the inspection object is instantaneously heated by a flash lamp or the like, and the subsequent surface temperature is measured by an infrared camera or the like. When there is a defect inside, the flow of heat propagating to the inside changes, and a local temperature abnormality occurs on the surface. By detecting this temperature abnormality, an internal defect can be detected.

  The pulse thermography methods disclosed in Patent Document 1 and Non-Patent Document 1 have a short time required for flaw detection and are easy to perform a wide range of inspections. It is being advanced.

JP-A-2005-274202

T. Sakagami and S. Kubo, Application of pulse heating thermography and lock-in thermography to quantitative nondestructive evaluations, Infraredphysics and Technology 43 (2002) 211-218 X.Maldague and S.Marinetti, Pulse phase infrared thermography, J.Appl.phys., Vol.79 (5), 1 March 1996 2694-2698

  However, the pulse thermography method has a drawback that only defects near the surface can be detected. In order to improve such a drawback of the pulse thermography method, a pulse phase thermography method as disclosed in Non-Patent Document 2 has been studied.

  The pulse phase thermography method is performed using data representing the relationship between the temperature of the surface of the object to be inspected and time obtained by the same experimental method as the pulse thermography method. In the pulse phase thermography method, the data representing the relationship between the phase and the frequency is calculated by performing Fourier transform on the data representing the relationship between the temperature and the time on the surface of the inspection object. Then, by selecting a frequency (inspection frequency) and observing an image displaying a phase value at the frequency, a defect inside the inspection object is visually found.

  Conventionally, there has been a tendency to perform inspection in a short time by increasing the sampling frequency representing the number of times of temperature acquisition per second when acquiring the temperature of the surface of the inspection object using an infrared camera. Accordingly, the inspection frequency selected to display the phase is also high. For example, the inspection frequency in Non-Patent Document 2 is 1.6 Hz at the minimum. Since the relationship between the inspection frequency and the depth of the detectable defect was not clear, the conventional pulse phase thermography method did not select the inspection frequency from the viewpoint of detecting the defect at a deep position.

  An object of the present invention is to detect a defect at a deep position by selecting an inspection frequency in the pulse phase thermography method.

  In order to achieve the above object, the present invention provides a heating step of pulse heating the surface of an object and a plurality of the inspection objects after heating at a set sampling frequency at a set time by a temperature detection means. A temperature detection step for detecting the surface temperature of the part, and data processing for performing a Fourier transform on the data indicating the relationship between the elapsed time since heating and the surface temperature, and converting the data to a data indicating the relationship between the frequency and the phase And a step of displaying the phase value at the set inspection frequency as an image, wherein the temperature detecting step extends the set time to lower the inspection frequency, and / or Lowering the sampling frequency, and the displaying step lowers the inspection frequency, thereby reducing the normal frequency. There is provided a testing method which comprises the step of displaying to visible the difference between the phase values in eine and defect. There is also provided a flaw detection apparatus for carrying out this method.

  By implementing the present invention, it becomes possible to detect a defect located at a deeper position than when the conventional technique is implemented.

It is the schematic which shows one Embodiment of the flaw detection system for implementing a pulse phase thermography method. It is a flowchart which shows the procedure for implementing the flaw detection system shown by FIG. It is the schematic of the axis | shaft object model used in the simulation by the finite element method performed in order to investigate the relationship between the inspection frequency in the pulse phase thermography method, and the depth of the detectable defect. It is a table | surface which shows the physical characteristic of the axis | shaft object model of FIG. It is a graph which shows the time change of the thermal load given to the undersurface of the axis object model as a heat source in simulation. It is a graph which shows the relationship between the phase and inspection frequency in the simulation using the thermophysical value of CFRP. It is a graph which shows the relationship between the depth of a defect, and the inspection frequency from which a phase difference becomes the maximum. It is a graph which shows the relationship between the phase and inspection frequency in the simulation using the thermophysical property value of an acrylic resin board. 1 is an overall photograph of a nondestructive material flaw detector according to an embodiment of the present invention. It is a photograph of the CFRP test piece used for verification experiment by one Embodiment of this invention. It is the schematic of the defect part of the CFRP test piece used for verification experiment by one Embodiment of this invention. It is an image which shows the relative value of the phase in test | inspection frequency 0.1Hz. It is an image which shows the relative value of the phase in test | inspection frequency 0.02Hz.

  An embodiment of a nondestructive material flaw detection data conversion method and a nondestructive material flaw detection device according to the present invention will be described below with reference to the drawings.

  In the pulse phase thermography method, for example, a flaw detection system shown in FIG. 1 is used. The procedure for implementing this technique is shown in FIG. First, the inspection object 01 is heated by heating means 02 such as a xenon flash lamp (step 202). Then, the temperature of the heated inspection object 01 is measured by the temperature measuring unit 03 such as an infrared camera, and data indicating the relationship between time and temperature is acquired (step 204). The acquisition of this data is performed by repeating the measurement of the temperature of the inspection object 01 at a preset time interval (sampling frequency) at a preset time. The temperature is measured at multiple points. Specifically, the temperature may be measured for each point having a constant interval in a two-dimensional plane, or at a point having a constant interval arranged in a line on the surface of the inspection object. The acquired data may be stored in storage means such as a ROM, a RAM, and a hard disk. The heating means 02 and the temperature measuring means 03 are desirably controlled by the computer 04.

  When data indicating the relationship between time and temperature is acquired, a Fourier transform is performed on the data to calculate data indicating the relationship between phase and frequency (step 206). The Fourier transform is performed on the acquired data using a processor. Since the acquired data is discrete, discrete Fourier transform is performed, but the Fourier transform can also be performed by fitting an analytical function and performing continuous Fourier transform.

The discrete Fourier transform is performed based on the following formulas 1 and 2.
Here, F _n represents a conversion result (frequency component, complex intensity) at a frequency n times the value obtained by dividing the sampling frequency by twice the sampling number N. Re _n represents the real part of the conversion result, and Im _n represents the imaginary part of the conversion result. T is the temperature of the kth sampling. A _n represents the intensity of the converted result, [Phi _n, represents the phase of the conversion result. In discrete Fourier transform, the frequency range after transformation is determined by the sampling frequency and the number of acquired data. The minimum value f _min and maximum value f _max of the frequency after conversion are obtained by using the sampling frequency f _s and the number N of acquired data.
It is expressed.

  For the data indicating the relationship between the phase and frequency obtained by Fourier transform, the user selects an inspection frequency using a user interface such as a keyboard connected to a computer (step 208), and the selected inspection is performed. The phase at each position of the inspection object 01 is visualized by displaying an image of the phase at the frequency with the display means 06 such as a monitor (step 210). Data represents the inspection position of the inspection object 01 on the image plane, and can be visualized in such a manner that the phase is represented by saturation, color shading, or the like. Fourier transform and phase visualization are performed by executing data analysis software (program) 05 on a computer as data processing means.

  As another aspect, the relative value of the phase may be displayed. That is, the phase of each part is compared, and when a phase of a certain part is different from the phase of another part, it can be seen that a defect exists in the certain part. The phase of each part may be compared by the user confirming the phase displayed in the image, or by a computer, for example, a threshold value in which the difference between the phase of one part and the other part is determined in advance. Depending on whether or not, it may be performed automatically.

In order to investigate the relationship between the display frequency and the depth of detectable defects in the pulse phase thermography method, a simulation using the finite element method was performed. As a simulation model, a flat plate model shown in FIG. 3 was used. The flat plate model of FIG. 3 is a disk-shaped object having a radius of 50 mm with the left end of the figure as the central axis. In order to analyze the relationship between the depth of the defect and the inspection frequency, simulation was performed by changing the plate thickness D of the flat plate model from 0.2 mm to 6 mm. The boundary of the flat plate model is set to 4.7 W / m ² · K and 0.9 in consideration of heat transfer and heat radiation to the outside of the flat plate model. The value of CFRP (Carbon fiber reinforced epoxy matrix composite) shown in FIG. 4 was used as the thermophysical property value of the inspection object. Considering the light emission characteristics of the flash lamp in the experiment, the heat load having the time change shown in FIG. 5 is uniformly added to the lower surface of the flat plate model, and the time and temperature at the center of the flat plate model surface after the heat load are The data showing the relationship was calculated by simulation. The Fourier transform was performed on the data indicating the relationship between the time and the temperature thus calculated, and data indicating the relationship between the phase and the frequency was obtained.

  Discrete Fourier transform was applied to the Fourier transform in the above simulation, the sampling frequency was 10 Hz, and the number of data acquisition points was 4096 (data acquisition time 409.6 seconds). Assuming a semi-infinite plate thickness when the inspection object is healthy, the difference between the phase value of each plate thickness (from 0.2 mm to 6 mm) and the phase value of the semi-infinite plate thickness was calculated. The calculation results are shown in FIG.

  By using Equations 3 and 4, the frequency range of FIG. 6 is derived from 0.0024 Hz to 5.0 Hz.

  Focusing on the curve showing the relationship between the phase value and the frequency when there is a defect at a depth of 2 mm in FIG. 6, the value of this curve is not 0 at an inspection frequency of 0.050 Hz or less. The phase difference can be detected during Therefore, it can be seen from FIG. 6 that a defect present at a depth of 2.0 mm can be detected at an inspection frequency of 0.0024 Hz to 0.050 Hz. Similarly, when attention is paid to the curve in FIG. 6 where there is a defect at a depth of 3 mm, the phase difference from the normal value can be detected at an inspection frequency of 0.020 Hz or less. Therefore, it can be seen from FIG. 6 that a defect at a depth of 3.0 mm can be detected at an inspection frequency of 0.0024 Hz to 0.020 Hz. Therefore, from FIG. 6, it can be confirmed on the simulation that the defect at a deeper position can be measured as the inspection frequency is lower.

FIG. 7 is a graph showing the relationship between the plate thickness and the frequency (f _dmax ) at which the absolute value of the phase difference is maximum, created based on the results of FIG. The solid line in FIG. 7 is an approximate straight line using the least square method, and is represented by the following equation.
It can be seen from FIGS. 7 and 5 that f _dmax is taken at a lower frequency as the position of the defect is deeper. For example, when calculated based on Equation 5, f _dmax for a defect located at a depth of 5 mm is 0.0015 Hz, and f _dmax for a defect located at a depth of 10 mm is 0.00052 Hz. Therefore, by using a lower inspection frequency, it is possible to detect a defect located deeper. From Equation 3, the inspection frequency can be lowered by decreasing the sampling frequency or increasing the sampling number (data acquisition time).

Moreover, although the above-mentioned simulation and experiment used CFRP as the object to be inspected, the depth of detectable defects can be improved by using the present invention for other materials such as resin materials or metal materials. Can be made. For example, the above simulation was performed on an acrylic resin plate (density: 1190 kg / m ³ , thermal conductivity: 0.19 W / (m · k), heat capacity: 1470 J / (kg · K)) in FIG. Results are shown. From FIG. 8, it can be seen that the lower the inspection frequency, the phase difference occurs even at the deeper position, and the deeper position can be inspected. This shows that the present invention is an effective flaw detection method and flaw detection apparatus for various materials.

  Next, in order to confirm the depth of the defect that can be detected for each inspection frequency by the pulse phase thermography method, an experiment was performed on a CFRP test piece. The flaw detection system used in the experiment is a thermo inspector manufactured by Nippon Kraut Kramer. A schematic perspective view of an overall photograph of this apparatus is shown in FIG. The thermo inspector has SC4000 which is an infrared camera manufactured by FLIR as temperature measuring means, and has two 1000J xenon lamps as heating means. In addition, a 200 × 200 × 6 mm plain weave CFRP laminate shown in FIG. 10 was used as a test piece. In FIG. 4, the thermophysical value of a test piece is shown. In the test piece, a flat bottom hole having a diameter d of 10 mm was formed as a defect, and the depth D of the defect from the flash heating surface shown in FIG. 11 was changed from 0.2 mm to 4.0 mm.

  The experiment was performed by flash heating the specimen with a xenon lamp and measuring the temperature of the specimen with an infrared camera. The sampling frequency of the infrared camera was 10 Hz, and the number of data acquisition points was 4096 (data acquisition time 409.6 seconds). Data representing the relationship between temperature and time acquired by an infrared camera was subjected to discrete Fourier transform to calculate data representing the relationship between phase and frequency. FIG. 12 shows data indicating the phase when the inspection frequency of data representing the relationship between the phase and the frequency is 0.1 Hz. FIG. 13 shows the phase data when the inspection frequency is 0.02 Hz. In FIG. 12, since the color in the region having a defect at a depth of 1.6 mm is different from the color of the other background region, the defect at a depth of up to 1.6 mm is detected at an inspection frequency of 0.1 Hz. It is understood that is possible. On the other hand, in FIG. 13, since the color in the region having a defect at a depth of 4.0 mm is different from the color of the other background region, the defect at a depth of 4.0 mm at an inspection frequency of 0.02 Hz. Can be detected. Therefore, from FIG. 12 and FIG. 13, it has been confirmed experimentally that the defect at a deeper position can be measured as the inspection frequency is lower.

  From the above simulation and experiment, it can be seen that in the pulse phase thermography method, the defect detection capability in the depth direction can be improved by lowering the inspection frequency. The present invention provides a flaw detection method and a flaw detection apparatus that improve the defect detection capability in the depth direction by utilizing the newly clarified property.

  The inspection frequency that can be displayed after the Fourier transform can be reduced by reducing the sampling frequency, increasing the number of acquired data, or both from Equation 3. As a result, even if there is a defect at a deep position that could not be detected in the past, there is a difference between the phase value in the part where the inspection object is normal and the phase value in the part where the inspection object has a defect, By detecting such a difference in phase value, it is possible to identify a portion where a defect exists.

  In particular, when the sampling frequency is reduced, the inspection frequency can be lowered without increasing the number of acquired data. Therefore, the inspection frequency can be lowered without increasing the capacity of the data recording medium required for storing the acquired data, and defects at deep positions that could not be detected conventionally can be detected. In addition, when the sampling frequency and the number of acquired data are determined in advance from Equation 3, the inspection frequency is minimized when the sampling frequency is divided by the number of acquired data, and defect detection under such conditions is performed. The maximum possible depth.

01 Inspection object 02 Heating means 03 Temperature measuring means 04 Heating means / temperature measuring means control computer 05 Data analysis software 06 Display means for displaying result image

Claims (12)

A heating step for pulse heating the surface of the object;
A temperature detection step of detecting surface temperatures of a plurality of portions of the inspection object after heating at a set sampling frequency at a set time by a temperature detection means;
A data processing step for performing Fourier transform on the data indicating the relationship between the elapsed time since heating and the surface temperature, and converting the data into data indicating the relationship between the frequency and the phase;
Displaying a phase value at the inspection frequency as an image,
The display step includes a step of displaying the difference between a phase value in a normal part and a phase value in a defective part so as to be visually recognized by setting the inspection frequency to 0.1 Hz or less .   The flaw detection method according to claim 1, wherein the inspection frequency is in a frequency range up to 0.00052 Hz.   The flaw detection method according to claim 1, wherein the inspection frequency is in a frequency range of 0.02 Hz to 0.00052 Hz. The flaw detection method according to claim 1, wherein the material of the object is CFRP.   The flaw detection method according to claim 1, wherein the inspection frequency is a value obtained by dividing the sampling frequency by the number of samples. The flaw detection method according to claim 1, wherein the display step displays the measurement position of the material as two-dimensional image data in a two-dimensional manner. Heating means for pulse-heating the surface of the inspection object;
Temperature detection means for detecting surface temperatures of a plurality of portions of the inspection object after heating at a set sampling frequency at a set time;
Data processing means for performing Fourier transform on data indicating the relationship between the elapsed time since heating and the surface temperature, and converting the data into data indicating the relationship between frequency and phase;
Display means for displaying the phase value at the inspection frequency as an image,
The flaw detection apparatus according to claim 1, wherein the display means displays the difference between a phase value in a normal part and a phase value in a defective part so that the inspection frequency is 0.1 Hz or less .   The flaw detection apparatus according to claim 7, wherein the inspection frequency is in a frequency range up to 0.00052 Hz.   The flaw detection apparatus according to claim 7, wherein the inspection frequency is within a frequency range of 0.02 Hz to 0.00052 Hz. The nondestructive material flaw detection apparatus according to claim 7, wherein the material of the object is CFRP.   The flaw detection apparatus according to claim 7, wherein the inspection frequency is a value obtained by dividing the sampling frequency by the number of samples.   The flaw detection apparatus according to claim 7, wherein the display means displays the measurement position of the material as two-dimensional image data in a two-dimensional manner.