METHOD AND DEVICE FOR NONDESTRUCTIVELY ACOUSTICALLY EXAMINING AT LEAST ONE REGION OF A COMPONENT OF A TURBOMACHINE FOR SEGREGATIONS

Abstract

The invention relates to a method for nondestructively acoustically examining at least one region of a component of a turbomachine, wherein at least the following steps are performed: a) arranging a transmitter comprising a plurality of individual oscillators on the region of the component to be examined, b) introducing at least one ultrasound beam into the component by means of the transmitter, c) receiving at least one ultrasound beam reflected by the component by means of a receiver comprising a plurality of individual receivers and d) checking, on the basis of the received ultrasound beam, whether there is a deviation in the region of the component which characterizes a segregation. The invention further relates to a device for carrying out a method of this type.

Claims

1. A method for nondestructively acoustically examining at least one region of a component of a turbomachine for segregations, comprising at least the steps a) arranging a transmitter comprising a plurality of individual oscillators on the region of the component to be examined; b) introducing at least one ultrasound beam into the component by the transmitter; c) receiving at least one ultrasound beam reflected by the component by a receiver comprising a plurality of individual receivers; and d) checking, on the basis of the received ultrasound beam, whether there is a deviation in the region of the component that characterizes a segregation.

2. The method according to claim 1, wherein, as transmitter, a phased array transmitter and/or, as a receiver, a phased array receiver is used.

3. The method according to claim 1, wherein, on the basis of the at least one reflected ultrasound beam, at least one false color image is computed, wherein colors of the false color image correspond to individual amplitudes of the ultrasound beam, and wherein, on the basis of the at least one false color image, it is checked whether a deviation that characterizes a segregation is present in the region of the component.

4. The method according to claim 1, wherein, in step a), as transmitter, a two-dimensional matrix transmitter with X*Y individual transmitters and/or, in step c), as receiver, a two-dimensional matrix receiver with X*Y individual receivers are used, wherein X and Y are chosen, independently of each other, from the set of whole positive numbers Z2.

5. The method according to claim 1, wherein, in step b), the ultrasound beam is produced and introduced with a frequency between 500 kHz and 20 MHz, and/or wherein the ultrasound beam is introduced into a surface region of the component with an area between 1 mm.sup.2 and 1000 mm.sup.2, and/or wherein the ultrasound beam is introduced into the component in a depth of introduction between 1 mm and 100 mm.

6. The method according to claim 1, wherein at least the steps b) to d) are repeated multiple times.

7. The method according to claim 6, wherein a plurality of ultrasound beams are introduced in different directions into the component, and/or wherein a plurality of ultrasound beams are introduced in different depths of the component, and/or wherein different focal point sizes are adjusted for a plurality of ultrasound beams.

8. The method according to claim 3, wherein a plurality of false color images are combined into a stack of images which is used for the examination in step d).

9. The method according to claim 1, wherein the examination in step d) is carried out an artificial neuronal network, which has been trained by a deep learning method.

10. The method according to claim 9, wherein a one-layer or multilayer feedforward network and/or a recurrent network is used, and/or wherein the neuronal network is trained on the basis of at least one unflawed part and/or at least one flawed part.

11. The method according to claim 1, wherein time signals of the at least one ultrasound beam are scaled in the human hearing range, and/or wherein the at least one ultrasound beam is analyzed by a sound event classification method.

12. The method according to claim 1, further comprising the steps of: providing at least one transmitter that comprises a plurality of individual oscillators and that can be arranged on at least one region of the component to be examined, and at least one ultrasound beam is introduced into the component; providing at least one receiver comprising a plurality of individual receivers for receiving at least one ultrasound beam that is reflected by the component; and providing at least one computing unit that is coupled to the receiver for data exchange and that is designed configured and arranged to check on the basis of the at least one reflected ultrasound beam whether a deviation characterizing a segregation is present in the region of the component.

13. The method according to claim 12, wherein the at least one transmitter is a matrix phased array transmitter, and/or wherein the at least one receiver is a matrix phased array receiver.

14. The method according to claim 12, wherein the at least one computing unit is configured and arranged to compute at least one two-dimensional false color image on the basis of the at least one reflected ultrasound beam and, on the basis of the at least one false color image, to check whether a deviation characterizing a segregation is present in the region of the component, and/or wherein, on the basis of the at least one reflected ultrasound beam, the computing unit is configured and arranged to check by an artificial neuronal network that has been trained by a deep learning method, whether a deviation characterizing a segregation is present in the region of the component.

15. The method according to claim 12, further comprising the step of providing a display device for displaying at least one false color image and/or one inspection result.

Description

BRIEF DESCRIPTION OF THE DRAWING FIGURES

[0029] Further features of the invention ensue from the claims, the figures, and the description of the figures. The features and combinations of features that are mentioned above in the description as well as the features and combination of features that are mentioned below in the description of the figures and/or shown in the figures alone can be used not only in the respectively presented combination, but also in other combinations, without leaving the scope of the invention. Accordingly, embodiments of the invention that are not explicitly shown and explained in the figures, but ensue and can be created by separate combinations of features from the explained embodiments are to be regarded as included and disclosed. Also to be regarded as embodiments and combinations of features are accordingly those that do not have all the features of an originally formulated independent claim. In addition, embodiments and combinations of features that go beyond the combinations of features described in reference back to the claims or else depart from them are to be regarded as being disclosed, in particular by the above-described embodiments. Here:

[0030] FIG. 1 shows a schematic sectional view of a component that is designed as a turbine disk, on which a nondestructive, acoustic examination is carried out;

[0031] FIG. 2 shows a schematic illustration of the production of an ultrasound beam;

[0032] FIG. 3 shows a schematic illustration of the receiving of an ultrasound beam that has been reflected from a region of the component;

[0033] FIG. 4 shows an exemplary false color image with amplitude values of the reflected ultrasound beam assigned to individual pixels;

[0034] FIG. 5 shows a time signal, by way of example, along a depth region of the component;

[0035] FIG. 6 shows a detailed enlargement of the region VI shown in FIG. 5; and

[0036] FIG. 7 shows a stack of images composed of a plurality of false color images that follow one another in succession.

DESCRIPTION OF THE INVENTION

[0037] FIG. 1 shows a schematic sectional view of a component 10, which is designed as a turbine disk of an aircraft engine, on which a nondestructive, acoustic inspection for the presence of anomalies, such as, for example, segregations in the material of the component 10, is carried out. For this purpose, a transmitter 12 with an array of individual transmitters 14 is arranged on a region Ito be investigated of the component 10. In the present case, the transmitter 12, which can be a phased array transmitter, has 121 individual transmitters 14, which are arranged in the form of a 2D matrix in a square X*Y grid with X, Y=11. Subsequently, at least one ultrasound beam 16 is produced by means of the transmitter 12 and introduced into the component 10 in a focused manner. The diameter of the ultrasound beam 16 is typically adjusted to be about 1 mm to about 3 mm. In this case, the depth of introduction ti can be chosen to be constant or variable as needed. In one exemplary embodiment, the depth of introduction or the depth range ti is 10 mm. For a speed of sound of typically about 6000 m/s, this corresponds to about 3.3 s transit time to a depth of 10 mm (transit time=forward transit and back transit). For a typical digitization rate of 100 megasamples per second, this results in 330 amplitude values. Alternatively or additionally, however, it is also fundamentally possible to inspect the entire region I of the component 10 from the inner side to the outer side of the turbine disk 10.

[0038] With the help of the transmitter 12, which, in the present case, is designed as a receiver 20, such as, for example, as a phased array receiver, also for receiving at least one ultrasound beam 18 (see FIG. 3) that has been reflected by the component 10, the at least one ultrasound beam 18 that is reflected by the component 10 is received and transmitted to a computing unit 22 for further analysis. The transmitting/receiving area can be, for example, 15 mm*15 mm=225 mm.sup.2.

[0039] In one embodiment of the invention, on the basis of the ultrasound beam 18, the computing unit 22 computes at least one false color image 24 (see FIG. 4), with colors of the false color image 24 corresponding to individual amplitudes of the received ultrasound beam 18. In other words, in the present example, there occurs a conversion of 11*11 reflected ultrasound amplitudes to afford the 2D false color image 24, which can be a grayscale image, for example. For the above-mentioned depth of introduction of 10 mm, by way of example, a digitization rate of 100 megasamples per second and a matrix of size 11*11, by way of example, a 2D false color image would have a size of 330 columns and 121 rows. Large amplitudes can be characterized here by using dark color values, while small amplitudes are characterized using light color values. Of course, it is also possible to provide a converse or deviating coloration. A summation of the individual amplitudes, which is conventional in the prior art, does not take place. In general, it can be provided that, by way of a corresponding offset, positive and negative amplitude values can be depicted exclusively in a positive region or characterized exclusively by positive numerical values, as a result of which unreliable negative values for individual image dots can reliably be prevented. Alternatively, however, other suitable depiction algorithms are conceivable.

[0040] In one exemplary embodiment, on the basis of the at least one false color image 24, it is checked by means of the computing unit 22 whether a deviation that characterizes a segregation or other anomaly is present in the examined region I of the component 10. Alternatively or additionally to the false color image 24, the received ultrasound beam 18 can be used for inspection either directly or after a scaling from the megahertz region to the kilohertz region. The inspection can be conducted, for example, by means of deep neuronal networks or by a deep learning model. The neuronal networks or the deep learning model or models employed can fundamentally be trained beforehand by use of data acquired for good parts and flawed parts. The inspection time is extremely short, because the ultrasound beams 16, 18 can be produced and processed at the same time or in very short intervals of time. Accordingly, the entire component 10 can be inspected completely in a correspondingly short period of time. Likewise, it can be provided that a so-called sound event classification is used to process the ultrasound beam 18 and to inspect for the presence of segregations. For this purpose, as already mentioned, the time signals of the ultrasound beam 18 are first scaled in the range of human hearing and subsequently analyzed for the presence of ultrasound signals that are typical of the structural signatures of segregations.

[0041] FIG. 2 shows a schematic illustration for producing an ultrasound beam 16. In this case, a pulse 26 from a pulse generator (not shown) is produced and guided according to arrow II to a fundamentally optional delay circuit 28, which, by way of phase modulation, produces a plurality of time-delayed pulses 30, which are guided to the individual piezoelectric transmitters 14. Owing to the pulses 30, the individual transmitters 14 are compressed at different points in time and, after the drop in voltage, spring back to their original shape normally after less than a microsecond. They thereby produce a mechanical energy impulse, which, in turn, produces an ultrasound wave. The individual ultrasound waves form the ultrasound beam 16, which, if needed, is emitted in a focused manner in the direction of the region Ito be inspected. Through in-phase controlled introduction onto a small inspected volume of the component 10, even small flawed sites (segregations, pores, cracks, etc.) can be detected.

[0042] In an alternative embodiment, current is applied to only a single individual transmitter 14 in each case in order to a emit an ultrasound pulse. The reflected ultrasound pulse is received by all individual receivers 32 in an in-phase manner (so-called full-matrix capture). By means of clocking of all individual transmitters 14, it is possible in this way to inspect the entire volume of the component 10 in a high-resolution manner, with the inspection requiring more time in comparison to the other embodiment.

[0043] FIG. 3 shows a schematic illustration of receiving an ultrasound beam 1 that has been reflected from the examined region I of the component 10. The individual ultrasound waves of the reflected ultrasound beam 18 are received by respective individual receivers 32 of the receiver 20, digitized, and guided to the computing unit 22, where, if needed, they are converted into a false color image 24 and/or transmitted to a neuronal network for analysis.

[0044] FIG. 4 shows, by way of example, a false color image 24 with amplitude values of the reflected ultrasound beam 18 assigned to individual pixels. The false color image 24 corresponds, by way of example, to a result that was obtained with the help of a 2D matrix transmitter 12 with 5*5 individual transmitters 14 or a 2D matrix receiver 20 with 5*5 individual receivers 32. It can be seen that small amplitudes, such as, for example, 0.04, were assigned to light color values, while large amplitudes, such as, for example, 0.96, were assigned to dark color values. Furthermore, it can be seen that not only the amplitude values, but also the local context of the individual ultrasound waves that have formed the ultrasound beams 16, 18 are retained as analyzable information. The false color image 24 can be displayed to an inspector of the component 10.

[0045] FIG. 5 shows, by way of example, a time signal along a depth range ti of the component over a time t of 3 s, with the depth range ti being between 0 mm and 10 mm starting from the surface of the component 10. Shown here are solely the amplitude values S(t) of a single ultrasound wave from the reflected ultrasound beam 18. FIG. 6 shows a detailed enlargement of the region VI shown in FIG. 5. The time interval indicated by T between two measured values is, in the present case, by way of example, about 10 ns, which corresponds to 100 megasamples per second.

[0046] FIG. 7 shows a stack of images 34 composed of false color images 24.sub.1, 24.sub.2, 24.sub.3, etc. that follow one another in succession. This allows, in addition to the incorporation of the spatial context, also taking into account the spectral composition of the individual ultrasound waves of which the ultrasound beam 18 is composed. For example, an ultrasound beam 16 can first be produced with a frequency of 10 MHz, leading to a corresponding reflected ultrasound beam 18. Depending on the frequency of the measurement, such as, for example, 15 MHz or 20 MHz, a large number n of false color images 24 are obtained in this way and make possible a corresponding analysis and thus an especially reliable identification of segregations and other anomalies.

[0047] In a further embodiment of the invention, the following steps are carried out:

[0048] By using conventional ultrasound phased array technology (multi-element ultrasonic probe, multichannel recording of measured values), a multichannel recording of the structural noise signal of the component 10 is carried out for a direction of introduction of ultrasonic waves in the coarse-grain region that varies slightly over time. The reflected ultrasound signals (structural signatures) are fed to a neuronal network. The neuronal network was trained beforehand by means of deep learning to recognize the signature of known segregations. For this purpose, a test object with many defined local coarse-grain regions was used. The ultrasound beams are scaled (MHz.fwdarw.KHz) and classified and analyzed by use of a sound event classification method in the human hearing range.

[0049] The parameter values given in the documentation in order to define process and measuring conditions for the characterization of specific properties of the subject of the invention are also to be regarded as included in the scope of deviations, such as, for example, those due to errors in measurement, system errors, weighing errors, DIN tolerances, and the like.