METHOD FOR CLASSIFYING AN ETCH INDICATION OF A COMPONENT

Abstract

A method (100) for classifying an etch indication (11) of a component (10), the method including the steps of: providing a captured image (13) of the at least one etch indication (11); detecting at least one criterion (15) of the etch indication (11) based on the captured image (13); comparing the determined criterion (15) to at least one criteria data set (16) of etch indications (11) that is stored in a database; and classifying the etch indication (11) into at least one predetermined defect class (D) based on the comparison.

Claims

1. A method or classifying at least one etch indication of a component, the method comprising the following steps: a) providing at least one captured image of the at least one etch indication; b) detecting at least one criterion of the etch indication based on the captured image; c) comparing the at least one determined criterion to at least one criteria data set of etch indications stored in a database; d) classifying the etch indication into at least one predetermined defect class based on the comparison, and e) classifying the etch indication into at least one predetermined criticality class based on the defect class of the at least one etch indication of the component.

2. The method as recited in claim 1 further comprising etching at least a region of a surface of a component to provide the etch indication.

3. The method as recited in claim 1 wherein the least one criterion characterizes a morphology or distribution of a visual structure of the etch indication.

4. The method as recited in claim 3 wherein the least one criterion characterizes a contrast of the etch indication, the contrast being displayed in the captured image.

5. The method as recited in claim 1 further comprising: d1) outputting the classification into the at least one defect class.

6. The method as recited in claim 1 further comprising: d2) outputting additional criteria data sets of the at least one defect class into which the etch indication was classified or outputting a manufacturing history.

7. The method as recited in claim 1 further comprising: e1) outputting the classification into the at least one criticality class.

8. The method as recited in claim 1 wherein the etch indication is classified into a criticality class, taking into account a weighting of the defect class.

9. A method of using a component having at least one etch indication, the method comprising: using the component depending on a classification of the etch indication into a criticality class, and the classification of the at least one etch indication of the component being provided using the method as recited in claim 1.

10. The method as recited in claim 9 wherein a normal intended use of the component takes place during operation of a turbomachine depending on the classification of the at least one etch indication of the component.

11. The method as recited in claim 9 wherein the component is a component of a rotor for a turbomachine or a Class 1 component.

12. The method as recited in claim 9 wherein the component is a compressor disk or turbine disk for receiving rotor blades.

13. The method as recited in claim 9 wherein the component is a compressor or turbine blisk.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Further features, advantages, and possible applications of invention will be apparent from the following description taken in conjunction with the drawings, in which:

[0037] FIG. 1 is a schematic diagram illustrating a sequence of the inventive method for classifying an etch indication of a component having at least one etch indication; and

[0038] FIG. 2 is a schematic flow chart of a use of a component in accordance with the invention.

DETAILED DESCRIPTION

[0039] FIG. 1 schematically shows a sequence of an inventive method 100 for classifying an etch indication 11 of a component 10.

[0040] In a first step i), at least one surface of a component 10 is etched or subjected to an etching process to provide at least one etch indication 11. In this exemplary embodiment, the illustrated component 10 has an etch indication 11. Using a capture device 12, an image 13 is captured of this etch indication 11, and, in a step a), captured image 13 of etch indication 11 is provided in the form of a data set to a processing unit 14, here a neural network. In other exemplary embodiments, a plurality of images 13 are captured, in particular under different imaging conditions, and/or provided.

[0041] In a step b), at least one criterion 15 of etch indication 11 is detected based on the captured image, the at least one criterion characterizing a morphology and/or distribution of a visual structure of etch indication 11. In the exemplary embodiment shown, the at least one criterion characterizes a contrast of etch indication 11 which contrast is displayed in captured image 13.

[0042] In a step c), the determined criterion 15 is compared to at least one criteria data set 16 of etch indications 11 that is stored in a database, and, in a step d), etch indication 11 is classified, based on the comparison, into at least one predetermined defect class D.sub.6 of a plurality of predetermined defect classes D.sub.1 through D.sub.6. A first defect class D.sub.1 may include a defect type which constitutes what is called a false indication, a second defect class D.sub.2 may include a defect type “LEI” which exhibits an increase in grain size, a third defect class D.sub.3 may include a defect type “moderate LEI” which exhibits a moderate increase in grain size and an off-spec delta structure, a fourth defect class D.sub.4 may include a defect type “Clean White Spot (CWS)”, a fifth defect class D.sub.5 may include a defect type “Dirty White Spot (DWS),” and a sixth defect class D.sub.6 may include a defect type “Non-Metallic Inclusion (NMI).”

[0043] In an optional step d1), the classification into defect class D.sub.6 is output by means of a display device 17, and, in an optional step d2), there may be output additional criteria data sets of the defect class D into which etch indication 11 was classified, as well as a manufacturing history and a numerical contrast value.

[0044] In a step e), etch indication 11 of component 10 is, in this exemplary embodiment, classified into a predetermined criticality class K.sub.2 based on the defect class D of etch indication 11 of component 10. A first criticality class K.sub.1 may, for example, be assigned first defect types, such as, for example, first defect class D.sub.1, second criticality class K.sub.2 may include second defect types, such as, for example, second and third defect classes D.sub.2, D.sub.3, and a third criticality class K.sub.3 may include third defect types, such as, for example, defect classes D.sub.4, D.sub.5, and D.sub.6. In this connection, it may be provided that all etch indications 11, or all components 10 having etch indications 11, which are classified into at least one criticality class K be subjected to a manual assessment by test personnel. This classification into criticality class K may also be output in an optional step e1), in particular together with additional criteria data sets of the defect class D into which etch indication 11 was classified, as well as a manufacturing history associated with component 10, and a numerical contrast value or contrast values of etch indication 11 or captured image 13.

[0045] FIG. 2 shows a schematic flow chart of a use 101 of an exemplary component 10 having at least one etch indication 11. During use 101, a normal intended use 102 of component 10 takes place during operation of an aircraft engine depending on a classification into a criticality class K, and the classification of component 10 is performed using a method 100 for classifying an etch indication of a component, in particular in accordance with the exemplary embodiment shown in FIG. 1. Components that do not meet certain quality specifications may be disposed of.

LIST OF REFERENCE NUMERALS

[0046] 10 component [0047] 11 etch indication [0048] 12 capture device [0049] 13 captured image [0050] 14 processing unit [0051] 15 criterion [0052] 16 data set [0053] 100 method [0054] normal intended use [0055] D defect class [0056] K criticality class [0057] a) through e), i) steps