# US 9,753,014 B2 · Detection and measurement of defect size and shape using ultrasonic fourier-transformed waveforms

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- Number: US 9,753,014 B2
- Document ID: US9753014B2
- Status: Granted
- Kind: B2
- Application number: 14/000,054
- Filed: 2012-02-17
- Published: 2014-03-13
- Granted: 2017-09-05
- Earliest claimed: 2011-02-18
- Assignees: ROLLS-ROYCE plc
- Applicants: Michael G. Glavicic; Jason A. Gilbert
- Inventors: Michael G. Glavicic; Jeffrey A. Gilbert
- Web page: https://patentgrep.com/patent/US9753014B2

## CPC

- G01N 29/11: by measuring attenuation of acoustic waves
- G01N 29/043: {in the interior, e.g. by shear waves}
- G01N 29/12: by measuring frequency or resonance of acoustic waves {(measuring frequency or resonant frequency of mechanical vibrations or acoustic waves in general G01H1/06, G01H3/04, G01H13/00; acoustic resonators G10K11/04; vibration or shock testing of structures G01M7/00)}
- G01N 29/30: Arrangements for calibrating or comparing, e.g. with standard objects
- G01N 29/4427: {with stored values, e.g. threshold values}
- G01N 29/46: by spectral analysis, e.g. Fourier analysis {or wavelet analysis (spectral signal processing per se G06F17/14)}
- G01N 2291/044: Internal reflections (echoes), e.g. on walls or defects
- G01N 2291/2693: Rotor or turbine parts
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)

## Abstract

A system may include a data analysis device that is configured to receive from an ultrasonic waveform detector ultrasonic waveform data representative of an ultrasonic waveform that propagated through a sample and resonated within a defect within the sample. The data analysis device may be further configured to select a portion of the ultrasonic waveform data, apply a Fast Fourier Transform to the portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain, identify a characteristic frequency of the portion in the frequency domain, and determine a characteristic of the defect based on the characteristic frequency of the portion. In some examples, the characteristic of the defect may be at least one of an approximate size or an approximate shape of the defect.

## Claims

### Claim 1

A system comprising:
a data analysis device configured to:
receive from an ultrasonic waveform detector ultrasonic waveform data representative of an ultrasonic waveform that propagated through a sample and resonated within a defect within the sample;
select a portion of the ultrasonic waveform data;
apply a Fast Fourier Transform to the portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain;
identify a characteristic frequency of the portion in the frequency domain; and
determine a characteristic of the defect by at least one of (1) comparing the characteristic frequency to a calibration curve or (2) calculating an approximate size of the defect using at least one equation that relates the characteristic frequency to the approximate size of the defect.

### Claim 2 (depends on 1)

The system of claim 1, wherein the data analysis device is configured to determine the characteristic of the defect by comparing the characteristic frequency to the calibration curve, and wherein the calibration curve comprises a plot of characteristic frequencies of defects of a known shape and known sizes versus an inverse of the known sizes.

### Claim 3 (depends on 1)

The system of claim 1, wherein the data analysis device is configured to determine the characteristic of the defect by calculating the approximate size of the defect using at least one equation that relates the characteristic frequency to the approximate size of the defect, and wherein the at least one equation comprises the equation:
D
=
17.87
⁢
d
f
2
3
wherein D is an approximate diameter of the defect, d is a diameter of a sound hole of the defect, and f is the characteristic frequency of the portion.

### Claim 4 (depends on 1)

The system of claim 1, wherein the data analysis device is configured to determine the characteristic of the defect by calculating the approximate size of the defect using at least one equation that relates the characteristic frequency to the approximate size of the defect, and wherein the at least one equation comprises the equation:
D
=
3
⁢
⁢
d
2
⁢
C
2
8
⁢
⁢
L
⁢
⁢
f
2
⁢
π
2
3
wherein D is an approximate diameter of the defect, d is a diameter of a sound hole of the defect, C is a speed of sound, L is a length of a neck of the defect, and f is the characteristic frequency of the portion.

### Claim 5 (depends on 1)

The system of claim 1, wherein the data analysis device is configured to determine the characteristic of the defect based on at least two equations that relate the characteristic frequency to a respective approximate size of the defect, and wherein the data analysis device is configured to output a range of approximate sizes based on the respective approximate sizes.

### Claim 6 (depends on 1)

The system of claim 1, wherein the data analysis device is configured to:
select a first portion of the ultrasonic waveform data;
apply a Fast Fourier Transform to the first portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain;
identify a first characteristic frequency of the first portion in the frequency domain;
select a second portion of the ultrasonic waveform data;
apply a Fast Fourier Transform to the second portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain;
identify a second characteristic frequency of the second portion in the frequency domain; and
generate a representation of at least the first characteristic frequency and the second characteristic frequency as a function of the portion.

### Claim 7 (depends on 6)

The system of claim 6, wherein the data analysis module is configured to:
receive an input from a user selecting at least one portion from the representation;
determine a representative characteristic frequency for the at least one portion; and
determine the characteristic of the defect based on the representative characteristic frequency of the at least one portion.

### Claim 8

A method comprising:
with one or more processors, receiving from an ultrasonic waveform detector ultrasonic waveform data representative of an ultrasonic waveform that propagated through a sample and resonated within a defect within the sample;
with the one or more processors, selecting a portion of the ultrasonic waveform data;
with the one or more processors, applying a Fast Fourier Transform to the portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain;
with the one or more processors, identifying a characteristic frequency of the portion in the frequency domain; and
with the one or more processors, determining a characteristic of the defect by at least one of (1) comparing the characteristic frequency to a calibration curve or (2) calculating an approximate size of the defect using at least one equation that relates the characteristic frequency to the approximate size of the defect.

### Claim 9 (depends on 8)

The method of claim 8, wherein the calibration curve comprises a plot of characteristic frequencies of defects of a known shape and known sizes versus an inverse of the known sizes.

### Claim 10 (depends on 8)

The method of claim 8, wherein determining the characteristic of the defect by at least one of (1) comparing the characteristic frequency to the calibration curve and (2) calculating the approximate size of the defect using at least one equation that relates the characteristic frequency to the approximate size of the defect comprises determining the characteristic of the defect based on:
D
=
17.87
⁢
d
f
2
3
wherein D is an approximate diameter of the defect, d is a diameter of a sound hole of the defect, and f is the characteristic frequency of the portion.

### Claim 11 (depends on 8)

The method of claim 8, wherein determining the characteristic of the defect by at least one of (1) comparing the characteristic frequency to the calibration curve and (2) calculating the approximate size of the defect using at least one equation that relates the characteristic frequency to the approximate size of the defect comprises determining the characteristic of the defect based on:
D
=
3
⁢
⁢
d
2
⁢
C
2
8
⁢
⁢
L
⁢
⁢
f
2
⁢
π
2
3
wherein D is an approximate diameter of the defect, d is a diameter of a sound hole of the defect, C is a speed of sound, L is a length of a neck of the defect, and f is the characteristic frequency of the portion.

### Claim 12 (depends on 8)

The method of claim 8, wherein determining the characteristic of the defect by at least one of (1) comparing the characteristic frequency to a calibration curve and (2) calculating an approximate size of the defect using at least one equation that relates the characteristic frequency to the approximate size of the defect comprises determining the characteristic of the defect based on at least two equations that relate the characteristic frequency to an approximate size of the defect, further comprising outputting a range of approximate sizes based on the approximate sizes determined based on the at least two equations.

### Claim 13 (depends on 8)

The method of claim 8, wherein:
selecting the portion of the ultrasonic waveform data comprises selecting a first portion of the ultrasonic waveform data;
applying the Fast Fourier Transform to the portion of the ultrasonic waveform data comprises applying a Fast Fourier Transform to the first portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain;
identifying the characteristic frequency of the portion in the frequency domain comprises identify a first characteristic frequency of the first portion in the frequency domain; and
wherein the method further comprises:
with the one or more processors, selecting a second portion of the ultrasonic waveform data;
with the one or more processors, applying a Fast Fourier Transform to the second portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain;
with the one or more processors, identifying a second characteristic frequency of the second portion in the frequency domain; and
with the one or more processors, generating a representation of at least the first characteristic frequency and the second characteristic frequency as a function of the portion.

### Claim 14 (depends on 13)

The method of claim 13, further comprising:
with the one or more processors, receiving an input from a user selecting at least one portion from the representation;
with the one or more processors, determining a representative characteristic frequency for the at least one portion; and
with the one or more processors, determining the characteristic of the defect based on the representative characteristic frequency of the at least one portion.

### Claim 15

A non-transitory computer readable medium comprising instructions that cause a programmable processor to:
receive from an ultrasonic waveform detector ultrasonic waveform data representative of an ultrasonic waveform that propagated through a sample and resonated within a defect within the sample;
select a portion of the ultrasonic waveform data;
apply a Fast Fourier Transform to the portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain;
identify a characteristic frequency of the portion in the frequency domain; and
determine a characteristic of the defect by at least one of (1) comparing the characteristic frequency to a calibration curve or (2) calculating an approximate size of the defect using at least one equation that relates the characteristic frequency to the approximate size of the defect.

### Claim 16 (depends on 15)

The non-transitory computer readable medium of claim 15, wherein the calibration curve comprises a plot of characteristic frequencies of defects of a known shape and known sizes versus an inverse of the known sizes.

### Claim 17 (depends on 15)

The non-transitory computer readable medium of claim 15, wherein the instructions cause the programmable processor to:
select a first portion of the ultrasonic waveform data;
apply a Fast Fourier Transform to the first portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain;
identify a first characteristic frequency of the first portion in the frequency domain;
select a second portion of the ultrasonic waveform data;
apply a Fast Fourier Transform to the second portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain;
identify a second characteristic frequency of the second portion in the frequency domain; and
generate a representation of at least the first characteristic frequency and the second characteristic frequency as a function of the portion.

### Claim 18 (depends on 17)

The non-transitory computer readable medium of claim 17, wherein instructions cause the programmable processor to generate a false color map of the first characteristic frequency and the second characteristic frequency as a function of the portion.

### Claim 19 (depends on 18)

The non-transitory computer readable medium of claim 18, further comprising instructions that cause the programmable processor to:
receive an input from a user selecting at least one portion from the representation;
determine a representative characteristic frequency for the at least one portion; and
determine the characteristic of the defect based on the representative characteristic frequency of the at least one portion.

### Claim 20 (depends on 19)

The non-transitory computer readable medium of claim 19, wherein the representative characteristic frequency comprises at least one of a mean of the characteristic frequencies of the at least one portion, a median of the characteristic frequencies of the at least one portion, or a mode of the characteristic frequencies of the at least one portion.