System and method of analyzing a curved surface

• US 10,451,407 B2
• Filed: 11/23/2015
• Issued: 10/22/2019
• Est. Priority Date: 11/23/2015
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Baker, Anthony W., Bellavia, Christopher
• Primary Examiner(s): Dulaney, Kathleen Y
• Application Number:
  US14/948,459
• Publication Number:
  US 20170146462A1
• Time in Patent Office: Days
• Field of Search: 382154, 382141, 382275, 382322
• CPC Class Codes: G01B 11/14 for measuring distance or clearance between spaced objects or spaced apertures G01B11/26 takes precedence; rangefinders G01C3/00
• CPC Class Codes: G01B 11/24 for measuring contours or curvatures
• CPC Class Codes: G01N 2021/8883 involving the calculation of gauges, generating models
• CPC Class Codes: G01N 21/8851 Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges G01N21/8806 and G01N21/93 - G01N21/95692 take precedence; optical measurement of dimensions G01B11/00; optical scanning G02B26/10; image transformation G06T3/00; computerised image enhancement G06T5/00; image processing per se for flaw detection G06T7/0002
• CPC Class Codes: G01N 21/9515 Objects of complex shape, e.g. examined with use of a surface follower device measuring contours and curvatures G01B11/24
• CPC Class Codes: G01N 2201/10 Scanning
• CPC Class Codes: G01N 2201/12 Circuits of general importance; Signal processing
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/20056 Discrete and fast Fourier transform, [DFT, FFT]
• CPC Class Codes: G06T 7/001 using an image reference approach

Abstract

A method of analyzing a curved surface is provided. The method includes obtaining a first data point set including data points representative of a distance between points along the curved surface and a reference axis, determining outlier data points in the first data point set, extracting the outlier data points from the first data point set, thereby defining a second data point set. The method also includes determining a fitted curve for the second data point set, wherein the fitted curve defines an approximate true curve of the curved surface.

Claims

1. A method of analyzing a curved surface of an object, said method implemented by a computing device including at least one processor in communication with at least one memory device, said method comprising:

scanning, by a light detection and ranging (LiDAR) device, the object to obtain a first data point set representative of vertical displacements of points along the curved surface from a reference axis along which the LiDAR device operates, wherein the reference axis is an axis in a Cartesian coordinate system such that the vertical displacements vary along the curved surface, and wherein scanning the object to obtain the first data point set further comprises scanning the object to obtain a three-dimensional point cloud representative of a distance between points along the curved surface and a reference plane;

determining, by the computing device, outlier data points in the first data point set based on a noise level of the LiDAR device, wherein determining the outlier data points comprises;

determining, for the first data point set, an initial fitted curve approximating a true curve of the curved surface, wherein determining the initial fitted curve comprises;

applying a surface fitting function to a two-dimensional array of data points of the first data point set to create a buffer on boundaries of the array and compute a Fast Fourier transform;

truncating frequency domain values resulting from the Fast Fourier transform using an elliptical mask, wherein the elliptical mask facilitates removing higher order Fourier coefficients such that the reference plane contains only low-frequency, smooth terms;

determining an inverse Fast Fourier transform from the truncated frequency domain values; and

generating a three-dimensional first fitted surface of the object based on the determined inverse Fast Fourier transform;

computing respective differences between each data point of the first data point set and the initial fitted curve;

determining a standard deviation of the respective differences; and

identifying the outlier data points among the first data point set as data points corresponding to respective differences greater than the standard deviation;

extracting, by the computing device, the outlier data points from the first data point set, leaving a second data point set;

determining, by the computing device using a plurality of Fourier transform for the second data point set, a second fitted curve for the second data point set, wherein the second fitted curve approximates the true curve of the curved surface; and

identifying, by the computing device, one or more anomalous portions of the object based on the second fitted curve and the second data point set, the one or more anomalous portions indicative of a potential defect in the curved surface of the object.

2. The method in accordance with claim 1 further comprising comparing the second fitted curve to data points of the first data point set to determine anomalies in the curved surface.

3. The method in accordance with claim 1, wherein determining the second fitted curve comprises:

determining a plurality of Fourier transforms for the second data point set; and

plotting the second fitted curve based on the plurality of Fourier transforms for the second data point set.

4. The method in accordance with claim 1, wherein extracting the outlier data points from the first data point set further comprises:

determining, using an averaging filter, a convolution of the data points from the first data point set to generate localized neighborhood mean values; and

replacing the outlier data points with the localized neighborhood mean values.

5. A system for use in analyzing a curved surface of an object, said system comprising:

a light detection and ranging (LiDAR) device that scans the curved surface and obtains a first data point set representative of vertical displacements of points along the curved surface from a reference axis along which the LiDAR device operates, wherein the reference axis is an axis in a Cartesian coordinate system such that the vertical displacements vary along the curved surface, and wherein to obtain the first data point set, said scanning device obtains a three-dimensional point cloud representative of a distance between points along the curved surface and a reference plane; and

a computing device coupled in communication with said scanning device, wherein said computing device is configured to;

determine, for the first data point set, an initial fitted curve approximating a true curve of the curved surface, wherein to determine, for the first data point set, the initial fitted curve, said computing device further;

applies a surface fitting function to a two-dimensional array of the data points of the first data point set to create a buffer on boundaries of the array and compute a Fast Fourier transform;

truncates frequency domain values resulting from the Fast Fourier transform using an elliptical mask, wherein the elliptical mask facilitates removing higher order Fourier coefficients such that the reference plane contains only low-frequency, smooth terms;

determines an inverse Fast Fourier transform from the truncated frequency domain values; and

generates a three-dimensional first fitted surface of the object based on the determined inverse Fast Fourier transform;

compute respective differences between each data point of the first data point set and the initial fitted curve;

determine a standard deviation of the respective differences;

identify outlier data points among the first data point set as data points corresponding to respective differences greater than the standard deviation and based on a noise level of said scanning device;

extract the outlier data points from the first data point set, leaving a second data point set;

determine a second fitted curve for the second data point set using a plurality of Fourier transforms for the second data point set, wherein the second fitted curve approximates the true curve of the curved surface; and

identify one or more anomalous portions of the object based on the second fitted curve and the second data point set, the one or more anomalous portions indicative of a potential defect in the curved surface of the object.

6. The system in accordance with claim 5, wherein said computing device is further configured to compare the second fitted curve to data points of the first data point set to determine anomalies in the curved surface.

7. The system in accordance with claim 5, wherein said computing device is further configured to:

determine a plurality of Fourier transforms for data points in the second data point set; and

plot the second fitted curve based on the plurality of Fourier transforms for the second data point set.

8. The system in accordance with claim 5, to extract the outlier data points from the first data point set, said computing device further:

determines, using an averaging filter, a convolution of the data points from the first data point set to generate localized neighborhood mean values; and

replaces the outlier data points with the localized neighborhood mean values.

9. A non-transitory computer-readable storage device having computer-executable instructions embodied thereon for use in analyzing a curved surface of an object, wherein, when executed by a computing device, the computer-executable instructions cause the computing device to:

receive, from a light detection and ranging (LiDAR) device, a first data point set based on one or more scans of the object by the LiDAR device, wherein the first data point set includes vertical displacements of points along the curved surface from a reference axis along which the LiDAR device operates, wherein the reference axis is an axis in a Cartesian coordinate system such that the vertical displacements vary along the curved surface, wherein to receive the first data point set, the instructions further cause the computing device to receive the first data point set including a three-dimensional point cloud representative of a distance between points along the curved surface and a reference plane;

determine outlier data points in the first data point set based on a noise level of the LiDAR device, wherein to determine the outlier data points the computer-executable instructions cause the computing device to;

determine, for the first data point set, an initial fitted curve approximating a true curve of the curved surface, wherein to determine, for the first data point set, the initial fitted curve, the instructions further cause the computing device to;

apply a surface fitting function to a two-dimensional array of the data points of the first data point set to create a buffer on boundaries of the array and compute a Fast Fourier transform;

truncate frequency domain values resulting from the Fast Fourier transform using an elliptical mask, wherein the elliptical mask facilitates removing higher order Fourier coefficients such that the reference plane contains only low-frequency, smooth terms;

determine an inverse Fast Fourier transform from the truncated frequency domain values; and

generate a three-dimensional first fitted surface of the object based on the determined inverse Fast Fourier transform;

compute respective differences between each data point of the first data point set and the initial fitted curve;

determine a standard deviation of the respective differences; and

identify the outlier data points among the first data point set as data points corresponding to respective distances greater than the standard deviation;

extract the outlier data points from the first data point set, leaving a second data point set;

determine a second fitted curve for the second data point set using a plurality of Fourier transforms for the second data point set, wherein the second fitted curve approximates the true curve of the curved surface; and

identify one or more anomalous portions of the object based on the second fitted curve and the second data point set, the one or more anomalous portions indicative of a potential defect in the curved surface of the object.

10. The non-transitory computer-readable storage device in accordance with claim 9 further comprising computer-executable instructions that cause the computing device to compare the true curve to data points of the first data point set to determine anomalies in the curved surface.

11. The non-transitory computer-readable storage device in accordance with claim 9 further comprising computer-executable instructions that cause the computing device to:

determine a plurality of Fourier transforms for data points in the second data point set; and

plot the second fitted curve based on the plurality of Fourier transforms for the second data point set.

12. The non-transitory computer-readable storage device in accordance with claim 9, wherein to extract the outlier data points from the first data point set, further comprising computer-executable instructions that cause the computing device to:

determine, using an averaging filter, a convolution of the data points from the first data point set to generate localized neighborhood mean values; and

replace the outlier data points with the localized neighborhood mean values.