Method of performing visualized measurement on thickness distribution of paint film and apparatus therefor

Patent metadata

Field	Value
Publication number	US-11371839-B2
Application number	US-201816307640-A
Country	US
Kind code	B2
Filing date	Nov 2, 2018
Priority date	Nov 24, 2017
Publication date	Jun 28, 2022
Grant date	Jun 28, 2022

Abstract

A method of performing visualized measurement on thickness distribution of a paint film and an apparatus therefor. A measurement target region is heated by a heating unit that applies a light beam while moving relative to the measurement target region of a measurement target structure. A sensing unit moving together with the heating unit generates a plurality of thermal images related to a phenomenon in which thermal energy is propagated in the measurement target region by scanning and photographing the heated measurement target region. The thermal images in a dynamic state are converted into time-spatial-integrated thermal images in a static state by performing coordinate transformation according to a time-spatial-integrated coordinate transformation algorithm. A thickness of the paint film is calculated by using a Fourier thermal conduction equation. A noise caused by an external heat source is removed by subtracting a pre-heating time-spatial-integrated thermal image from the converted time-spatial-integrated thermal image.

First claim

What is claimed is:

1. A method of performing visualized measurement on thickness distribution of a paint film of a structure coated with paint (hereinafter referred to as “measurement target structure”), the method comprising:
heating a measurement target region by a heating unit that applies a light beam while moving relative to the measurement target region of the measurement target structure;
generating, by a sensing unit moving together with the heating unit, a plurality of thermal images related to a phenomenon in which thermal energy is propagated in the measurement target region by scanning and photographing the heated measurement target region; and
converting the thermal images in a dynamic state into time-spatial-integrated thermal images in a static state by performing coordinate transformation according to a time-spatial-integrated coordinate transformation (TSICT) algorithm.

2. The method of claim 1 , further comprising measuring a thickness of the paint film by using the time-spatial-integrated thermal images based on a phenomenon that a propagation time at which the thermal energy caused by the light beam passes through the paint film varies according to the thickness of the paint film.

3. The method of claim 1 , wherein the TSICT algorithm performs time-spatial-integrated coordinate transformation (TSICT) by applying x*=tv, y*=y, and t*=x/v, in which x and y respectively denote an x-axis and a y-axis in the thermal images, t denotes a time, x* and y* respectively denote an x-axis and a y-axis in the time-spatial-integrated thermal images, t* denotes a thermal wave propagation time, and v denotes a relative velocity between the measurement target structure and the sensing unit.

4. The method of claim 3 , wherein a value of the thermal wave propagation time t* is determined such that a time point at which maximum average temperature distribution is realized in the time-spatial-integrated thermal images comes to be equal to a time at which the thermal energy reflected from an interface between the structure and the paint film reaches a surface of the measurement target structure.

5. The method of claim 1 , wherein a thickness of the paint film is calculated by using a Fourier thermal conduction equation L=Q/kAΔTt*, in which ΔT denotes a temperature increment of the paint film caused by the applied light beam, k denotes thermal conductivity of the paint film, L denotes the thickness of the paint film, Q denotes the thermal energy applied to the measurement target structure, A denotes a sectional area through which the thermal energy is propagated, and t* denotes a thermal wave propagation time.

6. The method of claim 1 , further comprising generating a pre-heating time-spatial-integrated thermal image of the measurement target region by performing the generating step and the converting step on the measurement target structure before applying the light beam to the measurement target structure; and generating a corrected time-spatial-integrated thermal image from which a noise component caused by an external noisy heat source is removed by subtracting the pre-heating time-spatial-integrated thermal image from the time-spatial-integrated thermal image generated by the converting step.

7. The method of claim 6 , wherein the heating step includes applying a linear light beam to the measurement target region by converting an arbitrary light beam into the linear light beam, and
the method further comprises removing an image noise which causes abnormal temperature distribution by dividing each longitudinal axis (y-axis) data in the corrected time-spatial-integrated thermal images by a non-uniform energy distribution profile of the linear light beam.

8. The method of claim 1 , wherein the heating step includes applying a linear light beam to the measurement target region by converting an arbitrary light beam into the linear light beam.

9. The method of claim 8 , further comprising removing an image noise which causes abnormal temperature distribution by dividing each longitudinal axis (y-axis) data in the time-spatial-integrated thermal image, which is generated in the converting step, by a non-uniform energy distribution profile of the linear light beam.

10. The method of claim 1 , further comprising removing a random pepper noise component generated in a heat wave photographing unit of the sensing unit by performing median filtering with a median filtering mask on the time-spatial-integrated thermal image generated in the converting step.

11. The method of claim 1 , further comprising generating normalized pixel data based on a gray scale by converting a color of the paint into the gray scale and dividing each pixel data value of the time-spatial-integrated thermal images generated in the converting step by the gray scale.

12. The method of claim 1 , further comprising generating normalized pixel data based on thermal conductivity of the paint by dividing each pixel data value of the time-spatial-integrated thermal image generated in the converting step by the thermal conductivity of the paint.

13. The method of claim 1 , wherein the method is applicable to both a wet paint film where the paint film is not dried and a dry paint film where the paint film is dried.

14. The method of claim 1 , wherein the heating step and the generating step are performed while a drone flies in parallel with the measurement target region of the measurement target structure in a state in which at least the heating unit and the sensing unit are combined into a single body and mounted on the drone.

15. An apparatus for performing visualized measurement on thickness distribution of a paint film of a structure coated with paint (hereinafter referred to as “measurement target structure”), the apparatus comprising:
a heating unit configured to generate a light beam to apply thermal energy to a measurement target region of the measurement target structure while moving relative to the measurement target structure;
a sensing unit configured to generate a plurality of thermal images related to a phenomenon in which the thermal energy is propagated by photographing the measurement target region of the measurement target structure to which the thermal energy is applied while moving together with the heating unit; and
a control unit configured to perform a function of controlling a heating operation of the heating unit and a photographing operation of the sensing unit and receiving the thermal images from the sensing unit to store the thermal images, and a function of converting the thermal images in a dynamic state into time-spatial-integrated thermal images in a static state by performing coordinate transformation based on a time-spatial-integrated coordinate transformation (TSICT) algorithm.

16. The apparatus of claim 15 , wherein the heating unit includes: a laser generator configured to continuously generate a laser beam; a line beam generator configured to convert a point laser beam generated by the laser generator into a linear laser beam; and a first focusing lens configured to adjust a focal point such that a length of the linear laser beam emitted from the line beam generator is adapted to a width of the measurement target region.

17. The apparatus of claim 15 , wherein the heating unit includes: a lamp light source unit configured to convert electric energy into light energy; a light linearization unit configured to collect light generated by the lamp light source unit to convert the light such that linear light is outputted; and a first focusing lens configured to adjust a focal point such that a length of

Assignees

• Korea Advanced Inst Sci & Tech

Inventors

• Sohn Hoon
• Hwang Soonkyu
• Park Jiho

Classifications

• G01B15/02 Primary

  for measuring thickness · CPC title

• G01B21/085 Primary

  using thermal means · CPC title

• G06T2207/10048

  Infrared image · CPC title

• G06T2207/30156

  Vehicle coating · CPC title

• G06T2207/20182

  Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering · CPC title