Bridge Crack Inspection Efficiency of an Unmanned Aerial Vehicle System with a Laser Ranging Module
Abstract
:1. Introduction
- (1)
- This study developed an adapted UAV for bridge inspection operations and the inspection camera. The camera is installed on the tripod head and can rotate from 90° (horizontal plane) to 180° (zenith), which enables the UAV to inspect the sides and bottom of bridges.
- (2)
- This study developed the architecture and method used to integrate the camera and the laser ranging module on the embedded system (Raspberry Pi 4). Additionally, the object projection measurement method was proposed, which can overcome the limitations of vertical photography.
- (3)
- This study proposed an image-processing method and process to extract crack information and metric size.
2. Materials and Methods
2.1. Design and Development of a UAV System for Bridge Inspection
2.2. Integration of the Camera and a Laser Ranging Module
2.2.1. Synchronization Mechanism for the Operation Time of the Camera and Laser Ranging Modules
2.2.2. Camera Calibrations
2.2.3. Overall Structural Calibrations for the Camera and Laser Ranging Modules
- (1)
- The positions of the ranging modules were adjusted so that the four laser beams were nearly parallel to each other. Subsequently, the measurement accuracy was increased by measuring the laser beam vectors after calibration.
- (2)
- As the spatial relationships between the laser beam vectors and the camera focus could not be directly measured, control points were marked on the wall of a research room, and relative spatial coordinates were measured using a total station. The room served as the system calibration site. Photos containing laser light spots and control points were captured from different distances (Figure 8a), and photogrammetry was used to calculate the spatial relationships between the laser beam vectors and the laser light spots, as well as those between the laser beam vectors and the control points. The experimental distance was increased from 1 to 3 m in 0.5-m increments. To demonstrate that the developed system can capture images with different attitudes, images were captured in five postures (i.e., facing forward, tilted to the left, tilted to the right, tilted up, and tilted down) in every test, and the ranging modules were used to measure distances. A total of 25 image sets and ranging data were collected, and the spatial coordinates of the laser light spots were simultaneously measured using the total station (Figure 8b).
- (3)
- As the camera was in different locations and at different attitudes when capturing different images, laser light spots could not be used to calculate the laser beam vectors. Thus, the control point coordinates of the photos and collinear spatial resections were used to calculate the outer orientation parameters of the images. The outer orientation was used as a basis to translate and rotate the coordinate system of each photo to a coordinate system in the same space. The converted laser light spots were subsequently used to calculate the laser beam vectors and laser launch point coordinates. The collinearity equations are as follows:
2.2.4. Indoor Measurement Accuracy Tests for the Camera and Laser Ranging Modules
2.3. Crack Identification and Measurement Methods
2.3.1. Extracting the Length of the Main Crack Skeleton
2.3.2. Extraction of Crack Widths
3. Crack Inspection Efficiency and Accuracy of the Developed UAV System
3.1. Outdoor Bridge Inspection Tests
3.2. Outdoor Bridge Inspection Tests
- (1)
- Case 1
- (2)
- Case 2
- (3)
- Case 3
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Items | Original UAV Camera | Inspection Camera |
---|---|---|
Resolution (pixels) | 976 × 494 | 4800 × 3200 |
Focus length (mm) | 2.5 | 9.346 |
Image sensor size (inch) | 1/3 | 1 |
Pixel size (mm) | 0.007743 | 0.00275 |
Item | Parameter Name | Parameter | Value |
---|---|---|---|
Elements of interior orientation (mm) | Focal length | f | 9.346 |
Principal point | xo | 6.442 | |
yo | 4.506 | ||
Lens distortion | Radial distortion coefficients | k1 | 0.0120 |
k2 | −0.0229 | ||
Tangential distortion coefficients | p1 | 0.0044 | |
p2 | −0.0021 |
Photo-Shooting Distance | Side Length Lo-Cation | True Value (m) | Projection Measurement Value (m) | Error (m) | Relative Error |
---|---|---|---|---|---|
1.0 m | F2~G2 | 0.500 | 0.499 | 0.001 | 0.2% |
G2~G7 | 0.741 | 0.737 | 0.004 | 0.5% | |
G7~F7 | 0.500 | 0.499 | 0.001 | 0.2% | |
F7~F2 | 0.739 | 0.738 | 0.001 | 0.1% | |
2.0 m | F6~G6 | 0.500 | 0.503 | 0.003 | 0.6% |
G6~G4 | 0.760 | 0.760 | 0.000 | 0.0% | |
G4~F4 | 0.500 | 0.502 | 0.002 | 0.4% | |
F4~F6 | 0.759 | 0.760 | 0.001 | 0.1% | |
3.0 m | F6~G6 | 0.500 | 0.499 | 0.001 | 0.2% |
G6~G4 | 0.760 | 0.758 | 0.002 | 0.3% | |
G4~F4 | 0.500 | 0.499 | 0.001 | 0.2% | |
F4~F6 | 0.759 | 0.753 | 0.006 | 0.8% |
Dimensions of the Rectangular Box | Side Length Location | True Value (m) | Projection Measurement (m) | Error (m) | Relative Error |
---|---|---|---|---|---|
0.50 m × 0.75 m | F6~G6 | 0.500 | 0.499 | 0.001 | 0.2% |
G6~G4 | 0.760 | 0.758 | 0.002 | 0.3% | |
G4~F4 | 0.500 | 0.499 | 0.001 | 0.2% | |
F4~F6 | 0.759 | 0.753 | 0.006 | 0.8% | |
1.0 m × 1.0 m | B2~D2 | 0.999 | 0.996 | 0.003 | 0.3% |
D2~D4 | 1.003 | 1.000 | 0.003 | 0.3% | |
D4~B4 | 1.001 | 0.998 | 0.003 | 0.3% | |
B4~B2 | 0.997 | 0.990 | 0.007 | 0.7% | |
2.0 m × 2.0 m | A1~E1 | 2.001 | 1.996 | 0.005 | 0.2% |
E1~E5 | 1.997 | 2.001 | 0.004 | 0.2% | |
E5~A5 | 2.004 | 1.996 | 0.007 | 0.4% | |
A5~A1 | 1.999 | 1.980 | 0.019 | 1.0% |
Rectangular Box Location | Coordinates (x, y, z) (m) | Side Location | Length (m) | Damage Situation |
C01 | (−0.141, −0.264, −4.700) | Left | 0.738 | Connected concrete crack |
C02 | (−0.108, −0.912, −4.348) | Bottom | 0.355 | |
C03 | (0.245, −0.880, −4.324) | Right | 0.727 | |
C04 | (0.236, −0.240, −4.669) | Top | 0.378 | |
Location | Coordinates (x, y, z) (m) | Crack Length (m) | Crack Width (mm) | Damage Situation |
Starting point (D01) | (0.477, −0.996, −4.233) | 0.421 | 3.9 | Unconnected concrete cracks |
End point (D02) | (0.615, −0.904, −4.266) |
Side Location | Length (m) | Error (m) | Relative Error | Damage Situation |
---|---|---|---|---|
Left | 0.738 | 0.011 | 1.5% | Connected concrete crack |
Right | 0.727 | |||
Bottom | 0.355 | 0.023 | 6.1% | |
Top | 0.378 |
Location | Coordinates (x, y, z) (m) | Side Location | Length (m) | Damage Situation |
---|---|---|---|---|
E01 | (−1.408, −1.217, −4.163) | Left | 0.638 | Refilled concrete |
E02 | (−1.140, −1.744, −4.403) | Bottom | 0.910 | |
E03 | (−0.338, −1.528, −4.031) | Right | 0.619 | |
E04 | (−0.584, −1.013, −3.791) | Top | 0.927 |
Side Length Location | Length (m) | Error (m) | Relative Error | Damage Situation |
---|---|---|---|---|
Left | 0.638 | 0.019 | 3.0% | Refilled concrete |
Right | 0.619 | |||
Bottom | 0.910 | 0.017 | 1.8% | |
Top | 0.927 |
Location | Coordinates (x, y, z) (m) | Side Location | Length (m) | Damage Situation |
---|---|---|---|---|
A01 | (−0.601, 0.211, −2.487) | Left | 0.230 | Incomplete concrete grouting (hive phenomenon) |
A02 | (−0.627, −0.016, −2.514) | Bottom | 0.383 | |
A03 | (−0.245, −0.049, −2.523) | Right | 0.264 | |
A04 | (−0.232, 0.213, −2.492) | Top | 0.369 | |
B01 | (0.303, 0.271, −2.491) | Left | 0.638 | Refilled concrete |
B02 | (0.204, −0.355, −2.566) | Bottom | 0.319 | |
B03 | (0.518, −0.408, −2.576) | Right | 0.643 | |
B04 | (0.618, 0.223, −2.501) | Top | 0.319 |
Side Length Location | Length (m) | Error (m) | Relative Error | Damage Situation |
---|---|---|---|---|
Left | 0.638 | 0.005 | 0.8% | Refilled concrete |
Right | 0.643 | |||
Bottom | 0.319 | 0.000 | 0.0% | |
Top | 0.319 |
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Kao, S.-P.; Wang, F.-L.; Lin, J.-S.; Tsai, J.; Chu, Y.-D.; Hung, P.-S. Bridge Crack Inspection Efficiency of an Unmanned Aerial Vehicle System with a Laser Ranging Module. Sensors 2022, 22, 4469. https://doi.org/10.3390/s22124469
Kao S-P, Wang F-L, Lin J-S, Tsai J, Chu Y-D, Hung P-S. Bridge Crack Inspection Efficiency of an Unmanned Aerial Vehicle System with a Laser Ranging Module. Sensors. 2022; 22(12):4469. https://doi.org/10.3390/s22124469
Chicago/Turabian StyleKao, Szu-Pyng, Feng-Liang Wang, Jhih-Sian Lin, Jichiang Tsai, Yi-De Chu, and Pen-Shan Hung. 2022. "Bridge Crack Inspection Efficiency of an Unmanned Aerial Vehicle System with a Laser Ranging Module" Sensors 22, no. 12: 4469. https://doi.org/10.3390/s22124469
APA StyleKao, S.-P., Wang, F.-L., Lin, J.-S., Tsai, J., Chu, Y.-D., & Hung, P.-S. (2022). Bridge Crack Inspection Efficiency of an Unmanned Aerial Vehicle System with a Laser Ranging Module. Sensors, 22(12), 4469. https://doi.org/10.3390/s22124469