Laser Line Scan Research Articles

Development of a confocal line-scan laser scattering probe for dark-field surface defects detection of transmissive optics.

Dark-field detection has long been used to identify micron/submicron-sized surface defects benefiting from the broadening effect of the actual defect size caused by light scattering. However, the back-side scattering of a transmissive optical slab is inevitably confused with the front-side scattering phenomenon, resulting in deterioration of the signal-to-noise ratio (SNR) of the scattering signal and false alarms for real defect detection. To this end, a confocal line-scan laser scattering probe equipped with optical sectioning ability is proposed to separate the back-side scattering from the front-side scattering. The optical sectioning ability is realized through a confocal light scattering collector, which overcomes the restriction imposed on the numerical aperture (NA) and the field of view (FOV), reaching an FOV length of 90mm and NA of 0.69. The line-scan principle of the probe protects itself from crosstalk because it produces only a laser spot on the tested surface in an instant. Experimental results verified that the probe has a line-scan length of 90mm with a uniformity better than 98%, an rms electronic noise of 3.4 mV, and an rms background noise of 6.4 mV with laser on. The probe can reject the false back-side scattering light for a 2mm thick fused silica slab at 17.1 dB SNR and operate at a high imaging efficiency of 720mm2/s with a minimum detectability limit of 1.4 µm at 12 dB SNR. This work put forward an effective method with great application value for submicron-sized defect detection in transmissive optics.

Automated geometry measurement and deep rolling of butt welds

During the joining of two metal sheets by welding, a process-specific geometry of the weld is created. The local geometry of the created weld has a decisive influence on its fatigue strength. This is due to stress concentration at the geometric notches. In this paper, a process known from mechanical engineering called deep rolling is applied on butt welds. The influence on the local weld geometry and the local stress concentration after deep rolling is investigated. Additionally, a novel automated measurement system using optical laser line scanning is presented. The system is qualified for the evaluation of the local weld geometry regarding its flank angles and toe radii. The presented investigations show that the deep rolling process influences the stress concentrations determined by 2D-FE-simulations using real scan data. A correlation between the difference in toe radii or local notch stresses before and after deep rolling and the initial flank angle was found. This indicates that there are process and geometry specific conditions for the successful application of the deep rolling process.

A deep-learning-based in-situ surface anomaly detection methodology for laser directed energy deposition via powder feeding

Laser Directed Energy Deposition via Powder Fed (LDED-PF) based Metal Additive Manufacturing suffers from inferior dimensional accuracy mainly due to thermal cycling, localized heat accumulation, inconsistency in the powder stream, deviation in the speed of the motion system and powder focus, etc. In-situ monitoring, along with defect detection algorithms, can be used for avoiding unpredictable build failures while minimizing the time and cost of exhaustive ex-situ characterization techniques. Existing surface quality assessment techniques for LDED-PF mainly focus on intermittent process monitoring, data acquisition, data post-processing, feature extraction, and error identification. The present work investigates the development of a novel in-situ monitoring software platform that can be used for the surface anomaly detection of LDED-PF parts using machine learning techniques. Despite the existing methods in the literature, this technique has shown high robustness and high confidence in defect detection regardless of the geometry, and varied density of point clouds. First, a novel method is developed to calibrate the laser line scanner with respect to the robotic end-effector with the sub 0.5 mm accuracy. Subsequently, 2D surface profiles obtained from the LDED-PF built part surface using the laser scanner are stitched together to create an accurate 3D point cloud representation. Further, the point cloud data is processed, and defect detection is carried out using unsupervised learning and supervised (deep) learning techniques. The overall accuracy and mean IoU of 91.3 % and 83.3 % are achieved, respectively. The study paves the way for the development of automatic tool path generation for the LDED-PF process to build high-quality components.

Small-bubble gas injection to mitigate cavitation-induced erosion damage and reduce strain in target vessels at the Spallation Neutron Source

The effectiveness of small-bubble gas injection to mitigate cavitation-induced erosion damage and decrease strain in Spallation Neutron Source (SNS) target vessels was characterized using photography, laser-line scanning, and in-situ vessel strain measurements. Observations from early targets showed that erosion damage caused appreciable mass loss along the target vessel inner wall. Later target designs incorporated a cavitation mitigation technique called small-bubble gas injection, in which small helium gas bubbles were introduced into the flowing mercury during operation. Samples removed from target vessels after operation revealed that gas injection greatly reduced or eliminated erosion damage. Photographs of the target interiors showed areas where significant erosion damage occurred in targets that were operated without gas injection. The same areas had no observable erosion damage in targets that were operated with gas injection. Laser-line scan measurements were performed on samples from several target vessels operated with and without gas injection to measure the extent of erosion damage and quantify the effect of gas injection on erosion. In-situ strain measurements during operation showed that gas injection reduced the target vessel strain by 25%–75%. These results provide conclusive confirmation that gas injection effectively mitigated erosion damage and reduced strain in SNS target vessels during operation.

Underwater Multispectral Laser Serial Imager for Spectral Differentiation of Macroalgal and Coral Substrates

The advancement of innovative underwater remote sensing detection and imaging methods, such as continuous wave laser line scan or pulsed laser (i.e., LiDAR—Light Detection and Ranging) imaging approaches can provide novel solutions for studying biological substrates and manmade objects/surfaces often encountered in underwater coastal environments. Such instruments can be used shipboard or coupled with proven and available deployment platforms as AUVs (Autonomous Underwater Vehicles). With the right planning, large areas can be surveyed, and more extreme and difficult-to-reach environments can be studied. A prime example, and representing a certain navigational challenge, is the under ice in the Arctic/Antarctic or winter/polar environments or deep underwater survey. Among many marine biological substrates, numerous species of macroalgae can be found worldwide in shallow down to 70+ m (clear water) coastal habitats and are essential ecosystem service providers through the habitat they provide for other species, the potential food resource value, and carbon sink they represent. Similarly, corals also provide important ecosystem services through their structure and diversity, are found to harbor increased local diversity, and are equally valid targets as “keystone” species. Hence, we expand current underwater remote sensing methods to combine macroalgal and coral surveys via the development of a multispectral laser serial imager designed for classification via spectral response. By using multiple continuous wave laser wavelength sources to scan and illuminate recreated benthic environments composed of macroalgae and coral, we show how elastic (i.e., reflectance) and inelastic (i.e., fluorescence) spectral responses can potentially be used to differentiate algal color groups and certain coral genus. Experimentally, three laser diodes (450 nm, 490 nm, 520 nm) are sequentially used in conjunction with up to 5 emission filters (450 nm, 490 nm, 520 nm, 580 nm, 685 nm) to acquire images generated by laser line scan pattern via high-speed galvanometric mirrors. Placed directly adjacent to a large saltwater imaging tank fitted with optical viewports, the optical system records target substrate spectral response using a photomultiplier preceded by a filter and is synchronously digitized to the scan rate by a high sample rate Analog-to-Digital Converter (ADC). Acquired images are normalized to correct for imager optical effects allowing for fluorescence intensity-based pixel segmentation via intensity thresholding. Overall, the multispectral laser serial imaging technique shows that the resulting high resolution data can be used for detection and classification of benthic substrates by their spectral response. These methods highlight a path towards eventual pixel-wise spectral response analysis for spectral differentiation.

Automatic Extraction Method of Urban Road Curb Boundary from Vehicle-Borne Laser Point Clouds

With the acceleration of urbanization, urban road networks are being extended and updated at an alarming rate. How to extract the boundary information of the urban road network efficiently and scientifically to support fine urban management has become a difficult problem. Vehicle-Borne Mobile Mapping System can quickly and efficiently obtain 3D road data, and further realize the extraction of urban road boundary. Based on the tracking information of the Vehicle-Borne Mobile Mapping System, this paper extracts contiguous laser scanning lines from vehicle-borne mobile laser scanning data. By further analyzing the spatial geometric distribution features of the point clouds on different terrain of scan lines, this paper proposes an adaptive window clustering classification method based on the scan line index to solve the problem of the automatic extraction of urban road curb boundary. Experiments are carried out on two point clouds data obtained by the vehicle-borne mobile measurement system. And the accuracy of the extraction of curbs boundary is 99%. The experiment results show that this method can effectively reduce the interference of road noise points as well as the influence of facade features on the boundary extraction of curbs and adapt to different shapes and distribution conditions of urban roads curbs.

Development and Extrinsic Calibration of a 3D Optical Multisensor Platform Using Laser Line Scanner and a Three-Axis Linear Motion Unit

Abstract The area-based three-dimensional optical inspection of workpiece geometries is the basis for quality control, maintenance tasks, and many other typical applications in mechanical engineering and automation such as adaptive manufacturing. In the context of a cyber–physical approach for semi-autonomous post-processing of additively manufactured parts, this method provides the basis for an iterative manufacturing approach. Commercially available systems for optical inspections often rely on camera-based methods, which are, however, susceptible to reflections. This article describes an approach for developing an optical scanstation that uses blue laser line scanners in combination with a Cartesian three-axis motion system and a turntable. The focus of the work is on the development of a method for the fast extrinsic calibration of the entire scanstation.

Automated visualization of steel structure coating thickness using line laser scanning thermography

This paper proposes a line laser scanning thermography system for automated visualization of coating thickness distribution within a steel structure. In the proposed system, a line laser scans the coated steel structure and generates heat energy on the coating surface; the resultant heat response is measured using an infrared camera. Thereafter, the proposed coating thickness visualization algorithm quantifies and visualizes the coating thickness distribution over the entire scanned surface. The proposed system achieves (1) noncontact and nondestructive inspection of invisible coating thickness; (2) automated coating thickness inspection of steel bridges; (3) quantification and visualization of coating thickness via algorithms based on laser-induced heat transfer analyses within the coating layer. The performance of the proposed line laser scanning thermography system was validated through laboratory and field tests. The coating thickness was quantified and visualized with an accuracy of approximately 20 μm.

In-process adaptive dimension correction strategy for laser aided additive manufacturing using laser line scanning

Additive manufacturing (AM) technologies have seen rapid growth in the past decade. Achieving high-quality consistency and accuracy remains a challenge in the fabrication of large-format metallic parts using the directed energy deposition AM processes. An efficient dimension correction strategy is required to prevent build failure during the AM process. In this paper, a laser line scanning sensor was integrated into a robot-based laser aided additive manufacturing (LAAM) system to realise the on-machine measurement of the part geometry. With this system, an in-process adaptive dimension correction strategy was proposed. The dimensional deviations in the intermediate layers could be corrected immediately after they were detected during the LAAM process, thus avoiding excessive dimensional deviation leading to build failure. A tool-path generation process for dimension correction was proposed which did not rely on traditional time-consuming CAD reconstruction. Only 3D point cloud was used directly, enabling the quick response of the LAAM system in restoring the dimensional accuracy. The deviated surface could be automatically filled up, and the subsequent deposition processes were resumed after each cycle of the dimension correction. To facilitate the proposed dimension correction strategy, a Robot Operating System (ROS)-based software platform was developed. Experimental comparisons between the part built with and without correction were conducted. The results demonstrated a significant improvement in dimensional accuracy when the correction strategy was applied.

Reconstruction and Calibration of Contactless Electroluminescence Images From Laser Line Scanning of Photovoltaic Modules

This article presents image processing methods for reconstructing and calibrating contactless electroluminescence (EL) images acquired with laser line scanning for diagnostic of photovoltaic modules. The method specifically focuses on two outputs: a contactless conventional EL that is calibrated to correspond to electrically biased EL and a contactless highlighted EL that emphasizes visualization of defects. Results are evaluated first by visual inspection, showing similar resolution to electrically biased EL at 2% or 5% Isc. A quantitative analysis by peak signal to noise ratio (PSNR) measures also assesses the resemblance between the reconstructed contactless conventional EL and the reference electrically biased EL.

Surface defect characterization and depth identification of CFRP material by laser line scanning

The detection of defects on the surface of carbon fiber reinforced polymer has increasingly become the focus of modern NDT research. In this paper, the shape characterization and depth identification of surface defects of CFRP materials are investigated by establishing reflective and transmissive line laser infrared thermography nondestructive inspection systems. First, we verified the feasibility of the work by simulation. Then, the temperature variation of surface defects was analyzed by two experimental schemes, reflective mode and transmissive mode. To characterize the shape of the defects, we deduced the size of the detect from the scan of the line laser. The results show that the characterization accuracy of defect size is different for different scanning speeds, and finally the characterization error can be controlled within 2.2%. In order to achieve the defect depth classification, we used the grey wolf optimization algorithm to optimize the hyper-parameters in the support vector machine, which can finally achieve 97% depth classification accuracy in 0.56s.

Defect Detection Method for CFRP Based on Line Laser Thermography.

A continuous line laser scanning inspection technique for tracing load-bearing structures was developed and applied to defect detection of unidirectional carbon-fiber-reinforced polymers for aero engines. The heat transfer model of the material was analyzed using the finite element software COMSOL. Meanwhile, a laser platform was built and an image algorithm was used to verify the feasibility of the method. The potential of this technique for detecting defects and providing information on the location of defects in carbon fiber composites was analyzed. Results indicate line laser thermal imaging can successfully determine the size, location, and crack angle of surface damage with extremely high accuracy. The positioning accuracy error for impact and fracture defects is less than 20%, and the detection rate can reach 100% if the defect is in the special position of just leaving the heating area. The angle detection of fracture cracks can be accurate within 10°.

Enhanced Edge Detection for 3D Crack Segmentation and Depth Measurement with Laser Data

With the usage of computer visual technology in civil engineering, pavement crack survey with imaging sensor gained wide attention in the past years. Unfortunately, it is still a challenge to achieve the satisfying results. This paper presents a pavement crack survey approach based on edge detection for laser data. At first, the LS-40 line-laser scanner is implemented to achieve 3D pavement surface data. With the advantage of the various depth information exhibited in the pavement data, an enhanced edge detection based on fractional differential is proposed for 3D crack segmentation. The proposed method could effectively enhance the crack boundary and maintain texture details, which can guarantee the high accuracy in crack segmentation. Moreover, a novel plane fitting method based on dynamic threshold is studied to calculate crack depth information. It can not only identify and remove invalid points effectively, but also accomplish plane calculation with errors in three directions. Experiments verify that the proposed approach can achieve the satisfying result and can work well in F-measure system.

Use of line laser scanning thermography for the defect detection and evaluation of composite material

Abstract The line laser scanning thermography was applied for the defect detection and evaluation of composite material in this work, which was carried out by the following procedures. First, a novel contrast enhancement method by homomorphic technology was proposed and validated by a case study. Then, a specimen containing 12 prefabricated defects was detected using line laser scanning thermography and the obtained thermal image sequence and changeable temperature were analyzed. Finally, the defect area was obtained via such thermal image processing as contrast enhancement based on the proposed method, threshold segmentation and quantitative evaluation. The obtained results show that the composite material defects with a depth of less than 4 mm can be detected using line laser scanning thermography but that with a depth of less than 3 mm can be evaluated quantitatively with a small error less than 10%.

Robotic weld groove scanning for large tubular T-joints using a line laser sensor

This paper presents a novel procedure for robotic scanning of weld grooves in large tubular T-joints. The procedure is designed to record the discrete weld groove scans using a commercially available line laser scanner which is attached to the robot end-effector. The advantage of the proposed algorithm is that it does not require any prior knowledge of the joint interface geometry, while only two initial scanning positions have to be specified. The position and orientation of the following scan are calculated using the data from two previous weld groove scans, so once initiated, the scanning process is fully autonomous. The procedure is a two-step algorithm consisting of the prediction and correction substeps, where the position and orientation of the sensor for the following scan are predicted and corrected. Such a procedure does not require frequent weld groove scanning for navigation along the groove. The performance of the proposed procedure is studied experimentally using an industrial-size T-joint specimen. Several cases of scanning motion parameters have been tested, and a discussion on the results is given.

Improvement of spatial resolution of elemental imaging using laser ablation-ICP-mass spectrometry.

Laser ablation-ICP-mass spectrometer (LA-ICPMS) now becomes one of the most principal analytical technique for mapping analysis for major to trace elements in rocks, minerals, functional materials, or biological tissue samples. In this study, imaging analysis was conducted with coupling of small volume cell and off-set laser ablation protocol to improve the spatial resolution. Combination of newly designed small volume cell and in-torch gas mixing protocols provides faster washout time of the signals (about 0.8s for reducing 238U being one part in a hundred, 1% level). This is very important to improve the spatial resolution in a direction of laser scanning. Moreover, combination of small distances between the laser-line scan (laser pitch distance) and preferential and total ablation of only biological tissue samples placed on glass substrate results in laser ablation of smaller areas than the size of laser ablation pit (shaving ablation). With the shaving ablation, laser-line scanning with narrower-band width (e.g., 2µm) can be achieved even by the laser beam of 8µm diameter. To demonstrate the practical usage of the present technique, imaging analysis of Gd-ethylenediamine tetra-methylene phosphonic acid-doped mouse bone was conducted. Preferential distribution of Gd at the edge of the apatite cell was more clearly identified by the present technique. Combination of the shorter washout system setup and the shaving ablation protocol enables us to improve the spatial resolution of the elemental imaging obtained with the LA-ICPMS technique.

Quantifying the reduction in cavitation-induced erosion damage in the Spallation Neutron Source mercury target by means of small-bubble gas injection

A model developed to represent the progress of erosion damage in liquid-metal spallation target vessels was modified to incorporate the effect of gas injection on the erosion rate. The liquid mercury target system for the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory now operates with helium gas injection to reduce target vessel fatigue stress and cavitation-induced erosion damage. Erosion damage is a primary degradation phenomenon affecting the service life of SNS target vessels, and cavitation mitigation techniques, such as small-bubble gas injection, have been implemented to reduce damage and extend target lifetimes. Erosion depths in samples removed from SNS targets after operation were measured using laser line scanning. These measurements confirmed that gas injection reduced erosion damage. However, quantifying the damage reduction due to gas injection was complicated by variations in lifetime, power, and gas injection rates between different targets. In this study, the operating power and gas injection rate of targets were incorporated into an erosion damage prediction model to quantify their effects on erosion damage reduction. Values of a power scaling factor, β, were calculated by comparing modeled with measured erosion damage. These values indicate that the use of gas injection at the SNS reduced damage to a level equivalent to operating targets without gas injection at 35–47% of the actual beam power. To account for the gas injection effect on the cavitation damage, a simple exponential form based on analysis of the scaling factor β was developed to incorporate the gas rate history with a scaling factor γ in the erosion damage modeling.

A fast self-calibration method of line laser sensors for on-machine measurement of honeycomb cores

Line laser scanning is an effective method used to measure the 3D shape of machined honeycomb core surfaces. The lack of laser-sensor calibrations in 3D space relative to the machine coordinate system restricts the industrial applications of line lasers for on-machine measurements. In this paper, a sensor calibration method based on scanning a honeycomb core itself is proposed. The sensor rotational errors are reversely calculated from the data dislocation originating from the sensor without calibration, and then calibrated by mechanical adjustment and numerical compensation. The sensor calibration parameters are determined once rather than performing data stitching one by one, greatly improving the operation efficiency. The sensor calibration effect is verified from the data seam analysis with and without sensor calibration as well as without stitching, and the comparison results demonstrate that the proposed method is effective in solving the misalignment of the measurement data after stitching. The experimental stitching error verified through a solid block is less than 8 μm. The proposed self-calibration stitching method possesses advantages in large-sized on-machine measurements of honeycomb cores.

Detection of Bubble Defects on Tire Surface Based on Line Laser and Machine Vision

In order to eliminate driving dangers caused by tire surface bubbles, the detection method of bubble defects on tire surfaces based on line lasers and machine vision is studied. Since it is difficult to recognize tire surfaces directly through images, line laser scanning is used to obtain tire images. The filtering method and morphology method are combined to preprocess these images. The gray centroid method is adopted to extract the center of the laser stripe, and then the algorithm to determine the positions of bubble defects on tire surfaces is proposed. According to the geometric characteristics of tire bubbles, the coordinates of starting points, ending points, and rough positions of vertices are determined. Then, the ordinates of the laser center with sub-pixel accuracy near bubble vertices are discretely magnified. The mask made of Gaussian function is convoluted with the magnified region, and the maximum value is obtained. Furthermore, the position of bubble vertices can be accurately extracted. The denoising effects of different methods for images are compared through experiments, and different positions of bubbles are detected. Experimental results show that the detection accuracy of this method is up to 93%, which is much higher than other methods. Experiments verify that the proposed method is effective for detecting tire surface bubbles.

3D mapping of submarine topography by laser line scanning based on pose correction by triangular displacement method

3D mapping of submarine topography by laser line scanning based on pose correction by triangular displacement method