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[IEEE 2019 14th IEEE Conference on Industrial Electronics and Applications (ICIEA) - Xi'an, China (2019.6.19-2019.6.21)] 2019 14th IEEE Conference on Industrial Electronics and Applications (ICIEA) - Real-Time 3D Profiling with RGB-D Mapping in Pipelines Using Stereo Camera Vision and Structured IR Laser Ring
摘要： This paper is focused on delivering a solution that can scan and reconstruct the 3D profile of a pipeline in real-time using a crawler robot. A structured infrared (IR) laser ring projector and a stereo camera system are used to generate the 3D profile of the pipe as the robot moves inside the pipe. The proposed stereo system does not require field calibrations and it is not affected by the lateral movement of the robot, hence capable of producing an accurate 3D map. The wavelength of the IR light source is chosen to be non overlapping with the visible spectrum of the color camera. Hence RGB color values of the depth can be obtained by projecting the 3D map into the color image frame. The proposed system is implemented in Robotic Operating System (ROS) producing real-time RGB-D maps with defects. The defect map exploit differences in ovality enabling real-time identification of structural defects such as surface corrosion in pipe infrastructure. The lab experiments showed the proposed laser profiling system can detect ovality changes of the pipe with millimeter level of accuracy and resolution.
关键词： stereo camera,3D profiling,structured IR laser,pipeline inspection,real-time mapping
更新于2025-09-12 10:27:22
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[IEEE 2019 Chinese Control And Decision Conference (CCDC) - Nanchang, China (2019.6.3-2019.6.5)] 2019 Chinese Control And Decision Conference (CCDC) - Infrared Vision Based Automatic Navigation and Inspection Strategy for Photovoltaic Power Plant Using UAVs
摘要： In order to improve the effectiveness and reliability of unmanned aerial vehicles (UAVs) automatic navigation and inspection for large photovoltaic (PV) power plants, a strategy of navigation and inspection based on infrared vision was proposed, according to the arrangement characteristics of PV strings. In order to implement the strategy, a PV strings recognition and localization algorithm combining color features and shape features was proposed to obtain information that can be used for navigation. At the same time, a navigation strategy based on the location of PV strings was presented for PV strings inspection. Experiments clearly demonstrated the adaptability and real-time of the proposed method, which makes a contribution to the automatic navigation and inspection for large PV power plants.
关键词： PV inspection,vision navigation,infrared vision,UAVs
更新于2025-09-12 10:27:22
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Degradation Mechanism Detection in Photovoltaic Backsheets by Fully Convolutional Neural Network
摘要： Materials and devices age with time. Material aging and degradation has important implications for lifetime performance of materials and systems. While consensus exists that materials should be studied and designed for degradation, materials inspection during operation is typically performed manually by technicians. the manual inspection makes studies prone to errors and uncertainties due to human subjectivity. in this work, we focus on automating the process of degradation mechanism detection through the use of a fully convolutional deep neural network architecture (f-cnn). We demonstrate that f-cnn architecture allows for automated inspection of cracks in polymer backsheets from photovoltaic (pV) modules. the developed f-cnn architecture enabled an end-to-end semantic inspection of the pV module backsheets by applying a contracting path of convolutional blocks (encoders) followed by an expansive path of decoding blocks (decoders). first, the hierarchy of contextual features is learned from the input images by encoders. next, these features are reconstructed to the pixel-level prediction of the input by decoders. the structure of the encoder and the decoder networks are thoroughly investigated for the multi-class pixel-level degradation type prediction for pV module backsheets. the developed f-cnn framework is validated by reporting degradation type prediction accuracy for the pixel level prediction at the level of 92.8%.
关键词： photovoltaic backsheets,automated inspection,degradation mechanism,fully convolutional neural network,semantic segmentation
更新于2025-09-12 10:27:22
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Determination of the Optimal State of Dough Fermentation in Bread Production by Using Optical Sensors and Deep Learning
摘要： Dough fermentation plays an essential role in the bread production process, and its success is critical to producing high-quality products. In Germany, the number of stores per bakery chain has increased within the last years as well as the trend to finish the bakery products local at the stores. There is an unsatisfied demand for skilled workers, which leads to an increasing number of untrained and inexperienced employees at the stores. This paper proposes a method for the automatic monitoring of the fermentation process based on optical techniques. By using a combination of machine learning and superellipsoid model fitting, we have developed an instance segmentation and parameter estimation method for dough objects that are positioned inside a fermentation chamber. In our method we measure the given topography at discrete points in time using a movable laser sensor system that is located at the back of the fermentation chamber. By applying the superellipsoid model fitting method, we estimated the volume of each object and achieved results with a deviation of approximately 10% on average. Thereby, the volume gradient is monitored continuously and represents the progress of the fermentation state. Exploratory tests show the reliability and the potential of our method, which is particularly suitable for local stores but also for high volume production in bakery plants.
关键词： fermentation monitoring,optical sensor,superellipsoid model fitting,process automation,quality inspection,deep learning
更新于2025-09-12 10:27:22
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Quality Inspection System for Robotic Laser Welding of Double-Curved Geometries
摘要： The quality of robotic laser welded parts is related to the joint location, the trajectory of the laser focal point and the process parameters. By performing in-process monitoring, it is possible to acquire sufficient process knowledge for post-inspection to evaluate the geometrical weld quality. The existing solutions for such systems operate along linear welds. This paper contributes with a quality inspection system for robot laser welding, that can handle double-curved geometries. The data acquisition system includes a CMOS camera, which is mounted such that it looks through the laser optics, external LED illumination and matching optical filters. During the process, the area around the moving laser focal point is captured, resulting in a sequence of images. The trajectory of the focal point is determined by estimating the 2D displacement field between each image using template matching and subsequently filtering the data through a Kalman filter to improve the accuracy and robustness of the system. The joint location is determined by applying a Canny edge detector and a standard Hough transform within a specified region of interest. As this paper deals with double-curved geometries, the region of interest is moved in relation to the laser trajectory, such that it always contains the visible part of the joint, that is closest to the focal point. The developed post-inspection system evaluates the quality of the weld by comparing the estimated trajectory relative to the determined location of the joint. The performance of the proposed quality inspection system was validated empirically on 18 samples. The tests showed promising results, as the system was able to accurately detect changes in the welding trajectory relative to the location of the joint with an accuracy of ± 0.2 mm.
关键词： Vision system,Image processing,Quality inspection,Laser welding,Welding trajectory
更新于2025-09-12 10:27:22
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ToF-SIMS of OLED Materials using Argon Gas Cluster Ion Beam: A Promising Approach for OLED Inspection
摘要： With the increasing adoption of organic light-emitting diodes (OLEDs), analytical methods and tools for their inspection are becoming an important part of the field. In this study, we analyzed four organic materials for OLEDs by using time-of-flight secondary ion mass spectrometry (ToF-SIMS) with 20 keV Ar cluster ion beam projectiles. The fragmentation ratio was plotted as a function of the size of the Ar cluster ions. We reconfirmed that a larger Ar cluster ion beam, which has lower energy per atom, is more effective for detecting secondary molecular ion signals. However, the fragmentation ratio of 4,4′-cyclohexylidenebis[N,N-bis(4-methylphenyl)benzenamine] (TAPC) showed a different tendency. The reason for this difference was investigated and validated by scanning the cluster ion size and comparing it with other mass spectrometric results. This study demonstrates the potential of ToF-SIMS in combination with a cluster ion beam to verify defects in OLEDs that might occur in the manufacturing process.
关键词： ToF-SIMS,Impurity,Fragmentation ratio,Defect inspection,OLED,Ar GCIB
更新于2025-09-12 10:27:22
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Geometry Acquisition and 3D Modelling of a Wind Tower using a 3D Laser Scanning Technology
摘要： This work aims at acquiring the interior shape of wind towers by means of a 3D laser scanning system (LSS). Typically, wind towers are made of structural steel sheets and their fabrication consists of rolling and welding of abutted rolled sheets. This task is typically carried out by welding robots moving through the tower structure. In this study, the developed setup consists of a camera and a circular laser module mounted on the welding robot’s arm traveling through the tower with a constant velocity. The deployed system assists in examining the tower’s interior surface, making it possible to obtain its 3D profile. It will therefore be beneficial for monitoring the geometric changes which occur during the welding process. Encouraging results have been achieved in the characterization of the tower’s geometry, contributing to the assessment of the robustness and accuracy of the deployed 3D LSS.
关键词： Image processing,Wind towers,3D laser scanning,Inspection
更新于2025-09-12 10:27:22
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Metro gauge inspection system based on mobile laser scanning technology
摘要： Detecting metro gauge is very important for the safe operation of the subway. In this study, we design a low-cost metro tunnel mobile scanning system (MDS-TJ-1), which integrates a laser profile scanner with an inertial measure unit and an odometer to provide positioning and attitude parameters of the trajectory. The Lagrange interpolation is used to accomplish the time unification of different sensors. A dynamic alignment scheme for profile scanner is proposed based on the designed plane reflector target with high reflectivity. The error accumulation of the odometer is corrected by recognising the tunnel longitudinal joints, and finish the multi-source data fusion. The horizontal ray method is developed to process the metro gauge inspection. The experiment results show that the alignment accuracy of scanner is within 8 mm, the inner coincidence of the point cloud is within 3 cm, and the average error of the gauge inspection is 7.8 mm.
关键词： Alignment,Data fusion,Gauge inspection,Point cloud,Mobile laser scanning,Metro tunnel,Multi-sensors
更新于2025-09-12 10:27:22
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - XUV Coherence Tomography with Nanoscale Resolution Driven by High Harmonic Generation
摘要： Optical coherence tomography (OCT) is a well-established method to retrieve three-dimensional, cross-sectional images of biological samples in a non-invasive way using near-infrared radiation. The axial resolution of OCT is on the order of the coherence length lc ∝ λ 2 /Δλ which depends on the central wavelength λ0 and the spectral width Δλ of the light source. As a consequence, the axial resolution only depends on the spectrum rather than the geometrical properties of the radiation. OCT with broadband visible and near-infrared sources typically reaches axial (depth) resolutions on the order of a few micrometers [1]. Here we present extreme ultra violet (XUV) coherence tomography (XCT) [2], which takes advantage of the fact that the coherence length can be signi?cantly reduced if broadband XUV and soft X-ray (SXR) radiation is used. XCT can display its full capabilities when used in the spectral transmission windows of the sample materials. For instance, the silicon transmission window (30-99 eV) corresponds to a coherence length of about 12 nm, thus suggesting applications for semiconductor inspection. In the water window at 280-530 eV, a coherence length as short as 3 nm can be achieved and highlights possible applications of XCT for life sciences. XCT utilizes a variant of the Fourier-domain OCT scheme that completely avoids a beam splitter. In the experiment, broadband XUV from a lab-based high-harmonic generation light source [3] is focused onto the surface of the sample. The re?ected spectrum is measured with a grating spectrometer (see Fig. 1 left side). The top layer re?ection assumes the role of a reference beam. Previously, this simpli?cation led to artifacts [2]. Here we show a novel one-dimensional phase retrieval algorithm (PR) to mitigate such disadvantages and enable artifact-free so-called PR-XCT [4]. The right side of Fig. 1 shows a 3D-tomogram of a nondestructive XCT scan of two nanometer thin laterally structured gold layers embedded in silicon. An axial resolution of 24 nm could be reached in the silicon transmission window with the table-top system. Another remarkable result is the high material sensitivity of XCT. At a depth of about 160 nm, a Silicon dioxide layer (blue) was detected which developed during the production process of the sample and has a thickness of a few nanometers only. This layer could not be detected with a SEM in a thin slice cut out of the sample, and even in a TEM image it is only barely visible. Furthermore, the PR-XCT algorithm is capable of extracting material information about the materials inside of the sample. We will present ?rst results on material-resolved XCT.
关键词： optical coherence tomography,high harmonic generation,XUV coherence tomography,nanoscale resolution,life sciences,semiconductor inspection
更新于2025-09-12 10:27:22
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A Laser-Based On-Machine Measuring System for Profile Accuracy of Double-Headed Screw Rotor
摘要： Great length, large weight and other factors may cause difficulty in measuring the profile accuracy of the double-headed screw rotor. To solve this problem, an on-machine measuring system based on a laser-displacement sensor (LDS) was designed and implemented in this paper by taking an LXK100 four-axis whirlwind milling machine as the carrier. To improve the measurement accuracy of the system, the generalized variable-structural-element morphological method, polynomial interpolation algorithm and ellipse fitting method were first combined to realize the rapid subpixel centroid extraction from a noise-containing spot image, thus improving the data acquisition accuracy of the LDS, and then the hybrid method was experimentally verified. Next, a wavelet threshold function with high-order differentiability and adaptive wavelet coefficient contractility was constructed based on the hyperbolic tangent function, so as to inhibit the disturbance from random errors and preserve real profile information, and this method was simulated and verified. Subsequently, a smoothing algorithm for point cloud data was proposed based on the Lagrange multiplier method to avoid the defect of the piecewise curve-fitting method, that is, function continuity and differentiability could not be satisfied at piecewise points. Finally, the profile accuracy was calculated in real time according to the data reconstruction result and the machining quality was judged. The measurement experiment of the double-headed screw rotor indicates that the proposed on-machine measuring system can complete the profile accuracy measurement for a screw pitch within 39.7 s with measurement accuracy reaching ±8 μm, and the measurement uncertainties of the major axis, minor axis and screw pitch are 0.72 μm, 0.69 μm and 1.24 μm, respectively. Therefore, the measurement accuracy and efficiency are both remarkably improved.
关键词： optical inspection,laser displacement sensor,data processing,screw rotor
更新于2025-09-11 14:15:04