Laser Triangulation Research Articles

Automatic optical structure optimization method of the laser triangulation ranging system under the Scheimpflug rule.

Optical structure parameter design is of great importance to ensure the accuracy of asymmetry systems such as the laser triangulation ranging system. The result often depends on the experience of optical designers, and it is inevitable to introduce human errors. In this paper, an automatic optimization method of optical structure parameters applied to the laser triangulation ranging system was proposed to assist in improving the measurement accuracy. First, the optical sensitivity optimization model of the laser triangulation ranging system was constructed, and the boundary conditions were established from two aspects of laser clear imaging and sensor geometric dimension. The constraint relationship between optical structure parameters under the Scheimpflug rule was established to ensure clear laser imaging, and the transverse distance and axial distance of the sensor geometric dimension were constrained when the laser imaging length was taken into consideration. Secondly, mutation operator-based particle swarm optimization (M-PSO) algorithm was proposed to search the optimal optical sensitivity, and three typical working distances and ranges were taken as examples to design the optical parameters. In addition, the results were verified by ZEMAX simulation and also the experimental platform, the maximum optical sensitivity of the structure was 3.496 and its corresponding optimal nonlinearity was 0.039% F.S. The automatic optimization method proposed in this paper was compared with the traditional GA method and PSO method, and it was verified that the convergence efficiency of the proposed method was much higher than the traditional ones.

Process-related characteristic–based topography evaluation of wear conditions on grinding wheels

Non-productive auxiliary processes affect the single part and small badge production of milling tools. The key production process grinding is inevitably linked to the auxiliary conditioning process. The time demand of those process steps decreases the overall productivity of the manufacturing process. However, today the machine operator decides on conditioning cycles individually by the use of experience. Until today, there is no objective data based approach available that supports the initiation of these conditioning processes or the adaption of the grinding process itself in order to improve its process efficiency. For this purpose, a process-related topography evaluation method of the grinding wheel surface is developed within this study. For the measurement, an optical method based on laser triangulation is used. The measurement system is implemented into a common tool grinding machine tool. In addition, characteristic topography values are defined that show the wear conditions of the grinding tool. Moreover, the data is summarized in a database of wear conditions. The developed measurement method can save grinding and dressing tool resources, process times and minimizes scrap parts. In addition, an adaptation of the process and a targeted launch of auxiliary processes can be enabled. The novel characteristic-based topography measurement creates the opportunity to enhance the tool life of the grinding wheels up to 30% without losing productivity.

A control strategy for incremental profile forming

Incremental profile forming (IPF) allows the flexible manufacture of metallic tubular structures with cross-sectional profiles that vary along their length, but its geometric accuracy is limited currently by exclusive reliance upon machine control of the process. Procedures for on-line sensing of process attributes and post-process sensing of part geometry, using laser triangulation sensors, are developed. Improved understanding of process characteristics for elementary IPF operations, obtained from FEM analysis and experiments, is described. Issues in developing a control-oriented process model are discussed along with prior related work. An overall control strategy for improving part geometry in IPF is formulated, indicating directions for needed research in process design, control-oriented modelling, sensing improvements, and control.

First trigonotarbid arachnids from the Pennsylvanian of Indiana and Oklahoma

AbstractA new specimen of the arachnid order Trigonotarbida is described from the Middle Pennsylvanian (lower Desmoinesian) Shelburn Formation of Indiana, which has previously yielded the remains of a phalangiotarbid. Two new trigonotarbid arachnid specimens are also described from the Middle Pennsylvanian (Desmoinesian) Senora Formation of Oklahoma. These are the first trigonotarbid specimens reported from Indiana and Oklahoma. The Indiana trigonotarbid belongs to the Eophrynidae, as indicated by distinct features such as the large tubercles on the dorsal surface of the opisthosoma and two pairs of terminal opisthosomal spines. This specimen is the first arachnid fossil to be imaged using a Multistripe Laser Triangulation scanner. The heavy dorsal tuberculation, lobed and subtriangular carapace, rounded clypeus, lack of terminal opisthosomal spines, and rounded opisthosoma on Oklahoma specimen FMNH PE 56932 indicate it belongs to the genusAphantomartus, in Aphantomartidae. The other Oklahoma specimen, FMNH PE 56955, possesses opisthosomal tergites that are divided into five plates longitudinally as well as a subquadrate carapace, which identify it as a member of Anthracomartidae; its rounded opisthosomal margin shows it to belong to the genusAnthracomartus.

Acoustic roughness measurement of railway tracks: Implementation of an optical measurement approach & possible improvements to the standard

The measure for assessing the acoustic quality of the rail surfaces, the acoustic roughness, is defined in the EN 15610 standard. It is shown that this standard contains gaps with regard to the applied procedures for processing the raw data to the quantity of acoustic roughness. Additions to the standard appear necessary to ensure better comparability of the results. A piece of rail tactilely measured by METAS (Swiss Federal Institute of Metrology) was used as a reference. Measurement data recorded by a laser triangulation sensor was used to quantify the adjustments to the standard. This paper provides an overview of the individual processing steps and systematically examines possible additions to the standard to improve the quality of the outcome. Special emphasis was given to a method for outlier removal, pre-filtering, spike removal, curvature correction and calculation of one-third octave bands. It becomes apparent that different implementations can have a significant impact on the final result. The filter used, the wavelength ranges, the methodology for removing outliers should be specified. The spike removal, curvature correction and the calculation of the one-third octave bands should be supplemented in detail to reduce ambiguities in the implementation.

Measurement accuracy assessment of the 3D laser triangulation scanner based on the iso-disparity surfaces

Measurement accuracy assessment of the 3D laser triangulation scanner based on the iso-disparity surfaces

Digital survey and reconstruction for enhancing epigraphic readings with erode surface

Abstract The contribution illustrates the applied procedure of the digital survey and documentation of a funerary epigraph written in Greek but dating back to the Roman period (dimensions of about 31 cm x 20 cm). It comes from Velia (Salerno), a Greek and then Roman city in southern Italy. It was found in 1967 and currently represents the only Greek funerary inscription of the Roman period coming, most probably, from the necropolis of Porta Marina Sud. The inscription presents many gaps and preserves only part of the upper right and lower margins. The surface is highly eroded, maybe due to the exposure to atmospheric agents, making the text interpretation extremely difficult. The implemented image-based and range-based techniques contributed to reading the inscriptions, letting to recover much information that was invisible to the naked eye. The 3D survey system choice has to be consistent with the work aims and the physical object characteristics. A high degree of geometric detail was essential for our case study. Therefore, a triangulation laser scanner performed the first digital capturing, subsequently integrated with a structured light system (Artec Eva and Leo) and finally, a close-range photogrammetric acquisition to produce a high-resolution orthophoto.

Experimental study on liquid metal free surface flow under magnetic and electric field for nuclear fusion

In the future application of nuclear fusion, the liquid metal flows are considered to be an attractive option of the first wall of the tokamak which can effectively remove impurities and improve the confinement of plasma. Moreover, the flowing liquid metal can solve the problem of the corrosion of the solid first wall due to high thermal load and particle discharge. In the magnetic confinement fusion reactor, the liquid metal flow experiences strong magnetic and electric, fields from plasma. In the present paper, an experiment has been conducted to explore the influence of electric and magnetic fields on liquid metal flow. The direction of electric current is perpendicular to that of the magnetic field direction, and thus the Lorentz force is upward or downward. A laser profilometer based on the laser triangulation technique is used to measure the thickness of the liquid film of Galinstan. The phenomenon of the liquid column from the free surface is observed by the high-speed camera under various flow rates, intensities of magnetic field and electric field. Under a constant external magnetic field, the liquid column appears at the position of the incident current once the external current exceeds a critical value, which is inversely proportional to the magnetic field. The thickness of the flowing liquid film increases with the intensities of magnetic field, electric field, and Reynolds number. The thickness of the liquid film at the incident current position reaches a maximum value when the force is upward. The distribution of liquid metal in the channel presents a parabolic shape with high central and low marginal. Additionally, the splashing, i.e. the detachment of liquid metal is not observed in the present experiment, which suggests a higher critical current for splashing to occur.

Analysis of line laser measurement error caused by nonlinear light refraction under the high-temperature environment

For optical measurement of high-temperature components, it is a challenge to analyze the measurement error caused by light refraction due to the inhomogeneous distribution of the air refractive index. Aiming at the problem of line laser measurement under the high-temperature environment, a method for analysis of line laser measurement error on high-temperature surfaces combined with backward ray tracing technology is proposed. The temperature field of the air is simulated based on the heat conduction theory, and the air refractive index is obtained according to the classical empirical formula. Combining with the refraction law of light and the laser triangulation method, the deviation of the spatial position corresponding to each point on the charged-coupled device is calculated. The imaging principle of backward ray tracing is applied to obtain the actual imaging point, and the measurement error of the sensor is calculated. The experiment results prove that the proposed method can effectively evaluate the line laser measurement error under the high-temperature environment. We analyze the system error of the laser sensor under high-temperature conditions and promote the development of high-temperature components on-machine measurement.

A stereo optical comparison method for detection of metallic surface defects based on machine vision and laser triangulation

Quality of metallic surfaces is essential to maintain performance and longevity of industrial products. The surface defects of products like holes and cracks not only affect their appearances and performance, but also may even result in potential danger to human health in some cases. Traditional surface inspection methods for metallic surfaces rely on manual inspection methods by naked eyes or with the help of close circuit cameras, presenting the problems of low efficiency, low accuracy, high labour intensity due to monotonous work. Today manual inspection is not possible in many applications, therefore an automated method with a high accuracy is desirable. In this paper we propose a novel stereo optical comparison method to detect defects on metallic surface based on machine vision and laser triangulation.

Directed Energy Deposition roughness mitigation through laser remelting

One of the remaining challenges faced by Directed Energy Deposition is the poor surface finish induced by unmolten particles and the inherent superposition of layers during the process. The DED roughness levels are known to be significantly higher than for conventional parts and can become critical for the fatigue life and corrosion of the component. This is why the production of a DED part always requires a post-processing surface finishing step, which is known to be costly and to have a significant impact on the production time. This paper therefore presents an evaluation of single-track roughness induced by the DED process through transversal cross-sections, top-view micrographs, in situ process monitored images, laser triangulation, and contact-type measurements. The main DED process parameters defining the roughness are identified as being the particle diameter, laser beam diameter, and laser power. Finally, laser remelting during the production of cubic samples is proposed as a solution to further mitigate the roughness. Roughness levels on the top surface are reduced up to 86% with sufficiently high laser power settings. Laser remelting is therefore recommended to minimize the roughness, in combination with an optimal process parameter selection.

In-line Sensor-based Process Control of the Calendering Process for Lithium-Ion Batteries

The calendering process is the final property-defining step in the manufacturing of electrodes for lithium-ion batteries. Calendering significantly affects mechanical properties by compacting the electrodes and increases the lithium-ion batteries’ volumetric energy density. The choice of calendering parameters is primarily based on empirical data, considering the final battery cell properties. The drive for increased energy densities and the corresponding high compaction rates results in an increased electrode defect and scrap occurrence. This leads to challenges in process control which are addressed in this paper by developing an agile and predictive sensor-based process control. Hereby an efficient determination of process parameters is enabled, resulting in a reduction of scrap and manufacturing costs. Applying in-line data acquisition for electrode thickness and surface topography allows real-time feedback of measurement data at the machine-product interface back into the calendering system control. Reliable data acquisition is established by integrating two sensor systems for coating thickness measurement (confocal sensors) and defect detection (laser triangulation sensor) in a cascaded arrangement, enabling real-time evaluation of the product properties achieved as a function of the process parameters. The associated potentials and challenges regarding a predictive analysis of machine and product behavior are addressed in this context. The experimental results demonstrate that the combination of both sensor systems offers the potential to establish an agile and innovative process control for the calendering process of lithium-ion batteries.

RESEARCH OF OPTIMIZATION OF LAMES OF THE LASER SENSOR OF VIBRATION TO COUNTER LASER INTELLIGENCE SYSTEMS

One of the most vulnerable issues in the technical protection of information is the receipt of data, private or confidential, due to leakage through the optoelectronic channel, the main source of data is laser acoustic intelligence systems or laser microphones. There are active and passive methods of protection against laser acoustic reconnaissance systems (ACS). Active methods use various noisy or vibrating devices that pose a danger to human health. With passive protection, it is recommended to use either special corrugated windows or completely closed shutters, which create some inconvenience now. Detecting a working laser microphone is very difficult and in some cases technically impossible. For example, the removal of information using ACS occurs through glass building structures, usually windows. This article is devoted to the analysis of the principle of operation of laser systems of acoustic intelligence and passive methods of reading acoustic information. Triangulation laser sensors are designed for non-contact measurement and control of position, movement, size, surface profile, deformation, vibration, sorting, recognition of technological objects, measuring the level of liquids and bulk materials. Accordingly, they can be used to study the vibrational properties of glass and films applied to them. It is described the method of working with laser triangulation vibration sensors, which allows to study the deviations of glass from different manufacturers from sound vibrations, thereby investigating the anti-laser properties of existing glass, as well as different types of spraying and films. In addition, this method allows you to conduct and test deviations from sound vibrations for new types of glass, films and spraying, proving the results of spectral studies and their impact on the amplitude of vibration of the glass. The vibration sensor was adjusted and the software parameters were experimentally optimized to obtain the truest deviation values ​​required to work with sprayed samples for passive protection.

Flexible Robot-Based In-Line Measurement System for High-Precision Optical Surface Inspection

Advances in industrial manufacturing and an increasing trend towards direct integration of measurement systems in the production line require flexible, fast, precise and robust systems. This paper presents the development and evaluation of a fully automated robot-based in-line measurement system, suitable for applications incorporating process variability and uncertainty, however, requiring single micrometer resolution and low instrumentation effort. The system utilizes laser triangulation in combination with mechanical 2D-scanning for fast and precise measurements. Lissajous trajectories and a computer vision algorithm based on edge detection are used to locate relevant features within the scan area. This allows alignment of the measurement tool, by using plane fits, to optimally utilize the measurement range of the sensor system for a high resolution scan, applied to a refined area, providing robustness and flexibility. For a scan area of 25×25mm the measurement uncertainty equals 6.4μm at 2σ. The system accuracy is evaluated to 2.2μm. The combined standard uncertainty of reference sample measurements equals 1.2μm.

Applying image processing for autonomous finding welding line for industrial robot

Currently, at the Vietnamese factory, continuous straight-line welding is still done manually or by workers. Some factories have manipulators to do this, but workers have to teach the robot to recognize the weld using a Teach-pendant device. Those jobs will take a lot of time for a welding job as well as uneven product quality. The purpose of the research is to develop an automatic system that combines computer vision and an industrial manipulator with 6 degrees of freedom (6DOF) that can recognize the weld line automatically and command the manipulator to follow the line profile. First, by using a 3D camera and laser system mounted at the end of the 6DOF manipulator and combined with the laser triangulation image processing algorithm, the position of the path from the starting point, sub-point and point weld end are extracted. Then, using an interpolation algorithm, the trajectory is calculated and transmitted to the manipulator. By using this method, the quality of the welded product is guaranteed and also the quantity of welding is increased as the Robot can work from time to time and especially for repetitive tasks. The installation time to weld the product is significantly reduced with the help of the computer vision system. The efficiency of the system is proven through experiments.

Comparison between 3D-reconstruction optical methods applied to bulge-tests through a feed-forward neural network

The mechanical behaviour of rubber-like materials can be investigated through numerous techniques that differ from each other in costs, execution times and parameters described. Bulge test method proved helpful for hyperelastic membranes under plane and equibiaxial stress state. In the present study, bulge tests in force control were carried out on SBR 20% CB-filled specimens. 3D reconstructions of the dome were achieved through two different stereoscopic techniques, the epipolar geometry and the Digital Image Correlation. Through a Feed-Forward Neural Network (FFNN), these reconstructions were compared with the measurements by a laser triangulation sensor taken as reference. 3D-DIC reconstruction was found to be more accurate. Indeed, bias errors of the 3D-DIC and epipolar techniques with respect to the relative reference values, under creep condition, were 0.53 mm and 0.87 mm, respectively.<br /><br />

Enriching Existing 3D Pavement Condition Survey Datasets to Support Paving Project Cost Estimates, Project Planning, Designs, and Automated Machine Guidance

State departments of transportation (DOTs) typically perform annual pavement condition inspections, which serve as an important input into pavement management systems (PMS) software. Road surface defects (cracking, rutting, smoothness, etc.) are analyzed by PMS software to model the deterioration of pavements and to make budget and performance-based recommendations about which roads to maintain and how and when to maintain them. Increasingly at the state DOT level, these data are captured using high-speed 3D lasers (laser triangulation systems) that acquire the 3D shape of the road surface to evaluate its condition. Traditionally the capture of road elevation data relied entirely on the use of survey crews. Although accuracy can be quite high, the process of capturing elevations can require a lot of manpower, is time-consuming, requires lane closures, and results in a relatively small number of points per kilometer of road with which to perform all of the tasks from early project planning through construction. This paper explores an alternate approach that leverages existing 3D laser technology utilized by DOTs to measure the condition of in-service pavements. Typically, these laser systems capture “relatively referenced” 3D profiles of the roadway to evaluate pavement condition based on surface distortion. However, there is often no connection between these “relative” 3D profiles and real-world locations. This new approach involves the addition of high-accuracy blended global navigation satellite system + inertial navigation system positioning systems, as well as specialized software, to map the absolute position of 3D profiles in real-world coordinates.

Sensor-based particle mass prediction of lightweight packaging waste using machine learning algorithms.

Sensor-based material flow characterization (SBMC) promises to improve the performance of future-generation sorting plants by enabling new applications like automatic quality monitoring or process control. Prerequisite for this is the derivation of mass-based material flow characteristics from pixel-based sensor data, which requires known individual particle masses. Since particle masses cannot be measured inline, the prediction of particle masses of lightweight packaging (LWP) waste using machine learning (ML) algorithms is investigated. Five LWP material classes were sampled, preprocessed, and scanned on a custom-made test rig, resulting in a dataset containing 3D laser triangulation (3DLT) images, RGB images, and corresponding masses of n=3,830 particles. Based on 66 extracted shape measurements, six ML models were trained for particle mass prediction (PMP). Their performance was compared with two state-of-the-art reference models using (i) material-specific mean particle masses and (ii) grammages. Obtained particle masses showed a high variation and significant differences between material classes and particle size classes. After feature selection, both reference models achieving R2-scores of (i) 0.422±0.121 and (ii) 0.533±0.224 were outperformed by all investigated ML models. A random forest regressor with an R2-score of 0.763±0.091 and a normalized mean absolute error of 0.243±0.050 achieved the most accurate PMP. In contrast to studies on primary raw materials, PMP of LWP waste is challenging due to influences of packaging design and post-consumer disposal behavior. ML algorithms are a promising approach for PMP that outperform state-of-the-art methods by 43% higher R2-scores.

Laser Triangulation-Based Measurement Device and Experimental Study of Industrial Timing Belt Profile Parameters

To address the problem of rapid and accurate measurement of tooth profile parameters in the production of industrial synchronous belts, a two-wheel synchronous belt tooth profile measurement device was built based on the laser triangulation method, and a tooth profile measurement data segmentation algorithm based on the slope feature discrimination was designed. Using the built measurement device and data segmentation algorithm, the tooth profile measurement test and tooth profile defect identification test were conducted for RU type synchronous belt with 90 teeth. The results show that the proposed device and algorithm can restore the shape of the measured synchronous belt, and the maximum deviation of the tooth profile parameter is 0.009 mm, and the missing tooth phenomenon can be identified.

3D Laser Triangulation and Deep Learning Approach to Tunnel Inspection

Regular inspection of tunnel surfaces is an important practice from both a safety and tunnel asset management perspective. However, inspection for cracking and spalling is still predominantly a manual task, which is time consuming, subjective, and exposes on-foot staff to risk. This presentation will explore the use of 3D laser scanning technology and artificial intelligence to automate the inspection process with a Canadian metro case study being presented.