Laser Measurements Research Articles

Development of a Mobile Laser Measurement System for Subway Tunnel Deformation Detection

In recent years, mobile laser measurement systems have markedly enhanced the capabilities of deformation detection and defect identification within metro tunnels, attributed to their superior efficiency, precision, and versatility. Nevertheless, challenges persist, including substantial equipment costs, inadequate after-sales support, technological barriers, and limitations in customization. This paper develops a mobile laser measurement system that has been specifically developed for the purpose of detecting deformation in metro tunnels. The system integrates multiple modules, comprising a rail inspection vehicle, a three-dimensional laser scanner, an odometer, and an inclinometer, to facilitate multi-sensor temporal synchronization. By leveraging data from the inclinometer and odometer, the system performs point cloud coordinate corrections and three-dimensional linear reconstructions. Experiments conducted on the Xuzhou Metro validate the reliability and stability of the system, demonstrating its capability to meet routine deformation detection requirements. To improve deformation detection utilizing point cloud data, a pre-processing algorithm has been proposed, which incorporates point cloud denoising, centerline calculation, roadbed removal, and relative positioning based on mileage. Disturbed points are systematically identified and eliminated, while the convergence of tunnel sections and inter-ring misalignment are evaluated through ellipse fitting. Furthermore, to address encroachments upon tunnel locomotive limits, encroachment points and associated information are identified using the ray method. In conclusion, the proposed mobile laser measurement system offers an efficient and reliable solution for metro tunnel deformation detection, with significant potential for broader applications and future advancements.

Complete RITZ Set of Ro-Vibrational Energy Levels of 16O3 Deduced from Experimental Spectra: Critical Analysis of Transition Frequencies in Spectroscopic Databases

In this work, we provide the most complete to date reference data for 28 572 rovibrational levels of the electronic ground state of the ozone 16O3 molecule up to the maximum rotational quantum numbers J = 80, Ka = 29 determined from 75 290 experimental transitions covering the range (0.3–7999) cm−1. These energy levels belong to 98 vibrational states extending up to 96.7% of the first dissociation threshold D0 of the molecule. The energy determination procedure is based uniquely on the fundamental Ritz-Planck-Einstein energy conservation principle without use of any approximate Hamiltonian models. A dedicated RITZ computer code produces uncertainties and the correlation matrix for all derived energy levels and permits the prediction of confidence intervals for all dipole-allowed transitions among these levels. The rms deviation of the RITZ transitions for microwave experimental data up to the THz range is 2.6 × 10−6 cm−1. For infrared transitions up to the fundamental and second overtone and combinational bands, including 10 and 5 µm regions important for atmospheric and astrophysical applications, the rms deviation is 1.8 × 10−4 cm−1. For the entire set of lines, the rms deviation is 5.5 × 10−4 cm−1 with the overall dimensionless weighted standard deviation of 0.7. Most of the energy level data is original. For the regions above 6000 cm−1, where empirical data have been previously obtained in the literature from CRDS laser measurements, our data agree well with the published values but provide a more realistic uncertainty analysis. Detailed comparisons of the RITZ transitions with the HITRAN2020 database are discussed and related recommendations are suggested.

(Invited) Laser Induced Generation of Emission and Photocurrent of GaN Nanoceramics

The measurements of laser induced emission (LIWE) and photocurrent (LIPC) of GaN semiconductor nanoceramics are reported. It was found that an origin of both the processes is related to the multiphoton ionization. They occur in a spot of focused laser beam irradiating a surface of ceramics. The emission and photocurrent are characterized by the excitation threshold and exponential increase of intensity. It was observed the hysteresis behavior in forward and backward measurement cycle for emission and photocurrent. A coexistence of both the effects open a possibility for applications in memory devices.The authors would like to thank the National Science Centre, Poland for financial support (grant no. NCN 2021/40/Q/ST5/00220)

Design and analysis of pump casing and impeller using reverse engineering technique

Abstract Advances in three-dimensional (3D) laser measurement technology have resulted in progress in the field of Reverse Engineering. This study introduces a Reverse Engineering technique utilized to restore the initial design of a Pump Casing and its Impeller. This study provides a detailed understanding of the creation of the casing and its impeller 3D model by using the scanned model and its detailed steps, and a 3D deviation report is plotted in order to get a complete deviation idea between the scan data and the design extracted. The Casing and Impeller both have a range of upper and lower is +/− 0.75 mm for the deviation measurement. The Casing is that all points are within its limit, and it’s 100% for most points within its limit and the impeller is 90.9% for most points is in its limit.

Laser ablation inductively coupled plasma mass spectrometry measurements for high-resolution chemical ice core analyses with a first application to an ice core from Skytrain Ice Rise (Antarctica)

Abstract. Conventional methods of inorganic impurity analysis do not provide high enough depth resolution for many scientific questions in ice core science. In this study, we present a setup of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) for high-resolution glacier ice impurity analysis to the sub-millimetre scale. This setup enables ice core chemical impurity analysis to a depth resolution of ∼182 µm while consuming only very small amounts of ice. The system performs simultaneous analysis of sodium, magnesium and aluminium incorporated in the ice matrix. In this case study within the framework of the WACSWAIN (WArm Climate Stability of the West Antarctic Ice Sheet in the last INterglacial) project, our method is applied to a selection of samples from the Skytrain ice core (West Antarctica) over a total length of 6.7 m consisting of about 130 single samples. The main goal of this study is to use the new LA-ICP-MS method to extract meaningful climate signals on a depth resolution level beyond the limits of continuous-flow analysis (CFA). A comparison between low-resolution CFA data and the high-resolution LA-ICP-MS data reveals generally good agreement on the decimetre scale. Stacking of parallel laser measurements together with frequency analysis is used to analyse the high-resolution LA-ICP-MS data at millimetre resolution. Spectral analysis reveals that despite effects of impurity accumulation along ice crystal grain boundaries, periodic concentration changes in the Skytrain ice core on the millimetre scale can be identified in ice from 26.8 ka (kiloyears before present, i.e. 1950 CE). These findings open new possibilities for climate data interpretation with respect to fast changes in the last glacial period and beyond, for example within the Beyond EPICA oldest-ice project.

Electro-Optical Relative Navigation for Inspection and Rendezvous in the SpEye Mission

The execution of autonomous in-orbit servicing operations is expected to play a crucial role to preserve and enhance satellites’ performance, as well as to ensure a sustainable use of outer space. In this respect, several research efforts are dedicated to addressing the technological challenges that characterize the development of an autonomous guidance, navigation, and control system. In this framework, the Space Eye (SpEye) mission, funded by the Italian Space Agency, aims to demonstrate safe and inexpensive on-orbit inspection of a target satellite using a CubeSat-based free-flying nanosatellite. This paper, which stems from the phase A mission study, describes the high-level architectural design of its electro-optical-based relative navigation subsystem, employing multisensor algorithmic approaches based on the combination of visual, laser, and Differential Global Navigation Satellite System measurements. A dedicated environment is developed for the simulation of measurements from the relative navigation suite (including a synthetic image generator), allowing a preliminary performance assessment of the proposed algorithmic approaches.

Research on laser measurement point cloud preprocessing and 3D reconstruction technology for free-form surfaces.

Surface morphology measurement and reconstruction technology based on point cloud data is one of the key technologies for 3D information processing in the digital manufacturing industry and has been widely applied in fields such as reverse engineering, computer vision, and unmanned driving system navigation. A method for 3D modeling of aircraft-engine blade profiles based on laser measurement point cloud data is proposed to address the difficulties in measuring the 3D morphology of aircraft-engine blades and the low modeling accuracy. This method first preprocesses the measured point cloud and then uses Poisson's algorithm to reconstruct the blade surface in three dimensions based on the calculation of the point cloud normal. Through error statistical analysis, the overall reconstruction effect is good. The experimental results further validated the generality and effectiveness of this method.

Intelligent Grinding System for Medium/Thick Plate Welding Seams in Construction Machinery Using 3D Laser Measurement and Deep Learning

With the rapid development of the construction machinery industry, thick plate welds are increasingly needing efficient, accurate, and intelligent processing. This study proposes an intelligent grinding system using 3D line laser measurement and deep learning algorithms to solve the problems of inefficiency and inaccuracy existing in traditional weld grinding methods. This study makes use of 3D line laser measurement technology and deep learning algorithms in tandem, which perform automated 3D measurement and analysis to extract key parameters of the weld seam, in conjunction with deep learning algorithms applied on image data of the weld seam for the automatic classification, positioning, and segmentation of the weld seam. The entire work is divided into the following: image acquisition, motion control, and image processing. Based on various weld seam detection algorithms, the selected model was MNet-based DeepLab-V3. An intelligent trimming system for welding seams based on deep learning was constructed. Experiments were conducted to verify the feasibility and accuracy of the 3D line laser measurement technology for weld seam inspections, and that the deep learning algorithm can effectively identify the type and location of the weld seam, thus predicting the trimming strategy. With an accuracy far superior to conventionally based methods in accurate detection and regrinding of weld surface defects, the system proves advantageous for improved weld regrinding productivity and quality. It was determined that the system presents significant advantages in reinforcing weld regrinding when it comes to efficiency and quality, thus initiating a paradigm of using intelligent treatments for medium/thick plate welds in the construction machinery industry.

Three-Dimensional Reconstruction of Zebra Crossings in Vehicle-Mounted LiDAR Point Clouds

In the production of high-definition maps, it is necessary to achieve the three-dimensional instantiation of road furniture that is difficult to depict on traditional maps. The development of mobile laser measurement technology provides a new means for acquiring road furniture data. To address the issue of traffic marking extraction accuracy in practical production, which is affected by degradation, occlusion, and non-standard variations, this paper proposes a 3D reconstruction method based on energy functions and template matching, using zebra crossings in vehicle-mounted LiDAR point clouds as an example. First, regions of interest (RoIs) containing zebra crossings are obtained through manual selection. Candidate point sets are then obtained at fixed distances, and their neighborhood intensity features are calculated to determine the number of zebra stripes using non-maximum suppression. Next, the slice intensity feature of each zebra stripe is calculated, followed by outlier filtering to determine the optimized length. Finally, a matching template is selected, and an energy function composed of the average intensity of the point cloud within the template, the intensity information entropy, and the intensity gradient at the template boundary is constructed. The 3D reconstruction result is obtained by solving the energy function, performing mode statistics, and normalization. This method enables the complete 3D reconstruction of zebra stripes within the RoI, maintaining an average planar corner accuracy within 0.05 m and an elevation accuracy within 0.02 m. The matching and reconstruction time does not exceed 1 s, and it has been applied in practical production.

Assessment of New Techniques for Measuring Volume in Large Wood Chip Piles

Our work aimed to compare the chip pile volumes calculated by laser ground scanning, UAV technology, and laser ground measurement and also to determine the accuracy, speed, and economic efficiency of each method. The large chip pile was measured in seven different ways: band measurement, laser measurement with Vertex, global navigation satellite system, handheld mobile laser scanner, terrestrial laser scanner, drone, and smartphone with a light detection and ranging sensor. All the methods were compared in terms of accuracy, price, user-friendliness, and time required to obtain results. The calculated pile volume, depending on the method, varied from 2588 to 3362 m3. The most accurate results were provided by the terrestrial laser scanning method, which, however, was the most expensive and the most demanding in terms of collecting and evaluating the results. From a time and economic point of view, the most effective methods were UAVs and smartphones with LiDAR.

Improved Multi-Sensor Fusion Dynamic Odometry Based on Neural Networks

High-precision simultaneous localization and mapping (SLAM) in dynamic real-world environments plays a crucial role in autonomous robot navigation, self-driving cars, and drone control. To address this dynamic localization issue, in this paper, a dynamic odometry method is proposed based on FAST-LIVO, a fast LiDAR (light detection and ranging)–inertial–visual odometry system, integrating neural networks with laser, camera, and inertial measurement unit modalities. The method first constructs visual–inertial and LiDAR–inertial odometry subsystems. Then, a lightweight neural network is used to remove dynamic elements from the visual part, and dynamic clustering is applied to the LiDAR part to eliminate dynamic environments, ensuring the reliability of the remaining environmental data. Validation of the datasets shows that the proposed multi-sensor fusion dynamic odometry can achieve high-precision pose estimation in complex dynamic environments with high continuity, reliability, and dynamic robustness.

Iterative line laser scanning for full profile of polyhedral freeform prism

Polyhedral freeform surface prism is an important optical part, and the measurement of its full profile plays a crucial role in evaluating and improving its manufacturing process. One of the most suitable methods is to combine line laser scanning with multi-degree-of-freedom motion mechanisms to perform scanning measurements on polyhedral freeform surface prisms. Currently, when using line laser for measuring polyhedral freeform surface prisms, there are issues such as insufficient system degrees of freedom, unstable S/N (signal-to-noise ratio) of the light stripe, and high accuracy requirements for the measurement path, resulting in incomplete measurement results. To address the issue of insufficient system degrees of freedom, this paper establishes a five-axis-based line laser scanning system, ensuring measurement accuracy through system calibration. For the problem of unstable S/N of the light stripe in line laser measurement of freeform prisms, this paper proposes a method to evaluate the S/N of the light stripe and confirms the curve of S/N change with view angle through experiments on the measured surface. The optimal view angles for each surface are selected from this curve to obtain light stripe curves with higher S/N. Regarding the issue of increased accuracy requirements for the measurement path due to the view angle selection, this paper proposes an iterative measurement method. By pre-cognizing the part posture, the initial measurement path and results are obtained, and the part posture is iterated continuously based on the measurement results and model information to converge to the actual posture, thus obtaining a high-precision measurement path and achieving full-profile measurement of the part. Full-profile measurements and comparative experiments on standard spheres, flat prisms, and freeform prisms were conducted. Experimental results show that the measurement accuracy of the system can reach the level of 10 µm, and the measurement repeatability can reach the sub-micrometer level. The measurement area can be expanded by about 30% after several iterations, verifying the feasibility of the proposed view angle selection method and iterative measurement method.

Attitude collaborative control strategy for space gravitational wave detection

This paper proposes a high-precision attitude cooperative control strategy for three spacecraft in space gravitational wave detection. Firstly, based on the layout of optical components on the spacecraft and factors such as external interference and model uncertainty, a relative attitude model based on the Euler angle is constructed for the characteristics of small angle motion in differential wavefront sensing mode. Secondly, aiming at the cooperative control problem of multi drag-free attitude control system after the laser link capture between two spacecraft is completed, an attitude control method based on consensus mode cooperative control strategy is proposed. It combines local neighbourhood error from star sensing and differential wavefront sensing with an adaptive controller for equilateral triangle configuration control. Additionally, a cooperative control strategy based on laser measurement information is established to improve control accuracy by avoiding star sensors with low accuracy. Simulation results indicate that the control accuracy of the consistency mode and its sub-mode laser measurement mode is superior to the master-slave and cyclic modes, achieving better than 5×10−6 rad. The laser measurement mode demonstrates the highest accuracy, with relative attitude control accuracy reaching 1.5×10−7 rad, meeting the requirements for space gravitational wave detection.

Laser Observations of GALILEO Satellites at the CBK PAN Astrogeodynamic Observatory in Borowiec

The laser station (BORL) owned by the Space Research Centre of the Polish Academy of Sciences and situated at the Astrogeodynamic Observatory in Borowiec near Poznań regularly observes more than 100 different objects in low Earth orbit (LEO) and medium Earth orbit (MEO). The BORL sensor’s laser observation range is from 400 km to 24,500 km. The laser measurements taken by the BORL sensor are utilized to create various products, including the geocentric positions and movements of ground stations, satellite orbits, the components of the Earth’s gravitational field and their changes over time, Earth’s orientation parameters (EOPs), and the validation of the precise Galileo orbits derived using microwave measurements, among others. These products are essential for supporting local and global geodetic and geophysics research related to time. They are crucial for the International Terrestrial Reference Frame (ITRF), which is managed by the International Earth Rotation and Reference Systems Service (IERS). In 2023, the BORL laser station expanded its list of tracked objects to include all satellites of the European satellite navigation system GALILEO, totaling 28 satellites. During that year, the BORL laser station recorded 77 successful passes of GALILEO satellites, covering a total of 21 objects. The measurements taken allowed for the registration of 7419 returns, resulting in 342 normal points. The average RMS for all successful GALILEO observations in 2023 was 13.5 mm.

Enhanced Analysis of Ice Accretion on Rotating Blades of Horizontal-Axis Wind Turbines Using Advanced 3D Scanning Technology

This study investigated the meteorological conditions leading to ice formation on wind turbines in a coastal mountainous area. An enhanced ice formation similarity criterion was developed for the experimental design, utilizing a scaled-down model of a 1.5 MW horizontal-axis wind turbine in icing wind tunnel tests. Three-dimensional ice shapes on the rotating blades were obtained and scanned using advanced 3D laser measurement technology. Post-processing of the scanned data facilitated the construction of solid models of the ice-covered blades. This study analyzed the maximum ice thickness, ice-covered area, and dimensionless parameters such as the maximum dimensionless ice thickness and dimensionless ice-covered area along the blade. Under the experimental conditions, the maximum ice thickness reached 0.5102 m, and the ice-covered area extended up to 0.5549 m2. The dimensionless maximum ice thickness and dimensionless ice-covered area consistently increased along the blade direction. Our analysis of 3D ice shape characteristics and the ice volume under different test conditions demonstrated that wind speed and the liquid water content (LWC) are critical factors affecting ice formation on blade surfaces. For a constant tip speed ratio, higher wind speeds and a greater LWC resulted in increased ice volumes on the blade surfaces. Specifically, increasing the wind speed can augment the ice volume by up to 57.2%, while increasing the LWC can enhance the ice volume by up to 149.2% under the experimental conditions selected in this study.

LAS-on-edge: A real-time laser absorption spectroscopic water vapor sensor on edge computing platforms

Real-time and in situ water vapor (H2O) sensors are increasingly demanded to indicate thermochemical parameters of energy systems. As an accurate, fast and non-intrusive sensing technology, laser absorption spectroscopy (LAS) enables simultaneous measurement of gas concentration and temperature. Due to the complex spectral computation, real-time and rapid LAS signal processing are still challenging. Most state-of-the-art LAS sensors utilize high-level computing units to post-process laser measurements in real time, hindering their portable deployment in harsh industrial environments. To address the above challenge, we developed an online LAS gas sensor on edging computing platforms, named as LAS-on-Edge. The developed sensor achieves an online monitoring rate up to 62.5 Hz by deploying a spectral-informed neural network on an embedded device. Simultaneously, it reserves the raw kilo-Hz measurements offline for underlying dynamics understanding. The LAS-on-Edge sensor’s compactness also enables its flexible and in situ integration. The sensor is firstly used to monitor a slow mist diffusion and accumulation process, exhibiting a high measurement accuracy with low spectra recovery residuals below 0.01. It is further applied to online monitor the H2O concentration and temperature variation during a lab-scale propane combustion process. It demonstrates a minimal temperature deviation of 1.86 % compared to the thermocouple reference in the flame. The sensor also successfully detects the fundamental flame pulsation at 5.65 Hz as well as high-frequency pulsations exceeding 200 Hz, thereby effectively reveals underlying flame dynamic behaviors.

Following fuel conversion during biomass gasification using tunable diode laser absorption spectroscopy diagnostics

The efficiency of the gasification process and product quality largely depend on the degree of fuel conversion. We present the real-time in-situ tunable diode laser measurements of main carbon and oxygen-containing species in the hot reactor core of a pilot-scale entrained flow biomass gasifier (EFG). The concentrations of CO, CO2, CH4, C2H2, H2O, soot, and gas temperature were measured during the air and oxygen-enriched gasification of stem wood at varying equivalence ratios. The experiments were made at the upper and lower optical ports inside a 4 m long, ceramic-lined, atmospheric EFG, allowing to access the degree of the fuel conversion inside the reactor. The exhaust composition was measured by micro-GC, FTIR, and low-pressure impactor. There was a good agreement between the data measured inside the reactor and at the exhaust for oxygen-enriched gasification implying that the chemical reactions are practically frozen downstream the optical ports. For air, the data indicated that the gasification reactions are still active at the measurement locations. Significant concentrations of C2H2, up to 5000 ppm, were found inside the reactor.

The flame macrostructure and thermoacoustic instability in a centrally staged burner operating in different pilot stage equivalence ratios

The main focus of this paper is to discover the link between flame macrostructure and thermoacoustic instability in a centrally staged swirl burner. In practical combustors, the flow rate in the pilot stage is much smaller than that in the main stage. However, the modification in the pilot stage could alter the flame macrostructure while maintaining a similar total flow rate. Therefore, the thermoacoustic instability was examined at different flame macrostructures by varying the pilot stage equivalence ratio under identical main stage inlet conditions. High-frequency planar laser measurements and chemiluminescence measurement were conducted to enhance spatial and temporal accuracy, providing a more comprehensive understanding of thermoacoustic instability. Two different flame macrostructures, S-type and I-type flames, were identified based on the preheating zone distribution. They exhibit distinct thermoacoustic instabilities, with the I-type flames demonstrating more intense instability than S-type flames. The results indicate that the variation of flame macrostructure influences the coupling of flame heat release and flow field. Specifically, the preheating zone and heat release of I-type flames exhibit greater sensitivity to flow field fluctuations, resulting in a more intense and complex fluctuation of the flame. This discrepancy leads to variations in thermoacoustic instability intensity, as well as the changes in the phase coupling between heat release and acoustic pressure, which in turn impact the total Rayleigh index. Meanwhile, significant differences exist in the distribution pattern and range of flow field fluctuations between I-type and S-type flames.

On the accuracy of the gradient method for determining the mean integral refractive index of air for large-scale dimensional measurements

The results of the analysis of the accuracy capabilities of the gradient method for determining the mean integral value of the group refractive index of air along the path of the laser radiation propagating on the surface atmospheric layer are presented. The mean integral refractive index of air is used in precision laser ranging as a correction to the results of large-scale dimensional measurements, taking into account the difference between the speed of the laser radiation propagation in the atmosphere and the speed of light in vacuum. The performed analysis includes a critical review of publications underpinning this method, and the prospects for its use in high-precision laser measurements of horizontal baselines of up to 5 km long with an expanded uncertainty of less than or equal to 1 mm are considered. This method has been studied in the framework of the Project 18 SIB01 GeoMetre “Large-Scale Dimensional Measurements for Geodesy” executed in accordance with the European Metrology Programme for Innovation and Research (EMPIR).

Detection efficiency measurement of an up-conversion single-photon detector at 3.39μm based on SPDC.

Up-conversion single-photon detector (UCSPD) is promising in weak light radiometry at mid-infrared spectrum. This paper proposed a method to measure the detection efficiency of UCSPD at 3.39μm based on the visible-infrared correlated photons generated by spontaneous parametric down-conversion (SPDC). No infrared standard light source or standard detector was used in measurement and calibration result was insensitive to ambient thermal radiation. An experimental facility was established to obtained a detection efficiency of 0.0085 with a relative uncertainty of 2.8% (k = 1). Factors affecting measuring uncertainty were analyzed and corrected. Bandwidth matching between trigger channel and channel under test is a key problem in detection efficiency calibration. By measuring the bandwidth of the trigger channel and analyzing the bandwidth of the optical elements in the channel under test, we confirm that the acceptance bandwidth of up-conversion crystal is the narrowest. The two channels meet the bandwidth matching conditions, and the detection efficiency can be obtained directly without the bandwidth correction algorithm. Measured detection efficiency agreed well with the result obtained by a continuous laser measurement facility within a difference about 4.7%.