Optical Measurement Technology Research Articles

Research on High-Speed Digital Optical Signal Jitter Measurement Technology Based on Clock Recovery Algorithm Using Eye Diagram Opening Area

With the rapid development of information technology, high-speed digital optical signal transmission technology has become the core of modern communication networks. However, the increase in transmission rates brings challenges such as noise, distortion, and interference, which affect the accuracy of clock recovery. To address these issues, this study proposes a clock recovery algorithm based on the eye diagram opening area to improve the accuracy and efficiency of high-speed digital optical signal jitter measurement. The proposed method extracts clock information from the signal using the opening area and curvature characteristics of the eye diagram for jitter measurement. Experimental results demonstrate that the clock recovery algorithm based on the eye diagram opening area can stably reconstruct the signal eye diagram and obtain jitter parameters under different optical power conditions. At optical powers of -7.2 dBm, -12.2 dBm, and -17.2 dBm, the Q-factors were 8.8, 7.6, and 4.3, respectively, and the RMS jitter values were 12.2 ps, 13.4 ps, and 21.2 ps, respectively. At optical powers of -2.3 dBm, 0.1 dBm, 2.4 dBm, 4.6 dBm, and 6.0 dBm, the Q-factors were 9.1, 9.3, 9.5, 9.7, and 10.0, respectively, and the average jitter values were 8.9 ps, 8.5 ps, 8.0 ps, 7.5 ps, and 7.0 ps. These results indicate that the proposed algorithm performs excellently under low optical power conditions and maintains high recovery accuracy even when jitter increases at higher optical powers. The clock recovery algorithm based on the eye diagram opening area significantly improves the accuracy and stability of high-speed digital optical signal jitter measurement, enriches the theoretical research of clock recovery algorithms, and shows significant advantages in improving signal transmission quality, reducing bit error rate, and enhancing communication link reliability. The research outcomes provide key technical support for the optimization of modern high-speed optical communication systems.

Temperature Evaluation Considering Gradient Distribution for MV Cable XLPE Insulation Based on Wave Velocity

Temperature is an important factor for the service life of cable insulation. To ensure safety, the operating temperature of cables must be monitored. Since optical fiber temperature measurement technology is difficult to be used widely in medium voltage (MV) cables due to cost, this paper proposes a temperature evaluation method based on wave velocity. Firstly, the dielectric constant of cross-linked polyethylene (XLPE) cable insulation under different temperature is obtained through experiment. Based on the result, the relationship curve between wave velocity and temperature is established. The asymmetry effect due to temperature gradient in the cable insulation is discussed via finite element simulation. The effectiveness of obtaining the average insulation temperature of the cable based on wave velocity is validated. In addition, the mechanism of the temperature influence on the cable insulation material’s dielectric constant is analyzed by molecular dynamics simulation, which further deepens understanding of the characteristics of cable insulation materials.

Dissecting PM sensor capabilities: A combined experimental and theoretical study on particle sizing and physicochemical properties

Recent advancements in particulate matter (PM) optical measurement technology have enhanced the characterization of particle size distributions (PSDs) across various temporal and spatial scales, offering a more detailed analysis than traditional PM mass concentration monitoring. This study employs field experiments, laboratory tests, and model simulations to evaluate the influence of physicochemical characteristics of particulate matter (PM) on the performance of a compact, multi-channel PM sizing sensor. The sensor is integrated within a mini air station (MAS) designed to detect particles across 52 channels. The field experiments highlighted the sensor's ability to track hygroscopicity parameter κ-values across particle sizes, noting an increasing trend with particle size. The sensor's capability in identifying the size and mass concentration of different PM types, including ammonium nitrate, sodium chloride, smoke, incense, and silica dust particles, was assessed through laboratory tests. Laboratory comparisons with the Aerodynamic Particle Sizer (APS) showed high consistency (R2 > 0.96) for various PM sources, supported by Kolmogorov-Smirnov tests confirming the sensor's capability to match APSsize distributions. Model simulations further elucidated the influence of particle refractive index and size distributions on sensor performance, leading to optimized calibrant selection and application-specific recommendations. These comprehensive evaluations underscore the critical interplay between the chemical composition and physical properties of PM, significantly advancing the application and reliability of optical PM sensors in environmental monitoring.

A novel methodology to assess optical profilometer stability to discriminate surface roughness

A new method is proposed to investigate the measurement variation of instruments and their ability to discriminate two TA6V surfaces obtained by grinding with SiC grit papers (80 and 120). Three optical measurement technologies included into a single apparatus, namely Confocal Microscopy (CM), Focus Variation (FV) and Coherence Scanning Interferometry (CSI), were used to measure both ground surfaces according to a specific experimental protocol (MorphoMeca Monitoring) based on measurement iterations and repetitions. From the measurements, four indices were built from the Sa roughness parameter to assess the Quality (ratio of the topographical variability over the measurement noise), the Drift (related to surface fluctuations) and the Stability (estimation of the temporal drift using a second order autoregressive model) of the three measurement technologies (modes), as well as their Relevance (computed from an analysis of variance) to discriminate ground surfaces with close roughness. For these investigated surfaces, it was especially highlighted that the Quality Index is four times higher for the CSI mode than for the FV and CM modes. All the used measurement modes experienced small drifting (Drift Index) during the measurements. The CSI mode was slightly more sensitive to drift than the FV and CM modes. The Stability Index indicated that there was no memory effect between two acquisitions for each measurement mode, i.e., the temporal drift did not depend on the measurement mode. Moreover, the three measurement modes are able to discriminate the two ground surfaces with the same accuracy through the Sa parameter. However, the Sa values may vary depending on the measurement modes, and it was finally shown that the Sa parameter is minimized by 0.03 μm for the FV mode compared with the CSI mode, due to its smoothing effect.

Advances in Aeroengine Cooling Hole Measurement: A Comprehensive Review.

Film cooling technology is of great significance to enhance the performance of aero-engines and extend service life. With the increasing requirements for film cooling efficiency, researchers and engineers have carried out a lot of work on the precision and digital measurement of cooling holes. Based on the above, this paper outlines the importance and principles of film cooling technology and reviews the evolution of cooling holes. Also, this paper details the traditional measurement methods of the cooling hole used in current engineering scenarios with their limitations and categorizes digital measurement methods into five main types, including probing measurement technology, optical measurement technology, infrared imaging technology, computer tomography (CT) scanning technology, and composite measurement technology. The five types of methods and integrated automated measurement platforms are also analyzed. Finally, through a generalize and analysis of cooling hole measurement methods, this paper points out technical challenges and future trends, providing a reference and guidance for forward researches.

Predictive dynamic modeling and analysis of blisks through digital representations constructed upon precise geometry measurements

Blade geometric variations generally have a significant impact on the structural dynamics of integrally bladed disks widely used in the advanced aero-engines. This paper presents a holistic research in regard to the predictive dynamic modeling, analysis and experimental verification for a blisk by taking advantage of the advanced 3D optical geometry measurement technology. Geometrically mistuned models (GMMs) are semi-automatically constructed upon the precisely measured blisk geometry by an efficient FE mesh updating strategy. They provide explicit, high-fidelity digital representations of the geometric variations within the integrally manufactured blisk. A ‘Sector Mode Assembling Reduction Technique’ is developed and specifically tailored for efficient dynamic analysis of the large-sized GMMs at a relatively low computational cost and memory requirement. Intensive test campaigns, including forced response tests in the stationary/spinning rig under well-controlled laboratory conditions, are carried out for a full assessment of the GMMs’ dynamic prediction capability. Experimental verification results show that the GMM is able to capture the modal dynamics and resonant vibration of the stationary/rotating blisk with satisfactory accuracy. The physical-reality-based GMM converted directly from the precise geometry measurement data can be considered as a viable and valuable tool for predictive vibration evaluation of blisks. However, its model accuracy exhibits a mode-related dependence on the mesh density. The tradeoff between model accuracy and prohibitive computational cost proved to be the bottleneck of this promising blisk modeling approach.

A novel deep learning algorithm applied to machine vision inspection for surface defects of injection moulded products

In modern industry, the surface defect inspection of injection moulded products is crucial for controlling product quality and optimising the manufacturing process. With the development of optical measurement and computer technology, machine vision inspection methods have been widely adopted instead of manual inspection. However, current machine vision inspection methods are difficult to simultaneously ensure the accuracy and efficiency of surface defect inspection of injection moulded products. Considering this problem, a novel deep learning algorithm applied to machine vision inspection for surface defects of injection moulded products is proposed. To train and evaluate the proposed deep learning algorithm, an image acquisition platform is established and the dataset of surface defects in moulded products is obtained. In the proposed deep learning algorithm, reparameterisation-based convolution modules are employed for feature extraction and feature fusion. A median iterative clustering algorithm based on hierarchical clustering initialisation is proposed to obtain prior anchors that are highly matched with the actual distribution of defect sizes. A novel focus-entire union over covering loss function is utilised for bounding box regression. On these bases, the proposed deep learning algorithm applied to machine vision inspection is evaluated on the dataset of surface defects in moulded products. The experimental results indicate that compared to the traditional inspection algorithms and other deep learning algorithms currently used in machine vision inspection, the proposed deep learning algorithm exhibits superior inspection accuracy and inspection efficiency on the acquired dataset. The inspection precision reaches 0.964, the inspection recall reaches 0.955, and the inference time for each subgraph is only 6.1 ms, confirming its effectiveness.

Optimization of Pipeline Leakage Detection System in Utility Tunnel Based on Finite Element Method

In addressing the problems of delayed detection, inefficient identification, and coverage blind spots in optical fiber‐based pipeline leakage detection within pipe galleries, this study proposes a leakage detection strategy utilizing distributed optical fiber temperature measurement technology. Finite element method is employed to analyze the temperature influence radius around the pipeline leakage hole and a model test is conducted as a validation. The results show that the temperature field image at the leakage site is elliptical, influenced by temperature differences between ambient and liquid. An increase in this temperature difference accelerates changes in the temperature field’s range. Adjustments to the optical fiber’s winding angle and pitch demonstrated that an optimal pitch is 1/24 of the pipeline’s length, with a 45° winding angle. This configuration maximizes the optical fiber’s distribution in detection while maintaining its cost‐effectiveness. When the leakage site is constant, and only the winding mode is altered, it is observed that when the ambient temperature exceeds the liquid temperature in the pipeline, the temperature of the escaping liquid impacts the temperature‐measuring fiber due to gravity, registering approximately 2°C higher than the temperature measured directly at the leakage site. The temperature anomaly from field diffusion is significantly less than that caused by the water flow from the leakage impacting the fiber due to gravity. Conversely, when the ambient temperature is lower than the pipeline’s liquid temperature, the opposite occurs. These research findings offer a novel approach for distributed detection in water supply and drainage pipeline leakage.

Noise and distortion suppression for industrial confocal microscopy

Industrial confocal microscopy is an optical imaging measurement technology used in the fields of material research, defect detection and industrial inspection. Noise will affect the quality of the image and thus affect its performance. We propose a denoising algorithm based on CNN minimisation in this paper. First, we give the object function of the algorithm and the adaptive calculation formula of the capped value. Then, by using the difference convex (DC) optimisation algorithm framework, the sub-gradient optimisation condition, and the feedback framework, we develop a simple and efficient adaptive-stop iterative optimisation algorithm to solve this model and provide the closed solution of the model at each iteration. The experimental results show that for industrial confocal images, our algorithm can not only effectively suppress noise, but also effectively avoid the distortion of denoised images. The signal-to-noise ratio of industrial confocal denoised images is increased by 1.93 times. In addition, experiments show that the algorithm has good noise reduction ability in other optical imaging instruments, and can suppress not only Gaussian noise, but also Gaussian-Poisson noise.

RESEARCH ON 3D MEASUREMENT TECHNOLOGY BASED ON MACHINE VISION

Measurement is an important means for humans to understand and transform the world, and it is the technological foundation for breaking through the forefront of science and solving major problems in economic and social development. The three-dimensional measurement system serves primary national needs, leads national economic development, and ensures national defense security. With the arrival of a new industrial revolution, major industrial countries worldwide have begun to accelerate the strategic deployment of intelligent manufacturing. As an essential component of the construction of smart factories and lighthouse factories, the 3D measurement system will play a vital role in deepening the implementation of the manufacturing power strategy and promoting the high-end, intelligent, and green manufacturing process. In recent years, optical 3D measurement technology represented by surface structured light has developed rapidly and has been widely applied in multiple material processing fields such as forging, casting, and sheet metal. To analyze the manufacturing accuracy of complex parts using surface structured light 3D measurement technology, it is necessary to first scan and reconstruct the overall 3D surface of the part. The reconstructed 3D point cloud data of the part surface should be roughly and precisely matched with the design model. Finally, based on this, data comparison and accuracy analysis should be carried out according to the actual detection requirements of different types of parts. In this process, the accuracy of 3D reconstruction of complex parts and the alignment accuracy between the reconstruction results and the design model directly determine the reliability and accuracy of the final part manufacturing and machining accuracy analysis. This article uses cases to illustrate the application of machine vision in 3D online measurement. The application of three-dimensional measurement technology in online quality inspection and grinding of blades can not only improve the measurement accuracy of online quality inspection of blades but also maintain the relative stability of robot grinding force and improve the grinding effect in robot grinding of aircraft engine blades. Applied to online quality inspection of train wheel hubs, three-dimensional measurement of train wheel adapters and high-speed train wheel size online inspection has been achieved.

Determination of quantity and volume of Carya cathayensis Sarg by line laser scanning combined with the point cloud fusion algorithm

Optical 3D measurement technology plays a vital role in diverse industries, particularly with the advancements in line laser scanning 3D imaging. In this paper, we propose a line laser scanning-based investigation for detecting Carya cathayensis Sarg. The Carya cathayensis Sarg specimens are scanned using a line laser to achieve three-dimensional reconstruction, enabling the calculation of their volume and quantity based on the acquired point cloud map. Through binocular acquisition and subsequent point cloud alignment and fusion, the error in the three-dimensional reconstruction is significantly reduced. The point cloud map facilitates the automatic identification of the number of scanned areas of Carya cathayensis Sarg areas and accurate volume calculations, with an error control of approximately 0.6% when compared to the actual volume. The application of this research in agriculture allows farmers to classify fruit sizes and optimize their selection, thus facilitating intelligent agricultural practices.

Use and Future Development of Optical Measurement Technology in the Study of Wood Surface Roughness CiteSpace-Based Scientometric Analysis (2003 through 2022)

Abstract Although the contact probe measurement technique is excellent for wood surface roughness measurement, it is necessary to reevaluate the advantages and future development direction of optical measurement techniques in this field, given the emergence of optical measurement techniques such as laser technology and the increasing academic interest in wood surface roughness. The traditional review method, due to its rather limited research directions, only provides a macroscopic and qualitative description of certain laws and conclusions. The purpose of this review is to use the bibliometrics theory and method to comprehensively sort out the research hot spots in this field and explore them in depth.

The UHURA project at a glance – motivation and objectives

The European H2020 project UHURA is focusing on the unsteady flow behaviour around high-lift systems and will first time deliver a deeper understanding of critical flow features at new types of high-lift devices of transport aircraft during their deployment and retraction together with a validated numerical procedure for its simulation. UHURA performed detailed experimental measurements in several wind tunnels to obtain a unique data set for validation purposes of Computational Fluid Dynamics (CFD) software, including detailed flow measurements by Particle Image Velocimetry (PIV) and other optical measurement technologies. Advanced CFD methods promising significant improvements in the design lead time are validated against this database to obtain efficient and reliable prediction methods for design.

Preview the Products on Display at Display Week 2023

Preview the Products on Display at Display Week 2023

The future of optical measurement technology

AbstractOptical metrology is one of the key technologies in today's manufacturing industry. It can be generally defined as the science of measuring with light, and it is widely used to evaluate the physical properties of products (or some of their parts or components) and to monitor large infrastructures and facilities. In this article we will review some of the current technologies for optical measurement in different manufacturing industries, the new developments and the trends related to the continuous demand for high‐ precision and high‐efficiency solutions.

Speckle Pattern Improvements for Digital Image Correlation to Capture Small Strains in Tensile Tests on Rock

Digital image correlation (DIC) is a popular optical strain measurement technology for deformation analysis in rock mechanics laboratory testing. Although reliable and repeatable, traditional strain gauge and extensometer measurement techniques have drawbacks including high recurring cost and limited spatial distribution of data. DIC utilizes continuous photography and computer software to track paint speckle pixel displacements of a material deforming under load, producing a full-field strain map for each recorded increment. Although DIC presents an opportunity to overcome the limitations of traditional methods, significant precision and care is required to track typical total displacements of 0.005 mm (0.01% strain) in Brazilian tensile stress (BTS) tests of igneous and sedimentary specimens measuring 47.6 mm diameter. For computer algorithms to precisely track individual pixels between frames, it is often necessary to apply a unique speckle pattern conforming to several criteria to the rock specimen. A variety of speckle application techniques have been reported in rock mechanics literature; however, the importance of a high-quality speckle pattern and resulting influence on the accuracy of DIC results is frequently overlooked. The laboratory testing program in this research utilized 2-Dimensional DIC on BTS tests to investigate the cost, efficiency, ease of application, and effectiveness for several speckle application methods. In addition to testing traditional spraypaint, airbrush, and stamp application methods, an innovative laser engravement speckle application technique was developed in this research that provides more reliable DIC results. This research provides practical speckle pattern application recommendations for small strain 2D DIC measurements.

Decoupling calibration method of long focal length camera using vanishing point

Optical measurement and perception technology is widely used in the field of smart energy. The accurate calibration of the internal and external parameters of the camera in the optical system is very important for the application of the system in three-dimensional (3D) reconstruction and geometric measurement. At present, the mainstream camera calibration methods include Zhang’s calibration method and Tsai’s calibration method. These methods all choose to calculate the distortion parameters together with the camera’s internal parameters. For long focal length and narrow-field-of-view cameras with smaller perspective distortion, the coupling calculation of parameters may cause inaccurate calibration parameters and more time-consuming problems. To improve the calibration accuracy of the long focal length camera, we propose an efficient noniterative camera calibration method, based on the equation relationship between the vanishing point coordinates and the first-order single-parameter division lens distortion coefficient, and based on the radial distortion separation model as well as the corner subpixel coordinates and checkerboard 3D space points. The spatial point correspondence is solved to obtain the homography matrix to complete the calculation of the internal parameters of the camera. Our work has potential applications in photovoltaic troubleshooting and intelligent inspection. It may also contribute to the practical application of the sensor in intelligent energy.

Spatial-mode Optical Measurement Technology to Support Diverse Global Services in the Future

Spatial-mode Optical Measurement Technology to Support Diverse Global Services in the Future

Review of Refractive Index-Matching Techniques of Polymethyl Methacrylate in Flow Field Visualization Experiments

The development of modern computational fluid dynamics (CFD) technology provides many preliminary references for experimental design. In addition, the CFD calculation results verified by experiments can display enormous microdata in areas that are difficult to measure through experiments, as an extension. This can make measurements more reasonable and effective, shorten measurement times, and save manpower and capital significantly. Therefore, it is vital to verify the accuracy of CFD calculation results, especially in cases of complex structures and multiphase flows. The results of model tests can be utilized in a prototype experiment by properly designing a test section and selecting a working fluid if the Reynolds similarity criterion is met. Optical measurement technology is a noninvasive measurement method, and the impact on the flow field can be almost negligible. It is advised to use transparent materials and prepare a refractive index-matching (RIM) fluid to obtain a good optical path. Polymethyl methacrylate (PMMA) is widely used in flow field visualization experiments because of its good light transmission and mechanical strength. This review is aimed at introducing the current status of different flow field measurement techniques; moreover, it is intended to help the readers to become more familiar with the principles of RIM, the characteristics, applications, and usage suggestions of various RIM fluid schemes of PMMA, providing references for researchers in the design, preparation, and conducting stages of flow field visualization measurement experiments. This review is divided into five sections. In the introduction section, Chapter 1, relevant research developments and related results of flow field measurements are presented, followed by the innovations and benefits of this paper. In Chapter 2, the flow field visualization measurements are presented and a derivation is shown. In Chapter 3, some RIM fluid schemes of PMMA and their applications are given, which are very valuable for peers. In Chapter 4, the measurement and analysis of some physical properties are described. In the RIM process, it is necessary to focus on the RI, density, dynamic viscosity, compatibility, stability, safety, and cost of RIM fluids. These factors greatly impact the accuracy of experimental results, experimental progress, and safety of the experimenters. Based on the analysis and our practical experience, some suggestions are given for preparing and using RIM fluids. In the conclusion section, Chapter 5, the results and practical implications of this paper are summarized.

Improved calibration method for displacement transformation coefficient in optical and visual measurements

Optical and visual measurement technology is used widely in fields that involve geometric measurements, and among such technology are laser and vision-based displacement measuring modules (LVDMMs). The displacement transformation coefficient (DTC) of an LVDMM changes with the coordinates in the camera image coordinate system during the displacement measuring process, and these changes affect the displacement measurement accuracy of LVDMMs in the full field of view (FFOV). To give LVDMMs higher accuracy in the FFOV and make them adaptable to widely varying measurement demands, a new calibration method is proposed to improve the displacement measurement accuracy of LVDMMs in the FFOV. First, an image coordinate system, a pixel measurement coordinate system, and a displacement measurement coordinate system are established on the laser receiving screen of the LVDMM. In addition, marker spots in the FFOV are selected, and the DTCs at the marker spots are obtained from calibration experiments. Also, a fitting method based on locally weighted scatterplot smoothing (LOWESS) is selected, and with this fitting method the distribution functions of the DTCs in the FFOV are obtained based on the DTCs at the marker spots. Finally, the calibrated distribution functions of the DTCs are applied to the LVDMM, and experiments conducted to verify the displacement measurement accuracies are reported. The results show that the FFOV measurement accuracies for horizontal and vertical displacements are better than ±15 µm and ±19 µm, respectively, and that for oblique displacement is better than ±24 µm. Compared with the traditional calibration method, the displacement measurement error in the FFOV is now 90% smaller. This research on an improved calibration method has certain significance for improving the measurement accuracy of LVDMMs in the FFOV, and it provides a new method and idea for other vision-based fields in which camera parameters must be calibrated.