Non-contact Measurement Method Research Articles

Interferometric-scale full-field vibration measurement by a combination of digital image correlation and laser vibrometer

Digital Image Correlation (DIC) is a crucial noncontact full-field optical measurement method used in various fields. However, in practical applications, DIC is affected by systematic and random noises, leading to experimental resolutions lower than theoretical ones. In this study, we proposed a laser Doppler vibrometer guided DIC to perform vibration measurements. 3D-DIC obtains a sequence of out of displacement field initially. A three-dimensional frequency domain collaborative filtering (3D-FDCF) method that utilizes Laser Doppler vibrometer (LDV) single-point data to assist in processing of the displacement field sequence pixel-wise is adopted. The 3D-FDCF method combines lowpass filtering in the spatial frequency domain with LDV-guided bandpass filtering in the temporal frequency domain. The effectiveness of the 3D-FDCF method is demonstrated through a comparison among DIC data, the filtered DIC data, and continuously scanning LDV data. The experiment results demonstrate the 3D-FDCF method's capability in measuring vibration amplitudes of several hundred nanometers with the size of a test sample of about 100 mm × 100 mm, supporting the statement of interferometric scale full-field vibration measurement by DIC with the guidance of the LDV data.

A Noncontact Method for Simultaneous Measurement of di/dt and dv/dt

This letter proposes a non-contact method for simultaneously measuring the current and voltage change rates by Rogowski coils. The dv/dt measurement capability is achieved based on electric field coupling, which is incorporated into the state-of-the-art Rogowski coil based current sensing solutions. The application of the proposed method for power semiconductor devices is demonstrated by a case study of an IGBT switching circuit. The Rogowski coils are integrated with a Printed Circuit Board (PCB) and fit with the IGBT module terminals. The comparable results from high-performance commercial instruments verify the di/dt and dv/dt measurement accuracy of the presented compact and cost-effective solution.

Thermoelastic wave generation and its longitudinal wave propagation measurement by a microscopic optical interferometer

Laser ultrasonics is a noncontact measurement method that uses a laser-induced elastic wave source in combination with an optical surface displacement-tracking system. This study compared the performances of two optical interferometers with different characteristics when applied to measurement of pulsed thermoelastic waves. The surface displacement-tracking system was designed to measure the center of the microscopic view. A pulsed laser beam irradiated a black ink layer to generate the thermoelastic waves. The out-of-plane displacement on the axially opposite side was then measured using either a Michelson interferometer or a Sagnac interferometer. The objective lens of the system was of a type commonly used in biological observations. The Michelson interferometer estimated a maximum displacement of 0.43 nm and a maximum sound pressure of 24.7 kPa. The signal-to-noise ratios from 16 averages were 14.9 dB (Michelson interferometer) and 19.2 dB (Sagnac interferometer). Furthermore, this paper compares the performance of the numerically estimated Sagnac interferometer outputs calculated from the measured Michelson interferometer outputs with the experimentally obtained Sagnac interferometer outputs. The numerically estimated Sagnac interferometer’s output was shown to be identical to the experimentally acquired output. The Michelson interferometer requires a higher average operating frequency (i.e., it needs a longer data acquisition time), although this interferometer does offer superior displacement output linearity. This property enables calculation of the sound pressure from the displacement amplitude. These findings indicated that combination of the measurement points of the Sagnac interferometer with those of the sparsely distributed Michelson interferometer reduced the measurement time when compared with a single use of the Michelson interferometer while also maintaining the data acquisition quality.

Nonlinear optimization DIC method inspired by unsupervised learning for high order displacement measurement

Digital Image Correlation (DIC) is the most widely used non-contact full-field strain measurement method, but due to the influence of subset calculations in principle, measuring complex deformation with high strain gradients within the subset remains a challenge. DIC based on neural networks performs well in complex deformation measurement scenarios, but its measurement accuracy and generalization ability depend on extensive training sets. This paper proposes a nonlinear optimization DIC method inspired by unsupervised learning that requires only a single pair of images. Unlike traditional unsupervised algorithms of optical flow estimation or Particle Image Velocimetry (PIV), the shape function in traditional DIC is incorporated into the loss function. This allows the use of only the reference image and the deformed image as input dataset, and the correct displacement field can be output after parameter optimization through training. This method does not require additional training sets to measure high-order strain fields like traditional neural networks-based DIC. The proposed method has demonstrated promising results in simulation experiments for high-order strain measurement and does not require additional datasets of the same type. In the measurement of the star-shaped displacement fields, its accuracy is better than the traditional DIC based on the subset, and it maintains convergence even when the strain is large, a situation where traditional DIC fails to converge. In addition, compared with the network obtained by supervised training as a pre-trained model, the method proposed in this paper can achieve superior results. The methods of the article can theoretically be applied to the result optimization of other networks beyond those discussed in this paper.

Nondestructive measurement of terahertz optical thin films by machine learning based on physical consistency

Optical scattering measurement is one of the most commonly used methods for non-contact online measurement of film properties in industrial film manufacturing. Terahertz photons have low energy and are non-ionizing when measuring objects, so combining these two methods can enable online nondestructive testing of thin films. In the visible light band, some materials are transparent, and their thickness and material properties cannot be measured. Therefore, a method based on physical consistency modeling and machine learning is proposed in this paper, which realizes the method of obtaining high-precision thin film parameters through single-frequency terahertz wave measurement, and shows good performance. Through the experimental measurement of organic material thin films, it is proved that the proposed method is an effective terahertz online detection technology with high precision and high throughput.

Non-contact near-field cavity perturbation method for quantitative dielectric measurement and metallic defect inspection

Low dielectric constant (low-k) materials are essential in electronic industry aiming at new generation high-speed communications. Dielectric constant of these materials are measured by standard procedures and instruments with conventional contact configuration. Non-contact and in-situ techniques for low-k dielectric measurement are highly demanded in practice and worth of investigation. We hereby proposed a near-field microwave probe (NFMP) to accurately measure dielectric constant of low-k samples in a non-contact manner with a quantitative electromagnetic (EM) cavity perturbation theory. An NFMP set was designed, optimized by finite-element method (FEM) and fabricated with handy materials in the lab. Frequency response of the NFMP was tested experimentally and further used for subsequent frequency displacement analysis. Various low-k samples were tested by the non-contact NFMP set and dielectric constant were extracted based on the field perturbation theory. The relative error was obtained less than 0.5 % for low-k materials. The NFMP was then fixed on a micrometer stage and worked in a line-scan mode to inspect conductive defects in a low-k substrate. Both surface and subsurface defects were inspected by analyzing displaced central frequencies. The NFMP system is promising to facilitate quantitative and non-contact dielectric property measurement in electronics.

An acoustic weighing method based on oscillation signal and feature enhanced network

Acoustic weighing is a promising method for non-contact mass measurement of tiny objects as it avoids contamination and contact losses. However, due to the highly nonlinear nature of the acoustic field, some parameters of the mechanism model of acoustic weighing cannot be accurately simulated, thereby reducing the accuracy of acoustic weighing. To improve the accuracy of acoustic weighing, we propose an acoustic weighing method based on oscillating signals and feature enhancement network. Firstly, to drive the object oscillation and collect oscillation data, an acoustic levitation-based data acquisition system is constructed. Then, to break the limitations of the mechanism model, a feature enhancement network named CNN-BiLSTM-SE is proposed, which directly establishes the correlation between oscillating signals and actual mass. Finally, these data are used to train and test the proposed network model, validating the effectiveness of the model. Experimental results show that the method achieves high accuracy in measuring object mass, following the actual measurements with remarkable consistency. In addition, our approach is also suitable for acoustic weighing of small and sensitive objects, opening up new perspective for the study and application of nonlinear acoustic systems.

Auto-Alignment Non-Contact Optical Measurement Method for Quantifying Wobble Error of a Theodolite on a Vehicle-Mounted Platform

Auto-Alignment Non-Contact Optical Measurement Method for Quantifying Wobble Error of a Theodolite on a Vehicle-Mounted Platform

Application of non-contact video quantitative measurement method in reservoir bank landslide monitoring

The geological structure of the reservoir bank landslide is complex and intricate. After deformation and damage, it causes river blockage, surges, and loss of people’s lives and property, posing a huge threat. At present, in academia and engineering applications, a large number of techniques such as inclinometers, rain gauges, and surface GNSS deformation monitoring are still used for monitoring landslides on reservoir banks. This type of monitoring method has the problem of “point to surface” which can easily lead to missed detection and reporting in some areas, some disaster points are close to water and steep, difficult to reach, and equipment installation is difficult. This work designs and implements a non-contact video quantitative monitoring system for surface deformation of geological disaster. By constructing a deep learning neural network, deformation area recognition and displacement quantitative calculation are achieved; By obtaining continuous images for a long time, draw the surface displacement-time curve, and output the surface deformation data and landform changes of the disaster. Meanwhile, this work explores the impact of different lighting conditions on the recognition results of target areas. This work can provide non-contact monitoring methods and dynamic warning support for large-scale monitoring of geological disasters.

Non-destructive characterization of pore structure and chloride diffusion coefficient of cementitious materials with modified non-contact electrical resistivity method

The intricate pore structure of cement-based materials passively influences chloride ion transport and mechanical properties. Existing non-contact electrical resistivity measurement (NC-ERM) methods lack precision for rigorous studies. the NC-ERM was upgraded in this research, which is suitable for assessing the pore structure and transport characteristics of hardened cementitious substrates. The results obtained from this method closely correspond to those obtained from CEMHYD3D, Mercury intrusion porosimetry (MIP), and other methods. Additionally, the impact of mixture proportions on the resistivity, pore structure parameters, and chloride ion diffusion coefficient of cementitious materials is discussed. With an increase in sand ratio and sand-to-stone ratio, the resistivity exhibits an initial rise followed by a decline. Chloride diffusion of 5 wt% NaCl-saturated specimens is 1.2–1.3 times higher than 3.5 wt% NaCl. This study provides a novel non-destructive, convenient and accurate method for characterising the pore structure and testing the transport properties of cementitious materials.

Non-Contact Measurement of Alcohol Content Based on Near Infrared Spectroscopy

In order to solve the influence of other external factors on the measurement concentration of alcohol solution, a non-contact measurement method based on near-infrared spectroscopy and BP neural network temperature correction method was proposed in this paper. This method takes into account the influence of temperature on the light intensity of alcohol liquid solution in the detection process, and trains it together with the measurement data as the input of neural network. At the same time, it is compared with the index fitting algorithm, which proves that the method has a good effect on the non-contact measurement of alcohol content.

A non-contact method for weighting of aggregate pile based on binocular vision

Concrete is indispensable in contemporary industry, and the weighing of aggregates directly determines the quality of concrete preparation. In response to the difficulty of traditional methods in meeting the industrial requirements for accuracy, efficiency, and cost of measurement, this paper proposes a non-contact bone pile weight measurement method based on binocular vision. Firstly, the on-site image is obtained through a binocular camera, and the camera parameters are used to improve the image edge information and preprocess the image. Then, the improved semi global matching (SGM) algorithm is used to improve computational efficiency, obtaining three-dimensional information of the aggregate pile for volume calculation. Based on the watershed algorithm and T-S inference, the aggregate clearance rate is calculated, and the initial volume is corrected. Finally, a linear relationship is established between the density of the aggregate pile and the clearance rate, and the weight of the aggregate pile can be obtained by the density formula. The experimental results on different sizes of aggregate piles shows that the average error of the experiment is less than 4%. Efficiency of improved SGM matching algorithm has increased several times compared to the original algorithm, providing a low-cost and efficient measurement method for industrial aggregate weighing.

An effective cross-scenario remote heart rate estimation network based on global-local information and video transformer.

Remote photoplethysmography (rPPG) technology is a non-contact physiological signal measurement method, characterized by non-invasiveness and ease of use. It has broad application potential in medical health, human factors engineering, and other fields. However, current rPPG technology is highly susceptible to variations in lighting conditions, head pose changes, and partial occlusions, posing significant challenges for its widespread application. In order to improve the accuracy of remote heart rate estimation and enhance model generalization, we propose PulseFormer, a dual-path network based on transformer. By integrating local and global information and utilizing fast and slow paths, PulseFormer effectively captures the temporal variations of key regions and spatial variations of the global area, facilitating the extraction of rPPG feature information while mitigating the impact of background noise variations. Heart rate estimation results on the popular rPPG dataset show that PulseFormer achieves state-of-the-art performance on public datasets. Additionally, we establish a dataset containing facial expressions and synchronized physiological signals in driving scenarios and test the pre-trained model from the public dataset on this collected dataset. The results indicate that PulseFormer exhibits strong generalization capabilities across different data distributions in cross-scenario settings. Therefore, this model is applicable for heart rate estimation of individuals in various scenarios.

Особенности расчета температуры резания при высокоскоростном фрезеровании алюминиевых сплавов без применения СОЖ

Introduction. The calculation of temperature during high-speed milling of aluminum alloys is of interest, since temperature can act as one of the main limiting factors in choosing rational milling modes. This is especially important when milling thin-walled products used in aircraft construction, since its high values can lead to local warping of the structure. It is not possible to control the temperature factor in production conditions, which makes it necessary to develop a mathematical model for calculating temperature. The purpose of the work is to develop a methodology for predicting the cutting temperature during high-speed milling of aluminum alloy workpieces for cutting conditions, in which it is not possible to use cutting fluid. Methods. This paper presents experimental studies of the cutting temperature during high-speed milling of aluminum alloy workpieces without the use of cutting fluid using non-contact temperature measurement methods. The results obtained were used to determine the coefficients substituted into formulas for calculating temperatures on the front and back surfaces of the cutting blade. Results and discussions. Based on the results of experimental tests and theoretical modeling, a temperature graph is drawn up. A comparison of experimental studies of milling of aluminum alloy D16T, with changing cutting conditions (the cutting speed changed) with theoretical data, gave a satisfactory result. The average relative error when comparing experimental data with theoretical one is 6.05 %. Based on experimental data, it can be concluded that the comparison of experimental data for measuring cutting temperatures is in satisfactory agreement with the proposed method of theoretical calculation of temperatures. The advantage of this technique is that it allows, without time-consuming and costly experimental studies, theoretically calculate (forecast) the temperatures on the front and back surfaces of the cutting blade, as well as the cutting temperature, for those narrow milling conditions, where effective heat removal from the cutting zone is impossible. It can also be used for milling aluminum alloys, the mechanical and thermophysical properties of which differ.

Research on Coaxiality Measurement Method for Automobile Brake Piston Components Based on Machine Vision

Aiming at addressing the problem of the online detection of automobile brake piston components, a non-contact measurement method based on the combination of machine vision and image processing technology is proposed. Firstly, an industrial camera is used to capture an image, and a series of image preprocessing algorithms is used to extract a clear contour of a test piece with a unit pixel width. Secondly, based on the structural characteristics of automobile brake piston components, the region of interest is extracted, and the test piece is segmented into spring region and cylinder region. Then, based on mathematical morphology techniques, the edges of the image are optimized. We extract geometric feature points by comparing the heights of adjacent pixel points on both sides of the pixel points, so as to calculate the variation of the spring axis relative to the reference axis (centerline of the cylinder). Then, we extract the maximum variation from all images, and calculate the coaxiality error value using this maximum variation. Finally, we validate the feasibility of the proposed method and the stability of extracting geometric feature points through experiments. The experiments demonstrate the feasibility of the method in engineering practice, with the stability in extracting geometric feature points reaching 99.25%. Additionally, this method offers a new approach and perspective for coaxiality measurement of stepped shaft parts.

Multi-View consistency-based point cloud registration method with low overlap rate

Accurate and efficient workpiece measurement is crucial for workpiece processing and quality monitoring. Non-contact optical measurement methods have gained more attention due to their simplicity, efficiency, and flexibility compared to complicated and inefficient contact measurement methods. Multi-view registration of measurement data is a key issue in workpiece measurement, as it relies on the system’s geometric accuracy and motion stability, presenting challenges such as the insufficient overlap of multi-viewpoint cloud data and cumulative error. To address these challenges, this paper proposes a multi-view planning and registration algorithm with a low overlap rate. The multi-view planning algorithm employs a greedy method to plan the scanning viewpoints of the workpiece to obtain complete point cloud data efficiently. The multi-view registration algorithm extracts features using a multi-scale geometric feature extraction network, matches the features based on the Hungarian algorithm, builds a graph, and optimizes workpiece positions based on the G2O algorithm for multi-view registration, effectively reducing cumulative error. Measurement experiments on blade workpieces confirm the feasibility of the proposed algorithms.

Non-contact measurement method of displacement of spherical joints in long-span space steel structures

For long-span space steel structures after a long period of operation, it is crucial to quickly and accurately measure the deformation for structural safety evaluation. To address the challenges in deformation measurement of space steel structures, this paper presents a non-contact, three-dimensional coordinate measurement method for key ball joints in their spatial positions. A high-precision Laser Total Station is utilized to measure the surface of the ball joints at multiple points. Three-dimensional coordinates of the center of the ball joints are then accurately determined by using three-dimensional analytical method and the least square error method. Subsequently, the deformation of key joints of the long-span space structures is obtained by comparing the determined coordinates with their initial coordinates. An engineering application by adopting the propose method to measure the deformation of a large-span steel structure gymnasium in Guangdong Province is presented. This method not only can be used to evaluate the safety of existing space steel structures, but also can be applied to rapid measurements and positioning of new long-span steel structures to improve the measurement efficiency and personnel safety.

Explicit model predictive control of magnetorheological suspension for all-terrain vehicles with road preview

The integration of magnetorheological (MR) semi-active suspension systems in all-terrain vehicles (ATV) has garnered significant attention due to their ability to enhance damping performance and off-road capabilities. However, traditional control strategies result in poor control accuracy and limited vibration reduction effects when facing complex road excitations and impact disturbances. With technological advancements, enhanced vehicle environmental perception and road sensing capabilities have made it possible to implement model predictive control (MPC) for vehicle suspensions. Nevertheless, traditional MPC is limited in vehicle suspension applications due to its high computational complexity. To address these issues, this study introduces an explicit model predictive control based on road preview (EMPC-P). Firstly, road data obtained through a non-contact measurement method enables the system to perceive road excitation information in advance. Subsequently, a 7 Degree-of-Freedom (7-DOF) suspension model incorporating road excitations is constructed. By adhering to system constraints and employing a multiparameter optimization method, the control problem based on rolling optimization is transformed into an explicit polyhedral system. The offline precomputation of control state relations enhances the computational efficiency of the control system. Through this approach, the designed EMPC allows the vehicle suspension system to make optimal control decisions quickly and accurately in response to complex driving conditions, thus improving the damping effect of the system. Through a combined approach of simulation and experimental validation, the designed EMPC-P controller is compared with the Skyhook controller under preview and non-preview states, respectively. Empirical testing confirms that the EMPC-P exhibits superior damping effects, significantly improving vehicle ride comfort and handling stability.

Design and Implementation of a Linear Active Disturbance Rejection Control-Based Position Servo Control System of an Electromotive Valve for Exhaust Gas Recirculation.

An exhaust gas recirculation (EGR) valve is used to quickly and dynamically adjust the amount of recirculated exhaust gas, which is critical for improving engine fuel economy and reducing emissions. To address problems relating to the precise positioning of an electromotive (EM) valve under slowly varying plant dynamics and uncertain disturbances, we propose a servo control system design based on linear active disturbance rejection control (LADRC) for the EGR EM valve driven by a limited angle torque motor (LATM). By analyzing the structure of the LATM and the transmission, the dynamic model of the system is derived. In addition, to solve the problems caused by slowly varying plant dynamics and uncertain disturbances, we combine the effects of uncertain model parameters and external disturbances as the total disturbance, which is estimated in real time by an extended state observer (ESO) and then compensated. In addition, accurate angular information is obtained using a non-contact magnetic angle measurement method, and a high-speed digital communication channel is established to help implement a closed-loop position control system with improved responsiveness and accuracy. Simulation and experimental results show that the proposed servo system design can effectively ensure the precision and real-time performance of the EM valve under slowly changing plant dynamics and uncertain disturbances. The proposed servo system design achieves a full-stroke valve control accuracy of better than 0.05 mm and a full-stroke response time of less than 100 ms. The controlled valve also has good robustness under shock-type external disturbances and excellent airflow control capability. The repeatability of the airflow control is generally within 5%, and the standard deviation is less than 0.2 m3/h.

Measurement and assembly methods for bolted flange joints using three-dimensional digital image correlation

Bolted flange joints are extensively used in pressure vessels and piping equipment. The assembly coaxiality accuracy and bolt pre-tightening force are particularly important in causing the risk of seal and leakage failure. This paper proposed a novel non-contact measurement and assembly adjustment method to reduce the coaxiality angle deviation efficiently. The flange joint is first bolted according to standard flange joint assembly guidelines and then adjusted using the proposed method. In the proposed method, the surface deformation and the coaxiality of the flange are evaluated using a 3D-DIC (three-dimensional digital image correlation) technique; RMS (root mean square) of the surface deformation is used to drive the correction of the bolts to further reduce the coaxiality angle deviation. Compared with existing bolting patterns, the established measurement and assembly adjustment method, which combines 3D-DIC measurement and adjustment based on RMS, can effectively reduce the coaxiality angle deviation. The experiments using a correction strategy demonstrated that the coaxiality angle deviation is reduced by 48.9 % and 60.1 % on average compared with the well-known star bolting pattern and modified star bolting pattern provided by ASME PCC-1, respectively, and even by 30.6 % and 51.9 % compared with their rotational pass patterns. Further experiments with an iterative strategy showed that the coaxiality angle deviation could be reduced by around 70 % and 75 %, tending to be stable around 0.01°–0.035°, after only 5 iterative adjustments.