Non-contact Measurement Research Articles

Non-contact measurement of torque in rotational truck flywheel using resistance strain gauges based on wireless telemetry system

Non-contact measurement of torque in rotational truck flywheel using resistance strain gauges based on wireless telemetry system

Penetrating Barriers: Noncontact Measurement of Vital Bio Signs Using Radio Frequency Technology.

The noninvasive measurement and sensing of vital bio signs, such as respiration and cardiopulmonary parameters, has become an essential part of the evaluation of a patient's physiological condition. The demand for new technologies that facilitate remote and noninvasive techniques for such measurements continues to grow. While previous research has made strides in the continuous monitoring of vital bio signs using lasers, this paper introduces a novel technique for remote noncontact measurements based on radio frequencies. Unlike laser-based methods, this innovative approach offers the advantage of penetrating through walls and tissues, enabling the measurement of respiration and heart rate. Our method, diverging from traditional radar systems, introduces a unique sensing concept that enables the detection of micro-movements in all directions, including those parallel to the antenna surface. The main goal of this work is to present a novel, simple, and cost-effective measurement tool capable of indicating changes in a subject's condition. By leveraging the unique properties of radio frequencies, this technique allows for the noninvasive monitoring of vital bio signs without the need for physical contact or invasive procedures. Moreover, the ability to penetrate barriers such as walls and tissues opens new possibilities for remote monitoring in various settings, including home healthcare, hospital environments, and even search and rescue operations. In order to validate the effectiveness of this technique, a series of experiments were conducted using a prototype device. The results demonstrated the feasibility of accurately measuring respiration patterns and heart rate remotely, showcasing the potential for real-time monitoring of a patient's physiological parameters. Furthermore, the simplicity and low-cost nature of the proposed measurement tool make it accessible to a wide range of users, including healthcare professionals, caregivers, and individuals seeking to monitor their own health.

Intelligent mobile robot for contagious disease treatments in hospitals

This paper provides a novel and applicable work that builds a real system for disinfecting the air and surfaces of the environment in a hospital room, with a non-contact measurement system for supporting contagious disease treatments in hospitals. The system is built on an intelligent mobile robot system that operates autonomously in a simulated real treatment room. The research team uses a new positioning algorithm. It is a combination of data from the Lidar sensor, encoder, and Extended Kalman filter. The program that applies segmentation and image feature extraction algorithms is developed to meet requirements of real-time environment mapping in the room. Control algorithms for moving and avoiding obstacles are also proposed. Next, techniques for collecting health data including patient identification, body temperature, and blood oxygen index via wireless sensor network are also mentioned in the article. Analysis and experimental results show qualified outcomes and promise. The main contribution of the paper can be listed as follows.•Design and build a new CEE-IMR, an intelligent mobile robot that can regconize patients, guide and lead them walking in hospitals, especially keep a safe distance avoiding contagious deseases.•A novel framework for controlling the robot is proposed. The robot can move flexible, avoid obstacles, etc. based on advanced control algorithms. A new control mechanism is also proposed.•Methods of collecting data and processing medical data to support either patients or doctors to improve the effecency in hospitals in contagious disease management.

Aerosolization ocular surface microorganisms accumulation effect during non-contact tonometer measurements

PurposeThis study aimed to verify that aerosolization ocular surface microorganisms (AOSMs) accumulated during non-contact tonometry (NCT) measurements.MethodsA total of 508 participants (740 eyes) were enrolled in the study. In Experiment 1, before NCT was performed on each eye, the air was disinfected, and environment air control samples were collected via Air ideal® 3P (Bio Merieux). During NCT measurements, microbial aerosol samples were collected once from each eye. In Experiment 2, we collected initial blank control samples and then repeated Experiment 1. Finally, in Experiment 3, after the background microbial aerosol investigation, we cumulatively sampled AOSMs from each 10 participants then culture once, without any interventions to interrupt the accumulation. The collected samples were incubated and identified using matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry (MALDI-TOF-MS).ResultsPathogenic Aerococcus viridans and other microorganisms from human eyes can spread and accumulate in the air during NCT measurements. The species and quantity of AOSMs produced by NCT measurements can demonstrate an accumulation effect.ConclusionAOSMs generated during NCT measurements are highly likely to spread and accumulate in the air, thereby may increase the risk of exposure to and transmission of bio-aerosols.

Noncontact Measurements of Resonance of Small Round Liquid Surfaces Using Sound Wave to Determine Surface Tension.

Various methods have been developed for measuring the surface tension of liquids, and the present study proposes a new method for measuring the surface tension of liquids. A small (9 mm diameter) round liquid surface was excited by sound waves with a common speaker. Nine liquids possessing various physical properties and functional groups were employed, and three resonance frequencies (frs) were observed for each liquid in a frequency range of 20-180 Hz. The resonances were analyzed with a forced oscillation model. In addition, the amplitudes and phases of the resonance oscillations at various positions of the liquid surface were measured, and the total deformations of the liquid surface were determined. The deformation was compared with the Bessel functions, and the oscillation modes and boundary conditions were decided. Finally, proportional relationships between frs and σ0.5ρ-0.5 (σ: surface tension, ρ: density) with high correlations were obtained, which were supported by a new theoretical equation using hydrodynamics.

Non-contact mechanical Q-factor measurement system based on electromagnetic acoustic transducer

The mechanical quality factor (Q-factor), which is the reciprocal of the vibration loss constant, is one of the most important parameters in vibration engineering; however, there are no methods for its precise measurement. Q-factor databases are thus commonly used. This study proposes a completely non-contact measurement system for the Q-factor that combines non-contact excitation (achieved using an electromagnetic acoustic transducer) with non-contact support (achieved using near-field ultrasonic levitation based on two Langevin transducers). The proposed method was used to measure the Q-factor for a stainless steel (SUS304) sample (thin cylindrical rod with a diameter of 1.5 mm and a length of 80 mm)and a duralumin (A2017). The 5 times average Q-factor was 2010 with standard deviation of 50 for stainless steel (SUS304), and 49,000 with standard deviation of 3900 for duralumin (A2017). The proposed method also allowed for the measurement of Young’s modulus, resulting in 217.17 ± 0.34 GPa for stainless steel (SUS304), and 71.39 ± 0.20 GPa for duralumin (A2017).

Non-Contact Eddy Current Conductivity Measurements as an Effective Tool for Evaluating Aluminum Alloys in Aircraft

ABSTRACT Aluminum alloys (AAs) are pivotal materials in modern aircraft due to their superior mechanical properties and low weight. The structural integrity of these alloys, crucial for aircraft safety, heavily depends on heat treatment processes that alter their mechanical characteristics. Nondestructive evaluation (NDE) techniques, such as eddy current (EC) conductivity measurements, play a vital role in assessing these alloys throughout their lifecycle. EC methods enable the measurement of electrical conductivity, a structure-sensitive parameter that correlates with mechanical properties affected by heat treatments and operational stresses. This paper reviews the application of EC conductivity measurements in the aerospace industry, focusing on their role in assessing AA structural integrity. It discusses how EC methods can penetrate non-conductive coatings, crucial for in-service measurements without surface removal. Recent developments include a novel small-size EC probe and signal processing algorithms aimed at enhancing sensitivity to conductivity changes through dielectric coatings, up to 0.5 mm thick, commonly found in aircraft structures. Key findings include analyses of specific electrical conductivity (SEC) changes in AAs due to heat treatment deviations and long-term operational stresses, crucial for predicting residual life and maintaining safety standards. Case studies on aircraft wing skins and helicopter rotor blades demonstrate the practical application of EC conductivity meters in identifying critical damage zones. The methodology proves effective in evaluating localized degradation based on SEC distributions, thereby enhancing maintenance efficiency and aircraft safety. Overall, this research underscores the significance of EC conductivity measurements in advancing NDE practices for AAs in aircraft applications. The methodologies and findings presented aim to improve safety, durability assessment, and maintenance efficiency in the aerospace industry.

Synthesis and upconversion color Tunability luminescence of K5Yb(MoO4)4 phosphor doped with Er3+and optical temperature sensing applications

A series of double molybdates with palmierite-related structure phosphors K5Yb1-x (MoO4)4:xEr3+ were synthesized by a solid-state method. It has been demonstrated that the K5Yb1-x (MoO4)4: xEr3+ phosphors are capable of exhibiting the characteristic green and red UC emission of Er3+ ions with excitation at 980 nm. Moreover, the green light emission is far more than the red light emission, so that the sample emits a powerful green light, which belongs to the two-photon absorption process. The upconversion efficiency is peaked when the content of Er3+ ions is 10 mol %. The optical thermometry properties of phosphors were explored by observing that the green UC emission intensity is temperature dependent. The maximum sensor sensitivity of the studied phosphor was discovered to be about 1.61%K−1 at the optimum doping concentration. And the phosphor is demonstrated to have high thermal stability by temperature cycling test. Eventually, a green light-emitting diode device was realized by using synthesized particles and a 980 nm near-infrared chip, which can emit a more obvious green light when the voltage reaches 1.80 V and the current can reach 800 mA, thus confirming its applicability in solid-state lighting. And the LED devices have been tested for life stability with little or no light degradation. These properties make the phosphors not only suitable for non-contact optical temperature measurement, but also able to be applied to solid state lighting.

Band gap generation in cantilever beams through periodic material removal

Traditional methods for generating band gaps in beams usually involve adding periodic elements like tuned mass dampers or masses, or applying complex geometrical changes. This research suggests a subtraction-based method achieved by removing material in the thickness direction through straightforward machining operations, thus forming periodic cells. The numerical studies start with band gap analysis, using periodic theory to assess different periodic cell configurations. This is followed by numerical and experimental studies on cantilever beams, each containing a set number of these periodic cells. Non-contact vibration measurements are conducted on one plain and six machined aluminum beams using a multipoint laser vibrometer and an automated impact hammer. The experimental findings corroborate the band gaps predicted by the numerical model, confirming the effectiveness of this approach. The study notes that the optimal periodicity of the cells and the contrast in thickness vary with the beam’s dimensions, and that the thickness contrast markedly affects the quantity, width, and intensity of the resulting band gaps. These results indicate that (1) periodic material removal in beam-like structures allows improved vibration reduction while mass is reduced, and (2) manufacturing can play a key role in vibration control in simple structures.

Lab-based scale measurements of internal storage of crude oil tank based on non-contact infrared thermography technique

Non-contact sludge measurement methods for storage tanks can address the challenge of measuring the volume of sedimented sludge during long-term storage. While infrared thermography technology can address the issue of liquid level detection, its measurement accuracy for the undulating interface of sludge is insufficient. This study designed and constructed experimental setups for measuring sludge in storage tanks. In this study, infrared images taken by an infrared camera were used to record the temperature distribution of the outer wall of the storage tank. The threshold segmentation method is used to determine the accurate sludge boundary line in image processing. Finally, the Three-Dimensional Tank Residue Recovery Algorithm (3D-TRRA) was applied to fit the 3D distribution of the sludge and calculate accurate sludge volumes. The results indicate that the best segmentation is achieved with a threshold of 170. The measurement error for sludge volume is less than 5%. Accurate visual positioning and recognition of sludge are achieved.

A prediction model of gear radial composite deviation based on digital twin mesh

The intelligent development of traditional detection technology through the application of emerging technologies is a crucial trend in achieving multi-information gear detection. In this paper, digital twin mesh (DTM) is proposed, and according to the proposed DTM, the prediction model (DTM model) of gear radial composite deviation is established. The DTM model is established by merging the mechanism and the data model with a parallel structure. The mechanism model is established based on the measurement principle. The data model is established through the Gaussian process regression algorithm. Comparing the predicted results of DTM model with the measured results, it is observed that the DTM model demonstrates superior precision. The DTM model achieves a prediction accuracy exceeding 87 % for total radial composite deviation and exceeding 90 % for tooth-to-tooth radial composite deviation. This DTM model holds significant engineering application value and offers insights for the non-contact dynamic measurement method of gears.

Background radiation compensation calibration method for film cooling infrared temperature measurement based on BP neural network

The precise non-contact temperature measurement method is essential for studying gas turbine component heat transfer. While infrared thermal imaging provides high-resolution two-dimensional temperature fields, errors arise from the measurement environment's complexity, emissivity variations, and reflection radiation effects. This study utilizes BP neural networks to correct infrared radiation on gas film cooled plates. By modeling background radiation and analyzing infrared emission processes, factors influencing temperature distribution are identified. Experimental data from uncooled plate are used for network training. Experimental measurements were conducted on uncooled plates to obtain training data. A BP neural network was established based on Planck's law and the radiation transmission process to relate the mainstream temperature to the background radiation. Calibration analysis was performed based on experimental data from the cooled plate, achieving the restoration of the two-dimensional temperature field under multiple operating conditions and significantly reducing measurement errors. This method comprehensively considers the entire process of radiation transmission, thereby eliminating background radiation embedded in the infrared images. The obtained measurement results vividly depict the real temperature distribution, offered significant support for gas turbine engineering applications.

A visual measurement method of vibration displacement of railway bridge bearings based on phase correlation

Currently, contact displacement meters for bearing displacement measurement are prone to fatigue failure. Non-contact visual measurement has become a more effective technique. In this study, an innovative model based on phase correlation is established for the visual measurement of vibration displacement of railway bridge bearings. Firstly, it is suggested to extract the vehicle–bridge interaction time using the sliding window average detection and K-means methods. Secondly, to circumvent the limited measurement accuracy of the existing methods, the phase correlation technique is applied to efficiently calculate the displacement of bearings within a two-dimensional plane. Thirdly, an image sharpness estimation method based on the Tenengrad function is proposed, and then a line segment detector is used for updating the measurement parameters. Through comparative experiments, the measurement error of presented method is within 0.04 mm. In the process of long-term service, the proposed method exhibits no fatigue failure issues, highlighting its good technical advantage.

Ultrasensitive detection of remote acoustic vibrations at 300 m distance by optical feedback enhancement

Sensitive detection of remote vibrations at nanometer scale owns promising potential applications such as geological exploration, architecture, and public security. Nevertheless, how to detect remote vibration information with high sensitivity and anti-disturbance has become a major challenge. Reported current non-contact measurement methods are difficult to simultaneously possess characteristics of high light intensity sensitivity, long working distance, high vibration response sensitivity, and anti-disturbance of ambient light. Here, we propose a polarization-modulated laser frequency-shifted feedback interferometry method with the above characteristics, to obtain remote vibration information. The method can directly measure non-cooperative targets without the need for any cooperative markers. In each interference cycle, the energy as low as 2.3 photons can be effectively responded to, and the vibration amplitude sensitivity at 300 m can reach 0.72 nm/Hz1/2 at 1 kHz. This approach provides a strategy for the ultrasensitive detection of remote vibration that is immune to electromagnetic interference.

Integrated error modeling and evaluation of the effect for the Wolter-I grazing incidence focusing mirror imaging quality

The imaging quality determines the performance of the Wolter-I grazing incidence focusing mirror. When the design parameters are specified, the factors affecting the imaging quality are mainly machining and assembly errors; finding the error sources and evaluating the main errors are critical fundamental issues to achieve process optimization and control and improve imaging quality. This paper constructs a model of surface distribution error based on Nurbs surface reconstruction by non-contact measurement. It proposes an integrated error modeling method based on the surface distribution error model, taking into account the typical assembly errors such as decenter error, defocus error, and tilt error formed during the assembly process. First, the theoretical modeling and analysis of imaging quality based on ideal surface shape are carried out, and the sensitivity analysis of each error is carried out by using the Monte Carlo ray tracing method; then, an integrated optical simulation model containing assembly errors based on the surface distribution error is established, and the imaging quality of the focused spot is evaluated; finally, the experimental validation is carried out. The results of the experiment and the integrated optical simulation model show overall consistency, where the decenter error and defocus error have less influence, and the tilt error has the greatest impact, with the 10′ tilt error causing a decrease in the angular resolution of the focused spot of about 50″. The method can provide effective modeling and computational approaches to support the optimization of the precision assembly process and quality control of the Wolter-I grazing incidence focusing mirror.

Vibration separation method for permanent magnet guideway irregularity measurement

High-temperature superconducting (HTS) pinning maglev has the potential to achieve high operational speed while having a low maintenance cost, attracting a lot of attention. The HTS pinning maglev system realizes the levitation of the vehicle through the flux pinning characteristics between the high-temperature superconducting bulk and the magnetic field of the permanent magnet guideway (PMG). Thus, the profile of the magnetic field of the PMG can significantly affect the levitation status of the vehicle, which makes the PMG irregularity become one of the main excitation sources of the system. The magnetic induction intensity on the surface of the PMG can be used to characterize the PMG irregularity, but the non-contact dynamic measurement may produce large errors by the vibration of the measurement system during the process. In order to evaluate the PMG irregularity, the vibration component needs to be separated from the overall signal. In this paper, through the synchronous measurement of the Hall sensor and accelerometer, the vibration separation method of the PMG irregularity measurement is simplified to the optimal filter estimation. The particle swarm optimization (PSO) algorithm is used to calculate the parameters of the optimal filter based on the correlation coefficient criterion. The effectiveness of the proposed method is verified by the test. The separated signal is more accurate in both time domain and frequency domain for the characterization of PMG irregularity.

A hybrid approach for vision-based structural displacement measurement using transforming model prediction and KLT

As civil infrastructures age, monitoring their health conditions has become increasingly critical. Dynamic displacement measurement is a prevalent method for assessing structural health. Traditional techniques, which often involve installing instruments and scaffolding, can interfere with the response of the structures. To address the challenge, non-contact measurement methods have been developed; however, these are typically costly and require expert operation. Advances in high-speed industrial cameras and image processing technology now enable vision-based displacement measurement. Despite their effectiveness, existing vision-based methods face significant limitations, including their inability to maintain tracking when line-of-sight is obstructed, sensitivity to lighting variations, and the need for manual intervention when feature points are lost. This study introduces a novel hybrid approach, termed ToMP-KLT, which combines the KLT tracker with a deep learning-based model. This method harnesses the precision of the KLT tracker under favorable conditions and the robustness of the deep learning-based tracker under adverse conditions. Its effectiveness is validated through simulation-based tests, lab-scale experiments, and field testing on Cheonsa Bridge, demonstrating substantial improvements in tracking robustness against occlusions and varying light conditions.

Prediction of Friction Coefficient Based on 3D Texture Characteristics of Road Surfaces

Accurate assessment of road pavement friction is crucial for maintaining road safety. This study explores the prediction of the friction coefficient (µ) using 3D texture parameters of pavement surfaces. Measurements were conducted on 17 different rural road sections using the Traction Watcher One (TWO) for friction coefficients and a newly developed Static Road Scanner (SRS) for surface texture. Multiple linear regression models were created, incorporating texture parameters such as the valley material portion (Smr2,MIC), arithmetic mean peak curvature (Spc,MAC), and dale void volume (Vvv,PS). The results demonstrate a strong correlation between texture characteristics and friction, with R2 values up to 0.80 and an RMSE as low as 0.076, validating the model’s accuracy. This approach highlights the potential of using non-contact texture measurements for reliable prediction of friction, offering a significant advancement in pavement management and safety.

Correction of thermal airflow distortion in warpage measurements of microelectronic packaging structures via deep learning-based digital image correlation

The projected speckle-based three-dimensional digital image correlation method (3D-DIC) is being increasingly used in the reliability measurement of microelectronic packaging structures because of its noninvasive nature, high precision, and low cost. However, during the measurement of the thermal reliability of packaging structures, the thermal airflow generated by heating introduces distortions in the images captured by the DIC measurement system, impacting the accuracy and reliability of noncontact measurements. To address this challenge, a thermal airflow distortion correction model based on the transformer attention mechanism is proposed specifically for the measurement of thermal warpage in microelectronic packaging structures. This model avoids the oversmoothing issue associated with convolutional neural networks and the lack of physical constraints in generative adversarial networks, ensuring the precision of grayscale gradient changes in speckle patterns and minimizing adverse effects on DIC calculation accuracy. By inputting the distorted images captured by the DIC measurement system into the network, corrected images are obtained for 3D-DIC calculations, thus allowing the thermal warpage measurement results of the sample to be acquired. Through experiments measuring topography with customized step block specimens, the effectiveness of the proposed method in improving warpage measurement accuracy is confirmed; this is particularly true when captured images are affected by thermal airflow at 140 °C and 160 °C, temperatures commonly encountered in thermal reliability testing of packaging structures. The method successfully reduces the standard deviation from 9.829 to 5.943 µm and from 12.318 to 6.418 µm, respectively. The results demonstrate the substantial practical value of this method for measuring thermal warpage in microelectronic packaging structures.

Dynamic Characterization of Diameter for Round Surfaces using a Non-contact Optical Measurement System

Ensuring uniformity in the final round product's diameter is essential to production line operations because it permits adherence to geometry specifications and fulfills client demands. Non-contact diameter measurement systems are essential for manufacturing cost savings as well as quality monitoring. However, because of their non-linear movement, lengthy manufactured specimens like rods might be difficult to measure the diameter of precisely. Typically, analysis systems rely on costly and intricate optical components, limiting accessibility to small businesses. This research aims to address this issue by presenting a low-cost and practical optical system for measuring the diameters of round samples in continuous lines. The aim here is to obtain instant feedback through dynamic measurement and to create a continuous control mechanism that will contribute to sustainability. Experimental results show that the proposed method exhibits a high level of precision, with a measurement accuracy of 0.25% of nominal diameter.