Measurement Technology Research Articles

Studying robotics through distance learning methods in crisis conditions

The rapid development of information technologies and their application in production necessitates the continuous increase in the theoretical and practical training requirements for specialists in the field of automation of technological processes. Addressing this issue requires a comprehensive approach to organizing education, which includes the development of new teaching methods and techniques, as well as the constant updating of educational materials. Analyzing practical teaching experience under such conditions highlights a special direction in education that combines methods of scientific research, technology, engineering skills, and mathematical knowledge, known as STEM education. The full integration of the STEM approach is most effectively realized through the study of robotics. The development of robotic systems combines elements of mechanics, electronics, machine theory, measurement, programming, automated control, and information and communication technologies. Teaching robotics in engineering specialties enhances overall training levels, fosters creative abilities, and improves communication skills. Traditionally, a significant portion of time in robotics studies is devoted to working with equipment. However, initially due to quarantine restrictions and now due to limitations associated with ongoing hostilities, such access is restricted. A logical solution to this situation is the organization of the educational process in a remote format. This paper substantiates the need to supplement and coordinate remote education methods considering the cultural, psychological, and sociological factors influenced by the hostilities. It is proposed to expand the robotics basics course with topics covering the theory and practical application of conceptual modeling in the design of robotic systems and complexes. The possibility of conducting practical and laboratory classes based on online platforms such as Tinkercad Circuits and WokWi is analyzed and justified. A series of examples demonstrating the potential and capabilities of using this software in conjunction with conceptual modeling methods is proposed.

Non-contact measurement of conveyor belt speed based on fast point cloud registration of feature block

Abstract Non-contact, real-time measurement of conveyor belt speed is critical for energy-saving speed regulation and efficient development of coal mine conveyor systems. Existing speed measurement technologies for conveyor systems are often limited by the slippage and wear in contact measurement and complex environmental disturbance. This study introduces three-dimensional point cloud technology into coal flow information detection and innovatively presents a non-contact measurement method of conveyor belt speed based on fast point cloud registration of feature blocks. In the proposed method, a three-dimensional camera is used to capture point cloud data of the dynamically running conveyor belt, and the raw point cloud is preprocessed and segmented into blocks. Then, the C-MANV (curvature and mean angle of normal vectors) features of block point clouds are constructed based on the point cloud neighborhood curvature and the mean angle of neighborhood normal vectors. Finally, an improved block point cloud registration method based on C-MANV features is adopted to achieve the accurate measurement of the dynamic running speed of conveyor belt. Experimental results demonstrate that the proposed method achieves an average relative error of less than 1.8% in high-speed conveyor belt operation with an average processing time of less than 35 ms, which fulfils the accuracy and real-time requirements for conveyor belt speed detection in coal mines. This study provides an effective technical solution for the speed monitoring of coal mine conveyor systems.

Application of Binocular Vision Algorithm Based on Measurement and Control Technology in Robot Measurement and Positioning

Application of Binocular Vision Algorithm Based on Measurement and Control Technology in Robot Measurement and Positioning

Investigating diverse photogrammetric techniques in the hazard assessment of historical sites of the Museum of the Coal Basin Area in Będzin, Poland

Abstract Assessing the condition of historical sites at risk requires an interdisciplinary approach based on combining multiple measurement technologies. Due to the dynamic development of technology, non-invasive remote sensing methods are gaining significant importance. Among these techniques is photogrammetry based on images taken from unmanned aerial vehicles (UAVs) and those taken with a smartphone. In the study, the authors specified the possibilities and limitations of using remote photogrammetric methods to build accurate digital models of the walls of historic buildings with cracks in them. Point clouds, TIN grids, and façade orthophotos were examined. Statistical analysis was used to determine the repeatability of the data. Two parameters were identified that affect the accuracy of the data: the first – the direction of the segment between two points in the façade plane, and the second – the distance of the segment between two points in the plane of the façade. The study showed that the average accuracy of crack width measurements on the data acquired with the DJI Mavic 3 Enterprise RTK is 1 mm. Testing of crack width measurements using a Samsung Galaxy S20 FE smartphone showed an average absolute error of 0.24 mm. Based on the results, it was concluded that the imagesacquired using mobile devices can be used to determine changes in crack widths on walls.

Experimental detection of mechanical deformations exploiting electromechanical effects

The present paper discusses experimental results concerning the deformation-induced generation of electric potential difference in steel specimens. According to our observations, voltages in the order of 10 microVolts can be measured between points on the surfaces of steel bodies during mechanical deformation. Three different experimental set-ups were used to determine the properties of the phenomenon, carefully excluding the influence of possible external electromagnetic fields. In order to exclude thermoelectric effects, a special steel specimen was fabricated. Further experimental campaigns were conducted with long, thin metallic rods in two different set-ups: the generation of voltage was measured during the traveling of longitudinal shock waves and during bending vibrations of the specimens. The results indicate that the variation of the magnetization of the material – the magnetoelastic effect – plays an important role in the phenomenon, but thermoelectricity also contributes to the measurable voltage signals. The electromechanical effect identified in the present paper may have several applications in measurement technology. The most relevant advantage of the applied measurement methods is that these are essentially sensor-free, since the mechanical vibrations can be detected by simply soldering, welding, or pressing copper wires to the examined steel specimen.

Interference inhibition of multimodal information in digital interfaces and its rule of cognitive processing

AbstractIn the digital interface of multimodal audio–visual presentation, the appearance of irrelevant information often brings cognitive interference or even confusion, leading to decision‐making errors when users focus on or manipulate the interface target. However, few studies have explored the brain's inhibition effect and cognitive law evoked by audio–visual interference from the perspective of interface information design. On the basis of Stroop's classic interference task, an experimental paradigm of multimodal audio–visual stimuli to induce event‐related potential (ERP) components was designed for digital interfaces in this study. Combining behavioral measurement and ERP technology, this study discussed the differences in the induced inhibition effects between the two carriers under various audio–visual interferences. The findings demonstrated that all five interference stimuli, based on functional icons and Chinese characters, elicited significant N250 and N400, with a similar time course. Compared with the Chinese character group, the functional icon group elicited more negative activity in the frontal and some parietal‐occipital regions, indicating that the functional icon required more cognitive inhibitory resources to resist interference stimuli. Moreover, the inhibition effect induced by audio–visual interference with the same semantics was significantly lower than that of opposite semantics and even lower than that of single‐sensory interference. The findings offered physiological evidence for the inhibition effect induced by audio–visual semantic interference in digital interfaces and proposed design principles for the interface information of human–machine systems.

Multi-Directional Strain Measurement in Fiber-Reinforced Plastic Based on Birefringence of Embedded Fiber Bragg Grating.

Embedded fiber Bragg gratings are increasingly applied for in-situ strain measurement in fiber-reinforced plastics, integral to high-end aerospace equipment. Existing research primarily focuses on in-plane strain measurement, limited by the fact that fiber Bragg gratings are mainly sensitive to axial strain. However, out-of-plane strain measurement is equally important for comprehending structural deformation. The birefringence of fiber Bragg gratings shows promise for addressing this problem; yet, the strain transfer relationship between composites and optical fibers, along with the decoupling method for multi-directional strains, remains inadequately explored. This study introduces an innovative method for multi-directional strain measurement in fiber-reinforced plastics using the birefringence of a single-fiber Bragg grating. The strain transfer relationship between composites and embedded optical fibers was derived based on Kollar's analytical model, leading to the development of a multi-directional strain decoupling methodology. This method was experimentally validated on carbon fiber/polyetherimide laminates under thermo-mechanical loading. Its reliability was confirmed by comparing experimental results and finite element simulations. These findings significantly broaden the application scenarios of fiber Bragg gratings, advancing the in-situ measurement technology crucial for the next generation of high-end aerospace equipment.

Force Measurement Technology of Vision‐Based Tactile Sensor

Marker‐type vision‐based tactile sensors (VTS) realize force sensing by calibrating marker vector information. The tactile visualization can provide high‐precision and multimodal force information to promote robotic dexterous manipulation development. Considering VTS's contribution to force measurement, this article reviews the advanced force measurement technologies of VTSs. First, the working principle of marker‐type VTSs is introduced, including single‐layer markers, double‐layer markers, color coding, and optical flow. Then, the relationship between the marker type and the category of force measurement is discussed in detail. On this basis, the process of marker feature extraction is summarized, including image processing and marker‐matching technologies. According to the learning approach, force measurement methods are classified into physical and deep learning models. Further, branches of each method are analyzed in terms of input types. Combined with measuring range and precision, the correlation of sensor design, materials, and recognition methods to force measurement performance is further discussed. Finally, the difficulties and challenges are analyzed, and future developments are proposed. This review aims to deepen understanding of the research progress and applications and provide a reference for the research community to promote technology generations in related fields.

Unmasking hidden ignition sources: A new approach to finding extreme charge peaks in powder processing

Powders acquire a high electrostatic charge during transport and processing. Consequently, in the aftermath of dust explosions, electrostatic discharge is often suspected to be the ignition source. However, definite proof is usually lacking since the rise of electrostatic charge cannot be seen or smelled, and the explosion destroys valuable evidence. Moreover, conventional methods to measure the bulk charge of powder flows, such as the Faraday pail, provide only the aggregate charge for the entire particle ensemble. Our simulations show that, depending on the flow conditions, contacts between particles lead to bipolar charging. Bipolar charged powder remains overall neutral; thus, a Faraday pail detects no danger, even though individual particles are highly charged. To address this gap, we have developed a machine learning-enhanced measurement technology to resolve the powder charge spatially. The first measurements have revealed a critical discovery: a localized charge peak near the inner wall of the conveying duct that is 85 times higher than the average charge that would be measured by the Faraday pail. This finding underscores the possibility of extremely high local charges that can serve as ignition sources, even though they remain undetected by conventional measurement systems. Our new technology offers a solution by spatially resolving the charge distribution within powder flows, unmasking hidden ignition sources, and preventing catastrophic incidents in the industry.

Investigation of near infrared and Raman fibre optic process sensors for protein determination in milk protein concentrate

This study investigated the potential of two fibre optic process sensors based on near infrared (NIR) or Raman spectroscopic technology for protein measurement in milk protein concentrate (MPC). Partial least squares (PLS) models were developed using NIR, Raman, and fusion of NIR and Raman spectra data. Calibration models developed were optimized by selecting different spectral pre-treatment methods and spectral regions. Overall, the three optimal models (NIR, Raman, fused NIR and Raman) yielded R2p values >0.9 and RMSEP values in the range of 0.168–0.185 %. The optimised fusion model outperformed all Raman models and had a similar protein prediction accuracy (R2p = 0.911 and RMSEP = 0.178 %) compared to the optimised NIR model (R2p = 0.917 and RMSEP =0.168 %). Results of the study demonstrated that both NIR and Raman process probes can be used as process analytical technology (PAT) tools for inline protein measurements of MPC post membrane filtration.

Forced Response of Rotating Blisks: Prediction and Correlation to Blade Tip-Timing Measurements

Abstract This paper explores two different blisk dynamic models for resonant vibration prediction of a rotating blisk test piece, i.e., the Model-BDTID and geometrically mistuned models (GMM). The former represents a mistuned blisk model with blade mistuning pattern experimentally retrieved by a recently proposed blade mistuning identification method based on blade detuning tests (BDTID). It falls into the scope of the frequency-mistuning modeling approach. The latter refers to a geometrically mistuned model constructed upon high-precision blisk geometry data by leveraging the advanced optical geometry measurement technology. A specifically developed “Sector Mode Assembling Reduction Technique” is exploited for efficient dynamic analyses of the large-sized GMM. Forced response tests are performed in a spinning rig under well-controlled laboratory condition. The blade tip-timing (BTT) technique is employed to give all-blade vibration measurements of the rotating blisk. Correlation results between the forced response predictions to BTT measurements demonstrate that both the Model-BDTID constructed upon the identified blade mistuning of the blisk at rest and the GMM, can predict the resonant vibration of the rotating blisk with satisfactory accuracy.

Optimisation of the hammer throw using parameterised synthetic motion kinematics in a multi‐body simulation

AbstractHammer throwing is a motorically demanding sport in which the execution of the movement significantly influences the result, that is the throwing distance. There are many approaches for supporting technical training that are based on measurement technology and image capturing. The accelerations and locus curves of the athlete and hammer are recorded and compared. In this article, these methods are supplemented by a multi‐body simulation (MBS) of the hammer throw. The kinematics of the hand movement is described using a parameterized synthetic trajectory. Scalar parameters in the approach allow the trajectory to be modified. With a MBS model of the wire cable and the hammer, the movement of the hammer can be determined by numerical time integration from the hand's trajectory. As a result the final throwing distance after free flight phase can be analyzed. Due to the complex spatial motion of the hammer during the acceleration phase only heuristic methods can be used to optimize the maximum throwing distance. In a final step the optimized movement can be used to improve the athlete's training.

Accelerated measurement technology quantifying packaging light protection performance for soymilk nutrient and chemical stability

An accelerated in situ (AIS) light exposure and measurement technology for prediction of retail light protection performance of soymilk packaging is reported. The ability of a packaging material to protect light sensitive marker solutions, either comprising riboflavin (RF) or chlorophyll-a (CHLA), from an intense light source was determined. The light-induced decay of the marker was tracked with in situ spectroscopy and modeled to quantify the light protection performance of each packaging material. For a set of packages, chemical analyses (RF, thiobarbituric acid reactive substances (TBARS), hexanal) of packaged soymilk under Simulated Retail (SR) storage conditions demonstrated excellent correlation to the light protection performance data of the same package set determined by AIS (R2 > 0.97). The use of AIS enables rapid quantification of soymilk packaging material light protection performance and the associated preservation of soymilk nutrient and sensory properties, thus it may be applied to improve the design of soymilk packaging materials for light protection performance and contribute towards the improvement of packaged soymilk product shelf life.

High-accuracy 3D reconstruction of step edge with ray aliasing based on projective parallel single-pixel imaging

Optical 3D measurement technology especially fringe projection profilometry (FPP) is widely utilized in industrial production. However, invalid mixed phases are common when measuring step edges in industrial parts which leads to outliers in reconstructed point cloud and ultimately causes reduction of valid point cloud and dimensional measurement errors. This paper first analyzes reasons for failure of step edge measurement in FPP and illustrates feasibility of parallel single-pixel imaging (PSI) applied to eliminate ray aliasing of step edge. Further for a good balance of accuracy and efficiency, we propose an optimized projective parallel single-pixel imaging (pPSI) method combing with edge detection in wrapped phase generated by pPSI patterns and adaptive bi-direction projection strategy to accurately identify direct correspondence matching points of step edge. Experimental results verified that the proposed method can achieve high accuracy of 3D reconstruction on step edge while taking less measurement time.

Multi-Spectral Radiation Temperature Measurement: A High-Precision Method Based on Inversion Using an Enhanced Particle Swarm Optimization Algorithm with Multiple Strategies.

Multi-spectral temperature measurement technology has been found to have extensive applications in engineering practice. Addressing the challenges posed by unknown emissivity in multi-spectral temperature measurement data processing, this paper adds emissivity constraints to the objective function. It proposes a multi-spectral radiation temperature measurement data processing model realized through a particle swarm optimization algorithm improved based on multiple strategies. This paper simulates six material models with distinct emissivity trends. The simulation results indicate that the algorithm calculates an average relative temperature error of less than 0.3%, with an average computation time of merely 0.24 s. When applied to the temperature testing of silicon carbide and tungsten, experimental data further confirmed its accuracy: the absolute temperature error for silicon carbide (tungsten) is less than 4 K (7 K), and the average relative error is below 0.4% (0.3%), while two materials maintain an average computation time of 0.33 s. In summary, the improved particle swarm optimization algorithm demonstrates strong performance and high accuracy in multi-spectral radiation thermometry, making it a feasible solution for addressing multi-spectral temperature measurement challenges in practical engineering applications. Additionally, it can be extended to other multi-spectral systems.

Experimental Characterization of Process Pressure Variations on The Accuracy and Performance of Liquid Ultrasonic Flow Meters

This paper investigated the influence of process pressure variations on the accuracy and performance of ultrasonic flow meters. Process measurement technology provides a tool for optimizing production processes and dosing operations. Accurate measurement is key and primary to profitability in the business of supply and purchase of liquids like petroleum, gas and chemical products. Three 6” size ultrasonic flow meters were mounted on a skid and used to carry out the experiment parallel in connections each other to take flows from a common header, measure and discharge their individual flows into a common discharge header. The three meters were designate 1, 2 and 3 respectively. Meters 1 and 2 being service meters while Meter 3 is the calibrated master meter. The experiment was carried ten times to increase reliability of results. Experimental data were collected and analyzed using computational formulae technique. Results showed that; Meter 1 had an optimum process pressure of 12.38 and 9.43 bar with respect to flow rate and meter factor respectively as performance indicator. While Meter 2 had an optimum process pressure of 12.4 and 12.41 bar with respect to flow rate and meter factor respectively as performance indicator. Findings indicated significant relationship between process pressure, flow rate and meter factor using ultrasonic flow meter. The outcome of this study will be a useful guide to users of ultrasonic flow meters to maintain optimum process pressures of each meter during fluid supply.

Selection and Pathways to Next Generation Innovations of Speed Over Ground (SOG) Measurement Technologies to Overcome Harsh Conditions and Technological Limitations: A Review

Selection and Pathways to Next Generation Innovations of Speed Over Ground (SOG) Measurement Technologies to Overcome Harsh Conditions and Technological Limitations: A Review

The accounting of virtual robots

Purpose: The aim of the article is to present the principles and methods of measuring the activity of virtual robots. We link the identified metrics to analogies of perceiving a bot as a machine, an automated process, or a digital employee. The latest phenomenon of the anthropomorphization of bots receives special attention.Methodology/approach: We used text analysis of technical and marketing documentation as the research method. We conducted the analysis as a case study using the software of a leading international RPA (Robotic Process Automation) provider.Findings: The results lead to the following conclusions: accounting using bots is multidimensional, embedded in technology, and carried out in real time. The virtual robot accounting solutions avoid the analogy of virtual employees; measurement covers both bots and operators, and the representation of activities is incomplete and distorted.Research limitations/implications: The research was focused on subjective recommendations of the RPA technology provider, taking into account their marketing goals. Originality/value: The research shows that embedded measurement technology automates raw data collection and enables real-time accounting for both bots and their operators. It thus contributes to the development of hybrid accounting. Simultaneously, this technology has a constraining effect, distorting measurement and redefining well-known and well-established effectiveness metrics.

Uncertainty analysis of FLiNaK thermophysical properties on convective heat transfer characteristics in circular tube

Molten salts have attracted a spate of quantity of interests in energy and chemistry fields due to their large volumetric capacity, and thermodynamic stability at elevated temperature. However, there are significant uncertainties in the physical properties of molten salts, such as density, specific heat capacity, dynamic viscosity, and thermal conductivity, due to inexperienced measurement techniques and technology. These uncertainties could have certain impact on the evaluation of molten salts heat transfer characteristics. Therefore, an uncertainty analysis is performed regarding FLiNaK thermophysical properties on convective heat transfer characteristics in circular tube. Then, a polynomial chaos expansion (PCE) method is performed to study the uncertainty affecting the heat transfer characteristic. In the process of uncertainty analysis, tensor product quadrature nodes are used to calculate representative sample points and reduce computational costs. Three primary physical properties of molten salt are taken into account as the input parameters. The Sobol composition method is also used to analyze the contributions of each parameter to heat transfer. The results of the uncertainty analysis suggest that the uncertainties in dynamic viscosity, thermal conductivity, and specific heat capacity have a significant impact on the heat transfer of molten salt, contributing to 80 %, 14 %, and 6 % of the total variability, respectively. It also suggests that the polynomial chaos expansion methodology is both novel and reliable when applied to uncertainty analysis of molten salt.

Ultra high-speed 3D shape measurement technology for specular surfaces based on μPMD

Phase measuring deflectometry (PMD) has been extensively applied to measure specular surfaces due to its non-contact, high-precision, full-field measurement capabilities. Liquid crystal display (LCD) screen is the most common structured light source in PMD. However, the response time of liquid crystal molecules limits its frame rate to around 100 frames per second (fps). Therefore, it is quite difficult for traditional PMD to measure rapidly moving surfaces. This paper proposes a 3D dynamic sensing technique, microsecond-PMD (µPMD) based on the high-frame-rate sinusoidal fringe display (HSFD). In the proposed method, the switching time for each fringe pattern display is at a sub-microsecond level, enabling high-speed fringe acquisition with kHz-level area array detection or 100kHz-level line array scanning. The HSFD method uses a specially designed LED array and two-step optical expansion. The high-speed switching characteristic of LED sources is utilized to allow a superfast display rate. Moreover, the superior sinusoidal property can be achieved by the combination of the specially designed discrete sinusoidal LED array, the light-diffracting effect of orthogonal gratings, and the filtering effect of the light diffuser. The mechanism and analytic model of fringe generation are thoroughly analyzed and discussed in this work. Furthermore, the swarm optimization algorithm and corresponding weighted fringe quality evaluation function are presented to obtain the optimal fringes. To the best of our knowledge, the proposed µPMD, for the first time, achieved a superfast fringe acquisition rate of 4000fps with sub-micrometer precision in three-dimensional (3D) reconstruction for specular surfaces. We envision this proposal to be broadly implemented for real-time monitoring in manufacturing.