This work presents the design, fabrication, and characterization of a novel microwave-based sensor utilizing multiple U-shaped resonators for non-contact measurement of volume percentages in water-crude oil mixtures. The sensor, fabricated on an RT/Duroid 4003 substrate (Sr = 3.55, thickness 0.787 mm), operates in the 2-2.3 GHz frequency range with a maximum insertion loss of 0.97 dB. Design optimization and electromagnetic simulations were performed using ADS software followed by experimental validation with 10 ml samples of varying water content (0-100%) placed in a 3D-printed PLA container. Significant shifts in center frequency and response prominence were observed, enabling clear differentiation of mixture compositions. The sensor achieved a high sensitivity of 4.12 MHz/Sr, surpassing many prior designs, while the non-contact configuration enhances practicality by minimizing contamination risks and interference. Although highly sensitive and compact, potential limitations include dependence on crude oil composition variability, temperature effects, and the fixed sample volume used in testing. These results demonstrate the sensor's reliability for real-time fluid analysis, with promising applications in petroleum, chemical, and environmental monitoring industries.
Image intensifier tube is the most important block of night vision devices that enable vision at low illumination conditions and are of critical importance for military and security agencies. SNR (signal to noise ratio) is one of two most important parameters of image intensifier tubes. This paper presents a review of methods used to measure the SNR of image intensifier tubes. Reasons why SNR test results of the same tube carried out by different laboratories often differ significantly are presented.
The precision rotary table is an angular positioning generator commonly used in the industry. Ensuring its long-term stability of positioning accuracy is a key concern. Researchers have conducted extensive studies on the online calibration and real-time compensation of rotary table positioning errors. However, existing research often involves some offline processing throughout the calibration and compensation stages. Currently, there is very little research on methods in which the entire process of calibrating and compensating rotary table positioning errors is fully online. Therefore, this paper proposes a fully online calibration-compensation method for rotary table positioning errors and develops a rotary table positioning error calibration-compensation system. Based on the Fourier self-calibration principle and the harmonic compensation principle, this method implements online calibration and real-time compensation of positioning errors using a heterogeneous processor. Throughout the entre process, data processing is guaranteed to be online. The experimental results show that the positioning accuracy of the rotary table improved from [-150.0 '', 137.9 ''] to [-1.3 '', 1.6 ''], effectively improving its precision. The proposed method is highly suitable for compact or cost-sensitive precision rotary tables, while also being applicable for spindle condition monitoring.
Wayside measurements by means of a strain gauge placed on rails are an important test method to measure the wheel-rail contact forces that determine the safety of rail vehicles traveling on the track. In this method, to enhance the reliability of the monitoring results, strain gauge sections and measurement equipment should be calibrated under operating conditions. In this study, a design of a device has been developed for the calibration of strain gauges used in wayside measurement techniques. The systematic approach proposed by Pahl and Beitz and further developed by Feldhusen and Grote was utilised in the design process. With this innovative design, a safe, simple, compact, and user-friendly device capable of applying both vertical and horizontal forces with a single unit has been developed.
The article presents an analysis of a three-phase electric circuit in terms of describing the power components measured and determined on a three-wire line connecting an unbalanced power source with periodic, non-sinusoidal waveforms with an unbalanced receiver. In this study, the case was considered when the load admittance changes its value when the direction of rotation of the symmetrical voltage and current components is changed. This is a typical situation where three-phase power must be measured on a three-wire line connecting a real source to a load that contains three-phase rotating machines. In real systems, such machines often change their current/voltage relationship when the direction of rotation changes. This paper presents a modification of the currents’ physical components (CPC) power theory to decompose currents and powers into symmetrical components. This constitutes the theoretical framework of this study. Using the determined dependencies, it is possible to develop a new measurement algorithm. As a result of these measurements, it is possible to determine the electromechanical efficiency of the rotating machine, i.e., the efficiency that does not take into account the influence of higher harmonics and power source asymmetry. This is important information needed to optimise the active power consumption of electromechanical machines. Measurement of active power using classical methods does not allow one to observe the influence of supply voltage asymmetry on the power that affects active conversion to mechanical power. Thanks to such measurements, it is possible to select optimal parameters of the electric motor in order to improve the efficiency of converting electrical energy into mechanical energy. In this approach, the asymmetry of the power supply and the introduction of higher voltage harmonics are perceived as external interferences in the optimisation process. This fragment of the article constitutes the practical side, i.e. the application of the theoretical considerations derived. In the presented calculation example, it was shown that the efficiency of the machine strongly depends on the asymmetry of the voltage source, and less on the harmonics.
Certified reference materials (CRMs) are indispensable tools in calibration, validation, and quality control across various fields, including chemical analysis, environmental monitoring, and industrial production. Their proper certification ensures the metrological traceability and reliability of the measurement results in laboratories around the world. This study presents a new application of an established statistical test (equality of coefficients of variation) to support the homogeneity assessment of multiparameter physicochemical CRMs. The method enables statistically justified indirect inferences about the homogeneity of untested properties based on the behaviour of tested ones, supporting more efficient and statistically defensible certification processes. The approach is demonstrated using CRMs that reproduce the density, refractive index, surface tension, and kinematic viscosity. The procedure is consistent with ISO 17034 and addresses the gaps identified in ISO 33405 regarding the assessment of homogeneity in multiparameter materials. By extending homogeneity assessment beyond conventional univariate methods, this work contributes a practical and statistically reliable tool for CRM producers developing complex, multiparameter materials.
The article presents the results of comparative tests of gear wheels based on non-contact and contact measurement methods. Comparative tests were performed on selected cylindrical gear wheels with straight teeth which are spare parts for transmission mechanisms. The paper compares important geometric parameters of gear wheels, such as the total deviation of the tooth line, the single and total pitch deviation, and the radial run-out deviation of the teeth. An optical measurement method was applied using the general tools available in the GOM ATOS II coordinate scanner software. The measurement results obtained using the non-contact method were compared with the results of the contact method using aWenzelWGT 600 specialised machine for measuring gear wheels. Based on the analysis conducted, the comparability of the measurement results of gear wheels performed in Accuracy Class 10 according to the DIN 3961/62 standard was demonstrated for the considered measurement methods, while at the same time indicating significant differences in the geometric parameters obtained between the parts manufactured under the manufacturer’s licence and commercial substitutes.
Measurement of the grounding resistance of very large installations is difficult because conventional fall-ofpotential methods require impractically long test leads. The Tagg slope method reduces this distance, but its traditional formulation neglects finite electrode dimensions and relies on curve extrapolations outside the range originally analysed, leading to large errors.This paper revises the method using finite element simulations that model realistic electrode geometry and soil conduction. A new relationship between the slope of the voltage profile and the position of the measuring electrode is obtained and fitted by a polynomial with errors below 0.02%. The corrected method is tested on large square grounding grids and on a photovoltaic-plant grounding system. Results show that, when measurements are taken away from corner regions and with auxiliary-electrode distances above about 20% of the system diagonal, the grounding resistance can be estimated with errors below 3%, while the traditional implementation may produce errors of up to 60.
The extraction and interpretation of personal data from speech signals, processed through various technical solutions, are key functions of Automatic Speaker Recognition (ASR) systems. Speech conveys information such as language, dialect, and emotions, making ASR systems increasingly essential due to the growing demand for human-computer interaction and biometric security applications in both the military and civilian sectors. Voice, as a unique human characteristic, enables identification without additional attributes that can be lost or destroyed. However, while humans recognize voices naturally, machines face significant computational challenges. Despite advancements in automatic speaker recognition, many challenges remain. This article addresses the use of behavioral voice features in automatic speaker recognition (ASR) systems. The authors aimed to develop and implement a set of behavioral features in an existing ASR system that would increase the number of correct identifications of speaker identity, particularly in the presence of various types of noise. By utilizing the publicly available LibriSpeech voice database, it was possible to compare the developed solution with other ASR systems. In addition, the authors developed a solution that can reduce the impact of external noise on speaker identity recognition accuracy. The key element proved to be the innovative data integration method, which leverages the advantages of various sources of distinctive feature sets. In the experiments conducted, the proposed ASR system demonstrated outstanding performance in automatic speaker recognition. Using the LibriSpeech database, the identification rate exceeded 99% for the train-clean-100 subset and close to 99% for the train-clean-360 subset. Compared with traditional Gaussian Mixture Model (GMM) approaches, which typically achieve about 83% accuracy, the developed solution provides a substantial improvement, reaching identification rates above 99% and demonstrating performance comparable to, or even exceeding, that of modern deep learning based techniques (approximately 98 to 99%).
To address low accuracy in defect detection of point clouds from binocular structured light 3D reconstruction caused by high reflectivity of the surface of silicon nitride ceramic balls, this study proposes a method integrating PointNetLK point cloud registration and PointNet++ defect recognition networks. Initially, PointNet segments and removes reflective regions from the point clouds. Subsequently, an enhanced PointNetLK network performs high-precision binocular point cloud registration with missing region compensation, demonstrating two orders of magnitude improvement in registration accuracy over the conventional Coherent Point Drift (CPD) + Iterative Closest Point (ICP) methods. Finally, the compensated complete point clouds are processed by an enhanced PointNet++ network incorporating a Multi-Scale Grouping (MSG) strategy for defect segmentation, effectively identifying two primary defect types (pits and scratches) with an average mIoU of 0.8565. Ablation studies confirm the critical contributions of the Set Abstraction (SA) module and MSG strategy. This approach significantly mitigates hyper-reflection interference, achieving high-precision, robust, and non-destructive quantification of ceramic ball surface defects.
In modern industrial applications, gears serve as pivotal transmission components, whose transmission performance is critical to operational stability of mechanical systems. For electric vehicles subject to stringent noise control specifications, the suppression and control of gear transmission noise carry heightened importance. To tackle gear noise at its root cause, this paper regards gear deviations as the primary excitation source of vibration and noise and systematically analyses six typical gear deviation shapes as well as the corresponding tooth-pair change-over characteristics in meshing. In addition, the mechanism of formation of the corner contact phenomenon and its influential effect on gear transmission errors are being investigated in depth. On this basis, in this paper a novel least-squares sine wave fitting method is proposed. The results demonstrate that the proposed method can effectively achieve the separation and quantitative characterisation of diverse gear deviations. Meanwhile, this paper conducts an in-depth analysis of transmission errors in noise-causing gears, verifying that eccentricity error, pitch deviation and tooth surface texture of gears are the key influencing factors dominating transmission errors and subsequent noise excitation. This research provides a refined analytical paradigm and reliable technical support for the precision quality evaluation and noise fault diagnosis of gears.
The dynamic response characteristics of sensors in heat flux measurement, such as rising time and frequency band width, determine the capture ability and measurement error of transient thermal load. In order to quantitatively evaluate the dynamic response characteristics of the heat flux sensor, including rise time and frequency band width, based on the differential equation constructed by one-dimensional heat conduction, an analytical expression of the temperature difference between the front and rear surfaces of the sensor sensitive element is derived. Furthermore, the heat flux-temperature transfer function model is established by differential operation and the Laplace transform, and the amplitude-frequency response characteristics of the system are analysed accordingly. The results of theoretical analysis are verified by finite element simulation, and the dynamic analysis characteristics of two types of heat flux sensors are analysed. Finally, the dynamic performance index of a plug calorimeter with an adiabatic rear wall is defined. The modelling method and quantitative conclusion put forward in this study provide a theoretical basis for the dynamic characteristic optimisation and system design of high-precision heat flux sensors.
Measurement uncertainty is a core term in metrology. It is widely used, but often under assumptions that are valid for a large number of measurements. However, the confidence interval of individual measurement uncertainty evaluations has not been analyzed in such depth. The confidence interval for measurement uncertainties evaluated increases as the number of measurements decreases. The paper addresses this problem, which is also important for calibration measurement capabilities as well as for evaluations of international metrological comparisons. Quantification of uncertainty is also important for new measurement and simulation methods. The paper discusses the bias and confidence interval of evaluated measurement uncertainties for normally distributed measurements and presents proposed formulae for the coverage factor for an improvement of their evaluations. The effect of correlations on measurements is also presented. The correlation estimator indicates a correlation for a small number of measurements, even though the measurements are not correlated. Therefore, a formula for the uncertainty of correlation is also presented for uncorrelated measurements. These formulae allow for an improved estimation of measurement uncertainty.
Certain applications of fused silica optical fibers, in particular fire-resistant cables and sensors working in hot environments (e.g., nuclear reactors) require short-or long-term operation at temperatures exceeding 800 degrees C. Peak temperatures during fire tests of fire-resistant cables vary between 830 degrees C and 1040 degrees C depending on applicable standards. If the fiber contains OH-ions and hydrogen, it exhibits both increased loss and incandescence in the corresponding absorption bands. Additionally, deteriorated fiber with multiple cracks and other microscopic defects collects radiation from glowing surroundings. During loss measurements with a standard setup including a light source and a power meter, thermal radiation from both sources adds to radiation from the light source, causing false decrease of indicated fiber loss. Several methods to eliminate this interference are presented.
Ultra-high-dose rate (FLASH) radiotherapy is a promising cancer treatment method in which high doses of radiation are delivered in a very short time, minimising damage to healthy tissue while effectively targeting tumour cells. In this study, the IORT AQURE accelerator was used in FLASH mode to irradiate breast cancer cells. Dosimetric verification was carried out to confirm the quality of the beam used in the study and to control the doses (5, 10, and 15 Gy) administered to the cells. Gamma index analysis confirmed the accuracy of dose distribution, with results exceeding 96% for all cell samples. Radiobiological testing demonstrated a 90% reduction in the viability of HCC38 breast cancer cells at a dose of 15 Gy. These results validate the film dosimetry for controlling the beam and doses and the use of the AQURE accelerator in the FLASH mode for preclinical research and confirm its potential for future preclinical studies and clinical applications.
Accurate measurement of low-frequency vibration parameters is critical for assessing the performance, stability, and dynamic characteristics of mechanical systems. This study proposes a monocular vision-based method for non-contact measurement of motion parameters in low-frequency shakers. The proposed method utilizes high-contrast sinusoidal fringe markers and high-resolution image acquisition to track fringe density variations caused by periodic out-of-plane motion. To enhance frequency estimation accuracy and mitigate spectral leakage, we introduce an improved time-shifting correction method, which features adaptive time-lapse selection and statistical outlier elimination to improve spectral resolution and robustness. Using a calibrated imaging model, the extracted fringe density signals are further processed to derive precise displacement and acceleration values. An experimental platform is established to validate the proposed method against conventional methods based on grating ruler displacement sensors and accelerometers. Experimental results demonstrate that the proposed method achieves high measurement accuracy, with displacement amplitude errors confined within 0.5% and total harmonic distortion values in acceleration measurements below 0.1. Additionally, the proposed method also exhibits excellent stability across a range of low-frequency scenarios. These findings confirm that the proposed method offers a reliable and non-contact alternative for low-frequency vibration measurement, holding strong potential for advancing applications in structural health monitoring, dynamic system diagnostics, and non-destructive testing.
Structural Health Monitoring (SHM) of pipe infrastructures is of paramount importance to prevent catastrophic failures induced by defects such as corrosion. Conventional damage identification methodologies are frequently faced with challenges, including baseline dependency, limitations inherent in single-sensor data, and considerable economic expenditure. This paper presents a novel, baseline-free, multi-modal damage identification methodology developed for Level 3 assessment of multiple damages, encompassing their detection, localisation, and quantification. Initially, Level 1 damage identification is accomplished through observation of the Regional Resonance Pair (RRP) phenomenon. Subsequently, potential damage regions are predicted by a Multilayer Perceptron (MLP) model that uses vibration modal frequencies, generating a Macro-F1 score of 0.8131 on the test set; this prediction is then integrated with a high-precision local point cloud, acquired via Line Structured Light (LSL) technology, to achieve precise Level 2 damage location, with a reported error as low as 1.78%. Following localisation, Level 3 quantification of the damage is performed using point cloud registration, fusion, and voxelisation techniques, enabling accurate prediction of damage volume with a quantification error of merely 2.47%.
The industrial production of parts with precision holes for various applications requires high manufacturing accuracy. The dimensional verification of precision holes with complex geometry remains a critical challenge in modern manufacturing, particularly in ensuring reliability and process efficiency. Existing CMM procedures are largely optimised for circular holes and lack validated methodologies for complex-shaped apertures. A new methodology for assessing the dimensional accuracy and inspection efficiency of epicycloid-shaped holes using CMMs is proposed: manufacturing surface samples with epicycloid-shaped holes using a Water Jet machine, conducting measurements on a ZEISS CONTURA CMM, optical validating measurement accuracy using microscopy on a Keyence VHX system and processing data through image segmentation of the hole, analysing results, and establishing dependencies of measurement accuracy and time on operational parameters. The dependencies of the mean deviation of epicycloid-shaped hole dimensions on the stylus movement speed and the number of measurement points have been established. Key findings indicate that the speed of the stylus significantly influences the accuracy of the measurement, while the number of probing points plays a secondary role. To address the limitations of conventional evaluation techniques, a new geometric complexity coefficient is proposed to quantify deviations from ideal shapes. This coefficient comprehensively characterises deviations from the ideal geometric shape and includes the length of the curve that forms the hole. The proposed methodology enables the optimisation of measurement parameters for complex-shaped holes and improves inspection efficiency on industrial production lines. This approach contributes original insights into the metrological assessment of non-standard geometries, addressing a significant gap in existing literature.
For decades, the deconvolution analysis of the thermoluminescence glow curve has been assessed using the figure of merit (FOM). In the present study, it has been shown that the FOM is not sufficient to assess the deconvolution analysis of TL glow curves. An alternative criterion has been proposed based on the uncertainty of the deconvolution analysis. A comparison between the proposed criterion and the FOM was conducted using theoretical simulations and experimental results. It has been shown that the developed criterion can provide detailed information about the fitting quality for each region in the glow curve as well as give an overall assessment of the deconvolution process. The uncertainty of deconvolution analysis using the general-order kinetics has been estimated for various glow curves. The TL-SDA toolkit has been updated to include the feature of evaluating the uncertainty of the deconvolution process.
A precise frequency stability measurement technology is proposed that utilises group periodic phase synchronisation of signals with varying frequencies. By quantifying the results of phase comparisons between different frequency signals and analysing these quantised outcomes, high-precision frequency measurements can be achieved. The phase coincidence points between the two comparison signals serve as the start and stop signals for the counter, where the time interval between identical phase coincidence points represents a complete cycle. Through the detection and analysis of phase coincidence points, the +/- 1 word counting error is eliminated, thereby enhancing the speed of frequency measurement. Employing the Field-Programmable Gate Array (FPGA) technology simplifies the measurement apparatus and reduces development costs. Experimental results demonstrate that this method achieves a frequency stability of 10-13 at 1s. Compared to traditional frequency measurement technologies, this approach offers significant advantages in terms of power consumption, equipment size, and measurement rate, making it crucial for high-tech applications such as Beidou satellite positioning, precision timing, high-precision time-frequency transmission and comparison, and scientific metrology.
