Number Of Measurement Points Research Articles

Correlation Analysis of Vertical Ground Movement and Climate Using Sentinel-1 InSAR

Seasonal vertical ground movement (SVGM), which refers to the periodic vertical displacement of the Earth’s surface, has significant implications for infrastructure stability, agricultural productivity, and environmental sustainability. Understanding how SVGM correlates with climatic conditions—such as temperatures and drought—is essential in managing risks posed by land subsidence or uplift, particularly in regions prone to extreme weather events and climate variability. The correlation of periodic SVGM with climatic data from Earth observation was investigated in this work. The European Ground Motion Service (EGMS) vertical ground movement measurements, provided from 2018 to 2022, were compared with temperature and precipitation data from MODIS and CHIRP datasets, respectively. Measurement points (MP) from the EGMS over Italy provided a value for ground vertical movement approximately every 6 days. The precipitation and temperature datasets were processed to provide drought code (DC) maps calculated ad hoc for this study at a 1 km spatial resolution and daily temporal resolution. Seasonal patterns were analyzed to assess correlations with Spearman’s rank correlation coefficient (ρ) between this measure and the DCs from the Copernicus Emergency Management Service (DCCEMS), from MODIS + CHIRP (DC1km) and from the temperature. The results over the considered area (Italy) showed that 0.46% of all MPs (32,826 MPs out of 7,193,676 MPs) had a ρ greater than 0.7; 12,142 of these had a positive correlation, and 20,684 had a negative correlation. DC1km was the climatic factor that provided the highest number of correlated MPs, roughly giving +59% more correlated MPs than DCCEMS and +300% than the temperature data. If a ρ greater than 0.8 was considered, the number of MPs dropped by a factor of 10: from 12,142 to 1275 for positive correlations and from 20,684 to 2594 for negative correlations between the DC1km values and SVGM measurements. Correlations that lagged in time resulted in most of the correlated MPs being within a window of ±6 days (a single satellite overpass time). Because the DC and temperature are strongly co-linear, further analysis to assess which was superior in explaining the seasonality of the MPs was carried out, resulting in DC1km significantly explaining more variance in the SVGM than the temperature for the inversely correlated points rather than the directly correlated points. The spatial distribution of the correlated MPs showed that they were unevenly distributed in clusters across the Italian territory. This work will lead to further investigation both at a local scale and at a pan-European scale. An interactive WebGIS application that is open to the public is available for data consultation. This article is a revised and expanded version of a paper entitled “Detection and correlation analysis of seasonal vertical ground movement measured from SAR and drought condition” which was accepted and presented at the ISPRS Mid-Term Symposium, Belem, Brasil, 8–12 November 2024. Data are shared in a public repository for the replication of the method.

Evaluation of Inherent Damping Feature of Beam Structure Based on Complex Modulus

Structural damping, which has been widely used to quantify the energy dissipation of engineering structures, plays an important role in dynamic analysis during the design phase and the assessment of existing structures. However, the development of an accurate damping model remains an open question due to the unclear mechanism. In this study, structural damping was identified based on loss factors for beam structures, which were used for presenting the damping behavior during vibrations. The equation of motion for the bending deformation of a Timoshenko beam was derived, accounting for the material damping. To identify the loss factor of the beam from the response signals at a limited number of measurement points, an inverse algorithm based on wave coefficient estimation was developed, considering the numerical stability for data interpretation. Based on the proposed loss factor identification method, several beam models with different shapes of cross-sections were investigated, focusing on the feasibility of the method of varying cross-section cases. Comparing the spectral element model with the loss factor and the finite element model with Rayleigh damping, it was confirmed that the loss factor can better describe the actual energy dissipation behavior of the structure. It provides a more accurate theoretical model for estimating structural damping in practical engineering.

Evaluation of Static Displacement Based on Ambient Vibration for Bridge Safety Management.

The evaluation of bridge safety is closely related to structural stiffness, with dynamic characteristics and displacement being key indicators. Displacement is a significant factor as it is a physical phenomenon that bridge users can directly perceive. However, accurately measuring displacement generally necessitates the installation of displacement meters within the bridge substructure and conducting load tests that require traffic closure, which can be cumbersome. This paper proposes a novel method that uses wireless accelerometers to measure ambient vibration data from bridges, extracts mode shapes and natural frequencies through the time domain decomposition (TDD) technique, and estimates static displacement under specific loads using the flexibility matrix. A field test on a 442.0 m cable-stayed bridge was conducted to verify the proposed method. The estimated displacement was compared with the actual displacement measured by a laser displacement sensor, resulting in an error rate of 3.58%. Additionally, an analysis of the accuracy of displacement estimation based on the number of measurement points indicated that securing at least seven measurement points keeps the error rate within 5%. This study could be effective for evaluating the safety of bridges in environments where load testing is difficult or for bridges that require periodic dynamic characteristics and displacement analysis due to repetitive vibrations, and it is expected to be applicable to various types of bridge structures.

Spatial and frequency identification of the dynamic properties of thin plates with the Frequency-Adapted Virtual Fields Method

Vibroacoustic inverse methods use the measured response of a vibrating structure to identify a structural parameter or a dynamic load. Two inverse methods are considered, the Force Analysis Technique (FAT) and the Virtual Fields Method (VFM). The Corrected Force Analysis Technique (CFAT) is a variant of FAT that corrects its singularity. This correction allows the method to be applied in the high-frequency domain, when the number of measurement points per flexural wavelength becomes small. In this study, the proposed novelty is the development of a Frequency-Adapted VFM (FA VFM) to the case of a Love–Kirchhoff plate. Thanks to this method, the VFM can now be applied to identify the equivalent bending stiffness and structural damping of a thin plate when the number of measurement points per wavelength is small. The method has previously been developed for an Euler–Bernoulli beam. An experimental identification of the complex bending stiffness of an locally damped aluminium plate using Laser Doppler Velocimetry (LDV) data and the developed method is performed. The experimental study shows for the first time that the FA VFM can be used to map the equivalent bending stiffness and structural damping as a function of position on a plate and identify these parameters as a function of frequency over a large frequency band. The results of the Frequency-Adapted VFM are compared with those of CFAT and the classical VFM approach. FA VFM results are more accurate than those of classical VFM and similar to those of CFAT.

Far-field directivity estimation with a cube-shaped array of 256 MEMS microphones

The far-field directivity function (FFDF) of a sound source characterises the angular dependence of the acoustic fields far away from this source. This function can be estimated by performing a spherical wave expansion (SWE) of the sound field from pressure measurements distributed around the source. The truncation order of the SWE is a critical parameter that depends on the number of measurement points and on the spatial sampling scheme used for the measurements. Unfortunately, for irregular sampling schemes, no theoretical result allows to determine a truncation order. In this work, a surrounding cuboid microphone array composed of 256 MEMS microphones is deployed. A cross-validation framework is used in order to determine an optimal truncation order for the SWE of the field radiated by a test source. The quality of the reconstructed field is assessed on the frequency range 100-5000 Hz. Finally, the estimated SWEs and far-field directivities are compared to an analytical model of the test source.

Identifikasi Struktur Bawah Permukaan Menggunakan Geomagnet Wilayah Hot Spring Lau Sigembura Deli Serdang

This research was conducted at the Lau Sigembura hot spring tour, STM Hilir sub-district, Deli Serdang district using the magnetic method. This study aims to determine. Subsurface structures and the distribution of magnetic anomalies which are geothermal manifestations. The number of measurement points is 50 with an area of ​​1000 square meters. Data acquisition was carried out using the PPM Model GEM System type GSM 19T.While data processing uses daily corrections and IGRF corrections as well as upward continuations. Modeling is done using Mag2DC software. The total magnetic field ranges from -900 nT to 500 nT based on the contour of the local magnetic anomaly, the variation in the value of the anomaly is around -1050 nT to 350 nT. While the quantitative interpretation indicates the presence sandstone rock with susceptibility value 0,1075 cgs, Andesit with susceptibility values 0,0183 cgs, limestone with a susceptibility value of 0.0001 cgs – 0.0021 cgs. And shales with susceptibility value 0,021 cgs.

Relationship between deflection basin parameters and backcalculated pavement layer moduli

In the case analysed, a glass fibre mesh was applied under the asphalt layer during a rehabilitation treatment. Because only one lane was reinforced, the test section can be used to observe the influence of glass fibre mesh on the relationship between the selected deflection basin parameters (RoC, BLI, MLI, and LLI) and back-calculated pavement layer moduli. The FWD measures were used to determine the bowl of deflection indicators and to back-calculate the layer’s moduli. The values of DBP-s allowed confirmation of the technical condition of pavement construction. The first measures were carried out in 2019 and repeated in 2021; the results were then compared and analysed. Influence was observed on the relationship between the deflection basin and moduli, especially for the base course and subgrade. The reinforced lane showed a better coefficient of determination between DBPs and moduli in 2019, but in 2021 relationships were observed only for LLI and subgrade moduli. The unreinforced lane, however, showed the mentioned relationships in both 2019 and 2021. Because of a relatively small number of measurement points, the presented analyses and observations should be considered as preliminary. Presented results and relationships are another step into developing an alternative approach to determining the initial pavement moduli i.e. to use as a seed moduli.

Optimization of pose samples for calibration of large component docking mechanisms

ABSTRACT The compensation for the positioning error of large component docking mechanisms (LCDM) is the core technology for improving the assembly quality of aircraft. The pose samples (PSs) of the LCDM for kinematic parameter calibration significantly impact the final effect of error compensation. This paper proposes a PSs optimization method for kinematic parameter calibration of LCDM. Firstly, the kinematic model and the principle of kinematic parameter identification of LCDM are introduced. Then, an optimization model for the PSs is established based on the proposed observability index of the kinematic parameters, and a dynamic weighted particle swarm optimization (PSO) algorithm is used to optimize the PSs. Thirdly, the effectiveness of the proposed PSs optimization method is verified by Monte Carlo simulation, and the impacts of the number of measurement points (MPs) and PSs on calibration accuracy are analyzed. Finally, a docking system for simulated LAC is built in the laboratory, and the calibration experiments of the LCDM are conducted based on the optimized PSs. The experimental results show that the assembly accuracy of large components can be significantly improved by reasonably arranging the MPs and using the PSs optimization method proposed in this article.

Comparative Analysis of Measurement Points for Structural Damage Identification in Free-Free Aluminium Beam using Response Surface Methodology and FRF Curvature

This research paper presents a comprehensive comparative analysis of measurement points for structural damage identification in free-free aluminium beams using Response Surface Methodology (RSM) and Frequency Response Function (FRF) curvature. The primary objective is to determine the optimal measurement points for establishing a relationship between the input parameters and response features, thus forming a surrogate model. The investigation focuses on analyzing the influence of the number of measurement points on RSM's capability to identify structural damage. Three distinct Design of Experiment (DOE) techniques are explored: central composite design (CCD), Box-Behnken design (BBD), and D-optimal design, each incorporating different numbers of measurement points (10 elements, 15 elements, and 20 elements). The study's results highlight BBD's strong capability in detecting damage with fewer measurement points, while CCD design accurately identifies damage in finer measurement points. The findings reveal a clear trend: as the number of measurement points increases, the model becomes more refined, yielding higher stiffness reduction factor (SRF) values. The results underscore the significance of selecting an appropriate number of measurement points to enhance RSM's efficiency in identifying structural damage, thereby optimizing damage identification processes. This study contributes valuable insights into the selection of measurement points for effective structural damage identification, offering practical implications for engineering applications.

Direct reconstruction of tissue temperature fields during thermal therapy by dynamic response matching and steady-state correction

In the field of oncology thermotherapy technology, online and real-time reconstruction of biological tissue temperature field is a fundamental work with important practical needs. In this paper, we proposed a new method for direct reconstruction of biological tissue temperature field by dynamic response feature matching and steady-state correction. Based on the bioheat transfer equation, the step response model of tissue temperature field during thermal therapy is established, and the dynamic response eigenvectors of biological tissue temperature and the steady-state gain of temperature response are determined offline. According to the optimal matching principle between the temperature dynamic response of the observation point and the internal space point of tissue, the optimal matching matrix of the dynamic response features between the observation point temperature and the internal temperature field of tissue is determined with the use of the dynamic response eigenvectors. Further, through the weighted synthesis of observation point temperature response by using the optimal matching matrix of dynamic response features, the tissue transient temperature field pre-estimation model is established. Finally, by correcting the tissue temperature field pre-estimation model with steady-state gain correction factor, the direct reconstruction scheme of temperature field based on dynamic response feature matching and steady-state gain correction is established. In this work, the non-destructive reconstruction of the internal temperature field of biological tissues during laser-induced thermal therapy is achieved based on the above direct reconstruction scheme. Numerical simulation experiments are performed to investigated the effects of pre-estimation time domain, the number of measurement points, laser irradiation form and measurement error on the temperature field reconstruction results.

Visualization of slit defect by scanning nonlinear airborne ultrasound source technique using compressed sensing

A high-speed, non-contact non-destructive testing method using a scanning airborne ultrasound source and a nonlinear harmonic method has been developed for plate-like structures. The testing time depends on the scanning speed and the number of measurement points. To solve this problem, we propose using compressed sensing with this method. In this paper, we investigated visualizing Lamb wave propagation using the proposed compressed sensing method. In addition, we detected a slit defect by using the Lamb wave propagation image. Our results demonstrated that compressed sensing could be used to reduce the testing time.

An Adaptive Tracking Method for Moving Target in Fluctuating Reverberation Environment

In environments with a low signal-to-reverberation ratio (SRR) characterized by fluctuations in clutter number and distribution, particle filter-based tracking methods may experience significant fluctuations in the posterior probability of existence. This can lead to interruptions or even loss of the target trajectory. To address this issue, an adaptive PF-based tracking method (APF) with joint reverberation suppression is proposed. This method establishes the state space model under the Bayesian framework and implements it through particle filtering. To keep the weak target echoes, all the non-zero entries contained in the sparse matrix processed by the low-rank and sparsity decomposition (LRSD) are treated as the measurements. The prominent feature of this approach is introducing an adaptive measurement likelihood ratio (AMLR) into the posterior update step, which solves the problem of unstable tracking due to the strong fluctuation in the number of point measurements per frame. The proposed method is verified by four shallow water experimental datasets obtained by an active sonar with a uniform horizontal linear array. The results demonstrate that the tracking frame success ratio of the proposed method improved by over 14% compared with the conventional PF tracking method.

Study on blade zoning measurement point planning method

Due to the complex surface profiles of blades, the current measurement point planning does not adequately capture the distinct zones, leading to low measurement efficiency and challenges in meeting online detection requirements. This study proposes a novel approach to blade zoning measurement point planning. First, it utilizes an improved centroid Voronoi extreme model and smoothness indicators to select seed points during the zoning process. Following that, feature tensor-driven regional clustering is carried out based on these seed points. Finally, measurement points are determined through adaptive sampling of profile deviations along the feature stacking axis within each zone. Simulation and real experiments demonstrate that the measurement points generated by this method effectively represent the blade surface's distinctive features, reducing the number of measurement points by 91.7% and significantly enhancing efficiency.

The Limit of Incomplete Information in Inverse Analysis for Hidden Corrosion Inference in Reinforced Concrete

One recurring problem in reinforced concrete structures is hidden corrosion. Detection of hidden corrosion is difficult due to incomplete information that can be measured. To overcome this problem, inverse analysis can be employed. Inverse analysis uses incomplete information from field measurement, and employs optimization to infer further information. Previous research has demonstrated the inference capability of inverse analysis for hidden corrosion detection in reinforced concrete. However, question remains on the limit of incompleteness of measurement data. The aim of this study is to simulate and examine the limit of incomplete information that can be allowed for an effective inverse analysis. The inverse analysis of hidden corrosion in reinforced concrete is formulated as a PDE-constrained optimization. The objective function of the optimization is the distance function between measurement data and FEM simulation. The search space is the PDE boundary conditions configuration. A FEM simulation is used to simulate measurement data by half-cell potential mapping on a concrete block of 2 by 1 meters. To simulate incomplete information, the number of measurement points is varied from 2 to 20 points on the surface of the concrete block. Results show that 20 measurement points are needed to successfully infer hidden corrosion profile. However, when the number of measurement points are below this, the effectiveness of inverse analysis varies and does not seem to correlate to the amount of information (i.e., number of measurement points). Further study is needed if this is due to a fluke or choice of measurement point’s location.

Validation of a Simplified Method for Estimating the Harmonic Response of Rogowski Coils with the Monte Carlo Method.

The need to monitor the power network is leading to a significant increase in the number of measurement points. These points consist of intelligent electronic devices and instrument transformers (or more in general sensors). However, as the number of devices increases, so does the demand for their characterization and testing. To this end, the authors formulated a new characterization procedure that offers numerous benefits for manufacturers and system operators. These benefits include: (i) reducing testing time (thus lowering costs), (ii) simplifying the existing procedures, and (iii) increasing the number of tested devices. In this study, to complete the validation of the proposed characterization procedure, the authors performed a comprehensive uncertainty evaluation. This included the identification and analysis of the uncertainty sources, the implementation of the Monte Carlo method to obtain the statistical parameters of the quantities of interest, and the final method assessment according to the obtained results. Each step is described in detail, and the results allow one to (i) replicate the uncertainty analysis on other types of instrument transformers and (ii) implement the proposed harmonic characterization procedure with the confidence that the method is accurate, flexible, and scalable.

Optimising laser-induced phased-arrays for defect detection in continuous inspections

This paper proposes a novel optimisation approach for laser induced phased-arrays for detection purposes in large area inspection. The optimisation aims to maximise the detection capability of a phased-array while minimising the inspection time. This is done by using a simulation ray-tracing model that evaluates multiple candidate configurations. The metrics that measure the detection performance for a target defect are the receiver operating characteristic curve and the signal-to-noise ratio. The inspection time is indirectly computed through the number of measurement points per unit length in a continuous inspection. This depends on the physical aperture and pitch of the phased-array and they are the quantities optimised. The optimisation and modelling approach are validated in an experimental case study for a side-drilled hole as target defect. Further recommendations about directional defects (e.g. cracks at different angles) are provided.

Non-contact impact load identification based on intelligent visual sensing technology

Accurate identification of impact loads is vital for structural assessment and design. Traditional methods rely on complex equipment, such as accelerometers or strain gauge, which can be expensive and prone to failure. This study introduces a non-contact intelligent identification approach incorporating visual sensing technology, providing a convenient means to identify impact loads. Numerical simulations explore the differences in identifying impact forces through acceleration and displacement responses, particularly by considering such variables as measurement noise and number of measurement points. A meticulously designed experiment verified the feasibility of the proposed method for measuring the displacement and velocity of rapidly moving targets, and evaluated its performance in terms of accuracy. A series of impact loading experiments were conducted on a simply supported girder bridge model to validate the effectiveness of the proposed impact force identification method. Results indicate strong agreement between displacement response measurements and percentile meters. The proposed non-contact method accurately identifies single or continuous impact loads, with a minimum peak relative error of 0.2%. This study represents a pioneering application of intelligent visual sensing technology in the field of impact load identification. Moreover, the current research introduces a novel approach to address the challenges faced by conventional methods in identifying impact loads. Future research can leverage the groundwork laid by this study to further optimize and expand the proposed method, enhancing its capabilities and fully harnessing its potential to offer advanced solutions in structural health monitoring.

Shape Sensing in Plate Structures through Inverse Finite Element Method Enhanced by Multi-Objective Genetic Optimization of Sensor Placement and Strain Pre-Extrapolation.

The real-time reconstruction of the displacement field of a structure from a network of in situ strain sensors is commonly referred to as "shape sensing". The inverse finite element method (iFEM) stands out as a highly effective and promising approach to perform this task. In the current investigation, this technique is employed to monitor different plate structures experiencing flexural and torsional deformation fields. In order to reduce the number of installed sensors and obtain more accurate results, the iFEM is applied in synergy with smoothing element analysis (SEA), which allows the pre-extrapolation of the strain field over the entire structure from a limited number of measurement points. For the SEA extrapolation to be effective for a multitude of load cases, it is necessary to position the strain sensors appropriately. In this study, an innovative sensor placement strategy that relies on a multi-objective genetic algorithm (NSGA-II) is proposed. This approach aims to minimize the root mean square error of the pre-extrapolated strain field across a set of mode shapes for the examined plate structures. The optimized strain reconstruction is subsequently utilized as input for the iFEM technique. Comparisons are drawn between the displacement field reconstructions obtained using the proposed methodology and the conventional iFEM. In order to validate such methodology, two different numerical case studies, one involving a rectangular cantilevered plate and the other encompassing a square plate clamped at the edges, are investigated. For the considered case studies, the results obtained by the proposed approach reveal a significant improvement in the monitoring capabilities over the basic iFEM algorithm with the same number of sensors.

Calculation of dielectric constant calibration characteristics of sensors using the method of moments

This research is devoted to the issues of further development of methods of experimental measurement of dielectric characteristics of solid materials, liquids and liquid–gas media, which are foam structures. In recent decades, foam structures have gradually filled and supplanted traditional dielectric materials. There are still no scientific and metrology-based methods and devices for correct measurements of foam. In the paper, the method of moments (MoM) is employed for resonator measurements. The obtained results for a wide range of dielectric constants from 1 to 80 are interesting for determining the sensitivity of measurements, the influence of frequency measurement errors, and determining the number of measurement points.

Study on the regional ASF prediction method based on the ordinary kriging interpolation

The eLoran system functions as a robust backup to the Global Navigation Satellite System (GNSS), providing substantial signal power, robust anti-jamming capabilities, and an easily maintainable ground system. Nonetheless, the propagation time delay of the system, primarily driven by the Additional Secondary Phase Factor (ASF), significantly influences the positioning accuracy. Compensating for ASF can effectively enhance the positioning performance. Traditional propagation delay theories frequently yield substantial discrepancies between the predicted and measured values in regions characterized by extended propagation distances and varying topographic features. To address this issue, we conducted ASF measurements within a selected test area using a limited number of measurement points. We employed the ordinary Kriging interpolation method to predict ASF values across the entire test area, and used cross-validation to validate our predictions. The results confirmed the accuracy and effectiveness of the Kriging interpolation algorithm in predicting ASF values within specific regions. The cross-validation demonstrated that the errors remained within acceptable ranges. Furthermore, we applied Ordinary Kriging, Inverse Distance Weighting, and Radial Basis Function Interpolation methods to evaluate the positioning accuracy of the test area before and after ASF correction. Compared to other methods, using the Ordinary Kriging interpolation algorithm for predicting ASF values resulted in a corrected positioning accuracy of up to 68.8 m at various test locations. This approach effectively resolves the challenge of low accuracy in theoretical calculations in complex environments. By utilizing ordinary Kriging interpolation, we required measurements of only a few ASF values within a specific region to create an ASF correction map, addressing the challenges related to inaccurate theoretical calculations in complex pathways and avoiding time-consuming and labor-intensive large-scale measurements. The results of this study offer valuable theoretical support for improving the accuracy of land-based navigation systems.