Curve and surface reconstruction methods play an important role in many research and engineering fields. It is an imperative procedure to carry out surface reconstruction from measurement data in reverse engineering, which is complicated with the presence of outliers. To achieve better accuracy and robustness of reconstruction, an improved moving total least squares (MTLS) algorithm based on k-means

In this article, a modified Minkowski fractal antenna with a circular-shaped split-ring resonator (CSSRR) structure is proposed for wireless applications. Fractal geometry is accountable for creating dual-band resonance, and CSSRR is responsible for obtaining a middle resonance frequency band. The proposed antenna has a compact dimension of 23.5 × 26.5 × 1.6 mm3 to be fabricated and measured. Antenna

Tool wears directly affect the quality of product and service life of tool. This paper proposes a machine vision-based measurement method for chisel edge wear of drills. Firstly, the full contour of a drill is extracted by local variance threshold segmentation. Secondly, the image is enhanced by using an adaptive contrast enhancement algorithm based on bidimensional local mean decomposition (BLMD)

A video-based indirect sensing procedure for dynamic identification purposes is presented. To overcome major limitations of video-based methods in real on-site measurements, a novel three step pre-modification, magnification, post-modification process is developed. This process includes revision of the initial input video record in order to delete disturbing objects, utilizing a magnification method

Acoustic sensing techniques have demonstrated to be promising methods for leak detection. A major challenge lies in the multi modes and dispersion nature in acoustic signals propagating along pipelines, which may cause inaccurate estimation of wave velocity and time delay. To find a best solution for precise leak identification considering a specific application scenario, a field test is conducted

In this paper, a simple singlemode-multimode-singlemode (SMS) optical fiber sensor is proposed and investigated for measuring the air pressure of a circular thin plate. Theoretical analysis and experimental demonstration are presents in this paper. The air pressure changes the strain and bending radius of the SMS sensor directly attached to the thin plate, and hence leads to shifts and intensity variation

Satellite Laser Ranging (SLR) to Low Earth Orbiters (LEOs) is traditionally used to validate orbits derived by microwave techniques, e.g., Global Positioning System (GPS). For most LEOs, SLR is the only possibility to independently assess the GPS orbit quality, to calibrate onboard instruments, and to reveal otherwise unnoticed systematic errors. However, the detector-specific errors in SLR measurements

This research puts forward a novel approach by proposing mathematical equations to estimate the fault intensity index in induction motor with stator inter-turn short circuit (ITSC) fault. Determination of the failure index is significant to create appropriate mitigation methods, as well as to define a safe working area for the motor to prevent the subsequent damage to the stator winding. Discrete Wavelet

The paper presents the diagnostic procedure for the ratchet mechanisms' fault detection based on the acoustic signal analysis. The diagnostic framework was proposed, consisting in three steps. First, the symptoms are extracted from audio recordings using the proposed measurement system. Next, training and testing data sets, representing various faults of the mechanism are created. Finally, the selected

Accurate passenger demand forecasting of high-speed railway is of great significance for railway line planning and daily operation management. Capturing the random factors hidden in complex data is the key to achieve accurate forecasting. In view of this, this paper presents a new system with deterministic and probabilistic forecasting capacities based on the residual component disposing. First, the

Cyclic weak disturbance caused by blasting, drilling, earthquake and transport is an important factor to deep rock projects failure. In order to study the influence of cyclic weak disturbance on the stress relaxation of rock under different confining pressures, a step loading stress cyclic weak disturbance relaxation test was carried out on marble, and an impact factor of weak disturbance was defined

In perspective projection images, apparent contours are important bases for recovering the three-dimensional (3D) shapes of constant diameter pipes (CDP). In order to complete the 3D reconstruction of CDP under perspective projection, this article first analyzes the single-view perspective projection model of CDP in detail. On this basis, coupled point pairs searching and projected axis extraction

Rubber bearings are a key component of base-isolated structures. Hence, it is important to effectively monitor the axial pressure in rubber bearings. A smart rubber bearing (SRB) and a wavelet-packet-based axial pressure index were introduced in the previous study. However, the wavelet-packet-based axial pressure index for evaluating the axial pressure in the SRB has notable shortcomings, because the

Lane-changing duration (LCD) measures the total time it takes for a vehicle to travel from the current lane to the target lane. However, there is still a paucity research on LCD up to now. In this paper, we present a comprehensive analysis of LCD from the perspective of survival analysis. Naturalistic vehicle trajectory HighD dataset is employed in this paper, which contains of 16.5 h of measurement

Generally, the transient characteristics of early bearing failure are not obvious. How to extract weak transient features is a big challenge. Dictionary learning has been successfully used to extract bearing fault features. However, the traditional dictionary learning is easy to fall into local optimum and cannot extract fault features from complex signals. And it often consumes huge computational

Remaining useful life (RUL) prediction plays a crucial role in ensuring reliability and safety of modern engineering systems. For complicated systems, the indirect manner of the conventional RUL prediction approaches restricts their universality and accuracy. The challenge to realize accurate RUL estimation consists in the direct exploration of the potential relationship between the RUL and the numerous

This paper proposes an innovative method for Integral Nonlinearity (INL) testing, that allows to measure the voltage corresponding only to a subset of all the codes of Digital-to-Analog Converters (DAC), shortening the duration of static characterization. The method operates, in fact, a pseudo-random selection of DAC codes to be tested but, through Compressed Sensing, it is able to recover the INL

This paper presents the measurement and prediction of the tunnelling-induced surface response in karst ground, Guangzhou, China. A predictive method of ground settlement is proposed named as the expanding deep learning method. This method kinetically uses the expanding tunnelling data to predict ground settlement in real time. Four types of deep learning methods are compared, including artificial neural

In this paper, we propose a new time–frequency analysis (TFA) method termed longitudinal synchrosqueezing transform (LSST). As a post-processing time–frequency analysis method, the theory of this method is based on the Reassignment method (RM) and Fourier-based synchrosqueezing transform (FSST). LSST combines the advantages of RM and FSST in signal processing and avoids their drawbacks. Compared with

Threaded fasteners are widely used in a variety of engineering applications. The quality of threaded connections directly affects the service performance. By aiming to acquiring a deeper understanding of the performance characteristics, the mechanical behavior of bolted joint was examined using transverse tensile test. The force–displacement curves of bolted joints exhibit linear characteristics during

This study presents a new optimal supplementary neuro-controller design for unified power flow controllers (UPFCs) using wide-area signals. The new design is oriented by the dual heuristic programming (DHP) method, which is a powerful adaptive critic procedure. The proposed controller injects additional signals to the UPFC series inverter to enhance power system stability. A model, action and critic

Computer vision has become widely applied for structural displacement monitoring. However, heat haze is one of the major challenges. Image distortions caused by heat haze in hot weather can result in displacement errors. Therefore, a comprehensive study of properties of heat haze-induced distortions and displacement errors is conducted. Firstly, an image distortion estimation method is proposed for

Accurate fastener positioning and state detection form the prerequisite for ensuring the safe operation of rail track. The demands for intelligent, fast and accurate detection cannot be satisfied by traditional methods using image processing and fastener classification. In view of this, a two-stage classification model based on the modified Faster Region-based Convolution Neural Network (Faster R-CNN)

In order to enhance the sensing performance and the sensitivity of surface plasmon resonance (SPR) sensor, a potential sensing layer should be immobilized on a metal thin film. Thus, the immobilization of nanocrystalline cellulose/poly(3,4-ethylenedioxythiophene) (NCC/PEDOT) on gold thin film has been fabricated for mercury ion (Hg2+) detection. Then, the sensing layer thin film has been incorporated

Real-time monitoring of unauthorized working activities above the subway tunnel is an intractable issue. Illegal drill rig working is one of the most threatening way of intrusion. Nowadays, the distributed optic fiber sensing technology promises to provide a viable means for the long distance monitoring in the complex working conditions. To tackle the difficult problem of drill rig intrusion, we use

This work presents an experimental study focused on the characterization of series arc faults in direct current (DC) photovoltaic (PV) systems. The aim of the study is to identify some relevant characteristics of arcing current, which can be obtained by means of low frequency spectral analysis of current signal. On field tests have been carried out on a real PV system, in accordance with some tests

Tactile sensing is very important for human-machine interaction. A new non-array flexible touching sensor based on variation of electrical impedance distribution (VEID) is proposed to detect position and pressure of external touching. The sensor includes two layers of piezoresistive film, and there are 16 electrodes at the inner and boundary of the film. Two of the electrodes are used for stimulation

The results of comparative studies of the electrically conductive properties of Co69Fe4Cr4Si12B11 glass coated amorphous microwires obtained during their heat treatment in a conventional furnace and by the Joule heating method are presented. The fully crystallized microwire dramatically changes its electrically conductive properties. We found that the crystallized microwire has a temperature coefficient

There is urgent demand for new absolute Linear Displacement Measurement (LDM) technology with high resolution and high precision, during the development of high-end numerical control technology. In previous research, we found that displacement measurement based on the image processing method performs well, however, the volume increases when using an imaging lens, and the system is susceptible to factors

Quantitatively monitoring the thickness reduction of a pipe by using magnetic flux density method remains a major challenge due to the small and gradual change in magnetic flux density over a long distance along a pipe. This signal change is hindered in the background signal of a detector that has a high temperature dependence and unstable background signal. In this paper, we verify the effectiveness

The measurements of time-difference-of-arrival (TDOA) and wave velocity have significant influence on localization accuracy. To reduce the loss in localization accuracy induced by TDOA noises and velocity errors, the constrained total least squares (CTLS) method using the TDOA measurements for jointly estimating AE source and wave velocity is proposed in this paper. The proposed method exploits the

Eddy current-based nondestructive detection was first used for testing self-sensing cement paste in this study. The effects of three functional fillers and aging on self-sensing cement paste were observed. First, the plain mortar exhibited self-sensing ability at the earliest curing time, but its gage factor significantly decrease with ages. Second, among the three functional fillers that were studied

In view of the problem that the increased difficulty of underwater moving targets detection caused by the development of acoustic stealth technology, a beaded cilia MEMS vector hydrophone (BCVH) is proposed in this paper. Compared with previous cilia structures, it can enlarge the receiving area of acoustic wave to improve sensitivity without the introduction of additional structures. Meanwhile, the

We present a method for detection of absorption change in skin tissue on the basis of simulated spectra extracted from an absorption-oriented database. We constructed the database with a moderate number of reflectance spectra which are simulated by the Monte Carlo method using the nine-layered skin model. In the construction of database, change of only absorption coefficients in the nine layers is

The bearing fault signal can be seen as convolution of periodical impulses and interference components. The minimum entropy deconvolution (MED) is effective approach for the deconvolution of signal. However, the MED is vulnerable to random impulse and interference components. To solve the problem, an improved method, named minimum entropy morphological deconvolution (MEMD), is proposed in this paper

Due to the solar radiation effect, current air temperature sensors may produce a radiation error that is on the order of 1 °C. In this paper, a temperature sensor with a new structure is proposed. Initially, a computational fluid dynamics (CFD) method is employed to quantify the radiation errors for the sensor under various environmental conditions. Then, a radiation error correction method is obtained

Near-field coseismic displacement information is very important for seismological research. High-rate GPS and seismic sensors are mutually advantageous for capturing earthquake-induced coseismic displacements. The combination of them can help to improve the near-field observation results. In this paper, we propose a combined model of fusing GPS and strong-motion records by taking into consideration

Multisensor systems are widely used in large-scale fringe projection profilometry, where the accuracy and efficiency of registration play an important role. However, existing methods using reference targets or auxiliary devices lengthen the coordinate transformation chain and are difficult to achieve high accuracy and efficiency. In this study, we propose a method that uses the absolute phase retrieved

A novel direct absorption spectroscopy gas sensing system based on end-to-end deep neural networks was proposed for measurements of gas concentration. One-dimensional convolutional neural network and deep multi-layer perceptron were explored to measure the concentrations of methane and acetylene. The accurate measurement results for both gases demonstrated that deep neural networks based direct absorption

During steel strip production, mechanical forces and environmental factors cause surface defects of the steel strip. Therefore, detection of such defects is key to the production of high quality products. Moreover, surface defects of the steel strip cause great economic losses to the high-tech industry. So far, few studies have explored methods of identifying the defects, and most of the currently

Automatic air brake systems are widely used in freight train braking to ensure railway operation safety. Various types faults pose an enormous threat to freight operations. Existing algorithms lack a unified framework for generating key features. In this research, we propose a novel feature engineering framework for the fault diagnosis of freight train air brakes. First, experimental data are collected

Unsupervised domain adaptation has achieved certain success in recent cross-domain fault diagnosis research. As a widely used transfer strategy, the distribution alignment often occurs with the problems of too few valid alignment samples, too low confidence of predicted labels, and the inadequate alignment of marginal or conditional distributions. Therefore, this paper proposes a statistical distribution

The response speed of the intelligent systems embedded in an autonomous vehicle is crucial for its correct operation and reduction of the risks on the road derived from autonomous driving. For that reason, it is necessary to optimize the algorithms that process the data from the sensors; with that aim the Field-Programmable Gate Arrays (FPGAs) offer the possibility of parallelizing the tasks to be

Traditionally, prognostics approaches to predictive maintenance have focused on estimating the remaining useful life of the equipment. However, from an industrial point of view, the goal is often not to predict the residual life but to determine the need for a maintenance action at a given time window. This approach allows us to frame the data-driven prognostics problem as a binary classification task

This paper proposes a sparsity adaptive matching pursuit and spectrum line interpolation (SAMP-SLI) method for measuring the radial and axial error motions of spindle rotation of machine tool. The method measures the displacements from the outside surface of a custom-fabricated cylindrical precision artifact using capacitive displacement sensors. The measured error motions are reconstructed with sparse

Sampling moiré method (SMM) is widely used for measuring high-accurate displacements and strains. However, it provides accurate measurement only when the displacement is smaller than half of grating pitch due to defects on phase difference calculation. To overcome the shortage of SMM, we improve the performance of SMM by adapting the integer-pixel digital image correlation (DIC). The improved SMM is

An application for sensing the stress-induced localization of damage in the form of a discrete crack in a concrete substrate is developed using embedded PZT patches. Stress-wave measurements are obtained through the stages of damage localization leading to crack formation, propagation, and opening of the discrete, localized crack in the concrete. A self-compensating attenuation factor is proposed to

This paper studies the error theory of the asymmetric chord-reference system (ACR-system) for track geometry measurement. In contrast to mid-chord offset system (MCO-system), ACR-system shows a much better band-pass response even in very short wavelengths. The implementation of the ACR-system is challenging due to its nonlinear phase response. Based on z-transform, the inverse system of the ACR-system

To construct concrete in recent decades, the reducing freshwater is one of the basic requirements. Feasibility of replacing freshwater with seawater has been confirmed in literature. This study aims to investigate the effects of fresh and salty water on the compressive strength of the concrete samples after 28 days. Then, two hybrid artificial intelligence techniques namely neuro-swarm and neuro-imperialism

Time series anomaly detection is one of the key challenges in the field of condition monitoring. Many anomaly detection methods are inefficient and easy to lose effective information due to manual features extracting. Deep learning-based methods can solve the problem effectively, but the detection accuracy is still not satisfactory. In addition, most of the methods cannot take the time-ordered specialty

The constant increase of switching power converters in distribution and transmission grids pushes the need for harmonic measurements. Recent literature has shown that inductive Voltage and Current Instrument Transformers (VTs and CTs) can be used for harmonic measurements, but their accurate frequency characterization involves the use of quite costly instrumentation. In this context, this paper proposes

The paper presents a novel loopback test method for frequency response characterization of Digital-to-Analog Converters (DACs). As in traditional loopback test method, the DAC output is acquired by means of a digitizer. However, by relying on Compressive Sampling (CS), the proposed method reduces the sampling frequency requirements for the digitizer allowing to embed it in the DAC. In this case, an

Dynamic temperature measurement is important in industry. The traditional method with a dual-thermocouple is easily disturbed by noise, so it is only suitable for a high signal-to-noise ratio (SNR). To obtain more accurate dynamic temperature, a dual-thermocouple method based on a one-dimensional convolutional neural network is proposed. This method extracts and fuses the temperature signals of two

As one of the fast-developed NDT&E (nondestructive testing and evaluation) techniques, eddy current pulsed thermography (ECPT) is extensively used for crack detection and quantification in ferromagnetic pressure components. However, in the practical inspection, the stress has significant influences on the permeability while that haven’t been concerned. To improve the detection accuracy of crack measurement

In this paper, the correlation between probability box (p-box) models was studied, and a method of constructing a correlation probability box (cp-box) model from raw bearing data was proposed. First, a copula function was used to construct the correlation model based on bearing data, and the inverse function of the cumulative distribution function was obtained by selecting the appropriate confidence