The advent of the fourth industrial revolution (Industry 4.0) aims at increasing automation and efficiency in manufacturing processes by the adoption of information and communication technologies. Several of the proposed solutions rely on precise localization of material, equipment, or operators. This article investigates the employment of ultrawideband (UWB) real-time location systems (RTLS) in a

Electrocardiogram (ECG) is a tool to help judge heart activity. In recent years, the convolutional neural network (CNN) and various deep learning algorithms have been widely used in ECG diagnosis. CNN only considers the local feature. However, the ECG signal is susceptible to noise, and the waveform is complex, making it difficult for existing methods to get a good result. This article presents a novel

Quick and accurate ellipse detection is essential for computer vision, automatic manufacturing, and other fields. In order to obtain more accurate ellipse parameters, the least-squares support vector regression is employed to establish the objective function and further convert the ellipse fitting problem into an optimization problem. This article proposes a hybrid BFGS algorithm integrated with an

The telemetry data obtained from an on-orbit spacecraft contain important information to indicate anomaly of the spacecraft. However, the large number of monitoring variables and the large amount of data points, as well as the lack of prior knowledge about anomaly due to complicated structure of spacecraft and its working conditions, pose great challenge to the anomaly detection. This article proposes

Industrial data are in general corrupted by noises and outliers. In this context, robustness to the contaminated data is a challenging issue in process monitoring. In this article, a novel method named low-rank joint embedding is proposed for robust process monitoring. By learning a low-rank coefficient matrix, low-rank joint embedding can capture the global structure of the original data and alleviate

In semantic visual simultaneous localization and mapping (VSLAM), accurate data association of semantic measurement from visual sensor is very crucial for robot state estimation and scene reconstruction. However, most of the related works assume a simple world for semantic association. It is still a challenge to deal with the ambiguity of data association in a cluttered environment. In this article

The location of the center of rotation (COR) of joints is a key parameter in multiple applications of human motion analysis. The aim of this work was to propose a novel real-time estimator of the center of fixed joints using an inertial measurement unit (IMU). Since the distance to this center commonly varies during the joint motion due to soft tissue artifacts (STAs), our approach is aimed at adapting

Stability is one of the most important characteristics of the potentiometric urea biosensors; however, it has rarely been discussed in previous literature. In this article, the stability of the potentiometric urea biosensor based on the urease-Ag NPs/RuO 2 sensing film was studied. Using the voltage–time ( $V$ – $T$ ) measurement system, the stability was verified by analyzing the biosensor’s reproducibility

This study aims to determine the relationship between Hounsfield Unit shift ( $\Delta {\mathrm{ HU}}$ ), tissue temperature change ( $\Delta T$ ), and tissue’s relative cross-sectional area change ( $\Delta A$ ) of ex vivo bovine liver tissues. The fresh bovine livers ( $n = 3$ ) were heated from 21 °C to 100 °C within 24 min using a custom-made ceramic hot plate and left for cooling to room temperature

A low cost, wearable textile-based respiratory sensing system is proposed and experimentally demonstrated. A highly sensitive D-shaped plastic optical fiber (POF) sensor that responds to bending is integrated into an elastic band structure to form a respiratory sensing system. The curvature sensing experiments were conducted on the D-shaped POF sensor, which has a coefficient of determination (R 2

Composite insulator is prone to internal defects such as air gaps which seriously endanger the safety of power systems. To detect the internal defects in composite insulators, a terahertz (THz) imaging method based on edge detection algorithm was proposed in this article. First, air gap defect sample consisting of planar multilayers was imaged based on the envelope area of the THz reflection waveform

This article presents investigation of 3-D electrical capacitance tomography (ECT) sensors with different excitation strategies, including dual-electrode excitation in the same plane, in adjacent plane, in planes separated by one plane or two planes, and in the adjacent position or opposite position in the same or different planes. The results show that a 3-D ECT sensor with dual-electrode excitation

Measuring the distance is one of the main objectives for sensor development. In this article, we present a new sensor system design for depth recovery. It is based on stereopsis with the integrated rotation of an image sensor. Different from conventional stereo vision systems with multiple cameras, the proposed rotational stereo configuration is built upon a single imaging device. By directing its

Automated pixel-level crack detection is one of the essential tasks in the field of defect inspection. Deep convolutional neural networks, typically using encoder–decoder architectures, have been successfully applied to many crack detection scenes in recent works. However, encoder–decoder networks commonly rely on downsampling and upsampling operations and have a large number of parameters, which may

In order to improve the accuracy of fire identification based on video in the Internet-of-Things environment, this article proposes a new fire identification algorithm by merging fire segmentation and multifeature fusion of fire. First, according to the relationship between R and Y channels, the improved YCbCr models are established for initial fire segmentation under reflection and nonreflection conditions

In this article, we propose an infrared and visible image fusion network based on the salient target detection, termed STDFusionNet, which can preserve the thermal targets in infrared images and the texture structures in visible images. First, a salient target mask is dedicated to annotating regions of the infrared image that humans or machines pay more attention to, so as to provide spatial guidance

During the past several decades, inexpensive compact nuclear magnetic resonance (NMR) instruments have been widely used for on-site detections of chemical identity and sample analyses in industrial applications. In general, via shim coils and control strategies, automatic search shimming methods are capable of improving the magnetic field uniformity so that optimized signals can be acquired and particularly

Optical tracking systems (OTS) can provide high position accuracy over a large workspace. However, the orientation from the OTS is related to the distance between markers, which contains large errors when the distance is small or line-of-sight problems occur. The orientation estimation with a gyroscope is complementary to the OTS-based orientation. In this article, an error-state Kalman filter (ESKF)

The oscillator fluctuations are described as the phase or frequency-noise spectrum or in terms of a wavelet variance as a function of the measurement time. The spectrum is generally approximated with the “power law,” i.e., a Laurent polynomial with integer exponents of the frequency. This article provides: 1) the analytical expression of the response of the wavelet variance parabolic variance (PVAR)

Calibrating high-precision 3-D measuring instruments by using traditional calibration methods is challenging because these instruments require the use of higher-precision calibration artifacts. Self-calibration models can separate system errors from overall measurement errors by using auxiliary artifacts with accuracy within that of the object to be calibrated; therefore, such models have substantial

In image charge sensing applications, a tradeoff exists between minimizing detector capacitance for improved amplifier noise performance and adding repeated sensing stages for noise improvement through averaging of repeated signals. In order to understand this tradeoff, the link between image charge detector geometry and capacitance is studied through finite element analysis. This knowledge is then

In this article, we introduce a pedestrian dead reckoning (PDR)-based navigation device that does not require global navigation satellite system (GNSS) signals or beacons and works with an inertial measurement unit (IMU) mounted on its waist belt. The system identifies the individual by their walking pattern to use the proper gains in the computations, estimates the attitude by applying an unscented

Local learning models have been widely applied for time-variant process soft sensor development, where historical samples that are similar to the online testing sample are selected for local modeling and prediction. However, those similarity measurements and local models are commonly established based on the static samples, which are seriously inadequate when process dynamics exist. To tackle this

Offshore wind turbines are complex pieces of engineering and are, generally, exposed to harsh environmental conditions that are making them to susceptible unexpected and potentially catastrophic damage. This results in significant downtime and high maintenance costs. Therefore, early detection of major failures is important to improve availability, boost power production, and reduce maintenance costs

Considering the nonlinear and nonstationary characteristics of rolling bearing vibration signals, we propose a rolling bearing fault diagnosis method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), refined composite multiscale fuzzy entropy (RCMFE), Laplace score (LS), and the particle swarm optimization-probabilistic neural network (PSO-PNN). First, the method

Unsupervised domain adaptation (UDA)-based methods have made great progress in mechanical fault diagnosis under variable working conditions. In UDA, three types of information, including class label, domain label, and data structure, are essential to bridging the labeled source domain and unlabeled target domain. However, most existing UDA-based methods use only the former two information and ignore

The primary optimization of the imaging speed of optical coherence tomography (OCT) has been keenly studied. In order to overcome the major speed limitation of spectral-domain OCT (SD-OCT), we developed an ultrahigh-speed SD-OCT system, with an A-scan rate of up to 1 MHz, using the method of space–time-division multiplexing (STDM). Multicameras comprising a single spectrometer were implemented in the

This article presents a method for real-time 3-D imaging and velocity measurement of two-phase flows using a twin-plane electrical capacitance tomography (ECT) sensor with 24 electrodes. A dedicated digital ECT system with a data acquisition rate of 241 frames/s is used for capacitance measurement. In this article, the sensitivity distribution of the ECT sensor is analyzed, and the two most commonly

Infrared noncontact detection has the advantages of having no power cut-off and convenient operation. However, when the SF 6 (sulfur hexafluoride) gas leakage is small, the existing detection algorithms have low accuracy and are easily disturbed by noise. To solve this problem, this article proposes an online detection method for SF 6 gas leakage based on a Gaussian mixture model. First, as a preprocessing

In this article, we consider the problem of extracting star spots for traditional star sensors under highly dynamic conditions. Under this setting, it is difficult to effectively extract star spots with a low signal-to-noise ratio (SNR), resulting in a failure to estimate the attitude of star sensors. We propose a method named optimal directional connected component (ODCC) for this task. According

The procedure of classifying a detected signal’s modulation scheme with no a priori information is known as automatic modulation classification (AMC). AMC has presented numerous contributions toward civilian and military applications. However, in the scientific literature, designing automatic modulation classifiers has been limited to a single particular simulated environment in most cases of study

The received signal strength (RSS) is widely used in range-based localization because of its practical advantages, such as low cost and low complexity. For accurate ranging based on the RSS in indoor environments, well-defined propagation models (PMs) that consider the distortion of the RSS due to abrupt obstructions are required. This article proposes an exponential PM for indoor hallways whose structures

In this article, an attractive resonant technique is devised for calculating the dielectric properties of arbitrary length material under test (ALMUT), which is partially filled inside a waveguide cavity sensor. The proposed technique exempts two major assumptions viz. the depolarization effect and the theory of images, which were neglected in earlier cavity perturbation methods. A numerical model

Dynamic object following is an essential ability for mobile robots in various application scenarios such as auxiliary cargo transportation, disabled assistant caring, and multirobot formation. A dynamic object following method for a mobile robot based on ultrahigh-frequency (UHF) radio frequency identification (RFID), which uses a phase difference information-based dynamic following model, is presented

Direct time-of-flight (dToF) sensors that measure depth by pulsing a laser and timing the photon return are used in many applications, including consumer electronics for proximity sensing and depth map generation. A histogram of photon return times is measured and then processed to estimate object depth. By collecting many photons that span multiple bins of the histogram the final depth estimate interpolates

Most of the available overvoltage sensors are too sensitive to the installation angle and inducing direction. Even a slight angular deflection will cause a nonnegligible error to the measurement. To reduce the impact caused by angular deflection, in this article, we propose a new spherical six-electrode overvoltage sensor to improve the measuring accuracy and stability. First, we presented the 3-D

To overcome the shortcomings of low energy conversion efficiency of electromagnetic acoustic transducers (EMATs), point-focusing shear horizontal (PFSH) wave EMAT is used to focus the wave energy into a specific area. Many factors will affect the capability of the focusing transducer, and in addition to considering the signal intensity, the detection accuracy is also required to be investigated. Specifically

Due to the noncontact, nonradiative, and low-cost features, magnetic induction tomography (MIT) is highly applicable in conductive medium imaging. To meet the demands of low-conductivity medium imaging in industrial and biomedical applications, a portable, flexible, and extensible MIT system with high-phase detection precision is proposed. The proposed system is designed with different modules. Therefore

Seven decades have passed since the Schumann resonances (SRs) were identified. Since then, their research interest has increased, currently being a topic of significance. Nonetheless, the papers that study their nature from the frequency perspective are in clear majority regarding those who focus on the time domain. To fill this gap in the literature and further characterize the SRs, a method to perform

Optical coherence tomography (OCT) is widely used for diagnosing and monitoring retinal disorders. However, despite hardware improvements, its scans are still highly affected by speckle noise. Speckle noise reduces quality of measurements and decreases reliability of further instrumentation. Recent OCT denoising methods are often complex and computationally inefficient, despite their valid performance

Industrial ultrasonic tomography (UT) possesses unique advantages in visualizing multiphase medium and has received broad attention in the past decades. Facing small bubble distribution imaging, the current independent-transducer-based UT faces bottleneck problems of limited projection number and large projection diameter. To image the cross-sectional bubble distribution, an original concept of ultrasonic

Contrast enhancement plays a vital role in image processing and computer vision applications. However, the existing work inevitably introduces some unwanted artifacts and often fails in revealing image details when enhancing the invisible images. This article presents a novel Bezier curve modification scheme to improve the visual quality of contrast degraded imperceptible images. First, a salp swarm

Fiber Bragg grating (FBG) acceleration sensor is an important branch of FBG application and has irreplaceable advantages compared with an electronic accelerometer. An FBG acceleration sensor with high sensitivity and high natural frequency is designed. This sensor adopts a double cantilever structure to sense the vibration perpendicular to the axis. Compared with a single cantilever structure, the

Indoor positioning approaches are often based on electromagnetic wave signals with high frequency. However, signal reflections and the corresponding signal superpositions are challenging. As a result, there is still no indoor positioning technology established in commercial products, such as smartphones or smartwatches. Recent publications have shown that this indoor positioning problem can be addressed

Nano- $g$ accelerometers are widely used in space exploration and measurement of the earth’s gravitational field. It is essential to precisely evaluate error effects at high orders such as cross-coupling for applications in a dynamic environment. Nevertheless, it remains challenging to meet the precision requirements using conventional calibration measures. In this article, we propose a method to separate

An important task in biomechanics is human body articulations’ internal torques measurement. This is known as a kinetic or inverse-dynamics problem. Its solution requires a combination of kinematic and dynamic measurements with a biomechanical model, involving subject-related anthropometric parameters. The uncertainty-evaluation thereof is here considered. The method poses on a probabilistic model

This article presents a low-cost circuit that generates narrow pulses with programmable waveform, amplitude, and position based on the spectrum stitching method. Specifically in this article, narrow pulses are generated through stitching the spectra of five subsignals, and the subsignals are generated by three regular arbitrary waveform generators with a bandwidth of 200 MHz. The experimental results

Wearable devices are increasingly popular for health monitoring via electrocardiograms (ECGs) as they can portably monitor heart conditions over a long time. However, so far there are no publicly available ECG data sets collected from wearable devices. Most ECG analysis algorithms target ECG data collected by hospital equipment. In the present study, we used the IREALCARE2.0 Flexible Cardiac Monitor

Deep learning (DL) has shown effectiveness in the field of Prognostic and Health Management (PHM) of rolling bearings and successfully solved many problems with its powerful feature learning and function fitting capabilities. However, it is still very challenging to transfer a remaining useful life (RUL) prediction model trained by historical data to bearings running under new operating conditions

Start point guiding and seam tracking are important parts of the robot’s intelligent welding process. However, some start point guiding methods have a large amount of calculation and low accuracy. In addition, due to the large curvature of the curved weld, the problem of visual advance in seam tracking should be solved. Therefore, an efficient and accurate start point guiding and seam tracking method

To improve extraction accuracy of bearing fault feature, a novel index named weighted characteristic energy ratio (WCER) is proposed in this article. In WCER, the fault feature in squared envelope spectrum is enhanced through a square operation, and a series of decreasing weights are imposed on the increasing fault harmonics to highlight the low-order fault feature and suppress the noise around the

Bearing faults are among the most common causes of machine failures. Therefore, bearing fault diagnosis should be performed reliably and rapidly. Currently, many types of modal data for monitoring the running state of bearings are available. They include data from different kinds of sensors and various domains (such as time and frequency domains). However, obtaining fault features with high quality

This article proposes a double-channel sequential probability ratio test (DCSPRT) failure detection algorithm for improving the fault-tolerant ability of the multisensor system. It develops a horizon-based sequential probability ratio test (HSPRT) using the horizon technique for the detection of slowing-growing failures and a current sample-based probability ratio test (CSPRT) for the detection of

Morphology reconstruction of neurons from 3-D microscopic images is essential to neuroscience research. However, many reconstructions may contain errors and ambiguities because of the crossover neuronal fibers. In this article, an automatic algorithm is proposed for the detection and separation of crossover structures and is applied to neuron tracing for improving the neuron reconstruction results

Traditional and deep learning-based fusion methods generated the intermediate decision map to obtain the fusion image through a series of postprocessing procedures. However, the fusion results generated by these methods are easy to lose some source image details or results in artifacts. Inspired by the image reconstruction techniques based on deep learning, we propose a multifocus image fusion network

Ultra-wideband (UWB) is a popular technology for indoor positioning systems (IPSs) due to its robust signaling in harsh environments, through-wall propagation, and high-resolution ranging. However, the propagation of wireless signals in indoor environments is affected by nonline-of-sight (NLOS) conditions, which can lead to positively biased distance estimates. Several research works were carried out

This article discusses an optical reflection-based method for equipment anomaly detection that enhances weak signals and has high sensitivity to abnormalities. Automatic warp knitting machine yarn breakage detection, which has become an acknowledged difficulty in the textile field, is achieved. To the best of our knowledge, this is the first time that visual inspection has been applied to yarn breakage

Whether in military or civilian use, frequency-modulated continuous-wave (FMCW) radars play a very important role, but common FMCW radars need to collect both radar echo signals and hardware synchronization signals during echo signal processing. Therefore, this article proposes a new synchronization algorithm, i.e., the four-threshold frequency band variance (FFBV) synchronization algorithm. Then,

Objective-coupled surface plasmon microscopy (SPM) features on both extremely high sensitivity and high resolution. However, this promising system is still operated in laboratories without commercial instrument. One big challenge is how to extract and classify the plasmonic signals from batches of experimentally acquired back focal plane (BFP) images accurately and automatically. To solve this problem

Mobile manipulation is essential for robots to accomplish everyday household chores such as set the table. In order to successfully perform manipulation tasks, a 3-D representation of the environment and the pose of the target object are needed. In this article, we propose a systematic solution for safe and efficient robot manipulation. Innovatively, a task-oriented environment modeling strategy is