Sensors, Vol. 24, Pages 2445: Bearing Fault Diagnosis via Stepwise Sparse Regularization with an Adaptive Sparse Dictionary
eng Luo Vibration monitoring is one of the most effective approaches for bearing fault diagnosis. Within this category of techniques, sparsity constraint-based regularization has received considerable attention for its capability to accurately extract repetitive transients from noisy vibration signals. The optimal solution of a sparse regularization problem is determined by the regularization term and the data fitting term in the cost function according to their weights, so a tradeoff between sparsity and data fidelity has to be made inevitably, which restricts conventional regularization methods from maintaining stron...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Lichao Yu Chenglong Wang Fanghong Zhang Huageng Luo Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2444: Real-Time Ferrogram Segmentation of Wear Debris Using Multi-Level Feature Reused Unet
heying Zong The real-time monitoring and fault diagnosis of modern machinery and equipment impose higher demands on equipment maintenance, with the extraction of morphological characteristics of wear debris in lubricating oil emerging as a critical approach for real-time monitoring of wear, holding significant importance in the field. The online visual ferrograph (OLVF) technique serves as a representative method in this study. Various semantic segmentation approaches, such as DeepLabV3+, PSPNet, Segformer, Unet, and other models, are employed to process the oil wear particle image for conducting comparative experiment...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Jie You Shibo Fan Qinghai Yu Lianfu Wang Zhou Zhang Zheying Zong Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2442: Centrifugal Pump Fault Detection with Convolutional Neural Network Transfer Learning
ke Newton The centrifugal pump is the workhorse of many industrial and domestic applications, such as water supply, wastewater treatment and heating. While modern pumps are reliable, their unexpected failures may jeopardise safety or lead to significant financial losses. Consequently, there is a strong demand for early fault diagnosis, detection and predictive monitoring systems. Most prior work on machine learning-based centrifugal pump fault detection is based on either synthetic data, simulations or data from test rigs in controlled laboratory conditions. In this research, we attempted to detect centrifugal pump fau...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Cem Ekin Sunal Vladan Velisavljevic Vladimir Dyo Barry Newton Jake Newton Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2446: A New Denoising Method for Belt Conveyor Roller Fault Signals
Wenliang Pei In the process of the intelligent inspection of belt conveyor systems, due to problems such as its long duration, the large number of rollers, and the complex working environment, fault diagnosis by acoustic signals is easily affected by signal coupling interference, which poses a great challenge to selecting denoising methods of signal preprocessing. This paper proposes a novel wavelet threshold denoising algorithm by integrating a new biparameter and trisegment threshold function. Firstly, we elaborate on the mutual influence and optimization process of two adjustment parameters and three wavelet coeffi...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Xuedi Hao Jiajin Zhang Yingzong Gao Chenze Zhu Shuo Tang Pengfei Guo Wenliang Pei Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2447: Thermal Imaging of the Tongue Surface as a Predictive Method in the Diagnosis of Type 2 Diabetes Mellitus
Conclusions: Tongue temperature measured using the IRT showed a correlation with standard biochemical parameters; it may also differentiate patients and constitute a specific screening method for patients with t2DM. (Source: Sensors)
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Daria Wzi ątek-Kuczmik Antoni Świątkowski Armand Cholewka Aleksandra Mrowiec Iwona Niedzielska Agata Stanek Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2448: Respiration and Heart Rate Monitoring in Smart Homes: An Angular-Free Approach with an FMCW Radar
chreurs This paper proposes a new approach for wide angle monitoring of vital signs in smart home applications. The person is tracked using an indoor radar. Upon detecting the person to be static, the radar automatically focuses its beam on that location, and subsequently breathing and heart rates are extracted from the reflected signals using continuous wavelet transform (CWT) analysis. In this way, leveraging the radar’s on-chip processor enables real-time monitoring of vital signs across varying angles. In our experiment, we employ a commercial multi-input multi-output (MIMO) millimeter-wave FMCW radar...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Pouya Mehrjouseresht Reda El Hail Peter Karsmakers Dominique M. M.-P. Schreurs Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2449: Digital Self-Interference Canceler with Joint Channel Estimator for Simultaneous Transmit and Receive System
g Songhu Ge Simultaneous transmit and receive wireless communications have been highlighted for their potential to double the spectral efficiency. However, it is necessary to mitigate self-interference (SI). Considering both the SI channel and remote transmission (RT) channel need to be estimated before equalizing the received signal, we propose two adaptive algorithms for linear and nonlinear self-interference cancellation (SIC), based on a multi-layered joint channel estimator structure. The proposed algorithms estimate the RT channel while performing SIC, and the multi-layered structure ensures improved performanc...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Shiyu Song Yanqun Tang Xianjie Lu Yu Zhou Xizhang Wei Zhengpeng Wang Songhu Ge Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2450: Application of Stereo Digital Image Correlation on Facial Expressions Sensing
Zhiyong Wang Facial expression is an important way to reflect human emotions and it represents a dynamic deformation process. Analyzing facial movements is an effective means of understanding expressions. However, there is currently a lack of methods capable of analyzing the dynamic details of full-field deformation in expressions. In this paper, in order to enable effective dynamic analysis of expressions, a classic optical measuring method called stereo digital image correlation (stereo-DIC or 3D-DIC) is employed to analyze the deformation fields of facial expressions. The forming processes of six basic facial exp...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Xuanshi Cheng Shibin Wang Huixin Wei Xin Sun Lipan Xin Linan Li Chuanwei Li Zhiyong Wang Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2451: Dynamic Stability, Symmetry, and Smoothness of Gait in People with Neurological Health Conditions
This study aimed to assess the ability to walk of patients with sTBI, stroke, and PD, identifying the differences in dynamic postural stability, symmetry, and smoothness during various dynamic motor tasks. Sixty people with neurological disorders and 20 healthy participants were recruited. Inertial measurement unit (IMU) sensors were employed to measure spatiotemporal parameters and gait quality indices during different motor tasks. The Mini-BESTest, Berg Balance Scale, and Dynamic Gait Index Scoring were also used to evaluate balance and gait. People with stroke exhibited the most compromised biomechanical patterns, with ...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Marco Tramontano Amaranta Soledad Orejel Bustos Rebecca Montemurro Simona Vasta Gabriele Marangon Valeria Belluscio Giovanni Morone Nicola Modugno Maria Gabriella Buzzi Rita Formisano Elena Bergamini Giuseppe Vannozzi Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2452: Influence on Sample Determination for Deep Learning Electromagnetic Tomography
Liu Deep learning (DL) has been frequently applied in the image reconstruction of electromagnetic tomography (EMT) in recent years. It offers the potential to achieve higher-quality image reconstruction. Among these, research on samples is relatively scarce. Samples are the cornerstone for both large and small models, which is easy to ignore. In this paper, a deep learning electromagnetic tomography (DL-EMT) model with nine elements is established. Complete simulation and experimental samples are obtained based on this model. On the sample sets, the reconstruction quality is observed by adjusting the size and configura...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Pengfei Zhao Ze Liu Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2453: TimeTector: A Twin-Branch Approach for Unsupervised Anomaly Detection in Livestock Sensor Noisy Data (TT-TBAD)
suk Kim Unsupervised anomaly detection in multivariate time series sensor data is a complex task with diverse applications in different domains such as livestock farming and agriculture (LF&A), the Internet of Things (IoT), and human activity recognition (HAR). Advanced machine learning techniques are necessary to detect multi-sensor time series data anomalies. The primary focus of this research is to develop state-of-the-art machine learning methods for detecting anomalies in multi-sensor data. Time series sensors frequently produce multi-sensor data with anomalies, which makes it difficult to establish st...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Junaid Khan Kakar Shahid Hussain Sang Cheol Kim Hyongsuk Kim Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2454: Comparative Analysis of Meteorological Versus In Situ Variables in Ship Thermal Simulations
This study aims to explore the impact of meteorological variables on thermal simulations, particularly focusing on ships. Using TRNSYS (TRaNsient System Simulation) software (v17), renowned for its capability to model complex energy systems within buildings, the significance of incorporating meteorological data into thermal simulations was analyzed. The investigation centered on a patrol vessel stationed in a port in Galicia, northwest Spain. To ensure accuracy, we not only utilized the vessel’s dimensions but also conducted in situ temperature measurements onboard. Furthermore, a dedicated weather station wa...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Arce Su árez-García L ópez-Vázquez Devesa-Rey Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2455: The Advantage of the 5G Network for Enhancing the Internet of Things and the Evolution of the 6G Network
Dossis The Internet of Things (IoT) is what we have as a great breakthrough in the 5G network. Although the 5G network can support several Internet of Everything (IoE) services, 6G is the network to fully support that. This paper is a survey research presenting the 5G and IoT technology and the challenges coming, with the 6G network being the new alternative network coming to solve these issues and limitations we are facing with 5G. A reference to the Control Plane and User Plane Separation (CUPS) is made with IPv4 and IPv6, addressing which is the foundation of the network slicing for the 5G core network. In compari...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Gkagkas Vergados Michalas Dossis Tags: Review Source Type: research

Sensors, Vol. 24, Pages 2456: Prediction of Degraded Infrastructure Conditions for Railway Operation
nández In the railway sector, rolling stock and infrastructure must be maintained in perfect condition to ensure reliable and safe operation for passengers. Climate change is affecting the urban and regional infrastructure through sea level rise, water accumulations, river flooding, and other increased-frequency extreme natural situations (heavy rains or snows) which pose a challenge to maintenance. In this paper, the use of artificial intelligence based on predictive maintenance implementation is proposed for the early detection of degraded conditions of a bridge due to extreme climatic conditions. For this predictio...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Juan de Dios Sanz Bobi Pablo Garrido Mart ínez-Llop Pablo Rubio Marcos Álvaro Solano Jiménez Javier G ómez Fernández Tags: Article Source Type: research

Sensors, Vol. 24, Pages 2458: VisionaryVR: An Optical Simulation Tool for Evaluating and Optimizing Vision Correction Solutions in Virtual Reality
fried Wahl In the rapidly advancing field of vision science, traditional research approaches struggle to accurately simulate and evaluate vision correction methods, leading to time-consuming evaluations with limited scope and flexibility. To overcome these challenges, we introduce ‘VisionaryVR’, a virtual reality (VR) simulation framework designed to enhance optical simulation fidelity and broaden experimental capabilities. VisionaryVR leverages a versatile VR environment to support dynamic vision tasks and integrates comprehensive eye-tracking functionality. Its experiment manager&r...
Source: Sensors - April 11, 2024 Category: Biotechnology Authors: Benedikt W. Hosp Martin Dechant Yannick Sauer Bj örn Severitt Rajat Agarwala Siegfried Wahl Tags: Article Source Type: research