Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks by Hussein A. M. Hussein, Sharafiz B. Abdul Rahim, Faizal B. Mustapha, Prajindra S. Krishnan, Nawal Aswan B. Abdul Jalil

“…The FRF signals were captured using accelerometers to monitor the structural health of the pipeline. …”
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Automatic System for Detection and Positioning of Impacts in Metals Based on Arduino by Carlos Morón, Daniel Ferrández, Pablo Saiz, Alberto Morón

“…For that, it was necessary to place the accelerometers at the ends of the structure that enables an automatic and efficient way to determine the moment and the position of the impact. …”
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Smart health-care systems for rheumatology by Suneeta Mohanty, Prasant Kumar Pattnaik

“…Sensor plays a vital role in smart health care for the collection of real-time data. Sensors such as accelerometers, wearable sensors, and thermal infrared camera sensors are extensively used to assemble data for patients with arthritis. …”
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An Integrated Test-Based Nonlinear Aeroelastic Analysis Method to Freeplay-Induced Limit-Cycle Oscillations by Yukai Sun, Zhigang Wu, Chao Yang, Xiangyu Wang, Chuansheng Wang

“…The wind tunnel tests are conducted with the model, and the stable limit-cycle oscillation is observed by accelerometers under the linear flutter boundary with a 0° angle of attack. …”
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Alignment of Fabry–Pérot Cavities for Optomechanical Acceleration Measurements by Marina Rezinkina, Claus Braxmaier

“…Such cavities are used, among other applications, in optomechanical accelerometers for precise measurement of displacement of moving elements. …”
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Determining the Coupling Source on a Set of Oscillators from Experimental Data by Juan Carlos Jauregui-Correa, Carlos S. López-Cajun, Mihir Sen

“…The vibratory motion of the blades was recorded with accelerometers, and the resulting information was analyzed with four techniques: correlation coefficients, Kuramoto parameter, cross-correlation functions, and the recurrence plot. …”
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Quantitative Analysis of Motor Status in Parkinson’s Disease Using Wearable Devices: From Methodological Considerations to Problems in Clinical Applications by Masahiko Suzuki, Hiroshi Mitoma, Mitsuru Yoneyama

“…Recent advances in biotechnology have seen the development of various types of wearable (body-worn) sensor systems. By using accelerometers and gyroscopes, these devices can quantify motor abnormalities, including decreased activity and gait disturbances, as well as nonmotor signs, such as sleep disturbances and autonomic dysfunctions in PD. …”
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Screw Remaining Life Prediction Based on Quantum Genetic Algorithm and Support Vector Machine by Xiaochen Zhang, Dongxiang Jiang

“…A screw accelerated test bench is introduced. Accelerometers are installed to monitor the performance degradation of ball screw. …”
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Output-Only Damage Detection of Steel Beam Using Moving Average Filter by Hadi Kordestani, Yi-Qiang Xiang, Xiao-Wei Ye

“…In this paper, a method is proposed to employ MAF to smooth acceleration signals obtained from a series of accelerometers and determine the damage location along a steel beam. …”
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A Vibration Signal-Based Active Noise Control Method for Liquid-Filled Pipelines by Yunhao Wang, Qichao Liu, Wenjing Yu, Guo Cheng

“…In this paper, we propose an active noise control method utilizing signals acquired by accelerometers, which adopts offline modeling of the secondary path and the notch narrowband FxLMS algorithm for controlling the secondary source actuation. …”
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Tire Pressure Monitoring System Using Feature Fusion and Family of Lazy Classifiers by Arpit Pandey, Sridharan Naveen Venkatesh, Prabhakaranpillai Sreelatha Anoop, B. R. Manju, Vaithiyanathan Sugumaran

“…It employs various feature extraction methods and lazy‐based classifiers to analyze vibration signals collected under idle, high‐speed, normal, and puncture conditions using MEMS accelerometers. The study examines autoregressive moving average (ARMA), histogram, and statistical features individually and in combinations (statistical‐histogram, histogram‐ARMA, statistical‐ARMA, and statistical‐histogram‐ARMA) to improve predictive accuracy. …”
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Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation by Huili Xue, Kun Lin, Yin Luo, Hongjun Liu

“…The influences of the number and location of accelerometers are examined and discussed. In order to study the stability of the proposed method, the effects of the errors in crucial factors such as natural frequency and damping ratio are discussed through detailed parametric analysis. …”
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A systematic review of passive data for remote monitoring in psychosis and schizophrenia by Siân Bladon, Emily Eisner, Sandra Bucci, Anuoluwapo Oluwatayo, Glen P. Martin, Matthew Sperrin, John Ainsworth, Sophie Faulkner

“…In total, 203 articles collecting passive data through smartphones or wearable devices, from participants with psychosis or schizophrenia were included in the review. Accelerometers were the most common device (n = 115 studies), followed by smartphones (n = 46). …”
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Natural Frequencies and Modal Damping Ratios Identification of Civil Structures from Ambient Vibration Data by Minh-Nghi Ta, Joseph Lardiès, Berthillier Marc

“…Ambient vibration of each cable is carried out using accelerometers. From output data only, the modal parameter are extracted using a subspace method and the wavelet transform method.…”
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Calibration of the Performance of Bidirectional Shaker Table in Centrifuge Model Tests Using Sensor Networks by Hongjun Li, Hong Zhong, Xuedong Zhang, Yanyi Zhang, Yujing Hou

“…The seismic input at the dam site and transmission along the dam axis were obtained by the five pairs of accelerometers. The extensive usage of the sensor networks technology in physical model test in centrifuge has significantly promoted the calibration of performance of bidirectional shaker table and would thus enable further insight into the dynamic response of rock-fill dam.…”
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Multimodal Adaptive Identity-Recognition Algorithm Fused with Gait Perception by Changjie Wang, Zhihua Li, Benjamin Sarpong

“…First, in combination with the collected gait information of individuals from triaxial accelerometers on smartphones, the collected information is preprocessed, and multimodal fusion is used with the existing standard datasets to yield a multimodal synthetic dataset; then, with the multimodal characteristics of the collected biological gait information, a Convolutional Neural Network based Gait Recognition (CNN-GR) model and the related scheme for the multimodal features are developed; at last, regarding the proposed CNN-GR model and scheme, a unimodal gait feature identity single-gait feature identification algorithm and a multimodal gait feature fusion identity multimodal gait information algorithm are proposed. …”
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A Review of Fault Detecting Devices for Belt Conveyor Idlers by Fahad Alharbi, Suhuai Luo

“…By synthesizing various research findings, the study assesses the effectiveness of different sensor devices in identifying defects, including built-in sensors, fixed sensor options like acoustic, ultrasonic sensors, cameras, accelerometers, and Distributed Optical Fibre Sensors (DOFS), as well as mobile sensor systems. …”
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Synergy between Embedded and Non-Embedded Sensors in IoT Networks for Structural Health Monitoring of Concrete Structures: A Literature Review by Najem Oumayma, Benbrahim Mohammed, Kabbaj Mohammed Nabil, Boumhidi Jaouad

“…This paper also covers the numerous kinds of sensors that are utilized for SHM, namely embedded sensors including piezoelectric and fiber optic sensors, and non-embedded sensors such as accelerometers and strain gauges. Through case studies, the practical applications of SHM are illustrated, emphasizing its effectiveness in real-world scenarios. …”
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Raising active children: how family and school shape health-promoting physical activity—findings from the FAMIPASS study by Michal Vorlíček, Jan Dygrýn, David Janda, Jaroslava Voráčová, Scott Duncan, Erik Sigmund, Dagmar Sigmundová

“…The device-based monitoring of movement behaviors in children and their parents was conducted over a one-week period using ActiGraph accelerometers, complemented by detailed family questionnaires. …”
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A CBA-KELM-Based Recognition Method for Fault Diagnosis of Wind Turbines with Time-Domain Analysis and Multisensor Data Fusion by Xiafei Long, Ping Yang, Hongxia Guo, Zhuoli Zhao, Xiwen Wu

“…The dataset includes a large number of samples involving 6 fault types under different operational conditions by 5 accelerometers. The effectiveness and feasibility of this proposed method are proved by adopting the datasets originated from the test rig, and it achieves a diagnostic accuracy of 96.25%. …”
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