Results 141 to 150 of about 17,291 (260)

Multi-Filter Clustering Fusion for Feature Selection in Rotating Machinery Fault Classification. [PDF]

Sensors (Basel), 2022
Mochammad S, Noh Y, Kang YJ, Park S, Lee J, Chin S.   +5 more
europepmc   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

Advanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue, Yuan Gao, Fanping Sui, Jason Wang, Megan Teng, Peggy Tsao, Huicong Deng, Yande Peng, Liwei Lin   +8 more
wiley   +1 more source

A fault diagnosis method for rotating machinery components based on enhanced YOLO v8 and integrated attention mechanism. [PDF]

PLoS One
Wang X, Yuan L, Ma L, Liu J.
europepmc   +1 more source

An Improved MobileNet Network with Wavelet Energy and Global Average Pooling for Rotating Machinery Fault Diagnosis. [PDF]

Sensors (Basel), 2022
Zhu F, Liu C, Yang J, Wang S.
europepmc   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

Fault Diagnosis of Rotating Machinery Using Supervised Machine Learning Algorithms with Integrated Data-Driven and Physics-Informed Feature Sets. [PDF]

Sensors (Basel)
Ignjatovska AA, Petreski Z, Gavriloski V, Shishkovski D, Domazetovska Markovska S, Anachkova M, Pecioski D.   +6 more
europepmc   +1 more source

Rotating machinery fault diagnosis based on a novel lightweight convolutional neural network. [PDF]

PLoS One, 2021
Yan J, Liu T, Ye X, Jing Q, Dai Y.
europepmc   +1 more source

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

Advanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu, Mengyao Xiao, Zhouli Sui, Yinpeng Wang, Daoye Zheng, Yuxin Liu, Luwei Wang, Huajun Liu, Chengkuo Lee   +8 more
wiley   +1 more source

Cointegration Approach for Vibration-Based Misalignment Detection in Rotating Machinery Under Varying Load Conditions. [PDF]

Sensors (Basel)
Szewczyk S, Barczewski R, Staszewski WJ, Janiga D, Dao PB.   +4 more
europepmc   +1 more source

Multi-Stream Convolutional Neural Networks for Rotating Machinery Fault Diagnosis under Noise and Trend Items. [PDF]

Sensors (Basel), 2022
Dong H, Lu J, Han Y.
europepmc   +1 more source