[HTML][HTML] A systematic review of data fusion techniques for optimized structural health monitoring
Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
Condition-based monitoring and maintenance: state of the art review
A Ali, A Abdelhadi - Applied Sciences, 2022 - mdpi.com
Manufacturing firms face great pressure to reduce downtime as well as maintenance costs.
Condition-based maintenance (CBM) can be used to effectively manage operations and …
Condition-based maintenance (CBM) can be used to effectively manage operations and …
A CNN-based transfer learning method for leakage detection of pipeline under multiple working conditions with AE signals
P Liu, C Xu, J Xie, M Fu, Y Chen, Z Liu… - Process Safety and …, 2023 - Elsevier
Pipeline leakage detection is a crucial part of pipeline integrity management. Acoustic
emission (AE) based leakage detection is widely used in this field. The latest detection …
emission (AE) based leakage detection is widely used in this field. The latest detection …
Vibration and infrared thermography based multiple fault diagnosis of bearing using deep learning
The occurrence of multiple faults is a practical problem in the bearings of rotating machines,
and early diagnosis of such issues in an intelligent manner is vital in the era of industry 4.0 …
and early diagnosis of such issues in an intelligent manner is vital in the era of industry 4.0 …
Transfer learning with time series data: a systematic mapping study
Transfer Learning is a well-studied concept in machine learning, that relaxes the assumption
that training and testing data need to be drawn from the same distribution. Recent success in …
that training and testing data need to be drawn from the same distribution. Recent success in …
Multi-sensor fault diagnosis for misalignment and unbalance detection using machine learning
Rotating machines frequently undergo various faults causing increased maintenance and
operation costs. To minimize these costs, effective and intelligent methods are thus required …
operation costs. To minimize these costs, effective and intelligent methods are thus required …
Deep learning based identification and uncertainty analysis of metro train induced ground-borne vibration
W Liu, R Liang, H Zhang, Z Wu, B Jiang - Mechanical Systems and Signal …, 2023 - Elsevier
The problems of ground-borne vibration induced by running metro trains are becoming a
major concern. Considering the uncertainty in train–track–tunnel–soil–building system, the …
major concern. Considering the uncertainty in train–track–tunnel–soil–building system, the …
Hybrid deep transfer learning architecture for industrial fault diagnosis using Hilbert transform and DCNN–LSTM
Early-stage fault detection has become an indispensable part of modern industry to prevent
potential hazards or sudden hindrances to the production process. With the advent of deep …
potential hazards or sudden hindrances to the production process. With the advent of deep …
Fault diagnosis in a hydraulic directional valve using a two-stage multi-sensor information fusion
J Shi, J Yi, Y Ren, Y Li, Q Zhong, H Tang, L Chen - Measurement, 2021 - Elsevier
As it is usually operating in bad working conditions and subjected to the severe interference
from diverse paths, internal faults of the hydraulic valve are difficult to be detected using …
from diverse paths, internal faults of the hydraulic valve are difficult to be detected using …
A sensor fusion based approach for bearing fault diagnosis of rotating machine
Fault diagnosis in rotating machines plays a vital role in various industries. Bearing is the
essential element of rotating machines, and early fault detection can reduce the …
essential element of rotating machines, and early fault detection can reduce the …