Machine learning-based methods in structural reliability analysis: A review
Structural Reliability analysis (SRA) is one of the prominent fields in civil and mechanical
engineering. However, an accurate SRA in most cases deals with complex and costly …
engineering. However, an accurate SRA in most cases deals with complex and costly …
A survey of convolutional neural networks: analysis, applications, and prospects
A convolutional neural network (CNN) is one of the most significant networks in the deep
learning field. Since CNN made impressive achievements in many areas, including but not …
learning field. Since CNN made impressive achievements in many areas, including but not …
A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
Monitoring structural damage is extremely important for sustaining and preserving the
service life of civil structures. While successful monitoring provides resolute and staunch …
service life of civil structures. While successful monitoring provides resolute and staunch …
[HTML][HTML] 1D convolutional neural networks and applications: A survey
During the last decade, Convolutional Neural Networks (CNNs) have become the de facto
standard for various Computer Vision and Machine Learning operations. CNNs are feed …
standard for various Computer Vision and Machine Learning operations. CNNs are feed …
A comprehensive review on convolutional neural network in machine fault diagnosis
With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …
increasingly significant to ensure safe equipment operation and production. Consequently …
Fault detection and diagnosis in electric motors using 1d convolutional neural networks with multi-channel vibration signals
RFR Junior, IA dos Santos Areias, MM Campos… - Measurement, 2022 - Elsevier
Fault detection and diagnosis in time series data are becoming mainstream in most
industrial applications since the increase of monitoring sensors in machinery. Traditional …
industrial applications since the increase of monitoring sensors in machinery. Traditional …
Deep learning-based construction equipment operators' mental fatigue classification using wearable EEG sensor data
Operator attention failure due to mental fatigue during extended equipment operations is a
common cause of equipment-related accidents that result in catastrophic injuries and …
common cause of equipment-related accidents that result in catastrophic injuries and …
A novel percussion-based method for multi-bolt looseness detection using one-dimensional memory augmented convolutional long short-term memory networks
In the past decade, bolt looseness detection has attracted much attention. Compared to
common approaches that require the implementation of constant-contact sensors, several …
common approaches that require the implementation of constant-contact sensors, several …
Real-time abnormality detection and classification in diesel engine operations with convolutional neural network
In this paper, we propose a real-time diagnostic method using a convolutional neural
network (CNN) to detect cylinder misfires and engine load conditions in multi-cylinder …
network (CNN) to detect cylinder misfires and engine load conditions in multi-cylinder …
Deep variational autoencoder classifier for intelligent fault diagnosis adaptive to unseen fault categories
With the rapid development of artificial intelligence (AI) in recent years, fault diagnostics for
industrial applications have leaped toward partially or fully automatic provided by the …
industrial applications have leaped toward partially or fully automatic provided by the …