A review of the optimal design of neural networks based on FPGA
C Wang, Z Luo - Applied Sciences, 2022 - mdpi.com
Deep learning based on neural networks has been widely used in image recognition,
speech recognition, natural language processing, automatic driving, and other fields and …
speech recognition, natural language processing, automatic driving, and other fields and …
Vibration-based anomaly detection using LSTM/SVM approaches
Fault detection is a critical step for machine condition monitoring and maintenance. With
advances in machine learning technologies, automated faulty condition identification can be …
advances in machine learning technologies, automated faulty condition identification can be …
[HTML][HTML] Machine learning algorithms for delaminations detection on composites panels by wave propagation signals analysis: Review, experiences and results
E Monaco, M Rautela, S Gopalakrishnan… - Progress in Aerospace …, 2024 - Elsevier
Performances are a key concern in aerospace vehicles, requiring safer structures with as
little consumption as possible. Composite materials replaced aluminum alloys even in …
little consumption as possible. Composite materials replaced aluminum alloys even in …
Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations
M Rautela, J Senthilnath, E Monaco… - Composite …, 2022 - Elsevier
With the introduction of damage tolerance-based design philosophies, the demand for
reliable and robust structural health monitoring (SHM) procedures for aerospace composite …
reliable and robust structural health monitoring (SHM) procedures for aerospace composite …
[HTML][HTML] Domain knowledge-informed synthetic fault sample generation with health data map for cross-domain planetary gearbox fault diagnosis
Extensive research has been conducted on fault diagnosis of planetary gearboxes using
vibration signals and deep learning (DL) approaches. However, DL-based methods are …
vibration signals and deep learning (DL) approaches. However, DL-based methods are …
Enhancing Lamb wave-based damage diagnosis in composite materials using a pseudo-damage boosted convolutional neural network approach
A Gonzalez-Jimenez, L Lomazzi… - Structural Health …, 2024 - journals.sagepub.com
Damage diagnosis of thin-walled structures has been successfully performed through
methods based on tomography and machine learning-driven methods. According to …
methods based on tomography and machine learning-driven methods. According to …
Anomaly detection in additive manufacturing processes using supervised classification with imbalanced sensor data based on generative adversarial network
Supervised classification methods have been widely utilized for the quality assurance of the
advanced manufacturing process, such as additive manufacturing (AM) for anomaly …
advanced manufacturing process, such as additive manufacturing (AM) for anomaly …
Deep generative model with time series-image encoding for manufacturing fault detection in die casting process
The increasing demand for advanced fault detection in manufacturing processes has
encouraged the application of industrial intelligence based on deep learning. However …
encouraged the application of industrial intelligence based on deep learning. However …
Anomaly detection for construction vibration signals using unsupervised deep learning and cloud computing
In-operation construction vibration monitoring records inevitably contain various anomalies
caused by sensor faults, system errors, or environmental influence. An accurate and efficient …
caused by sensor faults, system errors, or environmental influence. An accurate and efficient …
Dyedgegat: Dynamic edge via graph attention for early fault detection in iiot systems
In the Industrial Internet of Things (IIoT), condition monitoring sensor signals from complex
systems often exhibit nonlinear and stochastic spatial-temporal dynamics under varying …
systems often exhibit nonlinear and stochastic spatial-temporal dynamics under varying …