688 citations · 1.5k across the 7 of their papers we have counts for
7 papers
A Novel Unsupervised Graph Wavelet Autoencoder for Mechanical System Fault Detection
Tianfu Li, Chuang Sun, Ruqiang Yan +1
Reliable fault detection is an essential requirement for safe and efficient operation of complex mechanical systems in various industrial applications. Despite the abundance of exi…
Filter-informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis
Tianfu Li, Chuang Sun, Olga Fink +3
Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been i…
Superpixel perception graph neural network for intelligent defect detection of aero-engine blade
Hongbing Shang, Qixiu Yang, Chuang Sun +2
Aero-engine is the core component of aircraft and other spacecraft. The high-speed rotating blades provide power by sucking in air and fully combusting, and various defects will in…
Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction
Mohamed Ragab, Zhenghua Chen, Min Wu +3
Accurate estimation of remaining useful life (RUL) of industrial equipment can enable advanced maintenance schedules, increase equipment availability and reduce operational costs.…
Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study
Zhibin Zhao, Tianfu Li, Jingyao Wu +4
With the development of deep learning (DL) techniques, rotating machinery intelligent diagnosis has gone through tremendous progress with verified success and the classification ac…
Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study
Zhibin Zhao, Qiyang Zhang, Xiaolei Yu +4
Recent progress on intelligent fault diagnosis (IFD) has greatly depended on deep representation learning and plenty of labeled data. However, machines often operate with various w…
Deep Learning and Its Applications to Machine Health Monitoring: A Survey
Rui Zhao, Ruqiang Yan, Zhenghua Chen +3
Since 2006, deep learning (DL) has become a rapidly growing research direction, redefining state-of-the-art performances in a wide range of areas such as object recognition, image…