688 citations · 1.4k across the 5 of their papers we have counts for
5 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…
Smart filter aided domain adversarial neural network for fault diagnosis in noisy industrial scenarios
Baorui Dai, Gaëtan Frusque, Tianfu Li +2
The application of unsupervised domain adaptation (UDA)-based fault diagnosis methods has shown significant efficacy in industrial settings, facilitating the transfer of operationa…
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…
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…
WaveletKernelNet: An Interpretable Deep Neural Network for Industrial Intelligent Diagnosis
Tianfu Li, Zhibin Zhao, Chuang Sun +4
Convolutional neural network (CNN), with ability of feature learning and nonlinear mapping, has demonstrated its effectiveness in prognostics and health management (PHM). However,…