Detecting the Early Damages in Structures With Nonlinear Output Frequency Response Functions and the CNN-LSTM Model. - Baoxuan Zhao; Changming Cheng; Zhike Peng; Xingjian Dong; Guang Meng (IEEE Trans. Instrum. Meas., 2020)

Hybrid Pre-Training Strategy for Deep Denoising Neural Networks and Its Application in Machine Fault Diagnosis. - Baoxuan Zhao; Changming Cheng; Zhike Peng; Qingbo He; Guang Meng (IEEE Trans. Instrum. Meas., 2021)

TFN: An Interpretable Neural Network with Time-Frequency Transform Embedded for Intelligent Fault Diagnosis. - Qian Chen; Xingjian Dong; Guowei Tu; Dong Wang 001; Baoxuan Zhao; Zhike Peng (CoRR, 2022)

Relation-Aware Attentive Neural Processes Model for Remaining Useful Life Prediction. - Junzhong Lu; Changming Cheng; Baoxuan Zhao; Zhike Peng (IEEE Trans. Instrum. Meas., 2022)

An Instance and Feature-Based Hybrid Transfer Model for Fault Diagnosis of Rotating Machinery With Different Speeds. - Baoxuan Zhao; Changming Cheng; Guanzhen Zhang; Miaomiao Lin; Zhike Peng; Guang Meng (IEEE Trans. Instrum. Meas., 2022)

Hybrid Semi-Supervised Learning for Rotating Machinery Fault Diagnosis Based on Grouped Pseudo Labeling and Consistency Regularization. - Baoxuan Zhao; Changming Cheng; Shangyu Zhao; Zhike Peng (IEEE Trans. Instrum. Meas., 2023)