[HTML][HTML] Reliability modelling and assessment of CMOS image sensor under radiation environment

TAO Zhao, C Wenbin, LI Xiaoyang, K Rui - Chinese Journal of Aeronautics, 2024 - Elsevier
Abstract The Complementary Metal-Oxide Semiconductor (CMOS) image sensor is a critical
component with the function of providing accurate positioning in many space application …

A model-driven dual-derivation framework for quantitative fault detection in satellite power system

P Wang, L Liu, Y Song, Z Li, D Liu - Advanced Engineering Informatics, 2024 - Elsevier
Satellite power system (SPS) fault detection is of great significance to ensure the safety and
stability of satellites. On-orbit SPS can divide 11 near-mutation operating conditions (OCs) in …

A multi-adversarial joint distribution adaptation method for bearing fault diagnosis under variable working conditions

Z Cui, H Cao, Z Ai, J Wang - Applied Sciences, 2023 - mdpi.com
Deep network fault diagnosis requires a lot of labeled data and assumes identical data
distributions for training and testing. In industry, varying equipment conditions lead to …

TFPred: Learning discriminative representations from unlabeled data for few-label rotating machinery fault diagnosis

X Chen, R Yang, Y Xue, B Song, Z Wang - Control Engineering Practice, 2024 - Elsevier
Recent advances in intelligent rotating machinery fault diagnosis have been enabled by the
availability of massive labeled training data. However, in practical industrial applications, it is …

[HTML][HTML] CatBoost-SHAP for modeling industrial operational flotation variables–A “conscious lab” approach

SC Chelgani, A Homafar, H Nasiri - Minerals Engineering, 2024 - Elsevier
Flotation separation is the most important upgrading critical raw material technique.
Measuring interactions within flotation variables and modeling their metallurgical responses …

Fault detection for process industries via temporal CapsNet encoder-assisted one-class classifier

S Wang, Q Zhao, Y Han, J Wang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Fault detection plays a pivotal role in ensuring safety and efficiency in process industries.
Subspace learning-based fault detection methods have gained recognition for their effective …

IFRN: Insensitive feature removal network for zero-shot mechanical fault diagnosis across fault severity

Z Liu, R Yang, W Liu, X Liu - Neurocomputing, 2023 - Elsevier
Zero-shot learning is a promising technique for diagnosing mechanical faults in complex
and uncertain environments. However, when diagnosing mechanical faults across different …

A novel label-aware global graph construction method and spiking-coded graph neural network for intelligent process fault diagnosis

D Li, Y Zhu, Z Song, HR Karimi - Neurocomputing, 2025 - Elsevier
Fault diagnosis plays a crucial role in ensuring the safety and efficiency of industrial
processes. However, traditional techniques often face difficulties in handling large-scale …

A versatile feature selection learning method for satellite attitude control system fault diagnosis with limited data

H Xia, T Meng - Neurocomputing, 2025 - Elsevier
Fault diagnosis in satellite attitude control systems is crucial for ensuring the operation and
maintenance of satellites. However, current methods face challenges in achieving the …

Unsupervised model-guided online transfer learning framework for multiple fault detection of satellite control system

H Xia, T Meng - Neurocomputing, 2025 - Elsevier
Satellite in-orbit fault detection is critical for satellite reliability and safety. Although fault
detection has been extensively studied from signal processing to data-driven methods, there …