[PDF][PDF] A survey of predictive maintenance: Systems, purposes and approaches

Y Ran, X Zhou, P Lin, Y Wen… - arXiv preprint arXiv …, 2019 - researchgate.net
This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …

Technology development and commercial applications of industrial fault diagnosis system: a review

C Liu, A Cichon, G Królczyk, Z Li - The International Journal of Advanced …, 2021 - Springer
Machinery will fail due to complex and tough working conditions. It is necessary to apply
reliable monitoring technology to ensure their safe operation. Condition-based maintenance …

Residual-hypergraph convolution network: A model-based and data-driven integrated approach for fault diagnosis in complex equipment

L Xia, Y Liang, P Zheng, X Huang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Timely and accurate fault diagnosis plays a critical role in today's smart manufacturing
practices, saving invaluable time and expenditure on maintenance process. To date …

Hybrid multimodal fusion with deep learning for rolling bearing fault diagnosis

C Che, H Wang, X Ni, R Lin - Measurement, 2021 - Elsevier
For vibration signal of rolling bearing with long time series obtained from multiple sampling
points, hybrid multimodal fusion with deep learning is proposed for fault diagnosis. Feature …

Coupling data-driven and model-based methods to improve fault diagnosis

MA Atoui, A Cohen - Computers in Industry, 2021 - Elsevier
Monitoring a system is often not an easy task and the best approach to address it would be
to develop a monitoring system that uses data, expert knowledge, and mathematical models …

[HTML][HTML] Data-driven fault diagnosis analysis and open-set classification of time-series data

A Lundgren, D Jung - Control Engineering Practice, 2022 - Elsevier
Fault diagnosis of dynamic systems is done by detecting changes in time-series data, for
example residuals, caused by system degradation and faulty components. The use of …

Bond Graph-CNN based hybrid fault diagnosis with minimum labeled data

BM Dash, BO Bouamama, M Boukerdja… - … Applications of Artificial …, 2024 - Elsevier
Fault Isolation is a critical step in any fault diagnosis method, and the difficulty increases with
the complexity of the system. When there are not enough sensors in the system, the …

Self-supervised intermittent fault detection for analog circuits guided by prior knowledge

X Fang, J Qu, Y Chai - Reliability Engineering & System Safety, 2023 - Elsevier
Intermittent faults (IFs) are common in electronic systems, which are short-term, repeatable
and cumulative. IF samples are difficult to collect, so detection is usually performed using …

Dimensionality reduction for visualizing industrial chemical process data

M Joswiak, Y Peng, I Castillo, LH Chiang - Control Engineering Practice, 2019 - Elsevier
This paper explores dimensionality reduction (DR) approaches for visualizing high
dimensional data in chemical processes. Visualization provides powerful insight and …

Adaptive multiscale and dual subnet convolutional auto-encoder for intermittent fault detection of analog circuits in noise environment

X Fang, J Qu, Y Chai, B Liu - ISA transactions, 2023 - Elsevier
In avionics and industrial electronic systems, analog circuits are one of the most commonly
used components. Intermittent faults (IFs) are a no fault found (NFF) state in analog circuits …