Artificial intelligence for predictive maintenance applications: key components, trustworthiness, and future trends

A Ucar, M Karakose, N Kırımça - Applied Sciences, 2024 - mdpi.com
Predictive maintenance (PdM) is a policy applying data and analytics to predict when one of
the components in a real system has been destroyed, and some anomalies appear so that …

Advances in corrosion growth modeling for oil and gas pipelines: A review

H Ma, W Zhang, Y Wang, Y Ai, W Zheng - Process Safety and …, 2023 - Elsevier
To quantify the progress of corrosion damage and develop pipeline integrity management
strategies, it is necessary to establish a reliable corrosion growth model. Due to the …

Health status assessment and remaining useful life prediction of aero-engine based on BiGRU and MMoE

Y Zhang, Y **n, Z Liu, M Chi, G Ma - Reliability Engineering & System …, 2022 - Elsevier
Prognostics and health management (PHM) is a critical work to ensure the reliable operation
of industrial equipment, in which health status (HS) assessment and remaining useful life …

Intelligent technologies for construction machinery using data-driven methods

Z Zheng, F Wang, G Gong, H Yang, D Han - Automation in Construction, 2023 - Elsevier
Along with the rapid development of infrastructure worldwide, traditional manual operations
have been a concern that restricts the high efficiency, safety, and quality of construction …

Health state assessment of bearing with feature enhancement and prediction error compensation strategy

Y Zhang, J Sun, J Zhang, H Shen, Y She… - Mechanical Systems and …, 2023 - Elsevier
Bearing is one of the most important component of rotary machine, and its health state is
directly related to the safety of industrial production. In this paper, health state assessment of …

Data-model interactive prognosis for multi-sensor monitored stochastic degrading devices

T Li, X Si, H Pei, L Sun - Mechanical Systems and Signal Processing, 2022 - Elsevier
With advances in sensing and monitoring techniques, real time multi-sensor monitoring data
of stochastic degrading devices has become the reality. How to effectively fuse these multi …

Deep learning in nuclear industry: A survey

C Tang, C Yu, Y Gao, J Chen, J Yang… - Big Data Mining and …, 2022 - ieeexplore.ieee.org
As a high-tech strategic emerging comprehensive industry, the nuclear industry is committed
to the research, production, and processing of nuclear fuel, as well as the development and …

A review of remaining useful life prediction for energy storage components based on stochastic filtering methods

L Shao, Y Zhang, X Zheng, X He, Y Zheng, Z Liu - Energies, 2023 - mdpi.com
Lithium-ion batteries are a green and environmental energy storage component, which have
become the first choice for energy storage due to their high energy density and good cycling …

Analysis of energy consumption of tobacco drying process based on industrial big data

Z Li, Z Feng, Z Zhang, S Sun, J Chen, Y Gao… - Drying …, 2024 - Taylor & Francis
To promote green upgrading, energy conservation, and consumption reduction in the
tobacco manufacturing process, the process relationship between parameters of drying and …

[HTML][HTML] Summarization of remaining life prediction methods for special power plants

W Liang, C Li, L Zhao, X Yan, S Sun - Applied Sciences, 2023 - mdpi.com
With continuous improvements in integration, totalization and automation, remaining useful
life predictions of mechanical equipment have become a key feature of technology and core …