Predictive Maintenance for Gantry Crane Shafts: Enhancing Sensor Features With Dynamic Dual-Domain Competitive Attention GRU Autoencoder
Author:
Affiliation:
1. School of Logistics Engineering, Shanghai Maritime University, Shanghai, China
2. Design Software Room, Institute of Information Technology, Shanghai Dongxin Software Engineering Company Ltd., Shanghai, China
Funder
National Key Research and Development Program of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/7361/10546898/10508741.pdf?arnumber=10508741
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1. Predictive maintenance integrated production scheduling by applying deep generative prognostics models: approach, formulation and solution
2. An integrated fault diagnosis and prognosis approach for predictive maintenance of wind turbine bearing with limited samples
3. A new dynamic predictive maintenance framework using deep learning for failure prognostics
4. Deep learning for diagnosis and classification of faults in industrial rotating machinery
5. A systematic Failure Mode Effects and Criticality Analysis for offshore wind turbine systems towards integrated condition based maintenance strategies
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