Location of elevator fault components by using knowledge map with Neo4j-Reference-Cited by-同舟云学术

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Location of elevator fault components by using knowledge map with Neo4j

Published:2023-09-22 Issue: Volume: Page:
ISSN:
Container-title:2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)
language:
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Author:

Dapeng Zhang¹,Hao Ma¹,Jinkui Feng²

Affiliation:

1. Tianjin University,School of Electrical Automation and Information Engineering,Tianjin,China

2. China Special Equipment Inspection & Research Institute,Key Laboratory of Special Equipment Safety and Energy-Saving for State Market Regulation,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10295546/10295577/10295937.pdf?arnumber=10295937

Reference11 articles.

1. Monitoring and diagnosis of multiple incipient faults using fault tree induction

2. A Hybrid Approach: Dynamic Diagnostic Rules for Sensor Systems in Industry 4.0 Generated by Online Hyperparameter Tuned Random Forest

3. Construction and application of fault knowledge graph of NC equipment [J];qian;Tobacco on Aviation Manufacturing Technology,2020

4. A new model of elevator supervision based on big data [J];zhenzhen;Electronic Technology and Software Engineering,2016

5. Research on collection and preprocessing of multisource heterogeneous elevator data[C];chen;2020 IEEE International Conference on Power Intelligent Computing and Systems (ICPICS),2020

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