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Jun Yu Cai
Researcher at Jiangsu University
Publications - 5
Jun Yu Cai is an academic researcher from Jiangsu University. The author has contributed to research in topics: Fault tree analysis & Geology. The author has co-authored 1 publications.
Papers
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Proceedings ArticleDOI
A Bayesian-optimized Hybrid Neural Network Based on CNN and BiLSTM for Predictive Maintenance of Diesel Generator
Haoyang Tang,Xing Cui,Jun Yu Cai +2 more
TL;DR: In this article , a fault diagnosis and prognosis method for diesel generator in the power supply vehicles based on convolutional neural network (CNN) and bidirectional long short-term memory network (BiLSTM) is presented.
Proceedings ArticleDOI
A Fault Knowledge Graph Creation Method and Application based on Fault Tree Analysis and Failure Mode, Effects and Criticality Analysis
Lixiang Wang,Jun Yu Cai +1 more
TL;DR: In this paper , a Fault Knowledge Graph (FKG) based on the knowledge graph (KG) in the field of faults is proposed for fault diagnosis, which can well analyze the relationship between various faults, achieve prediction, and promote development.
Book ChapterDOI
Intelligent Fault Diagnosis System of Mining Dump Truck Based on Fault Tree and Neural Network
Journal ArticleDOI
Research on Road Test Technology of Automobile Braking Ability Based on MEMS
Jun Liu,Jun Yu Cai,Xiao Peng Shi +2 more
TL;DR: In this paper, a road test system of automobile braking ability is constituted in LabVIEW based on MEMS after the deeply analysis of rating principle and national standard of it Then the real car test is accomplished using this test system and the test result has been analyzed which prove the strategy of system building is feasible and has widespread application value and prospect in engineering.
Proceedings ArticleDOI
Spacecraft Operation Process Monitoring and Fault Diagnosis System
TL;DR: In this article , a knowledge-based diagnostic rule base is constructed by using flexible diagnostic rule customization methods to achieve automatic interpretation and early warning of spacecraft operation status based on the telemetry data.