Fault Diagnosis Method of Engineering Vehicles for Variable Working Condition Based on a Multi-Source Transfer Neural Network Algorithm-Reference-Cited by-同舟云学术

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Fault Diagnosis Method of Engineering Vehicles for Variable Working Condition Based on a Multi-Source Transfer Neural Network Algorithm

Published:2023-12-15 Issue: Volume:42 Page:842-846
ISSN:
Container-title:2023 3rd International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI)
language:
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Author:

Chang Fu¹,Qian Qingting¹,Zhou Na¹,Li Yaowei¹,Wu Jiaxiong¹,Yang Shudi²

Affiliation:

1. China North Vehicle Research Institute,Beijing,China

2. China North Artificial Intelligence & Innovation Research Institute,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10527436/10527786/10527821.pdf?arnumber=10527821

Reference14 articles.

1. Fault Diagnosis of Observation-aiming Based on LLSO-MKELM Algorithm;Wang;Ordnance Industry Automation,2023

2. Resampling Technique-Based Demodulation Analysis for Planet Bearing Cage Fault Diagnosis Under Nonstationary Conditions

3. Fault Diagnosis of Armored Vehicle Circuit Board Based on GA-BP Neural Network;Xie;Automation & Instrumentation,2022

4. Injector Fault Diagnosis of Armored Vehicle Diesel Engine Based on Multi-layer Bidirectional Long Short Term Memory Network;Jin;Ordnance Industry Automation,2022

5. Application of BP Neural Network Improved by Genetic Immune Algorithm in Armored vehicle Circuit Board Fault Diagnosis;Li;Computer Measurement & Control,2017

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