A hierarchical adversarial multi-target domain adaptation for gear fault diagnosis under variable working condition based on raw acoustic signal
Author:
Funder
National Natural Science Foundation of China
Publisher
Elsevier BV
Subject
Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering
Reference57 articles.
1. Fault diagnosis of single-phase induction motor based on acoustic signals;Adam;Mech. Syst. Signal Process.,2019
2. Anoosheh, A., et al., 2018. Combogan: Unrestrained scalability for image domain translation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops.
3. Rotating machine fault diagnosis by a novel fast sparsity-enabled feature-energy-ratio method;Biao;ISA Trans.,2022
4. Domain adversarial transfer network for cross-domain fault diagnosis of rotary machinery;Chen;IEEE Trans. Instrum. Meas.,2020
5. Choi, Y., et al., 2018. Stargan: Unified generative adversarial networks for multi-domain image-to-image translation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Alleviating confirmation bias in perpetually dynamic environments: Continuous unsupervised domain adaptation-based condition monitoring (CUDACoM);Engineering Applications of Artificial Intelligence;2024-11
2. Multi-target domain adaptation intelligent diagnosis method for rotating machinery based on multi-source attention mechanism and mixup feature augmentation;Reliability Engineering & System Safety;2024-10
3. CFENet: A contrastive frequency-sensitive learning method for gas-insulated switch-gear fault detection under varying operating conditions using acoustic signals;Engineering Applications of Artificial Intelligence;2024-09
4. A performance-interpretable intelligent fusion of sound and vibration signals for bearing fault diagnosis via dynamic CAME;Nonlinear Dynamics;2024-08-24
5. Smart filter aided domain adversarial neural network for fault diagnosis in noisy industrial scenarios;Engineering Applications of Artificial Intelligence;2023-11
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3