Artículos de revistas sobre el tema "Cross-domain fault diagnosis"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte los 50 mejores artículos de revistas para su investigación sobre el tema "Cross-domain fault diagnosis".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Explore artículos de revistas sobre una amplia variedad de disciplinas y organice su bibliografía correctamente.
Wang, Xiaodong, Feng Liu y Dongdong Zhao. "Cross-Machine Fault Diagnosis with Semi-Supervised Discriminative Adversarial Domain Adaptation". Sensors 20, n.º 13 (4 de julio de 2020): 3753. http://dx.doi.org/10.3390/s20133753.
Texto completoZhang, Yongchao, Zhaohui Ren y Shihua Zhou. "A New Deep Convolutional Domain Adaptation Network for Bearing Fault Diagnosis under Different Working Conditions". Shock and Vibration 2020 (24 de julio de 2020): 1–14. http://dx.doi.org/10.1155/2020/8850976.
Texto completoMeng, Yu, Jianping Xuan, Long Xu y Jie Liu. "Dynamic Reweighted Domain Adaption for Cross-Domain Bearing Fault Diagnosis". Machines 10, n.º 4 (30 de marzo de 2022): 245. http://dx.doi.org/10.3390/machines10040245.
Texto completoChang, Hong-Chan, Ren-Ge Liu, Chen-Cheng Li y Cheng-Chien Kuo. "Fault Diagnosis of Induction Motors under Limited Data for across Loading by Residual VGG-Based Siamese Network". Applied Sciences 14, n.º 19 (4 de octubre de 2024): 8949. http://dx.doi.org/10.3390/app14198949.
Texto completoLi, Dan, Yudong Xu, Yuxun Zhou, Chao Gou y See-Kiong Ng. "Cross Domain Data Generation for Smart Building Fault Detection and Diagnosis". Mathematics 10, n.º 21 (26 de octubre de 2022): 3970. http://dx.doi.org/10.3390/math10213970.
Texto completoWang, Yuanfei, Shihao Li, Feng Jia y Jianjun Shen. "Multi-Domain Weighted Transfer Adversarial Network for the Cross-Domain Intelligent Fault Diagnosis of Bearings". Machines 10, n.º 5 (29 de abril de 2022): 326. http://dx.doi.org/10.3390/machines10050326.
Texto completoZhang, Long, Hao Zhang, Qian Xiao, Lijuan Zhao, Yanqing Hu, Haoyang Liu y Yu Qiao. "Numerical Model Driving Multi-Domain Information Transfer Method for Bearing Fault Diagnosis". Sensors 22, n.º 24 (13 de diciembre de 2022): 9759. http://dx.doi.org/10.3390/s22249759.
Texto completoJang, Gye-Bong y Sung-Bae Cho. "Cross-Domain Adaptation Using Domain Interpolation for Rotating Machinery Fault Diagnosis". IEEE Transactions on Instrumentation and Measurement 71 (2022): 1–17. http://dx.doi.org/10.1109/tim.2022.3204093.
Texto completoShang, Qianming, Tianyao Jin y Mingsheng Chen. "A New Cross-Domain Motor Fault Diagnosis Method Based on Bimodal Inputs". Journal of Marine Science and Engineering 12, n.º 8 (1 de agosto de 2024): 1304. http://dx.doi.org/10.3390/jmse12081304.
Texto completoWang, Huaqing, Zhitao Xu, Xingwei Tong y Liuyang Song. "Cross-Domain Open Set Fault Diagnosis Based on Weighted Domain Adaptation with Double Classifiers". Sensors 23, n.º 4 (14 de febrero de 2023): 2137. http://dx.doi.org/10.3390/s23042137.
Texto completoLiu, Guokai, Weiming Shen, Liang Gao y Andrew Kusiak. "Automated broad transfer learning for cross-domain fault diagnosis". Journal of Manufacturing Systems 66 (febrero de 2023): 27–41. http://dx.doi.org/10.1016/j.jmsy.2022.11.003.
Texto completoZhang, Hongpeng, Xinran Wang, Cunyou Zhang, Wei Li, Jizhe Wang, Guobin Li y Chenzhao Bai. "Dynamic Condition Adversarial Adaptation for Fault Diagnosis of Wind Turbine Gearbox". Sensors 23, n.º 23 (23 de noviembre de 2023): 9368. http://dx.doi.org/10.3390/s23239368.
Texto completoBai, Jie, Xuan Liu, Bingjie Dou, Xiaohui Yang, Bo Chen, Yaowen Zhang, Jiayu Zhang, Zhenzhong Wang y Hongbo Zou. "A Fault Diagnosis Method for Pumped Storage Unit Stator Based on Improved STFT-SVDD Hybrid Algorithm". Processes 12, n.º 10 (30 de septiembre de 2024): 2126. http://dx.doi.org/10.3390/pr12102126.
Texto completoChen, Zhuyun, Guolin He, Jipu Li, Yixiao Liao, Konstantinos Gryllias y Weihua Li. "Domain Adversarial Transfer Network for Cross-Domain Fault Diagnosis of Rotary Machinery". IEEE Transactions on Instrumentation and Measurement 69, n.º 11 (noviembre de 2020): 8702–12. http://dx.doi.org/10.1109/tim.2020.2995441.
Texto completoLiu, Fuqiang, Wenlong Deng, Chaoqun Duan, Yi Qin, Jun Luo y Huayan Pu. "Duplex adversarial domain discriminative network for cross-domain partial transfer fault diagnosis". Knowledge-Based Systems 279 (noviembre de 2023): 110960. http://dx.doi.org/10.1016/j.knosys.2023.110960.
Texto completoLiu, Fuzheng, Faye Zhang, Xiangyi Geng, Lin Mu, Lei Zhang, Qingmei Sui, Lei jia, Mingshun Jiang y Junwei Gao. "Structural discrepancy and domain adversarial fusion network for cross-domain fault diagnosis". Advanced Engineering Informatics 58 (octubre de 2023): 102217. http://dx.doi.org/10.1016/j.aei.2023.102217.
Texto completoZhang, Chao, Peng Du, Dingyu Zhou, Zhijie Dong, Shilie He y Zhenwei Zhou. "Fault Diagnosis of Low-Noise Amplifier Circuit Based on Fusion Domain Adaptation Method". Actuators 13, n.º 9 (23 de septiembre de 2024): 379. http://dx.doi.org/10.3390/act13090379.
Texto completoZhou, Hongdi, Tao Huang, Xixing Li y Fei Zhong. "Cross-domain intelligent fault diagnosis of rolling bearing based on distance metric transfer learning". Advances in Mechanical Engineering 14, n.º 11 (noviembre de 2022): 168781322211357. http://dx.doi.org/10.1177/16878132221135740.
Texto completoZhao, Chao y Weiming Shen. "Dual adversarial network for cross-domain open set fault diagnosis". Reliability Engineering & System Safety 221 (mayo de 2022): 108358. http://dx.doi.org/10.1016/j.ress.2022.108358.
Texto completoZheng, Huailiang, Rixin Wang, Yuantao Yang, Jiancheng Yin, Yongbo Li, Yuqing Li y Minqiang Xu. "Cross-Domain Fault Diagnosis Using Knowledge Transfer Strategy: A Review". IEEE Access 7 (2019): 129260–90. http://dx.doi.org/10.1109/access.2019.2939876.
Texto completoChao, Ko-Chieh, Chuan-Bi Chou y Ching-Hung Lee. "Online Domain Adaptation for Rolling Bearings Fault Diagnosis with Imbalanced Cross-Domain Data". Sensors 22, n.º 12 (16 de junio de 2022): 4540. http://dx.doi.org/10.3390/s22124540.
Texto completoFeiyan Fan, Feiyan Fan, Jiazhen Hou Feiyan Fan y Tanghuai Fan Jiazhen Hou. "Fault Diagnosis under Varying Working Conditions with Domain Adversarial Capsule Networks". 電腦學刊 33, n.º 3 (junio de 2022): 135–46. http://dx.doi.org/10.53106/199115992022063303011.
Texto completoQin, Y. X., Y. Hong, J. Y. Long, Z. Yang, Y. W. Huang y C. Li. "Attitude data-based deep transfer capsule network for intelligent fault diagnosis of delta 3D printers". Journal of Physics: Conference Series 2184, n.º 1 (1 de marzo de 2022): 012017. http://dx.doi.org/10.1088/1742-6596/2184/1/012017.
Texto completoKim, Taeyun y Jangbom Chai. "Pre-Processing Method to Improve Cross-Domain Fault Diagnosis for Bearing". Sensors 21, n.º 15 (21 de julio de 2021): 4970. http://dx.doi.org/10.3390/s21154970.
Texto completoZhang, Yongchao, Zhaohui Ren, Ke Feng, Kun Yu, Michael Beer y Zheng Liu. "Universal source-free domain adaptation method for cross-domain fault diagnosis of machines". Mechanical Systems and Signal Processing 191 (mayo de 2023): 110159. http://dx.doi.org/10.1016/j.ymssp.2023.110159.
Texto completoWang, Yu, Jie Gao, Wei Wang, Xu Yang y Jinsong Du. "Curriculum learning-based domain generalization for cross-domain fault diagnosis with category shift". Mechanical Systems and Signal Processing 212 (abril de 2024): 111295. http://dx.doi.org/10.1016/j.ymssp.2024.111295.
Texto completoZheng, Huailiang, Yuantao Yang, Jiancheng Yin, Yuqing Li, Rixin Wang y Minqiang Xu. "Deep Domain Generalization Combining A Priori Diagnosis Knowledge Toward Cross-Domain Fault Diagnosis of Rolling Bearing". IEEE Transactions on Instrumentation and Measurement 70 (2021): 1–11. http://dx.doi.org/10.1109/tim.2020.3016068.
Texto completoZou, Yingyong, Wenzhuo Zhao, Tao Liu, Xingkui Zhang y Yaochen Shi. "Research on High-Speed Train Bearing Fault Diagnosis Method Based on Domain-Adversarial Transfer Learning". Applied Sciences 14, n.º 19 (26 de septiembre de 2024): 8666. http://dx.doi.org/10.3390/app14198666.
Texto completoXie, Fengyun, Gang Li, Qiuyang Fan, Qian Xiao y Shengtong Zhou. "Optimizing and Analyzing Performance of Motor Fault Diagnosis Algorithms for Autonomous Vehicles via Cross-Domain Data Fusion". Processes 11, n.º 10 (28 de septiembre de 2023): 2862. http://dx.doi.org/10.3390/pr11102862.
Texto completoChen, Zihan y Chao He. "Transformer-Based Unsupervised Cross-Sensor Domain Adaptation for Electromechanical Actuator Fault Diagnosis". Machines 11, n.º 1 (11 de enero de 2023): 102. http://dx.doi.org/10.3390/machines11010102.
Texto completoZhang, Yizong, Shaobo Li, Ansi Zhang, Chuanjiang Li y Ling Qiu. "A Novel Bearing Fault Diagnosis Method Based on Few-Shot Transfer Learning across Different Datasets". Entropy 24, n.º 9 (14 de septiembre de 2022): 1295. http://dx.doi.org/10.3390/e24091295.
Texto completoWei, Yuqian. "Bearing fault diagnosis based on XWT-CEEMD noise reduction". Journal of Physics: Conference Series 2196, n.º 1 (1 de febrero de 2022): 012035. http://dx.doi.org/10.1088/1742-6596/2196/1/012035.
Texto completoHa, Jong Moon y Olga Fink. "Domain knowledge-informed synthetic fault sample generation with health data map for cross-domain planetary gearbox fault diagnosis". Mechanical Systems and Signal Processing 202 (noviembre de 2023): 110680. http://dx.doi.org/10.1016/j.ymssp.2023.110680.
Texto completoXiao, Zhiguo, Dongni Li, Chunguang Yang y Wei Chen. "Fault Diagnosis Method of Special Vehicle Bearing Based on Multi-Scale Feature Fusion and Transfer Adversarial Learning". Sensors 24, n.º 16 (10 de agosto de 2024): 5181. http://dx.doi.org/10.3390/s24165181.
Texto completoMontesuma, Eduardo Fernandes, Michela Mulas, Francesco Corona y Fred-Maurice Ngole Mboula. "Cross-domain fault diagnosis through optimal transport for a CSTR process". IFAC-PapersOnLine 55, n.º 7 (2022): 946–51. http://dx.doi.org/10.1016/j.ifacol.2022.07.566.
Texto completoTian, Jilun, Jiusi Zhang, Yuchen Jiang, Shimeng Wu, Hao Luo y Shen Yin. "A novel generalized source-free domain adaptation approach for cross-domain industrial fault diagnosis". Reliability Engineering & System Safety 243 (marzo de 2024): 109891. http://dx.doi.org/10.1016/j.ress.2023.109891.
Texto completoLi, Guofa, Shaoyang Liu, Jialong He, Liang Wang, Chenchen Wu y Chenhui Qian. "A multi-domain adversarial transfer network for cross domain fault diagnosis under imbalanced data". Engineering Applications of Artificial Intelligence 136 (octubre de 2024): 108948. http://dx.doi.org/10.1016/j.engappai.2024.108948.
Texto completoWen, Weigang, Yihao Bai y Weidong Cheng. "Generative Adversarial Learning Enhanced Fault Diagnosis for Planetary Gearbox under Varying Working Conditions". Sensors 20, n.º 6 (18 de marzo de 2020): 1685. http://dx.doi.org/10.3390/s20061685.
Texto completoShen, Bingbing, Min Zhang, Le Yao y Zhihuan Song. "Novel Triplet Loss-Based Domain Generalization Network for Bearing Fault Diagnosis with Unseen Load Condition". Processes 12, n.º 5 (26 de abril de 2024): 882. http://dx.doi.org/10.3390/pr12050882.
Texto completoShe, Daoming, Zhichao Yang, Yudan Duan, Xiaoan Yan, Jin Chen y Yaoming Li. "A meta transfer learning method for gearbox fault diagnosis with limited data". Measurement Science and Technology 35, n.º 8 (9 de mayo de 2024): 086114. http://dx.doi.org/10.1088/1361-6501/ad4665.
Texto completoZhong, Zhidan, Zhihui Zhang, Yunhao Cui, Xinghui Xie y Wenlu Hao. "Failure Mechanism Information-Assisted Multi-Domain Adversarial Transfer Fault Diagnosis Model for Rolling Bearings under Variable Operating Conditions". Electronics 13, n.º 11 (30 de mayo de 2024): 2133. http://dx.doi.org/10.3390/electronics13112133.
Texto completoAn, Jing, Ping Ai y Dakun Liu. "Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning". Shock and Vibration 2020 (20 de marzo de 2020): 1–14. http://dx.doi.org/10.1155/2020/4676701.
Texto completoZhai, Lubin, Xiufeng Wang, Zeyiwen Si y Zedong Wang. "A Deep Learning Method for Bearing Cross-Domain Fault Diagnostics Based on the Standard Envelope Spectrum". Sensors 24, n.º 11 (29 de mayo de 2024): 3500. http://dx.doi.org/10.3390/s24113500.
Texto completoXu, Shu, Jian Ma y Dengwei Song. "Open-set Federated Adversarial Domain Adaptation Based Cross-domain Fault Diagnosis". Measurement Science and Technology, 13 de julio de 2023. http://dx.doi.org/10.1088/1361-6501/ace734.
Texto completoJia, Feng, Yuanfei Wang, Jianjun Shen, Lifei Hao y Zhaoyu Jiang. "Stepwise feature norm network with adaptive weighting for open set cross-domain intelligent fault diagnosis of bearings". Measurement Science and Technology, 9 de febrero de 2024. http://dx.doi.org/10.1088/1361-6501/ad282f.
Texto completoLi, Can, Guangbin Wang, Shubiao Zhao, Zhixian Zhong y Ying Lv. "Cross-domain manifold structure preservation for transferable and cross-machine fault diagnosis". Journal of Vibroengineering, 22 de agosto de 2024. http://dx.doi.org/10.21595/jve.2024.24067.
Texto completoMao, Xiaodong. "Cross domain fault diagnosis method based on MLP-mixer network". Journal of Measurements in Engineering, 30 de octubre de 2023. http://dx.doi.org/10.21595/jme.2023.23460.
Texto completoWang, Pei, Jie Liu, Jianzhong Zhou, Ran Duan y Wei Jiang. "Cross-domain fault diagnosis of rotating machinery based on graph feature extraction". Measurement Science and Technology, 9 de noviembre de 2022. http://dx.doi.org/10.1088/1361-6501/aca16f.
Texto completoLu, Weikai, Haoyi Fan, Kun Zeng, Zuoyong Li y Jian Chen. "Self‐supervised domain adaptation for cross‐domain fault diagnosis". International Journal of Intelligent Systems, 2 de septiembre de 2022. http://dx.doi.org/10.1002/int.23026.
Texto completoLiao, Yixiao, Ruyi Huang, Jipu Li, Zhuyun Chen y Weihua Li. "Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis". Chinese Journal of Mechanical Engineering 34, n.º 1 (4 de junio de 2021). http://dx.doi.org/10.1186/s10033-021-00566-3.
Texto completo