Publications： [1]Zhang Yuyan, Zhang Yongqi, Zhang Yafeng, Li Hao, Yan Lingdi, Wen Xiaoyu, Wang Haoqi. Multi-Class Data Augmentation and Fault Diagnosis of Wind Turbine Blades Based on ISOMAP-CGAN Under High-Dimensional Imbalanced Samples[J]. Renewable Energy, 2025, 122609. [2]Zhang Yongqi, Shen Guanghui, Zhang Yuyan*, Li Hao, Wang Haoqi. Fault Diagnosis of Wind Turbine Gearboxes Based on SVM Feature Selection and CGAN Data Augmentation Under Imbalanced Samples[J]. Journal of Vibration and Control, 2025, 10775463251322309. [3]Zhang Yuyan, Zhang Yongqi, Ming Wuyi, Li Hao, Wen Xiaoyu, Yan Lingdi. A roundtrip probability estimation method for mechanical equipment fault detection under imbalanced samples[J]. Measurement and Control, 2024.03: 00202940241237118 [4]Zhang Yuyan, Zhang YaFeng, Li Hao, et al. Semi-Supervised Diagnosis Method for Coupling Faults of Key Rotating Components Based on EEMD-KPCA under Cross Working Conditions[J]. Measurement Science and Technology, 2023, 35(2): 025014. [5]Zhang Yuyan, Zhang YaFeng, Li Hao, et al. Wind Turbine Blade Cracking Detection under Imbalanced Data Using a Novel Roundtrip Auto-Encoder Approach[J]. Applied Sciences, 2023, 13(21): 11628. [6]Zhang Y, Gao L, Wen X, et al. Intelligent fault diagnosis of machine under noisy environment using ensemble orthogonal contractive auto-encoder[J]. Expert Systems with Applications, 2022, 203: 117408. [7]Li H, Yan X, Zhang Y*(Corresponding Author), et al. Real-time detection method for welding parts completeness based on improved YOLOX in a digital twin environment[J]. Measurement Science and Technology, 2023, 34(5): 055004. [8]Wen X, Qian Y, Lian X, Zhang Y*(Corresponding Author). Improved genetic algorithm based on multi-layer encoding approach for integrated process planning and scheduling problem[J]. Robotics and Computer-Integrated Manufacturing, 2023, 84: 102593. [9]Zhang Y, Li X, Gao L, et al. Ensemble deep contractive auto-encoders for intelligent fault diagnosis of machines under noisy environment[J]. Knowledge-Based Systems, 2020,196:1-20. [10]Zhang Y, Li X, Gao L, et al. A new subset based deep feature learning method for intelligent fault diagnosis of bearing[J]. Expert Systems with Applications, 2018, 110: 125-142. [11]Zhang Y, Li X, Gao L, et al. Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning[J]. Journal of Manufacturing Systems, 2018, 48:34-50. [12]Zhang Y, Li X, Gao L, et al. Intelligent fault diagnosis of rotating machinery using a new ensemble deep auto-encoder method. Measurement, 2020, 151: 1-16. [13]Li M, Zhang Y, Zeng B, et al. The modified firefly algorithm considering fireflies visual range and its application in assembly sequences planning[J]. The International Journal of Advanced Manufacturing Technology, 2016, 82(5-8): 1381-1403. [14]Wen L, Li X, Gao L, Zhang Y. A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method[J]. IEEE Transactions on Industrial Electronics, 2018, 65(7): 5990-5998. |
