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2568 振 动 工 程 学 报 第 38 卷

fault diagnosis of machines[J]. IEEE Transactions on Indus- health diagnostics of wind turbine planetary gearbox[J].
trial Electronics，2020，67（11）：9747-9757. Renewable Energy，2023，219：119373.
[7] DU K N，WU D H，BAO K，et al. Unconstrained Wasser- [18] YANG B，LEI Y G，JIA F，et al. An intelligent fault diag-
stein distance and multi-attention fusion convolutional neural nosis approach based on transfer learning from laboratory
network guided adversarial domain adaptation for cross- bearings to locomotive bearings[J]. Mechanical Systems and
domain fault diagnosis of machines[J]. Mechanical Systems Signal Processing，2019，122：692-706.
and Signal Processing，2025，234：112797 [19] HAN T， LIU C， YANG W G， et al. A novel adversarial
[8] NIU M G， JIANG H K， SHAO H D. Dynamic weighted learning framework in deep convolutional neural network for
adversarial domain adaptation network with sparse representa- intelligent diagnosis of mechanical faults[J]. Knowledge-Based
tion denoising module for rotating machinery fault Systems，2019，165：474-487.
diagnosis[J]. Engineering Applications of Artificial Intelli- [20] LONG M S， ZHU H， WANG J M， et al. Deep transfer
gence，2025，142：109963. learning with joint adaptation networks[C]//International
[9] JIAO J Y，ZHAO M，LIN J. Multi-weight domain adversar- Conference on Machine Learning，PMLR. 2017：2208-2217.
ial network for partial-set transfer diagnosis[J]. IEEE Transac- [21] CAO Z J，MA L J，LONG M S，et al. Partial adversarial
tions on Industrial Electronics，2022，69（4）：4275-4284. domain adaptation[C]//Computer Vision-ECCV 2018. Cham：
[10] LIU X L，LIU F Z，HAN T Z，et al. Novel source domain Springer International Publishing，2018：139-155.
filtering dual classifier network with adaptive pseudo label [22] CAO Z J，LONG M S，WANG J M，et al. Partial transfer
refinement for partial domain fault diagnosis[J]. Neurocomput- learning with selective adversarial networks[C]//Proceedings
ing，2025，620：129260. of the IEEE/CVE Conference on Computer Vision and Pattern
[11] WANG R， HUANG W G， SHI M K， et al. Multiweight Recognition. IEEE，2018：2724-2732.
adversarial open-set domain adaptation network for machinery [23] LI W H，CHEN Z Y，HE G L. A novel weighted adversarial
fault diagnosis with unknown faults[J]. IEEE Sensors Jour- transfer network for partial domain fault diagnosis of machin-
nal，2023，23（24）：31483-31492. ery[J]. IEEE Transactions on Industrial Informatics， 2021，
[12] SUN K C， YIN A J， LU S. Domain distribution variation 17（3）：1753-1762.
learning via adversarial adaption for helicopter transmission [24] DAI Y，LIU J，REN X C，et al. Adversarial training based
system fault diagnosis[J]. Mechanical Systems and Signal multi-source unsupervised domain adaptation for sentiment
Processing，2024，215：111419. analysis[J]. Proceedings of the AAAI Conference on Artificial
[13] WU Z H， JIANG H K， ZHU H X， et al. A knowledge Intelligence，2020，34（5）：7618-7625.
dynamic matching unit-guided multi-source domain adapta- [25] WANG R， HUANG W G， WANG J， et al. Multisource
tion network with attention mechanism for rolling bearing fault domain feature adaptation network for bearing fault diagnosis
diagnosis[J]. Mechanical Systems and Signal Processing， under time-varying working conditions[J]. IEEE Transactions
2023，189：110098. on Instrumentation and Measurement，2022，71：3511010.
[14] LIU B，LI G F，HE J L，et al. Dual branch feature match- [26] SAPORTA A， VU T H， CORD M， et al. Multi-target
ing guided multi-source domain adaptive ensemble network adversarial frameworks for domain adaptation in semantic
for rotating machinery fault diagnosis[J]. Advanced Engineer- segmentation[C]//Proceedings of the IEEE/CVF International
ing Informatics，2025，64：103061. Conference on Computer Vision（ICCV）. IEEE，2021：9052-
[15] YAN S，SHAO H D，WANG X Y，et al. Compact-sparse 9061.
prototype calibration network for few-shot continual fault [27] CHEN Z Y，WU J，DENG C，et al. Residual deep subdo-
diagnosis of rotating machinery[J]. Engineering Applications main adaptation network：a new method for intelligent fault
of Artificial Intelligence，2025，155：111099. diagnosis of bearings across multiple domains[J]. Mechanism
[16] ZHANG Y T，ZHANG H L，WANG R，et al. Multi-level and Machine Theory，2022，169：104635.
weighted dynamic adversarial adaptation network for partial
set cross-domain fault diagnosis[J]. Measurement， 2023， 第一作者：张宇腾（1999—），男，博士研究生。
223：113712. E-mail：ytzhangz@bit.edu.cn
[17] KONG Y，HAN Q K，CHU F L，et al. Spectral ensemble 通信作者：孔 运（1993—），男，博士，副教授。
sparse representation classification approach for super-robust E-mail：kongyun@bit.edu.cn