[1] Wu Chong, Qi Juntong, Song Dalei et al. Simultaneous state and parameter estimation based actuator fault detection and diagnosis for an unmanned helicopter[J]. International Journal of Applied Mathematics and Computer Science, 25, 175-187(2015).

[2] Wang Xiaofeng, Mao Deqiang, Feng Shangcong. Review on modern fault diagnosis technologies[J]. China Measurement & Test, 39, 93-98(2013).

[3] Yuan Jie, Wang Fuli, Wang Shu. A fault diagnosis approach by D-S fusion theory and hybrid expert knowledge system[J]. Acta Automatica Sinica, 43, 1580-1587(2017).

[4] Wang Di, Liu Jia, Wang Yanfeng. Modeling method of fault diagnosis of electronic device based on multi-signal flow[J]. High Power Laser and Particle Beams, 29, 07510(2017).

[5] Li Han, Xiao Deyun. Survey on data driven fault diagnosis methods[J]. Control and Decision, 26, 1-9(2011).

[6] [6] Baskaya E, Bronz M, Delahaye D. Fault detection & diagnosis f small UAVs via machine learning[C]2017 IEEEAIAA 36th Digital Avionics Systems Conference (D). 2017: 16.

[7] [7] Bondyra A, Gasi P, Gardecki S, et al. Fault diagnosis condition moniting of UAV rot using signal processing[C]2017 Signal Processing: Algithms, Architectures, Arrangements, Applications (SPA). 2017: 233238.

[8] Liang Shaojun, Zhang Shirong, Huang Yuping et al. Data-driven fault diagnosis of FW-UAVs with consideration of multiple operation conditions[J]. ISA Transactions, 126, 472-485(2022).

[9] [9] Chen Yuepeng, Zhang Cong, Zhang Qingyong, et al. UAV fault detection based on GABP neural wk[C]2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC). 2017: 806811.

[10] [10] Sadhu V, Zonouz S, Pompili D. Onboard deeplearningbased unmanned aerial vehicle fault cause detection identification[C]2020 IEEE International Conference on Robotics Automation (ICRA). 2020: 52555261.

[11] Guo Dingfei, Zhong Maiying, Ji Hongquan et al. A hybrid feature model and deep learning based fault diagnosis for unmanned aerial vehicle sensors[J]. Neurocomputing, 319, 155-163(2018).

[12] Chen Qian, Dong Xingjian, Tu Guowei et al. TFN: an interpretable neural network with time-frequency transform embedded for intelligent fault diagnosis[J]. Mechanical Systems and Signal Processing, 207, 110952(2024).

[13] Salamon J, Bello J P. Deep convolutional neural networks and data augmentation for environmental sound classification[J]. IEEE Signal Processing Letters, 24, 279-283(2017).

[14] [14] He Kaiming, Zhang Xiangyu, Ren Shaoqing, et al. Deep residual learning f image recognition[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition. 2016: 770778.

[15] Liao Jingxiao, Dong Hangcheng, Sun Zhiqi et al. Attention-embedded quadratic network (Qttention) for effective and interpretable bearing fault diagnosis[J]. IEEE Transactions on Instrumentation and Measurement, 72, 3511113(2023).

[16] Lyu Y, Vosselman G, Xia Guisong et al. UAVid: a semantic segmentation dataset for UAV imagery[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 165, 108-119(2020).

[17] Antonini A, Guerra W, Murali V et al. The blackbird UAV dataset[J]. The International Journal of Robotics Research, 39, 1346-1364(2020).

[18] Nguyen T M, Yuan Shenghai, Cao Muqing et al. NTU VIRAL: a visual-inertial-ranging-lidar dataset, from an aerial vehicle viewpoint[J]. The International Journal of Robotics Research, 41, 270-280(2022).

[19] Keipour A, Mousaei M, Scherer S. ALFA: a dataset for UAV fault and anomaly detection[J]. The International Journal of Robotics Research, 40, 515-520(2021).

[20] Yu Daojie, He Kai, Guo Baisen. Failure process and mechanism of irradiation interference in unmanned aerial vehicle positioning system[J]. High Power Laser and Particle Beams, 35, 023002(2023).

[21] [21] Baskett B. Aeronautical design stard perfmance specification hling qualities requirements f military rotcraft[D]. Alabama: United States Army Aviation Missile Comm Aviation Engineering Dierctate Redstone Arsenal, 2000.

[22] Miao Jianguo, Wang Jianyu, Zhang Heng. Review of the development of fault diagnosis technology for unmanned aerial vehicle[J]. Chinese Journal of Scientific Instrument, 41, 56-69(2020).

[23] [23] Jun Wang, Tian Yuyang. Fault tolerant control of quadrot UAV based on suppt vect machine[C]2019 5th International Conference on Control Science Systems Engineering (ICCSSE). 2019: 1013.

[24] Wang Lina, Liu Zhenbao, Yuan Jinbiao. Adaptive fault diagnosis and estimation for quadrotor UAV[J]. Journal of Beijing University of Aeronautics and Astronautics, 49, 2395-2405(2023).

[25] He Kai, Yu Daojie, Wang Dong et al. Graph attention network-based fault detection for UAVs with multivariant time series flight data[J]. IEEE Transactions on Instrumentation and Measurement, 71, 3530213(2022).

[26] Liu Xuhang, Liu Xiaoxiong, Zhang Weiguo. UAV attitude calculation algorithm based on acceleration correction model[J]. Journal of Northwestern Polytechnical University, 39, 175-181(2021).