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A new fault diagnosis method based on convolutional neural network and compressive sensing
Yunfei Ma,Xisheng Jia,Huajun Bai,Guozeng Liu,Guanglong Wang,Chiming Guo,Shuangchuan Wang 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.11
Compressive sensing is an efficient machinery monitoring framework, which just needs to sample and store a small amount of observed signal. However, traditional reconstruction and fault detection methods cost great time and the accuracy is not satisfied. For this problem, a 1D convolutional neural network (CNN) is adopted here for fault diagnosis using the compressed signal. CNN replaces the reconstruction and fault detection processes and greatly improves the performance. Since the main information has been reserved in the compressed signal, the CNN is able to extract features from it automatically. The experiments on compressed gearbox signal demonstrated that CNN not only achieves better accuracy but also costs less time. The influencing factors of CNN have been discussed, and we compared the CNN with other classifiers. Moreover, the CNN model was also tested on bearing dataset from Case Western Reserve University. The proposed model achieves more than 90 % accuracy even for 50 % compressed signal.
Effect of Cyclic Deep Cryogenic Treatment on Corrosion Resistance of 7075 Alloy
Ruiming Su,Siyi Ma,Kaining Wang,Guanglong Li,Yingdong Qu,Rongde Li 대한금속·재료학회 2022 METALS AND MATERIALS International Vol.28 No.4
The cyclic deep cryogenic treatment was proposed to improve both the hardness and corrosion resistance of the high strength7075 aluminum alloy. The effect of different CDCT times on the exfoliation corrosion and intergranular corrosion of the alloyswere observed by scanning electron microscope. The corrosion behaviors of the alloys were monitored by electrochemicaltechniques. The hardness of the alloy was measured by Vickers hardness tester. Furthermore, the microstructures of thealloys were examined by transmission electron microscope. The results show that the corrosion resistance and hardness arestrongly affected by the precipitate state. The discontinuous grain boundary precipitates and the wide precipitate free zoneswill enhance the corrosion resistance. The fine precipitates distributed evenly in the matrix can increase the hardness. Afterthe CDCT, the corrosion resistance is remarkably improved without sacrificing the hardness. The best combination of thehardness and corrosion resistance is exhibited for the alloy treated with the CDCT twice.
Xiaoyu Zhang,Liyuan Fan,Yanshuai Cui,Tianming Cui,Shengfu Chen,Guanglong Ma,Wenlong Hou,Longgang Wang 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2020 NANO Vol.15 No.02
The green synthesis of gold nanoparticles (Au NPs) for catalytic and biological applications has been drawing great attention. To compare with plant extracts, the polysaccharides may be good reducing and stabilizing agents. In this work, we describe the preparation of longan polysaccharide stabilized gold nanoparticles (Aun-LP NPs) by reduction of gold ions using a green synthetic method. The formation of gold nanoparticles (Au NPs) was confirmed by UV-Vis spectra. TEM showed that Au NPs had a small size (7.8–15.6 nm) and were highly dispersed without any aggregation. XPS confirmed that the surface elemental composition of Aun-LP NPs was C, O, and Au. DLS demonstrated that Aun-LP NPs had good stability and negative zeta potential. In addition, Aun-LP NPs had high catalytic activity for the reduction of 4-nitrophenol. More importantly, Aun-LP NPs had ignorable cytotoxicity towards HeLa cells and showed good antioxidant activity. Taken together, the results indicated that longan polysaccharide can be used as reducing agents and stabilizers for the preparation of metallic nanoparticles, and the product had wide applications.