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1.
Comput Intell Neurosci ; 2022: 7592258, 2022.
Article in English | MEDLINE | ID: mdl-35875772

ABSTRACT

As a new generative model, the generative adversarial network (GAN) has great potential in the accuracy and efficiency of generating pseudoreal data. Nowadays, bearing fault diagnosis based on machine learning usually needs sufficient data. If enough near-real data can be generated in the case of insufficient samples in the actual operating condition, the effect of fault diagnosis will be greatly improved. In this study, a new rolling bearing data generation method based on the generative adversarial network (GAN) is proposed, which can be trained adversarially and jointly via a learned embedding, and applied to solve fault diagnosis problems with insufficient data. By analyzing the time-domain characteristics of rolling bearing life cycle monitoring data in actual working conditions, the operation data are divided into three periods, and the construction and training of the generative adversarial network model are carried out. Data generated by adversarial are compared with the real data in the time domain and frequency domain, respectively, and the similarity between the generated data and the real data is verified.


Subject(s)
Machine Learning
2.
Mater Sci Eng C Mater Biol Appl ; 128: 112264, 2021 Sep.
Article in English | MEDLINE | ID: mdl-34474823

ABSTRACT

Injectable self-healing hydrogels of natural polysaccharides that mimic the extracellular matrix to promote cellular growth are attractive materials for wound healing. Here, a novel hydrogel was fabricated based on carboxymethyl chitosan (CS) and aldehyde functionalized sodium alginate via Schiff base reaction. To enhance the hydrogel's properties, carboxymethyl-functionalized polymethyl methacrylate (PMAA) short nanofibers were obtained through sodium hydroxide-treated polymethyl methacrylate nanofibers, and added to a CS solution. Gelation time was determined for different hydrogels including 0-5 mg/mL PMAA short nanofibers. The nanofiber hydrogels were tested for their injectability and self-healing abilities and were demonstrated to be easily injectable with excellent self-healing abilities. Additionally, in vitro cytocompatibility experiments, good interaction between the cultured cells and hydrogels was seen. Further, the polysaccharide hydrogel containing short PMMA nanofibers significantly facilitated wound healing in rats compared with the polysaccharide hydrogel and control groups. Thus, the developed hydrogel has great potential for wound healing applications.


Subject(s)
Chitosan , Nanofibers , Alginates , Animals , Hydrogels , Polysaccharides , Rats , Wound Healing
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