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Akademický článek

Near-zero-wear with super-hard WB4 and a self-repairing tribo-chemical layer

Autor: Guixin Hou, Shengyu Zhu, Hui Tan, Wenyuan Chen, Jiao Chen, Qichun Sun, Juanjuan Chen, Jun Cheng, Peixuan Li, William Yi Wang, Jun Yang, Weimin Liu

Publikováno v: Communications Materials, Vol 5, Iss 1, Pp 1-10 (2024)

Abstract Achieving near-zero-wear remains a major challenge in mechanical engineering and material science. Current ultra-low wear materials are typically developed based on the self-consumption strategy. Here, we demonstrate a new self-repairing app

Externí odkaz: https://doaj.org/article/8712a596de9246f4a04ebf912693bef8

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Akademický článek

Research on degradation prediction of rolling bearing based on adaptive multi-GA-BP

Autor: Lingyu Hou, Yuanyuan Li, Wei Yao, Ming Tang, Qichun Sun, Jiahang Chen

Publikováno v: Measurement + Control, Vol 55 (2022)

Rolling bearings are widely used in industrial equipment. It is of great significance to study the degradation trend of rolling bearings. In this paper, an Adaptive Multi-population Genetic Algorithm (AMGA) is proposed. Firstly, Kernel Principal Comp

Externí odkaz: https://doaj.org/article/567b3a4c379f4408927ddf0d402ec961

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Akademický článek

Investigation of tribological characteristics of nickel alloy-based solid-lubricating composites at elevated temperatures under vacuum

Autor: Jinming Zhen, Jun Cheng, Hui Tan, Qichun Sun, Shengyu Zhu, Jun Yang, Weimin Liu

Publikováno v: Friction, Vol 9, Iss 5, Pp 990-1001 (2020)

Abstract The development of a high-performance solid-lubricating composite with excellent self-lubricity over a broad temperature range in vacuum is significant to solve the frictional problems of spatial mechanisms. In this study, the vacuum tribolo

Externí odkaz: https://doaj.org/article/5f9a216d5fbb4e0ca2f17b42eacd79db

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Akademický článek

Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm

Autor: Yuanyuan Li, Qichun Sun, Hua Xu, Xiaogang Li, Zhijun Fang, Wei Yao

Publikováno v: Shock and Vibration, Vol 2022 (2022)

In order to optimize traditional fault diagnosis models for practical applications, a fault diagnosis model based on support vector machines optimized with the adaptive quantum differential evolution of (AQDE-SVM) is proposed in this study. First, th

Externí odkaz: https://doaj.org/article/f0e5518e1ba94dd5b173fe0c9a241b4b

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Akademický článek

Bearing Fault Diagnosis Method Based on Convolutional Neural Network and Knowledge Graph

Autor: Zhibo Li, Yuanyuan Li, Qichun Sun, Bowei Qi

Publikováno v: Entropy, Vol 24, Iss 11, p 1589 (2022)

An effective fault diagnosis method of bearing is the key to predictive maintenance of modern industrial equipment. With the single use of equipment failure mechanism or operation of data, it is hard to resolve multiple complex variable working condi

Externí odkaz: https://doaj.org/article/7801c9e30e7a45b4899434f69447fdff

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