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An improved bearing fault detection strategy based on artificial bee colony algorithm 被引量:3
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作者 Haiquan Wang Wenxuan Yue +6 位作者 Shengjun Wen Xiaobin Xu Hans-Dietrich Haasis Menghao Su Ping liu Shanshan Zhang Panpan Du 《CAAI Transactions on Intelligence Technology》 SCIE EI 2022年第4期570-581,共12页
The operating state of bearing affects the performance of rotating machinery;thus,how to accurately extract features from the original vibration signals and recognise the faulty parts as early as possible is very crit... The operating state of bearing affects the performance of rotating machinery;thus,how to accurately extract features from the original vibration signals and recognise the faulty parts as early as possible is very critical.In this study,the one‐dimensional ternary model which has been proved to be an effective statistical method in feature selection is introduced and shapelet transformation is proposed to calculate the parameter of one‐dimensional ternary model that is usually selected by trial and error.Then XGBoost is used to recognise the faults from the obtained features,and artificial bee colony algorithm(ABC)is introduced to optimise the parameters of XGBoost.Moreover,for improving the performance of intelligent algorithm,an improved strategy where the evolution is guided by the probability that the optimal solution appears in certain solution space is proposed.The experimental results based on the failure vibration signal samples show that the average accuracy of fault signal recognition can reach 97%,which is much higher than the ones corresponding to traditional extraction strategies.And with the help of improved ABC algorithm,the performance of XGBoost classifier could be optimised;the accuracy could be improved from 97.02%to 98.60%compared with the traditional classification strategy. 展开更多
关键词 fault diagnosis feature extraction improved artificial bee colony algorithm improved one-dimensional ternary pattern method shapelet transformation
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A Theoretical Outline for National Security Studies for the New Era
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作者 Zhang Yuyan Feng Weijiang 李光辉 《Social Sciences in China》 2022年第2期16-35,共20页
China is tasked with attaining the great rejuvenation of the Chinese nation and facing global changes unseen in a century.To this end,a pressing task for China’s national security studies in the new era,under the gui... China is tasked with attaining the great rejuvenation of the Chinese nation and facing global changes unseen in a century.To this end,a pressing task for China’s national security studies in the new era,under the guidance of a holistic concept of national security,is to provide an analytical framework and scholarly insights.Seven theoretical propositions can be derived when we clarify the relationships between security level,security capability,and security threats.They are:absolute security is out of reach;growing security investment that eyes absolute security will create a security dilemma;under closed conditions,the country should put the brakes on building relative security when it achieves equilibrium security;under open conditions,hegemonic powers may generate security capabilities that exceed equilibrium security and tend to“protect”or prey on countries whose development has relatively high output efficiency rather than those whose security capabilities have relatively high output efficiency;and following separate technical routes for dealing with intentional and unintentional threats may achieve a higher security level than managing in an undifferentiated way.The“Great Yu Improvement”pattern is pivotal to“Building a Community with a Shared Future for Mankind”as it can transform other actors’capacity to address intentional threats into a capacity for shielding oneself against unintentional threats;and appropriate allocation of excessive security capability and stronger national system security capability are major solutions to the uncertain nature of security threats. 展开更多
关键词 holistic concept of national security national security studies in the new era security capability equilibrium security the Great Yu Improvement pattern
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