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关键词： deep one classification   fault diagnosis   multitasking   rolling bearing   self-supervised learning  

摘要： At present the intelligent fault diagnosis model is difficult to train due to the difficulty in obtaining the fault data of rolling bearings. A self-supervised deep one-class classification method was proposed for early fault warning of rolling bearings based on the training of normal class samples. Based on the deep one-class classification model, multi-task and self-supervision mechanisms were introduced. Input signal was extracted with the use of the depth of the deep residual network characteristics, and the proposed features were taken respectively as input of more child tasks, including support vector description (SVDD) as the output results of the classification subtasks supervision and label as the rest of the subtasks;through the joint loss function, only relying on normal class samples can complete the model of supervised learning. When the proposed method was applied to the fault warning of rolling bearings, the vibration acceleration signals of the whole life cycle were decomposed by frequency band, and the signals in different frequency bands were encoded as the input of the network. The proposed method was validated on two actual rolling bearing fault data sets. The verification results showed that the accuracy of the proposed depth classification method reached more than 99% in fault warning, which fully indicated that the proposed method has a high ability of fault warning and anomaly detection. © 2025 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.

关键词： Hamiltonians  

摘要： A fixed-time control strategy based on the port controlled Hamiltonian system model (PCHSM) is proposed for a class of coupled liquid level systems. The Hamiltonian function is selected from the perspective of material balance and the PCHSM is constructed for the coupled liquid level systems. The fixed-time controller is designed based on a novel objective Hamiltonian function, combined with matching conditions, to enable the system to converge in the stable domain within the fixed time. The method for tuning the parameters of the target structure matrix is proposed to reduce the complexity of the controller solving process, and the intrinsic correlation between the target matrix parameters and convergence time is provided. Based on the L2 gain disturbance attenuation theory, the global fixed-time H∞ controller is designed. The proposed control method can better achieve set-points tracking, has good robustness, and the controller is more concise. The effectiveness of the control strategy is verified through simulation results. © 2025 Northeast University. All rights reserved.

关键词： Trusses  

摘要： The multi-stage self-centering steel truss frame structure is proposed to enhance the seismic resilience of steel truss frame structures，and the nonlinear displacement demand of the novel structure is quantified. Based on the equivalent single degree of freedom（SDOF）system representing the novel structure and 182 velocity pulse-like ground motions，the nonlinear displacement ratio spectrum is developed through nonlinear dynamic analyses. The influences of period，damping ratio，and hysteretic parameters on the nonlinear displacement ratio are discussed. A probabilistic prediction model for the nonlinear displacement ratio is developed using the XGBoost algorithm in machine learning. In addition，to address the"black-box"issue in machine learning，the prediction results of the model are interpreted based on shapley additive explanations （SHAP）and partial dependence plots（PDP）methods. The results indicate that the nonlinear displacement ratio is sensitive to period，damping ratio，and hysteretic parameters. The probabilistic prediction model not only exhibits high predictive accuracy but also intuitively reflects the influence patterns of various parameters. This model can be applied to develop a displacement-based seismic design method for the multi-stage self-centering steel truss frame structure. © 2025 Southeast University. All rights reserved.

摘要： 中国科学院紫金山天文台研究员范一中领衔的研究团队,利用引力波探测器阵列LIGO-Virgo-KAGRA的GWTC-3观测数据研究了并合黑洞的形成问题,揭示了恒星塌缩形成和重复并合形成的两类黑洞的分布特征.研究成 果 以"Resolving the stellar-collapse and hierarchical-merger origins of the coalescing black holes"为题,发表在《物理评论快报》上.

关键词： 口腔就诊行为   口腔健康   全因死亡率   口腔诊疗   牙周治疗  

摘要： 目的:探究口腔就诊行为、口腔健康与全因死亡率之间的相关性.方法:分析美国国家健康与营养调查数据库1999年至2004年和2011年至2018年共计36 174名参与者的临床数据.口腔健康状况使用牙周健康状况、牙体健康状况和牙列完整性这三个指标进行评估.口腔就诊行为频率由最近一次口腔就诊至今的时间间隔评估.采用Cox比例风险回归模型估算死亡风险的危险比率及95%置信区间,通过中介分析探究口腔就诊行为在口腔健康状况欠佳与全因死亡率之间的中介作用.结果:30%的人群患有轻度至重度牙周炎,38.9%的人群至少有15个龋齿,21.2%的人群至少有15个牙齿缺失,超过50%的人群最后一次口腔就诊行为发生于1年以内.经过平均9.03年的随访,共发现6 012例死亡病例.口腔健康状况不佳与全因死亡率较高有关.最近一次口腔就诊行为发生于1年内与全因死亡率降低相关.无论口腔健康状况如何,参与者均能从良好的口腔就诊行为中获益.中介分析发现,口腔就诊行为对牙周炎、龋齿、牙齿缺失和全因死亡率之间的关联具有中介作用.口腔就诊行为的中介作用在60岁以上的参与者中最为明显,但在60岁以下的参与者中并不明显.结论:促进良好的口腔就诊行为对预防与口腔健康相关的全身健康风险具有的公共卫生意义.年轻群体通过良好的口腔就诊行为改善全因死亡率的作用有限,应探索其他切实可行的措施.

摘要： 2024 年,《四川省国土空间规划(2021—2035 年)》《成都市国土空间总体规划(2021—2035 年)》相继获国务院批复.同年 11 月 2 日,四川省政府批复成都市所辖县(市、区)国土空间总体规划.至此,四川共批复21个市级总体规划、159 个县级总体规划(数量均居全国第一),成为除直辖市外全国首个省、市、县三级总体规划全部获批的省份.在此过程中,四川省自然资源系统坚决落实党中央、国务院关于"多规合一"的重大改革部署,在自然资源部的坚强领导下,认真履职尽责、攻坚克难,全力推进建立全省国土空间规划体系并监督实施.