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An Analysis of the Static and Dynamic Behavior of the Hydraulic Compensation System of a Multichannel Valve
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作者 Jikang Xu Ruichuan Li +5 位作者 Yi Cheng Yanchao Li Junru Yang chenyu feng Xinkai Ding Huazhong Zhang 《Fluid Dynamics & Materials Processing》 EI 2023年第7期1817-1836,共20页
Electro-hydraulic proportional valve is the core control valve in many hydraulic systems used in agricultural and engineering machinery.To address the problem related to the large throttling losses and poor stability ... Electro-hydraulic proportional valve is the core control valve in many hydraulic systems used in agricultural and engineering machinery.To address the problem related to the large throttling losses and poor stability typically associated with these valves,here,the beneficial effects of a triangular groove structure on the related hydraulic response are studied.A mathematical model of the pressure compensation system based on the power-bond graph method is introduced,and the AMESim software is used to simulate its response.The results show that the triangular groove structure increases the jet angle and effectively compensates for the hydrodynamic force.The steady-state differential pressure at the valve port of the new pressure compensation structure was 0.65 MPa.Furthermore,experimental results show that the pressure difference at the main valve port is 0.73 MPa,and that the response time is less than 0.2 s.It is concluded that the new compensation structure has good pressure compensation response characteristics. 展开更多
关键词 Electrohydraulic proportional valve spool shape pressure compensation valve port differential pressure response time
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Unsupervised subdomain contrastive adaptation for elevator fault diagnosis based on time-frequency feature attention mechanism segmentation
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作者 chenyu feng Hao SUN +6 位作者 Pengcheng XIA Chengjin QIN Zhinan ZHANG Cheng HE Bin ZHENG Jiacheng JIANG Chengliang LIU 《Science China(Technological Sciences)》 2026年第2期302-323,共22页
Existing elevator fault diagnosis algorithms have limited engineering applicability due to variations in working conditions and differences in equipment structures.To address this limitation,this study proposes an uns... Existing elevator fault diagnosis algorithms have limited engineering applicability due to variations in working conditions and differences in equipment structures.To address this limitation,this study proposes an unsupervised subdomain adaptation method based on a time-frequency feature attention mechanism,LMMD-based subdomain alignment,and contrastive local alignment.This enables the application of the diagnosis model across different working conditions and equipment types.First,a novel time-frequency feature attention mechanism assigns weights to vibration signals of varying dimensions.Second,the time series is transformed to obtain a three-channel time-frequency diagram.This diagram is input into the proposed dimension-segmentation cross-channel multihead self-attention framework to extract high-dimensional frequencydomain fault features.These features are concatenated with the time-domain features to obtain a global feature representation.Then,the extracted high-dimensional features are sent to the classification module to obtain the predicted labels for the source and target domains.Finally,after confidence filtering,the true labels from the source domain and the prediction labels from the target domain are fed into a dynamically weighted multilevel feature alignment module to promote proximity between similar fault features across domains while enhancing separation among different fault types.The validity and superiority of the proposed method were demonstrated through simulation experiments conducted on two types of manned escalator systems under multiple working conditions.For the most challenging transfer task,the proposed method achieved higher accuracy on the target domain test set than DANN,ADDA,C-CLCN,TFA-CCN,and TFA-LCN by 26.87%,24.72%,11.44%,28.94%,and 16.85%,respectively. 展开更多
关键词 time-frequency feature attention mechanism unsupervised domain adaptation fault diagnosis transfer learning passenger elevator
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