Rotor blade is one of the most significant components of helicopters. But due to its highspeed rotation characteristics, it is difficult to collect the vibration signals during the flight stage.Moreover, sensors are h...Rotor blade is one of the most significant components of helicopters. But due to its highspeed rotation characteristics, it is difficult to collect the vibration signals during the flight stage.Moreover, sensors are highly susceptible to damage resulting in the failure of the measurement.In order to make signal predictions for the damaged sensors, an operational modal analysis(OMA) together with the virtual sensing(VS) technology is proposed in this paper. This paper discusses two situations, i.e., mode shapes measured by all sensors(both normal and damaged) can be obtained using OMA, and mode shapes measured by some sensors(only including normal) can be obtained using OMA. For the second situation, it is necessary to use finite element(FE) analysis to supplement the missing mode shapes of damaged sensor. In order to improve the correlation between the FE model and the real structure, the FE mode shapes are corrected using the local correspondence(LC) principle and mode shapes measured by some sensors(only including normal).Then, based on the VS technology, the vibration signals of the damaged sensors during the flight stage can be accurately predicted using the identified mode shapes(obtained based on OMA and FE analysis) and the normal sensors signals. Given the high degrees of freedom(DOFs) in the FE mode shapes, this approach can also be used to predict vibration data at locations without sensors. The effectiveness and robustness of the proposed method is verified through finite element simulation, experiment as well as the actual flight test. The present work can be further used in the fault diagnosis and damage identification for rotor blade of helicopters.展开更多
The continuous development of smart agriculture puts forward the requirement of high accuracy slope path tracking for the agricultural wheel-legged robot.Compared to flat terrain,path tracking control on sloped terrai...The continuous development of smart agriculture puts forward the requirement of high accuracy slope path tracking for the agricultural wheel-legged robot.Compared to flat terrain,path tracking control on sloped terrain faces the obstacle of motion instability of the wheel-legged robot induced by the slope gravitational force component,which causes instantaneous steering center to offset.To address this problem,this study proposed a slope path tracking control algorithm by combining the methods of virtual sensing radar and two-level neural network.Firstly,the kinematic and dynamic models of the wheel-legged robot are deduced,from which the crucial factors affecting control accuracy of slope path tracking are recognized.Secondly,this study constructs the slope path tracking control algorithm,in which the virtual sensing radar is utilized to realize route perception,and the two-level neural network is employed to provide drive motors’speeds to adapt to path tracking on different slopes.Furthermore,the corresponding compensation methods of the identified impacting factors are embedded in the proposed algorithm,including the lateral tracking deviation factor,heading angle deviation factor,slope change factor,and slip rate factor.Finally,the co-simulation model of slope path tracking control is constructed,including the multi-body dynamic model of the wheel-legged robot in RecurDyn and the proposed slope path tracking algorithm complied by Python.Subsequently,the simulation tests of the wheel-legged robot are carried out under various slope angles and velocities.The results reveal that the proposed algorithm’s effectiveness and accuracy are superior,with tracking errors reduced by more than 47.2%compared to an optimized pure pursuit algorithm.展开更多
Over the last few decades,cross-fertilization between marketing and fandom studies in a mediated world has been rare,hindering the knowledge development for marketing practitioners in the Chinese fan economy context.T...Over the last few decades,cross-fertilization between marketing and fandom studies in a mediated world has been rare,hindering the knowledge development for marketing practitioners in the Chinese fan economy context.The purpose of this study is to find and establish a conceptual framework that includes Online Interaction(OI),Parasocial Relationships(PSR)and virtual fan communities on Weibo,and how these contributory factors embedded in the interplay process of digital fandom practices in terms of enhancing fans’Purchase Intention(PI)and media consumption behaviours toward the celebrities’merchandise.Using an online survey instrument,this research collected 294 completed responses from fans who had online interactions with celebrities and engagement of virtual fan communities on Weibo.Key results and findings provided a clear framework of four antecedents based on the conceptual model and indicated that the high intensity of OI led to higher levels of the perception of PSR and the Sense of Virtual Community(SOVC).Increased PSR and the SOVC can be seen as significant positive predictors of the PI(a part of consumer identity construction as a fan)also.This study revealed the underlying mechanism of an emerging marketing genre,also provide useful implications of audiences’digital marketing practices for marketers,celebrities and policymakers.展开更多
基金supported by grants from the High-Level Oversea Talent Introduction Plan,Chinathe Special Fund for Basic Scientific Research in Central Universities of China-Doctoral Research and Innovation Fund Project,China(No.3072023CFJ0206).
文摘Rotor blade is one of the most significant components of helicopters. But due to its highspeed rotation characteristics, it is difficult to collect the vibration signals during the flight stage.Moreover, sensors are highly susceptible to damage resulting in the failure of the measurement.In order to make signal predictions for the damaged sensors, an operational modal analysis(OMA) together with the virtual sensing(VS) technology is proposed in this paper. This paper discusses two situations, i.e., mode shapes measured by all sensors(both normal and damaged) can be obtained using OMA, and mode shapes measured by some sensors(only including normal) can be obtained using OMA. For the second situation, it is necessary to use finite element(FE) analysis to supplement the missing mode shapes of damaged sensor. In order to improve the correlation between the FE model and the real structure, the FE mode shapes are corrected using the local correspondence(LC) principle and mode shapes measured by some sensors(only including normal).Then, based on the VS technology, the vibration signals of the damaged sensors during the flight stage can be accurately predicted using the identified mode shapes(obtained based on OMA and FE analysis) and the normal sensors signals. Given the high degrees of freedom(DOFs) in the FE mode shapes, this approach can also be used to predict vibration data at locations without sensors. The effectiveness and robustness of the proposed method is verified through finite element simulation, experiment as well as the actual flight test. The present work can be further used in the fault diagnosis and damage identification for rotor blade of helicopters.
基金supported by the National Key R&D Program of China(Grant No.2022YFD2202102)the Key Laboratory of Modern Agricultural Intelligent Equipment in South China,Ministry of Agriculture and Rural Affairs,China.
文摘The continuous development of smart agriculture puts forward the requirement of high accuracy slope path tracking for the agricultural wheel-legged robot.Compared to flat terrain,path tracking control on sloped terrain faces the obstacle of motion instability of the wheel-legged robot induced by the slope gravitational force component,which causes instantaneous steering center to offset.To address this problem,this study proposed a slope path tracking control algorithm by combining the methods of virtual sensing radar and two-level neural network.Firstly,the kinematic and dynamic models of the wheel-legged robot are deduced,from which the crucial factors affecting control accuracy of slope path tracking are recognized.Secondly,this study constructs the slope path tracking control algorithm,in which the virtual sensing radar is utilized to realize route perception,and the two-level neural network is employed to provide drive motors’speeds to adapt to path tracking on different slopes.Furthermore,the corresponding compensation methods of the identified impacting factors are embedded in the proposed algorithm,including the lateral tracking deviation factor,heading angle deviation factor,slope change factor,and slip rate factor.Finally,the co-simulation model of slope path tracking control is constructed,including the multi-body dynamic model of the wheel-legged robot in RecurDyn and the proposed slope path tracking algorithm complied by Python.Subsequently,the simulation tests of the wheel-legged robot are carried out under various slope angles and velocities.The results reveal that the proposed algorithm’s effectiveness and accuracy are superior,with tracking errors reduced by more than 47.2%compared to an optimized pure pursuit algorithm.
文摘Over the last few decades,cross-fertilization between marketing and fandom studies in a mediated world has been rare,hindering the knowledge development for marketing practitioners in the Chinese fan economy context.The purpose of this study is to find and establish a conceptual framework that includes Online Interaction(OI),Parasocial Relationships(PSR)and virtual fan communities on Weibo,and how these contributory factors embedded in the interplay process of digital fandom practices in terms of enhancing fans’Purchase Intention(PI)and media consumption behaviours toward the celebrities’merchandise.Using an online survey instrument,this research collected 294 completed responses from fans who had online interactions with celebrities and engagement of virtual fan communities on Weibo.Key results and findings provided a clear framework of four antecedents based on the conceptual model and indicated that the high intensity of OI led to higher levels of the perception of PSR and the Sense of Virtual Community(SOVC).Increased PSR and the SOVC can be seen as significant positive predictors of the PI(a part of consumer identity construction as a fan)also.This study revealed the underlying mechanism of an emerging marketing genre,also provide useful implications of audiences’digital marketing practices for marketers,celebrities and policymakers.
