In order to study the dynamic characteristics of multilayer fiber reinforced plastic(MFRP)shaft,the coupling model of three-dimensional equivalent bending stiffness theory and transfer matrix method is established,and...In order to study the dynamic characteristics of multilayer fiber reinforced plastic(MFRP)shaft,the coupling model of three-dimensional equivalent bending stiffness theory and transfer matrix method is established,and the influence of thickness-radius ratio,length-radius ratio,layer angles,layer proportion,and stacked approaches on MFRP shaft dynamic characteristics is investigated.The result shows that the proposed coupling model has high accuracy in MFRP shaft dynamic performance prediction.The proportion of small-angle layers is the decisive factor of MFRP shaft natural frequency.With the increase of thickness-radius ratio and length-radius ratio,the natural frequency of MFRP shaft decreases.The natural frequency of MFRP shaft with the angle layers combination of±45°and±90°is smaller compared with the metal shaft no matter in simple/free boundary condition or simple/simple supported boundary condition.展开更多
Glass fibre-reinforced(GFR)structure is extensively used in radome,spoiler and some other equipment.In engineering practice,due to the influence of wear,aging,impact,chemical corrosion of surface structure and other f...Glass fibre-reinforced(GFR)structure is extensively used in radome,spoiler and some other equipment.In engineering practice,due to the influence of wear,aging,impact,chemical corrosion of surface structure and other factors,the internal structure of this kind of structure gradually evolves into a defect state and expands to form defects such as bubbles,scratches,shorts,cracks,cavitation erosion,stains and other defects.These defects have posed a serious threat to the quality and performance of GFR structure.From the propagation process of GFR structure defects,its duration is random and may be very short.Therefore,designing a scientific micro defect intelligent detection system for GFR structure to enhance the maintainability of GFR structure will not only help to reduce emergencies,but also have positive theoretical significance and application value to ensure safe production and operation.Firstly,the defect detection mechanism of GFR structure is discussed,and the defect detection principle and defect area identification method are analyzed.Secondly,the processing process of defect edge signal is discussed,a classifier based on MLP is established,and the algorithm of the classifier is designed.Finally,the effectiveness of this method is proved by real-time monitoring and defect diagnosis of a typical GFR structure.The experimental results show that this method improves the efficiency of defect detection and has high defect feature recognition accuracy,which provides a new idea for the on-line detection of GFR structure defects.展开更多
文摘In order to study the dynamic characteristics of multilayer fiber reinforced plastic(MFRP)shaft,the coupling model of three-dimensional equivalent bending stiffness theory and transfer matrix method is established,and the influence of thickness-radius ratio,length-radius ratio,layer angles,layer proportion,and stacked approaches on MFRP shaft dynamic characteristics is investigated.The result shows that the proposed coupling model has high accuracy in MFRP shaft dynamic performance prediction.The proportion of small-angle layers is the decisive factor of MFRP shaft natural frequency.With the increase of thickness-radius ratio and length-radius ratio,the natural frequency of MFRP shaft decreases.The natural frequency of MFRP shaft with the angle layers combination of±45°and±90°is smaller compared with the metal shaft no matter in simple/free boundary condition or simple/simple supported boundary condition.
基金Guangdong Provincial University Key Special Project Fund(No.2020zdzx2032)National Entrepreneurship Practice Fund(No.202013684009s)。
文摘Glass fibre-reinforced(GFR)structure is extensively used in radome,spoiler and some other equipment.In engineering practice,due to the influence of wear,aging,impact,chemical corrosion of surface structure and other factors,the internal structure of this kind of structure gradually evolves into a defect state and expands to form defects such as bubbles,scratches,shorts,cracks,cavitation erosion,stains and other defects.These defects have posed a serious threat to the quality and performance of GFR structure.From the propagation process of GFR structure defects,its duration is random and may be very short.Therefore,designing a scientific micro defect intelligent detection system for GFR structure to enhance the maintainability of GFR structure will not only help to reduce emergencies,but also have positive theoretical significance and application value to ensure safe production and operation.Firstly,the defect detection mechanism of GFR structure is discussed,and the defect detection principle and defect area identification method are analyzed.Secondly,the processing process of defect edge signal is discussed,a classifier based on MLP is established,and the algorithm of the classifier is designed.Finally,the effectiveness of this method is proved by real-time monitoring and defect diagnosis of a typical GFR structure.The experimental results show that this method improves the efficiency of defect detection and has high defect feature recognition accuracy,which provides a new idea for the on-line detection of GFR structure defects.
