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
The purpose of this paper is to describe and demonstrate the validity of a methodology to distinguish, in the performances of high education institutions （HEIs）, real from perceived performances. The extension of ac...The purpose of this paper is to describe and demonstrate the validity of a methodology to distinguish, in the performances of high education institutions （HEIs）, real from perceived performances. The extension of accountability to the evaluation of educational programs involves significant topics concerning the gap between perceived and real performances. It means that, since many actors such as teachers, students, and external stakeholders are involved in the process, the research on methodologies to distinguish subjective from objective parameters is still on the floor. Debate about performance evaluation in this collaboration is still in progress particularly as it concerns the proposal of several parameters and indexes to quantify the topic and reduce the subjectivism in the assessment and the gap between real and perceived performances. After describing and discussing an evaluation model based on three interdependent typologies of indexes, this will be tested in two Tempus projects having the purpose of activating Ph.D. and masters courses. The results encourage deepening researches in this direction and disseminating this methodology and extending and enriching the validation process.展开更多
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.
文摘The purpose of this paper is to describe and demonstrate the validity of a methodology to distinguish, in the performances of high education institutions （HEIs）, real from perceived performances. The extension of accountability to the evaluation of educational programs involves significant topics concerning the gap between perceived and real performances. It means that, since many actors such as teachers, students, and external stakeholders are involved in the process, the research on methodologies to distinguish subjective from objective parameters is still on the floor. Debate about performance evaluation in this collaboration is still in progress particularly as it concerns the proposal of several parameters and indexes to quantify the topic and reduce the subjectivism in the assessment and the gap between real and perceived performances. After describing and discussing an evaluation model based on three interdependent typologies of indexes, this will be tested in two Tempus projects having the purpose of activating Ph.D. and masters courses. The results encourage deepening researches in this direction and disseminating this methodology and extending and enriching the validation process.
