Multi-Objective Parameter Optimization of Flexible Support System of Optical Mirror

During the processing of an optical mirror, the performance parameters of the bottom support system would affect the surface forming accuracy of the mirror. The traditional bottom support system has a large unadjustable support stiffness, which increases the difficulty of unloading the impact force generated by the grinding disc. In response to this scenario, a flexible support system (FSS) consisting of 36 support cylinders with beryllium bronze reeds (BBRs) and rolling diaphragms (RDs) as key components is designed. It is necessary to analyze the key components of the support cylinder to reduce its axial movement resistance, ensure a consistent force output of each support point. First, the internal resistance model of a flexible support cylinder is established, and the main factors of internal resistance are then analyzed. Thereafter, the multi-objective structural parameters of the BBR and RD are simulated in ANSYS using the control variable method. The optimal structural parameters of BBR and RD are determined by simulation. Finally, experiments are performed on the RD ultimate pressure, internal resistance of the support cylinder, and consistency of the force output of the FSS. The experimental results show that the support cylinder with the optimized design has good force output consistency, which provides a theoretical basis for the application of FSS in optical mirror processing.Transport Engineering and Logistic

Identifying and Characterizing Conveyor Belt Longitudinal Rip by 3D Point Cloud Processing

Real-time and accurate longitudinal rip detection of a conveyor belt is crucial for the safety and efficiency of an industrial haulage system. However, the existing longitudinal detection methods possess drawbacks, often resulting in false alarms caused by tiny scratches on the belt surface. A method of identifying the longitudinal rip through three-dimensional (3D) point cloud processing is proposed to solve this issue. Specifically, the spatial point data of the belt surface are acquired by a binocular line laser stereo vision camera. Within these data, the suspected points induced by the rips and scratches were extracted. Subsequently, a clustering and discrimination mechanism was employed to distinguish the rips and scratches, and only the rip information was used as alarm criterion. Finally, the direction and maximum width of the rip can be effectively characterized in 3D space using the principal component analysis (PCA) method. This method was tested in practical experiments, and the experimental results indicate that this method can identify the longitudinal rip accurately in real time and simultaneously characterize it. Thus, applying this method can provide a more effective and appropriate solution to the identification scenes of longitudinal rip and other similar defects.Transport Engineering and Logistic