Target Detection on Water Surfaces Using Fusion of Camera and LiDAR Based Information

To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle(USV)perception,this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection.Firstly,the visual recognition component employs an improved YOLOv7 algorithmbased on a self-built dataset for the detection of water surface targets.This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure,addressing the problemof excessive redundant information during feature extraction in the original YOLOv7 network model.Simultaneously,this modification simplifies the computational burden of the detector,reduces inference time,and maintains accuracy.Secondly,to tackle the issue of sample imbalance in the self-built dataset,slide loss function is introduced.Finally,this paper replaces the original Complete Intersection over Union(CIoU)loss function with the Minimum Point Distance Intersection over Union(MPDIoU)loss function in the YOLOv7 algorithm,which accelerates model learning and enhances robustness.To mitigate the problem of missed recognitions caused by complex water surface conditions in purely visual algorithms,this paper further adopts the fusion of LiDAR and camera data,projecting the threedimensional point-cloud data from LiDAR onto a two-dimensional pixel plane.This significantly reduces the rate of missed detections for water surface targets.

Structure Optimization of a Tesla Turbine Using an Organic Rankine Cycle Technology

The so-called ORC(Organic Rankine Cycle)heat recovery technology has attracted much attention with regard to medium and low temperature waste heat recovery.In the present study,it is applied to a Tesla turbine.At the same time,the effects of the disc speed,diameter and inter-disc gap on the internal flow field and output power of the turbine are also investigated by means of CFD(Computational Fluid Dynamics)numerical simulation,by which the pressure,velocity,and output efficiency of the internal flow field are obtained under different internal and external conditions.The highest efficiency(66.4%)is obtained for a number of nozzles equal to 4,a disk thickness of 1 mm,and a gap of 1 mm between the disks.The results of the study serve as a theoretical basis for the structural design and optimization of Tesla turbines.