基于任务相关性的机务虚拟维修系统的场景管理
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摘要
为解决机务虚拟维修训练系统中场景、模型一次性全部加载速度慢、内存占用量高的问题,基于任务的相关性提出一种场景管理方法。使用TF-IDF算法获取系统中包含的虚拟维修任务工卡的相似度并进行划分。工卡的相似度越高表示所描述的虚拟维修场景、维修工具、维修对象等虚拟资源相关性越强。当在场景资源加载、内存分配时,将相关性大于68%的任务工卡描述的虚拟资源利用伙伴系统进行加载分配,对于相关性小于42%的任务场景,则在伙伴系统中申请一块内存,并将这块内存划分为内存池进行加载分配。而任务相关性介于42%～68%的任务场景用双动态双链表的方法进行管理。解决了传统虚拟维修训练系统中加载资源时没有维修资源相关性分配管理的不足,分配方法没有任务针对性的局限,避免了单独划分内存块的系统分配时间。实验结果表明,改进后的分配方法减少了17%内存占用量,并提高了17.57的帧率。
In order to solve the problem of slow loading speed and high memory uage when loading the scene and model at one time in the virtual maintenance training system of machine service, we propose a scene management method based on task relevance. The method uses the TF-IDF algorithm to get the similarity of each task card in the virtual maintenance system and then classify them. The high similarity of work cards indicates that the correlation between virtual resources such as virtual maintenance scene, maintenance tools and maintenance objects is stronger. When loading scene resources and allocating memory, the virtual resources described by the task cards with a relevance greater than 68% are loaded and distributed by the buddy system. The task scenarios with relevance less than 42% apply for a memory in the buddy system and then the memory is divided into memory pools. The sub scenes with a task reference between 42% and 68% are managed by the double dynamic double linked list. The proposed method solves the problem that the traditional virtual maintenance training system has to face. That is there lacks maintenance resource related allocation management when loading resources. The allocation method has no task-specific limitation, and avoids system allocation time for separate memory blocks. Experimental results show that the improved allocation method reduces memory usage by 17% and improves the frame rate by 17.57.
In order to solve the problem of slow loading speed and high memory uage when loading the scene and model at one time in the virtual maintenance training system of machine service, we propose a scene management method based on task relevance. The method uses the TF-IDF algorithm to get the similarity of each task card in the virtual maintenance system and then classify them. The high similarity of work cards indicates that the correlation between virtual resources such as virtual maintenance scene, maintenance tools and maintenance objects is stronger. When loading scene resources and allocating memory, the virtual resources described by the task cards with a relevance greater than 68% are loaded and distributed by the buddy system. The task scenarios with relevance less than 42% apply for a memory in the buddy system and then the memory is divided into memory pools. The sub scenes with a task reference between 42% and 68% are managed by the double dynamic double linked list. The proposed method solves the problem that the traditional virtual maintenance training system has to face. That is there lacks maintenance resource related allocation management when loading resources. The allocation method has no task-specific limitation, and avoids system allocation time for separate memory blocks. Experimental results show that the improved allocation method reduces memory usage by 17% and improves the frame rate by 17.57.
引文
[1] Sun Zhong-yun,Tian Tao,Su Feng.Design and application of virtual maintenance training system for auxiliary locomotive[J].Plant Maintenance Engineering,2017,13(1):99-102.(in Chinese)
[2] Guo Zhi-rong,Wang Qi-lin,Gao Feng.Research of key technology of virtual maintenance training system[J].Journal of Sichuan Ordnance,2018,39(1):118-122.(in Chinese)
[3] Mei Zhao,Shu Tao,Song Tao,et al.Design of equipment virtual maintenance training system[J].Fire Control & Command Control,2016,41(9):151-155.(in Chinese)
[4] Yang Yi-bin,Li Min,Xie Hong-wen.Desktop virtual maintenance training system based on Unity3D[J].Journal of Computer Applications,2016,36(S2):125-128.(in Chinese)
[5] Wu Jing-jing,Dai Zhi-chao.Development of massively multiplayer online role-playing games based on Unity3D[J].Computer Systems & Applications,2017,26 (10):133-138.(in Chinese)
[6] Li Sen.Research on interactive virtual maintenance method of helicopter[D].Tianjing:Civil Aviation University of China,2016.(in Chinese)
[7] Wang Qian ,Gao Bao-lu ,Gao Rui-jun,et al.LOD algorithm based on enclosing ball screen error of quad-tree[J].Microelectronics & Computer,2016,33(5):127-132.(in Chinese)
[8] Du Zhen-lin,Tang Wen-qing,Qin Li,et al.Improved small feature culling for large scale process plant model based on octree[J].Journal of Computer Applications,2017,37(9):2626-2630.(in Chinese)
[9] Song Min-chao,Li Shao-bo.A new embedded dynamic memory allocation algorithm[J].Journal of Computer Applications,2017,37(Z2):244-247.(in Chinese)
[10] Zhang Dong-pei.A multistage ROI division algorithm for large scale scene based on memory cost[J].Computer Knowledge and Technology,2014,33(12) :8059-8061.(in Chinese)
[11] Thomas L C.A survey of maintenance and replacement models for maintainability and reliability of multi-item systems[J].Reliability Engineering,1986,16(4):297-309.
[12] Liu Xiao-bai,Liang Hong,Wang Dan.Test modeling and analyzing of warship system product based on relevant model[J].Ship Science and Technology,2017,39(21):158-163.(in Chinese)
[13] Yang Yuan,Li Fang,Liu Zhen-yu,et al.Optimal grouping preventive maintenance of a system under dependencies[J].Engineering Journal of Wuhan University,2012,45(4):539-544.(in Chinese)
[14] Ma Tian,Li Hong-an,Ma Ben-yuan,et al.Key technology of 3D virtual maintenance training system[J].Journal of Graphics,2016,37(1):97-101.(in Chinese)
[15] Wang Dong.Application of virtual maintenance technology on accessibility analysis of civil aircraft’s APU[J].Aviation Maintenance & Engineering,2017(7):44-47.(in Chinese)
[16] Li Zhong-zhu,Ye Miao,Zhang Tang-ling.Correlation research on aircraft maintenance task and cards lengths and standard labor hours[J].Aviation Maintenance & Engineering,2016 (4):68-70.(in Chinese)附中文参考文献:
[1] 孙忠云,田涛,苏锋.辅助机务虚拟维修训练系统的设计与应用[J].设备管理与维修,2017,13(1):98-102.
[2] 郭志荣,王其林,高峰.虚拟维修训练系统关键技术研究[J].兵器装备工程学报,2018,39(1):118-122.
[3] 梅朝,舒涛,宋涛,等.武器装备虚拟维修训练系统设计[J].火力与控制指挥,2016,41(9):151-155.
[4] 杨壹斌,李敏,解鸿文.基于Unity3D的桌面式虚拟维修训练系统[J].计算机应用,2016,36(S2):125-128.
[5] 吴晶晶,戴志超.基于Unity3D的多人在线网络游戏设计与开发[J].计算机系统应用,2017,26(10):133-138.
[6] 李森.直升机交互式虚拟维修方法研究[D].天津:中国民航大学,2016.
[7] 王倩,高保禄,高锐军,等.基于四叉树包围球和屏幕误差的LOD算法[J].微电子学与计算机,2016,33(5):127-132.
[8] 杜振林,唐卫清,覃力,等.基于八叉树的大规模流程工厂模型细节裁剪算法[J].计算机应用,2017,37(9):2626-2630.
[9] 宋敏超,李少波.一种新型嵌入式动态内存分配算法[J].计算机应用,2017,37(Z2):244-247.
[10] 张东培.基于内存占用的大规模场景的多级ROI分割算法[J].电脑知识与技术,2014,33(12):8059-8061.
[12] 刘晓白,梁鸿,王丹.基于相关性模型的舰船系统测试性建模与分析[J].舰船科学技术,2017,39(11):158-163.
[13] 杨元,黎放,刘振宇,等.基于相关性的系统预防性维修任务成组优化[J].武汉大学学报(工学版),2012,45(4):539-544.
[14] 马天,李洪安,马本源,等.三维虚拟维护训练系统关键技术研究[J].图学学报,2016,37(1):97-101.
[15] 王栋.虚拟维修技术在民用飞机辅助动力装置可达性分析上的应用[J].航空维修与工程,2017(7):44-47.
[16] 李中柱,叶苗,张唐岭.飞机维修工卡长度与标准工时的相关性研究[J].航空维修与工程,2016(4):68-70.
[2] Guo Zhi-rong,Wang Qi-lin,Gao Feng.Research of key technology of virtual maintenance training system[J].Journal of Sichuan Ordnance,2018,39(1):118-122.(in Chinese)
[3] Mei Zhao,Shu Tao,Song Tao,et al.Design of equipment virtual maintenance training system[J].Fire Control & Command Control,2016,41(9):151-155.(in Chinese)
[4] Yang Yi-bin,Li Min,Xie Hong-wen.Desktop virtual maintenance training system based on Unity3D[J].Journal of Computer Applications,2016,36(S2):125-128.(in Chinese)
[5] Wu Jing-jing,Dai Zhi-chao.Development of massively multiplayer online role-playing games based on Unity3D[J].Computer Systems & Applications,2017,26 (10):133-138.(in Chinese)
[6] Li Sen.Research on interactive virtual maintenance method of helicopter[D].Tianjing:Civil Aviation University of China,2016.(in Chinese)
[7] Wang Qian ,Gao Bao-lu ,Gao Rui-jun,et al.LOD algorithm based on enclosing ball screen error of quad-tree[J].Microelectronics & Computer,2016,33(5):127-132.(in Chinese)
[8] Du Zhen-lin,Tang Wen-qing,Qin Li,et al.Improved small feature culling for large scale process plant model based on octree[J].Journal of Computer Applications,2017,37(9):2626-2630.(in Chinese)
[9] Song Min-chao,Li Shao-bo.A new embedded dynamic memory allocation algorithm[J].Journal of Computer Applications,2017,37(Z2):244-247.(in Chinese)
[10] Zhang Dong-pei.A multistage ROI division algorithm for large scale scene based on memory cost[J].Computer Knowledge and Technology,2014,33(12) :8059-8061.(in Chinese)
[11] Thomas L C.A survey of maintenance and replacement models for maintainability and reliability of multi-item systems[J].Reliability Engineering,1986,16(4):297-309.
[12] Liu Xiao-bai,Liang Hong,Wang Dan.Test modeling and analyzing of warship system product based on relevant model[J].Ship Science and Technology,2017,39(21):158-163.(in Chinese)
[13] Yang Yuan,Li Fang,Liu Zhen-yu,et al.Optimal grouping preventive maintenance of a system under dependencies[J].Engineering Journal of Wuhan University,2012,45(4):539-544.(in Chinese)
[14] Ma Tian,Li Hong-an,Ma Ben-yuan,et al.Key technology of 3D virtual maintenance training system[J].Journal of Graphics,2016,37(1):97-101.(in Chinese)
[15] Wang Dong.Application of virtual maintenance technology on accessibility analysis of civil aircraft’s APU[J].Aviation Maintenance & Engineering,2017(7):44-47.(in Chinese)
[16] Li Zhong-zhu,Ye Miao,Zhang Tang-ling.Correlation research on aircraft maintenance task and cards lengths and standard labor hours[J].Aviation Maintenance & Engineering,2016 (4):68-70.(in Chinese)附中文参考文献:
[1] 孙忠云,田涛,苏锋.辅助机务虚拟维修训练系统的设计与应用[J].设备管理与维修,2017,13(1):98-102.
[2] 郭志荣,王其林,高峰.虚拟维修训练系统关键技术研究[J].兵器装备工程学报,2018,39(1):118-122.
[3] 梅朝,舒涛,宋涛,等.武器装备虚拟维修训练系统设计[J].火力与控制指挥,2016,41(9):151-155.
[4] 杨壹斌,李敏,解鸿文.基于Unity3D的桌面式虚拟维修训练系统[J].计算机应用,2016,36(S2):125-128.
[5] 吴晶晶,戴志超.基于Unity3D的多人在线网络游戏设计与开发[J].计算机系统应用,2017,26(10):133-138.
[6] 李森.直升机交互式虚拟维修方法研究[D].天津:中国民航大学,2016.
[7] 王倩,高保禄,高锐军,等.基于四叉树包围球和屏幕误差的LOD算法[J].微电子学与计算机,2016,33(5):127-132.
[8] 杜振林,唐卫清,覃力,等.基于八叉树的大规模流程工厂模型细节裁剪算法[J].计算机应用,2017,37(9):2626-2630.
[9] 宋敏超,李少波.一种新型嵌入式动态内存分配算法[J].计算机应用,2017,37(Z2):244-247.
[10] 张东培.基于内存占用的大规模场景的多级ROI分割算法[J].电脑知识与技术,2014,33(12):8059-8061.
[12] 刘晓白,梁鸿,王丹.基于相关性模型的舰船系统测试性建模与分析[J].舰船科学技术,2017,39(11):158-163.
[13] 杨元,黎放,刘振宇,等.基于相关性的系统预防性维修任务成组优化[J].武汉大学学报(工学版),2012,45(4):539-544.
[14] 马天,李洪安,马本源,等.三维虚拟维护训练系统关键技术研究[J].图学学报,2016,37(1):97-101.
[15] 王栋.虚拟维修技术在民用飞机辅助动力装置可达性分析上的应用[J].航空维修与工程,2017(7):44-47.
[16] 李中柱,叶苗,张唐岭.飞机维修工卡长度与标准工时的相关性研究[J].航空维修与工程,2016(4):68-70.