基于任务相关性的机务虚拟维修系统的场景管理

计算机工程与科学

基于任务相关性的机务虚拟维修系统的场景管理

陈静杰,李浩

(中国民航大学电子信息与自动化学院,天津 300300)

收稿日期:2018-06-11 修回日期:2018-08-22 出版日期:2019-05-25 发布日期:2019-05-25
基金资助:
国家自然科学基金重点项目(60832011)；天津市科技攻关计划重点项目(06YFGZGX00700)；中央高校基本科研业务费专项(ZXH2012B001)

A scene management method based on

task relevance in virtual maintenance system

CHEN Jingjie，LI Hao

(College of Electronic Information and Automation,Civil Aviation University of China,Tianjin 300300,China)

Received:2018-06-11 Revised:2018-08-22 Online:2019-05-25 Published:2019-05-25

摘要/Abstract

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。

关键词: 虚拟维修系统, 任务相似度, TF-IDF, 场景管理, 伙伴系统, 帧率

Abstract:

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.

Key words: virtual maintenance system, task similarity, TF-IDF, scene management, buddy system, frame rate

陈静杰,李浩. 基于任务相关性的机务虚拟维修系统的场景管理[J]. 计算机工程与科学.

CHEN Jingjie，LI Hao.

A scene management method based on

task relevance in virtual maintenance system

[J]. Computer Engineering & Science.