摘要
高速道岔检修是高铁维保工作的重要环节,道岔检修技术不断革新,这对工务人员提出新的要求。针对这一问题,文中提出基于BIM和虚拟现实技术相结合的铁路道岔检测培训系统。该系统以高速铁路18号道岔检测为研究对象,结合数字化建模和渲染技术,以虚拟现实交互设备和三维互动引擎Unity为基础进行开发。文中基于Kmeans和改进KNN算法建立成绩评估模型,对学员的培训成绩进行定量、客观地评估,改进的KNN算法是在多维数据中考虑欧式距离、余弦距离和马氏距离对数据相似度的影响因素。实际应用表明,所开发的铁路道岔检测虚拟现实培训系统能够满足学员道岔结构认知、道岔检测流程沉浸式体验的需求,对于提升道岔检测培训效率、节约培训成本具有十分重要的意义。
High-speed turnout maintenance is an important part of high-speed railway maintenance work.The continuous innovation of turnout maintenance technology puts new demands on public workers.In response to this problem,this paper proposes a railway turnout detection training system based on the combination of BIM and virtual reality technology.The system takes the detection of high-speed railway No.18 turnout as the research object,combines digital modeling and rendering technology,and is developed on the basis of virtual reality interactive equipment and three-dimensional interactive engine Unity.This paper establishes a performance evaluation model based on K-means and improved KNN algorithm to quantitatively and objectively evaluate trainees’training performance.The improved KNN algorithm considers euclidean distance,cosine distance,and mahalanobis distance as infulence factors to data similarity in multi-dimensional data.Practical applications show that the developed railway turnout detection virtual reality training system can meet the needs of trainees for cognition of turnout structure and immersive experience of turnout detection process.It is of great significance for improving the efficiency of turnout detection training and saving training costs.
作者
张超
何越磊
娄小强
校颖浩
叶鹏
ZHANG Chao;HE Yue-lei;LOU Xiao-qiang;XIAO Ying-hao;YE Peng(School of Urban Rail Transportation,Shanghai University of Engineering Science,Shanghai 201620,China)
出处
《物流工程与管理》
2021年第4期83-87,68,共6页
Logistics Engineering and Management
基金
国家自然科学基金项目(51978393)
甘肃省科技计划资助(19ZD2FA001)
上海工程技术大学科研创新项目(19KY1006)。
