摘 要:随着国家主干道计划的实施、公路隧道的规模不断增加,所涉及的机电设备数量和种类也日益庞大。但国内对隧道机电设备的后续管理和维修体系尚未成熟,因此提出了 PHM 技术以完善现有体系,介绍了 PHM 系统建模的主要方法,分析了公路隧道机电设备的工作特性,提出了基于数据驱动的射流风机 PHM 建模方法,通过交叉验证完成了模型测试,证明了将PHM 技术运用到隧道运营中具有一定的可行性。
关键词:故障预测和健康管理;隧道机电;数据驱动;射流风机
中图分类号:U453.5 文献标识码:A 文章编号:2096-4706(2020)06-0120-04
The Application of PHM in Highway Tunnel Operation
SHEN Jiayi
(Zhejiang University of Science and Technology,Hangzhou 310013,China)
Abstract:With the implementation of the national trunk road plan,the scale of road tunnel is increasing,and the number and types of electromechanical equipment are also increasing. But domestic follow-up of tunnel mechanical and electrical equipment management and maintenance system is not yet mature. Therefore puts forward the fault prediction and health management (PHM)techniques to improve the existing system,introduced the main methods of PHM system modeling,analyzed the working characteristic of highway tunnel electromechanical equipment,put forward the modeling method based on data driven,cross validation completed test,proved the PHM technology applied to the tunnel operation has certain feasibility.
Keywords:failure prediction and health management;tunnel electro mechanical;data-driven;jet fan
参考文献:
[1] 佚名 . 截至 2017 年末中国大陆公路隧道数据 [J]. 隧道建设(中英文),2018,38(3):398.
[2] QU Y J,MING X G,QIU S Q,et al. An Integrative Framework for Online Prognostic and Health Management Using Internet of Things and Convolutional Neural Network [J].Sensors,2019,19(10).
[3] 曾声奎,Michael G.Pecht,吴际 . 故障预测与健康管理(PHM)技术的现状与发展 [J]. 航空学报,2005(5):626-632.
[4] 李春 . 故障预测与健康管理(PHM)技术介绍 [J]. 中国高新技术企业,2008(15):43-44.
[5] HESS A,CALVELLO G,DABNEY T. PHM a key enabler for the JSF autonomic logistics support concept [C]// IEEE Aerospace Conference. IEEE,2004:3543-4549.
[6] BYINGTON C.S,ROEMER M.J,GALIE T. Prognostic enhancements to diagnostic systems for improved condition-based maintenance [C]//Aerospace Conference Proceedings,IEEE,2002:2815-2824.
[7] SUTHARSSAN T,STOYANOV S,BAILEY C,et al. Prognostic and health management for engineering systems:a review of the data-driven approach and algorithms [J]. The Journal of Engineering,2015.
[8] PECHT M,JAAI R. A prognostics and health management roadmap for information and electronics-rich systems [J]. Microelectronics Reliability,2010,50(3):317-323.
[9] PECHT M,GU J. Physics-of-failure-based prognostics for electronic products [J]. Transactions of the Institute of Measurement and Control,2009,31(3-4):309-322.
[10] 杨超,王志伟 . 公路隧道通风技术现状及发展趋势 [J].地下空间与工程学报,2011,7(4):819-824.
[11] 倪伟,李世立 . 基于振动分析的射流风机故障诊断与健康监测方法 [J]. 现代信息科技,2019,3(17):140-142+144.
[12] 李永亮 . 基于机器学习的故障预测与健康管理(PHM)方法研究 [D]. 成都:电子科技大学,2017.
[13] 柏帆 . 支持向量机辅助卡尔曼滤波在不动产实地调查技术中的研究 [D]. 南京:东南大学,2018.
作者简介:沈家怡(1995-),男,汉族,浙江宁波人,研究生在读,研究方向:隧道机电。