On the use of transmissibility for the detection of damaged springs in the primary suspension of a locomotive

Author:

Millan Pedro Moreira Ordiales1ORCID,Pagaimo João Emanuel Carvalho1,Neves Costa João1ORCID,Maia Nuno Manuel Mendes1,Ambrósio Jorge Alberto Cadete1

Affiliation:

1. LAETA, IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

Abstract

The condition monitoring of the suspensions of railway vehicles is of utmost importance, allowing the reduction of the maintenance actions and the increase in the operational safety. However, the available methods often require a simplification of the vehicle through linearised models, a high number of sensors, or the use of complex algorithms that disregard the mechanical phenomena that explain the vehicle dynamics. This work suggests the Localized Transmissibility Damage Indicator (LTDI), based on the existing Transmissibility Damage Indicator (TDI), to detect damage in the springs of a locomotive, using pairs of sensors placed in the bogie frame and the axle boxes. For that purpose, multibody simulations are used to simulate the dynamic behaviour of the vehicle in tangent tracks under nominal and damaged conditions. The results from multibody simulations allow the calculation of the LTDI values for different levels of damage and various operation conditions, as well as the study of the effect of the variability inherent to the railway operation. The results show that the LTDI is significantly sensitive to damage. However, depending on the use of the lateral or vertical response, the LTDI is more suitable to detect the stiffness increase or decrease, or even to locate the damage. In conclusion, the LTDI is a promising method for the detection of damage on suspension elements of railway vehicles.

Funder

Horizon 2020 Framework Programme

Fundação para a Ciência e a Tecnologia

Publisher

SAGE Publications

Subject

Mechanical Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3