|Table of Contents|

Comparison method of energy transfer characteristics for fault detection of vehicle suspension spring(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2013年04期
Page:
51-
Research Field:
载运工具运用工程
Publishing date:

Info

Title:
Comparison method of energy transfer characteristics for fault detection of vehicle suspension spring
Author(s):
DING Jian-ming LIN Jian-hui ZHAO Jie HUANG Chen-guang
State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, Sichuan, China
Keywords:
vehicle engineering suspension spring spring fault harmonic wavelet packet decomposition scale energy transfer characteristics dynamic detection
PACS:
U279.3
DOI:
-
Abstract:
The frequency shift characteristics of suspension transfer function under different spring stiffnesses were analyzed, and a new dynamic detecting method of vehicle suspension spring fault was developed. The vertical vibration accelerations of car body and bogie at the locations installed with suspension springs were respectively decomposed by seven-layer harmonic wavelet packet, and the eight low scales energies were calculated. The suspension's scale energy transfer characteristics were got through the division of car body and frame acceleration energies in each scale. The comparison method of suspension's scale energy transfer characteristics in adjacent periods was constructed to achieve the failure detection of suspension spring. Detection result shows that suspension's energy transfer characteristic changes to high scale due to spring stiffness metamorphosis, which is consistent with the conclusion drawn from the detection mechanism analysis to low frequency change, and the method correctly detects suspension failure with 10% stiffness metamorphosis. Therefor, the method has high reliability and good engineering applicability. 9 figs, 14 refs.

References:

[1] 程海涛,丁旭杰.装用SW-160型转向架客车动力学性能优化分析[J].中国铁道科学,2004,25(2):66-71. CHENG Hai-tao, DING Xu-jie. Dynamics performance optimization analysis of passenger cars equipped with SW-160 bogie[J]. China Railway Science, 2004, 25(2): 66-71.(in Chinese)
[2] 池茂儒,张卫华,曾 京,等.高速客车转向架悬挂参数分析[J].大连交通大学学报,2007,28(3):13-19. CHI Mao-ru, ZHANG Wei-hua, ZENG Jing, et al. Study of suspension parameter of high speed passenger car bogies[J]. Journal of Dalian Jiaotong University, 2007, 28(3): 13-19.(in Chinese)
[3] 赵 娜,曹登庆.铁道车辆含故障参数的非线性动力学模型[J].振动与冲击,2009,28(6):122-125,199.ZHAO Na, CAO Deng-qing. Nonlinear dynamical model with fault parameters for railway vehicles[J]. Journal of Vibration and Shock, 2009, 28(6): 122-125, 199.(in Chinese)
[4] LI P, GOODALL R, KADIRKAMANATHAN V. Estimation of parameters in a linear state space model using a Rao-Blackwellised particle filter[J]. IEE Proceedings—Control Theory and Application, 2004, 151(6): 727-738.
[5] LI P, GOODALL R, WESTON P, et al. Estimation of railway vehicle suspension parameters for condition monitoring[J]. Control Engineering Practice, 2006, 15(1): 43-55.
[6] KADIRKAMANATHAN V, LI P, JAWARD M H, et al. Particle filtering-based fault detection in nonlinear stochastic systems[J]. International Journal of Systems Science, 2002, 33(4): 259-265.
[7] HAYASHI Y, TSUNASHIMA H, MARUMO Y. Fault detection of railway vechicle suspension systems using multiple-model approach[J]. Journal of Mechanical Systems for Transportation and Logistics, 2008, 1(1): 88-99.
[8] MEI T X, DING X J. A model-less technique for the fault detection of rail vehicle suspensions[J]. Vehicle System Dynamics, 2008, 46(S): 277-287.
[9] BRUNI S, GOODALL R, MEI T X, et al. Control and monitoring for railway vehicle dynamics[J]. Vehicle System Dynamics, 2007, 45(7/8): 743-779.
[10] NEWLAND D E. Harmonic wavelet analysis[J]. Proceedings: Mathematical and Physical Sciences, 1993, 443(10): 203-225.
[11] YAN R Q, GAO R X. An efficient approach to machine health diagnosis based on harmonic wavelet packet transform[J]. Robotics and Computer-Integrated Manufacturing, 2005, 21(4/5): 291-301.
[12] 丁建明,林建辉,任 愈,等.基于谐波小波能量熵的轴承故障实时诊断[J].机械强度,2011,33(4):483-487. DING Jian-ming, LIN Jian-hui, REN Yu, et al. Real-time diagnosis of bearing faults based on harmonic wavelet energy entropy[J]. Journal of Mechanical Strength, 2011, 33(4): 483-487.(in Chinese)
[13] 陈 果.一种改进的谐波小波及其在转子故障诊断中的应用[J].机械工程学报,2011,47(1):8-16. CHEN Guo. An improved harmonic wavelet and its application to rotor faults diagnosis[J]. Journal of Mechanical Engin-eering, 2011, 47(1): 8-16.(in Chinese)
[14] 翟婉明.车辆-轨道垂向系统的统一模型及其耦合动力学原理[J].铁道学报,1992,14(3):10-21. ZHAI Wan-ming. The vertical model of vehicle-track system and its coupling dynamics[J]. Journal of the China Railway Society, 1992, 14(3): 10-21.(in Chinese)

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Last Update: 2013-08-30