Advertisement

Journal of Failure Analysis and Prevention

, Volume 17, Issue 4, pp 812–822 | Cite as

A Study on Dynamic Response and Diagnosis Method of the Wear on Connecting Rod Bush

  • Zhinong Jiang
  • Zhiwei Mao
  • Yidan Zhang
  • Jinjie Zhang
Technical Article---Peer-Reviewed

Abstract

Wear is a typical failure form for mechanical parts of a reciprocating compressor. The clearance of a connecting rod bearing will exceed the normal value due to the wear caused by poor lubrication or abnormal loads. Wear on the small-end bush of a connecting rod (SEBCR) in a reciprocating compressor is still a hard work to be monitored and diagnosed. In this paper, we focus on the study of the dynamic response and diagnosis method on wear fault of SEBCR based on the dynamic simulation and vibration signal analysis. A rigid-flexible coupling model of a connecting rod has been built, and the connecting rod is treated as a flexible body. The clearance between the crosshead pin and the small-end bush of a connecting rod is taken into account. The simulation results show that abnormal clearance will affect the dynamic characteristic significantly, and high acceleration impacts will occur at the reversal points of the crosshead pin. Based on the dynamic response and signal feature extraction, a new diagnosis method calculating the amplitude and change rate of average vibration energy per crank angle to detect the wear fault is proposed. The experiment results on a reciprocating compressor show that the vibration of the compressor crosshead is consistent with numerical simulation results, and the method is capable of detecting the wear fault in real time. Research presented in this paper is significant in providing tools for diagnosing wear fault of reciprocating compressors.

Keywords

Reciprocating compressor Connecting rod Dynamic characteristic Feature extraction Wear fault 

List of symbols

c

Radial clearance

Rb

Radius of bearing

Rj

Radius of neck journal

ɛ

Deviation degree of center

e

Eccentricity

Fn

Normal contact force

K

Contact stiffness

d

Damping coefficient

δ

Depth of relative penetration

\( \dot{\delta } \)

Relative impact velocity

vc

Cylinder volume

xp

Displacement of piston

Ti

The absolute temperature of the gas in cylinder

γ

The polytropic index of the air gas

\( \dot{m}_{vi} \)

Mass flow rates in the suction process

Cdz

The variable coefficient

ρc

Density of the air in cylinder

L

The number of samples in one crank angle

Dei

Change rate of average vibration energy per crank angle

σb, σj

Material properties

vz

Poisson’s coefficient

Ez

Young’s modulus

Ff

Friction force

fmax

Maximum friction forces

μ(v)

Friction coefficient

μs

Static friction coefficient

μd

Dynamic friction coefficient

vs, vd

Threshold velocities

pc

Gas pressure

sc

Piston cross-sectional area

Tc

Temperature

pi

Absolute pressure of the gas in cylinder

\( \dot{m}_{vd} \)

Mass flow rates in the discharge process

βz

The flow direction parameter

Afz

The maximum flow area

si

The amplitude

ei

Average vibration energy per crank angle

LD, LB

The angle ranges of the TDC and BDC, respectively

Notes

Acknowledgments

This work was supported by the National High Technology Research and Development Program of China (863 Program) under Grant No. 2014AA041806 and the Fundamental Research Funds for the Central Universities (ZY1617).

References

  1. 1.
    B. Lu, Y. Li, X. Wu, et al., A review of recent advances in wind turbine condition monitoring and fault diagnosis, in The Power Electronics and Machines in Wind Applications, PEMWA (IEEE, 2009), pp. 1–7Google Scholar
  2. 2.
    S. Fossen, E. Gemdjian, L. Cornelius, et al., Radar based sensors—a new technology for real-time, direct temperature monitoring of crank and crosshead bearings of diesels and hazardous media reciprocating compressors, in Proceedings of the 35th Turbo-machinery Symposium (Texas A&M University, Houston, 2006), pp. 97–102Google Scholar
  3. 3.
    S.M. Schultheis, C.A. Lickteig, R. Parchewsky, Reciprocating compressor condition monitoring, in 36th Turbo-Machinery Symposium, College Station (2007), pp. 10–13Google Scholar
  4. 4.
    Q. Tian, C. Liu, M. Machado et al., A new model for dry and lubricated cylindrical joints with clearance in spatial flexible multi-body systems. Nonlinear Dyn. 64(1–2), 25–47 (2011)CrossRefGoogle Scholar
  5. 5.
    P. Flores, A parametric study on the dynamic response of planar multi-body systems with multiple clearance joints. Nonlinear Dyn. 61(4), 633–653 (2011)CrossRefGoogle Scholar
  6. 6.
    S. Erkaya, İ. Uzmay, Experimental investigation of joint clearance effects on the dynamics of a slider-crank mechanism. Multibody Syst. Dyn. 24(1), 81–102 (2010)CrossRefGoogle Scholar
  7. 7.
    O. Bauchau, J. Rodriguez, Modeling of joints with clearance in flexible multi-body systems. Int. J. Solids Struct. 39(1), 41–63 (2002)CrossRefGoogle Scholar
  8. 8.
    C.S. Liu, K. Zhang, R. Yang, The FEM analysis and approximate model for cylindrical joints with clearances. Mech. Mach. Theory 42(2), 183–197 (2007)CrossRefGoogle Scholar
  9. 9.
    Z.F. Bai, Y. Zhao, Dynamic behavior analysis of planar mechanical systems with clearance in revolute joints using a new hybrid contact force model. Int. J. Mech. Sci. 54(1), 190–205 (2012)CrossRefGoogle Scholar
  10. 10.
    A. Pioli, A. Strozzi, A. Baldini et al., Influence of the initial clearance on the peak stress in connecting-rod small ends. Proc. Inst. Mech. Eng. Part D J. Automob. Eng. 223(6), 769–782 (2009)CrossRefGoogle Scholar
  11. 11.
    A. Gummer, B. Sauer, Modeling planar slider-crank mechanisms with clearance joints in RecurDyn. Multibody Syst. Dyn. 31(2), 127–145 (2014)CrossRefGoogle Scholar
  12. 12.
    H.M. Lankarani, P.E. Nikravesh, Continuous contact force models for impact analysis in multi-body systems. Nonlinear Dyn. 5(2), 193–207 (1994)Google Scholar
  13. 13.
    P. Flores, J. Ambrósio, J.C.P. Claro et al., A study on dynamics of mechanical systems including joints with clearance and lubrication. Mech. Mach. Theory 41(3), 247–261 (2006)CrossRefGoogle Scholar
  14. 14.
    M. Elhaj, F. Gu, A.D. Ball et al., Numerical simulation and experimental study of a two-stage reciprocating compressor for condition monitoring. Mech. Syst. Signal Process. 22(2), 374–389 (2008)CrossRefGoogle Scholar
  15. 15.
    G.R. Price, K.K. Botros, Numerical and experimental analysis of the flow characteristics through a channel valve, in International Compressor Engineering Conference (1992), pp. 1215–1225Google Scholar
  16. 16.
    P. Flandrin, G. Rilling, P. Goncalves, Empirical mode decomposition as a filter bank. IEEE Signal Process. Lett. 11(2), 112–114 (2004)CrossRefGoogle Scholar
  17. 17.
    W.X. Yang, Interpretation of mechanical signals using an improved Hilbert–Huang transform. Mech. Syst. Signal Process. 22(5), 1061–1071 (2008)CrossRefGoogle Scholar
  18. 18.
    E.D. Stoenescu, D.B. Marghitu, Dynamic analysis of a planar rigid-link mechanism with rotating slider joint and clearance. J. Sound Vib. 266(2), 394–404 (2003)CrossRefGoogle Scholar
  19. 19.
    C.A. Papadopoulos, P.G. Nikolakopoulos, G.D. Gounaris, Identification of clearances and stability analysis for a rotor-journal bearing system. Mech. Mach. Theory 43(4), 411–426 (2008)CrossRefGoogle Scholar
  20. 20.
    D.S. Rao, B.S. Shenoy, R.S. Pai et al., Stability of tri-taper journal bearings under dynamic load using a non-linear transient method. Tribol. Int. 43(9), 1584–1591 (2010)CrossRefGoogle Scholar

Copyright information

© ASM International 2017

Authors and Affiliations

  • Zhinong Jiang
    • 1
  • Zhiwei Mao
    • 1
  • Yidan Zhang
    • 1
  • Jinjie Zhang
    • 1
  1. 1.Diagnosis and Self-Recovering Engineering Research CenterBeijing University of Chemical TechnologyBeijingChina

Personalised recommendations