Improved gearbox simulations for diagnostic and prognostics purposes using finite element model reduction techniques

Abstract

Lumped parameter models (LPMs) are widely utilised to predict the dynamic behaviour of mechanical systems such as gearboxes. LPM gives reasonable representation of the dynamics of the system if masses can be lumped at certain locations, such as gears, shafts, bearings, etc. LPM have the advantage of simulating the structure using a limited number of degrees-of-freedom (DOF), which facilitates studying the behaviour of gears and bearings in the presence of nonlinearities and geometrical faults. However, it is difficult to account for the casing flexibility in the LPM models which is an important consideration in the lightweight structures such as in aircraft applications and this results in poor spectral matching over a wide frequency range. In the case of continuous systems, where masses are distributed equally over the structure (gearbox casing), other methods, such as finite element analysis, are often used to study the behaviour of the structure. The use of finite element model (FEM) results in a large number of DOF, which in turn complicates simulating the whole system’s response to the presence of nonlinearities and to gears and bearing faults. This in turn limits the validity of the simulated results and restricts their later usage in the diagnostics and prognostics of the gears and bearings. This paper describes the use of dynamic reduction technique to reduce the FEM of a gearbox casing into manageable and well representative DOF of the casing. The reduced model of the casing is embedded with the LPM of the internals (shafts, gears and bearings), which was previously developed with the aid of Simulink and has the capability of capturing stiffness nonlinearities arising from gears and bearings and has also the capability of simulating geometrical faults (spalls) for both gears and bearings. This paper mainly deals with the simulation of localised and extended inner race bearing faults. The results show the improvements obtained through combining the reduced model of the casing with the LPM model and a much better correspondence with measured signals.

Keywords:

• Bearing faults
• envelope analysis
• finite element analysis
• lumped parameter model
• model reduction techniques
• simulation
• spectral kurtosis

Additional information

Notes on contributors

L Deshpande

Lav Deshpande received his Bachelor of Mechanical Engineering in 1981 from the University of Pune, India, and Master of Technology in 1984 from the Indian Institute of Technology, Mumbai. He started his career as a Project Engineer in the Automotive Research Association of India. His main expertise is in the area of application of computer aided engineering and finite element based simulation tools in the product design and development of mechanical structures and components. He has more than 25 years of industry experience where he has worked as Senior Project Engineer, Team Leader and Business Development Manager. He has successfully completed several consulting projects in the automotive, mechanical, rail, mining and biomedical industries. Currently, he is working towards a PhD in “Diagnostics and Prognostics of Gears and Bearings” at the University of New South Wales under the supervision of Emeritus Professor Bob Randall and Dr Nader Sawalhi.

N Sawalhi

Nader Sawalhi received his BSc degree in mechanical engineering from the University of Jordan, Amman, Jordan, in 1997. He received his MEngSc degree and PhD in 2001 and 2007, respectively, all in mechanical engineering from the University of New South Wales (UNSW), Sydney. Between 1997 and 2003, he worked for Jordan cement factories as a predictive maintenance engineer and team leader. From 2003 to 2007 he worked on his PhD project at UNSW developing signal processing algorithms and simulation models for rolling element bearings in complex environments. The project under the supervision of Prof Bob Randall was fully supported by the Australian Defence Science and Technology Organisation (DSTO) as a part of its Centre of Expertise scheme. From 2007–2011 he has been working at the School of Mechanical and Manufacturing Engineering at UNSW as a research associate and lecturer. His research interests include signal processing, machine condition monitoring, diagnostics and prognostics, dynamic simulations of mechanical systems, and fluid structural interaction. Nader recently moved to work in Saudi Arabia and currently holds the position of assistant professor at the School of Mechanical engineering at Prince Mohammad Bin Fahd University in Khober.

R B Randall

Bob Randall is a visiting Emeritus Professor in the School of Mechanical and Manufacturing Engineering at the University of New South Wales (UNSW), Sydney, which he joined as a Senior Lecturer in 1988. Prior to that, he worked for the Danish company Bruel & Kjaer for 17 years, after 10 years’ experience in the chemical and rubber industries in Australia, Canada and Sweden. He was promoted to Associate Professor in 1996 and to Professor in 2001. He has degrees in Mechanical Engineering and Arts (Mathematics, Swedish) from the Universities of Adelaide and Melbourne, respectively. He is the invited author of chapters on vibration measurement and analysis in a number of handbooks and encyclopaedias, and a member of the editorial boards of four journals including Mechanical Systems and Signal Processing and Trans. IMechE Part C. His book Vibration-based Condition Monitoring was recently published by Wiley. He is the author of more than 190 papers in the fields of vibration analysis and machine diagnostics, and has successfully supervised 14 PhD and three Masters projects in those areas. Since 1996, he has been Director of the Defence Science and Technology Organisation’s Centre of Expertise in Helicopter Structures and Diagnostics at UNSW.