Most diagnostic algorithms of mechanical systems are based on empirical observations derived from actual measurements of vibration patterns. In this study, a different approach was examined. This approach is based on the assumption that reliable dynamic models can be utilized to predict the effects of faults on vibration patterns. Among the benefits of the proposed approach are increased understanding of various phenomena as expressed in vibration patterns, enhanced quality of the diagnostic algorithms and possibly reduced effort and cost related to extensive seeded tests. In the study, a simple spur gear transmission system is modelled and analysed. In the first stage, a non-linear dynamic model of a spur gear transmission was developed. In the second stage, an analytical method was proposed to estimate the gear mesh stiffness as a function of mesh angle in both cases of healthy and of faulty gears. The dynamic response of the system was computed applying the gear mesh stiffness derived from the analytic model. The model was applied to simulate the theoretical vibration response in healthy and spalled tooth gearwheels. The dynamic responses derived from the model were compared to and verified with experimental vibration data. The experimental phase included varying load and speed settings, allowing the examination of the fault effect on the vibration signature at different test conditions.
|State||Published - 1 Jan 2014|
|Event||11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014 - Manchester, United Kingdom|
Duration: 10 Jun 2014 → 12 Jun 2014
|Conference||11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM 2014 / MFPT 2014|
|Period||10/06/14 → 12/06/14|