Failure models for transmission gears health monitoring PhD

The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics.

Lack of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing zone in a very complex manner and lead the modelling to an imperfect zone of assumptions. These complexities allow the researchers to use approximations for useful lifetime calculations.

Based on modelling approximations and assumptions, several models have been introduced in academic research domain. But still the models are failure specific and have considered surface failures (i.e. scuffing and pitting) and bending fatigue separately. Practically, there is a very high possibility that a gear is operated under an influence of both types of failures and hence reaches to its breakage well before the life estimated by a failure specific model. Due to this, a model considering the theoretical aspects of both types of failures can reflect more practicality of gear meshing and can provide more good estimation of useful life.

In this research, a theory will be postulated for the combined mode of gear failures. The theory will be supported by the basic gear failure mathematics and preliminary validation will be done by comparing the results with the existing failure theories. The theoretical mathematical representation will further be used to develop a gear testing simulation. This simulation will test the model on different combination of critical operational parameters. Finally, experimentation will be performed on real gears for the validation.

Supervisors: Dr Muhammad Khan and Professor Andrew Starr.

Entry Requirements:
- A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, and manufacturing) with a minimum 60% mark in the Project element or equivalent with a minimum 60% overall module average
- The potential to engage in innovative research and to complete the PhD within a three-year period of study
- A minimum of English language proficiency (IELTS overall minimum score of 6.5)
- Excellent analytical, reporting and communication skills
- Self-motivated, independent and team player
- Genuine enthusiasm for the subject and technology
- Willingness to publish research findings in international journals

Funding: Self-funded.

Duration: 3 years.

Research students at Cranfield benefit from being part of the Cranfield Doctoral Network, which brings together research students and staff, providing a platform to share ideas, identify opportunities for collaboration, and create smaller communities of practice. Students are also expected to attend the Doctoral Researchers' Core Development (DRCD) Programme, comprising four 1-week units covering key stages of the research journey.