Development of Operational Transfer Path Effects Removal Tools for Enhanced Diagnostics and Prognostics of Rotating Machinery Critical Components

The vibration-based technique is a well-established and widely used measurement technique for condition monitoring, diagnostics, and prognostics of rotating machinery critical components, such as bearings, gears, blades, etc. Significant advancements in various algorithms and tools development have been demonstrated by the research community in the last decades to predict the faults that might be present in those components. 

However, modern rotating machines still pose more challenges in the context of vibration-based condition monitoring for diagnostics and prognostics as their design and operating conditions are more complex than conventional rotating machines.

One of the open challenges in vibration-based condition monitoring is to effectively remove the operational transfer path effects between the fault and sensor locations that bury the sought signature related to the fault development. This problem is even more escalated for machines that operate under varying operating conditions. Hence, the system representing the transfer path between the fault and sensor location can be treated as a time-varying system.

This PhD project will focus on developing and demonstrating advanced tools for removing the operational transfer path effects for enhancing vibration-based diagnostics and prognostics of the critical components of rotating machinery. More focus will be on the planetary gearbox applications. The student will have the opportunity to work with experts in advanced signal processing, data analytics, machine dynamics/vibration, condition monitoring, prognostics, and health management field, as well as be part of our strong and dynamic research centre at Cranfield University.

At a glance

• Application deadline26 Apr 2023
• Award type(s)PhD
• Start date05 Jun 2023
• Duration of award3 years
• EligibilityUK, EU, Rest of World
• Reference numberSATM346

Supervisor
Dr Agusmian Ompusunggu
Entry requirements

• Should have a minimum of a first or second-class UK honours degree or equivalent in a related discipline (e.g., mechanical, electrical, computer science, manufacturing, aerospace, and automotive) with a minimum 65% mark in the Project element or equivalent with a minimum 65% overall module average.
• Should have the potential to engage in innovative research and to complete the PhD within a three-year period of study.
• Must have a minimum of English language proficiency (IELTS overall minimum score of 6.5).

Also, the candidate is expected to:

• Have excellent analytical, reporting and communication skills
• Be self-motivated, independent and a team player
• Be genuine enthusiasm about the subject and technology
• Have the willingness to publish research findings in international journals

Funding

This is a self-funded opportunity so the student would need to source their own funding. However, a bursary can be considered for an exceptional candidate. The application is open to UK and international students.Find out more about tuition fees.

Cranfield Doctoral Network

Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network.  This network brings together both research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities.

How to apply

Before completing the application documentation, please contact

[email protected]

for an initial informal discussion about this opportunity.