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Intelligent Fault Diagnosis and Prognosis Solution for Rotating Machinery at Cranfield University - UCAS

Cranfield University

Degree level: Postgraduate

Intelligent Fault Diagnosis and Prognosis Solution for Rotating Machinery (Research)

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Course summary

This PhD project will focus on developing, evaluating, and demonstrating an intelligent solution of diagnosis and prognosis for rotating machinery to enhance safety, reliability, maintainability and readiness. A comprehensive test-bed for in-depth studies will be used for experiments for demonstration and evaluation. Rotating machinery has a fundamental role in many industries. Therefore, there is a need for a Condition-based maintenance (CBM) which holds the promise of predicting machinery maintenance requirements based on process performance measurements. Diagnostics and Prognostics are essential parts of CBM. Therefore, diagnostics and prognostics of rotating machinery can help to reduce machine downtime and cost. Many techniques such as vibration analysis, current signature analysis, acoustic emission analysis, wear and oil analysis,…,etc. have been used, through condition monitoring of the rotating machinery, to diagnose and prognosis different faults such as, bearing, crack shaft, gearbox, belt drive, reciprocating mechanism, mechanical rub, induction motor, pump, compressor, and fan. The student will have the opportunity to work with experts in the prognostics and condition monitoring field, as well as being part of our strong and dynamic research centre at Cranfield University.

Assessment method

Research project.


Entry requirements

A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, 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).; also, the candidate is expected to:; have excellent analytical, reporting and communication skills; be self-motivated, independent and team player; be genuine enthusiasm for the subject and technology; have the willing to publish research findings in international journals.


Fees and funding

Tuition fees

No fee information has been provided for this course

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

No additional fees or cost information has been supplied for this course, please contact the provider directly.
Intelligent Fault Diagnosis and Prognosis Solution for Rotating Machinery at Cranfield University - UCAS