M.Sc. Diploma Thesis Project – Blade tip timing method: advanced measurement data processing
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We are now looking for a student to take on the assignment M.Sc. Diploma Thesis Project – Blade tip timing method: advanced measurement data processing.
This Master thesis project will be carried out in collaboration with Siemens Energy AB in Sweden, one of the world leaders in the development, manufacturing and service of gas-turbines for industrial applications.
The aim of the study is the development and application of new approaches for the analysis of the measured vibration characteristics of bladed disks under different conditions, based on the Blade Tip Timing method (BTT). This research and development effort will be shared between the departments of Vibration & Acoustic and Structural Dynamics of Siemens in Sweden and globally.
Who are you?
You are someone in your last years studies with the specialization and interests related to digital signal processing, programming in general, math and physics since the proposed project scope would span over multi-disciplinary areas ensuring a gas-turbine engine operation
A well-known drawback of BTT is frequency aliasing. This is due to the low sampling rate, which is equal to the rotor speed for each probe. This drawback means that the data is effectively sampled non-uniformly. In the case of asynchronous vibrations (i.e. vibrations with a frequency that is not a multiple of the rotation speed) the vibration is measured at different phase angles at each revolution. If the measurement time is long enough, a complete picture of the vibration will eventually be captured but not in the correct order.
The digital signal processing research community has developed several anti-aliasing methods for non-uniformly sampled data. It has been shown that a band-limited signal can be uniquely determined from non-uniform samples, provided that the average sampling rate exceeds the Nyquist rate. Such approaches can be applied to solve the BTT aliasing problem.
A previous diploma thesis carried out a thorough initial investigation of several different methods for the analysis of BTT data. The successful candidate will:
- Investigate if the methods have been properly implemented.
- Identify the promising methods among the ones already studied.
- Carry out further development and refinement of these methods.
- The ultimate goal would be a complete methodology that can accurately and efficiently identify both synchronous and asynchronous blade vibrations for any bladed assembly.
It is required that the findings are documented in a thesis report (English language). Submission of results to a conference will be appreciated. Examples of dedicated publications would be:
- Kharyton and all, A Discussion on the Advancement of Blade Tip Timing Data Processing, ASME Turboexpo 2017 paper GT2017-63138
- Zachariah and P. Stoica, Online Hyperparameter-Free Sparse Estimation Method, EEE Transactions on Signal Processing 63(13): May 2015
Furthermore, the findings will be presented in a seminar internal to the company at the end of the work.
Why should you be working at Siemens?
Siemens steam- and gas turbines provides heat and light to the world!
Siemens is today one of the major companies within health care, energy and industry. Together we are approx 370.000 curious and competent employees in over 190 countries who are working with developing the future. You could be one of us – read more at Siemens.se.
At Siemens we value diversity by inclusion and by cooperating with people with different mindset, background, experience, competence and personal traits – in all organizational levels.
Do not hesitate - apply today via siemens.se/jobb ref nr 220506 and no later than October 31st.
For questions about the role please contact recruiting manager John Andersson +46 (0) 122 81620 or project responsible Vsevolod Kharyton +46 (0) 725 345188.
Trade Union representatives:
Veronica Andersson, Unionen, 0122-840 21
Simon Von Eckardstein, Sveriges Ingenjörer, 0122-842 24
Jan Lundgren, Ledarna, 0122-812 33
Jonny Persson, IF Metall, 0122-817 69
Organization: Siemens Energy
Company: Siemens Energy AB
Experience Level: Student (Not Yet Graduated)
Job Type: Either