Master Thesis Blade tip timing method: adv measurement data processing.

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.


The challenge
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
Work Plan:
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:
V. Kharyton and all, A Discussion on the Advancement of Blade Tip Timing Data Processing, ASME Turboexpo 2017 paper GT2017-63138
D. 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 Energy is one of the world’s leading energy technology companies. The company works with its customers and partners on energy systems for the future, thus supporting the transition to a more sustainable world. With its portfolio of products, solutions and services, Siemens Energy covers almost the entire energy value chain – from power generation and transmission to storage. The portfolio includes conventional and renewable energy technology, such as gas and steam turbines, hybrid power plants operated with hydrogen, and power generators and transformers. More than 50 percent of the portfolio has already been decarbonized. A majority stake in the listed company Siemens Gamesa Renewable Energy (SGRE) makes Siemens Energy a global market leader for renewable energies. An estimated one-sixth of the electricity generated worldwide is based on technologies from Siemens Energy. Siemens Energy employs 91,000 people worldwide in more than 90 countries and generated revenue of around €29 billion in fiscal year 2019. In Sweden Siemens Energy has 2600 employees in 10 locations.
At Siemens we value diversity by inclusion and by cooperating with people with different mindset, background, experience, competence and personal traits – in all organisational levels.
Read more about Siemens here:
www.siemens-energy.com.


Application
Do not hesitate - apply today via https://jobs.siemens-energy.com/jobs refnr 220506 and no later than November 6th. For questions about the role please contact recruiting manager John Andersson +46 (0) 122 81620 or project responsible Vsevolod Kharyton +46 (0) 725 345188.
Place of work: Finspång

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