M.Sc. Diploma Thesis Project – Blade tip timing method: advanced measurement data processing

Job Description

Are you a master student planning to write your Master Thesis during spring 2020? Join us on our journey into the future #Siemens


Be part of an open and dynamic workplace where professional and personal development is high on the agenda. By making sustainable energy solutions more cost effective, developing new technologies for the future's smart industry and electrifying passenger and freight transport, we make reality of our vision of a sustainable world.


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 assignment:

This Master thesis project will be carried out in collaboration with Siemens Industrial Turbomachinery 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.



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.


Your Profile: 

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


Application:

Do not hesitate - apply today via siemens.se/jobb ref nr 187004 and no later than 2019-11-30. For questions about the role please contact recruiting manager John Andersson +46 (0) 122 81620.


Trade Union representatives:
Christine Lindström, Unionen, 0122-817 28
Simon Bruneflod, Sveriges Ingenjörer, 0122-842 24
Jan Lundgren, Ledarna, 0122-812 33
Kenth Gustavsson, IF Metall, 0122-815 25

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In this recruitment we renounce all calls relating to advertising and recruitment support.

 


Job ID: 187004

Organization: Gas and Power

Company: Siemens Industrial Turbomachinery AB

Experience Level: Student (Not Yet Graduated)

Job Type: Full-time

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