Master Thesis - Sensor modelling for anomaly detection

You will be part of the customer technical support team working close to the analysis developers of the remote diagnostic center. The customer technical support team are handling reactive and proactive support to customers around the globe operating both gas and steam turbines.

We are offering a role which is highly connected to the proactive work conducted by the remote diagnostic center. The assignment will be to conduct a sensor health algorithm connected to our empirical thermodynamic performance model. Today this model is configured to run daily for more than 350 gas turbines. Anomalies identified by this model can origin from various sources one of them being faulty sensors. The desired anomalies to identify is however connected to turbine degradation. To increase the robustness of this model and for this model to only identify performance degradation for the gas turbines a layer removing sensor failures needs to be added. This is where you come in!

The project can be performed by one or two students.

LET’S TALK ABOUT YOU

Your profile
* Student at MSc level with focus in mechanical engineering, control, applied physics, electrical engineering, computer science or similar.
* Have a good knowledge about signal processing.
* Is structured and communicates well.
* Dedicated and not afraid to find your own ways and solutions for challenges and problems.
* Master programming languages such as Python, R and similar.

Your responsibilitites
* Conduct a literature review over viewing the state of the art in sensor health/check algorithms.
* Investigate the sensors used as input in the thermodynamic model and suggest a method to develop the sensor health algorithm.
* Implement the algorithm in the analysis tool used within the remote diagnostic center (graphical programming interface interfacing Python and other script languages).
* Conduct an offline test run on historical data to verify the implemented solution.

Your opportunities for personal growth:
* Gain knowledge about the complexity of how to monitor an entire fleet without customizing the algorithms for individual assets.
* Gain knowledge in how to apply gas turbine performance modeling.
* Gain insight in the customer technical support division and how the teams constantly turn data into value for the end-customers.

LET’S TALK ABOUT US

"Let’s make tomorrow different today" is our genuine commitment at Siemens Energy to all customers and employees on the way to a sustainable future.

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.

Read more about Siemens Energy here:

www.siemens-energy.com

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Job & Career: https://www.siemens-energy.com/global/en/company/jobs.html

Application

Don’t hesitate – apply via https://jobs.siemens-energy.com/jobs, id nr 227996 not later than 2021-11-21.

We will request a copy of your completed courses in the application phase.

For questions about the role, please contact the recruiting manager
Fredrik Tengvall at fredrik.tengvall@siemens-energy.com or
Andreas Tunemar at andreas.tunemar@siemens-energy.com.

For questions about the recruitment process please contact the responsible recruiter
Nelly Johansson at nelly.johansson@siemens-energy.com.

Location: 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