Läs mer om sommarjobbet Thesis - Automatic linearization methods, Epiroc 2020 i Örebro. Längre ned på sidan kan du också hitta ifall det finns fler sommarjobb i Örebro inom samma yrke eller från samma företag.
Epiroc is a leading productivity partner for the mining, infrastructure and natural resources industries. With cutting-edge technology, Epiroc develops and produces innovative drill rigs, rock excavation and construction equipment, and provides world-class service and consumables. The company was founded in Stockholm, Sweden, and has passionate people supporting and collaborating with customers in more than 150 countries. Learn more at www.epirocgroup.com.
Thesis Automatic linearization methods 2020
Epiroc is a leading productivity partner for the mining, infrastructure and natural resources industries. With cutting-edge technology, Epiroc develops and produces innovative drill rigs, rock excavation and construction equipment, and provides world-class service and consumables.
Epiroc Rock Drills AB in Örebro with over 2500 employees both develop, manufacture and market rock drilling equipment for mining and construction work all over the world. As a thesis student you will have the opportunity to work in an open and friendly environment, where we are committed to always find new innovative solutions through collaboration both within the team and externally. Join our journey towards developing future technology within electrification and automation.
Functional area: Measurement Technique, Rocktec Division
Recruiting manager: Mikael Lorin, Global Manager Measurement Technique
Phone: +46(0)19-670 7389
Other contacts: Martin J Persson, +46(0)19-676 5909, firstname.lastname@example.org
* Industrial engineering
* Electrical engineering
* IT/Computer science
Level of thesis project: Bachelor thesis.
Number of students in the project: 1 student
This project is intended to improve linearization in measurement systems.
Epiroc’s Measurement technique group performs measurements and develops sensors and measurement methods.
One of our customized sensors has a built-in linearization function based on a number of polynomials, which are placed at user defined points during a calibration process. At verification of the calibration the linearization is evaluated. If the errors are considered to be too large, another set of points can be selected and the calibration restarts. This iterative method is not optimal and can be time consuming.
Another sensor reads a repetitive pattern and calculates a position with significantly higher resolution than the pattern. Today, calibration of the linearization is performed in a test setup.
Your first mission is to develop an automatic linearization method based on the raw values from a large number of points and the relationship to ground truth. The method shall find the optimal points for the linearization polynomials resulting in a minimized linearization error.
Your second mission is to develop an automatic linearization method for the repetitive pattern that at best can be performed during operation without the need for a separate test setup. This will include error estimation and finding the linearization function that globally minimizes the error in the operating range.
The work includes implementing the methods, evaluate them versus today's performance and report your work (written and oral).
This project will be considered a success when methodologies and tools to perform accurate calibration that reduce the linearization error, give an estimate of the overall error and speed up the calibration process are available.
Implementation is preferably performed in Matlab, but alternatives can be discussed.
We are looking for a Bachelor student with both theoretical and practical skills. The candidate needs knowledge in interpolation and estimation methods, programming, and Matlab.
How to apply:
Does this sound interesting, and do you feel this is a match? Log in to the recruitment system. If you are new to the system, you need to start by making a profile. Do not forget to attach your CV and a short letter about your-self, describing why you are applying for this thesis. Please note that we do not accept applications via email. Send your application as soon as possible, but no later than November 14th.