• Functional area:Research and Development
  • Country:Sweden
  • City:Stockholm
  • Company name:Atlas Copco Industrial Technique AB
  • Date of Posting:October 8, 2020
  • Last date to apply:November 30, 2020
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    Education requirement: Mechatronics / Electronics Engineering
    Level of thesis project: Master thesis
    Number of people needed: 2

    The objective is to investigate if it is feasible to estimate friction online during the tightening of threaded fasteners and to find the limitations of using Kalman filtering to estimate the clamp force.

    During the tightening of threaded fasteners in bolted joints it is of great interest to know the resulting clamp force in the joint. If the clamp force is known with a high certainty, it is possible to utilize the fastener to an optimal degree. Further enables the precise knowledge of the resulting clamp force potential for optimizing the joint from a design perspective, with criteria as lightweight construction or economic dimensions.

    During a pre study in cooperation with the Royal Institute of Technology in Stockholm (KTH) algorithms for estimating the friction coefficients during tightenings were developed. These algorithms enable the calculation of the clamp force with the help of the Kellerman-Klein equation. The basis of the algorithm is the extended and unscented Kalman filter. During the Thesis work the students are expected to work on the following tasks
    • Further develop and improve the algorithm
    • Test the algorithm on available recordings for tightenings
    • Carry out tightening experiments to obtain further training data
    • Implement the algorithms on real hardware for online friction estimation

    • Mechatronics or Electrical Engineering
    • Embedded Systems
    • Control theory, MATLAB and Simulink or similar
    • Digital Signal Processing
    • Kalman Filtering or Adaptive Filtering
    • Electrical drives

    Functional area: Atlas Copco, Tightening technique
    Recruiting Manager: Nils Dressler
    Phone: +46 (0)72 142 49 23
    Email: nils.dressler@atlascopco.com

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Master Thesis - Kalman Filtering to Estimate Friction and Clamp Force in Threaded Fasteners

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