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Quantitative Performance Comparison of Thermal Structure Function Computations

Author

Listed:
  • Nils J. Ziegeler

    (Faculty of Electrical Engineering, South Westphalia University of Applied Sciences, 59494 Soest, Germany)

  • Peter W. Nolte

    (Fraunhofer Application Center for Inorganic Phosphors, Branch Lab of Fraunhofer Institute for Microstructure of Materials IMWS, 59494 Soest, Germany)

  • Stefan Schweizer

    (Faculty of Electrical Engineering, South Westphalia University of Applied Sciences, 59494 Soest, Germany
    Fraunhofer Application Center for Inorganic Phosphors, Branch Lab of Fraunhofer Institute for Microstructure of Materials IMWS, 59494 Soest, Germany)

Abstract

The determination of thermal structure functions from transient thermal measurements using network identification by deconvolution is a delicate process as it is sensitive to noise in the measured data. Great care must be taken not only during the measurement process but also to ensure a stable implementation of the algorithm. In this paper, a method is presented that quantifies the absolute accuracy of network identification on the basis of different test structures. For this purpose, three measures of accuracy are defined. By these metrics, several variants of network identification are optimized and compared against each other. Performance in the presence of noise is analyzed by adding Gaussian noise to the input data. In the cases tested, the use of a Bayesian deconvolution provided the best results.

Suggested Citation

  • Nils J. Ziegeler & Peter W. Nolte & Stefan Schweizer, 2021. "Quantitative Performance Comparison of Thermal Structure Function Computations," Energies, MDPI, vol. 14(21), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7068-:d:667383
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    Cited by:

    1. Nils J. Ziegeler & Peter W. Nolte & Stefan Schweizer, 2021. "Optimization-Based Network Identification for Thermal Transient Measurements," Energies, MDPI, vol. 14(22), pages 1-14, November.

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