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A library-based algorithm for evaluation of luminescent decay curves by shape recognition in time domain phosphor thermometry

Knappe, Christoph LU ; Pfeiffer, Kristin LU ; Richter, Mattias LU and Aldén, Marcus LU (2014) In Journal of Thermal Analysis and Calorimetry 115(1). p.545-554
Abstract
This work describes and characterizes an algorithm for the nonambiguous reduction of multiexponentially decaying luminescence signals to scalar values of corresponding calibration temperatures. Previous evaluation schemes in phosphor thermometry make use of an

intermediate step, where data reduction is achieved by fitting a model equation to phosphorescence decays in order to translate one or more fitting parameters into temperature. However, every slight mismatch between model equation and experimental data may lead to substantial errors in connection to noise-related inaccuracies during

the retrieval of adequate fitting windows. Additionally, there is a need for fitting windows, capable of automatically adapting to largely... (More)
This work describes and characterizes an algorithm for the nonambiguous reduction of multiexponentially decaying luminescence signals to scalar values of corresponding calibration temperatures. Previous evaluation schemes in phosphor thermometry make use of an

intermediate step, where data reduction is achieved by fitting a model equation to phosphorescence decays in order to translate one or more fitting parameters into temperature. However, every slight mismatch between model equation and experimental data may lead to substantial errors in connection to noise-related inaccuracies during

the retrieval of adequate fitting windows. Additionally, there is a need for fitting windows, capable of automatically adapting to largely varying signal time scales. In this context, the authors propose to set the fitting window length according to the time where the signal falls below a given percentage of the initial intensity. In comparison to fitting windows, defined by multiple decay times, modeling results suggest substantial precision benefits for as long as

signal-to-noise ratios stay above 4. Nevertheless, by comparing signal shapes of measured curves directly with a library of temperature-calibrated decay signals, all necessary assumptions on the mathematical description of measured signals become redundant and evaluation errors connected to uncertain fitting windows are largely circumvented. Resulting capabilities of the proposed signal shape recognition method (SSR) in terms of temperature precision and accuracy were compared to a conventional least-squares fitting approach, using a set of temperaturecalibrated phosphorescence decay signals from CdWO4. Accordingly, the SSR algorithm was found to reduce statistical temperature errors by at least 9 %. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Multiexponential decay, Lifetime, Decay time, Phosphor thermometry, Thermographic phosphors, Laser-induced phosphorescence
in
Journal of Thermal Analysis and Calorimetry
volume
115
issue
1
pages
545 - 554
publisher
Akademiai Kiado
external identifiers
  • wos:000329621100066
  • scopus:84893674534
ISSN
1588-2926
DOI
10.1007/s10973-013-3337-3
language
English
LU publication?
yes
id
e75e0f41-5ff9-4b71-a459-761b9fb23545 (old id 4022192)
alternative location
http://link.springer.com/article/10.1007%2Fs10973-013-3337-3
date added to LUP
2013-09-09 22:36:34
date last changed
2017-01-01 03:15:53
@article{e75e0f41-5ff9-4b71-a459-761b9fb23545,
  abstract     = {This work describes and characterizes an algorithm for the nonambiguous reduction of multiexponentially decaying luminescence signals to scalar values of corresponding calibration temperatures. Previous evaluation schemes in phosphor thermometry make use of an<br/><br>
intermediate step, where data reduction is achieved by fitting a model equation to phosphorescence decays in order to translate one or more fitting parameters into temperature. However, every slight mismatch between model equation and experimental data may lead to substantial errors in connection to noise-related inaccuracies during<br/><br>
the retrieval of adequate fitting windows. Additionally, there is a need for fitting windows, capable of automatically adapting to largely varying signal time scales. In this context, the authors propose to set the fitting window length according to the time where the signal falls below a given percentage of the initial intensity. In comparison to fitting windows, defined by multiple decay times, modeling results suggest substantial precision benefits for as long as<br/><br>
signal-to-noise ratios stay above 4. Nevertheless, by comparing signal shapes of measured curves directly with a library of temperature-calibrated decay signals, all necessary assumptions on the mathematical description of measured signals become redundant and evaluation errors connected to uncertain fitting windows are largely circumvented. Resulting capabilities of the proposed signal shape recognition method (SSR) in terms of temperature precision and accuracy were compared to a conventional least-squares fitting approach, using a set of temperaturecalibrated phosphorescence decay signals from CdWO4. Accordingly, the SSR algorithm was found to reduce statistical temperature errors by at least 9 %.},
  author       = {Knappe, Christoph and Pfeiffer, Kristin and Richter, Mattias and Aldén, Marcus},
  issn         = {1588-2926},
  keyword      = {Multiexponential decay,Lifetime,Decay time,Phosphor thermometry,Thermographic phosphors,Laser-induced phosphorescence},
  language     = {eng},
  number       = {1},
  pages        = {545--554},
  publisher    = {Akademiai Kiado},
  series       = {Journal of Thermal Analysis and Calorimetry},
  title        = {A library-based algorithm for evaluation of luminescent decay curves by shape recognition in time domain phosphor thermometry},
  url          = {http://dx.doi.org/10.1007/s10973-013-3337-3},
  volume       = {115},
  year         = {2014},
}