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TOOLS FOR QUALITY TESTING OF BATCHES OF ARTIFACTS: THE CRYOGENIC THERMOMETERS FOR THE LHC
Author(s) -
Daniela Ichim,
Franco Pavese,
C. Ballé,
J. Casas-Cubillos
Publication year - 2001
Publication title -
cern document server (european organization for nuclear research)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1142/9789812811684_0023
Subject(s) - large hadron collider , quality (philosophy) , cryogenic temperature , computer science , nuclear engineering , process engineering , materials science , engineering , nuclear physics , physics , quantum mechanics , composite material
In the processing of data series, such as in the case of the resistance R vs. temperature T calibrations of the thermometers (several thousands) necessary for the LHC new accelerator at CERN, it is necessary to use automatic methods for determining the quality of the acquired data and the degree of uniformity of the thermometer characteristics, that are of the semiconducting type. In addition, it must be determined if the calibration uncertainties comply with the specifications in the wide temperature range 1,6 – 300 K. Advantage has been taken of the fact that these thermometers represent a population with limited variability, to apply a Least Squares Method with Fixed Effect. This allows to fit the data of all the thermometers together, by taking into account the individuality of each thermometer in the model as a deviation from one of them taken as reference Ri = f(Ti) + bk0 + bk1 g(Tki) + bk1g(Tki) 2 + ... where f(Ti) is the model valid for all i data and all k thermometers, while the subsequent part is the “fixed effect” model for the k-th thermometer, where g(T) is a suitable function of T. This method is shown in the paper applied to different stages of the data processing. First, for efficient compensation for the thermal drift occurring during acquisition, robust against the occurrence of outliers. Second, for detection of clusters of thermometers with inherently different characteristics. Finally, for optimisation of the calibration-point distribution.

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