User independent tool for the analysis of data from tensile testing for database systems

Nima Babaei, Jing Wang, Elisabeth Kisseler,Marc Ackermann, Sebastian Wipp,Alexander Gramlich,Ulrich Krupp

MATERIALS TESTING(2024)

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摘要
Data streams in science and economy are becoming increasingly automatized. This has various advantages compared to previous, user-dependent analyses, in which the same results are analyzed differently by different persons. Even though these differences are only of a certain degree, they can lead to false estimations of underlying material and process parameters as well as to missing comparability. In order to automatize previously user-dependent processes in the analysis of material tests, a modular database management system, called idCarl, has been developed. This system places a module as analysis pipeline between the experimental machine and the database. The database management system can be expanded with diverse modules, enabling the generation of user-independent data, which are fed automatically into the database. To provide an example, a module is applied to the common procedure of tensile testing based on DIN EN ISO 6892 and CWA 15261-2. The module determines automatically Young's modulus and other parameters derived thereof. The method for determining the measurement uncertainties of the Young's modulus is improved and compatibility with the "Guide to the expression of uncertainty in measurement" (GUM) is achieved. The existing method in ISO and CWA standards provides in some cases an underestimation of about 112 %.
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关键词
machine learning,tensile testing,measurement uncertainty,user independent analysis,database management systems
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