Hendrik Pfeifer,
"A Visual Analytics Approach to Sensor Analysis for End-of-Line Testing"
, in TU Darmstadt, 10-2019
Original Titel:
A Visual Analytics Approach to Sensor Analysis for End-of-Line Testing
Sprache des Titels:
Deutsch
Englische Kurzfassung:
End-of-Line testing is the final step of modern production lines that assures the quality of
produced units before they are shipped to customers. Automatically deciding between functional
and defective units as well as classifying the type of defect are main objectives. In this
thesis, a dataset consisting of three phase internal rotor engine simulations is used to outline
opportunities and challenges of Visual Analytics for End-of-Line testing.
At first the simulation data is visually analyzed to understand the influence of the simulation
input parameters. Afterwards features are extracted from the signals using discrete
Fourier transform (DFT) and discreteWavelet transform (DWT) to represent the different simulations.
Principal Component Analysis (PCA) is applied to further reduce the dimensionality
of the data to finally apply K-Means to cluster the datasets and also perform a classification
using a support vector machine (SVM). It is discussed which methods are beneficial for the
End-of-Line testing domain and how they can be integrated to improve the overall testing
process.