direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Inhalt des Dokuments

Henrik Isernhagen, Helmut Neemann, Steffen Kühn and Clemens Gühmann (2007)

Intelligent Signal Processing in an Automated Measurement Data Analysis System

In: Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing (CIISP 2007), Honolulu, USA. IEEE, pages 83-87.

In the automotive sector a huge amount of measurement data is recorded for validation and safeguarding of vehicle components. These data has to be automatically evaluated for an effective data analysis. Therefore, we need a sophisticated approach, which offers a flexible and powerful parametrisation and different signal processing algorithms for multiple applications. In this paper software and signal evaluation modules for an automated analysis of vehicle measurement data are presented. The data can be evaluated signal or message based with a parametrisation with reusable XML templates. Exemplary, we describe three evaluation modules integrating different signal processing approaches: signal analysis using an analytical signal description in combination with fuzzy logic, an efficient sliding frequency detection and the detection of predefined patterns using a modified dynamic time warping algorithm. Furthermore, an approach for a connected evaluation in consideration of time correlation is presented. Concluding, we discuss a practical application.


The poster presentation can be found here:


Zusatzinformationen / Extras


Schnellnavigation zur Seite über Nummerneingabe

«Dezember 22»