Getting the most out of measurement data
A number of new functions have been added to the new version 14.0 of vSignalyzer from Vector. Electronic developers will now be able to benefit from a range measurement data visualisation functions for manual and automated analysis.
The software from Vector is able to read in data from network development, bus analysis and ECU calibration in all commonly used file formats. It can now even process very large MDF4.x measurement files with four gigasamples per signal or over 200,000 measurement parameters - such as those generated in test drives, test runs on test benches and laboratory measurement - with great speed.
Development software vSignalyzer enables time synchronous display of measurement signals, bus traces, GPS data and video or audio signals. New features of Version 14.0 include signal oriented offline analysis of Ethernet log files (BLF, PCAP, ARXML) via extended database support.
It is easy to execute quick evaluations of large data archives and search for special results in them. Even complex evaluation functions and data mining calculations can be started with just a few mouse clicks, and they run fully automatically. Specific data mining results from different measurement files can be documented in a single PDF document in vSignalyzer 14.0. The configurable print view offers a WYSIWYG interface to ensure predictable documentation format and content. Drag-and-drop functions make it a snap to copy data views to office programs like Word, PowerPoint or email, which accelerates the documentation of analysis results.
vSignalyzer comes complete with file converters for importing/exporting measurement data in all common file formats - including MDF, BLF, XLX, ASC, and CSV. Version 14.0 also supports GPS data in NMEA- 0183 standard format.
Measurement data from driver assistance systems (ADAS) can be displayed in video windows or on GPS maps with object overlays. Extended visualisation options for roadway curves, markings and sensor zones make it easy for ADAS developers to verify object recognition algorithms for a wide variety of (multi-) sensor systems.