imc Test & Measurement has launched imc FAMOS 2024 data analytics software, offering enhanced user experience and updated data analytics capabilities for engineers, researchers and technicians in industries including automotive, machinery, rail and aerospace.
New features in the software include a start page that allows users to launch and customize a number of FAMOS wizards and tools, as well as new data analysis functions that can be performed directly within the curve window (useful for quick evaluation while working with large data sets) and formatting options for polar plots.The new features are designed to simplify the processing of large data sets, from visualization and analysis to the creation of professional reports.
You have direct access to FAMOS tools and wizards, such as FAMOS code for import/export filters, Python or R code, templates for GUI elements, and educational demo projects, all from a customized start page. Frequently used sequences and project files can also be linked to the page individually.
The new Data Analysis feature allows you to select individual data segments within a window and calculate them using standard functions, enabling interactive browsing and helping you to understand the displayed data set more quickly.
Polar diagrams also provide more advanced formatting options for better visualization of acoustic data, directional characteristics, wind energy, and rotationally symmetric structures.Text data and arrays for applications where the measurement data contains text elements, such as diagnostic and error messages or fieldbus data, can also be edited and displayed in the software.
“With imc FAMOS, even new users can quickly learn the basics of viewing measurement data, getting an overview and assessing its quality,” says Damian Hirschler, team leader in flight test equipment at Swiss aircraft manufacturer Pilatus Aircraft. “Measurement data can be transferred directly from imcSTUDIO to imc FAMOS, displayed in various ways in a few easy steps and automatically used for calculations by sequences. We are always impressed with the performance of imc FAMOS, even with very large data sets.”
