MATLAB Based Analysis Software
Develop a MATLAB based analysis software GUI to convert .IDE files to .MAT and then leverage the MATLAB runtime to provide efficient, yet powerful, analysis capabilities.
Many of our customers, who are largely mechanical engineers, use MATLAB for their data analysis needs. Not only do they have familiarity with MATLAB, but MATLAB offers some performance advantages for processing of large arrays.
- Convert IDE files with all data to .MAT
- FFT, PSD, spectrogram
- Integration, double integration
- Moving metrics (RMS, peak-to-peak, max, min, mean)
- Phase response to FFT
- Filtering (Butterworth, Bessel, Elliptical, moving average, convolution)
- Find peaks routine to characterize shock events
- Compile Tom Irvine's MATLAB GUI and integrate with this analysis package
- Initial release of file conversion and basic plotting and analysis (FFT, PSD, spectrogram)
- Second release with advanced analysis as laid out above (integration, find peaks etc.)
- Third release to incorporate Tom Irvine's GUI
- Host and share the source code on GitHub
Cost to the Customer
This will be offered for free along with the source code.
- Shock testing to then optimize design: A customer is looking to design a new passenger rescue boat that can survive ejection from the larger ship. When the boat impacts the water there is a significant shock event that is a product of many internal resonances in the boat as well as the rigid body motion of the boat itself. The engineering team would like to not only filter out the higher frequency data, they also need to perform a shock response spectrum analysis to better understand how to effectively design improved support structures.
- Vibration testing to ensure electronics survivability: A customer is looking to design a new consumer robotic system. The robot can induce significant vibrations that the team need to understand and then simulate in the lab to ensure the electronics can survive. The shaker system they have in the lab requires a simplified PSD. They would like to take raw data to clean, apply a safety factor, and then use to simulate in the lab.