The very cool thing about sigma-delta conversion is that there are trade-offs that can be made with the data after it is captured – sampling rate versus inherent filtering versus resolution versus noise floor. These are all inter-related.
ERLPhase wanted to investigate travelling wave fault location. Technicians captured mock fault data in the lab, which I modelled in Python, performing analysis on the frequency content, and various processing techniques. I developed a proprietary front-end amplifier in LTspice, then implemented the circuit on a proof-of concept PCB. I wrote Python scripts to import the fault data into an Arbitrary Waveform Generator (often called “an ARB”), and played them into the new board, captured the data on the sigma-delta modulator evaluation board, post-processing the captured data in Python (including wavelet analysis), and displayed the results graphically in 2-D, 3-D and colour plots.
I wrote a report on the effort, providing details and outlining the path of product development.