Fast fourier transform data compression for vibration applications

Abstract

A data compression method, system, and device for a vibration application can involve applying a Fast Fourier Transform (FFT) to raw vibration data to obtain FFT coefficients, classifying the FFT coefficients as high energy coefficients or low energy coefficients based on predetermined thresholds, quantizing the high energy coefficients using a first quantization and the low energy coefficients using a second quantization as quantized coefficients, and generating an indicator array to identify positions of the high energy coefficients and the low energy coefficients for use in packetizing the positions and the quantized coefficients and recovering lossy raw data from the quantized coefficients for data compression of the raw vibration data. The vibration application can include one or more battery-based internet-of-things (IOT) devices that can generate the raw vibration data. The raw vibration data is transferrable over a wireless communications protocol.