Online frequency estimation with applications to engine and generator sets. (July 2017) - Manngård, Mikael; Böling, Jari M.
Highlights: The problem of online frequency estimation is considered. A survey of the sliding time window DFT and Goertzel filter is presented. A new method based on IIR filters and exponential forgetting is proposed. Methods are validated on simulations and on data from a marine engine-generator set. Abstract: Frequency and spectral analysis based on the discrete Fourier transform is a fundamental task in signal processing and machine diagnostics. This paper aims at presenting computationally efficient methods for real-time estimation of stationary and time-varying frequency components in signals. A brief survey of the sliding time window discrete Fourier transform and Goertzel filter is presented, and two filter banks consisting of: (i) sliding time window Goertzel filters (ii) infinite impulse response narrow bandpass filters are proposed for estimating instantaneous frequencies. The proposed methods show excellent results on both simulation studies and on a case study using angular speed data measurements of the crankshaft of a marine diesel engine-generator set.