Intelligent spectrogram – A tool for analysis of complex non-stationary signals. (15th March 2022)

• Record Type: Journal Article
• Authors: Jablonski, Adam; Dziedziech, Kajetan
• Is Part Of: Mechanical systems and signal processing. Volume 167:Part A(2022)
• Publication Date: 2022-03-15
• Subjects: Signal processing -- Time-frequency analysis -- Self-adjusting spectrogram -- Optimum window length of the spectrogram; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2021.108554
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: Semi-automatic selection of window length and overlap parameters for STFT. STFT can be calculated for different window lengths and all are meaningful. Validation of method done on simulated signals. Verification of method done on industrial data. Three sets of parameters are used for calculation of STFT for industrial dataset. Abstract: The paper introduces the concept of Intelligent Spectrogram as a general tool for analysis of non-stationary signals. The method is based on a self-tuning mechanism, which automatically provides optimum window length of the spectrogram. The method calculates coefficients of variation (also known as relative standard deviation) for time and frequency scales and finds extremum value of their product. The proposed Intelligent Spectrogram might serve as an auxiliary tool for initial analysis of complex non-stationary signals, for which selection of particular window length might be beneficial for one class of signal components, but highly detrimental to others. The idea of the method is presented on a simulated signal, while its practical performance is illustrated on a real signal from a wind turbine run-down.