STFT spectrogram based hybrid evaluation method for rotating machine transient vibration analysis. (1st June 2021)

• Record Type: Journal Article
• Authors: Manhertz, Gabor; Bereczky, Akos
• Is Part Of: Mechanical systems and signal processing. Volume 154(2021)
• Publication Date: 2021-06-01
• Subjects: Short-Time Fourier-Transformation -- Spectrogram image processing -- Component tracking -- Rotating machine -- Condition monitoring -- Transient analysis; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2020.107583
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A multidisciplinary analysis method for transient vibration evaluation. Short-Time Fourier-Transformation spectrogram image evaluation. Component tracking method development for frequency ridge detection on spectrogram image. Method validation on simulated and rotating machine vibration measurement signals. Abstract: The main purpose of this paper is to represent a methodenabling vibration components to be extracted from a high-resolution Short-Time Fourier-Transformation (STFT) based spectrogram assessed as an image to support transient analysis on rotating machines. Therefore, an improved STFT algorithm was developed to allocate and utilize computational memory more efficiently. The resulting spectrogram was compressed into a grey-scale image without any kind of information loss and was used for further image processing methods to obtain details about the vibration components. Furthermore, differential and moving average predictive tracking algorithms were developed for frequency ridge evaluation in the spectrogram image. For further analysis, the obtained results were transformed back with an inverse transformation method from image-space to time–frequency plane. Moreover, these results are able to be used to estimate the speed of rotation of the machine and to observe the frequency components. The methods were tested and validated with simulated signals and transient measurements on rotating machines. With the combination of vibration signal- and image processing techniques the evaluation time and computational resource requirements are decreased enhancing more efficient and accurate analysis, nevertheless opens the possibility of a real-time condition monitoring based on a basic vibration measurement.