Mid Sweden University

In condition monitoring based on vibrations for rotating machines fault detection, one of the typical symptoms is the presence of repetitive transients, which are characterized by impulsive and cyclostationarity signature. The approach quite popular nowadays in the industry for their detection is time–frequency techniques. Those techniques are mainly analysis tools instead of processing tools, and in any case, they are unable to offer a versatile methodology that applies to all mechanical signals in all circumstances. On the one hand, the paper is motivated by ideas borrowed from thermodynamics, where transients are seen as departures from a state of equilibrium; it is proposed to measure the negentropy of the squared envelope (SE) and the squared envelope spectrum (SES) of the signal. On the other hand, the paper proposes an adequate approach to exploit methods such as spectral correlation and kurtogram. The work's main objective is to investigate connections in those approaches to capture the signature of this repetitive behavior. The methodology used in this paper proposes to display as images all three proposed techniques. The impulsive events are then detected and localized in frequency by high values of the squared envelope spectrum (SES) infogram in some frequency bands. In order to analyze the signal in the frequency domain, the Short-Time Fourier Transform (STFT) is then used. The STFT is suggested in this study due to its simplicity and high flexibility. For fault, such as bearings, Kurtogram was demonstrated to be efficient. However, kurtosis based on temporal signals is effective under some conditions; its performance is low in the presence of a low signal-to-noise ratio. The paper analyzed the case of Ball Pass Frequency Inner Race (BPFI), where bearings are housed in a casing allowing the shaft to rotate while driven by a variable speed electric motor. A radial load is applied using a hydraulic cylinder, and different sizes of defects are realized. For fault like BPFI, the negentropy gives more information even for a shallow size of fault and allows a prompt fault detection, and it can also be used for fault localization. The paper demonstrated that results obtained from negentropy through infograms combining with spectral correlation could significantly extend the domain of the applicability of the Kurtogram. © 2021 Elsevier Ltd