Hilbert transform for covariance analysis of periodically nonstationary random signals with high-frequency modulation

Javorskyj, Ihor; Yuzefovych, Roman; Lychak, Oleh; Matsko, Ivan

doi:10.1016/j.isatra.2023.10.025

Cited by 7 publications

(2 citation statements)

References 47 publications

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Section: Methodsmentioning

confidence: 99%

“…However, in reality, the impulse signals caused by faults often cannot be described by a strictly periodic model. The latest discussions on this topic can be found in Javorskyj et al (2024aJavorskyj et al ( , 2024bJavorskyj et al ( , 2017, which use the periodically nonstationary random signal and periodic nonstationary random process to analyze the vibrations of faulty bearings. Early models of bearing vibration signals treated the fault-induced impulses as occurring in strict periodicity (McFadden and Smith, 1984), but the accuracy has been questioned, as discussed in Borghesani et al (2022) and Abboud et al (2019).…”

Section: Lock-in Amplifiermentioning

confidence: 99%

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Lock-in spectrum: a tool for representing long-term evolution of bearing fault in the time–frequency domain using vibration signal

Zhang

2024

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Purpose This study aims to propose a method for monitoring bearing health in the time–frequency domain, termed the Lock-in spectrum, to track the evolution of bearing faults over time and frequency. Design/methodology/approach The Lock-in spectrum uses vibration signals captured by vibration sensors and uses a lock-in process to analyze specified frequency bands. It calculates the distribution of signal amplitudes around fault characteristic frequencies over short time intervals. Findings Experimental results demonstrate that the Lock-in spectrum effectively captures the degradation process of bearings from fault inception to complete failure. It provides time-varying information on fault frequencies and amplitudes, enabling early detection of fault growth, even in the initial stages when fault signals are weak. Compared to the benchmark short-time Fourier transform method, the Lock-in spectrum exhibits superior expressive ability, allowing for higher-resolution, long-term monitoring of bearing condition. Originality/value The proposed Lock-in spectrum offers a novel approach to bearing health monitoring by capturing the dynamic evolution of fault frequencies over time. It surpasses traditional methods by providing enhanced frequency resolution and early fault detection capabilities.

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Section: Methodsmentioning

confidence: 99%