Abstract
Instantaneous frequency (IF) of shaft rotation is pivotal for bearing fault diagnosis under variable speed operations. However, shaft IF cannot always be measured as tachometers are not allowed to be installed in every case due to design reasons and cost concerns. Extracting the shaft IF ridge from time frequency representation (TFR) of vibration signals, therefore, becomes an alternative. Linear transform (LT), such as short time Fourier transform (STFT), has been widely adopted for such a purpose. Nevertheless, the accuracy of extracted IF ridges relies on the readability of TFR. Unfortunately, readability of TFR from STFT is often impaired by the smearing effect caused by non-synchronous frequencies between bases and signal components and limited time frequency resolution capability, which in turn adversely influences the accuracy of IF ridge extraction. To accurately extract IF ridges from vibration signals, this paper focuses on the first factor, which causes the smearing problem, and proposes a method named frequency matching linear transform (FMLT) to enhance the TFR, where transforming bases with frequencies varying with the shaft IF are constructed to alleviate the smearing effects. To construct the transforming bases with frequencies synchronous with shaft IF, a fast path optimization (FPO) algorithm, which generates all possible optimization paths among amplitude peaks and thereby ensures the continuity of extracted IF ridges, is adopted for IF pre-estimation. The TFR with improved readability can be subsequently obtained via FMLT, paving the way for accurate IF ridge extraction. Then, multiple IF ridges can be iteratively extracted using the FPO algorithm. The accuracy of extracted IF ridges before and after TFR enhancement is compared, indicating that the proposed FMLT can enhance the readability of TFR and lead to more accurate IF ridge extraction for bearing condition monitoring.
Highlights
Bearings are one of key components in rotating machinery; their fault detection and diagnosis have long been investigated to prevent severe equipment damage and unscheduled downtime [1].When a local fault occurs on the surface of the outer race, inner race or rolling elements, the measured vibration signals present repetitive fault impulses with exponential decay [2]
To accurately extract Instantaneous frequency (IF) ridges from vibration signals, this paper focuses on the first factor, which causes the smearing problem, and proposes a method named frequency matching linear transform (FMLT) to enhance the time frequency representation (TFR), where transforming bases with frequencies varying with the shaft IF are constructed to alleviate the smearing effects
With the literature reviewed above, the motivations of this paper are as follows: (1) IF estimation is vital for bearing fault diagnosis under time-varying speeds without a tachometer being involved; (2) accuracy of extracted IF depends on the readability of TFR which often suffers from the smearing problem due to base frequencies not matching the frequencies of signal components; (3) Time frequency analysis (TFA) is a promising tool for bearing fault diagnosis under variable speeds in addition to order tracking
Summary
Bearings are one of key components in rotating machinery; their fault detection and diagnosis have long been investigated to prevent severe equipment damage and unscheduled downtime [1]. (2) accuracy of extracted IF depends on the readability of TFR which often suffers from the smearing problem due to base frequencies not matching the frequencies of signal components; (3) TFA is a promising tool for bearing fault diagnosis under variable speeds in addition to order tracking. This paper aims at solving the smearing problems of TFR and exploiting the TFA-based fault diagnosis method for bearing condition monitoring under time-varying operations, from which multiple IF ridges are attempted to be extracted for the purpose of fault diagnosis. To achieve the purpose mentioned above, this paper proposes the frequency matching linear transform (FMLT) with the guidance of fast path optimization (FPO) for TFR enhancement and IF path extraction for bearing fault diagnosis under time-varying speed operations.
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