Abstract
The development of diagnostics for rolling element bearings (REBs) in recent years makes it possible to detect faults in bearings in real-time. Squared envelope analysis (SEA), in which the statistical characteristics of the squared envelope (SE) or the squared envelope spectrum (SES) are analysed, is widely recognized as both an effective and the simplest method. The most critical step of SEA is to find an optimal frequency band that contains the maximum defect information. The most commonly used approaches for selecting the optimal frequency band are derived from measuring the kurtosis of the SE or the SES. However, most methods fail to cope with the interference of a single or a few impulses in the corresponding domain. A new method is proposed in this paper called “PMFSgram”, which just calculates the kurtosis of the SES in the range centred at the first two harmonics with a span of three times the modulation frequency rather than the entire SES of the band filtered signals. It is possible to avoid most of the interference from a small number of undesired impulses in the SES. PMFSgram uses several bandwidths from 1.5 times to 4.5 times the fault frequency and for each bandwidth has the same number of central frequencies. The frequency setting method is able to select an optimal frequency band containing most of the useful information with less noise. The performance of the new method is verified using synthesized signals and actual vibration data.
Highlights
Condition monitoring and health management are important for the safe operation of modern locomotives
AAnew method in which just the spectrum, in the range centred the first two harmonics new method in which justenvelope the envelope spectrum, in the rangeatcentred at the first two with a span of three times modulation frequency, isfrequency, used to calculate kurtosis the of the squared envelope spectrum (SES) isof harmonics with a span ofthe three times the modulation is used the to calculate kurtosis proposed in this paper
It is quite different from the protugram and the enhanced kurtogram, which the SES is proposed in this paper
Summary
Condition monitoring and health management are important for the safe operation of modern locomotives. The fast kurtogram method calculates the kurtosis of the SE in every frequency band divided by the algorithm. Despite the fact that the fast kurtogram can be used to select the optimal frequency band for REB fault diagnosis in some cases, the performance of the fast kurtogram was limited due to its shortcomings, such as sensitivity to a single impulse in the signal and insensitivity to high repetition rate impulses in the signal. The protugram method was proposed to measure the kurtosis of the SES instead of the SE of the band filtered signal [10]. A maximum correlated kurtosis deconvolution method was proposed to extract the fault frequency component from the collected vibration signal [21].
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