Demonstrates a new machine diagnosis method using higher order cumulants and absolute deterioration factor, suggesting improved sensitivity.
Among many amplitude parameters, Kurtosis (4-th normalized moment of probability density function) is recognized to be the sensitive good parameter for machine diagnosis. On the other hand, new method of machine diagnosis can be considered utilizing higher order cumulants which have the characteristics that cumulants more than 3^<rd> order are 0 under Gaussian distribution. Cumulants are stated in combination with the same order moment and the moments under that order. Simple calculation method is required on the maintenance site. Furthermore, the absolute deterioration factor such as Bicoherence would be much easier to handle because it takes the value of 1.0 under the normal condition and tends to be 0 when damages increase. In this paper, n^ normalized cumulant is considered so as to intensify the sensitivity of diagnosis. Also, simplified calculation method for this new parameter by impact vibration is introduced. Furthermore, absolute deterioration factor is introduced. New calculation method is examined whether it is a sensitive good parameter or not. Compared with the results obtained so far, the new method shows fairly good results.
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Higuchi et al. (2006) studied this question.
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