Abstract
Vibratory fatigue has been indicated to be one of the most frequently encountered problems in engineering practice. And it is inevitable that the mechanical components of machine are excited by random signals. Most of the random vibrations in nature contain non-Gaussian components. In order to reduce the failure and economic losses which is caused by vibration, random vibration testing is usually conducted in laboratory to verify whether the components can survive a particular random vibration or to identify weaknesses of items. In this paper, the vibratory fatigue damages of Gaussian random signals and non-Gaussian random signals to a particular system are discussed. The process and difference are illustrated by using a case study.
Highlights
It is inevitable that the mechanical components of machine are excited by random signals in field [1]
In order to reduce the failure and economic losses which is caused by vibration, random vibration testing is usually conducted in laboratory to verify whether the components can survive a particular random vibration or to identify weaknesses of items
When the probability density function (PDF) is taken into consideration, it is obvious that the characteristic described by kurtosis and skewness between Gaussian signals and non-Gaussian signals are different
Summary
It is inevitable that the mechanical components of machine are excited by random signals in field [1]. When the probability density function (PDF) is taken into consideration, it is obvious that the characteristic described by kurtosis and skewness between Gaussian signals and non-Gaussian signals are different. The kurtosis is introduced to describe the overall shape of a probability density function (PDF) and is the main variable used to identify the differences from Gaussian signals to non-Gaussian signals. While compared to Gaussian signal, the probability density function (PDF) of non-Gaussian signal with kurtosis greater than 3, wider on both sides of the tail and the tail value is larger than the Gaussian signal, is called super-Gaussian signal. The fatigue damages of Gaussian random signals and non-Gaussian random signals to a particular system under two vibrational inputs are discussed. The process and difference are illustrated by using a case study
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
