Synthesizing nonstationary, non‐Gaussian random vibrations

Abstract

This paper presents a novel technique by which non-Gaussian vibrations are synthesized by generating a sequence of random Gaussian processes of varying root mean square (rms) levels and durations. The technique makes use of previous research by the authors which shows that non-Gaussian vibrations can be decomposed into a sequence of Gaussian processes. Synthesis is achieved by fi rst computing a modulation function which is produced from the rms and the segment length distribution functions, both of which were developed in previous research. This is achieved by fi rst generating a sequence of uniformly distributed random numbers scaled to the range of segment length, which itself is a function of the desired total duration of the synthesized process. In order to transform a uniformly distributed random variable into any arbitrary non-uniform distribution, the cumulative distribution function is established and used as a transfer function applied to the uniformly distributed random variable. This modulation function is applied to a Gaussian random signal itself generated by a standard laboratory random vibration controller (RVC) by means of a purposed-designed variable gain amplifi er system. In order to counteract the feedback function of the RVC, a second variable gain amplifi er is introduced into the system in order to attenuate the feedback signal in inverse proportion to the gain applied to the command signal. This result is a nonstationary, non-Gaussian random signal that statistically conforms to the desired PSD as well as the RMS distribution function.

Vibration and acceleration levels of multimodal container shipping physical environment

“…The statistical data for composite analysis confirmed that the vibration of the entire multimodal transportation also follows non‐Gaussian distribution. These results prove former studies that presented the non‐Gaussian nature of measured data for vehicle random vibration , ,…”

Comparison study on simulation effect of improved simulation methods for packaging random vibration test

“…• Modulated RMS distribution 9,10 • Wavelet decomposition 11,12 Shires et al 13 established a device to measure scuffing as a response to vibration input, which has been validated and shown to generate repeatable results in laboratory-based studies. Griffiths et al 11,14 investigated the correlation of several improved simulation techniques based on this scuff measuring device.…”

“…Accordingly, several improved simulation techniques have been proposed and developed as follows, and the detail introduction and comments of each method have been presented in our earlier study already, which will not be repeated here. Time replication Two‐way split spectral Three‐way split spectral Shock on random Kurtosis control Modulated RMS distribution Wavelet decomposition …”

Quantifying the Non-stationarity of Vehicle Vibrations with the Run Test

“…Another attempt at characterizing the non-stationary character of road vehicle vibrations is by means of the kurtosis statistic that describes the overall shape of the processes probability density function. 4 This paper employs a length-of-run analysis technique to quantify the level of non-stationarity of field vibration records collected from a range of vehicle types travelling various roads at normal (ambient) speeds.…”

“…1,2 This aspect of road vehicle vibrations is becoming increasingly important as novel methods are being proposed to better simulate transport vibrations in the laboratory by taking into account the nonstationary and non-Gaussian characters of such processes. [3][4][5][6] It has been shown that vibration simulation methods that do not take into account the non-stationary nature of transport vibrations fail to expose the product to the range of vibration levels that are encountered during transport. 3 Garcia-Romeu and Rouillard 7 studied the non-stationary character of numerous and varied road vibration data in terms of the statistical distribution of the RMS.…”