Application of Random Vibration Test Methods for Automotive Subsystems Using Power Spectral Density (PSD)

2000 ◽  
Author(s):  
J. S. Lin ◽  
Kui-Sun Yim
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Random Vibration ◽  
Test Methods ◽  
Vibration Test ◽  
Power Spectral

scholarly journals Analysing Random Vibration of KLT Box during Transporting by Finite Element Method

10.29007/b1th ◽  
2022 ◽  
Author(s):  
Cong Hoa Vu ◽  
Ngoc Thien Ban Dang
Keyword(s):  
Finite Element ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Automotive Industry ◽  
Random Vibration ◽  
Element Model ◽  
Vibration Testing ◽  
Time Data ◽  
Power Spectral ◽  
The Impact

Today, freight is an extremely important industry for the world we are living. Fast transportation, large volume...will optimize the cost, time and effort. Besides, ensuring the products safety is a matter of concern. During transporting, it is inevitable that the vibration caused by the engine, rough road surface...the cargo inside can be damaged. Automobile industries have prime importance to vibration testing. Sine vibration testing is performed when we have been given with only one frequency at given time instant. Trend to perform random vibration testing has been increased in recent times. As random vibration considers all excited frequencies in defined spectrum at known interval of time, it gives real-time data of vibration severities. The vibration severity is expressed in terms of Power Spectral Density (PSD). KLT box is an industrial stacking container conforming to the VDA 4500 standard that was defined by German Association of the Automotive Industry (VDA) for the automotive industry. The aim of this paper is study about random vibration and power spectral density analysis, how it can be used to predict the impact of hash road to the KLT box on container / truck during transportation. Finite element model is developed in ANSYS, modal analysis and random vibration analysis were done.

scholarly journals Optimum Resolution Bandwidth for Spectral Analysis of Stationary Random Vibration Data

1993 ◽  
Vol 1 (1) ◽  
pp. 33-43 ◽  
Author(s):  
Allan G. Piersol
Keyword(s):  
Spectral Analysis ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Random Vibration ◽  
Damping Ratio ◽  
Frequency Resolution ◽  
Power Spectral ◽  
Averaging Time ◽  
Resolution Bandwidth

This article presents a methodology for selecting the frequency resolution bandwidth for the spectral analysis of stationary random vibration signals in an optimum manner. Specifically, the resolution bandwidth that will produce power spectral density estimates with a minimum mean square error is determined for any given measurement duration (averaging time), and methods of approximating the optimum bandwidth using practical spectral analysis procedures are detailed. The determination of the optimum resolution bandwidth requires an estimate for the damping ratio of the vibrating structure that produced the measured vibration signal and the analysis averaging time. It is shown that the optimum resolution bandwidth varies approximately with the 0.8 power of the damping ratio and the bandwidth center frequency, and the −0.2 power of the averaging time. Also, any resolution bandwidth within ±50% of the optimum bandwidth will produce power spectral density (PSD) estimates with an error that is no more than 25% above the minimum achievable error. If a damping ratio of about 5% for structural resonances is assumed, a constant percentage resolution bandwidth of 1/12 octave, but no less than 2.5 Hz, will provide a near optimum PSD analysis for an averaging time of 2 seconds over the frequency range from 20 to 2000 Hz. A simple scaling formula allows the determination of appropriate bandwidths for other damping ratios and averaging times.

Random Vibration Analysis for Centrifugal Compressor Impellers With Unsteady Aerodynamic Excitations

2016 ◽  
Author(s):  
Yuefang Wang ◽  
Yan Liu ◽  
Xuejun Wang ◽  
Hongkun Li ◽  
Daren Jiang
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Centrifugal Compressor ◽  
Random Vibration ◽  
Pressure Field ◽  
Pseudo Excitation Method ◽  
Vibration Problem ◽  
Power Spectral ◽  
Pseudo Excitation ◽  
Excitation Method

Dynamic response of impeller of centrifugal compressor is studied considering pulsating pressure field on blades due to unsteady flow conditions. The aerodynamic forces on the blades are modeled as random load whose spectral characteristics are determined through computational fluid dynamic simulations in the time domain. The dynamical response in the unsteady case is solved as a random vibration problem in the frequency domain which provides useful power spectral density displacement and stress for early stage of impeller design. A semi-open impeller mounted with 19 blades is modeled using three dimensional solid finite elements. The random vibration problem of the impeller is solved through the Pseudo-Excitation Method considering spatial variance of the pressure field. A user-defined module is developed based on harmonic analysis to generate the auto power spectral density and variance of displacement and stress at 200 nodes. It is demonstrated that solving a random vibration problem through the Pseudo-Excitation Method is faster than the commonly adopted multiple-step transient analysis. It is concluded that evaluating the structural integrity of impeller solids in the regime of random vibration is a feasible and efficient approach at the early design stage of compressors.

Application of Power Spectral Density Method to Fatigue Life Estimation of the Axle Structure

2014 ◽  
Vol 487 ◽  
pp. 272-275
Author(s):  
Rui Feng Guo ◽  
Peng Li Wang
Keyword(s):  
Fatigue Life ◽  
Spectral Density ◽  
Density Function ◽  
Power Spectral Density ◽  
Random Vibration ◽  
Spectral Density Function ◽  
Power Spectral Density Function ◽  
Life Estimation ◽  
Power Spectral ◽  
Fatigue Life Estimation

Based on the random vibration theory, fatigue strength theory and Miner cumulative damage theory, the formulas for estimation of fatigue life which can be coped with narrowband and broadband random vibration was derived by the peak distribution function. The power spectral density function of axle structure is deduced after the power spectral density of standard road and the vibration model of wheel had studying. Combined the power spectral density function with broadband random vibration fatigue life estimation formula, the fatigue life of axle structure was obtained. This method is simple and has a strong engineering practicality.

Analysis on Random Response of a Simply Supported Beam Subjected to Distributed Load

2014 ◽  
Vol 518 ◽  
pp. 120-125 ◽  
Author(s):  
Xiao Jing Li
Keyword(s):  
Spectral Density ◽  
Density Function ◽  
Power Spectral Density ◽  
Random Vibration ◽  
Spectral Density Function ◽  
Random Response ◽  
Power Spectral Density Function ◽  
Simply Supported Beam ◽  
Simply Supported ◽  
Power Spectral

The random vibration of simply-supported beam is simplified of the random vibration of the SDOF theory ,the paper analyse its random response. We get the displacement power spectral density function the velocity power spectral density and the acceleration power spectral density function of the maximum displacement point. The same example is calculated by ANSYS, it also get the same results.It proved that using the finite element analysis software ANSYS to anlaysis the random vibration of the simply-supported beam has advantages of fast speedhigh precisioneasy stepsthe small error and so on..

Life Prediction and Damage Acceleration Based on the Power Spectral Density of Random Vibration

1995 ◽  
Vol 38 (1) ◽  
pp. 34-40
Author(s):  
Jimmy Hu
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Gaussian Processes ◽  
Life Prediction ◽  
Random Vibration ◽  
Wide Band ◽  
Accelerated Testing ◽  
Test Time ◽  
Element Analysis ◽  
Power Spectral

Fatigue life prediction and accelerated verification tests under a random vibration environment are important tasks for evaluating product reliability. This paper reviews the characteristics of random stress processes, discusses the methodology of life prediction and accelerated testing under various random loadings by using the stress power spectral density (PSD) function obtained from finite element analysis (FEA), and develops an engineering method to determine the acceleration level and test time in reliability verification tests. The discussions cover the narrow-band Gaussian processes, the wide-band Gaussian processes, and the nonGaussian processes. To illustrate the practical procedure of life prediction and accelerated testing based on the damage equivalent technique, the application example of an automotive component is presented.

scholarly journals Power spectral density analysis for nonlinear systems based on Volterra series

2021 ◽  
Author(s):  
Penghui Wu ◽  
Yan Zhao ◽  
Xianghong Xu
Keyword(s):  
Nonlinear System ◽  
Nonlinear Systems ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Random Vibration ◽  
Volterra Series ◽  
Harmonic Excitation ◽  
Random Load ◽  
Vibration Prediction ◽  
Power Spectral

AbstractA consequence of nonlinearities is a multi-harmonic response via a mono-harmonic excitation. A similar phenomenon also exists in random vibration. The power spectral density (PSD) analysis of random vibration for nonlinear systems is studied in this paper. The analytical formulation of output PSD subject to the zero-mean Gaussian random load is deduced by using the Volterra series expansion and the conception of generalized frequency response function (GFRF). For a class of nonlinear systems, the growing exponential method is used to determine the first 3rd-order GFRFs. The proposed approach is used to achieve the nonlinear system’s output PSD under a narrow-band stationary random input. The relationship between the peak of PSD and the parameters of the nonlinear system is discussed. By using the proposed method, the nonlinear characteristics of multi-band output via single-band input can be well predicted. The results reveal that changing nonlinear system parameters gives a one-of-a-kind change of the system’s output PSD. This paper provides a method for the research of random vibration prediction and control in real-world nonlinear systems.

Comparing Random Vibration Inputs: Power Spectral Density (PSD) Versus Root Mean-Square Acceleration (Grms)

2003 ◽  
Author(s):  
Ivan Straznicky
Keyword(s):  
Spectral Density ◽  
Root Mean Square ◽  
Power Spectral Density ◽  
Fatigue Damage ◽  
Random Vibration ◽  
Mean Square ◽  
Vibration Effect ◽  
Operating Environments ◽  
Power Spectral ◽  
Magnitude Difference

Many defense programs have vibration requirements for electronics which are often specified as random vibration input. Often, this input is based on measurements taken at the locations of interest for the spectrum of vehicle operating environments. The resulting specification is typically several power spectral density, or PSD, curves with associated durations. The root mean square acceleration, or Grms, can be readily calculated for each PSD curve. Grms values are sometimes used to compare different PSD curves for severity. However, this can be misleading. The impacts of two different random vibration inputs, with the same Grms value, can be very different. By calculating fatigue damage values for various components on a circuit card assembly subjected to these inputs, it can be shown that equal Grms values do not result in equal damage. In fact, there can be two orders of magnitude difference in component damage values. This means that Grms values are very poor indicators of random vibration effect, and should not be used for comparison purposes.

Sign in / Sign up

Export Citation Format

Share Document