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.

scholarly journals TESTING, ANALYSIS AND COMPARISON FOR CHARACTERISTICS OF AGRICULTURAL FIELD AND ASPHALT ROAD ROUGHNESS

2020 ◽  
pp. 147-154
Author(s):  
Lijuan Wang ◽  
Jianguo Yan ◽  
Shengshi Xie ◽  
Chunguang Wang
Keyword(s):  
Spectral Density ◽  
Root Mean Square ◽  
Power Spectral Density ◽  
Mean Square ◽  
Agricultural Field ◽  
Power Spectral ◽  
Fitting Method ◽  
Density Fitting ◽  
Asphalt Road ◽  
Surface Profiles

Measuring and analysing the roughness of agricultural field and road have great significance for studying the characteristics of tractor dynamic response. This study was designed to analyse and compare the roughness characteristics of agricultural field and asphalt road profiles. A profiling apparatus was developed to measure field and road surface profiles of parallel tracks. The profile measurements were conducted in a grass field, a corn stubble field, a harvested potato field and on an asphalt road. The root mean square value and two spectrum parameters of surface profiles were calculated and analysed to investigate the roughness characteristics of fields and asphalt road. The results of the study indicate that for the values of the agricultural field and asphalt road surface roughness, waviness and roughness index are both positive associated with the root mean square value. Most of the waviness values of all measured field profiles were less than 2 with the average of 1.8, while the waviness values of all measured asphalt road profiles were greater than 2 with the average of 2.08. The roughness of both field and asphalt road profiles can be distinguished by the power spectral density fitting method. However, it has better performance in characterizing asphalt road profiles than characterizing field profiles with the power spectral density fitting method.

scholarly journals The Silencing of U.S. Campuses Following the COVID-19 Response: Evaluating Root Mean Square Seismic Amplitudes Using Power Spectral Density Data

2021 ◽  
Author(s):  
David L. Guenaga ◽  
Omar E. Marcillo ◽  
Aaron A. Velasco ◽  
Chengping Chai ◽  
Monica Maceira
Keyword(s):  
Spectral Density ◽  
Root Mean Square ◽  
Power Spectral Density ◽  
Active Regions ◽  
The United States ◽  
School Closure ◽  
Mean Square ◽  
School Closures ◽  
Power Spectral ◽  
Seismic Amplitudes

Abstract In response to the COVID-19 global pandemic, many populated and active regions have become deserted and show significant reductions in their background seismicity, especially campuses across the United States (U.S.). Seismic sensors located in the vicinity of or within U.S. campuses show that anthropogenic seismic noise remains elevated during the ordinary, nonpandemic, academic year, only subduing during periods of recess (e.g., winter break). Here, we use power spectral density (PSD) data computed by the Incorporated Research Institutions for Seismology Data Management Center for quality assessment to calculate root mean square (rms) amplitude and analyze the effects of the COVID-19 school closures. We processed and analyzed PSD data for 46 seismic stations located within 50 m of a U.S. university or college. Results show that 42 campus stations show an overall rms drop following a statewide school closure.

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.

Optimal Wiener Filter for a Body Mounted Inertial Attitude Sensor

2008 ◽  
Vol 61 (3) ◽  
pp. 455-472 ◽  
Author(s):  
Peter Rizun
Keyword(s):  
Spectral Density ◽  
White Noise ◽  
Power Spectral Density ◽  
Human Body ◽  
Linear Acceleration ◽  
Mean Square ◽  
White Noise Process ◽  
Noise Process ◽  
Power Spectral ◽  
The Mean

An optimal attitude estimator is presented for a human body-mounted inertial measurement unit employing orthogonal triads of gyroscopes, accelerometers and magnetometers. The estimator continuously fuses gyroscope and accelerometer measurements together in a manner that minimizes the mean square error in the estimate of the gravity vector, based on known spectral characteristics for the gyroscope noise and the linear acceleration of points on the human body. The gyroscope noise is modelled as a white noise process of power spectral density δn2/2 while the linear acceleration is modelled as the derivative of a band-limited white noise process of power spectral density δv2/2. The estimator is robust to centripetal acceleration and guaranteed to have zero mean error regardless of the motion of the sensor. The mean square angular error in attitude is shown to be independent of the module's angular velocity and equal to 21/2g−1/2δn3/2δv1/2.

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.

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