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.

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.

Experimental and Theoretical Studies of the Fractal Scaling Parameter and the Lateral Scale Dependence of the Asperity Interference

2007 ◽  
Author(s):  
Shao Wang ◽  
Yi Hui Leong
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Numerical Scheme ◽  
Surface Profile ◽  
Density Data ◽  
Fractal Scaling ◽  
Scaling Parameter ◽  
Power Spectral ◽  
Surface Profiles ◽  
The Difference

The fractal scaling parameter was released in a recent study from its artificially assigned constant value to become a measurable parameter for simulated surface profiles. In the present study, this concept was extended to develop schemes for determining the fractal scaling parameter from experimental power spectral density data. The difference in the trends of peaks has been observed between experimental power spectral density data and those of the Weierstrass-Mandelbrot function. A modified W-M function was proposed based on a peak splitting behavior of the power spectrum. To verify a relationship between the interference and lateral length scale for asperities, which is commonly assumed in fractal modeling, a numerical scheme was developed to truncate measured surface profiles for finding asperity interferences for microcontacts of various sizes. This relationship was confirmed by the favorable results from a comparison of the power values obtained from truncation of a surface profile to those obtained by using the fast Fourier transform. A numerical scheme was developed to generate random power spectral density curves and fractal surface profiles for given values of the fractal scaling parameter.

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.

A Possibility of 1/f Evaluation on Surface Finishes Based on Fluctuation Behavior

1992 ◽  
Vol 114 (2) ◽  
pp. 207-212 ◽  
Author(s):  
M. Shiraishi
Keyword(s):  
Spatial Frequency ◽  
Spectral Density ◽  
Sensory Evaluation ◽  
Power Spectral Density ◽  
Optical Method ◽  
Laser Light ◽  
Surface Finishes ◽  
Power Spectral ◽  
Surface Profiles ◽  
Reflection Intensity

The effectiveness of the optical method for evaluating engineering surfaces is described in terms of fluctuation properties as a means of a more global measuring technique of products. This is based on the 1/f fluctuation in which the power spectral density is proportional to the inverse of frequency f. Turned surfaces machined under different cutting conditions are tested by the reflection technique of a laser light, and its reflection intensity is analyzed to obtain the relation between the power spectral density and the spatial frequency. As a consequence, surface profiles with 1/f and 1/f1.5 properties seem to be satisfactory in conjunction with the results of sensory evaluation.

Fuzzy Modeling of Multi-Degree-of-Freedom Power Spectral Density Systems

2009 ◽  
Vol 2 (1) ◽  
pp. 40-47
Author(s):  
Montasser Tahat ◽  
Hussien Al-Wedyan ◽  
Kudret Demirli ◽  
Saad Mutasher
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Fuzzy Modeling ◽  
Degree Of Freedom ◽  
Power Spectral
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