Vibration Measurement and Spectral Analysis of Chassis Frame Mounted Structure for Off-Road Wheeled Heavy Vehicles

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
V.R. Deulgaonkar
Keyword(s):  
Spectral Analysis ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Dominant Frequency ◽  
Vibration Measurement ◽  
Road Transportation ◽  
The Road ◽  
Power Spectral ◽  
Cross Country ◽  
Paved Road

Chassis mounted structure is a base component for shelters or containers mounted on heavy transport vehicles. When the vehicle is driven in rough terrains or during off-road transportation this structure has a significant role in protecting the sophisticated cargo and intelligent tracking systems placed inside the shelters. During off-road transportation or warhead conditions the vehicle is subjected to large unevenness in load due to road or soil irregularities in rough terrains, which causes vibrations to be induced in the vehicle. As the nature of vibrations induced in vehicle during travel on off-road or cross-country terrains is random and unpredictable, there is a concern to analyse the vibration response of chassis and chassis mounted structures is needed. Present work deals with vibration measurement and spectral analysis of a chassis mounted structure designed for off-road and commercial transport vehicles. The road profile on which the vibration measurement has been carried out includes paved road and cross-country terrain segments. The vibration measurement has been carried at three different vehicle speeds. Signal analysis procedure for the acquired test data is discussed. The chassis mounted structure under concern is intended to hold two shelters or containers. From the vibration measurement at critical locations, g-(RMS) and g-(peak) values for paved and cross-country roads have been found out. Power spectral density values have also been found on chassis and structure for the same transport situations. Major inferences include the evaluation of minimum and maximum g-values (peak and RMS) on chassis and chassis mounted structure. Power spectral density graphs are constructed from which the dominant frequency for both road profiles is found out.

scholarly journals Vehicle response on kinematic excitation

2018 ◽  
Vol 211 ◽  
pp. 13001
Author(s):  
Veronika Valašková ◽  
Jozef Melcer
Keyword(s):  
Spectral Density ◽  
Frequency Domain ◽  
Power Spectral Density ◽  
Engineering Problem ◽  
Kinematic Excitation ◽  
The Road ◽  
Power Spectral ◽  
Road Profile ◽  
Vehicle Response ◽  
On The Road

The vehicle - roadway interaction is actual engineering problem solved on many workplaces in the world. At the present time preference is given to numerical and experimental approaches. Vehicle designers are interested in the vibration of the vehicle and the forces acting on the vehicle. Civil engineers are interested in the load acting on the road. Solution of the problem can be carried out in time or in frequency domain. Road unevenness is the main source of kinematic excitation of the vehicle and therefore the main source of dynamic forces acting both on the road and the vehicle. The offered article deals with one of the possibilities of numerical analysis of the vehicle response in frequency domain. It works with quarter model of the vehicle. For the selected computational model of the vehicle it quantifies the Frequency Response Functions (FRF) of both force and kinematic quantities. It considers the stochastic road profile. The Power Spectral Density (PSD) of the road profile is used as input value for the calculation of Power Spectral Density of the response. All calculations are carried out numerically in the environment of program system MATLAB. When we know the modules of FRF or the Power Response Factors (PRF) of vehicle model the calculation of vehicle response in frequency domain is fast and efficient.

scholarly journals Power spectral analysis of heart rate in hypothyroidism

2000 ◽  
pp. 327-333 ◽  
Author(s):  
V Cacciatori ◽  
ML Gemma ◽  
F Bellavere ◽  
R Castello ◽  
ME De Gregori ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Spectral Density ◽  
Cardiovascular System ◽  
Power Spectral Density ◽  
Power Spectral Analysis ◽  
Control Subjects ◽  
Power Spectral ◽  
Hypothyroid Patients

OBJECTIVE: The aim of the present study was to evaluate the impact of hypothyroidism on the autonomic regulation of the cardiovascular system by analysing separately sympathetic and parasympathetic influences on the heart. DESIGN: In seven newly diagnosed untreated hypothyroid patients we analysed power spectral density of heart rate cyclic variations at rest, while lying, and while standing. The same protocol was repeated after the induction of stable euthyroidism by levothyroxine (L-T(4)) treatment. The results were also compared with those obtained from seven age-, sex- and body mass index-matched control subjects. METHODS: Heart rate variability was evaluated by autoregressive power spectral analysis (PSA). This method allows reliable quantification of low frequency (LF) and high frequency (HF) components of the heart rate power spectral density. These are considered to be under mainly sympathetic and purely parasympathetic control respectively. In addition, heart rate variations during deep breathing, lying to standing, and Valsalva's manoeuvre were assessed. RESULTS: PSA showed a sharp reduction in the HF (parasympathetic) component in hypothyroid subjects compared with controls (lying, 29.4+/-5.4 vs 47.7+/-6.3 normalized units (NU) (means +/- s.e.m.), P<0.05; standing, 14.0+/-3.5 vs 32.1+/-3.6NU, P<0.005). Conversely, the LF (mainly sympathetic) component was higher in hypothyroid subjects than in controls (lying, 61.6+/-6.4 vs 45.4+/-6.7 NU; standing, 71.7+/-8.0 vs 53.1+/-5.6NU), this difference being significant in the standing position. Hence, the LF/HF ratio, which is considered an index of sympathovagal balance, was increased in hypothyroid subjects while both lying (2.75+/-0.6 vs 1.16+/-0.3; P<0.05) and standing (10.0+/-3.7 vs 1.85+/-0.3; P<0. 02). Total heart rate variability, expressed as total power spectral density, was lower in hypothyroid patients than in control subjects, this difference being significant in the lying position (574+/-126 vs 2302+/-994ms(2), P<0.05). In patients re-examined after L-T(4) therapy, complete normalization of cardiovascular parameters was observed (LF/HF ratio, lying, 1.26+/-0.4; standing, 2.56+/-0.8, both P<0.01 vs baseline values). The response to conventional cardiovascular autonomic tests was not significantly different between hypothyroid patients and healthy controls, and did not change in patients after therapy. CONCLUSIONS: These results suggest that, contrary to the clinical picture, thyroid hormone deficiency is associated with an increased sympathetic influence on the autonomic cardiovascular system. The changes in sympathetic function could be explained by a secondary adaptation to an altered cardiovascular responsiveness.

Resolving the Issues of Capon and APES Approach for Projecting Enhanced Spectral Estimation

2016 ◽  
Vol 6 (2) ◽  
pp. 725
Author(s):  
Kantipudi MVV Prasad ◽  
H.N. Suresh
Keyword(s):  
Signal Processing ◽  
Spectral Analysis ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Simple Technique ◽  
Spectral Estimation ◽  
Research Work ◽  
Research Community ◽  
The Past ◽  
Power Spectral

There are various applications on signal processing that is highly dependent on preciseness and accuracy of the outcomes in spectrum of signals. Hence, from the past two decades the research community has recognized the benefits, significance, as well as associated problems in carrying out a model for spectral estimation. While in-depth investigation of the existing literatures shows that there are various attempts by the researchers to solve the issues associated with spectral estimations, where majority of teh research work is inclined towards addressing problems associated with Capon and APES techniques of spectral analysis. Therefore, this paper introduces a very simple technique towards resolving the issues of Capon and APES techniques. The outcome of the study was analyzed using correlational factor and power spectral density to find the proposed system offers better spectral estimations compared to existing system.

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.

scholarly journals Staggered-PRT Sequences for Doppler Weather Radars. Part I: Spectral Analysis Using the Autocorrelation Spectral Density

2017 ◽  
Vol 34 (1) ◽  
pp. 51-63 ◽  
Author(s):  
Sebastián M. Torres ◽  
David A. Warde
Keyword(s):  
Spectral Analysis ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Weather Radar ◽  
Real Data ◽  
Pulse Repetition ◽  
Spectral Processing ◽  
Weather Radars ◽  
Power Spectral ◽  
Repetition Time

AbstractThe autocorrelation spectral density (ASD) was introduced as a generalization of the classical periodogram-based power spectral density (PSD) and as an alternative tool for spectral analysis of uniformly sampled weather radar signals. In this paper, the ASD is applied to staggered pulse repetition time (PRT) sequences and is related to both the PSD and the ASD of the underlying uniform-PRT sequence. An unbiased autocorrelation estimator based on the ASD is introduced for use with staggered-PRT sequences when spectral processing is required. Finally, the strengths and limitations of the ASD for spectral analysis of staggered-PRT sequences are illustrated using simulated and real data.

scholarly journals Simulation of Pavement Random Excitation Based on Harmonic Superposition Method

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Kehui Ma ◽  
Yongguo Zhang ◽  
Xü Zhen
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Ride Comfort ◽  
Random Excitation ◽  
Superposition Method ◽  
Generation Model ◽  
The Road ◽  
Power Spectral ◽  
Control Research ◽  
The Relationship

The road input model is very important in the analysis of vehicle ride comfort and handling stability. Based on the analysis of the relationship between the spatial frequency power spectral density and the time power spectral density of the road, the road signal generation model is established. The simulation is carried out under different vehicle speeds, and the B and C-level random road time excitation signals are generated. The power spectral density is used to compare the simulation results of the model with the road classification standard. The experimental results show that the results are accurate and can provide reliable excitation signals for vehicle control research.

Power spectral density and probability analysis of electromyograms in shivering birds

1968 ◽  
Vol 46 (5) ◽  
pp. 703-706 ◽  
Author(s):  
George C. West ◽  
Edgar R. R. Funke ◽  
J. Sanford Hart
Keyword(s):  
Spectral Analysis ◽  
Spectral Density ◽  
Normal Distribution ◽  
Power Spectral Density ◽  
Species Differences ◽  
Probability Analysis ◽  
Frequency Of Occurrence ◽  
Power Spectral ◽  
Quiscalus Quiscula

The spectral analysis of electromyograms from evening grosbeaks, Hesperiphona vespertina, and common grackles, Quiscalus quiscula, revealed a statistically significant higher upper cut-off frequency during shivering in the former species. There was also a statistically significant decrease in the upper cut-off frequency with lowering of temperature in the evening grosbeak, but not in the grackle. The frequency of occurrence of various amplitudes during shivering followed the normal distribution closely in both species. The presence of frequencies in the range from 6 to 600 c.p.s. necessitates the use of wideband instrumentation for fidelity in measuring species differences.

Within-night variation in respiratory effort preceding apnea termination and EEG delta power in sleep apnea

1998 ◽  
Vol 85 (4) ◽  
pp. 1434-1441 ◽  
Author(s):  
Richard B. Berry ◽  
Musa A. Asyali ◽  
Michael I. McNellis ◽  
Michael C. K. Khoo
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Esophageal Pressure ◽  
Dominant Frequency ◽  
Arousal Threshold ◽  
Delta Power ◽  
Power Spectral ◽  
Obstructive Sleep

We studied the within-night variability of the maximum esophageal pressure deflection before apnea termination (DPmax) in nine patients with severe obstructive sleep apnea as an index of the arousal threshold and the mean electroencephalogram (EEG) delta power for each 30 s as an index of the timing of sleep cycles. Periodicity in the time variation of delta power and DPmax was analyzed by determining their power spectral density and their relationship determined by cross correlation. DPmax and delta power varied cyclically and in phase with a major periodicity (major peak in power spectral density) of 117.6 ± 8.8 (SE) min. The correlation between the values of DPmax and delta power was significant ( P < 0.001) in each subject (mean r = 0.47 ± 0.03), and the coherence between DPmax and delta power at their dominant frequency was high. Within cycles of non-rapid-eye-movement sleep, DPmax and delta power increased, reaching peak values on average at or after midcycle. These findings suggest that the arousal threshold to airway occlusion in patients with obstructive sleep apnea varies cyclically during the night synchronous to the underlying cycles of sleep.

Longitudinal road unevenness with periodic components: Characterization and effects on people in a traversing vehicle and the loading of the pavement

2005 ◽  
Vol 219 (6) ◽  
pp. 773-790 ◽  
Author(s):  
O Kropáč ◽  
P Múčka
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Longitudinal Profile ◽  
International Roughness Index ◽  
Passenger Car ◽  
The Road ◽  
Power Spectral ◽  
Roughness Index ◽  
Pavement Structure ◽  
Periodic Components

Firstly, the effect of periodic components (undulation) appearing in the otherwise random longitudinal profile of road on standard indicators of random unevenness is studied. The power spectral density characterized by its parameters, i.e. the unevenness index and waviness, three band variances, and international roughness index are considered. Secondly, a series of simulation examples is given of the response of two planar vehicle models (a passenger car and a truck) traversing along the road with periodic components of longitudinal unevenness. The effects on people sitting in the vehicle and on the loading of the vehicle undercarriage and pavement structure are studied. The wavelengths of undulation and the running speeds that appear as most inconvenient are emphasized

scholarly journals An Application of The Lomb-Scargle Periodogram To Investigate Heart Rate Variability During Haemodialysis

2020 ◽  
Author(s):  
Jill Stewart ◽  
Paul Stewart ◽  
Thomas Walker ◽  
Latha Gullapudi ◽  
Tarek Eldehni ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Circulatory System ◽  
False Alarm Probability ◽  
Process Time ◽  
Processing Methods ◽  
Power Spectral

<div><div><div><p>Objective: Short-term cardiovascular compensatory responses to perturbations in the circulatory system caused by haemodialysis can be investigated by spectral analysis of heart rate variability. This could provide an important variable for categorising individual patients response to haemodialysis leading to a more personalised treatment. However, data obtained over a four-hour haemodialysis treatment is significant in volume and subject to artefacts that can compromise its analysis.</p><p>Methods: The Lomb-Scargle Periodogram can provide a robust method of generating power spectral density estimates for large, irregularly sampled and noisy data sets obtained in clinical settings, provided that careful attention is given to frequency limits. The effect of different pre-processing methods on the resulting power spectrum is explored with simulated and real heart rate variability data.</p><p>Results: Common pre-processing methods for correcting individual artefacts in heart rate records, such as interpolation, are unreliable as they act as non-linear low-pass filters and distort the resulting spectral analysis. These distortions are present, but less apparent within patient data and can mislead clinical interpretations.</p><p>Conclusion: It is more appropriate to exclude suspect data points than to edit them prior to spectral analysis via the Lomb- Scargle periodogram, and where required, de-noise the entire heart rate signal by empirical mode decomposition. The use of a False Alarm Probability metric can help establish whether spectral estimates are valid</p><p>Significance: Methods established to pre-process time-invariant data prior to power spectral density estimation fail when used in conjunction with the Lomb-Scargle method.</p></div></div></div>

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