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«Abstract In vibration human body is unified and complex active dynamic system. Lumped parameters are offered used to capture and evaluate the human ...»

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Analytical Investigation and Numerical Prediction of Driving

Point Mechanical Impedance for Driver Posture By Using

ANN.

∗1 †2

Mr. Devendra N. Chaudhari and Prof.M.R.Phate

Department of Mechanical Engineering,PVPIT,Bavdhan,Pune 21

Department of Mechanical Engineering,PVPIT, Bavdhan,Pune 21

July 19, 2014

Abstract

In vibration human body is unified and complex active dynamic system. Lumped parameters

are offered used to capture and evaluate the human dynamic properties.Entire body vibration causes a multi fascinated sharing out of vibration within the body and disagreeable feelings giving rise to discomfort or exasperation result in impaired performance and health means. This distribution of vibration is dependent on intra subject variability and inters subject variability.

For this study a multi degree of freedom lumped parameter model has taken for analysis. The equation of motion is derived and the response function such as seat to head transmissibility (STHT) driving point mechanical impedance (DPMI) and apparent mass(APMS) are determined, for this kind of study we can use a neural network (ANN) which is a powerful data modeling tool that is able to capture and represent complex input/output relationship.

The goal of ANN is to create a model that correctly maps the input to the output using historic data so that the model can be then used to produce the output when the desired output is unknown.

Keywords : DPMI, APMS, HTST, ANN, Lumped Parameter.

1 Introduction Many researchers give their opinion about the vibrations of human body for both sitting as well as standing posture. Vibration is the main cause called oscillation to move up and down, which ∗ devchaudhari.2010@gmail.com † mangesh phate@gmail.com International Journal of Mechanical Engineering (IJME) Volume 4 Issue 2 (February 2014) ISSN : 2277-7059 http://www.ijmejournal.com/ affect the human comfort while driving, loss in productivity and various problems depending upon subjects like human age, human posture, magnitude of vibration and the time to exposure of vibration. The human body model is useful to simulate human response, which consist of various Branches like head, legs, right and left arms, as well as right and left legs model as a lumped masses.

The parameter employed in study are driving point mechanical impedance(DPMI), Apparent mass (APMS) and Seat to head transmissibility function (STHT).These various parameters can evaluate the vibration to body and how much particular element affected by vibration.

In 2011,wael abbas’, and et al[1],In journal of mechanics engineering and automation present 4DOF model of human body with linear seat suspension and Coupled with half car model.

For this model he applied a genetic algorithm to search for optimal parameters of seat in order to minimize seat suspension deflection and drivers body acceleration to achieve best comfort to drivers. The optimal linear seat model for the 4 DOF model was determined by genetic algorithm, and compared with current passive parameters, concluded that the optimal seat suspension has limitation on improving the vibration isolation, also the results and plots indicates that optimal linear seat suspension system is less oscillatory and have lower values of maximum overshoots than passive suspension System which is directly related to drivers fatigue,discomforts and safety.

In 1971, Hopkins’, [2], et al, developed 3 DOF model of human seated model consisting of upper torso, viscera and lower torso connected in series, For construction of model a bilinear spring were used to connect upper torso with viscera and viscera with lower torso, The model performance was compared with experimental impedance and transmission data values.The model displayed the same number of resonance and peaks as experimental impedance data but had different peak values. The model did not match with experimental transmibility data either in shape or peak values.

In 1974,Muksian and Nash [3],presented 7 DOF non linear model dedicated to analysis of vibration imposed on seated diaphragm abdomen and pelvis. linear spring were used between head and back and between back and pelvis, forces associated with relative motion of torso with respect to back and muscles forces were included in model as forces acting directly on masses. In that the sources of stiffnes model were not provided but values were similar to experimental data obtained by vogt et al [4]. The model performance were compared with experimental data for acceleration ratio given by Goldman and von Girke et al [11]. At higher frequencies, the model performance was significantly different than that observed experimentally. Matsumoto and Griffin [6] compared the dynamic responses of the human body in both standing and sitting positions. The apparent mass and transmissibility to the head, six locations along the spine, and the pelvis were measured with eight male subjects exposed to vertical random whole-body vibration. In both postures, the principal resonance in the transmissibility occurred in the range 5 to 6 Hz, with slightly higher frequencies and lower transmissibility in the standing posture.

In 1960, Coermann [7] presented a 6-degree-of-freedom (DOF) model of a human (for standing and sitting postures) used to simulate human dynamic response to longitudinal vibration of very low frequencies. This model included masses for the head, the upper torso, the arm-shoulder, a simplified thorax-abdomen subsystem, the hips, and the legs. A nonlinear spring was connected between the upper torso and the hips in parallel with the thorax-abdomen subsystem to represent the elasticity of the spinal column. Model parameters for each element were estimated from International Journal of Mechanical Engineering (IJME) Volume 4 Issue 2 (February 2014) ISSN : 2277-7059 http://www.ijmejournal.com/ measurements of the mechanical impedance. The performance of the whole-body model was not published and is therefore difficult to assess. The characteristics of the spine and the thorax-abdomen subsystem, however, were evaluated in detail. Each was modeled with 1 DOF in the whole-body model. Damping was not included in the spine and the performance of the thorax abdomen subsystem did not match the experimental data particularly well.





In 1976, Muksian and Nash [8] presented a 3-DOF model of the human body inThe sitting position that contained a parallel connection between the pelvis and the head. It included masses associated with the head (m1), body (m2), and pelvis (m3) connected in series, very similar to the model given by Coermann et al. [7]. It neglected the arms and legs, and combined the mass of the upper torso and thorax-abdomen into that of the body. The model was based on the assumption that: (1) all springs (kp1, kp2, and kp3) were linear in the frequency range between 1 and 30 Hz, (2) the damping between the head and body (cp2) was zero, and (3) all other dampers (cp1and cp3) were linear between 1 and 6 Hz but nonlinear between 6 and 30 Hz. The values of the masses were obtained from Hertzberg and Clauser [9]. The spring stiffness and damping coefficients were determined by matching existing experimental data at corresponding input frequencies by Magid et al. [10] and Goldman and von Gierke [11]. Since two kinds of damper were used for different frequency ranges, the model performed well when compared with experimental data for single-frequency input. However, since the damping values depend on the input frequencies, analysis of the model performance is difficult to assess for conditions involving multiple-frequency input (i.e., random vibration).

In 1987, ISO [12] published a 4-mass, 8-DOF model of a human for both sitting and standing positions. No correlation between the elements of the model and anatomical segments was established. Each spring damper set connecting masses included two springs and one damper (one spring parallel to the damper and the other in series). The model was developed to match a composite average seat-to-head acceleration transmissibility vs. frequency profile (amplitude and phase for the frequency range of 0.5 to 31.5 Hz) derived from existing experimental studies. The model matched the experimental data very well except for the transmissibility amplitude in the high-frequency range.

In 1987, Nigam and Malik [13] developed a 15-DOF un-damped model for which only a standing posture was considered. It included masses for the head, neck, upper, central, and lower torso, upper and lower arms, upper and lower legs, and feet. The mass of each element was obtained from a previous anthropomorphic body segment study by Bartz and Gianotti [14]. The stiffness was obtained by combining the stiffness of adjacent segments. The model performance was compared with some experimental data such as resonance peaks from Goldman and von Gierke [11], and resonant frequencies for two modes from Greene and McMahon [15]. The natural frequencies of the model were in the range of the experimental resonant data but were relatively high. The leg stiffness was compared with the experimental values from Greene and McMahon [15]. The approximate value of the single leg was 15 larger than the experimental data. As damping was ignored in this study, the model is less realistic and general.

In 2012,Zulkifli Mohd Nopiah [16]et al provide a program for optimization of noise and vibration model in passenger car cabin.In this paper effects of vibration to noise in passenger car cabin were investigated.A vehicle acoustical comfort index (VACI) was used to evaluate the noise International Journal of Mechanical Engineering (IJME) Volume 4 Issue 2 (February 2014) ISSN : 2277-7059 http://www.ijmejournal.com/ annoyance level and vibration does value (VDV) was used to evaluate the vibration level. They show that the increase of VACI values correspond to decrease level of vibration, and that of VDV decrease with increase of VACI values. Which conclude that more values of vibration can produce more annoyance of noise, also that increase of engine speed can influence the annoyance level by decreasing values of vehicle acoustical comfort index, in other words it will contribute to more noise.

by modifying the particular structure of car system to reduce the exposed vibration level, we are able to increase the VACI values and at same time decrease the level of noise in passenger car cabin.

According to Nicola cofelice et al[17], as published in international journal proposed a 3 dimensional model for virtual human dummy to represent a biomechanical response due to whole body vibration.They developed a model using a multi body simulation (MBS) and simulation environment LMS virtual lab. They take a detailed spine assembly in order to evaluate the human frequency response in the entire range at interest of whole body vibration. The model has been completely parameterized and model can be set up automatically allowing to define percentile of dummy and initial position. The model in car occupant position has been mainly used to compute human vibrational models and transmissibility functions.

In 2010,Li-xin Guo and Li-pin Zhang[18] present a mechanical and mathematical model of half car,5 DOF of vehicle was established,as well as the psudo excitation Model of road condition for the front wheel and rear wheel.By psudo-excitation method the equation of transient response and power spectrum density were established,after performing simulation to vehicle vibration of changeable driving show that psudo-excitation method is more convenient than traditional method and the smoothness computation problem of vehicle,while psudo-excitaton method is used to analyze the vehicle vibration under non-stationary random vibration.

In 2011,Dragon sekulic et al[19], presented a paper to determine a spring stiffness and shock absorber damping values of bus suspension system,needed to have acceptable oscillatory behavior.

He analyses 3 important oscillatory parameters in frequency domain. This type of analysis allows to choice values of oscillatory parameters of bus suspension system depending on different excitation frequency values,Similarly the analysis facilitate the choice of oscillatory parameters values for excitation frequency range which exerts a considerable influence on oscillatory behavior of bus.

Which in turn is of great importance while designing bus suspension system and found that the changes in suspension oscillatory parameters had effect that,

1. The drivers riding comfort was decreased as bus suspension spring stiffness was increased for excitation frequency to resonant frequencies of bus body.

2. Suspension deformation was reduced as bus suspension spring stiffness was increased at excitation frequencies below 1 Hz, within the zone of resonant frequency of sprung mass; the deformation amplitudes were increased as spring stiffness increased.

3. Higher shock absorber damping values provide better oscillatory comfort for the driver at excitation frequencies close to resonant frequency of bus body. At excitation frequencies above 1.5 Hz, the shock absorber with lower damping coefficient values ensured greater oscillatory comfort.

In 2010,Desta M. et al [20] taken an experiment in which he takes Wan’s and Schimmel’s (1995) 4 DOF lumped parameter model similar to the an automotive seating environment without back rest support.In order to study dynamic response of model the analytical study first implemented for the model to derive the equation of motion. He simulates the dynamic response under random International Journal of Mechanical Engineering (IJME) Volume 4 Issue 2 (February 2014) ISSN : 2277-7059 http://www.ijmejournal.com/ vibration. The random vibration are collected from 6 Indian railway trains at seat position using tri-axial accelerometer is used as an input,to analyze the dynamic response of the model. Concluded that the response acceleration spectral density with high vibration level is high and implies that the human beings feel more discomfort as vibration level increases, the spectral density of viscera is more related to other position of the body. The output acceleration spectral density of response function show that the peak values occurred between 3.4 to 5 Hz, for seat to head, seat to upper torso, seat to viscera transmissibility’s for different vibration level. The peak values decreases as vibration magnitude decreases.The acceleration spectral density of viscera has attained maximum at peak values more than other position, and vibration level has significant effect at resonance frequency and has less effect as frequency increases.



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