Delay-Bond Graph Models for Geared Torsional Systems

1974 ◽  
Vol 41 (2) ◽  
pp. 366-370 ◽  
Author(s):  
N. T. Tsai ◽  
S. M. Wang
Keyword(s):  
Transmission Line ◽  
Gear Tooth ◽  
Nonlinear Damping ◽  
Bond Graph ◽  
Dynamic Responses ◽  
State Variables ◽  
Graph Models ◽  
Wave Variables ◽  
Tooth Stiffness ◽  
Line Elements

The dynamic responses of geared torsional systems are analyzed with the delay-bond graph technique. By transforming the power variables into torsional wave variables, the torsional elements are modeled as transmission line elements. The nonlinear elements, e.g., varying tooth stiffness, gear-tooth backlash, and nonlinear damping, are incorporated into the ideal transmission line element. A computational algorithm is established where the state variables of the system are expressed in terms of wave scattering variables and the dynamic responses are then obtained in both time and space domains. The simulation results of several simple examples of linear and nonlinear geared torsional systems are presented to demonstrate the feasibility of this algorithm.

Analysis of Nonlinear Transient Motion of a Geared Torsional

1974 ◽  
Vol 96 (1) ◽  
pp. 51-59 ◽  
Author(s):  
S. M. Wang
Keyword(s):  
Gear Tooth ◽  
Nonlinear Damping ◽  
Gear Train ◽  
Transient Motion ◽  
Closed Form Solutions ◽  
Torsional Response ◽  
Tooth Stiffness ◽  
Nonlinear Transient ◽  
Linear And Nonlinear ◽  
Torsional Analysis

The dynamic torsional analysis of gear train systems has implemented many practical system designs. A computer analysis to predict the steady-state torsional response of a gear train system is presented in reference [1]. The current paper extends this work to the linear and nonlinear transient analysis of complex torsional gear train systems. Factors considered in the formulation are time-varying gear tooth stiffness, gear web rigidity, gear tooth backlash, shafts of nonuniform cross section, linear and nonlinear damping elements, multishock loadings, and complex-geared branched systems. For linear systems, the equations of transient motion are derived and closed-form solutions can be obtained by the state transition method [2]. For nonlinear systems, numerical methods are also presented. The method may be used as a means to analyze gear train start/stop operational problems, as well as constant speed response subject to internal and external disturbances.

Effects of the Gear Tooth Modification on the Nonlinear Dynamics of Gear Transmission System

2010 ◽  
Vol 97-101 ◽  
pp. 2764-2769
Author(s):  
Si Yu Chen ◽  
Jin Yuan Tang ◽  
C.W. Luo
Keyword(s):  
Nonlinear Dynamics ◽  
Gear Tooth ◽  
Simulation Method ◽  
Transmission Error ◽  
Dynamic Responses ◽  
Meshing Stiffness ◽  
Gear Transmission System ◽  
Tooth Modification ◽  
Static Transmission Error ◽  
Misalignment Error

The effects of tooth modification on the nonlinear dynamic behaviors are studied in this paper. Firstly, the static transmission error under load combined with misalignment error and modification are deduced. These effects can be introduced directly in the meshing stiffness and static transmission error models. Then the effect of two different type of tooth modification combined with misalignment error on the dynamic responses are investigated by using numerical simulation method. The numerical results show that the misalignment error has a significant effect on the static transmission error. The tooth crowning modification is generally preferred for absorbing the misalignment error by comparing with the tip and root relief. The tip and root relief can not resolve the vibration problem induced by misalignment error but the crowning modification can reduce the vibration significantly.

Investigation of Noise Features of Planetary Gear Trains Based on Human Aural Characteristic

2017 ◽  
Author(s):  
Masao Nakagawa ◽  
Dai Nishida ◽  
Deepak Sah ◽  
Toshiki Hirogaki ◽  
Eiichi Aoyama
Keyword(s):  
Gear Tooth ◽  
Structural Complexity ◽  
Planetary Gear ◽  
Transmission Error ◽  
Sound Level ◽  
Tooth Surface ◽  
Surface Error ◽  
Planetary Gear Trains ◽  
Tooth Stiffness ◽  
Gear Trains

Planetary gear trains (PGTs) are widely used in various machines owing to their many advantages. However, they suffer from problems of noise and vibration due to the structural complexity and giving rise to substantial noise, vibration, and harshness with respect to both structures and human users. In this report, the sound level from PGTs is measured in an anechoic chamber based on human aural characteristic, and basic features of sound are investigated. Gear noise is generated by the vibration force due to varying gear tooth stiffness and the vibration force due to tooth surface error, or transmission error (TE). Dynamic TE is considered to be increased because of internal and external meshing. The vibration force due to tooth surface error can be ignored owing to almost perfect tooth surface. A vibration force due to varying tooth stiffness could be a major factor.

Bond graph models of structured parameter uncertainties

2005 ◽  
Vol 342 (4) ◽  
pp. 379-399 ◽  
Author(s):  
Casimir Sié Kam ◽  
Geneviéve Dauphin-Tanguy
Keyword(s):  
Bond Graph ◽  
Parameter Uncertainties ◽  
Graph Models

Nonregular Static State Feedback for Linear Bond Graph Models

2001 ◽  
Vol 34 (13) ◽  
pp. 71-76
Author(s):  
C. Sueur ◽  
A. Karim ◽  
G. Dauphin-Tanguy
Keyword(s):  
State Feedback ◽  
Bond Graph ◽  
Graph Models ◽  
Static State ◽  
Static State Feedback

scholarly journals Approximation of Linearized Systems to a Class of Nonlinear Systems Based on Dynamic Linearization

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 854
Author(s):  
Raquel S. Rodríguez ◽  
Gilberto Gonzalez Avalos ◽  
Noe Barrera Gallegos ◽  
Gerardo Ayala-Jaimes ◽  
Aaron Padilla Garcia
Keyword(s):  
Nonlinear System ◽  
Nonlinear Systems ◽  
Nonlinear Dynamic ◽  
Bond Graph ◽  
Physical Domain ◽  
Graph Models ◽  
Simple Task ◽  
Analysis And Synthesis ◽  
Simulation Results

An alternative method to analyze a class of nonlinear systems in a bond graph approach is proposed. It is well known that the analysis and synthesis of nonlinear systems is not a simple task. Hence, a first step can be to linearize this nonlinear system on an operation point. A methodology to obtain linearization for consecutive points along a trajectory in the physical domain is proposed. This type of linearization determines a group of linearized systems, which is an approximation close enough to original nonlinear dynamic and in this paper is called dynamic linearization. Dynamic linearization through a lemma and a procedure is established. Therefore, linearized bond graph models can be considered symmetric with respect to nonlinear system models. The proposed methodology is applied to a DC motor as a case study. In order to show the effectiveness of the dynamic linearization, simulation results are shown.

scholarly journals Modeling a Helical Fluid Inerter System with Time-Invariant Mem-Models

2020 ◽  
Author(s):  
David Wagg ◽  
Jin-Song Pei
Keyword(s):  
Element Model ◽  
Feedforward Neural Network ◽  
Dynamic Responses ◽  
Experimental Measurements ◽  
The Novel ◽  
State Variables ◽  
Model Concept ◽  
Multilayer Feedforward Neural Network ◽  
Time Invariant ◽  
Model Family

In this paper, experimental data from tests of a helical fluid inerter are used to model the observed hysteretic behaviour. The novel idea is to test the feasibility of employing mem-models, which are time-invariant herein, to capture the observed phenomena by using physically meaningful state variables. Firstly we use a Masing model concept, identified with a multilayer feedforward neural network to capture the physical characteristics of the hysteresis functions. Following this, a more refined approach based on the concept of a multi-element model including a mem-inerter is developed. This is compared with previous definitions in the literature and shown to be a more general model. Through-out this paper, numerical simulations are used to demonstrate the type of dynamic responses anticipated using the proposed time- invariant mem-models. Corresponding experimental measurements are processed to demonstrate and validate the new mem-modeling concepts. The results show that it is possible to have a unified model constructed using both the damper and inerter from the mem-model family. This model captures many of the more subtle features of the underlying physics, not captured by other forms of existing model.

scholarly journals Analysing and simulating energy-based models in biology using BondGraphTools

2021 ◽  
Author(s):  
Peter Cudmore ◽  
Michael Pan ◽  
Peter J. Gawthrop ◽  
Edmund J. Crampin
Keyword(s):  
Systems Biology ◽  
Mathematical Models ◽  
Bond Graph ◽  
Experimental Measurements ◽  
Bond Graphs ◽  
Graph Models ◽  
Conservation Of Energy ◽  
Conservation Of Mass ◽  
Physical Systems ◽  
Complex Interactions

AbstractLike all physical systems, biological systems are constrained by the laws of physics. However, mathematical models of biochemistry frequently neglect the conservation of energy, leading to unrealistic behaviour. Energy-based models that are consistent with conservation of mass, charge and energy have the potential to aid the understanding of complex interactions between biological components, and are becoming easier to develop with recent advances in experimental measurements and databases. In this paper, we motivate the use of bond graphs (a modelling tool from engineering) for energy-based modelling and introduce, BondGraphTools, a Python library for constructing and analysing bond graph models. We use examples from biochemistry to illustrate how BondGraphTools can be used to automate model construction in systems biology while maintaining consistency with the laws of physics.

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