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Operational modal analysis techniques classically have been developed based on the assumption that the input to the system is a stationary white noise. While, in many practical cases, the systems are excited by combination of white noise and colored noises (harmonic excitations). Consequently, in conditions where non-white noises are present, the existing OMA methods cannot completely distinguish between the system poles and the induced poles due to colored noises. In order to overcome this weakness of OMA methods, some researches have been conducted in the field. In this paper, a new method is proposed for identifying the modal parameters of the system under the unknown colored noises, based on the Power Spectral Density Transmissibility (PSDT) function. In this work, the proposed methodology is established upon applying the auxiliary force, which can re-excite the system under operational conditions.

Operational modal analysis based on power spectral density transmissibility functions (PSDT) is a powerful tool to identify the modal parameters with low sensitivity to excitations. The rotor systems may have the asymmetric damping or stiffness matrices which can lead to increase the difficulties of the identification procedure. In this paper, a new method is proposed to identify the modal parameters of the asymmetric rotary systems by the operational modal analysis based on the power spectral density transmissibility functions. For pole extraction from the PSDT function, a proper parametric identification method such as the Poly-reference Least Squares Complex Frequency-domain method (PLSCF) or poly-Max method can be used. Then, the rotary system poles can be identified from a Stabilization Diagram (SD) with overestimating the system model order. The proposed algorithm is validated by a computer simulation.

Angular contact ball bearings are the most commonly used types of bearings. Although simple in appearance, these bearings have a complicated and nonlinear behavior, and have significant effect on the dynamics of a rotating system. Accounting for high speed effects adds to the complexity of their behavior. The governing equations of the bearing amount to the solution of a set of nonlinear equations for each rolling element at each iteration, which represents a tedious and expensive solution. In this work, a simplified model for angular contact ball bearings under the action of arbitrary loading including high speed effects and preload is presented. The model considers five degrees of freedom for relative displacement of rings and a mean contact angle for inner and outer raceway contacts are introduced which renders the solution for all rolling elements to that for a single one.

In this research, important parameters of a rack and pinion steering system in dynamic steady state and transient responses have been investigated. For this purpose, virtual model of a medium passenger car in ADAMS/Car has been used. The model has up to 121 kinematic degree of freedom and includes all components of the rack and pinion steering system. Several different experimental test results have confirmed the validity of the model. Sensitivity analysis have been done based on design of experiments (DOE) method. Two level fractional factorial designs have been selected for this purpose. Steady state cornering and step steer input are the analysis that used for this research. Understeering coefficient, steering wheel torque and steering sensitivity are obtained from the steady state cornering analysis, while the step steer analysis yields yaw velocity overshoot, yaw velocity rise time, lateral acceleration overshoot, lateral acceleration rise time and roll angle overshoot.

This paper focuses on design and modeling of anti-roll system for a subcompact passenger car. The system consists of Hydraulic Assisted torsion bars on car suspensions, a hydraulic power unit, and controls. A 158 degrees of freedom model of the car basic dynamics is made in ADAMS software. A bond graph model of the hydraulic anti roll system is contracted and its state equations are entered into MATLAB/Simulink. The two software are linked and a complete model is made for study and controller design. This paper introduces the method as a useful tool for vehicle dynamics studies and discusses the problems and advantages of the method.

Genetic Algorithm is applied to the physical parameter estimation of a full vehicle nonlinear multi-body ride model. Beforehand unity of system representation (identifiability) and sensitivity analysis for determining the effects of parameter changes on the response of the vehicle is discussed. A random road profile is designed as a persistent excitation. Input-output data required for the identification is obtained from ADAMS/CAR simulations of a more complex model. Robustness of the identification method is studied by adding different noise levels to the ADAMS output signals. Validation of the results is carried out by comparison of the identified model outputs with experimental measurements done on the same vehicle, which its ADAMS model was available. Test was performed on the Schenck hydropuls road simulator. Accuracy of estimated parameters is evaluated by information available from other sources such as technical drawings and performance tests of the vehicle parts.

A neural network model of a full car has been developed here on the basis of ADAMS simulation results. The model basically intended for roll control studies, is a completely non-liner model and has 104 degrees of freedom. ADAMS software has been used to determine the model behavior to specific steering inputs. The out put of the simulation program was then used to train a neural network constructed to approximate the model for controller design and real time studies of control action. Specific time delayed feedback inputs to the neural network resulted an efficient approximate model with good accuracy for control tasks.