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A multi-point hypoid gear mesh model based on 3-dimensional loaded tooth contact analysis is incorporated into a coupled multi-body dynamic and vibration hypoid gear model to predict more detailed dynamic behavior of each tooth pair. To validate the accuracy of the proposed model, the time-averaged mesh parameters are applied to linear time-invariant (LTI) analysis and the dynamic responses, such as dynamic mesh force, dynamic transmission error, are computed, which demonstrates good agreement with that predicted by single-point mesh model. Furthermore, a nonlinear time-varying (NLTV) dynamic analysis is performed considering the effect of backlash nonlinearity and time-varying mesh parameters, such as mesh stiffness, transmission error, mesh point and line-of-action. Simulation results show that the time history of the mesh parameters and dynamic mesh force for each pair of teeth within a full engagement cycle can be simulated.

Due to the design of lightweight, high speed driveline system, the coupled bending and torsional vibration and rotordynamics must be considered to predict vibratory responses more realistically. In the current analysis, a lumped parameter model of the propeller shaft is developed with Timoshenko beam elements, which includes the effect of rotary inertia and shear deformation. The propeller shaft model is then coupled with a hypoid gear pair representation using the component mode synthesis approach. In the proposed formulation, the gyroscopic effect of both the gear and propeller shaft is considered. The simulation results show that the interaction between gear gyroscopic effect and propeller shaft bending flexibility has considerable influence on the gear dynamic mesh responses around bending resonances, whereas the torsional modes still dominate in the overall frequency spectrum.

Current powertrain active noise control (ANC) systems are not sufficient enough to track the fast engine speed variations, and yield consistent convergence speeds for individual engine order such that a balanced noise reduction performance can be achieved over a broad frequency range. This is because most of these ANC systems are configured with the standard filtered-x least mean squares (FxLMS) algorithm, which has an inherent limitation in the frequency-dependent convergence behavior due to the existence of secondary path model (electro-acoustic path from the input of control loudspeaker to the output of monitoring error microphone) in the reference signal path. In this paper, an overview is given first to compare several recently modified FxLMS algorithms to improve the convergence speed for harmonic responses such as eigenvalue equalization FxLMS (EE-FXLMS) and normalized reference LMS (NX-LMS) algorithms.

Active noise control systems have been gaining popularity in the last couple of decades, due to the deficiencies in passive noise abatement techniques. In the future, a novel combination of passive and active noise control techniques may be applied more widely, to better control the interior sound quality of vehicles. In order to maximize the effectiveness of this combined approach, smarter algorithms will be needed for active noise control systems. These algorithms will have to be computationally efficient, with high stability and convergence rates. This will be necessary in order to accurately predict and control the interior noise response of a vehicle. In this study, a critical review of the filtered-x least mean square (FXLMS) algorithm and several other newly proposed algorithms for the active control of vehicle powertrain noise, is performed. The analysis examines the salient features of each algorithm, and compares their system performance.

High speed, precision geared rotor systems are often plagued by excessive vibration and noise problems. The response that is primarily excited by gear transmission error is actually coupled to the large displacement rotational motion of the driveline system. Classical pure vibration model assumes that the system oscillates about its mean position without coupling to the large displacement motion. To improve on this approach and understanding of the influences of the dynamic coupling, a coupled multi-body dynamic and vibration simulation model is proposed. Even though the focus is on hypoid geared rotor system, the model is more general since hypoid and bevel gears have more complicated geometry and time and spatial-varying characteristics compared to parallel axis gears.

The analytic wavelet transform (AWT) is a wavelet transform that works much like a transient Fourier transform. Therefore the AWT enables utilizing advantages of both the wavelet transform and Fourier transform. A special form of AWT developed for transient vibration and acoustics signal analyses is applied to various engineering signals in this paper. Application examples include a general time-frequency (T-F) analysis, analysis of exposures to impulsive vibrations and noises, and estimation of reverberation times. Some new definitions such as the T-F noise reduction and frequency weighted time history are defined by taking the advantage of unique capabilities of the AWT. Possible automotive applications of these new concepts are briefly discussed.

Automobile brake squeal has been experimentally studied in many ways over the past 65 years. A large body of published research and a substantial amount of unpublished work have attempted to experimentally define the variables involved with and describe the system dynamics initiating the friction-induced self-excited vibration. Much of this work has centered on pin on disk type test rigs used to characterize the contact mechanics and/or friction laws without considering the brake system influence. This paper describes a dynamometer designed and constructed to study brake squeal on a system level.

Spiral bevel gear dynamics are significantly affected by the flexibilities of shafts and bearings. In this study, a new shaft-bearing model has been proposed for computing the effective support stiffness. The results are applied to the lumped parameter dynamic model of spiral bevel geared rotor system with 3-bearing straddle-mounted pinion configuration. Also, using the multi-degree of freedom lumped parameter dynamic model and quasi-static three-dimensional finite element tooth contact analysis program, the responses of two typical shaft-bearing configurations used in automotive applications, that are the 3-bearing straddle mounted pinion configuration and the 2-bearing overhung mounted pinion configuration, are compared. The comparative analysis along with a set of parametric studies highlights their different contributions to the spiral bevel gear mesh characteristics and dynamic response.

This paper provides several examples of silicon “micromachined” semiconductor sensors with which the authors are involved for aerospace condition monitoring. This and related work in MEMS (Micro Electro Mechanical Systems) has the potential to revolutionize condition monitoring in aerospace condition and “health monitoring” by (1) moving “smart” electronics out to the sensor chip itself and (2) combining a vast quantity and types of, not only electronic, but micromechanical sensing schemes into the silicon chip . Precisely formed cantilevers, gears, valves, microplumbing and even micro motors of the cross-section of a human hair can be fabricated on a single silicon microchip. Silicon is an excellent mechanical material with a yield strength several times that of stainless steel. Also silicon has excellent thermal properties , whereas compatible silicon dioxide (which we typically use in connection with silicon microelectronics patterning) is virtually a thermal insulator.

In this work, the goal of enhanced reliability through redundancy is explored. Two levels of fusion have been defined: the first is a fusion of sensors, redundant in both number and type, and the second is a statistical fusion of the resulting data at a software level. An intermediate preprocessing level is required to connect both fusions. The various types of sensors which are included are bulk micromachined flow, pressure and hydrogen sensors and a thin film poly-crystalline silicon temperature sensor. Individual sensors have been fabricated and packaged in arrays. Associated preprocessing has been designed to be able to handle all of the signals coming from each sensor and prepare them for statistical analysis. Data fusion algorithms have been written and tested.

The High Pressure Oxidizer Turbine (HPOT) discharge temperature of the Space Shuttle Main Engine (SSME) was estimated using Radial Basis Function Neural Networks (RBFNN) during the startup transient. Estimation was performed for both nominal engine operation and during simulated input sensor failures. The K-means clustering algorithm was used on the data to determine the location of the basis function centers. The performance of the RBFNN is compared with that of a feedforward neural network trained with the Quickprop learning algorithm.

Efforts have been made to utilize Al constructs to identify flaws in the Space Shuttle Main Engine (SSME) faceplate regions. In order to expand the applicability of these algorithms to a larger problem domain, the automatic visual inspection system(AVIS) has been modified to enable a user with little or no image processing background to define a system capable of identifying flaws on a given set of imagery. This system requires the user to simply identify flawed regions and the selection of processing and feature descriptors is performed automatically. This paper explicates the motivations, definitions, and performance issues associated with the AVIS paradigm.

Electrically passive optical sensors have been formed using optical waveguides and micromachined-micromechanical structures on silicon substrates. We present recent results on an interferometric pressure sensor where pressure-induced strain in a micromachined diaphragm alters the path length of an optical channel waveguide ring resonator. Pressure is detected as a change in the resonant condition of the ring and found to vary linearly over a range of -100 to 400 kPa with a sensitivity of 0.0094 rad/kPa. Problems with attaching this sensor for testing will be discussed. Our second device is an intensity-type accelerometer utilizing a micromachined cantilever beam. Light transmission across a gap between two channel waveguides, one located on a beam bent by acceleration and another which remains fixed, is measured optically. We show preliminary measurements of the coupling between two closely spaced waveguide sections which agree with overlap integral calculations.

Building and operating dependable systems is fundamental to many critical applications, such as designing integrated hardware and software systems for vehicles or satellites. Dependable systems techniques, methods, and tools are developed and used by researchers and practitioners working in widely varying disciplines. In order to provide a unifying framework for the successful dissemination and sharing of dependability results, the development of a dependable systems knowledge base is underway.1 Two database support subsystems are under development: one that manages the storage and retrieval of document information, as well as communicating between the user interface layer and the physical database layer, and another that manages the lexicon of dependability terminology for the user interface layer. The system will provide access to information in a sophisticated, intelligent manner that enables a human user to function more effectively in learning and decision-making capacities.

A proposed multi-coordinate spectral-based inverse substructuring approach is applied experimentally to examine the vibration transmissibility through chassis mounts. In this formulation, the vehicle system is partitioned into two substructures. One substructure comprises of the chassis and suspension, while the second one is the body structure and other attached components. The approach yields the free substructure dynamic characteristics that are extracted from the measured coupled system response spectra. The resultant free substructure transfer functions are verified by comparison of the re-synthesized results to the actual vehicle system measurements. A real life vehicle setup is utilized to demonstrate the salient features and capabilities of this approach, which includes the ability to compute the main structure-borne paths, dynamic interactions between the chassis and body, and interior noise and vibration response.

Vehicle electronics and sensor systems have become indispensable parts in providing safety, comfort, personal communication mobility and many other advanced functions in today's vehicles. As a result, reliability requirements for these critical parts have become extremely important. To meet these requirements, more advanced technologies and tools for degradation monitoring and failure prevention are needed. Currently, the development of diagnostics and prognostics techniques, which employ accurate degradation quantification by appropriate sensor selection, location decision, and feature selection and feature fusion, still remains a vital and unsolved issue. This paper addresses several realistic concerns of failure prevention in vehicle electronics and sensor systems. A unified monitoring and prognostics approach that prevents failures by analyzing degradation features, driven by physics-of-failure, is suggested as a general framework to overcome the unsolved challenge.

Test sensors are evaluated for noise path analysis applications. Newly developed ICP™ piezo-electric strain gages are used with accelerometers and microphones in a conventional noise path analysis test on the front body/suspension attachment points of a vehicle. In a less conventional application, a steering knuckle is converted into a 6-DOF force transducer using an array of strain gages and using an array of 3-DOF load cells. The two sensor arrays are both calibrated with a 6-DOF load cell. The result is an estimate of the three translation force and three moment operating inputs entering the steering knuckle from the wheel.

Squeak and rattle (S&R) problems in body structure and trim parts have become serious issues for automakers because of their influence on the initial quality perception of consumers. In this study, various CAE and experimental methods developed by Hyundai Motors for squeak and rattle analysis of door systems are reported. Friction-induced vibration and noise generation mechanisms of a door system are studied by an intelligent combination of experimental and numerical methods. It is shown that the effect of degradation of plastics used in door trims can be estimated by a numerical model using the properties obtained experimentally. Effects of changes in material properties such as Young's modulus and loss factor due to the material degradation as well as statistical variations are predicted for several door system configurations. As a new concept, the rattle and squeak index is proposed, which can be used to guide the design.

A combined lumped parameter, finite element (FE) and boundary element (BE) model is developed to predict the whine noise from rear axle. The hypoid geared rotor system, including the gear pair, shafts, bearings, engine and load, is represented by a lumped parameter model, in which the dynamic coupling between the engaging gear pair is represented by a gear mesh model condensed from the loaded tooth contact analysis results. The lumped parameter model gives the dynamic bearing forces, and the noise radiated by the gearbox housing vibration due to the dynamic bearing force excitations is calculated using a coupled FE-BE approach. Based on the predicted noise, a new procedure is proposed to tune basic rear axle design parameters for better sound quality purpose. To illustrate the salient features of the proposed method, the whine noise from an example rear axle is predicted and tuned.

The compressor surge line of automotive turbochargers can limit the low-end torque of an engine. In order to determine how close the compressor operates to its surge limit, the Hurst exponent of the pressure signal has recently been proposed as a criterion. The Hurst exponent quantifies the fractal properties of a time series and its long-term memory. This paper evaluates the outcome of applying Hurst exponent based criterion on time-resolved pressure signals, measured simultaneously at different locations in the compression system. Experiments were performed using a truck-sized turbocharger on a cold gas stand at the University of Cincinnati. The pressure sensors were flush-mounted at different circumferential positions at the inlet of the compressor, in the diffuser and volute, as well as downstream of the compressor.