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Gear fault diagnosis is important in the vibration monitoring of any rotating machine. When a localized fault occurs in gears, the vibration signals always display non-stationary behavior. In early stage of gear failure, the gear mesh frequency (GMF) contains very little energy and is often overwhelmed by noise and higher-level macro-structural vibrations. An effective signal processing method would be necessary to remove such corrupting noise and interference. This paper presents the value of optimal wavelet function for early detection of faulty gear. The Envelope Detection (ED) and the Energy Operator are used for gear fault diagnosis as common techniques with and without the proposed optimal wavelet to verify the effectiveness of the optimal wavelet function. Kurtosis values are determined for the previous techniques as an indicator parameter for the ability of early gear fault detection. The comparative study is applied to real vibration signals.

In this paper, a nonlinear semi-active vehicle suspension system using MR fluid dampers is investigated to enhance ride comfort and vehicle stability. Fuzzy logic and fuzzy self-tuning PID control techniques are applied as system controllers to compute desired front and rear damping forces in conjunction with a Signum function method damper controller to assess force track-ability of system controllers. The suggested fuzzy self-tuning PID operates fuzzy system as a PID gains tuner to mitigate the vehicle vibration levels and achieve excellent performance related to ride comfort and vehicle stability. The equations of motion of four-degrees-of-freedom semi-active half-vehicle suspension system incorporating MR dampers are derived and simulated using Matlab/Simulink software.

The bearing capacity of soils stands as one of the most important parameters that determine the vehicles’ off-road mobility. Soil bearing capacity can be determined either experimentally or by calculation using analytical and or empirical formulas. One of the most famous formulas is the Bekker's. Recently, Artificial Neural Networks (ANNs) technique became a powerful tool that can be used for predicting systems’ behavior and performance. The main objective of this paper is to predict the bearing capacity of the soil (plate-sinkage relationships) by using Artificial Neural Networks and to compare the actual results of soil bearing capacity (collected data from Ph.D. Thesis) with results obtained from neural network model and Bekker's formula. The comparison showed clear superiority and accuracy of neural network technique. Another objective is to check the generalization ability of the neural network model in predicting the plate-sinkage relationships by using the hypothetical plate.

In the design of recreational vehicle alternators, a particular challenge arises from marketing and engineering teams' desire to ensure that their products meet “best in class” sound quality characteristics. Furthermore, it is desirable to know these characteristics in measurable engineering terms in the product design stage, preferably before prototypes are built and tested. However, the aim of this paper is to investigate experimentally the electromagnetic sound quality characteristics of a vehicle alternator with the view of determination. For this reason, a special test rig was designed to simulate the alternator electromagnetic noise source. The results indicate that significant information can be obtained for this source. This can be an effective way to control this generated noise and consequently improve the vehicle alternator sound quality and look promising.

Vehicle suspension along with tires and steering linkages is designed for safe vehicle control and to be free of irritating vibrations. Therefore the suspension system designs are a compromise between ride softness and handing ability. However, this work is concerned with a theoretical investigation into the ride behavior of actively suspended vehicles. It is based on using fuzzy logic control (FLC) to implement a new sort of active suspension system. Comparisons between the behavior of active suspension system with FLC with those obtained from active systems with linear control theory (LQR), ideal skyhook system and the conventional passive suspension systems. Results are introduced in such a way to predict the benefits that could be achieved from fuzzy logic system over other competing systems. Furthermore, a controller is designed and made by using results of FLC system, theoretical inputs are used to examine the validity of this controller.

The DC power supply is ingredient part in the automotive industries as it has been used as a DC power supplies for a wide range of loads. Meanwhile, it is mandatory for battery charging. These types however, causes many problems such as poor power factor, high input current harmonics distortion and uncontrolled DC voltage. In this paper, an improved input power factor correction that uses a combined control system consists of two nested loops with a feedback of the DC voltage and input current as long as a feed forward from the output power. The system has been analyzed, modeled, simulated and experimentally verified. The novel feature of the proposed control scheme resides in fact that it is not only achieve nearly unity power factor with minimum input current total harmonics distortion only but it also introduce superior performance in DC voltage transient conditions.

In this paper, a hybrid roll control system, including passive and active roll control units, is designed to improve the roll dynamics of tanker vehicles and to reduce the lateral shifts of the liquid cargo due to lateral accelerations. The passive control system consists of radial partitions installed inside the vehicle container. These partitions rotate in phase with the liquid cargo as one unit about the longitudinal axis of the container in response to the induced momentum forces due to the lateral acceleration excitation. Torsion dampers are fixed between the partitions and the container's front and rear walls to reduce the oscillating motion of the liquid cargo. While the passive partition dampers control the dynamics of the liquid cargo inside the container, the dampers of the vehicle suspension are switchable, generating anti-roll damping moments based on the lateral acceleration level and the container filling ratio.

During the last few decades, fibrous composite materials have been diversified and replaced some traditional metallic materials. These materials provide high strength to weight ratio together with high environmental corrosion resistance. One of the basic engineering applications, which have been attracted by the properties of these composites, is the automotive engineering. In this paper, the authors manipulated the composite C-compression springs as a new trend of vehicle suspension system instead of coil or leaf springs. This type of springs can be safely and efficiently implemented in the vehicles' suspension systems and most probably be used in the new suspension design proposed earlier by one of the authors. Previous work on this context had shown a quality nature and economical technology in the use of composite springs in transportation and/or industrial applications.

In this paper, the Kalman filter algorithm is used to design a practical adaptive control strategy. The adaptation is intended to adjust the system operation according to the changes of road input. A moderate adaptive time of at least 3 seconds is used. Limit stops are added to prevent the increase in the wheel travel behind the specified limit. The active suspension feedback system is designed based on measuring only the suspension displacement. A gain scheduling adaptive scheme which consists of four sets of state feedback gains is designed. The estimation process of dynamic tyre deflection and other necessary state variables through the Kalman filter is illustrated. Among other things, this estimate is used to derive the gain scheduling adaptive scheme. The strategy is applied to a quarter car active suspension system. Results are generated at a constant speed on random road profiles.

E-spring is a recent innovation in vehicle suspension springs. Its behavior and characteristics are investigated experimentally and verified numerically. The mechanical and frequency-response-based properties of E-springs are investigated experimentally at both of the structural and constitutional levels. Thermoplastic-based and thermoset-based fibrous composite structures of the E-springs are modified at micro-scale with various additives and consequently they are compared. The experimental results reveal that additives of micrometer-sized particles of mineral clay to an ISO-phthalic polyester resin of the composite E-spring can demonstrate distinguished characteristics. A hybrid approach of the inter-laminar shear stress and Tsai-Wu criteria is implemented in order to identify failure indices numerically at the utmost level of loading and verify the experimental results.

Many basic studies were conducted to discover the main reason for squeal occurrence in both disc and drum brake systems. As, it is well-known that the squealed brake system is more effective than the non-squealed brake system and it is also a common discomfort. So, cancellation of the squeal is not preferable, however, elimination of the brake squeal is a favorable. An approach to study the drum brake squeal is presented based mainly on the Finite Element Method (FEM) representation. The brake system model is based also on the model information extracted from finite element models for individual brake components. This finite element method (FEM) was used to predict the mode shape and natural frequency of the brake system after appropriate verification of FEM.

The main objective of this research is to find a general empirical formula to predict vehicle frontal area applied to most types of vehicles. This was done on 21 vehicles; passenger cars, buses and trucks by calculating their frontal area by using image processing technique on cars photos extracted from catalogues. The software (Data Fit) is used to establish the required empirical formula. The results showed that the empirical formula is simple and accurate enough for finding out the vehicles frontal areas.

A non-contact analysis of a drum brake based on three-dimensional Finite Element analysis using Ansys is presented. The effect of drum-lining interface stiffness and line pressure on the interface contact is examined. The modal analysis of the vehicle drum brake is also studied to get the natural frequency and instability of the drum. It is shown that the unsymmetric modal analysis is efficient enough to solve this linear problem after transforming the non-linear behaviour of the contact between the drum and the lining to a linear behavior. A linear element which is used in the modal analysis is transferred to non-linear elements which are Targe170 and Conta173 that represent the drum and lining to study the contact analysis. The contact analysis problems are highly non-linear and require significant computer resources to solve it, however, the contact problem give two significant difficulties.

The previous research work on Active Independent Front Steering (AIFS) system concluded an enhanced vehicle response and tire adhesion utilization. Some research emphasizes the importance of Tire Work load (TWL) in the generation of maximum possible tire forces that ensures vehicle controllability and stability. In this study, a mathematical model is constructed to investigate the effect of TWL as a parameter on AIFS performance. Toward such a target, a new Fuzzy control strategy is developed based on TWL and vehicle yaw rate as control inputs for the AIFS controller. Unfortunately, the TWL is not a measurable parameter or even easy to be estimated. Consequently, another control strategy was implemented based on slip angle and vehicle yaw rate as inputs for the AIFS controller.

Vehicle suspension is considered a vital system of modern automotive and necessary to offer an adequate level of ride comfort and roadholding. In the present paper, a fuzzy-based sliding surface (FBSS) controller is designed, as a system controller for the first time, for a semi-active vehicle suspension using a magnetorheological (MR) damper in order to minimize the transmitted unwanted vibrations to the passengers. Therefore, an ideal reference skyhook model is employed to construct the sliding surface, which is the input of fuzzy logic. MR damper is a semi-active device and is controlled indirectly using an external voltage source. So a neural-based damper controller is used to compute the applied voltage to the magnet coil of the MR damper in series with the FBSS system controller. The proposed semi-active controlled quarter-vehicle suspension using an MR damper is solved numerically by Matlab.

A hybrid search optimization is presented in order to optimize hybrid laminated fibrous composite E-springs for vehicle suspension systems. This optimization is conducted with both of the geometrical configuration and laminate structure of the E-spring. A genetic algorithm along with a hill-climbing random-walk approach are used through a developed NURBS-based technique in order to conduct this optimization. A mathematical-modeling-based mid-ware technology is introduced in order to fully automate the optimization process through linking the run engines of mathematical modeling and finite element analysis from within the mathematical modeling engine. A hybrid approach of the inter-laminar shear stress and Tsai-Wu criteria is first implemented in order to identify failure indices of the resulting optimum shape and laminate structure.

Adaptive neuro-fuzzy inference system (ANFIS) technique has been developed and applied by numerous researchers as a very useful predictor for nonlinear systems. In this paper, non-parametric models have been investigated to predict the direct and inverse nonlinear dynamic behavior of magnetorheological (MR) fluid dampers using ANFIS technique to demonstrate more accurate and efficient models. The direct ANFIS model can be used to predict the damping force of the MR fluid damper and the inverse dynamic ANFIS model can be used to offer a suitable command voltage applied to the damper coil. The architectures and the learning details of the direct and inverse ANFIS models for MR fluid dampers are introduced and simulation results are discussed. The suggested ANFIS models are used to predict the damping force of the MR fluid damper accurately and precisely. Moreover, validation results for the ANFIS models are proposed and used to evaluate their performance.

The anti-lock brake system (ABS) is a vital system in modern vehicles that prevents automotive wheels from locking during an emergency brake. This paper aims to introduce an efficient, optimized proportional integral derivative (PID) controller tuned using a genetic algorithm (GA) to enhance the performance of ABS. The PID control method is a very famous control algorithm employed in numerous engineering applications. The GA is used to solve the nonlinear optimization problem and search for the optimum PID controller gains by identifying the solution to the problem. A mathematical model of ABS is derived and simulated using Matlab and Simulink software. The proposed optimized PID-controlled ABS is compared to the conventional ABS controlled using a Bang-Bang controller. System performance criteria are evaluated and assessed under different road adhesion coefficient values to judge the success of the proposed PID controller tuned using GA.

In this paper, a fuzzy-PID controller is applied in a half vehicle active suspension system to enhance vibration levels of vehicle chassis and passenger seat. The fuzzy-PID controller consists of fuzzy and PID connecting in a series manner, the fuzzy output is considered as the PID input. Genetic Algorithm (GA) is selected to tune controller parameters to obtain optimal values that minimize the objective function. The equations of motion of five-degrees-of-freedom active half-vehicle suspension system are derived and simulated using Matlab/Simulink software. Double bumps and random road excitations are used to study the performance of suspension systems including bounce and pitch motion. The performance of the active suspension system using optimized fuzzy-PID controller is compared with conventional passive to show the efficiency of the proposed active suspension system.

Welding is an excellent attachment or repair method. The advanced industries such as oil, automotive industries, and other important industries need to rely on reliable welding operations; collapse because of this welding may lead to an excessive cost in money and risk in human life. In the present research, an automatic system has been described to detect, recognize and classify welding defects in radiographic images. Such system uses a texture feature and neural network techniques. Image processing techniques were implemented to help in the image array of weld images and the detection of weld defects. Therefore, a proposed program was build in-house to automatically classify and recognize eleven types of welding defects met in practice.