Farag K. Omar

Mathematical modeling of gearbox including defects with experimental verification

A nine degree-of-freedom model of one stage gear system is presented in this research work. The gearbox structure is coupled with the vibration of the gear shaft. The model considers gear size, errors, and faults. The model includes varying meshing stiffness and a realistic representation of the gear transmission error (TE) and gear faults. Gear TE is modeled as a displacement excitation. The model equations are solved using Matlab and using parameters representing a real experimental gearbox rig. Experimental and simulated data are compared for different operating speeds, torque loads, and gear cracks. The simulation results are in good agreement with the experimental ones. The authors believe that the model presented here can be used in studying gear faults and would be very useful in developing gear fault monitoring techniques.

Control of interval parameter overhead cranes via Monte Carlo simulation

Variations in system parameters because of changing operating conditions could result in deteriorated system performance. To ensure robustness, modelling of such systems requires uncertain parameters to be dealt with as interval quantities. An overhead crane is a type of system that has inherent variation in some of its parameters. These parameters include cable length, trolley mass and payload. Hence, the interval parameter concept plays an important role in the control of overhead cranes. This paper considers the control problem of an overhead crane system with interval parameters. The paper presents a new technique based on Monte Carlo simulation to select properly optimal controller parameters. The objective of the control is to minimize the overshoot of the swing angle response throughout the crane travel regardless of the variations of the cable length. The cable length is assumed known within lower and upper bounds. The presented results show the usefulness of the Monte Carlo simulation approach as applied to the control problem of overhead cranes. A scaled-down crane model has been built and used to validate the results of the numerical simulation.

Gear tooth diagnosis using wavelet multi-resolution analysis enhanced by Kaiser’s windowing

Wavelet multi-resolution analysis shows promising results for gear tooth damage diagnostics. However, selecting an accurate mother wavelet, defining dynamic threshold value and identifying the resolution levels to be considered in gear fault detection and diagnosis are still challenging tasks. This paper proposes an enhanced wavelet-based technique for detecting, locating and estimating the severity of defects in gear tooth fracture. The proposed technique improves the wavelet multi-resolution analysis by decomposing the noisy data into different resolution levels with data sliding through Kaiser’s window. Only the maximum expansion coefficients at each resolution level are used in de-noising, detecting and measuring the severity of the defects. A small set of coefficients is used in the monitoring process without assigning threshold values or performing signal reconstruction. The proposed technique shows accurate results in detecting and localizing gear tooth fracture.

Optimum controller design of an overhead crane: Monte Carlo versus pre-filter-based designs

In this paper, we consider an overhead crane model with some of its parameters known within given upper and lower bounds. It is shown that a controller with single valued gains based on the nominal values of the parameters could lead to unsatisfactory performance. Two design methodologies are applied to guarantee the desired performance of the considered overhead crane model and their results are compared. The first method utilizes the Monte Carlo approach to find optimum values of the controller gains based on minimizing a least-square error function representing the deviation of the swing angle from a desired trajectory. The second method uses a pre-filter to ensure that the closed-loop performance lies within two given desired responses. Simulation results are provided to compare the performance of the two methods where both show reasonable responses. The Monte Carlo-based approach, however, does not require additional hardware components, compared with the pre-filter technique.

Integrating EIS and Wavelet Multi-Resolution Analysis; Part 1: Enhancing Monitoring of Nonconductive Coatings

The goal of this study is to develop a new tool for enhancing monitoring and modeling the quality of nonconductive coatings. The work is divided into two parts. In part 1, the time-frequency domain features using wavelet-based tool and the traditional Electrochemical Impendence Spectroscopy (EIS) measurements are integrated to enhance the monitoring process. In part 2, the modeling process of nonconductive coatings by integrating both tools is described. In this paper, enamel coatings on aluminum substrates are excited with high frequency voltage source of a square wave using three-electrode arrangement. Signals of non-stationary features of the current and voltage response of an enamel coated sample are analyzed using a wavelet-based tool. The rapid result extracted from the wavelet transform is used to detect and monitor any variation in the enamel coating and hence identify the locations where further investigation using EIS should be implemented. The proposed technique is implemented on large sets of laboratory data and shows promising results.

Effect of Dual Fuel Engine Parameters and Fuel Type on Engine Noise Emissions

Investigating experimentally the effects of different fuel types and engine parameters on the overall generated engine noise levels. Engine parameters such as: Engine speed, Injection timing angle, engine loading, different pilot fuel to gases fuel ratio and engine compression ratio. Engine noises due to combustion, turbulent flow and motoring were reported in this study by direct sound pressure level SPL (dB) measurements and compared to the maximum cylinder pressure rise rate with respect to the engine crank angle (dP/dθ)max . Experimental procedures conducted using a Ricardo diesel version variable compression research engine. The study was conducted for three different fuels: single diesel fuel, and dual fuel engine that uses LPG or natural gas. The study for each fuel type covered the following operating parameters range, engine speed from 20–28 rev/sec, injection timing form 20 to 45° BTDC, compression ratio from 16 to 22, load range 2 to 14 N.m, and ratio of pilot to gaseous fuel from 0 to 10%. The study reported the location (crank angle) corresponding to maximum cylinder pressure and max pressure rise rate. Results from testing dual fuel engine with varying design and operating parameters are presented and discussed. The present work reported higher SPL (dB) generated from burning a dual fuel compared to burning diesel fuel only.Copyright