Rahman Yousefi Moghaddam

Education:

·         PhD Candidate, Mechanical Engineering, University of Alberta, Canada           2007 – Present

·         PhD Candidate, Mechanical Engineering, University of Manitoba, Canada        2005 – 2007

·         MSc, Mechanical Engineering, University of Guilan, Iran                                    2003 – 2005

·         BSc, Mechanical Engineering, University of Guilan, Iran                                    1998 – 2003

 

Selected Publication:

·         Yousefi Moghaddam R. and Lipsett Michael G., Developing a Shovel Test Rig for Fault Diagnosis Studies of Time-varying Systems, to be Submitted to Journal of MSSP

·         Yousefi Moghaddam R. and Lipsett Michael G., Design, Commissioning & Modeling of A Shovel Test Rig For Fault Diagnosis Of A Time-Varying System, 8 pages, CSME 2010

·         Yousefi Moghaddam R. and Lipsett Michael G., Modeling, Simulation & Fault Detection in Excavators with Time-Varying Loading, 6 pages, IEEE/ASME AIM 2010

·         Yousefi Moghaddam R. and Lipsett Michael G., Reliability Assessment and Condition Monitoring of a Shovel Test bed, 8 pages,  3rd World Congress on Engineering Asset Management (WCEAM-IMS), Beijing, China October 2008

·         Yousefi Moghaddam R. and Lipsett Michael G., Dynamic Effects of Ground Looseness on Hydraulic Shovel Performance,8th International Workshop on Bifurcations and Degradations in Geomaterials (IWBDG), Lake Louise, Canada, May 2008

Project Title: Design, Commissioning & Modeling of A Shovel Test Rig for Fault Diagnosis of A Time-Varying System

 

Motivation: The time-varying nature of the soil-tool interaction forces, causes stresses in machine components and may result in damage. Avoiding fault propagation in the system depends on identifying and isolating the faulty component in the early stages of failure, which requires close observations of the tool-ground interaction period.

 

Objectives: Assuming that a fault does not occur instantaneously, there would be a degradation process that shifts the state of the system from normal to abnormal over a period of time, and this variation is identifiable in most cases using fault detection techniques. Having a proper test rig, we would like to investigate the application of FDI techniques on the performance of the system.

 

Solution methodology: A variant of crank-slider mechanism is equipped with a thin plate mounted on the slider to fragment the soil. The whole system is modeled as a rigid-body, lumped-parameter, dynamical system. The Coulomb-Mohr earth pressure model used to represent the soil-tool interaction. The rig is equipped with sensors that acquire data from different machine parts to monitor the process as well as machine condition. Residual signals need to be defined based on the difference between the actual readings and the predictions.

 

Progress to date: Cutting force prediction and soil parameter estimation achieved by digging through a certain medium at various depths of penetration and blade angles. Processing the acquired signals, fault signatures are successfully identified for certain types of fault in the rig components, without any prior knowledge of the fault type or position. Next steps are: Design of experiments, Detailed soil parameter estimation, Model validation, Model-based FDI, and finally study the application of fault tolerant control on the system and its effect on the reliability of the system.

 

Limitations: A failure modes and effects analysis (FMEA), might be required in advance. Compared to signal-based approaches, an accurate model of the system is necessary for any model-based fault detection technique, which is not always available through the conventional methods. Additionally, If the system behaves nonlinearly, linearization is also required. Simplifications in the model might affect the accuracy of the study.

 

Expected completion date: December 2011

 

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