Saud Altaf

Research Objectives

Industrial Fault Traceability using distributed fault signature analysis

Industrial machine incipient fault detection and diagnosis are important and difficult topics in the computer engineering field. These topics deal with motors ranging from small DC motors used in intensive care units to the huge motors used in industrial sector. With proper machine monitoring, fault detection schemes, improved safety and reliability can be achieved for different engineering system operations. The importance of incipient fault detection can be found in the cost saving which can be obtained by detecting potential machine failures before they occur. Non-invasive, economical, and consistent fault detection techniques are often preferred by many engineers. A large number of techniques, such as expert system approaches and vibration analysis etc have been developed for machine fault detection purposes. Those techniques have achieved a certain degree of success. However, due to the complexity and importance of the systems, there is a need to further improve existing fault detection techniques. The aim of my research is to develop a remote WSN scheme of machine fault detection using distributed fault signature analysis techniques.

Conference Papers

  • Tahir, N., Altaf, S., "A supportive Immunological Approach for Detecting Network Anomaly", Elsevier Editorial System (submitted)
  • Altaf, S., Azam, C. M., "Future eLearning prospects and challenges: Higher Education in Pakistan", Paper presented to the Second International SOLSTICE Conference on "Researching eLearning for Innovation and Development" at the EDGEHILL University Ormskirk, UK, 11 May 2007.
  • Altaf, S., Azam, C. M., "The Future Challenges of Biometrics", Multimedia Cyberscape Journal Malaysia, Volume 3, Number 2, Year 2005, p.p 20-27.