Abstract
Equipment fault diagnosis plays an important role in industry as it can increase productivity, product quality and life of machinery. However, existing diagnostic tools cannot detect randomly occurred faults and are too complex and expensive to use. Therefore, many failure warnings have been missed and ultimately leads to fatal machine breakdown and affects the company operation seriously. The Smart Asset Maintenance System (SAMS) is an effective, low-cost, portable and easy-to-use monitoring and diagnostic tool for equipment preventive maintenance. The system is equipped with the state-of-the-art tools to detect periodically and randomly occurred faults. It can perform fault diagnosis through either direct listening to the equipment operating sound for routine maintenance or an intensive analysis for research purpose. SAMS has been tested successfully in many industrial machines. Using SAMS makes the health monitoring of equipment simple but affordable.

Features
• low cost as the system is implemented by virtual instruments, which can be as low as 1/10 of the cost of commercially available hardware type of instruments;
• portable as it provides USB, PCMCIA, or wireless interface for connecting sensors to a notebook PC or a pocket PC.
• easy-to-use by detecting faults via instant visual or audible inspection;
• equipped with state-of-the-art tools, such as fast Fourier transform, envelop detection, exact wavelet analysis, active noise cancellation, orbit analysis, impact test, 3D trend plot for fault prediction, smart data manager etc.
• automatic report generation and alarm level setting
• Web-based equipment remote sensing and health monitoring
• user-friendly and video type of self-learning for training purpose.

Applications
The scope of application for SAMS is wide. It is applicable to industries such as air conditioning, production lines, lifts and escalators, transportation, and marine. SAMS has been tested successfully in many industrial machines, such as traction motors on trains, chillers in buildings, water pumps, stacker cranes for logistics and warehouse, press rollers for offset printing machinery, beverage production lines, and milling machines, etc.

Contact Information
Mr H Y Wong
Director, Technology Transfer Office
City University of Hong Kong
83 Tat Chee Avenue
Kowloon, Hong Kong
Tel : (852) 2788 8428
Fax : (852) 2788 9119
Email : hy.wong@cityu.edu.hk