Mo-Yuen Chow


Key words:

Intelligent systems, Control systems, Distribution systems, Electric machinery, Outage management

Research description:

Dr. Chow is working in the area of Control and Networking. His core technology is diagnosis and control, artificial neural network and fuzzy logic. Since 1987, Dr. Chow has been applying his core technology to areas including motors, process control, power systems and communication systems. Dr. Chow's recent research projects include:

Laboratory facilities:

1 ADAC Lab Establishment

National Science Foundation has supported Dr. Chow with the NSF Equipment Grant: Fast Prototyping System for Motor Incipient Fault Detection to establish the Advanced Diagnosis and Control Laboratory (ADAC lab) to verify our theoretic and simulation results experimentally with an actual motor system. The motor fault detection and diagnosis scheme has been implemented in a dedicated personal computer connected directly to an actual motor through a data acquisition system to validate its performance for on-line motor monitoring, fault detection and diagnosis.

2 MotorSIM and MotorVIEW

We have also developed the Fast Prototype Motor System Simulation Program based on the MATLAB SIMULINK platform and is named MotorSIM. We can use MotorSIM, as shown in Figure 6 to effectively and efficiently generate different transient and steady state motor data under different fault and operating conditions for the motor fault study and test different fault detection techniques investigated. MotorSIM provides the data required to test the neural-fuzzy motor incipient fault detection and diagnosis system developed by the PI before and can be used for this proposed incipient fault accommodation control. We have also developed MotorVIEW, which is an easy to use, platform-independent LabVIEW application that works with standard National Instruments data acquisition and signal conditioning hardware. It is presently used to collect voltage, current, temperature, speed, and vibration information from motors, drives and a machinery fault simulator. These data provide experimental validation of the proposed motor incipient fault management schemes.

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