Incipient fault diagnostics of rotating electrical machines using adaptive neuro-fuzzy inference system

Condition monitoring and fault diagnostics of electrical machines are extremely important in any industrial setup. In some applications, such as the oil and gas industries, production units, power generation, refining and milling, the failure of critical equipment like generators, milling machines, motors, fans and pumps costs millions of dollars in reduced output, emergency maintenance costs and lost revenues. However, in the utility industry, malfunctioning of the electrical machinery is not acceptable not only because of its financial damage, but also the threat that is caused by a sudden failure or malfunctioning of the part.