Trends in fault diagnosis for electrical machines

Fault diagnosis of rotating electrical machines has received an intense research interest for the last thirty years. Condition monitoring leading to fault diagnosis and failure prediction of electrical machines and drives has attracted researchers because of its considerable influence on the operational continuation of many industrial processes. Reducing maintenance costs and preventing unscheduled F downtimes, which result in losses of production and financial incomes, are the priorities of electrical drives manufacturers and operators. In fact, both correct diagnosis and earlyr detection of incipient faults lead to fast unscheduled maintenance and short downtime for the process under consideration. They also avoid harmful and sometimes devastating consequences e of faults and failures. An ideal diagnostic procedure should take the minimum necessary measurements from the electrical machine and should iextract a diagnosis, so that its condition can e be inferred to give a clear indication of incipient failure modes in a minimum time. During the last years, there has been a considerable amount of research into the creation of new condition monitoring O techniques for induction motors and drives, overcoming the drawbacks of traditional methods. The topic is becoming far more attractive and critical as the population of electric machines l has largely increased in recent years. The number of operating electrical machines has been around 16.1 billion in 2011, with a growth of about 50% in the last five years [1]. Specifically, there has been a transition from techniques suitable for electrical machines in steady state conditions to operation in time- varying conditions. Also, new classes of electrical machines have been considered as for example multi-phase induction or synchronous machines.