Fault detection and safety mechanisms are as old as electrical machines themselves. Customers and manufacturers used to rely on simple protection schemes like overcurrent, overvoltage, earth-fault, and so on to ensure safe and dependable performance.
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However, as the complexity of the jobs performed by these machines increased, so did the need for improved defect detection methods. Unexpected machine downtime can disrupt workflow and cause significant financial losses. As a result, early fault identification has become critical.[1]
According to research on the durability of electrical machines, any component can fail, and the possibility varies depending on the machine’s type and design, operating conditions, and application [2,3]. For a long time, thermal/vibration supervision and off-line diagnostics were the primary mechanisms for monitoring the condition of electric devices.
Because it allows for low-cost remote monitoring, a significant amount of research has gone into developing electrical monitoring instruments that prevent in-service failure of the equipment and process. Several literature reviews describe the study of electrical fault detection for machine problems as the primary area of research.
In this thesis, A study of faults three type of faults and their combinations using 3D finite element models for an induction machine, and some experimental results are presented. The discussed and proposed diagnostic technique can be extended and applied also to other kind of machines. In this chapter are presented information related to sources of faults for induction motors, types of faults, mechanisms of fault and faults diagnosis methods.