The basic key for implementing technology for predictive maintenance (PdM) is to estimate the time before equipment failure. The first step is to establish a baseline for the lifetime of an electric motor, which can be done by using motor circuit analysis. The second important thing is to study the different operating conditions such as environment, load, cycling, and many more. A variety of conditions may cause electric motor winding failure such as load variation, power supply conditions, severity of faults, environmental conditions, and mechanical conditions.
A breakdown of electric winding insulation is determined by motor current analysis, which helps the predictive maintenance professionals to know about the premature failure of a potential problem. Motor winding analysis (MWA) gives three important tests to know the motor winding insulation. MWA helps you to reduce motor failures preventing lost production and increased maintenance costs. It is a good method for eliminating the motor windings, which cause motor failure and a good tool for monitoring the dielectric strength of winding insulation. Therefore it is an essential component for the predictive maintenance of electric motors.
Motor winding analysis is used for performing non-destructive and in-place trending of electrical machines; especially for predictive/preventive maintenance programs. It is capable of trending DC as well as AC rotating equipment. Trending AC motor rotors and transformers is another function that MWA provides. Limits can be set to know the severity of the changes if they occur and how soon action should be done to protect the equipment from failure. Predictive maintenance for electric motors includes traditional tests that are essential to examine the insulation of the stator and integrity of the rotor bars. These tests are essential for estimating the remaining life of the motor that can be done by analyzing the past performance of the motor.
The trending program is not suitable because many tests cannot be done outside the controlled environment. Moreover the tests of a trending program do not predict the mechanism responsible for causing the failure of the machine. A very common mistake made by most maintenance technicians is that they wait until something breaks down before fixing it. Using predictive maintenance, you can save your time as well as expenses. Maintenance managers organize various resources to manage emergency repairs, but you can limit those emergencies by implementing an effective predictive maintenance program.
