Measuring 10 x 10 x 13 cm, MCM's device is usually installed on or near motor control panels, where it provides diagnostic information in three categories-bearing/coupling, rotor, and current sensors are attached separately, depending on the power of the motor to be monitored. MCM works  standalone or it can be networked under command of one unit.

MCM's simple prediction process also will allow creation of smart motors and motor-based systems that detect and diagnose their own faults before failures occur

Operating principles

The basic principle of MCM's modelbased fault detection and diagnosis methodology for early fault prediction in electric motors compares the dynamic behavior of the actual motor with its nonlinear mathematical model-differential equations that describe the motor's electromechanical behavior. MCM uses  data from  this motor, and processes it proprietary set of system identification alogorithms, which yield the mathematical model's 16 papameters. The sophisticated algorithm then looks for, detects, and reports changes from normal conditions. Normal parameters are established during a short seuence of running and exeiting the motor over its operating frequency range. MCM has four operational modes:

Check mode. which checks if current drawn by the motor is below user-specified thersholds, whether voltage applied is within user specified limits, and determines current and voltage ordering in three phases;

• Learning mode, which repeatedly runs data through the motor's duty cycles to determine the model under varying load conditions;
• Update-learning mode, which modifies the learning mode model with new data; and
• Testing mode, which tests if the actual motor behaves as the model obtained in the learning mode.

Any behavioral change is indicated by colored LEDs, which also display secondary outputs, such as voltage and current imbalance, three-phase currents (rms values), power factor, and input power factor, and input power. The algorithms are also available on a chip for implementing MCM in an overall data acquisition system.

Fault simulator results

A specially designed electrical and mechanical fault simulator performs MCM's fault detection verification and  failure predication functions. Its two "fault creation mechanisms" simulate tilting the rotor from both ends and applying torsion to bearing housings, which induce the effect of static and dynamic eccentricity and bearing faults respectively. Bearing contamination is determined by simulating a spray of 75-160 micron diameter iron particles into the bearing housings. For stator short circuits and rotor faults, two electrical fault inducements are used.
  

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