MCM uses model-based fault detection and diagnosis techniques for monitoring and early fault detection in equipment or processes driven by electric motors.

The principle of this approach, as illustrated in Figure a, is to compare the dynamic behaviour of the mathematical model and the actual motor based system, in our case, it is the measured voltages. Y(n) corresponds to the output of the motor based system, it corresponds to the output measured currents. V(n), on the other hand, is the currents calculated by the model. Y(n)-V(n) is the difference between the measured and calculated currents.

The model consists of a set of differential equations, which describe the electromechanical behaviour of the motor. The real time data acquired from the system is processed by system identification algorithms for the calculation of model parameters. The motor driving the machinery or process is being used as a sensor. Faults developing in the motor based system affect the model parameters. The mathematical model parameters are obtained during a learning period.

MCM is manufactured as a small, box-shaped device that is suitable for installation on motor control panels. After the device completes a learning period, it starts to monitor the system by acquiring real time data from the motor and processing that data to compare the actual condition with the one obtained during the learning mode. If the difference exceeds a set of thresholds, the user is warned by means of a liquid crystal display and a number of light emitting diodes on the front panel on the device. Different light emitting diodes are lit depending upon the severity of the impending fault. Fluctuations in the line and load conditions are also indicated by other diodes being lit.

The device measures only three phase voltage and current signals of a motor, therefore it is highly immune to external influences such as the ones present in vibration measurements. Using the measured three phase voltage and current signals, in addition to the non-physical model parameters, it calculates a set of physical parameters such as rms-values of three phase voltage and current, powerfactor, etc., therefore monitors the system continuously. This set also includes parameters such as total harmonic distortion, harmonic content of the incoming signal and voltage imbalance which give an idea about the quality of incoming power. Active and reactive power parameters in this set might be used for energy consumption estimations.

The device can be integrated into Mimic Condition Monitoring Software and to other maintenance management systems. Using this desktop application, the status, physical and non-physical parameters of several electronic motor based machinery, equipment and processes on a vessel can be monitored from several different computers at remote locations. Trend analysis might be performed on the past values stored a database.

Maintenance activities like improper installation or adjustment might eventually lead to additional failures of machinery and equipment. Frequently these failures occur very soon after the maintenance activity. MCM also has the capability of verifying any corrective action taken during a maintenance activity. Comparison of the status of a motor before and after the maintenance activity gives an idea about the quality of corrective action.