Frequently Asked Questions


Artesis’s unique patented Model Based Fault Detection (MBFD) technology detects a wide range of faults by utilizing voltage & current of Three-Phase AC Electric Motors. This model-based approach works on the principle that the current drawn by an electric motor is affected by not only the applied voltage but also the behaviour of both the motor and the driven equipment. It identifies the distortions of the current waveform that have not been caused by distortions on the voltage waveform and therefore must have been caused by the behaviour of the motor and driven equipment system. The frequency of these distortions indicates the nature of the cause, and the magnitude of the distortions indicates the severity of the cause.

MBFD Technology does not indicate fluting issue on bearings directly, however it will detect an alert the issue as a bearing fault.

MBFD Technology does not use any vibration standards. It uses standard deviations from the learned model of the system.
There is no license fee for the AMTPro itself, we only charge for the cloud subscription option.
MBFD technology captures the amplitude (Standard deviation) of the frequency peaks of the residual current signal, not the vibration at the system.
With our E-mcm (online 24/7 continuous monitoring device) you can receive an email notification if the alarm reaches a pre-set threshold percentage.

The frequency range of the equipment should be between 21Hz to 119Hz

Integration packages are available to a wide range of 3rd party systems, including Integrated Condition Monitoring, SCADA/HMI, and Reporting/Business Intelligence through Open-Platform-Communications OPC Interface. Please contact further information enquiry@artesis.com

Yes, we offer both options, you can use your local network or Cloud Server

Yes, Artesis Predictive Maintenance Solutions illuminate your blind spots at your factory by monitoring the conditions of submersible pumps, borehole pumps, cryogenic pumps & cooling tower fans.

No, Artesis Technologies does not have any limitation for the power & voltage of the equipment. Up to 690V Phase to Phase, you may connect the probes/cables directly. Upper than 690V, you have to connect the voltage connections to the existing PT’s secondary side (preferably the measurement type).
Our technology monitors the three-phase AC Motors & Permanent Magnet(PM) Motors & Driven Equipments & Generator. Artesis Technologies does not monitor the Single Phase, DC Equipment or transformers, since our technology uses 3-Phase AC Voltage and Current Signals, to detect the faults.
The accuracy of MBFD Technology in fault detection is over 90%.

The minimum speed of the motor or driven equipment should be 300 RPM.


When the bearing has been replaced, you do not need to repeat the learning period. e-MCM will indicate the latest condition of the bearing parameter.

No need for a license, the history will be available in the Amt Pro Memory, you can optionally choose to store it on the online cloud software, where a minimal amount will be charged annually for storage allocated.


7 Minutes test time is the optimal duration to get snapshot of the equipments condition. If the test period will be extended, the accuracy will not change. For interrupted operations test duration can be extended. Further info…

At the online monitoring solutions, e-MCM learns the motor’s different operating conditions and cluster each condition to learn more about the operation of the motor. In the AMTPro device, it does not look for different operating conditions, it only checks the steady-state condition of the monitored equipment.

AMT Pro monitors motors, generators, pumps, compressors, fans, chillers, mixers, air handling units, conveyors.

Yes, the AMT Pro generates the reports without the need for Internet or Cloud Connections.
The AMTPro can test one equipment within 7 minutes and allowing up to 40 motors per day.

The Female connection is installed permanently at the MCC panel, the male connection is swappable as it will be connected to the AMT Pro device



      Case Study: Hamestring - Identifying Root Cause