Enertics CbM

Enertics Developer

About this app

Enertics CbM is one-stop AI driven solution for complete asset health monitoring, diagnostics and predictive analytics solution, leveraging a portfolio of eM Saver hardware and eM AISuite software platform. The offered solutions can be deployed, in matter of minutes, for the brownfield as well as greenfield applications to provide the best Return on Investment for the users. Enertics offers the most advanced sensing, connectivity and data analytics technologies to provide a reliable and cost effective solution to its customers.

Condition-based maintenance (CBM) is a Maintenance Technique that evaluates an Asset’s current condition to decide the Architecture of Maintenance required. Maintenance is performed when the Real-Time Metrics reflect abnormalities or signals of declining performance. The following parameters are considered to carry out the complete health analysis:

1. VIBRATION ANALYSIS: Enertics System uses Vibration analysis to evaluate the Health of Machines by detecting the Vibration Levels and Frequencies of machinery

Vibration analysis helps in:
– the detection of issues such as Unbalance
– Bearing Failure
– Mechanical looseness
– Resonance
– Bent Shaft
– Other issues

2. ULTRASONIC ANALYSIS: Enertics system includes: Ultrasonic analysis to detect High-frequency Sounds and convert them into Audio and Digital Data to identify potentially failing assets.
Enertics solution helps in assessing:
a. The detection of bearing faults
b. lubrication issues that generate a High- Frequency
c. Rhythmic pattern

3. TEMPERATURE SIGNATURE ANALYSIS: The Operational Temperature of the Motors is Measured as part of the Temperature Signature Analysis. Enertics’ Advanced Sensor and Condition-based Maintenance Techniques to Monitor Machine Temperature:
a. Resistance thermometers
b. In Advance Predictions of Potential Failures with Up-to-Date Sensors that determine Machine Conditions

4. MAGNETIC FIELD ANALYSIS BY OUR DEVICES: Our Technology assists to correlate the location of the problem using the magnetic field analysis. We use high-Sensitivity, high-Resolution leakage magnetic flux sensor to monitor the magnetic flux from the electrical rotating machine. This analysis helps us determining the root cause for various types of faults in electrical machines.