Register Here To View: Using Motor Current Signature To Detect The Number Of Cracked Rotor Bars In Induction Motors
Please complete the form to continue. Your personal information is treated with care and will be handled in accordance with GDPR regulations.
Webinar Description:
Broken/Cracked rotor bar/s is one of the commonly encountered induction motor faults that may cause serious motor damage to the motor if not detected timely. Past efforts on broken rotor bar diagnosis have been focused on vibration analysis and current signature analysis using spectral analysis . These methods require accurate slip estimation along with high resolution data , and very pericise judgement of severity to confidently pull out the motor to the workshop with no doubt . This presentation will not only focus on collecting current signature , but also will cover the analysis part of spectral data to determine the number of cracked/broken bars along with the severity level and needed corresponding corrective actions . This will be clearly shown through two real case studies in my plant for two 1.2 MW induction motors.
Learning Takeaways
1. What is Motor Current Signature and how to use it effectively to complement vibration diagnosis.
2. How to Collect data using MCS .
3. Analysis of cracked/broken rotor bars and detecting the number of defected bars through MCS.
About the Presenter
Mohamed has over 12 years of highly diversified experience in the heavy industries. He has held a variety of roles across operations, projects, and predictive maintenance at EzzSteel, the largest independent steel producer in the Middle East and North Africa. He is currently responsible for the reliability of five large plants that include almost four hundred of rotating equipment. He implements a PdM system that includes many predictive technologies like (vibration analysis, Oil analysis, Thermal Imaging, Laser Alignment, Field Balancing, Motor current signature . …etc). Mohamed is a CAT III Analyst and had CMRP BoK. He has a extensive experience in Hydraulic systems control and troubleshooting and holds a post-graduate degree in the application of automatic control in mechanical power engineering.
Mohamed has over 12 years of highly diversified experience in the heavy industries. He has held a variety of roles across operations, projects, and predictive maintenance at EzzSteel, the largest independent steel producer in the Middle East and North Africa. He is currently responsible for the reliability of five large plants that include almost four hundred of rotating equipment. He implements a PdM system that includes many predictive technologies like (vibration analysis, Oil analysis, Thermal Imaging, Laser Alignment, Field Balancing, Motor current signature . …etc). Mohamed is a CAT III Analyst and had CMRP BoK. He has a extensive experience in Hydraulic systems control and troubleshooting and holds a post-graduate degree in the application of automatic control in mechanical power engineering.
By using this site you agree to our use of cookies. You are free to manage this via your browser setting at any time. To learn more about how we use the cookies please see our cookies policy.