Condition Monitoring and Faults Diagnosis of Induction Motors
Electrical Signature Analysis
Nonfiction, Science & Nature, Technology, Power Resources, Electronics
| Author: | Nordin Saad, Muhammad Irfan, Rosdiazli Ibrahim | ISBN: | 9781351172547 |
| Publisher: | CRC Press | Publication: | July 11, 2018 |
| Imprint: | CRC Press | Language: | English |
| Author: | Nordin Saad, Muhammad Irfan, Rosdiazli Ibrahim |
| ISBN: | 9781351172547 |
| Publisher: | CRC Press |
| Publication: | July 11, 2018 |
| Imprint: | CRC Press |
| Language: | English |
The book covers various issues related to machinery condition monitoring, signal processing and conditioning, instrumentation and measurements, faults for induction motors failures, new trends in condition monitoring, and the fault identification process using motor currents electrical signature analysis. It aims to present a new non-invasive and non-intrusive condition monitoring system, which has the capability to detect various defects in induction motor at incipient stages within an arbitrary noise conditions. The performance of the developed system has been analyzed theoretically and experimentally under various loading conditions of the motor.
- Covers current and new approaches applied to fault diagnosis and condition monitoring.
- Integrates concepts and practical implementation of electrical signature analysis.
- Utilizes LabVIEW tool for condition monitoring problems.
- Incorporates real-world case studies.
- Paves way a technology potentially for prescriptive maintenance via IIoT.
The book covers various issues related to machinery condition monitoring, signal processing and conditioning, instrumentation and measurements, faults for induction motors failures, new trends in condition monitoring, and the fault identification process using motor currents electrical signature analysis. It aims to present a new non-invasive and non-intrusive condition monitoring system, which has the capability to detect various defects in induction motor at incipient stages within an arbitrary noise conditions. The performance of the developed system has been analyzed theoretically and experimentally under various loading conditions of the motor.
- Covers current and new approaches applied to fault diagnosis and condition monitoring.
- Integrates concepts and practical implementation of electrical signature analysis.
- Utilizes LabVIEW tool for condition monitoring problems.
- Incorporates real-world case studies.
- Paves way a technology potentially for prescriptive maintenance via IIoT.
