Power Converter Fault Detection: Enhancing Power System Reliability with AI
| Start Time | End Time |
|---|---|
| 16 Sep 2025, 04:00 EDT | 16 Sep 2025, 05:00 EDT |
Overview
Power converters are the backbone of modern industries, facilitating efficient energy conversion and distribution. This webinar focuses on modeling power converters in Simscape Electrical to simulate faults and aging processes. By generating synthetic data, we’ll show how to develop a predictive maintenance algorithm capable of detecting faults and estimating the remaining useful life of power converters. This approach enhances performance, reduces downtime, and optimizes maintenance strategies.
Whether you are involved in renewable energy, manufacturing, utilities, or any industry utilizing power electronics, mastering power converters is essential for ensuring reliable and sustainable operations. The session is pre-recorded with a live Q&A session at the end, held by Nils Hornik and Rainer Mümmler.
Highlights
- Modeling and simulation: create and simulate a power converter system using Simscape Electrical.
- Synthetic data generation: produce voltage and current data to represent IGBT aging.
- Automated feature engineering: utilize the Diagnostic Feature Designer for efficient feature extraction.
- Custom feature integration: incorporate domain-specific features for improved accuracy.
- Machine learning for fault detection: train models to detect, isolate, and assess fault severity.
- Algorithm deployment: implement predictive algorithms in operational systems or edge devices.
About the Presenters
Mohsen Aleenejad
Senior Application Engineer | MathWorks
Mohsen joined MathWorks in 2020. In his role as senior application engineer, he supports customers in the energy and power, and industrial automation industries. Before joining MathWorks, he worked as a senior power electronics engineer with a focus on renewable energy systems at InnoCit LLC, and active front end motor drive at PowerItPerfect Inc. Mohsen has a Ph.D. in power electronics from the University of Kansas. He also held a postdoctoral researcher position with New York University, where he collaborated with Boeing Company on building an active load profiler for testing the aircraft's power sources.
Nils Hornik
Application Engineer | MathWorks
Nils is an Applications Engineer at MathWorks in Munich. Here he works closely with customers in the fields of energy generation, transport and storage. The main focus of his work is consulting customers in the area of physical systems modeling.
Before joining MathWorks, he was a software engineer responsible for the model-based development of the PLC-based Energy Management System (EMS) and its commissioning for microgrid projects at DHYBRID Power Systems GmbH.
Rainer Mümmler
Principal Application Engineer | MathWorks
Rainer is a Principal Application Engineer at MathWorks, specializing in Data Analytics, Artificial Intelligence, Predictive Maintenance, Hardware Connectivity, and IoT solutions. Prior to his tenure at MathWorks, he gained valuable experience as a wind tunnel test engineer and served as a freelance consultant for multiple aerospace companies.
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