Company Filing History:
Years Active: 2013-2023
Title: Jürgen Zettner: Innovator in Machine Condition Monitoring
Introduction
Jürgen Zettner is a prominent inventor based in Auburn Hills, MI (US), known for his contributions to the field of machine condition monitoring. With a total of 10 patents to his name, Zettner has made significant advancements in the technology used to predict and analyze machine failures.
Latest Patents
Among his latest patents is the "Automated health state classifier for rotating machines based on expert knowledge." This invention relates to a computer-implemented method, a data processing system, and a computer program product designed to indicate machine failures. The method involves transforming input signals based on physical quantities of machine parts into features that a neural network uses to predict the class and severity of machine failures.
Another notable patent is the "Smart motor data analytics with real-time algorithm." This invention provides a computer-implemented method and system for Condition Monitoring (CM) of rotating machines. It includes continuously receiving samples of physical quantity data, updating accumulator variables in real-time, and computing spectral features to determine the condition of the machine. The use of the Goertzel Algorithm allows for real-time computation of these features, enhancing the reliability of machine condition assessments.
Career Highlights
Zettner has worked with renowned companies such as Siemens Aktiengesellschaft and Siemens Aktiengesellschaft, where he has honed his expertise in machine monitoring technologies. His work has significantly impacted the efficiency and reliability of rotating machines in various industries.
Collaborations
Throughout his career, Zettner has collaborated with notable professionals in the field, including Dirk Scheibner and Martin Meyer. These collaborations have contributed to the development of innovative solutions in machine condition monitoring.
Conclusion
Jürgen Zettner's contributions to the field of machine condition monitoring through his patents and collaborations highlight his role as a key innovator. His work continues to influence the industry, paving the way for advancements in predictive maintenance technologies.
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