Munich, Georgia

Hermann Holtmannspötter


Average Co-Inventor Count = 8.0

ph-index = 1

Forward Citations = 6(Granted Patents)


Company Filing History:


Years Active: 2017

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1 patent (USPTO):Explore Patents

Title: Hermann Holtmannspötter: Innovator in Data Analysis Technologies

Introduction

Hermann Holtmannspötter, an inventive mind hailing from Nordrhein-Westfalen, Germany, has made significant contributions to the field of data analysis through his innovative patent. His work focuses on leveraging oversampled digital data to enhance machine characteristic information, showcasing the potential of discarded data in providing meaningful insights.

Latest Patents

Holtmannspötter holds a noteworthy patent for "Selective decimation and analysis of oversampled data." This invention improves the extraction of useful information from oversampled data captured by dynamic signal analyzers, such as vibration analyzers. Traditionally, such data were overlooked, but his methodology enables the analysis of not only peak and decimated values but also other oversampled values that correspond with the monitored machine's characteristics. This advancement allows for a richer understanding of machine performance and sensor information.

Career Highlights

Currently, Hermann Holtmannspötter is employed at Emerson Electric Holding Corporation, a prominent player in the technology sector. His role at the company has enabled him to apply his innovative ideas in practical applications, ultimately contributing to the advancement of data analysis tools used for monitoring machine performance.

Collaborations

Throughout his career, Holtmannspötter has collaborated with esteemed colleagues such as Raymond Earl Garvey, III and Joseph A. Vrba. These partnerships have fostered innovative approaches to data analysis and have contributed to the successful development of the technologies associated with his patent.

Conclusion

Hermann Holtmannspötter stands out as an influential inventor whose work has transformed the way oversampled data is utilized in dynamic signal analysis. By uncovering meaningful insights from previously discarded data, his innovations have laid the groundwork for advancements in machine monitoring technologies, underscoring the importance of continuous innovation in the engineering and technology fields.

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