Method for automatic detection of physical modes in a modal analysis model

Jan Helsen; Patrick Guillaume; Nicoletta Gioia

Method for automatic detection of physical modes in a modal analysis model

Jan Helsen (Inventor), Patrick Guillaume (Inventor), Nicoletta Gioia (Inventor)

Research output: Patent

Abstract

The first aspect of the invention is related to a new method for automatically detecting physical modes within the data resulting from a modal analysis estimation algorithm (e.g. LSCE, PolyMax or other). The automatic detection method of the invention is based on a non-hierarchical clustering method wherein the number of clusters is automatically optimized, further making use of a metric for spuriousness within each cluster. According to the second aspect of the invention, the method for automatically detecting modes is used in a method removing harmonics from a signal.

Original language	English
Patent number	WO2019007970
Publication status	Published - 2019

Handle.net

Persistent link

Cite this

@misc{fdc1bcf670ed45229d625f7acb29aa5c,

title = "Method for automatic detection of physical modes in a modal analysis model",

abstract = "The first aspect of the invention is related to a new method for automatically detecting physical modes within the data resulting from a modal analysis estimation algorithm (e.g. LSCE, PolyMax or other). The automatic detection method of the invention is based on a non-hierarchical clustering method wherein the number of clusters is automatically optimized, further making use of a metric for spuriousness within each cluster. According to the second aspect of the invention, the method for automatically detecting modes is used in a method removing harmonics from a signal.",

author = "Jan Helsen and Patrick Guillaume and Nicoletta Gioia",

year = "2019",

language = "English",

type = "Patent",

note = "WO2019007970",

}

TY - PAT

T1 - Method for automatic detection of physical modes in a modal analysis model

AU - Helsen, Jan

AU - Guillaume, Patrick

AU - Gioia, Nicoletta

PY - 2019

Y1 - 2019

N2 - The first aspect of the invention is related to a new method for automatically detecting physical modes within the data resulting from a modal analysis estimation algorithm (e.g. LSCE, PolyMax or other). The automatic detection method of the invention is based on a non-hierarchical clustering method wherein the number of clusters is automatically optimized, further making use of a metric for spuriousness within each cluster. According to the second aspect of the invention, the method for automatically detecting modes is used in a method removing harmonics from a signal.

AB - The first aspect of the invention is related to a new method for automatically detecting physical modes within the data resulting from a modal analysis estimation algorithm (e.g. LSCE, PolyMax or other). The automatic detection method of the invention is based on a non-hierarchical clustering method wherein the number of clusters is automatically optimized, further making use of a metric for spuriousness within each cluster. According to the second aspect of the invention, the method for automatically detecting modes is used in a method removing harmonics from a signal.

UR - https://worldwide.espacenet.com/patent/search/family/059298262/publication/WO2019007970A1?q=WO2019007970

M3 - Patent

M1 - WO2019007970

ER -

Method for automatic detection of physical modes in a modal analysis model

Abstract

Handle.net

Other files and links

Fingerprint

IOF3002: IOF Gear: Industrial Valorization of Smart Structural Health and Usage Monitoring Strategies for Key Technologies

Cite this

Method for automatic detection of physical modes in a modal analysis model

Abstract

Handle.net

Other files and links

Fingerprint

Projects

IOF3002: IOF Gear: Industrial Valorization of Smart Structural Health and Usage Monitoring Strategies for Key Technologies

Cite this