Title

Modal Identification of Gelatinous Structure Using Vision-Based Vibrometry

Presenter Information

Kenneth NwaguFollow

Location

Presentation- Allen E. Paulson College of Engineering and Computing

Document Type and Release Option

Thesis Presentation (Restricted to Georgia Southern)

Faculty Mentor

Jinki Kim

Faculty Mentor Email

jinkikim@georgiasouthern.edu

Presentation Year

2021

Start Date

26-4-2021 12:00 AM

End Date

30-4-2021 12:00 AM

Keywords

Gelatinous materials, vision based vibrometry

Description

Gelatinous-based materials show promising uses in various fields such as tissue engineering and bioengineering. However, measuring important structural characteristics of gelatin and hydrogel-based materials are challenging because of the characteristics of the material. Important dynamic characteristics such as natural frequencies and mode shapes are difficult to measure with conventional contact and non-contact based techniques such as accelerometers, strain gauges and laser vibrometers. Solutions have been made by others using 3D laser imaging, x-ray imaging and ultrasound, but these are expensive and have drawbacks for certain scenarios such as translucent gels and small gelatinous objects.

The goal of this research focuses on advancing the state of the art of characterizing structural properties of gelatinous materials using vision based vibrometry. The technique uses video footage of the relevant material taken with a high-speed camera. By analyzing the changes in pixels, the natural frequencies and mode shapes of the material are determined. This method is non-contact based and allows the relevant mode shapes to be observed while eliminating challenges presented by conventional methods such as cost and inaccuracy with small or translucent objects.

Academic Unit

Allen E. Paulson College of Engineering and Computing

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Apr 26th, 12:00 AM Apr 30th, 12:00 AM

Modal Identification of Gelatinous Structure Using Vision-Based Vibrometry

Presentation- Allen E. Paulson College of Engineering and Computing

Gelatinous-based materials show promising uses in various fields such as tissue engineering and bioengineering. However, measuring important structural characteristics of gelatin and hydrogel-based materials are challenging because of the characteristics of the material. Important dynamic characteristics such as natural frequencies and mode shapes are difficult to measure with conventional contact and non-contact based techniques such as accelerometers, strain gauges and laser vibrometers. Solutions have been made by others using 3D laser imaging, x-ray imaging and ultrasound, but these are expensive and have drawbacks for certain scenarios such as translucent gels and small gelatinous objects.

The goal of this research focuses on advancing the state of the art of characterizing structural properties of gelatinous materials using vision based vibrometry. The technique uses video footage of the relevant material taken with a high-speed camera. By analyzing the changes in pixels, the natural frequencies and mode shapes of the material are determined. This method is non-contact based and allows the relevant mode shapes to be observed while eliminating challenges presented by conventional methods such as cost and inaccuracy with small or translucent objects.