Author Information

Tyler CampbellFollow

individual

What campus are you from?

Daytona Beach

Authors' Class Standing

Tyler Campbell, Junior

Lead Presenter's Name

Tyler Campbell

Faculty Mentor Name

Sathya Gangadharan

Abstract

In the aviation industry, intense and prolonged vibrations during flight, particularly for seated individuals, induce whole-body vibrations. When these vibrations are on the lower spectrum (generally 1-20 Hz), they resonate with the human body’s natural biomechanical frequencies, causing certain parts of the body to undergo amplified stress. After long-term exposure, these amplified stresses can cause chronic health issues including spondylosis, vestibular dysfunction, oscillopsia, and hypertension. Beyond the chronic health implications, these vibrations also contribute to pilot fatigue, degraded visual perception, and can compromise mission effectiveness and flight safety. Current aviation systems utilize both passive (e.g., foams, material layering, etc.) and semi-active (reactive) dampers to mitigate the vibrations. Existing systems, while partially effective, exhibit three significant shortcomings: the inherent control latency of reactive systems, the mass and power demands of fully active systems, and the fixed-performance compromise of passive systems. This project aims to overcome these deficiencies with an intelligent controller that integrates a dynamics rheological damper with a deep neural network (DNN). This lightweight, low-power architecture directly resolves the critical trade-offs of current solutions: it eliminates control latency, avoids the penalties of fully active systems, and provides the dynamic adaptability that passive systems lack. This research introduces a scalable, intelligent controller design across any field where humans are exposed to harsh, unpredictable vibratory environments.

Did this research project receive funding support from the Office of Undergraduate Research.

No

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Bio-Integrated Adaptive Seat System for Real-Time Vibration Mitigation in Aviation utilizing Deep Neural Networks

In the aviation industry, intense and prolonged vibrations during flight, particularly for seated individuals, induce whole-body vibrations. When these vibrations are on the lower spectrum (generally 1-20 Hz), they resonate with the human body’s natural biomechanical frequencies, causing certain parts of the body to undergo amplified stress. After long-term exposure, these amplified stresses can cause chronic health issues including spondylosis, vestibular dysfunction, oscillopsia, and hypertension. Beyond the chronic health implications, these vibrations also contribute to pilot fatigue, degraded visual perception, and can compromise mission effectiveness and flight safety. Current aviation systems utilize both passive (e.g., foams, material layering, etc.) and semi-active (reactive) dampers to mitigate the vibrations. Existing systems, while partially effective, exhibit three significant shortcomings: the inherent control latency of reactive systems, the mass and power demands of fully active systems, and the fixed-performance compromise of passive systems. This project aims to overcome these deficiencies with an intelligent controller that integrates a dynamics rheological damper with a deep neural network (DNN). This lightweight, low-power architecture directly resolves the critical trade-offs of current solutions: it eliminates control latency, avoids the penalties of fully active systems, and provides the dynamic adaptability that passive systems lack. This research introduces a scalable, intelligent controller design across any field where humans are exposed to harsh, unpredictable vibratory environments.

 

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