UAV Acoustic Adjustment via Dynamic Rotor Control
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs), particularly those with rotor propulsion, generate disruptive and unpleasant noise that can affect activities and environments, leading to noise pollution issues, especially in populated or sensitive areas.
Innovation Solution
A dynamic acoustics adjustment system using machine learning algorithms to detect environmental settings and adjust rotor pitch, angle, and speed in real-time to minimize noise disruption, creating an optimal acoustic profile that matches the surroundings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If rotor speed and pitch are increased to improve UAV propulsion performance, then flight capability is improved, but noise generation increases causing disruption to surrounding environments
Solution Approach 1:
The patent implements dynamic adjustment of rotor pitch and speed based on real-time environmental context detection. The system continuously monitors surrounding noise levels and activity types, then dynamically modifies rotor parameters to minimize noise disruption while maintaining necessary propulsion performance for the current operational phase.
Solution Approach 2:
The system changes physical parameters of rotor operation (pitch angle, rotational speed) based on environmental conditions. By adjusting these parameters dynamically according to detected context such as residential areas, commercial zones, or open spaces, the UAV optimizes the balance between propulsion needs and noise generation.
2Object-generated harmful factors
If rotor pitch and angle are adjusted to reduce noise, then noise disruption is minimized, but propulsion efficiency may be compromised
Solution Approach 1:
The system dynamically adjusts rotor parameters based on the UAV's current flight phase and environmental context. During phases requiring high propulsion (takeoff, ascent), the system allows higher noise-generating settings, while during stable cruise or descent in sensitive areas, it transitions to low-noise configurations, optimizing the trade-off in real-time.
Solution Approach 2:
The noise reduction measures are applied periodically based on the UAV's operational phase and environmental context rather than continuously. The system transitions between different rotor configurations corresponding to different flight phases, applying noise minimization only when environmental conditions and propulsion requirements align.
3Object-generated harmful factors
If real-time environmental monitoring and machine learning processing are implemented, then noise optimization is improved, but system complexity increases
Solution Approach 1:
The UAV system performs self-monitoring of its own noise impact through onboard sensors and automatically adjusts its rotor parameters based on machine learning processing of environmental data. The system serves itself by detecting contextual information, determining appropriate noise levels, and modifying its operation without external intervention, reducing the need for complex external control systems.
Data Source
AI summary
According to one embodiment, a method, computer system, and computer program product for dynamic acoustics adjustment is provided. The embodiment may include capturing contextual information of an environment surrounding an unmanned aerial vehicle (UAV). The embodiment may also include generating an environmental model using a cluster of machine learning techniques based on the captured contextual information. The embodiment may further include identifying one or more dominant sounds within a soundscape of the captured contextual information. The embodiment may also include calculating an impact of an operation of the UAV on one or more activities within the environment based on the generated environmental model and the one or more identified dominant sounds. The embodiment may further include, in response to determining the calculated impact affects an activity within the one or more activities, modifying the operation to minimize the impact on the soundscape.