Drone Propulsion Noise Cancellation via Motor Voltage Modeling
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Solution Overview
Problem
Drones emit high noise levels from their propulsion systems, making it impractical to record audio effectively, which is a limitation in various applications including multimedia productions and potential retail or workplace uses where voice commands are needed.
Innovation Solution
A method is developed to model the noise emitted by drone propulsion systems based on voltage supplied to the motors, allowing for noise reduction in captured audio signals using a noise model generated from a database of noise signals, with the drone transmitting voltage data to perform real-time noise reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If the propulsion system operates at high power to enable drone flight and maneuvering, then the drone achieves sufficient thrust and mobility, but the noise level increases making audio recording impractical
Solution Approach 1:
The patent converts the harmful propulsion noise into a useful signal by using it as a reference for adaptive noise cancellation. The noise that was previously making audio recording impractical is now utilized to generate cancellation signals that remove the noise from captured audio, transforming the harmful acoustic interference into a beneficial reference for noise reduction processing
Solution Approach 2:
The system implements feedback by continuously monitoring the propulsion system's operational parameters (voltage, current, RPM) and using this information to dynamically adjust the noise cancellation process. The adaptive filter uses real-time feedback from the propulsion system state to optimize the noise cancellation signals, ensuring effective noise removal across varying flight conditions
2Measurement precision
If adaptive noise reduction is applied to cancel propulsion noise, then audio quality improves, but the system complexity increases due to additional processing requirements
Solution Approach 1:
The patent introduces an intermediary adaptive filter that acts as a mediator between the raw audio signal and the final processed output. This filter serves as a processing layer that selectively removes propulsion noise while preserving genuine audio content, achieving noise cancellation without requiring complete system redesign or overly complex processing architectures
Solution Approach 2:
The system creates a copy or model of the propulsion noise signal based on measured parameters and uses this copied noise profile for cancellation. By generating a representative model of the noise rather than attempting to directly invert or complexly process the original noisy signal, the system achieves effective noise reduction with manageable computational complexity
3Reliability
If real-time noise cancellation is performed using voltage data, then noise reduction effectiveness improves, but the data transmission and processing requirements increase
Solution Approach 1:
The system performs preliminary action by pre-establishing the relationship between propulsion system parameters (voltage, current, RPM) and the resulting noise characteristics during calibration phases. This pre-characterization allows the real-time noise cancellation to rely on straightforward parameter lookups and computations rather than requiring transmission of large amounts of raw audio data for analysis, reducing data transmission requirements while maintaining effectiveness
Data Source
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AI summary
In some embodiments, a method, apparatus and computer program for reducing noise from an audio signal captured by a drone (e.g., canceling the noise signature of a drone from the audio signal) using a model of noise emitted by the drone's propulsion system set, where the propulsion system set includes one or more propulsion systems, each of the propulsion systems including an electric motor, and wherein the noise reduction is performed in response to voltage data indicative of instantaneous voltage supplied to each electric motor of the propulsion system set. In some other embodiments, a method, apparatus and computer program for generating a noise model by determining the noise signature of at least one drone based upon a database of noise signals corresponding to at least one propulsion system and canceling the noise signature of the drone in an audio signal based upon the noise model.