Acoustic Phased Array Noise Source Localization
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Solution Overview
Problem
Current noise detection and analysis systems struggle to distinguish and analyze noise signals from multiple, spatially separated and distributed noise sources due to interference from extraneous noise, making it difficult to determine correlation and spatial extent of noise signals in complex environments like jet engine noise fields.
Innovation Solution
A system utilizing multiple acoustic transducers arranged in phased arrays to generate time series data, which is processed using beamforming algorithms and digital signal processing techniques to isolate and analyze noise signals from multiple sources, suppressing extraneous noise and determining correlations and spatial extent within the noise measurement field.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single omni-directional microphones are used to collect noise signals, then the system is simple and easy to operate, but it is incapable of discriminating between different noise signals from multiple spatially separated noise sources
Solution Approach 1:
The system divides the measurement task by using multiple microphones spatially distributed in an array configuration. Each microphone captures noise signals from different spatial locations, enabling the system to discriminate between noise sources through spatial segmentation of the acoustic field.
Solution Approach 2:
The system transitions from single-point omnidirectional measurement to multi-point spatial measurement by adding spatial dimensionality through array configuration. This enables directionality and spatial discrimination capabilities that were absent in single microphone systems.
2Measurement precision
If multiple acoustic transducers arranged in arrays are used to monitor noise at spatially separated locations, then noise signal discrimination and correlation analysis improve, but the system complexity and data processing requirements increase
Solution Approach 1:
The system segments the acoustic measurement task across multiple transducers positioned at different locations. Each transducer monitors a specific spatial zone, and the segmented measurements are integrated through correlation analysis to determine noise source characteristics with high precision.
Solution Approach 2:
The system introduces data processing and correlation analysis as intermediary steps between raw microphone signals and final noise source identification. This intermediary processing layer transforms complex multi-source signals into interpretable correlation data that reveals noise source relationships.
3Measurement precision
If time series data from multiple acoustic arrays is processed to identify noise signals, then extraneous noise is suppressed and detection accuracy improves, but processing time and computational complexity increase
Solution Approach 1:
The system performs preliminary signal conditioning and preprocessing on time series data from multiple acoustic arrays before full correlation analysis. This preliminary action organizes the data structure and applies initial filtering, reducing the computational burden of subsequent processing steps.
Solution Approach 2:
The system applies correlation analysis selectively to identify and suppress extraneous noise rather than processing all possible signal combinations. By focusing computational resources on the most relevant correlations for noise suppression, the system achieves high detection accuracy with reduced processing time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively filters out extraneous noise, enabling accurate detection and analysis of correlations between noise signals from spatially separated sources, allowing for precise localization and spatial extent determination of noise sources in complex environments.
Implementation Method 1
acoustic transducers such as microphones are employed to collect noise signals
Implementation Method 2
processing said time series data by beamforming a first set of acoustic transducer outputs from a first acoustic array to generate a first beamformed time series output signal, and beamforming a second set of acoustic transducer outputs from a second acoustic array to generate a second beamformed time series output signal
Data Source
AI summary
A method for detecting the presence of a noise signal within a noise measurement field, where the noise measurement field includes a noise signal emanating from a noise source, and where the noise signal is mixed with extraneous noise existing within the noise measurement field. The method involves using a plurality of acoustic transducers arranged in a plurality of arrays to monitor the noise measurement field at a plurality of spatially separated locations. Outputs of the transducers are sampled to generate time series data. The time series data is processed to identify whether the noise signal is present.