Multi-Modal Acoustic Imaging with Adaptive Array Selection
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Solution Overview
Problem
Acoustic imaging devices face limitations in detecting and imaging both high and low frequency ranges due to sensor array configurations and calculation algorithms, requiring expertise and multiple equipment setups, leading to time-consuming and costly inspections with potential misalignment issues when combined with other imaging technologies.
Innovation Solution
A system comprising multiple acoustic sensor arrays and a processor that selects appropriate arrays based on input parameters, generates acoustic image data through back-propagation calculations, and integrates electromagnetic imaging to align and display combined image data, facilitating user-friendly and efficient acoustic analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sensor array is optimized for lower frequencies with larger sensor spacing, then low frequency detection is improved, but high frequency detection capability deteriorates
Solution Approach 1:
The acoustic sensor array is divided into multiple sub-arrays with different sensor spacing configurations. Some sub-arrays use larger spacing optimized for low frequency detection, while others use smaller spacing optimized for high frequency detection. This segmentation allows the system to simultaneously handle both frequency ranges without compromising either capability.
Solution Approach 2:
The system dynamically selects which sub-arrays to activate based on the frequency range of the acoustic signals being analyzed. The processor can switch between different sub-arrays with different spacing configurations depending on whether low frequency or high frequency detection is required, enabling adaptive optimization for different operational conditions.
2Measurement precision
If a sensor array is optimized for higher frequencies with smaller sensor spacing, then high frequency detection is improved, but low frequency detection capability deteriorates
Solution Approach 1:
The acoustic sensor array is divided into multiple sub-arrays with different sensor spacing configurations. Some sub-arrays use larger spacing optimized for low frequency detection, while others use smaller spacing optimized for high frequency detection. This segmentation allows the system to simultaneously handle both frequency ranges without compromising either capability.
Solution Approach 2:
The system dynamically selects which sub-arrays to activate based on the frequency range of the acoustic signals being analyzed. The processor can switch between different sub-arrays with different spacing configurations depending on whether low frequency or high frequency detection is required, enabling adaptive optimization for different operational conditions.
3Adaptability or versatility
If multiple acoustic sensor arrays with different configurations are used to cover various frequency ranges, then frequency coverage versatility is improved, but device complexity increases
Solution Approach 1:
Multiple sub-arrays with different sensor spacing configurations are merged into a single integrated acoustic sensor array structure. All sub-arrays share common mounting infrastructure, control electronics, and processing pathways, which reduces the overall complexity compared to having separate independent arrays while still providing multi-frequency capability.
Solution Approach 2:
The integrated sensor array structure serves multiple functions simultaneously - it can detect both low frequency and high frequency acoustic signals depending on which sub-arrays are activated. The same physical structure and processing system handle all frequency ranges, eliminating the need for separate dedicated systems for each frequency band.
4Adaptability or versatility
If manual selection of hardware and software is required for acoustic analysis, then customization flexibility is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically selects which sub-arrays to activate and which processing algorithms to apply based on analysis of the acoustic signals themselves. The processor examines the frequency content and distance information from the acoustic data and autonomously configures the appropriate hardware and software settings, eliminating the need for manual user configuration while maintaining optimal analysis parameters.
Solution Approach 2:
The system continuously monitors the acoustic signal characteristics and adjusts its configuration in real-time based on feedback from the incoming data. This feedback mechanism enables the system to adapt its sub-array selection and processing parameters dynamically, providing optimal performance without requiring user intervention or manual reconfiguration.
5Productivity
If multiple imaging technologies are used simultaneously for comprehensive analysis, then inspection thoroughness is improved, but alignment precision deteriorates due to parallax errors
Solution Approach 1:
A registration process acts as an intermediary between the acoustic sensor array and electromagnetic imaging systems. This registration mechanism uses acoustic signals and electromagnetic image data as reference points to calculate and apply transformation matrices that align the coordinate systems of different imaging modalities, compensating for parallax errors and ensuring precise spatial correspondence across all image types.
Solution Approach 2:
The system dynamically adjusts the focus position and spatial parameters of the electromagnetic imaging tools to match the acoustic imaging plane. By changing the focus distance and spatial coordinates of the electromagnetic sensors to correspond with the acoustic sensor array geometry, the system eliminates parallax misalignment and ensures that all imaging modalities are registered to the same reference frame.
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
Enables simultaneous detection and imaging of various frequency ranges with reduced user expertise requirements, improving inspection efficiency and accuracy by aligning acoustic and electromagnetic image data for precise localization.
Implementation Method 1
The acoustic sensor elements in the first and second acoustic sensor arrays can be configured to receive acoustic signals from an acoustic scene and output acoustic data based on the received acoustic signals
Implementation Method 2
The processor can be configured to generate acoustic image data representative of an acoustic scene based on the received acoustic data from the selected one or more acoustic sensor arrays
Implementation Method 3
an electromagnetic imaging tool in communication in the processor and configured to receive electromagnetic radiation from a target scene and output electromagnetic image data
Data Source
AI summary
Systems and methods directed toward acoustic analysis can include a plurality of acoustic sensor arrays, each including a plurality of acoustic sensor elements, and a processor in communication with the plurality of acoustic sensor arrays. The processor can be configured to select one or more of the plurality of acoustic sensor arrays based on one or more input parameters, and generate acoustic image data representative of an acoustic scene based on received acoustic data from the selected one or more acoustic sensor arrays. Such input parameters can include distance information and/or frequency information. Different acoustic sensor arrays can share acoustic sensor elements in common or can be entirely separate from one another. Acoustic image data can be combined with electromagnetic image data from an electromagnetic imaging tool to generate a display image.