Speaker Array Optimization Using Automated Splay Angle Adjustment
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Solution Overview
Problem
Current methods for configuring speaker arrays in sound systems are inefficient, relying on manual adjustments and simplistic radiation models, which can lead to cumbersome feedback and suboptimal sound distribution, especially when dealing with complex venues and multiple frequency responses.
Innovation Solution
A computer-based optimization method using generalized pattern search techniques to adjust splay angles and speaker positions, incorporating objective functions that balance target sound pressure, frequency response flatness, and leakage to the audience, allowing for automated configuration of speaker arrays to achieve desired sound fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment methods are used to configure speaker arrays, then the user can control splay angles and spacing, but the process is time-consuming and requires repeated iterations to achieve acceptable output
Solution Approach 1:
The system automatically optimizes the speaker array configuration by computing optimal splay angles and positioning without requiring manual iterative adjustments. The automated optimization algorithm evaluates multiple configurations and selects the optimal one based on predefined criteria, eliminating the need for repeated manual trials and iterations.
Solution Approach 2:
The system incorporates feedback mechanisms where the predicted sound field output is continuously evaluated against target criteria. The optimization algorithm uses this feedback to iteratively adjust and refine the configuration parameters, automatically converging on the optimal solution without requiring manual intervention for each adjustment cycle.
2Productivity
If simple radiation models are used for predictions, then the calculations are faster and easier to compute, but the accuracy of sound field prediction is reduced
Solution Approach 1:
The system changes the parameters of the radiation model dynamically based on the specific configuration being evaluated. It uses advanced models that can adapt to different speaker types, orientations, and positions, incorporating frequency-dependent directivity patterns and other relevant parameters to maintain high prediction accuracy across diverse scenarios while keeping computations efficient.
Solution Approach 2:
The radiation model is made dynamic and adaptive rather than static. The system automatically selects and adjusts model parameters based on the specific speaker configuration, frequency range, and environmental conditions, allowing the prediction accuracy to evolve with the problem requirements rather than remaining fixed at a simple or complex level.
3Reliability
If full audience plane calculations are performed, then comprehensive sound field coverage is achieved, but the computational complexity and time required increase significantly
Solution Approach 1:
The system segments the audience plane into multiple zones or regions and evaluates the sound field characteristics for each segment separately. This allows comprehensive coverage of the entire audience area while reducing the computational burden by processing smaller, manageable portions of the problem rather than attempting to calculate every individual position simultaneously.
Solution Approach 2:
The system performs calculations at strategically selected representative points across the audience plane rather than exhaustively at every possible position. By choosing key evaluation points that capture the essential acoustic characteristics of different zones, the system achieves reliable overall assessment with reduced computational complexity.
4Reliability
If multiple frequency responses are evaluated simultaneously, then comprehensive acoustic performance is assessed, but the complexity of analyzing and interpreting results increases
Solution Approach 1:
The system merges the analysis of multiple frequency responses into a unified evaluation framework. It combines spectral information, temporal characteristics, and spatial distribution data into integrated metrics that provide comprehensive acoustic performance assessment without requiring separate analysis of each frequency component, thereby reducing the complexity of result interpretation.
Solution Approach 2:
The system employs universal evaluation criteria and visualization tools that can handle multiple frequency responses simultaneously. The same analysis framework and display mechanisms work across different frequency ranges, eliminating the need for separate specialized analysis procedures for each frequency band and simplifying the overall interpretation process.
Data Source
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AI summary
A method of configuring an array of speaker elements is disclosed. The method computes a sound that pressure level at various points in the venue and is evaluated by various objective functions. The configuration of a candidate array is changed, for example by the orientation or position of the speakers and the sound field is recalculated. The process is then iterated until an acceptable configuration is found. The real physical array of speakers is then configured in that manner. The method also provides a 3D plot of the sound pressure level displayed against freguency and position in the venue.