Loudspeaker Configuration Optimization Using Objective Functions
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Solution Overview
Problem
Current loudspeaker configuration methods lack a straightforward solution for achieving optimal acoustic performance due to the complexity of sound system design and the large number of possible configuration variants, often resulting in suboptimal results from iterative processes.
Innovation Solution
A method and computer program product that utilize an objective-function-based optimization procedure to determine the configuration of loudspeaker arrangements by incorporating both sound-field-dependent and sound-field-independent function terms, allowing for the evaluation and selection of candidate configurations based on criteria such as sound level distribution, filter settings, and amplification factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If iterative configuration variants are evaluated using traditional objective functions, then the configuration process can be automated, but the results are suboptimal due to the large number of configuration variants and geometric complexity
Solution Approach 1:
The patent transforms the configuration optimization problem by changing parameters from evaluating individual configuration variants to directly optimizing configuration parameters (positions, orientations, filter settings) using gradient-based methods. This allows continuous parameter adjustment rather than discrete variant evaluation, achieving higher precision while maintaining automation.
Solution Approach 2:
The patent replaces the traditional iterative trial-and-error mechanical evaluation process with a mathematical optimization system using objective functions and gradient descent algorithms. This substitution enables direct computation of optimal parameters without manually evaluating numerous configuration variants.
2Reliability
If the number of configuration variants is increased to cover more possibilities, then the chance of finding an optimal configuration improves, but the evaluation time and computational resources increase significantly
Solution Approach 1:
The patent performs preliminary action by directly computing the gradient of the objective function with respect to configuration parameters at the starting point, then using this gradient information to guide the search direction. This eliminates the need to evaluate numerous variants before finding the optimal configuration, significantly reducing evaluation time while maintaining reliability.
Solution Approach 2:
The patent implements feedback through the objective function and its gradient, which continuously provide information about how configuration parameters affect acoustic performance. This feedback mechanism guides the optimization process efficiently toward the optimal configuration without requiring exhaustive evaluation of all possible variants.
3Device complexity
If traditional objective functions focusing only on sound pressure uniformity are used, then the evaluation is simple, but the acoustic performance in terms of early reflections and late reflections is not adequately optimized
Solution Approach 1:
The patent segments the acoustic performance evaluation into multiple independent objective function components: sound pressure uniformity, early reflection enhancement, and late reflection suppression. Each component can be evaluated and optimized separately, maintaining mathematical tractability while comprehensively addressing all acoustic performance requirements.
Solution Approach 2:
The patent creates a composite objective function that combines multiple acoustic performance criteria (sound pressure uniformity, early reflections, late reflections) into a single unified evaluation framework. This composite function enables simultaneous optimization of all acoustic aspects without increasing computational complexity, as gradient-based methods can handle the combined function efficiently.
Data Source
AI summary
The invention relates to a method for determining a configuration for a loudspeaker arrangement for radiating sound into a space, wherein the method comprises the following steps: providing an initial configuration having initial configuration parameters for a loudspeaker arrangement for radiating sound into a space in the computer, determining configurations having respectively associated configuration parameters by means of a target function-based optimisation method, wherein, proceeding from the initial configuration, in the computer a sound field for the space and/or parts thereof into which sound is to be radiated is determined iteratively to a candidate configuration by means of simulation, a value of a target function associated with the candidate configuration and the simulated sound field is determined and a new candidate configuration for the loudspeaker arrangement is selected, and selecting a configuration having configuration parameters from the iteratively determined candidate configurations in accordance with at least one selection criterion, which takes into consideration at least the values determined for the target function, wherein a target function is used in the optimisation method. The invention further relates to a computer program product.