Secondary sound source laying method for helicopter cabin active noise control system

Abstract

The invention provides a secondary sound source laying method for a helicopter cabin active noise control system. The secondary sound source laying method for a helicopter cabin active noise control system is characterized in that: based on a quantum particle swarm optimization algorithm, encoding the position of a secondary sound source, taking one encoding string as a particle, performing iterative computation, and computing the fitness value of each particle during each iteration process, and performing element value updating on the particles. The secondary sound source laying method for a helicopter cabin active noise control system has memory so that each particle can still maintain the individual historical extremum of each particle when the algorithm is ended, and taking regard of the situation that the secondary sound source in a helicopter cabin has constraint, various meaningful selection schemes can be provided. Besides, the secondary sound source laying method can search the secondary sound source position in a plurality of secondary sound source working faces, and can select better laying of secondary sound source in the helicopter cabin; and the secondary sound source laying method can take regard of a plurality of frequencies at the same time, laying of secondary sound source robustness at a plurality of harmonic frequencies, that is, good noise reduction effect can be obtained when the secondary sound source is laid at the frequencies.

Description

technical field [0001] The invention relates to the technical field of noise control, in particular to a method for deploying secondary sound sources in an active noise control system for a helicopter cabin, which solves the problem of the helicopter cabin under the condition that the multi-harmonic noise field and additional sound sources in the helicopter cabin have installation constraints. Optimal Layout of Secondary Sound Source Locations in Active Noise Control Systems Background technique [0002] The ultimate noise reduction effect of an active noise control system depends on many factors, such as figure 1 shown. Among them, the first factor limiting system performance is primary sound source and primary sound field characteristics, which are objective factors faced by active control technology and cannot be changed. Among the designable factors, the placement of secondary sound sources (referring to the number of secondary sound sources and their positions in spac...

AI Technical Summary

Problems solved by technology

However, the currently commonly used GA algorithm is cumbersome and requires complex operations such as selection, crossover, and mutation. It is generally implemented with the help of toolbox programming; and there are many parameters of GA, which need to be optimized according to specific applications, which is very inconvenient to use.

However, SA does not have parallel computing capability, and its calculation efficiency is low. Generally, it is only used in combination with other algorithms.

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