一个适应算法用于声反补偿和主动噪声控制系统的二次路径识别
Zhu Jie Feng1, Tian Ran Lin1, Li Cheng2
1Qingdao Key Rail Transportation Centre for Noise and Vibration Control & Automated Fault Diagnostic, Qingdao University of Technology, China.
The Journal of the Acoustical Society of America
|December 19, 2023
概括
本研究引入了一种适应性算法,用于主动噪声控制,改善实时声学反和二次路径识别. 这种新的方法通过平衡融合速度和路径精度来提高降噪.
科学领域:
- 声学和信号处理
- 控制系统工程 控制系统工程
背景情况:
- 主动噪声控制 (ANC) 系统面临的挑战是实时声学反和二次路径识别.
- 传统的算法难以平衡快速收与低路径错位,从而影响噪声降低.
研究的目的:
- 为ANC系统提出一个可适应的可变阶段大小算法.
- 解决实时声学反和二次路径识别对降噪性能的影响.
- 通过使用自动调整权重因子来增强系统的融合并防止分歧.
主要方法:
- 开发了一种具有自动调整重量因子的自适应变量阶段大小算法.
- 引入一个优化的控制结构与自适应增益调整.
- 用模拟的多组件和宽带噪声信号测试算法.
主要成果:
- 拟议的算法加速了声反和二次路径识别.
- 它解决了收速度和路径不对齐之间的权衡.
- 通过模拟证明的有效性,在很少的代中实现了良好的降噪.
结论:
- 新的自适应算法显著提高了ANC的性能.
- 它在降噪方面提供了更高的实用性和效率.
- 该方法为实时声学挑战提供了强大的解决方案.
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