基于局部寻优的噪声特征线谱智能识别算法研究

Research on the local optimization based noise feature line spectrum intelligent recognition algorithm

针对舰船噪声特征线谱的筛选问题,提出一种面向海量数据的线谱特征数据识别算法:噪声谱由连续谱和线谱组成,将连续谱作为该趋势项进行处理,基于最小二乘原理拟合功率谱得到功率谱趋势项,以趋势项为准零基线,将功率谱划分为上下两部分,对零线上不连续的谱线分组并进行局部寻优获取初步特征线谱,根据谱线权重进行峰值排序得到舰船噪声特征线谱。算法实现了特征线谱的有效提取,并通过实测数据验证了算法的有效性,具有一定的工程应用价值。

To screen out ship noise feature line spectrum,a feature data recognition algorithm for massive data is proposed.The noise spectrum is composed of continuous spectrum and line spectrum,which is treated as the trend term.The power spectrum trend term is obtained by fitting the power spectrum based on the least square principle.Taking the trend term as the quasi-zero baseline,the power spectrum is divided into two parts.The discontinuous spectral lines on the zero line are grouped and the local optimization is carried out to obtain the initial feature line spectrum.The ship noise feature line spectrum is obtained by peak sorting according to the spectral line weight.The algorithm realizes the effective extraction of feature line spectrum.The effectiveness of the algorithm is verified by the measured data,which has a certain practical engineering application value.