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用Marple算法建模而进行的自回归谱估计具有分辩率高、数据可以短、抗干扰力强以及计算效率高等优点。本文用Marple算法分别在短数据和强噪声的情况下进行了计算机模拟研究,并和最小二乘法、Yule-Walker法、最大熵谱法和新最大熵谱法等的谱估计作了比较分析,并对滚齿机分度传动链误差的实测数据作了分析,获得了一些具有工程实用价值的意见。另外,还通过Marple算法与FFT算法的性能比较,说明了自回归谱估计的优越性。
Autocorrelation spectrum estimation with Marple algorithm has the advantages of high resolution, short data, strong anti-jamming ability and high computational efficiency. In this paper, the Marple algorithm is used in the case of short data and strong noise, respectively. Computer simulations are carried out and compared with the spectral estimation methods such as least square method, Yule-Walker method, maximum entropy spectrum method and new maximum entropy method, The measured data of gear shifting error of gear hobbing machine was analyzed, and some opinions with engineering practical value were obtained. In addition, by comparing the performance of Marple algorithm and FFT algorithm, the superiority of autoregressive spectral estimation is illustrated.