【摘要】：針對(duì)復(fù)指數(shù)法(CE)需要準(zhǔn)確定階且對(duì)噪聲敏感的問題,提出一種稀疏改進(jìn)的復(fù)指數(shù)算法。先用高階次的擬合模型進(jìn)行模態(tài)計(jì)算,然后用稀疏優(yōu)化法代替最小二乘法計(jì)算振型系數(shù),從眾多振型系數(shù)中自動(dòng)選出真實(shí)模態(tài)對(duì)應(yīng)的系數(shù),最終達(dá)到剔除虛假模態(tài)的目的。通過引入稀疏優(yōu)化方法解決了使用高階擬合模型難以有效剔除虛假模態(tài)的問題,突破了模型階次不能過高的限制,提高了算法的精度和抗噪聲性能,令其在斜拉索基頻測(cè)試中表現(xiàn)出更高的識(shí)別精度。
[Abstract]:Aiming at the problem that complex exponential method (CE) needs to be quasi-deterministic and sensitive to noise, a sparse and improved complex exponential algorithm is proposed. First, the modal calculation is carried out with the fitting model of higher order, then the modal coefficient is calculated by sparse optimization method instead of least square method, and the corresponding coefficients of real modes are automatically selected from many modal coefficients, finally the false modes are eliminated. The sparse optimization method is introduced to solve the problem that it is difficult to eliminate the false modal effectively by using the high-order fitting model, which breaks through the limitation that the model order can not be too high, and improves the accuracy and anti-noise performance of the algorithm. It can show higher recognition accuracy in the basic frequency measurement of stay cables.
【作者單位】： 寧波大學(xué)信息科學(xué)與工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(61071198) 浙江省自然科學(xué)基金資助項(xiàng)目(LY13F0110015) 寧波市自然科學(xué)基金資助項(xiàng)目(2012A610019)
【分類號(hào)】：TN911.7

【參考文獻(xiàn)】

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