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Subspace-based identification of a distributed nonlinearity in time and frequency domains

機(jī)譯：基于子空間的時(shí)域和頻域分布非線性識(shí)別

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摘要

Nonlinear system identification has become of great interest during the last decades. However, a common and shared framework is not present yet, and the identification may be challenging, especially when real engineering structures are considered with strong nonlinearities. Subspace methods have proved to be effective when dealing with local nonlinearities, both in time domain (TNSI method) and in frequency domain (FNSI method). This study reports an improvement for both methods, as a first attempt to account for distributed nonlinearities, which is still an open question in the research community. A numerical beam under moderately large oscillations that exhibits geometric nonlinearity is considered. The object of the identification process is to exploit its behavior through the correct identification of the parameters that define the nonlinearity. Results show a high level of confidence between the two methods, and suggest that a more complete analysis of distributed nonlinear phenomena can be conducted based on these approaches.
機(jī)譯：在過去的幾十年中，非線性系統(tǒng)識(shí)別已引起人們極大的興趣。但是，目前還沒有一個(gè)通用和共享的框架，因此識(shí)別可能具有挑戰(zhàn)性，尤其是當(dāng)考慮具有強(qiáng)非線性的真實(shí)工程結(jié)構(gòu)時(shí)。在時(shí)域（TNSI方??法）和頻域（FNSI方法）中，子空間方法在處理局部非線性時(shí)都是有效的。這項(xiàng)研究報(bào)告了這兩種方法的改進(jìn)，這是首次嘗試解決分布式非線性問題，這在研究界仍然是一個(gè)未解決的問題?？紤]在較大的振蕩下表現(xiàn)出幾何非線性的數(shù)值束。識(shí)別過程的目的是通過正確識(shí)別定義非線性的參數(shù)來利用其行為。結(jié)果表明這兩種方法之間具有很高的置信度，并且表明可以基于這些方法對(duì)分布的非線性現(xiàn)象進(jìn)行更完整的分析。

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