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本文在介绍应用振动的时域信号识别系统模态参数的ITD方法时,提出了形成数据矩阵的新方法—均布法,更充分地利用了信号中所提供的系统信息。面对从随机振动信出号中提取自由振动信号的随机减量技术进行了理论上的推导,并成功地在7T08信号处理机上实现这个技术。最后,通过对实际振动模型的振动信号的处理和识别,验证了上述理论和方法的正确性。近年来,通过振动信号的处理,对机械振动系统进行模态分析的方法发展很快,除了传统的频域方法外,还提出了一些新的时域处理方法,ITD方法就是其中之一。随着ITD方法的发展,随机减量技术也开始被应用于振动模态分析的领域。本文在应用ITD法时,提出了组成数据矩阵的新方法——均布法。该方法充分地利用了信号数据所提供的信息,使识别的精度得到进一步提高。对随机减量法的理论论证,尚是目前没有解决的问题,文中对比进行了探讨和分析。最后对实际模型的振动信号进行了处理,从实验结果也证实了上述理论和方法的准确性和实用性。
When introducing the ITD method to identify modal parameters of a system by using time-domain signals of vibration, this paper proposes a new method of forming a data matrix-uniform distribution method, which makes full use of the system information provided in the signal. In the face of random stochastic reduction technique of extracting free vibration signal from stochastic vibration signal, a theoretical deduction is made and this technique is successfully implemented on 7T08 signal processor. Finally, the correctness of the above theories and methods is verified through the processing and identification of the vibration signal of the actual vibration model. In recent years, the method of modal analysis of mechanical vibration system has developed rapidly through the processing of vibration signals. In addition to the traditional frequency-domain methods, some new time-domain processing methods have also been proposed, and the ITD method is one of them. With the development of ITD methods, random reduction techniques have also been applied to the field of vibration modal analysis. When applying ITD method, this paper presents a new method of forming data matrix - uniform method. The method makes full use of the information provided by the signal data, so that the accuracy of recognition is further improved. The theoretical proof of the random reduction method is still not solve the problem, the text of the comparison were discussed and analyzed. Finally, the vibration signal of the actual model is processed. The experimental results also confirm the accuracy and practicability of the above theories and methods.