CAJ | 학술논문

针对结构密集模态参数识别精度不高的问题，提出了一种小波Shannon熵与最小标准差相结合来优化复Morlet 小波参数的方法。首先理论推导了中心频率与带宽参数的取值范围，其次采用两个最小原则对中心频率与带宽参数同时进行优化，通过仿真算例和模型实验的参数识别，验证了参数优化后的 Morlet 小波可准确地识别结构的密集模态参数，并且具有一定的抗噪性能。
침대결구밀집모태삼수식별정도불고적문제，제출료일충소파Shannon적여최소표준차상결합래우화복Morlet 소파삼수적방법。수선이론추도료중심빈솔여대관삼수적취치범위，기차채용량개최소원칙대중심빈솔여대관삼수동시진행우화，통과방진산례화모형실험적삼수식별，험증료삼수우화후적 Morlet 소파가준학지식별결구적밀집모태삼수，병차구유일정적항조성능。
A method for identification of structural closely spaced modes parameters was presented.A new optimization method concerning the optimization of parameters of center frequency and bandwidth of complex Morlet wavelet was proposed,which combines the techniques of wavelet Shannon entropy and minimum standard deviation.The ranges of the center frequency and bandwidth parameters were derived theoretically and the center frequency and bandwidth parameters were optimized by two minimum criteria simultaneously.The accuracy and anti-noise performance of the optimization method were verified through numerical simulations and model tests.