| 基于GNAR模型和Itakura距离的结构非线性损伤识别方法 |
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| 引用本文： | 左恒,郭惠勇.基于GNAR模型和Itakura距离的结构非线性损伤识别方法[J].工程力学,2022,39(2):189-199+221. |
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| 作者姓名： | 左恒 郭惠勇 |
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| 作者单位： | 重庆大学土木工程学院，重庆 400045 |
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| 基金项目： | 国家重点研发计划项目(2018YFC0809400)；;国家自然科学基金项目(51578094)； |
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| 摘 要： | 为了有效地解决时域非线性损伤的识别问题，提出了基于线性/非线性自回归一般表达式模型(general expression for linear and nonlinear autoregressive model，GNAR模型)和Itakura距离的损伤识别方法。描述了GNAR模型的基本理论，给出了基本的模型定阶和参数估计方法。采用剪枝算法对GNAR模型结构进行了优化选取，并提出了以Itakura距离作为损伤指标的非线性损伤识别方法。采用3层框架非线性损伤实验验证了该方法的有效性，并将提出的方法运用于输电塔钢架模型的非线性损伤识别实验中。结果表明:提出的结构非线性损伤识别方法对框架和输电塔钢架结构的非线性损伤识别效果良好，且环境变化对其识别结果影响较小，由该方法计算得到的损伤层损伤概率明显大于未损伤层，有利于高效地确定非线性损伤源的位置。
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| 关 键 词： | 损伤识别 实验研究 线性/非线性自回归一般表达式模型 时间序列分析 非线性损伤 |
| 收稿时间： | 2021-01-02 |
STRUCTURAL NONLINEAR DAMAGE IDENTIFICATION BASED ON THE GNAR MODEL AND ITAKURA DISTANCE |
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| ZUO Heng,GUO Hui-yong.STRUCTURAL NONLINEAR DAMAGE IDENTIFICATION BASED ON THE GNAR MODEL AND ITAKURA DISTANCE[J].Engineering Mechanics,2022,39(2):189-199+221. |
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| Authors: | ZUO Heng GUO Hui-yong |
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| Affiliation: | School of Civil Engineering, Chongqing University, Chongqing 400045, China |
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| Abstract: | To solve the problem of time-domain nonlinear damage identification, a damage identification method based on the general expression of the linear and nonlinear auto-regressive model (GNAR model) and the Itakura distance is proposed. Describe the basic theory and give the basic model order determination and parameter estimation methods. The optimized structure of the GNAR model is selected by the pruning algorithm. The Itakura distance is used as the damage indicator for nonlinear damage identification. The nonlinear damage experiment of a three-story frame was used to verify the effectiveness of the proposed method. The method is applied to the nonlinear damage identification experiment of a transmission tower steel frame model. The results show that the proposed nonlinear damage identification method can easily identify the nonlinear damage of the frame and transmission tower steel frame structure. The environmental change has little effect on the damage identification results. The damage probability of the damaged floor calculated by the proposed method is higher than the undamaged floors. The proposed method is helpful to find the location of the nonlinear damage source efficiently. |
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| Keywords: | damage identification experimental study general expression for linear and nonlinear auto-regressive model time series analysis nonlinear damage |
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