Structural Damage Identification Based on AR Model with Additive Noises Using an Improved TLS Solution

Cai, Wu; Li, Shujin; Zhang, Yuanjin

doi:10.3390/s19194341

Cited by 6 publications

(2 citation statements)

References 29 publications

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“…20 The total least squares method is then used to solve the extended order matrix parameters. [21][22][23][24][25] This method takes into account the noise disturbance of the observation vector and data matrix at the same time as it solves the parameters. This reduces the effect of noise on the parameter estimate and makes the enhanced spectrum more accurate.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation in Spectral Resolution Enhancement Based on Forward–Backward Linear Prediction Total Least Square Method

Qin

Han

et al. 2023

Appl Spectrosc

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In a Fourier transform infrared (IR) spectrometer, the Michelson interference signal extrapolation method based on linear prediction is often used to improve spectral resolution. In this method, an autoregressive (AR) model is established for the Michelson interference signal in the spectrometer. Once the AR model parameters are determined, the AR process is predictable. The interference signal can be used to figure out the AR model's parameters. Based on this, the AR model can be used to extrapolate the interference signal to improve the spectral resolution. In this paper, the forward–backward linear prediction total least squares (FB-TLS) method is proposed to estimate the parameters of the AR model. The parameters that are estimated are used to improve the IR spectral resolution. By simulating different order and signal-to-noise ratio situations, the effects of the Burg, the least square, and the FB-TLS parameter estimation methods on spectral resolution enhancement are studied. The simulation results demonstrate that the FB-TLS parameter estimation method can effectively suppress noise and avoid spurious peaks. The experimental results demonstrate that the FB-TLS parameter estimation method is effective for spectral resolution enhancement technology based on linear prediction. When the FB-TLS method is used to enhance NH3 IR spectral resolution from 2 cm−1 to 1 cm−1, the spectral prediction error in the NH3 characteristic band is only 0.21% compared with the measured NH3 spectrum, whose spectral resolution is 1 cm−1.

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Section: Introductionmentioning

confidence: 99%

Parameter Estimation in Spectral Resolution Enhancement Based on Forward–Backward Linear Prediction Total Least Square Method

Qin

Han

et al. 2023

Appl Spectrosc

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“…The damage levels and distributions of the model building were successfully identified based on the observations in the experiment. In addition, some research investigated effective damage detection methods including vibration-based methods, and they have been successfully applied to detecting and identifying the damages in structures constructed from various types of materials, such as reinforced concrete [16], steel [17], and composites [18]. Morita et al [19] detected and estimated the damage of steel frames through a shaking table test by two identification methods.…”

Section: Introductionmentioning

confidence: 99%

Detection of Structural Damage in a Shaking Table Test Based on an Auto-Regressive Model with Additive Noise

Xiao,

Zhu,

et al. 2023

Buildings

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Damage identification plays an important role in enhancing resilience by facilitating precise detection and assessment of structural impairments, thereby strengthening the resilience of critical infrastructure. A current challenge of vibration-based damage detection methods is the difficulty of enhancing the precision of the detection results. This problem can be approached through improving the noise reduction performance of algorithms. A novel method based partially on the errors-in-variables (EIV) model and its total least-squares (LS) algorithm is proposed in this study. Compared with a classical damage detection approach involving adoption of auto-regressive (AR) models and the least-squares (LS) method, the proposed method accounts for all the observation errors as well as the relationships between them, especially in an elevated level of noise, which leads to a better accuracy. Accordingly, a shaking table test and its corresponding finite element simulation of a full-scale web steel structure were conducted. The acceleration time-series output data of the model after suffering from different seismic intensities were used to identify damage using the presented detection method. The response and identification results of the experiment and the finite element analysis are consistent. The finding of this paper indicated that the presented approach is capable of detecting damage with a higher accuracy, especially when the signal noise is high.

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A time series modeling approach for damage monitoring of concrete dam under seismic effects

Xu,

Shao,

Zheng

et al. 2024

Structures

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Structural Damage Identification Based on AR Model with Additive Noises Using an Improved TLS Solution

Cited by 6 publications

References 29 publications

Parameter Estimation in Spectral Resolution Enhancement Based on Forward–Backward Linear Prediction Total Least Square Method

Parameter Estimation in Spectral Resolution Enhancement Based on Forward–Backward Linear Prediction Total Least Square Method

Detection of Structural Damage in a Shaking Table Test Based on an Auto-Regressive Model with Additive Noise

A time series modeling approach for damage monitoring of concrete dam under seismic effects

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