scholarly journals Damage Index Analysis of Retaining Wall Structures Based on the Impulse Response Function and Virtual Impulse Response Function

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Qian Xu
Keyword(s):  
Standard Deviation ◽  
Impulse Response ◽  
Response Function ◽  
Damage Identification ◽  
Feature Vector ◽  
Retaining Wall ◽  
Damage Index ◽  
Impulse Response Function ◽  
Damage State ◽  
Wall Structures

To identify the damage within retaining wall structures, the Hilbert–Huang Transforms of the impulse response function and virtual impulse response function were performed. The Hilbert marginal energy ratio spectrums of the impulse response function and virtual impulse response function were acquired. To reflect damage information effectively, those bands with stronger damage sensitivity were extracted via the threshold value ε0. Then, the Hilbert feature bands, which were more sensitive to damage within retaining walls, were selected by considering the contribution of the residual band to the damage identification. Based on the feature bands, the Hilbert damage feature vector, which reflects the variations of Hilbert marginal energy ratio caused by damage, was created. Based on the damage feature vector, two damage identification indexes (the energy ration standard deviation and Energy Ration Standard Deviation), which were based on the impulse response function and virtual impulse response function, respectively, were proposed to identify damage within retaining walls. To investigate the validity of the damage indexes, vibration tests on a pile plate retaining wall were done. The test results show that the damage feature vector is a zero vector or the value of damage index is zero when the wall is undamaged. The damage feature vector is a nonzero vector or the value of the damage index is more than zero when the wall is damaged. Thus, the damage state of the wall can be detected sensitively via the damage feature vector or damage indexes. Partial damage causes greater fluctuation of trend surface of the damage index. The location of partial damage can be diagnosed validly via the coordinate of peak value in the trend surface. The quantitative relationship formula between the damage index and damage intensity is established. The damage intensity of the wall can be calculated reversely, when the damage index is available. Either the energy ration standard deviation or Energy Ration Standard Deviation can be used to detect the damage state, diagnose the damage location, and identify the damage intensity. In comparison with the energy ration standard deviation, the stability and damage sensitivity of the Energy Ration Standard Deviation is much better.

scholarly journals Damage Identification Investigation of Retaining Wall Structures Based on a Virtual Impulse Response Function

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Qian Xu
Keyword(s):  
Impulse Response ◽  
Response Function ◽  
Frequency Band ◽  
Damage Identification ◽  
Wavelet Packet ◽  
Retaining Wall ◽  
Damage Index ◽  
Impulse Response Function ◽  
Energy Ratio ◽  
Wall Structures

To eliminate the influence of excitation on the wavelet packet frequency band energy spectrum (ES), ES is acquired via wavelet packet decomposition of a virtual impulse response function. Based on ES, a character frequency band vector spectrum and damage eigenvector spectrum (DES) are created. Additionally, two damage identification indexes, the energy ratio standard deviation and energy ratio variation coefficient, are proposed. Based on the damage index, an updated damage identification method for retaining wall structures is advanced. The damage state of a retaining wall can be diagnosed through DES, the damage location can be detected through the damage index trend surface, and the damage intensity can be identified by establishing a quantitative relationship between the damage intensity and damage index. To verify the feasibility and validity of this damage identification method, a vibration test on a pile plate retaining wall is performed. Test results demonstrate that it can distinguish whether the retaining wall is damaged, and the location of partial damage within the retaining wall can be easily detected; in addition, the damage intensity of the wall can also be identified validly. Consequently, this damage identification theory and method may be used to identify damage within retaining wall structures.

scholarly journals Investigation of Damage Diagnosis of Retaining Wall Structures Based on the Hilbert Damage Feature Vector Spectrum

2019 ◽  
Vol 2019 ◽  
pp. 1-22
Author(s):  
Qian Xu
Keyword(s):  
Energy Spectrum ◽  
Feature Vector ◽  
Retaining Wall ◽  
Damage Index ◽  
Wall Structure ◽  
Impulse Response Functions ◽  
Damage State ◽  
Damage Diagnosis ◽  
Wall Structures ◽  
Diagnosis Method

To diagnose damages within the retaining wall structure, the Hilbert marginal energy spectrum was acquired via the Hilbert–Huang transformation of virtual impulse response functions of responses to the retaining wall under ambient excitations. Based on the Hilbert marginal energy spectrum, the Hilbert damage feature vector spectrum was created. On the basis of the damage feature vector spectrum, a damage identification index was proposed. Based on the damage feature vector spectrum and damage index, the damage state of the retaining wall was detected by the damage feature vector spectrum, damage locations of the wall were diagnosed by the damage index trend surface, and the damage intensity of the wall was identified by the quantitative relationship between the damage index and damage intensity. Based on this, a damage diagnosis method for retaining wall structures was proposed. To verify the feasibility and validity of the damage diagnosis method, both model tests and field tests on a pile plate retaining wall are performed under ambient excitations. Test results show that the damage state of the wall can be detected sensitively, damage locations can be diagnosed validly, and damage intensity can be identified quantitatively via this damage diagnosis method.

scholarly journals Structural Damage Diagnosis-Oriented Impulse Response Function Estimation under Seismic Excitations

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5413
Author(s):  
Jian-Fu Lin ◽  
Junfang Wang ◽  
Li-Xin Wang ◽  
Siu-seong Law
Keyword(s):  
Damage Detection ◽  
Impulse Response ◽  
Response Function ◽  
Structural Damage ◽  
Numerical Study ◽  
Damage Index ◽  
Impulse Response Function ◽  
Function Estimation ◽  
Seismic Excitations ◽  
Transformation Matrices

Impulse response function (IRF) is an ideal structural damage index for the identification of structural damage associated with changes in modal properties. However, IRFs from multiple excitations applied at different degrees-of-freedoms jointly contribute to the dynamic response, and their estimation is often underdetermined. Although some efforts have been devoted to the estimation of IRF for a structure under single excitation, the case under multiple excitations has not been fully investigated yet. The estimation of IRF under multiple excitations is generally an ill-conditioned inverse problem such that an incorrect or non-feasible solution is common, preventing its application to damage detection. This work explores this problem by introducing dimensionality reduction transformation matrices relating two sets of IRFs of a structure with discussions on the performance of the non-unique transformation matrices. Then, the extraction of IRF via wavelet-based and Tikhonov regularization-based methods are compared. Finally, a numerical study with a truss structure is conducted to validate the estimation of the IRFs and to demonstrate their applicability for damage detection under seismic excitations. Both the damage locations and severity are accurately identified, indicating the proposed methodology can enable the IRFs estimation under multiple excitations for successful damage detection.

scholarly journals Wage-Increment and Development of Black Economy in Nigeria: Influences of Inflation and Taxation

2020 ◽  
Vol 1 (2) ◽  
pp. 141-153
Author(s):  
Emmanuel Okon
Keyword(s):  
Standard Deviation ◽  
Minimum Wage ◽  
Impulse Response ◽  
Response Function ◽  
Value At Risk ◽  
Positive Impact ◽  
Impulse Response Function ◽  
Black Economy ◽  
Dynamic Relationship ◽  
Negative Effect

Purpose: In this paper, wage-black economy relationship was examined while taking into consideration the influences of inflation and taxation. Approach/Methodology/Design: In particular, Value at Risk (VAR) approach was implemented using annually data for Nigeria covering the period 1990-2018 to assess the dynamic relationship among the variables. In light of national minimum wage in Nigeria, impulse response function was used to highlight the plausible responses from black economy to a shock of one standard deviation in each indicated variable. Findings: The result shows that a shock to national minimum wage (LOGMWA) will have a negative effect on black economy (LOGBEC) in Nigeria.  Shocks to inflation (LOGINFL) will have a positive impact on black economy (LOGBEC). Shocks to tax (LOGATAX) will have asymmetric impacts on black economy (LOGBEC). The results were robust even when unemployment (LOGUEMP) was included. An unemployment shock was shown to enhance black economy in Nigeria. Practical Implications: The study is significant for the concerned authorities in Nigeria so that policy measures are taken and directed towards the causes that drive the black economy in the country. Originality/value: The impulse response function was estimated. It was estimated to show the plots of the responses from black economy (LOGBEC) to a one standard deviation shock in each indicated variable (national minimum wage (LOGMWA), inflation (LOGINFL), and tax (ATAX)). The shocks to national minimum wage (LOGMWA) will have a negative effect on black economy (LOGBEC) in Nigeria.

scholarly journals Structure Damage Identification Based on Regularized ARMA Time Series Model under Environmental Excitation

Vibration ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 138-156 ◽  
Author(s):  
Xuan Zhang ◽  
Dongsheng Li ◽  
Gangbing Song
Keyword(s):  
Time Series ◽  
Impulse Response ◽  
Response Function ◽  
Structural Damage ◽  
Damage Identification ◽  
National Laboratory ◽  
Impulse Response Function ◽  
Time Series Model ◽  
Vibration Response ◽  
Structural Vibration

In this paper, a non-modal parametric method to identify structural damage using a regularized autoregressive moving average time series model under environmental excitation is proposed in combination with the virtual impulse response function. This method can use the structural vibration response to determine the damage caused to the structure during environmental excitation. Firstly, the virtual impulse response function is obtained by using the structural vibration response. Then, a regularized ARMA time series model is used to fit the virtual impulse response function. Based on the change of auto-regression coefficients in the regularization model under different damage cases, the structural damage is identified. The authors derive the regularization equation of an ARMA time series model to solve the problems in a time series model and obtain the regularization coefficient. Finally, this method is applied to a three-degrees-of-freedom chain structure and a three-floor shear structure of the Los Alamos National Laboratory (LANL). The experimental results show that the method based on the regularized ARMA time series model under environmental excitation can effectively identify the structural damage, which is a reliable method for damage identification. The regularized ARMA time series model can accurately extract signal features and has invaluable application prospects in the field of structural health monitoring.

Fractional Vector-Order h-Realisation of the Impulse Response Function

2020 ◽  
Vol 14 (2) ◽  
pp. 108-113
Author(s):  
Ewa Pawłuszewicz
Keyword(s):  
Control Systems ◽  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Linear Control ◽  
Linear Control Systems

AbstractThe problem of realisation of linear control systems with the h–difference of Caputo-, Riemann–Liouville- and Grünwald–Letnikov-type fractional vector-order operators is studied. The problem of existing minimal realisation is discussed.

scholarly journals Convolution-based time-domain simulation for fluidelastic instability in tube arrays

2021 ◽  
Author(s):  
Mingjie Zhang ◽  
Ole Øiseth
Keyword(s):  
Impulse Response ◽  
Response Function ◽  
Time Domain ◽  
Impulse Response Function ◽  
Time Domain Simulation ◽  
Unit Step ◽  
Tube Arrays ◽  
Unit Impulse ◽  
The Time Domain ◽  
Unit Impulse Response

AbstractA convolution-based numerical algorithm is presented for the time-domain analysis of fluidelastic instability in tube arrays, emphasizing in detail some key numerical issues involved in the time-domain simulation. The unit-step and unit-impulse response functions, as two elementary building blocks for the time-domain analysis, are interpreted systematically. An amplitude-dependent unit-step or unit-impulse response function is introduced to capture the main features of the nonlinear fluidelastic (FE) forces. Connections of these elementary functions with conventional frequency-domain unsteady FE force coefficients are discussed to facilitate the identification of model parameters. Due to the lack of a reliable method to directly identify the unit-step or unit-impulse response function, the response function is indirectly identified based on the unsteady FE force coefficients. However, the transient feature captured by the indirectly identified response function may not be consistent with the physical fluid-memory effects. A recursive function is derived for FE force simulation to reduce the computational cost of the convolution operation. Numerical examples of two tube arrays, containing both a single flexible tube and multiple flexible tubes, are provided to validate the fidelity of the time-domain simulation. It is proven that the present time-domain simulation can achieve the same level of accuracy as the frequency-domain simulation based on the unsteady FE force coefficients. The convolution-based time-domain simulation can be used to more accurately evaluate the integrity of tube arrays by considering various nonlinear effects and non-uniform flow conditions. However, the indirectly identified unit-step or unit-impulse response function may fail to capture the underlying discontinuity in the stability curve due to the prespecified expression for fluid-memory effects.

IMPROVING EXTRACTION OF IMPULSE RESPONSE FUNCTIONS USING STATIONARY WAVELET SHRINKAGE IN TERAHERTZ REFLECTION IMAGING

2010 ◽  
Vol 09 (04) ◽  
pp. 387-394 ◽  
Author(s):  
YANG CHEN ◽  
YIWEN SUN ◽  
EMMA PICKWELL-MACPHERSON
Keyword(s):  
Experimental Data ◽  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Terahertz Imaging ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Inverse Filtering ◽  
Wavelet Shrinkage ◽  
Gaussian Filtering

In terahertz imaging, deconvolution is often performed to extract the impulse response function of the sample of interest. The inverse filtering process amplifies the noise and in this paper we investigate how we can suppress the noise without over-smoothing and losing useful information. We propose a robust deconvolution process utilizing stationary wavelet shrinkage theory which shows significant improvement over other popular methods such as double Gaussian filtering. We demonstrate the success of our approach on experimental data of water and isopropanol.

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