Two-Step Method for Instability Damage Detection in Tower Body of Transmission Structures

Qu, Weilian; Song, Weijie; Xia, Yong; Xu, You Lin; Qin, Wenke; Jiang, Zhicai

doi:10.1260/1369-4332.16.1.219

Cited by 11 publications

(8 citation statements)

References 13 publications

(12 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, there are only a few studies on the application of damage detection techniques in power transmission equipment. According to Qu et al [22], power transmission towers are susceptible to sudden damages and instabilities which may lead to total collapse of the structure. Huang et al [23] investigated the effect of foundation settlement on the variations in natural frequencies of the tower.…”

Section: Damage Detection Of Power Transmission Equipmentmentioning

confidence: 99%

“…Qu et al [22] presented a two-stage method to identify the damage in the vertical elements of the power transmission towers. In this method, wavelet packet energy and modal strain energy of the structure were used as a damage indicator.…”

Section: Damage Detection Of Power Transmission Equipmentmentioning

confidence: 99%

“…Stipulating ideal conditions for obtaining modal parameters and the large number of required sensors are disadvantages of this detection procedure. The method presented by Qu et al [22] effectively detected the damage that occurred in the major element of the tower. Their method is applicable for the identification of the instability damage only in the major element of the tower.…”

Section: Comparison With Other Studiesmentioning

confidence: 99%

See 2 more Smart Citations

Vibration Anatomy and Damage Detection in Power Transmission Towers with Limited Sensors

Mohammadi

Mirtaheri

Salkhordeh

et al. 2020

Sensors

View full text Add to dashboard Cite

This study presents a technique to identify the vibration characteristics in power transmission towers and to detect the potential structural damages. This method is based on the curvature of the mode shapes coupled with a continuous wavelet transform. The elaborated numerical method is based on signal processing of the output that resulted from ambient vibration. This technique benefits from a limited number of sensors, which makes it a cost-effective approach compared to others. The optimal spatial location for these sensors is obtained by the minimization of the non-diagonal entries in the modal assurance criterion (MAC) matrix. The Hilbert–Huang transform was also used to identify the dynamic anatomy of the structure. In order to simulate the realistic condition of the measured structural response in the field condition, a 10% noise is added to the response of the numerical model. Four damage scenarios were considered, and the potential damages were identified using wavelet transform on the difference of mode shapes curvature in the intact and damaged towers. Results show a promising accuracy considering the small number of applied sensors. This study proposes a low-cost and feasible technique for structural health monitoring.

show abstract

Section: Damage Detection Of Power Transmission Equipmentmentioning

confidence: 99%

Section: Damage Detection Of Power Transmission Equipmentmentioning

confidence: 99%

Section: Comparison With Other Studiesmentioning

confidence: 99%

See 1 more Smart Citation

Vibration Anatomy and Damage Detection in Power Transmission Towers with Limited Sensors

Mohammadi

Mirtaheri

Salkhordeh

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…us far, the majority of studies on damage identification have focused on structural components [2][3][4], building structures [5,6], bridge structures [7,8], and other structures [9,10]. Because the retaining wall structure system is constituted by the wall and soil, it is difficult to analyze the complicated interaction between the wall and soil.…”

Section: Introductionmentioning

confidence: 99%

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

2019

Shock and Vibration

View full text Add to dashboard Cite

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.

show abstract

“…In 1998, Doebling et al noted that damage within structures could be detected from changes in structural characteristics [6]. Thus far, the majority of studies on damage identification have focused on structural components [7][8][9], building structures [10], bridge structures [11,12], and other structures [13,14]. In contrast, damage identification research on retaining wall structures is much rarer.…”

Section: Introductionmentioning

confidence: 99%

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

2016

Shock and Vibration

View full text Add to dashboard Cite

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.

show abstract

Two-Step Method for Instability Damage Detection in Tower Body of Transmission Structures

Cited by 11 publications

References 13 publications

Vibration Anatomy and Damage Detection in Power Transmission Towers with Limited Sensors

Vibration Anatomy and Damage Detection in Power Transmission Towers with Limited Sensors

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

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

Contact Info

Product

Resources

About