Wavelet Energy Accumulation Method Applied on the Rio Papaloapan Bridge for Damage Identification

Machorro-Lopez, Jose M.; Amezquita-Sanchez, Juan P.; Valtierra-Rodríguez, Martín; Carrion-Viramontes, Francisco J.; Quintana-Rodriguez, Juan A.; Valenzuela-Delgado, Jesus I.

doi:10.3390/math9040422

Cited by 7 publications

(15 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…de Sena et al (2021) combined wavelet subband coefficients with entropy. Machorro-Lopez et al (2021) presented a wavelet energy method for damage identification. Radi et al (2019) developed a wavelet variance-based method for modeling sensor error.…”

Section: Methodsmentioning

confidence: 99%

RETRACTED: Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm

2021

View full text Add to dashboard Cite

Aim: Multiple sclerosis (MS) is a disease, which can affect the brain and/or spinal cord, leading to a wide range of potential symptoms. This method aims to propose a novel MS recognition method.Methods: First, the bior4.4 wavelet is used to extract multiscale coefficients. Second, three types of biorthogonal wavelet features are proposed and calculated. Third, fitness-scaled adaptive genetic algorithm (FAGA)—a combination of standard genetic algorithm, adaptive mechanism, and power-rank fitness scaling—is harnessed as the optimization algorithm. Fourth, multiple-way data augmentation is utilized on the training set under the setting of 10 runs of 10-fold cross-validation. Our method is abbreviated as BWF-FAGA.Results: Our method achieves a sensitivity of 98.00 ± 0.95%, a specificity of 97.78 ± 0.95%, and an accuracy of 97.89 ± 0.94%. The area under the curve of our method is 0.9876.Conclusion: The results show that the proposed BWF-FAGA method is better than 10 state-of-the-art MS recognition methods, including eight artificial intelligence-based methods, and two deep learning-based methods.

show abstract

Section: Methodsmentioning

confidence: 99%

RETRACTED: Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm

2021

View full text Add to dashboard Cite

show abstract

“…Aiming at the identification of bridge mode shapes in the field of structural health monitoring (SHM), Jian et al [87] proposed a wavelet analysis method to directly obtain mode shapes based on the dynamic responses of a tractor trailer vehicle model, and a wavelet denoising algorithm was utilized to enhance the accuracy. Machorro-Lopez et al [88] presented a novel wavelet-based method, called the wavelet energy accumulation method, to assess the damage of vehicular bridges. First, a continuous wavelet transform was used to localize the site, then the wavelet energy was used to quantify the extent, and finally, the Rio Papaloapan Bridge was adopted to validate the method's feasibility.…”

Section: Wavelet-based Methodsmentioning

confidence: 99%

Temperature Effect on Vibration Properties and Vibration-Based Damage Identification of Bridge Structures: A Literature Review

2022

View full text Add to dashboard Cite

In civil engineering structures, modal changes produced by environmental conditions, especially temperature, can be equivalent to or greater than the ones produced by damage. Therefore, it is necessary to distinguish the variations in structural properties caused by environmental changes from those caused by structural damages. In this paper, we present a review of the technical literature concerning variations in the vibration properties of civil structures under varying temperature conditions and damage identification methods for bridge structures. First, the literature on the effect of temperature on vibration properties is roughly divided into experimental and theoretical studies. According to the classification of theoretical research methods, the progress in research on the probability analysis method, the artificial intelligence method, and the optimization algorithm method in this field is reviewed. Based on the different methods of experimental research employed in this field, the experimental research is reviewed according to qualitative and quantitative analyses. Then, damage identification methods for bridge structures are reviewed, considering data-based and model-based methods. Finally, different research methods are summarized.

show abstract

“…At present, scholars have proposed a series of damage detection methods based on wavelet theory. Machorro-Lopez et al [28] proposed a wavelet energy accumulation method based on wavelet changes for the detection, location and quantification of axle damage. Saadatmorad et al [29] proposed a new method for damage detection of beam structures by combining the statistical characteristics of the vibration modes of beam structures and their discrete wavelet transform (hereinafter called 'DWT').…”

Section: Introductionmentioning

confidence: 99%

BPF-WT combined filtering method for indirect identification of bridge dynamic characteristics

Zheng,

Yang,

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

The indirect measurement method of extracting the dynamic characteristics of the bridge structure from the dynamic response of passing vehicles is a new method for bridge structure health monitoring, which has the advantage of cost-effectiveness. However, how to improve the accuracy of the indirect measurement method to identify the dynamic characteristics of the bridge is the current research focus. In this paper, combining the characteristics and advantages of bandpass filter (BPF) and wavelet transform (WT), a simple and effective joint filtering method BPF-WT is proposed for indirect identification of bridge dynamic characteristics. This method can eliminate the peak caused by the known vehicle frequency, and realize the layer-by-layer decomposition and reconstruction of the signal through the advantage of WT, to achieve the purpose of automatically executing the packet filtering task. This paper takes a simple trolley as an example to conduct a scaled test study to identify the dynamic characteristics of a bridge and proves that the BPF-WT joint filtering method can perform bridge dynamics under three conditions: different vehicle weights, different driving speeds, and driving on bridge decks with different roughness. Characteristic identification results and their influence rules. According to the research findings, the method of combined filtering suggested in this paper can efficiently filter out the noise produced by the vehicle's frequency and the surroundings. This method can also distinctly detect the initial three frequencies of the bridge. Therefore, it demonstrates the practicality and efficiency of the BPF-WT combined filtering technique, which has a broad range of potential applications.

show abstract

Wavelet Energy Accumulation Method Applied on the Rio Papaloapan Bridge for Damage Identification

Cited by 7 publications

References 33 publications

RETRACTED: Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm

RETRACTED: Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm

Temperature Effect on Vibration Properties and Vibration-Based Damage Identification of Bridge Structures: A Literature Review

BPF-WT combined filtering method for indirect identification of bridge dynamic characteristics

Contact Info

Product

Resources

About