Vibration-Based Condition Monitoring

Wu, Yulin; Sheng-cai, LI; Liu, Shuhong; Dou, Hua-Shu; Qian, Zhongdong

doi:10.1007/978-94-007-6422-4_11

Cited by 38 publications

(7 citation statements)

References 11 publications

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“…[3][4][5] In recent 30 years, vibration-based methods have been developed for structural damage detection. 6 These methods have been used for damage detection in different structural systems, and even for large and sophisticated structures. 7 Generally, vibration-based methods are based on the concept that it is possible to consider the structural system as a dynamic system, having structural parameters such as stiffness, mass, and damping.…”

Section: Shm Methodsmentioning

confidence: 99%

“…(5) AI-based SHM algorithm is computationally costly and depends tightly on the graphical processing unit (GPU); (6) it is generally challenging to fully train a deep model due to the gradient vanishing or exploding during back-propagation; and (7) rare study has been carried out on deep DRN for vibration-based SHM applications, especially for damage recognition based on the raw ambient vibration acceleration signals acquired from an external complex structure.…”

Section: In Vibration-based Shmmentioning

confidence: 99%

“…Structural Health Monitoring 21 (6) Table 11 and shown in Figure 13. The damage actions began with the partial intersection of the mid-span vertical member (Damage1), before its full intersection was completed (Damage2).…”

Section: Steel Truss Bridgementioning

confidence: 99%

“…According to the application type, there are two main directions of technical diagnostics: monitoring and diagnostics of rotating machinery, [1][2][3][4] and structural health monitoring (SHM), which is defined as a process of implementing a damage detection and characterisation strategy for various engineering structures. [5][6][7][8] According to the used technique, diagnostic methods can be divided into: destructive technique when maximum load or fatigue test of samples are performed 9,10 ; and non-destructive technique when the state of the structure is evaluated without causing damage to it. 11,12 Due to this advantage, the nondestructive technique has become the most common technique for technical diagnostics nowadays.…”

Section: Introductionmentioning

confidence: 99%

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A novel structural damage identification method based on the acceleration responses under ambient vibration and an optimized deep residual algorithm

Al-Azzawi

Wang

2022

Structural Health Monitoring

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Recently, structural health monitoring (SHM) methods for civil structures have been investigated widely, especially Deep Learning (DL)-based methods. However, it is usually difficult to fully train a deep neural network, and thus, typical DL-based SHM methods are limited in terms of performance. While addressing these issues, in this paper, a novel methodology is proposed for smart damage identification of frame structures. The newly proposed SHM method is based on raw time-domain structural response signals and deep residual network (DRN). The introduced DRN algorithm has been designed and tested in an effective way for extracting and learning the optimum features of the 1D raw ambient vibration acceleration signals, without any need for engineered features. Also, the network’s performance has been optimized using Bayesian optimization, which clearly enhances the network’s accuracy and information flow across it. Next, the outputs of DRNs are further utilized through new methods for damage size estimation and damage localization. The proposed methodology has been evaluated using the datasets of numerical and experimental frames of the SHM benchmark problem and the dataset of a real-world full-scale truss bridge. The results show that the proposed method is capable of detecting, localizing, and quantifying structural damage accurately for all of the simulated cases of the two examples. Furthermore, conducted comparison studies have approved that the new approach is more efficient than other machine learning-based methods, and it can overcome the major limitations of Artificial intelligence-based SHM models.

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Section: Shm Methodsmentioning

confidence: 99%

Section: In Vibration-based Shmmentioning

confidence: 99%

Section: Steel Truss Bridgementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel structural damage identification method based on the acceleration responses under ambient vibration and an optimized deep residual algorithm

Al-Azzawi

Wang

2022

Structural Health Monitoring

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“…and Fanning(Carden & Fanning, 2004) conducted a detailed review of the vibration based condition monitoring techniques. Their review emphasized on the structural engineering applications.…”

mentioning

confidence: 99%

Spectral Features-Based Damage Diagnosis of Structural Steel Plate

Krishnan*,

Yaacob,

M P

et al. 2019

IJITEE

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Cracks and physical damages are a threat to the strength of the structures. Non-destructive test (NDT) measures are used to detect the damages at the earlier phase to avoid any major damages to the structures. Vibration signal processing is one of the NDT methods to determine the damages based on the experimental modal analysis. In this study, an experimental setup is devised to freely suspend a steel plate of size 30 cm by 60 cm. Based on the experimental modal analysis, the steel structure is struck using an impact hammer and the dispersed mechanical energy is bagged as vibration response using an accelerometer. The damages of size 512 µm to 1852 µm were manually simulated at arbitrary locations on the surface of the steel structure. The data acquisition procedure is repeated before and after the simulation of damage. The vibration signals are then processed, and the spectral features are extracted. The feature set is normalized between 0 and 1 are then mapped towards the condition of the plate to formulate the final dataset. Using a k-fold cross validation technique, the dataset is trained and tested using Least square support vector machine (LS-SVM) and k-nearest neighbor (KNN) classifiers. The results are compared and discussed

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