Wavelet analysis of static deflections for multiple damage identification in beams

Ma, Qiaoyu; Solís, Mario; Galvín, P.

doi:10.1016/j.ymssp.2020.107103

Cited by 26 publications

(15 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sharma and Pachori [17], in turn, proposed an iterative decomposition of the Hankel matrix, enabling the decomposition of the monocompetent signal and following Hilbert transform, the amplitude is determined as well as frequency functions of each decomposed component. Another use of wavelet analysis can be found, for example, in [18][19][20]. Yeap et al [21] and Sejdić et al [22] summarise some of the advantages and disadvantages of the FFT and WT methods.…”

Section: Signal Analysis and Anomaly Detection Methodsmentioning

confidence: 99%

Advanced Supervision of Smart Buildings Using a Novel Open-Source Control Platform

Minarčík

Procházka²,

Gulan

2020

Sensors

View full text Add to dashboard Cite

Gathering data and monitoring performance are at the heart of energy efficiency and comfort securing strategies in smart buildings. Therefore, it is crucial to present the obtained data to the user or administrator of such a building in an appropriate form. Moreover, evaluating the data in real time not only helps to maintain comfort, but also allows for a timely response from the user or operator to a possible fault. Continuous online monitoring and analysis of process behaviour, which is referred to as advanced supervision, is addressed in this paper by developing a procedure that will form an artificial operator autonomously supervising process. After introducing several techniques that are used for signal analysis, we propose an approach to advanced supervision of processes in smart buildings or other industrial control systems. The developed procedure is implemented on a control system platform that is particularly suitable for this purpose. Moreover, this platform includes a framework that provides support for the implementation of advanced control techniques and it is based on open-source tools, which is rarely seen in industrial applications. The developed advanced supervision procedure has been tested in simulation as well as in a practical case study using a real two-storey family house.

show abstract

Section: Signal Analysis and Anomaly Detection Methodsmentioning

confidence: 99%

Advanced Supervision of Smart Buildings Using a Novel Open-Source Control Platform

Minarčík

Procházka²,

Gulan

2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Song et al [ 6 ] used the static strain data to obtain the corresponding static displacement for detecting structural damages. Ma et al [ 7 ] employed wavelet analysis to diagnose structural defects using the static displacements of the structures. The fault position can be determined from the wavelet maxima lines and the fault severity can be assessed by the wavelet coefficients along the corresponding maxima lines.…”

Section: Introductionmentioning

confidence: 99%

Structural Damage Identification Using the Optimal Achievable Displacement Variation

2022

View full text Add to dashboard Cite

To ensure the safe use of structures, it is essential to develop efficient damage identification techniques. In this paper, a brand-new approach to identifying structural deterioration based on static displacement is proposed. First, the relationship between the displacement variation and the damaged element is derived from the static response equations before and after damage. Subsequently, the optimal achievable displacement variation is defined to determine the damage location in the structure. A progressive elimination strategy is suggested to identify the real damaged parts and weed out the pseudo-damaged elements by measuring the distance between the measured and the best possible displacement variation. After determining the damage location, the corresponding damage extent can be calculated by a system of linear equations. The proposed approach has been tested on a beam structure and truss structure using simulated and experimental data. Compared with the existing static sensitivity method, the suggested method does not result in misjudgment and has higher identification accuracy. It has been demonstrated that the suggested approach is effective at locating and assessing the extent of structural damage.

show abstract

“…Nevertheless, there is always a difference between a model and a real structure, which can not be ascertained unless it is identified using measurements. In this paper, existing formulation of a Damage Locating Index (DLI) and a Damage Severity Index (DSI) [1] based on the Continuous Wavelet Transform (CWT) and Lipschitz exponent are redefined and extended for the application of damage identification from the experimental mode shapes of a damaged beam. The paper explores the applicability of the identification method from three perspectives: (1) the robustness and limitations of the proposed DLI on an oscillating signal (mode shapes) obtained from a sparse measuring grid; (2) the application of the DSI to modal displacements and its independence from boundary conditions and damage location; and (3) the potential use of the same DSI Reference values from either a static or any modal response for the evaluation of the damage.…”

Section: Introductionmentioning

confidence: 99%

“…Kumar and Singh [8] compares the use of 100, 200, and 1000 measurement points for the application of CWT for damage detection and indicates that the accuracy of the results is affected significantly. Hence, numerical studies on this topic consider usually a high number of measurement points and the experimental studies are conducted with measuring systems that can obtain a dense measurement grid, such as laser scanning [7,11] and photogrammetry measuring system [1,8,[12][13][14]. In Table 1, the number of samples in some relevant research studies are listed.…”

Section: Introductionmentioning

confidence: 99%

Wavelet and Lipschitz exponent based damage identification method for beams using mode shapes

Solís²,

Rodríguez-Mariscal³

et al. 2022

Measurement

Self Cite

View full text Add to dashboard Cite

Wavelet analysis of static deflections for multiple damage identification in beams

Cited by 26 publications

References 28 publications

Advanced Supervision of Smart Buildings Using a Novel Open-Source Control Platform

Advanced Supervision of Smart Buildings Using a Novel Open-Source Control Platform

Structural Damage Identification Using the Optimal Achievable Displacement Variation

Wavelet and Lipschitz exponent based damage identification method for beams using mode shapes

Contact Info

Product

Resources

About