In this study we investigate the feasibility of detecting structural damage using the Hilbert--Huang Transform (HHT) method. A damage detection index, which we call the ratio of equivalent damping ratio (RED), is proposed. The damage detection index is evaluated using the HHT and the Fast Fourier Transform (FFT) methods for the analysis of shaking table test data obtained for benchmark models based upon the Kobe and El Centro earthquakes. The results indicate that, when the response of the structure is in the elastic region, the RED value changes only slightly in both the HHT and the FFT spectra. In addition, when the structural response is nonlinear (i.e., member yielding occurs), the RED and peak ground acceleration curves indicate the incremental change in the HHT spectra. However, the same phenomena cannot be found in the FFT spectra. Moreover, there is greater change in the value of the RED for the top floor than for the other floors. Furthermore, structural damage is detected only when acceleration response data from the top floor is used. Therefore, the RED estimated from the smoothed HHT spectra is an effective and sensitive index for detecting structural damage. The proposed RED strategy will be used to establish an on-line health monitoring scheme for detecting structural damage in steel structures right after the occurrence of ground motion.

A case study of damage detection in benchmark buildings using a Hilbert-Huang Transform-based method

Dam and powerhouse operation sustainability is a major concern from the hydraulic engineering perspective. Powerhouse operation is one of the main sources of vibrations in the dam structure and hydropower plant; thus, the evaluation of turbine performance at different water pressures is important for determining the sustainability of the dam body. Draft tube turbines run under high pressure and suffer from connection problems, such as vibrations and pressure fluctuation. Reducing the pressure fluctuation and minimizing the principal stress caused by undesired components of water in the draft tube turbine are ongoing problems that must be resolved. Here, we conducted a comprehensive review of studies performed on dams, powerhouses, and turbine vibration, focusing on the vibration of two turbine units: Kaplan and Francis turbine units. The survey covered several aspects of dam types (e.g., rock and concrete dams), powerhouse analysis, turbine vibrations, and the relationship between dam and hydropower plant sustainability and operation. The current review covers the related research on the fluid mechanism in turbine units of hydropower plants, providing a perspective on better control of vibrations. Thus, the risks and failures can be better managed and reduced, which in turn will reduce hydropower plant operation costs and simultaneously increase the economical sustainability. Several research gaps were found, and the literature was assessed to provide more insightful details on the studies surveyed. Numerous future research directions are recommended.

https://www.mdpi.com/2071-1050/12/4/1676/pdf

State-of-the Art-Powerhouse, Dam Structure, and Turbine Operation and Vibrations

Bayesian estimation approach based on modified SCAM algorithm and its application in structural damage identification

Concrete arch dams have been widely constructed worldwide, and many of these dams are located in areas with high seismic activity. However, strong seismic loading poses a severe threat to concrete arch dams, and dams have the risk of suffering damage and the possibility of an ensuing dam break. In past decades, seismic and structural health monitoring has undergone rapid growth in the context of arch dams to track the operation state of arch dams under strong seismic loading. In fact, arch dams with damage caused by seismic loading normally exhibit nonlinear dynamic behaviors and time-variable dynamic properties. To effectively identify the structural damage state development of arch dams under seismic loading, an online damage identification method using a novel recursive time-variable autoregressive with exogenous (TVARX) input model was presented in this paper. To improve the tracking capability for the time-variable coefficients of the TVARX model, an adaptive adjustment algorithm of variable weighting factors was incorporated into the recursive least-squares method. In the proposed method, the predicted model residual, a damage index named the fit ratio (FR), the difference between fit ratios (DF), and a damage index based on the change in ARX model parameters (CH) were proposed to identify the presence of damage, damage area, and relative damage extent for arch dams. Eventually, the proposed approach was used for the online damage state identification of arch dams in a numerical simulation example and a shaking table test, and the identification results demonstrated the effectiveness of the proposed approach.

Online structural damage state identification of concrete arch dams under dynamic loads using a recursive TVARX approach

Priority Determination of Repairing Embankment Dam using Analytical Hierarchy Process (AHP), Case Studies: Saguling Dam and Djuanda Dam

Abstract Damage detection in concrete gravity dams using Hilbert-Huang Method, as one of the most common signal processing techniques, is studied in this research. After considering a typical geometry for dams, damage is modelled by a reduction in the modulus of elasticity in the dam’s body (in three levels of damage) and in different areas of the structure. The dam is excited by a horizontal earthquake and the primary natural frequencies of the dam are calculated by applying Hilbert-Huang Method to the measured response, which is the acceleration of five points in the system. Based on the changes in the frequencies of the damaged and undamaged structure, a parameter, called relative frequency error, has been introduced. The results show that the proposed criterion used in this study can not only properly identify the location of damage but also predict the severity of the structural damage in concrete gravity dams accurately.

/pdf/damage-detection-of-concrete-gravity-dams-using-hilbert-3ms20zt3c3.pdf

Damage Detection of Concrete Gravity Dams using Hilbert-Huang Method

In structural engineering, damage detection in concrete gravity dams (CGDS) is a practical problem. Dam destruction can have severe financial consequences and may even lead to fatalities. Therefore, structural health monitoring in advance is crucial. In this regard, a well-known CGD, namely the Pine Flat Dam, has been chosen for the Finite Element Modeling. In this paper, damage is induced in the dam neck through elasticity modulus reduction by 40 % and 80 %. In addition, after applying Northridge earthquake, the acceleration in structure nodes for intact and damaged cases are recorded in vector formats. Using various methods, such as Discrete-time Fourier Transform (DTFT), Wavelet transform and Wiener transform, the differences between these two signals are investigated. The standard deviation (S.D.) of variations is chosen as the performance metric and is applied to the signal amplitude between intact and damage observations/signals. The reason why several signal processing algorithms are used is finding an approach which shows more clearly the differences caused by the destruction. This is evaluated via S.D. values for different algorithms. The results confirm the superiority of DTFT over other given algorithms. DTFT has a negligible outperformance (approximately zero dB) with respect to the Wavelet transform in both the crest and the lower nodes of the dam. This rate for DTFT and Wavelet is 10dB higher than that of Wiener and 35 dB in comparison with the simple amplitude difference. Moreover, the detection thresholds for the given methods are compared, and it is verified that the DTFT and Wavelet indicate the best performance.

/pdf/damage-detection-in-concrete-gravity-dams-using-signal-2v3jqdva1s.pdf

Damage detection in concrete gravity dams using signal processing algorithms based on earthquake vibrations

Detection of damage in concrete gravity dams (CGDs) is one of the challenges that need to be overcome since dam failure may lead to irreversible consequences. This research aims to detect structural damage within CGDs by wavelet analysis. From a structural point of view, stiffness is an important factor in the dynamic behaviour of concrete gravity dam systems. Any sudden change in the stiffness leads to alteration in the dynamic response of the structures. The proposed analysis of such a condition will help to investigate the responses before and after the occurrence of any structural damage. The main contributions of this paper are to detect the existence of any damage in the dam structure and determine the damage location along the height of the dam. In order to achieve these purposes, three finite element models of the Pine Flat, Bluestone, and Folsom dams are chosen as case studies. These dams have been modelled for both intact and damaged states, and their geometrical, physical, and mechanical characteristics are defined by SAP2000 software. A series of modal analyses was performed to determine the frequencies and shapes of the structural motions. After reduction of the elasticity modulus by 20% and 50%, the Discrete Wavelet Transform (DWT) was applied to the difference between the intact and damaged observations. Then, the DWT outputs were analysed to get information about the existence of damage as well as its location in the dam structure. Overall, from the obtained results, the main finding of this study states that the location and severity of the structural damages have been efficiently detected according to the significant amplitude variations in DWT diagrams.
ABSTRAK: Pengesanan kerosakan pada empangan graviti konkrit (CGDs) adalah salah satu cabaran yang perlu diatasi disebabkan kegagalan empangan yang boleh membawa kepada akibat buruk. Kajian ini bertujuan bagi mengesan kerosakan struktur dalam CGDs menggunakan analisis wavelet. Dari sudut pandang struktur, struktur yang kukuh adalah faktor penting dalam sifat dinamik sistem empangan graviti konkrit. Sebarang perubahan secara tiba-tiba pada struktur bangunan membawa kepada perubahan tindak balas dinamik struktur. Analisis yang dicadangkan terhadap keadaan ini membantu dalam memberi tindak balas sebelum dan selepas jika berlaku sebarang kerosakan struktur. Sumbangan utama kajian ini adalah bagi mengesan jika terdapat sebarang kerosakan pada struktur dalam empangan dan menentukan lokasi kerosakan sepanjang ketinggian empangan. Bagi mencapai matlamat ini, tiga model unsur terhingga daripada empangan Pine Flat, Bluestone dan Folsom telah dipilih sebagai kes kajian. Kesemua empangan ini dimodelkan bagi kedua-dua keadaan iaitu ketika baik dan rosak. Ciri geometri, fizikal dan ciri-ciri mekanikal juga telah ditakrif menggunakan perisian SAP2000. Satu siri model analisis telah dijalankan bagi menentukan frekuensi dan bentuk gerakan struktur. Selepas pengurangan modulus keanjalan sebanyak 20% dan 50%, Transformasi Wavelet Diskret (DWT) telah digunakan bagi mengesan perbezaan antara keadaan baik dan rosak. Kemudian, hasil dari DWT ini dianalisis bagi mendapatkan maklumat mengenai kewujudan kerosakan pada empangan dan juga lokasi kerosakan dalam struktur empangan. Secara keseluruhan, hasil kajian berjaya menentukan lokasi dan tahap kerosakan struktur dengan cekap mengikut variasi amplitud ketara dalam rajah DWT.

/pdf/a-survey-of-matlab-efficiency-in-damage-detection-of-3hos3ibodi.pdf

Sajad Esmaielzadeh

Papers

Damage Detection of Concrete Gravity Dams using Hilbert-Huang Method

Damage detection in concrete gravity dams using signal processing algorithms based on earthquake vibrations

A survey of matlab efficiency in damage detection of concrete gravity in concrete gravity dams

Application of signal processing techniques in structural health monitoring of concrete gravity dams