Undamaged Structures Research Articles

Importance of Heritage Structures as Bat Roosts in the Sahara Desert

ABSTRACTIn addition to the availability of water and invertebrate prey, roost sites are considered the main factors enabling bats to survive in desert areas. Because suitable roost sites are often limiting resources, human constructions are also important for these animals. Conversely, in the context of built heritage conservation, bats are often discussed as a cause of damages. However, if historic structures deteriorate, they may lose their suitability as roosting sites for bats. This study examines how the condition of domed tombs in Sudan affects their use by bats. Inspections of 19 tombs revealed that bats occupied only undamaged structures, with 1652 individuals of four species found. Slightly and partially damaged tombs were not used by bats. These findings highlight the importance of preserving man‐made structures as critical roosting sites in arid environments to support local bat populations.

Predicting delamination in composite laminates through semi-analytical dynamic analysis and vibration-based quantitative assessment

Delamination is a frequent failure mode of laminated fiber-reinforced polymer (FRP) composites structure in aeronautical and other industries, leading to changes in vibration characteristics. Vibration-based techniques evaluate and compare the dynamic response between damaged and undamaged structures, and guarantee the non-destructive measurement with reliability and repeatability. Previous studies typically concentrate on using finite element method to obtain vibration characteristics and enhance the database for intelligent algorithms. This paper presents a semi-analytical result using the Chebyshev−Ritz method to expand delamination prediction. Vibration frequency serves as a global damage indicator, and multi-order frequency characteristics are utilized to identify the delamination length and location of FRP composite plates. A database of natural frequencies corresponding to damage parameters for FRP laminated plates is generated based on the established model using the region approach. An intelligent approach, known as a genetic algorithm optimization-based back-propagation (GA-BP) artificial neural network, is utilized for system identification. The network model is subjected to a sensitivity analysis, where artificial noise is added to vibration frequency to distinguish between the actual structure and the numerical model. The results indicate that the GA-BP algorithm shows good accuracy and stable performance against the standard neural networks for delamination analysis.

Progressive collapse of regular RC structure considering flexibility of slabs under gravity and wind loads

Abstract Progressive collapses are disastrous phenomena which occur in the structure due to manmade incidents or natural disasters. There are not any significant studies considering the flexibility of slabs in the structures, as an alternative to treating them as rigid diaphragms. The present study deals with the progressive collapse of a regular reinforced concrete structure considering flexibility of slabs, comparing the same when the slabs are considered as rigid diaphragms. 20 storey(G+19) building is modeled using ETABS software and nonlinear static analysis is performed under the action of gravity and wind loads. At the outset, the analysis is done for undamaged structure to find the behavior of structure and then the damaged models have been analyzed by removing one of the critical column in different locations at first storey, based on general services administration (GSA) guidelines[16]. Various response parameters such as base force capacity, storey stiffness and storey displacements have been compared for undamaged and damaged structures considering and not considering the flexibility of slabs. From the comparison of the results, it was noticed that the chance of progressive collapse is high when the corner column is damaged and also resistance to wind load is considerably higher when stiffness of slabs is considered for the analysis in both undamaged structure and the four cases of damaged structure (ii), which is about three times higher.

Amplitude Dispersion Compensation in Time-Reversed Lamb Waves for Enhanced Sensitivity in Damage Detection

In Lamb wave-based baseline-free damage detection employing the time-reversal method (TRM), the damage index (DI) is computed from the similarity between the main mode of the reconstructed signal obtained after the time-reversal process (TRP) and the input signal, both normalized. However, a perfect similarity with a zero DI value cannot be achieved for undamaged structures due to the amplitude dispersion of Lamb waves, which is not compensated in the TRP. Thus, a nonzero DI does not necessarily indicate the presence of damage. Even worse is the fact that the similarity and, therefore, the DI for the pristine structure depend on the probing frequency, making it difficult to estimate a unique threshold value of DI for damage identification. The imperfect reconstruction also significantly reduces the relative sensitivity of the DI to the presence of damage. In this article, we propose a method to compensate the amplitude dispersion in the main mode of the reconstructed signal for undamaged metallic plates to achieve a zero threshold of DI. First, the transfer function of the main mode of the reconstructed signal for an undamaged path (the path with the least DI for a network of sensing paths) is obtained by exciting the actuator with a broadband excitation and extracting the S0 and A0 modes from the forward response measured at the sensor. To compensate the amplitude dispersion in the TRP-generated main mode, the transfer function of the recorded signal of a path is divided by the transfer function of the main mode obtained for the undamaged path. A comprehensive numerical study shows that the DI computed with the compensated reconstructed signal has much higher sensitivity to damage than that without applying the proposed compensation at all frequencies, providing the flexibility to choose the probing frequency according to the desired damage size to be detected.

A New Approach to Structural Damage Identification Based on Power Spectral Density and Convolutional Neural Network

In the field of structural health monitoring, vibration-based damage identification remains a formidable challenge. Key to this challenge is the establishment of a reliable association between observed vibration characteristics and the actual state of structural damage (e.g. stiffness reduction). This association not only accurately indicates the presence of damage, but also the location and severity of the damage. To solve this complex pattern identification problem, a large number of approaches, including deep learning, have emerged in recent years. In this paper, we propose a new structural damage identification method that utilizes the vibration information of the structure and a convolutional neural network based on Alex NET improvement. The method consists of calculating the acceleration response power spectral density of damaged and undamaged structures under impact loading separately, and then making a difference between the two power spectral data, and subsequently introducing these power spectral difference data into the convolutional neural network for training. The use of power spectral density analysis as a preprocessing step converts the time-domain signals into frequency-domain signals, and this conversion allows the convolutional neural network to capture and learn from the specific frequency characteristics of the data, thus facilitating the learning process of the neural network model. In this paper, the effectiveness of the method is critically evaluated through numerical simulation and experimental validation, and 3% and 5% noise are added to the numerical study to test the robustness of the method. During the convolution neural network training process, the optimal training mean squared error (MSE) is [Formula: see text] in the case of no noise addition; the optimal training MSE is [Formula: see text] in the case of noise addition. Both the results of simulations and experiments confirm the high accuracy and good robustness of the method in localizing structural damage.

WITHDRAWAL – Administrative Duplicate Publication: From Source to Building Fragility: Post-event Assessment of the 2013 M7.1 Bohol Philippines Earthquake

We use ground motion simulations of the 2013 Bohol Philippines earthquake along with a new post-disaster exposure/damage database to constrain building fragility and vulnerability. The large number of damaged buildings (>70,000) and the wide spread of seismic intensities caused by this earthquake make it an ideal candidate for such a study. An extensive survey was conducted leading to a robust description of over 25,000 damaged and undamaged structures. Ground motion fields were simulated using ground motion prediction equations and stochastic modeling, and the estimated and observed values were compared. The finite source model used in the simulation was based on the analysis of aftershocks and SAR data. The ground motions were associated with the empirical database to derive fragility and vulnerability models. Results indicate that the pattern of damage is best captured in the stochastic simulation. Constraints were placed on seismic building fragility and vulnerability models, which can promote more effective implementation of construction regulations and practices.

A damage-oriented ground motion intensity for degrading super high-rise buildings

To explicitly identify the influence of different seismic damages on the correlation between ground motion intensity measure (IM) and demand measure (DM), with a specific concern of super high-rise buildings, a novel damage-integrated spectral acceleration-based combination-type IM is developed for degrading systems. With the integration of seismic damage measure, inelastic displacement spectrum, and design acceleration spectrum, the prototype of the IM is theoretically derived for single-degree-of-freedom systems with a Q-type hysteretic model. The high-mode effect is reflected by an optimal number of lower modes combined with corresponding modal damage. To estimate the optimal number of modes while maximizing the case-independency of DM predictions, the dynamic properties of concerned damaged and undamaged structures are estimated with the collaboration of the modified flexure-shear model (FSM-MS), and further utilized to establish the regression expression with a large number of near-field and far-field ground motions. The performance of the proposed IM is systematically demonstrated via a case study on two super high-rise buildings, along with other selected IMs.

Deep learning enhanced metamodel design based on reduced mode shapes for delamination identification in composite structures

Structures requiring robust maintenance and accessibility pose challenges for structural integrity monitoring. This monitoring, crucial in various engineering applications, enables corrective actions to ensure machinery and equipment safety. Laminated composite materials, prevalent in aeronautical structures, often exhibit imperceptible delaminations or cracks, demanding the use of artificial intelligence for damage characterization. This study employs a numerical-experimental methodology, integrating artificial neural networks, to identify delaminations. Delamination, a structural damage form, was intentionally induced in epoxy-fiberglass composite structures. Modal tests captured characteristics in damaged and undamaged structures, revealing artificial intelligence effectiveness in pinpointing damage location and size. Damage significantly altered beam mode shapes, generating complex modes. Induced delaminations led to a measurable 15% reduction in natural frequencies, and damping ratios increased by approximately 10% in damaged structures. Artificial neural networks achieved an impressive 92% accuracy in predicting delamination location and size. Quantitative analysis of mode shape alterations validated the proposed methodology’s efficacy. This study provides valuable quantitative insights into damage detection in laminated composite structures, highlighting AI's potential for enhanced structural health monitoring. The numerical–experimental approach, supported by quantitative results, emphasizes the importance of advanced techniques for precise and efficient damage characterization in critical engineering applications.

Unsupervised Vision‐Based Structural Anomaly Detection and Localization with Reverse Knowledge Distillation

Most of vision‐based methods for structural damage detection rely on supervised learning, requiring a substantial number of labeled images for model training, which is labor‐intensive and time‐consuming. To address these challenges, this study introduces a vision‐based structural anomaly detection and localization approach using unsupervised learning and reverse knowledge distillation. The proposed model incorporates a teacher model, a student model, and a trainable one‐class bottleneck embedding module. The asymmetrical architecture of the teacher and student models forms an encoder‐decoder structure for parameter transfer and feature extraction. The student network receives a specific embedding from the teacher network as input and target, facilitating the recovery of multiscale information from the teacher. Training images only contain the undamaged structures, and the teacher model, a pretrained model, instructs the student model to remember their undamaged features to detect and localize damages in unseen testing images. Through experiments, including a comparison among five candidate backbones for pretrained teacher models based on the residual network and testing across various structural damage types, the optimal model is identified, demonstrating good performance in both anomaly detection and localization. Furthermore, the model’s generalization performance is thoroughly validated, confirming its efficacy across diverse scenarios.

Investigation of Buckling Behavior of Cracked FG Cylindrical Panels Reinforced by Graphene Platelets

The buckling behavior of a functionally graded graphene-platelet-reinforced composite (FG-GPLRC) was traditionally investigated, mostly with respect to its undamaged structures. In this context, the current study investigated the buckling behavior of an FG-GPLRC cylindrical panel with an anti-symmetric central crack by introducing a 2-D extended natural element method (XNEM). The displacement was basically expressed with the first-order shear deformation theory (FSDT) and approximated using Laplace interpolation functions (for the non-singular displacement part) and crack-tip singular functions (for the singular displacement part) without grid refinement around the crack tips. The complex numerical manipulation on the curved shell surface was resolved by geometrically transforming the curved shell surface to a 2-D planar rectangular NEM grid. The painstaking numerical locking was suppressed by adopting the concept of a stabilized MITC3+ shell element. The validity of the developed numerical method was examined through a benchmark test, and the fundamental buckling loads of cracked FG-GPLRC cylindrical panels were investigated in depth by changing the major parameters. The numerical results also included a comparison with the FG-CNTRC. The numerical results indicated that the developed numerical method effectively predicts the buckling loads with reasonable accuracy, and that the fundamental buckling load of cracked FG-GPLRC cylindrical panels are remarkably influenced by the inclination angle and length of the crack as well as the other associated parameters.

Predictive probability of detection curves based on data from undamaged structures

This paper develops a model-assisted approach for determining predictive probability of detection curves. The approach is “model-assisted,” as the damage-sensitive features are evaluated in combination with a numerical model of the examined structure. It is “predictive” in the sense that probability of detection (POD) curves can be constructed based on measurement records from the undamaged structure, avoiding any destructive tests. The approach can be applied to a wide range of damage-sensitive features in structural health monitoring and non-destructive testing, provided the statistical distribution of the features can be approximated by a normal distribution. In particular, it is suitable for global vibration-based features, such as modal parameters, and evaluates changes in local structural components, for example, changes in material properties, cross-sectional values, prestressing forces, and support conditions. The approach explicitly considers the statistical uncertainties of the features due to measurement noise, unknown excitation, or other noise sources. Moreover, through confidence intervals, it considers model-based uncertainties due to uncertain structural parameters and a possible mismatch between the modeled and the real structure. Experimental studies based on a laboratory beam structure demonstrate that the approach can predict the POD before damage occurs. Ultimately, several ways to utilize predictive POD curves are discussed, for example, for the evaluation of the most suitable measurement equipment, for quality control, for feature selection, or sensor placement optimization.

Damage Identification in Reinforced Concrete Beams Using Wavelet Transform of Modal Excitation Responses

This study focuses on identifying damage in reinforced concrete (RC) beams using time-domain modal testing and wavelet analysis. A numerical model of an RC beam was used to generate various damage scenarios with different severities and locations. Acceleration time histories were recorded for both damaged and undamaged structures. Two damage indices, DI_MW and DI_SW, derived from the wavelet analysis, were employed to determine the location and severity of the damage. The results showed that different wavelet families and specific mother wavelets had varying effectiveness in detecting damage. The Daubechies wavelet family (db2, db6, and db9) detected damage at the center and sides of the RC beams due to good time and frequency localization. The Biorthogonal wavelet family (bior2.8 and bior3.1) provided improved time–frequency resolution. The Symlets wavelet family (sym2 and sym7) offered a balanced trade-off between time and frequency localization. The Shannon wavelet family (shan1-0.5 and shan1-0.1) exhibited good time localization, while the Frequency B-Spline wavelet family (fbsp2-1-0.1) excelled in frequency localization. Certain combinations of mother wavelets, such as shan1-0.5 with the DI_SW index, were highly effective in detecting damage. The DI_SW index outperformed DI_MW across different numerical models. Selecting appropriate wavelet analysis techniques, particularly utilizing shan1-0.5 in the DI_SW, proved effective for detecting damage in RC beams.

Feasibility of microencapsulated phytochemical as disinfectant for inhibition of Candida albicans proliferation on denture base produced by digital light processing.

A proper disinfection of denture is vital to prevent a fungal infection. A study on the feasibility of microencapsulated phytochemical as complementary disinfectant and its interaction with effervescent tablet immersion on denture base resin is lacking. The aim of this study was to examine the feasibility of phytochemical-filled microcapsules as disinfectant for the inhibition of Candida albicans (C. albicans) attachment on the denture base produced by digital light processing (DLP). 54 denture base specimens uniformly mixed with or without 5wt% phytochemical-filled microcapsules were prepared using DLP. Fungal cells were inoculated onto the surfaces of the specimens, which were divided into three different disinfection treatment groups (n = 9): 1) none, 2) sterile tap water immersion for 15 min, and 3) effervescent tablet immersion for 15 min. After each treatment, the biofilm on denture surface was stained with a crystal violet solution to measure the absorbance. The number of fungal colonies was counted as colony-forming units (CFU) per mL. Morphological changes were examined by microscopy. An aligned rank transform analysis of variance was performed to analyze the interaction of presence of microcapsule and disinfection condition, with statistical significance set at P < 0.05. Both for the absorbance and CFU, there was no significant interaction between the presence of microcapsules and disinfection conditions (P = 0.543 and P = 0.077, respectively). The presence of microcapsules was statistically significant (both P < 0.001), while the effect of disinfection condition was not significant (P = 0.165 and P = 0.189, respectively). Morphological changes in fungi were detected in the groups containing microcapsules, whereas undamaged hyphal structures were found in those without microcapsules, irrespective of disinfection treatments. The presence of phytochemical-filled microcapsules significantly reduced the adhesion of C. albicans and inhibited its proliferation on denture surfaces, regardless of disinfection conditions.

Dynamic analysis of RC frame structure subjected to various damage severity in beams and columns

ABSTRACT The Reinforced Concrete (RC) systems are composed of different structural RC members such as beams, columns, shear walls, etc. Damage in RC members is found in the form of cracks, compression failure, reduction in effective area etc. Due to the presence of damages, there is a change in the dynamic behaviour. In the present work, the dynamic behaviour of undamaged and damaged RC multi-storey structures is studied with different damage locations in beams and columns at different stories. The damage is introduced by reducing Young’s modulus of concrete by 25%. The critical damage level is identified by using modal analysis. The damage severity in the columns and beams varied from 25% to 75%. The modal analysis and lateral load analysis are carried out to understand the dynamic behaviour of damaged structures. The Equivalent Static Method (ESM) is considered for earthquake analysis as per IS 1893 (Part −1): 2016. Analysis is done by using ETABS software. The natural frequency and time periods are considered as dynamic parameters. From the results, it has been observed that, there is a change in the natural frequency of the structural system with the introduction of damage of certain severity and at a particular location.

The influence of the type of fabric on the static and dynamic behavior of composite tubes with ply drop-off

A comparative study of the static and dynamic behavior of a new type of tubular structure with drop-offs used in lower limb prostheses is presented in this paper. Composite structures that present mass reduction, low cost, and excellent performance are a great challenge for many researchers. In order to overcome these difficulties, numerical and experimental methods are performed, generating results regarding natural frequencies, damping loss factors, and maximum compression load for five different setups for tubes with drop-offs. For the manufacture of the structures, three types of fabrics are considered: carbon, glass, and a carbon/aramid hybrid fabric. Beyond the three types of tubes, two more setups are created considering hybridization, with the inner ply manufactured with glass fabric, the outer ply of the first setup manufactured with carbon fabric, and the outer ply of the second setup manufactured with carbon/aramid hybrid fabric. The structural hybridization and insertion of drop-offs provide a reduction in the cost of material. Firstly, an optimization strategy using the Lichtenberg algorithm is executed, aiming at the basic material properties in relation to elasticity modulus, strain modulus, Poisson ratio, and density. Then, it is possible to perform numerical modal analysis using the Finite Element Method in Ansys® software with the aim of obtaining the first natural frequencies for each setup. Modal experimental tests before and after failure obtained in the compression test are performed to measure the first natural frequency and damping loss factor for each setup, providing a comparison between the dynamic behavior of the undamaged and damaged structures, and, posteriorly, the numerical and experimental modal results before failure are compared. The compression test is performed to measure the maximum compression load supported by each structure. The results revealed that the hybrid structure with drop-offs is an appropriate option that offers the best cost-benefit for pylon tubes.

FEATURES OF CONSTRUCTIVE, ORGANIZATIONAL AND TECHNOLOGICAL SOLUTIONS FOR THE RESTORATION OF REINFORCED CONCRETE BRIDGE STRUCTURES

The article provides information on effective structural and organizational-technological solutions for surveying, designing and restoring the bridge structure, which was partially destroyed as a result of the armed aggression of the Russian Federation. It was established that information from scientific and regulatory sources does not sufficiently reflect the situation with bridges, where a part of the load-bearing structures has been completely lost and it is necessary to carry out work on the construction of new structures with the possible use of a part of the old (undamaged) ones. The current operating condition of the main elements of the structure (bridge web, span structure, supports and support parts, foundations, approaches) is determined. When predicting the term of accident-free operation, it was established that the remaining resource of the bridge, taking into account the actual technical condition of the main elements at the time of the inspection (destruction), which is determined from the equation of element degradation, is completely exhausted. The obtained data made it possible to predict the technical condition of the bridge in accordance with regulatory requirements and to prescribe operational and restoration measures. The use of undamaged underground structures for the construction of new reinforced concrete supports is substantiated, where preparatory work is provided with the use of complex mechanization tools. When concreting the bodies of the supports, the rationality of the new fastening of the braces of the formwork blocks was confirmed, which ensured increased rigidity and stability of the assembled formwork, for which it was proposed to install one plate between the supports on a rigid metal frame structure with a height of corresponds to the lower limit of the concreting massif, with the possibility of attaching braces working in different planes to it. It is proposed not to change the position of the two slabs intended for braces along the axis of the bridge, while they were also placed on similar metal frames. Placing the plates for fastening the braces at the mentioned height made it possible to reduce the length of the braces and ensure their working angles within the most effective limits.

A procedure to estimate the Minimum Observable Damage in truss structures using vibration-based Structural Health Monitoring systems

In this work, we propose a procedure to estimate the Minimum Observable Damage (MOD) by a vibration-based Structural Health Monitoring (SHM) system. The MOD is defined as the smallest damage size that can be detected by an SHM system with given Probability of Detection (POD) and Probability of False Alarm (PFA). To this purpose, the MOD is computed by exploiting the Receiver Operating Characteristic (ROC) analysis, once a damage index (DI) built on monitoring data/features is defined. In particular, the MOD is defined as the damage intensity corresponding to an area under the ROC curve of 95%. The proposed idea is discussed by utilizing pseudo-experimental data generated via numerical simulations for undamaged and damaged structures. In the developed simulations, environmental uncertainties and measurement noises are considered. As case studies, we consider truss structures and use modal data, namely frequencies of vibrations and mode shapes, to build the DIs. Using the dataset of DIs, the ROC methodology is exploited to establish the probability of detecting certain damage over the probability of false alarms. For a given DI, results are provided in terms of MOD for each structural element of the truss structure considering one damaged element at a time. By establishing a relation between modal data, damage size, and POD/PFA, the proposed approach can assess the quality of the adopted DI, thus supporting the initial design of an SHM system.

Engineering structures stability against progressive collapse

The calculating stability of an engineering structure against progressive collapse is considered in this article. The calculations results are analyzed. A dangerous emergency scenario was developed and measures were developed to prevent the progressive building collapse in the structures local destruction in accordance with the regulatory documents requirements for such an object. The most dangerous design schemes are considered to assess the structure stability against progressive collapse. A scenario for calculating stability against progressive collapse in the case of local failure has been selected, and a consistent action algorithm has been obtained that makes it possible to perform a calculation for resistance to progressive collapse., The kinematic method of the limit equilibrium theory for structures with elastic-plastic materials properties is used to calculate the resistance to progressive collapse. It corresponds to the turning the system into a plastic kinematic chain, the links movement is carried out due to the plastic flow of the system's links. Two types of undamaged structures were identified to assess the building resistance to progressive collapse: neighbouring beams and columns, in which local destruction impact does not cause a qualitative change in the stress state, but leads to an increase in stresses and forces (neighboring beams, columns); pavement slabs resting on a beam and welded through embedded parts to a beam that has lost its original support, and located above a local fracture, the stress state changes. The conclusion is made about the requirements that should be met in order to conclude the calculation justification so it can be said that resistance to progressive collapse is ensured. It has been established that the calculations performed confirm the object stability - the drainage chamber to progressive collapse in the local destruction as an emergency situations result.

Unsupervised statistical estimation of offshore wind turbine vibration for structural damage detection under varying environmental conditions

Assessing the structural health condition of offshore wind turbines (OWTs) is necessary to ensure their later stages of service. A widely adopted strategy is to identify the damage by a significant deviation between the serviced structural responses and data obtained from undamaged structures. However, dynamic responses of OWTs show high dependency on ambient environments. To evaluate the variabilities of structural responses, in this paper an unsupervised statistical estimation method is proposed based on the integration of data bin processing and interval correlation techniques to eliminate the effects of environmental and operational conditions on evaluation results of a sensor, called a single indicator. Moreover, the improved network analysis model using information entropy has been established to consider the interactions of the multiple indicators for the valuation of the predicted results. As compared with the traditional methods, the proposed method combination between environmental variables clustering analysis and interval correlation could has demonstrated better robustness and higher computational efficiency using the developed probabilistic model. To validate the correctness and robustness of the proposed method, numerical simulations of a 5 MW monopile OWT by OpenFAST have been carried out. Based on the stiffness loss between 4% and 16% in natural frequencies and ten different wind speeds in the range of 5 to 23 m/s, four scenarios have been investigated to evaluate the sensitivity of damage detection. Results have shown that the proposed method has the ability to effectively and robustly assess the structural damage condition under different wind speed conditions. Furthermore, field test data from a 4 MW monopile OWT has been utilized to demonstrate the feasibility of the established statistical estimation method. It has been noted that the false alarm number of multiple indicators has been reduced to 0 from 3 in the case where there is no consideration of environmental condition classification and this evaluation result has well agreed with the data obtained under the actual working state of the OWT.

Locating damages of space trusses by combining cross-model modal strain energy and wavelet transform

To effectively locate damages of a space truss which usually has hundreds of elements, a new damage index is proposed by combining the cross-model modal strain energy (CMSE) and the wavelet transform (WT). Firstly, the novel CMSE are introduced to construct the damage index CMSEI. It is noted that the traditional modal strain energy (MSE) is calculated based only on mode shapes of the same model, i.e., the undamaged structure or the damaged structure. In contrast, the CMSE is computed by simultaneously utilizing mode shapes from two different models, i.e., both undamaged and damaged structures. Secondly, the WT is further conducted on the space-domain sequence composed of elemental values of the CMSEI, with high-frequency detail coefficients extracted to form the new damage index WT_CMSEI. Finally, damages are located for the elements with outstanding values of the WT_CMSEI. A space truss with as many as 504 elements is numerically analyzed. Results show that the proposed WT_CMSEI can better indicate damage locations than widely used indexes based on traditional MSE. It presents high robustness to resist the influences of noise, and can effectively decrease the disturbances from other undamaged elements. This study provides a potential application of the WT_CMSEI in damage localization for large-scale space trusses which have many elements.