Nondestructive Damage Detection Method Research Articles

Life Cycle Assessment of a Coastal Concrete Bridge Aided by Non-Destructive Damage Detection Methods

Recently, using economic damage identification techniques to ensure the safety of bridges has become essential. But investigating the performance of those techniques for various conditions and environments and, in addition, a life cycle assessment (LCA) through these methods depending on the situation and during the life of a structure could help specialists and engineers in this field. In these regards, analyzing the implementation of a technique for the restoration and maintenance stages of costly structures such as bridges can illustrate the effect of each damage detection method on the LCA. This research assessed non-destructive abilities and a dynamic approach to predict the amount and location of damages in the LCA. For this purpose, the power spectral density (PSD) technique’s performance by different approaches in identifying corrosion damages for a coastal bridge and the effectiveness of using this technique on reducing the environmental impact compared with a conventional method were evaluated. The results demonstrate a reduction of the environmental impacts by approximately 23% when using the PSD during the bridge’s service life. In conclusion, the PSD approach does well in anticipating the damage quantity and location on a coastal bridge, which reduces the environmental impacts during the repair and maintenance.

PERFORMANCE COMPARISON OF STRUCTURAL DAMAGE DETECTION METHODS BASED ON FREQUENCY RESPONSE FUNCTION AND POWER SPECTRAL DENSITY

Recent catastrophic events have aroused great interest in the scientific community regarding the evaluation and prediction of the structural response along the life cycle of infrastructures. Efforts are put into developing adequate health monitoring systems to help prevent future human life and economic losses. Here, two non-destructive damage detection methods are presented: the Frequency Response Function-based and the Spectral Density Function-based methods. The damage detection performance of both methods is compared through a particular case study, where different damage scenarios are analyzed in a 2D truss bridge. The reliability of each method is studied in terms of different prediction errors. Numerical results show that the PSD method for damage detection on a steel truss bridge structure provides more accurate and robust results when compared to that based on FRF. Keywords: Structural Health Monitoring, Power Spectral Density Function, Frequency Response Function, Construction, Structures, Damage detection, Non-destructive

Application of artificial neural networks for quantitative damage detection in unidirectional composite structures based on Lamb waves

This article provides a quantitative nondestructive damage detection method through a Lamb wave technique assisted by an artificial neural network model for fiber-reinforced composite structures. For simulating damages with a variety of sizes, rectangular Teflon tapes with different lengths and widths are applied on a unidirectional carbon fiber–reinforced polymer composite plate. Two characteristic parameters, amplitude damage index and phase damage index, are defined to evaluate effects by the shape of the rectangular damage in the carbon fiber–reinforced polymer composite plate. The relationships between the amplitude damage index and phase damage index parameters and the damage sizes in the carbon fiber–reinforced polymer composite plate are quantitatively addressed using a three-layer artificial neural network model. It can be seen that a reasonable agreement is achieved between the pre-assigned damage lengths and widths and the corresponding predictions provided by the artificial neural network model. This shows the great potential of using the proposed artificial neural network model for quantitatively detecting the damage size in fiber-reinforced composite structures.

A Review of Non-Destructive Damage Detection Methods for Steel Wire Ropes

As an important load-bearing component, steel wire ropes (WRs) are widely used in complex systems such as mine hoists, cranes, ropeways, elevators, oil rigs, and cable-stayed bridges. Non-destructive damage detection for WRs is an important way to assess damage states to guarantee WR’s reliability and safety. With intelligent sensors, signal processing, and pattern recognition technology developing rapidly, this field has made great progress. However, there is a lack of a systematic review on technologies or methods introduced and employed, as well as research summaries and prospects in recent years. In order to bridge this gap, and to promote the development of non-destructive detection technology for WRs, we present an overview of non-destructive damage detection research of WRs and discuss the core issues on this topic in this paper. First, the WRs’ damage type is introduced, and its causes are explained. Then, we summarize several main non-destructive detection methods for WRs, including electromagnetic detection method, optical detection method, ultrasonic guided wave detection method, and acoustic emission detection method. Finally, a prospect is put forward. Based on the review of papers, we provide insight about the future of the non-destructive damage detection methods for steel WRs to a certain extent.

A generalized flexibility matrix-based model updating method for damage detection of plane truss and frame structures

Nowadays, many non-destructive damage detection methods for determining the location and severity of damage in the field of health monitoring are considered in order to reduce the cost of maintenance and improve safety and reliability of structure. In this paper, damage specification is obtained by sensitivity-based updating approach. By applying changes on sensitivity matrix and using measured flexibility data, it is concluded that the results of proposed method are more accurate and efficient than the old modal flexibility methods. The mass modeling error and measurement error of flexibility and natural frequency are calculated in order to ensure the accuracy and robustness of proposed method for 2-D finite element truss and frame model. Close index, measuring the performance of the method, and the coefficient of variation, which represents the distribution of response, are used. Compared with Wang method, the proposed method is capable of accurately localizing and quantifying damage in all scenarios.

Damage Detection of Shear Connectors in Composite Bridges

Headed shear studs are commonly used to resist longitudinal shear forces in composite railway bridges. Due to the growth of traffic and increase in train speed, these studs are subjected to high-cycle fatigue loading which may lead to damage, thus affecting the integrity between the steel girder and the concrete slab. Therefore, it is necessary to find a corresponding nondestructive damage detection method. Within the frame of this paper, the occurrence of damage in shear studs is studied by numerical analysis. In the numerical model of a real composite bridge, headed shear studs are represented by spring elements. A damage indicator based on the local modal curvature and the wavelet transform modulus maxima is proposed for stud damage identification. The efficiency of the damage indicator is investigated by means of numerical simulations where different levels of damage are introduced to the stud by decreasing the spring stiffness. It is verified that the proposed damage index can be used to locate and to quantify the damage.

Monitoring structural damage of components using an effective modulus approach

This paper describes a novel nondestructive damage detection method that was developed to study the influence of a crack on the dynamic properties of a cantilever beam subjected to bending. Experimental measurements of transfer functions for the cracked cantilever beam revealed a change in the natural frequency with increasing crack length. A finite element model of a cracked element was created to compute the influence of severity and location of damage on the structural stiffness. The proposed model is based on the response of the cracked beam element under a static load. The change in beam deflection as a result of the crack is used to calculate the reduction in the global component stiffness. The reduction of the beam stiffness is then used to determine its dynamic response employing a modal analysis computational model. Euler–Bernoulli and Timoshenko beam theories are used to quantify the elastic stiffness matrix of a finite element. The transfer functions from both theories compare well with the experimental results. The experimental and computational natural frequencies decreased with increasing crack length. Furthermore the Euler–Bernoulli and Timoshenko beam theories resulted in approximately the same decrease in the natural frequency with increasing crack length as experimentally measured.

Time Domain Reflectometry for Void Detection in Grouted Posttensioned Bridges

The presence of voids is a serious problem in grouted posttensioned bridges because voids greatly reduce the corrosion-protective capabilities of the grout. Current methods for void detection suffer several significant drawbacks. A new method utilizing time domain reflectometry (TDR) is discussed. TDR is a well-developed method for detecting discontinuities in electrical transmission lines. A recent study has indicated that TDR can be used as an effective nondestructive damage detection method for concrete bridges. A void changes the electrical properties of transmission lines and therefore introduces electrical discontinuities. It can be detected and analyzed by TDR. Experiments on short specimens that are used to model grouted posttensioning ducts with built-in voids have been conducted and demonstrate the potential of TDR as a void detection method.