Experimental Damage Detection Research Articles

Structural adaptive damage detection under uncertainty based on probability dissimilarity and moving average control chart

For engineering applications of guided-wave-based online structural damage detection, dealing with uncertainty caused by time-varying conditions (TVCs) is an issue of fundamental importance. In this study, a structural adaptive damage detection method based on probability dissimilarity and moving average control chart (MACC) is proposed. To suppress the uncertain effects of TVCs on signals, the probability dissimilarity-based damage index (PDDI) is extracted based on the proposed adaptive probability modeling of signal feature and probability distribution dissimilarity measure. Then, the automatic damage alarm mechanism based on MACC is proposed to determine alarm threshold adaptively and restrain the uncertain influence further by the moving average of PDDI. The proposed method is verified by the damage detection experiments on typical aircraft lug specimens under varying load and temperature, and then the method is applied to the full-scale aircraft fatigue test. The results demonstrate that the proposed method realizes reliable and adaptive structural damage detection under uncertain conditions.

Multisource-Domain Adaptation-Based Damage Detection Method for Air-Conditioning Condenser Using Laser Ultrasonic Guided Wave

Air conditioning condenser (ACC) is a key component of air-conditioning equipment. ACC tube leakage damage will cause huge economic losses and energy waste. The laser ultrasonic guided wave detection method is suitable for ACC damage detection due to its high sensitivity and non-contact advantages. However, the ACC tube size is small and the weld joint is not standardized, which makes it difficult for the laser to aim at the tube. And the detection signals generated by laser excitation at different laser incident angles are different. In this paper, the Unsupervised Multi-source Adaptation Adversarial Network (UMAAN) is proposed to improve the generalization ability of the ACC detection model. Firstly, the feature diagrams of the signal are obtained by time-frequency analysis, and the diagrams are set to different source and target domains according to the different incident angles of laser excitation. Then, the shared feature extractor is used to obtain features of all samples. And the model parameters are optimized by adversarial network to make the features distance of the target and source domains closer. Among them, the adaptive weight coefficients are designed to adjust the loss value weights of the different source domains. And the label error weight factor is designed to improve the damaged signals detection accuracy by adjusting the loss weight of damaged samples and normal samples. Finally, the damage detection experiments of the ACC are carried out. The experimental results illustrate that the proposed UMAAN can achieve high-precision detection of ACC damages.

Damage detection in plate structures based on baseline construction of ultrasonic Lamb wave using designed mobile transducer set

The ultrasonic Lamb wave-based damage detection method is widely used in plate structures. Due to the multimode characteristic, the collected Lamb wave signals are very complicated, making it difficult to obtain damage information. This paper proposes a damage imaging algorithm based on the baseline construction of the Lamb wave for plate structures. A mobile transducer set including two transducers is designed for Lamb wave excitation and signal collection. To extract damage scattering signals, the response of the signal in healthy areas (the structural response signal) is measured as a temporarily constructed baseline signal. The structural response signal is obtained based on the identified healthy signals collected in different areas of the same structure. Damage scattering signals are extracted as the differences between the current signals and the structural response signal. Damage indexes are calculated based on the damage scattering signals to locate the damage with the imaging algorithm. A damage detection experiment is conducted on an aluminum plate to verify this proposed method. The imaging result is in good agreement with the damage location in the experiment. This paper provides a potential alternative for damage detection of plate structures in practice.

Numerical and experimental structural damage detection in an offshore flare bridge using a proposed modal strain energy method

Providing a connection tool between different structures in an offshore complex, flare bridges are one of the most important offshore structures. Early damage identification in these structures is of great importance, as it may prevent casualties as well as financial and environmental losses. Modal strain energy is one of the most promising structural health monitoring methods which is based on changes in the dynamic properties of the structure. So far, different modifications have been performed on the original MSE damage index named Stubbs index. In this paper, reviewing these modifications and making some changes on one of the latest proposed indices, a new relation is used for damage identification. The accuracy of this relation is examined by identifying damages in the flare bridge of the Foroozan offshore complex, located in the Persian Gulf which is comprised of a large number of elements. Along with this numerical study, an experimental modal analysis is performed on the structure. Results showed the superiority of damage identification of the proposed method of single and multiple damage localization.

Surface damage detection of steel plate with different depths based on Lamb wave

A new experimental procedure for damage detection based on active acoustic emission was developed which is sensitive to damage depth. Two new damage indexes were proposed by analyzing the amplitudes of low-frequency signal direct wave and high-frequency signal maximum component. The relations between damage depths of a steel plate and damage indexes were studied through numerical simulation considering different signal-to-noise ratios (SNR). It was found that the values of the damage indexes increased with the depth of damage, and the stability of the indexes was further analyzed by the coefficient of variation (Cov). Damage detection experiments for steel plates with different damage depths were carried out, and the results showed good agreement with the numerical simulation which further verifies the feasibility of the proposed method. The present method can provide basis for the engineering application of damage detection with different depths.

Concrete Surface Damage Volume Measurement Based on Three-Dimensional Reconstruction by Smartphones

Surface damage of structures is an important indicator that further inspection of the structure is needed. However, existing detection methods rarely detect three-dimensional data of damage. Aiming at the inspection of structural surface damage, this study proposes a method based on 3-D structural surface damage reconstruction techniques for reconstructing and extracting data for damage volume calculation. The surface damage of concrete specimen is three-dimensionally reconstructed using multi-view smartphone-taken images and compared with a depth camera. The point cloud data was obtained, and then the damage plane was fitted and removed by a Random Sample Consensus algorithm to obtain the damage site data, finally, the damage volume was calculated. In the experimental process, accuracy and post-processing difficulty, equipment cost, data acquisition efficiency, and overall applicability of the two methods were compared and analyzed. In conclusion, it was determined that the 3-D damage parameters obtained through the smartphone multi-view stereo reconstruction performs better, at a lower cost and is more convenient for use in inspection work. Finally, the practicability of the method was proved by the damage detection experiment of real building.

Passive Tap‐scan damage detection method for beam structures

Efficient damage detection technologies are highly demanded in the maintenance of bridge structures. For this purpose, the authors have developed the active Tap-scan damage detection method, which can extract bridge damage from the acceleration of a passing vehicle mounted with a shaker. Although this method can be efficiently implemented in a noisy environment with normal traffic, the damage detection accuracy could be deteriorated by the fluctuation of vehicle velocity, and the portability of the vehicle is impeded by the cumbersome shaker system. To solve these problems, this paper proposes a passive Tap-scan damage detection method, which uses an automatic driving vehicle with specially designed tire treads to scan the bridge. Instead of using the shaker, the tapping force is passively generated by coordinating the vehicle velocity with the periodic pattern of the tire tread. The theoretical basis of this method is firstly established on the analysis of the interaction between a simply supported beam and a passing vehicle with tapping contact forces, as well as the analytical solution of the deflection of a damaged beam subjected to a unit point force. Then, in-house experimental damage detection results of a simply supported aluminium box beam are reported to demonstrate the effectiveness of the proposed method.

Experimental Study on Foci Development in Mortar Using Seawater and Sand.

Mortar using seawater and sand was the material studied here. The mortar specimens, in particular, were cured in natural seawater. The foci development in the mortar was the principal interest in this study. The on-line damage detection experiment art, including dynamically global MSHCT (Multi-Slices Helical Computer Tomography) scan and the local detection of EDS (Energy Dispersive Spectrometer), SEM (Scanning Electron Microscopy), and XRD (X-ray Diffraction) was designed to research the foci development in the mortar specimen. The mortar specimens with 70-day age were produced and investigated by the on-line damage detection experiments. The experiment results indicated that the mortar using seawater and sand offered appreciable strength at the early age, at least, although some saline minerals were generated during the preparation. The residual strength of the mortar was above 13 MPa, which helped to prevent the sharp damage of engineering bodies. The micro-interfacial behavior and the parental foci development controlled the damage evolution in the mortar using seawater and sand, the performance of which was still the adjustable one by composition optimization.

Photogrammetry-based structural damage detection by tracking a visible laser line

Research works on photogrammetry have received tremendous attention in the past few decades. One advantage of photogrammetry is that it can measure displacement and deformation of a structure in a fully non-contact, full-field manner. As a non-destructive evaluation method, photogrammetry can be used to detect structural damage by identifying local anomalies in measured deformation of a structure. Numerous methods have been proposed to measure deformations by tracking exterior features of structures, assuming that the features can be consistently identified and tracked on sequences of digital images captured by cameras. Such feature-tracking methods can fail if the features do not exist on captured images. One feasible solution to the potential failure is to artificially add exterior features to structures. However, painting and mounting such features can introduce unwanted permanent surficial modifications, mass loads, and stiffness changes to structures. In this article, a photogrammetry-based structural damage detection method is developed, where a visible laser line is projected to a surface of a structure, serving as an exterior feature to be tracked; the projected laser line is massless and its existence is temporary. A laser-line-tracking technique is proposed to track the projected laser line on captured digital images. Modal parameters of a target line corresponding to the projected laser line can be estimated by conducting experimental modal analysis. By identifying anomalies in curvature mode shapes of the target line and mapping the anomalies to the projected laser line, structural damage can be detected with identified positions and sizes. An experimental investigation of the damage detection method was conducted on a damaged beam. Modal parameters of a target line corresponding to a projected laser line were estimated, which compared well with those from a finite element model of the damaged beam. Experimental damage detection results were validated by numerical ones from the finite element model.

Damage Detection in a Steel Beam Based on an Impact-Acoustics Approach

Vibration and acoustics travel through a structure under the action of an impact force at a position on that structure. The acoustic detection system comprises either an accelerometer or a microphone to capture the acoustic signatures of the vibrations. Both signatures can be simultaneously collected by an impact hammer test and are analysed by this non-destructive test to obtain more reliable results than those of a single signature. This work investigates the damage identification of the beam structure based on the experimental data collected from the impact hammer test using an accelerometer and a microphone. The damage detection experiment on a steel beam illustrates the reliability of the defect detection using the simultaneous measurements by two sensors.

Damage imaging in composites using nonlinear vibro-acoustic wave modulations

The paper deals with the application of nonlinear vibro-acoustic modulation technique for detection and localization of impact damage in a laminated composite plate. An imaging procedure—based on the nonlinear vibro-acoustic modulation sidebands—is proposed. The procedure relies on simultaneous low-frequency modal and high-frequency ultrasonic excitations. Laser scanning vibrometry is used to analyze the amplitude of modulation sidebands in vibro-acoustic responses. This analysis is performed for different positions on monitored structure to reveal the location and shape of damage. The method is illustrated using a simple example of impact damage detection in a composite plate. The experimental damage detection results are compared with the results obtained from the previously used approach on the basis of higher harmonic generation. The proposed method demonstrates better ability to locate damage in these comparative tests without the need to increase the measurement bandwidth to the higher harmonics regime. The work shows that the local defect resonance analysis can improve damage detection results of both compared approaches.

Model- and Non-model-based Damage Detection Methods Using Vibration Data

Modal parameters of a structure, including natural frequencies, modal damping ratios and mode shapes, are directly related to its material properties, such as mass, damping and stiffness. Changes in material properties of astructure due to occurrence of damage can result in those in its modal properties. In this work, model- and non-modelbased structural damage detection methods by use of modal parameters are introduced. The model-based method uses changes in natural frequencies of a structure; it requires an accurate physics-based model of the structure and a minimum amount of vibration measurement. The nonmodel-based methods use measured mode shapes and curvature mode shapes, and they do not require use of structural models. Experimental damage detection on a space frame, a beam and a plate are carried out to validate the model- and non-model-based methods.

Damage Assessment in Bridges Based on Measured Natural Frequencies

This paper presents an identification technique for damage assessment of structures where only the information about the changes of measured natural frequencies can be directly utilized. The structural damage is characterized by a local decrease in the stiffness as represented by a scalar reduction of the material modulus. The objective of this study is to investigate the feasibility of using such a technique for identifying the structural damage in a real steel girder bridge. Numerical examples involving damaged reinforced concrete beams are first used to demonstrate the capability of the proposed computational technique, based on the nonlinear perturbation theory, to predict the exact location and severity of the damage. To experimentally validate the theory, laboratory damage detection experiments were performed on a simply supported reinforced concrete beam with various damage scenarios as the example. The results of the damage identification procedure based on the measurement of structure’s frequencies before and after occurrence of the damage show that this method can accurately locate the damage and predict the extent of damage. The method performs well even for a structure with a very serious damage as demonstrated by application of the proposed direct iteration technique to a six-span steel girder bridge. Using a limited number of measured natural frequencies, significant reduction in the stiffness of the bridge at multi-sites is detected.

Vibration-based experimental damage detection of a small-scale wind turbine blade

Structural health monitoring offers an attractive tool for condition assessment, fault prognosis and life-cycle management of wind turbine components. However, owing to the intense loading conditions, geometrical nonlinearities, complex material properties and the lack of real-time information on induced structural response, damage detection and characterization of structural components comprise a challenging task. This study is focused on the problem of damage detection for a small-scale wind turbine (Sonkyo Energy Windspot 3.5 kW) experimental blade. To this end, the blade is dynamically tested in both its nominal (healthy) condition and for artificially induced damage of varying types and intensities. The response is monitored via a set of accelerometers; the acquired signals serve for damage detection via the use of appropriate statistical and modal damage detection methods. The former rely on extraction of a characteristic statistical quantity and establishment of an associated statistical hypothesis test, while the latter rely on tracking of damage-sensitive variations of modal properties. The results indicate that statistical-based methods outperform modal-based ones, succeeding in the detection of induced damage, even at low levels.

A synthesis of peak picking method and wavelet packet transform for structural modal identification

Damage identification problem involves detection, localization and assessment of the extent of damage in a structure so that the remaining life could be predicted. Visual or nondestructive experimental damage detection methods such as ultrasonic and acoustic emission ones are based on a local evaluation in easily accessible areas, and therefore, they require a certain prior knowledge of the damage distribution. With the purpose of providing global damage detection methods applicable to complex structures, techniques based on modal testing and signal processing constitute a promising approach for damage identification. These methods examine changes in the dynamic characteristics of structure, such as natural frequencies and mode shapes to detect the structural damage. Modal parameters including natural frequencies, mode shapes and damping ratios are known as essential parameters for analyzing the dynamic behavior of a structure. This paper deals with identification of modal parameters of structures using a two-step algorithm. In the proposed method, free vibration response of structure is decomposed using wavelet packet transform. Then, decomposed signal, which has the same energy with the main signal, is used for modal parameter identification using peak picking method. The performance of the proposed method is verified against the results of an experimental benchmark problem.

Experimental damage detection in a wind turbine blade model using principal components of response correlation functions

The utilization of vibration signals for structural damage detection (SDD) is appealing due to the strong theoretical foundation of such approaches, ease of data acquisition and processing efficiency. Different methods are available for defining damage sensitive features (DSFs) based on vibrations, such as modal analysis or time series methods. The present paper proposes the use of partial autocorrelation coefficients of acceleration responses as DSFs. Principal component (PC) analysis is used to transform the initial DSFs to scores. The resulting scores from the healthy and damaged states are used to select the PCs which are most sensitive to damage. These are then used for making decisions about the structural state by means of statistical hypothesis testing conducted on the scores. The approach is applied to experiments with a laboratory scale wind turbine blade (WTB) made of glass-fibre reinforced epoxy composite. Damage is non-destructively simulated by attaching small masses and the WTB is excited with the help of an electrodynamic shaker using band-limited white noise. The SDD results for the selected subsets of PCs show a clear improvement of the detectability of early damages compared to other DSF selections.

High-frequency lowest torsional wave mode ultrasonic inspection using a necked pipe waveguide unit

We propose an effective method to transmit only the non-dispersive lowest torsional wave mode at a high frequency range even above the cutoff frequency of the third torsional mode. Unlike existing methods that tune the wavelength or phase of the target wave mode, the proposed method is based on the thickness change and the cutoff phenomenon. A specially configured necked waveguide, consisting of three regions of which the middle region is thinner than the so-called cutoff thickness, is put in end-to-end contact with a test pipe to transmit only the first torsional wave mode to a test pipe. After explaining the underlying role of the proposed necked waveguide, we propose a technique to mainly transmit the lowest torsional wave mode at a frequency where higher modes can also propagate. Numerical simulations and damage detection experiments were carried out to show the effectiveness of the proposed method.

The development of a multi-channel GPR system for roadbed damage detection

This paper describes the development of a novel six-channel ground penetrating radar (GPR) for roadbed damage inspections, which can be operated in the customized cart-loading units and driven by vehicles at regular speed(60km/h). In comparison with an existing GPR system, this novel GPR system is improved with the following design features: six channels operation which effectively improves the survey efficiency; positioning capability by implementing joint positioning and video system; FPGA control module coordinates the multi-channel microwave circuit synchronization; customized designed cart-loading units which can be operated in series mode or parallel mode, guarantees the operating capability at regular driving speed. Moreover, the pavement damage detection experiments are conducted for design validations, and the measurement results show the high inspection performance of the novel GPR system

Detecting Loosening of Bolted Connections in a Pipeline Using Changes in Natural Frequencies

Loosening of bolted connections in a structure can significantly reduce its load-bearing capacity. Detecting loosening of bolted connections at an early stage can prevent failure of the structure. Due to the complex geometry of a bolted connection and material discontinuity between clamped components, it is difficult to detect loosening of a bolted connection using conventional nondestructive test methods. A vibration-based method that uses changes in natural frequencies of a structure to detect locations and extent of damage can be used to detect loosening of bolted connections since the method focuses on detecting a stiffness reduction, which can result from loosening of bolted connections. Experimental and numerical damage detection was conducted to detect loosening of bolted connections in a full-size steel pipeline with bolted flanges using the vibration-based method. With the recent development of a modeling technique for bolted connections in thin-walled structures, an accurate physics-based finite element model of the pipeline that is required by the vibration-based damage detection method is developed. A trust-region search strategy is employed to improve the damage detection method so that global convergence of the damage detection algorithm can be ensured for underdetermined systems, and robustness of the algorithm can be enhanced when relatively large modeling error and measurement noise are present. The location and extent of loosened bolted connections were successfully detected in experimental damage detection using changes in natural frequencies of the first several elastic modes of the pipeline; the exact location and extent of the loosened bolted connections can be detected in numerical simulation where there are no modeling error and measurement noise.

FRF-based damage localization method with noise suppression approach

Abstract In this paper a noise-robust damage identification method is presented for localization of structural damage in presence of heavy noise influences. The method works based on Frequency Response Functions (FRFs) of the damaged structure without any prior knowledge of the healthy state. The main innovation of this study starts with convolving FRFs with Gaussian kernel to suppress the noise. Denoised signals are then used to develop shape signals according to the second derivative of the operational mode shapes at frequencies in the half-power bandwidth of the center resonant frequencies. The scheme is followed by normalization of shape signals to create a two-dimensional map indicating the damage pattern. The validation of the method was carried out based on simulated data and experimental measurements. The simulated data polluted with 10 percent random noise considering four different conditions: (i) un-correlated noise with Gaussian distribution (ii) noise with non-Gaussian exponential distribution (iii) noise with non-Gaussian Log-normal distribution and (iv) correlated colored noise. The robustness of the method was examined with respect to the damage severity with various damage conditions. Finally, damage detection experiments of a fixed–fixed steel beam are presented to illustrate the feasibility and effectiveness of the proposed method. According to the numerical and experimental investigations, it was demonstrated that the proposed approach presents satisfactory damage indices both in single and multiple damage states in presence of high level noise. Hence, the method can overcome the problems of output measurement noise and deliver encouraging results on damage localization.