This paper presents an improved damage detection technique for composite structures using a steady state excitation based on the use of a laser doppler vibrometer (LDV). Employing a single, fixed frequency excitation from a mounted piezoelectric transducer, the full steady-state wavefield could be obtained using a LDV with a mirror-tilting device. After scanning completed in high speed, a wavenumber filtering is applied to determine the dominant wavenumber components of the measured wavefield, which could be used for a damage sensitive feature. In this process, the directional correction of the wavenumber is performed to minimize the anisotropic characteristic in local wavenumber estimation. For validation of this proposed technique, several experiments were performed on composite structures with delamination damage. The results showed that the proposed technique is very efficient in detecting and quantifying delamination and debonding damage on composite structures.
Cracks on sheet metals can significantly affect the overall strength. Crack detection during manufacturing is, thus, an important process for the quality assessment on a press line. Deep learning, a data-driven structure, has been extensively used to detect cracks on various surfaces. In this study, a crack detection technique for a press line using Retina Net and a novel data augmentation method is proposed, which mainly focuses on three steps, shape acquisition, style transfer, and edge fusion. First, the shapes of crack on different materials are extracted. Then, images are created by providing metal crack textures to those shapes using a fusion network with a relatively small number of real crack images. Real crack images are captured from a sheet metal forming line. Training data can be enriched using the proposed data augmentation method. Validation experiments are conducted to demonstrate the effectiveness of the proposed crack detection and data augmentation techniques.
Single frequency standing wave based ultrasonic imaging techniques have the advantage of enabling efficient laser scanning through high signal to noise ratio(SNR) compared to guided wave based ultrasonic imaging techniques. This paper describes a full field steady-state ultrasonic imaging techniques using a dual point laser scanning system. Traditional ultrasonic imaging systems use a mirror tilting device and single point laser doppler vibrometer(LDV) to measured the responses. After obtaining the steady-state responses, several wavenumber based damage detection algorithms are applied to detect structural damage. In this work, we develop a system that utilizes a dual point laser scanner to simultaneously measure the dual points of a structural response to reduce the interrogation time and to make the system applicable to multiple structure. To validate the proposed technique, experiments are conducted on plates with different thickness and defect sizes. The result show that the proposed technique could detect and qualify the various type of damage on the multiple structures with the improved speed.
The computer vision-based measurements offer the superior capabilities over traditional sensing systems, including high spatial resolutions, no mass-loading effects, and low cost. This capability allows the vision-based technique to be widely applied to the damage detection practice as a more efficient way compared to conventional methods. The recently developed phase-based motion processing technique can measure the displacement signals with high accuracy and noise robustness. In this study, an automated damage identification and localization technique based on the phase-based motion processing is proposed. The local phase of the object is extracted using a optimal steerable filter. The modal parameters are then obtained after performing the morphological operation on the edge image in conjunction with the phase signals. Damage is finally localized and assessed by the features extracted by the identified modal parameters. Several experiments are carried out to validate the proposed technique on a 5-story structure under different bolt losing conditions. The experimental results show that the proposed technique can automatically detect and evaluate the damage with high accuracy.
The advanced displacement measurement technique using computer vision has shown several advantages, such as high spatial resolution and no mass loading effect, compared to conventional sensing techniques. However, the accuracy and robustness of vision-based techniques are subjected to the various conditions, including uneven illumination and insufficient lighting. This study introduces an accurate 2-dimension displacement measuring technique with high robustness to the illumination change, which uses two complex Gabor filters and a specially designed marker. The linear phase can be generated around the marker by optimizing the filter parameter for accurate motion estimation. The nonlinearity caused by the complex conditions, such as low light and uneven illumination, can also be reduced by emphasizing marker features. Phase-based optical flow is further employed to extract the displacement based on the extracted phase. The measurement performance is compared with Laser Doppler Velocimetry (LDV) to validate the proposed technique under various lighting conditions and its robustness is demonstrated. The proposed technique is also applied to different structures to show the ability of measuring high-accuracy displacement signals under various conditions.
This paper presents the improved thickness estimation technique using Steady-state excitation Continuous-scanning Laser Doppler Vibrometery(SCLDV).
In this study, the wavenumber sensitivity with respect to the thickness variations of a structure, along with the information of wave modes, is utilized to find an optimal interrogation frequency band for SCLDV. In addition, the use of multi-frequency steady-state response is used to improve the accuracy of the thickness variation. By utilizing the wavenumber sensitivity along with the multi-frequency excitations, the proposed SCLDV shows the improved depth estimation, compared to the previous approaches which empirically select the interrogation frequency.
For validation of this technique, several experiments were performed on steel plates, which contain corrosion damage with various depth variations. The results showed that the proposed technique is very efficient in detecting and visualizing very small thickness variations of a structure at high speed.
This paper presents the comparison study of wavenumber-based defect detection performance in full field laser scanning techniques. Two types of wave excitation are used for damage detection; guided waves and standing waves. A piezoelectric actuator is mounted on surface of the thin plate to generate guided and standing waves with a single excitation frequency. Subsequent responses on each grid point are measured using a Laser doppler vibrometer (LDV) with a mirror tilting device. Full field wave image is then generated from the measured wave signals. After the laser scanning, wavenumber based processing is applied to the measurements to generate two types of full wave field images and to detect structural damage. Three wavenumber based signal processing are applied to the wave filed images to estimate damage size and depth, including the Local wavenumber mapping, Acoustic Wavenumber Spectroscopy, 2D wavelet based wavenumber spectroscopy. For the comparison of these two techniques, several experiments are performed on thin walled structures with several different types of damage, including corrosion in an aluminum plate and debonding on composite plates. This paper outlines pros and cons of these two excitation techniques in terms of several parameters, including damage sensitivity, processing time and their applicability.
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