Defect Detection Sensitivity Research Articles

Damage detection technique using ultrasonic guided waves and outlier detection: Application to interface delamination diagnosis of integrated circuit package

This paper presents the development of a robust data-driven damage diagnosis technique to accurately detect sealant delamination in an integrated circuit (IC) package. A sealant is used to bond the integrated heat spreader (IHS) to the substrate of IC packages for effective thermal dissipation. Delamination of the sealant causes significant reduction in heat management capability of the package, which leads to degradation of processor performance and component reliability. In this work, non-destructive evaluation (NDE) using ultrasonic guided wave (UGW) is performed to interrogate the integrity of the IC package. The advantage of using UGW is its large area inspection capability and small defect detection sensitivity. Ultrasonic tests using a pitch-catch active sensing method with removable piezoelectric (PZT) tranducers are performed with a wide range of excitation frequencies to classify various delamination scenarios in the IC package. Data preprocessing and Hilbert transform-based feature extraction method are also performed on the collected UGWs to extract dominant UGW features. Pattern analysis using a density-based spatial clustering of applications with noise (DBSCAN) algorithm is conducted on the UGW feature space to classify the damage indicators. These damage indicators (outliers) are then used to identify the IC packages with sealant delamination. The proposed technique is validated by comparing it to dye-and-pry tests, delamination metrics, and detection method using a multivariate Gaussian model. The results demonstrate that the proposed diagnosis technique has the potential to be a part of the industrial quality assurance process for IC packages for its capability to detect manufacturing defects with high accuracy.

SSWT and VMD Linked Mode Identification and Time-of-Flight Extraction of Denoised SH Guided Waves

Ultrasonic guided wave testing technology is currently widely used in industrial nondestructive testing (NDT), including defect detection in the floors of large tanks and oil pipelines. However, in addition to noise, practical scenarios of signal detection also present mode aliasing problems, which make it difficult to accurately identify and locate defects. In this paper, we propose an improved shear horizontal guided wave mode identification method using a variational mode decomposition (VMD) algorithm and a time-of-flight (TOF) extraction method using the synchrosqueezed wavelet transform (SSWT) algorithm. Moreover, we use the wavelet denoising method to denoise the original signal before applying VMD. The results show that the TOF errors obtained by the VMD method are all less than 5% and that the wavelet denoising of the original guided wave data can further reduce the errors (to less than 2%). In addition, the SSWT can modify the time-frequency analysis results of intrinsic mode functions obtained by the VMD method and provides accurate TOF data for different modes. Therefore, the proposed ultrasonic guided wave signal method is helpful for improving the defect detection sensitivity and accuracy of SH waves.

Methods for enhancement of high-sensitivity detection for a surface wave EMAT

Due to the poor conversion efficiency and signal-to-noise ratio (SNR) of Electromagnetic Acoustic Transducer (EMAT) testing, the defect detection sensitivity is limited, which restricts the extensive industrial applications. A finite element model for the testing process of a meander-coil EMAT was established that considers the simplified excitation and detection circuits for the EMAT. Based on this model, the effect of the connection methods (parallel or series) of the coils in the generating and receiving EMATs on their generating and receiving efficiency was investigated, and the simulation results were validated experimentally. Subsequently, the pulse compression technique with a 13-bit Barker code was used for the EMAT detection, and improvements of the SNR and range resolution were established through numerical simulation and experimental measurement. The results show that compared with the traditional EMAT design, which comprises single-layer transmitting and receiving coils, the conversion efficiency of the optimized EMAT with two excitation and receiving coils in the parallel connection can be improved by 52.8%. With the application of the Barker-coded pulse compression to detect the ultrasonic A-scan signal with no synchronous average, the SNR of the defect echo can be improved by 9.5 dB compared with the A-scan signal with 128 synchronous averages.

Projection aided digital shearography scanning detection technology

Digital shearography has been widely used in non-destructive testing of composite materials. But the conventional detection area is limited and the defect detection of large-size composite materials is difficult to achieve. A digital shearography assisted with projection scanning detection for large-size composite materials was introduced. Based on digital shearography and the auxiliary projection which could project additional surface features, global matching and coordinate unification of the sub-view original images and the speckle interferograms were calculated by the homography matrix of the corresponding projection images to realize the multi-field scanning and matching stitching of projection, origin, and interferogram images. At the same time, a 4f optical path and an ultra-wide-angle lens were imported for the one detection to expand the detection area. Experimental results show that the scanning detection system can achieve more accurate measurement of the defect position and size. The root mean square error of location positioning is 7.0 mm, and the root mean square value of dimension measurement error is 4.9 mm. At a working distance of 1.2 m, the single detection area can reach 600 mm×500 mm and the global scanning detection area can reach 3.5 m×4.0 m. This method has the advantages of strong resistance to rigid body displacement interference and high sensitivity of defect detection, which is suitable for non-destructive testing of large-size and high performance composite materials.

Analysis of Flaw Detection Sensitivity of Phased Array Ultrasonics in Austenitic Steel Welds According to Inspection Conditions.

The anisotropy and inhomogeneity exhibited by austenitic steel in welds poses a challenge to nondestructive testing employing ultrasonic waves, which is predominantly utilized for the inspection of welds in power plants. In this study, we assess the reliability of phased array ultrasonic testing (PAUT) by analyzing the flaw detection sensitivity of ultrasonic beams in anisotropic welds, based on the inspection conditions. First, we simulated the sectorial scan technique, frequently employed for the inspection of actual welds, while taking into account the ultrasonic wave mode, frequency, and shape and position of a flaw. Subsequently, we analyzed the flaw sensitivity by comparing A-scan signals and S-scan results. The sensitivity analysis results confirmed the detection of all flaws by considering at least two inspection methods based on the shape and position of the flaw. Furthermore, we verified our model by performing an experiment under the same conditions as the simulation and found that the results were in agreement. Hence, we find that the simulation modeling technique proposed in this study can be utilized to develop suitable inspection conditions, according to the flaw characteristics or inspection environment.

Change detection using the generalized likelihood ratio method to improve the sensitivity of guided wave structural health monitoring systems

The transition from one-off ultrasound–based non-destructive testing systems to permanently installed monitoring techniques has the potential to significantly improve the defect detection sensitivity, since frequent measurements can be obtained and tracked with time. However, the measurements must be compensated for changing environmental and operational conditions, such as temperature, and careful analysis of measurements by highly skilled operators quickly becomes unfeasible as a large number of sensors acquiring signals frequently is installed on a plant. Recently, the authors have developed a location-specific temperature compensation method that uses a set of baseline measurements to remove temperature effects from the signals, thus producing “residual” signals on an unchanged structure that are essentially normally distributed with zero-mean and with standard deviation related to instrumentation noise. This enables the application of change detection techniques such as the generalized likelihood ratio method that can process sequences of residual signals searching for changes caused by damage. The defect detection performance offered by the generalized likelihood ratio when applied to guided wave signals adjusted either via the newly developed location-specific temperature compensation method or the widely used optimal baseline selection technique is investigated on a set of simulated measurements based on a set of experimental signals acquired by a permanently installed pipe monitoring system designed to monitor tens of meters of pipe from one location using the torsional, T(0,1), guided wave mode. The results presented here indicate that damage on the order of 0.1% cross section loss can reliably be detected with virtually zero false calls if the assumptions of the study are met, notably the absence of sensor drift with time. This represents a factor of 20–50 improvement over that typically achieved in one-off inspection and makes such monitoring systems very attractive. The method will also be applicable to bulk wave ultrasound signals.

Eddy Current Testing in Service of the Boiler Heating Surface Tube Elbow in Thermal Power Plants

According to the characteristics of closed ends, tight tube screen and narrow testing spaces of the eddy current testing in service of the boiler heating surface tube elbow in thermal power plants, an external placed saddle eddy current testing probes which could be used to test the small diameter austenitic stainless steel tube elbow was designed. Then the comparative sample tube was processed in accordance with the eddy current testing technical standards. Through the sample testing and the applications in thermal power plants, the results show that the designed saddle-shaped eddy current detecting probe device has high detection sensitivity and reliability for linear defects above 0.2 mm and hole defects above Φ1.4 mm. It can realize the non-destructive testing in service of the austenitic stainless steel tube elbow, which has more serious oxidation, corrosion and more focused stress.

Investigations on probability of defect detection using differential filtering for pulse compression favourable frequency modulated thermal wave imaging for inspection of glass fibre reinforced polymers

Thermal Non-Destructive Testing and Evaluation (TNDT&E) plays a crucial role in industrial quality control and structural health monitoring of a variety of materials. Among various TNDT&E modalities, active Infrared Thermography (IRT) has emerged as an extremely promising approach and has gained enormous significance due to its quick, whole field, non-contact and quantitative defect detection capabilities. Pulse Compression favourable Thermal Wave Imaging (PCTWI) especially Frequency Modulated Thermal Wave Imaging (FMTWI) has become popular among a number of active IRT techniques because of increment in defect detection sensitivity as well as test resolution. The present work attempts to explore the applicability of differential filtering post processing scheme for pulse compression favourable FMTWI for enhanced detection contrast, resolution and Probability of Detection (PoD). The proposed scheme has been applied on a Glass Fibre Reinforced Polymer (GFRP) sample with sub-surface flat bottom hole (FBH) defects located inside the sample at different depths. The results presented clearly demonstrate that the differential contrast approach enhances the defect detection probabilities by considering maximum and minimum deviation dip values as a figure of merit. Hence, pulse compression favourable FMTWI employing differential filtering manifests higher Probability of Detection (PoD) for defects located at different depths as compared to taking into account the peak Correlation Coefficient (CC) as a statistical figure of merit. Further Probability of Detection (PoD) of the pulse compression favourable FMTWI technique has been improved by differential filtering post-processing based scheme that reduces the memory requirement, computational cost as well as complexity.

Visual detection of defects in carbon steel using magnetic nanoemulsions: Effect of stabilizing moieties on the defect detection sensitivity

The defect detection sensitivity of magnetic nanoemulsions (MNEs) stabilized with different functional moieties such as anionic surfactant, co-polymer and a weak polyelectrolyte is reported here. The visually discernible colour contrast over the defective regions and the corresponding Bragg’s reflection, originating from the linear chain-like structures formed by the leakage magnetic flux are experimentally measured and compared with the theoretically obtained profiles. The linear chain-like structures, formed by the MNEs, are also visualized using atomic force and optical phase contrast microscopy studies. Defect detection studies are carried out on carbon steel samples with artificially made defects (rectangular slots) and the variations in defect detection sensitivity (colour contrast) are assessed under different stabilizing moieties. It is found that the electrostatically stabilized MNEs exhibited superior defect detection sensitivity, as compared to the polymeric stabilizers. The microscopic origin for sensitivity variations, is studied by measuring the inter-droplet forces and hydrodynamic diameter. The inter-droplet force measurements show that the lower decay length is better for improving the defect detection sensitivity. Through image processing and intensity profiling, the defect widths are accurately estimated, which are in good agreements with the actual defect dimensions. The intensity profiles are found to vary linearly with the defect depth for the shallower defects. These results are useful to tailor MNEs with superior defect detection sensitivity and long-term stability towards development of MNE-based thin film sensors for automated and superior defect detection strategies.

Interaction of Acoustic and Electromagnetic Waves in Nondestructive Evaluation and Medical Applications

Nonlinear acoustic nondestructive evaluation (NA NDE) methods have a higher sensitivity for defect detection than standard methods. These methods use various kinds of acoustic wave interactions. In this paper, we suggest augmenting the acoustic framework and use the interaction between acoustic and electromagnetic waves. A brief review of NA NDE and medical nonlinear acoustic imaging methods is presented. Medical methods based on electromagnetic wave modulation by an acoustic radiation force are discussed where improvements using ultrasound contrast agents are suggested. The estimation of the modulation of a radar signal by a crack vibration were made based on standard static measurements. The effects of modulation of an acoustic wave by an electromagnetic field are briefly considered for the method of crack detection in metal materials. The effects considered in this paper may be used in the new methods of NDE and medical diagnostics.

Automated defect detection in FRP-bonded structures by Eulerian video magnification and adaptive background mixture model

A computer-aided methodology for automated defect detection in fiber-reinforced polymer (FRP) bonded civil engineering structures via Eulerian video magnification integrated with adaptive background mixture model is demonstrated. In this methodology, Eulerian video magnification is firstly used to render the stimulated de-bonding motion visible in a high-speed and high-resolution video. Then, adaptive background mixture model is applied in the motion-magnified video for automated tracking of the de-bonding motion. The combined use of these two computer-aided vision techniques aims at developing an innovative way for intuitive, straightforward, and automated defect detection. In the application of this methodology, two operational parameters (i.e. motion amplification factor and de-noising factor) in the video processing can greatly affect the sensitivity of defect detection. After evaluation of their effects, the present work shows a practice guide for adjusting the above two influencing parameters in order to improve the automated defect detection.

A Defect Detection Method for the Image With Intersecting Feature

Since the intersecting feature between the defect and the background of the image, the defect detection often results in under-segmentation or over-segmentation. To solve this problem, we propose a new defect extraction method by calculating the maximum mutual information of intersecting features. Firstly, we construct a new two-dimensional histogram according to the defect features. The new histogram is called Gray Level and Local Spatial Difference histogram (GLSD), which is constructed by grayscale and the improved local gray difference with the spatial relationship. Secondly, considering the geometric distribution of high-probability background events, we improve the segmentation shape of the background event distribution and divide the GLSD histogram preliminary. Finally, we calculate the maximum mutual information of the intersecting feature between the defect and the background. At this point, the boundary of the intersecting feature interval of the GLSD histogram is determined. To verify the effectiveness of the proposed method, we used two sets of databases for performance evaluation. The experimental results show that the proposed method is suitable for non-obvious defect detection under the local uniform background. Meanwhile, it can improve the sensitivity, specificity, and accuracy of defect detection compared with the classical threshold segmentation methods.

Guided wave sensitivity prediction for part and through-thickness crack-like defects

Guided waves allow for the efficient structural health monitoring of large structures using phased or distributed arrays of sensors. The sensitivity for specific defects can be improved by accounting for the angular scattering pattern. The scattering of the fundamental anti-symmetric guided wave mode (A0 Lamb mode) at through-thickness and part-through crack-like defects was studied experimentally and from three-dimensional finite element simulations. Experimentally, the scattered field around manufactured notches of different depths and lengths in an aluminium plate was measured using a laser interferometer. The scattered field was extracted by taking the complex difference in the frequency domain between baseline measurement and measurements around the defect. Good agreement was found between measurements and three-dimensional finite element simulations, and the amplitude and directionality pattern of the scattered field can be predicted accurately. The angular directionality pattern of the scattered field depending on the direction of the incident wave relative to the crack-like defect orientation, depth and length relative to the wavelength was investigated. For short and part-thickness defects, the main scattering effect is a reduction of the (forward) wave propagating past the defect with very limited backscattered amplitude. Significant energy scattered back towards the incident wave direction was only found for perpendicular incidence on long and deep defects. Even for large defects, almost no energy is scattered in certain directions from the defect, possibly complicating defect detection. Based on the predicted amplitude and angular dependency of the scattered guided waves, the sensitivity for defect detection using localized and distributed structural health monitoring sensor array systems can be quantified.

Detection sensitivity analysis of pipe pile defects during low-strain integrity testing

The detection sensitivity of pipe pile defects during low-strain integrity testing is investigated with the consideration of soil plug, the soil sandwiched in neck defect and high-frequency interference at pile head. The additional mass model and fictitious ring-soil pile model (FRSPM) are introduced to simulate the soil plug effect and the dynamic interaction between the sandwiched soil and neck defect, respectively. The high-frequency interference is realized by considering the stress wave propagating both in the vertical and circumferential directions. An analytical solution for the dynamic velocity response of pipe pile is derived in the frequency domain through the transfer function method, and the corresponding semi-analytical solution in the time domain is then obtained by using the inverse Fourier transform. The reasonability and accuracy of the developed solution are verified by a series of field experiments. The dynamic interaction between the neck defect and the FRSPM is clarified via the parameter sensitivity analysis. The non-detection zone of pipe pile during low-strain integrity testing is analyzed. It is shown that the main factors to affect detection accuracy are the reduction degree and the location of defects, and there exists a location non-detection zone near the pipe pile toe.

Defect detection capabilities of independent component analysis for Barker coded thermal wave imaging

Active pulse compression favourable infrared imaging techniques are promising evaluation techniques among other thermal non-destructive testing and evaluation modalities for identification of subsurface defects in the test samples. This is due to their merits such as high defect detection sensitivity and resolution by using relatively low peak power heat sources and in a moderate experimentation time in comparison with widely used pulse and modulated conventional thermal wave imaging modalities. Various data processing methods have been developed to extract the thermal features of defects from the captured thermographic data. The cross-correlation based pulse compression method is recommended for Barker coded thermal wave imaging technique as it enhances the concentration of applied thermal energy into mainlobe and distributes the significantly less energy into the sidelobes of cross correlation data. In this paper, the stated property of Barker coded thermal wave imaging along with the independent component analysis approach has been utilised. The study in this paper is focused on the application of independent component analysis approach on captured thermal response data, entire cross correlation data and only the mainlobe of CC data. The results obtained clearly indicate that the application of independent component analysis on cross correlation data has improved the detectability, visibility, and contrast (interms of signal-to-noise values) of the defects. Further, the results obtained with the different methods have been compared by taking Signal to noise ratio as the figure of merit.

An efficient data processing approach for frequency modulated thermal wave imaging for inspection of steel material

Non-destructive testing & evaluation (NDT&E) plays a vital role in industrial quality control. Among various NDT&E modalities, active thermal NDT&E gained its importance due to its inherent merits such as remote, whole-field, fast and quantitative inspection capabilities. Of various thermal NDT&E schemes, recently proposed pulse compression favorable frequency modulated thermal wave imaging (FMTWI) became popular due to its enhanced defect detection sensitivity along with improved test resolution. This paper presents noise rejection capabilities of FMTWI with principal component analysis (PCA) based post-processing schemes. PCA based post-processing helps in efficient interpretation of the thermographic data by removing artefacts and producing few significant images depicting sub-surface defects in the test specimen. The results obtained by PCA can be made more interpretable by using sparser version of PCA (SPCA). In this paper, SPCA based thermographic data processing technique is proposed in which SPCA has been considered in two different ways. Firstly it has been implemented to induce sparsity in empirical orthogonal functions (EOFs) which improves spatial contrast over the defective regions. Secondly, it has been used to modify principal components (PCs) (time series components) to obtain resultant images by projecting thermographic data on modified PCs which manages to enhance the signal to noise ratio (SNR). The sub-surface defect detection capabilities of the proposed methods are studied by a matched filter based pre-processing scheme which reduces the computational cost and memory usage also. The performance of the proposed methods has been evaluated on the experimental investigation of the mild steel specimen having flat bottom holes as defects.

Probability of defect detection in pulse compression favourable frequency modulated thermal wave imaging

Infrared thermography plays a vital role in the thermal non-destructive testing and evaluation (TNDT) due to its merits such as whole-field, remote and quantitative defect detection capabilities. Among the various TNDT methods, recently proposed, pulse compression favourable thermal wave imaging gained its importance due to its merits in terms of defect detection sensitivity and resolution. This Letter attempts to compare different post-processing schemes to compare their sub-surface defect detection capabilities for a glass fibre reinforced polymer test sample. Results obtained clearly show defect detection probability of the matched filter-based post-processing approaches are far superior to that of the conventional frequency domain phase approach.

Experimental investigation on noise rejection capabilities of pulse compression favourable frequency‐modulated thermal wave imaging

Among the various non-destructive testing and evaluation methods, infrared thermography gained its importance due to its fast, whole field, remote and quantitative evaluation capabilities for inspection of various materials. Being an optimum technique in terms of usage of low peak power heat sources in a moderate experimentation time, frequency-modulated thermal wave imaging (FMTWI) plays a vital role in the infrared thermographic community. The noise rejection capabilities of the proposed pulse compression favourable FMTWI by using principal component analysis as a post-processing technique are highlighted. The proposed scheme has been tested on a mild-steel sample having sub-surface flat bottom hole defects located inside the test specimen at various depths. It is clear from the obtained results that the reconstructed pulse (main lobe) concentrates much of the imposed energy into a narrow duration, which enhances the defect detection sensitivity and resolution in order to visualise the sub-surface defects with higher signal-to-noise ratio.

Novel design of a smart and harmonized flexible printed coil sensor to enhance the ability to detect defects in pipes

The interaction between the static and dynamic magnetic fields generated from a conventional magnetostrictive sensor (MsS) is an important factor in the sensitivity of defect detection. Normally, the dynamic magnetic field of an MsS is generated by its electric coils, whereas the static magnetic field is generated by permanent magnets. The magnitude of the generated fields and their interactions significantly affect the amplitude of the induced guided-wave signals. The conventional hard coil-based MsS is usually bulky and is not sufficiently flexible to fit pipes of various sizes. Such inflexibility limits the use of conventional MsS in practical situations. To overcome these limitations, the authors designed an innovative type of coil, called the flexible printed coil (FPC), to replace the inflexible hard coil. Because the FPC is a thin film, it can be easily wrapped around any size pipe, whereas the conventional hard coil–based MsS requires modification with changes in the size of pipes. Although the smart FPC-MsS can work as expected, due to the design of the flexible coils, the interference caused by the coils exerted an uneven magnetostrictive force on the tested pipe. This increases the sensitivity required to detect defects, which differ at each circumferential location of the inspected pipe. Hence, the smart FPC-MsS generates different results at different circumferential locations even though the sizes of the cracks are the same at each circumferential location. To address this deficiency, we designed a smart and harmonized FPC-MsS, called smart HFPC-MsS, which can generate an even magnetostrictive force regardless of the circumferential location of the crack. Ultimately, an evenly distributed amplitude of guided waves can be emitted into the entire pipe, which improves the accuracy of crack detection. In this paper, the theoretical foundation of designing the smart HFPC-MsS is explained, and its working principles are introduced. Both the simulated and experimental results prove the effectiveness of such a novel HFPC-MsS, and the results show that it can generate even amplitude of the guided waves to the pipe regardless of the circumferential location of the crack, resulting in more accurate crack detection than that provided by the author's previously designed smart FPC-MsS.

Grease-like coupling agent based on metal ionization method for low-frequency ultrasonic NDT

Abstract In long-distance NDT based on ultrasonic guided waves with low-frequency excitation, the most commonly used industrial coupling agents are grease-like coupling agents. However, these agents show the poor performance in NDT, because they can cause more acoustic energy loss and lower acoustic transmissivity. In the study, to improve the acoustic transmission property of grease-like coupling agents, a new method was proposed to combine different metal ions like Li+, Na+ and Ca2+ with base grease, thus forming new grease-like coupling agents. By comparing with the ultrasonic transmitting property of the regular coupling agents, selects a premium ultrasonic grease-like coupling agent. In the experimental results, when low-frequency ultrasonic guided waves transmitted through the lithium-based coupling agent, except the slight delay of peak response time, pulse signals showed the higher energy transmission efficiency with the better pulse vibration waveforms in the iron medium than other oil-based coupling agents. The newly developed grease-like coupling agent can be easily prepared at a lower cost. Importantly, the new coupling agent can improve the energy transmission performance and greatly enhance the sensitivity of ultrasonic flaw detection.