Inspection Capability Research Articles

Spectral finite element method for efficient simulation of nonlinear interactions between Lamb waves and breathing cracks within the bi-potential framework

Nonlinear ultrasonic guided waves are of great importance in structural health monitoring, since they have both the large-area inspection capability of guided waves and the desirable sensitivity to incipient defects from nonlinear ultrasonic features. Efficient numerical methods play a key role in investigating the nonlinear features of guided waves. In this work, a time domain spectral finite element method (TDSFEM) combined with the bi-potential contact theory is developed to capture the nonlinear interactions between guided waves and breathing cracks. The bi-potential approach has better accuracy than the conventional penalty method, since there is no any user-defined parameter for computation in the former method while the latter one requires a user-experience-based penalty factor. In addition, a semi-explicit algorithm is proposed to integrate the wave equation, which can take full advantage of the diagonal mass matrix of TDSFEM while not sacrificing numerical stability. Numerical verifications against ANSYS show that the computational efficiency of the bi-potential method-based TDSFEM is much higher than that of the FEM via the penalty method. Numerical case studies are then performed to investigate the nonlinear interactions between Lamb waves and breathing cracks. Results show that the proposed method can successfully capture the classical nonlinear features, such as higher harmonic generation and zero frequency (DC) response. Moreover, the influence of the length and gap of a breathing crack on the contact acoustic nonlinearity (CAN) is investigated. As an efficient numerical approach, the bi-potential method-based TDSFEM may be a good tool for investigating the CAN.

Development of an optical measurement system for surface depth measurements and study of focus effect on determination of steel inclusion content by EN-10247

Surface inspections are important in steelmaking processes to characterize the final product’s quality. We present a method to measure surface depth profile using laser scattering geometry. This technique is used to analyze the focus effect on microscopic analyses of steel inclusions using the EN-10247 standard. The results presented herein offer promising new perspectives for the metal manufacturing industry through cost-effective solutions that attain quasi in-line process inspection capabilities.

Denoising Autoencoder based Noise Reduction Technique for Raman Spectrometers for Standoff Detection of Chemical Warfare Agents

Raman spectrometers are studied and developed for the military purposes because of their nondestructive inspection capability to capture unique spectral features induced by molecular structures of colorless and odorless chemical warfare agents(CWAs) in any phase. Raman spectrometers often suffer from random noise caused by their detector inherent noise, background signal, etc. Thus, reducing the random noise in a measured Raman spectrum can help detection algorithms to find spectral features of CWAs and effectively detect them. In this paper, we propose a denoising autoencoder for Raman spectra with a loss function for sample efficient learning using noisy dataset. We conduct experiments to compare its effect on the measured spectra and detection performance with several existing noise reduction algorithms. The experimental results show that the denoising autoencoder is the most effective noise reduction algorithm among existing noise reduction algorithms for Raman spectrum based standoff detection of CWAs.

Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE.

The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs.

Automatic Rail Surface Defects Inspection Based on Mask R-CNN

Rail surface defects have negative impacts on riding comfort and track safety, and could even lead to accidents. Based on the safety database (2020) of the Federal Railroad Administration (FRA), rail surface defects have been among the main factors causing derailments. During the past decades, there have been many efforts to detect such rail surface defects. However, the applications of earlier methods are limited by the high requirements of specialized equipment and personnel training. To date, rail surface defect inspection is still a very labor-intensive and time-consuming process, which hardly satisfies the field maintenance expectations. Therefore, a cost-effective and user-friendly automatic system that can inspect the rail surface defects with high accuracy is urgently needed. To address this issue, this study proposes a computer vision-based instance segmentation framework for rail surface defect inspection. A rail surface database including 1,040 images (260 source images and 780 augmented images) has been built. The classic instance segmentation model, Mask R-CNN, has been re-trained and fine-tuned for inspecting rail surface defects with the customized dataset. The influences of different backbones and learning rates are investigated and discussed. Experimental results indicate the ResNet101 backbone reaches better inspection capability. With a learning rate of 0.005, the re-trained Mask R-CNN model can achieve the best performance on the bounding box and mask predictions. Sixteen images are used to test the inspection performance of the fine-tuned model. The results are promising and indicate potential field applications in the future.

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.

Drone-Based StereoDIC: System Development, Experimental Validation and Infrastructure Application

Digital Image Correlation (DIC) is widely used for remote and non-destructive structural health evaluation of infrastructure. Current DIC applications are limited to relatively small areas of structures and require the use of stationary stereo vision camera systems that are not easy to transfer and deploy in remote areas. The enclosed work describes the development and validation of an Unmanned Aircraft System (UAS, commonly known as drone) with an onboard stereo-vision system capable of acquiring, storing and transmitting images for analysis to obtain full-field, three-dimensional displacement and strain measurements. The UAS equipped with a StereoDIC system has been developed and tested in the lab. The drone system, named DroneDIC, autonomously hovers in front of a prestressed railroad tie under pressure and DIC data are collected. A stationary DIC system is used in parallel to collect data for the railroad tie. We compare the data to validate the readings from the DroneDIC system. We present the analysis of the results obtained by both systems. Our study shows that the results we obtain from the DroneDIC system are similar to the ones gathered from the stationary DIC system. This work serves as a proof of concept for the successful integration of DIC and drone technologies into the DroneDIC system. DroneDIC combines the high accuracy inspection capabilities of traditional stationary DIC systems with the mobility offered by drone platforms. This is a major step towards autonomous DIC inspection in portions of a structure where access is difficult via conventional methods.

Inspection technology of remote transmission towers based on a vertical take-off and landing fixed-wing UAV

Transmission towers in remote areas are located in a complex terrain, usually far away from roads, making it difficult for inspectors to approach to deploy auxiliary inspection equipment. Therefore, inspection tasks for such transmission towers have become a time-consuming and laborious hard bone. In response to this problem, this paper proposes a new, safe and efficient form of inspection operations based on a vertical take-off and landing unmanned aerial vehicle (VTOL) which is equipped with a strap-down lateral imaging module to assist in the inspection of electrical towers. Based on the known longitude and latitude information of transmission towers, the inspection route is pre-planned offline. When the VTOL reaches a certain transmission tower, it can be controlled to hover around the center point of the transmission tower at a fixed height. The strap-down lateral imaging module could obtain image information of the transmission tower to monitor the status of the transmission tower. In addition, line-of-sight angles of the center point of the transmission tower in the image can be extracted to help to adjust the height and radius of the VTOL hovering around the transmission tower, so as to achieve the most effective inspection of the transmission tower with a low-cost strap-down industrial camera. The algorithms of the scheme in this paper have been implemented in reliable hardware modules. The scheme has the capability of an actual flight inspection.

Graphical Method for Examining Complex Natural Frequencies of Dispersive Materials

A graphical method is extended to and applied for visual inspection of solution patterns (region of complex natural frequencies s <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> ) in the complex s-plane for dispersive materials characterized by the Debye and Lorentz models. These patterns are in the form of exponential decay and C-shaped profiles for the Debye and Lorentz models, respectively. Their forms are observed to be affected (e.g., moving left/right) in different manners with a variation of dispersion parameters. This method, thanks to its visual inspection capability, can help in analyzing/synthesizing filters and frequency-selective surfaces.

ISafeUAS: An unmanned aerial system for construction safety inspection

Unmanned Aerial Systems (UASs) have recently been utilized as an efficient safety inspection and monitoring tool on construction jobsites. However, their deployment could potentially result in hazardous situations such as worker distraction or struck-by accidents. This paper introduces iSafeUAS as an initial effort to develop and assess a platform designed for safety inspection purposes with customized features such as a super optical zoom RGB Camera and a Parachute Recovery System to ensure safe yet accurate visual data acquisition without the need to fly over or near populated areas. After conducting multiple flight tests to evaluate its technical performance, the iSafeUAS was deployed on a construction jobsite to validate its safety inspection capabilities. The study results showed that the Parachute Recovery System reduced the fatality probability by more than 40%, and the super optical zoom capabilities helped safety managers better identify and inspect potential safety hazards.

Review of Current Guided Wave Ultrasonic Testing (GWUT) Limitations and Future Directions.

Damage is an inevitable occurrence in metallic structures and when unchecked could result in a catastrophic breakdown of structural assets. Non-destructive evaluation (NDE) is adopted in industries for assessment and health inspection of structural assets. Prominent among the NDE techniques is guided wave ultrasonic testing (GWUT). This method is cost-effective and possesses an enormous capability for long-range inspection of corroded structures, detection of sundries of crack and other metallic damage structures at low frequency and energy attenuation. However, the parametric features of the GWUT are affected by structural and environmental operating conditions and result in masking damage signal. Most studies focused on identifying individual damage under varying conditions while combined damage phenomena can coexist in structure and hasten its deterioration. Hence, it is an impending task to study the effect of combined damage on a structure under varying conditions and correlate it with GWUT parametric features. In this respect, this work reviewed the literature on UGWs, damage inspection, severity, temperature influence on the guided wave and parametric characteristics of the inspecting wave. The review is limited to the piezoelectric transduction unit. It was keenly observed that no significant work had been done to correlate the parametric feature of GWUT with combined damage effect under varying conditions. It is therefore proposed to investigate this impending task.

A Localization and Navigation Method for an In-Pipe Robot in Water Distribution System Through Wireless Control Towards Long-Distance Inspection

In this paper, we propose an operation procedure for our previously developed in-pipe robotic system that is used for water quality monitoring in water distribution systems (WDS). The proposed operation procedure synchronizes a developed wireless communication system that is suitable for harsh environments of soil, water, and rock with a multi-phase control algorithm. The new wireless control algorithm facilitates smart navigation and near real-time wireless data transmission during operation for our in-pipe robot in WDS. The smart navigation enables the robot to pass through different configurations of the pipeline with long inspection capability with a battery in which is mounted on the robot. To this end, we have divided the operation procedure into five steps that assign a specific motion control phase and wireless communication task to the robot. We describe each step and the algorithm associated with that step in this paper. The proposed robotic system defines the configuration type in each pipeline with the pre-programmed pipeline map that is given to the robot before the operation and the wireless communication system. The wireless communication system includes some relay nodes that perform bi-directional communication in the operation procedure. The developed wireless robotic system along with operation procedure facilitates localization and navigation for the robot toward long-distance inspection in WDS.

Defect Detection Capabilities of Pulse Compression Based Infrared Non-Destructive Testing and Evaluation

Infrared Thermography is one of the widely used method for non-destructive testing and evaluation methods due to its merits (remote, full field, safe and quantitative inspection capabilities) for testing and evaluation of wide variety of materials (metals, semiconductors and composites). Among the various thermal non-destructive evaluation modalities such as pulse based and mono frequency excited modulated lock-in thermography, recently proposed matched filter based non-periodic infrared thermographic approaches gained their importance due to superior test resolution and sensitivity for detection of defects hidden inside the test material. Further, feasibility to implement with low peak power heat sources in moderate experimentation time in comparison with conventional (pulse based thermographic techniques and in a limited span of time in comparison with mono frequency lock-in) thermographic techniques makes these pulse compression favorable techniques more economical and reliable. The present manuscript demonstrates the advantages of pulse compression favorable frequency modulated thermal wave imaging approach for identification of flat bottom holes in a glass fibre reinforced polymer material. The obtained results have been compared with widely used principal component thermography by taking the signal to noise ratio as a figure of merit.

Computed time average digital holographic fringe pattern under random excitation.

Time average digital holography under random excitation or square wave excitation is established as an on-site non-destructive testing tool for defect detection in large metallic and composite sandwich structures due to its high sensitivity, single exposure interferogram, and fast inspection capability. However, extensive calibration studies are necessary to corroborate the defect type and defect size with the excitation frequency range and excitation magnitude. In this paper, a method to simulate a time average digital holographic fringe pattern under random excitation is proposed with the idea to minimize the number of calibration experiments and also for better evaluation of the size and type of defect. The proposed method circumvents the requirement for a closed form expression for the complex characteristic fringe function for time average interferometry under random excitation. The computed fringe pattern is illustratively compared with an experimental time average digital holographic fringe pattern.

The Finite-interval Spectral Power method for detecting underground cavities using seismic ambient noise

SUMMARYUndetected natural and man-made cavities pose a serious geotechnical hazard to human safety. It is therefore important to develop methods for identifying and locating underground cavities in urban development and civil construction. Another important type of cavity is the one generated by an underground nuclear explosion. Identification and location of such cavities is an important proof in case of suspicion of violating the Comprehensive Nuclear-Test-Ban Treaty (CTBT), an international treaty banning nuclear weapon test explosion or any other nuclear explosion which is yet to come into force. We present a new method for detecting and locating a horizontal position of cavity which uses the Finite-interval Spectral Power of seismic ambient noise. The method makes it possible to use single-station measurements at a set of potentially irregularly distributed points in the area on the Earth's free surface over a suspected cavity. Because the method gives better results for undistorted segments of noise records, we also present a method of automatic identification of such segments. We tested our method using records of noise from a site near the Felsőpetény, Hungary, which were collected for the CTBT Organization during a field test in the framework of developing on-site inspection capabilities. The method is ready for further tests in different cavity conditions and applications.

A Novel Inspection Technique for Electronic Components Using Thermography (NITECT).

Unverified or counterfeited electronic components pose a big threat globally because they could lead to malfunction of safety-critical systems and reduced reliability of high-hazard assets. The current inspection techniques are either expensive or slow, which becomes the bottleneck of large volume inspection. As a complement of the existing inspection capabilities, a pulsed thermography-based screening technique is proposed in this paper using a digital twin methodology. A FEM-based simulation unit is initially developed to simulate the internal structure of electronic components with deviations of multiple physical properties, informed by X-ray data, along with its thermal behaviour under exposure to instantaneous heat. A dedicated physical inspection unit is then integrated to verify the simulation unit and further improve the simulation by taking account of various uncertainties caused by equipment and samples. Principle component analysis is used for feature extraction, and then a set of machine learning-based classifiers are employed for quantitative classification. Evaluation results of 17 chips from different sources successfully demonstrate the effectiveness of the proposed technique.

Probability of defect detection in pulse compression favourable thermal excitation schemes for infra‐red non‐destructive testing

InfraRed non-destructive testing and evaluation (IRNDT&E) has emerged as a promising approach for non-destructive testing and evaluation (NDT&E) of various materials because of its inherent merits such as remote, non-invasive, qualitative as well as quantitative inspection capabilities. Among the various IRNDT&E techniques, recently proposed modulated pulse compression favourable thermal wave imaging (PCTWI) techniques, especially frequency modulated thermal wave imaging (FMTWI) and its digitised version digitised FMTWI (DFMTWI) have gained popularity over the conventional sinusoidal modulated [lock-in thermography (LT)] and pulse-based thermographic techniques [pulse thermography (PT) and pulse phase thermography (PPT)] by providing better depth resolution, in less experimentation time, using low peak power excitation heat sources. The present work highlights a comparative study on highly depth resolved continuous depth scanning PCTWI techniques, with single frequency thermal excited LT, on the basis of defect detection probability. The proposed study has been carried out on a glass fibre reinforced polymer test sample with Teflon inserts as defects by considering peak side lobe ratio as a figure of merit. The experimental results clearly show that the probability of detection of defects for DFMTWI is far superior as compared to FMTWI and LT.

Influence of composition and surface discoloration of concrete on active thermographic nondestructive inspection

The capability of active thermographic nondestructive inspection of concrete is influenced by the concrete testing condition. In this study, the influence of concrete composition and surface discoloration caused by efflorescence is investigated. Experiments performed on the concrete specimens under various conditions indicate that active thermography is barely affected by the variation in the concrete composition. This feature makes active thermography a practical tool for inspecting concrete structures with coarse aggregates. Furthermore, it is observed that the surface discoloration caused by efflorescence enhances the surface reflectance in the wavelength range of a halogen lamp. This leads to a reduction in inspection capability owing to heat input reduction. Based on the results, the active thermography method is unsuitable for concrete with great efflorescence.

Design and experimental tests of an active cooling system for a kind of in-vessel inspection manipulator

PurposeThis paper aims to present the design and experimental tests of an active circulating cooling system for the Experimental Advanced Superconducting Tokamak in-vessel inspection manipulator, which will help the current manipulator prototype to achieve a full-scale in-vessel high temperature environment compatibility.Design/methodology/approachThe high-temperature effects and heat transfer conditions of the manipulator under in-vessel environment were analyzed. An active circulating cooling system was designed and implemented on the manipulator prototype. A simulative in-vessel inspection task in a high temperature environment of 100°C was carried out to evaluate the performance of the active circulating cooling system.FindingsThe proposed active circulating cooling system was proved effective in helping the manipulator prototype to achieve its basic in-vessel inspection capability in a high temperature environment. The active circulating cooling system performance can be further improved considering the cooling structure coefficient differences in different manipulator parts.Originality/valueFor the first time, the active circulating cooling system was implemented and tested on a full-scale of the in-vessel inspection manipulator. The experimental data of the temperature distribution inside the manipulator and the operating status of the circulating system were helpful to evaluate the current active circulating cooling system design and provided effective guidance for improving the overall system performance.

Lot-dependent sampling plans for qualifying long-term production capability with a one-sided specification

Acceptance sampling plan establishes a required sample size for lot inspection and decisive capability criteria for lot dispositions. The multiple-lot dependent state (MDS) and the generalized MDS (GMDS) plans have been recently developed for operating capability-qualified compliance testing of a process with a one-sided specification in continuous submissions. However, both lot-dependent plans are incapable for sustaining a long-lasting supplier-buyer relationship. The MDS plan’s benefits deteriorate as the number of deliberated anteceding lot-sentencing outcomes increases; the GMDS plan may suffer a schematic problem in some cases where the current lot having marginal capability will be accepted with an inferior capability history. To remedy those shortcomings, an adjustable MDS (AMDS) sampling plan on qualifying the process capability with a one-sided specification is constructed. This AMDS plan not only allows more backtracking lots encompassed in the lot-disposition decision but also substantially improves the inspection efficiency regarding the required sample size and lot-discriminatory power. More importantly, the plan, operating for the long-run inspection, exhibits a consistent upward-trend phenomenon for the required acceptance-capability standard, which firmly advocates the sustainability of business whose suppliers show continuous improvement of process capability. Finally, the industrial applicability of AMDS is illustrated in a case study.