Sparse Low-Rank Tensor Decomposition for Metal Defect Detection Using Thermographic Imaging Diagnostics

With the increasing use of induction thermography (IT) for non-destructive testing (NDT) in the mechanical and rail industry, it becomes necessary for the manufactures to rapidly and accurately monitor the health of specimens. The most general problem for IT detection is due to strong noise interference. In order to counter it, general post-processing is carried out. However, due to the more complex nature of noise and irregular shape specimens, this task becomes difficult and challenging. In this paper, a low-rank tensor with a sparse mixture of Gaussian (MoG) (LRTSMoG) decomposition algorithm for natural crack detection is proposed. The proposed algorithm models jointly the low rank tensor and sparse pattern by using a tensor decomposition framework. In particular, the weak natural crack information can be extracted from strong noise. Low-rank tensor based iterative sparse MoG noise modeling is carried out to enhance the weak natural crack information as well as reducing the computational cost. In order to show the robustness and efficacy of the model, experiments are conducted for natural crack detection on a variety of specimens. A comparative analysis is presented with general tensor decomposition algorithms. The algorithms are evaluated quantitatively based on signal-to-noise-ratio (SNR) along with the visual comparative analysis

A Lightweight Spatial and Temporal Multi-Feature Fusion Network for Defect Detection

This article proposes a hybrid multi-dimensional features fusion structure of spatial and temporal segmentation model for automated thermography defects detection. In addition, the newly designed attention block encourages local interaction among the neighboring pixels to recalibrate the feature maps adaptively. A Sequence-PCA layer is embedded in the network to provide enhanced semantic information. The final model results in a lightweight structure with smaller number of parameters and yet yields uncompromising performance after model compression. The proposed model allows better capture of the semantic information to improve the detection rate in an end-to-end procedure. Compared with current state-of-the-art deep semantic segmentation algorithms, the proposed model presents more accurate and robust results. In addition, the proposed attention module has led to improved performance on two classification tasks compared with other prevalent attention blocks. In order to verify the effectiveness and robustness of the proposed model, experimental studies have been carried out for defects detection on four different datasets. The demo code of the proposed method can be linked soon: http://faculty.uestc.edu.cn/gaobin/zh_CN/lwcg/153392/list/index.ht

DeftectNet: Joint loss structured deep adversarial network for thermography defect detecting system

In this paper, a novel joint loss Generative Adversarial Networks (GAN) framework is proposed for thermography nondestructive testing named Defect-Detection Network (DeftectNet). A new joint loss function that incorporates both the modified GAN loss and penalty loss is proposed. The strategy enables the training process to be more stable and to significantly improve the detection rate. The obtained result shows that the proposed joint loss can better capture the salient features in order to improve the detection accuracy. In order to verify the effectiveness and robustness of the proposed method, experimental studies have been carried out for inner debond defects on both regular and irregular shaped carbon fiber reinforced polymer/plastic (CFRP) specimens. A comparison experiment has been undertaken to study the proposed method with other current state-of-the-art deep semantic segmentation algorithms. The promising results have been obtained where the performance of the proposed method can achieve end-to-end detection of defects

Characterisation and probability of detection analysis of rolling contact fatigue cracks in rails using eddy current pulsed thermography

PhD ThesisWith transportation volumes continuously increasing, railway networks are now facing problems of greater axle loads and increasing vehicle speeds. The most direct consequence is the initiation of rolling contact fatigue (RCF) defects in rails, which have become safety issues for all types of railway systems and received more attention due to lack of timely examination and management. Among different RCF defects, the RCF crack probably presents the biggest hazard in rails. Detection and characterisation of RCF cracks aim to provide detailed guidelines for safety management and preventative grinding. Unfortunately, current nondestructive testing and evaluation techniques are still facing several challenges and research gaps. One outstanding challenge is the characterisation of RCF cracks under their complex geometries and clustered distributions. One major research gap is how to evaluate the probabilistic performance in crack characterisation via a proper framework. By combining the advantages of eddy current pulse excitation and infrared thermography, this thesis proposes the use of eddy current pulsed thermography (ECPT) technique to address the detection and characterisation of RCF cracks in rails. To quantitatively investigate the ECPT’s performance in crack characterisation, a performance evaluation framework based on probability of detection (POD) analysis is proposed. The major contributions of the thesis are summarised as follows: (1) implementations of three-dimensional FEM models and a lab-based ECPT system for investigating the characterisation of RCF cracks under clustered distributions and geometric influences; (2) temporal/spatial-thermal-feature-based ECPT for angular slots and RCF cracks detection and characterisation; (3) investigations into the capability and the performance of ECPT for characterising angular slots and natural RCF cracks via a POD analysis framework. The thesis concludes that the proposed feature-based ECPT system can characterise RCF cracks in both light and moderate stages. Based on feature comparison and POD evaluation, tempo-spatial-based patterns are better fits for pocket length characterisation. Temporal domain-based features show better performances for inclination angle characterisation. A spatial domain-based feature, SST, can characterise vertical depths with reasonable POD values. One tempo-spatial-based pattern at the early heating stage, IET-PCA, gives the best performance for characterising surface lengths. Still, several issues need to be further investigated in future work, such as feature selection for crack characterisation, three-dimensional reconstruction of RCF cracks, model-assisted POD frameworks for improving the effectiveness of POD analysis with a limited number of physical specimens

Three-dimensional subsurface defect reconstruction for industrial components using pulsed thermography

Pulsed thermography is a promising method for detecting subsurface defects, but most pulsed thermographic inspection results are represented in the form of 2D images. Such a representation can limit the understanding of where the defects initiate and how they grow by time, which is a key to predict the remaining use of life of component and feedback to the design to avoid such defects. Threedimensional subsurface defect visualisation is a solution that can unlock this limitation. A straightforward approach to reconstruct 3D subsurface defect is conducting two inspections on both front and rear sides. However, the deployment of this approach can be limited because 1) one side of the inspected component could be inaccessible; 2) the accuracy of measurement could be compromised if the defect thickness is very thin due to extreme closed values of defect depths from two inspections; and 3) if the defect is too deep for one side, the defect could be missed. Addressing the challenge of 3D subsurface defect reconstruction and visualisation, this thesis proposes a novel technique to measure defect depth and estimate defect thickness simultaneously through estimating the thermal wave reflection coefficient value achieved by introducing a modified heat transfer model based on a single-side inspection method. The proposed method is validated through model simulations, experimental studies, and a use case. Four composite samples with different defect types, sizes, depths and thicknesses, are used for experimental studies; a steel sample with a ‘s’ shape triangular air-gap inside is used for a use case. The simulation results show that under the noise level of 25 dB, the percentage error of the developed depth measurement method is 0.25% whilst the minimum error of the best existing method is 2.25%. From the experimental study results, the averaged percentage error of the defect thickness estimation is less than 10% if the defect thickness is no more than 3 mm. For the use case, the reconstructed defect shape is similar to the X-ray image.Manufacturin

The Second Joint NASA/FAA/DOD Conference on Aging Aircraft

The purpose of the Conference was to bring together world leaders in aviation safety research, aircraft design and manufacturing, fleet operation and aviation maintenance to disseminate information on current practices and advanced technologies that will assure the continued airworthiness of the aging aircraft in the military and commercial fleets. The Conference included reviews of current industry practices, assessments of future technology requirements, and status of aviation safety research. The Conference provided an opportunity for interactions among the key personnel in the research and technology development community, the original equipment manufacturers, commercial airline operators, military fleet operators, aviation maintenance, and aircraft certification and regulatory authorities. Conference participation was unrestricted and open to the international aviation community

Research and technology highlights, 1993

This report contains highlights of the major accomplishments and applications that have been made by Langley researchers and by our university and industry colleagues during the past year. The highlights illustrate both the broad range of the research and technology activities supported by NASA Langley Research Center and the contributions of this work toward maintaining United States leadership in aeronautics and space research. This report also describes some of the Center's most important research and testing facilities

Aeronautical engineering: A continuing bibliography with indexes (supplement 258)

This bibliography lists 536 reports, articles, and other documents introduced into the NASA scientific and technical information system in October 1990. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Research & Technology 2005

This report selectively summarizes NASA Glenn Research Center's research and technology accomplishments for fiscal year 2005. It comprises 126 short articles submitted by the staff scientists and engineers. The report is organized into three major sections: Programs and Projects, Research and Technology, and Engineering and Technical Services. A table of contents and an author index have been developed to assist readers in finding articles of special interest. This report is not intended to be a comprehensive summary of all the research and technology work done over the past fiscal year. Most of the work is reported in Glenn-published technical reports, journal articles, and presentations prepared by Glenn staff and contractors. In addition, university grants have enabled faculty members and graduate students to engage in sponsored research that is reported at technical meetings or in journal articles. For each article in this report, a Glenn contact person has been identified, and where possible, a reference document is listed so that additional information can be easily obtained. The diversity of topics attests to the breadth of research and technology being pursued and to the skill mix of the staff that makes it possible. For more information, visit Glenn's Web site at http://www.nasa.gov/glenn/. This document is available online (http://www.grc.nasa.gov/WWW/RT/). For publicly available reports, visit the Glenn Technical Report Server (http://gltrs.grc.nasa.gov)

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically