Research on the Weld Position Detection Method for Sandwich Structures from Face-Panel Side Based on Backscattered X-ray.

Web-core sandwich panels are a typical lightweight structure utilized in a variety of fields, such as naval, aviation, aerospace, etc. Welding is considered as an effective process to join the face panel to the core panel from the face panel side. However, it is difficult to locate the joint position (i.e., the position of core panel) due to the shielding of the face panel. This paper studies a weld position detection method based on X-ray from the face panel side for aluminum web-core sandwich panels used in aviation and naval structures. First, an experimental system was designed for weld position detection, able to quickly acquire the X-ray intensity signal backscattered by the specimen. An effective signal processing method was developed to accurately extract the characteristic value of X-ray intensity signals representing the center of the joint. Secondly, an analytical model was established to calculate and optimize the detection parameters required for detection of the weld position of a given specimen by analyzing the relationship between the backscattered X-ray intensity signal detected by the detector and the parameters of the detection system and specimen during the detection process. Finally, several experiments were carried out on a 6061 aluminum alloy specimen with a thickness of 3 mm. The experimental results demonstrate that the maximum absolute error of the detection was 0.340 mm, which is sufficiently accurate for locating the position of the joint. This paper aims to provide the technical basis for the automatic tracking of weld joints from the face panel side, required for the high-reliability manufacturing of curved sandwich structures.

A laser driven pulsed X-ray backscatter technique for enhanced penetrative imaging.

X-ray backscatter imaging can be used for a wide range of imaging applications, in particular for industrial inspection and portal security. Currently, the application of this imaging technique to the detection of landmines is limited due to the surrounding sand or soil strongly attenuating the 10s to 100s of keV X-rays required for backscatter imaging. Here, we introduce a new approach involving a 140 MeV short-pulse (< 100 fs) electron beam generated by laser wakefield acceleration to probe the sample, which produces Bremsstrahlung X-rays within the sample enabling greater depths to be imaged. A variety of detector and scintillator configurations are examined, with the best time response seen from an absorptive coated BaF2 scintillator with a bandpass filter to remove the slow scintillation emission components. An X-ray backscatter image of an array of different density and atomic number items is demonstrated. The use of a compact laser wakefield accelerator to generate the electron source, combined with the rapid development of more compact, efficient and higher repetition rate high power laser systems will make this system feasible for applications in the field. Content includes material subject to Dstl (c) Crown copyright (2014). Licensed under the terms of the Open Government Licence except where otherwise stated. To view this licence, visit http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: psi@ nationalarchives.gsi.gov.uk.

Locally optimized non-local means denoising for low-dose X-ray backscatter imagery.

While recent years have seen considerable progress in image denoising, the leading techniques have been developed for digital photographs or other images that can have very different characteristics than those encountered in X-ray applications. In particular here we examine X-ray backscatter (XBS) images collected by airport security systems, where images are piecewise smooth and edge information is typically more correlated with objects while texture is dominated by statistical noise in the detected signal. In this paper, we show how multiple estimates for a denoised XBS image can be combined using a variational approach, giving a solution that enhances edge contrast by trading off gradient penalties against data fidelity terms. We demonstrate the approach by combining several estimates made using the non-local means (NLM) algorithm, a widely used patch-based denoising method. The resulting improvements hold the potential for improving automated analysis of low-SNR X-ray imagery and can be applied in other applications where edge information is of interest.

Simulation of defect detection for the buried petroleum pipe by the X-ray backscatter imaging.

Ensuring the integrity, safety, and compliance of oil pipelines is crucial for operators. Two significant factors affecting pipeline integrity are metal loss due to corrosion or air gouging and the presence of cracks. This paper introduces an X-ray backscatter nondestructive testing model on a smart pig(an intelligent robot) for internal inspection of petroleum pipelines. The paper investigates the X-ray source and detection system, essential components of the backscatter imaging technology, to provide technical guidance for model design. The imaging system's layout is modeled using GEANT4, and its performance in detecting defects of various formats on pipe walls is studied. The research demonstrates the feasibility of using X-ray backscatter imaging for pipeline inspection and provides insights into different defect detection. The findings contribute to designing and optimizing the robot's scanning head for effective pipeline inspection.