Estimation of Position and Size of a Contaminant in Aluminum Casting Using a Thin-Film Magnetic Sensor

Advanced manufacturing processes require an in-line full inspection system. A nondestructive inspection system able to detect a contaminant such as tool chipping was utilized for the purpose of detecting a defective product as well as damaged machine tools used to fabricate the product. In a previous study, a system able to detect magnetic tool steel chipping in conductive material such as aluminum was developed and tested. In this study, a method of position and size estimation for magnetic chipping was investigated and is described. An experimental confirmation of the proposed method was also carried out using an actual prototype system.

Image Preprocessing Method in Radiographic Inspection for Automatic Detection of Ship Welding Defects

Welding defects must be inspected to verify that the welds meet the requirements of ship welded joints, and in welding defect inspection, among nondestructive inspections, radiographic inspection is widely applied during the production process. To perform nondestructive inspection, the completed weldment must be transported to the nondestructive inspection station, which is expensive; consequently, automation of welding defect detection is required. Recently, at several processing sites of companies, continuous attempts are being made to combine deep learning to detect defects more accurately. Preprocessing for welding defects in radiographic inspection images should be prioritized to automatically detect welding defects using deep learning during radiographic nondestructive inspection. In this study, by analyzing the pixel values, we developed an image preprocessing method that can integrate the defect features. After maximizing the contrast between the defect and background in radiographic through CLAHE (contrast-limited adaptive histogram equalization), denoising (noise removal), thresholding (threshold processing), and concatenation were sequentially performed. The improvement in detection performance due to preprocessing was verified by comparing the results of the application of the algorithm on raw images, typical preprocessed images, and preprocessed images. The mAP for the training data and test data was 84.9% and 51.2% for the preprocessed image learning model, whereas 82.0% and 43.5% for the typical preprocessed image learning model and 78.0%, 40.8% for the raw image learning model. Object detection algorithm technology is developed every year, and the mAP is improving by approximately 3% to 10%. This study achieved a comparable performance improvement by only preprocessing with data.

On the assessment of non-metallic inclusions by part 13 of API 579 -1/ASME FFS-1 2016

Improvement of nondestructive inspection techniques has allowed more frequent detection of closely spaced zones of non-metallic inclusions in pressure vessels made of low carbon steel. In the present study, closely spaced inclusions in an in-service cylindrical horizontal pressure vessel were detected by Scan-C ultrasonic inspection and considered as laminations to be assessed by Part 13 of the API 579-1/ASME FFS-1 2016 standard. The outcoming results were considered as a rejection for Level 1 assessment, and a repair or replacement of the component was required, even though it retained a significant remaining strength. Thus, an alternative procedure to assess the mechanical integrity of pressure vessels containing zones of non-metallic inclusions is proposed by adopting some criteria of the API 579-1/ASME FFS-1 Part 13 standard procedure and taking into consideration the dimensions and grouping characteristics of the inclusion zones.

Failures Related to Welding

This article describes some of the welding discontinuities and flaws characterized by nondestructive examinations. It focuses on nondestructive inspection methods used in the welding industry. The sources of weld discontinuities and defects as they relate to service failures or rejection in new construction inspection are also discussed. The article discusses the types of base metal cracks and metallurgical weld cracking. The article discusses the processes involved in the analysis of in-service weld failures. It briefly reviews the general types of process-related discontinuities of arc welds. Mechanical and environmental failure origins related to other types of welding processes are also described. The article explains the cause and effects of process-related discontinuities including weld porosity, inclusions, incomplete fusion, and incomplete penetration. Different fitness-for-service assessment methodologies for calculating allowable or critical flaw sizes are also discussed.

Technological life increase of ICE piston rings

The problems of nondestructive inspection method use for piston rings of internal combustion engines of exoelectronic emission are considered. The ties of this parameter with the methods and conditions of piston ring machining are defined and on this basis there are given recommendations for the optimization of an operation technology of their manufacturing.

High-Speed Time- and Frequency-Domain Terahertz Tomography of Glass-Fiber-Reinforced Polymer Laminates with Internal Defects

Composite materials are increasingly being utilized in many products, such as aircrafts, wind blades, etc. Accordingly, the need for nondestructive inspection of composite materials is increasing and technologies that allow nondestructive inspection are being studied. Existing ultrasound methods are limited in their ability to detect defects due to high attenuation in composite materials, and radiographic examination methods could pose a danger to human health. Terahertz (THz) wave technology is an emerging approach that is useful for imaging of concealed objects or internal structures due to high transmittance in non-conductive materials, straightness, and safety to human health. Using high-speed THz tomography systems that we developed, we have obtained THz tomographic images of glass-fiber-reinforced polymer (GFRP) laminates with artificial internal defects such as delamination and inclusion. The defects have various thicknesses and sizes, and lie at different depths. We present THz tomographic images of GFRP samples to demonstrate the extent to which the defects can be detected with the THz tomography systems.