Camera-based spatter detection in laser welding with a deep learning approach

Laser welding, semantic segmentation, u-net, quality assurance, spatter detectio

Automatic Compensation of Workpiece Positioning Tolerances for Precise Laser

Precise laser welding plays a fundamental role in the production of high-tech goods, particularly in precision engineering. In this working field, precise adjustment and compensation of positioning tolerances of the parts to be welded with respect to the laser beam is of paramount importance. This procedure mostly requires tedious and error-prone manual adjustment, which additionally results in a sharp increase in production costs. We therefore developed a system which automates and thus accelerates this procedure significantly. To this end, the welding machine is equipped with a camera to acquire high resolution images of the parts to be welded. In addition, a software framework is developed which enables precise automatic position detection of these parts and adjusts the position of the welding contour correspondingly. As a result, the machine is rapidly prepared for welding, and it is much more flexible in adapting to unknown parts.This paper describes the entire concept of extending a conventional welding machine with means for image acquisition and position estimation. In addition to this description, the algorithms, the results of an evaluation of position estimation, and a final welding result are presented.

Time Series Analysis and Classification with State-Space Models for Industrial Processes and the Life Sciences

In this thesis the use of state-space models for analysis and classification of time series data, gathered from industrial manufacturing processes and the life sciences, is investigated. To overcome hitherto unsolved problems in both application domains the temporal behavior of the data is captured using state-space models. Industrial laser welding processes are monitored with a high speed camera and the appearance of unusual events in the image sequences correlates with errors on the produced part. Thus, novel classification frameworks are developed to robustly detect these unusual events with a small false positive rate. For classifier learning, class labels are by default only available for the complete image sequence, since scanning the sequences for anomalies is expensive. The first framework combines appearance based features and state-space models for the unusual event detection in image sequences. For the first time, ideas adapted from face recognition are used for the automatic dimension reduction of images recorded from laser welding processes. The state-space model is trained incrementally and can learn from erroneous sequences without the need of manually labeling the position of the error event within sequences. %The limitation to weakly labeled data helps to reduce the labeling effort. In addition, a second framework for the object-based detection of sputter events in laser welding processes is developed. The framework successfully combines for the first time temporal change detection, object tracking and trajectory classification for the detection of weak sputter events. %This is the first time that object tracking is successfully applied to automatic sputter detection. For the application in the life sciences the improvement and further development of data analysis methods for Single Molecule Fluorescence Spectroscopy (SMFS) is considered. SMFS experiments allow to study biochemical processes on a single molecule basis. The single molecule is excited with a laser and the photons which are emitted thereon by fluorescence contain important information about conformational changes of the molecule. Advanced statistical analysis techniques are necessary to infer state changes of the molecule from changes in the photon emissions. By using state-space models, it is possible to extract information from recorded photon streams which would be lost with traditional analysis techniques

Study on fibre optic sensors embedded into metallic structures by selective laser melting

Additive Manufacturing, which builds components layer by layer, opens up exciting possibilities to integrate sophisticated internal features and functionalities such as fibre optic sensors directly into the heart of a metal component. This can create truly smart structures for deployment in harsh environments. The innovative and multidisciplinary study conducted in this thesis demonstrates the feasibility to integrate fibre optics sensors with thin, protective nickel coatings (outer diameter ~350 μm) into stainless steel (SS 316) coupons by Selective Laser Melting technology (SLM). Different concepts for fibre embedment by SLM are investigated. The concepts differ in which way the fibre is positioned and how the powder is deposited and solidified by the laser in respect to the optical fibre. Only one approach is found suitable to reliably and repeatable encapsulate fibres whilst preserving their structural integrity and optical properties. In that approach SS 316 components are manufactured using SLM, incorporating U-shaped grooves with dimensions suitable to hold nickel coated optical fibres. Coated optical fibres containing Fibre Bragg Gratings (FBG) for strain and temperature sensing are placed in the groove. Melting subsequent powder layers on top of the FBGs fuses the fibre’s metallic jacket to the steel and completes the integration of the fibre sensor into the steel structure. Cross-sectional microscopy analysis of the fabricated components, together with analysis of fibre optic sensors’ behaviour during fabrication, indicates proper stress and strain transfer between coated fibre and added SS 316 material. During the SLM process embedded Fibre Bragg grating (FBG) sensors provide in-situ temperature measurements and potentially allow measuring the build-up of residual stresses. Subsequently, FBG sensors embedded into SS 316 structures using our approach follow elastic and plastic deformations of the SS 316 component, with a resolution of better than 3 pm*μɛ-1. Temperature measurements are also conducted with a precision of 3 pm*K-1. Such embedded fibre sensors can also be used to high temperatures of up to ~400 °C. However, at elevated temperatures issues arise from the significantly larger thermal expansion coefficient of SS 316, leading to delamination of the more rapidly expanding metal from the glass. Rapid thermal expansion of the metal also leads to high axial stresses within the glass exceeding the fibres tensile strength and ultimately leading to structural damage of the optical fibre

Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation and Experimentation

Among the many additive manufacturing (AM) processes for metallic materials, selective laser melting (SLM) is arguably the most versatile in terms of its potential to realize complex geometries along with tailored microstructure. However, the complexity of the SLM process, and the need for predictive relation of powder and process parameters to the part properties, demands further development of computational and experimental methods. This review addresses the fundamental physical phenomena of SLM, with a special emphasis on the associated thermal behavior. Simulation and experimental methods are discussed according to three primary categories. First, macroscopic approaches aim to answer questions at the component level and consider for example the determination of residual stresses or dimensional distortion effects prevalent in SLM. Second, mesoscopic approaches focus on the detection of defects such as excessive surface roughness, residual porosity or inclusions that occur at the mesoscopic length scale of individual powder particles. Third, microscopic approaches investigate the metallurgical microstructure evolution resulting from the high temperature gradients and extreme heating and cooling rates induced by the SLM process. Consideration of physical phenomena on all of these three length scales is mandatory to establish the understanding needed to realize high part quality in many applications, and to fully exploit the potential of SLM and related metal AM processes

Materials Science and Technology

Materials are important to mankind because of the benefits that can be derived from the manipulation of their properties, for example electrical conductivity, dielectric constant, magnetization, optical transmittance, strength and toughness. Materials science is a broad field and can be considered to be an interdisciplinary area. Included within it are the studies of the structure and properties of any material, the creation of new types of materials, and the manipulation of a material's properties to suit the needs of a specific application. The contributors of the chapters in this book have various areas of expertise. therefore this book is interdisciplinary and is written for readers with backgrounds in physical science. The book consists of fourteen chapters that have been divided into four sections. Section one includes five chapters on advanced materials and processing. Section two includes two chapters on bio-materials which deal with the preparation and modification of new types of bio-materials. Section three consists of three chapters on nanomaterials, specifically the study of carbon nanotubes, nano-machining, and nanoparticles. Section four includes four chapters on optical materials

George C. Marshall Space Flight Center Research and Technology Report 2014

Many of NASA's missions would not be possible if it were not for the investments made in research advancements and technology development efforts. The technologies developed at Marshall Space Flight Center contribute to NASA's strategic array of missions through technology development and accomplishments. The scientists, researchers, and technologists of Marshall Space Flight Center who are working these enabling technology efforts are facilitating NASA's ability to fulfill the ambitious goals of innovation, exploration, and discovery

An open-architecture laser powder bed fusion system and its use for in-situ process measurements

Design and development of an open-architecture laser powder bed fusion (LPBF) system for in-situ process measurements of the build process during additive manufacture is described. The aim of this work is to create new knowledge and contribute towards further understanding of complex laser powder interaction through in-situ process monitoring. The designed system is sufficiently automated to enable single tracks and high density multiple layer components to be built. It is easily transportable to enable measurements at different measurement facilities and its modular design enables straightforward modification for specific measurements to be made. The system produces components with >99% density, hence, the build conditions are representative to observe process fundamentals and to develop process control strategies. Open-architecture design enabled access to the build area allowing a range of insitu measurements such as high energy flash x-ray imaging, camera-based high-speed imaging, schlieren imaging and temperature measurements. High speed imaging of the LPBF process results reveal that the process is more dynamic than is generally appreciated and can involve considerable motion of powder particles and agglomerates in and above the powder bed. Many critical process regimes were observed for the first time, such as changes in inclination of the laser with varying power and scan speed; and denudation became less severe with respects to an increase in layer number. Schlieren imaging results enabled the visualisation of the argon gas flow and laser plume propagation in the atmosphere above the powder bed. In-situ monitoring has been extended to study the effect of ambient pressures from a high vacuum to 5 bar positive pressure on the LPBF. Considerable disruption to the powder bed is observed at pressures below 20 mbar. As the pressure decreases, the expansion of the laser plume prevents particles reaching the melt pool: profiles and crosssections of the track reveal a drastic reduction in its cross-sectional area. At above atmospheric pressure, argon (up to 5 bar), the process was further disrupted by severe plasma formation along with an increase in size and number of spatter. The particle entrainment and resulting denudation was reduced, and single-track continuity was enhanced. In further study, it has been found that helium, used as shielding gas at higher pressure, mitigates negative effects of argon; generates smooth and uniform tracks and islands. The smoothness and continuity of built layers at 5 bar in helium was comparable to argon at atmospheric pressure, with considerable increase in scan speed.School of Engineering and Physical Sciences - James Watt Scholarshi