Thick Section Laser Beam Welding of Structural Steels: Methods for Improving Welding Efficiency

Laser beam welding (LBW) is applicable for a wide range of industrial sectors and has a history of fifty years. However, it is considered an unusual method with applications typically limited to welding of thin sheet metal. With a new generation of high power lasers there has been a renewed interest in thick section LBW (also known as keyhole laser welding). There was a growing body of publications during 2001-2011 that indicates an increasing interest in laser welding for many industrial applications, and in last ten years, an increasing number of studies have examined the ways to increase the efficiency of the process. Expanding the thickness range and efficiency of LBW makes the process a possibility for industrial applications dealing with thick metal welding: shipbuilding, offshore structures, pipelines, power plants and other industries. The advantages provided by LBW, such as high process speed, high productivity, and low heat input, may revolutionize these industries and significantly reduce the process costs. The research to date has focused on either increasing the efficiency via optimizing process parameters, or on the process fundamentals, rather than on process and workpiece modifications. The argument of this thesis is that the efficiency of the laser beam process can be increased in a straightforward way in the workshop conditions. Throughout this dissertation, the term “efficiency” is used to refer to welding process efficiency, specifically, an increase in efficiency refers an increase in weld’s penetration depth without increasing laser power level or decreasing welding speed. These methods are: modifications of the workpiece – edge surface roughness and air gap between the joining plates; modification of the ambient conditions – local reduction of the pressure in the welding zone; modification of the welding process – preheating of the welding zone. Approaches to improve the efficiency are analyzed and compared both separately and combined. These experimentally proven methods confirm previous findings and contribute additional evidence which expand the opportunities for laser beam welding applications. The focus of this research was primarily on the effects of edge surface roughness preparation and pre-set air gap between the plates on weld quality and penetration depth. To date, there has been no reliable evidence that such modifications of the workpiece give a positive effect on the welding efficiency. Other methods were tested in combination with the two methods mentioned above. The most promising - combining with reduced pressure method - resulted in at least 100% increase in efficiency. The results of this thesis support the idea that joining those methods in one modified process will provide the modern engineering with a sufficient tool for many novel applications with potential benefits to a range of industries.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.

Laser- plasma- hybridihitsauksen käytettävyys teollisuudessa

Hybridihitsaukseksi nimitetään yleensä hitsausprosesseja, joissa yhdistetään kaari- ja laserhitsauksen vahvuudet. Laser- MIG/MAG- prosessit ovat näistä selvästi yleisimpiä, mutta muillekin prosesseille on sovelluksia. Tässä kandidaatintyössä on arvioitu laser- plasma- hybridihitsausprosessin käytettävyyttä teollisuuden prosesseissa. Arviointi on tehty vertailevana kirjallisuustutkimuksena laser- plasma- hybridiprosessin, laserhitsauksen, sekä muiden laser- hybridihitsausprosessien kesken. Prosessien vertailun lisäksi työssä on käsitelty hybridihitsausprosessien parametrien valintaa ja laser- plasma- hybridiprosessin erityispiirteitä.

The tree we heard fall : analyzing the societal processes following focusing events

Fokuserande händelser är plötsliga, ovanliga och för med sig negativa konsekvenser för ett stort antal människor. Det handlar om det vi i vardagligt tal kallar kriser och katastrofer. En intensiv medierapportering i kombination med oroade medborgare gör att kriser och katastrofer är viktiga samhällspåfrestningar som beslutsfattare måste hantera. Syftet med avhandlingen är att öka förståelsen för hur fokuserande händelser påverkar samhälleliga processer. Avhandlingens två övergripande forskningsfrågor tar fasta på jämförelsen av olika typer av fokuserande händelser. För det första, skillnader i hur naturkatastrofer och katastrofer som tillkommit genom mänskligt handlade påverkar samhället, och för det andra, hur händelser med olika stark fokuseringskraft påverkar samhället. Medborgarreaktioner studeras i en experimentell laboratoriestudie, den mediala rapporteringen analyseras genom kvantitativ innehållsanalys av texter och bilder, och på den parlamentariska arenan analyseras riksdagsdebatten genom kvantitativ innehållsanalys. De temaområden som identifieras i den teoretiska referensramen ligger till grund för analysen och tar fasta på de känslor som händelsen ger upphov till, hur händelsen kontextualiseras (framing), skuldbeläggning samt möjliga lösningar som förs fram. Resultatet från studierna visar att skillnader mellan olika typer av händelser syns tydligast hos medborgare, uttryckt genom starkare emotionella reaktioner för händelser med stark fokusering, och på den mediala arenan, genom mer utrymme för dessa händelser. Då kriser och katastrofer med olika stark fokuseringskraft når riksdagen får de däremot ett relativt likadant mottagande. I jämförelsen mellan naturkatastrofer och människoskapade händelser visar resultaten att naturkatastrofer ofta diskuteras som specifika händelser, medan människoskapade händelser placeras i en bredare samhällelig kontext och diskuteras under längre tid. Avhandlingen bidrar till diskussionen om hur våra känslor och vår kognition samspelar i krissituationer. De omedvetna signaler som vår kropp ger oss gällande hur vi ska reagera på en farlig situation kan påverka om vi är rädda, oroliga eller till och med positivt inställda. I ljuset av de tre studierna är det tydligt att de emotionella reaktionerna minskar ju högre upp i den politiska processen vi kommer. Trots att medborgare och medier reagerar starkt är de emotionella reaktionerna på den politiska arenan relativt milda och skuldbeläggningen näst intill icke-existerande.

Real-time adaptive control of ultra-fast laser scribing process with spectrometer online monitoring

There exist several researches and applications about laser welding monitoring and parameter control but not a single one have been created for controlling of laser scribing processes. Laser scribing is considered to be very fast and accurate process and thus it would be necessary to develop accurate turning and monitoring system for such a process. This research focuses on finding out whether it would be possible to develop real-time adaptive control for ultra-fast laser scribing processes utilizing spectrometer online monitoring. The thesis accurately presents how control code for laser parameter tuning is developed using National Instrument's LabVIEW and how spectrometer is being utilized in online monitoring. Results are based on behavior of the control code and accuracy of the spectrometer monitoring when scribing different steel materials. Finally control code success is being evaluated and possible development ideas for future are presented.

Real-time monitoring of laser scribing process utilizing high-speed camera

Currently, laser scribing is growing material processing method in the industry. Benefits of laser scribing technology are studied for example for improving an efficiency of solar cells. Due high-quality requirement of the fast scribing process, it is important to monitor the process in real time for detecting possible defects during the process. However, there is a lack of studies of laser scribing real time monitoring. Commonly used monitoring methods developed for other laser processes such a laser welding, are sufficient slow and existed applications cannot be implemented in fast laser scribing monitoring. The aim of this thesis is to find a method for laser scribing monitoring with a high-speed camera and evaluate reliability and performance of the developed monitoring system with experiments. The laser used in experiments is an IPG ytterbium pulsed fiber laser with 20 W maximum average power and Scan head optics used in the laser is Scanlab’s Hurryscan 14 II with an f100 tele-centric lens. The camera was connected to laser scanner using camera adapter to follow the laser process. A powerful fully programmable industrial computer was chosen for executing image processing and analysis. Algorithms for defect analysis, which are based on particle analysis, were developed using LabVIEW system design software. The performance of the algorithms was analyzed by analyzing a non-moving image from the scribing line with resolution 960x20 pixel. As a result, the maximum analysis speed was 560 frames per second. Reliability of the algorithm was evaluated by imaging scribing path with a variable number of defects 2000 mm/s when the laser was turned off and image analysis speed was 430 frames per second. The experiment was successful and as a result, the algorithms detected all defects from the scribing path. The final monitoring experiment was performed during a laser process. However, it was challenging to get active laser illumination work with the laser scanner due physical dimensions of the laser lens and the scanner. For reliable error detection, the illumination system is needed to be replaced.