Welded steel in marine environment – Experimental and numerical study of mechanical properties degradation

Pastorcic, Darko; Vukelić, Goran; Ivošević, Špiro

doi:10.1016/j.mtcomm.2022.105280

Cited by 6 publications

(2 citation statements)

References 34 publications

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“…Now that the state-of-the-art principle of the IWS has been proven successful, the IWS can be used in more demanding applications with extended use of sensors. Furthermore, the understanding of the causality between the NN input and output parameters could be better visualized and clarified by using numerical modelling techniques [28][29][30]. A deeper analysis and understanding of the welding process itself could also help to decide the most beneficial sensors for each use case.…”

Section: Discussionmentioning

confidence: 99%

Possibilities of Artificial Intelligence-Enabled Feedback Control System in Robotized Gas Metal Arc Welding

Penttilä

Lund

Skriko

2023

JMMP

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In recent years, welding feedback control systems and weld quality estimation systems have been developed with the use of artificial intelligence to increase the quality consistency of robotic welding solutions. This paper introduces the utilization of an intelligent welding system (IWS) for feedback controlling the welding process. In this study, the GMAW process is controlled by a backpropagation neural network (NN). The feedback control of the welding process is controlled by the input parameters; root face and root gap, measured by a laser triangulation sensor. The NN is trained to adapt NN output parameters; wire feed and arc voltage override of the weld power source, in order to achieve consistent weld quality. The NN is trained offline with the specific parameter window in varying weld conditions, and the testing of the system is performed on separate specimens to evaluate the performance of the system. The butt-weld case is explained starting from the experimental setup to the training process of the IWS, optimization and operating principle. Furthermore, the method to create IWS for the welding process is explained. The results show that the developed IWS can adapt to the welding conditions of the seam and feedback control the welding process to achieve consistent weld quality outcomes. The method of using NN as a welding process parameter optimization tool was successful. The results of this paper indicate that an increased number of sensors could be applied to measure and control the welding process with the developed IWS.

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Section: Discussionmentioning

confidence: 99%

Possibilities of Artificial Intelligence-Enabled Feedback Control System in Robotized Gas Metal Arc Welding

Penttilä

Lund

Skriko

2023

JMMP

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“…Many studies selected optimal corrosion models and analyzed corrosion mechanisms, the intensity of influencing factors, different types of corrosion, corrosion rates and depths. There are a number of studies conducted in real conditions that examined the effect of corrosion on welded constructions (Pastorčić et al, 2023;Vukelić et al, 2022) or stainless steal in a simulated environment (Gudić et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Analyses of the Failures of Hull Structure Plating Caused by Corrosion

Ivošević,

Kovač

2023

Trans. Marit. Sci.

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There are a lot of different factors of hull structure degradation such as cracks, damage, fatigue or corrosion. Fatigue and corrosion were the most thoroughly examined in the previous studies. Corrosion is a more dominant form of degradation that causes the reduction of the original thickness of materials over time, which can be expressed through weight loss, in millimeter or percentage of thickness diminution of steel plates. Corrosion process can reduce carrying capacity and longitudinal strength of vessels, cause different types of failures or lead to the pollution of surrounding areas. This study analyzes the corrosion of a structural element of a fuel tank on the old bulk carrier that has been in operation for 25 years. The database consists of thickness measures expressed as percentage of diminution of the original plate thickness and the analysis of the chemical composition of a corroded and replaced steel plate. The study examined the total of 350 measured data after 5, 10, 15, 20 and 25 years of ship exploitation. Similarly, the research observed the chemical composition of the replaced steel plate. Linear corrosion models were developed while the chemical composition was analyzed by means of Energy Dispersive X-ray analysis of the samples from both sides of the corroded plate. The obtained results indicated that the degree of corrosion significantly varies depending on the environment of the plate. Furthermore, the formed linear corrosion model adequately follows the empirical data and value of 1,55 %/year.

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Effect of various rotational speeds on the inhomogeneous distribution of microstructure and toughness in friction stir weld joint of Q1100 ultra-high strength steel

Hu,

Wang,

Tao

et al. 2024

Weld World

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Welded steel in marine environment – Experimental and numerical study of mechanical properties degradation

Cited by 6 publications

References 34 publications

Possibilities of Artificial Intelligence-Enabled Feedback Control System in Robotized Gas Metal Arc Welding

Possibilities of Artificial Intelligence-Enabled Feedback Control System in Robotized Gas Metal Arc Welding

Analyses of the Failures of Hull Structure Plating Caused by Corrosion

Effect of various rotational speeds on the inhomogeneous distribution of microstructure and toughness in friction stir weld joint of Q1100 ultra-high strength steel

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