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Luis Volnei Sudati Sagrilo

Bio: Luis Volnei Sudati Sagrilo is an academic researcher from Federal University of Rio de Janeiro. The author has contributed to research in topics: Mooring & Extreme Response. The author has an hindex of 13, co-authored 84 publications receiving 726 citations.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors evaluated the use of artificial neural networks (ANNs) for pattern recognition of magnetic flux leakage (MFL) signals in weld joints of pipelines obtained by an intelligent pig.
Abstract: This work evaluates the use of artificial neural networks (ANNs) for pattern recognition of magnetic flux leakage (MFL) signals in weld joints of pipelines obtained by intelligent pig. Initially the ANNs were used to distinguish the pattern signals with non-defect (ND) and signals with defects (D) along of the weld bead. In the next step the ANNs were applied to classify signal patterns with three types of defects in the weld joint: external corrosion (EC), internal corrosion (IC) and lack of penetration (LP). The defects were intentionally inserted in the weld bead of a pipeline of API 5L-X65 steel with an outer diameter of 304.8 mm. In this way, the MFL signal itself, digitized with 1025 points, was used as the ANN input. Initially the signals were used as inputs for the neural network without any type of pre-processing, later four types of pre-processing were applied to the signals: Fourier analysis, Moving-average filter, Wavelet analysis and Savitzky–Golay filter. Signal processing techniques were employed to improve the performance of the neural networks in distinguishing between the defect classes. The results showed that it is possible to classify signals of classes D and ND using ANN with very efficient results (94.2%), as well as for corrosion (CO) and LP signals (92.5%). Also it is possible to classify the defect pattern signals: EC, IC and LP using neural networks with an average rate of success of 71.7% for the validation set.

129 citations

Journal ArticleDOI
TL;DR: In this paper, the reliability of non-destructive test (NDT) techniques for inspection of pipeline welds employed in the petroleum industry was evaluated, and the results showed the superiority of automatic ultrasonic tests for defect detection compared with the manual ultrasonic and radiographic tests.

93 citations

Journal ArticleDOI
TL;DR: In this article, a hybrid Artificial Neural Network (ANN) and finite element method (FEM) is used to perform a nonlinear mapping of the current and past system excitations (inputs) to produce subsequent system response (output) for the random dynamic analysis of mooring lines and risers.

75 citations

Journal ArticleDOI
TL;DR: In this paper, a linear single-degree-of-freedom (SDOF) system along with a bi-lognormal probability model for significant wave heights and zero-crossing wave periods have been used for numerical tests.

51 citations

Journal ArticleDOI
TL;DR: In this article, a reliability-based partial safety factor calibration study for a LRFD mooring line design criteria considering the three approaches mentioned above is presented, which is applied to three FPSOs considering North Sea environmental conditions and different water depths.

50 citations


Cited by
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Journal ArticleDOI
TL;DR: A review for application of robotics in onshore oil and gas industry and semi-autonomous robots, where actions are performed by robots but cognitive decisions are still taken by skilled operator are presented.

269 citations

Journal ArticleDOI
TL;DR: On the open hull, integrated acoustic and visual mapping processes to achieve closed-loop control relative to features such as weld-lines and biofouling are integrated, and new large-scale planning routines are implemented so as to achieve full imaging coverage of all the structures, at a high resolution.
Abstract: Inspection of ship hulls and marine structures using autonomous underwater vehicles has emerged as a unique and challenging application of robotics. The problem poses rich questions in physical design and operation, perception and navigation, and planning, driven by difficulties arising from the acoustic environment, poor water quality and the highly complex structures to be inspected. In this paper, we develop and apply algorithms for the central navigation and planning problems on ship hulls. These divide into two classes, suitable for the open, forward parts of a typical monohull, and for the complex areas around the shafting, propellers and rudders. On the open hull, we have integrated acoustic and visual mapping processes to achieve closed-loop control relative to features such as weld-lines and biofouling. In the complex area, we implemented new large-scale planning routines so as to achieve full imaging coverage of all the structures, at a high resolution. We demonstrate our approaches in recent op...

230 citations

Journal ArticleDOI
Yan Shi1, Chao Zhang1, Rui Li1, Rui Li2, Maolin Cai1, Guanwei Jia1 
10 Dec 2015-Sensors
TL;DR: The main principles, measurement and processing of MFL data, the identification of the leakage magnetic signal is discussed, and future developments in pipeline MFL detection are predicted.
Abstract: Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted.

227 citations

Journal ArticleDOI
TL;DR: A novel online bag-of-words measure for intra and interimage saliency are introduced and are shown to be useful for image key-frame selection, information-gain-based link hypothesis, and novelty detection.
Abstract: This paper reports a real-time monocular visual simultaneous localization and mapping (SLAM) algorithm and results for its application in the area of autonomous underwater ship hull inspection. The proposed algorithm overcomes some of the specific challenges associated with underwater visual SLAM, namely, limited field of view imagery and feature-poor regions. It does so by exploiting our SLAM navigation prior within the image registration pipeline and by being selective about which imagery is considered informative in terms of our visual SLAM map. A novel online bag-of-words measure for intra and interimage saliency are introduced and are shown to be useful for image key-frame selection, information-gain-based link hypothesis, and novelty detection. Results from three real-world hull inspection experiments evaluate the overall approach, including one survey comprising a 3.4-h/2.7-km-long trajectory.

219 citations

Book
01 Jan 1994
TL;DR: This document explains how to identify the different types of fonts used in the construction of font-magnifying lenses and how to select the correct ones for a given application.
Abstract: Note: Includes index + new features guide (1995) + quick reference Reference Record created on 2004-09-07, modified on 2016-08-08

189 citations