Application of robotics in offshore oil and gas industry- A review Part II

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...

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Advanced perception, navigation and planning for autonomous in-water ship hull inspection

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.

https://www.mdpi.com/1424-8220/15/12/29845/pdf

Theory and Application of Magnetic Flux Leakage Pipeline Detection

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.

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Real-Time Visual SLAM for Autonomous Underwater Hull Inspection Using Visual Saliency

Note: Includes index + new features guide (1995) + quick reference Reference Record created on 2004-09-07, modified on 2016-08-08

Signal processing toolbox for use with MATLAB : ユーザーズガイド

Time domain stochastic wave dynamic analyses of offshore structures are computationally expensive Considering the wave-induced fatigue assessment for such structures, the combination of many environmental loading cases and the need of long time-series responses make the computational cost even more critical In order to reduce the computational burden related to the wave-induced fatigue analysis of Steel Catenary Risers (SCRs), this work presents the application of a recently developed hybrid methodology that combines dynamic Finite Element Analysis (FEA) and Artificial Neural Networks (ANN) The methodology is named hybrid once it requires short time series of structure responses (obtained by FEA) and imposed motions (evaluated analytically) to train an ANN Subsequently, the ANN is employed to predict the remaining response time series using the prescribed motions imposed at the top of the structure by the floater unit In this particular work, the methodology is applied aiming to predict the tension and bending moments’ time series at structural elements located at the top region and at the touchdown zone (TDZ) of a metallic riser With the predicted responses (tensions and moments), the stress time series are determined for eight points along the pipe cross sections, and stress cycles are identified using a Rainflow algorithm Fatigue damage is then evaluated using SN curves and the Miner-Palmgren damage accumulation rule The methodology is applied to a SCR connected to a semisubmersible platform in a water depth of 910 m The obtained results are compared to those from a full FEA in order to evaluate the accuracy and computer efficiency of the hybrid methodology

/pdf/neural-networks-applied-to-the-wave-induced-fatigue-analysis-4ao5eu0knh.pdf

Neural Networks Applied to the Wave-Induced Fatigue Analysis of Steel Risers

Probability-based design of offshore structures usually require a joint distribution of significant wave heights and zero-up-crossing periods, or spectral peak periods, in order to describe the long-term wave scenario, and thus predict long-term extreme responses. Several joint statistical models have been proposed in the literature, often comprising environmental parameters aside from significant wave heights and zero-up-crossing or spectral peak periods, such as wind and current velocities, among others. However, since there is no theoretical environmental distribution function, the assessment of different models is done on an empirical basis for each available data set. The fitting of a joint distribution model on a set of long-term wave data, given the extensive number of available joint statistical models and the inherent extrapolations required for extreme conditions, can be extremely cumbersome. This paper proposes the application of Taylor diagram in the assessment of the fit of joint models. The aim is to find the models with the best performances through an easy and straightforward visual comparison. For simplification purposes, the joint statistical model considered comprises significant wave heights and spectral peak periods only. Results show that Taylor diagram is a useful tool for primarily evaluations of adjusted probability models. The indicatives for better model performances identified in the diagram were shown to correspond to other common identifiers, which demonstrates that the diagram can be a reliable indicator for good models. Some study cases are presented to demonstrate Taylor diagram application in joint probability distributions fittings for wave environmental parameters.

Application of Taylor diagram in the evaluation of joint environmental distributions' performances

One of the standardized procedures used in the design of floating systems and their mooring and production lines is the so-called short-term design approach where the system is analyzed for some specific extreme environmental conditions. Along with this procedure, a nonlinear time-domain coupled dynamic analysis, considering the floater and its risers and mooring lines, can nowadays be incorporated as a feasible part of the design practice. One very important and challenging aspect of this process is concerned with the estimation of the characteristic short-term extreme values of the system response parameters based on the sampled time-series. In this paper a common procedure used to establish these extreme values for floater system response parameters, which is based upon a Weibull distribution model for the peaks of the time-series, is reviewed in the light of a recently proposed approach based on a general parametric model for the average conditional exceedance rate of peaks. It is shown that the former model corresponds to a particular case of the latter one. Numerical results are presented for the response parameters of a turret-moored Floating, Production, Storage and Offloading (FPSO) unit considering a short-term coupled analysis of the whole system under an extreme environmental condition of wind, wave, and current. Specifically, the extreme response of surge motion, top tension of the most loaded mooring line, and Det norske Veritas (DnV) codes utilization factor for the most critical section of an 0.20 m outer diameter SLWR (steel lazy wave riser) are investigated.

Luis Volnei Sudati Sagrilo

Papers

Neural Networks Applied to the Wave-Induced Fatigue Analysis of Steel Risers

Application of Taylor diagram in the evaluation of joint environmental distributions' performances

On the Extreme Value Analysis of the Response of a Turret Moored FPSO

A modal finite element approach to predict the lateral buckling failure of the tensile armors in flexible pipes

Reliability-based design criterion for TLP tendons