Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

A team of researchers at Google's DeepMind Technologies has been working on a means to increase the capabilities of computers by combining aspects of data processing and artificial intelligence and have come up with what they are calling a differentiable neural computer (DNC.) In their paper published in the journal Nature, they describe the work they are doing and where they believe it is headed. To make the work more accessible to the public team members, Alexander Graves and Greg Wayne have posted an explanatory page on the DeepMind website. [13]

Convolutional Neural Network를 이용한 한국어 영화평 감성 분석

Advances, limitations and prospects of nondestructive testing and evaluation of thick composites and sandwich structures: A state-of-the-art review

Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms

Ultrasonic guided wave (UGW) is one of the most commonly used technologies for non-destructive evaluation (NDE) and structural health monitoring (SHM) of structural components. Because of its excellent long-range diagnostic capability, this method is effective in detecting cracks, material loss, and fatigue-based defects in isotropic and anisotropic structures. The shape and orientation of structural defects are critical parameters during the investigation of crack propagation, assessment of damage severity, and prediction of remaining useful life (RUL) of structures. These parameters become even more important in cases where the crack intensity is associated with the safety of men, environment, and material, such as ship’s hull, aero-structures, rail tracks and subsea pipelines. This paper reviews the research literature on UGWs and their application in defect diagnosis and health monitoring of metallic structures. It has been observed that no significant research work has been convened to identify the shape and orientation of defects in plate-like structures. We also propose an experimental research work assisted by numerical simulations to investigate the response of UGWs upon interaction with cracks in different shapes and orientations. A framework for an empirical model may be considered to determine these structural flaws.

Structural Health Monitoring (SHM) and Determination of Surface Defects in Large Metallic Structures using Ultrasonic Guided Waves.

Effective intelligent condition monitoring, as an effective technique to enhance the reliability of wind turbines and implement cost-effective maintenance, has been the object of extensive research and development to improve defect detection from supervisory control and data acquisition (SCADA) data, relying on perspective signal processing and statistical algorithms. The development of sophisticated machine learning now allows improvements in defect detection from historic data. This paper proposes a novel condition monitoring method for wind turbines based on Long Short-Term Memory (LSTM) algorithms. LSTM algorithms have the capability of capturing long-term dependencies hidden within a sequence of measurements, which can be exploited to increase the prediction accuracy. LSTM algorithms are therefore suitable for application in many diverse fields. The residual signal obtained by comparing the predicted values from a prediction model and the actual measurements from SCADA data can be used for condition monitoring. The effectiveness of the proposed method is validated in the case study. The proposed method can increase the economic benefits and reliability of wind farms.

https://www.mdpi.com/1996-1073/12/18/3411/pdf

A Novel Condition Monitoring Method of Wind Turbines Based on Long Short-Term Memory Neural Network

The application of the fundamental shear-horizontal wave mode for guided wave structural health monitoring is undoubtedly beneficial due to its nondispersive characteristics. Existing guided wave shear mode transducers are rigid and brittle, because of these characteristics, bonding them to irregular surfaces (i.e., curved surfaces) is challenging. There is a huge market interest in the development of a flexible shear mode transducer, which eases the transducer bonding process onto irregular surfaces and improves the surface contact between the transducer and the structure. This study presents a flexible shear mode transducer for structural health monitoring using low-frequency guided waves (20–120 kHz). The proposed transducer is manufactured using piezoceramic, and based on the results of this study, it exhibits the directional excitation of fundamental shear-horizontal mode at 20–120 kHz. Finite element analysis and laboratory experiments were conducted to study the behavior of the proposed transducer. Field trials were conducted on a liquid storage tank with an undulated surface (due to corrosion). The performance of the proposed transducer is also compared to the commercially available macro fiber composite transducers. The proposed transducer was driven by the industrialized ultrasonic guided wave inspection system; Teletest Focus+ in line with the application of tank floor inspection using ultrasonic guided waves.

/pdf/flexible-shear-mode-transducer-for-structural-health-4uqris4lxm.pdf

Flexible Shear Mode Transducer for Structural Health Monitoring Using Ultrasonic Guided Waves

There is an increasing interest in using ultrasonic guided waves to assess the structural degradation of above-ground storage tank floors. This is a non-invasive and economically viable means of assessing structural degradation. Above-ground storage tank floors are ageing assets which need to be inspected periodically to avoid structural failure. At present, normal-stress type transducers are bonded to the tank annular chime to generate a force field in the thickness direction of the floor and excite fundamental symmetric and asymmetric Lamb modes. However, the majority of above-ground storage tanks in use have no annular chime due to a simplified design and/or have a degraded chime due to corrosion. This means that transducers cannot be mounted on the chime to assess structural health according to the present technology, and the market share of structural health monitoring of above-ground storage tank floors using ultrasonic guided wave is thus limited. Therefore, the present study investigates the potential of using the tank wall to bond the transducer instead of the tank annular chime. Both normal and shear type transducers were investigated numerically, and results were validated using a 4.1 m diameter above-ground storage tank. The study results show shear mode type transducers bonded to the tank wall can be used to assess the structural health of the above-ground tank floors using an ultrasonic guided wave. It is also shown that for the cases studied there is a 7.4 dB signal-to-noise ratio improvement at 45 kHz for the guided wave excitation on the tank wall using shear mode transducers.

/pdf/structural-health-monitoring-of-above-ground-storage-tank-3jwzi87mks.pdf

Structural Health Monitoring of Above-Ground Storage Tank Floors by Ultrasonic Guided Wave Excitation on the Tank Wall.

The accumulation of fouling within a structure is a well-known and costly problem across many industries. The build-up is dependent on the environmental conditions surrounding the fouled structure. Many attempts have been made to detect fouling accumulation in critical engineering structures and to optimize the application of power ultrasonic fouling removal procedures, i.e., flow monitoring, ultrasonic guided waves and thermal imaging. In recent years, the use of ultrasonic guided waves has been identified as a promising technology to detect fouling deposition/growth. This technology also has the capability to assess structural health; an added value to the industry. The use of ultrasonic guided waves for structural health monitoring is established but fouling detection using ultrasonic guided waves is still in its infancy. The present study focuses on the characterization of fouling detection using ultrasonic guided waves. A 6.2-m long 6-inch schedule 40 carbon steel pipe has been used to study the effect of (Calcite) fouling on ultrasonic guided wave propagation within the structure. Parameters considered include frequency selection, number of cycles and dispersion at incremental fouling thickness. According to the studied conditions, a 0.5 dB/m drop in signal amplitude occurs for a fouling deposition of 1 mm. The findings demonstrate the potential to detect fouling build-up in lengthy pipes and to quantify its thickness by the reduction in amplitude found from further numerical investigation. This variable can be exploited to optimize the power ultrasonic fouling removal procedure.

/pdf/characterization-of-the-use-of-low-frequency-ultrasonic-2583810xvo.pdf

Characterization of the Use of Low Frequency Ultrasonic Guided Waves to Detect Fouling Deposition in Pipelines

Ultrasonic guided waves are widely used to inspect and monitor the structural integrity of plates and plate-like structures, such as ship hulls and large storage-tank floors. Recently, ultrasonic guided waves have also been used to remove ice and fouling from ship hulls, wind-turbine blades and aeroplane wings. In these applications, the strength of the sound source must be high for scanning a large area, or to break the bond between ice, fouling and plate substrate. More than one transducer may be used to achieve maximum sound power output. However, multiple sources can interact with each other, and form a sound field in the structure with local constructive and destructive regions. Destructive regions are weak regions and shall be avoided. When multiple transducers are used it is important that they are arranged in a particular way so that the desired wave modes can be excited to cover the whole structure. The objective of this paper is to provide a theoretical basis for generating particular wave mode patterns in finite-width rectangular plates whose length is assumed to be infinitely long with respect to its width and thickness. The wave modes have displacements in both width and thickness directions, and are thus different from the classical Lamb-type wave modes. A two-dimensional semi-analytical finite element (SAFE) method was used to study dispersion characteristics and mode shapes in the plate up to ultrasonic frequencies. The modal analysis provided information on the generation of modes suitable for a particular application. The number of point sources and direction of loading for the excitation of a few representative modes was investigated. Based on the SAFE analysis, a standard finite element modelling package, Abaqus, was used to excite the designed modes in a three-dimensional plate. The generated wave patterns in Abaqus were then compared with mode shapes predicted in the SAFE model. Good agreement was observed between the intended modes calculated in SAFE and the actual, excited modes in Abaqus.

Jamil Kanfoud

Papers

A Novel Condition Monitoring Method of Wind Turbines Based on Long Short-Term Memory Neural Network

Flexible Shear Mode Transducer for Structural Health Monitoring Using Ultrasonic Guided Waves

Structural Health Monitoring of Above-Ground Storage Tank Floors by Ultrasonic Guided Wave Excitation on the Tank Wall.

Characterization of the Use of Low Frequency Ultrasonic Guided Waves to Detect Fouling Deposition in Pipelines

A Numerical Study on the Excitation of Guided Waves in Rectangular Plates Using Multiple Point Sources