This paper suggests a new short wave infrared (SWIR)-imaging technique which can overcome these limitations. In addition to a two dimensional (2D) SWIR camera, the system also comprises a 2D visible light camera, an Inertial Measurement Unit (IMU), and global positioning system (GPS) to accurately determine the location of the leak using image correlation and triangulation techniques. The paper also suggests a low cost experimental setup used to assess the performance of the system to accurately quantify and localize CH4 gas leak. An Artificial Neural Network (ANN), was assessed using this setup. Series of extensive experimental tests demonstrate the capability of the system to detect, quantify, and localize CH4 gas leak for different scenarios. The corresponding results reveal that the ANN algorithm yields accurate results for gas mass leak measurement and localization using a SWIR optical filter. Uncertainties of gas mass leak flow measurement did not exceed 2.1% and 3.76% using a SWIR LED source with and without a SWIR filter respectively. This leads to state that the suggested system can be a tangible alternative for next generation leak detection systems.
In oil and gas fields, gas leakage is one of the major concerns, as it causes serious economical, safety, and health consequences. This requires a frequent and periodic inspections of all equipment which either store or transport gases, such as gas pipelines and gas storage tanks. In this paper, a real-time leak detection and localization system which can operate fully autonomously either in a drone or a mobile robot is suggested. The apparatus has the advantage of remotely detecting leaks even in case of humid weather, situation for which most recent leak detection systems such as Long wave Infrared (LWIR) and Medium wave IR (MWIR) fail. The system consists of a Short wave IR (SWIR) camera to remotely detect the existing of leaks even in case of humid weather or during the rain. In addition, the system is not sensitive to thermal radiations which is the case of LWIR and MIIR radiations. A CCD camera, together with a set of sensors that include an Inertial Measurement Unit (IMU) and global positioning system (GPS) are used to accurately determine the location of the leak using image correlation and triangulation techniques. A series of extensive experimental tests demonstrate the capability of the system to detect different types of gas leaks for different scenarios. This leads to state that the suggested system can be a tangible alternative for next generation leak detection systems.
Measuring in real-time two phase flow composition of a mixed fluid having high gas void fraction (GVF) remains a challenging task in oil-gas fields. Such fluid is abundant in gas pipelines where pressure and temperature fluctuations lead to condensate gas. This may also be the case of crude oil produced from CO2 or steambased enhanced oil recovery (EOR); where the injected gas is mixed with the produced oil. This paper presents a new concept of high GVF measurement using a Terahertz-based imaging system. It explores the fact the gas phase has very low absorption of THz waves, while it yields an absorption factor that is proportional to the amount of liquid. The recent availability of low cost THz imaging systems that can generate two dimensional (2D) images at more than 100 frames/seconds make them well suitable for flow metering applications. Two different Artificial Intelligence (AI) algorithms, namely Support Vector Machine (SVM) and Artificial Neural Network (ANN), were assessed using an inhouse multiphase flow loop. The corresponding results reveal that while ANN and SVM yield very accurate results, the SVM technique performed slightly better where a maximal error of 0.46 % for GVF in the GVF range from 80 to 100% could be achieved. This suggests that the technique can be considered as a good candidate for next generation flow metering and imaging of multiphase flows.
In this paper, a real-time perception system for autonomous car is presented. It is based on a highly parallel architecture using state of the art Field Programmable Gate Array (FPGA) to perform both low and intermediary levels image processing tasks at video frame rate (i.e. 30 frames / s). The hardware algorithm consists to perform noise removal and edge detection, followed by Hough transform task to extract the segments corresponding the lanes boundaries. The rich hardware resources which are available in nowadays FPGAs (e.g. large built-in distributed RAM memories, DSP blocks, and reconfigurable PLLs) yielded for a compact and low power consumption real-time vision system. Series of tests on different roads within Abu Dhabi city were successfully conducted for different scenarios such as continues lines, discontinues lines and slightly curved lines for which the car speed reached up to 122 km/h.
In this paper, submillimeter three dimensional tomography imaging of paramagnetic contaminants flow rate in multiphase flow pipelines is presented. The device, which is based on Magnetic Particle Imaging (MPI), consists of an array of twelve coils and a pair of permanent magnets and is not influenced with the other phases that constitute the crude oil (e.g. oil, water, sand, and gas) and which are mainly diamagnetic materials. The concentration of the paramagnetic particles can be measured in a three dimensional volumetric space with high spatial and temporal sensitivities which are proportional to the strength of the applied magnetic field. This is also influenced by the size and distribution of the particles and the anisotropy of the permanent magnet. To increase the sensitivity and improve the spatioencoding field, a two dimensional Linear Field Scanning (LFS) technique coupled with a two dimensional excitation field is proposed. The results demonstrate that the technique would constitute a breakthrough in the area of solid flow measurements and imaging.
In this paper, near infrared-based technique of oil-water mixture for water-cut measurement using neural network technique is presented. It uses a multivariate (MDA) algorithm which comprises the Partial least Square regression (PLS), Polynomial PLS, and an Artificial Neural Network (ANN) for spectrum analysis. The NIR spectra is postprocessed using the principal component analysis (PCA).Experimental results indicate that an accurate water-cut measurement can be achieved with less than 0.5% error in the range of [90 to 100%] water-cut. This interesting result, in addition to the fact that the NIR array device is non-invasive, non-intrusive and can be easily inserted into deep oil wells using optical fiber would lead to concluded that near-infrared spectroscopy can be a good candidate for downhole accurate water-cut measurement.
In this paper, a new innovative closed-loop and autonomous electronic device for oil-water separation in the
emulsion layer is presented. The device is designed for crude oil separation tanks and is sought to replace
other traditional methods such as the ones using chemicals. It is modular and comprises three subsystems:
sensing subsystem, actuating subsystem, and data communication/interfacing subsystem. The sensing
subsystem is intrinsically safe and consists of a one dimensional level array of non intrusive ultrasonic
transducers that monitor in real-time the low and high levels of the emulsion layer in a tank with a vertical
resolution of 15 cm. The actuating system includes a microwave generator which stimulates the emulsion at a
predefined position to breaks it out. A built-in feedback PID-based controller determines the optimal position
of this generator based on the oil-water content which is provided by the sensor array and moves the
generator accordingly. The data communication/interfacing system is responsible to transfer to the control
room real-time data (e.g. the actual position of the emulsion layer and the actual temperature inside the tank)
using field bus network protocol (RS485 protocol). This would help a continuous and effective monitoring by
the operator using a dedicated GUI. In addition of being safe and environmentally friendly, the device
provides faster and more efficient separation than the traditional techniques.
KEYWORDS: Digital filtering, Edge detection, Field programmable gate arrays, Image processing, Detection and tracking algorithms, Image segmentation, Video, Filtering (signal processing), Image processing algorithms and systems, Digital signal processing
Currently, in image processing, segmentation algorithms comprise between real time video rate processing and accurate results. In this paper, we present an efficient and not recursive algorithm filter originated from Deriche filter. This algorithm is implemented in hardware by using FPGA technology. Thus, it permits video rate edge detection. In addition, the FPGA board is used as an edge tracking accelerator, it allows us to greatly reduce execution time by avoiding scanning the whole image. We also present the architecture of our vision system dedicated to build 3D scene every 200 ms.
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