Khaled Al-Wahedi

A New Optical-Based Device for Online Black Powder Detection in Gas Pipelines

In this paper, an optical-based device for online black powder detection in gas pipelines is proposed. The device uses different optical wavelengths within the infrared (IR) range and applies chemometric algorithms to quantify the actual amount of black powder. Hence, three methods based on near-infrared (NIR), mid-infrared (MIR), and Raman spectroscopy are used to acquire various spectra. The principal component regression (PCR) and the partial least square regression (PLSR) algorithms are then applied to assess the capability of each of the three methods when black powder is subject to different environmental conditions that may occur in real-life fields. The experimental results indicated that the mean squared error of prediction for the PLSR is 0.0008731, 0.0001983, and 5.04e-5 for NIR, MIR, and Raman, respectively, while for the PCR it is 0.0009065, 0.0002068, and 5.099e-5. Also, the coefficient of determination (R2) for the PLSR was 0.9744, 0.9753, and 0.998199 for NIR, MIR, and Raman, respectively, while for the PCR it was 0.9743, 0.9744, and 0.998165. In addition, both PCR and PLSR completed the analysis very fast (in tens or hundreds of microseconds), however, PLSR accomplished the prediction analysis faster than PCR which serves as an advantage for online monitoring especially when multiprobes are used for the monitoring. Hence, while both PLSR and PCR perform equally well, the PLSR is even more robust since it can compensate for systematic and human errors more than PCR. The predictions from all three techniques (NIR, MIR, and Raman spectroscopy) were similarly good and no specific technique was superior to the others.

Microwave Sensing System for Real-Time Monitoring of Solid Contaminants in Gas Flows

The presence of undesired solid contaminants, such as black powder (BP), in natural gas flows diminishes the integrity of the pipeline network. The success of any efficient integrity management program applied to the affected pipeline requires real-time monitoring of the amount of BP traversing the given pipeline and its distribution in the network. In this paper, a new microwave-based system for real-time BP monitoring is introduced and its performance is thoroughly analyzed. The proposed system utilizes custom-designed hermetically sealed probe to interrogate the flow mixture with low-power microwaves in the industrial, scientific, and medical frequency band and monitors the signals reflected from the flow and transmitted through it. Based on extensive simulation and measurement results, it will be shown that the presence of the BP, even in small quantities within the flow, is manifested with considerable variations in the microwave transmission and reflection properties of the flow rendering high overall sensor detection sensitivity and specificity. Experimentally, it will be shown that the developed system can detect flowing BP as well as other contaminants, such as sand, in subgram quantities within 101 mm-ID pipe while utilizing simple detection scheme.

A Near-Infrared-Based Magnetic Induction Tomography Solution to Improve the Image Reconstruction Accuracy in Opaque Environments

In this paper, we propose a new magnetic induction tomography (MIT) system which uses, in addition to the set of magnetic coils, some infrared launch-detector fibers surrounding the cross-sectional image plane. The system is used to reconstruct the interior conductivity distribution of the body and to enhance the accuracy of images obtained by a single MIT. A constrained Landweber algorithm is proposed for image reconstruction. It uses both the boundary data obtained from the coils, and the foreground-background fractions at some neighboring elements of the mesh obtained using the infrared fibers. The effectiveness of the proposed method is demonstrated by numerical data generated for some circular phantoms. Comparisons, in terms of several metrics, between the reconstructed images obtained using the new method and a conventional MIT based on Landweber reconstruction clearly show the outperformance of the method.

WiFi based communication and localization of an autonomous mobile robot for refinery inspection

Oil and gas refineries can be a dangerous environment for numerous reasons, including heat, toxic gasses, and unexpected catastrophic failures. In order to augment how human operators interact with this environment, a mobile robotic platform is developed. This paper focuses on the use of WiFi for communicating with and localizing the robot. More specifically, algorithms are developed and tested to minimize the total number of WiFi access points (APs) and their locations in any given environment while taking into consideration the throughput requirements and the need to ensure every location in the region can reach at least k APs. When multiple WiFi APs are close together, there is a potential for interference. A graph-coloring heuristic is used to determine AP channel allocation. In addition, WiFi fingerprinting based localization is developed. All the algorithms implemented are tested in real world scenarios with the robot developed and results are promising.

Development of an Oil and Gas Refinery Inspection Robot

Oil and gas refineries present challenging environments in which to work and operate, especially in places like the Middle East where temperatures can reach 50 C and sand storms which can reduce visibility to a few meters. In addition, there can be gas or steam leaks which present health and safety hazards to the workers. At present, continuous operation of these plants requires that human workers venture out into these conditions in order to observe and report on the conditions within the plant. The goal of this work is to design, fabricate, assemble, and test an inspection robot in an effort to reduce the exposure and risks to human operators while increasing the flexibility and range of remote observations provided by a mobile robot. In this paper, we will report on the design approach taken, the subsystems identified and developed, the software environment chosen, and the application tasks envisioned. We will also report on the challenges of developing a robust localization algorithm for use in the challenging environment of a refinery as well as the needs for robust wireless communications in order to maintain command and control from the operators control room. An overview of the fivedegree-of-freedom arm designed and fabricated, and its realtime control will also be presented. Results from GPS navigation and localization experiments will be presented. While average errors during parked operations were often less than one meter for the WAAS enabled GPS system, locational errors during dynamic operations were often more than three meters. This is due to multi-path signals near building structures and piping infrastructure. Real-time arm control has been implemented using FPGAs and while tuning presented some challenge, the FPGA has provided smooth and repeatable operation. Sensors include gas detectors, acoustic sensors, thermal imaging, and video camera streaming. In addition, we will report on a multi-faceted approach to localization using three different sensor technologies and integrated using a Kalman filter. NOMENCLATURE DOF Degrees-of-Freedom GPS Global Positioning System FPGA Field Programmable Gate Array PWM Pulse Width Modulation

Optimal design of cascaded control scheme for PV system using BFO algorithm

In this paper presents Bacteria Foraging Optimization (BFO) algorithm based approach to find the optimum design values for the Proportional-Integral (PI) Controllers in cascaded structure is presented. Tuning the values of four PI controllers is very complex when the system is difficult to express in terms of mathematical model due to system nonlinearity. Response surface methodology (RSM) is used to formulate a mathematical design which is required to apply optimization algorithm. To examine the performance of BFO algorithm in obtaining optimum values of multiple PI controllers, a grid connected Photovoltaic (PV) system is chosen. Transient performance of the PI controller with optimum design values is evaluated under grid fault conditions. The system is simulated using PSCAD/EMTDC. Simulation results have shown the validity of the optimal design values obtained from RSM-BFO approach under different disturbances and system parameter variations.

Cost Based Navigation for Autonomous Vacuum Cleaners

In this paper, the Autonomous Vacuum Cleaner Navigation Problem is defined, formulated, and a solution is provided. In the design of an Autonomous Vacuum Cleaner (AVC), the most critical aspect is its navigation. An AVC is required to sweep the whole environment in order to clean it, and hence, this problem belongs to a category of problems known as Coverage Problems.

Laser-based gap finding approach to mobile robot navigation

In this paper, a real-time laser based gap finding obstacle avoidance algorithm is presented. This algorithm layers on top of a global planner to maintain the overall goal of a given task. In the presence of an unknown obstacle, the algorithm computes a trajectory toward a gap that is wide enough and is closest to the path pre-planned by the global planner. In order to achieve this result, a four-stage process is executed sequentially namely: data classification, obstacle detection, collision avoidance, and online trajectory generation. During these stages, the algorithm classifies the environment into free space and obstacle regions, adjusts the vehicle velocity as a function of surrounding obstacles proximity, makes a decision to avoid the obstacles and then execute a new trajectory. This trajectory can either be an offset from the original path or a normal path to the best gap depending on the size of the free space, width of the robot and the allowable clearance from obstacles. Experiments show that this approach can avoid obstacles efficiently and effectively achieve the overall goal.

RF Sensor for Material Delivery Monitoring in Powder Feeding Systems

Precise dielectric powder delivery is the key objective in feeding systems, such as the ones used in thermal spraying, additive manufacturing, conveying systems, and alike. In particular, the accuracy of the feeding system is determined by the accuracy of the material sensing element. Conventionally, loss-in-weight methods applied to main material storage have been used to measure the amount of material deposited into the process. This paper investigates a new sensing method devised to measure the amount of powder deposited into a flow with high resolution and accuracy. The proposed method is based on the interaction of electric field, produced within a radio-frequency resonator with the geometrical and dielectric properties of the material filling the resonator. Fundamentally, the amount of material present at any time during the feeding process is related to the resonant frequency shift of the resonator. Based on extensive numerical simulation and experimental results, it will be shown that the proposed method exhibits high agility in measuring solid material, such as sand, in sub-gram quantities.