Teena Abbas Ali; Ahmed Mudheher Hasan
Volume 20, Issue 4 , October 2020, , Page 58-70
Abstract
Autonomous vehicle navigation has witnessed a huge revolutionary revision regarding development in Micro-Electro Mechanical System (MEMS) technology. Most recently, Strapdown Inertial Navigation System (SDINS) has successfully been integrated with Global Positioning System (GPS). However, different grades ...
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Autonomous vehicle navigation has witnessed a huge revolutionary revision regarding development in Micro-Electro Mechanical System (MEMS) technology. Most recently, Strapdown Inertial Navigation System (SDINS) has successfully been integrated with Global Positioning System (GPS). However, different grades of MEMS inertial sensors are available and choosing the convenient grade is quite important. Noises in inertial sensor are mostly treated through de-noising the additive errors to improve the precision of SDINS output. Unfortunately, integration in SDINS mechanization causes a growing in SDINS error output which considered the main challenge in integrating MEMS inertial sensors with GPS. This paper aims to promote the long-term performance of the MEMS-SDINS/GPS integrated system. A new integrated structure is proposed to model the nonlinearities that exist in SDINS dynamics in addition to the error uncertainty in the inertial sensors’ measurements. A robust Nonlinear AutoRegressive models with eXogenous inputs (NARX) based algorithm are designed for data fusion in the proposed GPS/INS integrated system. Validation for the proposed integrated system has been carried out using different field tests data in order to assess the accuracy of the system during GPS denied environment. The results obtained demonstrate that the proposed NARX model is applicative and satisfactory which shows a desired prediction performance.
Ahmed H. Hadi; Waleed F. Shareef
Volume 20, Issue 2 , April 2020, , Page 33-46
Abstract
Due to the recent advancements in the fields of Micro Electromechanical Sensors (MEMS), communication, and operating systems, wireless remote monitoring methods became easy to build and low cost option compared to the conventional methods such as wired cameras and vehicle patrols. Pipeline Monitoring ...
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Due to the recent advancements in the fields of Micro Electromechanical Sensors (MEMS), communication, and operating systems, wireless remote monitoring methods became easy to build and low cost option compared to the conventional methods such as wired cameras and vehicle patrols. Pipeline Monitoring Systems (PMS) benefit the most of such wireless remote monitoring since each pipeline would span for long distances up to hundreds of kilometers. However, precise monitoring requires moving large amounts of data between sensor nodes and base station for processing which require high bandwidth communication protocol. To overcome this problem, In-Situ processing can be practiced by processing the collected data locally at each node instead of the base station. This Paper presents the design and implementation of In-situ pipeline monitoring system for locating damaging activities based on wireless sensor network. The system built upon a WSN of several nodes. Each node contains high computational 1.2GHz Quad-Core ARM Cortex-A53 (64Bit) processor for In-Situ data processing and equipped in 3-axis accelerometer. The proposed system was tested on pipelines in Al-Mussaib gas turbine power plant. During test knocking events are applied at several distances relative to the nodes locations. Data collected at each node are filtered and processed locally in real time in each two adjacent nodes. The results of the estimation is then sent to the supervisor at base-station for display. The results show the proposed system ability to estimate the location of knocking event.
Nasheed F. Mossa; Waleed F. Shareef; Faez F. Shareef
Volume 18, Issue 2 , September 2018, , Page 53-62
Abstract
The oil export industry dominates the economy of the world and itdepends heavily on oil pipelines. Exposed pipelines are prone to malfunctioningdue to intentional or unintentional tampering and vandalism, which is usuallycaused by damaging form of either knocking or drilling. Continuous structurehealth ...
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The oil export industry dominates the economy of the world and itdepends heavily on oil pipelines. Exposed pipelines are prone to malfunctioningdue to intentional or unintentional tampering and vandalism, which is usuallycaused by damaging form of either knocking or drilling. Continuous structurehealth monitoring (SHM) of pipelines using conventional methods is difficultand expensive due to the extensive length of the pipelines and the harshenvironment. Recent development in printed electronic circuits andmicrocontrollers open new possibilities in the field of monitoring and haveproven their practicality in vibration monitoring process. This paper presents amonitoring system for pipeline heal of the structure based on the wirelesssensor network. The system senses the pipeline vibration and relays the data toa base station for the procession. A WSN consists of three nodes is designed andimplemented. Each node is built around 32-bit ARM core microcontroller, andequipped with an accelerometer to measure the pipeline vibration. Themeasurements of each sensor are collected wirelessly through ZigBee protocolto a base station. Results on a 2 m pipeline sample show the ability of thesystem to precisely detect damaging events e.g. knocking and drilling to thepipeline.
