Micro-Inertial-Aided High-Precision Positioning Method for Small-Diameter PIG Navigation

Pipeline leakage or explosion has caused huge economic losses, polluted the environments and threatened the safety of civilian’s lives and assets, which even caused negative influences to the society greatly. Fortunately, pipeline inspection gauge (PIG) could accomplish the pipeline defect (corrosions, cracks, grooves, etc.) inspection effectively and meanwhile to localize these defects precisely by navigation sensors. The results are utilized for pipeline integrity management (PIM) and pipeline geographic information system construction. Generally, the urban underground pipeline presents with small-diameter and complicated-distribution properties, which are of great challenges for the pipeline defects positioning by PIG. This chapter focuses on in-depth research of the high-precision positioning method for small-diameter PIG navigation. In the beginning, the problems and system errors statement of MEMS SINS-based PIG are analyzed step by step. Then, the pipeline junction (PJ) identification method based on fast orthogonal search (FOS) is studied. After that, a PIG positioning system that comprises of micro-inertial/AGM/odometer/PJ is proposed, and also the application mechanism of extended Kalman filter and its smoothing technology on PIG navigation system is researched to improve the overall positioning precision for the small-diameter PIG. Finally, the proposed methods and research conclusions are verified by the indoor wheel robot simulation platform

Pipeline Bending Strain Measurement and Compensation Technology Based on Wavelet Neural Network

The bending strain of long distance oil and gas pipelines may lead to instability of the pipeline and failure of materials, which seriously deteriorates the transportation security of oil and gas. To locate the position of the bending strain for maintenance, an Inertial Measurement Unit (IMU) is usually adopted in a Pipeline Inspection Gauge (PIG). The attitude data of the IMU is usually acquired to calculate the bending strain in the pipe. However, because of the vibrations in the pipeline and other system noises, the resulting bending strain calculations may be incorrect. To improve the measurement precision, a method, based on wavelet neural network, was proposed. To test the proposed method experimentally, a PIG with the proposed method is used to detect a straight pipeline. It can be obtained that the proposed method has a better repeatability and convergence than the original method. Furthermore, the new method is more accurate than the original method and the accuracy of bending strain is raised by about 23% compared to original method. This paper provides a novel method for precisely inspecting bending strain of long distance oil and gas pipelines and lays a foundation for improving the precision of inspection of bending strain of long distance oil and gas pipelines

An overview of robotics and autonomous systems for harsh environments

Across a wide range of industries and applications, robotics and autonomous systems can fulfil the crucial and challenging tasks such as inspection, exploration, monitoring, drilling, sampling and mapping in areas of scientific discovery, disaster prevention, human rescue and infrastructure management, etc. However, in many situations, the associated environment is either too dangerous or inaccessible to humans. Hence, a wide range of robots have been developed and deployed to replace or aid humans in these activities. A look at these harsh environment applications of robotics demonstrate the diversity of technologies developed. This paper reviews some key application areas of robotics that involve interactions with harsh environments (such as search and rescue, space exploration, and deep-sea operations), gives an overview of the developed technologies and provides a discussion of the key trends and future directions common to many of these areas

A dead reckoning localization method for in-pipe detector of water supply pipeline: an application to leak localization

Urban water supply pipeline system integrity is important for the urban life. The aim of the study reported in this paper is to locate the water pipeline leaks by using an in-pipe detector. In this study, a mathematical model is extracted from an actual inspection system. By using the homogeneous transformation theory, transformation matrix which is from carrier to a reference coordinate system is deduced, and then the global transformation matrix is obtained to describe the detector’s posture. Through measuring the distance increment of each sample time step in carrier coordinate system, the cumulative distance result is calculated. After combining the data of the inertial measurement unit (IMU) and odometer, the leak can be located. To improve the accuracy of leak localization, the magnetic markers are implemented about one in each 1 km distance, which provide reference points to be used to compensate accumulative error during the localization process. Furthermore, a dead reckoning localization method combining data of a micro electro-mechanical IMU, three odometers, and magnetic markers is proposed. To verify above localization algorithm, a simulation case study is conducted with the artificial error generated by the white noise. The simulation results show that the dead reckoning algorithm can effectively provide leak locations with a reasonable uncertainty. Based on this, an experimental platform was built in this study. The experimental results show that the relative error of leak locating achieves a reasonably good performanc

Advancing Climate Change Research and Hydrocarbon Leak Detection : by Combining Dissolved Carbon Dioxide and Methane Measurements with ADCP Data

With the emergence of largescale, comprehensive environmental monitoring projects, there is an increased need to combine state-of-the art technologies to address complicated problems such as ocean acidifi cation and hydrocarbon leak detection

Selected instruments and related products : 2000

Current industrial report. Contains annual data for selected instruments and related products produced in the United State

An alternative approach for robot localization inside pipes using RF spatial fadings

Accurate robot localization represents a challenge inside pipes due to the particular conditions that characterize this type of environment. Outdoor techniques (GPS in particular) do not work at all inside metal pipes, while traditional indoor localization methods based on camera or laser sensors do not perform well mainly due to a lack of external illumination and distinctive features along pipes. Moreover, humidity and slippery surfaces make wheel odometry unreliable. In this paper, we estimate the localization of a robot along a pipe with an alternative Radio Frequency (RF) approach. We first analyze wireless propagation in metallic pipes and propose a series of setups that allow us to obtain periodic RF spatial fadings (a sort of standing wave periodic pattern), together with the influence of the antenna position and orientation over these fadings. Subsequently, we propose a discrete RF odometry-like method, by means of counting the fadings while traversing them. The transversal fading analysis (number of antennas and cross-section position) makes it possible to increase the resolution of this method. Lastly, the model of the signal is used in a continuous approach serving as an RF map. The proposed localization methods outperform our previous contributions in terms of resolution, accuracy, reliability and robustness. Experimental results demonstrate the effectiveness of the RF-based strategy without the need for a previously known map of the scenario or any substantial modification of the existing infrastructure