Pipeline Trajectory Reconstruction Using Junction-Constrained MEMS IMUs
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Solution Overview
Problem
Current pipeline inspection gauge (PIG) systems face challenges in accurately reconstructing pipeline trajectories, especially in small diameter pipelines, due to the large size and high cost of high-end Inertial Measurement Units (IMUs, and the need for precise position referencing of defects detected by sensors.
Innovation Solution
The use of Micro-Electro-Mechanical Systems (MEMS) IMUs with an Extended Kalman Filter (EKF) algorithm and pipeline junction detection, which combines inertial sensor data with odometer readings to improve navigation accuracy by identifying patterns indicative of pipeline junctions and determining the PIG's position within the pipeline.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-end Inertial Measurement Units (IMUs) are used for pipeline trajectory reconstruction, then position accuracy is improved, but device size increases and cost increases
Solution Approach 1:
The patent replaces expensive high-end IMUs with low-cost MEMS IMUs that have smaller size and lower cost. The system compensates for the lower inherent accuracy of MEMS sensors through software-based techniques including pipeline junction detection using accelerometer patterns, odometry integration, and Kalman filtering to achieve acceptable position accuracy for small diameter pipelines
Solution Approach 2:
The patent substitutes mechanical/physical measurement systems (high-end IMUs) with a hybrid approach combining low-cost MEMS sensors, optical odometry wheels, and computational algorithms. The system uses pattern recognition of accelerometer signatures at pipeline junctions and odometry-based distance measurement to compensate for the lower precision of MEMS inertial sensors
2Measurement precision
If high-end Inertial Measurement Units (IMUs) are used for pipeline trajectory reconstruction, then position accuracy is improved, but cost increases
Solution Approach 1:
The patent replaces expensive high-end IMUs with low-cost MEMS IMUs that have smaller size and lower cost. The system compensates for the lower inherent accuracy of MEMS sensors through software-based techniques including pipeline junction detection using accelerometer patterns, odometry integration, and Kalman filtering to achieve acceptable position accuracy for small diameter pipelines
Solution Approach 2:
The patent creates a multi-functional navigation system where the low-cost MEMS IMU is combined with odometry wheels and pipeline junction detection capabilities. This hybrid system performs multiple functions (inertial navigation, odometry, feature detection) using inexpensive components, making the overall system more cost-effective than using high-end IMUs alone
3Device complexity
If velocity wheels (odometers) are used for position determination, then device size is reduced, but position accuracy deteriorates due to cumulative error
Solution Approach 1:
The patent merges odometry wheel measurements with MEMS IMU data and pipeline junction detection in an integrated navigation system. The odometry provides distance measurement along the pipeline, the IMU provides orientation and acceleration data, and pipeline junction patterns serve as reference features to reset and correct cumulative errors, achieving accurate position determination without relying on odometry alone
Solution Approach 2:
The patent implements feedback correction by detecting pipeline junction patterns in the accelerometer data and using these detected features to reset and correct the cumulative position error from odometry integration. The system continuously compares expected versus actual accelerometer patterns at junctions and uses these corrections to maintain accurate trajectory reconstruction over long pipeline distances
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces position RMS errors by up to 85% and enhances the accuracy of reconstructed trajectories, making it suitable for low-cost, lightweight navigation systems without the need for extensive Above Ground Marker installations.
Implementation Method 1
a Micro-Electro-Mechanical Systems (MEMS) Inertial Measurement Unit (IMU) or other IMUs onboard PIG device configured to generate sensor data indicative of motion of the PIG device
Implementation Method 2
detect a pattern in the sensor data indicative of a junction in the pipeline
Implementation Method 3
determine a position of the PIG device within the pipeline in response to the identified junction and the rate of travel of the PIG device
Data Source
AI summary
The present embodiments include new methods for low-cost inertial measurement units (IMU) using an extended Kalman filter (EKF) to increase the navigation parameters accuracy or reduce the total RMS errors even during the unavailability of Above Ground Markers (AGM) using new developed method called PipeLine Junctions (PLJ) detection. This method detects the pipeline junctions and adds heading and pitch constraints to the Pipeline Inspection Gauge (PIG) motion between junctions. The results of this such embodiments with a micro-electro-mechanical systems (MEMS) based IMU showed that the position RMS errors have been reduced around 85% of the original applied EKF solution. Therefore, this approach is a useful solution for PIG navigation system.