Pipeline Integrity Monitoring for Predictive Leak Prevention
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Solution Overview
Problem
Conventional pipeline monitoring systems lack an integrated approach for cost-effective, predictive maintenance and fail to provide adequate granularity and visibility along the pipeline, leading to potential leaks and environmental damage, with existing solutions primarily focusing on external detection after significant damage has occurred.
Innovation Solution
A non-intrusive Pipeline Integrity Monitoring System (PIMS) with sensor modules equipped with thickness, vibration, and leak sensors, coupled with a central facility for data processing and analysis, providing real-time alerts and predictive capabilities for preventive maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional external-based detection systems are used to detect leakage after it occurs, then detection capability is provided, but the system lacks predictive maintenance capability and cannot provide quantifiable pipeline integrity data for preventive action
Solution Approach 1:
The system performs preliminary measurements of pipeline integrity parameters (thickness, vibration, temperature, pressure) continuously along the pipeline before leakage occurs. The computational pipeline monitoring (CMP) system analyzes these preliminary data to predict potential failures and schedule maintenance before actual leakage happens, enabling preventive action rather than reactive response.
Solution Approach 2:
The patent introduces an intermediary computational monitoring system that processes data from multiple sensor types (thickness sensors, vibration sensors, temperature sensors, pressure sensors) and integrates information from different pipeline locations. This intermediary system transforms raw sensor data into quantifiable integrity assessments, providing the bridge between simple detection and predictive maintenance capability.
2Loss of information
If traditional SCADA systems with sensors at widely separated locations are used, then flow and data information are provided, but adequate granularity and visibility along the pipeline are not achieved
Solution Approach 1:
The system segments the pipeline into multiple monitoring zones with sensors distributed at regular intervals along the pipeline length. Each sensor module independently measures local conditions (thickness, vibration, temperature, pressure), and the computational system integrates these segmented measurements to provide continuous granular visibility along the entire pipeline, transforming sparse point data into comprehensive distributed monitoring.
3Measurement precision
If manually onsite inspection and excavation are performed for pipeline monitoring, then direct measurement is achieved, but the process is not continuous and cannot provide real-time predictive maintenance data
Solution Approach 1:
The system replaces intermittent manual inspection with continuous automated sensing. Sensors continuously measure pipeline thickness, vibration, temperature, and pressure without interruption, providing ongoing data streams that enable real-time detection of degradation trends. This continuous monitoring allows the system to identify early signs of failure and trigger predictive maintenance actions immediately, eliminating the time loss associated with periodic manual inspections.
Data Source
AI summary
A monitoring system for a system, may comprise: thickness sensors and vibration sensors disposed on the monitored system, controller processors coupled to the sensors to receive and geo-tag sensor data, communication devices for transmitting geo-tagged data, a communication device receiving the geo-tagged data, and servers to analyze the data from the sensors to determine, e.g., element thickness and/or vibration producing events, and to compare same to standardized exception data therefor; wherein when an exception exists, to generate and communicate an alert therefrom via a display, a human interface device and/or the communication device of the central facility. Additional sensors such as temperature sensors, strain gages, flow sensors, leak sensors and/or other sensors may also be disposed on the system, and data therefrom processed to determine exceptions.