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iPIM Report Summary

Project ID: 673727

Periodic Reporting for period 1 - iPIM (Development of an Intelligent Onshore Pipeline Integrity Monitoring System)

Reporting period: 2015-10-01 to 2016-09-30

Summary of the context and overall objectives of the project

European gas pipeline infrastructure has grown from 32,000 km (19,884 miles) in 1970 to 135,211 km (84,016 miles) in 2007 . The number is increasing rapidly since. With such an extensive and growing network of pipelines, and a corollary increasing incidence of failures, it is no longer feasible to rely upon current intermittent manual inspection techniques to maintain safe operation, from the twin perspectives of probability of detection over such large network, and consequence of failure given the hazardous materials being distributed. Existing pipeline monitoring systems, including corrosion coupons, pigging and localised sensor arrays suffer from considerable inherent deficiencies, given their lack of sophistication, practicality of use or lack of coverage. Clearly, a wide-area coverage of continuous monitoring of pipelines is urgently required.

The iPIM is a pipeline integrity monitoring system that can offer complete coverage of the pipeline structural integrity monitoring, with improved accuracy compared to other methods and at a cost-effective manner.
A developed prototype of sophisticated non-destructive technique (NDT) for structural health monitoring system (SHM) of oil and gas (O&G) pipelines is being further modified so that the system can be made available for commercialization. iPIM will continuously monitor the pipeline for cracks, corrosion and other faults and send the information over a wireless communication system to the network monitoring centre where the fault will be displayed over a 3D map of the pipeline. This will help the pipeline operators to take preventive and corrective measures before any accident stemmed from pipeline failure occurs.

A low profile wireless Acoustic Emission (AE) and Long Range Ultrasonic (LRU) dual mode sensors will be permanently attached on the pipeline with a collar installed on locations identified by the robotic pig or, if the client requires, at intervals of 100m apart from each other that can monitor 50m of pipeline in either side. The sensors will act in passive AE mode in normal operation and on detection of an anomaly will switch to LRU mode to locate and determine the characteristics of the anomaly. A machine learning method will be used and data fusion system will intelligently manage data acquisition and analysis functions based on data received from the installed sensor nodes. An energy harvesting system is being developed to power the onsite electronics. A new software is being developed that will enable advanced signal processing with improved signal/noise separation in handling sensor data, thus supporting more sensitive measurement and more effective analysis.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

 Defined the scope of monitoring and parameters of operation;
- Running the Machine Learning method and data fusion system; (ongoing)
- Advanced signal processing requirements;
- Theoretical modelling;
- Requirements of wireless system;
- Energy harvesting module calculations and results;
- Development of dual sensor transducer; (ongoing)

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Key features of iPIM to overcome limitations of current SOA
1. iPIM offers a permanent monitoring system for oil and gas pipeline.
2. As very sophisticated hardware and software system will be more accurate and offer precision in prediction of progress of fault over time. This gives the tools to operators to reduce costs as well as risk by planning ahead: minimising down time, increasing procurement efficiency , early fault detection, prevention of pipeline failure.
3. iPIM will be able to detect corrosion and erosion defects under insulation at any location.
4. The location of the fault along with the distance from a reference point will be displayed on a 3D map.
5. The power consumption will be very low as it will make use of energy harvesting system.

Benefits for pipeline operators:
> Minimise down time (=cost) for pipeline operations: The system reduces significantly the frequency of need for pigging operations (including pipeline cleaning pigging necessary prior to intelligent pigging) thus minimises down time.
>Increase cost efficiency through accurate maintenance planning: The iPIM system monitoring allows for accurate prediction of Progression of Cracks over time which is a valuable contribution to maintenance work planning to increase cost efficiency. Accuracy of monitoring is enhanced through Machine Learning and Data Fusion. The accumulation of data over time is used to feed the Machine Learning function and learn from input of the analysed data. Data fusion is used to improve the accuracy of prediction of faults and their classification according to parameters determined for that particular pipeline and in integration with other sources of SHM (Structural Health Monitoring) offering increased Probability of Detection (POD) and higher Cross Sectional Area (CSA) resolution.

Impact to society:
iPIM will ensure onshore pipeline safety and reduce cost due to pipeline failure in Europe.
- Increase in the detection, evaluation and monitoring of defects in pipelines.
- Decrease in the probability of pipeline failure.
- Providing a substantial reduction in risk to communities, economies and the environment stem from pipeline rupture.
-Provide the pipeline owners and regulatory authorities with very valuable data that will facilitate the integration of the non-destructive testing (NDT) and structural integrity (SI) assessment, thus improving the confidence in NDT performance and enabling the SI community to adopt novel and more sophisticated approaches to pipe design, operation and life extension
- The monitoring and other related cost will be reduced. As estimated the cost reduction will be about 50% when compared to the use of existing NDT systems.

Related information

Record Number: 195023 / Last updated on: 2017-02-20
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