4 Ways the IoT Creates Intelligent Pipeline Monitoring
IoT sensors make it possible to detect and pinpoint leaks in pipelines more effectively in the pipeline industry. How can they improve pipeline monitoring?
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In the U.S. alone, pipeline operators maintain around 3 million miles of natural gas distribution mains and pipelines. They often run through stretches of remote wilderness, across difficult-to-access terrain, or deep underwater. While traditional monitoring tools like SCADA systems can be effective, they also have significant weak points.
American water infrastructure is similar in length, made up of around 2.2 million miles of pipes that can be difficult to monitor due to location. Innovations are helping to provide more effective pipeline monitoring solutions. Internet of Things (IoT) devices could have a major impact on how pipelines are monitored. Why is the IoT the foundation for a new kind of intelligent pipeline monitoring?
1. Extended Leak Detection Systems
IoT sensors expand existing pipeline telemetry systems, like SCADA networks that monitor for leaks with pressure and flow analysis. Low-power IoT sensors, often powered by solar panel attachments, can capture various operational variables.
These sensors can provide an exterior monitoring complement to a SCADA system’s interior pipeline monitoring. IoT devices like acoustic or ultrasonic sensors can listen for abnormal sound waves that may suggest leaks or crack initiation and growth.
Methane gas detectors provide a more straightforward means of leak detection. Abnormal methane levels can trigger an alert to pipeline operators, helping them pinpoint a leakage’s location.
A sufficiently large fleet of sensors posted at regular intervals can improve leak detection and eliminate false positives that internal pressure sensors can sometimes generate.
2. Improved Troubleshooting and Pipeline Repair
A system that tracks pipeline pressure can tell you if there is a leak, but it may not be able to help an operator pinpoint its exact location. This lack of accuracy can result in the loss of valuable time as the pipeline repair team has to comb an area of the pipe looking for the leak.
IoT smart sensors working in tandem with a conventional leak detection system can communicate the extent and specific location of pipeline damage. This can accelerate the troubleshooting process and minimize the attendant risks of a leak — downtime, lost gas, and potential environmental damage.
Analysis of abnormal sound waves detected by acoustic sensors may suggest galling on the pin or box ends of a pipe section. With this information, pipeline technicians can prioritize a visual thread inspection, potentially helping them discover damage to the pipe threading.
Relative location error with the use of ultrasonic and acoustic sensors can be as low as 1% with a pair of acoustic emissions sensors while also covering up to 80 meters of pipeline length.
Research on the use of piezoelectric acoustic sensors in pipeline leak detection has also found they are effective in detecting both transient and continuous leaks. Regardless of leak type, these sensors can help repair teams pinpoint the location.
3. Leak Forecasting and Improved Trend Predictions
Better data on leaks can lead to improved forecasting models. The speed and scale of IoT data can provide the foundation for new forecasting and trend prediction models that can identify actions and events likely to lead to pipeline failures.
Data gathered from a fleet of IoT sensors can be analyzed by a big data analytics solution. Both real-time and historical sensor data can be analyzed to uncover new patterns in failure events. These can help pipeline operators build more effective forecasting models that offer earlier leak and damage detection.
This application can resemble predictive maintenance in pipelines, one of the most common applications of IoT technology. It uses operational data from IoT sensors to forecast machine failure or abnormal behavior.
Coupled with data from other sources—like environmental, weather, and information from other pipeline systems—these analytics models can be further improved, providing new insights on the causes of failure and leaks.
Long-term data and analysis can help pipeline operators construct a more effective strategic monitoring strategy. Insights may uncover blind spots in telemetry or help operators pioneer new approaches in monitoring.
4. Creating the Foundation for Autonomous and Self-Optimizing Pipeline Management
In the near future, IoT sensors and remote controls may help build self-optimizing pipeline management systems.
An AI- and IoT-powered pipeline management system can automate most or all steps in the traditional pipeline leak reporting process. This includes alerting pipeline operators, opening or closing valves, notifying government agencies, and dispatching technicians to the point of failure.
IoT-controlled pipeline valves and terminals and other technology allow key pipeline infrastructure to be controlled remotely. In combination with IoT sensors, these controls enable the pipeline system to effectively monitor and manage itself, adjusting gas flow as needed to minimize damage or the impact of the leak.
Over time, new information can be looped back into the system. By bringing in data from emergency events, the system can further optimize responses and build a more effective pipeline leak management system.
The data could also be used in engineering and planning new pipelines, helping to optimize designs to reduce the risk of leaks.
Using IoT Technology to Improve Pipeline Monitoring and Management
Internet-connected sensors can be used to create new, intelligent pipeline monitoring solutions. These solutions can expand the capabilities of more conventional technology, like SCADA, and also improve the quality of leak forecasting and pipeline maintenance algorithms. Remote-controlled valves and mains can allow a system to automatically adjust pipeline operation in response to the possibility of a leak. Ultimately, incorporating the IoT into these processes can reduce failures and improve efficiency.
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