In large-scale pipeline inspections, managing data from multiple Above Ground Markers (AGMs) can become overwhelming. These inspections generate enormous volumes of data, and traditional AGMs often require time-consuming manual data retrieval, compounded by a high number of false detections. For In-line Inspection (ILI) tool vendors, simplifying the collection and post-run analysis of this data is critical, and this is where the APEX AGM paired with PigView Web offers a revolutionary solution.
The Challenge of Large Pipeline Inspections
When inspecting long pipeline sections, the sheer number of AGMs needed increases exponentially. Each AGM must be individually downloaded, and false positives from environmental factors like passing vehicles, power lines, or magnetic interference slow down data analysis. For ILI tool vendors, whose primary goal is to locate and assess pipeline defects, the time and labor required to sort through irrelevant data can be significant.
Traditional systems make it difficult to quickly retrieve the actionable data needed to ensure pipeline integrity. This is especially challenging when dealing with hundreds of miles of pipeline where each AGM generates numerous detections, many of which are not relevant to the pig’s passage.
How APEX Above Ground Marker (AGM) and PigView Web Simplify Data Collection
The APEX AGM paired with PigView Web offers a modern solution to these challenges. The real-time connectivity of the APEX AGM allows operators to remotely access data from multiple AGMs across vast distances via LTE cellular networks or Iridium modems. This eliminates the need for manual downloads and gives ILI tool vendors the ability to instantly retrieve data, significantly reducing the time and labor involved.
The PigView Web platform provides an intuitive interface for managing AGMs. It allows users to download data, monitor operations, and configure multiple devices simultaneously. This remote access and multi-device management dramatically simplify the data collection process. This way teams can focus on analyzing the results rather than spending hours retrieving them.
Reducing False Positives with Advanced Machine Learning
One of the major challenges of traditional AGMs is the large number of false positive detections, which can result from external magnetic fields, cathodic protection, or passing vehicles. Sorting through these false positives manually takes time, delaying the analysis of real pig detections.
Propipe North America has developed advanced machine learning algorithms, integrated with PigView Web, to address this challenge. By leveraging the company’s vast training set — processing thousands of waveforms daily — Propipe NA has created highly accurate models capable of filtering out irrelevant data with precision. Here’s how the system works:
Pattern Recognition
The machine learning algorithms analyze magnetic and ELF waveform patterns reported by the APEX AGM. These algorithms are trained on vast datasets, allowing them to distinguish between genuine PIG passages and false signals caused by interference.
Continuous Learning
With each new run, the system continues to refine its detection capabilities, making it smarter and more accurate over time. By processing thousands of waveforms a day, the machine learning model grows more adept at detecting legitimate PIG passages and dismissing irrelevant signals.
Efficiency
With fewer false positives to review, data analysts can focus on the most critical information, significantly speeding up the post-run data analysis process.
Passage Waveforms for Advanced Analysis
In addition to reducing false positives, PigView Web provides comprehensive visualizations of magnetic and ELF waveforms recorded by the APEX AGM. These waveform visualizations give data analysts detailed insights into the pig’s journey through the pipeline, helping them identify specific issues, such as bends, obstructions, or defects, based on the shape and characteristics of the waveform data.
Streamlining Data Analysis for ILI Tool Vendors
For ILI tool vendors, the APEX AGM combined with PigView Web simplifies both the collection and analysis of AGM data. The system’s remote connectivity eliminates the need for manual downloads, and the integration of advanced machine learning drastically reduces false positives. With detailed waveform visualizations and a seamless data management interface, this system provides ILI vendors with a powerful tool for improving pipeline integrity assessments and ensuring more efficient, cost-effective inspections.
