Working Smart versus Working Hard: Wireless UT Sensors for Asset Integrity Monitoring

Abstract

In the 21st century of NDE technology and deployment, monitoring technologies and strategies are completely different than inspection technologies and strategies. Monitoring is no longer sending a technician to a location to take repeated manual data – this is still inspection, just more frequently. Monitoring takes place after a manual/automated inspection has located an anomaly and instrumentation (a sensor in this case), is installed to take recurring readings at that precise location to gather a large sample size of data to be analyzed. These two strategies, when employed in concert, even only on the most critical (10%) circuits/tanks/units, are optimizing asset health, reducing unplanned downtime, and eliminating the need to have people in potentially unsafe situations to the tune of tens of millions of dollars per year. This article will provide real life examples of the ~20% of the best run refineries, chemical, paper, and power plants which have cracked the code and are successfully using an inspect to monitor strategy to change the game of how they implement asset integrity in the 21st century. As you read this article, ask yourself the question, is my facility a part of this ~20%? If not, what can I start doing, and what incremental step changes can I make to my legacy inspection & asset integrity strategy, to use technology to spend my precious budget and resources to be a part of this ~20% in 2024 and beyond? Many asset owners struggle to identify the root cause of fluctuating corrosion rates due to unreliable, infrequent, or sheer lacks of quantity (and quality) of inspection data to make informed decisions on asset health. Facilities worldwide are tasked with monitoring thousands of Condition Monitoring Locations (CMLs) with established NDE techniques such as manual ultrasonic testing and radiography. While these techniques can provide valuable “snapshots” of the condition of particular locations, limitations and inherent errors can compound leading to ill-advised decision making. Manually taken thickness data can vary greatly and result in unwarranted complacency or excessive and costly inspections. Utilizing long range wireless continuous monitoring systems have drastically improved operators understanding of how process changes influence corrosion rates. Installed UT sensors provide near real-time data with a 0.001” accuracy. This influx of data provides a trend line whereas with manually taken data, sometimes only taken a few times a year, only provides a few points scattered across a graph. Asset owners have realized they can use this wealth of new information to validate and discover the effects of operational changes on corrosion rates and make more informed decisions to impact asset extension, retirement, and increasing the efficiency of assets during its useful life.