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| Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
|---|---|
| Author | Rasool, Noman Nabi, Waqas Un |
| Copyright Year | 2018 |
| Abstract | Ultrasonic meters are widely accepted as being robust, reliable and having the ability to provide custody transfer accuracy over varied application ranges. Because of these characteristics and their inherent advanced signal processing and non-intrusive design, the meters have the capability to deliver unique performance and diagnostic information that can be used to improve Pipeline operations and Leak Detection applications. This paper presents real time data from liquid ultrasonic meters. The data helps to improve pipeline operations including dual Drag Reducing Agent (DRA) injections, Batch Detection (BD), Commodity Movement Tracking (CMT) etc. Diagnostic data can also identify upstream instrumentation anomalies and illustrate the abilities of the utilizing diagnostics within liquid ultrasonic meters to further improve current leak detection real time transient models (RTTM) and pipeline operational procedures. The paper discusses considerations addressed while evaluating data and understanding the importance of accuracy within the metering equipment utilized. It also elaborates on significant benefits associated with the utilization of ultrasonic meters capabilities and the importance of diagnosing other pipeline issues and uncertainties outside of measurement errors. |
| Sponsorship | Pipeline Division |
| File Format | |
| ISBN | 9780791851883 |
| DOI | 10.1115/IPC2018-78266 |
| Volume Number | Volume 3: Operations, Monitoring, and Maintenance; Materials and Joining |
| Conference Proceedings | 2018 12th International Pipeline Conference |
| Language | English |
| Publisher Date | 2018-09-24 |
| Publisher Place | Calgary, Alberta, Canada |
| Access Restriction | Subscribed |
| Subject Keyword | Leakage Design Errors Uncertainty Pipelines Signal processing Instrumentation Drag (fluid dynamics) Transients (dynamics) |
| Content Type | Text |
| Resource Type | Article |
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