A Combined Leak Detection Method Using Pattern Recognition Techniques

2014 ◽  
Author(s):  
Gerhard Geiger ◽  
Daniel Vogt
Keyword(s):  
Pattern Recognition ◽  
Detection Method ◽  
Leak Detection ◽  
Excellent Performance ◽  
Transient Model ◽  
The Public ◽  
Pattern Recognition Techniques ◽  
Detection Systems ◽  
Volume Balance ◽  
Public Environment

Due to the vast mileage of pipelines throughout the world, it is important that dependable leak detection systems (LDSs) are used to promptly identify when a leak has occurred so that appropriate response actions are initiated quickly. The swiftness of these actions can help reduce the consequences of accidents or incidents to the public, environment, and property. Internal systems [4] such as volume balance, mass balance or real-time transient model (RTTM) based methods are used successfully for that purpose. RTTM based methods offer excellent performance but more field sensors are needed than for simpler methods such as volume balancing, and therefore these methods are less robust because of their greater dependence on sensors which could fail. This paper describes a new leak detection methodology which uses pattern recognition techniques to combine two or more internal methods seamlessly into one scheme hence improving performance, robustness and applicability.

scholarly journals Leak Detection Systems for Short Pipelines

2000 ◽  
Author(s):  
Renan Martins Baptista
Keyword(s):  
Detection System ◽  
Leak Detection ◽  
Low Complexity ◽  
Transient Model ◽  
Service Companies ◽  
Detection Systems ◽  
Volume Balance ◽  
Pipeline Networks ◽  
Phase Liquid ◽  
Flow Detection

This paper describes procedures developed by PETROBRAS Research & Development Center to assess a software-based leak detection system (LDS) for short pipelines. These so-called “Low Complexity Pipelines” are short pipeline segments with single-phase liquid flow. Detection solutions offered by service companies are frequently designed for large pipeline networks, with batches and multiple injections and deliveries. Such solutions are sometimes impractical for short pipelines, due to high cost, long tuning procedures, complex instrumentation and substantial computing requirements. The approach outlined here is a corporate approach that optimizes a LDS for shorter lines. The two most popular implemented techniques are the Compensated Volume Balance (CVB), and the Real Time Transient Model (RTTM). The first approach is less accurate, reliable and robust when compared to the second. However, it can be cheaper, simpler, faster to install and very effective, being marginally behind the second one, and very cost-efective. This paper describes a procedure to determine whether one can use a CVB in a short pipeline.

Pipeline Leak Detection Technologies and Emergency Shutdown Protocols

2014 ◽  
Author(s):  
Gerhard Geiger
Keyword(s):  
Real Time ◽  
Potential Risk ◽  
Leak Detection ◽  
Measurement Equipment ◽  
Transient Model ◽  
Detection Systems ◽  
Emergency Shutdown ◽  
Field Instrumentation ◽  
Emergency Actions ◽  
Detection Technologies

Pipelines are the least expensive and most efficient way to move liquids and gases, but there is a high potential risk of danger in case of a leak. This paper therefore describes pipeline leak detection technologies and emergency shutdown protocols to ensure reliable and safe pipeline operations. The main focus of this paper is on internal leak detection systems which use existing field instrumentation and usually run continuously. External leak detection systems using dedicated measurement equipment such as probes and sensor cables are briefly considered. Particular emphasis will be placed on model-based techniques such as the Real Time Transient Model (RTTM) and Extended Real Time Transient Model (E-RTTM) methods. In case of a leak, appropriate emergency actions are required to limit the consequences and in particular to protect people and the environment. The last part of the paper therefore is devoted to emergency shut-down protocols.

Leak Detection and Operations Management in Offshore Pipelines

2016 ◽  
Author(s):  
Jun Zhang ◽  
Adrian Kane
Keyword(s):  
Operations Management ◽  
Leak Detection ◽  
Offshore Pipelines ◽  
Natural Gas Pipelines ◽  
Detection Systems ◽  
Volume Balance ◽  
Fluid Properties ◽  
Oil And Natural Gas ◽  
Measured Flow ◽  
Transient Models

This paper will demonstrate that with limited instruments at the terminals and platforms only, it is feasible to monitor the integrity of offshore pipelines effectively. Some examples of applications will be shown, including both crude oil and natural gas pipelines. The statistical volume balance technology based on flow and pressure measurements at the inlets and outlets only provides the detection and location of leaks. The paper describes the performance of these leak detection systems for incidents ranging from small leaks to pipeline rupture. To help operators run pipelines safely and cost effectively, real-time transient models are used to calculate the flow, pressure, temperature, density and other fluid properties along the pipeline. Instead of using measured flow and pressure, the operators rely on these calculated values to take operational decisions. The combination of hydraulic modelling and statistical leak detection provides the operators with the information and confidence in the integrity of their pipelines. In the event of any incident the operators can take actions quickly and correctly to minimize the consequences.

Pipeline Rupture Detection Based on Machine Learning and Pattern Recognition

2016 ◽  
Author(s):  
Martin Di Blasi ◽  
Zhan Li
Keyword(s):  
Machine Learning ◽  
Pattern Recognition ◽  
Task Force ◽  
Detection System ◽  
Leak Detection ◽  
Guidance Document ◽  
Performance Expectations ◽  
Detection Systems ◽  
Short Period ◽  
Recognition And Response

Pipeline ruptures have the potential to cause significant economic and environmental impact in a short period of time, therefore it is critical for pipeline operators to be able to promptly detect and respond to them. Public stakeholder expectations are high and an evolving expectation is that the response to such events be automated by initiating an automatic pipeline shutdown upon receipt of rupture alarm. These types of performance expectations are challenging to achieve with conventional, model-based, leak-detection systems (i.e. CPM–RTTMs) as the reliability measured in terms of the false alarm rate is typically too low. The company has actively participated on a pipeline-industry task force chaired by the API Cybernetics committee, focused on the development of best practices in the area of Rupture Recognition and Response. After API’s release of the first version of a Rupture Recognition and Response guidance document in 2014, the company has initiated development of its own internal Rupture Recognition Program (RRP). The RRP considers several rupture recognition approaches simultaneously, ranging from improvements to existing CPM leak detection to the development of new SCADA based rupture detection system (RDS). This paper will provide an overview of a specific approach to rupture detection based on the use of machine learning and pattern recognition techniques applied to SCADA data.

scholarly journals Vacuum Leak Detection Method Using Index Regression and Correction for Semiconductor Equipment in a Vacuum Chamber

2021 ◽  
Vol 11 (24) ◽  
pp. 11762
Author(s):  
Taekyung Ha ◽  
Hyunjung Shin
Keyword(s):  
Vacuum Chamber ◽  
Detection Method ◽  
Pressure Control ◽  
Leak Detection ◽  
Process Yield ◽  
Mass Spectrometers ◽  
Detection Systems ◽  
Isolation Condition ◽  
In Situ Detection

In semiconductor manufacturing, fault detection is an important method for monitoring equipment condition and examining the potential causes of a fault. Vacuum leakage is considered one of the major faults that can occur in semiconductor processing. An unnecessary O2 and N2 mixture, a major component of the atmosphere, creates unexpected process results and hence drops in yield. Vacuum leak detection systems that are currently available in the vacuum industry are based on helium mass spectrometers. They are used for detecting the vacuum leakage at the sole isolation condition where the chamber is fully pumped but cannot be used for in situ detection while the process is ongoing in the chamber. In this article, a chamber vacuum leak detection method named Index Regression and Correction (IRC) is presented, utilizing common data which were gathered during normal chamber operation. This method was developed by analyzing a simple list of data, such as pressure, the temperature of the chamber body, and the position of the auto pressure control (APC), to detect any leakages in the vacuum chamber. The proposed method was experimentally verified and the results showed a high accuracy of up to 97% when a vacuum leak was initiated in the chamber. The proposed method is expected to improve the process yield of the chamber by detecting even small vacuum leakages at very early stages of the process.

A Note About the Sensitivity Curve of Compensated Volume Balance Leak Detection Systems

2002 ◽  
Author(s):  
Felipe Bastos de Freitas Rachid ◽  
Jose´ Henrique Carneiro de Araujo ◽  
Renan Martins Baptista
Keyword(s):  
Steady State ◽  
Lower Bounds ◽  
Leak Detection ◽  
Theoretical Development ◽  
Rate Measurement ◽  
Sensitivity Curve ◽  
Flow Rate Measurement ◽  
Detection Systems ◽  
Volume Balance ◽  
System Uncertainties

This work presents a simple theoretical development which aims to derive the sensitivity curve of compensated volume balance leak detection systems. The analysis carried out is not limited to steady state and also automatically provides the bounds with which the sensitivity curve is predicted, as a function of the system uncertainties. It is demonstrated that the performance of leak detection systems of this nature depends upon the operation of the pipeline at the time instants of the leak onset and of leak detection. As a result, it is also shown that there are an upper and a lower bounds of the minimum response time and that the minimum detectable leak is independent of the pipeline operational regime, being equal to the overall flow rate measurement uncertainty.

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