Dual Threshold Analysis and its Tuning Tool Development for Leak Detection

2014 ◽  
Author(s):  
Jianping Gao ◽  
Mike Chen
Keyword(s):  
Steady State ◽  
Real Time ◽  
Design Process ◽  
Detection System ◽  
Leak Detection ◽  
Tool Development ◽  
Operating Period ◽  
Data Set ◽  
Threshold Setting ◽  
Threshold Tuning

Dual threshold setting in CPM (Computational Pipeline Monitoring) systems is a concept to apply two kind of thresholds, namely steady state threshold and transient threshold setting to improve sensitivity during steady state operating period and reduce false alarm rate during transient operating period. Dual threshold implementation in CPM systems is not a trivial task since a real time pipeline may go through very complicated hydraulic scenarios. During design phase of dual threshold, the data set evaluated needs to cover on operational scenario long enough to represent the typical operation of the pipeline. The design process needs to include the design of transient/steady state switching, transient and steady state threshold, waiting time etc and tuning of those design parameter to achieve the optima. This calls for effective analysis to ensure its validity and a tuning tool development with user-friendly graphical user interface (GUI) to facilitate the tuning efforts from leak detection engineers. This paper details the process from dual threshold design and analysis to tuning tool development and application of the tool in real time CPM systems. At first, the concept of dual threshold and its design process being employed in CPM systems are reviewed; Secondly the paper discusses an analysis approach in testing and evaluation of dual threshold design in current CPM systems with identification of room for improvement. Next, the paper elaborates the design and development of a dual threshold tuning tool to simplify the process with intensive application of the tool during the threshold tuning of real time CPM systems to improve the detectability of the current leak detection system, finally concludes with some closing remarks.

Pipeline Diagnostics With Ultrasonic Meters

2016 ◽  
Author(s):  
Nicole Gailey ◽  
Noman Rasool
Keyword(s):  
Real Time ◽  
Measurement Errors ◽  
Flow Measurement ◽  
Detection System ◽  
Leak Detection ◽  
The United States ◽  
Time Data ◽  
Critical System ◽  
Detection Systems ◽  
Transient Models

Canada and the United States have vast energy resources, supported by thousands of kilometers (miles) of pipeline infrastructure built and maintained each year. Whether the pipeline runs through remote territory or passing through local city centers, keeping commodities flowing safely is a critical part of day-to-day operation for any pipeline. Real-time leak detection systems have become a critical system that companies require in order to provide safe operations, protection of the environment and compliance with regulations. The function of a leak detection system is the ability to identify and confirm a leak event in a timely and precise manner. Flow measurement devices are a critical input into many leak detection systems and in order to ensure flow measurement accuracy, custody transfer grade liquid ultrasonic meters (as defined in API MPMS chapter 5.8) can be utilized to provide superior accuracy, performance and diagnostics. This paper presents a sample of real-time data collected from a field install base of over 245 custody transfer grade liquid ultrasonic meters currently being utilized in pipeline leak detection applications. The data helps to identify upstream instrumentation anomalies and illustrate the abilities of the utilization of diagnostics within the 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 the ultrasonic meter’s capabilities and the importance of diagnosing other pipeline issues and uncertainties outside of measurement errors.

scholarly journals A Real Time Image Processing Bird Repellent System Using Raspberry Pi

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Oluwole Arowolo ◽  
Adefemi A Adekunle ◽  
Joshua A Ade-Omowaye
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Moving Objects ◽  
Detection System ◽  
Local Binary Patterns ◽  
Raspberry Pi ◽  
Feature Identification ◽  
Data Set ◽  
Haar Features ◽  
Haar Feature

Rice is one of the most consumed foods in Nigeria, therefore it’s production should be on the high as to meet the demand for it. Unfortunately, the quantity of rice produced is being affected by pests such as birds on fields and sometimes in storage. Due to the activities of birds, an effective repellent system is required on rice fields. The proposed effective repellent system is made up of hardware components which are the raspberry pi for image processing, the servo motors for rotation of camera for better field of view controlled by Arduino connected to the raspberry pi, a speaker for generating predator sounds to scare birds away and software component consisting of python and Open Cv library for bird feature identification. The model was trained separately using haar features, HOG (Histogram of Oriented Gradients) and LBP (Local Binary Patterns).Haar features resulted in the highest accuracy of 76% while HOG and LBP were, 27% and 72% respectively. Haar trained model was tested with two recorded real time videos with birds, the false positives were fairly low, about 41%. This haar feature trained model can distinguish between birds and other moving objects unlike a motion detection system which detects all moving objects. This proposed system can be improved to have a higher accuracy with a larger data set of positive and negative images. Keywords—Electronic pest repeller Haar cascade classifier, ultrasonic

Field Test of a Leak Detection System: Planning, Execution and Results

2010 ◽  
Author(s):  
Daniel Sampaio da Silva ◽  
Si´lvio A. Melo Filho ◽  
Mauro Niehues de Farias ◽  
Anderson Pacheco
Keyword(s):  
Steady State ◽  
Field Test ◽  
Communication Systems ◽  
Detection System ◽  
Transient State ◽  
Leak Detection ◽  
Point Of View ◽  
Measuring System ◽  
Operational Parameters ◽  
Pump Station

The OLAPA pipeline (Oleoduto Arauca´ria–Paranagua´) is a 12in diameter pipeline and, with its 97,6 km in length, crosses a mountain region called “Serra do Mar” attaining elevations of about 900m in a dense forest region. Besides that, this pipeline crosses cities, farms, rivers, including a short submerse stretch in the Paranagua´’s bay. An incident in this pipeline could result in severe consequences, especially under the environmental point of view. Therefore, this pipeline was chosen to test the performance of a new leak detector system in Transpetro. The test consists in comparing the theoretical results with practical values of alarm times obtained from a controlled removal of product in an adequate point, in the middle of the pipeline, simulating a real leak. The system chosen to be tested was the LeakWarn system, which is a computational system that uses the mass balance principle with line pack change to analyze the pipeline operational parameters in order to alert when there is a risk of product leak. This test had the objective to evaluate the LDS and help Transpetro’s management team to analyze and decide whether or not to replace its current leak management system, since this new one showed the expected results and was compatible with the excellence level already achieved in the company. The field test was performed in July 7th 2009, through a vent valve far from the ends of the pipeline and it was made in three different conditions: 1) A big leak in the steady state of operation; 2) A small leak also in the steady state of operation; and 3) A big leak in the transient state of operation (immediately after the pump station start up). In order to proceed this test, a multidisciplinary team was assigned and several resources were used such as: Two tank trucks, a specially designed leakage line with control valves, measuring system, flexible hoses, communication systems and emergency equipments. The complete operation was monitored from the Control Center in Transpetro’s Headquarter, Rio de Janeiro. This paper describes the way the tests were performed and presents the results in order to contribute with useful information to be used in any field test for any other leak detection system. It shows how planning were done in order to insure that all operations would be performed according to strict procedures and in a safe way. It also describes the milestones and the work of each team involved in the activity, as well as their constraints and difficulties that had to be overcome during the planning and execution phases, that lasted approximately one year.

Dynamic Modelling and Real-Time Leak Detection for NGL Pipelines

2004 ◽  
Author(s):  
Brent R. Young ◽  
J. Greg Cooke ◽  
Ron E. Daye ◽  
William Y. Svrcek
Keyword(s):  
Real Time ◽  
Detection System ◽  
Dynamic Modelling ◽  
Leak Detection ◽  
Balance System ◽  
Volume Balance ◽  
Control Scheme ◽  
Dynamic Simulation Model ◽  
Flow Pressure ◽  
Real Time Information

This paper describes the development and use of a dynamic simulation model and the implementation of a novel leak detection system. Experiences from the implementation and operation of the system will also be detailed from a user perspective. The dynamic model may be used for the transient simulation of the pipelines. The model was used to test the real-time leak detection system. The results of the simulation also prompted a change in the control scheme of the pipelines that resulted in less transient operation. The leak detection system is based upon rigorous thermodynamics and dynamic mass balance calculations driven by real-time information from field flow, pressure and temperature sensors. This system was successfully implemented to replace a simple volume balance system for NGL pipelines near Empress, Alberta.

Modeling of Ethylene in Pipeline Leak Detection System

2004 ◽  
Author(s):  
Jakob Bu¨chert
Keyword(s):  
Real Time ◽  
Detection System ◽  
Leak Detection ◽  
Practical Experience ◽  
Time Model ◽  
Pump Stations ◽  
Pipeline Model ◽  
Improve Determination

This paper describes experiences with an improved equation of state (EOS) for ethylene for an existing real time pipeline model. The main scope of the model is leak detection, batch, contaminant and pig tracking. Altogether the pipeline model includes transportation of batched liquid ethylene, ethane, propane, butane and natural gas liquids (NGL). The pipeline is approximately 1900 miles miles long and includes laterals, 33 pump stations, 9 injection/delivery stations and 5 propane terminals. Originally the model used a BWRS EOS for all the above products. At that time a number of false leak alarms were experienced related to pipeline sections containing ethylene. A case study was carried out, specifically for ethylene, to investigate the effect of replacing the BWRS EOS with a modified Helmholtz EOS. The study showed that replacing the EOS on average would improve determination of the ethylene densities by 1.6%–5.6% with an expected reduction in the alarm rate for ethylene cases by approximately 50%. As a result the modified Helmholtz EOS was implemented in the real time model. Results are presented to show the practical experience with the new EOS gained over the last years.

Remote and Intelligent Diagnostic Methods on Leakage Fault for Crude Oil Pipelines

2006 ◽  
Author(s):  
Lai-Bin Zhang ◽  
Zhao-Hui Wang ◽  
Wei Liang
Keyword(s):  
Real Time ◽  
Remote Monitoring ◽  
Data Exchange ◽  
Detection System ◽  
Leak Detection ◽  
Diagnostic Methods ◽  
Oil Fields ◽  
Detection Methods ◽  
Development Environment ◽  
Oil Pipelines

Oil and gas transportation pipelines are the key equipment in petroleum and chemical industry. At present, with the increase of transportation task in oil fields, real-time leak detection system becomes a demand that petroleum companies need to safeguard routines. At the heart of the leakage monitoring and detection procedures are the report of leakage event timely and of leakage point precisely. This paper presents a more realistic approach for using rarefaction-pressure wave technique in oil pipelines, which aims to two targets, one is the improvement of remote and intelligent degree, and the other is the improvement of the leakage location ability. This paper introduces a new scheme to meet the requirements of real time and high data transferring necessary for remote monitoring and leak detection methods for pipelines. The scheme is based on SCADA framework for remote pipeline leakage diagnosis, in which the Dynamic Data Exchange technology is utilized to construct the data-acquiring component to acquire the real-time information that could perform remote test and analysis. It also introduces a basic concept and structure of the remote leak detection system. Primarily, an embedded leak-detection package is designed to exchange the diagnostic information with the RTU data package of Modbus protocol, and then via fiber network, the SCADA-based remote monitoring and leak detection system is realized. Existing data acquisition apparatus applied in oil fields and city underground water pipeline is used, without changing the structure of pipeline supervisory system. This paper introduces the method of constructing DDE-based hot links between servers and client terminals, using Borland C++ Builder 6.0 development environment, and also explains the universality and friendliness of the method. It can easily access similar Windows’ applications simply by modifying Service names, Topic options and data Items. System feasibility was tested using negative-pressure data from oil-fields. Additionally, the applied results show that the whole running status of pipeline can be monitored effectively, and a higher automation grade and an excellent leak location precision of the system can be obtained.

Computational Pipeline Monitoring in Challenging Situations

2002 ◽  
Author(s):  
James E. Short
Keyword(s):  
Real Time ◽  
Detection System ◽  
Measurement Data ◽  
Leak Detection ◽  
Data Uncertainty ◽  
Computational Pipeline ◽  
Individual Measurement ◽  
General Terms ◽  
Pipeline Monitoring

This paper introduces a new, active methodology to modeling and leak detection intended to mitigate the effects of data uncertainty in such challenging situations, and presents three case studies. The American Petroleum Institute (API) has coined the phrase Computational Pipeline Monitoring (CPM) to encompass several methods of leak detection. The use of real-time transient hydraulic simulation tools, driven by data gathered by a Supervisory Control and Data Acquisition (SCADA) system, is one form of CPM system. Such real-time simulations impose SCADA-gathered data (typically pressures, flows, temperatures) onto a characterization of the pipeline (the model) and the fluids in the system. In a tuned CPM system, if the SCADA-gathered data cannot be successfully imposed on the model without transgressing the laws of fluid mechanics, this signifies a pipeline anomaly, which may be a release. However, in reality, many pipeline hydraulic anomalies are due to changing uncertainties in the data presented to the model and if annunciated to the pipeline operators would constitute a “false leak alarm.” While they typically are not large enough to compromise pipeline operations, uncertainties abound in the SCADA-gathered data. Even were the SCADA-gathered pressure and temperature data to contain no uncertainty, the fluid properties might not be sufficiently characterized for the simulation to accurately calculate how the fluid behaves under pressure and/or temperature changes. Measurement failure further complicates the task of the CPM application, as does slack line flow. Uncertainty in the CPM-driving data is not constant, it is ever-changing with variations in the pipeline flow rate, the characterization of the fluids in the line, and the quality of the individual measurement data, to mention only a few. CPM systems use a variety of methodologies to vary their sensitivity according to the uncertainty in the data used for their calculations. However, in general terms, the more uncertainty there is in the data, the lower the resulting system sensitivity becomes. Active features in a CPM leak detection system can mitigate the performance degradation due to varying data uncertainty.

Reality Check: Improving Real-Time Pipeline Monitoring Using Near Real-Time Fluid Data

2008 ◽  
Author(s):  
Joseph Jutras ◽  
Rick Barlow
Keyword(s):  
Real Time ◽  
Detection System ◽  
Leak Detection ◽  
Fluid Type ◽  
Transient Model ◽  
Oracle Database ◽  
Detection Model ◽  
The Past ◽  
Batch Data ◽  
Time Injection

MBS, the software based leak detection system employed by Enbridge, is a real time transient model and as such requires fluid characteristics of the various batches that enter the pipeline. In the past, of the 25 plus pipelines modeled, only 4 received fluid identifiers from the field. These fluid identifiers are a sub-string of the batch identifiers stored in flow computers located at custody transfer locations. On the remaining pipelines, Enbridge used fluid density from the field to infer fluid type and therefore characteristics. In the past whenever a number of fluids had the same density, MBS assigned a best-guess of fluid type. The ‘MBS Real Time Injection Batch Data’ project was proposed to bring fluid identifiers to MBS on the remaining lines with the purpose of improving MBS’ selection of fluid properties. Since injection points on the remaining lines were not custody transfer there were no flow computers at these locations. An existing application called Commodity Movement Tracking, or CMT, was used to provide fluid names to the leak detection model. CMT holds past, present, and future injection batch information in an Oracle database. Batch identifiers are queried, placed into the SCADA system, and forwarded on to MBS. This paper explores the new approach, introduced by the ‘MBS Real Time Injection Batch Data’ project, of providing MBS with batch identifiers.

Gas Pipeline Simulation: Use of a Single System for All Simulations

2006 ◽  
Author(s):  
Heribert Scheerer ◽  
Stewart Midwinter
Keyword(s):  
Steady State ◽  
Real Time ◽  
Simulation Models ◽  
Leak Detection ◽  
Gas Pipeline ◽  
Simulation Tools ◽  
Cost Of Energy ◽  
Time Simulation ◽  
Long Time ◽  
Training Simulation

Simulation tools have been used for a long time in the gas pipeline industry to do things like system planning and training simulation, using both steady state and transient simulators. Companies have also tried using simulation models in real time environments, to do applications such as line pack management and leak detection, with less than great results. With the increased cost of energy, more importance has been placed on use of simulation to optimize the operation of gas pipelines. One of the biggest problems with using simulation in so many areas is that many different models from potentially different suppliers had to be used. This resulted in a high cost to implement and maintain several systems. This paper will show a simulation system that is capable of performing steady state and transient simulation, off-line and real time simulation, leak detection and optimization, all using a single modeling platform. Examples of field use of the system will show the benefits that can be realized.

Pipeline Rupture Detection Using Real-Time Transient Modelling and Convolutional Neural Networks

2018 ◽  
Author(s):  
Joel Smith ◽  
Jaehee Chae ◽  
Shawn Learn ◽  
Ron Hugo ◽  
Simon Park
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Detection System ◽  
High Reliability ◽  
Leak Detection ◽  
Sudden Onset ◽  
False Alarms ◽  
Pipeline System ◽  
Transient Model ◽  
Social License

Demonstrating the ability to reliably detect pipeline ruptures is critical for pipeline operators as they seek to maintain the social license necessary to construct and upgrade their pipeline systems. Current leak detection systems range from very simple mass balances to highly complex models with real-time simulation and advanced statistical processing with the goal of detecting small leaks around 1% of the nominal flow rate. No matter how finely-tuned these systems are, however, they are invariably affected by noise and uncertainties in a pipeline system, resulting in false alarms that reduce system confidence. This study aims to develop a leak detection system that can detect leaks with high reliability by focusing on sudden-onset leaks of various sizes (ruptures), as opposed to slow leaks that develop over time. The expected outcome is that not only will pipeline operators avoid the costs associated with false-alarm shut downs, but more importantly, they will be able to respond faster and more confidently in the event of an actual rupture. To accomplish these goals, leaks of various sizes are simulated using a real-time transient model based on the method of characteristics. A novel leak detection model is presented that fuses together several different preprocessing techniques, including convolution neural networks. This leak detection system is expected to increase operator confidence in leak alarms, when they occur, and therefore decrease the amount of time between leak detection and pipeline shutdown.

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