Leak Quantification Research Articles

A novel case of simultaneous tracheal stenting and endobronchial valve (EBV) deployment for tracheal stenosis and persistent air leak guided by an endobronchial collateral ventilation assessment system and digital chest drain in malignant esophageal carcinoma.

Persistent air leak may complicate malignant disease of the thorax, causing significant morbidity and mortality. A 51-year-old male with a 30-pack-year history of smoking was diagnosed with metastatic esophageal carcinoma with invasion into the right upper lobe of the lung. He developed a large right hydropneumothorax complicated by empyema leading to persistent air leak despite the insertion of two chest drains. Computed Tomography imaging with 3-dimensional reconstruction showed severe tracheal compression from the enlarging esophageal tumour as well as bronchopleural fistulas in the right upper lobe. Rigid bronchoscopy with metallic tracheal stenting was performed. This was followed by localization and quantification of air leak with an endobronchial collateral ventilation assessment system and a digital chest drain to guide endobronchial valve placement, in a single operative procedure. This novel combination of interventional bronchoscopy techniques enabled successful transition to an ambulatory chest drain and subsequent hospital discharge.

Characterisation of pulmonary air leak measurements using a mechanical ventilator in a bench setup

Prolonged air leakage (AL) following pulmonary resections leads to prolonged hospital stay and post-operative complications. Intra- and postoperative quantification of AL might be useful for improving treatment decisions, but these measurements have not been characterised. AL calculations based on inspiratory and expiratory tidal volumes were investigated in an Intensive Care Unit mechanical ventilator circuit (Servo-I). AL was also measured by a digital chest drainage system. This study shows that AL measurements increase in accuracy when corrected for baseline deviations (R: 0.904 > 0.997, p < 0.001). Bland-Altman analysis revealed a funnel-shape, indicative of a detection threshhold. Corrected measurements were most accurate when averaged over five breaths and AL was >500 mL/min, with an estimated mean systemic bias of 7.4% (95%-limits of agreement [LoA]: 1.1%-13.7%) at 500 mL/min air leak. Breath-by-breath analysis showed most accurate results at AL >20 mL/breath (R: 0.989–0.991, p < 0.001) at tidal volumes between 350–600 mL. The digital drain had a mean systemic bias of −11.1% (95%-LoA: −18.9% to −3.3%) with homogenous scatter in Bland-Altman analysis and a strong correlation to the control measurement over a large range (0–2000mL/min, R: 0.999, p < 0.001). This study indicates that the Servo-I can be used for air leak quantification in clinically relevant ranges (>500 mL/min), but is unsuited for small leak detection due to a detection threshold. Researchers and clinicians should be aware of varying accuracy and interoperability characteristics between AL measurement devices.

Relative humidity prediction of a leakage area for small RCS leakage quantification by applying the Bi-LSTM neural networks

In nuclear power plants, reactor coolant leakage can occur due to various reasons. Early detection of leaks is crucial for maintaining the safety of nuclear power plants. Currently, a detection system is being developed in Korea to identify reactor coolant system (RCS) leakage of less than 0.5 gpm. Typically, RCS leaks are detected by monitoring temperature, humidity, and radioactivity in the containment, and a water level in the sump. However, detecting small leaks proves challenging because the resulting changes in the containment humidity and temperature, and the sump water level are minimal. To address these issues and improve leak detection speed, it is necessary to quantify the leaks and develop an artificial intelligence-based leak detection system. In this study, we employed bidirectional long short-term memory, which are types of neural networks used in artificial intelligence, to predict the relative humidity in the leakage area for leak quantification. Additionally, an optimization technique was implemented to reduce learning time and enhance prediction performance. Through evaluation of the developed artificial intelligence model's prediction accuracy, we expect it to be valuable for future leak detection systems by accurately predicting the relative humidity in a leakage area.

Daily detection and quantification of methane leaks using Sentinel-3: a tiered satellite observation approach with Sentinel-2 and Sentinel-5p

The twin Sentinel-3 satellites have multi-band radiometers which observe in methane-sensitive shortwave infrared bands with daily global coverage and 500 m ground pixel resolution. We investigate the methane observation capability of Sentinel-3 and how its coverage-resolution combination fits between Sentinel-5p and Sentinel-2 within a tiered observation approach for methane leak monitoring. Sentinel-5p measures methane with high precision and daily global coverage, allowing worldwide leak detection but with a coarse spatial resolution of 7 km × 5.5 km. The Sentinel-2 twin satellites have multi-band instruments that can identify source locations of major leaks (> 1 t/h) with their methane observations of 20 m resolution under favorable observational conditions, but these satellites lack daily global coverage.We show that methane enhancements can be retrieved from the shortwave infrared band measurements of Sentinel-3. We report the lowest emission detections by Sentinel-3 in the 8-20 t/h range, depending on location and wind conditions. We demonstrate Sentinel-3's capability of identification and monitoring of methane leaks using two case studies. Near Moscow, Sentinel-3 shows that two major short-term leaks, separated by 30 km, occurred simultaneously at a gas pipeline and appear as a single methane plume in Sentinel-5p data. For another Sentinel-5p leak detection near the Hassi Messaoud oil/gas field in Algeria, Sentinel-3 identifies the leaking facility emitting continuously for 6 days, and Sentinel-2 pinpoints the source of the leak at an oil/gas well. Sentinel-2 and Sentinel-3 also show the 6-day leak was followed by a four-month period of burning of the leaking gas, suggesting a gas well blowout to be the cause of the leak. We find similar source rate quantifications from plume detections by Sentinel-3 and Sentinel-2 for these leaks, demonstrating Sentinel-3's utility for emission quantification. We show that zooming in with Sentinel-3 and Sentinel-2 in synergy allows precise identification, quantification, and monitoring of the sources corresponding to methane plumes observed in Sentinel-5p's global scans.

Quantitative DECT of Iodine in Chronic Subdural Hematoma as Surrogate of Membrane Exudation: A Pilot Feasibility Study.

We explore the feasibility to estimate the exudation from chronic subdural hematoma (CSDH) membranes, by using dual-energy computed tomography (DECT) quantification of iodine leak and test if the derived quantitative variables and membrane morphology correlates with hematoma volume, internal architecture (homogeneous, laminar, separated, and trabecular types), and fractional hyperdense hematoma at presentation. In this retrospective study, consecutive CSDH patients with postcontrast DECT head images from January 2020 and June 2021 were analyzed. Predictor variables derived from DECT were correlated with outcome variables followed by mixed-effects regression analysis. The study included 36 patients with 50 observations (mean age, 72.6 years; standard deviation, 11.6 years); 31 were men. Dual-energy CT variables that correlated with hematoma volume were external membrane volume (ρ, 0.37; P = 0.008) and iodine concentration (ρ, -0.29; P = 0.04). Variables that correlated with separated type of hematoma were total iodine leak (median [Q 1 , Q 3 ], 68.3 mg [48.5, 88.9] vs 38.8 mg [15.5, 62.9]; P = 0.001) and iodine leak per unit membrane volume (median [Q 1 , Q 3 ], 16.47 mg/mL [10.19, 20.65] vs 8.68 mg/mL [5.72, 11.41]; P = 0.002). Membrane grade was the only variable that correlated with fractional hyperdense hematoma (ρ, 0.28; P = 0.05). Regression analysis showed total iodine leak as the strongest predictor of separated type hematoma (odds ratio [95% confidence interval], 1.06 per mg [1.01, 1.1]). Dual-energy CT demonstrates iodine leak from CSDH membranes. The variables derived from DECT correlated with hematoma volume, internal architecture, and fractional hyperdense hematoma.

Quantification of paravalvular leaks associated with TAVI implants using 4D MRI in an aortic root phantom made possible by the use of 3D printing.

Transcatheter aortic valve implantation (TAVI) has become an alternative to surgical replacement of the aortic valve elderly patients. However, TAVI patients may suffer from paravalvular leaks (PVL). Detecting and grading is usually done by echocardiography, but is limited by resolution, 2D visualization and operator dependency. 4D flow magnetic resonance imaging (MRI) is a promising alternative, which did not reach clinical application in TAVI patients. The aim of this study was applying 3D printing technologies in order to evaluate flow patterns and hemodynamics of PVLs following TAVI, exploiting 4D flow MRI and standard ultrasound. An MR-compatible, anatomically left ventricle, aortic root, and ascending aorta model was fabricated by combining 3D-printed parts and various soft silicone materials to match physiological characteristics. An Abbott Portico™ valve was used in continuous antegrade flow (12-22 l/min), retrograde flow with varying transvalvular pressures (60-110 mmHg), and physiological pulsatile hemodynamics (aortic pressure: 120/80 mmHg, cardiac output: 5 l/min) Time-resolved MR measurements were performed above and below the TAVI stent and compared with color Doppler ultrasound measurements in exactly the same setup. The continuous antegrade flow measurements from MRI largely agreed with the flowmeter measurements, and a maximum error of only 7% was observed. In the retrograde configuration, visualization of the paravalvular leaks was possible from the MR measurements, but flow was overestimated by up to 33%. The 4D MRI measurement in the pulsatile setup revealed a single main PVL, which was also confirmed by the color Doppler measurements, and velocities were similar (2.0 m/s vs. 1.7 m/s). 4D MRI techniques were used to qualitatively assess flow in a patient-specific, MR-compatible and flexible model, which only became possible through the use of 3D printing techniques. Flow patterns in the ascending aorta, identification and quantification of PVLs was possible and the location and extent of PVLs were confirmed by ultrasound measurements. The 4D MRI flow technique allowed evaluation of flow patterns in the ascending aorta and the left ventricle below the TAVI stent with good results in identifying PVLs, demonstrating its capabilities over ultrasound by providing the ability to visualize the paravalvular jets in three dimensions at however, additional expenditure of time and money.

PO-698-08 COMPARING CARDIAC COMPUTED TOMOGRAPHY AND TRANSESOPHAGEAL ECHOCARDIOGRAPHY IN POST-OPERATIVE LEAK AFTER LEFT ATRIAL APPENDAGE CLOSURE DEVICE PLACEMENT

Left atrial appendage closure (LAAC) devices are a practical replacement to long term oral anticoagulation in the appropriate patient. Incomplete occlusion and resulting device leak are important clinical endpoints which may prompt anticoagulation continuation. During the coronavirus pandemic, cardiac computed tomography (CCT) was used as an alternative to transesophageal echocardiogram (TEE) for pre-planning and post-operative confirmation. A residual leak of >5mm on TEE has been used as a cutoff for anticoagulation continuation, but CCT is less codified for device leak quantification and its significance.

Source apportionment and quantification of liquid and headspace leaks from closed system drug-transfer devices via Selected Ion Flow Tube Mass Spectrometry (SIFT-MS).

A system to differentiate and quantify liquid and headspace vapor leaks from closed system drug-transfer devices (CSTDs) is presented. CSTDs are designed to reduce or eliminate hazardous drug (HD) exposure risk when compounding and administering HDs. CSTDs may leak liquid, headspace, or a mixture of the two. The amount of HD contained in liquid and headspace leaks may be substantially different. Use of a test solution containing two VOCs with differences in ratios of VOC concentrations in the headspace and liquid enables source apportionment of leaked material. SIFT-MS was used to detect VOCs from liquid and headspace leaks in the vapor phase. Included in this report is a novel method to determine the origin and magnitude of leaks from CSTDs. A limit of leak detection of 24 μL of headspace vapor and 0.14 μL of test liquid were found using Selected Ion Flow Tube Mass Spectrometry (SIFT-MS).

Remote quantification of methane leaks in the laboratory and in biogas plants

ABSTRACT Gas leaks can occur not only in industrial environments such as refineries but also in biogas plants. The main compound of the emitted biogas is methane, which is a greenhouse gas with a higher global warming potential than carbon dioxide (CO). Considering that the climate change and the reduction of greenhouse gases are becoming more and more important, it is crucial to be able to not only localize but also to quantify methane leakages. Based on the quantification of methane leakages, not only the effect of the effluent gases to the atmosphere but also the economic loss can be estimated. Another aspect is safety: biogas consists of different gases, mainly methane which can create an explosive mixture with air, but also hydrogen sulphide, which is toxic. This motivates remotely measuring the gas emissions. In this paper a remote measurement system and model is presented to estimate the methane volume flow due to a leak based on infrared optical sensors and sensor data fusion. The sensors are calibrated and the system is tested in the laboratory as well as in biogas plants. The laboratory results show that the measurement model allows an estimation of the methane volume flow if the assumptions of the measurement model are met. The highest relative deviations occur for small reference methane volume flows while the absolute deviations are similar. In contrast to the laboratory measurements the results of the measurements in biogas plants show partially high deviations from the reference. These deviations can have multiple reasons which cannot be determined for each single case because many of them occur at the same time. Future work includes improvements in order to reduce the deviations of the methane volume flow estimation. This could be done not only by improving the processing steps of the velocity estimation but also by using more accurate sensors.

Quantification of air leakage paths: a comparison of airflow and acoustic measurements

Today, the fan pressurization method is the most frequently used method to evaluate a building's airtightness. However, the localization and quantification of leaks remain difficult. In this paper, an acoustic method is introduced to estimate the leakage size of single leaks. Acoustic and airflow measurements were conducted and compared in laboratory tests within the same boundary conditions. This work aims to investigate if various leak sizes can be predicted using acoustic measurement methods. The test apparatus consists of two chambers, separated by a test wall. This wall represents a single characteristic air leakage path. Various types of wall structures with different slit geometries, wall thicknesses, and insulation materials were investigated. The acoustic measurements were performed with a sound source placed in one chamber and ultrasonic microphones located in both chambers. These results were compared to measured airflows through the test wall to provide estimates of uncertainty in the acoustic approach, which indicate a linear trend. Finally, these laboratory measurements were compared to the same measurements at a real office building. Although the acoustic measurement uncertainty is still significant (greater than +/- 50%), the acoustic method has the potential to give an order of magnitude of single leak sizes.

An integrated approach for non-revenue water reduction in water distribution networks based on field activities, optimisation, and GIS applications

This paper describes the development of an integrated approach for water pipe network calibration and lea quantification. The proposed approach provides a practical procedure that merges field measurements and mathematical modeling for leak quantification and network calibration. The use of Evolutionary Algorithms (EA) using both Genetic Algorithms (GA) and Shuffled Complex Evolution – University of Arizona (SCE-UA) to calculate the pinpointed leak outflows well as to identify any faulty meters. Also, by treating pinpointed physical leaks as junction points, the model, via EPAnet connection, calibrates the network and calculates their demands (which is equivalent to physical losses) and estimating pipes roughness factor (CHW) for better network calibration. Besides, throughout the process, the developed model uses GA and SCE-UA but departs from traditional use in using floating-point representations and introducing a new self-adaptive constraint handling function, which yields optimal results in fewer generations (model runs). Two pilot networks are selected, a well-known hypothetical network (Hanoi network) to present the general mathematical model, while a real network (Faisal city network) is used to test the integrated approach. The model integrates EPAnet for the required hydraulic modeling during the simulation and GIS for input data integration and output representation during the whole procedure. The results prove the approach's accuracy and efficiency.

Peridevice Leak Following Amplatzer Left Atrial Appendage Occlusion: Cardiac Computed Tomography Classification and Clinical Outcomes.

This study aimed to investigate cardiac computed tomography (CT) and transesophageal echocardiography (TEE) peridevice leak (PDL) assessments, and the clinical relevance of PDL. PDL assessment is integral during follow-up after left atrial appendage (LAA) occlusion. Comparative studies of TEE and cardiac CT are sparse, and the clinical relevance of PDL is uncertain. This was a single-center observational study of consecutive patients undergoing LAA occlusion with Amplatzer devices (Amplatzer Cardiac Plug/Amulet) between 2010 and 2018 (N=415). Patients with both 8-week CT and TEE were included for analysis (n=346). Images were analyzed by blinded investigators (K.K. and A.S.). PDL on cardiac CT was classified from grade 1 to 3, based on PDL at the device disc, device lobe, and LAA contrast patency. Primary clinical outcome was a composite of ischemic stroke, transient ischemic attack, systemic embolism, or all-cause death. PDL was present in 110 patients (32%) by TEE, with 29 (8%) >3mm. By cardiac CT, 210 patients (61%) had PDL at the disc, with contrast patency in 204 patients (59%). A grade 3 PDL (gap at disc, lobe, and LAA contrast patency) was present in 63 patients (18%). Bland-Altman analysis showed poor agreement between CT and TEE for leak sizing. CT and TEE detected PDL was not significantly associated with worse outcome, hazard ratio: 1.82 (95 % confidence interval: 0.95 to 3.50); p=0.07 and hazard ratio: 1.43 (95% confidence interval: 0.74 to 2.76); p=0.28, respectively. PDL occurrence is substantially higher with CT compared with TEE, with a large discrepancy between modalities in leak quantification. A novel CT-based classification is proposed, yet PDL was not associated with worse clinical outcome.

An Advanced Sensor Placement Strategy for Small Leaks Quantification Using Lean Graphs

Small leaks in water distribution networks have been a major problem both economically and environmentally, as they go undetected for years. We model the signature of small leaks as a unique Directed Acyclic Graph, called the Lean Graph, to find the best places for k sensors for detecting and locating small leaks. We use the sensors to develop dictionaries that map each leak signature to its location. We quantify leaks by matching out-of-normal flows detected by sensors against records in the selected dictionaries. The most similar records of the dictionaries are used to quantify the leaks. Finally, we investigate how much our approach can tolerate corrupted data due to sensor failures by introducing a subspace voting based quantification method. We tested our method on water distribution networks of literature and simulate small leaks ranging from [0.1, 1.0] liter per second. Our experimental results prove that our sensor placement strategy can effectively place k sensors to quantify single and multiple small leaks and can tolerate corrupted data up to some range while maintaining the performance of leak quantification. These outcomes indicate that our approach could be applied in real water distribution networks to minimize the loss caused by small leaks.

Catadioptric Stereo Optical Gas Imaging System for Scene Flow Computation of Gas Structures

The need for reducing greenhouse gas emissions from industrial facilities has motivated the development of new and more reliable techniques for gas leak localization and quantification. Optical gas imaging (OGI) systems offer a fast and intuitive approach by exploiting the absorption properties of gases, such as methane, in the infrared range. Based on this, several efforts have been made in the recent years for gaining additional quantitative information from the measurement data, e.g. gas concentration or gas velocity. In this work, a catadioptric stereo OGI system based on four planar mirrors and an OGI camera is proposed for computing spatio-temporal (also referred to as scene flow) information from stereo gas images. The proposed system represents a way to reduce the effects of temporal and radiometric differences and the cost and size of two-camera-based stereo OGI systems and leads to more reliable results under the tested conditions.

INCREASING THE ROBUSTNESS OF CLASSIFICATION ALGORITHMS TO QUANTIFY LEAKS THROUGH OPTIMIZATION

Leaks in water pipeline networks have cost billions of dollars each year. Robust leak quantification (to detect and to localize) methods are needed to minimize the lost. We quantify leaks by classifying their locations using machine learning algorithms, namely Support Vector Machine and C4.5. The algorithms are chosen due to their high performance in classification. We simulate leaks at different positions at different sizes and use the data to train the algorithms. We tune the algorithm by optimizing the algorithms' parameters in the training process. Then, we tested the algorithms' models against real observation data. We also experimented with noisy data, due to sensor inaccuracies, that often happen in real situations. Lastly, we compared the two algorithms to investigate how accurate and robust they localize leaks with noisy data. We found that C4.5 is more robust against noisy data than SVM.

Intra-procedural monitoring protocol using routine transthoracic echocardiography with backup trans-oesophageal probe in transcatheter aortic valve replacement: a single centre experience.

The aim of this study is to describe our 9-year experience in transcatheter aortic valve replacement (TAVR) using transthoracic echocardiography (TTE) as a routine intra-procedural imaging modality with trans-oesophageal echocardiography (TEE) as a backup. From January 2008 to December 2017, 1218 patients underwent transfemoral TAVR at our Institution. Except the first 20 cases, all procedures have been performed under conscious sedation, with fluoroscopic guidance and TTE imaging monitoring. Once the TTE resulted suboptimal for final result assessment or a complication was either suspected or identified on TTE, TEE evaluation was promptly performed under general anaesthesia. Only 24 (1.9%) cases required a switch to TEE: 6 cases for suboptimal TTE prosthetic valve leak (PVL) quantification; 12 cases for haemodynamic instability; 2 cases for pericardial effusion without haemodynamic instability; 4 cases for urgent TAVR. The 30-days and 1-year all-cause mortality were 2.1% and 10.2%, respectively. Cardiac mortality at 30-days and 1-year follow-up were 0.6% and 4.1%, respectively. Intra-procedural and pre-discharge TT evaluation showed good agreement for PVL quantification (k agreement: 0.827, P = 0.005). TTE monitoring seems a reasonable imaging tool for TAVR intra-procedural monitoring without delay in diagnosis of complications and a reliable paravalvular leak assessment. However, TEE is undoubtedly essential in identifying the exact mechanism in most of the complications.

Quantification of adherens junction disruption and contiguous paracellular protein leak in human lung endothelial cells under septic conditions.

Sepsis is associated with dysfunction of MVEC resulting in organ edema and inflammation. VE-cadherin, a component of MVEC adherens junctions, may be disrupted in sepsis. However, the direct connection between individual MVEC VE-cadherin disruption and increased paracellular permeability is uncertain. Human pulmonary MVEC were cultured on a biotin matrix and treated with cytomix, as a model of sepsis, vs PBS. MVEC permeability was assessed by trans-MVEC monolayer leak of Oregon green 488-conjugated avidin, which bound subcellular biotin to localize sites of paracellular leak. Leak was correlated with individual cell-specific MVEC surface VE-cadherin continuity by fluorescence microscopy. Cytomix treatment reduced total MVEC VE-cadherin density, disrupted surface VE-cadherin continuity, was associated with intercellular gap formation, and enhanced paracellular avidin leak. Cytomix-induced MVEC paracellular avidin leak was strongly correlated temporally and was highly contiguous with focal MVEC surface VE-cadherin disruption. Total cellular VE-cadherin density was less strongly correlated with MVEC paracellular avidin leak and individual cell-specific focal surface VE-cadherin discontinuity. These data support a mechanistic link between septic human lung MVEC VE-cadherin disruption and contiguous paracellular protein leak, and will permit more detailed assessment of individual cell-specific mechanisms of septic MVEC barrier dysfunction.

Preclinical quantification of air leaks in a physiologic lung model: effects of ventilation modality and staple design.

PurposeThoracic air leaks are a common complication following pulmonary resections. Limitations in clinical studies and preclinical models have hindered efforts to understand the pathophysiology of air leaks. With an emphasis on staple-line specific air leaks, we hypothesize that ventilation modality – intraoperative positive pressure vs postoperative negative pressure – and stapler design may play a role in air leaks.MethodsUsing a novel physiologic lung model, air leaks associated with graduated and uniform staple designs were evaluated under positive and negative pressure ventilation, simulating perioperative breathing in porcine lungs. Air leak incidence, air leak volume, and air leak rate were captured along with ventilation pressure and tidal volume.ResultsIn all cases, negative pressure ventilation was associated with a higher occurrence of leaks when compared to positive pressure ventilation. Lungs leaked more air and at a faster rate under negative pressure ventilation compared to positive pressure ventilation. Graduated staple designs were associated with higher occurrence of leaks as well as larger leak rates when compared to uniform staples. Tissue thickness was not associated with differences in air leaks when tested with appropriate staple heights.ConclusionUsing a novel lung model to investigate the pathophysiology of air leaks, we have identified breathing modality and staple design as two important variables that may impact air leaks. This work will help guide device design and drive future studies in human tissue, and it may help inform clinical practice to ultimately improve patient outcomes.

Natural Gas Fugitive Leak Detection Using an Unmanned Aerial Vehicle: Measurement System Description and Mass Balance Approach

Natural gas is an abundant resource across the United States, of which methane (CH4) is the main component. About 2% of extracted CH4 is lost through leaks. The Remote Methane Leak Detector (RMLD)-Unmanned Aerial Vehicle (UAV) system was developed to investigate natural gas fugitive leaks in this study. The system is composed of three major technologies: miniaturized RMLD (mini-RMLD) based on Backscatter Tunable Diode Laser Absorption Spectroscopy (TDLAS), an autonomous quadrotor UAV and simplified quantification and localization algorithms. With a miniaturized, downward-facing RMLD on a small UAV, the system measures the column-integrated CH4 mixing ratio and can semi-autonomously monitor CH4 leakage from sites associated with natural gas production, providing an advanced capability in detecting leaks at hard-to-access sites compared to traditional manual methods. Automated leak characterization algorithms combined with a wireless data link implement real-time leak quantification and reporting. This study placed particular emphasis on the RMLD-UAV system description and the quantification algorithm development based on a mass balance approach. Early data were gathered to test the prototype system and to evaluate the algorithm performance. The quantification algorithm derived in this study tended to underestimate the gas leak rates and yielded unreliable estimations in detecting leaks under 7 × 10 − 6 m3/s (~1 Standard Cubic Feet per Hour (SCFH)). Zero-leak cases can be ascertained via a skewness indicator, which is unique and promising. The influence of the systematic error was investigated by introducing simulated noises, of which Global Positioning System (GPS) noise presented the greatest impact on leak rate errors. The correlation between estimated leak rates and wind conditions were investigated, and steady winds with higher wind speeds were preferred to get better leak rate estimations, which was accurate to approximately 50% during several field trials. High precision coordinate information from the GPS, accurate wind measurements and preferred wind conditions, appropriate flight strategy and the relative steady survey height of the system are the crucial factors to optimize the leak rate estimations.

Online leak diagnosis in pipelines using an EKF-based and steady-state mixed approach

This paper proposes a methodology for leak detection and isolation (LDI) in pipelines based on data fusion from two approaches: a steady-state estimation and an Extended Kalman Filter (EKF). The proposed method considers only pressure head and flow rate measurements at the pipeline ends, which contain intrinsic sensor and process noise. The LDI system is tested in real-time by using an USB data acquisition device that is implemented in MATLAB environment. The effectiveness of the method is analyzed by considering: online detection, location as well as quantification of non-concurrent leaks at different positions. The leak estimation error average is less than 1% of the flow rate and less than 3% in the leakage position. Furthermore, the incorporation of a steady-state estimation shows that the solution of the LDI problem has improved significantly with respect to the one that only considers the EKF estimation. An experimental analysis was also performed on the effectiveness of the proposed approach for different sampling rates and for different leakage positions.