Valve Leakage Research Articles

Comprehensive management of paravalvular mitral valve leakage through a transapical approach: a case study

Paravalvular leaks (PVL) following mitral valve replacement occur in 7% to 17% of cases, with 1% to 5% being clinically significant. Although surgical repair is often recommended, transcatheter PVL closures have shown positive outcomes with fewer complications. This case report discusses a patient with a severe paravalvular leak after aortic and mitral valve replacement treated via a transapical approach, evaluating outcomes and potential complications.

Enhancing commercial check valves in downhole pump applications through laboratory testing system development

In this study, we aim to enhance the performance and longevity of downhole pumps employed in crude oil extraction in the oil industry. Downhole pumps play a pivotal role in the rod-pump system, comprising traveling and standing valves that function similarly to ball check valves. However, these valves often experience premature wear and tear. To address this concern, we embarked on experiments involving various check valve alternatives to conventional ball valves within downhole pumps. The testing conditions were controlled precisely. Furthermore, we evaluated four distinct check valve types, the original (representing the incumbent ball valves), spring-poppet (C), spring-ball (CB), and spring-poppet with soft-seated (S6C) check valves, within a controlled laboratory environment. We employed a TEXAPON N70 solution to replicate the properties and temperature conditions of crude oil. A portable ultrasonic flow meter was used to quantify the pump flow rate and assess its volumetric efficiency. In addition, we recorded data on the polished-rod load and plunger displacement to generate dynamometer cards, thereby enabling a comprehensive evaluation of the operational performance of the pump. Furthermore, we conducted a vacuum test to scrutinize valve leakage, which is a crucial indicator of the operational lifespan of a downhole pump. Our findings show that incorporating the CB check valve with the RHB pump in oil wells operated by the PTT Exploration and Production Public Company Limited (PTTEP) could result in a 15 % increase in volumetric efficiency and a remarkable 160 % improvement in durability compared to the original ball check valve.

Multi-objective optimization design of low-power-driven, large-flux, and fast-response three-stage valve

Intrinsically safe solenoids drive solenoid valves in coal mining equipment. The low power consumption of these solenoids limits the response time of the solenoid valves. Additionally, the low viscosity and high susceptibility to dust contamination of the emulsion fluid often lead to leakage and sticking of hydraulic valves. This study proposes a low-power-driven, large-flux, fast-response three-stage valve structure with an internal displacement feedback device to address these issues. The critical parameters of the valve were optimized using a novel multi-objective optimization algorithm. A prototype was manufactured based on the obtained parameters and subjected to simulation and experimental verification. The results demonstrate that the valve has an opening time of 21 ms, a closing time of 12 ms, and a maximum flow rate of approximately 225 L/min. The driving power of this structure is less than 1.2 W. By utilizing this valve for hydraulic cylinder control, a positioning accuracy of ± 0.15 mm was achieved. The comparative test results show that the proposed structural control error fluctuation is smaller than that of the 3/4 proportional valve.

Physical model and Bayesian theory based hydraulic component fault diagnosis method

Hydraulic components are integral parts of hydraulic systems, and their failures directly impact the normal operation of hydraulic systems. Due to the dynamic variation of working pressure in hydraulic components with load, it is challenging to diagnose faults of hydraulic components under dynamic pressure conditions using existing methods. This paper focuses on the research of internal leakage faults in hydraulic directional control valves and proposes a fault diagnosis method based on physical model and Bayesian theory for hydraulic components. Firstly, this method investigates the working fault mechanism of hydraulic directional control valves and constructs an internal leakage model. Then, correlation analysis is introduced to select fault feature signals, and principal component analysis is adopted to construct internal leakage features. Finally, based on Bayesian model, Markov chain Monte Carlo sampling, and internal leakage features, the parameters of the internal leakage model are estimated to achieve fault diagnosis of internal leakage in hydraulic directional control valves. Experimental results demonstrate that compared to several traditional fault diagnosis methods, the proposed method exhibits higher adaptability and accuracy under dynamic pressure conditions. This method, based on the internal leakage model and Bayesian theory, realizes fault diagnosis of hydraulic components under dynamic pressure conditions, avoiding the shortcomings of deep learning methods that rely on a large amount of fault data to train fault models.

A systematic approach for data generation for intelligent fault detection and diagnosis in District Heating

This study introduces a novel systematic approach to address the challenge of labeled data scarcity for fault detection and diagnosis (FDD) in District Heating (DH) systems. To replicate real-world DH fault scenarios, we have created a controlled laboratory emulation of a generic DH substation integrated with a climate chamber. Furthermore, we present an FDD pipeline using an isolation forest and a one-class support vector machine for fault detection alongside a random forest and a support vector machine for fault diagnosis. Our research analyzed the impact of data sampling frequencies on the FDD models, revealing that shorter intervals, such as 1-min and 5-min, significantly improve FDD performance. We provide detailed information on six scenarios, including normal operation, a minor valve leak, a valve leak, a stuck valve, a high heat curve, and a temperature sensor deviation. For each scenario, we present their signature, quantifying their unique behavior and providing deeper insights into the operational implications. The signatures suggest that, while variable, faults have a consistent pattern seen in the generic DH substation. While this work contributes directly to the DH field, our methodology also extends its applicability to a broader context where labeled data is scarce.

Percutaneous versus surgical closure of paravalvular leaks in prosthetic valves: A cross-sectional comparison of clinical outcomes.

Paravalvular leak (PVL) is a serious complication of prosthetic valve replacement. Both surgical and percutaneous closure techniques are used for PVL closure, but optimal strategies and comparative outcomes are uncertain. This study aimed to compare the efficacy and safety of percutaneous versus surgical PVL closure by analyzing changes in leak severity, functional status, echocardiographic parameters, and clinical outcomes. A total of 72 patients were included in this retrospective cross-sectional single-center study comparing percutaneous (n = 25) and surgical (n = 47) PVL closure from 2015 to 2022. Demographics, medical history, echocardiograms, laboratory data, complications, and mortality data were extracted from the records. Changes in leak severity, NYHA class, echocardiographic parameters, and clinical outcomes were compared between the percutaneous and surgical groups. Both percutaneous and surgical PVL closure significantly reduced leak severity and improved NYHA class (both p < 0.01), with no difference between the quantity of changes in each group. The 30-day mortality was 4% after percutaneous and 6.4% after surgical closure (p = 0.65). At 90 days, mortality was 24% percutaneous versus 17% surgical (p = 0.48). The length of stay in the hospital and post-procedural decrease in hemoglobin were considerably lower in the percutaneous group. The rate of complication rates was similar between the groups. Echocardiographic changes were also comparable. Percutaneous and surgical PVL closure had similar efficacy in reducing leaks and improving symptoms, with no significant difference in early outcomes. Both options should be considered viable for PVL repair after heart team evaluation.

EXPERIMENTAL INVESTIGATION INTO MAGNETORHEOLOGICAL FINISHING OF POLYMER VALVE SEAT SURFACE FOR BALL VALVE PERFORMANCE

A polymer valve seat is an essential component of ball valves. However, a gas pipeline valve leakage during the gas or oil transportation process causes major issues. Therefore, the fine finishing of the polymer valve seat is important. This work describes the effect of the magnetorheological finishing (MRF) process on the surface characteristics of the polymer valve seat. To achieve a finely finished polymer valve seat surface, the best process parametric combination of current, workpiece rotational, and tool rotational speed are obtained using the response surface methodology. The optimum process parameters are further used to enhance surface characteristics (including surface roughness, microhardness, and surface morphology) through fine finishing. Using the optimum process conditions, the surface roughness was reduced to 110[Formula: see text]nm from 570[Formula: see text]nm in 140[Formula: see text]min of finishing on a 4878[Formula: see text]mm2 surface area of the polymer valve seat. The circularity of the valve seat surface’s dimensional correctness is investigated further. The current MRF process can fine-finish the polymer valve seat surface consistently, resulting in improved surface characteristics and functional performance.

Research on internal leakage detection of the ball valves based on stacking ensemble learning

Abstract Natural gas is an important clean energy source that is mainly transported through pipelines. The ball valve is a crucial piece of control equipment for the pipeline transportation system for natural gas, and the failure of internal leakage of the ball valve will seriously affect the natural gas transmission and increase the risk of sudden safety accidents. In response to the problems of the limitations of a single machine learning model in the traditional ball valve internal leakage rate prediction methods and failure to qualitatively analyze unilateral and bilateral internal leakage recognition of ball valve, a study of ball valve internal leakage detection based on Stacking ensemble learning is proposed. A total of 15 time and frequency domain feature parameters were obtained by feature extraction of 125 and 96 sets of raw acoustic emission signals from the ball valve; the parameters of a single machine learning model were adjusted by Bayesian optimization grid search. An internal leakage rate prediction model and an internal leakage recognition model are constructed, and the proposed model is compared and analyzed with a single model through a field ball valve internal leakage test. The results indicate that the Stacking ensemble learning model outperforms each single machine learning model in terms of SMAPE (17.2583), RMSE (1.1009), and MAE (0.9375) for internal leakage rate prediction. The Stacking ensemble learning model outperformed the single machine learning model in terms of accuracy (1), recall (1), precision (1), FAR(0), and F1-score (1) for internal leakage recognition. Stacking ensemble learning significantly enhances the model's ability to detect internal ball valve leaks.&amp;#xD;

Comparative analysis of four classification algorithms for fault detection of heat pumps

Heat Pumps (HPs) technology had a remarkable diffusion and growth in the Heating, Ventilation, and Air-Conditioning (HVAC) field, with an increase predicted to be greater than 200% until 2030. Therefore, efficient asset management must be achieved by ensuring their maintainability and reliability. For this purpose, several methodologies have been used in the last years for HPs fault diagnosis. These methodologies include, with the advances of computational systems and reduced costs of several components, machine learning and other artificial intelligence techniques. In the present paper, a connection weight approach is used to identify the clout of each component for the fault detection (FD) of HPs. The results show that the method provides a more comprehensive assessment of the importance of each component, yielding a reduction of 50% of the features. A comparative analysis of supervised learning classification algorithms is performed, for fault detection of an air-to-air HP in cooling mode. Such algorithms include Naïve Bayes, Support Vector Machine, Logistic Regression, and K-nearest Neighbors. The faults considered include compressor and reversing valve leakage, improper condenser and evaporator fouling, liquid line restriction, refrigerant undercharge and overcharge, and also the presence of non-condensable gases. Algorithms are compared in terms of accuracy, precision, recall, and F1 Score. The best results were achieved with K-nearest Neighbors, since it presented the highest values for these four metrics, over 99% after a cross validation considering a reduced number of components. Naïve Bayes, Support Vector Machine, and Logistic Regression also achieved over 90% performance metrics. Other models were superficially analysed and Ridge Regression with metrics performance of 100%, on average, revealed to be a promising tool for fault diagnosis in HPs.

Detection of Gate Valve Leaks through the Analysis Fractal Characteristics of Acoustic Signal

This paper considers the possibility of using monofractal and multifractal analysis of acoustic signals to detect water leaks through gate valves. Detrended fluctuation analysis (DFA) and multifractal detrended fluctuation analysis (MF-DFA) were used. Experimental studies were conducted on a ½-inch nominal diameter wedge valve, which was fitted to a ¾-inch nominal diameter steel pipeline. The water leak was simulated by opening the valve. The resulting leakage rates for different valve opening conditions were 5.3, 10.5, 14, 16.8, and 20 L per minute (L/min). The Hurst exponent for acoustic signals in a hermetically sealed valve is at the same level as a deterministic signal, while the width of the multifractal spectrum closely matches that of a monofractal process. When a leak occurs, turbulent flow pulsations appear, and with small leak sizes, the acoustic signals become anticorrelated with a high degree of multifractality. As the leakage increases, the Hurst exponent also increases and the width of the multifractal spectrum decreases. The main contributor to the multifractal structure of leak signals is small, noise-like fluctuations. The analysis of acoustic signals using the DFA and MF-DFA methods enables determining the extent of water leakage through a non-sealed gate valve. The results of the experimental studies are in agreement with the numerical simulations. Using the Ansys Fluent software (v. 19.2), the frequencies of flow vortices at different positions of gate valve were calculated. The k-ω SST turbulence model was employed for calculations. The calculations were conducted in a transient formulation of the problem. It was found that as the leakage decreases, the areas with a higher turbulence eddy frequency increase. An increase in the frequency of turbulent fluctuations leads to enhanced energy dissipation. Some of the energy from ordered processes is converted into the energy of disordered processes.

Commissioning of the cryogenic distribution system of the ESS superconducting linac

The European Spallation Source (ESS) is a neutron-scattering facility being built with extensive international collaboration in Lund, Sweden. An essential part of the project is the linear 2.0 GeV proton accelerator. Its superconducting part is designed to comprise 13 spoke and 30 elliptical cryomodules that are cooled at 2K. The cryogenic distribution system (CDS) connects the refrigeration plant with the cryomodules via multi-transfer lines, individual valveboxes for every cryomodule and an endbox. It is designed, manufactured and installed under the responsibility of two ESS in-kind partners. The CDS for the spoke cryomodules (CDS-SL) is supplied by IJCLab, France, the CDS for the elliptical cryomodules (CDS-EL) is supplied by WUST, Poland. Pre-commissioning, commissioning and operation is done by ESS whereby IFJ PAN contributed with valuable advice. Pre-commissioning activities like loop checks, temperature curve validation, pressure sensor calibration or valve initialization and leak tightness tests followed after mechanical or electrical completion of the respective CDS parts and started in summer 2022. Eventually, the system was ready for commissioning and a first cooldown was performed in December 2022. Goal of this commissioning was to acceptance test and check off the system before pilot cryomodule installation in the tunnel started in March 2023. The paper describes diverse challenges regarding TAO and cryo operation. Test results, lessons learnt, and required modifications are discussed as well as preliminary results of retesting and an outlook.

Identification method of internal leakage in nuclear power plants valves using convolutional block attention module

Valves are indispensable fluid control devices widely employed in Nuclear Power Plant (NPP) structures. Due to prolonged exposure to high-temperature environments, the internal sealing components become susceptible to thermal deformation or wear, leading to compromised sealing and potential leakage accidents in the valves. Therefore, detecting internal leakage in valves holds great significance. We propose an effective acoustic emission detection device designed for identifying internal leakage in valves within high-temperature environments. A valve internal leakage monitoring system based on the Acoustic Emission (AE) method is developed, utilizing high-temperature piezoelectric transducers as AE sensors. To efficiently and rapidly identify leakage states, an artificial intelligence (AI) algorithm incorporating a Convolutional Neural Network (CNN) with the Convolutional Block Attention Module (CBAM) is employed. The approach integrates both a channel attention module and a spatial attention module to capture global and local features, respectively. Normalized spectral data is used as the training set to optimize the CNN parameters. The performance of this method is then compared with BAM and SENET. The results indicate that CBAM can effectively enhance and suppress features by allocating weights among channels according to task requirements. Moreover, it can more efficiently identify multiple damage features under the constraints of limited computing resources.

Intelligent condition monitoring with CNN and signal enhancement for undersampled signals

High-frequency signals like vibration and acoustic emission are crucial for condition monitoring, but their high sampling rates challenge data acquisition, especially for online monitoring. Our research developed a novel method for condition identification in undersampled signals using a modified convolutional neural network integrated with a signal enhancement approach. A frequency-domain filtering is applied to suppress similar sidebands and obtain more discriminative features of different conditions, followed by an interpolation-based upsampling in the time domain to restore the signal length and strengthen the low-frequency harmonic information. Enhanced signals are converted into two-dimensional grayscale images for neural network analysis. Tested on bearing datasets and real-world data from regenerative thermal oxidizer lift valve leakage, our method effectively extracts features from low-frequency signals, achieving over 95% fault identification accuracy.

Automated Gas Line Shut Off Mechanism Using Solenoid Operated Valve and Gas Leak Detector (At the Event of Gas Leakage in PNG Line)

Gas leaks that cause deadly flames have become a major issue in homes and other places where domestic gas is handled and utilized. Gas leaks cause a variety of mishaps that result in financial damage as well as personal injuries and/or loss. The project’s goal is to create a system that detects gas leaks and notifies the subscriber through alarm and status display, as well as shutting off the gas supply valve as the main safety precaution. The turning off of the supply valve prevents further gas flow to the cooker, preventing a fire breakout caused by an attempt to ignite the cooker. The device, which functions more like a first- aid kit, utilizes a usually closed solenoid valve to shut off the gas valve before asking for assistance via visual display and loud alert to anyone in the vicinity. The system is clever in that it does not cause a loud nuisance by constantly sounding the alarm, but rather the siren stops beeping once the concentration of the gas in the atmosphere after leaking falls below the predetermined value and the valve is opened again for regular operations. This effort will reduce injuries and losses caused by explosions caused by gas leaks, as well as enhance the safety of people and property while utilizing home cooking gas.

ANALISA KERUSAKAN POMPA OLI TEMPERATURE CONTROL UNIT PADA MESIN LONGITUDINAL STRECHER DITINJAU DARI KERUGIAN BIAYA PRODUKSI DI PT. POLIDAYAGUNA PERKASA UNGARAN

A pump is a machine that functions to move fluids by converting mechanical energy into fluid energy and pressure, transporting fluids through a piping system. Head, flow, efficiency, performance and performance are the main concerns for centrifugal pumps, these aspects can be used as benchmarks in choosing the type of pump that suits your needs. Damage to the TCU oil pump is caused by bearing damage due to lack of lubrication, shaft wear, damage to the couple and rubber couple, leaks in pipes and valves, leaks in the and pump mechanical seal. Various designs and configurations of centrifugal pumps have been carried out, both experimentally and in simulations with various configurations and variations. In short, this research will examine damage to the oil pump temperature control unit on longitudinal stretcher machines in terms of production cost losses at PT. POLYDAYAGUNA PERKASA Ungaran with a mathematical analysis approach. The research results show that the estimated loss in production costs due to damage to the TCU oil pump with within 6 months is IDR. 600,000,000,- and Rp. 120,000,000,- for pumps with mechanical seals. Estimated production cost losses for oil pumps with mechanical seals are highly recommended for use on longitudinal stretching machines because they are more efficient, but there must be further development.

Spreadsheet-Based Car Engine Temperature And Compression Pressure Gauge

Measuring the engine's temperature and compression pressure in cars is a crucial part of engine maintenance and performance evaluation. The objective of this study is to develop an accurate and efficient spreadsheet-based measurement system for determining engine temperature and compression pressure in automobiles. For this investigation, data from car engines was collected using engine temperature thermometers and compression pressure gauges. The collected data is then fed into a spreadsheet designed specifically to assess and automatically calculate engine temperature and compression pressure. The results show how reliable and accurate the measurements made using this spreadsheet-based measurement technique are. This approach's main benefits are also its flexibility and ease of use, since users can rapidly adapt the spreadsheet to the particular needs of the engine being tested. With this technology in place, car owners or professionals who do engine maintenance can quickly detect potential engine problems, such as valve leakage or unexpected temperature increases. Therefore, to increase fuel efficiency and extend engine life, spreadsheets can be utilized as a tool for measuring engine performance. The goal of this project is to facilitate the work of auto repair shop owners by utilizing the Esp8266 microcontroller for the DS18b20 sensor and compression sensor. Even so, there are several difficulties, like a sluggish internet connection that delays uploading data to the LCD and spreadsheets that are less useful because of a bad internet connection.

A novel order-separated generalized feedforward design for motion control in energy-efficient electrohydraulic system with proportional and integral feedback

Existing feedforward, or FF, controllers are based on differentially flat models. For double-acting single-rod cylinders, more compact than the double-rod ones, flat models could be constructed either under an incompressible-flow assumption for low-pressure, slow-response applications or for a matched valve-cylinder combination. Contrasting the existing models tackling only a single nonlinear aspect like valve leakage, oil compressibility or friction, a novel FF controller, generalized for different types of valve-cylinder-pump combinations, has been developed here. It is based on the highest-order assumption of incompressible flow that sustains the piston motion. An FFPI controller has been implemented in a laboratory setup for displacement tracking against sinusoidal demands up to 9 Hz frequency. The FF parameters has been estimated by minimizing the deviation of simulation prediction from an offline experimental time-varying response. The PI gains have been selected through a stability analysis by extending Routh criteria for linearized time-variant error dynamics. Comparison against a PI-only controller with identical gains has established the energy-saving potential of the FFPI controller both working with the same variable-displacement pump. In comparison to existing nonlinear adaptive controllers, more precise and smoother responses have been obtained over wider frequency range at lower control expenses, admittedly with occasional marginal penalty in the phase variation. The FFPI controller has exhibited the shortest transient and the highest resilience against measurement noise.

A patient with Tuberculous para-valvular leak and tuberculous hepatic abscesses treated conservatively with anti-tuberculous medication without the need for surgical intervention. “Case report”

Introduction: We report a case of a young lady with rheumatic heart disease who underwent mechanical prosthetic mitral valve replacement and tricuspid valve repair. The case was complicated after one year by multi system tuberculous abscesses, para-valvular leak and hemolytic anemia. Case summary: The case started one year following mechanical prosthetic mitral valve replacement, and after contact with a tuberculous patient. The lady developed, sterile pyuria, two tuberculous hepatic abscesses, and a big pelvic tuberculous abscess. She first needed percutaneous drainage for the pelvic abscess followed by laparotomy and surgical drainage after recurrence. The case was complicated by Para-valvular leak in the prosthetic mitral valve detected by Transoesophageal echocardiography as well as refractory hemolytic anemia needing multiple transfusions. She required six months of anti-tuberculous therapy for the hemolysis to stop. Treatment continued for a total of one year of anti-tuberculous therapy. The patient restored normal valve dynamics and hematological parameters without the need for surgical intervention for the para-valvular leak. Conclusion: We report this case to show that small tuberculous para-valvular leak and hemolytic anemia as well as tuberculous hepatic abscesses can be treated medically as an alternative option to the well-known and recommended surgical indication. We also confirm delayed healing of the abdominal surgical wound due to tuberculosis.

A New Calculation Method of Well Leakage in Gas Well with Annular Pressure

The gradual promotion of the concept of gas well integrity has made major oil and gas fields pay more and more attention to the integrity management and evaluation of gas wells with annular pressure. Annular leakage rate is one of the key parameters for gas well integrity evaluation. However, the leakage rate measurement of high-temperature, high-pressure, and acid-containing gas wells has high risks and costs, which are often difficult to obtain in field operations. In order to obtain the bottom hole leakage rate parameters of the gas well to assist the integrity evaluation, this article is based on the safety valve leakage model and the small hole leakage model, combined with the characteristics of the gas well with annulus pressure, the idea of applying the annulus leakage rate calculation from the perspective of model mechanism is analysed, and the model parameters are clarified as well. The application of the two leak models is compared by case wells calculation, which verifies their rationality and feasibility. The research of this paper provides a theoretical basis for the leakage evaluation of gas well with annular pressure, and promotes development of gas well integrity management research.

RNA sequencing provides novel insights into the pathogenesis of naturally occurring myxomatous mitral valve disease stage B1 in beagle dogs.

Myxomatous mitral valve disease (MMVD) is the most common cardiovascular disorder in dogs with a high prevalence, accounting for approximately 75% of all canine heart disease cases. MMVD is a complex disease and shows variable progression from mild valve leakage to severe regurgitation, potentially leading to heart failure. However, the molecular mechanisms and age-related changes that govern disease progression, especially at the early stage (B1) before the development of discernable clinical signs, remain poorly understood. In this prospective study, we aimed to compare gene expression differences between blood samples of aged beagle dogs with stage B1 MMVD and those of healthy controls using RNA sequencing. Clinical evaluation was also conducted, which revealed minimal differences in radiographic and echocardiographic measurements despite distinct biomarker variations between the two groups. Comparative transcriptomics revealed differentially expressed genes associated with extracellular matrix remodeling, prostaglandin metabolism, immune modulation, and interferon-related pathways, which bear functional relevance for MMVD. In particular, the top 10 over- and under-expressed genes represent promising candidates for influencing pathogenic changes in MMVD stage B1. Our research findings, which include identified variations in clinical markers and gene expression, enhance our understanding of MMVD. Furthermore, they underscore the need for further research into early diagnosis and treatment strategies, as, to the best of our knowledge, no prior studies have explored the precise molecular mechanisms of stage B1 in MMVD through total RNA sequencing.