Solenoid-operated Valves Research Articles

AI-augmented failure modes, effects, and criticality analysis (AI-FMECA) for industrial applications

Design failure modes, effects, and criticality analysis (d-FMECA)22The term FMEA and FMECA are used interchangeably throughout this paper. The user has the option in the interface to choose either FMEA or FMECA based on their desired application. is a bottom-up, semi-quantitative risk assessment approach that is used by reliability engineers across all industries (nuclear, chemical, environmental, pharmaceuticals, aerospace, etc.) for identifying the effects of postulated components failure modes such as solenoid-operated valves (SOV), motor-operated valves (MOV), controllers, pumps, sensors of various types, printed circuit boards (PCBs). This research aims to develop a novel AI-augmented tool that guides, in real-time, the risk-analyst to a host of potential failure modes and their effects for each component contained in a bigger system. Through a user-friendly graphical interface and a robust statistical modeling backend, the AI-driven tool streamlines the risk assessment process by prompting the risk analyst to input a system’s name and subsequently generate an extensive array of failure modes and associated effects for each constituent component within the system. This AI-augmented tool allows the user to select either a simplified d-FMEA or a detailed d-FMECA for the system under investigation. This novel AI-driven tool offers significant effort and time savings in conducting d-FMECA, which is known to be a labor-intensive engineering task. In addition, this tool can be used for training risk and reliability professionals.

Quantitative Evaluation of Electric Features for Health Monitoring and Assessment of AC-Powered Solenoid Operated Valves⋆

Quantitative assessment of feature performance for health monitoring is key to feature selection. This paper illustrates the application of well-established metrics in the research community - namely, monotonicity, robustness and prognosability - to the quantitative performance assessment of features for health monitoring of alternating-current (AC) powered solenoid operated valves (SOVs). These features are extracted from voltage and current signals measured on the valves and builds on previous work of the authors. Based on these metrics, the appropriate features are selected to be used as condition indicators. The selected features are inputs to a logistic regression model to predict a health index ranging from 0 to 1, which can be easily monitored and assessed by non-experts. We demonstrated the developed methodology on the experimental data acquired from accelerated life tests on 48 identical AC-powered SOVs.

An improved first-principle model of AC powered solenoid operated valves for maintenance applications

Solenoid operated valves (SOVs) are critical components in many industrial applications. There has been a continuing interest in the industry to have robust condition monitoring, prognostics and health management tools to support the condition based maintenance and predictive maintenance program for such valves. For critical assets like SOVs, it is of paramount interest to understand why a component might be declared as defective. In such a situation, a first principle-model based approach will always be preferred to a purely data-driven approach, because of its inherent interpretability. Furthermore, first principle-models typically have less free parameters than their data driven counterparts and will require less data to identify their parameters. In this paper, we present the improvement of a first-principle model of alternating current (AC) powered SOVs taking into account two important degradation effects. Using this model, we show that the state of degradation can be estimated from current and input voltage measurement signals on the solenoids. Our method is validated using data from an accelerated life test campaign on 48 identical AC-powered SOVs.

Investigating the Effect of Prior Distributions on Posterior Estimates of Common Cause Failure Parameters Using Bayesian Method

Abstract Quantification of common cause failure (CCF) parameters and their application in multi-unit PSA are important to the safety and operation of nuclear power plants (NPPs) on the same site. CCF quantification mainly involves the estimation of potential failure of redundant components of systems in a NPP. The components considered in quantification of CCF parameters include motor operated valves, pumps, safety relief valves, air-operated valves, solenoid-operated valves, check valves, diesel generators, batteries, inverters, battery chargers, and circuit breakers. This work presents the results of the CCF parameter quantification using check valves and pumps. The systems considered as case studies for the demonstration of the proposed methodology are auxiliary feedwater system (AFWS) and high-pressure safety injection (HPSI) systems of a pressurized water reactor (PWR). The posterior estimates of alpha factors assuming two different prior distributions (Uniform Dirichlet prior and Jeffreys prior) using the Bayesian method were investigated. This analysis is important due to the fact that prior distributions assumed for alpha factors may affect the shape of posterior distribution and the uncertainty of the mean posterior estimates. For the two different priors investigated in this study, the shape of the posterior distribution is not influenced by the type of prior selected for the analysis. The mean of the posterior distributions was also analyzed at 90% confidence level. These results show that the type of prior selected for Bayesian analysis could have effects on the uncertainty interval (or the confidence interval) of the mean of the posterior estimates. The longer the confidence interval, the better the type of prior selected at a particular confidence level for Bayesian analysis. These results also show that Jeffreys prior is preferred over Uniform Dirichlet prior for Bayesian analysis because it yields longer confidence intervals (or shorter uncertainty interval) at 90% confidence level discussed in this work.

Fault state detection and remaining useful life prediction in AC powered solenoid operated valves based on traditional machine learning and deep neural networks

Solenoid operated valves (SOV) play important roles in industrial process to control the flow of fluids. Solenoid valves can be found in so many industries as well as the nuclear plant. The ability to be able to detect the presence of faults and predicting the remaining useful life (RUL) of the SOV is important in maintenance planning and also prevent unexpected interruptions in the flow of process fluids. This paper proposes a fault diagnosis method for the alternating current (AC) powered SOV. Previous research work have been focused on direct current (DC) powered SOV where the current waveform or vibrations are monitored. There are many features hidden in the AC waveform that require further signal analysis. The analysis of the AC powered SOV waveform was done in the time and frequency domain. A total of sixteen features were obtained and these were used to classify the different operating modes of the SOV by applying a machine learning technique for classification. Also, a deep neural network (DNN) was developed for the prediction of RUL based on the failure modes of the SOV. The results of this paper can be used to improve on the condition based monitoring of the SOV.

Impedance-Based Condition Monitoring for Insulation Systems Used in Low-Voltage Electromagnetic Coils

Electromagnetic induction coils are widely used in a variety of applications, many of them safety-critical. The insulation around the wire in an electromagnetic coil accounts for a significant portion of the failures in solenoid-operated valves and in electric motors. This paper presents a method of detecting the degradation of insulation used in low-voltage applications by assessing changes in impedance responses. The results indicate that coil impedance, resolved into resistance and reactance, evolves differently when the coil is subjected to different loading conditions, which reflects insulation degradation signatures due to different failure mechanisms. This method can be used to assess the insulation life of an electromagnetic coil, allowing replacement prior to the formation of harmful shorts or critical coil opens.

Sensor for Detecting Caviar Maturity in Farmed Sturgeon

<abstract> Depletion of wild sturgeon around the world has forced the transition from wild-caught to farm-raised caviar. Farmers face difficult challenges to produce eggs of sufficient size and firmness to yield high-quality caviar at reasonable production costs. Females reach sexual maturity at about seven years, and the oocytes (eggs) are examined by surgical biopsy of the ovary in the late fall for color and size. Egg harvest follows in the winter and spring, but the exact time to harvest optimum quantity and quality of caviar cannot be predicted based on egg size or color because of individual variations in the rate of egg development. Changes in the concentration of plasma vitellogenin, a yolk precursor protein, reflect growth of the eggs and the transition to final maturation. Total plasma calcium is highly correlated with vitellogenin concentration. An automated sensor was designed to measure calcium in sturgeon blood plasma by chemical assay. The sensor used solenoid-operated, fixed-volume pumps, and solenoid-operated valves and was run with an embedded controller. It was able to measure total calcium (free and bound ions) in white sturgeon blood plasma with adequate accuracy to distinguish vitellogenic from non-vitellogenic fish. The sensor was tested in late fall during the normal commercial screening to identify ripe sturgeon. The readings were used to separate half of the ripe fish into low and high calcium groups based on plasma levels previously reported in the literature. The remainder of the ripe fish were used as the control. The harvest groups were selected to compare yields from groups of fish harvested under the current practice (random harvest from winter to spring) and groups harvested based on plasma calcium. Our hypothesis was that caviar harvesting based on plasma calcium gives more uniform size and yield compared to random harvesting, which is the current practice. The early harvest group and low calcium group were sampled in March, and the late harvest group and high calcium group were sampled in May. The high calcium group had greater yield per body mass than the low calcium and early harvest groups. No differences were found in body mass, fork length, ovary mass, egg diameter, and caviar yield. Only one fish was found to be atretic, and that individual was in the early harvest group. These results suggest that a better strategy might be to delay the current time of harvest by several months, with the higher calcium fish processed last.

Design verification methodology for a solenoid valve for industrial applications

Solenoid operated valves (SOV) are widely used in many applications due to their fast dynamic responses, cost effectiveness, and less contamination sensitive characteristics. In this paper, we tried to provide a convenient method of design verification of SOV to design engineers who depend on their experiences and experiment during design and development process of SOV. First, we summarize a detailed procedure for designing SOVs for industrial applications. All of the design constraints are defined in the first step of the design, and then the detail design procedure is presented based on design experiences as well as various physical and electromagnetic relationships. Secondly, we have suggested a verification method of this design using theoretical relationships, which enables optimal design of SOV from a point of view of safety factor of design attraction force. Lastly, experimental performance tests using several prototypes manufactured based on this design method show that the suggested design verification methodology is appropriate for designing new models of solenoids. We believe that this verification process is novel logic and useful to save time and expenses during development of SOV because verification tests with manufactured specimen may be substituted partly by this verification methodology.

원전용 솔레노이드 밸브의 기기검증 절차 및 방법

Key Words: Solenoid Operated Valve(솔레노이드밸브), Equipment Qualification(기기검증), Power Operated Valve(동력구동밸브), Nuclear Power Plant(원자력발전소)초록: 원자력발전소용솔레노이드밸브의국산화에필수과정인기기검증기술을개발하기위해관련규정을분석하고, 시험절차및방법, 시험조건, 시험장치및허용기준등을구체화하였다. 솔레노이드밸브의기기검증규격은법규, 가이드, 규정등의순으로계층화되어있으며, 시험기기와시험항목에따라규정이세분화되어있다. 세부규정인IEEE를분석한결과기기검증시험은크게기능시험, 일반환경시험및사고시험으로구분되어있는데, 일반환경시험과사고시험을통해발전소환경과동일한조건에서솔레노이드밸브를노화시킨후기능시험에서노화된밸브의성능을확인하는방식으로검증시험을수행하도록구성되어있었다. 본논문에서제시한솔레노이드밸브의기기검증시험절차와방법은기기검증수행자뿐만아니라밸브제조사에게매우유용한기술자료가될것으로판단된다.Abstract: In order to develop technology for an equipment qualification (EQ) test, which is an importantprocess in localizing solenoid-operated valves used in nuclear power plants, we analyzed related regulations,test procedures, conditions, equipment, and acceptance criteria. EQ regulations for the solenoid-operated valveare classified as law, guide, and standard, and are subdivided according to test specimens and contents. TheEQ test is composed of functional, normal-, and accident- condition tests. The solenoid-operated valve is agedunder normal and accident conditions, which are predicted in the design conditions of a nuclear power plant,and the performance of the valve is measured by a functional test. The test method and procedure analyzedin this paper might be very useful for manufacturers as well as EQ testers.

Miniature solenoid valves for aggressive fluids

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Nonintrusive methods for monitoring the operational readiness of solenoid-operated values

Solenoid-operated valves (SOVs) are being studied at Oak Ridge National Laboratory as part of the USNRC Nuclear Plant Aging Research (NPAR) Program. The primary of the study is to identify, evaluate, and recommend methods for inspection, surveillance, monitoring and maintenance of SOVs that can ensure their operational readiness — that is, their ability to perform required safety functions under all anticipated operating conditions. An earlier (Phase 1) study described SOV failure modes and causes and identified measurable parameters that might be used to monitor the various degradations that lead to functional failure. The present (Phase II) study focuses on devising and then demonstrating the effectiveness of techniques and/or equipment with which to measure the previously identified performance paramaters (or others) and thus detect and ascertain the trend of the progress of any degradation that may be occuring. Several nonintrusive techniques are presently under investigation. These include monitoring coil mean temperature during operation by means of DC coil resistance, monitoring valve position by means of coil AC impedance, verifying free SOV plunger movement by measuring current and volatage at their critical bistable (pickup/dropout) values, and detecting the presence of shorted turns or insulation breakdown within the solenoid coil using interrupted-current test methods. A technique slated for later investigation is monitoring coil hum or chatteringm, using acoustic sensors or electrical noise indications. Experimental results are presented demonstrating the technical feasibility and practicality of the diagnostic techniques being assessed in this continuing study.

Modifications allowing 24-hour continuous fail-safe pumping of a transmission electron microscope

Fail-safe facilities allowing 24-h continuous pumping of a transmission electron microscope (TEM) are incorporated in only a few more recent models. Modifications to a Hitachi HU-125S are described which allow the instrument to be pumped continuously with fail-safe facilities in the event of power failure. Changes include the addition of solenoid-operated valves, activated alumina sorbent and liquid-nitrogen cold traps to the backing-pump lines, an efficient liquid-nitrogen storage container for the backing-pump line cold traps, an accurate reliable timing facility for topping up the diffusion-pump cold traps with liquid nitrogen, and simple electronic changes to the power supply. The modifications allow more hours of use, as well as being a positive influence in the maintenance of a better vacuum environment in the TEM.

Solenoid-Operated Control Valves

THE presentation of a paper on electric aircraft apparatus by manufacturers of hydraulic control equipment is very likely to lead to a discussion1,5 of the relative advantages and disadvantages of hydraulic and electric systems for accessory actuation. Let us evade this controversy for the present by stating that the writers are not advocating either an all-electric or all-hydraulic system but are describing a type of device that makes possible the utilization of some of the best features of both forms of power.

Solenoid-Operated Hydraulic Valves for Aircraft Applications

DURING the past several years there has been a definite trend by some aircraft manufacturers to eliminate hydraulic controls from combat airplanes. The vulnerability of hydraulic systems used on airplanes manufactured during this period and to a certain extent today are big factors in promoting this trend. Space requirements in the cockpit of an airplane to mount control valves and accommodate necessary piping to these valves, difficulty with packings at extremely cold temperatures, and the lack of flexibility of the control system are other factors that contributed to the aforementioned trend.