Safety Of Nuclear Power Plants Research Articles

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.

Optimization of prevention and mitigation of severe accidents through Research: Major outcomes and outlook of the Spanish programme

Severe accidents research activities in Spain have grown substantially since the Fukushima-Daiichi accident. Most of these research activities have been conducting by a few organizations (national research center and academia) with the support of the Regulatory Authority, utilities and engineering companies. A great number of these activities were conducted in the analytical field and their main outcomes are contributing to a better understanding of severe accident phenomena (i.e., pool scrubbing; combustible gas distribution and combustion; fission products transport; etc.) and the efficiency of severe accident management actions (i.e., FLEX; PARs; activation of safety systems, long-term measures; etc.). The national framework set between researchers and end-users (regulators and utilities) is improving the safety of the Spanish nuclear power plants and allows for the assimilation of the research results by the nuclear industry.

Interplay of human factors and safety culture in nuclear safety for enhanced organisational and individual Performance: A comprehensive review

The incidents at Three Mile Island and Chernobyl have poignantly spotlighted the indispensable role of human factors and organisational dimensions in ensuring nuclear safety. These events illuminated that beyond the intricate technicalities of nuclear operations, lie the equally significant non-technical facets that warrant utmost attention. While human factors delve into the cognitive and ergonomic challenges faced by operators, safety culture represents the ingrained organisational ethos that promotes or impedes safety standards. While a myriad of studies has dissected the impact of these elements on nuclear safety, the quest for an encompassing methodology that holistically integrates them is still ongoing. This paper embarked on an exhaustive review that probed the symbiotic relationship between human factors, safety culture, organisational performance, and individual performance within nuclear power plants, all the while bearing the indelible imprints of the Three Mile Island and Chernobyl disasters. Beginning with an elucidation of the core tenets of human factors and safety culture and their intrinsic ties to nuclear safety, the review delved deeper into empirical research that illustrated their influence on the overarching safety climate of nuclear establishments. It shines a light on recurrent challenges like communication lapses, leadership oversights, and the ever-present spectre of human error. In its culmination, the review underscored the intertwined nature of these pivotal elements and expounds on their collective import in sculpting a resilient safety culture in nuclear setups. Recommendations for bolstering human factors and safety culture practices, gleaned from the bitter lessons of Three Mile Island and Chernobyl, are proffered. At its core, this paper advocated for an integrative paradigm that melds organisational and individual performance metrics with human factors and safety culture insights, perpetually underscored by rigorous research and evaluation, to ensure the unerring safety and dependability of nuclear power plants.

Study of the impact of hydrides on the fracture toughness of Zr-2.5Nb alloy

Hydrogen absorption and hydride formation in zirconium (Zr) alloys is a well-known issue and has been extensively studied in the past. Hydrogen has an impact not only on the strength but also on the fracture toughness of Zr alloys. As various Zr alloys are used for manufacturing the core components of nuclear reactors, such as nuclear fuel claddings, fuel channels, fuel assemblies, fixtures, and etc., their structural integrity has a great impact on the safety and reliability of the whole nuclear power plant. Furthermore, the hydrogen absorption ageing mechanism retains its significance not just during reactor operation but also throughout decommissioning and storage of spent nuclear fuel, especially when sufficient levels of absorbed hydrogen concentrations are reached, potentially leading to a delayed hydride cracking mechanism. Assessing the impact of hydrogen absorption on the strength of zirconium alloys typically involves time-consuming, costly, and sample-intensive experimental studies. Consequently, there is a demand for alternative research approaches. This article introduces the methodology to evaluate the fracture toughness of the Zr-2.5Nb alloy with varying hydrogen concentrations.

Analysis of main steam line break accident on a BWR test facility using TRACE

PUMA-E is an integral test facility, which is used for extensive experimental investigations to study the behavior of Boiling Water Reactor (BWR) plants under accident conditions. The TRACE code is the best estimate thermal hydraulic system code developed by the U.S. Nuclear Regulatory Commission for performing nuclear power plant safety analysis. The aim of the present work is to conduct a short validation study of the TRACE code applied to the PUMA-E facility. Firstly, a TRACE model of the PUMA-E facility was developed based on the existing RELAP5 input deck. Then, an additional facility TRACE model with reactor pressure vessel modeled by three dimensional “VESSEL” component was also established. After that, a Main Steam Line Break accident test was simulated, and the calculation results were compared with experimental data and RELAP5 simulation results. The TRACE simulation capability to predict the accident phenomenon of BWR test facility was evaluated using both qualitative and quantitative methods. On the basis of the above research, the base case accompanying with one Gravity Driven Cooling System tank failure accident was carried out based on the three facility models. The validity and reliability of the simulation results of the different facility numerical models were mutually verified through a qualitative comparison of the simulation results.

Event Sequence Based Fault Tree Analysis to Evaluate Minimal Combination of Event Sequences Leading to the Reactor Core Damage

Probabilistic safety assessment has been widely used to evaluate nuclear power plant safety systems. It couples fault tree (FT) analysis and event tree (ET) analysis. FT analysis is to develop failure scenarios, to quantify the failure probability and to identify critical components. ET analysis is to develop event sequences (ESs) leading to reactor core damage and quantify core damage frequency. Currently, there is no approach in probabilistic safety assessment that can be used to identify minimal combinations of safety system failures leading to reactor core damage. This study proposes an event sequence based fault tree analysis, which integrates FT model with ET model. The ET model is to identify the ESs leading to the reactor core damage. Meanwhile, the FT model is to identify minimal combinations of those ESs found in the ET model. The motivation of this study is on how to identify critical safety systems in nuclear power plants to mitigate disturbances caused by a group of postulated initiating events to avoid core damage. To confirm the feasibility and the applicability of the proposed approach, the performance of the AP1000 passive core cooling system is evaluated. It is found that if in-containment refueling water storage tank, automatic depressurization system - full, accumulator, core make-up tank, and passive residual heat removal work properly, the reactor core will intact. These results confirmed that the proposed approach can be applicable to identify minimal combinations of safety systems to keep the reactor core intact.

Rocking induced axial response and performance of lead‐rubber bearings in seismically isolated nuclear plants

AbstractSeismic isolation using lead‐rubber (LR) bearings can be an effective earthquake mitigation technique to ensure the safety of Nuclear Power Plants (NPPs) against extreme earthquake events. Accurate estimation of the axial and rocking response of NPPs is critical to the design of the safety‐related secondary components, piping, and auxiliary system crossing the interface of the isolation system. The isolators along the periphery of the isolation interface are especially susceptible to buckling in compression and cavitation in tension due to the rocking motion of the structure. No study so far has looked into rocking response of base‐isolated NPP and its consequence on isolator's performance. This paper investigates the axial and rocking behavior of base‐isolated NPPs at a site of high seismic hazard. A numerical study is conducted on the different representations of NPP models with the varying height of the center of mass isolated using a range of isolation systems of different periods and characteristic strengths. The rocking responses are obtained using simplified and advanced isolator models, which consider the interaction between the axial and shear response. The results provide estimates of the rocking responses and their influence on the axial response of isolators. It was observed that the rocking response of a base‐isolated NPP increases with an increase in the isolation period and the characteristics strength of the isolation system. Rocking effects may amplify the axial forces in the lead‐rubber isolators by more than 100% and need to be considered for true performance assessment of isolators when the horizontal to vertical shaking intensity exceeds a ratio of 0.5.

Condition monitoring for nuclear turbines with improved dynamic partial least squares and local information increment

Performing online condition monitoring for nuclear turbines in the rapidly changing environment is a challenging but imperative task to enhance the safety and reliability of nuclear power plants. Given the nonlinear and dynamic properties of nuclear turbine operation, this paper proposes an innovative method for condition monitoring. Specifically, the paper first redesigns time augmented matrices based on lagged data to reflect the process dynamics. Subsequently, a dynamic auto-regressive model, integrated with the variant of kernel partial least squares, is built between input and output variables, which represents auto-correlations and cross-correlations of operation data simultaneously. The prediction of the model serves as the baseline for the monitoring indicator. Additionally, since the operation process involves variable working excitation and random noise, making static control limits insufficient to satisfy the requirements of condition monitoring, the proposed method utilizes a novel monitoring indicator based on local information increment. The indicator comprehensively incorporates the prediction value and past measurement for monitoring statistics and control limits. Finally, the proposed method is applied to a real nuclear turbine operation process, and the results are compared with three other methods to demonstrate its superiority.

Optimization strategy for SAM in nuclear power plants based on NSGA-II

Abstract The Severe Accident Management Guide (SAMG) is an important component of nuclear safety regulations. Many studies are being conducted to optimize severe accident management (SAM) strategies. To ensure the safety of nuclear power plants, decision makers need to monitor multiple parameters with security threats. Therefore, it is particularly important to search optimal SAM strategies under different numbers of mitigation targets. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is an evolutionary algorithm that does not require derivative differentiation and is capable of population search. In this study, a nuclear power plant accident optimization strategy is developed using the Modular Accident Analysis Program (MAAP) in conjunction with NSGA-II. The strategy enables decision makers to consider multiple mitigation objectives in a complex decision environment. Focusing on the CPR1000, this study applies the optimization strategy to automatically search for optimal mitigation strategies for small break loss of coolant accident (SBLOCA) and station blackout hot leg creep rupture accidents (SBOHLCR). Comparing the optimization results with the basic accident sequence, it is found that the reactor pressure vessel (RPV) failure time is delayed from 72,702 s to 128,730 s under SBLOCA and from 23,828 s to 28,363 s under SBOHLCR. This study has also verified that the optimal SAM strategy obtained by the strategy through dual objective optimization has better mitigation effects than a strategy that only considers one objective. This optimization strategy has the potential to be applied to other types of severe accident management studies in the future.

Comparison of seismic analysis methods within analytical approach

Introduction. In the nuclear power industry, ensuring nuclear and radiation safety is of paramount importance, therefore all aspects that may affect safety are considered in a deterministic and probabilistic approaches.
 As part of the safety justification, consideration of earthquakes of various intensity levels is regulated by safety standards. At the same time, the deterministic analysis of the earthquake and the models and calculation methods used are quite well-established, and in the probabilistic way, a relatively large number of different approaches have been developed and used as part of PSA level 1. The results of the evaluation of the conditional probability of failure of system elements, buildings and structures depending on the intensity of seismic impact on the free ground surface of the site depends on the approach used for the calculations.
 Aims. To perform a comparative analysis of various methods for constructing a failure probability curve under seismic impact.
 Materials and methods. A comparative analysis of the use of various approaches to the construction of a failure curve under seismic impact for a relatively simple case is performed. The results of the calculations showed that the scaling method leads to the most conservative results. The use of linearization methods and the method of moments give more realistic estimates, which can have a positive impact on the results of PSA level 1.
 Conclusions. A comparative analysis of some approaches has practical interest and is relevant, since various methods can contribute more than 50% to the core damage frequency, which creates a significant imbalance in the safety of nuclear power plants.

Determination of heat transfer process in vertical cable tunnels of nuclear power plants under real fire conditions

The object of the study was heat and mass transfer processes occurring in vertical cable tunnels. The problem to be solved was the definition of process mechanisms in the inner space of the tunnel. For this, field tests were conducted, mathematical models were created, and computational experiments were conducted to establish specific parameters that affect the temperature regime of a fire in a vertical cable tunnel of a nuclear power plant. The dynamics of temperature changes with known geometric parameters and fire load were determined, and the adequacy of mathematical models built in the Fire Dynamics Simulator software was investigated and computational experiments were carried out. It has been proven that they consist in determining the temperature regime in a vertical cable tunnel of a nuclear power plant with known technical and geometric parameters. Such studies have practical applications in the field of safety of nuclear power plants and the development of new technologies in this field. An important conclusion of these studies is the possibility of determining the fire resistance of building structures of vertical cable tunnels of nuclear power plants with the selection of the most severe temperature regime, according to the conducted field test. This means that research results can be used in practice in designing and evaluating the safety of such objects. The conducted research established that the temperature in the inner space of the tunnel can reach values from 1200 to 1400 ℃. The following factors influence the maximum temperature value and the maximum time to reach the maximum temperature in the fire cell: fire load, height and area of the tunnel. With a lower fire load, the maximum temperature in the vertical cable tunnel of the nuclear power plant was 75 % lower. Therefore, the results of these studies have a direct practical application in the field of safety of nuclear power plants and can be used to improve and develop new technologies in this field

A framework to determine the holistic multiplier of performance shaping factors in human reliability analysis – An explanatory study

The safety of nuclear power plants is the uppermost goal to be emphasized for their sustainability. To this end, it is crucial to evaluate their anticipated risk by visualizing accident scenarios resulting in undesirable consequences. In quantifying the likelihood of an accident scenario occurrence, it is necessary to estimate values of human error probabilities with respect to the performance of safety-critical tasks following relevant human reliability analysis (HRA) methods. One of the technical issues pertaining to the quality of HRA results is to determine the multipliers of performance shaping factors (PSFs) that specify the contexts in which human operators have to accomplish the required safety-critical tasks. Unfortunately, since PSFs are entangled with complicated interrelations, it is hard to properly determine their multipliers. To address this problem, in this study, a framework that can quantify the holistic multiplier of a specific PSF is proposed that can encompass the effect of these complicated interrelations. In order to corroborate the applicability of the proposed framework, an explanatory case study is conducted by using data available from the literature. Based on the result of this case study, it is expected that the proposed framework would be effective for determining PSF multipliers.

Autonomous Thermosiphon System of Passive Residual Heat Removal from the Primary Circuit of the Reactor Plant: Features of Operation, Characteristics and Basic Advantages

An autonomous system of passive removal of residual heat (PRRHS) of a reactor installation with VVER designed to ensure the safety of nuclear power plants in an accident with complete long-term blackout is considered. The system provides for the removal of heat directly from the first circuit of the reactor plant (PRRHS R). In order to increase the reliability and safety of the emergency heat sink, heat exchange equipment based on closed-type evaporation and condensation devices – two-phase thermosyphons – has been used in the system. The main feature of such heat exchangers is that their thermosiphon assemblies structurally separate the primary circuit and the auxiliary circuit of the PRRHS, which is removed outside the reactor compartment, and provide safe and efficient heat removal, reduce the risk of radioactive contamination spreading beyond safety barriers. Such autonomous passive systems will provide effective heat removal directly from the primary circuit by changing the chain of successive heat transfer sites from nuclear fuel to the final absorber and excluding from it such elements, as for example steam generators, the condition and operability of which in the emergency process of heat removal have a major impact on the safety of the reactor core. The article presents a diagram of an autonomous heat sink system; also, a description of its operation is given. The main characteristics of the course of the emergency process of removal of residual heat by the autonomous thermosiphon PRRHS R obtained by computational modeling have been considered. The advantages of an autonomous thermosiphon passive system in comparison with a passive heat removal system of a reactor installation with VVER through the second circuit are analyzed. The obtained results are proposed to solve the problems of diversification of passive safety systems of evolutionary reactor plants of nuclear power plants with VVER type reactors.

Problems of safe operation of Zaporizka NPP in the conditions of war in Ukraine

Among the specified types of terrorist threats, the most dangerous today is the nuclear threat, which has moved from the realm of the probable to a real military-terrorist attack on the Zaporizhzhia NPP and its capture by the occupiers. Therefore, the issue of determining the level of nuclear and environmental safety of Ukraine's nuclear power plants in extreme war conditions, using the example of the situation that developed at the Zaporizhzhia Nuclear Power Plant (ZNPP), the largest in Europe, is extremely urgent, precisely because of the station's location in the war zone.During the period of the full-scale war, there have already been dozens of warheads hitting the objects of the critical infrastructure of the ZNPP, the external and emergency power supply of the ZNPP (transformer equipment, power supply systems to consumers, the premises of diesel generators, the industrial site of the station, and others). There have been corresponding emergency shutdowns of the power units of the ZNPP due to the blackout of the station and due to the forced disconnection of consumers as a result of the destruction of various objects in the power grid systems. These events cause great alarm and concern of the world public regarding the possibility of new global nuclear-ecological disasters due to nuclear-radiation accidents at the ZNPP. Many years of global experience in the operation of nuclear power reactor facilities (NPRF) and their safety regulation, as well as lessons from the largest nuclear and radiation accidents at NPPs, have revealed the insufficient validity of traditional probability indicators and safety criteria for NPPs, including the Zaporizhzhya plant. Probabilistic approaches to assessing the objective level of safety of the Zaporizhzhya NPP in extreme conditions of war are insufficiently substantiated, taking into account, among other things, the need to predict the possibility of the occurrence of unlikely emergency events and their combinations, which will have catastrophic consequences.Therefore, conducting an objective assessment of the level of nuclear and radiation safety at the ZNPP due to the station's location in the war zone, as well as substantiating practical recommendations for preventing nuclear and environmental disasters at the NPPs of Ukraine, is an extremely urgent issue for the entire nuclear energy industry of Ukraine.

Vibroconverter mathematical model based on the levitation effect

Modern requirements for the safe operation of nuclear power plants dictate the need to introduce systems for early reactor plants state diagnosis. Vibrations have always been a threat to the safe nuclear power plants operation, therefore, solving the issues of improving the nuclear power plants vibronoise diagnostics accuracy, especially in the field of ultra-low frequencies, is an urgent task. The most promising way to solve the problem of flexible guides in electromechanical vibration transducers is the levitation effect, which makes it possible to completely eliminate mechanical contact and, accordingly, reduce the sensitivity threshold of the transducer. The article presents an analysis of existing vibration transducers and offers analogue and digital mathematical models of the magnetic levitation system, taking into account the influence of the electromagnetic force nonlinearity. The characteristics of such a nonlinear system are studied using the method of harmonic linearization, which makes it possible to obtain an equivalent linear system. At the same time, the third order terms of the electromagnetic force expansion in the Taylor series are taken into account, which made it possible to obtain a more accurate analogue the vibration transducer model. For the developed vibration transducer digital model, using the z-form method, a system function and the corresponding difference equation were obtained. Expressions and graphs of transient, pulse and frequency characteristics are derived for both analogue and digital vibration converter models, which allow us to conclude about the accuracy and adequacy of the developed digital model. Using obtained vibration transducer digital models will make it easier to model its operation and reasonably select the vibration transducer initial parameters.

MOPSO-based structure optimization on RPV sealing performance with machine learning method

The structure integrity of reactor pressure vessels (RPV) plays an important role in the safety of nuclear power plants, which mainly concerns the risk of sealing failure. In the present work, a hybrid method consisting of an artificial neural network (ANN) and multi-objective particle swarm optimization (MOPSO) is proposed, aiming to find an optimized RPV structure with improved sealing performance. The ANN model provides a more accurate prediction of sealing performance than the radial basis function neural network (RBFNN) model. There is also a better generalization ability in the ANN model with R2 above 0.96 and RMSE below 0.06 in the test set. With ANN as a surrogate model, multi-objective optimization is applied in RPV structure design. Compared with that of the original RPV structure, the sealing performance can be improved by even over 25% in the optimized structure. The application of ANN surrogate models can save more than 99% computation cost, compared with optimization based on finite element analysis (FEA).

Critical heat flux and heat transfer behaviors on aged RPV outer wall surface in flow boiling under IVR conditions

Critical Heat Flux (CHF) plays an important role in the nuclear power plant safety strategy both during normal operation and under accident conditions. During normal operation, the outside wall is exposed to high-temperature environment. The surface is oxidized by air, which is so-called “aged surface”. To specify the characteristics of aged surface and the effect on CHF, the specimen aging experiments and flow boiling experiments under External Reactor Vessel Cooling (ERVC) were conducted. The results of specimen aging experiments show that surface characteristics get steady after 500 h aging and the oxide layer is the Fe-Fe2O3-Fe3O4 mixture. After aging, the surface gets rougher and has better hydrophily. In the flow boiling experiments, characteristics of heat transfer and CHF are studied. Heat transfer is enhanced by extended surface area and increased nucleation sites at lower angle. The influence of capillary suction is not obvious and the enhancement of CHF is limited. As the inclination angle increases, the departure of bubbles is more frequent and capillary suction is dominant to assist liquid supply into the liquid sublayer and delay the boiling process. At higher angle, CHF is more obviously enhanced but heat transfer gets worse. Overall, CHF of RPV outer wall is increased after surface aging, and it is beneficial to improving the safety margin of IVR mitigation measures.

Small Modular Reactors: Opportunities and Challenges as Emerging Nuclear Technologies for Power Production

Abstract Small modular reactors (SMRs) have gained international attention due to their modular design, small footprint, and cost advantages compared to conventional reactors. Multiple types of SMRs are under development globally, and regulatory agencies are working toward a comprehensive and harmonized regulatory framework for ensuring safety and environmental protection. However, several aspects related to SMRs require further investigation, including the behavior of nuclear fuel under high pressures and temperatures (1000 °C), radiation exposure levels during normal and accident conditions, management of different types and volumes of nuclear waste, and their safe storage and disposal. Additionally, the modular design and compact size of SMRs make them suitable for deployment in remote locations, including the Arctic region. However, before introducing SMR technology, a thorough study of Arctic soil is necessary, particularly in the context of changing climate. Probabilistic risk assessment (PRA) plays a vital role in evaluating the safety and reliability of nuclear power plants, specifically focusing on assessing cross-unit interactions in the case of multimodule SMRs. Furthermore, given the use of low-enriched uranium fuel and the potential for limited on-site personnel in remote locations, effective nuclear safeguards and material accountancy measures are crucial to prevent the diversion of nuclear materials. In this paper, an investigation is conducted to explore the advantages and challenges involved in the deployment of emerging SMR technologies for electricity generation and other applications.

In-reactor behaviour and economic assessment of enriched gadolinia burnable absorbers

The increasing demand for energy and rising energy prices have increased the importance of the efficiency and economic viability of operating nuclear power plants. One approach to improving the reactivity control in such cases is the use of burnable absorbers such as gadolinium oxide (Gd2O3). While Gd2O3 has proven effective in regulating reactivity in light water reactors, it has certain drawbacks, including the displacement of fissile isotopes from the fuel composition and residual reactivity penalties caused by isotopes other than the main neutron absorbers. In this study, the potential impacts of 157Gd-enriched Gd2O3 on the operation, safety, and economy of nuclear power plants were assessed. Fuel cycle analyses were conducted using the advanced nuclear design code system Studsvik CASMO4/SIMULATE3. Several aspects were analysed, including peaking factors, reactivity feedback parameters, power distribution, and shutdown margin. The results of the analysis revealed that by removing the isotopes responsible for residual reactivity from Gd2O3, it was possible to achieve the same fuel cycle length with lower uranium enrichment levels, enabling a higher concentration of fissile isotopes and yielding economic benefits without compromising safety.

Research on fault diagnosis method of electric gate valve under strong background noise

Electric gate valves are essential equipment in nuclear power plants. The safe and stable operation of an electric gate valve is key in maintaining the safety of nuclear power plant. However, due to the strong surrounding noise during the signal acquisition process that affect nuclear power plant electric gate valves, the early status monitoring and fault diagnosis of the electric gate valve are ineffective. However, the traditional fault diagnosis methods are not suitable for electric gate valves and fail to classify faults classification under the strong background noise. To achieve the noise reduction of electric gate valve acceleration signals based on strong background noise, the work proposes a Variational Mode Decomposition (VMD) method to denoise the strong noise in the collected signal. Seven genetic optimization algorithms are combined with VMD to enhance the model parameter selection of VMD. This selection criterion helps to select the most suitable algorithm combination for processing the acceleration signal of the electric gate valve under the background of strong noise. In order to obtain a better fault classification effect, the weak noise in the acceleration signal is further removed by Singular Value Decomposition (SVD). Moreover, the time-domain feature parameter extraction is performed on the denoised acceleration signal. Consequently, the model training of the Bidirectional Gate Recurrent Unit (BGRU) and the development of the electric gate valve fault diagnosis system under the background of strong noise are completed. The final experimental results show that the system developed in this paper has a good fault classification effect.