Hydraulic Valve Research Articles

An Ontology-based Knowledge Modeling towards Eco-Design for Additive Manufacturing

Owing to the unique technological merits of additive manufacturing (AM), design for AM, particularly eco-design for AM, has been gaining attention in improving the sustainable performance of AM-fabricated (AMed) parts. The main challenge in harvesting potential sustainability benefits is how to capture the impact of design on sustainable performance. Though several existing studies adopted quantitative evaluation on AM sustainability and investigated the relationships between design information and sustainability information of AMed part, the sustainability information is still unavailable in the design phase. This hardly guides eco-design for AM in practice. To support the increasing industrial applications of AM, this paper illustrates related knowledge, that is, material-process-structure-ecoProperty (MPSeP) relationships to connect design and sustainability information in eco-design for AM. An ontology-based method is proposed to model the MPSeP relationships of the AMed part in a structured way. An example of an AMed hydraulic valve body was used to demonstrate the MPSeP modeling process. It is discussed that how the constructed model effectively assists AM designers through providing eco-design recommendation, and enables design software tools to perform sustainability analysis towards eco-design for AM.

Ұқсастық пайдалану шартында екі тактілі қозғалтқышты жасау саласындағы эксперименттік зерттеу

The article applies to similar conditions of use and the creation of a competitive two-stroke engine. Currently, there are prerequisites for creating an effective two-stroke engine, such as direct-flow scavenging, a valve-slotted gas distribution system with a multi-valve mechanism, hydraulic valve control, a diesel cycle with a high compression ratio, etc. To implement a set of promising technical solutions, a design basis is required, on the basis of which a two-stroke engine can be configured. As such, a crank-yoke kinematic mechanism for converting motion was chosen. The mechanism unloads the piston from lateral forces and allows the cylinder to be isolated from the oil sump, using the sub-piston volume as a purge pump. This required the development and research of a cylinder-piston group based on solid lubricant. The sliding bearing has also been improved with improved quality indicators based on the use of thermally conductive and antifriction materials of copper and graphite.

The Preparation, Microstructure, and Wet Wear Properties of an Fe55-Based Welding Layer with the Co-Addition of 0.01 wt% CeO2 and 1.5 wt% SiC Particles Using the Plasma Beam Spraying Method

Severe erosion wear is found on valve spools, which threatens the safety and reliability of these units. The use of the plasma beam spraying surfacing method can significantly improve the corrosion resistance and sealing performance of hydraulic valve spools, reduce material waste, and reduce maintenance costs. The effects of the co-addition of CeO2 and SiC particles on the morphology, surface cracks, microstructure, precipitated phases, and wear property of plasma-beam-sprayed Fe55-based coatings on 1025 steel were investigated using OM, EDS, ultra-deep field microscopy, and a wet sand rubber wheel friction tester, respectively. The dendrite exhibited a directional growth pattern perpendicular to the substrate and the transitional states of the microstructure with the co-addition of CeO2 and SiC particles. CeO2 or SiC reduced the liquid phase diffusion coefficient DL of Cr and C and resulted in a decrease in the G/R ratio. The dendrites changed into equiaxed grains. The main phase composition of the Fe55 welding layer was Cr7C3, γ-Fe. The martensite in the surfacing layer and the carbides formed Cr7C3, which can improve the hardness of the surfacing layer. The grain boundaries consisted mainly of a reticular eutectic structure. The uniform distribution of the Cr7C3 hard phase in the Fe55+1.5 wt% SiC+0.01 wt% CeO2 resulted in a uniformly worn surface. The sub-wear mechanisms during the friction process were micro-ploughing and micro-cutting. The hardness and toughness of Fe55+1.5 wt% SiC+0.01 wt% CeO2 were well-matched, avoiding excessive micro-cutting and microplastic deformation. A low content of CeO2 could lead to the formation of equiaxed grain and effectively improve the uniformity of the microstructure. The wear-resistant layer of Fe55+1.5 wt% SiC+0.01 wt% CeO2 can effectively improve the service life and long-term sealing performance of the valve spools.

Performance Analysis of Additively Manufactured Hydraulic Check Valves with Different Postprocessing

Performance Analysis of Additively Manufactured Hydraulic Check Valves with Different Postprocessing

Intelligent Fault Diagnosis of Hydraulic Multi-Way Valve Using the Improved SECNN-GRU Method with mRMR Feature Selection

Hydraulic multi-way valves as core components are widely applied in engineering machinery, mining machinery, and metallurgical industries. Due to the harsh working environment, faults in hydraulic multi-way valves are prone to occur, and the faults that occur are hidden. Moreover, hydraulic multi-way valves are expensive, and multiple experiments are difficult to replicate to obtain true fault data. Therefore, it is not easy to achieve fault diagnosis of hydraulic multi-way valves. To address this problem, an effective intelligent fault diagnosis method is proposed using an improved Squeeze-Excitation Convolution Neural Network and Gated Recurrent Unit (SECNN-GRU). The effectiveness of the method is verified by designing a simulation model for a hydraulic multi-way valve to generate fault data, as well as the actual data obtained by establishing an experimental platform for a directional valve. In this method, shallow statistical features are first extracted from data containing fault information, and then fault features with high correlation with fault types are selected using the Maximum Relevance Minimum Redundancy algorithm (mRMR). Next, spatial dimension features are extracted through CNN. By adding the Squeeze-Excitation Block, different weights are assigned to features to obtain weighted feature vectors. Finally, the time-dimension features of the weighted feature vectors are extracted and fused through GRU, and the fused features are classified using a classifier. The fault data obtained from the simulation model verifies that the average diagnostic accuracy of this method can reach 98.94%. The average accuracy of this method can reach 92.10% (A1 sensor as an example) through experimental data validation of the directional valve. Compared with other intelligent diagnostic algorithms, the proposed method has better stationarity and higher diagnostic accuracy, providing a feasible solution for fault diagnosis of the hydraulic multi-way valve.

Vibration suppression of an armature assembly in hydraulic servo valve based on distributed parameters mathematical models

As a commonly used hydraulic control component, the nozzle-flapper servo valve has the advantages of small structure and sensitive dynamic response. Due to the small size and complex structure of the servo valve, the classical control methods based on various feedback information cannot effectively improve its performance. In order to effectively improve the performance of the servo valve, this paper implemented the feedforward control method to suppress the dynamic performance of the armature assembly of the servo valve. The distributed parameters mathematical models of the armature assembly are established and verified which can accurately predict the vibration of the armature assembly. With the mathematical model, the feedforward control signal is calculated based on the real-time velocity, acceleration, and deflection of the armature assembly, respectively. The applicability of different signals is analyzed and the signals calculated by velocity and deflection are verified which can effectively suppress the vibration amplitude of armature assembly. The numerical simulation and experimental methods are implemented to verify the performance of different control signals and the optimal feedforward control signal under different external loads is obtained.

Identification of pressure pulsation spectrum in a hydraulic system with a vibrating proportional valve

In this paper, attention was focused on identifying the components of the amplitude-frequency spectrum of pressure pulsations in a hydraulic system in which an external low-frequency mechanical vibration was subjected to a proportional hydraulic directional control valve. It was observed that an operating machine or device equipped with hydraulic valves is a source of mechanical vibrations with a wide frequency spectrum. The influence of these vibrations on the pressure pulsation spectrum was analyzed, identifying the components resulting from the forcing of the directional control valve spool. In addition, it was noted that the pressure pulsation spectrum includes components resulting from the pulsation of the displacement pump output feeding the hydraulic system. A description of these spectrum components was also made and, using the solution superposition method, the components of the pressure pulsation spectrum over a wide frequency range were identified.

Impact of hypertension on mean transvalvular gradients in aortic stenosis Lessons learned from in silico modelling

Abstract Introduction The influence of hypertension on the diagnostic assessment of aortic stenosis (AS) severity is unclear, yet clinically relevant. To clarify the effect of hypertension on transvalvular gradients, requires a better understanding of the impact that blood pressure change has on mean flow rate. Also, the effect of various degrees of AS severity, the valve geometry and intrinsic left ventricular contractile function (elastance) on this interaction, needs to be clarified. Existing clinical research on this topic is limited by not incorporating the full complement of factors that influences the directionality and magnitude of mean transvalvular gradient change for any given change in blood pressure. Purpose To use validated flow dynamics modelling grounded in fundamental physics principles to create a digital platform where various parameters can be manipulated to quantify the effects of bloodpressure change on mean transvalvular gradients in various pathological states. Methods A validated, zero-dimensional electro-hydraulic analogue computer model of the human cardiovascular circulatory system was generated. It was used to assess the impact of blood pressure changes on left ventricular pressure and transvalvular gradients at various flow rates, left ventricular elastances, a range of aortic valve areas and for different aortic valve morphologies. Results Mean transvalvular gradients are flow dependent. The impact of hypertension on mean flow rate (MFR), and hence on mean gradient (MG), is influenced by the aortic valve area as well as the underlying left ventricular elastance (Figure 1). Subsequently, the relationship between MFR and MG could be modelled (Figure 2). Generally, for a given change in systemic arterial pressure, the impact on MG will be the most marked for lower flow rate states such as is expected in more severe degrees of AS and for worse intrinsic left ventricular (LV) contractility. Furthermore, for a constant hemodynamic valve area, the hydraulic valve orifice area was found to be smaller in rheumatic AS compared to degenerative AS. This results in less susceptibility to blood pressure induced changes in mean transvalvular gradient. Similarly, the size of the aortic root was found to be inversely related to the susceptibility to induce a change in mean gradient for a change in blood pressure. Conclusion The interaction between hypertension and mean gradients in AS is complex. The current work places previous recommendations in perspective by quantifying the magnitude of the effect that a change in blood pressure has on mean gradient in various pathophysiological states. By doing so it provides more granularity into this multifaceted interaction compared to previously oversimplified deductions from clinical studies. The findings of this study creates a basic science framework based on first principles that dictates the scope of parameters that should be considered in future clinical research on the topic.Modelling 1Modelling 2

A Review of Pilot-operated Hydraulic Valves – Development, Challenges, and a Comparative Study

Hydraulic systems have been widely used due to their high power-to-weight ratio. Despite the growing instances of being superseded by the electromechanical counterparts at low power levels, the market was incapable of presenting alternatives for large-size applications. Additionally, in recent years, the demand for more significant heavy machinery (Mobile & Industrial) has increased, which led to the necessity of even higher flow and pressure Pilot-operated valves, despite the fact that these valves have several issues. One might think the alternative could be developing a hydraulic system that does not rely on Pilot-operated valves, but after decades of research, these systems could not get close to the performance of Pilot-operated Multistage valves. The paper presents a comprehensive study of the progress accomplished from the year 2016 to early 2022 in hydraulic Pilot-operated valves; they are widely employed among ordinary valves, proportional valves, and state-of-the-art digital hydraulics. Higher efficiency will be a primary factor in the success of the new designs. The academia presented several studies to improve the Pilot valves’ performance, but still, they are limited. There are no dramatic developments, and there are only a few upgrades.

Extraction and Application of Hydraulic Support Safety Valve Characteristic Parameters Based on Roof Pressure Data

The safety valves of powered supports control the maximum working resistance, and their statuses must be known to ensure the safety of both the support and the overlying strata. However, the inspection of powered support valves involves manual or semiautomated operations, the costs of which are high. In this study, an extreme point extraction method was developed for the determination of the characteristic parameters of safety valves using roof pressure data, and a safety valve state monitoring module was constructed. Using the longwall face of 0116306 with top coal caving in the Mindong Mine as an example, the characteristic parameters of the safety valves were extracted, including the peak, reseating, and blowdown pressures, as well as the recovery and unloading durations. The results of the field tests showed the following: (1) The amplitude threshold method based on extreme points can be used to accurately extract characteristic parameters, and the distribution of the characteristic parameters of the safety valves follows either a Gaussian or an exponential distribution. (2) The mining pressure analysis results, derived from the characteristic parameters, closely align with the in situ mining pressure observations. This method can be used for the online monitoring of safety valve conditions, increasing the operational efficiency and quality of safety valve inspections.

Comprehensive Numerical Analysis of a Four-Way Two-Position (4/2) High-Frequency Switching Digital Hydraulic Valve Driven by a Ring Stack Actuator

This paper presents a feasibility study using a commercially available ring stack actuator to develop a four way-two position (4/2) high frequency switching digital hydraulic valve. The excellent characteristics of multilayer piezoelectric actuators, such as a simple design, reduced moving parts, high reliability, and fast response, make them ideal for constructing this type of digital hydraulic valve. High frequency switching digital hydraulic valves (HFSVs), indeed, must be able to switch from fully open to fully closed positions in less than 5 ms, while maintaining minimal pressure losses and delivering large flows. The proposed valve architecture is assessed using well-established equations implemented in a Simulink model, allowing the hydraulic, mechanical, and electrical parts of the valve to be accurately simulated. The paper first provides a detailed description of the numerical model. Next, the hysteresis model of the ring stack actuator is validated against the data provided by the manufacturers on their website. Finally, the numerical results obtained with both open-loop and closed-loop control systems are presented. The simulations show that at a switching frequency of 200 Hz with maximum amplitude and duty cycle of the input pulse digital signal, the valve exhibits high average flow rates (~60 L/min), low average power consumption (~1500 W), and maintains a pressure drop of only 15 bar. Moreover, the simulations reveal that the control system is very effective since the valve switching time is within 1 ms.

A Hydraulic Online Monitoring System for Forestry Harvesters Based on LabVIEW

The hydraulic system is a key component of intelligent forestry harvesters. In the testing of a forestry harvester, researchers need to analyze the operating efficiency and energy consumption of the forestry harvester based on the pressure and flow rate data in the hydraulic system of the forestry harvester and formulate energy-efficient control strategies. In order to enable researchers to monitor and extract the parameters of the hydraulic system of an intelligent forestry harvester in real time, this paper designs a hydraulic online monitoring system for forestry harvesters based on the LabVIEW 2019 software platform. This system realizes the following functions by reading the CAN (controller area network, a serial communication protocol for multi-host localized networks) bus of the harvester: (1) it collects and stores hydraulic system pressure, flow, and other data and displays the value curve in the system interface in real time, and (2) it monitors the control signals received by the hydraulic system and displays the control signal status and value received by the system interface in real time. This paper used this system to carry out on-site testing of an actual machine, and compared and analyzed the online monitoring data of the hydraulic system and the theoretical pressure data of the main hydraulic valve manifold. The average value of the relative error between the two was 1.65%, and the maximum value of the relative error was 2.75%. The results show that the designed system has good accuracy and stability, and can effectively realize online monitoring of the working status of the hydraulic system of forestry harvesters during their operation.

Biomimetic composite structural water hydraulic valve plug for erosive wear resistance based on additive manufacturing processes

Developing materials with good erosive wear properties has broad prospects and economic benefits, especially in the field of water hydraulic system. By studying key information in the online biological strategy library-AskNature, we were able to identify strategies for improving the erosive wear resistance of materials. Specifically, we developed a biomimetic composite structural valve plug (BCSVP) with erosive wear resistance based on the multi-scale observation of shellfish, realized through additive manufacturing (AM). The phase composition and microstructure were analyzed by X-ray diffraction (XRD), scanning electron microscope (SEM), and energy dispersive spectrometer (EDS). The erosive wear resistance was evaluated by morphology observation and slurry erosive wear experiments. The results of these experiments indicate that the BCSVP exhibited a 26.3% higher volumetric erosive wear resistance than a 3D printed 316L stainless steel valve after 7 h of slurry erosive wear. This interdisciplinary research highlights the potential of BCSVP in applications requiring high slurry erosive wear resistance in water hydraulic applications.

Denoising graph neural network based hydraulic component fault diagnosis method

Accurately identifying faults in hydraulic components is essential for improving the reliability and safety of hydraulic systems. Since the hydraulic components of heavy-duty equipment usually work in complex and variable environments and are subject to interference from multiple sources of noise. As a result, fault diagnosis of hydraulic components is challenging, leading to the development of various fault diagnosis models. However, current hydraulic component fault diagnosis models have the following limitations: (1) only able to handle Euclidean space data and ignore the topological relationships within the signals that could provide additional useful information for fault diagnosis, (2) only diagnose faults using single-dimensional acceleration data and fail to incorporate more equipment working conditions. This study focuses on the hydraulic directional valve and proposes a fault diagnosis method based on denoising graph neural network. Firstly, computational fluid dynamics(CFD) is used to analyze the flow field of the spool and sleeve of the valve under different wear states and working conditions. It is found that different degrees of wear have similarities under different working conditions, and there is a regular correlation between the acceleration signal of the valve body and the fault mode under the same working condition. Therefore, acceleration and working condition information are selected as the raw information for fault diagnosis. Then, horizontal visibility graph(HVG) was utilized to transform acceleration signal to graph, and the graph nodes, which can incorporate multidimensional information, were set to be the equipment working conditions and acceleration values. However, the noise in the raw signal could seriously affect the quality of the HVG. To solve this problem, an adaptive threshold denoising algorithm was proposed to reduce the interference noise in the acceleration signal. The denoising threshold parameter was learned directly from the raw data. Finally, graph neural network(GNN) is applied to fault diagnosis of hydraulic components from non-Euclidean multidimensional information. Experimental results demonstrate the superior robustness and accuracy of this method in handling strong noise and multiple working conditions compared to several classical fault diagnosis methods. This research provides an effective approach for hydraulic component fault diagnosis.

The controlling the hydraulic electro drive system on the basis of the adaptive sliding mode control method

In this paper, presents the construction of an automatic control system for mobile lifting machines applied in industry and traffic. The control algorithm is built on the basis of calculations from the actual system taking into account the estimation of the nonlinear factors of frictional moment uncertainty, on the basis of the adaptive sliding mode control method. Using programming and simulation tools on the basis of MATLAB/Simulink to demonstrate the research results. The results of the simulation study are the basis for the design and calculation of the hydraulic electro drive system, which shows the practical effectiveness of the study of electromechanical traction electric transmission systems such as mobile lifting machines. The motion uses hydraulic valve systems to transmit power control (lifting and lowering as required).

Design and Flow Analysis of Special-Shaped Cross-Section Flow Channel Based on Selective Laser Melting

Selective laser melting has the potential to be applied into hydraulic pipelines manufacturing because it can realize the forming of flow channels with arbitrary direction and curvature. Due to the stacking of layers, selective laser melting still has many limitations while processing complex flow channels. In particular, the manufacturing of overhanging structures with circular cross sections needs to use internal supports to prevent surface collapse, which is challenging to be removed. Therefore, it is necessary to optimize the flow channel with a self-supporting ability, then systematically discussing its forming quality with the influence on fluid dynamics to compromise. In this paper, a simplified multi-channel structure with 1 inlet and 4 outlets is extracted from a hydraulic valve block of an aero-engine system, and the cross-section of its branch channel is re-designed to guarantee its self-supporting ability based on additive manufacturing optimization strategy. Numerical simulation was used to analyze the influence of different shape sections on the pressure loss and mass flow rate of multi-channel structure. The results show that the pressure loss and outlet flow of the 45° rhombus + ellipse section are the closest to the circular area. According to the maximum internal deformation of the three outlets, the 65° rhombus section has the better forming quality and the non-circular section is not the worst.

State of the art of hydraulic packer testing in clay rocks in the Swiss national radioactive waste disposal program

Abstract. To provide input for site selection and the safety case for deep geological repositories for radioactive waste, Nagra has drilled a series of deep boreholes in northern Switzerland. As part of the hydrogeological characterization of this exploratory drilling campaign, hydraulic packer tests in the sedimentary rocks were carried out under the supervision of Nagra, in depths from 300 to 1130 m b.g.l. (below ground level). Single or straddle-packer hydraulic tests were conducted in different low-permeability rocks. The hydraulic testing equipment used was specially designed to reduce uncertainty associated with the low-permeability testing conditions and included a downhole hydraulic shut-in valve (DHSIV), a hydraulic piston, a probe carrier, and inflatable packer(s). Pressure and temperature are monitored with sensors connected to the bottom of the borehole, the test interval, the annulus above the upper packer, and the test tubing above the DHSIV. Hydraulic test sequences consisted of multiple withdrawal and shut-in phases. Test phases started with a compliance phase to allow some of the pressure and temperature transients caused by tool installation and packer inflation to dissipate, followed by a pressure static recovery phase to allow the test interval pressure to establish a recovery trend after being isolated. In general, in the low-permeability formations the active test sequence consisted of a pulse withdrawal performed using a hydraulically operated piston displacing a precisely defined volume, a slug withdrawal, and lastly a slug-withdrawal shut-in phase. The pressure data collected during the hydraulic tests were analyzed using the well-test simulator nSIGHTS®. The use of a numerical model is necessary for the analyses of the tests in low-permeability rocks as borehole history and temperature equilibration during the test can have a significant impact on test responses. Analyses started with the definition of a borehole-formation conceptual flow model based on geological information and interpretation of diagnostic plots. Input model parameters composed of non-fitting parameters and fitting parameters are defined. Preliminary automated calibrations are performed to identify the appropriate conceptual model and obtain baseline estimates of the fitting parameters for each tested interval. Perturbation analyses entailing hundreds to thousands of optimizations are performed to obtain the final best-fit parameter values and the corresponding uncertainty ranges. Our presentation will give an overview on methodologies and workflows with emphasis on the numerical design and analysis techniques applied to the hydraulic packer tests performed. The applied methodology provided high-quality results and reliable estimates of the hydraulic conductivities in the low-permeability rocks. The results from the hydraulic packer tests will be presented, and implications for further research by Nagra will be discussed.

Standalone and Interconnected Analysis of an Independent Accumulator Pressure Compressibility Hydro-Pneumatic Suspension for the Four-Axle Heavy Truck

This paper has proposed a new hydro-pneumatic damper, allowing independent accumulator pressure compressibility from the chamber pressure which enhances isolation performances due its lower F-V hysteresis effect at moderate velocities. The system utilizes the generic hydraulic damper with two hydro-pneumatic accumulators and four check valves in its design. To evaluate the active suspension capability of proposed damper effectiveness, a 22-degrees-of-freedom (DOF), four-axle truck model is integrated with a hydraulic control valve, which is built in an LMS-AME sim environment. Then, the model is exported as an S-function into Matlab/Simulink co-simulation platform for the hydraulic servo-valve control input of a model predictive control (MPC) and proportional-integral-derivative (PID) output signal. Simulation results show that the MPC and an additional supply of fluid to the proposed damper provide better performances and an adaptive damping capability is established. This work also showcases the development and results of a roll interconnected suspension study to assess the proposed damper characteristics when it is interconnected. The various advantages of the proposed-HPIS system over the well-known hydraulic interconnected system (HIS) and hydro-pneumatic interconnected suspension (HPIS) system are studied.

Review of Recent Advances in the Drive Method of Hydraulic Control Valve

Hydraulic control valves are widely used in industrial production, agricultural equipment, construction machinery, and other large power equipment for controlling the pressure and flow of fluids in hydraulic systems. The driving method has a significant impact on the response and control accuracy of hydraulic valves. This paper reviews the driving methods of spools from five aspects: solenoid drive, material expansion drive, motor drive, hydraulic valve drive, and another drive. It summarizes the various schemes currently available for spool drive and analyzes each of them. After optimizing the driving method of the valve core, the control accuracy can reach 3%, and the minimum response time is 7 ms. According to the characteristics of the different drive methods, the differences between them are compared, the advantages and disadvantages of each drive method are analyzed, and the application scenarios for each drive method are identified. Solutions to the drawbacks of the existing drive methods are proposed, which provide directions for further optimization. We have found that solenoid drives are simple to control, low cost, and the most widely used. Material telescopic drives, motor drives, hydraulic valve drives, and other drives are costly, complex to control, and optional for use in special requirement situations. Based on the existing spool drive methods, an outlook on future drive methods is presented. This review facilitates a comprehensive understanding of the drive methods of hydraulic valve spools, points out the shortcomings of the existing drive methods, and is of great significance in improving the existing drive methods and proposing new drive methods. This paper has a positive effect on improving the control accuracy and responsiveness of hydraulic valves.

A Convolutional Autoencoder Based Fault Diagnosis Method for a Hydraulic Solenoid Valve Considering Unknown Faults.

The hydraulic solenoid valve is an essential electromechanical component used in various industries to control the flow rate, pressure, and direction of hydraulic fluid. However, these valves can fail due to factors like electrical issues, mechanical wear, contamination, seal failure, or improper assembly; these failures can lead to system downtime and safety risks. To address hydraulic solenoid valve failure, and its related impacts, this study aimed to develop a nondestructive diagnostic technology for rapid and accurate diagnosis of valve failures. The proposed approach is based on a data-driven model that uses voltage and current signals measured from normal and faulty valve samples. The algorithm utilizes a convolutional autoencoder and hypersphere-based clustering of the latent variables. This clustering approach helps to identify patterns and categorize the samples into distinct groups, normal and faulty. By clustering the data into groups of hyperspheres, the algorithm identifies the specific fault type, including both known and potentially new fault types. The proposed diagnostic model successfully achieved an accuracy rate of 98% in classifying the measurement data, which were augmented with white noise across seven distinct fault modes. This high accuracy demonstrates the effectiveness of the proposed diagnosis method for accurate and prompt identification of faults present in actual hydraulic solenoid valves.