Jam Fault Research Articles

A hybrid intelligent diagnostic approach for spool jamming faults of hydraulic directional valves

A hybrid intelligent diagnostic approach for spool jamming faults of hydraulic directional valves

Fault Detection and Isolation in Simulated Batch Operation of Fine Motion Control Rod Drives

Control rods and elements manage the power distribution in nuclear reactors through the motion of banks of rods distributed throughout the core. These positional changes are achieved through the actuation of fine motion control rod drive (FMCRD) mechanisms. In the BWRX-300 design by GE-Hitachi, this mechanism is electrically driven by a servomotor that allows for high-precision control of power outputs. Under operational transients, such as load-following, accurate and precise operation of these servomotors is necessary over long periods of time, so they are key maintenance targets to maintain availability and operational flexibility. Swiftly and precisely identifying faults in the drive mechanisms will support predictive maintenance and reduced costs. This paper used three different types of simulated faults to test the fault detectability of principal component analysis (PCA) when considering the simulated operations of banks of control rods and their associated servomotors. These faults were stator short-circuit faults, ball screw jam faults, and ball screw wear faults. Torque and position were monitored in the simulation. The position signal was insufficient to detect mechanical faults. Torque signals for each servomotor in the bank of rods undergoing multiple position demand changes were projected to a reduced dimensional space via PCA. Q and T2 statistics were employed for anomaly detection. Using this approach, all faults were detected, and the anomalies were isolated to the faulty FMCRD mechanism.

Deep Learning Approach to Within-Bank Fault Detection and Diagnostics of Fine Motion Control Rod Drives

Control rod motion is one of the primary means of regulating the rate of fission in a nuclear reactor core to ensure safe and stable operation. Reactor power distribution and thermal power output can be fine-tuned by adjusting the control rod position. For high-precision control of rod movements, Fine Motion Control Rod Drives (FMCRDs) are often used. The operation of FMCRDs provides a unique opportunity to implement condition monitoring related to the intermittency of motion and the use of control rod banks. This research sets out to detect three types of faults in an electrically driven FMCRD. In addition to detecting faults, this work will attempt to determine both the type of fault and the source of each fault, completing the fault detection and diagnostics (FDD) pipeline on a scarcely researched system. The three types of faults to be investigated are short-circuit faults, ball screw wear faults, and ball screw jam faults. This is a potential advancement to the within-bank FDD of this specific drive system intended for deployment in an advanced nuclear reactor plant. Using encoder-decoder structured convolutional neural networks and autoencoders, the three tested faults were confidently detected and isolated as well as reasonably diagnosed by monitoring the FMCRD servomotor torque.

Adaptive Feed-Forward Control for Gust Load Alleviation on a Flying-Wing Model Using Multiple Control Surfaces

Based on measured gust information, a multi-input multi-output (MIMO) adaptive feed-forward control scheme for gust load alleviation (GLA) on a semi-span flying-wing aircraft using multiple control surfaces is proposed. In order to remedy weight drift and biased estimation problems that are commonly encountered in adaptive control, the circular leaky LMS (CLLMS) algorithm is employed, which utilizes gust measurement information, filtered reference signals, and error signals to update controller parameters online. The results demonstrate that good load reductions are achieved in both continuous and discrete gust environments. For instance, the designed GLA control system leads to an 80.72% reduction in the root-mean-square (RMS) values of wing-root bending moment in the Dryden gust environment and a 77.59% reduction of its maximum value in the 1-cos discrete gust condition. Based on the limited power of the actuator and the limited authority for control surface deflections when integrating GLA into the flight control system, a weight-updating algorithm with deflection angle and rate constraints on control surfaces is proposed. The simulation results show that the strict constraints on control surface deflections will degrade the GLA performance. Finally, the influence of the partial jamming fault of actuators on GLA performance is studied. It is found that good GLA performance can be preserved despite the degraded performance during the initial stage of the actuator jamming fault. This is due to the robustness brought about by multiple control surfaces and the adaptability of the control algorithm.

Intelligent diagnosis and prediction of turbine digital electro-hydraulic control system faults: Design and experimentation.

A physical modeling approach was adopted to build a Digital Electro-Hydraulic Control (DEH) system simulation model and the fault models using the SIMULINK tool. This research combined the advantages of the gray system and neural network to build a multi-parameter gray error neural network fault prediction model for the first time. Furthermore, an embedded platform for intelligent fault diagnosis and prediction was developed using an Application Specific Integrated Circuit chip. The results show that the simulation model of the DEH system has good performance. A jam fault, internal leakage, and a device fault could be accurately identified through the fault diagnosis model. The multi-parameter gray error neural network prediction model improves the accuracy of fault prediction. The embedded platform developed by the Application Specific Integrated Circuit chip solves the problem of transmission limitation and insufficient computing power. It realizes the intelligent diagnosis and prediction of DEH system faults and guarantees the regular operation of the DEH system.

Fault Prediction of Railway Turnout Systems Based on Improved Sparse Auto Encoder and Gated Recurrent Unit Network

Railway turnout systems (RTS), as one of the most critical ground infrastructures of the high-speed rail, which directly impact the railway operation safety, are also susceptible to frequent faults. Hence, efficient fault prediction and intelligent maintenance decision support of RTS are significant to avoid unexpected outages and guarantee the operation safety of trains. A key challenge for fault prediction of RTS is to extract and select effective feature combinations that describe the degradation status of the system and then generate health indicators (HI) with high monotonicity, correlation, and robustness. In this paper, we focus on the jam fault caused by insufficient lubrication, which is one of the most frequent faults of RTS, and we present a novel unsupervised adaptive latent feature extraction method based on the improved sparse auto-encoder (ISAE). The locally weighted regression (LOESS) is performed to smooth the extracted latent features to overcome the influence of the noise. Improved auto-associative kernel regression (IAAKR) is utilized to fuse the feature combination and generate HI, which can intuitively describe the degradation status of RTS. Finally, the gated recurrent unit (GRU) network is introduced to enhance the correlation data process and construct the fault prediction models. The parameters of GRU are optimized by the improved particle swarm optimization (IPSO) algorithm. Extensive experiments are conducted on a real-world RTS degradation dataset collected from the Changsha Railway Station in China, which is related to the jam fault caused by the lubrication reduction, and the results show the proposed method achieves better prediction performance compared to state-of-the-art methods in terms of different evaluation metrics.

A Recognition Method for the Coil Plunger Motion Resist Force Based on Coil Current in Vacuum Circuit Breaker

Jams in the tripping devices are common faults in circuit breakers, which will lead to the failures in circuit breaker. The resist force of the coil plunger in the tripping device could effectively reveal the jam faults. In this paper, a recognition method for the coil plunger motion resist force based on coil current is proposed. The electromagnetic motion model of the coil is established, and the plunger resist force in VS1‐12 is recognized. According to the recognition result and the moving process of the coil plunger, the fitting formula of the resist force is proposed. The resist force from the coil is 5 N, while the force from the latch is 52 N. Based on the fitting formula, the trip coil current of the circuit breaker is simulated. The result is in good agreement with the test result, which verifies the validity of the fitting formula and the recognition method. The method can be applied to the circuit breaker with spring operating mechanism and effectively extract the resist force from the coil current. This research can provide reference for the condition detection and fault warning of coils in circuit breaker. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

The on-line detection technology of oil level in main transformer conservator of an 110kV Substation

The oil level of transformer conservator is related to the safe operation of transformer. There is no better way to detect the oil level of the conservator, when the indication of the oil level gauge is unclear or the jam fault. Through the selection of ultrasonic sensor, design of measurement and verification device and field practice, this paper studies and develops an on-line detection technology based on the ultrasonic principle, which can effectively and accurately detect the oil level of existing conservator types such as diaphragm, capsule and corrugated conservator, and is not limited by the detection environment.

Evaluation of thermal effects on temperature-sensitive operating force of flow servo valve for fuel metering unit

Abstract The temperature-induced variation in operating force of flow control valves may result in performance degradation or even jam faults of fuel metering unit (FMU), which significantly affects the safety of aircrafts. In this work, an analytical modeling approach of temperature-sensitive operating-force of servo valve is proposed to investigate the temperature characteristics in varying temperature conditions. Considering the temperature effects, a new extended model of flow force is built and an analytical model of valve friction is also derived theoretically based on the dynamic clearance induced by thermal effects. The extremum condition of friction is obtained to analyze the characteristic-temperature points where jam faults occur easily. The numerical results show that flow force increases firstly and then decreases as temperature increases under a constant valve opening. The maximum friction of flow servo valve can be uniquely determined when the structural parameters and ambient temperature are given. The worst situation just happens at the characteristic-temperature points, which are linearly related to the axial temperature gradients of valve spool. Such evaluations may give an explanation for the temperature-induced jam faults of vulnerable valves and provide a reference for designers to determine a suitable working-temperature range of valves in practice.

Fault‐tolerant reference generation for model predictive control with active diagnosis of elevator jamming faults

SummaryThis paper focuses on the longitudinal control of an Airbus passenger aircraft in the presence of elevator jamming faults. In particular, in this paper, we address permanent and temporary actuator jamming faults using a novel reconfigurable fault‐tolerant predictive control design. Due to their different consequences on the available control authority and fault duration, the above 2 actuator jamming faults need to be distinguished so that appropriate control reconfigurations can be adopted accordingly. Their similarity in symptoms, however, prevents an effective discrimination of the root cause of the jamming when using only a passive fault‐diagnosis approach. Hence, we propose the use of model predictive control (MPC) as a fault‐tolerant controller to actively help the fault‐detection (FD) unit discriminate between a permanent and a temporary jamming fault, while ensuring the performance of the aircraft. The MPC controller and the FD unit closely interact during the detection and diagnosis phases. In particular, every time a fault is detected, the FD module commands the MPC controller to perform a predefined sequence of reconfigurations to diagnose the root cause of the fault. An artificial reference signal that accounts for changes in the actuator operative ranges is used to guide the system through this sequence of reconfigurations. Our strategy is demonstrated on an Airbus passenger aircraft simulator.

Improving train position accuracy in case of wheel jamming faults

Abstract This paper is about position estimation and fault detection under jamming fault for rail transportation system. The motivation is to improve the accuracy of the position estimator in real-world conditions, considering modeling errors, perturbations and expected faults. The approach is based on an unknown input observer used to estimate perturbations and detect jamming faults for a class of polytypic linear parameter-varying (LPV) system. Moreover, the mixed H∞/H_ approach is applied to help in the robustness of the fault detection via a residual. Offline experiments results are provided for illustration.

Design of Longitudinal Axial Flow Threshing and Separating Device of Maize Grain Combine Harvester

Harvesting grain directly has been the development trend of modern maize combine harvester. To satisfy the demand of harvesting grain straightly type maize combine harvester for large feeding rate, low damage rate, high threshing rate, the longitudinal axial flow threshing and separating device was designed. It could also increase the separating rate of grain and miscellaneous, and reduce the burden of cleaning device. Threshing gap was adjustable in the range of 30 to 60mm, which reduced the incidence of jam faults effectively in the threshing process. Spiral blade on feeder, threshing rasp-bar and separating nail were replaceable, which improved the efficiency for threshing and separating.

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Variational Mode Decomposition and Multi-Layer Classifier.

Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analysis is one of the most significant issues in improving the reliability and reducing the outage cost for power systems. The limitation of training samples and types of machine faults in HVCBs causes the existing mechanical fault diagnostic methods to recognize new types of machine faults easily without training samples as either a normal condition or a wrong fault type. A new mechanical fault diagnosis method for HVCBs based on variational mode decomposition (VMD) and multi-layer classifier (MLC) is proposed to improve the accuracy of fault diagnosis. First, HVCB vibration signals during operation are measured using an acceleration sensor. Second, a VMD algorithm is used to decompose the vibration signals into several intrinsic mode functions (IMFs). The IMF matrix is divided into submatrices to compute the local singular values (LSV). The maximum singular values of each submatrix are selected as the feature vectors for fault diagnosis. Finally, a MLC composed of two one-class support vector machines (OCSVMs) and a support vector machine (SVM) is constructed to identify the fault type. Two layers of independent OCSVM are adopted to distinguish normal or fault conditions with known or unknown fault types, respectively. On this basis, SVM recognizes the specific fault type. Real diagnostic experiments are conducted with a real SF6 HVCB with normal and fault states. Three different faults (i.e., jam fault of the iron core, looseness of the base screw, and poor lubrication of the connecting lever) are simulated in a field experiment on a real HVCB to test the feasibility of the proposed method. Results show that the classification accuracy of the new method is superior to other traditional methods.

Intelligent Fault Diagnosis System of Plate Heat Exchanger Based on GIS

In order to improve the degree of digital urban central heating system in our country、manage many heat exchangers in the central heating system and timely and accurately diagnose with scale or jam faults of heat exchangers in the operation process, from the viewpoint of engineering application, this paper established the intelligent fault diagnosis system of plate heat exchanger, aimed at “the urban heating system intelligent decision-making platform development and demonstration ”project. Plate heat exchanger scale or jam fault diagnosis model is established based on real-time monitoring. Meanwhile association between pressure drop and flow of plate heat exchanger is given and applied to an actual plate heat exchanger for calculation and experimental verification. Results show that the fault diagnosis model can basically meet the requirements for engineering application,has a strong applicability and has a broad application prospect in the fault diagnosis system of plate heat exchanger.

Real-Time Diagnosis of Slide Valve and Oil Servomotor’s Jam Faults Based on Strong Tracking Filter

Jam fault occurs most times in the hydraulic servo system, and is the one of the factors that mainly influences the reliability of the system. For parallel-operated turbine, the jam faults of regulating system are elusive and fatal. In order to monitor operation condition and improve the reliability of the system online, the model of jam fault had been built, the sizes of the dead zones which describe jam fault had been viewed as unmeasured parameters, which avoided the model uncertainty brought by the linearization of nonlinear system, and strong tracking filter had been used to estimate unmeasured parameter. Simulation and experimental results verified that, this technique could accurately, synchronously estimate respective degrees of jam faults of slide valve and pilot valve online whether in daily operation or moving test.

The Research of the Jam Fault Features and Diagnostic Methods of the Slide Valve Oil Motive Based on DEH Data

The jam fault diagnosis of slide valve oil motive has great significance on the safe and stable operation of steam turbine. As limited data available from DEH, the jam fault is difficultly diagnosed directly by DEH data. This paper defines insensitivity to represent the level of the jam fault of slide valve oil motive system. Through the simulation and research of the jam fault features of the slide valve oil motive, the relationship between the rate of change of the input signal and the insensitivity of the jam fault diagnosis is be found . Then jam fault diagnosis strategy based on DEH data was put forward and it shows good results with verification by the actual data.

An investigation of the temperature distributions inside a spool valve owing to a viscous heating effect

The objective of this article is a numerical analysis of the temperature distributions around the notches of a spool valve, because of the viscous heating effect caused by high-speed flow of the large-viscosity hydraulic oil. Two valve spools fabricated with different shapes of notches are investigated, of which spool A is an earlier one, being reported to cause a jam fault under specific working conditions. Spool B is an improved one, which has shown no evidence of damage from jamming in applications up to the present. However, except for practical application, no experimental or numerical tests have been carried out to support it. The deformation of the spool caused by viscous heating is very small, so it is difficult to be observed by conventional experimental methods. In this article, a numerical method is employed to uncover the flow field inside the valve as well as the temperature distributions on the valve spool. The results show important differences between spool A and spool B, including local temperature distributions and peak temperatures around the notches. In conclusion, spool B is evaluated to be more reliable from jam faults than spool A. However, present studies are limited to computational fluid dynamics analysis, which restricts studies on flow and heat transfer. More reliable predictions will be made in the future.

Evaluation of the viscous heating induced jam fault of valve spool by fluid–structure coupled simulations

Abstract In this paper, the steady high speed oil flow in the spool valve and the local temperature distributions around the notches are simulated using a finite volume based CFD code. The temperature increase is due to the viscous heating effect, which is generally significant in highly-viscous fluid flow. Moreover, the deformation of the spool is simulated by the code ABAQUS (a finite element based software). These two codes are simply coupled on the spool surface, where the temperature distributions obtained from the CFD results are imposed as the boundary conditions of the deformation calculations. It is noted that this fluid–structure interaction (FSI) is modeled based on a loosely-coupled strategy, where the ABAQUS is started when the flow converges to a steady state and a stable thermal distribution has been reached. The aim of this study is to evaluate two different valve spools of the damage from jamming. Results have presented qualitative exhibitions of the temperature contours, appearances of the deformed spools, as well as the quantitative measurements of the radial deformations. Such evaluation provides the engineers a good assistant for design. Especially when the real case experiments are difficult to implement, the computer-based simulations are even powerful.

Study of Electro-Hydraulic Converter with Strong Restoring-Motion

In order to eliminate the disadvantages of the traditional electro-hydraulic converters in the turbine governor, a new electro-hydraulic converter with strong restoring-motion was studied in this paper. The basic structure and working principal were analyzed, and the basic characteristics were described in detail. The simulation analysis of its dynamic characteristics was made by using Simulink software and the methods for improvement of the performances were suggested. The results of field tests indicated that the performance indexes of the hydro-turbine governors with this new technology were conformable to or higher than GB. It is concluded that the new electro-hydraulic converter has a promising future in engineering applications, especially in turbine governing systems that suffer from jam fault.

Design of controller switching strategy for reusable launch vehicle with elevon jamming failure

AbstractWhen a reusable launch vehicle (RLV) returns to earth, it flies just by gliding without thrust. In this phase, one of the most likely and important faults to occur in the airframe is a jamming of the elevon. To tolerate this failure, the flight control system must keep stability and performance during such a failure. One of the effective ways to overcome this problem is to switch the controllers based on the information of the detected failure in the plant. Generally speaking, the controller must have integrators so as to yield the zero steady‐state error for the controlled output even if there exist some perturbations in the plant dynamics. In this paper, the design of controller switching scenario is addressed especially focusing on the decision of the controller state at the instant of switching the controllers with integrator. Then, the proposed switching scenario is applied to the control of ALFLEX (Automatic Landing FLight EXperiment), which is the automatic landing experimental vehicle being developed for RLV, considering the occurrence of the jamming fault. Some simulations are shown to verify the usefulness of the proposed idea. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 164(2): 80–90, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20356