Leakage Fault Research Articles

A non-contacting leak fault diagnosis method for subsea Christmas tree valve based on deep neural network with skip connections

Due to the complex and diverse underwater environment, underwater acoustic transmission is easily disturbed, absorbing many noise components. To deal with the complex noise components is a challenge with the traditional signal processing method. Moreover, it is hard to diagnose the valve's leakage and the leakage degree in the subsea Christmas tree using underwater acoustic signals. This paper proposes a new non-contacting fault diagnosis method based on a deep neural network (DNN) with skip connections. First, we obtain the required time-domain data using acoustic sensors (a digital hydrophone) in experiments. Second, the time-domain data is preprocessed and is converted by the short-time Fourier transform into time-frequency domain signals. The time-frequency domain signals are then input into a constructed DNN model to minimize the noise components in the signal. After that, the denoised data are applied to a convolutional neural network for fault diagnosis. Finally, an underwater acoustic experiment is designed and performed to validate the proposed method's effectiveness. The experimental results demonstrate that our proposed method can effectively diagnose the leakage fault of the valve, and the diagnosis accuracy reaches 98.89%.

Discriminability Analysis of Characterization Parameters in Micro-Leakage of Turbocharged Boiler’s Evaporation Tube

It is extremely dangerous for a turbocharged boiler to have a leakage fault in its vaporization tube. However, early detection and fault diagnosis of micro-leakage faults are very difficult. On the one hand, there are few fault samples that lead to a difficult and intelligent diagnosis. On the other hand, the system fault response characteristics of the characterization parameters in the process are complex and easily confused with the load-changing characteristics. In order to obtain fault samples and identify fault characteristics, a fault simulation model for the micro-leakage of the boiler evaporation tube is established based on the dynamic mathematical model of all working conditions. The model’s effectiveness is verified by typical fault experiments. The dynamic simulation experiments of three kinds of micro-leakage and four kinds of load changing were carried out. Through the analysis of combustion equilibrium and vapor-liquid equilibrium of 14 groups of characterization parameters, it is found that: (1) The reason for the poor discriminability in micro-leakage faults is that most of the characterization parameters tend to balance after 300 s and the dynamic response characteristics are similar to those of load increase. (2) There are four highly distinguishable parameters: the speed of the turbocharger unit, the air supply flow, the flue gas temperature at the superheater outlet, and the furnace pressure. When the micro-leakage fault is triggered, the first three parameters have a large disturbance. They show a trend of decreasing first and then increasing in short periods, unlike normal load-changing conditions. The fourth parameter (furnace pressure) rises abnormally fast after failure. (3) Under the normal working condition of varying loads, the main common parameters take 300 s to stabilize; the common stability parameter values should be recorded because when the micro-leakage fault of evaporation occurs, the steady-state increment of failure is larger than the normal steady increment under variable load conditions, by 2 to 3 times. (4) As the leakage fault increases, the disturbance amplitude of the characteristic parameters becomes larger. In addition, the stability of the steam system becomes worse, and fault discrimination becomes more obvious.

Performance Prediction of an Axial Piston Pump With Increasing Severity of Leakage Fault in Single and Multiple Cylinders

Abstract As axial piston pumps (APP) become increasingly compact to meet the size, weight, and performance demands (high pressure ratings), they are prone to wear, and hence the leakage between the sliding parts, which run under tight tolerances. This leakage fault can degrade the pump's performance and limit its predictability and reliability. In this study, a simulation and mathematical model-based approach are presented to simulate the effect of increasing severity of leakage fault (increasing annular gap) in both single, and multiple cylinders simultaneously, on the pump performance. The Leakage is modeled as laminar flow past the uniform annular gap between the piston and cylinder. With a single faulty cylinder, as the wear (annular gap) increases the time-mean outlet flow and pressure of the pump remain constant until a critical threshold, and then reduce rapidly, leading to deterioration in the pump's volumetric efficiency. With increase in faulty cylinders this critical threshold shifts to lower magnitudes, and in the limit of more than four faulty cylinders this threshold saturates to a constant magnitude. The dynamic signal's data show that the increasing severity of leakage and increasing number of faulty cylinders modulate both the time signature and the amplitude fluctuations of the outlet pressure waveform due to the reduced flow in the discharge cycle. Further, FFT analysis of these dynamic signals, and the time-mean value of pressure and flow rate leakage fault diagnosis is presented to classify the pump's condition as either healthy or moderately faulty or severely faulty.

External temperature field test and leakage fault diagnosis for SOFC stacks

The uniformity of Solid Oxide Fuel Cell (SOFC) stacks largely affects the stability and performance of the SOFC power generation system with multiple stacks. However, the health conditions of the stacks are usually assessed by the long-time electrochemical performance test, and some small faults are not able to be quickly identified when the I–V performances have small differences. In this paper, a non-contact temperature sensor array constructed by thermocouples is proposed for NDE (non-destructive evaluation) application in SOFC stacks. The temperature sensor array is fixed near the outer surfaces of the 1 kW-class stack to measure the external temperature field of the stack. Based on the experimental results, it is found that the proposed method is feasible for the examination of the external temperature field of stacks under different operation conditions, which helps to screening the stacks before assembling to the system. At the same time, a real-time online monitoring of fuel leakage is performed using the temperature sensor array, and stacks with unusual temperature distribution due to the leakages can be quickly recognized by comparing with the healthy stack.

Judgment of Low-voltage leakage fault type and fault point finding method in power distribution platform area

In the development of modern social economy and technological innovation, the technical application of the power industry is more and more demanding, and researchers have gradually strengthened the judgment and search technology research of low-voltage leakage fault type in distribution platform area. From the perspective of practical application, when the leakage fault occurs in the low-voltage line, it is necessary to find the area as soon as possible and put forward an effective solution, so as to avoid further expansion of the fault problem. In this paper, on the basis of understanding the causes of low-voltage leakage faults in distribution platform area, according to the various judgment schemes proposed by scholars at home and abroad, an intelligent fault identification and positioning system is deeply discussed, so as to clarify the types of faults and find methods. Finally, the practical results show that the causes of leakage faults are different, and the practical judgment and search methods should be targeted and diversified.

Control Approach to Fault Disambiguation

To ensure resilience, systems must be endowed with capabilities for rapid detection, response, and recovery to disruptiveevents. In this paper we focus on faults as disruptive events and use a diagnosis engine for their detection and isolation. In particular we use model-based diagnosis, where the diagnosis engine is provided with a model of the system, nominal values of the parameters of the model and values of some of its inputs and outputs. However, there is no guarantee that the information measured by sensors is sufficient to distinguish between multiple root-causes. We address this challenge using an optimal control approach: we design control inputs such that the similarity between outputs in ambiguous fault modes is reduced. We show that under certain assumptions on the system model, minimizing a similarity metric in terms of outputs is equivalent to increasing the diagnosis certainty. We use an optimization-based approach to input design, where the system model acts as a constraint. We show that by using a surrogate model expressed with constructs endowed with differential operators, we improve the time efficiency of the optimal control problem. We demonstrate our approach on a fuel line system, where feedback control is used to ensure the mass flow rate at the engine follows a prescribed reference. We consider leak faults that affect the fuel lines. We show that under the control inputs generated by the nominal controller, mass flow rate measurements are not enough to accurately isolate leaks. We demonstrate that by using custom inputs that minimize the similarity between the outputs in the ambiguous faults modes, the diagnosis uncertainty is eliminated.

Analysis of hydraulic system’s weak fault based on variable parameter multi-scale permutation entropy and deep belief network

Aiming at automatic recognition of hydraulic system’s weak fault, an analysis method based on variable parameter multi-scale permutation entropy (VPMPE) and deep belief network (DBN) is proposed in this paper. The external vibration signals of experimental hydraulic equipment in normal state and three different leakage state (slight, moderate and severe) are taken as research object. By the proposed method, experiment signals are first processed to obtain their multi-scale permutation entropy in different conditions by changing the embedding dimension m and the scale factor s, then the multi-scale permutation entropy under different m and s are combined to form feature vectors, and lastly the DBN classifier is used to identify and analyze the testing samples. Verification test shows that the proposed method has good effects on hydraulic system’s weak fault, which can accurately judge whether there is leakage fault and measure the fault severity.

Influence of high pressure pulsating excitation on pipe joint sealing based on multiscale contact analyses

Most of the leakage faults in hydraulic pipeline systems occur in the pipe joint. The research on the high-pressure sealing and reliability of the pipe joint is very important in the application of civil aircraft parts. On the basis of studying the characteristics of pressure pulsating fluid, this paper explores the influence of a high pressure pulsating fluid on the sealing performance of flameless extruded pipe joints and analyzes the influence of the internal fluid pulsating amplitude and fluid under different pressures on the contact stress distribution of the sealing surface of the pipe joint. The results show that with the increase in flow pulsation amplitude from 0.5% to 5%, the amplitude of contact stress on the sealing surface decreases with creep time, which makes the sealing performance better. However, the effective working time of the joint as a whole decreases from 2000 to 194 h. The high-stress area of the contact surface expands as the fluid pressure increases, and the high internal fluid pressure obviously improves the sealing effectiveness and reliability of the pipe joint. In addition, the influence of fluid pulsation amplitude on the leakage rate of the joint is much greater than that of the fluid pressure.

Real-Time Leak Detection in High Frequency Hydraulic Cylinder Based on Intelligent Control

Most of the existing hydraulic cylinder internal leakage detection methods are laboratory testing methods, mainly the pressure-holding method, measurement of hydraulic cylinder settlement method, and measuring cup measurement method. The internal leakage of the hydraulic cylinder affects the damping characteristics of the control system. Therefore, real-time internal leakage detection plays an important role in the control characteristics. This paper first proposes a wavelet analysis-based extraction of hydraulic cylinder internal leakage fault eigenvalues for analysis, that is, data processing. A convolutional neural network-based detection method is also proposed, in which the pressure signal of a chamber of a hydraulic cylinder is first obtained through simulation under four operating conditions: no leakage, small leakage, medium leakage, and large leakage. Compared to traditional modelling methods, the method overcomes the difficulties in modelling nonlinear hydraulic systems, requires only pressure signal acquisition, is simple and reliable, and is compared with traditional BP neural networks to demonstrate its superiority.

Position Control of a Single-Rod Electro-Hydrostatic Actuator Experiencing a Leaky Piston Seal

Single-rod cylinders are generally employed in electro-hydrostatic actuators (EHAs). A condition that is difficult to detect and could degrade the performance in single-rod EHAs, is the faulty cylinder piston seal. It causes internal leakage from one chamber of the actuator to another. In this work, a position controller with tolerance to actuator internal leakage is synthesized for a single-rod EHA using quantitative feedback theory (QFT). The controller is also robust to different loading and environmental stiffnesses. The ability of the controller is compared with another QFT controller that is synthesized without considering leakage fault. The simulation results show that the QFT fault-tolerant controller can meet prescribed specifications despite internal leakage up to 8.6 L/min.

Optimized-Based Fault-Tolerant Control of an Electro-Hydraulic System with Disturbance Rejection

In this article, the design and implementation of a fault-tolerant controller are proposed for an electro-hydraulic actuator (EHA) in the presence of disturbances and actuator faults. The existence of nonlinearities, uncertainties, and a bias fault (i.e., internal leakage fault) in the system dynamics significantly decreases the desired performance. The nonlinear disturbance observers (NDO) are constructed to handle the adverse influences caused by the above disadvantages. The whole fault-tolerant control (FTC) scheme consists of two design loops: an inner force control loop and an outer position control loop. The inner loop is based on an optimized backstepping framework to achieve the optimal performance, whilst the problem of uncertainties and disturbances is dealt with using a terminal sliding mode directly designed from the position tracking error. It is shown by theoretical analysis that system stability is ensured under faulty conditions. Finally, simulation results and comparison studies are conducted to further verify the effectiveness of the proposed approach.

The Detection of Open and Leakage Faults for Prebond TSV Test Based on Weak Current Source

During the manufacturing process of three-dimensional integrated circuits (3-D ICs), many defects may occur in through-silicon vias (TSVs). These defects affect the integrity of the signal passing through TSVs, therefore detecting these defects in the early production stage is crucial. This article proposed a built-in-self-test (BIST) method with a simple test structure and easily implemented fault detection process. Due to the fact that the defects in TSVs influence the charge/discharge speed of TSVs’ equivalent capacitance, a weak current source is designed as the central part of the proposed test structure, which can measure the TSVs’ charge/discharge speed and quantify it using digital values. The effectiveness and robustness of the proposed method is validated by HSPICE simulation. The minimum measurable fault, test time, and test circuit area are also assessed in this article. The simulation results show that the method this article proposed can detect weaker faults, compared with the traditional test methods.

Actuator failure compensation-based command filtered control of electro-hydraulic system with position constraint

In this article, the design and experimental evaluation of a fault-tolerant controller are introduced for a double-rod electro-hydraulic actuator subjected to actuator faults and disturbances. The internal leakage fault is captured as a bias fault, whilst the faults in servo-valve and supply failure are considered as a partial loss of effectiveness (LOE) fault. The design obstacles caused by the disturbances and bias fault are suppressed by nonlinear disturbance observers (NDO) while an asymmetric barrier Lyapunov function is used to ensure the non-violated boundary of the output position. To tackle the LOE fault, the development of an enhanced adaptive compensation technique for actuator fault-tolerant control (FTC) is then constructed. Moreover, to mitigate the “explosion of complexity” in the traditional backstepping design, the command-filtered control is utilized to elaborate the FTC scheme. It is shown by theoretical analysis that system stability is ensured under faulty conditions. Finally, simulation/experiment results and comparison studies are performed to further verify the effectiveness of the proposed approach.

Node Monitoring as a Fault Detection Countermeasure against Information Leakage within a RISC-V Microprocessor

Advanced, superscalar microprocessors (μP) are highly susceptible to wear-out failures because of their highly complex, densely packed circuit structure and extreme operational frequencies. Although many types of fault detection and mitigation strategies have been proposed, none have addressed the specific problem of detecting faults that lead to information leakage events on I/O channels of the μP. Information leakage can be defined very generally as any type of output that the executing program did not intend to produce. In this work, we restrict this definition to output that represents a security concern, and in particular, to the leakage of plaintext or encryption keys, and propose a counter-based countermeasure to detect faults that cause this type of leakage event. Fault injection (FI) experiments are carried out on two RISC-V microprocessors emulated as soft cores on a Xilinx multi-processor System-on-chip (MPSoC) FPGA. The μP designs are instrumented with a set of counters that records the number of transitions that occur on internal nodes. The transition counts are collected from all internal nodes under both fault-free and faulty conditions, and are analyzed to determine which counters provide the highest fault coverage and lowest latency for detecting leakage faults. We show that complete coverage of all leakage faults is possible using only a single counter strategically placed within the branch compare logic of the μPs.

Investigation on calendar experiment and failure mechanism of lithium-ion battery electrolyte leakage

Electrolyte leakage is one of the typical faults that lead to battery failure, and its failure mechanism is still ambiguous. Therefore, it is crucial to investigate the experimental method and failure mechanism of lithium-ion battery electrolyte leakage. The electrolyte leakage behavior of commercial lithium-ion batteries is imitated by controlling the leakage location, extent and duration in the study. The evolution characteristics of external comprehensive performance are quantitatively evaluated. Furthermore, a thermodynamic investigation method combining in-situ synthesis and ex-situ disassembly is performed to reveal the equilibrium potential degradation mechanism. The intrinsic property of kinetic degradation is explored based on the electrochemical impedance interconnection of half-cell and full-cell. Eventually, the dominant degradation of the negative electrode active material and the most serious deterioration of the negative electrode charge transfer process are illustrated. Moreover, attractive phenomena of the voltage plateau during relaxation and the current peak at the constant-voltage charging stage are detected, indicating the potential lithium plating. The detection results based on X-ray diffraction (XRD) and scanning electron microscopy (SEM) technology corroborate the destruction of the negative electrode and the existence of lithium plating. The disclosure of performance failure mechanisms and diverse characterizations provides support for the electrolyte leakage fault diagnosis method.

Electrical Line Fault Detection and Line Cut-Off Equipment and Control

In order to locate the leakage fault location of low-voltage electrical lines, cut off the power supply of electrical lines, and ensure the safety and reliability of the power supply network, this paper proposes an electrical line leakage fault detection system based on a signal trigger. Based on the research on the current leakage protection system of low-voltage electrical lines, the author puts forward that the leakage current of the selected test analog trigger signal is not less than twice the maximum value of the normal leakage current of electrical lines and equipment with STC15F2K60S2 single-chip microcomputer as the control core. The experimental results show that 30 mA is preferred for the sensitivity of the leakage fault test signal. When the rated leakage action current is equal to or less than 30 mA, the protection action time is required to be less than 0.1 s, and when the rated leakage action current is greater than 30 mA, it is required to be less than 0.2 S. The device is a supplement to the traditional leakage protection device. According to the comparison between the indirect leakage detection and direct leakage detection results and the actual leakage position distance, the error is within 10%. It is proved that the system meets the actual needs and improves the protection performance of the leakage protection system of low-voltage electrical lines.

Detecting hydrocarbon micro-seepage and related contamination, probable prospect areas, deduced from a comparative analysis of multispectral and hyperspectral satellite images

Detecting mineralogical alteration by hydrocarbon micro-seepage from trap to surface across the deformed structure, through Comparative analysis study of hyperspectral image (EO-1, Hyperion), and multispectral (landsat7 and Advanced land imager (Ali) to map soil alteration by petroleum seepage with applying remote sensing techniques as (band ratios, supervised, SAM classification, and hydrocarbon detection and index (HD and HI) calculation to detect the potentiality of hydrocarbon seepage in the area. The type of spectral resolution accuracy available for each space imaging platform can be used to choose which is best in determining the target and whether exploration yields oil. Hyperspectral remote sensing data are integrated with a GIS framework Weighted Sum (Spatial Analyst) classified hydrocarbon seepage prospects into five potential zones very good, good, intermediate, poor, and very poor probable potentiality. The spatial lithologic carbonaceous alteration appears closely coincident along reactivated leaking faults that cause hydrocarbon micro-seepage and altered surface lithology and mineralogical cement. The hyperspectral images have proven their worth in identifying and studying hydrocarbon leaks and the resulting environmental pollution and mineral alteration, as well as use micro-seeps as a pathfinder to locations of new oil explorations discoveries that can use as a pre-drill prediction of hydrocarbon occurrence and detected a prospect area for hydrocarbon drill.

Proxy Capacitance-Resistance Modeling for Well Production Forecasts in Case of Well Treatments

Summary We disclose a new-age field-scale production forecast model that handles complex treatment of wellbores during their life cycle. Predictive production models have been an object of increased interest and research for a long time due to the need for a fast tool for forecasting production rates or choosing an optimal field development scheme. The existing approaches based on the material balance equation have several limitations and are not very applicable for real objects. Full-scale reservoir modeling is relatively slow and requires large computing resources. In this paper, we propose a proxy model based on advanced capacitance-resistance approach. The model predicts multiphase flow rates based on the available historical data of field production and information about well treatments. In addition, it provides preferable transmissibility trends, the presence of sealed or leaking faults, and the degree of dissipation between injector-producer well pairs. The advanced feature of the model is time-dependent weight coefficients, which have not been studied previously. They help in accounting the shut-in and workover periods and can be found during the optimization procedure simultaneously. Another feature is fast calculations due to a vectorized form of the model and application of modern optimization techniques. All these options allow modeling real oil fields with a large number of wells and a complex system of production control.

Leakage Diagnosis of Air Conditioning Water System Networks Based on an Improved BP Neural Network Algorithm

Compared with traditional pipe networks, the complexity of air conditioning water systems (ACWSs) and the alternation of cooling and heating are more likely to cause pipe network leakage. Pipe leakage failure seriously affects the reliability of the air conditioning system, and can cause energy waste or reduce human comfort. In this study, a two-stage leakage fault diagnosis (LFD) method based on an Adam optimization BP neural network algorithm, which locates leakage faults based on the change values of monitoring data from flow meters and pressure sensors in air conditioning water systems, is proposed. In the proposed LFD method, firstly, the ACWS network’s hydraulic model is built on the Dymola platform. At the same time, a cuckoo algorithm is used to identify the pipe network’s characteristics to modify the model, and the experimental results show that the relative error between the model-simulated value and the actual values is no more than 1.5%. Secondly, all possible leakage conditions in the network are simulated by the model, and the dataset is formed according to the change rate of the observed data, and is then used to train the LFD model. The proposed LFD method is verified in a practical project, where the average accuracy of the first-stage LFD model in locating the leaking pipe is 86.96%; The average R2 of the second-stage LFD model is 0.9028, and the average error between the predicted location and its exact location with the second-stage LFD model is 6.3% of the total length of the leaking pipe. The results show that the proposed method provides a feasible and convenient solution for timely and accurate detection of pipe network leakage faults in air conditioning water systems.

Analysis and detection of fault for substation GIS insulating part based on integrated automation system data

Insulators are important components in gas-insulated metal-enclosed switchgear (GIS), and their safe operation is of great engineering significance. In an air leakage fault accident caused by the cracking of the insulating part of the grounding knife switch of 500kV HGIS equipment, the following measures were taken to find out the cause of the failure: disassembly inspection, equipment assembly review, insulation performance test and residual stress analysis during casting and curing. It turned out that the failure was caused by a lack of cache firmware in the production process. The thermal conductivity and thermal expansion coefficient of the central copper conductor and epoxy resin are different. When the two are solidly adhered, the incompletely reacted insulating parts shrink too quickly when the temperature difference is too large. The copper conductor locally produces excessive residual stress to the epoxy resin, which causes the insulation to crack. According to the causes of the fault, suggestions are put forward, such as replacing the central copper conductor with aluminum material, adding secondary pre-curing procedure in the production process, and adding Remote longitudinal Wave probe on the Insulated Basin side to monitor residual stress in real time.