Transmission Fault Research Articles

DC Commutation Failure Analysis for the Sending-Side System Fault in Hybrid UHV Half-Wavelength and UHV DC Transmission System

Commutation failure (CF) caused by the failure which occurs on the sending side of the ultra-high voltage (UHV) half-wavelength AC (HWAC) transmission system is studied. Firstly, a hybrid UHV HWAC and UHV DC transmission system model is built, and the essence of CF is revealed regarding the influences of various factors on occurrence probability of CF. Then, the mechanism of CF of the UHV DC transmission system caused by the fault at the HWAC line in the hybrid system is explored. The steady-state operation characteristics are obtained through characteristic analysis according to the quasi-steady-state model of the HWAC line, and a three-phase short-circuit fault is assumed on the sending-side of a HWAC line and its voltage characteristics are deeply analyzed. In the actual power system, the specific situation of DC CF caused by the fault of the HWAC line is verified and analyzed based on a large quantity of transient stability calculations. Comparative analysis of the effects on UHV DC lines of the faults which occur on different locations of a HWAC line is presented. The conclusions can provide a useful reference and reliable technical support for the development of HWAC system and maintain power grid security and stability.

Lightweight Multidimensional Encrypted Data Aggregation Scheme With Fault Tolerance for Fog-Assisted Smart Grids

Encrypted data aggregation is an effective approach to preserve power consumption data confidentiality as well as reduce communication overhead in smart grids. As the core component of smart grids, smart meters periodically report encrypted multidimensional data to an aggregator gateway. However, heavy computation and communication overhead may hinder the wide applications of smart meters. Besides, once the secret key is leaked, encrypted data will be broken, thereby violating users’ privacy. In this article, we present a lightweight multidimensional encryption data aggregation (MD-EDA) scheme, enabling a grid control center to retrieve fine-grain aggregated data in a confidential way. In particular, each fog node is installed at the edge of networks, playing the role of aggregator gateway for data verification and aggregation in the same grid area. MD-EDA prevents adversaries from extracting valuable data even if the secret key is compromised. MD-EDA exploits Shamir secret-sharing technique to achieve transmission fault tolerance mechanism from smart meters to a corresponding fog node. The performance evaluation demonstrates the lightweight computation advantages of MD-EDA in the deployment of fog-assisted smart grids.

Assessment of Low-Voltage Motor Ride Through: A Comparison of Solutions for Critical Processes in the Oil and Gas Industry

Voltage sags initiated by utility transmission system faults cause nuisance trips of low-voltage (LV) motors, due to contactors dropping off as a result of the undervoltage condition. Since voltage disturbances by utility systems cannot be prevented, it is essential to mitigate the impact of LV motors trips on critical process systems in the oil and gas industry, such as lubrication and shaft-sealing systems. To address this challenge, there is a tendency in the industry to modify standard LV motor control schemes to hold contactors closed during voltage sags to maintain process continuity. This approach will be evaluated against restarting schemes and sag correction devices in terms of their impact on motor performance and motor controller design. A simulation model was developed using Power Systems CAD to assess motor performance and subsequent current and torque profiles associated with various ride-through solutions. The reliability and safety aspects of modifications associated with different ride-through solutions were evaluated and benchmarked against relevant international standards and industrial practices.

Evaluation, Analysis and Diagnosis for HVDC Transmission System Faults via Knowledge Graph under New Energy Systems Construction: A Critical Review

High voltage direct current (HVDC) transmission systems play a critical role to optimize resource allocation and stabilize power grid operation in the current power grid thanks to their asynchronous networking and large transmission capacity. To ensure the operation reliability of the power grid and reduce the outage time, it is imperative to realize fault diagnosis of HVDC transmission systems in a short time. Based on the prior research on fault diagnosis methods of HVDC systems, this work comprehensively summarizes and analyzes the existing fault diagnosis methods from three different angles: fault type, fault influence, and fault diagnosis. Meanwhile, with the construction of the digital power grid system, the type, quantity, and complexity of power equipment have considerably increased, thus, traditional fault diagnosis methods can basically no longer meet the development needs of the new power system. Artificial intelligence (AI) techniques can effectively simplify solutions’ complexity and enhance self-learning ability, which are ideal tools to solve this problem. Therefore, this work develops a knowledge graph technology-based fault diagnosis framework for HVDC transmission systems to remedy the aforementioned drawbacks, in which the detailed principle and mechanism are introduced, as well as its technical framework for intelligent fault diagnosis decision.

Application of power grid wind monitoring data in transmission line accident warning and handling affected by typhoon

With the increasing number of transmission line monitoring points, it is possible to obtain meteorological monitoring data of power grid, and the meteorological monitoring data of power grid can be further used to guide typhoon disaster early prevention, fault repair and disposal of transmission faults. This paper innovatively proposes a typhoon microscale (100 m) wind field simulation method suitable for the complex terrain conditions in different coastal areas of China, and uses the power grid meteorological monitoring data to improve the early warning accuracy and credibility in the local terrain space of typhoon disasters. The prediction robustness and accuracy of the scale reduction prediction model are improved through continuous observation and statistical correction, several engineering examples show that the method is correct and effective. The dynamic typhoon prevention strategy of the power grid and the timely adjustment of the power grid operation mode can be guided for the preliminary analysis of the cause of the transmission failure after the typhoon transit, so as to provide scientific guidance for the subsequent emergency repair. This method has a general practical and guiding value for the coastal power grid of the typhoon influence area.

Automatic fault identification in WSN‐based smart grid environment

SummaryWireless sensor network (WSN) plays a vital role in the smart grid (SG) environment. Due to the fault tolerance characteristics, cost reduction, and large‐scale convergence, SG introduces many unique challenges caused by system and functional devices. To solve this problem, a WSN‐based SG network is used to identify faults. During data transmission, faulty nodes occur in the transmission line. The node failures, calibration, network failures, low battery, dead nodes, environmental changes, software failures, and so on lead to the interruption in data delivery and spoil the entire WSN‐based SG network. In order to tackle these problems, the new WSN model is designed to detect the faults in the transmission line based on the SG environment. This paper uses the Adaptive Zigbee‐Aquila communication protocol (AZACP) to find the optimal shortest path for transferring data. AZACP finds the shortest optimal path for transmitting the sensed data to the base station with low cost and less time consumption. Fault detection automatically identifies the fault in the transmission line and isolates the faulty nodes to ensure efficient data transmission in WSN. Here, enhanced recurrent equilibrium neural network (ERENN) is introduced to identify the fault in data transmission. The proposed approach provides better performance in terms of evaluating performance metrics like throughput, delay, reliability, average residual energy, number of total transmissions, network lifetime, efficiency, and bit error rate (BER).

Error Correction and Error Detection in Network

Errors manipulation explains how errors are handled and determined using the network, specifically on the data connection layer. We offer a top level view of error manipulate in this paintings, including mistakes detection and mistakes restore. Information hyperlink layer mistakes manipulate takes place there. We specially communicate approximately the varieties of error detection algorithms used to locate faults and the way to repair them so the receiver can get the real statistics. The essential requirement of each communique system in the realm of wi-fi conversation these days is the potential to ship and receive errorless statistics over any noisy channel. The assets of noise and interference have also grown as a result of the development in records transmission. Engineers have made several tries to address the demand for more dependable and effective strategies for detecting and correcting errors within the acquired statistics. Various techniques are hired to pick out and attach information transmission faults. This evaluation paper affordan a extensive range of error detection and correction strategies thathave been around for a while. More than one tend error in SRAM memory rise whilst the technology scaled down, inflicting unmarried cellular and more than one cellular upsets to emerge. Blunders-correcting codes, such the preliminary approach of the (7,four) hamming code, wherein 7 stands for the overall code word, four stands for statistics bits, and 3 stands for parity bits, had been positioned into use and their encoding and decoding processes have been examined. The main drawback of this hamming code is that it's far handiest suitable forsingle-bitt errors detection and rectification.

Analysis of fault coupling vibration and transmission characteristics of multistage gear transmission system

In multi-stage gear transmission system, the accident is often not caused by a single fault, but by coupling fault. The decoupling and identification of coupling faults has always been a hot topic. Through the analysis of frequency characteristics and transmission characteristics, this paper explored the correlation of coupling faults in multistage gear transmission system, and analyzed the coupling mechanism of faults. According to the fault test-bed, a 3D model was built to analyze the contact force and vibration characteristics of gears at all stages. STFT and waterfall diagram were used to analyze the coupling correlation characteristics of experimental signals under two single faults and coupling faults: fixed-axis gear crack and planetary gear wear. The contact force transfer function of all stages of gears to the box was built by using the system identification theory. The source of the fault characteristic frequency component was found through the transfer function, and the transmission characteristic of the fault was revealed. It can be seen from the results that the fault coupling is not the superposition of frequency characteristics. In the coupled signal, the frequency characteristic with the largest amplitude increase is not the fault gear itself, but the intermediate gear connected with them and affected by them. This phenomenon is often misled and misjudged in the analysis.

Analytical reliability evaluation method of smart micro‐grids considering the cyber failures and information transmission system faults

The reliability of smart micro-grids (SMGs), as a cyber-physical system (CPS), might be influenced by cyber failures and information transmission faults. Several Monte Carlo simulation (MCS)-based approaches have been reported to assess the reliability of SMGs and smart grids. On the other hand, analytical reliability assessment methods have been presented in some research works, while the cyber system has not been concerned. However, the literature shows a research gap in developing an accurate and fast reliability evaluation method for SMGs based on the unavailability of cyber elements and information transmission faults. This article tries to fill the discussed gap by adding the analytical modelling of cyber-physical interdependencies and information transmission faults to available analytical methods, focusing on physical uncertainties. Comparing the proposed model with existing MCS-based and analytical reliability evaluation methods illustrates the advantages of this research. Test results show that less than 5.7% expected energy not supplied (EENS) error occurs by the proposed method, which would be much faster than MCS-based ones. Moreover, the sensitivity analyses highlight the impacts of the cyber network topologies on the cyber-physical interdependencies.

Normal fault transmissibility characteristics under the transition condition of fault conduction and sealing observed in simulation experiments

In rift basins, normal faults conducting and sealing fluids are the main mechanisms for evaluating fault-related reservoirs, and the defined threshold value of fault conduction or sealing is based on statistics. However, fault transmissibility characteristics under a transition condition of fault conduction and sealing have not been clarified. This study used structural deformation and hydrocarbon charging as a foundation to quantitatively characterize fault transmissibility under the transition condition of fault conduction and sealing. This study examined faults occurring in sandstone–mudstone interbeds and used the fault throw and mudstone content as the main variables. The physical simulation results revealed that despite all models exhibiting simple “one-layer” fault architecture with only a fault core, their internal composition undergoes a sequential change from the mudstone drag, mudstone drag and sliding surface to the mudstone breccia and sliding surface. Similarly, when the fault is in the transition condition of fault conduction and sealing under the constraints of mudstone, a normal distribution is observed in terms of the number of oil-bearing layers, oil-bearing length, and oil-bearing area of the lateral fault conduction. However, when the shale smear factor (SSF) is too high, the “one-layer” fault architecture mainly comprises the mudstone breccia and sliding surface, which increases the vertical fault transmission and reduces the lateral fault conduction. Conversely, an excessively small SSF, where the fault zone is a “one-layer” fault architecture comprising mainly the mudstone drag or mudstone drag and sliding surface, will restrict the vertical fault transmission and reduce the lateral fault conduction. When the lateral fault conduction near the inflection point of the normal distribution reaches its threshold, the superposition of mudstone along the fault and the presence of mudstone breccia in the fault zone become critical for decelerating the vertical fault transmission and accelerating the lateral fault conduction. The study of normal fault transmissibility characteristics under the transition condition of fault conduction and sealing provides a solid theoretical foundation for the risk assessment of fault-related hydrocarbon accumulation.

Application of active magnetic bearings in control and estimation of geared-rotor faults in high speed offset spur gear transmission system

This study is focused on the mathematical modelling, analysis, active transverse vibration control and fault analysis of a single-stage spur geared-rotor system. It uses Active Magnetic Bearings (AMBs) as an auxiliary bearing in addition to the conventional mechanical bearing in rotor fault detection considering the dynamic model with gyroscopic effects. The change in dynamic forces primarily due to the mesh deformation, gear runout, and variable transmission error are considered, which causes unwanted vibration and noise. To prevent the damage of gears and other supporting structures, these forced vibrations and control currents are meticulously investigated. From the dynamic responses of geared-rotor, the AMB control the stiffness and damping to minimize the transmission of forced vibrations to the mountings by closed-loop feedback control system. For an accurate modelling the dynamic transmission error is taken in two orthogonal transverse directions, which has asymmetric transmission error characteristics. Full spectrum is used for frequency domain analysis with tilting phenomena of the gears at high spin speed. An identification algorithm is developed for fault detection and estimation of system parameters from vibration and current of the proposed geared-rotor-AMB system. The robustness of the proposed algorithm is verified with different added percentage of noise and modeling errors.

Permanent Magnet Synchronous Motor Driving Mechanical Transmission Fault Detection and Identification: A Model-Based Diagnosis Approach

This paper presents a model-based scheme for permanent magnet synchronous motor (PMSM) driving transmission fault detection and identification (FDI) in a steady-state condition. The proposed framework utilizes a PMSM state-space model and an approximated transmission model to construct the regression models for parameter estimation using the Recursive Least-Square (RLS) algorithm. The FDI are accomplished by the residual current spectrum thresholding method to assess the fault characteristic frequency magnitude and also by parameter clustering. Two types of mechanical transmission with three different fault conditions are tested in the experiments. As a preliminary effort in the condition monitoring of PMSM driving transmission, the study results demonstrate a promising approach by considering both residual current spectrum and parameter cluster, which achieved a satisfactory decision making in detecting and identifying the faulty condition.

Fault Modeling and Simulation of Engine Driven Pump in Aircraft Hydraulic System

Abstract The structure of engine driven pump in aircraft hydraulic system is complex, its fault forms are diverse, and the fault transmission path is complex and multi factor coupling. In view of the above problems, based on the in-depth analysis of the working principle of the engine driven pump, the engine driven pump model is established, and the leakage fault injection mechanism of the friction pair is added. The relationship between the flow fluctuation characteristics of engine driven pump and the changes of pump spindle speed, swashplate inclination and pump outlet cavity volume are obtained through model simulation analysis. The mechanism of internal leakage fault of plunger pair, port pair and slipper pair are analyzed, the influence of leakage clearance parameters on key performance indexes such as pump pressure and flow are simulated, and the simulation test data of internal leakage fault of pump are obtained. The simulation results show that the inclination angle of swashplate and spindle speed are positively correlated with the output flow of the pump. The increase of pump outlet volume can effectively alleviate the pressure and flow fluctuation behind the pump. In addition, when the radial clearance of the plunger pair of this type of pump exceeds 0.2mm, the pump fault characteristics begin to appear. At the same time, the load change behind the pump will affect the characterization of the fault of internal leakage of the pump.

DFIG based WT harmonics Analysis subjected to Diverse Transmission Fault

This paper is focused on harmonic analysis for an energy conversion sys- tem using wind power (WECS) based on a Double Fed Induction Generator (DFIG). A Frequency converter is coupled back to back is used to excite the rotor winding and stator winding excited by different electrical networks. This work also focuses on harmonic distortion based on the DFIG Model. This approaches also analyzed on the basis of different kind of Line and Ground faults of Transmission line. The research work is Conducted using Simulink software with the SimPower System. The MATLAB simulation shows a major work in the design, study, and assessment of different controller based power electronic converter. A Research Case study for a 5 Mega Watt renewable wind turbine mill is Described , which is Designed for the load flow calculation of harmonic

Investigation of Spur Gear Dynamics with Gear MeshImpacts Induced by Tooth Wear

Abstract Tooth wear is one of the most common faults in gear transmission systems. However, due to its limited influences on gear dynamics, the condition monitoring of gear wear experiences more challenges. To investigate the relationship between tooth wear and gear dynamics, this study develops an eight-degree of freedom dynamic model which takes into account the gear mesh impact induced by tooth wear. In this model, the gear mesh impact force induced by tooth wear was calculated as an extra input excitation for the gear dynamic model. Besides, a comparative study was carried out to explore the real reason that causes the poor dynamic behaviour due to the wear from two points of view: 1) the reduction in gear mesh stiffness; 2) the increase in gear mesh impact force. The simulation results show that the wear causes a slight reduction in gear mesh stiffness, thus leading to the decrease in the amplitude of gear mesh frequency. This is not consistent with the phenomena observed in the lab experiment which shows the increase in the gear vibrations. The second simulation of impact force demonstrates that the wear causes an increase in the impact force which further leads to the increase in the amplitude of gear mesh frequency. This study investigates the cause for the deterioration in gear dynamics induced by gear wear, which can benefit the early condition monitoring and fault diagnosis of the gear tooth wear.

Mitigation of voltage sags in distribution line system using static VAR compensator and static synchronous compensator

Voltage sag is one of the power quality disturbances most frequently by customers because it can cause economic loss for the customers especially industries and commercial customers. The main source of voltage sags are faults in transmission and distribution beside two others namely motor large starting and transformer energizing, both the voltage sags have less effect on the equipment. Voltage sags can cause degradation performance of the equipment, and it depends on the magnitude and the duration. The voltage sags that occur in the power system can be compensated with installed Static VAR compensator (SVC) and Static synchronous compensator (STATCOM) in the distribution system bus. The purpose of the study is to compare both types of the device used to mitigate voltage sags in simulation using Alternative transient program (ATP) software. The voltage sag results from the short circuit faults. The method proposes the installation of the two compensator devices alternatively at one of the IEEE thirteen busses systems. The result shows the STATCOM is better than the SVC to handle mitigation of voltage sags compared with the SVC.

Fusion Deconvolution for Reliability Analysis of A Flywheel-Battery Hybrid Energy Storage System

A hybrid flywheel-battery energy storage system is able to smooth the battery charging/discharging; harmful impact can be filtered by the flywheel to reduce battery damage and extend battery life. However, due to extremely high rotating speed of the flywheel, the hybrid storage system is often subject to mechanical failures in the flywheel transmission system. Therefore, it is critical to detect unexpected faults in the flywheel transmission to ensure the normal operation of the hybrid energy storage system. To this end, in this study a new fusion deconvolution is proposed to perform reliability analysis on the hybrid flywheel-battery energy storage system. Firstly, the Deterministic Random Separation (DRS) is used to simplify the sensory signal components to obtain the fault impulse. Then, the multipoint kurtosis (MKurt) of the impulse is used to determine the parameters of the multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) model. Lastly, the envelope analysis of the signal filtered by the MOMEDA deconvolution is carried out to obtain the characteristics of the periodic fault pulses. Both numerical and experimental results demonstrate that the proposed fusion deconvolution method produces satisfactory diagnostic performance. Compared with existing popular deconvolution algorithms, the proposed method proposed improves the extraction of the periodic fault pulses.

Research on Event Logic Knowledge Graph Construction Method of Robot Transmission System Fault Diagnosis

Knowledge graph technology has important guiding significance for efficient and orderly fault diagnosis of robot transmission system. Taking the historical robot maintenance logs of robot transmission system as the research object, a top-down fault diagnosis event logic knowledge graph construction method is proposed. Firstly, we define event arguments of fault phenomenon and fault cause events, define event argument classes and relation between classes, and construct an event logic knowledge ontology model. According to the event logic knowledge ontology, the fault diagnosis event argument entity and relation in the corpus are labeled, and an event logic knowledge extraction dataset is formed. Secondly, an event argument entity and relation joint extraction model is proposed. Using stacked bidirectional long short-term memory(BiLSTM) to obtain deep context features of text. As a supplement to stacked BiLSTM, self-attention mechanism extracts character dependency features from multiple subspaces, and uses conditional random field(CRF) to realize entity recognition. The character dependency features are mapped to the entity label weight embedding, and spliced with deep context features to extract relations. Bidirectional graph convolutional network(BiGCN) is introduced for relation inference, graph convolution features are used to update deep context features to perform joint extraction in the second phase. Experimental results show that this method can improve the effect of event argument entity and relation joint extraction and is better than other methods. Finally, an event logic knowledge graph of robot transmission system fault diagnosis is constructed, which provides decision support for autonomous fault diagnosis of robot transmission system.

Improving the transmission error source tracing method for gear hobbing machines

By considering the uncertainness of initial measuring position of encoders and signal sidebands caused by the fault gear pair, this paper presented a new comprehensive harmonic analysis method for the transmission error of gear hobbing machine. Based on that, a test platform was established, in which two circle grating encoders were connected to the hob spindle and workpiece spindle respectively. With the help of this new harmonic analysis method as well as the self-developed test platform, a new improved transmission error fault diagnosis method was developed for the gear hobbing machines. To verify its accountability, a case study was conducted on a YS-type gear hobbing machine. According to the spectrum amplitude comparison and the analysis of harmonic frequency distribution, the fault transmission gear pair was successfully located. This improved transmission error source tracing method was very helpful for quantifying both the manufacturing qualities and assembly qualities of parts and locating potential error source for new gear hobbing machines.

Dynamic reliability analysis approach based on fault tree and new process capability index

AbstractThis paper proposes a dynamic reliability analysis approach based on fault tree (FT) and new process capability index (PCI). This work has three contributions. First, new PCIs, namely, Cp‐R, Cpk‐R, Cpm‐R, and Cpmk‐R, are proposed on the basis of traditional PCI prototypes, and the data stability analysis results converge to (0∼1] interval. These new PCI advantages and defects are compared, and the result shows that Cpmk‐R can identify the stability of the dynamic data effectively. Second, fault risk index (FRI) based on Cpmk‐R index, namely, Rpmk‐R, is proposed to approximate the probability of basic events (BEs) for FT. Third, FRI and FT are used to analyze fault transmission and assess dynamic fault risk of equipment. A circulating cooling water heat exchange system is used for simulation to verify the practicability of the approach. Results show that the FT based on Rpmk‐R can assess the dynamic fault risk of equipment accurately.