Open Fault Research Articles

Microgrid line protection method using the cosine similarity of the time domain traveling waveform

For the existing microgrid line traveling wave protection method, the head information of traveling wave is hard to extract, which probably leads false action or non-action of protection. This paper proposes a transient-state protection method that utilizes cosine similarity of time domain voltage traveling wave to identify microgrid line faults. By deriving the time domain expression of the transient voltage traveling wave at both ends of the microgrid line, the conclusion can be summarized that the forward wave at the one end and the backward wave at the other end of the non-fault line are the same traveling wave, while the waves at both ends of the fault line are distinct. Based on this, fault discrimination is achieved by using the cosine similarity coefficient between the time domain voltage waveforms of the forward and backward waves. This method does not need to extract the initial wave head information of the traveling wave, which improves the reliability; and the speed of protection is enhanced by using the signal of transient traveling. The simulation results show that this protection method is independent of the microgrid operation state, fault location and fault type, which verifies the feasibility of the proposed method.

Evaluation of Tractor Quality Based on Vibration Characteristics

Problem. The overall development time for agricultural tractors is 7-10 years, with testing accounting for approximately 63-80% of the total time. Within testing, reliability testing under operating conditions comprises 58-73% of the workload. However, even after extensive testing, serially produced tractors often fail to meet the specified lifespan and reliability requirements. Final refinements are only made to tractors after a certain accumulation of operational faults, resulting in hidden defects remaining in the serial production of tractors, as testing primarily addresses major structural and manufacturing defects. Goal. The aim of this study is to evaluate the design and manufacturing quality of tractors based on their vibration characteristics. These characteristics can identify structural and technological defects that decrease the reliability and lifespan of tractors. Methodology. Analytical research methods were employed to improve the quality of traction electric motors for electric transportation. Experimental research methods and the determination of electric motor technical conditions based on their vibrodiagnostic parameters were utilized. Statistical methods were employed to process experimental studies. Results. Vibration measurement results indicated that tractors belonging to vibration class E are not recommended for serial production. These tractors have an estimated lifespan of 6-8 thousand engine hours and incur high maintenance costs compared to tractors of vibration class D. Tractors with vibration levels of class E are not recommended for serial production due to the excessive vibration load on components. Originality. The T-150K tractor family requires significant redesign of its structure, manufacturing processes for components, and bearing unit assembly. This is achieved through constructive measures, such as ensuring bearing preload in shaft supports, using class 4 precision bearings with a noise index of QE1, and providing a floating fit with a clearance of no more than 15 μm between the bearing and the housing. Introducing intermediate bushings into the design of gearbox output shaft bearings improves the accuracy of machining bearing seating surfaces and the assembly of bearing units. Practical value. The developed vibration evaluation methods for T-150K tractors enable the assessment of their design and manufacturing quality. The research data obtained during the design stage allows for more reliable predictions of tractor quality.

Absolute stress levels in models of low-heat faults: Links to geophysical observables and differences for crack-like ruptures and self-healing pulses

Absolute levels of stress on faults have profound implications for earthquake physics and fault mechanics. A number of observations suggest that well-developed, mature faults such as the San Andreas Fault are generally “weak,” i.e. operate at much lower levels of shear stress compared to the higher expected shear resistance ∼100 MPa at seismogenic depths. In particular, low heat flow measurements suggest shear stress levels of ∼10 MPa or less on highly localized faults. Geodynamic constraints based on topography and similar considerations also support “weak” fault operation, and are comparable with heat-based constraints for some mature faults, but potentially higher for regions with substantial topography. Here, we investigate measures of average fault shear stress and their relationship to geophysically inferable quantities using numerical simulations of earthquake sequences on rate-and-state faults with low heat production, due to chronic fluid overpressure and/or enhanced dynamic weakening from the thermal pressurization of pore fluids. We review the earthquake energy balance, focusing on energy-based definitions of average shear stress and how the average fault prestress (a measure of fault strength plausibly relevant to geodynamic constraints) can be expressed as the sum of the dissipation-based average rupture stress (which can, in principle, be inferred from shear-heating constraints), and seismologically inferable source properties, such as the static stress drop and apparent stress. Our modeling demonstrates that rapid dynamic weakening and healing of shear resistance during ruptures, as exhibited in self-healing pulses, allows faults to maintain higher average interseismic stress levels despite low dynamic resistance and realistic static stress drops, providing a physical explanation for potential differences between topography-based and heat-based constraints on fault shear stress. In our models, the difference is related to stress undershoot and apparent stress, which can be as large as 1-3 times the static stress drop based on our simulations. Yet suitably large values of apparent stress (and hence radiated energy) are rarely inferred for natural earthquakes, either because radiated energy is underestimated, or suggesting that most large earthquakes do not propagate as sharp enough self-healing pulses with sufficiently large undershoot. Our results emphasize the distinction between dynamic versus static stress changes when relating earthquake source observations to absolute levels of fault stress and suggest that reviewing estimates of radiated energy and static stress drop from large earthquakes, with input from finite-fault numerical modeling, may improve constraints on absolute fault stress levels.

Research on the Access Planning of SOP and ESS in Distribution Network Based on SOCP-SSGA

This paper proposes a two-stage planning model for soft open point (SOP) and energy storage system (ESS) that considers the cost of faults in response to the current issue of SOP and ESS systems not considering the impact of SOP access on load transfer in the event of a fault in the distribution network. Firstly, considering the uncertainty of “PV-load”, typical scenarios of PV and load are constructed based on the clustering algorithm. Secondly, aiming at the economic performance of the distribution network and the capacity of PV access, a two-stage optimization model is established for the joint integration of SOP and ESS into the distribution network (normal and fault operation) under typical scenarios. The model is solved by using the second-order cone programming algorithm and steady-state genetic algorithm (SOCP-SSGA). Stage one involves planning for the integration capacity and location of SOP and ESS into the distribution network under each scenario within a period based on SOCP with the goal of minimizing economic costs. In stage two, the PV access capacity of the distribution network is optimized using SSGA with the goal of enhancing the PV accommodation capability. Finally, verification and analysis are conducted on an improved IEEE33 node system. The results show that when the system optimizes access to a group of SOP and ESS, the total economic cost is reduced by RMB 61,729 compared to random access, and the accessible PV capacity is increased by 0.5278 MW. Moreover, optimizing access to two sets of SOP and ESS can further reduce the total economic cost by RMB 107,048 compared to the optimized access group and increase accessible PV capacity by 1.5751 MW. Therefore, the proposed plan for SOP and ESS planning in this paper can significantly reduce the economic cost of distribution networks, enhance the absorption capacity of distributed photovoltaics, improve the voltage level of power grid operation, and, thereby, improve the economic and reliability of distribution network operation.

Online Prediction of Electric Vehicle Battery Failure Using LSTM Network

The electric vehicle industry is developing rapidly as part of the global energy structure transformation, which has increased the importance of overcoming power battery safety issues. In this paper, first, we study the relationship between different types of vehicle faults and battery data based on the actual vehicle operation data in the big data supervisory platform of new energy vehicles. Second, we propose a method to realize the online prediction of electric vehicle battery faults, based on a Long Short-Term Memory (LSTM). Third, we carry out prediction research for two kinds of faults: low State of Charge (SOC) alarm and insulation alarm. Last, we show via experimental results that the model based on the LSTM network can effectively predict battery faults with an accuracy of more than 85%. Through this research, it is possible to complete online pre-processing of vehicle operation data and fault prediction of power batteries, improve vehicle monitoring capabilities and ensure the safety of electric vehicle use.

A fault location method based on ensemble complex spatio-temporal attention network for complex systems under fluctuating operating conditions

Recently, traditional fault diagnosis methods achieve fault identification by establishing a sample set covering all fault degrees of different fault components in complex systems. However, the uncertainties including environmental stresses and own physical and chemical variations lead to an infinite number of fault degrees of fault components, and the fault identification of complex systems in practical engineering applications faces the challenge of fluctuating operating conditions due to variations of rotational speed and load. To address the above problem, a fault location method based on ensemble complex spatio-temporal attention network (ECSAN) is proposed in this paper, which can identify the critical fault components of complex systems by combining an ensemble learning mechanism with excellent basic estimators. A basic estimator consists of a feature extraction module, a feature enhancement module, and a classification module. In the first module, a complex spatio-temporal backbone network with strong generalization is developed to provide spatio-temporal features containing the inherent information of the sample data for complex systems. In the feature enhancement module, a lightweight complex attention layer is constructed to enhance the effective structural information of the features and reduce the interference of their redundant information. The classification module then adopts a Softmax layer to perform fault classification. Finally, an ensemble learning mechanism is designed to integrate the basic estimators. By constructing sample weights and introducing a knowledge transfer strategy, the generalization is further improved while saving training expenses. Two datasets from different experimental platforms are concerned to verify the effectiveness and superiority of this method under various operating conditions and fault degrees. The experimental results indicate that this method achieves 99.81% accuracy on a standard dataset of the mechanical system and 98.88% accuracy on a real dataset of the closed-loop control system of the water jet propulsion device, which is superior to comparison approaches.

CRACK RESISTANCE OF BRIDGE REINFORCED CONCRETE STRUCTURES BASED ON THE FRACTURE MECHANICS PRINCIPLES

Purpose The work purpose is to establish the real technical condition of reinforced concrete and steel-reinforced concrete bridges based on the surveys and tests, as well as the analysis and synthesis of scientific and technical sources. Methodology. To achieve the goal, a review and synthesis of scientific and technical sources and regulatory documents regarding the technical condition of reinforced concrete and steel-reinforced concrete bridges and overpasses of Ukraine is carried out. It is shown that the development and implementation of new technologies for repairing the existing bridge defective structures, in particular on the highways of Ukraine is an urgent problem. A thorough analysis of experience and publications on the operation of newly built and long-term specified bridges in the mentioned environments is carried out. The data on the main unacceptable defects and faults of bridge structures as well as the causes, including concrete and reinforcement corrosion, and other defects and faults are presented. The quality indicators of reinforced concrete and steel-reinforced concrete bridge structures are considered, the problems and analysis of ensuring reliability and durability in the operation conditions on the highways of Ukraine are formulated. Results. The analysis of domestic and foreign scientific and technical sources as well as the experience of surveys and tests regarding the technical condition of reinforced concrete bridges structures in Ukraine is carried out. In particular, the analysis and synthesis of the problems of ensuring the reliability and durability of the specified bridges in the operation conditions on the highways of Ukraine is carried out. The design errors, construction defects and faults, and long-term operational faults in the mentioned environments are summarized and clarified. In addition, the obtained data are as the basis to specify the criteria and models of the destruction mechanics in relation to reinforced concrete bridge structures. In particular, based on the obtained data, the methods to determine the VAT and the residual resource of the specified bridges are created. Scientific novelty. Based on the analysis and synthesis of scientific and technical sources and a number of surveys and tests, reinforced concrete and steel-reinforced concrete structures and long-term bridges newly built after the floods in 1998 and 2001, it is possible to summarize the main reasons that significantly affect the structures degradation of both the newly built and long-term bridges. This allows generalizing the design errors, construction defects and faults, and long-term operational faults. In addition, the state data served as the basis to specify the criteria and models of the destruction mechanics in relation to reinforced concrete bridge structures. In particular, based on these data, the methods to determine the assessment of the strength and crack resistance and the VAT and the residual resource of such bridges are created. Practical significance. Based on the given data and observations of real objects for 30 years, the main faults, defects and errors of the design, construction, and long-term bridges are summarized and set up. The methods to determine the VAT and calculate the residual resource, giving an opportunity to work out the repair and restoration method to increase the durability and reliability of long-term bridges are created.

VDDNet: An Object Detection Model for Measuring the Vibration Displacement of Rotating Structure

The signal acquisition and analysis of the structure vibration can effectively diagnose the operation status and fault type. The visual inspection method has the advantage of non-destructive testing and providing full-field vibration information for monitoring the vibration of rotating machinery. However, the accuracy requirements for measuring the small displacements generated by the low-amplitude vibration of high-speed rotating machinery are extremely high. It remains a challenge to achieve accurate, precise, and fast extraction of high-frequency and small-amplitude micro-vibrations using visual-based displacement measurement methods. Therefore, this paper proposes the object detection model, the Vibration Displacement Detection Network (VDDNet), for measuring vibration displacement of rotating bodies. VDDNet reduces the required computational complexity of the actual detection target and optimizes the quality of vibration displacement measurement. Additionally, by introducing an attention module and adopting different learning strategies to share rotating body target features, the real-time and accuracy of vibration monitoring are ensured. Furthermore, the evaluation method used in this paper comprehensively considers detection accuracy, real-time performance in deep learning methods, and displacement capture accuracy in vibration displacement monitoring. Actual vibration experimental results demonstrate that the proposed method is minimally affected by illumination and can achieve a better real-time capture accuracy of rotor micro-displacements, further proving its effectiveness and feasibility, which is helpful in advancing related research in this field.

Robust Superamphiphobic Coating Applied to Grease-Proof Mining Transformer Components.

The iron core and heat sink in a mining transformer are susceptible to damage from oil spills or the harsh mine environment; the deterioration of oil products in the underground environment and transformers produce massive amounts of harmful liquid substances, which may lead to unnecessary economic losses in drilling engineering. To overcome this issue, a convenient and economical way to protect transformer components was developed. Herein, we proposed an air spray technology at room temperature for the preparation of antigreasy superamphiphobic coatings, which are suitable for bulk metallic glass transformer cores and ST13 heat sinks. The addition of polypyrrole powder effectively improves the thermal conductivity and specific heat of the coating in the range of 50-70 °C. More importantly, the fabricated coating has excellent repellency to liquids, such as water, ethylene glycerol, hexadecane, and rapeseed oil. Meanwhile, the coating has excellent physical and chemical resistance and outstanding antifouling features, which provide a feasible solution for combating grease pollution and corrosion in the mine environment. Taking multifaceted stability into consideration, this work contributes to enhancing the application of superamphiphobic coatings in the fields of protecting transformer components in the harsh environment or during transformer operation faults.

Health indicator construction and application of coal mill based on the dynamic model

As the vital auxiliary machine of the coal-fired power plant, monitoring the real-time operating status of coal mills is critical to the secure and stable operation of the power plant. In this study, a new method of construction of the coal mill health indicator (HI) is proposed, and the operation condition monitoring approaches of the device are designed based on the HI value. Firstly, an improved coal mill dynamic model considering the joint influence of drying force, ventilation force, and grinding force is established, and a synchronous optimization approach of model structures and parameters based on the genetic algorithm is designed. Then the deviation between the model output and the actual value is computed by the designed distance measuring approach, and the typical fault characteristic factors are designed based on the relation between the dynamic model and the actual operating state. And the HI value is calculated by fusing the deviation with the characteristic factors. Finally, the HI value is applied to the process of operation condition evaluation, fault diagnosis, and trend prediction, and has obtained favorable application effects. The results of this research show that the established HI value can reflect the operating status of the coal mill promptly and accurately, and the monitoring method designed based on the values have satisfactory practicality.

Modeling of Symmetrical Six-Phase Induction Machines Under Stator Faults

This paper addresses the occurrence of stator faults in six-phase induction machines, with a symmetrical winding, operating under both balanced and unbalanced supply voltage conditions. A dynamic model of the motor was developed in Matlab/Simulink environment, taking into consideration the occurrence of inter-turn short circuit faults. To validate the proposed approach, simulation results, covering the full range of operation and different fault severity levels, are compared with the motor experimental performance. The voltages and currents obtained from the simulation present a good agreement with the corresponding experimental results, demonstrating the accuracy of the proposed model

Multi-Fault Classification and Diagnosis of Rolling Bearing Based on Improved Convolution Neural Network.

At present, the fault diagnosis methods for rolling bearings are all based on research with fewer fault categories, without considering the problem of multiple faults. In practical applications, the coexistence of multiple operating conditions and faults can lead to an increase in classification difficulty and a decrease in diagnostic accuracy. To solve this problem, a fault diagnosis method based on an improved convolution neural network is proposed. The convolution neural network adopts a simple structure of three-layer convolution. The average pooling layer is used to replace the common maximum pooling layer, and the global average pooling layer is used to replace the full connection layer. The BN layer is used to optimize the model. The collected multi-class signals are used as the input of the model, and the improved convolution neural network is used for fault identification and classification of the input signals. The experimental data of XJTU-SY and Paderborn University show that the method proposed in this paper has a good effect on the multi-classification of bearing faults.

Adaptive additional current-based line differential protection in the presence of converter- interfaced sources with four quadrant operation capability

As typical representatives of converter-interfaced sources with four quadrant operation capability, battery energy storage station (BESS) and VSC-HVDC station behave differently with synchronous generator. This leads to the high risk of incorrect operation of current differential protection (CDP), seriously threatening the security of transmission network. Motivated by this issue, this paper presents adaptive additional current-based differential protection (AAC-DP). Adaptive additional current is introduced to modify the criterion of current differential protection. Ulteriorly, the unified expression of adaptive additional current for internal and external faults is designed. Adaptive additional current can increase the sensitivity during internal fault, whereas it improves the security during external fault. The sensitivity and dependability of AAC-DP was widely evaluated by changing operation mode, fault condition, and type of power source using PSCAD and RTDS-based experimental platform. Also, the adverse factors, such as saturation and error of current transformer(CT), and noise, were taken into account; thereof, the excellent security of AAC-DP was confirmed. The results confirm that AAC-DP exhibits excellent performance in operating speed, sensitivity, the adaptation to fault behaviors of BESS and VSC-HVDC, and robustness against saturation and error of CT, and noise.

Metal Particle Movement and Induced Insulator Flashover Under Impact Vibration Generated By Switching Operation in GIS

Gas insulated switchgear (GIS) insulation failures occur frequently in field operations, seriously affecting the reliability of power systems. Fault statistics show that nearly half of the insulation flashover faults in field operation are strongly related to the switching operation, and metal particles are considered to be a crucial cause of flashover. The impact vibration generated by the switching operation may activate the metal particles and make them lift and jump in the GIS, reducing the insulation performance. Therefore, in this study, an experimental platform was established to simulate the impact vibration generated by the switching operation. The flashover characteristics induced by metal particles under impact vibration were studied, and the movement behavior of metal particles was also analyzed. The results show that metal particles lying on the enclosure lift under the impact vibration and then keep jumping in the GIS. These particles can jump to cause insulator flashover with high probability after the impact vibration. The longer the metal particles, the higher the probability of insulator flashover, and the shorter the average jump duration of the metal particles before the flashover. Moreover, compared with the flake particles, linear particles are more likely to cause insulator flashover after the impact vibration. This study demonstrates the mechanism of insulator flashover caused by metal particles under impact vibration, which provides a significant support for understanding the insulation failures strongly related to the switching operation in practical applications.

Power disturbance waveform analysis and proactive application in power systems

AbstractPower disturbances, defined as the waveform distortion of a power system under normal or abnormal conditions, contain considerable system and equipment state information. Obtaining equipment and system state information from power disturbance is very important to ensure the safety of power grids. To adapt to the development of power electronics, informatisation and digitisation of power systems, several applications with waveform‐recording devices have obtained large amounts of disturbance waveform data, laying an important foundation for the analysis and application of power disturbance waveform data. First, typical disturbance waveform monitoring devices and a disturbance trigger detection algorithm are introduced. Then, disturbances are classified as switching, fault, or abnormal operations, according to the cause. The characteristics of various typical disturbance waveform data were analysed by combining the simulation and measured data. This paper summarises the application analysis of power disturbance waveform data at both the system and equipment levels. Finally, the construction scheme of a power disturbance waveform data monitoring and analysis platform for two different application scenarios was proposed for commutation failure monitoring and medium‐voltage distribution network fault warning. The research conducted here is expected to support the construction of a power disturbance waveform analysis platform.

Integration of charging time, migration pathways and sealing analysis to understand hydrocarbon accumulation in complex fault blocks, the Pinghu Slope Belt of the Xihu Depression, East China Sea Basin

A large number of oil and gas fields have been successfully discovered in complex fault blocks worldwide. However, the role played by the fault-rock seal in the hanging wall traps is not fully understood due to the paucity of datasets. The trap examples of the Pinghu Slope Belt are used to analyze the migration and accumulation of hydrocarbons in the complex fault blocks, as well as the fault-sealing mechanism of the hanging wall traps. The burial history in typical wells, combined with the homogenization temperature of fluid inclusions, is used to determine the hydrocarbon charging time. Based on detailed 3D seismic interpretation, the paleo-structural features at critical moments and their control on hydrocarbon migration were discussed. Hydrocarbon accumulation characteristics were illustrated based on triangle juxtaposition diagrams. The result shows that there are two hydrocarbon charging episodes in the study area, respectively, 10.6–8.1 Ma and 2.8 Ma-present, with the latter being predominant. This phenomenon that the homogenization temperatures of inclusions are generally higher than the measured formation temperatures at the same depth is attributed to late fluid accumulation and not reaching thermal equilibrium with the reservoir fluids. The analysis of hydrocarbon generation history, trap fixation history and fluid inclusions indicate that the critical moment of the generation-migration-accumulation of most hydrocarbons ranges from 2.8 Ma to the present. Due to the difficulty in effectively recognizing the reflector (the top of the Santan Fm) and the nearly horizontal sediments above T20, the reflector T20 (5 Ma) near the top of the Santan Fm was chosen as an approximate proxy for this critical time (2.8 Ma). The paleo-structures of the Pinghu Slope Belt at 5 Ma are a gentle southeast-dipping slope. Based on the numerical simulation of three different fault scenarios (no faults, closed faults and open faults), wells A-H are located on the preferential migration pathways. Fault seal analysis shows that multiple juxtaposition types on the fault surface and moderate-potential to effective SGR values at the sandstone reservoirs in the middle and lower Pinghu Formation. Lateral and vertical reservoir compartmentalizations are presented in clean sand-sand juxtapositions with low-potential sealing (SGR<20%) in well A. The SGR-buoyancy pressure relationship from hanging wall traps and the global calibration plots from footwall traps have a consistent trend. The fault sealing mechanism of hanging wall traps is similar to that of the footwall traps. Therefore， those global calibration plots can be simultaneously applied to the fault seal evaluation of both hanging wall traps and footwall traps.

Proposal of Hybrid Discontinuous PWM Technique for Five-Phase Inverters under Open-Phase Fault Operation

One of the most common issues in inverters are open-circuit faults (OPF). In this scenario, a proper fault-tolerant technique must be used to improve the motor performance. Although basic fault-tolerant modulation techniques are normally preferred, this paper proposes a discontinuous pulse-width modulation algorithm (HD-PWM) to operate five-phase inverters under a single OPF. In particular, loss equalization between the remaining switches after a fault occurs is the main objective of the HD-PWM algorithm, thus preventing future faults from occurring. The efficiency and harmonic distortion of the proposed technique are compared to the well-known sinusoidal PWM by simulation and experimentation under OPF conditions. The results obtained show a great performance of the proposed modulation technique, obtaining a relevant efficiency improvement.

A Sensitivity Study of a Thermal Propagation Model in an Automotive Battery Module

Thermal runaway is a major concern for lithium-ion batteries in electric vehicles. A manufacturing fault or unusual operating conditions may lead to this event. Starting from a single battery cell, more cells may be triggered into thermal runaway, and the battery pack may be destroyed. To prevent this from happening, safety solutions need to be evaluated. Physical testing is an effective, yet costly, method to assessing battery safety performance. As such, the potential of a numerical tool, which can cut costs and reduce product development times, is investigated in terms of capturing a battery module’s tolerance to a single cell failure. A 3D-FE model of a battery module was built, using a commercial software, to study thermal runaway propagation. The model assumes that when the cell jelly roll reaches a critical value, thermal runaway occurs. This approach was considered to study the module’s tolerance to a single cell failure, which was in reasonable agreement with what had been observed in full-scale experiments. In addition, quantitative sensitivity study on the i) model input parameters, ii) model space, and iii) time resolutions on the computed start time instant and time duration of thermal runaway were performed. The critical temperature was found to have the greatest influence on thermal runaway propagation. The specific heat capacity of jelly roll was found to significantly impact the thermal runaway time duration. The multi-physics model for battery thermal propagation is promising and worth to be applied with care for designing safer batteries in combination with physical testing.

COMPASS-U Global Heat Balance Calculations

COMPASS-U is a medium size, high magnetic field experimental tokamak ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R =0.9$ </tex-math></inline-formula> m, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$B_{t} = 5$ </tex-math></inline-formula> T, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$I_{p} = 2$ </tex-math></inline-formula> MA), built at the Institute of Plasma Physics, Czech Academy of Sciences (IPP-CAS). This global heat balance calculation for COMPASS-U was done at Princeton Plasma Physics Laboratory (PPPL). Based on our previous experience of building global thermal model for National Spherical Torus Experiment-Upgrade (NSTX-U) at PPPL, this 2-D global thermal model geometry represents a typical cross section of COMPASS-U machine. The model includes thermal radiation, conduction, and convection among components and also between the machine and outer environment. Helium gas heating/cooling was modeled with fluid element and surface element. This model was used to calculate component temperatures and heat distribution during heat up, cryogenic cool down, normal operation, and fault operation scenarios. Definition of 14 main thermal scenarios was provided by IPP-CAS. First nine are normal operation scenarios. Scenarios #10–#14 are fault scenarios. Some results of thermal scenario #5 will be given and discussed in this article, including peak temperatures, temperature ratcheting, energy distribution, and required cooling power.

Research on Knowledge Graph-based Fault Diagnosis Method for Substation Equipment Operation

The current image processing-based fault diagnosis method for substation equipment operation realizes fault diagnosis by monitoring the thermal status of the equipment, which leads to low diagnostic accuracy due to the lack of analysis of alarm signals. In this regard, the research of substation equipment operation fault diagnosis method based on knowledge mapping is proposed. A fault diagnosis model is established by building a behavior map of substation accident-like alarm signals, analyzing the alarm behavior as well as the causes of faults, and predicting the posterior probability of faults. In the experiment, the diagnosis accuracy of the proposed method is verified. The analysis of the experimental results shows that the fault diagnosis model constructed by the proposed method has good diagnostic performance and high diagnostic accuracy.