An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.

Data-driven short circuit resistance estimation in battery safety issues

Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries(LIBs).In this paper,we developed a Convolutional Neural Networks(CNN)based model that can quickly and precisely predict the short circuit resistance of LIB cells during various working conditions.Cycling tests of cells with an external short circuit(ESC)are produced to obtain the database and generate the training/testing samples.The samples are sequences of voltage,current,charging capacity,charging energy,total charging capacity,total charging energy with a length of 120 s and frequency of 1 Hz,and their corresponding short circuit resistances.A big database with~6×10^(5)samples are generated,covering various short circuit resistances(47~470Ω),current loading modes(Constant current-constant voltage(CC-CV)and drive cycle),and electrochemical states(cycle numbers from 1 to 300).Results show that the average relative absolute error of five random sample splits is 6.75%±2.8%.Further parametric analysis indicates the accuracy estimation benefits from the appropriate model setups:the optimized input sequence length(~120 s),feature selection(at least one total capacity-related variable),and rational model design,using multiple layers with different kernel sizes.This work highlights the capabilities of machine learning algorithms and data-driven methodologies in real-time safety risk prediction for batteries.

A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.

Low-field, high-gradient NMR shows diffusion contrast consistent with localization or motional averaging of water near surfaces

Nuclear magnetic resonance(NMR)measurements of water diffusion have been extensively used to probe microstructure in porous materials,such as biological tissue,however primarily using pulsed gradient spin echo(PGSE)methods.Low-field single-sided NMR systems have built-in static gradients(SG)much stronger than typical PGSE maximum gradient strengths,which allows for the signal attenuation at extremely high b-values to be explored.Here,we perform SG spin echo(SGSE)and SG stimulated echo(SGSTE)diffusion measurements on biological cells,tissues,and gels.Measurements on fixed and live neonatal mouse spinal cord,lobster ventral nerve cord,and starved yeast cells all show multiexponential signal attenuation on a scale of b with significant signal fractions observed at b×Do>1 with b as high as 400 ms/um2.These persistent signal fractions trend with surface-to-volume ratios for these systems,as expected from porous media theory.An exception found for the case of fixed vs.live spinal cords was attributed to faster exchange or permeability in live spinal cords than in fixed spinal cords on the millisecond timescale.Data suggests the existence of multiple exchange processes in neural tissue,which may be relevant to the modeling of time-dependent diffusion in gray matter.The observed multi-exponential attenuation is from protons on water and not macromolecules because it remains proportional to the normalized signal when a specimen is washed with D20.The signal that persists to b×Do>1 is also drastically reduced after delipidation,indicating that it originates from lipid membranes that restrict water diffusion.The multiexponential or stretched exponential character of the signal attenuation at b×Do>1 appears mono-exponential when viewed on a scale of(b×Do)/3,suggesting it may originate from localization or motional averaging of water near membranes on sub-micron length scales.To try to disambiguate these two contributions,signal attenuation curves were compared at varying temperatures.While the curves align when normalizing them using the localization length scale,they separate on a motional averaging length scale.This supports localization as the source of non-Gaussian displacements,but this interpretation is still provisional due to the possible confounds of heterogeneity,exchange,and relaxation.Measurements on two types of gel phantoms designed to mimic extracellular matrix.one with charged functional groups synthesized from polyacrylic acid(PAC)and another with uncharged functional groups synthesized from polyacrylamide(PAM),both exhibit signal at b×Do>1,potentially due to water interacting with macromolecules.These preliminary finding motivate future research into contrast and attenuation mechanisms in tissue with low-field,high-gradient NMR。

Imaging changes in neural circuits in patients with depression using 1 H-magnetic resonance spectroscopy and diffusion tensor imaging

1 H-magnetic resonance spectroscopy imaging and diffusion tensor imaging were performed in 19 patients with mild depression and in 13 controls.The mean age of the patients was 31 years.The mean Hamilton depression score of the patients was 22.5±13.2.N-acetylaspartate,choline and creatine concentrations and the average diffusion coefficient and fractional anisotropy values were measured in the bilateral hippocampus,striatum,thalamus and prefrontal deep white matter. Compared with the control group,the mild depressed patients had：（1）a higher choline/creatine ratio and a negative correlation between the choline/creatine ratio and the average diffusion coefficient in the hippocampus;（2）a lower choline/creatine ratio and a higher fractional anisotropy in the striatum;（3）a lower fractional anisotropy and a positive correlation between the fractional anisotropy and the choline/creatine ratio in the prefrontal deep white matter;and（4）a higher average diffusion coefficient and a positive correlation between the choline/creatine ratio and the N-acetylaspartate/creatine ratio in the thalamus,as well as positive correlation between the choline/creatine ratio and Hamilton depression scores.These data suggest evidence of abnormal connectivity in neurofibrotic microstructures and abnormal metabolic alterations in the limbic-cortical-striatal-pallidal-thalamic neural circuit in patients with mild depression.

Low switching loss and increased short-circuit capability split-gate SiC trench MOSFET with p-type pillar

A split-gate SiC trench gate MOSFET with stepped thick oxide, source-connected split-gate(SG), and p-type pillar(ppillar) surrounded thick oxide shielding region(GSDP-TMOS) is investigated by Silvaco TCAD simulations. The sourceconnected SG region and p-pillar shielding region are introduced to form an effective two-level shielding, which reduces the specific gate–drain charge(Q_(gd,sp)) and the saturation current, thus reducing the switching loss and increasing the short-circuit capability. The thick oxide that surrounds a p-pillar shielding region efficiently protects gate oxide from being damaged by peaked electric field, thereby increasing the breakdown voltage(BV). Additionally, because of the high concentration in the n-type drift region, the electrons diffuse rapidly and the specific on-resistance(Ron,sp) becomes smaller.In the end, comparing with the bottom p~+ shielded trench MOSFET(GP-TMOS), the Baliga figure of merit(BFOM,BV~2/R_(on,sp)) is increased by 169.6%, and the high-frequency figure of merit(HF-FOM, R_(on,sp) × Q_(gd,sp)) is improved by310%, respectively.

Association between scrub typhus encephalitis and diffusion tensor tractography detection of Papez circuit injury:A case report

BACKGROUND It is difficult to restore the cognitive functions of patients with impaired cognition caused by brain injury.Diffusion tensor imaging can visualize the integrity of neural tracts in the white matter(WM)three-dimensionally.It is unclear whether encephalitis following scrub typhus damages the WM.For the first time,we aimed to report diffusion tensor tractography(DTT)findings in a chronic patient with cognitive impairment following scrub typhus encephalitis,which revealed injury to the Papez circuit of the WM.CASE SUMMARY A 70-year-old male patient was affected by encephalitis caused by scrub typhus that occurred 23 years ago.He had poor cognition and his clinical examination findings were as follows:Mini-Mental Status Examination score,14;and handgrip strength(right/left,kg),32.3/31.3.DTT revealed serious injuries of the left thalamocingulate tract and right mammillothalamic tract in the Papez circuit,and a partial injury of the anterior part of the fornix.CONCLUSION Using DTT,we found a relationship between cognitive impairment and the integrity of the Papez circuit following scrub typhus.

The Transformer Short-Circuit Test and the High Power Laboratory in China-the Past,Present,and Future

We review the short-circuit testing of distribution and power transformers, and include a list of 110-220kV power transformers tested up to February 2002.

APPLICATION OF WHOLE BODY DIFFUSION WEIGHTED MR IMAGING FOR DIAGNOSIS AND STAGING OF MALIGNANT LYMPHOMA

Objective To evaluate the clinical impact of whole body diffusion weighted imaging （WB-DWI） on diagnosis and staging of malignant lymphoma. Methods Thirty-one patients with suspected lymphadenopathy were enrolled. WB-DWI was performed by using short TI inversion recovery echo-planar imaging sequence with free breathing and built-in body coil. Axial T2- weighted imaging images of the same location were used as reference. The results of WB-DWI were compared with pathological results and other imaging modalities. The mean apparent diffusion coefficient （ADC） values of different kinds of lymph nodes were compared. Results WB-DWI was positive in all 18 cases with lymphoma, 5 cases with metastatic lymph nodes and 4 of 8 eases with benign lymphadenopathy. The mean ADC value of lymphomatous, metastatic and benign lymph nodes was （0.87 ± 0.17） × 10^3, （0.98± 0.09） × 10^3 and （1.20 ± 0.10） × 10^3 mm^2/s. There was significant difference in ADC value between benign lymph nodes and other two groups （P 〈 0.01）. The sensitivity, specificity and accuracy of WB-DWI in diagnosis of lymphoma were 100% （18/18）, 30.8% （4/13） and 71.0% （22/31）. When an ADC value of 1.08 × 10^-3 mm^2/s was used as the threshold value for differentiating malignant from benign lymph nodes, the best results were obtained with sensitivity of 87.8% and specificity of 91.3%. Sixteen of eighteen cases （88.9%） of lymphoma were accurately staged in accordance with clinical staging. Conclusions WB-DWI is a sensitive, but less specific technique for diagnosis of lymphoma. It is difficult to differentiate lymphnmatous from metastatic lymph nodes using WB-DWI. However, it is a valuable imaging modality for staging of patients with malignant lymphoma.

Extreme Learning Machine-Based Thermal Model for Lithium-Ion Batteries of Electric Vehicles under External Short Circuit

External short circuit(ESC)of lithium-ion batteries is one of the common and severe electrical failures in electric vehicles.In this study,a novel thermal modelis developed to capture the temperature behavior of batteries under ESC conditions.Experiments were systematically performed under different battery initial state of charge and ambient temperatures.Based on the experimental results,we employed an extreme learming machine(ELM)-based thermal(ELMT)model to depict battery temperature behavior under ESC,where a lumped-state thermal model was used to replace the activation function of conventional ELMs.To demonstrate the effectiveness of the proposed model,wecompared the ELMT model with a multi-lumped-state thermal(MLT)model parameterized by thegenetic algorithm using the experimental data from various sets of battery cells.It is shown that the ELMT model can achieve higher computa-tional efficiency than the MLT model and better fitting and prediction accuracy,where the average root mean squared error(RMSE)of the fitting is 0.65℃ for the ELMT model and 3.95℃ for the MLT model,and the RMES of the prediction under new data set is 3.97℃ for the ELMT model and 6.11℃ for the MLT model.

Effects of current waveform parameters during droplet transfer on spatter in high speed waveform controlled Short-circuiting GMAW

Aim at improving the stability of the Short-circuiting Gas Metal Arc Welding （GMAW-S） process for the enhanced speed usage, effects of current waveform parameters during short-term on the welding stability have been investigated by experimental method. The welding power source used for the research is an inverter with a special current waveform control. It is shown that the spatter decreases at first then increases with each increase of the low current period, current increase rate and the maximum current limit. The test results are provided for welding of 1 mm and 3 mm mild steel at speed of 1.2 m/min. The stable GMA W-S process under high speed welding condition has been achieved by optimizing the parameters.

Internal short circuit evaluation and corresponding failure mode analysis for lithium-ion batteries

Internal short circuit(ISC)is the major failure problem for the safe application of lithium-ion batteries,especially for the batteries with high energy density.However,how to quantify the hazard aroused by the ISC,and what kinds of ISC will lead to thermal runaway are still unclear.This paper investigates the thermal-electrical coupled behaviors of ISC,using batteries with Li(Ni_(1/3)CO_(1/3)Mn_(1/3))O_(2) cathode and composite separator.The electrochemical impedance spectroscopy of customized battery that has no LiPF6 salt is utilized to standardize the resistance of ISC.Furthermore,this paper compares the thermal-electrical coupled behaviors of the above four types of ISC at different states-of-charge.There is an area expansion phenomenon for the aluminum-anode type of ISC.The expansion effect of the failure area directly links to the melting and collapse of separator,and plays an important role in further evolution of thermal runaway.This work provides guidance to the development of the ISC models,detection algorithms,and correlated countermeasures.

DETECTION AND ANALYSIS OF WELD POOL SHAPE FOR CO_2 SHORT CIRCUITING ARC WELDING

A general industrial CCD( ICCD) camera is redesigned to detect the weld pool without arc at the period of short circuiting, so that the interference of arc and spatter during CO2 short circuiting arc welding is eliminated. Through the analysis of weld pool image, both size parameters (such as weld pool area A, weld pool length L1, L2 and weld pool breadth b) and contour parameters (b, which describe the curves of weld pool boundany) ,which could indicate the shape features of weld pool, had been defined to express weld pool information quantitatively. The investigation of the relationships between weld pool shape parameters and welding process parameters may be beneficial to the quality control of CO2 welding.

A fault warning for inter-turn short circuit of excitation winding of synchronous generator based on GRU-CNN

Synchronous generators are important components of power systems and are necessary to maintain its normal and stable operation.To perform the fault diagnosis of mild inter-turn short circuit in the excitation winding of a synchronous generator,a gate recurrent unit-convolutional neural network(GRU-CNN)model whose structural parameters were determined by improved particle swarm optimization(IPSO)is proposed.The outputs of the model are the excitation current and reactive power.The total offset distance,which is the fusion of the offset distance of the excitation current and offset distance of the reactive power,was selected as the fault judgment criterion.The fusion weights of the excitation current and reactive power were determined using the anti-entropy weighting method.The fault-warning threshold and fault-warning ratio were set according to the normal total offset distance,and the fault warning time was set according to the actual situation.The fault-warning time and fault-warning ratio were used to avoid misdiagnosis.The proposed method was verified experimentally.

Study on chaos in short circuit gas metal arc welding process

Based on the chaos theory, an idea is put forward to analyze the short circuit Gas Metal Arc Welding （ GMAW-S） process. The theory of phase space reconstruction and related algorithms such as mutual information and so on, are applied to analyze the chaos of the GMAW-S process. The largest Lyapunov exponents of some current time series are calculated, and the results indicate that chaos exists in the GMAW-S process. The research of the chaos in the GMAW-S process can be help to get new knowledge of the process.

Influence of optical interference and carrier lifetime on the short circuit current density of organic bulk heterojunction solar cells

Based on simple analytical equations, short circuit current density （Jsc） of the organic bulk heterojunction solar cells has been calculated. It is found that the optical interference effect plays a very important role in the determination of Jsc; and obvious oscillatory behaviour of Jsc was observed as a function of thickness. At the same time, the influence of the carrier lifetime on Jsc also cannot be neglected. When the carrier lifetime is relatively short, Jsc only increases at the initial stage and then decreases rapidly with the increase of active layer thickness. However, for a relatively long carrier lifetime, the exciton dissociation probability must be considered, and Jsc behaves wave-like with the increase of active layer thickness. The validity of this model is confirmed by the experimental results.

Investigation on microprocessor based waveform control of short circuit transfer CO_2 welding

A new kind of simple and flexible CO2 welding system was developed to carry out waveform control. The system consisted of IGBT inverter, PWM circuit and microprocessor unit （ MPU） , in which the output current of constant current （CC） power supply could be changed according to transient physical state, and the variable down slope rate control could be used to ensure a stable welding process. The welding experiment results proved the effectiveness of this control approach.

Determining the feature values of parameters indicating the critical states of molten metal bridge in short circuit transfer

Short circuit transfer involves bridging between the consumable electrode and the weld pool, associated with variations of electrical parameters which characterize the change of molten metal bridge state and are very important for the control of .spatter. In this paper, electrical process parameters and short circuit transfer images were simultaneously recorded with a LabView-based synchronous sensing and visualizing system. The arc^bridge resistance and derivatives of welding current, arc voltage and arc resistance at various instants were calculated by means of offline analysis of the welding current, arc voltage and droplet images. Parameters and their feature values indicating the onset of short circuit and the oncoming necking-down of molten metal bridge were determined. Using the calculated feature values, bridge-state-feedback control for .short circuit transfer was realized with a spatter rate less than 0. 25%.

A New Method of Early Short Circuit Detection

To reduce the pressure on contacts and circuit breaker and realize the zone selective interlocking (ZSI) function above the instantaneous protection threshold (e.g., >10In), the short circuit current needs to be early detected. The state-of–art of early short circuit detection (ESCD) method is reviewed. Based on the equivalent model of the short circuit, a new method based on the current and its integration is proposed. The prospective current value can be detected in the early stage of the short circuit. According to the evaluation result, the short circuit current can be early forecasted with the proposed method.

Effect of welding speed and electrode extension on the approximate entropy of welding current in short-circuiting GMAW

Based on the phase space reconstruction of welding current in short-circuiting transfer arc welding under carbon dioxide, the approximate entropy of welding current and its standard deviation have been calculated and analyzed at different welding speeds and different electrode extensions respectively. The experimental and calculated results show that at a certain arc voltage, wire feeding rate and gas flow rate, welding speed and electrode extension have significant effects not only on the approximate entropy of welding current, but also on the stability of welding process. Further analysis proves that when the welding speed and electrode extension are in an appropriate range respectively, the welding current approximate entropy attains maximum and its standard deviation minimum. Just under such circumstances, the welding process is in the most stable state.