Three-phase grid-connected inverters(GCIs)are essential components in distributed generation systems,where the accuracy of current measurement circuits is fundamental for reliable closed-loop operation.Nevertheless,th...Three-phase grid-connected inverters(GCIs)are essential components in distributed generation systems,where the accuracy of current measurement circuits is fundamental for reliable closed-loop operation.Nevertheless,the presence of a DC offset in the measured current can disrupt the regulation of grid currents and significantly degrade system performance.In this work,a fault-tolerant control approach is introduced to counteract the impact of such offset faults through a dedicated current compensation mechanism.The proposed solution is built around two main stages:(i)detecting and isolating DC offset faults that may appear in one or multiple phases of the measured grid currents,and(ii)estimating the fault magnitude and reconstructing the corrected current signal.The offset magnitude is obtained analytically by examining the grid current projected onto the synchronous d-axis at the grid angular frequency,eliminating the need for any additional sensing hardware.Simulation and experimental investigations conducted under several fault scenarios confirm the robustness of the proposed strategy and highlight significant improvements in detection speed and diagnostic accuracy.展开更多
To apply the advantages of deep learning in recognizing two-dimensional(2D)images to three-phase inverter fault diagnosis,a threephase inverter fault diagnosis model based on gramian angular field(GAF)combined with co...To apply the advantages of deep learning in recognizing two-dimensional(2D)images to three-phase inverter fault diagnosis,a threephase inverter fault diagnosis model based on gramian angular field(GAF)combined with convolutional neural network(CNN)was proposed.Since the current signals of the inverter in different working states are different,the images formed by the time series encoding are also different,which enables the image recognition technology to be used for time series classification to identify the fault current signal of the inverter.Firstly,the one-dimensional(1D)inverter fault current signal was converted into a 2D image through the GAF.Next,the CNN model suitable for inverter fault diagnosis was input to realize the detection,classification and location of inverter fault.The simulation results show that the recognition accuracy of this method is 99.36%under different noisy data.Compared with other traditional methods,it has higher accuracy and reliability,and stronger anti-noise interference capability and robustness in dealing with noisy data.Therefore,it is an effective fault diagnosis method for inverters.展开更多
Half-wavelength AC transmission(HWACT) is an ultra-long distance AC transmission technology, whose electrical distance is close to half-wavelength at the system power frequency. It is very important for the constructi...Half-wavelength AC transmission(HWACT) is an ultra-long distance AC transmission technology, whose electrical distance is close to half-wavelength at the system power frequency. It is very important for the construction and operation of HWACT to analyze its fault features and corresponding protection technology. In this paper, the steady-state voltage and current characteristics of the bus bar and fault point and the steady-state overvoltage distribution along the line will be analyzed when a three-phase symmetrical short-circuit fault occurs on an HWACT line. On this basis, the threephase fault characteristics for longer transmission lines are also studied.展开更多
The paper presents an accurate analytical subdomain model for predicting the electromagnetic performance in the symmetrical dual three-phase surface-mounted permanent magnet synchronous machine(PMSM)under open-phase f...The paper presents an accurate analytical subdomain model for predicting the electromagnetic performance in the symmetrical dual three-phase surface-mounted permanent magnet synchronous machine(PMSM)under open-phase faulty conditions.The model derivations are extended from previous accurate subdomain models accounting for slotting effects.Compared with most conventional subdomain models for traditional three-phase machines with nonoverlapping winding arrangement,the subdomain model proposed in this paper applied for the 24-slot/4-pole dual three-phase machine with symmetrical overlapping winding arrangement.In order to investigate the postfault electromagnetic performance,the reconfigured phase currents and then current density distribution in stator slots under different open-circuit conditions are discussed.According to the developed model and postfault current density distribution,the steady-state electromagnetic performance,such as the electromagnetic torque and unbalanced magnetic force,under open-circuit faulty conditions are obtained.For validation purposes,finite element analysis(FEA)is employed to validate the analytical results.The result indicate that the postfault electromagnet performance can be accurately predicted by the proposed subdomain model,which is in good agreement with FEA results.展开更多
To achieve high power rating and low current harmonics of motor drive,this paper develops a dual three-phase open-winding permanent magnet synchronous motor(DTP-OW-PMSM)drive with the DC-link voltage ratio of 2:1:1.Ba...To achieve high power rating and low current harmonics of motor drive,this paper develops a dual three-phase open-winding permanent magnet synchronous motor(DTP-OW-PMSM)drive with the DC-link voltage ratio of 2:1:1.Based on this topology,this paper proposes a DTP four-level space vector pulse width modulation(DTP-FL SVPWM)strategy.First,two identical three-phase four-level space vector diagrams are constructed and divided.Then,three adjacent vectors nearest to the reference vector in each diagram are selected for the vector synthesis to guarantee high modulation precision and low switching frequency.Furthermore,to avoid the modulation error caused by the voltage deviation,the proposed DTP-FL SVPWM strategy is further optimized through unified duty ratio compensation(UDRC).The effectiveness of the proposed strategy is verified through experiments.展开更多
The growing demand for efficient high-power switching power supplies has spurred interest in advanced topologies.The three-phase VIENNA converter stands out for its high power factor,simplified structure,and robust pe...The growing demand for efficient high-power switching power supplies has spurred interest in advanced topologies.The three-phase VIENNA converter stands out for its high power factor,simplified structure,and robust performance.Current research focuses on its operational principles,control strategies,and behavior under various load conditions.Key considerations include component selection,thermal management,and EMI/EMC optimization.This topology finds applications across renewable energy systems,industrial equipment,telecommunications,and electric vehicle charging infrastructures.Comparative analyses with alternative topologies and cost-benefit evaluations are also addressed.Future developments are expected to emphasize the integration of wide-bandgap devices and advancements in digital control techniques to further enhance efficiency and system performance.展开更多
The dual three-phase PMSM(DTP-PMSM)drives have received wide attention at high-power high-efficiency applications due to their merits of high output current ability and copper-loss-free field excitation.Meanwhile,the ...The dual three-phase PMSM(DTP-PMSM)drives have received wide attention at high-power high-efficiency applications due to their merits of high output current ability and copper-loss-free field excitation.Meanwhile,the DTPPMSM drive provides higher fault-tolerant capability for highreliability applications,e.g.,pumps and actuators in aircraft.For high-power drives with limited switching frequencies and highspeed drives with large fundamental frequencies,the ratio of switching frequency to fundamental frequency,i.e.,the carrier ratio,is usually below 15,which would significantly degrade the control performance.The purpose of this paper is to review the recent work on the modulation and control schemes for improving the operation performance of DTP-PMSM drives with low carrier ratios.Specifically,three categories of methods,i.e.,the space vector modulation based control,the model predictive control(MPC),and the optimized pulse pattern(OPP)based control are reviewed with principles and performance.In addition,brief discussions regarding the comparison and future trends are presented for low-carrier-ratio(LCR)modulation and control schemes of DTP-PMSM drives.展开更多
Polygonal fault systems(PFS),characterized by multi-directional fault patterns within layered sequences,are well-documented features in global continental margin basins.While the geometry and formation mechanisms of P...Polygonal fault systems(PFS),characterized by multi-directional fault patterns within layered sequences,are well-documented features in global continental margin basins.While the geometry and formation mechanisms of PFS have been extensively studied in the northern South China Sea,the PFS in the Zhongjiannan Basin(western South China Sea)remain relatively unexplored,with a lack of quantitative analysis regarding their propagation.This study addresses this gap by using high-resolution three-dimensional(3D)seismic data and conducting a quantitative fault analysis to thoroughly examine the planform,cross-sectional geometry,and evolution of PFS in the northern Zhongjiannan Basin.The absence of a dominant strike direction among these polygonal faults suggests that their evolution is not controlled by anisotropic stress.Our interpretation of seismic data,constrained by the spatial relationship among PFS,gullies,and pockmarks,indicates that PFS mainly developed within the Miocene strata,with their initiation occurring during the late Miocene.Furthermore,the PFS act as key conduits connecting gullies to pockmarks in this area.The formation and development of PFS may be primarily driven by thermally triggered processes within siliceous sediments.The necessary heat source is probably associated with the abundant submarine magmatism observed in the Zhongjiannan Basin.To reconstruct the regional geological history,a four-stage evolutionary model,incorporating the formation of PFS,is presented.This research significantly improves our understanding of the regional geological evolution of the Zhongjiannan Basin,providing critical insights into the initiation and development of PFS in the western South China Sea.展开更多
The Guanxian-Anxian fault zone in the Longmen Shan,Sichuan,China,exhibits long-term creep-slip but ruptured during the 2008 Wenchuan earthquake,challenging the view that creeping faults rarely generate strong earthqua...The Guanxian-Anxian fault zone in the Longmen Shan,Sichuan,China,exhibits long-term creep-slip but ruptured during the 2008 Wenchuan earthquake,challenging the view that creeping faults rarely generate strong earthquakes.To investigate the transition from creep-slip to stick-slip,we analyzed fault rocks from the WFSD-3,using microstructural observations,XRD,μXRF,Raman spectroscopy,and quartz grain size statistics.Fault rocks show intense foliation,pressure-solution structures,and abundant clay minerals,reflecting long-term aseismic creep.At the interface between black and gray fault gouges at~1249.98 m,microstructures indicate stick-slip behavior,including truncated grains,angular fragments,and finer grain sizes.Here,clay content drops sharply while strong minerals(quartz,feldspar,calcite,dolomite)increase.Elemental mapping shows Al and K enriched in black gouge,whereas Ca and Si in gray gouge;Raman spectroscopy indicates possible graphitization;the finest quartz grains occur in black gouge.These features mark co-seismic principal slip zone of the Wenchuan earthquake.We propose that fluid-driven transformation of strong minerals into clays facilitates creep-slip,whereas localized precipitation of strong minerals strengthens the fault,causing stress accumulation and controlling the creep-slip to stick-slip transition.This mechanism has implications for reassessing seismic hazards of creeping faults.展开更多
With the rapid development of large-scale offshore wind farms,efficient and reliable power transmission systems are urgently needed.Hybrid high-voltage direct current(HVDC)configurations combining a diode rectifier un...With the rapid development of large-scale offshore wind farms,efficient and reliable power transmission systems are urgently needed.Hybrid high-voltage direct current(HVDC)configurations combining a diode rectifier unit(DRU)and a modular multilevel converter(MMC)have emerged as a promising solution,offering advantages in cost-effectiveness and control capability.However,the uncontrollable nature of the DRU poses significant challenges for systemstability under offshore AC fault conditions,particularly due to its inability to provide fault current or voltage support.This paper investigates the offshore AC fault characteristics and fault ride-through(FRT)strategy of a hybrid offshore wind power transmission system based on a diode rectifier unit DRU and MMC.First,the dynamic response of the hybrid system under offshore symmetrical three-phase faults is analyzed.It is demonstrated that due to the unidirectional conduction nature of the DRU,its AC current rapidly drops to zero during faults,and the fault current is solely contributed by the wind turbine generators(WTGs)and wind farm MMC(WFMMC).Based on this analysis,a coordinated FRT strategy is proposed,which combines a segmented current limiting control for the wind-turbine(WT)grid-side converters(GSCs)and a constant AC current control for the WFMMC.The strategy ensures effective voltage support during the fault and prevents MMC current saturation during fault recovery,enabling fast and stable system restoration.Electromagnetic transient simulations in PSCAD/EMTDC verify the feasibility of the proposed fault ride-through strategy.展开更多
The Yingxiu-Beichuan fault zone(YBFZ)has long been active and experienced repeated large earthquakes.The physicochemical properties of the deep fault zone(>1000 m)are the key to understanding the deformation mechan...The Yingxiu-Beichuan fault zone(YBFZ)has long been active and experienced repeated large earthquakes.The physicochemical properties of the deep fault zone(>1000 m)are the key to understanding the deformation mechanism of large earthquakes.This study uses rock magnetic,microstructural,and geochemical analyses of representative samples exposed in FZ1681 within the Wenchuan Earthquake Fault Scientific Drilling borehole 2(WFSD-2)cores.Fault gouge and fault breccia have higher magnetic susceptibility values than wall rocks,and they contain abundant paramagnetic minerals and small quantities of magnetite and monoclinic pyrrhotite.The magnetite and monoclinic pyrrhotite in the fault gouge were mainly formed by coseismic frictional heating,indicating that large earthquakes with frictional heating temperatures of~500-900℃once occurred in the YBFZ.The seismogenic and coseismic environment was reducing with a relatively high sulfur content.The monoclinic pyrrhotite in the fault breccia was formed mainly by low-temperature hydrothermal fluid.This indicates that the fault zone experienced reducing and low-temperature(<400℃)hydrothermal fluid with a relatively high sulfur content after the earthquake.The YBFZ,which experiences frequent large earthquakes,is weakly oxidizing environment at different depths,but the effect of the low-temperature hydrothermal fluid is weaker at depth.展开更多
Grid-Forming(GFM)converters are prone to fault-induced overcurrent and power angle instability during grid fault-induced voltage sags.To address this,this paper develops a multi-loop coordinated fault ridethrough(FRT)...Grid-Forming(GFM)converters are prone to fault-induced overcurrent and power angle instability during grid fault-induced voltage sags.To address this,this paper develops a multi-loop coordinated fault ridethrough(FRT)control strategy based on a power outer loop and voltage-current inner loops,aiming to enhance the stability and current-limiting capability of GFM converters during grid fault conditions.During voltage sags,the GFM converter’s voltage source behavior is maintained by dynamically adjusting the reactive power reference to provide voltage support,thereby effectively suppressing the steady-state component of the fault current.To address the active power imbalance induced by voltage sags,a dynamic active power reference correction method based on apparent power is designed to mitigate power angle oscillations and limit transient current.Moreover,an adaptive virtual impedance loop is implemented to enhance dynamic transient current-limiting performance during the fault initiation phase.This approach improves the responsiveness of the inner loop and ensures safe system operation under various fault severities.Under asymmetric fault conditions,a negative-sequence reactive current compensation strategy is incorporated to further suppress negative-sequence voltage and improve voltage symmetry.The proposed control scheme enables coordinated operation of multiple control objectives,including voltage support,current suppression,and power angle stability,across different fault scenarios.Finally,MATLAB/Simulink simulation results validate the effectiveness of the proposed strategy,showcasing its superior performance in current limiting and power angle stability,thereby significantly enhancing the system’s fault ride-through capability.展开更多
This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of ...The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of issues,including mechanical faults,air path malfunctions,and combustion irregularities.Traditional modelbased approaches face inherent limitations due to their inability to handle nonlinear problems,natural factors,measurement uncertainties,fault coupling,and implementation challenges.The development of artificial intelligence algorithms has provided an effective solution to these issues,sparking extensive research into data-driven fault diagnosis methodologies.The review mechanism involved searching IEEE Xplore,ScienceDirect,and Web of Science for peerreviewed articles published between 2019 and 2025,focusing on multi-fault diagnosis techniques.A total of 220 papers were identified,with 123 meeting the inclusion criteria.This paper provides a comprehensive review of diagnostic methodologies,detailing their operational principles and distinctive features.It analyzes current research hotspots and challenges while forecasting future trends.The study systematically evaluates the strengths and limitations of various fault diagnosis techniques,revealing their practical applicability and constraints through comparative analysis.Furthermore,this paper looks forward to the future development direction of this field and provides a valuable reference for the optimization and development of gas turbine fault diagnosis technology in the future.展开更多
A．Switch-Redundant Topology An early attempt to add fault tolerant capacity to a standard three-phase inverter topology for induction motors was presented．This topology will be referred to as the switch-redundant t...A．Switch-Redundant Topology An early attempt to add fault tolerant capacity to a standard three-phase inverter topology for induction motors was presented．This topology will be referred to as the switch-redundant topology and is shown in Fig.5．This topology incorporates four TRIACs or back-to-back connected SCRs and three fast acting fuses．The fuses are connected in series with the load phases．Since this topology is a combination of topologies and control methods to accommodate an opened phase，and a shorted switch，they will be considered separately．展开更多
Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction.However,several challenges remain.First,signal noise collected during blade operati...Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction.However,several challenges remain.First,signal noise collected during blade operation masks fault features,severely impairing the fault diagnosis performance of deep learning models.Second,current blade fault diagnosis often relies on single-sensor data,resulting in limited monitoring dimensions and ability to comprehensively capture complex fault states.To address these issues,a multi-sensor fusion-based wind turbine blade fault diagnosis method is proposed.Specifically,a CNN-Transformer Coupled Feature Learning Architecture is constructed to enhance the ability to learn complex features under noisy conditions,while a Weight-Aligned Data Fusion Module is designed to comprehensively and effectively utilize multi-sensor fault information.Experimental results of wind turbine blade fault diagnosis under different noise interferences show that higher accuracy is achieved by the proposed method compared to models with single-source data input,enabling comprehensive and effective fault diagnosis.展开更多
To ensure the safe and stable operation of rotating machinery,intelligent fault diagnosis methods hold significant research value.However,existing diagnostic approaches largely rely on manual feature extraction and ex...To ensure the safe and stable operation of rotating machinery,intelligent fault diagnosis methods hold significant research value.However,existing diagnostic approaches largely rely on manual feature extraction and expert experience,which limits their adaptability under variable operating conditions and strong noise environments,severely affecting the generalization capability of diagnostic models.To address this issue,this study proposes a multimodal fusion fault diagnosis framework based on Mel-spectrograms and automated machine learning(AutoML).The framework first extracts fault-sensitive Mel time–frequency features from acoustic signals and fuses them with statistical features of vibration signals to construct complementary fault representations.On this basis,automated machine learning techniques are introduced to enable end-to-end diagnostic workflow construction and optimal model configuration acquisition.Finally,diagnostic decisions are achieved by automatically integrating the predictions of multiple high-performance base models.Experimental results on a centrifugal pump vibration and acoustic dataset demonstrate that the proposed framework achieves high diagnostic accuracy under noise-free conditions and maintains strong robustness under noisy interference,validating its efficiency,scalability,and practical value for rotating machinery fault diagnosis.展开更多
This study examines a 1.32 m thick sediment sequence from the Cunge sag pond in the Litang Basin,eastern Tibetan Plateau,to assess the seismicity of the Litang fault during the Holocene.High-resolution geochemical,gra...This study examines a 1.32 m thick sediment sequence from the Cunge sag pond in the Litang Basin,eastern Tibetan Plateau,to assess the seismicity of the Litang fault during the Holocene.High-resolution geochemical,grain size,magnetic susceptibility,and total organic carbon indicators are employed to obtain a continuous record of changes in elemental,physical,and biological properties within the profile to identify seismic events.The seismic event layer generally comprises two sedimentary rhythms:a lower coarse sand layer and an upper fine silt-clay layer.These layers represent rapid deposition associated with fault activity(Earthquake A)and slower deposition during calm periods or earthquake recurrence intervals(Seismic interval A).Through six^(14)C dating,five seismic events have been identified in the Cunge sag pond section:E1(before 3955 a B.P.),E2(3713-3703 a B.P.),E3(3492-3392 a B.P.),E4(2031-1894 a B.P.),and E5(1384-1321 a B.P.).E1-E4 had shown a good consistency with the paleo-earthquake recorded by the trench,and whereas E5 is a newly identified seismic event,further improving the continuous earthquake sequence of the Litang fault.Based on existing trench data and the seismic event record from the Cunge sag pond,a total of 11 paleo-earthquakes are identified along the Litang fault since the Holocene.The paleo-earthquake activity of the Litang fault exhibits a clustered pattern,with recurrence intervals of both long periods(1000 a)and short periods(500 a).Since 5000 a,the interval between strong earthquake recurrences gradually decreases,indicating an increasing risk of strong earthquakes along the Litang fault.This study presents a continuous record of paleo-earthquakes along the Litang fault,eastern Tibetan Plateau,and can enhance the understanding of regional seismic activity.展开更多
The Almus Fault Zone(AFZ)is one of the major splay faults of the North Anatolian Fault Zone(NAFZ)and is important for understanding its tectonic features and assessing regional seismic hazards.This research presents t...The Almus Fault Zone(AFZ)is one of the major splay faults of the North Anatolian Fault Zone(NAFZ)and is important for understanding its tectonic features and assessing regional seismic hazards.This research presents the integration of morphometric indices to quantitatively assess the spatial variation of tectonic activity along the AFZ.The AFZ is an active fault with both strike-slip and normal fault components and consists of two main branches,Mercimekdağı-Çamdere Fault(MÇF)and Tokat Fault(TF)segments.This study aims to assess the relative tectonic activity of the AFZ using various morphometric indices,based on a 10 m resolution DEM,with the aid of ArcGIS and MATLAB software.For this purpose,morphometric indices such as hypsometric integral(HI:0.35-0.65),mountain front sinuosity(Smf:1.3-1.44),valley floor width-height ratio(Vf:0.15-2.28),asymmetry factor(AF:23-77),drainage basin shape(Bs:1.13-6.10)and normalized steepness index(ksn:1-498)were applied to 53 drainage basins.When the Smf and mean Vf indices results were evaluated,it was calculated that the uplift ratio of the region was more than 0.5 mm/yr.The spatial distribution of the relative tectonic activity(Iat)of the area was revealed by combining the obtained morphometric indices analysis results.According to the Iat result,it was concluded that the MercimekdağıÇamdere Fault and Tokat Fault segments have high tectonic activity,but the Mercimekdağı-Çamdere Fault segment has higher tectonic activity.The results obtained were also confirmed by field observations.This research provides valuable information for the evaluation of tectonic activity in drainage systems controlled by splay faults.展开更多
To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervis...To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.展开更多
文摘Three-phase grid-connected inverters(GCIs)are essential components in distributed generation systems,where the accuracy of current measurement circuits is fundamental for reliable closed-loop operation.Nevertheless,the presence of a DC offset in the measured current can disrupt the regulation of grid currents and significantly degrade system performance.In this work,a fault-tolerant control approach is introduced to counteract the impact of such offset faults through a dedicated current compensation mechanism.The proposed solution is built around two main stages:(i)detecting and isolating DC offset faults that may appear in one or multiple phases of the measured grid currents,and(ii)estimating the fault magnitude and reconstructing the corrected current signal.The offset magnitude is obtained analytically by examining the grid current projected onto the synchronous d-axis at the grid angular frequency,eliminating the need for any additional sensing hardware.Simulation and experimental investigations conducted under several fault scenarios confirm the robustness of the proposed strategy and highlight significant improvements in detection speed and diagnostic accuracy.
文摘To apply the advantages of deep learning in recognizing two-dimensional(2D)images to three-phase inverter fault diagnosis,a threephase inverter fault diagnosis model based on gramian angular field(GAF)combined with convolutional neural network(CNN)was proposed.Since the current signals of the inverter in different working states are different,the images formed by the time series encoding are also different,which enables the image recognition technology to be used for time series classification to identify the fault current signal of the inverter.Firstly,the one-dimensional(1D)inverter fault current signal was converted into a 2D image through the GAF.Next,the CNN model suitable for inverter fault diagnosis was input to realize the detection,classification and location of inverter fault.The simulation results show that the recognition accuracy of this method is 99.36%under different noisy data.Compared with other traditional methods,it has higher accuracy and reliability,and stronger anti-noise interference capability and robustness in dealing with noisy data.Therefore,it is an effective fault diagnosis method for inverters.
基金supported by National Key Research and Development Program of China(2016YFB0900100)
文摘Half-wavelength AC transmission(HWACT) is an ultra-long distance AC transmission technology, whose electrical distance is close to half-wavelength at the system power frequency. It is very important for the construction and operation of HWACT to analyze its fault features and corresponding protection technology. In this paper, the steady-state voltage and current characteristics of the bus bar and fault point and the steady-state overvoltage distribution along the line will be analyzed when a three-phase symmetrical short-circuit fault occurs on an HWACT line. On this basis, the threephase fault characteristics for longer transmission lines are also studied.
基金supported in part by National Natural Science Foundation of China(NSFC)under Project No.51737010in part by State Key Laboratory of Electrical Insulation and Power Equipment(EIPE19109)。
文摘The paper presents an accurate analytical subdomain model for predicting the electromagnetic performance in the symmetrical dual three-phase surface-mounted permanent magnet synchronous machine(PMSM)under open-phase faulty conditions.The model derivations are extended from previous accurate subdomain models accounting for slotting effects.Compared with most conventional subdomain models for traditional three-phase machines with nonoverlapping winding arrangement,the subdomain model proposed in this paper applied for the 24-slot/4-pole dual three-phase machine with symmetrical overlapping winding arrangement.In order to investigate the postfault electromagnetic performance,the reconfigured phase currents and then current density distribution in stator slots under different open-circuit conditions are discussed.According to the developed model and postfault current density distribution,the steady-state electromagnetic performance,such as the electromagnetic torque and unbalanced magnetic force,under open-circuit faulty conditions are obtained.For validation purposes,finite element analysis(FEA)is employed to validate the analytical results.The result indicate that the postfault electromagnet performance can be accurately predicted by the proposed subdomain model,which is in good agreement with FEA results.
基金supported in part by the National Natural Science Foundation of China under Grant 62303333in part by the Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone under Grant HZQB-KCZYB-2020083.
文摘To achieve high power rating and low current harmonics of motor drive,this paper develops a dual three-phase open-winding permanent magnet synchronous motor(DTP-OW-PMSM)drive with the DC-link voltage ratio of 2:1:1.Based on this topology,this paper proposes a DTP four-level space vector pulse width modulation(DTP-FL SVPWM)strategy.First,two identical three-phase four-level space vector diagrams are constructed and divided.Then,three adjacent vectors nearest to the reference vector in each diagram are selected for the vector synthesis to guarantee high modulation precision and low switching frequency.Furthermore,to avoid the modulation error caused by the voltage deviation,the proposed DTP-FL SVPWM strategy is further optimized through unified duty ratio compensation(UDRC).The effectiveness of the proposed strategy is verified through experiments.
文摘The growing demand for efficient high-power switching power supplies has spurred interest in advanced topologies.The three-phase VIENNA converter stands out for its high power factor,simplified structure,and robust performance.Current research focuses on its operational principles,control strategies,and behavior under various load conditions.Key considerations include component selection,thermal management,and EMI/EMC optimization.This topology finds applications across renewable energy systems,industrial equipment,telecommunications,and electric vehicle charging infrastructures.Comparative analyses with alternative topologies and cost-benefit evaluations are also addressed.Future developments are expected to emphasize the integration of wide-bandgap devices and advancements in digital control techniques to further enhance efficiency and system performance.
基金supported by the National Key Research and Development Program of China under the grant of 2022YFB3403100。
文摘The dual three-phase PMSM(DTP-PMSM)drives have received wide attention at high-power high-efficiency applications due to their merits of high output current ability and copper-loss-free field excitation.Meanwhile,the DTPPMSM drive provides higher fault-tolerant capability for highreliability applications,e.g.,pumps and actuators in aircraft.For high-power drives with limited switching frequencies and highspeed drives with large fundamental frequencies,the ratio of switching frequency to fundamental frequency,i.e.,the carrier ratio,is usually below 15,which would significantly degrade the control performance.The purpose of this paper is to review the recent work on the modulation and control schemes for improving the operation performance of DTP-PMSM drives with low carrier ratios.Specifically,three categories of methods,i.e.,the space vector modulation based control,the model predictive control(MPC),and the optimized pulse pattern(OPP)based control are reviewed with principles and performance.In addition,brief discussions regarding the comparison and future trends are presented for low-carrier-ratio(LCR)modulation and control schemes of DTP-PMSM drives.
基金financially supported by the National Key Research and Development Program of China(No.2021YFC3100700)the National Natural Science Foundation of China(No.42376070)+1 种基金the Natural Science Foundation of Guangdong Province(No.2024A1515012371)the Rising Star Foundation of the South China Sea Institute of Oceanology(No.NHXX2019DZ0201)。
文摘Polygonal fault systems(PFS),characterized by multi-directional fault patterns within layered sequences,are well-documented features in global continental margin basins.While the geometry and formation mechanisms of PFS have been extensively studied in the northern South China Sea,the PFS in the Zhongjiannan Basin(western South China Sea)remain relatively unexplored,with a lack of quantitative analysis regarding their propagation.This study addresses this gap by using high-resolution three-dimensional(3D)seismic data and conducting a quantitative fault analysis to thoroughly examine the planform,cross-sectional geometry,and evolution of PFS in the northern Zhongjiannan Basin.The absence of a dominant strike direction among these polygonal faults suggests that their evolution is not controlled by anisotropic stress.Our interpretation of seismic data,constrained by the spatial relationship among PFS,gullies,and pockmarks,indicates that PFS mainly developed within the Miocene strata,with their initiation occurring during the late Miocene.Furthermore,the PFS act as key conduits connecting gullies to pockmarks in this area.The formation and development of PFS may be primarily driven by thermally triggered processes within siliceous sediments.The necessary heat source is probably associated with the abundant submarine magmatism observed in the Zhongjiannan Basin.To reconstruct the regional geological history,a four-stage evolutionary model,incorporating the formation of PFS,is presented.This research significantly improves our understanding of the regional geological evolution of the Zhongjiannan Basin,providing critical insights into the initiation and development of PFS in the western South China Sea.
基金supported by the National Natural Science Foundation of China(42230312,42272270,42172262,42372266)the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(2024ZD1000500)the China Geological Survey Project(DD20240041).
文摘The Guanxian-Anxian fault zone in the Longmen Shan,Sichuan,China,exhibits long-term creep-slip but ruptured during the 2008 Wenchuan earthquake,challenging the view that creeping faults rarely generate strong earthquakes.To investigate the transition from creep-slip to stick-slip,we analyzed fault rocks from the WFSD-3,using microstructural observations,XRD,μXRF,Raman spectroscopy,and quartz grain size statistics.Fault rocks show intense foliation,pressure-solution structures,and abundant clay minerals,reflecting long-term aseismic creep.At the interface between black and gray fault gouges at~1249.98 m,microstructures indicate stick-slip behavior,including truncated grains,angular fragments,and finer grain sizes.Here,clay content drops sharply while strong minerals(quartz,feldspar,calcite,dolomite)increase.Elemental mapping shows Al and K enriched in black gouge,whereas Ca and Si in gray gouge;Raman spectroscopy indicates possible graphitization;the finest quartz grains occur in black gouge.These features mark co-seismic principal slip zone of the Wenchuan earthquake.We propose that fluid-driven transformation of strong minerals into clays facilitates creep-slip,whereas localized precipitation of strong minerals strengthens the fault,causing stress accumulation and controlling the creep-slip to stick-slip transition.This mechanism has implications for reassessing seismic hazards of creeping faults.
基金funded by the Science and Technology Projects of State Grid Zhejiang Electric Power Co.,Ltd.(5211DS24000G).
文摘With the rapid development of large-scale offshore wind farms,efficient and reliable power transmission systems are urgently needed.Hybrid high-voltage direct current(HVDC)configurations combining a diode rectifier unit(DRU)and a modular multilevel converter(MMC)have emerged as a promising solution,offering advantages in cost-effectiveness and control capability.However,the uncontrollable nature of the DRU poses significant challenges for systemstability under offshore AC fault conditions,particularly due to its inability to provide fault current or voltage support.This paper investigates the offshore AC fault characteristics and fault ride-through(FRT)strategy of a hybrid offshore wind power transmission system based on a diode rectifier unit DRU and MMC.First,the dynamic response of the hybrid system under offshore symmetrical three-phase faults is analyzed.It is demonstrated that due to the unidirectional conduction nature of the DRU,its AC current rapidly drops to zero during faults,and the fault current is solely contributed by the wind turbine generators(WTGs)and wind farm MMC(WFMMC).Based on this analysis,a coordinated FRT strategy is proposed,which combines a segmented current limiting control for the wind-turbine(WT)grid-side converters(GSCs)and a constant AC current control for the WFMMC.The strategy ensures effective voltage support during the fault and prevents MMC current saturation during fault recovery,enabling fast and stable system restoration.Electromagnetic transient simulations in PSCAD/EMTDC verify the feasibility of the proposed fault ride-through strategy.
基金supported by the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(2024ZD1000500)the National Natural Science Foundation of China(42172262 and 42372266)+1 种基金the China Geological Survey(DD20240041)the Fundamental Research Funds of the Institute of Geomechanics(DZLXJK202516).
文摘The Yingxiu-Beichuan fault zone(YBFZ)has long been active and experienced repeated large earthquakes.The physicochemical properties of the deep fault zone(>1000 m)are the key to understanding the deformation mechanism of large earthquakes.This study uses rock magnetic,microstructural,and geochemical analyses of representative samples exposed in FZ1681 within the Wenchuan Earthquake Fault Scientific Drilling borehole 2(WFSD-2)cores.Fault gouge and fault breccia have higher magnetic susceptibility values than wall rocks,and they contain abundant paramagnetic minerals and small quantities of magnetite and monoclinic pyrrhotite.The magnetite and monoclinic pyrrhotite in the fault gouge were mainly formed by coseismic frictional heating,indicating that large earthquakes with frictional heating temperatures of~500-900℃once occurred in the YBFZ.The seismogenic and coseismic environment was reducing with a relatively high sulfur content.The monoclinic pyrrhotite in the fault breccia was formed mainly by low-temperature hydrothermal fluid.This indicates that the fault zone experienced reducing and low-temperature(<400℃)hydrothermal fluid with a relatively high sulfur content after the earthquake.The YBFZ,which experiences frequent large earthquakes,is weakly oxidizing environment at different depths,but the effect of the low-temperature hydrothermal fluid is weaker at depth.
文摘Grid-Forming(GFM)converters are prone to fault-induced overcurrent and power angle instability during grid fault-induced voltage sags.To address this,this paper develops a multi-loop coordinated fault ridethrough(FRT)control strategy based on a power outer loop and voltage-current inner loops,aiming to enhance the stability and current-limiting capability of GFM converters during grid fault conditions.During voltage sags,the GFM converter’s voltage source behavior is maintained by dynamically adjusting the reactive power reference to provide voltage support,thereby effectively suppressing the steady-state component of the fault current.To address the active power imbalance induced by voltage sags,a dynamic active power reference correction method based on apparent power is designed to mitigate power angle oscillations and limit transient current.Moreover,an adaptive virtual impedance loop is implemented to enhance dynamic transient current-limiting performance during the fault initiation phase.This approach improves the responsiveness of the inner loop and ensures safe system operation under various fault severities.Under asymmetric fault conditions,a negative-sequence reactive current compensation strategy is incorporated to further suppress negative-sequence voltage and improve voltage symmetry.The proposed control scheme enables coordinated operation of multiple control objectives,including voltage support,current suppression,and power angle stability,across different fault scenarios.Finally,MATLAB/Simulink simulation results validate the effectiveness of the proposed strategy,showcasing its superior performance in current limiting and power angle stability,thereby significantly enhancing the system’s fault ride-through capability.
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
基金funded by the Science and Technology Vice President Project in Changping District,Beijing(Project Name:Research on multi-scale optimization and intelligent control technology of integrated energy systemProject number:202302007013).
文摘The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of issues,including mechanical faults,air path malfunctions,and combustion irregularities.Traditional modelbased approaches face inherent limitations due to their inability to handle nonlinear problems,natural factors,measurement uncertainties,fault coupling,and implementation challenges.The development of artificial intelligence algorithms has provided an effective solution to these issues,sparking extensive research into data-driven fault diagnosis methodologies.The review mechanism involved searching IEEE Xplore,ScienceDirect,and Web of Science for peerreviewed articles published between 2019 and 2025,focusing on multi-fault diagnosis techniques.A total of 220 papers were identified,with 123 meeting the inclusion criteria.This paper provides a comprehensive review of diagnostic methodologies,detailing their operational principles and distinctive features.It analyzes current research hotspots and challenges while forecasting future trends.The study systematically evaluates the strengths and limitations of various fault diagnosis techniques,revealing their practical applicability and constraints through comparative analysis.Furthermore,this paper looks forward to the future development direction of this field and provides a valuable reference for the optimization and development of gas turbine fault diagnosis technology in the future.
文摘A．Switch-Redundant Topology An early attempt to add fault tolerant capacity to a standard three-phase inverter topology for induction motors was presented．This topology will be referred to as the switch-redundant topology and is shown in Fig.5．This topology incorporates four TRIACs or back-to-back connected SCRs and three fast acting fuses．The fuses are connected in series with the load phases．Since this topology is a combination of topologies and control methods to accommodate an opened phase，and a shorted switch，they will be considered separately．
基金supported by the China Three Gorges Corporation(No.NBZZ202300860)the National Natural Science Foundation of China(No.52275104)the Science and Technology Innovation Program of Hunan Province(No.2023RC3097).
文摘Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction.However,several challenges remain.First,signal noise collected during blade operation masks fault features,severely impairing the fault diagnosis performance of deep learning models.Second,current blade fault diagnosis often relies on single-sensor data,resulting in limited monitoring dimensions and ability to comprehensively capture complex fault states.To address these issues,a multi-sensor fusion-based wind turbine blade fault diagnosis method is proposed.Specifically,a CNN-Transformer Coupled Feature Learning Architecture is constructed to enhance the ability to learn complex features under noisy conditions,while a Weight-Aligned Data Fusion Module is designed to comprehensively and effectively utilize multi-sensor fault information.Experimental results of wind turbine blade fault diagnosis under different noise interferences show that higher accuracy is achieved by the proposed method compared to models with single-source data input,enabling comprehensive and effective fault diagnosis.
基金supported in part by the National Natural Science Foundation of China under Grants 52475102 and 52205101in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2023A1515240021+1 种基金in part by the Young Talent Support Project of Guangzhou Association for Science and Technology(QT-2024-28)in part by the Youth Development Initiative of Guangdong Association for Science and Technology(SKXRC2025254).
文摘To ensure the safe and stable operation of rotating machinery,intelligent fault diagnosis methods hold significant research value.However,existing diagnostic approaches largely rely on manual feature extraction and expert experience,which limits their adaptability under variable operating conditions and strong noise environments,severely affecting the generalization capability of diagnostic models.To address this issue,this study proposes a multimodal fusion fault diagnosis framework based on Mel-spectrograms and automated machine learning(AutoML).The framework first extracts fault-sensitive Mel time–frequency features from acoustic signals and fuses them with statistical features of vibration signals to construct complementary fault representations.On this basis,automated machine learning techniques are introduced to enable end-to-end diagnostic workflow construction and optimal model configuration acquisition.Finally,diagnostic decisions are achieved by automatically integrating the predictions of multiple high-performance base models.Experimental results on a centrifugal pump vibration and acoustic dataset demonstrate that the proposed framework achieves high diagnostic accuracy under noise-free conditions and maintains strong robustness under noisy interference,validating its efficiency,scalability,and practical value for rotating machinery fault diagnosis.
基金supported by the National Natural Science Foundation of China(42202131 and 42177184).
文摘This study examines a 1.32 m thick sediment sequence from the Cunge sag pond in the Litang Basin,eastern Tibetan Plateau,to assess the seismicity of the Litang fault during the Holocene.High-resolution geochemical,grain size,magnetic susceptibility,and total organic carbon indicators are employed to obtain a continuous record of changes in elemental,physical,and biological properties within the profile to identify seismic events.The seismic event layer generally comprises two sedimentary rhythms:a lower coarse sand layer and an upper fine silt-clay layer.These layers represent rapid deposition associated with fault activity(Earthquake A)and slower deposition during calm periods or earthquake recurrence intervals(Seismic interval A).Through six^(14)C dating,five seismic events have been identified in the Cunge sag pond section:E1(before 3955 a B.P.),E2(3713-3703 a B.P.),E3(3492-3392 a B.P.),E4(2031-1894 a B.P.),and E5(1384-1321 a B.P.).E1-E4 had shown a good consistency with the paleo-earthquake recorded by the trench,and whereas E5 is a newly identified seismic event,further improving the continuous earthquake sequence of the Litang fault.Based on existing trench data and the seismic event record from the Cunge sag pond,a total of 11 paleo-earthquakes are identified along the Litang fault since the Holocene.The paleo-earthquake activity of the Litang fault exhibits a clustered pattern,with recurrence intervals of both long periods(1000 a)and short periods(500 a).Since 5000 a,the interval between strong earthquake recurrences gradually decreases,indicating an increasing risk of strong earthquakes along the Litang fault.This study presents a continuous record of paleo-earthquakes along the Litang fault,eastern Tibetan Plateau,and can enhance the understanding of regional seismic activity.
文摘The Almus Fault Zone(AFZ)is one of the major splay faults of the North Anatolian Fault Zone(NAFZ)and is important for understanding its tectonic features and assessing regional seismic hazards.This research presents the integration of morphometric indices to quantitatively assess the spatial variation of tectonic activity along the AFZ.The AFZ is an active fault with both strike-slip and normal fault components and consists of two main branches,Mercimekdağı-Çamdere Fault(MÇF)and Tokat Fault(TF)segments.This study aims to assess the relative tectonic activity of the AFZ using various morphometric indices,based on a 10 m resolution DEM,with the aid of ArcGIS and MATLAB software.For this purpose,morphometric indices such as hypsometric integral(HI:0.35-0.65),mountain front sinuosity(Smf:1.3-1.44),valley floor width-height ratio(Vf:0.15-2.28),asymmetry factor(AF:23-77),drainage basin shape(Bs:1.13-6.10)and normalized steepness index(ksn:1-498)were applied to 53 drainage basins.When the Smf and mean Vf indices results were evaluated,it was calculated that the uplift ratio of the region was more than 0.5 mm/yr.The spatial distribution of the relative tectonic activity(Iat)of the area was revealed by combining the obtained morphometric indices analysis results.According to the Iat result,it was concluded that the MercimekdağıÇamdere Fault and Tokat Fault segments have high tectonic activity,but the Mercimekdağı-Çamdere Fault segment has higher tectonic activity.The results obtained were also confirmed by field observations.This research provides valuable information for the evaluation of tectonic activity in drainage systems controlled by splay faults.
基金supported by the National Natural Science Foundation of China Funded Project(Project Name:Research on Robust Adaptive Allocation Mechanism of Human Machine Co-Driving System Based on NMS Features,Project Approval Number:52172381).
文摘To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.
