The extended Kalman filter(EKF)is extensively applied in integrated navigation systems that combine the global navigation satellite system(GNSS)and strap-down inertial navigation system(SINS).However,the performance o...The extended Kalman filter(EKF)is extensively applied in integrated navigation systems that combine the global navigation satellite system(GNSS)and strap-down inertial navigation system(SINS).However,the performance of the EKF can be severely impacted by non-Gaussian noise and measurement noise uncertainties,making it difficult to achieve optimal GNSS/INS integration.Dealing with non-Gaussian noise remains a significant challenge in filter development today.Therefore,the maximum correntropy criterion(MCC)is utilized in EKFs to manage heavytailed measurement noise.However,its capability to handle non-Gaussian process noise and unknown disturbances remains largely unexplored.In this paper,we extend correntropy from using a single kernel to a multi-kernel approach.This leads to the development of a multi-kernel maximum correntropy extended Kalman filter(MKMC-EKF),which is designed to effectively manage multivariate non-Gaussian noise and disturbances.Further,theoretical analysis,including advanced stability proofs,can enhance understanding,while hybrid approaches integrating MKMC-EKF with particle filters may improve performance in nonlinear systems.The MKMC-EKF enhances estimation accuracy using a multi-kernel bandwidth approach.As bandwidth increases,the filter’s sensitivity to non-Gaussian features decreases,and its behavior progressively approximates that of the iterated EKF.The proposed approach for enhancing positioning in navigation is validated through performance evaluations,which demonstrate its practical applications in real-world systems like GPS navigation and measuring radar targets.展开更多
To investigate the effects of the maximum principal stress direction(θ)and cross-section shape on the failure characteristics of sandstone,true-triaxial compression experiments were conducted using cubic samples with...To investigate the effects of the maximum principal stress direction(θ)and cross-section shape on the failure characteristics of sandstone,true-triaxial compression experiments were conducted using cubic samples with rectangular,circular,and D-shaped holes.Asθincreases from 0°to 60°in the rectangular hole,the left failure location shifts from the left corner to the left sidewall,the left corner,and then the floor,while the right failure location shifts from the right corner to the right sidewall,right roof corner,and then the roof.Furthermore,the initial failure vertical stress first decreases and then increases.In comparison,the failure severity in the rectangular hole decreases for variousθvalues as 30°>45°>60°>0°.With increasingθ,the fractal dimension(D)of rock slices first increases and then decreases.For the rectangular and D-shaped holes,whenθ=0°,30°,and 90°,D for the rectangular hole is less than that of the D-shaped hole.Whenθ=45°and 60°,D for the rectangular hole is greater than that of the D-shaped hole.Theoretical analysis indicates that the stress concentration at the rectangular and D-shaped corners is greater than the other areas.The failure location rotates with the rotation ofθ,and the failure occurs on the side with a high concentration of compressive stress,while the side with the tensile and compressive stresses remains relatively stable.Therefore,the fundamental reason for the rotation of failure location is the rotation of stress concentration,and the external influencing factor is the rotation ofθ.展开更多
In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenario...In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.展开更多
Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stre...Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.展开更多
The age at which a woman enters natural menopause has also been associated to death from any cause.Menopause is a natural component of aging that happens between the ages of 45 and 55,with the average menopausal age b...The age at which a woman enters natural menopause has also been associated to death from any cause.Menopause is a natural component of aging that happens between the ages of 45 and 55,with the average menopausal age being 51.Previous research has revealed the age at which women reach menopause,but there is no evidence to support the link between menopause and longevity.We made a study in assessing the limits of maximum lifespan at menopausal age in our previous article.In this paper,we aim to predict the maximum lifespan of women at mean menopausal age.展开更多
The turbidity maximum zone(TMZ)is a distinctive aquatic environment marked by consistently higher turbidity compared to upstream and downstream section.In the TMZ,physicochemical properties such as intense light limit...The turbidity maximum zone(TMZ)is a distinctive aquatic environment marked by consistently higher turbidity compared to upstream and downstream section.In the TMZ,physicochemical properties such as intense light limitation,abundant nutrients,and rapid salinity shifts play a crucial role in shaping phytoplankton dynamics.The Qiantang River estuary-Hangzhou Bay(QRE-HZB)is a macrotidal estuary system known for its exceptionally high suspended solids concentration.To investigate the impact of TMZ on the standing crop and size structure of phytoplankton in the QRE-HZB,we conducted three cruises in dry,wet,and dry-to-wet transition seasons during 2022-2023,by assessing parameters including size fractionated chlorophyll a(chl a),turbidity,Secchi depth,temperature,salinity,nutrients,and mesozooplankton.Results reveal significant variations in the TMZ and associated environmental factors in different periods,which markedly influenced the phytoplankton chl-a concentration,size structure,and cell activity(pheophytin/chl a).The chl-a concentration was high with micro-phytoplankton predominance in wet season,while nano-phytoplankton dominated in dry season.Within the TMZ,lower chl-a concentrations and pico-chl-a contributions,alongside higher pheophytin/chl-a and micro-chl-a contributions,were observed.The Spearman’s rank correlation and generalized additive model analyses indicated strong correlations of chl-a concentrations with turbidity,nutrients,and mesozooplankton.Redundancy analysis further revealed that salinity,nutrients,and turbidity significantly regulated variations in size structure.Phytoplankton mortality within the TMZ was primarily driven by high turbidity and salinity fluctuations,reflecting the vigorous resuspension and mixing of freshwater and seawater in the QRE-HZB.These findings highlight that the standing crop and size structure of phytoplankton were strongly regulated by the TMZ and associated physicochemical factors in the macrotidal QRE-HZB.展开更多
Coal dust explosions are severe safety accidents in coal mine production,posing significant threats to life and property.Predicting the maximum explosion pressure(Pm)of coal dust using deep learning models can effecti...Coal dust explosions are severe safety accidents in coal mine production,posing significant threats to life and property.Predicting the maximum explosion pressure(Pm)of coal dust using deep learning models can effectively assess potential risks and provide a scientific basis for preventing coal dust explosions.In this study,a 20-L explosion sphere apparatus was used to test the maximum explosion pressure of coal dust under seven different particle sizes and ten mass concentrations(Cdust),resulting in a dataset of 70 experimental groups.Through Spearman correlation analysis and random forest feature selection methods,particle size(D_(10),D_(20),D_(50))and mass concentration(Cdust)were identified as critical feature parameters from the ten initial parameters of the coal dust samples.Based on this,a hybrid Long Short-Term Memory(LSTM)network model incorporating a Multi-Head Attention Mechanism and the Sparrow Search Algorithm(SSA)was proposed to predict the maximum explosion pressure of coal dust.The results demonstrate that the SSA-LSTM-Multi-Head Attention model excels in predicting the maximum explosion pressure of coal dust.The four evaluation metrics indicate that the model achieved a coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute percentage error(MAPE),and mean absolute error(MAE)of 0.9841,0.0030,0.0074,and 0.0049,respectively,in the training set.In the testing set,these values were 0.9743,0.0087,0.0108,and 0.0069,respectively.Compared to artificial neural networks(ANN),random forest(RF),support vector machines(SVM),particle swarm optimized-SVM(PSO-SVM)neural networks,and the traditional single-model LSTM,the SSA-LSTM-Multi-Head Attention model demonstrated superior generalization capability and prediction accuracy.The findings of this study not only advance the application of deep learning in coal dust explosion prediction but also provide robust technical support for the prevention and risk assessment of coal dust explosions.展开更多
Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the spe...Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the special case where p and n are comparable,we consider a much more general case in which log n=o(p^(1/3)).We prove that the maximum interpoint distance Mn=max{|X_(i)-X_(j)|;1≤i<j≤n}converges to an extreme-value distribution,where X_(i)and X_(j)denote the i-th and j-th row of M_(n,p),respectively.The proofs are completed by using the Chen-Stein Poisson approximation method and the moderation deviation principle.展开更多
The presence of circles in the network maximum flow problem increases the complexity of the preflow algorithm.This study proposes a novel two-stage preflow algorithm to address this issue.First,this study proves that ...The presence of circles in the network maximum flow problem increases the complexity of the preflow algorithm.This study proposes a novel two-stage preflow algorithm to address this issue.First,this study proves that at least one zero-flow arc must be present when the flow of the network reaches its maximum value.This result indicates that the maximum flow of the network will remain constant if a zero-flow arc within a circle is removed;therefore,the maximum flow of each network without circles can be calculated.The first stage involves identifying the zero-flow arc in the circle when the network flow reaches its maximum.The second stage aims to remove the zero-flow arc identified and modified in the first stage,thereby producing a new network without circles.The maximum flow of the original looped network can be obtained by solving the maximum flow of the newly generated acyclic network.Finally,an example is provided to demonstrate the validity and feasibility of this algorithm.This algorithm not only improves computational efficiency but also provides new perspectives and tools for solving similar network optimization problems.展开更多
Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a netwo...Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.展开更多
Research on changes in the redox conditions of bottom waters is essential for understanding deep water circulation,global ocean currents,climate change,and ecosystem health.Through sedimentary geological methods,a dee...Research on changes in the redox conditions of bottom waters is essential for understanding deep water circulation,global ocean currents,climate change,and ecosystem health.Through sedimentary geological methods,a deeper understanding of the complex relationships between various environmental changes can be achieved,providing detailed evidence and theoretical support for global climate change research.The Ross Sea in Antarctica plays a key role in the formation of Antarctic bottom water(AABW),and the complex climate changes since the last glacial maximum(LGM)make it particularly significant for study.This research analyzes core ANT32-RB16C from the Ross Sea using geochemical proxies such as major and trace elements,grain size,and redox-sensitive indicators like Mn/Ti,Co/Ti,Mo/Ti,Cd/Ti,U/Th,and Ni/Co molar concentration ratios.Combining this data with a previously established chronological framework,the study explores the evolution of redox conditions in the Ross Sea’s deep waters since the LGM.The results show that the deep waters have remained oxygen-rich since the LGM,with significant changes in four stages.Stage 1(24.7–15.7 cal ka BP):Strong oxidizing conditions,likely due to enhanced formation of Ross Sea bottom water(RSBW),increasing oxygen levels.Stage 2(15.7–4.5 cal ka BP):Weakened oxidizing conditions as temperatures rose and ice shelves retreated,increasing primary productivity and depleting oxygen.Stage 3(4.5–1.5 cal ka BP):Continued decline in oxidizing conditions,possibly linked to high primary productivity and oxygen consumption.Stage 4(1.5 cal ka BP to present):A rapid recovery of oxidizing conditions,likely driven by temperature drops,increased RSBW formation,and decreased productivity.展开更多
The annual maximum rainfall event(AMRE)refers to the maximum consecutive five-day rainfall in a year.In North China,these events account for 15%–80%of the total summer(June–August)rainfall amount and pose a great ch...The annual maximum rainfall event(AMRE)refers to the maximum consecutive five-day rainfall in a year.In North China,these events account for 15%–80%of the total summer(June–August)rainfall amount and pose a great challenge for subseasonal-to-seasonal forecasting.Based on data analyses during 1979–2023,this study shows the interannual variability of AMRE is significantly influenced by the phase and amplitude mode of the annual cycle of the East Asian summer monsoon(EASM),characterized by two orthogonal patterns of southeasterly winds at 850 h Pa over the northwestern Pacific.The EASM phase-locked AMRE shows heavy rainfall events occurring extremely early and late in Beijing and surrounding areas,corresponding to the peak southeasterly wind anomalies in June and August.The EASM amplitude-locked AMRE exhibits extreme heavy or light rainfall over southwest areas with normal phase.Therefore,AMRE has a potential predictability on the seasonal time scale due to its phase-and amplitude-locking with the slow variation of the annual cycle of the EASM.展开更多
This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between th...This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between the NCEP Climate Forecast System version 2(CFSv2) and a high-resolution Weather Research and Forecasting(WRF) model,using gridded Tmax observation data and ERA5 reanalysis data as benchmarks. The WRF model is driven by CFSv2 multi-member ensemble hindcast and forecast data. Results indicate that the WRF model improves Tmax prediction across China, with particularly significant enhancement over the southern region of the middle and lower reaches of the Yangtze River, although a systematic cold bias remains. By applying bias correction to the daily Tmax simulations from both models, we find that the corrected WRF predictions exhibit marked improvement for both the annual and extended-range Tmax. Furthermore, this study explores the physical mechanisms contributing to the improved predictability in the regional model. The WRF model, with its refined physical parameterization schemes, better simulates middle to lower tropospheric geopotential height fields, as well as surface sensible and latent heat fluxes. These results demonstrate that the dynamical downscaling approach can significantly improve the temperature prediction in southern China, highlighting the potential applicational value of this method for extended-range high-temperature forecasting.展开更多
Over the past few decades, numerous adaptive Kalman filters(AKFs) have been proposed. However, achieving online estimation with both high estimation accuracy and fast convergence speed is challenging, especially when ...Over the past few decades, numerous adaptive Kalman filters(AKFs) have been proposed. However, achieving online estimation with both high estimation accuracy and fast convergence speed is challenging, especially when both the process noise and measurement noise covariance matrices are relatively inaccurate. Maximum likelihood estimation(MLE) possesses the potential to achieve this goal, since its theoretical accuracy is guaranteed by asymptotic optimality and the convergence speed is fast due to weak dependence on accurate state estimation.Unfortunately, the maximum likelihood cost function is so intricate that the existing MLE methods can only simply ignore all historical measurement information to achieve online estimation,which cannot adequately realize the potential of MLE. In order to design online MLE-based AKFs with high estimation accuracy and fast convergence speed, an online exploratory MLE approach is proposed, based on which a mini-batch coordinate descent noise covariance matrix estimation framework is developed. In this framework, the maximum likelihood cost function is simplified for online estimation with fewer and simpler terms which are selected in a mini-batch and calculated with a backtracking method. This maximum likelihood cost function is sidestepped and solved by exploring possible estimated noise covariance matrices adaptively while the historical measurement information is adequately utilized. Furthermore, four specific algorithms are derived under this framework to meet different practical requirements in terms of convergence speed, estimation accuracy,and calculation load. Abundant simulations and experiments are carried out to verify the validity and superiority of the proposed algorithms as compared with existing state-of-the-art AKFs.展开更多
Weighted exponential distribution W ED(α,λ)with shape parameterαand scale parameterλpossesses some good properties and can be used as a good fit to survival time data compared to other distributions such as gamma,...Weighted exponential distribution W ED(α,λ)with shape parameterαand scale parameterλpossesses some good properties and can be used as a good fit to survival time data compared to other distributions such as gamma,Weibull,or generalized exponential distribution.In this article,we proved the existence and uniqueness of the maximum likelihood estimator(MLE)of the parameters of W ED(α,λ)in simple random sampling(SRS)and provided explicit expressions for the Fisher information number in SRS.Moreover,we also proved the existence and uniqueness of the MLE of the parameters of W ED(α,λ)in ranked set sampling(RSS)and provided explicit expressions for the Fisher information number in RSS.Simulation studies show that these MLEs in RSS can be real competitors for those in SRS.展开更多
As a frequently-observed phenomenon in the northern South China Sea(nSCS),subsurface chlorophyll maximum(SCM)evolution from summer to winter remains unclear,neither the associated hydrographic control.In this study,on...As a frequently-observed phenomenon in the northern South China Sea(nSCS),subsurface chlorophyll maximum(SCM)evolution from summer to winter remains unclear,neither the associated hydrographic control.In this study,on the basis of in-situ data of fall-season cruises in 2004–2006,we characterized the depth,thickness and intensity of the SCM in the nSCS using a general Gaussian-function fitting approach,and investigated a linkage to the corresponding ocean vertical buoyance properties.Our results show that the SCM becomes deeper,thicker and less intense offshore-wards in the nSCS during fall seasons.In parallel,a correlation between the SCM variation and mixed layer depth exists in the nSCS,and it becomes pronounced in the shelf region compared to the slope and basin areas in autumn.Physically,once warmer surface ocean and thus stronger thermo-determined stratification,the SCM layer goes deeper and becomes thicker and less intense in the nSCS,especially in the shelf area of the nSCS.Moreover,the impact of water temperatures at deeper layers on the vertical stratification exerts more consequent roles on the spatial variability of SCM,compared to surface temperatures in the nSCS.Specifically,the isotherm line of 22℃ acts as crucial indicator for variations of the SCM in the nSCS during autumns.展开更多
This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mod...This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.展开更多
The quantum alternating operator ansatz algorithm(QAOA+)is widely used for constrained combinatorial optimization problems(CCOPs)due to its ability to construct feasible solution spaces.In this paper,we propose a prog...The quantum alternating operator ansatz algorithm(QAOA+)is widely used for constrained combinatorial optimization problems(CCOPs)due to its ability to construct feasible solution spaces.In this paper,we propose a progressive quantum algorithm(PQA)to reduce qubit requirements for QAOA+in solving the maximum independent set(MIS)problem.PQA iteratively constructs a subgraph likely to include the MIS solution of the original graph and solves the problem on it to approximate the global solution.Specifically,PQA starts with a small-scale subgraph and progressively expands its graph size utilizing heuristic expansion strategies.After each expansion,PQA solves the MIS problem on the newly generated subgraph using QAOA+.In each run,PQA repeats the expansion and solving process until a predefined stopping condition is reached.Simulation results show that PQA achieves an approximation ratio of 0.95 using only 5.57%(2.17%)of the qubits and 17.59%(6.43%)of the runtime compared with directly solving the original problem with QAOA+on Erd?s-Rényi(3-regular)graphs,highlighting the efficiency and scalability of PQA.展开更多
In the multilevel thresholding segmentation of the image, the classification number is always given by the supervisor. To solve this problem, a fast multilevel thresholding algorithm considering both the threshold val...In the multilevel thresholding segmentation of the image, the classification number is always given by the supervisor. To solve this problem, a fast multilevel thresholding algorithm considering both the threshold value and the classification number is proposed based on the maximum entropy, and the self-adaptive criterion of the classification number is given. The algorithm can obtain thresholds and automatically decide the classification number. Experimental results show that the algorithm is effective.展开更多
In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenom...In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenomena is considered. Based on the theory of fuzzy recognition and fault diagnosis, this method only depends on experience and statistical data to set up fuzzy query relationship between the outside phenomena (fault characters) and the fault sources (fault patterns). From this relationship the most probable fault sources can be obtained, to attain the goal of quick diagnosis. Based on the above approach, the standard fuzzy relationship matrix is stored in the computer as a system database. And experiment data are given to show the fault diagnosis results. The important parameters can be on line sampled and analyzed, and when faults occur, faults can be found, the alarm is given and the controller output is regulated.展开更多
基金the support from National Science and Technology Council,Taiwan under grant numbers NSTC 113-2811-E-019-001 and NSTC 113-2221-E-019-059.
文摘The extended Kalman filter(EKF)is extensively applied in integrated navigation systems that combine the global navigation satellite system(GNSS)and strap-down inertial navigation system(SINS).However,the performance of the EKF can be severely impacted by non-Gaussian noise and measurement noise uncertainties,making it difficult to achieve optimal GNSS/INS integration.Dealing with non-Gaussian noise remains a significant challenge in filter development today.Therefore,the maximum correntropy criterion(MCC)is utilized in EKFs to manage heavytailed measurement noise.However,its capability to handle non-Gaussian process noise and unknown disturbances remains largely unexplored.In this paper,we extend correntropy from using a single kernel to a multi-kernel approach.This leads to the development of a multi-kernel maximum correntropy extended Kalman filter(MKMC-EKF),which is designed to effectively manage multivariate non-Gaussian noise and disturbances.Further,theoretical analysis,including advanced stability proofs,can enhance understanding,while hybrid approaches integrating MKMC-EKF with particle filters may improve performance in nonlinear systems.The MKMC-EKF enhances estimation accuracy using a multi-kernel bandwidth approach.As bandwidth increases,the filter’s sensitivity to non-Gaussian features decreases,and its behavior progressively approximates that of the iterated EKF.The proposed approach for enhancing positioning in navigation is validated through performance evaluations,which demonstrate its practical applications in real-world systems like GPS navigation and measuring radar targets.
基金supported by the National Natural Science Foundation of China (Grant Nos.52304227 and 52104133)Scientific and Technological Research Platform for Disaster Prevention and Control of Deep Coal Mining (Anhui University of Science and Technology) (Grant No.DPDCM2208).
文摘To investigate the effects of the maximum principal stress direction(θ)and cross-section shape on the failure characteristics of sandstone,true-triaxial compression experiments were conducted using cubic samples with rectangular,circular,and D-shaped holes.Asθincreases from 0°to 60°in the rectangular hole,the left failure location shifts from the left corner to the left sidewall,the left corner,and then the floor,while the right failure location shifts from the right corner to the right sidewall,right roof corner,and then the roof.Furthermore,the initial failure vertical stress first decreases and then increases.In comparison,the failure severity in the rectangular hole decreases for variousθvalues as 30°>45°>60°>0°.With increasingθ,the fractal dimension(D)of rock slices first increases and then decreases.For the rectangular and D-shaped holes,whenθ=0°,30°,and 90°,D for the rectangular hole is less than that of the D-shaped hole.Whenθ=45°and 60°,D for the rectangular hole is greater than that of the D-shaped hole.Theoretical analysis indicates that the stress concentration at the rectangular and D-shaped corners is greater than the other areas.The failure location rotates with the rotation ofθ,and the failure occurs on the side with a high concentration of compressive stress,while the side with the tensile and compressive stresses remains relatively stable.Therefore,the fundamental reason for the rotation of failure location is the rotation of stress concentration,and the external influencing factor is the rotation ofθ.
基金supported by the National Science and Technology Council,Taiwan under grants NSTC 111-2221-E-019-047 and NSTC 112-2221-E-019-030.
文摘In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.
基金financially supported by the National Natural Science Foundation of China(No.52204084)the Open Research Fund of the State Key Laboratory of Coal Resources and safe Mining,CUMT,China(No.SKLCRSM 23KF004)+3 种基金the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities),China(No.FRF-IDRY-GD22-002)the Fundamental Research Funds for the Central Universities and the Youth Teacher International Exchange and Growth Program,China(No.QNXM20220009)the National Key R&D Program of China(Nos.2022YFC2905600 and 2022 YFC3004601)the Science,Technology&Innovation Project of Xiongan New Area,China(No.2023XAGG0061)。
文摘Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.
文摘The age at which a woman enters natural menopause has also been associated to death from any cause.Menopause is a natural component of aging that happens between the ages of 45 and 55,with the average menopausal age being 51.Previous research has revealed the age at which women reach menopause,but there is no evidence to support the link between menopause and longevity.We made a study in assessing the limits of maximum lifespan at menopausal age in our previous article.In this paper,we aim to predict the maximum lifespan of women at mean menopausal age.
基金Supported by the National Key Research and Development Program of China(No.2021 YFC 3101702)the Key R&D Program of Zhejiang(No.2022 C 03044)+2 种基金the Scientific Research Fund of the Second Institute of Oceanography,MNR(No.JG 1521)the Project of State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography(No.SOEDZZ 2202)the National Program on Global Change and Air-Sea Interaction(Phase Ⅱ)-Hypoxia and Acidification Monitoring and Warning Project in the Changjiang River estuary,and Long-term Observation and Research Plan in the Changjiang River estuary and Adjacent East China Sea(LORCE)Project(No.SZ 2001)。
文摘The turbidity maximum zone(TMZ)is a distinctive aquatic environment marked by consistently higher turbidity compared to upstream and downstream section.In the TMZ,physicochemical properties such as intense light limitation,abundant nutrients,and rapid salinity shifts play a crucial role in shaping phytoplankton dynamics.The Qiantang River estuary-Hangzhou Bay(QRE-HZB)is a macrotidal estuary system known for its exceptionally high suspended solids concentration.To investigate the impact of TMZ on the standing crop and size structure of phytoplankton in the QRE-HZB,we conducted three cruises in dry,wet,and dry-to-wet transition seasons during 2022-2023,by assessing parameters including size fractionated chlorophyll a(chl a),turbidity,Secchi depth,temperature,salinity,nutrients,and mesozooplankton.Results reveal significant variations in the TMZ and associated environmental factors in different periods,which markedly influenced the phytoplankton chl-a concentration,size structure,and cell activity(pheophytin/chl a).The chl-a concentration was high with micro-phytoplankton predominance in wet season,while nano-phytoplankton dominated in dry season.Within the TMZ,lower chl-a concentrations and pico-chl-a contributions,alongside higher pheophytin/chl-a and micro-chl-a contributions,were observed.The Spearman’s rank correlation and generalized additive model analyses indicated strong correlations of chl-a concentrations with turbidity,nutrients,and mesozooplankton.Redundancy analysis further revealed that salinity,nutrients,and turbidity significantly regulated variations in size structure.Phytoplankton mortality within the TMZ was primarily driven by high turbidity and salinity fluctuations,reflecting the vigorous resuspension and mixing of freshwater and seawater in the QRE-HZB.These findings highlight that the standing crop and size structure of phytoplankton were strongly regulated by the TMZ and associated physicochemical factors in the macrotidal QRE-HZB.
基金funded by the Research on Intelligent Mining Geological Model and Ventilation Model for Extremely Thin Coal Seam in Heilongjiang Province,China(2021ZXJ02A03)the Demonstration of Intelligent Mining for Comprehensive Mining Face in Extremely Thin Coal Seam in Heilongjiang Province,China(2021ZXJ02A04)the Natural Science Foundation of Heilongjiang Province,China(LH2024E112).
文摘Coal dust explosions are severe safety accidents in coal mine production,posing significant threats to life and property.Predicting the maximum explosion pressure(Pm)of coal dust using deep learning models can effectively assess potential risks and provide a scientific basis for preventing coal dust explosions.In this study,a 20-L explosion sphere apparatus was used to test the maximum explosion pressure of coal dust under seven different particle sizes and ten mass concentrations(Cdust),resulting in a dataset of 70 experimental groups.Through Spearman correlation analysis and random forest feature selection methods,particle size(D_(10),D_(20),D_(50))and mass concentration(Cdust)were identified as critical feature parameters from the ten initial parameters of the coal dust samples.Based on this,a hybrid Long Short-Term Memory(LSTM)network model incorporating a Multi-Head Attention Mechanism and the Sparrow Search Algorithm(SSA)was proposed to predict the maximum explosion pressure of coal dust.The results demonstrate that the SSA-LSTM-Multi-Head Attention model excels in predicting the maximum explosion pressure of coal dust.The four evaluation metrics indicate that the model achieved a coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute percentage error(MAPE),and mean absolute error(MAE)of 0.9841,0.0030,0.0074,and 0.0049,respectively,in the training set.In the testing set,these values were 0.9743,0.0087,0.0108,and 0.0069,respectively.Compared to artificial neural networks(ANN),random forest(RF),support vector machines(SVM),particle swarm optimized-SVM(PSO-SVM)neural networks,and the traditional single-model LSTM,the SSA-LSTM-Multi-Head Attention model demonstrated superior generalization capability and prediction accuracy.The findings of this study not only advance the application of deep learning in coal dust explosion prediction but also provide robust technical support for the prevention and risk assessment of coal dust explosions.
基金Supported by the National Natural Science Foundation of China(Grant Nos.1177117812171198)+2 种基金the Science and Technology Development Program of Jilin Province(Grant No.20210101467JC)the Technology Program of Jilin Educational Department During the“14th Five-Year”Plan Period(Grant No.JJKH20241239KJ)the Fundamental Research Funds for the Central Universities.
文摘Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the special case where p and n are comparable,we consider a much more general case in which log n=o(p^(1/3)).We prove that the maximum interpoint distance Mn=max{|X_(i)-X_(j)|;1≤i<j≤n}converges to an extreme-value distribution,where X_(i)and X_(j)denote the i-th and j-th row of M_(n,p),respectively.The proofs are completed by using the Chen-Stein Poisson approximation method and the moderation deviation principle.
基金The National Natural Science Foundation of China(No.72001107,72271120)the Fundamental Research Funds for the Central Universities(No.NS2024047,NP2024106)the China Postdoctoral Science Foundation(No.2020T130297,2019M660119).
文摘The presence of circles in the network maximum flow problem increases the complexity of the preflow algorithm.This study proposes a novel two-stage preflow algorithm to address this issue.First,this study proves that at least one zero-flow arc must be present when the flow of the network reaches its maximum value.This result indicates that the maximum flow of the network will remain constant if a zero-flow arc within a circle is removed;therefore,the maximum flow of each network without circles can be calculated.The first stage involves identifying the zero-flow arc in the circle when the network flow reaches its maximum.The second stage aims to remove the zero-flow arc identified and modified in the first stage,thereby producing a new network without circles.The maximum flow of the original looped network can be obtained by solving the maximum flow of the newly generated acyclic network.Finally,an example is provided to demonstrate the validity and feasibility of this algorithm.This algorithm not only improves computational efficiency but also provides new perspectives and tools for solving similar network optimization problems.
基金National Natural Science Foundation of China (61773044,62073009)National key Laboratory of Science and Technology on Reliability and Environmental Engineering(WDZC2019601A301)。
文摘Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.
基金The National Key R&D Program of China under contract No. 2023YFC28 11305the Scientific Research Fund of the Second Institute of Oceanography,MNR under contract No. SZ2405the Impact and Response of Antarctic Seas to Climate Change under contract No. IRASCC
文摘Research on changes in the redox conditions of bottom waters is essential for understanding deep water circulation,global ocean currents,climate change,and ecosystem health.Through sedimentary geological methods,a deeper understanding of the complex relationships between various environmental changes can be achieved,providing detailed evidence and theoretical support for global climate change research.The Ross Sea in Antarctica plays a key role in the formation of Antarctic bottom water(AABW),and the complex climate changes since the last glacial maximum(LGM)make it particularly significant for study.This research analyzes core ANT32-RB16C from the Ross Sea using geochemical proxies such as major and trace elements,grain size,and redox-sensitive indicators like Mn/Ti,Co/Ti,Mo/Ti,Cd/Ti,U/Th,and Ni/Co molar concentration ratios.Combining this data with a previously established chronological framework,the study explores the evolution of redox conditions in the Ross Sea’s deep waters since the LGM.The results show that the deep waters have remained oxygen-rich since the LGM,with significant changes in four stages.Stage 1(24.7–15.7 cal ka BP):Strong oxidizing conditions,likely due to enhanced formation of Ross Sea bottom water(RSBW),increasing oxygen levels.Stage 2(15.7–4.5 cal ka BP):Weakened oxidizing conditions as temperatures rose and ice shelves retreated,increasing primary productivity and depleting oxygen.Stage 3(4.5–1.5 cal ka BP):Continued decline in oxidizing conditions,possibly linked to high primary productivity and oxygen consumption.Stage 4(1.5 cal ka BP to present):A rapid recovery of oxidizing conditions,likely driven by temperature drops,increased RSBW formation,and decreased productivity.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.U2242205 and 42375033)the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(Grant No.2019QZKK0105)+1 种基金the Basic Scientific Research and Operation Foundation of CAMS(2023Z018)the S&T Development Fund of CAMS(Grant No.2023KJ036)。
文摘The annual maximum rainfall event(AMRE)refers to the maximum consecutive five-day rainfall in a year.In North China,these events account for 15%–80%of the total summer(June–August)rainfall amount and pose a great challenge for subseasonal-to-seasonal forecasting.Based on data analyses during 1979–2023,this study shows the interannual variability of AMRE is significantly influenced by the phase and amplitude mode of the annual cycle of the East Asian summer monsoon(EASM),characterized by two orthogonal patterns of southeasterly winds at 850 h Pa over the northwestern Pacific.The EASM phase-locked AMRE shows heavy rainfall events occurring extremely early and late in Beijing and surrounding areas,corresponding to the peak southeasterly wind anomalies in June and August.The EASM amplitude-locked AMRE exhibits extreme heavy or light rainfall over southwest areas with normal phase.Therefore,AMRE has a potential predictability on the seasonal time scale due to its phase-and amplitude-locking with the slow variation of the annual cycle of the EASM.
基金National Natural Science Foundation of China(42275030, U2242206, 41730964)Joint Research Project for Meteorological Capacity Improvement (22NLTSZ002)+4 种基金National Key Research and Development Program (2018YFC1506006)China Meteorological Administration Project for Innovation and Development (CXFZ2022J009, CXFZ2022J031)Key Innovation Team of Climate Prediction of China Meteorological Ministration (CMA2023ZD03)Shandong Provincial Natural Science Foundation (ZR2023QD086)UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund。
文摘This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between the NCEP Climate Forecast System version 2(CFSv2) and a high-resolution Weather Research and Forecasting(WRF) model,using gridded Tmax observation data and ERA5 reanalysis data as benchmarks. The WRF model is driven by CFSv2 multi-member ensemble hindcast and forecast data. Results indicate that the WRF model improves Tmax prediction across China, with particularly significant enhancement over the southern region of the middle and lower reaches of the Yangtze River, although a systematic cold bias remains. By applying bias correction to the daily Tmax simulations from both models, we find that the corrected WRF predictions exhibit marked improvement for both the annual and extended-range Tmax. Furthermore, this study explores the physical mechanisms contributing to the improved predictability in the regional model. The WRF model, with its refined physical parameterization schemes, better simulates middle to lower tropospheric geopotential height fields, as well as surface sensible and latent heat fluxes. These results demonstrate that the dynamical downscaling approach can significantly improve the temperature prediction in southern China, highlighting the potential applicational value of this method for extended-range high-temperature forecasting.
基金supported in part by the National Key Research and Development Program of China(2023YFB3906403)the National Natural Science Foundation of China(62373118,62173105)the Natural Science Foundation of Heilongjiang Province of China(ZD2023F002)
文摘Over the past few decades, numerous adaptive Kalman filters(AKFs) have been proposed. However, achieving online estimation with both high estimation accuracy and fast convergence speed is challenging, especially when both the process noise and measurement noise covariance matrices are relatively inaccurate. Maximum likelihood estimation(MLE) possesses the potential to achieve this goal, since its theoretical accuracy is guaranteed by asymptotic optimality and the convergence speed is fast due to weak dependence on accurate state estimation.Unfortunately, the maximum likelihood cost function is so intricate that the existing MLE methods can only simply ignore all historical measurement information to achieve online estimation,which cannot adequately realize the potential of MLE. In order to design online MLE-based AKFs with high estimation accuracy and fast convergence speed, an online exploratory MLE approach is proposed, based on which a mini-batch coordinate descent noise covariance matrix estimation framework is developed. In this framework, the maximum likelihood cost function is simplified for online estimation with fewer and simpler terms which are selected in a mini-batch and calculated with a backtracking method. This maximum likelihood cost function is sidestepped and solved by exploring possible estimated noise covariance matrices adaptively while the historical measurement information is adequately utilized. Furthermore, four specific algorithms are derived under this framework to meet different practical requirements in terms of convergence speed, estimation accuracy,and calculation load. Abundant simulations and experiments are carried out to verify the validity and superiority of the proposed algorithms as compared with existing state-of-the-art AKFs.
基金Supported by the National Science Foundation of China(11901236,12261036)Scientific Research Fund of Hunan Provincial Education Department(21A0328)+2 种基金Provincial Natural Science Foundation of Hunan(2022JJ30469)Young Core Teacher Foundation of Hunan Province([2020]43)Provincial Postgraduate Innovation Foundation of Hunan(CX20221113)。
文摘Weighted exponential distribution W ED(α,λ)with shape parameterαand scale parameterλpossesses some good properties and can be used as a good fit to survival time data compared to other distributions such as gamma,Weibull,or generalized exponential distribution.In this article,we proved the existence and uniqueness of the maximum likelihood estimator(MLE)of the parameters of W ED(α,λ)in simple random sampling(SRS)and provided explicit expressions for the Fisher information number in SRS.Moreover,we also proved the existence and uniqueness of the MLE of the parameters of W ED(α,λ)in ranked set sampling(RSS)and provided explicit expressions for the Fisher information number in RSS.Simulation studies show that these MLEs in RSS can be real competitors for those in SRS.
基金Supported by the Ministry of Science and Technology of the People’s Republic of China(No.2019 YFE 0125000)the National Natural Science Foundation of China-Shandong Joint Fund(No.U 1906215)+1 种基金the National Natural Science Foundation of China(No.41406010)partially by the Key Laboratory of Coastal Environmental Processes and Ecological Remediation,Chinese Academy of Sciences Opening Fund(No.2020 KFJJ 04)。
文摘As a frequently-observed phenomenon in the northern South China Sea(nSCS),subsurface chlorophyll maximum(SCM)evolution from summer to winter remains unclear,neither the associated hydrographic control.In this study,on the basis of in-situ data of fall-season cruises in 2004–2006,we characterized the depth,thickness and intensity of the SCM in the nSCS using a general Gaussian-function fitting approach,and investigated a linkage to the corresponding ocean vertical buoyance properties.Our results show that the SCM becomes deeper,thicker and less intense offshore-wards in the nSCS during fall seasons.In parallel,a correlation between the SCM variation and mixed layer depth exists in the nSCS,and it becomes pronounced in the shelf region compared to the slope and basin areas in autumn.Physically,once warmer surface ocean and thus stronger thermo-determined stratification,the SCM layer goes deeper and becomes thicker and less intense in the nSCS,especially in the shelf area of the nSCS.Moreover,the impact of water temperatures at deeper layers on the vertical stratification exerts more consequent roles on the spatial variability of SCM,compared to surface temperatures in the nSCS.Specifically,the isotherm line of 22℃ acts as crucial indicator for variations of the SCM in the nSCS during autumns.
基金supported by the 2022 Sanya Science and Technology Innovation Project,China(No.2022KJCX03)the Sanya Science and Education Innovation Park,Wuhan University of Technology,China(Grant No.2022KF0028)the Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City,China(Grant No.2021JJLH0036).
文摘This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.
基金supported by the National Natural Science Foundation of China(Grant Nos.62371069,62372048,and 62272056)BUPT Excellent Ph.D.Students Foundation(Grant No.CX2023123)。
文摘The quantum alternating operator ansatz algorithm(QAOA+)is widely used for constrained combinatorial optimization problems(CCOPs)due to its ability to construct feasible solution spaces.In this paper,we propose a progressive quantum algorithm(PQA)to reduce qubit requirements for QAOA+in solving the maximum independent set(MIS)problem.PQA iteratively constructs a subgraph likely to include the MIS solution of the original graph and solves the problem on it to approximate the global solution.Specifically,PQA starts with a small-scale subgraph and progressively expands its graph size utilizing heuristic expansion strategies.After each expansion,PQA solves the MIS problem on the newly generated subgraph using QAOA+.In each run,PQA repeats the expansion and solving process until a predefined stopping condition is reached.Simulation results show that PQA achieves an approximation ratio of 0.95 using only 5.57%(2.17%)of the qubits and 17.59%(6.43%)of the runtime compared with directly solving the original problem with QAOA+on Erd?s-Rényi(3-regular)graphs,highlighting the efficiency and scalability of PQA.
文摘In the multilevel thresholding segmentation of the image, the classification number is always given by the supervisor. To solve this problem, a fast multilevel thresholding algorithm considering both the threshold value and the classification number is proposed based on the maximum entropy, and the self-adaptive criterion of the classification number is given. The algorithm can obtain thresholds and automatically decide the classification number. Experimental results show that the algorithm is effective.
文摘In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenomena is considered. Based on the theory of fuzzy recognition and fault diagnosis, this method only depends on experience and statistical data to set up fuzzy query relationship between the outside phenomena (fault characters) and the fault sources (fault patterns). From this relationship the most probable fault sources can be obtained, to attain the goal of quick diagnosis. Based on the above approach, the standard fuzzy relationship matrix is stored in the computer as a system database. And experiment data are given to show the fault diagnosis results. The important parameters can be on line sampled and analyzed, and when faults occur, faults can be found, the alarm is given and the controller output is regulated.
