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State identification of home appliance with transient features in residential buildings

Frontiers in Energy 2022, Volume 16, Issue 1,   Pages 130-143 doi: 10.1007/s11708-022-0822-z

Abstract: The states of the working appliances are identified from aggregated power signals using the Kalman filtering

Keywords： nonintrusive load monitoring (NILM)     load disaggregation     online load disaggregation     Kalman filtering    

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ApproximateGaussian conjugacy: parametric recursive filtering under nonlinearity,multimodality, uncertainty Review

Tian-cheng LI, Jin-ya SU, Wei LIU, Juan M. CORCHADO

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 12,   Pages 1913-1939 doi: 10.1631/FITEE.1700379

Abstract: Kalman in the 1960s, considerable efforts have been devoted to time series state space models for a large

Keywords： Kalman filter     Gaussian filter     Time series estimation     Bayesian filtering     Nonlinear filtering     Constrainedfiltering     Gaussian mixture     Maneuver     Unknown inputs    

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A novel multiple-outlier-robust Kalman filter Research Articles

Yulong HUANG, Mingming BAI, Yonggang ZHANG,heuedu@163.com,mingming.bai@hrbeu.edu.cn,zhangyg@hrbeu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 3,   Pages 422-437 doi: 10.1631/FITEE.2000642

Abstract: This paper presents a novel multiple-outlier-robust Kalman filter (MORKF) for linear stochastic discrete-time

Keywords： Kalman filtering     Multiple statistical similarity measure     Multiple outliers     Fixed-point iteration    

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Convergence analysis of distributed Kalman filtering for relative sensing networks Research

Che LIN, Rong-hao ZHENG, Gang-feng YAN, Shi-yuan LU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 9,   Pages 1063-1075 doi: 10.1631/FITEE.1700066

Abstract:

We study the distributed Kalman filtering problem in relative sensing networks with rigorous analysisinformation and measurement communication, we design a novel distributed suboptimal estimator based on the Kalmanfiltering technique for comparison with a centralized optimal estimator.

Keywords： Relative sensing network     Distributed Kalman filter     Schur stable     Linear matrix inequality    

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Studies on Precise Spacecraft Navigation and Positioning Using GPS

Xiang Kaiheng,Qu Guangji

Strategic Study of CAE 2004, Volume 6, Issue 1,   Pages 86-91

Abstract: paper, GPS measurement technology, Encke method to solve satellite orbit perturbation and generalized Kalmanfiltering technology are organically combined together, and an innovative solution— carrier phase

Keywords： spacecraft     navigation     GPS     carrier phase     Kalman filtering    

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Tacholess order-tracking approach for wind turbine gearbox fault detection

Yi WANG, Yong XIE, Guanghua XU, Sicong ZHANG, Chenggang HOU

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 3,   Pages 427-439 doi: 10.1007/s11465-017-0452-z

Abstract:

Monitoring of wind turbines under variable-speed operating conditions has become an important issue in recent years. The gearbox of a wind turbine is the most important transmission unit; it generally exhibits complex vibration signatures due to random variations in operating conditions. Spectral analysis is one of the main approaches in vibration signal processing. However, spectral analysis is based on a stationary assumption and thus inapplicable to the fault diagnosis of wind turbines under variable-speed operating conditions. This constraint limits the application of spectral analysis to wind turbine diagnosis in industrial applications. Although order-tracking methods have been proposed for wind turbine fault detection in recent years, current methods are only applicable to cases in which the instantaneous shaft phase is available. For wind turbines with limited structural spaces, collecting phase signals with tachometers or encoders is difficult. In this study, a tacholess order-tracking method for wind turbines is proposed to overcome the limitations of traditional techniques. The proposed method extracts the instantaneous phase from the vibration signal, resamples the signal at equiangular increments, and calculates the order spectrum for wind turbine fault identification. The effectiveness of the proposed method is experimentally validated with the vibration signals of wind turbines.

Keywords： wind turbine     variable-speed operating conditions     Vold-Kalman filtering     tacholess order tracking    

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Filtering and tracking with trinion-valued adaptive algorithms Article

Xiao-ming GOU,Zhi-wen LIU,Wei LIU,You-gen XU

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 8,   Pages 834-840 doi: 10.1631/FITEE.1601164

Abstract: computationally more efficient, while having similar or comparable performance in terms of adaptive linear filteringMoreover, the trinion model can effectively represent the general relationship of state evolution in Kalmanfiltering, where the pure quaternion model fails.

Keywords： Three-dimensional processes     Trinion     Least mean squares     Kalman filter    

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Sensorless direct torque control for salient-pole PMSM based on extended Kalman filter fed by AC/DC/AC

F. BENCHABANE, A. TITAOUINE, O. BENNIS, K. YAHIA, D. TAIBI, A. GUETTAF

Frontiers in Energy 2012, Volume 6, Issue 3,   Pages 247-254 doi: 10.1007/s11708-012-0190-1

Abstract: paper, a new sensorless interior permanent magnet synchronous motor (IPMSM) drives method with extended KalmanThe Kalman filter is an observer for linear and non-linear systems and is based on the stochastic intromission

Keywords： direct torque control (DTC)     sensorless control     extended Kalman filter (EKF)     permanent magnet synchronous    

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基于ARIMA和Kalman滤波的道路交通状态实时预测 Article

东伟 徐,永东 王,利民 贾,勇 秦,宏辉 董

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 2,   Pages 287-302 doi: 10.1631/FITEE.1500381

Abstract: 本文提出了一种基于ARIMA模型和Kalman滤波算法的道路交通流预测方法。首先，基于道路交通历史数据建立时间序列的ARIMA模型。其次，结合ARIMA模型和Kalman滤波法构建道路交通预测算法，获取Kalman滤波的测量方程和更新方程。然后，基于历史道路交通数据进行算法的参数设定。实验结果表明，基于ARIMA模型和Kalman滤波的实时道路交通状态预测方法是可行的，并且可以获得很高的精度。

Keywords： ARIMA模型；Kalman滤波；建模；训练；预测    

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Ion beam figuring of continuous phase plates based on the frequency filtering process

Mingjin XU,Yifan DAI,Xuhui XIE,Lin ZHOU,Shengyi LI,Wenqiang PENG

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 1,   Pages 110-115 doi: 10.1007/s11465-017-0430-5

Abstract: This study proposes a multi-pass IBF approach with different beam diameters based on the frequency filteringWe present the selection principle of the frequency filtering method, which incorporates different removalA high-precision surface can be obtained as long as the filtering frequency is suitably selected.

Keywords： beam figuring (IBF)     continuous phase plates (CPPs)     machining accuracy     machining efficiency     frequency filtering    

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Filtering antennas: from innovative concepts to industrial applications Review Articles

Yun-fei CAO, Yao ZHANG, Xiu-yin ZHANG

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 1,   Pages 116-127 doi: 10.1631/FITEE.1900474

Abstract: A filtering antenna is a device with both filtering and radiating capabilities.The filtering antenna designs include single- and dual-polarized filtering patch antennas, a single-polarizedomni-directional filtering dipole antenna, and a dual-polarized filtering dipole antenna for the baseThe filtering antennas in this paper feature an innovative concept of eliminating extra filtering circuitsFor each design, the filtering structure is finely integrated with the radiators or feeding lines.

Keywords： Filtering antenna     Dual-band     Antenna array    

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A filtering-based bridge weigh-in-motion system on a continuous multi-girder bridge considering the influence

Hanli WU, Hua ZHAO, Jenny LIU, Zhentao HU

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 5,   Pages 1232-1246 doi: 10.1007/s11709-020-0653-0

Abstract: A real-time vehicle monitoring is crucial for effective bridge maintenance and traffic management because overloaded vehicles can cause damage to bridges, and in some extreme cases, it will directly lead to a bridge failure. Bridge weigh-in-motion (BWIM) system as a high performance and cost-effective technology has been extensively used to monitor vehicle speed and weight on highways. However, the dynamic effect and data noise may have an adverse impact on the bridge responses during and immediately following the vehicles pass the bridge. The fast Fourier transform (FFT) method, which can significantly purify the collected structural responses (dynamic strains) received from sensors or transducers, was used in axle counting, detection, and axle weighing technology in this study. To further improve the accuracy of the BWIM system, the field-calibrated influence lines (ILs) of a continuous multi-girder bridge were regarded as a reference to identify the vehicle weight based on the modified Moses algorithm and the least squares method. experimental results indicated that the signals treated with FFT filter were far better than the original ones, the efficiency and the accuracy of axle detection were significantly improved by introducing the FFT method to the BWIM system. Moreover, the lateral load distribution effect on bridges should be considered by using the calculated average ILs of the specific lane individually for vehicle weight calculation of this lane.

Keywords： bridge weigh-in-motion     continuous bridge     fast Fourier transform     influence line     axle weight calculation    

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Resampling methods for particle filtering: identical distribution, a new method, and comparable study

Tian-cheng LI,Gabriel VILLARRUBIA,Shu-dong SUN,Juan M. CORCHADO,Javier BAJO

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 11,   Pages 969-984 doi: 10.1631/FITEE.1500199

Abstract: Resampling is a critical procedure that is of both theoretical and practical significance for efficient implementation of the particle filter. To gain an insight of the resampling process and the filter, this paper contributes in three further respects as a sequel to the tutorial (Li et al., 2015). First, identical distribution (ID) is established as a general principle for the resampling design, which requires the distribution of particles before and after resampling to be statistically identical. Three consistent metrics including the (symmetrical) Kullback-Leibler divergence, Kolmogorov-Smirnov statistic, and the sampling variance are introduced for assessment of the ID attribute of resampling, and a corresponding, qualitative ID analysis of representative resampling methods is given. Second, a novel resampling scheme that obtains the optimal ID attribute in the sense of minimum sampling variance is proposed. Third, more than a dozen typical resampling methods are compared via simulations in terms of sample size variation, sampling variance, computing speed, and estimation accuracy. These form a more comprehensive understanding of the algorithm, providing solid guidelines for either selection of existing resampling methods or new implementations.

Keywords： Particle filter     Resampling     Kullback-Leibler divergence     Kolmogorov-Smirnov statistic    

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Performance analysis of two EM-based measurement bias estimation processes for tracking systems None

Zhi-hua LU, Meng-yao ZHU, Qing-wei YE, Yu ZHOU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 9,   Pages 1151-1165 doi: 10.1631/FITEE.1800214

Abstract: With the assistance of extended Kalman filtering and smoothing, we derive two EM estimation processes

Keywords： Non-linear state-space model     Measurement bias     Extended Kalman filter     Extended Kalman smoothing     Expectation-maximization    

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Efficientmesh denoising via robust normal filtering and alternate vertex updating Article

Tao LI, Jun WANG, Hao LIU, Li-gang LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1828-1842 doi: 10.1631/FITEE.1601229

Abstract: The most challenging problem in mesh denoising is to distinguish features from noise. Based on the robust guided normal estimation and alternate vertex updating strategy, we investigate a new feature-preserving mesh denoising method. To accurately capture local structures around features, we propose a corner-aware neighborhood (CAN) scheme. By combining both overall normal distribution of all faces in a CAN and individual normal influence of the interested face, we give a new consistency measuring method, which greatly improves the reliability of the estimated guided normals. As the noise level lowers, we take as guidance the previous filtered normals, which coincides with the emerging rolling guidance idea. In the vertex updating process, we classify vertices according to filtered normals at each iteration and reposition vertices of distinct types alternately with individual regularization constraints. Experiments on a variety of synthetic and real data indicate that our method adapts to various noise, both Gaussian and impulsive, no matter in the normal direction or in a random direction, with few triangles flipped.

Keywords： Mesh denoising     Guided normal filtering     Alternate vertex updating     Corner-aware neighborhoods    

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Title Author Date Type Operation

State identification of home appliance with transient features in residential buildings

Journal Article

ApproximateGaussian conjugacy: parametric recursive filtering under nonlinearity,multimodality, uncertainty

Tian-cheng LI, Jin-ya SU, Wei LIU, Juan M. CORCHADO

Journal Article

A novel multiple-outlier-robust Kalman filter

Yulong HUANG, Mingming BAI, Yonggang ZHANG,heuedu@163.com,mingming.bai@hrbeu.edu.cn,zhangyg@hrbeu.edu.cn

Journal Article

Convergence analysis of distributed Kalman filtering for relative sensing networks

Che LIN, Rong-hao ZHENG, Gang-feng YAN, Shi-yuan LU

Journal Article

Studies on Precise Spacecraft Navigation and Positioning Using GPS

Xiang Kaiheng,Qu Guangji

Journal Article

Tacholess order-tracking approach for wind turbine gearbox fault detection

Yi WANG, Yong XIE, Guanghua XU, Sicong ZHANG, Chenggang HOU

Journal Article

Filtering and tracking with trinion-valued adaptive algorithms

Xiao-ming GOU,Zhi-wen LIU,Wei LIU,You-gen XU

Journal Article

Sensorless direct torque control for salient-pole PMSM based on extended Kalman filter fed by AC/DC/AC

F. BENCHABANE, A. TITAOUINE, O. BENNIS, K. YAHIA, D. TAIBI, A. GUETTAF

Journal Article

基于ARIMA和Kalman滤波的道路交通状态实时预测

东伟 徐,永东 王,利民 贾,勇 秦,宏辉 董

Journal Article

Ion beam figuring of continuous phase plates based on the frequency filtering process

Mingjin XU,Yifan DAI,Xuhui XIE,Lin ZHOU,Shengyi LI,Wenqiang PENG

Journal Article

Filtering antennas: from innovative concepts to industrial applications

Yun-fei CAO, Yao ZHANG, Xiu-yin ZHANG

Journal Article

A filtering-based bridge weigh-in-motion system on a continuous multi-girder bridge considering the influence

Hanli WU, Hua ZHAO, Jenny LIU, Zhentao HU

Journal Article

Resampling methods for particle filtering: identical distribution, a new method, and comparable study

Tian-cheng LI,Gabriel VILLARRUBIA,Shu-dong SUN,Juan M. CORCHADO,Javier BAJO

Journal Article

Performance analysis of two EM-based measurement bias estimation processes for tracking systems

Zhi-hua LU, Meng-yao ZHU, Qing-wei YE, Yu ZHOU

Journal Article

Efficientmesh denoising via robust normal filtering and alternate vertex updating

Tao LI, Jun WANG, Hao LIU, Li-gang LIU

Journal Article