Applied Mechanics and Materials Vols. 373-375

Abstract: For the multi-sensor descriptor system with correlated measurement noises and same measurement matrix, the reduced-order sub-systems are obtained, applying singular value decomposition method. And measurements of every sensor are transformed to the measurement of one state component. For this new reduced-order normal system, the new fused measurement can be obtained applying the weighted least squares method. Then, the weighted measurement fusion Kalman filter and its filtering error variance are presented, applying a single Kalman filter. This method avoids computing the cross-variances among all local filters, compared with the state fusion Kalman filtering algorithm. And the accuracy of this fused filter is higher than that of local filter and state fusion Kalman filter. A simulation example verifies its effectiveness.

Abstract: For multisensor system with colored measurement noises, the common disturbance noises and measurement biases, the batch covariance intersection fusion (BCI) Kalman filter and the sequential covariance intersection fusion (SCI) Kalman filter are presented, which can avoid the computation of the local filtering errors and reduce the computational burden significantly. Under the linear unbiased minimum variance (ULMV) criterion, the three weighted fusion Kalman filters (weighted by matrices, scalars or diagonal matrices) are also presented. Their accuracy relations are analyzed and compared. Specially, the accuracy of the proposed covariance intersection fusion Kalman filters are higher than that of each local Kalman filters, and is lower than that of optimal fuser weighted by matrices. The geometric interpretation of the accuracy relations is given by the covariance ellipses. A Monte-Carlo simulation example for a tracking system verifies the correctness of the theoretical accuracy relations.

Abstract: It is a big problem how to finish intraoperative functional localization precisely, rapidly and no-invasively during neurosurgery operations. Previous researchs shown that the SCP (slow cortical potential) is a specific ECoG (electrocorticography) rhythm in the cortical motor areas. A real limb movement induced ERP(event-related potential) of SCP in the motor cortex. In this study, based on ERP of SCP phenomenon, wavelet analysis and SVM (support vector machine) were used to extract and classify the ERP of SCP feature, an algorithms for classification of the ERP in the motor regions utilizing experimental data was designed and verified. Then the results of classification were used to mapping the boundary curve of motor cortex functional areas. Results demonstrated that the accuracy of localization detection was 93.75% , the degree of accuracy was less than 5 mm, with an operation time of 2 minutes, avoiding the problems of cerebral cortex injury and epilepsy onset. The cerebral motor cortex functional localization based on SCP in ECoG detecting technique is accurate, safe and rapid.

Abstract: there is a novel data transfer integration system by using single image proposed in this paper. There are many sensors use to monitoring the landslide occurred or not, but the monitoring results have different transmit protocol such as: Wi-Fi, transmit line, 2.4 GHz and ZigBee. This system is a data transfer integration system for all sensors, and it can achieve a real time monitoring system. The system integrate many sensor signals to microprocessor, and convert analog signal to digital signal by using A/D converter, i2c and UART, and the measuring results of sensors and display on a 8*8 matrix LED board. The system use the existing landslide-monitoring camera, and the matrix LED board install in the monitoring area. The result of sensors can be transmit to monitoring center by using single image, the data will not affect by environment, weather and mountain terrains.

Abstract: In this study, Kolmogorov complexity (KC) and approximate Entropy (AE) were adopted to characterize the irregularity and complexity of EEG data. Fifty subjects were instructed to perform two different mental tasks to induce two kinds of fatigue states. Then the Kernel Principal Component Analysis (KPCA) and Support Vector Machine (SVM) are combined to differentiate these two states. The KPCA was used to extract nonlinear features from the complexity parameters of EEG and to effectively reduce the dimensionality of the feature vectors. SVM was used to classify two fatigue states. The experimental result shows that complexity parameters are significantly decreased as the fatigue level increases, which suggests that the proposed parameters can be used to characterize mental fatigue level. Furthermore, compared with several typical classification models, the joint method KPCA-SVM can achieve higher classification accuracy (85%) of mental fatigue with less training and classifying time, which indicates that KPCA-SVM is suitable for the estimation of mental fatigue.

Abstract: One of the most important ways to enhance the speed of state estimation is to establish the constant matrix Jacobian. This essay puts forward the state estimation method of the equivalent current transformation based on the Generalized Tellegens Theorem. This estimation method establishes the constant Jacobian matrix without neglecting the secondary factor making use of the Generalized Tellegens Theorem, solves the numerical stability problem caused by the establishment of the constant Jacobian matrix in the current state estimation, and has the advantages of a relatively rapid computing rate, making advantage of measuremnt of WAMS and SCADA system, and an unparalleled astringency. The method put forward in this essay has been verified through IEEE-30 Node System, and the efficiency of it has been fully proved by the example results.

Abstract: This template carries out a three-terminal accurate fault location method for distribute cable network. It is improved from type D principle fault location method. Radial distribution network is decomposed into T-type networks. A set of formulas based on three-terminal data can calculate fault distance and find fault branch. Only first transient wave heads is needed. Shorter transmission distance makes it more accurate to extract first wave heads with wavelet. The distributed measurement offers redundant transient voltage data. These data is fully used to improve location success rate and accuracy. The simulation result in ATP-EMTP shows that the location accuracy isnt influenced by wave speed, catadioptric wave, grounding resistance and initial fault phase angle.

Abstract: Microwave cavity with complicated structure and rubidium gas is studied by mode matching method. By calculating resonant frequencies of HE₁₁₁ mode under different parameters, main factors that influence resonant frequency is studied. In addition, the resonant frequency of HE₁₁₁ mode is compared with commercial software (CST) results. The computed results show good agreement with CST simulations. It can be seen that this method is of high credibility and efficiency. This paper is of great significance for cavity design and theoretical perfection.

Abstract: This paper introduces an on-line monitoring system for partial discharge of 10kV cable joint based on LabVIEW. It calculates transfer characteristic of wideband current transformer for monitoring partial discharge current after analyzing the mechanism of production of partial discharge. The proposed current transformer can restrain the noise signal efficiently in electromagnetic induction part. Since the on-line monitoring system was installed in transformer substation, the LabVIEW monitoring platform can keep a lookout over partial discharge current of cable joint constantly. It can monitor the cable joint accurately.

Abstract: This paper arrives at a method of harmonic and reactive current real-time detection applied on active power filter based on the three-phase circuit instantaneous reactive power theory. With Matlab simulation software, a research on simulation of harmonic detection means is carried out, and an analysis of the simulation result is presented. The result indicates: the harmonic detection means based on instantaneous reactive power theory can detect harmonic and reactive component in three-phase current precisely and real-time, to supply reliable harmonic and reactive current for harmonic restraint and reactive power compensation. It could provide reliable indicator parameters for research and development of active power filter.