Abstract:The information of image, voice, and text (language), which is closely related to the human perception of visual and auditory, plays an important role in socioeconomic development and country security assurance. Braincomputer interface (BCI) is an innovative technology that directly controls peripheral equipment and makes ‘thought’ into ‘action’ with nonmuscular methods. Visual and auditory stimuli based BCI system has extremely broad application prospects. It is commonly believed that brain has stronger eventrelated potential, higher reaction accuracy and faster reaction speed on visualauditory crossmodal stimuli (VACS) than single modal stimuli (visual or auditory) in current cognitive psychology researches, while BCI researches have difficulty on the verification of the VACS superiority. In this paper, the VACS researches in cognitive psychology and BCI paradigms were reviewed respectively, which included the information integration mechanism of VACS, the facilitation and competition relationship between visual stimuli and auditory stimuli in VACS system, the influence of congruence and the research status of VACS based BCI paradigms. Also, the reasons for not showing the superiority of VACS in BCI system were discussed. Then, the countermeasure of defusing the difficulties were presented from aspects of the selection of BCI paradigms, the performance improvement of system hardware, the signal processing of electroencephalography(EEG) and so on. In the end, the future trends of VACS based BCI research were presented.

Abstract:The systematic design around the key technology of hightemperature complex permittivity measurement of microwave medium is presented. Dielectric property test at variable temperature is realized by the exact field theory solution. A TM010 mode cylindrical resonant cavity is designed and variabletemperature test system is constructed by using rapid specimen movement platform and induction heating technology. The system can realize the complex permittivity test automatically at 915 MHz and up to 1 400 ℃.For the influence caused by the heating of the test system, the realtime calibration technology is presented to reduce the error from the fluctuation of dielectric property of the fixture. The repeated variabletemperature measurements of the complex permittivity of fused quartz sample are done, and the test data is compared with published data. The results indicate that the test deviations of permittivity and loss tangent at high temperature is less than 2% and 6% respectively.

Abstract:Based on the principle of prestress release and strain measurement of the fiber Bragg grating (FBG), an optical fiber grating sensor for monitoring the corrosion of underwater reinforcing steel was proposed in this paper. As the core component of the sensor, FBG1 was prestretched and tightly wound on the surface of the finely fabricated reinforcing bar for monitoring the prestressing relaxation caused by the loss of corrosion products, and FBG2 was installed in the axial throughhole of the reinforcing bar for eliminating the crosssensitivity of FBG1. In order to improve the survival rate of the sensors, the sensors were embedded into mortar specimens, and the evaluation formula to evaluate mass loss rate of steel rebar was derived.Theperformance of the sensor wasresearched inadesignedelectrochemicalcorrosionaccelerationexperiment, and the corrosion degree could be measured by detecting the wavelength of FBG.By the central wavelength, the corrosion degree of reinforcing steel would be monitored. The experimental results show that the sensor can beusedtomonitor the steelrebar corrosion ofunderwater reinforced concretestructure with large monitoring range, has high sensitivity and good stability. The sensor can be employed to monitor the steel bar corrosion in reinforced concrete structure, such as harbor and pier, bridge pier, dam, reservoir and so on.

Abstract:A chipless humidity sensor integrated with RFID is presented in the paper. The slot scatterer structure is fabricated on the copperclad FR4 by grooving etching. The encoding unit stores the ID information by the combination of the different length slots. To make a scatterer sensitive to the humidity on the premise of low cost, the silicon nanowires are deposited on the surface of sensing unit without any posttreatment process. Based on the principle of radar electromagnetic backscattering, two horn antennas with cross polarization are utilized as the transmitting and receiving antennas so that to measure the transmission coefficient curve. The experiment results show that a stable linear relationship between the center resonant frequency and the relative humidity in the frequency band of 215 MHz is appeared at the temperature of 25 ℃ and the range of 30％~90％RH, the sensitivity of the sensor exceeds 2.9 MHz/% RH.

Abstract:During liquidsolid twophase flow erosion wear, part kinetic energy of solid particle convert into heat energy,it makes temperature of flow component and slurry rise, erosion wear and friction heat accelerate the corrosion rate and the wear rate of flow components material, they speed up the damage of flow component.Under the condition of high speed erosion wear, the friction heat effect should be attracted more attentions.In this paper, a rotary erosion wear test apparatus with temperature measurement system is selfdesigned and developed to carry out realtime measurement of sample temperature during liquidsolid twophase flow erosion wear test. Three holes were machined near the surface, center, and near the back of the sample for erosion wear test, three thermocouples were inserted and connected to the temperature sensor as well as computer through the wires, thus it can online measure and draw temperature curve of different parts of the sample in the process of erosion wear test. The apparatus has many advantages such as simple structure, convenient operation, stable and reliable data, and good visual features. This device can simulate erosion wear working conditions of wet metallurgy, chemical, mining, hydropower and so on, especially measurement and analysis on generation and transfer of sample friction heat as well as its influence on erosion wear characteristics.

Abstract:A new fault diagnosis method based on the variational mode decomposition and permutation entropy (VMDPE) is proposed to deal with the problem of the loss of signal feature and not reflecting the essential feature of the signal with the fault signal analysis methods of the transmission line of power system. Taking the transmission line of singlephase grounding fault as an example, the IEEE 14 nodes standard test system is selected. Taking the singlephase grounding fault current as the fault signal, each phase fault signal is firstly decomposed with VMD. And then, the decomposed fault signal is analyzed with PE. At last, according the total PE value of each phase fault signal, the transmission lines fault is identified, and the comparison with the wavelet transform and the PE is carried out. The results show that the proposed algorithm can effectively diagnose the fault of transmission line and be accurate and reliable for transmission line fault diagnosis.

Abstract:The problem of applying the wireless charging equipment (WCE) for charging the sensor periodically is investigated in this paper, in which the charging energy and the traveling energy of the WCE are assumed limited. For each charging period, the total consumed energy of the WCE for charging and travelling is minimized when maximizing the charging period. In this way, the wireless recharging sensors network (WRSNs) can work permanently by using the minimum energy of the WCE. The optimization model of minimizing the energy of WCE is built based on analyzing the energy constraint of sensor nodes and the charging and travelling constraints of WCE. The charging problem is a NPComplete problem in this paper. Combining with the optimization model, the chaotic particle swarm optimization algorithm (CPSO) is applied to solving this optimization problem for getting the charging route of WCE and charging time of sensor node. Furthermore, six simulation scenes of WRSNs which are consisted of two kinds of data routing and three kinds of nodes distribution are designed. The convergence rates of CPSO is double the convergence rates of genetic algorithm (GA) at least.

Abstract:Aiming at the problems that the eigenvalues of independent component analysis(ICA) are approximately equal and the representative variables cannot be extracted effectively after dimensionless standardization processing, a fault detection method based on relativetransformation ICA (RTICA) is proposed. The method introduces the relativetransformation based on Euclidean distance. Firstly, the RTICA approach transfers the original data space into relative space by computing the Euclidean distance. Secondly, ICA approach is used to reduce the dimensions of the data in the relative space, extract the independent PCs possess greater adaptability, build the fault detection model and implement online fault detection. The proposed method has been applied to Tennessee Eastman (TE) and the fault simulation experiment in electric spindle system. The results show that the method can effectively reduce the number of independent principal components, simplify the complexity of fault detection model, and enhance the performance of state detection.

Abstract:Delay tolerant networks (DTN) often use the copies of message to improve the success rate of message transmission. It can deduce the flooding of the messages in the network. So, the copies of message need to be limited. A social activity and copylimited based DTN routing algorithm (SACRA) is proposed. The algorithm defines the social activity based on the historical track and the movement characteristic of adjacent nodes. According to the social activity and the size of the unused buffer, the number of message copies and the exchange type of its carrying messages are distributed in a reasonable way. The message can be diffused across the network and carried to its destination node quickly. The simulation results show that SACRA can reduce the network load effectively while retain the message delivery ratio well. When the time is 1 000 s, the success rate is above 50%, and thus the network overhead is reduced and the success ratio of the message delivery is increased compared with other typical routing algorithms.

Abstract:The complexity and diversity of the texture of the surface defects on the surface of strip steel, as well as the false defects in the background texture, have brought great difficulties to the feature extraction and recognition of the strip steel surface defects. Therefore, this paper presents a new method for the selection and identification of steel strip surface defects. First of all, through the inhibition of anisotropic diffusion algorithm for suppression of false defect on strip surface; secondly, selection of surface defect features using PRelief method in this paper, compared with the traditional Relief method, this method considers the different dimensions of feature correlation. Finally, using the feature set and SVM kernel classifier to classify and recognize the surface defects of steel strip. The experimental results show that the proposed method can extract the features of strip surface defect pairwise independence and robustness, and for scratches, bumps and folds, stains and other different types of defects, this method compared with the traditional method can get higher recognition rate.

Abstract:The process of welding has strong repeatability for the welding of the same parts and the same welding track. A tracking control method for gas tungsten arc welding (GTAW) process based on iterative learning control is proposed. An iterative learning control algorithm for the control of GTAW process is designed based on the dynamic process model of welding. And the convergence of the algorithm is proved. The results of research show that the repeated information of welding can be effectively used by the iterative learning control in the process of welding. After about 60 times of iteration learning, the output of welding system can better track on the desired trajectory to meet the expected control effect. It verifies the effectiveness of the proposed method. The better tracking performance can be acquired by ILC in contrast to PID algorithm and it also can suppress the effect of repetitive external disturbances.

Abstract:The image feature is an important branch of texture feature, which reflects the different images and object shape, size, distribution, direction, and other important parameters and plays a decisive factor on image characteristics recognition. But the texture feature extraction process is very complex and time cost. In order to solve the problem, a new method to extract texture feature based on FPGA is implemented. First, the texture feature extraction method is optimized with parallel algorithm, then the error is analyzed and controlled based on numerical range and representation accuracy, so the method can operate on FPGA efficiently. Also, a method to improve the data stream transmission on FPGA is designed, which employs pipeline optimization on main modules and register allocation model. The system on FPGA can modify parameters online to adapt for different environmental variables, such as image size, convolution kernel and so on. The results show that the proposed model extracts image texture feature up to ten times faster than CPU under the same power consumption, and it is an ideal system to fast extract image texture feature based on FPGA.

Abstract:In order to identify wheat unsound kernel by hyperspectral image processing technology quickly and accurately, a detection method was researched based on spectral and image feature of wheat unsound kernel combined with multiclassification support vector machine. The hyperspectral images of wheat unsound kernels were collected and processed by image enhancement and threshold segmentation, which were used to extract 7 texture features and 5 morphological features as input to the classifier. The identification accuracy of model was established by multiclass support vector machine and then compared with different feature combination (spectral features, image features, spectral and image feature). The total identification rate of the 4 classification models based on spectral features was 94.73%, and the identification rate of black germ kernel and sound kernel was 100% and 98.63% respectively, but the identification rate of insectdamaged kernel and broken kernel were less than 90%. The recognition rate of unsound kernel based on image feature was relative lower. And when the spectral and image features were integrated, the recognition rate of the four class support vector machine model was 97.89%, the recognition rate of insectdamaged kernel was increased from 89.79% to 95.91%, and the recognition rate of broken kernel was increased from 84% to 94%. The results show that the hyperspectral image can quickly and nondestructively identify the unsound kernel of single grain wheat, which has potential application on rapid, highthrough and nondestructive detection of wheat seed quality.

Abstract:An electronic tongue system based on virtual instrument technology was developed and used todistinguish andanalyze 4 kinds of Chinese patent medicines in the treatment of cold symptom. The respond signal of electronic tongue was first preprocessed by the feature point extraction (FPE)method and discrete wavelet transform (DWT)method, respectively. According to clustered property and classification results of sample points, the DWT applied “db4”as mother wavelet and decomposed 8 levels was selected as a recommended feature extraction method.The principal component analysis(PCA),cluster analysis (CA)and back propagation neural network (BPNN) were then used to distinguish and identify the 4 kinds of Chinese patent medicines.The results showed that the cumulative contribution rate of PC1 and PC2 was reached 95.6% when PCA was employed.All medicines were effectively distinguished except that Lingyang cold tablet and Yinqiao antidotal tablet had an overlapping trend. The CA could obviously observe the dissimilarity of the 4 kinds of Chinese patent medicines, but the classification result of CA was so poor that 4 kinds of medicines were classified into 2 groups, while nonlinear model BPNNexhibited a better result than other classification model. The parameters of BPNN such as the training algorithm, the activation function and the number of hidden layer nodes were optimized and determined for improving the model performance. The validation set results indicate that all samples are perfectly discriminated by BPNN with the correct classification rate reaching 100%. This research can provide a technical reference for the research on nonsensory quality evaluation and identification of Chinese patent medicines.

Abstract:To improve the fall detection accuracy in substation, a human fall detection algorithm based on improved D-S evidence theory was proposed in this paper. Human minimum area external rectangle and vertical external rectangle were used to describe the human and the characteristics of rectangle ratio, centroid height ratio and inclination angle of object region were analyzed. The characteristic conflicts in the complex situations can be resolved by using DS evidence theory to combine the characteristic information. The basic probability assignments of three characteristics were created by using selfdefined generalized triangular fuzzy function. An improved method Dual Weighted Average Evidence (DWAE) based on Murphy algorithm was proposed to merge the different independent evidence effectively. The experimental results show that the proposed method has high detection accuracy by generating BPA reasonably and combining the evidences effectively which can be integrated in the security monitoring system of transformer substation.

Abstract:On the basis of using double terminal traveling wave method to carry out on line detection and location of PD of high voltage cable, the time varying kurtosis method used in the field of seismic signal detection is introduced to solve the problem that the precision of the first break time affects the positioning accuracy. Firstly, the PD events is detected by using the method of time window energy ratio, then the pulse arrival time is preliminary picked up by calculating the time varying kurtosis change rate and the maximum point in determining the discharge time window. In order to overcome the influence of strong noise on picking precision, the main frequency band of partial discharge pulse is separated by wavelet packet, and the timevarying kurtosis maximum is obtained in this frequency band, which ensures that the high precision picking up of the first break time of PD pulse is achieved. Finally, the PD source is located by the method of twoterminal traveling wave. The simulation results show that this method can meet the highvoltage power lines on the PD line fault positioning accuracy requirements and effectively improve the reliability of power supply, not only has high precision and strong antiinterference ability, but also can realize that the error is less than 2 m in -14 dB noise environment.

Abstract:Aiming at the problem that it is difficult to determine the arrival time from the echo signal of the ultrasonic gas flowmeter and the instrument is required to have high realtime, a new signal processing method for ultrasonic gas flowmeter based on peak fitting of rising echo and a method to determine the fitting peak range are proposed. Firstly, according to the fitting peak range, several peak points are selected in the rising section of the echo signal, and they are fitted by the least squares to achieve the feature straight line. The intersection of this line and the Xaxis is regarded as a feature point to determine the arrival time of the echo signal, and then the ultrasonic propagation times are calculated to obtain the gas flow rate. The ultrasonic gas flowmeter is developed to implement the signal processing method based on peak fitting of rising echo. The calibration experiments are preformed to validate the effectiveness of the methods and the meter.

Abstract:Aiming at the fast steering mirror driven by four voice coil actuators, a drive control method was proposed in this paper. The high bandwidth current loop was designed for each motor, and the pushpull motion was realized by changing the current direction and magnitude. In order to improve the system damping and suppress the mechanical resonance, accurate transfer function was identified based on FFT analysis, and then a compensator with a biquad filter was introduced. The test results show that the 20 dB resonance peak is effectively suppressed, -3 dB bandwidth is increased from 118 Hz to 177 Hz, the setting time is reduced from 151 ms to 3.5 ms, the overshoot is reduced from 83.3% to 1.51%. And the dynamic response of the fast steering mirror is improved obviously, which proves the validity of this method.

Abstract:In order to improve the measurement quality of ABS gear detector, according to the measuring principle, the structure feature and the reason of error produced during measuring, the basic factor influencing the measurement accuracy is analyzed in this paper. And an error correction method based on the principle of least square curve fitting and affine transformation of space rectangular coordinate is developed to solve the key problem of error production, which could improve measuring accuracy without affecting mearing speed. At the same time a mathematical model is built according to the measuring principle. The result of simulation by MATLAB7.10 proves that the error correction method is correct and feasible. The calculation proves that the measurement repeatability and uncertainty of ABS gear detector after error correcting is acceptable. It proves that the error correction method can be used into the ABS gear detecting system, and has high practical value.

Abstract:In order to improveultrasonic testing capability on austenitic stainless steel weld, ultrasonic propagation characters and related ultrasonic time of flight diffraction method (TOFD) were investigated. The direction of detection beam was changed through adjusting the probes center spacing (PCS) to analyze the signal to noise ratio (SNR) varies with the angle between testing beam and columnar grain. And then, the probe distribution method of primary wave and secondary wave based on ultrasonic TOFD techniquewere proposed. Moreover,the model of wave propagation was constructedtoidentifythe characteristic signal of defect in the light of complex wave structure in secondary wave method. The research indicates that the ultrasonic propagated in the stainless steel weld reflects obvious anisotropy characters, and the angle between columnar grain and detection beam is the main influencing factor to SNR of testing signal. Primary wave method and secondary wave method is respectively adopted for testing, when theprobe is located on the side of weld root and reinforcement. The testing capability on stainless steel weldcan be effectively improved when the angle between detection beam and columnar grain is within the range of 35°~48°and high beam amplitude is obtained. The primary and secondary wave methods of ultrasonic TOFD based on anisotropic characteristic of wave propagation are very important to improve the ultrasonic testing capability on inner defect of austenitic stainless steel weld.

Abstract:The traditional submodule capacitor voltage measuring method requires the same number of submodule voltage sensor, which increases the system costs and burden of data acquisition system. In this paper, a new method based on the nearest level approach to detect the voltage of the MMC submodule is proposed. The method divides the submodule into groups, each group has only a voltage sensor to correct the observer voltage, and the method for improving the number of correction is proposed. Then a compensation method is proposed to solve the delay of voltage sampling circuit affecting the output voltage measurement accuracy. The simulation and experimental results show that the proposed method is correct and effective.

Abstract:The cogging torque in stator permanent magnets of axial field fluxswitching permanent magnet motor (SPAFFSPM) is too large and with high noise due to the flux focusing. In order to reduce the cogging torque and improve the motors output performance, an analytic expression of the cogging torque of motor is deduced by energy perturbation method to analyze the parameters of stator and rotor structure. Based on the response surface methodology (RSM) and FEM, the response surface numerical model about stator slot width, rotor tooth inclination angle and shape factor of permanent magnet with cogging torque is obtained, then the optimal combination of the cogging torque with stator slot width, rotor tooth inclination angle and shape factor of permanent magnet is deduced. The accuracy of the analysis is examined by the 3D finite element and prototype of the experimental platform.

Abstract:The traditional multi objective optimization algorithms are complex with too many regulation parameters and large amount of calculation, and they are easily trapped in the local optimal solution. Aiming at the problem above, a novel optimization method based on fruit fly optimization algorithm(FOA) is proposed in the paper. The switched reluctance motor (SRM) is then modeled by extreme learning machine algorithm, and optimized by FOA. Finally, the proposed algorithm is verified by various simulations, and the comparative analysis with traditional PSO are carried out. It is demonstrated that better optimization results of torque ripple and efficiency are achieved by the proposed algorithm, and it has fewer regulation parameters, faster convergence speed and avoidance of local optimal solution. Therefore, the proposed algorithm has better application value in the optimization of SRM.