Abstract:In order to solve the problem that the efficiency of surface reconstruction based on vehicle point cloud data is low and the quality of the reconstruction model based on simplified data is poor, an improved point cloud simplification algorithm is proposed. Firstly, a spatial index structure of the scattered cloud data is established with kdtree, which obtains the k neighborhood index of each data point. Secondly, a simplification algorithm based on fast identification of boundary lines is proposed to avoid the loss of boundary data in the process of reducing and ensure the real vehicle surface reconstruction model. Finally, the nonboundary point’s neighborhood is classified, and the neighborhood is reserved according to the classification, which accelerates the processing speed of point cloud data and reduces memory overhead. The paper not only designs the software program of the simplification algorithm and realizes the simulation experiment, but also carries out a real vehicle experiment on a platform of vehiclebody dimension measurement system based on the 3D laser scanning. The experimental results show that the improved algorithm preserves the boundary features and detail shapes of the vehicle point cloud to the maximum extent, which improves the quality of surface reconstruction. The improved simplification algorithm could reduce the vehicle point cloud data by 45% ~ 70%, therefore, it improves the speed of surface reconstruction of vehicle point cloud and enhances the performance of the vehiclebody dimension measurement system.

Abstract:The structure of truncated quadtree for binary image is proposed. The collapse of quadtree is performed until the level of small image block of a given size rather than single pixel. The main structure of a binary image is represented by a relative small number of quadtree nodes, and for the small image blocks with mixed colors, they are represented by their raw image pixels. The combination of quadtree and raw image blocks leads to the higher representation efficiency of the truncated quadtree. The truncated quadtree is traversed in a depthfirst manner, and the quadtree nodes and raw image blocks are respectively encoded in the order of traversal, resulting in the truncatedquadtreebased codes of the binary image. The equivalent forms of binary image logical operations on the codes are presented. The experimental results on realworld images show that, with a proper truncating level setting, the memory cost of the truncatedquadtreebased code is 1/10 to 1/3 of the cost of the raw binary image, and the logical operation time on the code is below 1/5 of that of the pixelbypixel approach. The proposed methods are suitable for applications where the number of logical operation is significantly larger than the number of encoding and decoding.

Abstract:Accuracy and speed of reconstruction algorithm play an important role in the temperature field measurement for a boiler by acoustic tomography. A dynamic model of a 3D temperature field reconstruction by acoustic tomography is established. A dynamic reconstruction algorithm is proposed considering both the acoustic measurement information and the dynamic evolution information of the temperature field. An objective function is built, which fuses the measurement information, space constraint of the temperature field and the dynamic evolution information. A regularization matrix is established based on the smooth constraint method which reflects the positional relationship between spatially adjacent pixels. A method combining Tikhonov regularization and optimization is adopted to solve the function. The numerical simulations show that the reconstruction speed of the algorithm fusing dynamic evolution information is similar to static reconstruction algorithm including the least square method, the algebraic reconstruction technique and the standard Tikhonov regularization algorithm. The image quality and noise immunity of the algorithm fusing dynamic evolution information are better than the results obtained from the static algorithms. An innovative method with high effectiveness is provided for temperature field reconstruction by acoustic.

Abstract:Magnetic target location method has important application in many fields, such as aerospace magnetic detection, underground mineral detection. Normally, when the distance between the gradiometer and the magnetic target is long enough, the magnetic target can be equivalent to a magnetic dipole. The magnetic field and magnetic field gradient is obtained by using magnetic sensor, and the location result is gotten by an algorithm. The location error mainly including system error and random error is analyzed. The error caused by the baseline distance is analyzed, and the error is corrected by the iterative correction method. For the magnetic dipole with magnetic moment intensity of 2 Am2, the distance error can be reduced to 5% by the iterative correction method with range of 70 cm. A generalized inverse matrix is proposed to eliminate the blind zone caused by the change of magnetic moment direction, and the target can be detected without blind.

Abstract:The power quality affects the normal operation of electrical equipment and power system directly. Accurate measurement of voltage amplitude and frequency is a prerequisite for the analysis of power quality. In this paper, a fiber Bragg grating(FBG) voltage sensor based on CCD demodulation is proposed. Using the inverse piezoelectric effect of piezoelectric ceramics to change the wavelength of the FBG attached to the piezoelectric ceramic, the purpose of detecting the voltage is achieved. The relationship between the voltage and the wavelength of grating is analyzed theoretically. The experiments show that the nonlinear error is 2.998% and loaded voltage sensitivity of the sensor is 8.47 pm/V, which can detect the waveform of the voltage below 50 Hz. This method provides a reference for assessing the power quality in complex environments.

Abstract:Aiming at the problem that the D matrix model based on single feature quantity can lose a lot of information about the test signal, a testability analysis model based on multifeature quantity is proposed. Firstly, based on the study of D matrix model, the feature extraction and multivalue coding of the test signal are carried out, and a D matrix model based on multifeature quantity is established. Then, the diagnostic strategies are developed based on the information entropy, the fault diagnosis tree is generated, and the model is analyzed to assess its diagnostic capabilities. The results show that the D matrix model based on multifeature quantity adopts a smaller number of test points and fuzzy group, and has a higher fault isolation rate, less diagnostic test step, and lower average test cost compared with the D matrix model based on the single feature quantity.

Abstract:Aiming at the problem of how to effectively obtain the full diversity gain in the wireless ultraviolet Multiinput Multipleoutput (MIMO) turbulence channel in the case of accurate estimation of the channel, the transmission characteristics of wireless ultraviolet communication are firstly studied, and then the MIMO channel and the main factors affecting the ultraviolet communication are studied. Finally, the bit error rate formula of LOS and NLOS is derived by using bit complementary orthogonal spacetime code (BCOSTBC) coding. The experimental results show that the bit error rate performance of 1×2, 2×1, 2×2 system is improved by 3, 6 and 9 dB respectively in LOS and NLOS. Increasing the number of photodetector can increase the diversity gain. The 2×2 system needs the least transmission power, the transmission distance is farther, the data transmission rate is bigger, the bit error rate is lower. In the NLOS condition, through the small angle transmission angle can improve the system bit error rate performance.

Abstract:During the movement of segment winding permanent magnet linear synchronous motor (SWPMLSM), the loss of sensor signal may lead to sharp fluctuations in speed, and result in out of step. In order to solve these problems, a fault diagnosis and faulttolerant control method is presented. The detection method of winding switching position is designed. The fault types and signal characteristics of the proximity sensors are studied. By using the speed of mover and the signals of the adjacent position sensors, the sensor state is predicted. The fault diagnosis of sensor is realized by using the edge triggering sequence of adjacent sensors and the predictive value of sensor state. When the position sensor fault is detected, the control system isolates the fault sensor. The stator winding of the SWPMLSM is successfully triggered by the estimated value instead of the fault sensor signal. The experimental tests have been carried out on a prototype of SWPMLSM ropeless lifting system. The results show that when the sensor gap is increased, the sensor signal is lost, the stator windings of the motor can be switched reliably and the speed is stable. The position sensor fault diagnosis and faulttolerant control method can satisfy the realtime and reliability requirements of SWPMLSM winding switching control, and the experimental results prove its feasibility and effectiveness.

Abstract:The effective information of 3D multifocal image stack is distributed on different image layers, so the feature extraction and classification of image stacks are significantly different from that of 2D images. In this paper, an image fusion based multilinear analysis approach is presented to use for classification of multifocal image stacks. First, the image fusion techniques are used to combine the relevant information of multifocal images within a given image stack into a single image. Besides, multifocal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by using canonical correlation analysis (CCA). Furthermore, because multifocal image stacks represent the effect of different factorstexture, shape, different instances within the same class and different classes of objects, the image fusion method within a multilinear framework is embeded to propose an image fusion based multilinear classifier. The experimental results demonstrate that the multidirection image fusion based multilinear classifier can reach a higher classification rate (97%) than other classification methods.

Abstract:The testing efficiency of ELISA analyzer is seriously affected the timeconsuming incubation and the accuracy will be reduced by the differences in the degree of reagent reaction due to temperature instability. Aiming at these problems, a method of segmentation incubation based on the improved digital PID algorithm was proposed. Firstly, the temperature characteristics of reagent and incubation system were analyzed and the parameters in preheating and constant temperature stage were determined. Secondly, different algorithms were applied in the different sections of incubation process according to the parameters and control indicators. And then, the experiment system was set based on ELISA analyzer framework to verify the time of temperature rising and stability of reagent. The experiment results indicate that the reagent is heated up from 21 ℃ to 37.5 ℃ in 239±5 seconds, meanwhile, the temperature deviation of isothermal segment is less than ±0.2 ℃. The method proposed in this paper achieves fast and stable temperature control and ensures enzyme reaction fast and stable.

Abstract:In order to solve these defects as serious dispersion of band clutter, signal projection difficult to match and the high bit error rate during the network signal reception process, a precise receiving algorithm for subcarrier OFDM networks based on gradient mapping mechanism was proposed. Firstly, minimum mean square predictive inhibitory mechanism was constructed by fast Fourier transform and its inverse transform, as well as interpolation technique, and band pass filtering was used to eliminate the out of band clutter in full frequency domain. Then the gradient mapping mechanism was constructed based on real and imaginary part signals of digital features to match the projection points of the signal with the projected quadrants for reducing the network error rate. The simulation results show that this proposed algorithm has lower error rate reducing by 2, 3 orders, as well as higher signal gain intensity, increasing 20.5% and 4163% respectively under the Rician channel condition, and the power spectrum performance is closest to the ideal state compration compared with the current amplitude filter algorithm and the wave band frequency suppression algorithm. This algorithm has ideal signal reception precision and antifading performance with certain practical deployment value.

Abstract:To raise the response speed of the ultrasonic gas flowmeter system, a new signal processing method of ultrasonic gas flowmeter is proposed according to the maximum difference value of adjacent peak. In order to improve the measurement precision of this signal processing method, a new kind of intermittent excitation method is presented. The intermittent excitation method is adopted to obtain the echo signal with the maximum difference value of adjacent peaks. The relative position of the maximum difference value of adjacent peaks in the echo signal is always the same under different flow rates. During the actual measurement, the position of the maximum difference value of adjacent peaks is utilized to determine the arrival time of the echo signal, and then the ultrasonic propagation times are calculated to obtain the gas flow rate. The intermittent excitation method and the signal processing method based on the maximum difference value of adjacent peaks are realized on the hardware system in real time. The calibration experiments are conducted to verify the effectiveness of the excitation method and the signal processing method.

Abstract:In order to solve the problem that the bandpass filter parameters in resonance demodulation are difficult to select and the fault signals of rolling bearing in early failure period aredrowned in strong background noise,thefault diagnosis methodcombining variational mode decomposition (VMD)withspectral kurtosis is proposed. Firstly, the fault signals need to bereconstructed selfadaptively, so several intrinsic mode function (IMF) are obtained by VMD, and adaptive reconstruction is performed by computing the kurtosis of IMFs. Next,we can analyze the reconstructed signals by spectral kurtosis and design the bandpass filter. Finally, the working status of rolling bearingis identified through the resonance demodulation spectrum of reconstructedsignal. By processing real data,the results show that the method is more accurate than traditional resonance demodulation in diagnosing the fault of rolling bearing. Thus, it can be seen, the spectral kurtosis is reliable in selection of the filter parameters, and combining VMD and spectral kurtosis can reduce the noise and extract weak fault signal.

Abstract:In order to detect the edge of pipeline inner corroded image, the classic edge detection method is analyzed. And it is found that the detection precision is not high and the antinoise performance is poor. On this basis, an image edge detection algorithm based on BP neural network is researched. To build the BP neural network, standard image is made as input data, and the edge image of standard image detected by traditional edge detection operator is made as output data. And a large amount of data is used for training. Finally, the experimental result of the edge detection of the corroded image inside the pipeline detected with the BP neural network method is given, and it is compared with the result of traditional edge detection algorithm. The results show that the proposed algorithm can improve the detection precision and antinoise ability significantly, and it is a kind of algorithm with extensive adaptability.

Abstract:Aiming at the shortcomings of the existing image restoration algorithms, a 2D blind restoration algorithm based on novel DNA genetic glowworm swarm optimization is proposed. Firstly, the proposed algorithm improves the crossover and mutation operation in the traditional DNA genetic algorithm, and then combines the novel DNA genetic algorithm with the glowworm swarm optimization algorithm to propose a new DNA genetic glowworm swarm optimization algorithm. Secondly, the new DNA genetic glowworm swarm optimization algorithm is applied to the 2D image blind restoration, and a blind restoration algorithm based on the new DNA glowworm swarm optimization is obtained. The proposed algorithm has a good global search capability, which optimizes the initial weight matrix of the blind equalizer. After the fuzzy image is processed by the 2D blind equalizer, the image quality is improved and the image recovery is good. The simulation results verify the effectiveness of the proposed algorithm.

Abstract:The RKDG（RungeKutta discontinuous galerkin）method that is the combination of discontinuous galekin method for space discretization together with an explicit RungeKutta approach for time derivatives has been adopted to show the 3D simulation of a Z type ultrasonic flowmeter in water flow measurement field, which divided into flow field and sound field. Based on the stationary background meanflow obtained by solving the standard k－ε model, the control equations are derived from continuity, momentum, and equation of state to describe the propagation of linear acoustic wave in an adiabatic way. The acoustic characteristic is shown in figure when it moves in the direction of the main flow with the presence of a background flow by defining the normal velocity on the surface of transmitter. Through the recalculation, the average sound pressure on corresponding surface of receiver under upstream propagation can be generated by simply switching the source and receiver boundary, as the difference in travel times by comparing the average sound pressure for downstream and upstream propagation which is lower than experimental result. This numerical methodology opens the possibilities in simulating acoustic propagation in other complex configurations, as well as complicated flows.

Abstract:The signal collected by a non contact physiological signal monitoring system should be separated fast and accurately in real time. In this paper, the fast complementary ensemble empirical mode decomposition (FCEEMD) was used for the physiological signal processing, in which white noise was added in pairs into the original signal and the empirical mode decomposition (EMD) was used to obtain a series of intrinsic mode functions（IMFs）. The separation of the original signal was realized, a fixed iterations time of sifting to the stoppage criterion is used to ensure that the algorithm is fast in realtime. By analyzing the simulation and actual signals, the results show that the algorithm can solve the modemixing problem effectively and obtain heartbeat and respiration signals accurately and quickly.

Abstract:A novel method consisting of fault detection, rough set generation, element isolation and parameter estimation is presented for multiplefault diagnosis on analog circuit under tolerance. Firstly, a linearprogramming concept is developed to transform the fault detection of circuit with limited accessible terminals for measurement to check existence of a feasible solution under tolerance constraints. Secondly, the fault characteristic equation is deduced to generate a fault rough set. It is proved that the node voltage of nominal circuit can be used in fault characteristic equation under tolerance. Finally, fault detection of circuit with revised deviation restriction for suspected fault components is proceeded to locate faulty elements and estimate their parameters. The diagnosis accuracy and parameter identification precision of the method are verified by simulation results.

Abstract:In order to research the dynamic characteristics of the ball screw on the Fiveaxis linkage machining center, such as positioning accuracy, repeated positioning accuracy, speed and acceleration tracking, dynamic friction torque, load disturbance, preload, fatigue performance, temperature rise and mechanical vibration, an intelligent precision measurement and control test platform is designed, which includes servo motor + ball screw driving, linear motor simulation load disturbance and multichannel signal acquisition. And the dynamic model of timevarying parameter uncertainty and external force disturbance is described. Meanwhile, the adaptive nonlinear PID control model and feedforward error compensation based on genetic algorithm are established. The test result shows that the control strategy has a small tracking error, strong antijamming capability and stability.

Abstract:Aiming at the problem that the Beidou satellite positioning system (BDS) has cycle slip in the carrier phase observation, the method of improved polynomial fitting model can make cycle slip detection and repair in carrier phase observation. This method uses the carrier phase observations with the same satellite measured by three receivers, combined the carrier with the phase between the receiver and satellite can measure two groups of single difference. Using a set of single difference with polynomial fitting can obtain the epoch number of cycle slip, using another group of single difference with polynomial fitting can determine which group to have carrier phase cycle slip, at the end of the week, repair the cycle slip. The experimental results show that this method not only can measure more than 0.2 jumps, but also can measure more than 0.2 week jump which group of carrier observations occurred.

Abstract:The algorithm empirical mode decomposition(EMD) has the issue of mode mixing, and the algorithm ensemble empirical mode decomposition(EEMD) has poor realtime performance. Aiming at these defects, the method of empirical wavelet transform (EWT) combining the EMD with wavelet analysis is proposed. In this paper, the method is taken to segment ECG signal spectrum adaptively, and constructs wavelet filter banks in segmental intervals to extract the single component equipped with tight support, then eliminates direct component and noise residual. After that the signal from other component can be reconstructed. The experimental data comes from the real ECG signal in the MITBIH database, and the simulation result shows that the algorithm removes baseline wander and powerline interference. The parameters of signal noise ratio, meanrootsquare error and autocorrelation coefficient are better than other two adaptive algorithms: EMD and EEMD. The whole running time of algorithm is less than 1 s, which can satisfy the requirements of realtime and accurate ECG monitor.

Abstract:A system based on the infrared image and the heat transfer mechanism of radiation and convection is developed to measure the heat loss of rotary kiln through the kiln shell, with which the models of the total heat loss is derived for heat loss calculation. By using LabVIEW programming language, a software is then developed to measure the heat loss. The effectiveness of the proposed method is tested by using a cement rotary kiln as example. It is shown that, the system is able to capture the axial temperature of the kiln shell of interest and calculates the corresponding heat loss correctly. It is also found that the heat loss through radiation has similar magnitude to the heat loss through convection, and the heat loss in the burning zone is about 4% of the total input thermal energy into the kiln. The result of the present work has potential usage in the energysaving production and optimization of process parameters.

Abstract:It becomes more and more attention of the public that the research on the reduction of the specific absorption rate (SAR) of electromagnetic radiation on the human brain with the development of the mobile communications. The electromagnetic band gag（EBG）structure has highimpedance in some frequency band and its reflection wave is inphase with that of the incident wave, so it could suppress the surface waves formed on the printed board and improve antenna’s radiation preventing the transmission of electromagnetic wave in the direction of the human head. The simulation is carried out on the antenna with EBG at 1.8 GHz. The results show that comparing with the antenna without EBG structure, the SAR of electromagnetic wave is greatly reduced. Meanwhile, the antenna satisfies the technique indication such as Sparameters, radiation etc. The simulation also show that the antenna’s dimension is smaller. Based on the inphase reflection a lowprofile antenna with low SAR is achieved in this paper.

Abstract:Aiming at the problem of musical noise in dereverberation of spectral subtraction, a post processing masking method based on frequency normalization is researched. Firstly, the reverberation signal is processed by spectral subtraction to remove the reverberation. Secondly, the reverberation signal and the dereverberation signal are normalized in frequency. Then the dereverberation signal and the reverberation signal are subtracted correspondingly in frequency domain to get the mask factor. Finally, the mask factor is used to deal with the dereverberation signal in order to reduce the musical noise. In the simulation experiment, the spectrogram and the perceptual evaluation of speech quality are used to evaluate the masking method. The spectrogram verifying the musical noise is reduced obviously in the post processed speech signal, and the perceptual evaluation of speech quality shows that the post processing method improves the score of the speech signal 0.55.

Abstract:Aiming at the problems such as complex environment, low separation rate and difficult to identify the targets in the process of underwater sonar target search, a new method based on dual tree double density complex wavelet subband model is proposed to identify the underwater target automatically.Firstly, the dual tree double density complex wavelet is used to decompose the acoustic image to get different direction subbands.Then,usingthe three parametersgeneralizesΓ function of different directional subband coefficients to fit as feature items.Finally, usingthe difference in distribution characteristicsbetween acoustic target image and background sonarimage calculating the KL distance,the similarityis matchedandthe optimal threshold is setto distinguish the existingtarget automatically.The experiments prove that the proposed methodis applied to the identification of sonar images with multiple targets,the quality factor of detection is 97.2% and the detection quality factor is 10% higher than that of other methods at different noise levels,and has high detection rate and robustness.

Abstract:Aiming at the perspectives of big errors and difficult compatibility of existing automatic weather station signal simulator, this paper has analyzed the temperature measurement theory of CAWS600 and the series of ZQZ automatic weather station collectors. In this paper, the temperature channel of JJQ1 signal simulator is tested by using different types of automatic weather station collectors, and the reasons for fluctuations of test data are analyzed. Based on the temperature measurement principle of fourwire system, the high precision and extremely low temperature drift resistance, the fourwire network is constructed by signal relay, and the software compensation is adopted. It can be adapted to the temperature simulation scheme of different collectors. At last, the modified temperature channel is tested by collector and high precision multimeter. The experimental data show that the maximum error of the simulated temperature is ±0.03 ℃, the maximum error of the corresponding resistance is ±12 mΩ. It meets the industry standard QX / T 3462016 “automatic weather station signal simulator”, and provides reference for the improvement of the automatic weather station signal simulator.