Industrial shape detecting system of cold rolling strip

A high-precision shape detecting system of cold rolling strip is developed to meet industrial application, which mainly consists of the shape detecting roller, the collecting ring, the digital signal processing （DSP） shape signal processing board and the shape control model. Based on the shape detecting principle, the shape detecting roller is designed with a new integral structure for improving the precision of shape detecting and avoiding scratching strip surface. Based on the DSP technology, the DSP shape signal processing circuit board is designed and embedded in the shape detecting system for the reliability and stability of shape signal processing. The shape detecting system was successfully used in Angang 1 250 mm HC 6-high reversible cold rolling mill. The precision of shape detecting is 0.2 I and the shape deviation is controlled within 6 1 after the close loop shape control is input.

Digital Signal Processing Based Real Time Vehicular Detection System

Traffic monitoring is of major importance for enforcing traffic management policies.To accomplish this task,the detection of vehicle can be achieved by exploiting image analysis techniques.In this paper,a solution is presented to obtain various traffic parameters through vehicular video detection system(VVDS).VVDS exploits the algorithm based on virtual loops to detect moving vehicle in real time.This algorithm uses the background differencing method,and vehicles can be detected through luminance difference of pixels between background image and current image.Furthermore a novel technology named as spatio-temporal image sequences analysis is applied to background differencing to improve detection accuracy.Then a hardware implementation of a digital signal processing (DSP) based board is described in detail and the board can simultaneously process four-channel video from different cameras. The benefit of usage of DSP is that images of a roadway can be processed at frame rate due to DSP′s high performance.In the end,VVDS is tested on real-world scenes and experiment results show that the system is both fast and robust to the surveillance of transportation.

PROJECTED GRADIENT DESCENT BASED ON SOFT THRESHOLDING IN MATRIX COMPLETION

Matrix completion is the extension of compressed sensing.In compressed sensing,we solve the underdetermined equations using sparsity prior of the unknown signals.However,in matrix completion,we solve the underdetermined equations based on sparsity prior in singular values set of the unknown matrix,which also calls low-rank prior of the unknown matrix.This paper firstly introduces basic concept of matrix completion,analyses the matrix suitably used in matrix completion,and shows that such matrix should satisfy two conditions:low rank and incoherence property.Then the paper provides three reconstruction algorithms commonly used in matrix completion:singular value thresholding algorithm,singular value projection,and atomic decomposition for minimum rank approximation,puts forward their shortcoming to know the rank of original matrix.The Projected Gradient Descent based on Soft Thresholding(STPGD),proposed in this paper predicts the rank of unknown matrix using soft thresholding,and iteratives based on projected gradient descent,thus it could estimate the rank of unknown matrix exactly with low computational complexity,this is verified by numerical experiments.We also analyze the convergence and computational complexity of the STPGD algorithm,point out this algorithm is guaranteed to converge,and analyse the number of iterations needed to reach reconstruction error.Compared the computational complexity of the STPGD algorithm to other algorithms,we draw the conclusion that the STPGD algorithm not only reduces the computational complexity,but also improves the precision of the reconstruction solution.

An Anti-multipath Frequency Hopped Communication Technique in Shallow-water Acoustic Channels

This paper introduces a frequency-hopped (FH) communication system to anti-intersymbol interferences (ISI) caused by the multipath propagation in shallow-water acoustic channels, and uses high-speed digital signal processor (DSP) and serial ADC (MAX121) chip to demodulate received signal efficiently based Fast Fourier Transform (FFT) algorithm. The field experimental results show: a data rate of 1Kbit/s with the bit error rates on the order of 10 -4 is demonstrated at 2000 m in the shallow-water acoustic channel of Xiamen harbor, and the key techniques of the system is analyzed in the paper.

Supervised Kernel Uncorrelated Discriminant Neighborhood Preserving Projections

To separate each pattern class more strongly and deal with nonlinear ease, a new nonlinear manifold learning algorithm named supervised kernel uneorrelated diseriminant neighborhood preserving projections （SKUDNPP） is proposed. The algorithm utilizes supervised weight and kernel technique which makes the algorithm cope with classifying and nonlinear problems competently. The within-class geometric structure is preserved, while maximizing the between-class distance. And the features extracted are statistically uneorrelated by introducing an uneorrelated constraint. Experiment results on millimeter wave （MMW） radar target recognition show that the method can give competitive results in comparison with current papular algorithms.

THE METHOD OF SEPARATING HARMONIC SIGNALS FROM MULTIPLICATIVE AND ADDITIVE NOISES

This paper focuses on the extraction of a harmonic signal from multiplicative and additive noises. A method is proposed in two stages： （1） to square the original discrete time series, which includes both signals and noises, and form a new time series. By this means, the multiplicative noise is converted to additive noise; and （2） to filter out the noise by using existing noise removal schemes. With a large amount of simulation, experimental results demonstrated the efficiency and effectiveness of this newly developed method in terms of Signal-to-Noise Ratio （SNR） and other criteria. Prom the experiment, it is also found that： the two kinds of noises affect the SNR differently. In general, the SNR is not influenced by multiplicative Gaussian noise regardless of its variance. However, if both kinds of noise exist, the SNR decreases with the incensement of the Variance of Additive Noise to Multiplicative Noise Ratio （VAMNR）. This analysis is also supported by simulation work.

A RESEARCH TO HIGH-PERFORMANCE MULTI-LEVEL SINGLE-PHASE AC/DC POWER FACTOR CORRECT SWITCHING CONVERTER

This letter studies and analyzes the working features of main circuit of tri-level boost Power Factor Correct(PFC) converter and the advantages of tri-level switch converter in aspects of bearing high-voltage of power components,overall system loss and magnetic component selection based upon the single-level boost PFC switch converter.Besides,relying on the application of mi-croprocessor in power converter technology and DSP(Digital Signal Processing) chip's strong cal-culating capacity,the letter presents the adoption of modified scheme of tri-level boost PFC converter under the control of predictive control algorithm.Moreover,the operating principle and control method are specified,the results of circuit test and analysis are provided and the advantages of pre-dictive control technology-based multi-level boost PFC converter is verified.

Development of Sensor Oriented Dynamic Rotor Model as the Basis of Machine Diagnostics

Today, digital signal processing based on new microprocessor technology allows for successful machine protection and is acceptably cost-effective. Furthermore, by means of vibration-diagnostics monitoring of machines assisted by analytical methods it is possible to monitor and quantify dynamic parameters of a machine. By means of the analysis of dynamic behavior of rotor, it is possible to diagnose and solve the defects relating to rotor and other parts of machine. Recently, vibrations analysis and monitoring have become the most widespread method of machine diagnostics. Detection, identification and elimination of problems related to machine work can be simplified by modeling some dynamics solutions. The paper presents a mathematical model of elastic rotor with concentrated weight designed for the purpose of detecting defects with the help of vibrations measured by sensors based in bearings. Experimental results from test tables of the world＇s leading company, Bentley Nevada Co. USA, were used as the basis for development of this model. Accordingly, mathematical model for most of the cases was based on radial oscillation of rotor while torsion oscillations were used as the basis in some cases. Torsion vibrations cannot be detected without special sensors even at their highest magnitudes. Reliability of this model and accuracy of vibrodiagnostic analysis has been experimentally confirmed when applied on machines in operation.