Ultrasonic Nondestructive Signals Processing Based on Matching Pursuit with Gabor Dictionary

The success of ultrasonic nondestructive testing technology depends not only on the generation and measurement of the desired waveform, but also on the signal processing of the measured waves. The traditional time-domain methods have been partly successful in identifying small cracks, but not so successful in estimating crack size, especially in strong backscattering noise. Sparse signal representation can provide sparse information that represents the signal time-frequency signature, which can also be used in processing ultrasonic nondestructive signals. A novel ultrasonic nondestructive signal processing algorithm based on signal sparse representation is proposed. In order to suppress noise, matching pursuit algorithm with Gabor dictionary is selected as the signal decomposition method. Precise echoes information, such as crack location and size, can be estimated by quantitative analysis with Gabor atom. To verify the performance, the proposed algorithm is applied to computer simulation signal and experimental ultrasonic signals which represent multiple backscattered echoes from a thin metal plate with artificial holes. The results show that this algorithm not only has an excellent performance even when dealing with signals in the presence of strong noise, but also is successful in estimating crack location and size. Moreover, the algorithm can be applied to data compression of ultrasonic nondestructive signal.     

一种改进的最优步长积分迭代法

本文基于位场向下延拓的最优步长积分迭代法,通过结合当前迭代步骤得到的迭代信息,经过推导得到了一种新的改进的最优步长积分迭代法迭代形式。此种改进迭代法的实质是将最优迭代法的一步迭代分为两步迭代,且每次迭代过程都使用积分迭代法的迭代形式,因此迭代过程中的计算量并没有明显增加,其收敛性同最优步长积分迭代法。理论模型及实测数据的对比试验表明,改进迭代法的收敛速度和延拓精度均优于最优步长积分迭代法、泰勒级数迭代法和导数迭代法。     

Data-mining based fault detection

This paper presents a fault-detection method based on the phase space reconstruction and data mining approaches for the complex electronic system. The approach for the phase space reconstruction of chaotic time series is a combination algorithm of multiple autocorrelation and Г-test, by which the quasi-optimal embedding dimension and time delay can be obtained. The data mining algorithm, which calculates the radius of gyration of unit-mass point around the centre of mass in the phase space, can distinguish the fault parameter from the chaotic time series output by the tested system. The experimental results depict that this fault detection method can correctly detect the fault phenomena of electronic system.     

湿度和温度对聚合物光纤光栅反射波长漂移量的影响

针对固体火箭发动机纤维缠绕壳体状态监测中局部可能出现大应变情况,采用聚合物光纤布拉格光栅(polymer op-tical fiber Bragg grating,POFt3G)传感器对大应变进行检测;分析了湿度和温度对光纤光栅反射波长漂移量的影响,建立了湿度传感模型、温度传感模型和温度湿度混合模型.并通过MATLAB进行数值仿真,结果表明,反射波长随温度的升高而减小,随湿度的增加而增大,并受到温度和湿度的交叉影响,这与文献报道的实验结果比较吻合.     

Sliding mode learning control for T-S fuzzy system and an application to hypersonic flight vehicle

Sliding mode-based learning control is presented for T-S fuzzy system. A T-S fuzzy model with both uncertainties and unmodeled dynamics is proposed firstly, in which the information of uncertainties and unmodeled dynamics are assumed to be unknown. Then, according to a given reference model, state-tracking error system is built. Respecting facts, the input matrices of the built T-S fuzzy model are different from each other. An extended state observer is built for estimating the unknown uncertainties and unmodeled dynamics, and a corresponding sliding surface is proposed. A learning controller is then presented for the closed loop system. Moreover, a numerical simulation result on hypersonic flight vehicles is considered to testify the controller's availability.     

On the Discrete-Time Dynamics of Cross-Coupled Hebbian Algorithm

Principal/minor component analysis(PCA/MCA),generalized principal/minor component analysis(GPCA/GMCA),and singular value decomposition(SVD)algorithms are important techniques for feature extraction.In the convergence analysis of these algorithms,the deterministic discrete-time(DDT)method can reveal the dynamic behavior of PCA/MCA and GPCA/GMCA algorithms effectively.However,the dynamic behavior of SVD algorithms has not been studied quantitatively because of their special structure.In this paper,for the first time,we utilize the advantages of the DDT method in PCA algorithms analysis to study the dynamics of SVD algorithms.First,taking the cross-coupled Hebbian algorithm as an example,by concatenating the two cross-coupled variables into a single vector,we successfully get a PCA-like DDT system.Second,we analyze the discrete-time dynamic behavior and stability of the PCA-like DDT system in detail based on the DDT method,and obtain the boundedness of the weight vectors and learning rate.Moreover,further discussion shows the universality of the proposed method for analyzing other SVD algorithms.As a result,the proposed method provides a new way to study the dynamical convergence properties of SVD algorithms.     

Synthesis and microwave absorption properties of Ni–Zn–Mn spinel ferrites

A series of Ni_0·5?xZn_0·3?xMn_0·2+2xFe₂O₄ ferrites was successfully prepared by the sol–gel autocombustion method. The structure and electromagnetic properties of the powders were characterised by X-ray diffraction, SEM and vector network analysis. The pure powders were formed by heating at 1200°C for 3 h in air, and grain sizes increased as the amount of substitution ranged from x?=?0·0 to x?=?0·25. For samples with x?=?0·1, a minimum reflection loss of ?27·57 dB was observed at 11·0 GHz with the less than ?10 dB absorption bandwidth at 8·0 GHz with 3·8 mm thickness. The results indicate that substitution with Mn and Zn ions can greatly improve the microwave absorption properties of NiFe₂O₄ ferrites.     

Coupled Cross-correlation Neural Network Algorithm for Principal Singular Triplet Extraction of a Cross-covariance Matrix

This paper proposes a novel coupled neural network learning algorithm to extract the principal singular triplet (PST) of a cross-correlation matrix between two high-dimensional data streams. We firstly introduce a novel information criterion (NIC), in which the stationary points are singular triplet of the crosscorrelation matrix. Then, based on Newton's method, we obtain a coupled system of ordinary differential equations (ODEs) from the NIC. The ODEs have the same equilibria as the gradient of NIC, however, only the first PST of the system is stable (which is also the desired solution), and all others are (unstable) saddle points. Based on the system, we finally obtain a fast and stable algorithm for PST extraction. The proposed algorithm can solve the speed-stability problem that plagues most noncoupled learning rules. Moreover, the proposed algorithm can also be used to extract multiple PSTs effectively by using sequential method.      

位场向下延拓的波数域正则—积分迭代法

本文将正则方法与积分迭代法相结合,提出波数域正则—积分迭代法用于位场向下延拓。该迭代法以位场正则向下延拓值为迭代初值,并用正则向下延拓算子处理迭代过程中的剩余谱,使得在加快迭代收敛的同时,压制噪声谱,以提高延拓的稳定性;计算了改进迭代法的最优步长,对比分析了改进迭代法的收敛性和滤波特性,同时提出采用L-曲线准则计算正则向下延拓的正则参数,并将其扩展到波数域以提高计算速度和适应波数域迭代法。基于理论模型和航磁数据的对比试验分析表明,改进迭代法位场向下延拓的精度、稳定性及收敛速度都有提高,其延拓效果优于现有广义逆法、积分迭代法、泰勒级数迭代法和Landweber迭代法。