Wuhan University

Baiqiang Yin

Yigang He

Hui Zhang

Liulu He

Bing Li

Jiajun Duan

Chaolong Zhang

Guolong Shi

Yuan Huang

Lei Zuo

Shudong Wang

Jinguang Jiang

Jian Zheng

Qiwu Luo

A system for testing a Nakagami fading channel and a verification method thereof are provided. The testing system includes a signal generator, a Nakagami fading channel simulator, and a computer. The signal generator is used to output a sine wave signal whose frequency is f and transmit the sine wave signal to the Nakagami fading channel simulator and the computer. The Nakagami fading channel simulator is used to generate a Nakagami fading channel. The computer is used to perform data processing and analysis. In the verification method, time domain fading characteristics, first-order statistics characteristics, and second-order statistics characteristics of the Nakagami fading channel are respectively verified. Verifying the time domain fading characteristics is verifying a waveform fluctuation rate and a fluctuation range on a time domain under different Nakagami fading factors. Verifying the first-order statistics characteristics is mainly verifying amplitude and phase distribution statistics characteristics of the Nakagami fading channel by means of Kolmogorov Smirnov (KS) hypothesis test. Verifying the second-order statistics characteristics is mainly verifying the shape and bandwidth of a power spectrum density function. In the present invention, verification on performance of the Nakagami fading channel simulator or a simulation model has features of accuracy and feasibility.

System for testing Nakagami fading channel and verification method thereof

An analog circuit fault feature extraction method based on a parameter random distribution neighbor embedding winner-take-all method, comprising the following steps: (1) collecting a time-domain response signal of an analog circuit under test, wherein the input of the analog circuit under test is excited by using a pulse signal, a voltage signal is sampled at an output end, and the collected time-domain response signal is an output voltage signal of the analog circuit; (2) applying a discrete wavelet packet transform for the collected time-domain response signal to acquire each wavelet node signal; (3) calculating energy values and kurtosis values of the acquired wavelet node signals to form an initial fault feature data set of the analog circuit; and (4) analyzing the initial fault feature data by the parameter random distribution neighbor embedding winner-take-all method, to acquire optimum low-dimensional feature data. The invention effectively reduces redundancy and interference elements in the fault features, and greatly improves degree of separation of different fault features and degree of polymerization of samples of same fault category.

Analog circuit fault feature extraction method based on parameter random distribution neighbor embedding winner-take-all method

A nonlinear model transformation solving and optimization method for partial discharge positioning based on multi-ultrasonic sensor includes the following steps: (1) constructing a spatial rectangular coordinate system in a transformer, and setting a position of each ultrasonic sensor; (2) constructing a positioning model on the basis of an arrival time positioning method to obtain a nonlinear positioning equation set for solving a position of a PD source; (3) eliminating second-order terms in the nonlinear positioning equation set to transform the nonlinear positioning equation set into a linear equation set; (4) obtaining multiple sample initial values of a coordinate of the PD source; (5) screening the multiple sample initial values; (6) performing clustering processing on the multiple effective sample initial values by adopting an improved K-means algorithm; and (7) selecting a class with most cluster elements, and calculating a mean of the elements of the class to finally determine an optimal coordinate of the PD source. According to the present invention, the present problems of selection difficulty, iteration non-convergence, long operation time, sensitivity to an arrival time error and the like of an iteration algorithm adopted when a nonlinear model is solved are effectively solved.

Nonlinear model transformation solving and optimization method for partial discharge positioning based on multi-ultrasonic sensor

An electromagnetic interference objective complexity evaluation method based on a fast S-transformation time-frequency space model comprises the following steps: (1) carrying out fast S-transformation on space electromagnetic signals acquired in real time to obtain a fast speed S-transformation two-dimensional time-frequency matrix of the signal; (2) calculating time domain occupancy rate T, frequency occupancy rate F, and energy occupancy rate Eof an evaluation object and interference signals in the fast speed S-transformation two-dimensional time-frequency matrix; (3) calculating electromagnetic interference objective complexity C=T*F*Eaccording to the time-frequency space model; and (4) finding a grading standard according to an objective complexity value so as to determine an electromagnetic interference objective complexity type. Compared with the prior art, the electromagnetic interference objective complexity evaluation method based on the fast S-transformation time-frequency space model has the characteristics that a fast S-transformation method is adopted, one-dimensional limitation of Fourier transformation is overcome, three evaluation parameters including the time domain occupancy rate, the frequency occupancy rate and the energy occupancy rate can be rapidly extracted simultaneously, and by adopting the time-frequency space model, the problem of synchronous and overall evaluation of multiple evaluation parameters can be effectively solved.

Electromagnetic interference objective complexity evaluation method based on fast S-transformation time-frequency space model

A Deep Belief Network (DBN) feature extraction-based analogue circuit fault diagnosis method comprises the following steps: a time-domain response signal of a tested analogue circuit is acquired, where the acquired time-domain response signal is an output voltage signal of the tested analogue circuit; DBN-based feature extraction is performed on the acquired voltage signal, wherein learning rates of restricted Boltzmann machines in a DBN are optimized and acquired by virtue of a quantum-behaved particle swarm optimization (QPSO); a support vector machine (SVM)-based fault diagnosis model is constructed, wherein a penalty factor and a width factor of an SVM are optimized and acquired by virtue of the QPSO; and feature data of test data are input into the SVM-based fault diagnosis model, and a fault diagnosis result is output, where the feature data of the test data is generated by performing the DBN-based feature extraction on the test data.

Deep belief network feature extraction-based analogue circuit fault diagnosis method

A space vector pulse width modulation (SVPWM) method for suppressing a common-mode voltage of a multiphase motor includes the following steps: (1) dividing all basic vectors of the multiphase motor into q types, and selecting therefrom x types having equal common-mode voltage magnitude of which an absolute value is smallest; (2) for each type in the x types of basic vectors, structuring y classes of auxiliary vectors according to an optimization model; (3) synthesizing reference vectors by virtue of the auxiliary vectors to obtain functioning time of basic vectors functioning in each switching period; and (4) obtaining an optimal functioning sequence of the basic vectors functioning in each switching period with fewest switching operations of a converter as a purpose. The present invention may effectively suppress a magnitude and frequency of the common-mode voltage of the multiphase motor without increasing calculation complexity or reducing other performance indexes.

Space vector pulse width modulation method for suppressing common-mode voltage of multiphase motor

A 5G-oriented multidimensional adaptive MIMO system including a transmitting antenna array, a first rotary table, a broadband vector signal generator, a receiving antenna array, a second rotary table, a broadband vector signal analyzer and a data acquisition terminal is provided. The broadband vector signal generator and the broadband vector signal analyzer are respectively connected with the transmitting antenna array and the receiving antenna array. The data acquisition terminal is connected with the broadband vector signal generator and the broadband vector signal analyzer. In addition, a method for adjusting radiating modes of antenna ports by using the 5G-oriented multidimensional adaptive MIMO system is also provided.

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Hubei, China

Baiqiang Yin