利用快速傅里叶变换(FFT)研究了一种角度轨迹监测技术,并将其用于航空发电机旋转整流器故障特征提取及在线诊断应用中.首先,连续采集发电机交流励磁机励磁电流信号,每相邻两次数据采集间隔同样的时间.其次,对每次采集的数据均进行FFT处理以获取故障特征信息,该过程在每两次数据采集的间隔内完成.每次处理得到的故障特征信息会形成连续的变化轨迹,通过对该轨迹的研究可以在线监测并诊断旋转整流器的故障模式.最后,通过试验对所提方法进行了验证.

SiC功率管器件广泛应用在航空领域的电能变换、配电等场合,其健康状况十分重要.在SiC器件的健康监测应用中,导通电阻的检测是一项十分重要的技术.为了能够简单准确地得到碳化硅(SiC)MOSFET功率器件的导通电阻,本文提出了一种基于神经网络的SiC MOSFET器件导通电阻估测方法.本文搭建SiC MOSFET导通电阻测试电路仿真和物理试验平台,并使用BP神经网络(BP neural networks,BPNN)对不同温度、不同栅极电压以及不同漏极电流下SiC MOSFET器件的导通电阻数据进行详细描述.最后,对基于BPNN的SiC MOSFET导通电阻估测方法进行效果验证.结果表明,该方法具有精度高和泛化能力强的优点,能够实现SiC MOSFET器件导通电阻的有效估测.

Aiming at the problem of fault prediction of DC/DC converters,the failure characteristic parameter that can reflect the performance degradation status of the converter is studied,and a failure prediction method of DC/DC converter based on the degradation of characteristic parameters is proposed.Firstly,the failure mechanisms of the key components in the converter are analyzed and the failure sensitive parameters that reflect the degradation rules of the components are determined.Then,considering the effect of component degradation on the overall performance of the converter,the change rate of the output voltage ωis taken as the failure characteristic parameter of the converter,which can reflect the failure states of both converter and components.Lastly,Least Square(LS) method,Grey System and Least Square Support Vector Machine(LS-SVM) algorithms are used separately to predict the time series of DC-DC converter fault characteristic parameters and realize the failure prediction of DC/DC converter,and the prediction results are compared and analyzed.The Boost circuit was taken as an example to carry out simulation and experiment,which validates the effectiveness and accuracy of the proposed method.

Digital Circuit and System Design as the basis for professional and technical courses,in cultivating students′ engineering practical ability plays an important role.From the perspecrive of textbook system reform and based on analysis of traditional digital electronic technology teaching material system,this paper introduces in detail the stereoscopic teaching material construction practice,including teaching materials,supporting multimedia courseware,network teaching platform reform content,provides new ideas for the reform of teaching system,for reference.

当前电力电子电路故障预测多为元件级,且未考虑电源、负载波动等工作条件影响。针对此问题,提出了一种仅与电路本身故障相关的电路级故障评估新指标——故障特征参数相对变化量,并基于最小二乘支持向量机(LSSVM)算法实现电力电子电路级故障预测。首先,采用LSSVM算法对电路工作条件时间序列、电路参数时间序列预测;其次求解所预测电路未来工作条件下对应的健康电路参数;利用相同工作条件下,健康电路参数与预测的电路参数计算故障评估指标,最终判定未来某时刻电路是否发生故障。以Buck电路为例进行仿真实验验证了方法的可行性和有效性。

This paper proposes a new module level fault diagnosis method for analog circuits. Firstly, the transfer function is constructed according to the relationship between output and input of the circuit under test (CUT). Every system parameter of the transfer function is expressed by several component parameters. These components are divided into several modules. Then, the way of objective function optimization based on genetic algorithm (GA) is adopted to solve nonlinear equations, which are obtained by multi-frequency testing. Finally, the module level faults are detected by comparing the estimated system parameters to their normal values. The results show that the proposed method is effective to identify system parameters and locate module level faults. (C) 2011 Elsevier Ltd. All rights reserved.

The existing test node selection methods of analog dictionary technique assume that the voltage gap of ambiguity group is 0.7 V. However, this technique is not always accurate to determine the right ambiguity gap for each fault mode. As the probability density of the circuit output approximately satisfies the normal distribution, an accurate technique is introduced to determine the ambiguity gap. Then, this paper proposes a new test node selection method with an extended fault dictionary and the overlapped area values. Firstly, the fault dictionary is constructed with the mean and standard variance values of node voltage. Then, the area detection table is generated by the overlapped area values under normal curves for ambiguity faults, which represent the failure probability of ambiguity faults. Finally, the optimal test node set is selected by fusing fault isolation and overlapped area information. The results show that the proposed method is effective to select the optimal test node set and improve the performance of analog fault diagnosis.

Taking quality course Digital Circuit and System Design as background,the course content as basis,uses project teaching method to make teaching mode exploration and practice.Practice shows that,the project teaching method is able to arouse the students' subjective initiative,is beneficial to blending knowledge,in favor of research teaching and research learning development,so it has better demonstration function and teaching effect.

Currently, fault predictions of power electronic circuit mostly focus on components, and seldom consider the influences of working conditions such as electric network and load fluctuation. An innovative metric only related to the circuit fault for power electronic circuit failure evaluation, named relative shift of fault feature parameter, and a novel method of power electronic circuit fault prediction based on least squares support vector machine(LSSVM) are proposed according to this problem. Working condition time series and circuit parameters time series are predicted based on LSSVM. And then circuit parameters are calculated as the circuit under the predicted working condition is healthy. Thus, the failure evaluation metric is calculated based on the predicted circuit parameters and healthy circuit parameters under same working condition and the future circuit state can be judged finally. Simulation studies on Buck circuit show that the proposed method is feasible and effective.

Using different test stimuli have an affect on the testability of the circuit under test(CUT).According to the Fourier series expression theory,which is described as the periodic function can be decomposed into a direct current component and a series of sine functions,a new optimization method for test stimulus generation of analog circuit is proposed.In this method,the random stimulus function is used as the optimal object,the optimal target is to obtain the maximal distance of different classes of faulty samples in the kernel space,and the constraint conditions are designed on the base of the relationship of amplitude,frequency and phase between the input and the output of the CUT,so a linear optimal model is constructed with one target and multiple constraints.This method has general adaptability.The optimal test stimuli succeed in improving the diagnosis results.

Conventional discrete time mode reconfigurable analog circuits are designed with the switched capacitor technology,which have the disadvantage of function limitation,lower band pass,and being not compatible with digital CMOS process technology in hybrid integrated circuits.This paper presented a Reconfigurable Analog Circuit(RAC) based on Current Mode Sampled Data Technology(CMSDT),which was fully compatible with the digital CMOS process.The Configurable Analog Block(CAB) based on switched current technology was developed,and the programmable interconnect network structure for the switched current CAB was proposed.Three analog circuits for application examples have been achieved respectively by reconfiguration in the 4×2 reconfigurable analog array.The simulation experimental results show that the designed reconfigurable analog circuit is effective and can realize multi-function analog circuit with reconfiguration.

This paper presents a new fault feature preprocessor method for analog circuit fault diagnosis. An information fusion method based on fractional Fourier transform (FRFT) is introduced to extract features from voltages of the circuit under test (CUT). Firstly, the voltage signals gathered from test nodes of the CUT are preprocessed by FRFT, the fractional order p of the FRFT changes from 0 to 1 with a given step. Then, we gain the amplitudes of the transformed signals in fractional space and extract the mutual information entropies as features by a defined division scale. After normalization, the extracted features are used to train a neural network to diagnose faulty components in the CUT. The proposed feature preprocessor method is applied to two CUTs and is compared with three ordinary preprocessing methods in analog circuit fault diagnosis. The experiment results reveal that the proposed method can simplify the structure of the network and improve the diagnosis performance.

There are problems of limited function, low operational speed and insufficient flexibility in the conventional reconfigurable analog circuits. A new current-mode reconfigurable analog circuit is proposed to solve them. The configurable analog block (CAB) based on second-generation current controlled conveyor (CCCII) is designed, which has the advantages of smaller nonlinear distortion, higher operational speed and better anti-interference ability. A new crossbar switch inter-connection network is developed, which can reduce the number of switches, and improve the flexibility and high frequency response of the reconfigurable analog circuit. The forth-order butterworth low-pass filter (LPF) and the analog multiplier are reconfigured with 2×4 reconfigurable analog circuit array. The experimental results show that the proposed reconfigurable analog circuit can effectively realize analog signal processing circuits of different functions through reconfiguration.

Parametric identification method of power electronic circuits is studied in this paper. A new method based on transfer function model in frequency domain (TFMFD) and genetic algorithm (GA) for the parameter identification of power electronic circuits is proposed. Taking the Buck converter circuit as an example, the parameter identification of power electronic circuits is achieved. Firstly, the Buck converter’s transfer function model in frequency domain is established. Secondly, the output voltage and the inductor input voltage are selected as monitoring signals. And the monitoring signals are analyzed by FFT in frequency domain, and the frequency-domain characteristics of the transfer function model are obtained. Lastly, by selecting appropriate frequency points in transfer function model, the frequency response characteristics and GA method are used to estimate the circuit’s parameter. The experimental results show that the new method can be effectively applied in the parameter identification of power electronic circuits.

本文对功率变换电路中电解电容故障预测方法进行了研究,提出了一种基于快速傅立叶变换(FFT)与最小二乘支持向量机(LS-SVM)相结合的故障预测方法.通过对电解电容失效机理进行研究,建立其等效电路故障模型,并选择等效串联电阻(ESR)作为寿命特征参数、输出纹波电压和电容电流作为监测信号;通过FFT对监测信号进行频域分析,计算ESR;利用LS-SVM对ESR回归建模、预测.将提出的方法应用于Buck电路,对电解电容的故障进行预测.实验结果表明,该方法可以准确的对电解电容故障进行预测.

Aiming at the maintenance of equipment in most power plants at home, this paper details the concept of condition maintenance, proposes an overall design scheme for the framework of condition maintenance suitable for electric equipment. The presented scheme takes modular principle as its design thoughts, and the interface of the above framework possesses the features of simpleness and convenience. It is a fleasible condition maintenance scheme for power plants.