Misalignment Fault Prediction of Wind Turbines Based on Improved Artificial Fish Swarm Algorithm

A misalignment fault is a kind of potential fault in double-fed wind turbines. The reasonable and effective fault prediction models are used to predict its development trend before serious faults occur, which can take measures to repair in advance and reduce human and material losses. In this paper, the Least Squares Support Vector Machine optimized by the Improved Artificial Fish Swarm Algorithm is used to predict the misalignment index of the experiment platform. The mixed features of time domain, frequency domain, and time-frequency domain indexes of vibration or stator current signals are the inputs of the Least Squares Support Vector Machine. The kurtosis of the same signals is the output of the model, and the 3σ principle of the normal distribution is adopted to set the warning line of misalignment fault. Compared with other optimization algorithms, the experimental results show that the proposed prediction model can predict the development trend of the misalignment index with the least prediction error.     

Reducing Cognitive Effort in Scoring Negotiation Space Using the Fuzzy Clustering Model

Negotiation scoring systems are fundamental tools used in negotiation support to facilitate parties searching for negotiation agreement and analyzing its efficiency and fairness. Such a scoring system is obtained in prenegotiation by implementing selected multiple criteria decision-aiding methods to elicit the negotiator’s preferences precisely and ensure that the support is reliable. However, the methods classically used in the preference elicitation require much cognitive effort from the negotiators, and hence, do not prevent them from using heuristics and making simple errors that result in inaccurate scoring systems. This paper aims to develop an alternative tool that allows scoring the negotiation offers by implementing a sorting approach and the reference set of limiting profiles defined individually by the negotiators in the form of complete packages. These limiting profiles are evaluated holistically and verbally by the negotiator. Then the fuzzy decision model is built that uses the notion of increasing the preference granularity by introducing a series of limiting sub-profiles for corresponding sub-categories of offers. This process is performed automatically by the support algorithm and does not require any additional preferential information from the negotiator. A new method of generating reference fuzzy scores to allow a detailed assignment of any negotiation offer from feasible negotiation space to clusters and sub-clusters is proposed. Finally, the efficient frontier and Nash’s fair division are used to identify the recommended packages for negotiation in the bargaining phase. This new approach allows negotiators to obtain economically efficient, fair, balanced, and reciprocated agreements while minimizing information needs and effort.     

基于FDTD的时域混合方法及其在天线前门耦合数值模拟中的应用

强电磁脉冲环境下的平台-机载天线一体化耦合计算属于典型多尺度时域电磁计算问题,采用传统的FDTD方法数值模拟时,由于精细结构的存在导致网格量巨大,计算效率低下。介绍了一种将非均匀FDTD方法与细导线FDTD方法以及多网格集总元件FDTD方法相结合的时域混合方法,能够有效降低计算开销,结合并行计算技术,快速计算得到天线端口上耦合产生的瞬态电压和电流响应,并将该方法成功应用于无人机平台-天线一体化前门耦合数值模拟中。     

Intelligent Fault Diagnosis of Rolling-Element Bearings Using a Self-Adaptive Hierarchical Multiscale Fuzzy Entropy

The fuzzy-entropy-based complexity metric approach has achieved fruitful results in bearing fault diagnosis. However, traditional hierarchical fuzzy entropy (HFE) and multiscale fuzzy entropy (MFE) only excavate bearing fault information on different levels or scales, but do not consider bearing fault information on both multiple layers and multiple scales at the same time, thus easily resulting in incomplete fault information extraction and low-rise identification accuracy. Besides, the key parameters of most existing entropy-based complexity metric methods are selected based on specialist experience, which indicates that they lack self-adaptation. To address these problems, this paper proposes a new intelligent bearing fault diagnosis method based on self-adaptive hierarchical multiscale fuzzy entropy. On the one hand, by integrating the merits of HFE and MFE, a novel complexity metric method, named hierarchical multiscale fuzzy entropy (HMFE), is presented to extract a multidimensional feature matrix of the original bearing vibration signal, where the important parameters of HMFE are automatically determined by using the bird swarm algorithm (BSA). On the other hand, a nonlinear feature matrix classifier with strong robustness, known as support matrix machine (SMM), is introduced for learning the discriminant fault information directly from the extracted multidimensional feature matrix and automatically identifying different bearing health conditions. Two experimental results on bearing fault diagnosis show that the proposed method can obtain average identification accuracies of 99.92% and 99.83%, respectively, which are higher those of several representative entropies reported by this paper. Moreover, in the two experiments, the standard deviations of identification accuracy of the proposed method were, respectively, 0.1687 and 0.2705, which are also greater than those of the comparison methods mentioned in this paper. The effectiveness and superiority of the proposed method are verified by the experimental results.     

Significance Support Vector Regression for Image Denoising

As an extension of the support vector machine, support vector regression (SVR) plays a significant role in image denoising. However, due to ignoring the spatial distribution information of noisy pixels, the conventional SVR denoising model faces the bottleneck of overfitting in the case of serious noise interference, which leads to a degradation of the denoising effect. For this problem, this paper proposes a significance measurement framework for evaluating the sample significance with sample spatial density information. Based on the analysis of the penalty factor in SVR, significance SVR (SSVR) is presented by assigning the sample significance factor to each sample. The refined penalty factor enables SSVR to be less susceptible to outliers in the solution process. This overcomes the drawback that the SVR imposes the same penalty factor for all samples, which leads to the objective function paying too much attention to outliers, resulting in poorer regression results. As an example of the proposed framework applied in image denoising, a cutoff distance-based significance factor is instantiated to estimate the samples’ importance in SSVR. Experiments conducted on three image datasets showed that SSVR demonstrates excellent performance compared to the best-in-class image denoising techniques in terms of a commonly used denoising evaluation index and observed visual.     

Analysis of Electromagnetic Information Leakage Based on Cryptographic Integrated Circuits

Cryptographic algorithm is the most commonly used method of information security protection for many devices. The secret key of cryptographic algorithm is usually stored in these devices’ registers. In this paper, we propose an electromagnetic information leakage model to investigate the relationship between the electromagnetic leakage signal and the secret key. The registers are considered as electric dipole models to illustrate the source of the electromagnetic leakage. The equivalent circuit of the magnetic field probe is developed to bridge the output voltage and the electromagnetic leakage signal. Combining them, the electromagnetic information leakage model’s function relationship can be established. Besides, an electromagnetic leakage model based on multiple linear regression is proposed to recover the secret key and the model’s effectiveness is evaluated by guess entropy. Near field tests are conducted in an unshielded ordinary indoor environment to investigate the electromagnetic side-channel information leakage. The experiment result shows the correctness of the proposed electromagnetic leakage model and it can be used to recover the secret key of the cryptographic algorithm.     

水体重金属激光诱导击穿光谱定量分析方法对比研究

建立了适用于激光诱导击穿光谱探测的多元线性回归、神经网络回归和支持向量机回归三种定量反演算法模型, 以水体重金属Ni为例进行了回归实验测试和对比分析. 多元线性回归、神经网络回归和支持向量机回归的平均相对标准偏差分别为7.60%, 4.86%, 2.35%; 最大相对标准偏差分别为23.35%, 15.20%, 8.29%; 平均相对误差分别为25.98%, 10.58%, 2.72%, 最大相对误差分别为116.47%, 47.38%, 9.89%. 研究为进一步实现水中痕量金属元素的快速定量分析提供了方法和数据参考. 关键词： 光谱学 激光诱导击穿光谱 支持向量机回归 重金属     

Temperature Dependence of Integrated Intensity Bands in IR-Absoption Spectra of (NH4)2AF6 Complexes

The contribution refers to the temperature dependence of IR-absorption spectra (NH₄)₂AF₆ (A - Si and Ge). It is found that with temperature decreasing, the integrated intensities of the bands corresponding to anion fundamentals, increase, while those of cation, decrease. An explanation is given to the phenomena detected, which is based on variations in the strength of the outer-sphere interaction with the temperature, and subsequent redistribution of electron density.     

Theoretical analysis of the radiation effect on the transient behavior of optoelectronic integrated devices

Theoretical analysis of the radiation effect on transient behavior of an optoelectronic integrated device composed of a heterojunction phototransistor and a light emitting diode is studied theoretically. First, the transient behavior and the rise time of this device before radiation are investigated based on the frequency response of the constituent devices and the optical feedback inside the device. Second, the effect of neutron irradiation flux on the transient behavior of this device is theoretically studied. The results show that, by increasing the optical feedback inside the device, the rise time in the amplification mode is increased along with an increasing output, while that in the switching mode can be reduced effectively, and the neutron irradiation reduces the transient response and the rise time in both the amplification and switching modes. This type of model can be exploited as optical amplifier, optical switching device, and other applications.     

某工程地基基坑支护探讨

软土地基中的支护是基础工程的关键,在节约成本的前提下,选择合理的支护结构至关重要．通过对某公司将要开发的2个基坑支护方案的项目进行的相关分析、计算和探讨,总结出了软土地基中的基坑支护方案的选择原则及其相对应的施工措施等．