Multi-objective iterative optimization algorithm based optimal wavelet filter selection for multi-fault diagnosis of rolling element bearings

Rolling element bearings (REBs) play an essential role in modern machinery and their condition monitoring is significant in predictive maintenance. Due to the harsh operating conditions, multi-fault may co-exist in one bearing and vibration signal always exhibits low signal-to-noise ratio (SNR), which causes difficulties in detecting fault. In the previous studies, maximum correlated kurtosis deconvolution (MCKD) has been validated as an efficient method to extract fault feature in the fault signals. Nonetheless, there are still some challenges when MCKD is applied to fault detection owing to the rigorous requirements of multiple input parameters. To overcome limitation, a multi-objective iterative optimization algorithm (MOIOA) for multi-fault diagnosis is proposed. In this method, correlated kurtosis (CK) is taken as a criterion to select optimal Morlet wavelet filter using the whale optimization algorithm (WOA). Meanwhile, to further eliminate the effect of the inaccurate period on CK, the update process of period is incorporated. After that, the simulated and experimental signals are utilized to testify the validity and superiority of the MOIOA for multiple faults detection by the comparison with MCKD. The results indicate that MOIOA is efficient to extract weak fault features even with heavy noise and harmonic interferences.     

高程点与高程注记的匹配及其应用

在基于AutoCAD的地形图中,提出解决高程点与高程注记匹配方法,并利用高程注记作为高程点的属性的方法实现高程点与高程注记的组合,以及在高程处理中的一些应用.     

An improved attribute reduction scheme with covering based rough sets

Attribute reduction is viewed as an important preprocessing step for pattern recognition and data mining. Most of researches are focused on attribute reduction by using rough sets. Recently, Tsang et al. discussed attribute reduction with covering rough sets in the paper (Tsang et al., 2008), where an approach based on discernibility matrix was presented to compute all attribute reducts. In this paper, we provide a new method for constructing simpler discernibility matrix with covering based rough sets, and improve some characterizations of attribute reduction provided by Tsang et al. It is proved that the improved discernibility matrix is equivalent to the old one, but the computational complexity of discernibility matrix is relatively reduced. Then we further study attribute reduction in decision tables based on a different strategy of identifying objects. Finally, the proposed reduction method is compared with some existing feature selection methods by numerical experiments and the experimental results show that the proposed reduction method is efficient and effective.     

基于ATP-ABE的访问控制方案

对访问控制机制中存在的安全性和有效性的问题进行了研究，提出了基于访问树剪枝的属性加密ATP-ABE（Access Tree Pruning Attribute Based Encryption）的访问控制方案。当ATP-ABE算法需要访问它的树型结构访问策略时，通过剪枝处理访问树结构中包含用户ID属性节点的分支，提高了用户所有者DO（Data Owner）管理和控制属性的效率，更加有效地实现了数据共享。还为访问树结构设计了许可访问属性，使DO仍保留共享数据的关键属性，并且能够完全控制它们的共享数据。基于决策双线性密钥交换算法DBDH（Decisional Bilinear Diffie-Hellman）假设分析了ATP-ABE方案的安全性，研究结果表明与两种经典ABE方案比较，ATP-ABE更加有效地减少了算法的系统设置、私钥生成、密文大小、用户属性撤销以及加解密过程中的计算开销，并给出了定量结论。     

Hierarchical correlated Q-learning for multi-layer optimal generation command dispatch

This paper presents a novel hierarchical correlated Q-learning (HCEQ) algorithm to solve the dynamic optimization of generation command dispatch (GCD) in the Automatic Generation Control (AGC). The GCD problem is to dynamically allocate the total AGC generation command from the central to each individual AGC generator. The proposed HCEQ is a novel multi-agent Q-learning algorithm based on the concept of correlated equilibrium point, and each AGC generator with an agent is to optimize its regulation participation factor and coordinate its decision with others for the overall GCD performance enhancement. In order to cope with the curse of dimensionality in the GCD problem with the increased number of AGC plants involved, a multi-layer optimum GCD framework is developed in this paper. In this hierarchical framework, the multiobjective design and a time-varying coordination factor have been formulated into the reward functions to improve the optimization efficiency and convergence of HCEQ. The application of the proposed approach has been fully verified on the China southern power grid (CSG) model to demonstrate its superior performance and dynamic optimization capability in various power system scenarios.     

Estimation of the Parameters of the Gamma Distribution by Sample Quantiles

This paper deals with large sample estimation of the location parameter (α₁ and the scale parameter α₂ in the gamma distribution with known shape parameter. Best linear unbiased estimates based on k sample quantiles are used. For a given k, the optimum spacings of the sample quantiles can be replaced by simpler “nearly optimum” spacings at virtually no loss of asymptotic efficiency. The theory behind the nearly optimum spacings is briefly reviewed. The major part of the paper concerns estimation of α₂ when α₂ is known. Nearly optimum spacings together with the coefficients to be used in computing the estimates are presented in a number of tables for k = 1(1) 10, and various values of the shape parameter. The paper also contains brief discussions of estimation of α₁, when α₂ is known, and simultaneous estimation of α₁ and α₂.     

Further investigations into the reproducibility of check-all-that-apply (CATA) questions for sensory product characterization elicited by consumers

The purpose of the present research was further investigate the reproducibility of check-all-that-apply (CATA) questions for sensory product characterization. Evaluations obtained when such questions are used by consumers are rarely replicated and therefore reproducibility of the data may be at risk. Results from the present work, which included five studies, each with 100–200 consumers across a range of product categories, revealed that sensory product characterizations obtained using CATA questions with consumers are highly reproducible. Hence, the research confirms previous research by Jaeger, Chheang, et al. (2013) and extends it to the use of CATA terms in randomised presentation order as has been recommended to avoid satisficing response behavior. In the future, if CATA studies are conducted without replication and researches seek to examine the reliability of CATA data, the use of a posterior bootstrapping re-sampling approach is suggested.     

General equivalence between two kinds of noise-correlation filters

A recent comment (Chang, 2014) theoretically demonstrated that for the linear system with the correlated process and measurement noises, the GASF framework proposed in the paper Wang et al. (2012) was equivalent to the conventional de-coupling filtering framework. In this note, we would further show that such equivalence between the two frameworks can be justified in a more general way, even for the nonlinear system.     

Reliability analysis of uncertain dynamical systems using correlated function expansion

Reliability analysis of uncertain dynamical systems is considered. The excitations are modeled as non-stationary Gaussian processes, whereas parametric uncertainties due to structural randomness are modeled as non-Gaussian random variables. The structural responses are, therefore, non-Gaussian processes. The limit state is formulated in terms of the extreme value distribution of the response process. Developing these extreme value statistics analytically is not straightforward, which makes failure probability estimations difficult. An alternative procedure is investigated for computing exceedance probabilities. Proposed approach involves generating a full functional operational model, which approximates the original limit surface. Once the approximate form of the original limit state is defined, the failure probability can be obtained by statistical simulation. Thus, the method can be integrated with commercial finite element software, which permits uncertainty analysis of large structures with complexities that include material and geometric nonlinear behavior.     

利用.Net4.0的特性实现AOP的方法研究

AOP技术为开发者提供了一种描述横切关注点的机制,现介绍了一种在.Net开发环境下利用.Net4.0的新特性实现的方法拦截,从而实现AOP技术的设计方案,同时给出了动态织入和静态织入.