螺旋侧板厚度对浮式风力机Spar平台涡激载荷的影响

Spar平台因其特殊的深吃水立柱式结构,在来流影响下极易发生涡激运动。为探究不同厚度螺旋侧板对浮式风力机Spar平台涡激载荷的影响,基于CFD方法,针对不同厚度螺旋侧板,对平台进行了数值模拟并详细分析平台的升阻力系数、压力场及涡量场等流场参数。结果表明:螺旋侧板可有效抑制涡激载荷,且随厚度增加,升力系数幅值先增加后减小,阻力系数逐步减小;在研究范围内,螺旋侧板厚度为0.10 D时,升力系数幅值最小,阻力系数与原型平台在同一范围内,对涡激载荷的抑制效果最好。     

海上风机基础与塔架体系实时安全评估方法研究

海上风机所处环境恶劣,基础与塔架等支撑结构在使用阶段受到荷载和非荷载因素,会产生累积损伤和性能退化。为了实时掌握基础与塔架体系的运行状态及安全性,进行合理的检修与维护,提出了一种基于神经网络的实时安全评估方法。结果表明:结合风况、风机运行等信息,仅在风机基础及塔架关键部位设置少量监测设备即可满足安全实时评估的数据要求;考虑限值比较、单点误差分析、总体误差分析后,可对基础与塔架局部及整体安全性进行实时评价。经实例论证,预测结果与监测数据较为接近,具有较好的实用性,可为类似工程提供参考。     

Optimal linear filter design for systems with correlation in the measurement matrices and noises: recursive algorithm and applications

This paper addresses the optimal least-squares linear estimation problem for a class of discrete-time stochastic systems with random parameter matrices and correlated additive noises. The system presents the following main features: (1) one-step correlated and cross-correlated random parameter matrices in the observation equation are assumed; (2) the process and measurement noises are one-step autocorrelated and two-step cross-correlated. Using an innovation approach and these correlation assumptions, a recursive algorithm with a simple computational procedure is derived for the optimal linear filter. As a significant application of the proposed results, the optimal recursive filtering problem in multi-sensor systems with missing measurements and random delays can be addressed. Numerical simulation examples are used to demonstrate the feasibility of the proposed filtering algorithm, which is also compared with other filters that have been proposed.     

ECOC-DRF: Discriminative random fields based on error correcting output codes

We present ECOC-DRF, a framework where potential functions for Discriminative Random Fields are formulated as an ensemble of classifiers. We introduce the label trick, a technique to express transitions in the pairwise potential as meta-classes. This allows to independently learn any possible transition between labels without assuming any pre-defined model. The Error Correcting Output Codes matrix is used as ensemble framework for the combination of margin classifiers. We apply ECOC-DRF to a large set of classification problems, covering synthetic, natural and medical images for binary and multi-class cases, outperforming state-of-the art in almost all the experiments.     

Towards subject independent continuous sign language recognition: A segment and merge approach

This paper presents a segment-based probabilistic approach to robustly recognize continuous sign language sentences. The recognition strategy is based on a two-layer conditional random field (CRF) model, where the lower layer processes the component channels and provides outputs to the upper layer for sign recognition. The continuously signed sentences are first segmented, and the sub-segments are labeled SIGN or ME (movement epenthesis) by a Bayesian network (BN) which fuses the outputs of independent CRF and support vector machine (SVM) classifiers. The sub-segments labeled as ME are discarded and the remaining SIGN sub-segments are merged and recognized by the two-layer CRF classifier; for this we have proposed a new algorithm based on the semi-Markov CRF decoding scheme. With eight signers, we obtained a recall rate of 95.7% and a precision of 96.6% for unseen samples from seen signers, and a recall rate of 86.6% and a precision of 89.9% for unseen signers.     

On solutions to fuzzy stochastic differential equations with local martingales

This paper deals with a class of fuzzy stochastic differential equations (FSDEs) driven by a continuous local martingale under the Lipschitzian condition. Such equations can be useful in modeling hybrid systems, where the phenomena are simultaneously subjected to two kinds of uncertainties: randomness and fuzziness. The solutions of the FSDEs are the fuzzy stochastic processes, and their uniqueness is considered to be in a strong sense. Thus, the existence and uniqueness of solutions to the FSDEs under the Lipschitzian condition is first proven. Moreover, some asymptotic properties of the solutions to the FSDEs are investigated. Finally, an illustrating example on the interest term model is provided.     

用三元共聚改性剂制PVC耐热管材

利用自行研制的三元共聚耐热改性剂与聚氯乙烯（PVC）共混制成耐热管材专用料，考察了共混体系中耐热改性剂、抗冲改性剂、填料及热稳定剂等各组分对材料拉伸强度、冲击强度和维卡软化点等综合性能的影响，同时对氯化聚氯乙烯和自制耐药改性剂的耐药和加工性能进行了比较，所研制的耐热改性剂与PVC混合后耐热效果较好，且易挤出加工。研制的耐热管材的维卡软化点可达100℃，比无规聚丙烯管材的维卡耐热性能要高。     

Monte Carlo simulation of radiation-induced solid state polymerization

A Monte Carlo method was used for a computer simulation of radiation-induced solid state polymerization. The propagation of polymer chains was simulated by means of self-avoiding random walks on a tetrahedral lattice. The initiation and termination of the chains were modelled by pseudorandom processes. The influence of conditions of the in-source process on the post-polymerization kinetics and on the degree of polymerization of the polymers was studied.     

垃圾焚烧管式布风流化床的冷态实验

在床截面为300mm×300mm、床高为4. 4m的管式布风流化床实验台上,分别对宽筛分下不同颗粒粒度、不同床层高度、不同截面流速、布风的均匀性以及非平衡布风时颗粒流化特性进行实验研究,为未来垃圾衍生燃料的流化燃烧实验提供基础数据。管式布风流化床的开孔方向与夹角大小对床层压降变化影响明显,向下开孔角度越小,动能消耗越大,但床层稳定性能好。随着料层高度增加,各布风管间的布风更趋于平衡,流化的稳定与均匀性能也越好。管组压降失衡时,床层压降不平衡明显增加,波动幅度增大,不稳定性明显高于正常流化状态。     

Markov随机场与Gaussian曲线在MR图像分割中的应用

针对扫描的人脑组织MR图像边缘分辨率低、模糊性大的特点,本文提出了一种基于模糊Markov随机场和Gaussian曲线相结合的MR图像最佳阈值分割方法。该方法通过对图像的像素邻域属性的统计将模糊论引入其中,建立模糊Markov随机场,并利用Gaussian曲线对二维直方图最佳一维投影进行拟合,确定出图像中各脑组织的二维阈值点,在二维直方图上实现对脑组织的分割。通过实验表明,本算法能够有效提高脑组织的分辨率,对噪声的鲁棒性、结果区域的连通性相对于一维Otsu和二维Otsu算法都有了很大的提高。