Damage Identification of A TLP Floating Wind Turbine by Meta-Heuristic Algorithms

Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring (SHM). In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP (Tension-Leg Platform) floating wind turbine structure. The Genetic Algorithms (GA), Artificial Immune System (AIS), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine (TLPFWT) is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine.     

广西钦州湾红树林抗菌活性菌株Erwinia sp. 5-8的筛选及发酵条件的优化

以金黄色葡萄球菌为指示菌,采用琼脂扩散法从国家海洋局海洋生物活性物质重点实验室广西钦州湾红树林微生物资源库中筛选获得一株具有明显抑菌效果的菌株5-8,对该菌株进行了分子鉴定与系统发育分析。结果表明,此菌为欧文氏菌属(Erwinia)。通过单因子试验对其发酵条件进行了优化,优化后发酵条件为:最佳氮源为蛋白胨,最佳碳源为葡萄糖,发酵培养基初始pH值为8.0,发酵温度为25℃,盐度为1.5,摇瓶装液量30%,接种量为1%(V种子液∶V培养液=1∶100)。     

A blind deconvolution method for ground based telescopes and Fizeau interferometers

In the case of ground-based telescopes equipped with adaptive optics systems, the point spread function (PSF) is only poorly known or completely unknown. Moreover, an accurate modeling of the PSF is in general not available. Therefore in several imaging situations the so-called blind deconvolution methods, aiming at estimating both the scientific target and the PSF from the detected image, can be useful. A blind deconvolution problem is severely ill-posed and, in order to reduce the extremely large number of possible solutions, it is necessary to introduce sensible constraints on both the scientific target and the PSF.In a previous paper we proposed a sound mathematical approach based on a suitable inexact alternating minimization strategy for minimizing the generalized Kullback–Leibler divergence, assuring global convergence. In the framework of this method we showed that an important constraint on the PSF is the upper bound which can be derived from the knowledge of its Strehl ratio. The efficacy of the approach was demonstrated by means of numerical simulations.In this paper, besides improving the previous approach by the use of a further constraint on the unknown scientific target, we extend it to the case of multiple images of the same target obtained with different PSFs. The main application we have in mind is to Fizeau interferometry. As it is known this is a special feature of the Large Binocular Telescope (LBT). Of the two expected interferometers for LBT, one, LINC-NIRVANA, is forthcoming while the other, LBTI, is already operating and has provided the first Fizeau images, demonstrating the possibility of reaching the resolution of a 22.8 m telescope. Therefore the extension of our blind method to this imaging modality seems to be timely.The method is applied to realistic simulations of imaging both by single mirrors and Fizeau interferometers. Successes and failures of the method in the imaging of stellar fields are demonstrated in simple cases. These preliminary results look promising at least in specific situations. The IDL code of the proposed method is available on request and will be included in the forthcoming version of the Software Package AIRY (v.6.1).     

基于支持向量机的水资源预测模型

水资源信息的预测可以为水资源的合理调配、管理和规划提供依据,为提高拟合和预测精度,建立基于支持向量机的水资源信息预测模型,采用捕鱼算法对其参数优化,并应用于地下水水位预测的实例分析,且拟合及预测精度均较高,与神经网络模型方法所取得的结果进行比较,能取得更好效果,表明将回归支持向量机用于水资源信息的拟合、预测是可行的。     

Statistical analysis of fracture properties based on particle swarm optimization and Pearson correlation coefficient method

Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.     

航空影像接缝线的分水岭分割优化方法

提出了一种基于自适应标记分水岭分割的航空影像接缝线优化方法。该方法利用分割区域差异确定接缝线优先穿越区域,然后在优先穿越区域中使用基于最小二叉堆的Dijkstra最短路径算法得到最终的接缝线。试验表明,本文方法获得的接缝线能很好地避开投影差较大的区域,与其他算法的比较也表明本文方法具有更好的效果和效率。     

约束非负矩阵分解框架下高维自适应粒子群端元提取

传统基于约束非负矩阵分解NMF(Nonnegative Matrix Factorization)的高光谱端元提取算法一般存在两个问题:一方面,以固定惩罚系数方法处理端元提取的约束优化问题,难以较好权衡目标项与约束项间的关系,影响提取效果;另一方面,求解过程通常基于梯度算法,依赖于初始值和步长的设定,容易陷入局部最优。针对这些问题本文提出约束NMF框架下高维自适应粒子群端元提取算法HAPSO(High-dimension Adaptive Particle Swarm Optimization)。该算法在端元距离最小约束的NMF框架下,利用粒子群算法PSO替代原梯度算法以增强全局搜索能力;采用高维PSO方法解决了多波段高维问题,并结合种群信息构建自适应惩罚机制以实现端元提取中目标与约束的合理权衡。通过模拟影像和真实影像的实验,证实该算法与传统的NMF端元提取算法相比能够更合理地权衡约束和避免局部最优,具有较好的端元提取效果。     

无人直升机电力线路巡检自动航迹优化

针对目前关于无人直升机的航迹布设研究大多是讨论从起始点到目标点的,而复杂地形条件下的超低空电力线路巡检还没有一套完整的航迹布设方案这一问题,该文在充分考虑无人直升机性能、传感器参数、任务要求以及电力线路巡检过程中应注意问题的基础上,提出了针对无人直升机超低空电力线巡线的自动航迹布设及优化方案,并系统阐述了航迹分段布设、航迹平滑、航迹异常检测和优化等关键技术算法。实验结果表明,该方案可以为无人直升机进行超低空的电力线巡线设计出安全、可靠的航迹。     

高光谱影像特征子集选择方法

针对高维遥感数据的降维困难问题,该文提出并构建了一种融合粒子群优化算法全局寻优能力和支持向量机优秀分类性能的高光谱遥感影像特征子集选择与分类方法。通过引入混沌优化搜索技术改进融合粒子群优化算法的全局寻优能力;提出并采用一种基于粒度的网格搜索策略对支持向量机模型参数进行优化;利用二进制融合粒子群优化算法进行特征选择;然后,支持向量机采用该特征子集所对应的训练数据集进行模型参数优化和分类。实验结果表明该方法能有效地提取出用于分类的最佳波段,具有较高的分类精度。为高光谱遥感影像的特征选择与分类探索出了一种可行的方法。     

地貌学研究趋向与教材内容构建

针对我国地貌学教材既滞后于学科发展,又不能适应新时期人才培养的问题,该文基于近20年来国际地貌学研究内容及发展趋势的分析,提出在现行地貌学教材基础上,增加行星地貌、生物地貌、地貌系统与气候变化、数字地貌、中国地貌概要五个版块内容;教材结构可设计为绪论、内营力地貌、外营力地貌、行星地貌、中国地貌概要、地貌调查与研究方法六部分;将部门地貌学内容删减至整个教材的50%左右;在绪论中增补近20年地貌学理论、技术方法进展,在每章末尾增列建议阅读文献和书目;更新地貌灾害和应用地貌案例、地貌调查与研究方法;制作教学课件和光盘;编写与教材配套的实习指导书。