基于高光谱成像的小麦白粉病与条锈病识别

小麦白粉病和条锈病是我国两种最普遍、最具破坏性的小麦病害，且田间常常混合发生。由于病源和发病机理不同，有必要对这两种病害进行准确区分和识别，以采取不同的防治措施。基于ImSpector V10E高光谱成像系统采集的条锈菌侵染叶片、白粉菌侵染叶片和健康叶片(共计320个)在375～1 017 nm范围内的高光谱图像，利用高斯平滑等预处理方法得到三种小麦叶片的平均光谱曲线，发现小麦白粉病和条锈病的敏感波段均集中在550～680 nm的色素强吸收位置，且趋势基本一致。针对两种病害的响应波段交叉重叠的问题，通过主成分分析-载荷法(PCA)、连续投影算法(SPA)和竞争性自适应重加权算法(CARS)对小麦叶片的光谱信息进行有效降维，分别优选出3、6、30个敏感波段和特征波长；在此基础上，采用最小二乘-支持向量机和极限学习机两种分类算法分别基于全波段、PCA、SPA和CARS的优选波段，建立白粉病、条锈病和健康叶片的判别模型。结果表明，8种模型的准确识别率均在94.58%以上。其中，主成分分析-载荷法结合极限学习机模型最优，训练集与校正集的正确识别率分别为99.18%和100%，且结构简单，仅含有三个变量(占全波段的1.1%)。最后，通过对小麦白粉病、条锈病以及健康叶片的显微结构分析，发现病菌入侵叶片，破环细胞结构，导致叶绿素含量减少，光合作用效能降低,进而使得小麦在可见光波段光吸收程度减弱，反射率增大。可见，利用作物的高光谱图像信息能够准确地识别不同类型的小麦病害，为研发作物病害在线识别的多光谱系统提供重要的理论依据。     

Properties of cat-eye modulating retro-reflector and its application with piezoelectric transducer

Piezoelectric cat-eye modulating retro-reflector (MRR) is the core component of an acousto-optic retro-identification system. The influence of the optical parameters (link distance l, lens focal length f and the detector diameter r) to the cat-eye effect was analyzed theoretically and experimentally. A piezoelectric cat-eye retro-identification (PCERI) system was built, and an information transmission ratio of 2 kHz was achieved which can satisfy an access control system.     

不同产地黄芪的红外光谱鉴别研究

采用红外光谱、二阶导数红外光谱和二维相关红外光谱,对四种不同产地的黄芪原药材进行了鉴别研究。结果表明:不同产地黄芪的红外光谱和二阶导数红外谱具有一定的相似度,与淀粉的红外谱图比对,4个不同产地的黄芪均含有淀粉,其中陕西绥德产黄芪的淀粉含量比其它3个产地黄芪的都要高。山西浑源和山西天镇产黄芪谱图的1 510、1 425cm-1木质素特征峰比内蒙古固阳和陕西绥德产黄芪的更为明显,说明前二者产黄芪中木质素含量高于后二者产黄芪。在二维相关红外谱图上,根据4个产地黄芪的相对峰强度的差异,可进行产地的鉴别。研究结果表明对于不同产地黄芪的鉴别,红外三级鉴定法是一种快速有效的新方法。     

Bias in modal parameters using the direct and iterative RFP identification procedures

In the rational fraction polynomial method [1] the identification of modal parameters is obtained through a direct linear least-square optimization technique but a particular form of fitting error is minimized. An iterative algorithm has been recently developed which uses the true fitting error [2]. In this paper a statistical analysis is developed to estimate the bias effects on the identified parameters when the data are polluted with noise. Both the direct and iterative procedures are considered. Numerical simulations are used to validate the results predicted by the theoretical analysis, which shows that the iterative approach is by far more efficient than the direct method.A first version of this paper was presented at 17th Int. Seminar on Modal Analysis, Leuven (Belgium), 23–25 September 1992, and preprinted in the Proceedings.     

Development of adaptive modeling techniques for non-linear hysteretic systems

Adaptive estimation procedures have gained significant attention by the research community to perform real-time identification of non-linear hysteretic structural systems under arbitrary dynamic excitations. Such techniques promise to provide real-time, robust tracking of system response as well as the ability to track time variation within the system being modeled. An overview of some of the authors’ previous work in this area is presented, along with a discussion of some of the emerging issues being tackled with regard to this class of problems. The trade-offs between parametric-based modeling and non-parametric modeling of non-linear hysteretic dynamic system behavior are discussed. Particular attention is given to (1) the effects of over- and under-parameterization on parameter convergence and system output tracking performance, (2) identifiability in multi-degree-of-freedom structural systems, (3) trade-offs in setting user-defined parameters for adaptive laws, and (4) the effects of noise on measurement integration. Both simulation and experimental results indicating the performance of the parametric and non-parametric methods are presented and their implications are discussed in the context of adaptive structures and structural health monitoring.     

Linear Dynamical Identification: An Integral Transform seen as a Complex Wavelet Transform

This paper presents a technique that allows the direct linearidentification of frequency response functions from the computation ofa weighted integral transform. This transform allows toemphasize the influence of the poles and zeros of the frequencyresponse functions its formation is based on the Cauchy--Weierstrass theorem. It isthen shown that this transform is directly linked to a complex wavelettransform. This representation with a wavelet transform provides abetter understanding of the amplification effects of the weightedintegral transform and allows the singularities analysis.     

结构模态参数的时序分析(ARMAV模型)识别法

本文简述了用时间序列分析(ARMAV 模型)识别结构模态参数的原理,对建模方法进行了分析,并对建模分析中至关重要的初值选择问题进行了讨论,提出了一种有效的初值的选取方法;在模拟计算部分中,用 Wilson-θ积分法模拟了一个三个自由度的振动和低信噪比、大阻尼振动和密集模态等复杂情形,对用时序方法(ARMAV 模型)识别模态参数的能力进行了检验;最后通过对实验数据进行有效的预处理后,用时序方法(ARMAV 模型)识别出一个真实结构(圆盘)的第一、二阶模态参数,并得到结构的完整振型.     

木材种类的近红外光谱和模式识别

木材的种类识别是木材加工和贸易的一个重要环节，传统的木材种类识别方法主要有显微检测法和木材纹理识别法，其操作繁琐，耗时长，成本高，不能满足当前需求。本研究利用木材的近红外光谱(NIRS)结合模式识别方法，以期实现木材种类的快速准确识别。采用近红外光谱结合主成分分析法(PCA)、偏最小二乘判别分析法(PLSDA)和簇类独立软模式法(SIMCA)三种模式识别对58种木材进行种类鉴别研究；5点平滑、标准正态变量变换(SNV)、多元散射校正(MSC)、Savitzky-Golay一阶导数(SG 1st-Der)和小波导数(WD)五种光谱预处理方法用于木材光谱的预处理；校正集和测试集样品的正确识别率(CRR)用于模型的评价。采用PCA方法，通过样品的前三个主成分空间分布图分辨木材种类的聚类情况。在建立PLSDA模型，原始光谱的正确识别率最高，分别为88.2%和88.2%；5点平滑处理的光谱校正集和测试集的CRR分别为88.1%和88.2%；SNV处理的光谱校正集和测试集的CRR分别为84.4%和84.5%；MSC处理的光谱校正集和测试集的CRR分别为83.1%和84.2%；SG 1st-Der处理的光谱校正集和测试集的CRR分别为81.8%和82.7%；WD(小波基为“Haar”，分解尺度为80)处理的光谱校正集和测试集的CRR分别为87.3%和87.2%。可知，在PLSDA模型中，木材光谱未经预处理种类识别效果最后好。在建立SIMCA模型过程中，原始光谱的校正集和测试集的CRR分别为99.7%和99.4%；5点平滑处理的光谱校正集和测试集的CRR分别为100%和100%；SNV处理的光谱校正集和测试集的CRR分别为99.5%和99.1%；MSC处理的光谱校正集和测试集的CRR分别为99.0%和98.4%；SG 1st-Der的光谱校正集和测试集的CRR分别为81.8%和82.7%；WD处理的光谱校正集和测试集的CRR分别为100%和100%。可知，在SIMCA模型中，木材光谱经平滑和小波导数处理后的识别效果最好，且光谱的校正集和测试集CRR都为100%。采用三种模式结合五种不同的预处理方法对木材近红外光谱进行定性建模识别时，由于木材样本属性复杂，主成分分布图相互交织，PCA无法识别出58种木材；原始光谱的PLSDA模型可以得到较好的判别模型，但校正集和测试集的CRR只有88.2%和88.2%；木材光谱经过5点平滑或WD预处理后的SIMCA模型可达到最好的识别效果，校正集和测试集的CRR均为100%，且WD-SIMCA模型因子数比5点平滑SIMCA模型小，模型更为简化，故WD-SIMCA为58种木材种类识别的最优模型。研究表明光谱预处理方法可以有效的提高木材种类识别精度，有监督模式识别方法SIMCA可以用来建立有效的木材识别模型，近红外光谱结合模式识别可以为木材种类的识别提供一种快速简便的分析方法。     

木蜡油涂饰对檀香紫檀易混树种的红外光谱影响分析

卢氏黑黄檀和染料紫檀木材特征与檀香紫檀相似，特别是两者经过加色精的木蜡油涂饰后，用肉眼很难与珍贵的檀香紫檀分辨。市场上销售的很多红木家具为了达到防腐、防尘、防开裂的性能以及提高红木表面光泽度和显现珍贵木材的纹理，大都进行了木蜡油表面涂饰加工，因而只研究木材本身的鉴别不能满足市场需求。借助红外光谱（FTIR）结合二阶导数红外光谱（SDIR）和二维相关红外光谱（2D-IR）技术，对经过木蜡油涂饰的檀香紫檀（Pterocarpus santalinus）、染料紫檀（P.tinctoricus Welw）和卢氏黑黄檀（Dalbergia louuelii）进行了红外光谱分析。通过打磨-涂底油-打磨-涂面油-干燥的涂饰工艺对3个树种进行表面涂饰。分别取3个树种素材的木粉和经过表面涂饰的木材表面的木粉进行FTIR，SDIR和2D-IR三级鉴别分析，同时测定了木蜡油的FTIR谱图。结果表明：(1）木蜡油FTIR谱图在2 925，1 733，1 465和1 378 cm-1较强的特征峰出峰位置与3个树种木材本身的出峰位置基本重合，且在2 854 cm-1处归属于亚甲基C-H对称伸缩振动，1 233 cm-1处归属于羧基C-O伸缩振动，729 cm-1处归属于长链的亚甲基C-H弯曲振动的特征峰在涂饰后三种样品的FTIR谱图中有相同的体现，说明木蜡油涂饰未对3个树种红外谱图的特征峰产生影响；3个树种表面涂饰前后FTIR谱图的相关系数同时可以对木蜡油涂饰未对3个树种的特征峰产生影响进行佐证；(2）FTIR谱图在1 595，1 060和836 cm-1处可以将染料紫檀与檀香紫檀和卢氏黑黄檀两个树种区分开；SDIR谱图可以在1 551 cm-1将卢氏黑黄檀区分开，并能进一步对染料紫檀的特征峰进行验证；在2D-IR光谱中，在1 425~1 800和850~1 300 cm-1两个波段范围，檀香紫檀的自动锋明显区别于其他两个树种，在1 250 cm-1处归属于醚类化合物的吸收峰可以将檀香紫檀区分开。目前红木识别主要利用木材解剖方法，表面涂饰大多集中在木材材色变化研究。借助红外光谱技术，最终利用各个树种和木蜡油在红外光谱谱图中不同的特征峰体现的官能团差异直接推测特征成分的含量差异，无须测定其特征成分的具体物质，进而实现准确、快速地把经木蜡油表面涂饰的檀香紫檀及与其易混淆的染料紫檀和卢氏黑黄檀区分鉴别。     

Time reversal for obstacle location in elastodynamics from acoustic recording

The Note is concerned with a feasibility study of time reversal in a non-homogeneous elastic medium, from data recorded in an acoustic medium. Our aim here is to determine the presence and some physical properties of elastic “inclusions” (unknown, not observable solid objects, characterized by their elastic properties) from partial observations of acoustic waves scattered by these inclusions. A finite element numerical method, based on a variational acousto-elastodynamics formulation, is derived and used to solve the forward, and then, the time-reversed problem. A criterion, derived from the reverse time migration framework, is introduced, to help construct images of the inclusions to be determined. Numerical illustrations on configurations that mimic the breast cancer configuration are proposed, and show that one can differentiate between two inclusions, even with different properties.