MRSVD敏感分量在单频周跳探测修复中的应用

准确探测微小周跳历元是周跳修复的关键,精准修复周跳是高质量北斗卫星导航系统(Bei Dou Navigation Satellite System,BDS)定位的难点,为此提出一种基于多分辨奇异值分解(Multi-Resolution Singular Value decomposition,MRSVD)的敏感分量预测模型,用于周跳探测与修复。该方法对探测信号构造Hankle矩阵,并对其进行MRSVD分析,得到一组具有不同分辨率的分量信号。然后对分量信号进行敏感因子评估分析,选取包含周跳特征的分量,构成敏感特征向量,凸显信号的周跳信息,进而通过模极大值谱精准检测出信号中奇异点的位置,实现对微小周跳的准确探测。以筛选出的MRSVD敏感特征向量为基础,构建最小二乘支持向量机(Least Square Support Vector Machine,LS-SVM)预测模型,进行周跳修复。实验结果表明,该方法能够对载波相位中出现的微小周跳进行准确探测与修复,证明了该方法的可行性和有效性。

基于故障敏感分量和改进K近邻分类器的故障状态识别

针对故障状态下的滚动轴承振动信号非线性非平稳性强、噪声干扰大导致的故障敏感特征提取难的问题,在对轴承振动信号进行局域均值分解(local mean decomposition,LMD)的基础上,提出了一种基于故障敏感分量的特征提取与改进K近邻分类器(K-nearest neighbor classifier,KNNC)的故障状态辨识方法。该方法采用相关系数法对LMD分解出的振动分量进行故障敏感性的量化表征,然后对筛选出的信号分量进行时域/频域的特征提取,构建不同故障状态下的特征样本集。为加快故障状态识别速度,排除不良样本的影响,提出一种基于二分K均值聚类的改进KNNC算法,精简了大容量的训练样本,有效去除不良特征样本和干扰点。实验结果表明,以敏感分量特征作为输入的改进KNNC算法能够快速准确地识别轴承不同故障状态。

VMD敏感分量在风电机组主轴故障诊断中的应用

提出基于VMD敏感分量的风力发电机主轴故障诊断方法。利用变分模态分解分析风机主轴的振动信号,将其分解、评估、分析,选取包含信号特征的有效模态分量重构信号。然后提取重构信号的特征值,构成模态分析向量,凸显信号故障信息,结合VPMCD方法进行故障诊断。将所提方法应用于风电机组仿真实验,对主轴外圈、内圈和滚动体故障数据进行分析验证,结果表明该方法的有效性。

一种改进特征模态分解的滚动轴承复合故障特征提取方法

针对滚动轴承故障信号非平稳、多分量并伴随强背景噪声,导致其复合故障特征难以有效分离的问题,提出一种改进特征模态分解(feature mode decomposition,FMD)的特征提取方法。采用FMD将滚动轴承复合故障信号分解为一系列模态分量,对影响分解精度的关键参数特性进行研究,提出了相关参数选取方法。从信号间关联程度和能量角度出发,通过综合评价因子算法选择对故障敏感的模态分量,并经包络解调获取敏感模态分量的包络谱以提取故障特征频率,实现滚动轴承复合故障的诊断。通过仿真信号及实测信号分析,并同变分模态分解(variational mode decomposition,VMD)方法进行比较。结果表明,所提方法可有效抑制噪声干扰影响,提升滚动轴承故障特征信息获取能力,实现滚动轴承复合故障的有效诊断。

基于变分模态分解与最小熵解卷积的齿轮故障诊断

为了准确地进行齿轮故障诊断,结合变分模态分解和最小熵解卷积,给出了一种新的故障诊断方法;首先,以包含啮合频率的分量的包络峭度最大作为原则,确定变分模态分解的分量个数;然后,将齿轮振动信号运用变分模态分解,得到多个分量;选取包含啮合频率的分量作为敏感分量;接着,应用最小熵解卷积,将敏感分量降噪;最后,应用包络分析技术进行故障诊断。通过齿轮断齿故障振动数据的分析,验证了方法的有效性。

基于改进经验小波变换的行星齿轮箱故障诊断

行星齿轮箱振动信号具有复杂多分量和调幅-调频的特点。幅值解调和频率解调方法能够避免传统Fourier频谱中的复杂边带分析,有效识别故障特征频率。经验小波变换通过对信号Fourier频谱的分割构造一组正交滤波器组,能提取具有紧支撑Fourier频谱的单分量成分,再对单分量成分运用Hilbert变换即可实现信号的解调分析。经验小波变换能够有效分离出调幅-调频成分,不存在模态混叠现象,具有完备的理论基础,自适应性好、算法简单、计算速度快。将改进的经验小波变换应用于行星齿轮箱振动信号的解调分析;提出了一种单分量个数的估算方法,解决了经验小波变换中的Fourier频谱划分问题;给出了对故障敏感的信号分量的选取方法,提高了分析的针对性。将改进方法应用于行星齿轮箱振动仿真信号和实验信号分析,验证了该方法的有效性。

基于CEEMD和3点对称差分能量算子的滚动轴承故障诊断方法

为解决传统信号处理方法提取滚动轴承故障特征不精确和Teager能量算子解调信号的解调频率和幅值误差较大的问题,课题组提出一种基于互补集合经验模态分解和3点对称差分能量算子结合的轴承故障特征提取方法CEEMD-DEO3S。课题组首先对滚动轴承进行CEEMD分解前进行去噪处理来增强信号的故障脉冲;然后利用CEEMD将去噪后信号分解为一系列固有模态函数,并依据相关系数原则选择最能表征故障的敏感分量,重构后进行DEO3S解调,依据解调后得到的幅值和频率计算信号的包络谱。实验分析表明:所提方法解调信号的误差更小,提取轴承故障频率更精确。

Application of support vector machine in trip chaining pattern recognition and analysis of explanatory variable effects

In order to improve the accuracy of travel demand forecast and considering the distribution of travel behaviors within time dimension, a trip chaining pattern recognition model was established based on activity purposes by applying three methods： the support vector machine （SVM） model, the radial basis function neural network （RBFNN） model and the multinomial logit （MNL） model. The effect of explanatory factors on trip chaining behaviors and their contribution to model performace were investigated by sensitivity analysis. Results show that the SVM model has a better performance than the RBFNN model and the MNL model due to its higher overall and partial accuracy, indicating its recognition advantage under a smai sample size scenario. It is also proved that the SVM model is capable of estimating the effect of multi-category factors on trip chaining behaviors more accurately. The different contribution of explanatory, factors to trip chaining pattern recognition reflects the importance of refining trip chaining patterns ad exploring factors that are specific to each pattern. It is shown that the SVM technology in travel demand forecast modeling and analysis of explanatory variable effects is practical.

Analysis and Measurement of Mass Transfer in Airlift Loop Reactors

Inter-phase mass transfer is important to the design and performance of airlift loop reactors for either chemical or biochemical applications, and a good measurement technique is crucial for studying mass transfer in multiphase systems. According to the model of macro-scale mass transfer in airlift loop reactors, it was proved that the airlift loop reactor can be regarded as a continuous stirred tank reactor for measuring mass transfer coefficient. The calculated mass transfer coefficient on such a basis is different from the volumetric mass transfer coefficient in the macro-scale model and the difference is discussed. To describe the time delay of the probe response to the change of oxygen concentration in the liquid phase, a model taking into account the time constant of response is es-tablished. Sensitivity analysis shows that this model can be used to measure the volumetric mass transfer coefficient. Applying this model to the measurement of volumetric mass transfer coefficient in the loop reactor, results that co-incide with the turbulence theory in the literate were obtained.

Quantitative investigation on micro-parameters of cemented paste backfill and its sensitivity analysis

The mechanical properties of cemented paste backfill(CPB) depend heavily on its pore structural characteristics and micro-structural changes. In order to explore the variation mechanisms of macro-mechanical characteristics and micro-structure of CPB. CPB specimens with different mass concentrations prepared from the full tailings of Xianglushan Tungsten Ore were micro-tests. Moreover, acquired pore digital images were processed by using the pores(particles) and cracks analysis system(PCAS), and a sensitivity analysis was performed. The results show that as the mass concentration of CPB increases from 70% to 78%, the porosity, the average pore area and the number of pores drop overall, leading to a decline in the pores opening degree and enhancing the mechanical characteristics. As the mass concentration of CPB increases, the trend of fractal dimension, probability entropy and roundness is reduced, constant and increased, which can result in an enhancement of the uniformity, an unchanged directionality and more round pores. According to the definition of sensitivity, the sensitivities of various micro-parameters were calculated and can be ranked as porosity > average pore area > number of pores > roundness > fractal dimension > probability entropy.

Temporal and Spatial Variations of ET 0 and Sensitivity Coefficients in Spring-summer in Eastern Agricultural Areas of Qinghai,China

Reference crop evapotranspiration(ET 0) is a key parameter to calculate crop water requirements.In the paper,ET 0 during 1960-2005 was calculated with FAO-56 PM in eastern agricultural areas of Qinghai,China.Then the sensitivity coefficients of ET 0 to meteorological variables were estimated through the nondimensional partial derivative in FAO-56 PM.Results show that the mean annual ET 0 of the whole area is 904 mm,and ET 0 portrays a very significant decrease during the 46 years.In spatial,ET 0 decreases from southeast to northwest,firstly increases then decreases from southwest to northeast.Through sensitivity analysis,in spring the most sensitive variable is relative humidity,while in summer is temperature.The temperature,sunshine duration and wind speed sensitivity coefficients(S(TA),S(n),S(u)) are higher in middle areas as opposed to surrounding areas,while the relative humidity sensitivity coefficient(S(RH)) has an opposite distribution rule.

Design and optimization of vector coil sensor suited to magnetometric resistivity method

Magnetometric resistivity(MMR)method is a new way to detect dam leakage.The coil sensor is generally used to collect data in geophysical exploration methods.Given the characteristics of accurate vector data requirements and high sensitivity requirement,a three-component MMR air-core coil sensor is designed.Through the analysis of sensor sensitivity and coil structure parameters,the coil structure and turn number are designed.By analyzing the noise source of the sensor,a suitable amplifier is selected to reduce the background noise of the system.Through the analysis of the three-component non-orthogonal angles,the parameters of the non-orthogonal angles of the coils are corrected.Finally,a three-component MMR induction magnetic field sensor is designed.The volume of the sensor is controlled at 0.027 m 3.The background noise of X、Y and Z are 5.030435 nV/Hz@380 Hz and magnetic field sensitivities are 0.18995 pT/Hz@380 Hz.The three channels have good consistency,and the three-component nonorthogonal angles correction error of three components is controlled within 0.2%.

Landslide Susceptibility Mapping by Using Landslide RatioBased Logistic Regression:A Case Study in the Southern Taiwan

The object of the research is to compare the model performance and explain the error source of original logistic regression landslide susceptibility model(abbreviated as or-LRLSM) and landslide ratio-based logistic regression landslide susceptibility model(abbreviated as lr-LRLSM) in the Chishan watershed with a serious landslide disaster after 2009 Typhoon Morakot. The landslide inventory induced by 2009 Typhoon Morakot in South Taiwan is the main research material, while the Chishan watershed is the research area. Six variables, including elevation, slope, aspect, geological formation, accumulated rainfall, and bank erosion, were included in the two models. The performance of lr-LRLSM is better than that of or-LRLSM. The Cox & Snell R2, Nagelkerke R2 value, and the area under the relative operating characteristic curve(abbreviated as AUC) of lrLRLSM is larger than those of or-LRLSM, and the average correct ratio for the lr-LRLSM to predict landslide or non-landslide is larger than that of orLRLSM by 5.0%. The increase of the average correct ratio(abbreviated as ACR) difference from or-LRLSM to lr-LRLSM shows in slope, revised accumulated rainfall, aspect, geological formation and bank erosion variables, and only light decreases in elevation variable. The error sources of continuous variables in building the or-LRLSM is the dissimilarity between the distribution of landslide ratio and production of coefficient and characteristic values, while those of categorical variables is due to low correlation of landslide ratio and the coefficient value of each parameter. Using the classification of landslide ratio as the database to build logistic regression landslide susceptibility model(abbreviated as LRLSM) can revise the errors. The comparison of or-LRLSM and lr-LRLSM in the Chishan watershed also shows that building the landslide susceptibility model(abbreviated as LSM) by using lr-LRLSM is practical and of better performance than that by using the or-LRLSM.

Sensitivity Analysis of a Simplified Fire Dynamic Model

This paper discusses a method for performing a sensitivity analysis of parameters used in a simplified fire model for temperature estimates in the upper smoke layer during a fire. The results from the sensitivity analysis can be used when individual parameters affecting fire safety are assessed. If the variation of a single parameter is found to have a major impact on fire safety, it may be necessary to conservatively select this parameter in order to incorporate additional safety. We compare fire scenarios in rooms surrounded by lightweight as well as heavy walls in order to investigate which parameters are the most significant in each case. We apply the Sobol method, which is a quantitative method that gives the percentage of the total output variance that each parameter accounts for. The most important parameter is found to be the energy release rate that explains 92% of the uncertainty in the calculated results for the period before thermal penetration （te） has occurred. The analysis is also done for all combinations of two parameters in order to find the combination with the largest effect. The Sobol total for pairs had the highest value for the combination of energy release rate and area of opening, which explains 96% of the uncertainty. After thermal penetration, the energy release rate is still the most important parameter, but now only explains 49% of the variation. The second parameter is the thickness of the surface material, which explains 43%.

Prediction of the Maximum Flow by the Model SASIS： Sensibility to the Empirical Parameters of the Shape of the Furrow

The model developed in this research presents effective mechanisms in simulations of a discharge strip understood between the minimum and the maximum allowable values, aiming to determine the relationship between discharge and water application efficiency, deep percolation and runoff rates, and consequently to optimize the performance of the furrow irrigation systems with continuous flow. The flow applied in each furrow must be adapted to the length, to the field slope and to the nature of the ground. The authors studied the maximum non erosive flow （Q,,,~）, in function of parameters obtained from the dimensions of the furrow, being Pl and/92, respectively, the linear and exponential parameters of the potential functions that described the relationship between the area of the cross section of flow （or wetted perimeter） and height of flow; in this way, the multiplicative effect of,01 on the area of the cross section of flow is linear, while ,02 is exponential. It verified a conjugated effect of,or and p20n the value of Q,,~. The results of this research point out for the importance of having an estimate of the parameters of the geometry of the cross section of flow （,01 and ,02） the most precise as possible, being known that the dimensions of this section can result in impracticable values of Qmax, outside of the acceptable strip in the literature, that is from 1.2 to 4.0 L.sl. This sensibility analysis was also of great benefit to create an interface in the software SASIS, capable to guide the user of this tool in the input of appropriate values for ,01 and P2 to the process of simulation of the irrigation for furrow with continuous flow and of the optimization of its performance.

Evaluating the Impact of Adoption of Improved Maize Varieties on Yield in Uganda： A Propensity Score Matching Approach

The main objective of this study was to evaluate the impact of adopting improved maize varieties on crop yield in Uganda using propensity score matching （PSM） algorithms to control for hidden selection bias. The study employed cross-sectional household data collected in 2005/2006 by the Uganda Bureau of Statistics （UBOS） across the country. Data were divided into two parts; the full sample and smallholder farmer sub-sample （those that cultivated less than 5 acres or 2 Hectares of maize in 2004 and 2005）. Then estimation was made of the difference in yields between the adopters and non adopters, the average treatment effect on the treated （ATT） for the full sample and smallholder farmer sub-sample. Matching methods were used to control for hidden selection bias and the standardized bias measure was used to check for the quality of matching. The results indicate that adoption of improved maize seed had a robust positive and significant effect on yields obtained by farmers. The results were consistent for both the full and smallholder farmer sub-samples. Sensitivity analysis using Rosenbaum bounds indicated that the ATT results were fairly robust to hidden selection bias. That is, the results were not sensitive to unobserved selection bias. Therefore it is confidently asserted that the estimated average difference in maize yields between the adopters and non-adopters was due to the effect of planting improved maize seed.

Influences of the Suspension Parameters on the Vehicle Suspension Performance for a Terrain Vehicle

This paper describes an effective methodology for evaluation of the suspension parameters intended to be used for a terrain vehicle. The objective of this approach is to make quick analyses of the sensitivity of the vehicle suspension parameters. For the purpose of developing such a methodology, a mathematical modeling of a quarter vehicles suspension system is developed. Sensitive analysis of the suspension parameters is performed by employing the standard deviation of the vehicle body acceleration, dynamic tire load, and suspension travel. Sensitivity analysis results have shown that the spring stiffness, damping coefficient, tire stiffness and sprung mass have substantial influence on the ride comfort and road holding, while un-sprung mass on the other side has much lower impact in performance of the vehicle suspension system.

Downscaling Crop Water Sensitivity Index Using Monotone Piecewise Cubic Interpolation

Crop-water production functions quantitatively describe the relationship between crop yield and field evapotranspiration. The crop water sensitivity indexes of crop-water production functions, a key factor for optimizing irrigation scheduling in case of water scarcity, are usually obtained from field experiments or other sources for crop growth stages, while their values in shorter intervals are preferred for practical irrigation scheduling. We proposed a method to downscale the sensitivity index from growth stages to shorter intervals by monotone piecewise cubic interpolation of the cumulative sensitivity index curve. This method was used to estimate sensitivity indexes in irrigation intervals of about 10 d for corn and wheat in central Shanxi Province of China. Results showed that the downscaled sensitivity index could reflect the impact of water stress on crop growth both at different growth stages and within each stage. Scenario analysis of water stress at a single growth stage of wheat showed the rationality of downscaling water sensitivity index from growth stages to shorter intervals through interpolation of cumulative sensitivity index, and this proposed downscaling method was superior to the traditional linear downscalin~ method.

Simultaneous sensing of displacement and temperature with a single FBG

A novel fiber Bragg grating(FBG) sensor with simultaneous sensing of displacement and temperature is presented.The FBG is affixed on the cantilever inclinedly.The midpoint of FBG exactly coincides with the zero strain layer of a rectangular beam.The vertical displacement can be measured by the broadened bandwidth of FBG as the bandwidth is insensitive to temperature,while the temperature can be measured by the center wavelength shift as the wavelength shift is insensitive to vertical displacement.With 0.1 nm spectral resolution of the analyzer,sensitivities of bandwidth-displacement and center wavelength-temperature are 0.48 nm/mm and 0.05 nm/℃,resolutions are 0.2 mm and 2.0 ℃,and sensing ranges of displacement and temperature are up to 8.5 mm and 45℃ respectively.Experimental results match theoretical analyses very well.

Electrochemically sensitive supra-crosslink and its corresponding hydrogel

In this work, through inclusion complexation between cyclodextrin (CD) host and ferrocene (Fc) guest, a monomer with double bond was incorporated to the surface of CdS quantum dot (QD). The obtained supra-structure could act as a supra-crosslink (Fc-SCL) in its copolymerizing with N,N-dimethylacrylamide (DMA) leading to a hybrid supramolecular hydrogel (Fc-Gel). Fc-SCL inherited satisfactory electrochemical activity from Fc. When the weight percentage of Fc-SCL in Fc-Gel was increased, an apparent increase of elastic modulus (G ′) was observed. Furthermore, Fc-Gel also exhibited good fluorescent properties. It was also demonstrated that the inclusion complexation of CD and Fc played a crucial role in constructing the hydrogel; therefore, this Fc-Gel was an organic-inorganic hybrid hydrogel induced by supramolecular interaction.