直接数字频率合成技术在声学释放器中的应用

直接数字频率合成技术(DDS)是一种新的频率合成方法,它具有转换时间短、相位变化连续、全数字可编程等优点.文中介绍了ADI公司生产的AD7008芯片作为频率信号源在声学释放器中的应用.     

Effects of salinity fluctuation amplitudes on growth, osmolarity, Na＋-K＋-ATPase activity and Hsp70 of juvenile Chinese shrimp Fenneropenaeus chinensis Osbeck

The effects of various salinity fluctuation amplitudes (2, 4, 6 and 8) on the growth, osmolarity, Na⁺-K⁺-ATPase activity and Hsp70 of juvenile Fenneropenaeus chinensis cultured in seawater with a salinity of 20 were studied. The results show that weight gain in the salinity fluctuation treatments was better than that in control; in particular, the weight gain of treatments S4 and S0, at 231.8% and 196.3%, respectively, was significantly different (P<0.05). The hemolymph osmolarity of treatments S0, S2, S4, S6 and S8 was 635.4, 630.8, 623.6, 614.4 and 600.3 mOsm/kg, respectively, and decreased with increasing salinity fluctuation amplitude. The level of Na⁺-K⁺-ATPase activity in gills of F. chinensis was higher than that in hepatopancreas, but there were no significant differences among all treatments, either in gills or hepatopancreas (P>0.05). The relative level of Hsp70 in treatment S4 was 48.4% and 40.4% higher than control in muscle and eyestalks, respectively, with the highest values being recorded under a salinity fluctuation amplitude of 4.     

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基于自适应峰值分解的广义局部频率时频分析方法

往复压缩机振动信号具有复杂的多源冲击特性,表现较强的非平稳性,传统的时频分析方法难以提取有效的故障特征.以傅氏变换为基础的传统频率概念和以希尔伯特变换为基础的瞬时频率概念存在固有缺陷,提出一种广义局部频率的概念,并结合自适应峰值分解方法,实现信号时频分布的构造途径;与HHT时频分析方法进行仿真对比,并应用到往复压缩机振动信号故障特征提取.结果表明,基于自适应峰值分解的广义局部频率方法有效揭示往复压缩机不同故障的多源冲击振动信号时频特征,为往复压缩机故障诊断提供一种新的手段.     

基于洪峰模数的山洪灾害雨量预警指标研究

山洪灾害预警是防御山洪的重要非工程措施,雨量预警指标是山洪灾害预警的关键。目前的雨量预警指标计算方法对水文气象资料条件以及模型建模率定都有很高的要求,并不适用于基层防汛人员。因此,本文基于全国山洪灾害调查评价成果数据,提出了一种运用洪峰模数计算雨量预警指标的简便、易用的方法。该方法以小流域洪水计算推理公式为基础,将公式中流量与流域面积的比值用洪峰模数表示,得到基于洪峰模数的临界雨量估算公式,并考虑流域土壤含水量等因素,分析临界雨量变化阈值,最终得到雨量预警指标。本文以云南省绥江县双河小流域为例,计算结果显示不同时段（1 h、3 h、6 h）净雨量和预警时段呈线性关系。降雨损失计算中洼地蓄水和植被截留在不同时段相同,土壤下渗在不同的时段不相同。在此基础上,计算不同土壤含水量条件下,不同时段的雨量预警指标。最后,对临界流量、降雨损失和预警指标进行了合理性分析,结果显示预警指标和调查评价结果及实测降雨都比较接近,计算的预警指标合理。本研究为基层山洪灾害预警提供了一种快速、便捷的预警指标计算方法,为预警指标计算提供技术支持。     

利用三维地震资料研究夹河煤矿煤层厚度

夹河煤矿位于徐州市西北部,设计生产能力为140万t/a,新构造活动不强,构造稳定性较好。通过对矿区地震特征、煤储层特征分析,认为区内煤层稳定且储量大,该文以夹河煤矿为例,利用常规解释方法和地震属性参数技术解释了2煤层的煤层厚度,分析了地震属性剖面及煤层厚度图的成图方法,从而找出煤层厚度的变化规律,取得了较好的地质效果,为矿井采掘提供高精度地震勘探资料。     

基于局部回波幅值统计的海杂波背景下小目标检测

针对传统舰载雷达和岸基雷达很难检测出海杂波背景下小目标的现状,提出一种基于局部回波幅值统计的方法来检测海杂波背景下小目标.该算法基于数学统计思想:计算不同距离单元海杂波的幅值的最大值和标准偏差,分析发现距离单元含有小目标回波的最大幅值明显小于其它距离单元只含有海杂波回波的最大幅值,距离单元含有小目标回波的幅值的标准偏差明显大于距离单元只含有海杂波回波的幅值的标准偏差,因此可以在对小目标没有任何先验知识条件下,较准确地检测出海杂波背景下的小目标.实验证明,该算法是有效的.     

近20年来中国滨海地带区域经济分异特点研究

以地级行政区为地域单元,采用多指标综合作为衡量指标,对中国滨海地带经济地域分异特征即经济发展水平的峰谷相间特征进行了研究。首先研究了峰谷相间地域格局的发育过程;然后探讨了区域产业结构和城市化水平的时序演化特征;最后总结了上述时序过程和空间过程的时空关联特征。研究的结果表明,中国滨海地带已经形成了区域之间、区域组合之间、南与北之间多层次的地域经济分异。     

Spatial and multivariate analysis of geochemical data from metavolcanic rocks in the Ben Nevis area, Ontario

A study of the lithogeochemistry of metavolcanics in the Ben Nevis area of Ontario, Canada has shown that factor analysis methods can distinguish lithogeochemical trends related to different geological processes, most notably, the principal compositional variation related to the volcanic stratigraphy and zones of carbonate alteration associated with the presence of sulphides and gold. Auto- and cross-correlation functions have been estimated for the two-dimensional distribution of various elements in the area. These functions allow computation of spatial factors in which patterns of multivariate relationships are dependent upon the spatial auto- and cross-correlation of the components. Because of the anisotropy of primary compositions of the volcanics, some spatial factor patterns are difficult to interpret. Isotropically distributed variables such as CO ₂ are delineated clearly in spatial factor maps. For anisotropically distributed variables (SiO ₂ ), as the neighborhood becomes smaller, the spacial factor maps becomes better. Interpretation of spatial factors requires computation of the corresponding amplitude vectors from the eigenvalue solution. This vector reflects relative amplitudes by which the variables follow the spatial factors. Instability of some eigenvalue solutions requires that caution be used in interpreting the resulting factor patterns. A measure of the predictive power of the spatial factors can be determined from autocorrelation coefficients and squared multiple correlation coefficients that indicate which variables are significant in any given factor. The spatial factor approach utilizes spatial relationships of variables in conjunction with systematic variation of variables representing geological processes. This approach can yield potential exploration targets based on the spatial continuity of alteration haloes that reflect mineralization.List of symbols c _i Scalar factor that minimizes the discrepancy between andU _i - D Radius of circular neighborhood used for estimating auto- and cross-correlation coefficients - d Distance for which transition matrixU is estimated - d _ij Distance between observed valuesi andj - E Expected value - E _i Row vector of residuals in the standardized model - F(d _ij) Quadratic function of distanced _ij F(d _ij)=a+bd _ij+cd _ij ² - L Diagonal matrix of the eigenvalues ofU - _i Eigenvalue of the matrixU;ith diagonal element ofL - N Number of observations - p Number of variables - Q Total predictive power ofU - R Correlation matrix of the variables - R _0j Variance-covariance signal matrix of the standardized variables at origin;j is the index related tod andD (e.g.,j=1 ford=500 m,D=1000 m) - R _1j Matrix of auto- and cross-correlation coefficients evaluated at a given distance within the neighborhood - R _m ² Multiple correlation coefficient squared for themth variable - S _i Column vectori of the signal values - s _k ² Residual variance for variablek - T _i Amplitude vector corresponding toV _i;ith row ofT=V ^–1 - T Total variation in the system - U Nonsymmetric transition matrix formed by post-multiplyingR ₀₁ ^–1 byR _ij - U _i Componenti of the matrixU, corresponding to theith eigenvectorV _i;U _i= _iV_iT_i - U* _i ComponentU _i multiplied byc _i - U _ij Sum of componentsU _i+U _j - V _i Eigenvector of the matrixU;ith column ofV withUV=VL - w Weighting factor; equal to the ratio of two eigenvalues - X _i Random variable at pointi - x _i Value of random variable at pointi - y _i Residual ofx _i - Z _i Row vectori for the standardized variables - z _i Standardized value of variable