雨流-回线法及二维疲劳载荷分布假设检验

提出对实测载荷谱进行计数处理的雨流 -回线法 ,使用该法能够简便地将实测载荷谱分离出独立的完整应力循环 ;并提出了二维疲劳载荷分布假设检验及其参数估计方法。最后 。

高压回线法探测电力电缆故障实测案例分析

笔者对阻抗探测技术及其电缆故障经典探测法进行了深入分析,指出了基于电桥电路技术的回线法的特点与存在问题。然后,笔者根据实测经验,针对隐蔽性较强的高阻故障,给出了基于电缆故障回线法(经典探测法)的电缆故障探测技巧,并通过实测案例予以说明。

第三讲 回线法应用举例

难点与技巧 1.难点传统回线法具有较强的环境适应性,尤其适用于矿山、化工厂、石油厂等有易燃易爆物质场合的电缆故障探测。回线法测距的接线方式有两种:缪氏回线法(Murry Loop)和范氏回线法(Varlay Loop),见图3-1。

Influence of confined water on the limit support pressure of tunnel face in weakly water-rich strata

In the process of shield tunneling through soft soil layers,the presence of confined water ahead poses a significant threat to the stability of the tunnel face.Therefore,it is crucial to consider the impact of confined water on the limit support pressure of the tunnel face.This study employed the finite element method(FEM)to analyze the limit support pressure of shield tunnel face instability within a pressurized water-containing layer.Subsequently,a multiple linear regression approach was applied to derive a concise solution formula for the limit support pressure,incorporating various influencing factors.The analysis yields the following conclusions:1)The influence of confined water on the instability mode of the tunnel face in soft soil layers makes the displacement response of the strata not significant when the face is unstable;2)The limit support pressure increases approximately linearly with the pressure head,shield tunnel diameter,and tunnel burial depth.And inversely proportional to the thickness of the impermeable layer,soil cohesion and internal friction angle;3)Through an engineering case study analysis,the results align well with those obtained from traditional theoretical methods,thereby validating the rationality of the equations proposed in this paper.Furthermore,the proposed equations overcome the limitation of traditional theoretical approaches considering the influence of changes in impermeable layer thickness.It can accurately depict the dynamic variation in the required limit support pressure to maintain the stability of the tunnel face during shield tunneling,thus better reflecting engineering reality.

TEM中心回线测深解释新参数Δn的数学模型研究

层状大地上中心回线及重叠回线的近区视电阻率公式中,延时t的幂指数n以往都当作常数,实际是一变数。笔者推导证明它的差值Δn与视纵向电导S的对数差分相当,因此可以用于直接划分地层的解释。为此做了相当数量的数学模型计算,结果表明在一定条件下能较好地划分地层,但观测精度要求很高。

常见地下电力电缆故障及其探测方法讲座——第二讲 电缆故障常用探测方法分析

由于电缆种类繁多,故障状态复杂,故电缆故障探测是一件费时、费力的事。电缆故障探测常会给用户带来长时间停电,如探测方法选择不当,还可能给被测电缆带来新的伤害。实践过程中常有'六分靠仪器,四分靠经验'的说法。因此,了解仪器特性与选择合适方法对电缆安全有效的故障探测非常必要。下面把当前现场传统的电缆故障探测基本步骤与方法做简单的说明。

地下电缆故障探测技术

本文对故障电缆绝缘层的损伤进行了分析,根据实践经验,针对隐蔽性较强的高阻故障,提出了环境适应性较强的回线法探测技巧。

INCREMENTAL AUGMENT ALGORITHM BASED ON REDUCED Q-MATRIX

Reduced Q-matrix （Qr matrix） plays an important role in the rule space model （RSM） and the attribute hierarchy method （AHM）. Based on the attribute hierarchy, a valid/invalid item is defined. The judgment method of the valid/invalid item is developed on the relation between reachability matrix and valid items. And valid items are explained from the perspective of graph theory. An incremental augment algorithm for constructing Qr matrix is proposed based on the idea of incremental forward regression, and its validity is theoretically considered. Results of empirical tests are given in order to compare the performance of the incremental augment algo-rithm and the Tatsuoka algorithm upon the running time. Empirical evidence shows that the algorithm outper-forms the Tatsuoka algorithm, and the analysis of the two algorithms also show linear growth with respect to the number of valid items. Mathematical models with 10 attributes are built for the two algorithms by the linear regression analysis.

回线装置在探测地下金属管线中的应用

“回线法”也就是电磁法勘探中的“不接地回线法”,本文从理论到实践介绍回线装置在探测地下金属管线中的应用 重点介绍该方法在为勘察施工提供指定区域(钻孔)地下有无地下金属管线、探测地下电性连接不良的金属管线或探测长度规模较小的地下金属管线及探测口径较大或口径较小管线所具有的显著效果。

中心回线瞬变电磁测深能力分析

为了了解中心回线瞬变电磁法的测深能力,建立了4个不同的地电模型,运用CST软件进行了数值模拟,模拟了低阻均匀薄层周围磁场的空间分布规律,并对不同埋深下低阻均匀薄层的感应电动势曲线进行对比分析。数值模拟结果表明中心回线瞬变电磁法在数百米深度范围内具有明显的异常特征,埋深越浅,异常的幅值越大。仿真结果很好地反映了低阻薄层异常体的存在。

Feasibility of central loop TEM method for prospecting multilayer water-fi lled goaf

With deep mining of coal mines, prospecting multilayer water-filled goaf has become a new content that results from geophysical exploration in coalfields. The central loop transient electromagnetic （TEM） method is favorable for prospecting conductive layers because of the coupling relationship between its field structure and formation. However, the shielding effect of conductive overburden would not only require a longer observation time when prospecting the same depth but also weaken the anomalous response of underlying layers. Through direct time domain numerical simulation and horizontal layered earth forward modeling, this paper estimates the length of observation time required to prospect the target, and the distinguishable criterion of multilayer water-filled goal is presented with observation error according to the effect of noise on observation data. The observed emf curves from Dazigou Coal Mine, Shanxi Province can distinguish multilayer water-filled goaf. In quantitative inversion interpretation of observed curves, using electric logging data as initial parameters restrains the equivalence caused by coal formation thin layers. The deduced three-layer and two-layer water-filled goals are confirmed by the drilling hole. The result suggests that when observation time is long enough and with the anomalous situation of underlying layers being greater than the observation error, the use of the central loop TEM method to orosoect a multilaver water-filled goaf is feasible.

Using Path Analysis to Identify the Influence of Climatic Factors on Spring Peak Flow Dominated by Snowmelt in an Alpine Watershed

Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.

Thermal Error Compensation for Telescopic Spindle of CNC Machine Tool Based on SIEMENS 840D System

In this paper, eddy current sensors and thermocouple sensors were employed to measure the thermal field and thermal deformation of a spindle of a telescopic CNC boring-milling machine tool, respectively. A linear regression method was proposed to establish the thermal error model. Furthermore, two compensation methods were implemented based on the SIEMENS 840D system by using the feed shaft of z direction and telescopic spindle respectively. Experimental results showed that the thermal error could be reduced by 73.79% when using the second compensation method, and the thermal error could be eliminated by using the two compensation methods effectively.

The Impacts of Permafrost Change on NPP and Implications:A Case of the Source Regions of Yangtze and Yellow Rivers

This paper studies the relationship between net primary productivity (NPP) and annual average air temperature (GT) at 0cm above ground in permafrost regions by using revised Chikugo NPP model,cubic spline interpolating functions,and non-linear regression methods.The source regions of the Yangtze and Yellow Rivers were selected as the research areas.Results illustrate that:(1) There is significant non-linear relationship between NPP and GT in various typical years;(2) The maximum value of NPP is 6.17,5.87,7.73,and 5.41 DM·t·hm-2 ·a-1 respectively,and the corresponding GT is 7.1,10.0,21.2,and 8.9 o C respectively in 1980,1990,2000 and 2007;(3) In 1980,the sensitivity of NPP to GT is higher than in 1990,2000 and 2007.This tendency shows that the NPP presents change from fluctuation to an adaptation process over time;(4) During 1980～2007,the accumulated NPP was reduced to 8.05,and the corresponding carrying capacity of theoretical livestock reduced by 11%;(5) The shape of the demonstration region of ecological compensation system,livelihood support system,and science appraisal system in the source regions of Yangtze and Yellow Rivers are an important research for increasing the adaptation capacity and balancing protection and development.

Development of a mass model in estimating weight-wise particle size distribution using digital image processing

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.

Pyrolysis Characteristics and Kinetics of Methyl Oleate Based on TG-FTIR Method

The thermal decomposition characteristics of methyl oleate were preliminarily investigated under nitrogen atmo-sphere by a thermogravimetric analyzer when the ester was heated at a heating rate of 10℃/min from room temperature to 600℃. Furthermore, the pyrolytic and kinetic characteristics of methyl oleate were intensively studied at different heating rates. The gaseous species obtained during thermal decomposition were also identiifed by the TG-FTIR coupling analysis. The results showed that the pyrolysis of methyl oleate proceeded in three stages, viz. the drying stage, the main pyrolysis stage and the residual pyrolysis stage. The initial decomposition temperature, the maximum weight loss temperature, the peak decomposition temperature and the rate of maximum weight loss of methyl oleate increased with the increasing heating rates. Gaseous CO, CO2 and H2O were the typical decomposition products from pyrolysis of methyl oleate. In addition, a kinetic model for thermal decomposition of methyl oleate was built up based on the experimental results using the Coats-Redfern integral method and the multiplelinear regression method. The activation energy, the preexponential factor, the reaction order and the kinetic equation for thermal decomposition of methyl oleate were obtained. Comparison of the experimental data with the calculated ones and analysis of statistical errors of pyrolysis ratios demonstrated that the kinetic model was reliable for studying the pyrolysis of methyl oleate. Finally, the kinetic compensation effect between the preexponential factors and the activation energy in the pyrolysis of methyl oleate was also conifrmed.

Policy variables affecting marginal level of low carbon employment: an empirical study based on provincial data of China

Low Carbon Employment is an inevitable choice for the purpose of ＂energy-saving and emission reduction＂ and ＂promoting employment＂. By Multi-variable Linear Backward Regression method, this study presents an empirical analysis of the emplovment impact of policy variables indexes that involves economic pull, industry upgrading, population development, technical inputs and so on. The paper demonstrates that wide range offactors will affect low carbon employment, that industry upgrading will affect how carbon employment remarkably, that to increase years of people education will notably improve low carbon employment level of secondary vocational-technical labor, and that to raise technical inputs will significantly enhance college students＇ low carbon employment.

Parameter estimation of cutting tool temperature nonlinear model using PSO algorithm

In cutting tool temperature experiment, a large number of related data could be available. In order to define the relationship among the experiment data, the nonlinear regressive curve of cutting tool temperature must be constructed based on the data. This paper proposes the Particle Swarm Optimization (PSO) algorithm for estimating the parameters such a curve. The PSO algorithm is an evolutional method based on a very simple concept. Comparison of PSO results with those of GA and LS methods showed that the PSO algorithm is more effective for estimating the parameters of the above curve.

Study on mine earthquake activity rules for Laohutai coal mine in Fushun of Liaoning

According to earthquake data of Fushun earthquake administration,the seismic analysis and statistical methods are utilized in order to analyze earthquake frequency,"b"-value timing and energy creep trends in Laohutai coal mine. By using least squares linear regression method,the relational expression between frequency and magnitude of mine earthquake in Laohutai coal mine is given. And the possible largest magnitude mine earthquake inferred has also been calculated. And this paper also provides a theoretical basis for further study of mine earthquake activity.

NonliNonlinear GPC with In-place Trained RLS-SVM Model for DOC Control in a Fed-batch Bioreactor

In this study, Saccharomyces cerevisiae (baker's yeast) was produced in a fed-batch bioreactor at the optimal dissolved oxygen concentration (DOC) and growth medium temperature. However, it is very difficult to control the DOC using conventional controllers because of the poorly understood and constantly changing dynamics of the bioprocess. A generalized predictive controller (GPC) based on a nonlinear autoregressive integrated moving average exogenous (NARIMAX) model is presented to stabilize the DOC by manipulation of air flow rate. The NARIMAX model is built by an improved recursive least-squares support vector machine, which is trained by an in-place computation scheme and avoids the computation of the inverse of a large matrix and memory reallocation. The proposed nonlinear GPC algorithm requires little preliminary knowledge of the fermentation process, and directly obtains the nonlinear model in matrix form by using iterative multiple modeling instead of linearization at each sampling period. By application of an on-line bioreactor control, experimental results demonstrate the robustness, effectiveness and advantages of the new controller.