Grey GM(1,1) Model with Function-Transfer Method for Wear Trend Prediction and its Application

Trend forecasting is an important aspect in fault diagnosis and work state supervision. The principle, where Grey theory is applied in fault forecasting, is that the forecast system is considered as a Grey system; the existing known information is used to infer the unknown information's character, state and development trend in a fault pattern, and to make possible forecasting and decisions for future development. It involves the whitenization of a Grey process. But the traditional equal time interval Grey GM (1,1) model requires equal interval data and needs to bring about accumulating addition generation and reversion calculations. Its calculation is very complex. However, the non equal interval Grey GM (1,1) model decreases the condition of the primitive data when establishing a model, but its requirement is still higher and the data were pre processed. The abrasion primitive data of plant could not always satisfy these modeling requirements. Therefore, it establishes a division method suited for general data modeling and estimating parameters of GM (1,1), the standard error coefficient that was applied to judge accuracy height of the model was put forward; further, the function transform to forecast plant abrasion trend and assess GM (1,1) parameter was established. These two models need not pre process the primitive data. It is not only suited for equal interval data modeling, but also for non equal interval data modeling. Its calculation is simple and convenient to use. The oil spectrum analysis acted as an example. The two GM (1,1) models put forward in this paper and the new information model and its comprehensive usage were investigated. The example shows that the two models are simple and practical, and worth expanding and applying in plant fault diagnosis.

EFFICIENT ESTIMATION OF FUNCTIONAL-COEFFICIENT REGRESSION MODELS WITH DIFFERENT SMOOTHING VARIABLES

In this article,a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different coefficient functions is defined.First step,by the local linear technique and the averaged method,the initial estimates of the coefficient functions are given.Second step,based on the initial estimates,the efficient estimates of the coefficient functions are proposed by a one-step back-fitting procedure.The efficient estimators share the same asymptotic normalities as the local linear estimators for the functional-coefficient models with a single smoothing variable in different functions.Two simulated examples show that the procedure is effective.

Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

In heating, ventilating and air-conditioning （HVAC） systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno （T-S） fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.

Universal triple I fuzzy reasoning algorithm of function model based on quotient space

Aiming at the deficiencies of analysis capacity from different levels and fuzzy treating method in product function modeling of conceptual design, the theory of quotient space and universal triple I fuzzy reasoning method are introduced, and then the function modeling algorithm based on the universal triple I fuzzy reasoning method is proposed. Firstly, the product function granular model based on the quotient space theory is built, with its function granular representation and computing rules defined at the same time. Secondly, in order to quickly achieve function granular model from function requirement, the function modeling method based on universal triple I fuzzy reasoning is put forward. Within the fuzzy reasoning of universal triple I method, the small-distance-activating method is proposed as the kernel of fuzzy reasoning; how to change function requirements to fuzzy ones, fuzzy computing methods, and strategy of fuzzy reasoning are respectively investigated as well; the function modeling algorithm based on the universal triple I fuzzy reasoning method is achieved. Lastly, the validity of the function granular model and function modeling algorithm is validated. Through our method, the reasonable function granular model can be quickly achieved from function requirements, and the fuzzy character of conceptual design can be well handled, which greatly improves conceptual design.

FURTHER RESEARCH ON THE SPLINE MODEL METHOD OF KED ANALYSIS IN A PLANAR FLEXIBLE LINKAGE

This paper relates to the deep research on the Splinc Model Method of KED analysis. With the use of cubic B-splinc function as a link’s transverse deflection interpolation function, the principle of virtual displacement is presented as a basic theory for the general formulation of the equations of motion, and thus abandoned the kinematic assumption and the instantaneous structure assumption which arc used in the Spline Model Method. In thc same time, the nonlinear terms sue as coupling terms between thc rigid body motion and elastic deformation arc included. New member’s spline models are established. Mass matrix, Coriolis mass matrix, normal and tangential mass matrix, linear stiffness matrix, nonlinear stiffness matrix and rotation matrix arc derived. The kinematic differential equations of a member and system are deduced in the end. The Newmark direct integration method is used as the solution scheme of the kinematic differential equations to get the periodic response.

Numerical modeling calculation for the spatial distribution characteristics of horizontal field transfer functions

Applying 3-dimension finite difference method, the distribution characteristics of horizontal field transfer functions for rectangular conductor have been computed, and the law of distribution for Re-part and Im-part has been given. The influences of source field period, the conductivity, the buried depth and the length of the conductor on the transfer functions were studied. The extrema of transfer functions appear at the center, the four corners and around the edges of conductor, and move with the edges. This feature demonstrates that around the edges are best places for transfer functions' observation.

Extended Jacobian Elliptic Function Expansion Method and Its Applications in Biology

In this work, an extended Jacobian elliptic function expansion method is proposed for constructing the exact solutions of nonlinear evolution equations. The validity and reliability of the method are tested by its applications to Dynamical system in a new Double-Chain Model of DNA and a diffusive predator-prey system which play an important role in biology.

Study of visualized simulation and analysis of nuclear fuel cycle system based on multilevel flow model

Complex energy and environment system, especially nuclear fuel cycle system recently raised socialconcerns about the issues of economic competitiveness, environmental effect and nuclear proliferation. Only underthe condition that those conflicting issues are gotten a consensus between stakeholders with different knowledgebackground, can nuclear power industry be continuingly developed. In this paper, a new analysis platform has beendeveloped to help stakeholders to recognize and analyze various socio-technical issues in the nuclear fuel cycle systembased on the functional modeling method named Multilevel Flow Models (MFM) according to the cognition theoryof human being. Its character is that MFM models define a set of mass, energy and information flow structures onmultiple levels of abstraction to describe the functional structure of a process system and its graphical symbol representationand the means-end and part-whole hierarchical flow structure to make the represented process easy to beunderstood. Based upon this methodology, a micro-process and a macro-process of nuclear fuel cycle system wereselected to be simulated and some analysis processes such as economics analysis, environmental analysis and energybalance analysis related to those flows were also integrated to help stakeholders to understand the process of decision-making with the introduction of some new functions for the improved Multilevel Flow Models Studio, and finallythe simple simulation such as spent fuel management process simulation and money flow of nuclear fuel cycleand its levelised cost analysis will be represented as feasible examples.

Optimization Mathematical Model of Pile Forces for Offshore Piled Breasting Dolphins

An optimization mathematical model of the pile forces for piled breasting dolphins in the open sea under various loading conditions is presented. The optimum layout with the well distributed pile forces and the least number of piles is achieved by the multiplier penalty function method. Several engineering cases have been calculated and compared with the result of the conventional design method. It is shown that the number of piles can be reduced at least by 10%～20% and the piles' bearing state is improved greatly.

Three-Di mensional Model for Strip Hot Rolling

A three-dimensional model for strip hot rolling was developed, in which the plastic deformation of strip, the thermal crown of rolls, roll deflection and flattening were calculated by rigid-plastic finite element method, finite difference method, influential function method and elastic finite element method respectively. The roll wear was taken into consideration. The model can provide detailed information such as rolling pressure distribution, contact pressure distribution between backup rolls and work rolls, deflection and flattening of work rolls, lateral distribution of strip thickness, and lateral distribution of front and back tensions. The finish rolling on a 1 450 mm hot strip mill was simulated.

Fast Time-Varying Channel Model Research for Data Processing of Wireless

With the complexity and uncertainty of mobile communication network environment, solving the classical mathematical analysis also becomes more complicated. The model tree of basis function method based on Fourier series is proposed in this paper. Model tree method is the improvement of regression tree analysis. Basis function applied here is four-order Fourier series. When the Fourier coefficients are calculated, the Gauss elimination method is implemented for solving equations. The complexity of the algorithm is n3log(n).

轨道车辆垂向轮轨力时域识别对比及其机器学习修正

为了尽可能减小轨道车辆垂向轮轨力时域识别中存在的误差,以时域法为基础,开展了基于机器学习修正的轨道车辆垂向轮轨力识别研究.首先建立了车辆动力学仿真模型,获取了车辆在随机轨道激励下以250km/h速度行驶时的轴箱加速度响应和垂向轮轨力.其次,建立了Green函数法、状态空间法这2种时域法对应的动载荷识别模型,对状态空间法的初值误差进行了分析,并引入多项式拟合法修正其趋势项误差,进而对比分析了2种方法的计算精度和计算效率.然后,针对时域法存在的识别误差,提出采用NARX(nonlinear autoregressive models with exogenous inputs)模型对识别误差进行训练和预测,用于消减模型中存在的如响应观测不全与观测噪声等因素造成的影响,进而对时域法识别结果进行修正,提高识别精度.最后,通过一个10自由度轨道车辆垂向动力学模型,对方法的正确性进行了验证.研究结果表明:2种方法对轨道车辆垂向轮轨力均具有较高的识别精度,对于各轮对的识别精度各有优劣;在计算效率方面,状态空间法比Green函数法更优;经NARX模型修正的2种时域法对轨道车辆垂向轮轨力均具有很好的识别效果,识别值与正演值的Pearson相关系数大于0.99,为极强相关.基于NARX模型的机器学习误差修正方法可有效提高时域识别精度,可以为后续轨道车辆轮轨力预测提供参考,具有较强的工程运用价值.

Stability of Stochastic Logistic Model with Ornstein-Uhlenbeck Process for Cell Growth of Microorganism in Fermentation Process

Current research is concerned with the stability of stochastic logistic equation with Ornstein-Uhlenbeck process. First, this research proves that the stochastic logistic model with Ornstein-Uhlenbeck process has a positive solution. After that, it also introduces the sufficient conditions for stochastically stability of stochastic logistic model for cell growth of microorganism in fermentation process for positive equilibrium point by using Lyapunov function. In addition, this research establishes the sufficient conditions for zero solution as mentioned in Appendix A due to the cell growth of microorganism μmax, which cannot be negative in fermentation process. Furthermore, for numerical simulation, current research uses the 4-stage stochastic Runge-Kutta (SRK4) method to show the reality of the results.

A STUDY OF B-P UNIFIED VISCOPLASTIC CONSTITUTIVE MODEL

By combining the Bodner-Partom constitutive model and equivalent stressfunction, finite element methods and program on analyzing non-elastic deformation and stress forthermal viscoplastic material are studied in this paper, and it's the first time that this materialmodel is used in a kind of engineering software-MARC. Thermal viscoplastic behavior of hightemperature alloy GH536 specimen with gap is analyzed by this program. The research results show itis feasible to analyze thermal viscoplastic behavior of specimen or structure by applying B-P model.

Object-Oriented Modeling of the Variation of Acceleration and Deceleration Characteristics in Relation to Speed Bands for Railway Vehicles

Automated operation and artificial intelligence technology have become essential for ensuring the safety, efficiency, and punctuality of railways, with applications such as ATO (Automatic Train Operation). In this study, the authors propose a method to efficiently simulate the kinematic characteristics of railroad vehicles depending on their speed zone. They utilized the function overloading function supported by a programming language and applied the fourth-order Lunge-Kutta method for dynamic simulation. By constructing an object model, the authors calculated vehicle characteristics and TPS and compared them with actual values, verifying that the developed model represents the real-life vehicle characteristics accurately. The study highlights potential improvements in automated driving and energy consumption optimization in the railway industry.

关于函数逼近法理论的一点认识

现有教材中常将本质相同的连续函数最佳平方逼近问题、离散数据最小二乘曲线拟合问题分开阐述.本文重新组织现有理论结构给出一般性结论同时也阐述两类问题的区别——最小二乘法思想在空间理论上的统一、同一向量组在不同线性空间中线性无关性表达形式的不同、元素在不同线性空间上内积表达式的差异.最后通过例题说明两类问题求解步骤的统一——连续函数最佳平方逼近也需要“造型”,并通过实例显示同一向量组的线性无关性在不同空间中的具体表现.这种新的知识点组织方式即避免了相同公式的重复性推导,又可使学生通过比较学习避免混淆便于理解.

基于分数阶黏壶元件的岩石损伤蠕变模型

目的为了建立一个能描述岩石蠕变全过程的蠕变模型。方法首先以分数阶黏壶元件描述岩石的黏弹性,采用基于Kachanov损伤率公式的损伤体描述岩石的粘塑性并串联一个胡克体建立成只有四个元件的蠕变模型。然后,将其本构方程推广到三维应力状态,考虑球应力,并引入一个屈服函数来准确判断岩石是否发生非稳定蠕变。最后,采用最小二乘法分析得到模型参数,用红砂岩和砂质泥岩的蠕变实验数据验证模型的有效性。结果新的蠕变模型理论曲线与实验数据曲线吻合较好,可以描述岩石蠕变的全过程。结论新的蠕变模型解决了经典模型在描述岩石蠕变时的模型复杂和参数较多的问题,对研究岩石蠕变特性具有一定的参考价值。

变形监测灰色预测模型对比及替代方法研究

将变形监测灰色预测模型分为传统GM(1,1)模型及其改进模型、非齐次灰色模型、GM(1,1)幂模型及其改进模型3种类型,以Origin拟合函数Exp2PModl、Exponential和SRichards2作为3类灰色预测模型的替代方法,基于理论研究和实例验证对比分析3类灰色预测模型及其替代方法。结果表明,3类灰色预测模型在拟合函数、有无极限值、适合等时距或非等时距建模和适用范围等方面存在显著差异,需要根据变形监测数据特征选择合适的灰色预测模型类别;与3类灰色预测模型相比,Origin拟合函数在参数求解和建模数据要求上更具优势,而且可以得到相当甚至更高的拟合或预测精度,除需要编程实现的特殊优化目标外,完全可以代替灰色预测模型用于变形监测。

Fuzzy image restoration using modulation transfer function

The key difficulty of restoring a fuzzy image is to estimate its point spread function( PSF). In the paper,PSF is modelled based on modulation transfer function( MTF). The first step is calculating the image MTF. In the traditional slanted-edge method,a sub-block is always manually extracted from original image and its MTF will be viewed as the result of the whole image. However,handcraft extraction is inefficient and will lead to inaccurate results. Given this,an automatic MTF computation algorithm is proposed,which extracts and screens out all the effective sub-blocks and calculates their average MTF as the final result. Then,a two-dimensional MTF restoration model is constructed by multiplying the horizontal and vertical MTF,and it is combined with conventional image restoration methods to restore fuzzy image. Experimental results indicate the proposed method implementes a fast and accurate MTF computation and the MTF model improves the performance of conventional restoration methods significantly.

Cox Proportional Hazard Model for Survival Time of Neonatal Mortality in Neonatal Intensive Care Unit of Hospitals in River Nile State-Sudan

Cox Proportional Hazard model is a popular statistical technique for exploring the relationship between the survival time of neonates and several explanatory variables. It provides an estimate of the study variables’ effect on survival after adjustment for other explanatory variables, and allows us to estimate the hazard (or risk) of death of newborn in NICU of hospitals in River Nile State-Sudan for the period (2018-2020). Study Data represented (neonate gender, mode of delivery, birth type, neonate weight, resident type, gestational age, and survival time). Kaplan-Meier method is used to estimate survival and hazard function for survival times of newborns that have not completed their first month. Of 700 neonates in the study area, 25% of them died during 2018-2020. Variables of interest that had a significant effect on neonatal death by Cox Proportional Hazard Model analysis were neonate weight, resident type, and gestational age. In Cox Proportional Hazard Model analysis all the variables of interest had an effect on neonatal death, but the variables with a significant effect included, weight of neonate, resident type and gestational age.