Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

72 MHz/54 MHz SAMPLING RATE CONVERSION SYSTEM OF HDTV STUDIO SIGNAL

Sampling rate conversion finds great use in the area of multirate signal processing, communications system, speech processing system, etc. In this paper, we describe a structure of 72 MHz/54 MHz sampling rate conversion system which is applied to HDTV system. First, we discuss the theoretical model of a 4/3 conversion scheme and then design the hardware structure implemented in parallel and illustrate the subsystem structure in detail. Finally, the phase diagrams are presented to show the relations between the clocks.

Dropping Rate Simulation for a Handover Scheme Using Importance Sampling

The process of changing the channel associated with the current connection while a call is in progress is under consideration. The estimation of dropping rate in handover process of a one dimensional traffic system is discussed. To reduce the sample size of simulation, dropping calls at base station is considered as rare event and simulated with importance sampling - one of rare event simulation approaches. The simulation results suggest the sample size can be tremendously reduced by using importance sampling.

Finite rate of innovation sparse sampling for a binary frequency-coded ultrasonic signal

To achieve sparse sampling on a coded ultrasonic signal,the finite rate of innovation(FRI)sparse sampling technique is proposed on a binary frequency-coded(BFC)ultrasonic signal.A framework of FRI-based sparse sampling for an ultrasonic signal pulse is presented.Differences between the pulse and the coded ultrasonic signal are analyzed,and a response mathematical model of the coded ultrasonic signal is established.A time-domain transform algorithm,called the high-order moment method,is applied to obtain a pulse stream signal to assist BFC ultrasonic signal sparse sampling.A sampling of the output signal with a uniform interval is then performed after modulating the pulse stream signal by a sampling kernel.FRI-based sparse sampling is performed using a self-made circuit on an aluminum alloy sample.Experimental results show that the sampling rate reduces to 0.5 MHz,which is at least 12.8 MHz in the Nyquist sampling mode.The echo peak amplitude and the time of flight are estimated from the sparse sampling data with maximum errors of 9.324%and 0.031%,respectively.This research can provide a theoretical basis and practical application reference for reducing the sampling rate and data volume in coded ultrasonic testing.

On the Performance of Blind Chip Rate Estimation in Multi-Rate CDMA Transmissions Using Multi-Rate Sampling in Slow Flat Fading Channels

This paper considers blind chip rate estimation of DS-SS signals in multi-rate and multi-user DS-CDMA systems over channels having slow flat Rayleigh fading plus additive white Gaussian noise. Channel impulse response is estimated by a subspace method, and then the chip rate of each signal is estimated using zero crossing of estimated differential channel impulse response. For chip rate estimation of each user, an algorithm which uses weighted zero-crossing ratio is proposed. Maximum value of the weighted zero crossing ratio takes place in the Nyquist rate sampling frequency, which equals to the twice of the chip rate. Furthermore, bit time of each user is estimated using fluctuations of autocorrelation estimators. Since code length of each user can be obtained using bit time and chip time ratio. Fading channels reduce reliability factor of the proposed algo-rithm. To overcome this problem, a receiver with multiple antennas is proposed, and the reliability factor of the proposed algorithm is analyzed over both spatially correlated and independent fading channels.

A Novel Dual-Rate Sampling Switched-Capacitor Configuration and Its Application

In order to realize accurate bilinear transformation from s- to z-domain,a novelswitched-capacitor configuration is proposed in the light of principles of dual-rate sampling and chargeconservation,which has also been used for building a 5th-order elliptic lowpass filter.The filter issimulated and measured in typical 0.34 μm/3.3 V Si CMOS process models,special full differentialoperational amplifiers and CMOS transfer gate switches,which achieves 80 MHz sampling rate,17.8MHz cutoff frequency,0.052 dB maximum passband ripple,42.1 dB minimum stopband attenuation and74 mW quiescent power dissipation.At the same time,the dual-rate sampling topology breaks thetraditional restrictions of filter introduced by unit-gain bandwidth and slew rate of operational amplifiersand also improves effectively their performances in high-frequency applications.It has been applied forthe design of an anti-alias filter in analog front-end of video decoder IC with 15 MHz signal frequencyyet.

Experimental and numerical simulation of loading rate effects on failure and strain energy characteristics of coal-rock composite samples

The deformation and failure of coal and rock is energy-driving results according to thermodynamics.It is important to study the strain energy characteristics of coal-rock composite samples to better understand the deformation and failure mechanism of of coal-rock composite structures.In this research,laboratory tests and numerical simulation of uniaxial compressions of coal-rock composite samples were carried out with five different loading rates.The test results show that strength,deformation,acoustic emission(AE)and energy evolution of coal-rock composite sample all have obvious loading rate effects.The uniaxial compressive strength and elastic modulus increase with the increase of loading rate.And with the increase of loading rate,the AE energy at the peak strength of coal-rock composites increases first,then decreases,and then increases.With the increase of loading rate,the AE cumulative count first decreases and then increases.And the total absorption energy and dissipation energy of coal-rock composite samples show non-linear increasing trends,while release elastic strain energy increases first and then decreases.The laboratory experiments conducted on coal-rock composite samples were simulated numerically using the particle flow code(PFC).With careful selection of suitable material constitutive models for coal and rock,and accurate estimation and calibration of mechanical parameters of coal-rock composite sample,it was possible to obtain a good agreement between the laboratory experimental and numerical results.This research can provide references for understanding failure of underground coalrock composite structure by using energy related measuring methods.

Distribution and Migration of Heavy Metals in Undisturbed Forest Soils:A High Resolution Sampling Method

The vertical distribution and migration of Cu,Zn,Pb,and Cd in two forest soil profiles near an industrial emission source were investigated using a high resolution sampling method together with reference element Ti.One-meter soil profile was sectioned horizontally at 2 cm intervals in the first 40 cm,5 cm intervals in the next 40 cm,and 10 cm intervals in the last 20 cm.The migration distance and rate of heavy metals in the soil profiles were calculated according to their relative concentrations in the profiles,as calibrated by the reference element Ti.The enrichment of heavy metals appeared in the uppermost layer of the forest soil,and the soil heavy metal concentrations decreased down the profile until reaching their background values.The calculated average migration rates of Cd,Cu,Pb,and Zn were 0.70,0.33,0.37,and 0.76 cm year-1,respectively,which were comparable to other methods.A simulation model was proposed,which could well describe the distribution of Cu,Zn,Pb,and Cd in natural forest soils.

Guaranteed cost control of networked control systems under limited communication capacity and variable sampling

The problem of guaranteed cost control for the networked control systems(NCSs) with time-varying delays, time-varying sampling intervals and signals quantization was investigated, wherein the physical plant was continuous-time one, and the control input was discrete-time one. By using an input delay approach and a sector bound method, the network induced delays, quantization parameter and sampling intervals were presented in one framework in the case of the state and the control input by quantized in a logarithmic form. A novel Lyapunov function with discontinuity, which took full advantages of the NCS characteristic information, was exploited. In addition, it was shown that Lyapunov function decreased at the jump instants. Furthermore, the Leibniz-Newton formula and free-weighting matrix methods were used to obtain the guaranteed cost controller design conditions which were dependent on the NCS characteristic information. A numerical example was used to illustrate the effectiveness of the proposed methods.

Stability analysis of networked control systems with time-varying sampling periods

In this paper, we present an interval model of networked control systems with time-varying sampling periods and time-varying network-induced delays and discuss the problem of stability of networked control systems using Lyapunov stability theory. A sufficient stability condition is obtained by solving a set of linear matrix inequalities. In the end, the illustrative example demonstrates the correctness and effectiveness of the proposed approach.

Convergence Rate of E·B Estimation for Location Parameter Function of One-side Truncated Family Under NA Samples

In this paper, we construct the E·B estimation for parameter function of one-side truncated distribution under NA samples. Also, we obtain its convergence rate at O(n-q), where q is approaching 1/2.

Quality Assessment of Attribute Data in GIS Based on Simple Random Sampling

On the basis of the principles of simple random sampling, the statistical model of rate of disfigurement (RD) is put forward and described in detail. According to the definition of simple random sampling for the attribute data in GIS, the mean and variance of the RD are deduced as the characteristic value of the statistical model in order to explain the feasibility of the accuracy measurement of the attribute data in GIS by using the RD. Moreover, on the basis of the mean and variance of the RD, the quality assessment method for attribute data of vector maps during the data collecting is discussed. The RD spread graph is also drawn to see whether the quality of the attribute data is under control. The RD model can synthetically judge the quality of attribute data, which is different from other measurement coefficients that only discuss accuracy of classification.

Fast Rate Fault Detection Filter for Multirate Sampled-data Systems

This paper focuses on the fast rate fault detection filter (FDF) problem for a class of multirate sampled-data (MSD) systems. A lifting technique is used to convert such an MSD system into a linear time-invariant discrete-time one and an unknown input observer (UIO) is considered as FDF to generate residual. The design of FDF is formulated as an H∞ optimization problem and a solvable condition as well as an optimal solution are derived. The causality of the residual generator can be guaranteed so that the fast rate residual can be implemented via inverse lifting. A numerical example is included to demonstrate the feasibility of the obtained results.

Double sampling derivatives and truncation error estimates

This paper investigates double sampling series derivatives for bivariate functions defined on R2 that are in the Bernstein space. For this sampling series, we estimate some of the pointwise and uniform bounds when the function satisfies some decay conditions. The truncated series of this formula allow us to approximate any order of partial derivatives for function from Bernstein space using only a finite number of samples from the function itself. This sampling formula will be useful in the approximation theory and its applications, especially after having the truncation error well-established. Examples with tables and figures are given at the end of the paper to illustrate the advantages of this formula.

Parameter estimation for dual-rate sampled Hammerstein systems with dead-zone nonlinearity

The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.

Augmented line sampling and combination algorithm for imprecise time-variant reliability analysis

Assessment of imprecise time-variant reliability in engineering is a critical task when accounting for both the variability of structural properties and loads over time and the presence of uncertainties involved in the ambiguity of parameters simultaneously.To estimate the Imprecise Time-variant Failure Probability Function(ITFPF)and derive the imprecise reliability results as a byproduct,Adaptive Combination Augmented Line Sampling(ACALS)is proposed.It consists of three integrated features:Augmented Line Sampling(ALS),adaptive strategy,and the optimal combination.ALS is adopted as an efficient analysis tool to obtain the failure probability function w.r.t.imprecise parameters.Then,the adaptive strategy iteratively applies ALS while considering both imprecise parameters and time simultaneously.Finally,the optimal combination algorithm collects all result components in an optimal manner to minimize the Coefficient of Variance(C.o.V.)of the ITFPF estimate.Overall,the proposed ACALS method outperforms the original ALS method by efficiently estimating the ITFPF while guaranteeing a minimal C.o.V.Thus,the proposed approach can serve as an effective tool for imprecise time-variant reliability analysis in real engineering applications.Several examples are presented to demonstrate the superiority of the proposed approach in addressing the challenges of estimating the ITFPF.

Bootstrap抽样下基于贝叶斯估计的地震人员死亡评估研究

选取1950-2022年中国内地地区历史震例数据信息,以极震区烈度、发震时间及人口密度为主要影响因素,建立三级场景,运用Bootstrap抽样方法对各场景下的历史震例进行扩充,进而采用贝叶斯估计给出不同场景下地震人员死亡变化分布函数,再根据实际情况对此分布函数进行截断分析,以明确地震人员死亡的不确定性变化范围及死亡率区间概率值,最后随机选取历史地震灾害事件验证模型精度。结果表明:①各场景的死亡率均值及95%死亡率区间基本符合在极震区烈度相等并且人口密度条件下夜间死亡率大于白天死亡率的规律;②模型估计死亡人数区间能够较好覆盖实际上报的死亡人数。

Empirical Determination of the Tolerable Sample Size for Ols Estimator in the Presence of Multicollinearity (<i>ρ</i>)

This paper investigates the tolerable sample size needed for Ordinary Least Square (OLS) Estimator to be used when there is presence of Multicollinearity among the exogenous variables of a linear regression model. A regression model with constant term (β0) and two independent variables (with β1 and β2 as their respective regression coefficients) that exhibit multicollinearity was considered. A Monte Carlo study of 1000 trials was conducted at eight levels of multicollinearity (0, 0.25, 0.5, 0.7, 0.75, 0.8, 0.9 and 0.99) and sample sizes (10, 20, 40, 80, 100, 150, 250 and 500). At each specification, the true regression coefficients were set at unity while 1.5, 2.0 and 2.5 were taken as the hypothesized value. The power value rate was obtained at every multicollinearity level for the aforementioned sample sizes. Therefore, whether the hypothesized values highly depart from the true values or not once the multicollinearity level is very high (i.e. 0.99), the sample size needed to work with in order to have an error free estimation or the inference result must be greater than five hundred.

RELIABILITY ANALYSIS FOR A REPAIRABLE PARALLEL SYSTEM WITH TIME-VARYING FAILURE RATES

To solve a real problem:how to calculate the reliability of a system with time-varying failure rates in industry systems,this paper studies a model for the load-sharing parallel system with time-varying failure rates,and obtains calculating formulas of reliability and availability of the system by solving differential equations.In this paper,the failure rates are expressed in polynomial configuration.The constant,linear and Weibull failure rate are in their special form.The polynomial failure rates provide flexibility in modeling the practical time-varying failure rates.