An integrated fuzzy simulation-fuzzy data envelopment analysis algorithm for job-shop layout optimization: The case of injection process with ambiguous data

This paper puts forward an integrated fuzzy simulation-fuzzy data envelopment analysis (FSFDEA) algorithm to cope with a special case of single-row facility layout problem (SRFLP). Discrete-event-simulation, a powerful tool for analyzing complex and stochastic systems, is employed for modeling different layout formations. Afterwards, a range-adjusted measure (RAM) is used as a data envelopment analysis (DEA) model for ranking the simulation results and finding the optimal layout design. Due to ambiguousness associated with the processing times, fuzzy sets theory is incorporated into the simulation model. Since the results of simulation are in the form of possibility distributions, the DEA model is treated on a fuzzy basis; therefore, a recent possibilistic programming approach is used to convert the fuzzy DEA model to an equivalent crisp one. The proposed FSFDEA algorithm is capable of modeling and optimizing small-sized SRFLP’s in stochastic, uncertain, and non-linear environments. The solution quality is inspected through a real case study in a refrigerator manufacturing company.     

Single row facility layout problem using a permutation-based genetic algorithm

In this paper, a permutation-based genetic algorithm (GA) is applied to the NP-hard problem of arranging a number of facilities on a line with minimum cost, known as the single row facility layout problem (SRFLP). The GA individuals are obtained by using some rule-based as well as random permutations of the facilities, which are then improved towards the optimum by means of specially designed crossover and mutation operators. Such schemes led the GA to handle the SRFLP as an unconstrained optimization problem. In the computational experiments carried out with large-size instances of sizes from 60 to 80, available in the literature, the proposed GA improved several previously known best solutions.     

一种免装配微惯性测量单元的研制与开发

以柔性材料和高精度六面体作为惯性传感器的安装载体和基准,设计了一种免装配、安装误差小、体积小、功耗低且便于标定的微惯性测量单元。给出了安装误差小角度前提下的传感器的测量方程和标定方法;利用微控制器的并行工作机制,提出了一种快速有效的基于均值滤波和FIR滤波的组合滤波方案。实验结果表明:MIMU可以100 Hz的频率更新测量输出,加速度测量噪声小于2.5 mg、测量误差小于0.8 mg,旋转角速度测量噪声小于0.15 o/s、测量误差小于0.2 o/s,可满足微小型惯性导航系统的功耗、体积、测量精度和响应速度的应用需求。     

Calibration of a multiple axes 3-D laser scanning system consisting of robot, portable laser scanner and turntable

A multiple axes 3-D laser scanning system consisting of a portable 3-D laser scanner, a industrial robot and a turntable is demonstrated. By using a criterion sphere, a robot tool center point (TCP) calibration approach is proposed to calibrate the relation between the laser 3-D scanner and the robot end-effector. In this approach, two different translational motions of robot are first made to determine the rotation part, and then at least three different rotational motions are made to determine the translation part. Meanwhile, by using the criterion sphere, a turntable approach is proposed to calibrate the pose of the turntable relative to the robot. In this approach, several rotational angles of turntable and two different heights of the sphere are made to determine the rotational axis of turntable. Experiment is performed on a portable laser scanner mounted on an industrial robot ABB IRB4400 with a turntable. The experiment results show that the two proposed calibration algorithms are stable and flexible. The application of 3-D measurement is also given to demonstrate the effectiveness and stability of the multiple axes 3-D laser scanning system.     

大视场星敏感器标定技术研究

大视场星敏感器光学系统,由于畸变量较大,在轨标定过程中,直接采用最小二乘最优估计(LMS)或扩展卡尔曼滤波方法(EKF)无法精确求解其标定参数。在深入分析星敏感器测量误差因素的基础上,对考虑畸变和不考虑畸变两种情况的在轨标定结果进行了仿真对比;指出了标定焦距之前需先标定光学畸变的必要性,并介绍了4种可用于在轨校正光学畸变的方法;提出先标定主点偏差,再标定光学畸变参数,最后标定焦距的标定方法。仿真结果表明,可以采用像面旋转法求取主点偏差,利用高阶多项式方法求取光学畸变参数,畸变校正后,采用LMS和EKF标定算法估计焦距,标定精度达到了3.1μm和2.2μm。对100幅模拟星图处理后,星间角距统计偏差约为传统在轨标定方法的1/10～1/8。     

透射光栅的实验标定和衍射效率的理论模拟

透射光栅广泛应用于软X射线能谱测量.为了获得用于惯性约束聚变研究的透射光栅的各级衍射效率及其他参数,在北京同步辐射源上200—1600 eV能量范围内对其进行了标定,获得了透射光栅衍射效率的实验结果.扩展了透射光栅衍射效率的计算方法,提出了7边准梯形截面衍射效率计算模型.分析拟合了实验数据,理论结果与实验结果很好符合.得到了7边准梯形的透射光栅栅线截面结构. 关键词： 透射光栅 衍射效率 实验标定 光栅模型     

土壤重金属铬元素的激光诱导击穿光谱定量分析研究

利用Nd ∶YAG脉冲激光器(波长:1064 nm)作为光源,在实验室自然大气环境下诱导产生土壤激光等离子体,通过等离子体原子发射光谱法定量分析了国家标准土壤样品中元素Cr的含量.实验上研究了在最佳实验条件下土壤中Cr的LIBS分析谱线,测定了Cr元素的定标曲线.实验结果表明,Cr元素浓度在(60—400)×10^-6范围内,元素含量与光谱线强度之间有较好的线性关系;元素Cr浓度分析测量的相对标准偏差(RSD)为7.89%,定量分析结果与标准值的相对偏差为5.3%,Cr元素的检测限为1 关键词： 土壤污染 定量分析 激光诱导击穿光谱 定标曲线     

多组分烟用香精定量分析方法的研究进展

综述了近年来烟用香精、香料各组分化合物的定量分析方法的研究进展。面积归一化法、内标法、外标法和标准加入法等常用色谱定量分析方法主要用于烟用香精、香料中目标化合物或单个组分的测定;多标定量法、特征峰-内标定量法和多元校正法能深入剖析烟用香精复杂体系中各组分含量(引用文献48篇)。     

A novel second-order standard addition analytical method based on data processing with multidimensional partial least-squares and residual bilinearization

In the presence of analyte-background interactions and a significant background signal, both second-order multivariate calibration and standard addition are required for successful analyte quantitation achieving the second-order advantage. This report discusses a modified second-order standard addition method, in which the test data matrix is subtracted from the standard addition matrices, and quantitation proceeds via the classical external calibration procedure. It is shown that this novel data processing method allows one to apply not only parallel factor analysis (PARAFAC) and multivariate curve resolution-alternating least-squares (MCR-ALS), but also the recently introduced and more flexible partial least-squares (PLS) models coupled to residual bilinearization (RBL). In particular, the multidimensional variant N-PLS/RBL is shown to produce the best analytical results. The comparison is carried out with the aid of a set of simulated data, as well as two experimental data sets: one aimed at the determination of salicylate in human serum in the presence of naproxen as an additional interferent, and the second one devoted to the analysis of danofloxacin in human serum in the presence of salicylate.     

Rapid determination of sucrose in chocolate mass using near infrared spectroscopy

This paper reports the results of a rapid method to determine sucrose in chocolate mass using near infrared spectroscopy (NIRS). We applied a broad-based calibration approach, which consists in putting together in one single calibration samples of various types of chocolate mass. This approach increases the concentration range for one or more compositional parameters, improves the model performance and requires just one calibration model for several recipes. The data were modelled using partial least squares (PLS) and multiple linear regression (MLR). The MLR models were developed using a variable selection based on the coefficient regression of PLS and genetic algorithm (GA). High correlation coefficients (0.998, 0.997, 0.998 for PLS, MLR and GA-MLR, respectively) and low prediction errors confirms the good predictability of the models. The results show that NIR can be used as rapid method to determine sucrose in chocolate mass in chocolate factories.