Geometric Error Identification of Gantry-Type CNC Machine Tool Based on Multi-Station Synchronization Laser Tracers

Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine tools.This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method.We consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain.The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor’s first-order linearization iteration.The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer.For a volume of 800 mm×1000 mm×350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0μm,2.7μrad,and 12.0μm,respectively,which verifies the accuracy of the proposed algorithm.This research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.

Synthesized Multi-station Tribo-test System for Bio-tribological Evaluation in Vitro

Tribological tests play an important role on the evaluation of long-term bio-tribological performances of prosthetic materials for commercial fabrication.Those tests focus on the motion simulation of a real joint in vitro with only normal loads and constant velocities,which are far from the real friction behavior of human joints characterized with variable loads and multiple directions.In order to accurately obtain the bio-tribological performances of artificial joint materials,a tribological tester with a miniature four-station tribological system is proposed with four distinctive features.Firstly,comparability and repeatability of a test are ensured by four equal stations of the tester.Secondly,cross-linked scratch between tribo-pairs of human joints can be simulated by using a gear-rack meshing mechanism to produce composite motions.With this mechanism,the friction tracks can be designed by varying reciprocating and rotating speeds.Thirdly,variable loading system is realized by using a ball-screw mechanism driven by a stepper motor,by which loads under different gaits during walking are simulated.Fourthly,dynamic friction force and normal load can be measured simultaneously.The verifications of the performances of the developed tester show that the variable frictional tracks can produce different wear debris compared with one-directional tracks,and the accuracy of loading and friction force is within ？5%.Thus the high consistency among different stations can be obtained.Practically,the proposed tester system could provide more comprehensive and accurate bio-tribological evaluations for prosthetic materials.

Controllers Design for the Multi-Shuttle and Multi-Station Transportation System

Nowadays, the Multi-Shuttle and Multi-Station Transportation System (MMTS) is one of the most interesting research topics in many fields of industries. It is an effective solution to reduce unexpected accidents that occur during transportation as well as increase productivity in manufacturing. The aim of this paper is to introduce the controller design for the MMTS which is built in our BK-Recme BioMech Lab at Ho Chi Minh City University of Technology (VNU-HCM), Viet Nam. Based on the design of this system, the control algorithms will be conducted to check the operation of the whole system. To evaluate the feasibility and effectiveness of this model, we design a series of random instances for different quantities of nodes as well as the different quantities of shuttles. Our system includes 4 stations and 6 shuttles which are assembled in the serial chain system. However, the number of stations and number of shuttles can be expanded to any desired ones which are based on the requirement of the industries. In this paper, we mainly focus on the controller design of this system to make it operate in an effective way that the goods will be transported and delivered to the target station as fast as possible. In order to solve the large-scale instances and realistic transport problems, we propose three algorithms for three progresses as shuttles calling, path reading and shuttles communicating. The shuttles calling is to decide which shuttle should be called to the start-node. Path reading to determine the shortest way to go from start-node to end-node. Finally, shuttles communicating, which allow one shuttle to interact with the next shuttles so we have a loop of orders (shuttle 1 to shuttle 2;shuttle 2 to shuttle 3;etc.;shuttle n-1 to shuttle n). This proposes solution can help us to solve the huge numbers of shuttles and stations in the system. The specific result of this study is applying Dijkstra’s algorithm to propose an algorithm that allows handling a transportation system without caring about the number of shuttles as well as the number of stations for the closed-loop path. Several test problems are carried out in order to check the feasibility and the effectiveness of our purposed control algorithm.

Stroke optimization of a novel multi-station rotary polishing robot based on workspace analysis

In order to meet the polishing requirement of faucets and other products,a novel multi-station rotary polishing robot is designed,which is a PPPR + RR type of degree of freedom( DOF) distribution structure,and is similar to dual-arm robot. Forward and inverse kinematic analysis is carried out by robot modeling. In order to make this robot structure more compact,first of all,X,Y and Z three moving degrees of freedom( DOF) limit stroke polishing need is calculated by using an artificial fish swarm algorithm,which analyzes dexterous workspace of this robot. Then,on the basis of the above analysis,the three DOF stroke is optimized. Simulation and polishing experimental results verify that this polishing robot with optimized stroke parameters can meet the polishing needs of faucets and other bathroom pieces.

Quality Stability of Multi-Station Assembly Process Based on Variation Stream

To analyze the physical structure of assembly process and assure product quality, the quality stability of multi-station assembly process was investigated. First, the assembly process was modeled as a one-dimensional discrete variant system by state space equation based on variation stream. Then, the criterion to judge whether the process is stable or not and the index, stability degree, to show the level of stability were proposed by analyzing the bounded-input bounded-output (BIBO) stability of system. Finally, a simulated example of a sheet metal assembly process with three stations, was provided to verify the effectiveness of the proposed method.

Study on quality evaluation model in multi-station assembly processes

Based on features of dimension variation propagation in multi-station assembly processes,a new quality evaluation model of assembly processes is established. Firstly,the error source of multi-station assembly system is analyzed,the relationship of dimension variation propagation in multi-station assembly processes is studied and the state equation for variation propagation is constructed too. Then,the feature parameters which influence variation propagation and accumulation in multi-station assembly processes are found to evaluate quality characteristic of the assembly system. Through the derivation of equation on dimension variation propagation,station coefficient matrices which are combined and conversed to determine the max eigenvalue are educed. The max eigenvalue is multiplied by the weight coefficient to establish the quality evaluation model in multi-station assembly processes. Furthermore,assembly variation indexes are proposed to judge of the assembly technology process. Finally,through the practical example,the application of the model and assembly variation indexes are presented.

Planning Method and Coordinated Operation Strategy for Multi-station Integration System

A multi-station integration system(MSIS)integrat-ing other multi-type stations provides a new way to realize an intensive development of resources and promote low-carbon en-ergy and its high-efficiency utilization.To this end,a novel multi-station integration planning method and coordinated operation strategy model for the MSIS are established in a new business model.In this study,a new business model of the MSIS,with substations as the carrier,integrating distributed photovoltaic,energy storage,electric vehicle charging,data center,and 5G base stations is proposed.From the social environment,natural conditions,and complementary characteristics,a comprehensive index system is established to analyze expansion capability of substations and multi-station combination scheme.Scenario reduction is performed by extracting feature vectors and build-ing a comprehensive evaluation function to select the optimal combination scheme under a specific scenario.Moreover,for the combination scheme in a specific scenario,the optimal ca-pacity configuration and coordinated operation strategy chance-constrained programming model of the MSIS are established under different operating conditions.Finally,simulations are performed on a practical MSIS located in Wuxi,China,and simulation results demonstrate the rationality and effectiveness of the planning method and coordinated operation strategy model for the MSIS.

Development of diabetic complications and influencing factors among 32653 type 2 diabetes patients:retrospective cohort study using a multi-state Markov

Background:Patients with type 2 diabetes are at high risk for developing multiple chronic complications.However,there is a lack of studies of the cumulative number of diabetic complications in China.Methods:A retrospective cohort study was performed from 2009 to 2021.Type 2 diabetes patients who were first diagnosed after the age of 35 years between January 1,2009,and December 31,2017,were included.Five states were defined according to the number of chronic complications:no(S0),one(S1),two(S2),three(S3),and four or more complications(S4).A multi-state Markov model was constructed to estimate transition probability,transition intensity,mean sojourn time,and the possible factors for each state.Results:The study included 32653 type 2 diabetes patients(mean age,59.59 years;15929(48.8%)male),and mean follow-up time of 7.75 years.In all,4375 transitions were observed.The 12-year transition probability of from state S0 to S1 was the lowest at 16.4%,while that from S2 to S3 was the highest,at 45.6%.Higher fasting blood glucose,lower high-density lipoprotein cholesterol,higher total cholesterol,and an unhealthy diet were associated with higher risk of progression from S0 to S1.Being female,less than 60 years old,weekly physical activity,and vegetarian diet decreased this risk.Being female and less than 60 years old reduced the likelihood of transition from S1 to S2,whereas lower high-density lipoprotein cholesterol increased this likelihood.Conclusions:Following the occurrence of two complications in type 2 diabetes patients,the risk for accumulating a third complication within a short time is significantly increased.It is important to take advantage of the stable window period when patients have fewer than two complications,strengthen the monitoring of blood glucose and blood lipids,and encourage patients to maintain good living habits to prevent further deterioration.

A Two-Step Algorithm to Estimate Variable Importance for Multi-State Data:An Application to COVID-19

Survival data with amulti-state structure are frequently observed in follow-up studies.An analytic approach based on a multi-state model(MSM)should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events.One main objective in the MSM framework is variable selection,where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression.The usual variable selection methods,including stepwise and penalized methods,do not provide information about the importance of variables.In this context,we present a two-step algorithm to evaluate the importance of variables formulti-state data.Three differentmachine learning approaches(randomforest,gradient boosting,and neural network)as themost widely usedmethods are considered to estimate the variable importance in order to identify the factors affecting disease progression and rank these factors according to their importance.The performance of our proposed methods is validated by simulation and applied to the COVID-19 data set.The results revealed that the proposed two-stage method has promising performance for estimating variable importance.

基于TRIZ理论的多工位柔性压曲机设计

针对压曲机单点单次压制曲块质量不稳定、提浆效果差等问题,采用TRIZ理论对压曲机进行总体方案创新设计。利用分割、多维化原理设计多工位压曲装置,包括落料、预压整形、3次捶打和脱模输出等6个工位,平均产量为500块/h。采用复制、动态化、改变参数、近似化原理设计锤头装置,每个模盒均对应包含8个可独立捶打的柔性锤头装置,实现24次/周期的多点、多频次柔性捶打。运用SolidWorks进行设备虚拟建模,通过样机验证方案。试验结果表明,设备压制的曲块含水率约为12%,曲块表面提浆效果面积比约为82%,曲皮厚度约为0.96 cm,曲块中间松、四周紧,断面整洁。研究为压曲机的创新设计提供新的思路。

多站融合的微能源系统站 网协同布局

为了促进资源的共享,提高能源利用率,建立了双层站网优化布局模型,对多站融合的微能源系统的融合站数量、位置、设备容量配置,以及管线分布进行了协同规划。上层模型采用最小生成树和谱聚类求解,解决了融合站数量、位置和管线分布问题;下层模型采用提出的改进的粒子群优化算法,解决了设备容量配置问题。通过对规划区域进行算例仿真,得出了系统站网协同布局的优化结果,验证了所提模型和算法的可行性与合理性。

基于改进水波算法的复杂多人共站装配线平衡研究

针对实际装配环境中存在多人协同装配和共站的情况,研究了考虑工序复杂程度与工人能力差异的多人协作共站装配线平衡问题。首先,考虑到装配工序的复杂程度需指派不同规模和类型的工人组,建立了以最小化工作站数量和工人数量为目标函数的多目标优化数学模型;在此基础上,提出一种改进的离散水波优化算法,对算子进行了离散化改造,并设计了基于拓扑排序的编码方案和启发式的解码方案,同时引入扰动个体和路径重连的搜索策略来增加解的多样性,进而提高解的质量;最后,通过求解两类测试用例,以线效率和平滑指数作为性能指标,验证了改进离散水波算法在求解复杂多人共站装配线平衡问题上的可行性与有效性,并将算法应用到动车装配线平衡优化中。

基于多维效用函数的多基站运行成本优化方法

现有移动通信系统出现业务量迅猛增长现象,为缓解增长的基站负荷带来的基站功耗,移动通信系统中为基站配备了可再生能源产能设备。如何实现通信系统信息流与能量流匹配,完成通信业务与基站可再生能源储备的精确配对,更加充分的利用通信系统内可再生能源,是下一步优化通信系统网络性能并降低系统运行成本的关键。为此,本文构建了一个多维效用函数,该函数联合考虑了用户的接受信干噪比、可再生能源利用与基站负载3种因素。通过将求解多基站系统运行成本最小化问题转化为多维效用函数效用值最大化问题,对多基站系统进行优化,并实现系统运行成本最小化。问题转化后为一个混合整数非线性优化的非凸问题。为求解该问题本文提出了多维效用函数迭代优化算法,将该问题拆分为用户调度、功率分配与基站负载均衡3个子问题,通过采用交替优化和连续凸近似技术对问题进行迭代求解。仿真结果表明,相比于最大SINR关联优化算法与“最大SINR+可再生能源利用”优化算法,本文算法在可再生能源利用率方面分别提升了58.68%和29.74%,且系统总费用一直维持在较低水平,具备显著优势。

一种提高多基地天波雷达目标定位精度的方法

分析了引起多基地天波雷达目标定位误差的原因,对测距误差和定位模型误差两种影响定位精度的主要因素进行了仿真计算。比较发现,定位误差主要来源于多站定位模型,由定位模型中电离层虚高的假定条件与实际不符所引起。给出了减小模型误差,提高定位精度的方法。以某多基地天波雷达系统为对象,对修正后的定位模型进行了不同误差条件下的模拟测试,并利用系统对目标船的跟踪数据进行了验证。结果表明,模型改进后目标定位的精度得到了较大程度的提高。

考虑新能源消纳的黄河上游水电站群生态优化调度研究

为降低黄河上游水电站群调度中新能源消纳对河流径流情势和生态完整度的影响,以河流径流情势变化最小、水电站群发电量最大、发电出力平稳性最高为目标,建立了风水光多能互补系统生态调度模型,采用多目标进化算法求解,探讨了多能互补系统发电出力、新能源消纳及河流生态保护之间的均衡关系。结果表明:水电站群发电量和河流生态保护目标之间呈现明显的竞争关系,多能互补系统的发电出力波动越大,水电站群发电量越大,径流情势变化也越大;入库径流量越大,水电站群生态调度对径流情势的影响越小;多能互补系统生态调度对径流情势的影响主要集中在年发生高/低流量脉冲次数和流量平均增加率/减少率这两项指标,在枯水年发电量最大的调度结果中,年发生低流量脉冲次数和流量平均减少率指标的变化最大。

含电动汽车的光/储/燃充电站最优容量配置及经济性分析

针对城市居民区充电难状况,建立一种包含光伏电池、燃料电池和储能蓄电池的电动汽车充电站容量配置模型。以成本最小化和负荷方差最小化为目标,采用NSGA-Ⅱ(二代非支配排序遗传算法)对模型进行求解。对于求得的可行解,首先使用净现值法对部分解进行经济性评估,然后采取峰谷负荷差率进行进一步评估,经过两轮筛选得出最优解。仿真算例验证了模型及评估方法的可行性。

含循环换电负荷及充电站的微电网多目标优化调度

电动换电重卡由于具有充电功率高、周期性强的循环换电负荷特性,一旦短时大量接入微电网中,将带来经济性和安全性的挑战。首先讨论电动汽车充电、循环换电负荷的不同特性,建立含循环换电负荷及充电站的微电网模型;提出一种综合考虑微电网经济性及联络线功率波动性的多目标调度优化方法;采用线性加权方法将多目标问题转化为单目标问题;最后利用CPLEX工具对仿真算例进行求解,仿真算例表明,所提优化方案可有效求解综合考虑不同权重下微电网净利润、联络线交换功率及换电站内电池最优调度问题,能在尽可能减小微电网与上级电网交换功率波动性的同时,使得微电网获得最大净利润。

基于多信息融合的换流站直流设备健康状态决策树评价模型

针对换流站直流设备间交互信息融合能力较差、小样本与大样本难以均衡的问题,设计基于多信息融合的换流站直流设备健康状态决策树评价模型。使用同质多传感器多信息数据融合方法对多信息实施融合处理;利用k近邻方法和层次聚类方法划分换流站直流设备健康状态量,提取健康状态量的有效信息作为输入,构建决策树评价模型,输出换流站直流设备健康状态评价结果。实验结果表明,该模型具备较好的多信息融合能力和样本均衡能力,且可从不同角度实现换流站直流设备健康状态评价,评价结果较为准确。

基于多种群混沌遗传算法的GEO目标服务任务规划

面向地球同步轨道(geosynchronous Earth orbit,GEO)空间目标碎片清除、燃料加注等不同在轨服务需求,研究了“固定储油站+往返航天器”相结合的航天器任务规划问题。首先,建立了多任务混合的燃料最优双层任务规划模型,外层为目标服务序列规划,内层为轨道机动规划。随后,针对该连续-离散混合变量组合优化问题,提出了一种多种群混沌遗传算法(multi-group chaotic genetic algorithm,MGCGA),采用混合编码表征决策变量,引入立方混沌映射算子提高初始种群质量,多种群及精英保留策略使得算法在求解过程中能更为显著地逼近全局最优解。最后,参考实际GEO目标构建了典型算例,规划结果表明所提算法具有全局收敛性好、收敛速度快的优点。

一种多站雷达协同时空误差配准方法研究

多站雷达协同系统各个节点工作具有异步性,多节点雷达对同一个或多个目标的测量误差不一致,导致在多站雷达协同进行数据融合时将同一目标误认为不同目标,使得融合航迹性能下降,失去多雷达协同的优势。文中研究了一种基于多站协同数据处理的航迹误差校准方法,利用最小二乘滤波对多站雷达航迹进行关联,同时利用多站协同关联的优势剔除转发式干扰航迹,对多站探测到的同一目标航迹进行时间统一。并基于多站协同迭代最近点算法,使用多站协同系统中高精度节点数据对低精度节点数据进行误差配准。仿真结果表明,文中方法在多目标复杂运动场景中具有更高的航迹关联正确率,且具有较好的抗转发干扰能力。与传统空间误差配准算法相比,具有更低的配准均方根误差。