Variable Stiffness Identification and Configuration Optimization of Industrial Robots for Machining Tasks

Industrial robots are increasingly being used in machining tasks because of their high flexibility and intelligence.However,the low structural stiffness of a robot significantly affects its positional accuracy and the machining quality of its operation equipment.Studying robot stiffness characteristics and optimization methods is an effective method of improving the stiffness performance of a robot.Accordingly,aiming at the poor accuracy of stiffness modeling caused by approximating the stiffness of each joint as a constant,a variable stiffness identification method is proposed based on space gridding.Subsequently,a task-oriented axial stiffness evaluation index is proposed to quantitatively assess the stiffness performance in the machining direction.In addition,by analyzing the redundant kinematic characteristics of the robot machining system,a configuration optimization method is further developed to maximize the index.For numerous points or trajectory-processing tasks,a configuration smoothing strategy is proposed to rapidly acquire optimized configurations.Finally,experiments on a KR500 robot were conducted to verify the feasibility and validity of the proposed stiffness identification and configuration optimization methods.

Stiffness identification of four-point-elastic-support rigid plate

As the stiffness of the elastic support varies with the physical-chemical erosion and mechanical friction, model catastrophe of a single degree-of-freedom(DOF) isolation system may occur. A 3-DOF four-point-elastic-support rigid plate(FERP) structure is presented to describe the catastrophic isolation system. Based on the newly-established structure, theoretical derivation for stiffness matrix calculation by free response(SMCby FR) and the method of stiffness identification by stiffness matrix disassembly(SIby SMD)are proposed. By integrating the SMCby FR and the SIby SMD and defining the stiffness assurance criterion(SAC), the procedures for stiffness identification of a FERP structure(SIFERP) are summarized. Then, a numerical example is adopted for the SIFERP validation, in which the simulated tested free response data are generated by the numerical methods, and operation for filtering noise is conducted to imitate the practical application. Results in the numerical example demonstrate the feasibility and accuracy of the developed SIFERP for stiffness identification.

Stability of an explicit time-integration algorithm for hybrid tests, considering stiffness hardening behavior

An explicit unconditionally stable algorithm for hybrid tests,which is developed from the traditional HHT-α algorithm,is proposed.The unconditional stability is first proven by the spectral radius method for a linear system.If the value of α is selected within [-0.5,0],then the algorithm is shown to be unconditionally stable.Next,the root locus method for a discrete dynamic system is applied to analyze the stability of a nonlinear system.The results show that the proposed method is conditionally stable for dynamic systems with stiffness hardening.To improve the stability of the proposed method,the structure stiffness is then identified and updated.Both numerical and pseudo-dynamic tests on a structure with the collision effect prove that the stiffness updating method can effectively improve stability.

Spectral properties and identification of aerostatic bearings

Modified rotor kit Bently Nevada was used for dynamic characteristics measurements of new developed aerostatic bearings.Mathematical model of these bearings is considered as linear.Model was identified with the help of harmonic force excitation independently from the speed of journal rotation.The stiffness and damping matrices were identified for different air inlet pressures.The calculated spectral properties allow to determine the stability boundary for suitable variation of model parameters.

A method for support stiffness failure identification in a steel spring floating slab track of urban railway: a case study in China

The extensive use of steel spring floating slab tracks has effectively addressed the challenge of alleviating the environmental vibrations induced by urban rail transit systems.However,under the combined action of train dynamic loads and complex environmental factors,problems,such as the fracture of steel spring vibration isolators and suspension vibrations induced by the uneven settlement of the base,often occur.The failure of isolator support stiffness is often hidden in its early stages and is challenging to identify by conventional detection methods.At the same time,it will aggravate the wheel-rail interaction,accelerate the deterioration of track structure,and even affect the driving safety.This study first establishes a detailed coupled train-floating slab track-foundation analytical model.Then the influence of the vibration isolator support stiffness failure on the dynamic indices of the floating slab track system response is analyzed.A set of defect identification methods that can detect the number of failed steel springs,severity of damage,and their location is proposed.Finally,an intelligent monitoring system for support stiffness of floating slab track is built by combining the density-based spatial clustering of applications with noise algorithm and statistical data analysis and is applied to a rail line in southern China.During a three-year monitoring campaign,a suspension failure and a fracture of a steel spring were each successfully detected and detailed failure information was obtained.Field investigation results were consistent with the damage identification results.After repair,the track structure dynamic response returned to the average pre-damage level and further deterioration had been arrested.The proposed damage identification methods and monitoring system provide an approach for intelligent identification of track structure support stiffness failures.

试验台约束对滑动轴承动特性识别精度的影响

在滑动轴承的动特性测试中,试验台参数对动特性测试精度有重要的影响。以某倒置式轴承动特性试验台为研究对象,基于轴承动力学正反问题,提出滑动轴承动特性系数识别精度的仿真评估方法,分析不同激振频率时试验台约束参数对轴承动特性系数识别精度的影响规律,并对激振频率和约束参数的取值范围进行优选。结果表明:在较低激振频率的条件下,当约束刚度和约束阻尼取值较小时,动特性系数的识别精度受测试误差的影响不大,随着约束刚度和约束阻尼取值增大到一定值,动特性系数的识别精度受测试误差的影响迅速增大。针对研究的试验台,选择激振频率在30~300 Hz之间,选择试验台约束刚度小于试验轴承刚度的0.3%,试验台约束阻尼小于试验轴承阻尼的7%时,能够保证较好的轴承动特性系数的测试精度。

非线性结构系统的局部连接刚度辨识方法研究

连接结构在工程应用领域广泛存在,连接位置处的局部非线性特征对结构系统的动力学建模与特性预示具有重要影响。针对非线性结构系统局部连接参数未知或难以测量的问题,本文从结构动力学反问题的角度出发,提出一种基于频响函数变换的局部线性连接刚度辨识方法,通过与时域非线性子空间辨识方法相结合,可进一步获取非线性结构系统的局部线性和非线性连接刚度。设计并搭建三自由度结构系统的数值算例和实验系统,开展辨识方法的数值和实验验证,结果表明,所提方法能够分离并辨识得到非线性结构系统的标称线性系统频响函数和非线性参数,进而实现局部线性和非线性连接刚度的联合辨识。

基于状态/参数交替优化估计的齿轮时变啮合刚度辨识方法研究

齿轮副啮合刚度是齿轮传动动力学模型中的重要参数,啮合刚度识别对于齿轮传动系统振动与噪声的分析以及状态监测具有重要意义。由于齿轮传动系统的时变啮合刚度很难用直接测量的方法得到,因此有必要发展基于数据驱动的齿轮时变啮合刚度辨识方法。为了解决该难题,本文提出了一种系统状态和模型参数交替优化方法以辨识齿轮传动系统时变啮合刚度。该方法以齿轮啮合频率为基频构造傅里叶基函数库表征齿轮时变啮合刚度,并进一步提出了一种基于再生核希尔伯特空间的降噪方法来估计系统状态和模型参数。系统状态变量与时变啮合刚度在动力学模型与数据双重约束下进行交替迭代优化,实现对齿轮传动系统时变啮合刚度的辨识。齿轮传动动力学仿真和齿轮传动系统实验结果验证了所提齿轮时变啮合刚度辨识方法的有效性。

一种改进的残余力向量法在结构损伤识别中的应用

残余力向量法是结构损伤识别中常用的方法,复杂结构中单元数量较多而损伤位置较少,容易造成无关变量增多,进而导致计算量过大的问题。鉴于此,本文提出一种改进的残余力向量法用于结构的损伤识别。该方法利用刚度联系向量与残余力向量之间线性相关的特性,以向量投影值作为损伤定位的影响系数,初步筛选出结构可能出现损伤的单元范围。在此基础上,构建出残余力向量对应的线性方程组,根据顺序主子式不为零的条件,对线性方程组进行行初等变换,再根据单元的数量保留前n维线性方程,通过求解该方程组的代数解可得到该结构单元的刚度损伤参数。以简支梁为例的数值模拟表明,本文方法可减少无关单元变量的计算,降低残余力向量的维度并且具有较好的抗噪能力。

考虑螺栓预紧力差异的箭体连接结构动力学响应分析

针对广泛地应用在航空航天箭体结构中的螺栓法兰连接结构的动力学响应特征会显著受到螺栓预紧力大小影响的问题,在螺栓法兰连接结构不同工况下螺栓预紧力出现差异时,研究箭体连接结构的静动力学响应特征。通过对特定的筒壳螺栓法兰连接结构,基于有限元分析和敲击试验来提出一套考虑螺栓预紧力差异的箭体连接结构动力学响应分析方法。并由此研究螺栓松动时的响应特征,基于互补集合经验模态分解算法设计一种新的螺栓松动探测流程,可以量化螺栓发生松动时连接结构的中高频段频响幅值升高的特征,能无损快速地识别松动工况的发生。

Gear fault diagnosis using gear meshing stiffness identified by gearbox housing vibration signals

Gearbox fault diagnosis based on vibration sensing has drawn much attention for a long time.For highly integrated complicated mechanical systems,the intercoupling of structure transfer paths results in a great reduction or even change of signal characteristics during the process of original vibration transmission.Therefore,using gearbox housing vibration signal to identify gear meshing excitation signal is of great significance to eliminate the influence of structure transfer paths,but accompanied by huge scientific challenges.This paper establishes an analytical mathematical description of the whole transfer process from gear meshing excitation to housing vibration.The gear meshing stiffness(GMS)identification approach is proposed by using housing vibration signals for two stages of inversion based on the mathematical description.Specifically,the linear system equations of transfer path analysis are first inverted to identify the bearing dynamic forces.Then the dynamic differential equations are inverted to identify the GMS.Numerical simulation and experimental results demonstrate the proposed method can realize gear fault diagnosis better than the original housing vibration signal and has the potential to be generalized to other speeds and loads.Some interesting properties are discovered in the identified GMS spectra,and the results also validate the rationality of using meshing stiffness to describe the actual gear meshing process.The identified GMS has a clear physical meaning and is thus very useful for fault diagnosis of the complicated equipment.

大跨度铁路斜拉桥索力快速识别方法研究

大跨度铁路桥梁天窗时间有限且上道条件苛刻,如何基于常规监测设备利用简易方式实现大跨度铁路斜拉桥索力高精度识别十分重要。研究提出一种考虑斜拉索抗弯刚度的索力快速识别方法,既可提高索力识别精度又可大量简化运营期索力识别步骤,且不受拉索边界条件和铁路桥梁实际运营状态的限制。研究表明,抗弯刚度是对索力识别精度影响较大的因素之一,通过考虑拉索实际抗弯刚度可以提高索力识别的准确性,基于拉索加速度振动实测数据在拉索简支梁模型基础上建立索频、索力以及抗弯刚度的函数关系,通过数值方法计算实测多阶模态下抗弯刚度—索力连续变化图,再通过多阶模态的交线则可进一步确定拉索的唯一抗弯刚度和索力值,并以某大跨度铁路斜拉桥为依托工程,对方法的有效性进行了验证。结果表明:(1)该方法识别的索力结果相对误差可降低5.22%,换算成绝对索力值可达254.45 kN;(2)在实际应用中识别结果易受到低阶频率干扰,宜采用拉索高阶频率进行识别,建议采用5阶及以上实测频率。

基于位姿变化的钻铆机器人刚度优化

钻铆机器人广泛应用于航空薄壁件加工装配中,当末端配备重载执行器进行钻铆作业时,因受到自身重力和横向切削力的影响会导致末端变形,加工质量变差,工业机器人这种弱刚性限制了其在精密加工领域的发展。以工业机器人自动钻铆系统为研究对象,建立运动学模型;选择合适的试验进行关节刚度辨识;在刚度模型基础上定义关节刚度性能指标;并通过粒子群优化算法寻找工业机器人作业时刚度最大位姿,确定所处位姿的关节角参数。通过选择合适的加工位姿提升工业机器人的刚度性能,保证孔位加工质量,提高生产效率,也可避免危险事故的发生。通过以上研究,可以求得符合钻铆工况下刚度最优的机器人工作位姿,并在假设实验中,验证了该姿态优化方法的可行性和有效性。

考虑螺栓预紧力作用范围不均影响的结合面刚度识别

螺栓连接结合面的刚度和阻尼的变化会引起整个螺栓连接结构的动态特性变化,准确得到结合面动态参数在工程中具有极大的实用价值。基于螺栓连接结构,提出螺栓预紧力作用范围内结合面刚度分布不均的结合面等效改进模型,并对有限元建模中不同数量刚度矩阵单元分布作出分析。采用实验与有限元分析相结合的方法对螺栓连接结合面进行刚度参数辨识。结果表明:在一定程度上,增加刚度矩阵单元数量可以提高固有频率解的精度。同时考虑螺栓预紧力作用范围内结合面刚度分布不均,可以有效地提高螺栓连接结构的等效建模精度。

致密砂岩气藏气井产水来源综合识别方法——以苏里格气田西区为例

针对在缺少单井产水计量的情况下,苏里格西区致密砂岩气藏气井产水来源识别困难的问题,通过引入水化学图示并结合矿化度分析、生产动态与核磁共振,创新性地建立了苏里格西区致密砂岩气藏气井产水来源综合识别方法。利用该方法对凝析水、工作液与地层水进行了识别。结果表明:气井凝析水与工作液的Stiff图版均被辅助线切割成两部分,而地层水的Stiff图版位于辅助线一侧,且不同时间的Stiff图版可判断气井是否发生水侵。工作液的矿化度大于20000 mg/L,而凝析水的矿化度小于20000 mg/L。对于地层水,层内水在井筒积液前油套压稳定,且压差小于2 MPa,而层间水油套压波动幅度大,且压差高于2 MPa。当含水饱和度小于驱替压力0.51 MPa的核磁饱和度时,地层水为束缚水;当含水饱和度大于驱替压力0.51 MPa的核磁饱和度或小于驱替压力0.032 MPa的核磁饱和度时,地层水为毛细管水;当含水饱和度大于驱替压力0.032 MPa的核磁饱和度时,地层水为自由水。

机床结合部动力学建模与辨识方法的研究

针对机床结合部动力学建模与辨识过程中对子结构间耦合关系与内部激振对外部响应影响考虑不充分问题,采用频响函数矩阵建立完备的机床结合部动力学理论模型;基于力学平衡条件和位移兼容条件推导了辨识方程,提出一种新的动力学辨识方法;辨识过程中融入了子结构间耦合关系,将难测频响矩阵作为中间变量抵消,避免使用难以测量频响或估算难以测量频响所引入的方程误差。在此基础上,将辨识方程拓展至整个测量频段,构建包含辨识关系的矛盾方程,通过最小二乘法求解确定了结合部的等效动刚度,建立了结构的有限元模型。为验证方法的正确性与可行性,基于LMS试验平台进行了现场试验,获得了良好的试验效果;与缩减维度、忽略内部激振作用的建模方法进行了对比分析,结果表明本文方法具有更好的预测性。

子结构界面连接刚度参数识别的一种直接方法

提出一种通过特征方程反问题识别子结构界面连接刚度参数的直接方法。新方法以动柔度矩阵特征方程为基础，建立通过界面位移求解界面内力的方程，由模态叠加法对可测自由度上不完全的振型拟合估计界面不可测自由度上的位移，适合于部分子结构不具备可测自由度的复杂组合结构。数值仿真算例和工程实例表明本方法具有良好的识别精度和数值稳定性。计算量和对计算机存贮量的要求也较小。

机床整机动刚度薄弱环节辨识与优化方法研究

提出一种机床整机动态分析指导薄弱部件改进的优化思路,即通过对机床整机的动刚度进行分析,辨识出不同激振频率下整机中的薄弱环节,明确优化目标,提高优化效率。利用ANSYS Workbench软件对一种卧式加工中心进行谐响应分析和模态分析,辨识出立柱是整机x向和z向动刚度的最薄弱环节。以立柱结构为优化对象,运用灵敏度分析法计算出立柱质量和固有频率对各个壁板的灵敏度。以立柱固有频率为优化目标,立柱质量为约束条件,建立优化方程。利用Matlab软件求解该方程,得到立柱的优化结果。通过谐响应分析得到优化后机床整机的动刚度,结果表明,优化后立柱在质量不增加的情况下,整机在x向和z向的最大共振峰值降低约6.5%,相应的共振频率提高约10%。

古建筑木结构地震损伤分析及抗侧刚度识别

为研究地震作用下古建筑木结构层间抗侧能力损伤和识别,根据缩尺比为1∶3.52殿堂式古建筑木结构振动台试验,分析不同地震损伤下模型层间等效抗侧刚度、侧移响应及侧移对刚度损伤的敏感性.在考虑柱脚滑移的结构简化力学模型基础上,推导模型的状态方程和观测方程.考虑试验环境噪声干扰,利用奇异值分解偏最小二乘(PLS-SVD)和扩展卡尔曼滤波(EKF)方法定量识别模型等效抗侧刚度.结果表明,随着地震损伤增加,结构层间等效抗侧刚度比减小、侧移峰值对柱架层结构损伤较乳层敏感.无损工况下结构等效抗侧刚度识别误差在10%左右;损伤工况下结构等效抗侧刚度识别误差为15%～20%.通过明代古建筑木结构西安钟楼等效抗侧刚度在线识别,验证了PLS-SVD和EKF方法可为古建筑木结构等效抗侧能力监测和震前抗倒塌预警提供理论依据.

基于热误差神经网络预测模型的机床重点热刚度辨识方法研究

为了合理分配机床热刚度并为机床零部件的热刚度优化提供依据,提出一种基于热误差神经网络预测模型的机床重点热刚度辨识方法。该方法针对机床不同零部件的热刚度对整机热刚度的影响具有不完全相同的特征,定义一种机床重点热刚度的概念。根据机床温度和热误差试验数据,利用径向基神经网络建模精度高和泛化能力强的特点,建立一种机床热误差神经网络预测模型。以机床不同零部件达到热平衡后产生的单位温升为热误差预测模型的输入矢量,计算热误差变化值作为机床重点热刚度的辨识依据,在此基础上阐述机床重点热刚度辨识方法的原理和实施步骤。将该方法应用在一台高架桥式龙门加工中心的重点热刚度辨识上,辨识结果与验证试验得到的结果相一致。