The Application of Combination Slice Analysis of Spectral Correlation Density in Rolling Element Bearing Diagnosis

通过对滚动轴承点蚀故障模型的研究,得到其二阶循环平稳特征,指出利用谱相关密度函数在循环频率域的信息,能够有效识别加性噪声干扰的点蚀故障类型,以此为依据提出了针对轴承局部故障识别的组合切片分析方法。该方法基于频域平滑循环谱估计算法,利用特征循环频率组对应的谱相关密度切片,通过切片间能量的对比判断轴承故障类型。组合切片分析计算效率较高,对噪声不敏感,在低信噪比信号特征识别中具有较大优势。文章最后通过来自实验台的内圈和外圈点蚀故障振动信号验证了该分析方法的有效性和实用性。A statistical model of rolling element bearing with spot defect is studied.Theoretical analysis shows that vibration from rolling element bearing with local defect is a typical second-order cyclostationary phenomenon,and the information in the cyclic frequency domain is sufficient for fault diagnosis.Therefore,a specialized method for bearing local defect detection is brought forward,and it is named as C-SSCD.The new method employs spectral smoothing algorithm to evaluate character slices of spectral correlation density.Those slices show distinct energy distribution for different bearing faults that can be used for fault diagnosis.C-SSCD method possesses high efficiency and high resolution at the same time,and it also has the advantage of weak fault detection.Experimental result shows that our method is effective and practical

压电柔性臂的传感器/致动器优化配置与振动主动控制

以欧拉-伯努利(Euler-Bernoulli)悬臂梁为模型,对压电柔性臂系统的传感器/致动器的优化配置和振动主动控制问题进行推导,简化了智能压电柔性臂系统的动力学方程和压电传感/致动方程,并建立了系..

Mid-spatial Frequency Error Identification of Precision Optical Surface Based on Empirical Mode Decomposition

对于高端光学元件,除限制低频面形误差和高频表面粗糙度之外,需要严格控制中频误差,以确保其使用性能。目前国际上广泛采用功率谱密度(POWEr SPECTrAl dEnSITy,PSd)曲线评价中频误差,该方法以fOurIEr变换为基础,在全局水平上给出中频误差的综合评价。但是,光学元件磨削与抛光工艺过程中,局部波动和变周期波动是常见的中频误差存在形式。为更加准确地评价中频误差,指导补偿加工,需要识别中频误差频率及位置信息。鉴于此,从光学表面属于非平稳空间信号的角度出发,提出基于经验模态分解的精密光学表面中频误差提取和识别方法,对光学表面拟合残差进行经验模态分解,得到一系列固有模态函数,根据各阶固有模态函数特征,识别不同空间位置存在的表面误差和波动频率,并将其合成得到光学表面的中频和高频误差。仿真与实际检测结果分析证实该方法可以有效识别中频误差特征及其方位。Mid-spatial frequency surface error of optical lens is crucial to the performance of high-energy laser systems and high-resolution optical systems.Power spectrum density(PSD) is generally employed to evaluate mid-spatial frequency error of optical surface.PSD is based on Fourier transform which averages local characters to the whole space.And it gives a whole evaluation of mid-spatial frequency error of optical surface.It not only weakens characters but also loses location information of surface error.Abrasive processing,such as grinding and polishing,always introduces local waviness with time-varying frequency on optical lens surface,PSD fails for this situation.A new error separation method,which is based on empirical mode decomposition,is introduced in this paper in order to more accurately evaluate mid-spatial frequency error and guide compensation machining.Curve of optical surface is preliminary fitted and the difference between the origin data and the fitting curve is decomposed to a series of intrinsic mode functions(IMFs).Local waviness characters of optical lens surface and its frequency can be recognized from each IMF and the corresponding instantaneous frequency plot.All IMFs are divided into high-frequency group and mid-spatial frequency group by average of instantaneous frequency of each IMF considering with IMF characters.IMFs in the same group are added to acquire high-frequency error or mid-spatial frequency error of optical surface.The simulation and experimental results of optical surface with different machining methods are employed to validate the effectiveness and correctness of the method.国家自然科学基金(51075343); 福建省自然科学基金(2012J05098)资助项

ON-LINE IDENTIFICATION of WHEEL WEAR CONDITION IN PRECISION GRINDING BASED ON INFORMATION FUSION

高质量非球面光学元件批量制造是目前精密磨削技术力求实现的目标。为了提高非球面光学元件精密磨削的加工效率,必须在加工过程中动态识别砂轮磨损状态,在砂轮接近或达到寿命周期时对其进行修整。寻求一种经济可行的方式,实现砂轮寿命周期在线评估,利用声发射、砂轮振动、磨削力等多种类型加工过程信号,提取和选择能够全面、灵敏反应砂轮磨损状态的特征,基于dEMPSTEr-SHAfEr证据理论,进行多源信息融合,实现精密磨削砂轮磨损状态在线识别。Grinding wheel should be addressed when it just reaches its expectancy in order to achieve high machining efficiency of aspheric optical lens.The realization of on-line estimating wheel life is based on the automatic identification of the wheel wear condition.Characters of dynamical process signals change accompanied with the lapse of the wheel life.Therefore,process signals can be used to monitor and estimate the wheel condition.Acoustic emission(AE),wheel vibration and grinding force are picked up to abstract three kinds of representative monitoring parameters.They are the skewness of the AE power spectrum,the complexity degree of the wheel vibration and the ratio of normal component and tangential component of the grinding force.These monitoring parameters are sensitive to different macro- and micro- wear of grinding wheel.The DempsterShafer evidence theory,which is one of the decision-level information fusion technologies,is employed to acquire a reliable decision about the status of the grinding wheel.福建省自然科学基金计划资助项目(2012J05098)~

Effects of Grinding Wheel Vibration on Surface Topography

砂轮振动将会使得光学元件表面产生周期性波动,从而降低后续抛光工序的加工效率,增加光学元件表面的中频误差成分,影响光学元件的使用性能。本文针对平行磨削方式,研究了砂轮周期性强迫振动下的工件表面形貌特征,分析了砂轮与工件表面的干涉现象,以及加工参数对加工表面波纹度特征的影响。研究结果表明:加工参数满足一定的条件下,工件表面振纹小于砂轮本身振动振幅,通过合理选择加工参数有利于改善工件表面波纹度,提高加工表面质量。Grinding wheel vibration has big influence on optical lens manufacturing.It not only reduces the efficiency of the following polishing procedure but also results in mid-frequency error on the surface.All the work in this paper expanded on the forced vibration of grinding wheel in parallel grinding of flat surface.The interference between wheel and workpiece is studied under different processing parameters.The research results show that waveness on the workpiece surface is decided by processing parameters;once the value of them is out of the critical points,the amplitude of the waveness on the workpiece surface will be lower than that of the wheel vibration.Therefore,reasonable choice of processing parameters is helpful to the improvement of the smoothness of the grinding surface.福建省自然科学基金计划项目(2012J05098)资

基于单元状态监控的机联网智能制造系统架构设计探析

随着\"工业4.0\"和\"中国智能制造2025\"指导框架的提出,制造领域面临急迫的产业转型与升级改造,机械制造产业也必将向智能制造时代迈进。精密制造领域作为机械制造产业中的重要分支,其对质量控制的要求越来越高,尤其在同类型产品的批量化精密制造中,高精度、高质量与高良率是制造过程必须考虑的首要因素。基于同类产品批量化精密制造的特点,本文在以大数据及物联网为架构的智能制造基础上,提出一种基于制造单元加工状态监控与决策的机联网智能制造子系统框架模型,并对其功能组成及架构设计进行了初步探析。首先论述了大数据、物联网与精密制造的内在联系;然后介绍了可实现制造单元加工状态和过程监测的相关技术与系统功能,并详细分析了制造单元加工状态大数据的获取与处理以及智能制造单元的智能控制方法;再次围绕实现车间级或局部制造区域内批量化精密制造系统的质量控制需求,探析了以无线自组网为基础组建批量化精密制造智能控制与决策的机联网子系统功能架构设计;最后以课题组目前开发的光学精密制造智能控制子系统为例进行了说明。国家自然科学基金项目(51675453);;深圳科技计划项目(JCYJ 20160517103720819

大口径光学元件的精密磨抛与检测装备开发及应用

大口径光学元件超精密加工是一个复杂的系统性工程,涉及精密机床、数控、加工技术与工艺、精密检测和补偿控制等机电控各领域的专业知识,其发展与一个国家的高端制造技术及装备发展能力息息相关,也是一个国家综合国力的集中体现。主要介绍了厦门大学微纳米加工与检测联合实验室在大口径光学元件超精密加工技术及装备方面取得的研究进展,针对大口径光学元件磨削和抛光两个加工流程及其配套的精密检测技术,详细阐述了磨削装备及单元技术、可控气囊抛光机床及相关单元技术、精密检测装备及相关单元技术等的研究应用情况。这些技术研究从超精密加工的需求出发,借鉴国内外的研究经验和成果,通过对装备、工艺、检测等各方面整合,形成了具有自主知识产权的集磨削、抛光和检测装备及工艺技术的大口径光学元件超精密加工体系,这些技术与装备确保了大口径光学元件的高质量超精密加工。国家自然科学基金项目(51675453);;深圳科技计划项目(JCYJ 20160517103720819

Research on Detection of Subsurface Damage on Grinding Optical Elements

基于氢氟酸刻蚀对光学元件亚表面裂纹影响的刻蚀模型,将化学刻蚀、逐层抛光技术和激光共聚焦扫描技术相结合,提出了一种磨削加工光学元件亚表面损伤的检测方法。实验证实该方法得到的亚表面损伤深度与公认的亚表面损伤预测模型的预测结果吻合性较好,是一种可靠的亚表面深度检测方法。Based on the etching model which hydrofluoric acid etching has an impact on the subsurface cracks of the optical elements, combined chemical etching, step-by-step polishing techniques and confocal laser scanner,a method of detecting sub-surface damage of the optical element was proposed.Research shows that this detection method is intuitive and effective,and the depth of subsurface damage match with the grinding results predicted by the model.国家自然科学基金(51275433); 福建省自然科学基金(2012J05098

金刚石砂轮磨削性能退化评估

为了提取高精度磨削干涉中的声发射信号特征,实现砂轮磨削性能退化评估,针对熔石英开展全寿命周期金刚石砂轮磨削实验,基于小波包分析确定砂轮磨损敏感频段为低频段,然后计算声发射信号在低频段的归一化能量占比,再利用主成分分析对能量占比进行特征降维获得单值特征,利用该单值特征绘制砂轮磨削性能退化曲线。研究结果表明,监测特征能够清晰反映砂轮初期磨损、正常磨损和过度磨损三个阶段,且监测结果不受加工参数影响;砂轮磨削材料破裂尺度与声发射频率具有一定关系,伴随砂轮磨损的加剧,较大尺度破裂的比例上升,造成65kHz以下低频段特征的能量占比增大,监测特征显著增加,磨粒崩碎产生新的切削刃,砂轮的去除能力有所改善,监测特征数值回落,但是,不同样本的声发信号频谱差异性显著增加,说明砂轮加工状态不稳定,不利于精密与超精密加工中维持稳定质量的要求。砂轮形貌图像的白像素占比变化曲线验证了声发射特征对砂轮磨损状态判断的正确性。科学挑战计划专题资助(JCKY2016212A506-0504);;\n国家自然科学基金资助项目(No.51805459

Formation and solving for the micro-waves of fly-cut surface introduced by spindle error

为分析超精密飞切机床加工表面微波纹的形成机理,研究了主轴回转误差信息提取与表面形貌仿真技术,获取微波纹误差来源并研究解决方案。首先,在超精密飞切机床主轴上搭载五通道在线电容位移检测系统,并对采集到的信号进行误差分析提取。然后,建立飞切加工表面微观形貌三维仿真模型,仿真分析主轴误差引入的加工表面微波纹,并与表面检测结果比对确定误差来源。最后,通过调整主轴电机控制系统抑制该误差。三维仿真和实测结果相吻合,证实超精密飞切机床主轴转速波动导致的回转误差造成了工件表面1 Hz左右的规律性条纹,对主轴转速控制系统进行数字化改造后,基本消除了该因素导致的表面微波纹,表面粗糙度从5 nm以上抑制到2 nm左右,PV值优于10 nm。超精密飞切机床主轴转速波动会对飞切加工表面微观形貌以及表面粗糙度产生显著影响,需至少控制在0.5 r/min以内。In order to find out the formation mechanism of micro-waves on the fly-cut surface,the spindle motion error was sampled and a 3D topography simulation model was compiled. Firstly,a nano-class testing and evaluation system was established on the fly cutting machine,the displacement data was sampled and the spindle motion error was analyzed.Then a 3D surface profile topography simulation model was established to analyze the micro-waves caused by the spindle motion error. The simulated surface was compared with the measured surface to find out the error sources. Finally,the characteristics of spindle were improved by adjusting the control system of the spindle motor. The simulated 3D surface profile topography was similar to that of the measured profile,which verified that the macro-waves was caused by the undulate of the spindle speed. When the spindle characteristics was improved,the macro-waves caused by the spindle motion error almost disappeared,and the surface roughness reduced from more than 5 nm to 2 nm. It is thus concluded that the undulate of ultra-precision fly cutting machine spindle speed causes macro-waves on the work-piece surface,and the undulate spindle speed must less than 0. 5 r / min.基金项目:高档数控机床与基础制造装备《强激光光学元件超精密制造关键装备研制》(2013ZX04006011-102-001