Remote vibration measurement: a wireless passive surface acoustic wave resonator fast probing strategy

Surface acoustic wave (SAW) resonators can advantageously operate as passive sensors which can be interrogated through a wireless link. Amongst the practical applications of such devices, structural health monitoring through stress measurement and more generally vibration characteristics of mechanical structures benefit from the ability to bury such sensors within the considered structure (wireless and battery-less). However, measurement bandwidth becomes a significant challenge when measuring wideband vibration characteristics of mechanical structures. A fast SAW resonator measurement scheme is demonstrated here. The measurement bandwidth is limited by the physical settling time of the resonator (Q/π periods), requiring only two probe pulses through a monostatic RADAR-like electronic setup to identify the sensor resonance frequency and hence stress on a resonator acting as a strain gauge. A measurement update rate of 4800 Hz using a high quality factor SAW resonator operating in the 434 MHz Industrial, Scientific and Medical band is experimentally demonstrated.     

无源无线应变传感器中压电材料接触力学模型研究

针对现有无源无线传感器存在稳定性差,抗干扰能力不强,传输距离过短的问题,提出一种新型无源无线应变传感器。 该传感器由两个线圈和一个体声波传感器组成,体声波传感器包括传力结构和石英晶片,其可将被测表面的应变转化为可检测 的石英谐振频率偏移。 首先,建立了半椭圆接触模型,研究接触力、激励电压、接触元件形状对石英的影响,以提高传感器性能; 其次,设计了石英加载装置,实现石英表面微力加载研究;最后,搭建了无源无线应变传感系统,传输距离可达 5 cm,分辨率约 为 4. 2 Hz/ με,应变测量范围为 600 με,重复性实验显示 RSD 为 5. 47% 。 实验结果表明,该传感系统具有良好性能,在未来将与 无人机结合为大型结构应变测量提供有效的解决方案。     

数控车削加工过程的刀具磨损动态监测

对车削加工刀具磨损的各阶段信号进行采集,通过动态时频域分析,找到车削加工过程中刀具磨损的重要参数变化,对其进行振铃记数和人工神经网络的模式识别,实现了车削加工刀具磨损的状态检测。     

Differential strain measurement using multiplexed fiber Bragg grating sensors

We investigate differential measurement of strain using fiber Bragg gratings and spatial demultiplexing methods. Differential measurement is shown to improve strain resolution in the presence of noise by an average of 34% compared to absolute measurements of the Bragg wavelengths. Spatial demultiplexing of the gratings provides potentially high-resolution sensing without calculating the sensor wavelengths. The differential method is still temperature dependent. We apply the differential technique to the problem of oil-water boundary detection in production columns, with promising preliminary results.     

利用声表面波实现液体的二维驱动

报道了利用声表面波实现水滴二维驱动的实验.在127.8° Y切X向传播的铌酸锂衬底上制作了4个叉指换能器.每个叉指换能器由10对电极构成,其叉指周期为400 μm,宽度为100 μm,孔径为12 mm,整个器件的尺寸为26 mm×26 mm×0.45 mm.由于铌酸锂晶体的各向异性,叉指换能器沿Y、X方向的谐振频率不同,分别为9.3 MHz 和9.6 MHz.基于铜材料相对于铝材料的优点,选用了铜材料并采用剥离工艺制作了电极,得到了优化的工艺参数.最后,用了超长时间超声波辅助方法彻底去除残胶,实现了对水滴的二维驱动,输入功率为9 W,液滴运动的平均速率为5 mm/s.利用ANSYS软件分析了声表面波在铌酸锂衬底内的传播,内部振动的模拟结果与理论分析一致.实验表明,利用声表面波实现液体的二维驱动是可行的,该液体驱动原型可用于片上系统和μ-TAS.     

Prediction of surface roughness in CNC turning by model-assisted response surface method

Various statistical approaches such as classical regression and modern machine learning methods have been applied to measurement data for estimating the status of manufacturing processes, which is now boosted by the movement of Internet of Things (IoT). In this study, we attempt to integrate an analytical tool model of surface roughness and measurement data of CNC turning to develop a modeling approach which does not depend too much on data, but also effectively uses existing analytical models. As in previous researches, we use cutting speed, feed rate, depth of cut and three acceleration components from an accelerometer to predict surface roughness. Co-Kriging method is employed to integrate the above measurements and a well-known model of surface roughness in turning. It was confirmed that the approach improved the prediction accuracy when only small amount of data is available for model construction. Meanwhile, the accuracy of ordinary Kriging method, which only depends on data, is suitable when measurement data sufficiently spans the parameter space, being expected that it may be rare in actual operations. We also attempted to detect outlier of measurements using the Co-Kriging method, which might be a non-trivial task when there is no additional information to evaluate the validity of the measurement data.     

Prediction and analysis of surface roughness characteristics of a non-ferrous material using ANN in CNC turning

Surface roughness, an indicator of surface quality is one of the most-specified customer requirements in a machining process. For efficient use of machine tools, optimum cutting parameters (speed, feed, and depth of cut) are required. So it is necessary to find a suitable optimization method which can find optimum values of cutting parameters for minimizing surface roughness. The turning process parameter optimization is highly constrained and non-linear. In this work, machining process has been carried out on brass C26000 material in dry cutting condition in a CNC turning machine and surface roughness has been measured using surface roughness tester. To predict the surface roughness, an artificial neural network (ANN) model has been designed through feed-forward back-propagation network using Matlab (2009a) software for the data obtained. Comparison of the experimental data and ANN results show that there is no significant difference and ANN has been used confidently. The results obtained conclude that ANN is reliable and accurate for predicting the values. The actual R _a value has been obtained as 1.1999???m and the corresponding predicted surface roughness value is 1.1859???m, which implies greater accuracy.     

基于宏程序的非圆曲面数控车削编程

非圆曲面编程过程存在计算量大、加工精度低、表面质量差等不足,基于此,提出了在非圆曲面加工中应用宏程序进行程序编制的方法.以抛物面为例,分析了抛物面应用宏程序进行数控加工的流程,并对零件上的抛物面的粗加工进行了实例编程,有效地提升了数控加工的经济效益.     

Monitoring of hard turning using acoustic emission signal

Monitoring of tool wear during hard turning is essential. Many investigators have analyzed the acoustic emission (AE) signals generated during machining to understand the metal cutting process and for monitoring tool wear and failure. In the current study on hard turning, the skew and kurtosis parameters of the root mean square values of AE signal (AERMS) are used to monitor tool wear. The rubbing between the tool and the workpiece increases as the tool wear crosses a threshold, thereby shifting the mass of AERMS distribution to right, leading to a negative skew. The increased rubbing also led to a high kurtosis value in the AERMS distribution curve.     

柔性声表面波器件的波模式分析

用反应磁控溅射法在柔性聚酰亚胺衬底上沉积了ZnO压电薄膜,并制备了基于ZnO压电薄膜的柔性声表面波(SAW)器件。制备的柔性SAW器件显示了良好的谐振性能,而且展现出两个波模式:模式0和模式1。当波长为32μm,ZnO厚度为4μm时,SAW器件的模式0和模式1的谐振频率分别为34.4MHz和158.5MHz,对应声速为1 100.8m/s和5 072m/s。模式0为已知的瑞利波,模式1为新的高频模式。沉积了不同厚度的ZnO薄膜制备柔性SAW器件,进一步分析了薄膜厚度对SAW器件和模式1的影响。分析认为该高频模式不是传统硬质衬底上SAW器件产生的Sezawa波,而是S_0兰姆波,并且是有衬底情况下的S_0兰姆波。文中还采用Comsol仿真分析了新的高频模式1的粒子振动位移,结果和S_0兰姆波粒子振动位移一致,从而验证了其为广义兰姆波的正确性。     

考虑温度影响的表面波压力测量模型研究

薄壁压力容器是一种常见的工业设备,为了保证生产过程的顺利进行,经常需要检测它们的压力。表面波在材料表面的传播速度与表面应力有关,因此以表面应力为中间变量,建立了被测容器压力与由此引起的表面波传播时间变化之间的关系模型。考虑温度、温度应力对表面波传播速度的影响,以及温度变化引起的热变形对传播距离的影响,推导了表面波压力检测的修正模型,并对修正模型各参数进行了分析,得到简化模型。实验证明了模型的正确性。使用该方法时,压力测量最大误差为0.11 MPa,平均误差为0.045 MPa。     

Bubble size measurement using wire-mesh sensors

A wire-mesh sensor with a time resolution of 1.2 kHz was used to measure bubble size distributions in a gas-liquid flow. It is designed for a pipe of 51.2 mm diameter and consists of two electrode grids with 16 electrodes each, put in the flow direction behind each other. The local instantaneous electrical conductivity is directly measured between all pairs of crossing wires, a tomographic image reconstruction is not necessary. The resulting 16 × 16 sensitive points are equally distributed over the cross section. This resolution is sufficient to detect individual bubbles, which are imaged in several successive frames during their transition through the measuring plane. To investigate the influence on bubbles, a model of the sensor was tested in a transparent channel with a rectangular cross section of 50 × 50 mm at liquid velocities between 0 and 0.8 m/s. A comparison with high-speed video observations has shown that the sensor causes a significant fragmentation of the bubbles. Nevertheless, the measured signals still represent the structure of the two-phase flow before it is disturbed by the sensor. Bubble sizes can therefore be determined by integrating local instantaneous gas fractions over an area of the measuring points occupied by the bubble. Bubble size distributions are obtained by analysing large assemblies of bubbles. The method was applied to study the formation of slug flow along a vertical tube. The bubble size distributions obtained show the effect of coalescence as well as bubble fragmentation.     

数控车床加工中刀具补偿问题

在数控车床加工中合理运用刀具补偿会在很大程度上提高编程效率,同时也能提高工件的加工精度.但刀具补偿问题一直是一个难点.     

双刀架曲轴数控车削在线测量及自动补偿的实现

为提高曲轴数控加工自动化程度,采用了双刀架曲轴数控加工与在线检测集成的方法,开发了上、下刀架刀具磨损自动补偿子程序.实际应用表明在线尺寸检测及自动补偿技术改善了加工质量和提高了加工效率.     

表面粘贴式MEMS应变传感器的应变传递分析

表面粘贴式MEMS应变传感器已被广泛运用于航空航天、汽车工业及土木工程等领域的应变测量和监测中。但由于粘接层的影响,结构的应变并不能全部准确、有效地传递到MEMS应变传感器上,造成传感器的测量值与结构的真实应变之间存在一定误差。为了分析表面粘贴式MEMS应变传感器的应变传递机理,基于剪滞理论建立了MEMS应变传感器的力学分析模型,推导出基体和MEMS应变传感器基底上的应变分布、粘接层中的剪力分布及表征MEMS应变传感器应变传递效果的应变传递率,并与有限元数值模拟结果进行了比较。特别地,具体分析了粘接层及MEMS应变传感器基底的几何参数和物理特性参数对应变传递率的影响。结果表明,金属类粘接材料的应变传递率明显高于有机胶的应变传递率,且粘接层厚度越薄,应变传递效果越好。此外,在制造MEMS应变传感器时,采用厚度较薄的Si或Si C基底能保证较高的应变传递率。     

数控车削铝合金表面粗糙度的实验研究

在数控车床上车削铝合金工件是当前高速切削的一个热点,选择合理的切削用量和刀具参数,成了提高切削效率和保证切削质量的关键技术。通过实验研究,分析了影响车削锻铝2A16表面粗糙度的切削用量因素、刀具几何因素。研究结果表明:在稳定切削条件下,大吃刀深度对表面粗糙度影响不大,采用合理刀尖圆弧半径和较小的进给速度,是减小表面粗糙度值的主要原因。     

Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis

This study presents a new method to determine multi-objective optimal cutting conditions and mathematic models for surface roughness (Ra and Rz) on a CNC turning. Firstly, cutting parameters namely, cutting speed, depth of cut, and feed rate are designed using the Taguchi method. The AISI 304 austenitic stainless workpiece is machined by a coated carbide insert under dry conditions. The influence of cutting speed, feed rate and depth of cut on the surface roughness is examined. Secondly, the model for the surface roughness, as a function of cutting parameters, is obtained using the response surface methodology (RSM). Finally, the adequacy of the developed mathematical model is proved by ANOVA. The results indicate that the feed rate is the dominant factor affecting surface roughness, which is minimized when the feed rate and depth of cut are set to the lowest level, while the cutting speed is set to the highest level. The percentages of error all fall within 1%, between the predicted values and the experimental values. This reveals that the prediction system established in this study produces satisfactory results, which are improved performance over other models in the literature. The enhanced method can be readily applied to different metal cutting processes with greater confidence.     

激光聚变冲击波被动式测速光学系统设计

针对激光聚变装置冲击波速度被动测量的需求,设计了一种测速光学系统。采用高紫外透过率的氟化玻璃,实现了透射式300～800nm复消色差设计。系统光路具有前后两组镜头,中间为平行光,镜头间距可变,光路适应能力强。系统前端两侧的双目机器视觉能够完成自动寻的。平行光路中设置5个激光器,轴上的1个前向照明靶点用来观察条纹相机狭缝处的目标像质,轴外的4个与光轴平行后向传输用来标识系统光轴的位置,激光器部件可电动切入/切出。系统前组镜头F/#数为4,宽谱工作物方分辨率优于10μm,532nm单波长工作物方分辨优于5μm。该光学系统光路排布灵活,可单独被动测速,也可与主动测速系统VISAR耦合构成主被一体复合测速系统,满足激光聚变装置冲击波测速的需求。     

数控车削中切削参数对表面质量的影响分析

切削参数的选择主要依赖于工艺人员的水平,往往由工艺设计人员凭经验决定,有一定的盲目性。针对数控车削中铝合金的切削参数选择展开研究。首先,针对影响表面质量的几个参数,在CK6136数控车床上加工102铝棒实验工件,得出实验数据,并对实验数据进行分析;其次,对主要参数的交互影响进行研究,结合具体工况,总结出选择方法。     

基于无线网络传感器技术的危险源实时监测系统

本文介绍了一种基于无线网络传感器技术的危险源的实时监控系统,系统由DS18B20温度传感器、涡流振动传感器、LPC900系列低功耗MCU、ZigBee无线模块等组成,主要实现对危险源的温度检测和振动监测,并将其温度和振动信号的实时状态经ZigBee模块传送给上位机.本文对系统的原理、无线网络传感器的电路原理图和程序设计、无线通信模块中的信息帧格式和无线网络传感器的组网设计做了详细介绍.