Monitoring of strain induced by heat of hydration,cyclic and dynamic loads in concrete structures using fiber-optics sensors

Advances in sensors technology provided an opportunity to monitor structures during different construction stages, as well as the behavior of concrete elements during hydration and strength gain. In this paper, embedded Fabry–Pérot fiber-optic sensors were utilized in an experimental investigation to study the hydration process in two different concrete volumes. In addition, the sensors performance under cyclic and torsional loading was investigated. The results showed that up to +300 μstrains could be developed until the final setting is reached. The increase in strain was accompanied by a 55 °C (130 °F) increase in temperature during the first 24 h. These values vary based on the nature of the mix and the concrete volume. In the cyclic and torsion tests, the fiber-optic sensors responded to load variations and were capable of recording samples responses as small as 1 μstrain.     

嵌入式容栅传感技术及轴功率测试研究

针对旋转轴功率测试存在的传感器信号引线困难、安装空间受限、信号易受干扰的问题,设计了一种嵌入式容栅扭矩、转速传感器和测试系统.测试时在轴的两端分别安装容栅传感器,轴在受到扭矩时产生扭角,则两容栅的输出信号会产生一个相位差,通过测量相位差的变化得到扭矩.容栅传感器的差动结构提高了灵敏度减小了误差,容栅的嵌入式安装,将对被测轴的影响降到了最低.实验证明容栅传感器可靠性高,可以在环境要求严格的情况下长时间使用,并且无需通过滑环、无线或红外进行供电和信号的传输,克服了以上方式安装复杂、信号易受干扰的缺点.     

光纤光栅传感技术在分岔隧道模型中的实验研究

基于光纤光栅测量应变的诸多优势,将自制的光纤光栅传感器模块埋到分岔隧道三维地质力学模型中,在隧道开挖过程中,测量各埋入点的应变,将其与埋入相应点的应变片的测量结果以及数值分析结果进行了比较.结果表明,光纤光栅、应变片测得的结果与数值分析所得的结果趋势基本一致,但光纤光栅实测数据相比应变片测得数据更接近于仿真数据,并且可靠性高,在大型工程的长期监测中有较好的应用前景.     

Tool breakage detection in CNC high-speed milling based in feed-motor current signals

Tool condition monitoring, mainly tool breakage detection for high-speed machining (HSM), is an important problem to solve; however, the techniques or types of sensors applied in other research projects present certain inconveniences. In order to improve tool breakage monitoring systems, a simple, effective, and fast method is presented herein. This method is based on the discrete wavelet transform (DWT) and statistical methodologies. The effectiveness of the method is based on the measurements of the feed-motor current signals using inexpensive sensors. It is well-known that during the cutting process, the motor current is related to the tool condition. The current consumption changes when the tool is broken as compared to when the tool is in normal cutting condition. This difference can be obtained from the waveform variances between the signals in order to ascertain the tool condition. The algorithms of this research project consist of obtaining compressed signals from the I _rms feed-motor current signals applying the DWT. Then from these compressed signals, we detect the asymmetries between them. The arithmetic mean value is applied to asymmetries of consecutive machining lengths to reduce noise in the data having a mean value of a series of asymmetries; also, a normal cutting threshold is set up in order to make decisions regarding the tool conditions so as to detect tool breakage. Therefore, this research project shows a low-cost monitoring system that is simple to implement.     

Application of a data-driven monitoring technique to diagnose air leaks in an automotive diesel engine: A case study

This paper presents a case study of the application of a data-driven monitoring technique to diagnose air leaks in an automotive diesel engine. Using measurement signals taken from the sensors/actuators which are present in a modern automotive vehicle, a data-driven diagnostic model is built for condition monitoring purposes. Detailed investigations have shown that measured signals taken from the experimental test-bed often contain redundant information and noise due to the nature of the process. In order to deliver a clear interpretation of these measured signals, they therefore need to undergo a ‘compression’ and an ‘extraction’ stage in the modelling process. It is at this stage that the proposed data-driven monitoring technique plays a significant role by taking only the important information of the original measured signals for fault diagnosis purposes. The status of the engine's performance is then monitored using this diagnostic model. This condition monitoring process involves two separate stages of fault detection and root-cause diagnosis.The effectiveness of this diagnostic model was validated using an experimental automotive 1.9 L four-cylinder diesel engine embedded in a chassis dynamometer in an engine test-bed. Two joint diagnostics plots were used to provide an accurate and sensitive fault detection process. Using the proposed model, small air leaks in the inlet manifold plenum chamber with a diameter size of 2–6 mm were accurately detected. Further analyses using contribution to T² and Q statistics show the effect of these air leaks on fuel consumption. It was later discovered that these air leaks may contribute to emissions fault.In comparison to the existing model-based approaches, the proposed method has several benefits: (i) it makes no simplifying assumptions, as the model is built entirely from the measured signals; (ii) it is simple and straight-forward; (iii) there is no additional hardware required for modelling; (iv) it is a time and cost-efficient way to deliver condition monitoring (i.e. fault diagnosis application); (v) it is capable of pin-pointing the root-cause and the effect of the problem; and (vi) it is feasible to be implemented in practice.     

Performance evaluation of an indigenously designed copper (U) tube Coriolis mass flow sensors

This paper describes an experimental study carried out for three different sets of U tube configurations made of copper for an indigenously developed setup of Coriolis mass flow sensor integrated with virtual instrumentation. The setup has been installed on an especially designed and constructed foundation using Passive Vibration Isolation technique. The location of sensors, drive frequency and L/d ratio were found to be influencing design parameters on the performance. In the present study water has been used as fluid for flow measurement. The setup was calibrated for the experimentally obtained result indicates a linear relationship between measured time lag and mass flow rate. The results also indicates that for the undertaken experimental conditions the case C is the optimum configuration from the point of view of minimum percentage of error in calibrated mass flow rate.     

刀具嵌入镍铬合金薄膜微传感器切削力测量的研究

切削力的测量旨在改进和提高切削加工性能。本文设计和制备了一种镍铬合金薄膜微传感器,将其焊接嵌入刀具的刀杆上以测量加工中的切削力。该传感器由Ti6A14V钛合金基体、镍铬合金薄膜层及氧化铝绝缘层组成。切削力引起的薄膜变形使四个电阻栅组成的惠斯通电桥产生输出电压,对其输入和输出电压之间的关系进行了理论分析。构建了切削力测量系统。研究结果表明,该薄膜传感器具有良好的线性度和更小的相互干扰,适合于各种条件下车削力的测量。     

Effect of wafer size on material removal rate and its distribution in chemical mechanical polishing of silicon dioxide film

Chemical mechanical polishing (CMP) is a semiconductor fabrication process. In this process, wafer surfaces are smoothed and planarized using a hybrid removal mechanism, which consists of a chemical reaction and mechanical removal. In this study, the effects of wafer size on the material removal rate (MRR) and its uniformity in the CMP process were investigated using experiments and a mathematical model proposed in our previous research; this model was used to understand the MRR and its uniformity with respect to wafer size. Under constant process conditions, the MRR of a silicon dioxide (SiO₂) film increased slightly along with an increase in wafer size. The increase in MRR may be attributed to the acceleration of the chemical reaction due to a rise in process temperature. Based on the results obtained, the k and α values in the mathematical model are useful parameters for understanding the effect of wafer size on the MRR and its distribution under a uniform, relative velocity. These parameters can facilitate the prediction of CMP results and the effective design of a CMP machine.     

基于数字域TDI算法改进面阵CMOS图像传感器功能

为使面阵CMOS图像传感器具有TDI成像功能,研究了TDICCD的工作原理,提出了一种基于数字域的TDI算法,并讨论了如何利用FPGA实现该算法。该算法可在不改变CMOS器件构造的前提下,使其具有时间延迟积分功能。通过举例法推导出面阵CMOS图像传感器数字域TDI计算公式,并在此基础上优化了算法结构,优化后可以节省(m-1)(m-2)/2行内存空间。最后以航天相机为背景,讨论了地面像元分辨力、行转移时间与CMOS帧频的关系,通过一个算例计算出不同分辨力和积分级数条件下对CMOS帧频的要求。计算结果表明,帧频大于648frame/s的1280×1024CMOS,可以满足600km轨道高度下地面像元分辨力为1m的96级积分成像要求。     

Radial gas-permeability measurement in cement-based materials under steady-state flow

An innovative apparatus guided by a proposed theoretical-model was developed for evaluating the radial gas-permeability of cement-based materials under steady-state flow. The testing condition is of higher inlet-gas pressure in an annular concrete cavity to monitor the pressure decrease over time. The gas-tightness for the cavity was effectively enhanced and quantitatively characterized by an ingenious silicone-rubber washer with embedded flexible sensors. The radial gas-permeabilities of the annular concrete with different water-to-cement (w/c) ratios of 0.35–0.55 were measured using various inlet-gas pressures (1.0 bar–30.0 bars) and compared to those obtained by the traditional axial-direction method. The results show that the concrete gas permeability in radial-direction reaches stable permeability zone (SPZ) with inlet-gas pressure exceeding 6.0 bars, which is faster than the SPZ with inlet-gas pressure exceeding 15.0 bars of the axial-direction gas permeability obtained by the traditional method. Under the same inlet-gas pressures of 6.0 bars–10.0 bars, the intrinsic permeability values in the radial and axial directions are near to each other with the standard deviations of 2.83%~9.90% while the apparent permeability values in the radial direction are lower than those in the axial direction by reductions of 3.69%~21.89%. The evolution of apparent gas permeability in radial-direction obeys well the typical model with the low coefficients of variation from 1.01% to 12.55%, indicating that the as-obtained apparatus combined with the proposed theoretical-model can quantitatively and accurately evaluate the radial-direction gas permeability of cement-based materials.     

A high-stress tri-axial cell with pore pressure for measuring rock properties and simulating hydraulic fracturing

A high-stress tri-axial cell that can accommodate pore pressures was designed to simulate hydraulic fracturing processes in the laboratory. The cell can maintain its integrity and causes negligible deformations up to 100 MPa, providing sufficient precision for measuring rock properties and simulating hydraulic fracturing under reservoir conditions. Wedged spacers embedded with O-seals provide the pore pressure inside the cell. Special considerations are taken to avoid stress concentrations, including tapering the flat jacks to ensure uniform stresses on the sample. Acoustic sensors can be attached to the samples to detect acoustic emission signals. Simulations using the designed cell were performed and provided reasonable results.     

低速重载球面摩擦副石墨镶嵌润滑结构设计及比较

人字闸门底枢作为半球面摩擦副，在水下长时间以低速、重载工况运行，易因磨损导致故障。传统的油脂润滑容易造成环境污染，而固体镶嵌润滑是更为适宜的润滑方式。为了研究不同材料和轴瓦镶嵌结构对底枢摩擦副摩擦学性能的影响，通过试验得到石墨填充润滑材料的力学性能以及不同条件下的摩擦因数；以三峡大坝人字闸门底枢为研究对象，从工程实际与理论分析角度设计了相同孔径和渐变孔径2种不同轴瓦镶嵌结构，利用有限元软件分析了球面静态接触和旋转运行状态下的接触应力，对比了光滑轴瓦、相同孔轴瓦和渐变孔轴瓦的理论摩擦因数。结果表明：从应力角度，相同镶嵌结构下石墨润滑优于高分子赛龙材料润滑；在相同填充面积条件下，3种结构中最大等效应力从大到小依次为渐变孔结构、相同孔结构和光滑结构，而从润滑以及理论摩擦因数角度看，渐变孔结构性能最好，然后依次为相同孔结构和光滑结构；相比镶嵌孔路径，无镶嵌孔路径上的轴瓦等效应力较小。因此，在实际应用中，应确保力学偏置方向与轴瓦的无镶嵌孔区域相符，以减小应力集中并提高润滑性能。     

精细积分法在车辆动力学仿真中的应用

Euler积分方法在解决具有刚性问题的微分方程时不能够很好地满足车辆动力学仿真的需要。采用精细积分法，将其应用于纯侧向车辆动力学模型中，并与相同工况下Euler积分方法的仿真结果进行了比较，解决了Euler积分方法在车轮低转速、积分大步长的情况下无法得到稳定仿真结果的问题。     

Locating acoustic emission sources in complex structures using Gaussian processes

A standard technique in the field of non-destructive evaluation is to use acoustic emissions to characterise and locate the damage events that generate them. The location problem is typically posed in terms of the times of flight of the waves and results in an optimisation problem, which can at times be ill-posed. A method is proposed here for learning the relationship between time of flight differences and damage location using data generated by artificially stimulated acoustic emission (AE)—a classic problem of regression. A structure designed to represent a complicated aerospace component was interrogated using a laser to thermoelastically generate AE at multiple points across the structure's surface. Piezoelectric transducers were mounted on the surface of the structure, and the resulting waveforms were recorded. A Gaussian process (GP) with RBF kernels was chosen for regression. Since during AE monitoring not all events can be guaranteed to be detected by all sensors, a GP was trained on data for all possible combinations (subsets) of sensors. The inputs to the GPs were the differences in time of flight between sensors in the set, and the targets were the locations of the source of ultrasonic stimulation. Subsequent (test) data points were located by every possible GP, given the active sensors. It is shown that maps learned on a given structure can generalise effectively to nominally identical structures.     

Model-based techniques for the testing and diagnosis of micro-manufacturing devices and machines

One of the main difficulties in developing a testing-and-diagnosis system for micro-manufacturing devices and machines is that the measurement process can require a high number of sensors, and is often too complex, in order to avoid external disturbances under normal working conditions, and the sensors are also not easy to allocate due to the minimal space available. At the present time, modern techniques of control-system engineering can be applied to propose a model-based testing and diagnosis methodology that reduces the number of the required sensors, due to a priori knowledge of the system expressed in terms of mathematical relationships between the physical variables. The Mechatronic Variable Estimation Library was created as a tool to estimate the value of “unknown” variables and parameters of the micro-device or machine using only a few sensors, reducing in this way the cost of the testing system and making the product of interest for industrial applications.     

WEIS wheel speed real-time measuring method for VOSM

Wheel speed is one of the key parameters of vehicle operating attitude. To solve the problems in traditional wheel speed measuring methods, such as low measurement precision and the lack of real-time monitoring of the vehicle’s operating attitude, a wheel embedded intelligent sensors (WEIS) wheel speed measuring method for vehicle operating safety states monitoring (VOSM) is innovatively proposed. Radial acceleration signal is obtained through a WEIS module embedded in the hub. Using wavelet packet to implement wavelet de-noising for the non-stationary acceleration signals, and adopting short-time Fourier transform (STFT) algorithm to extract the signal characteristics, the wheel speed measurement can be achieved. The experimental result shows that under experimental conditions the speed measurement error is −2.05%, and the speed measuring response time is 0.45 s.     

基于嵌入式多参量传感器的智能轴承

提出了一种新型的基于嵌入式多参量传感器的智能轴承结构。多参量复合传感器包括2个微型振动加速度传感器、2个微型转速传感器和2个微型温度传感器。通过轴承外圈上的槽式结构,将复合传感器与轴承端面进行嵌入式结合,实现对轴承运转过程中水平和垂直地面两方向的振动信号、轴承转速信号、内圈(轴)和外圈温度信号的采集。对其原理样机进行了实验验证,验证结果表明,该智能轴承监测参数准确,其参数监测和故障诊断能力较传统的方式更具优越性。     

A Bayesian machine learning method for sensor selection and fusion with application to on-board fault diagnostics

In applications like feature-level sensor fusion, the problem of selecting an optimal number of sensors can lead to reduced maintenance costs and the creation of compact online databases for future use. This problem of sensor selection can be reduced to the problem of selecting an optimal set of groups of features during model selection. This is a more complex problem than the problem of feature selection, which has been recognized as a key aspect of statistical model identification. This work proposes a new algorithm based on the use of a Bayesian framework for the purpose of selecting groups of features during regression and classification. The hierarchical Bayesian formulation introduces grouping for the parameters of a generalized linear model and the model hyper-parameters are estimated using an empirical Bayes procedure. A novel aspect of the algorithm is its ability to simultaneously perform feature selection within groups to reduce over-fitting of the data. Further, the parameters obtained from this algorithm can be used to obtain a rank order among the selected sensors. The performance of the algorithm is first tested on a synthetic regression example. Finally, it is applied to the problem of fault detection in diesel engines (30,000 data records from 43 sensors, 8 classes) and used to compare the misclassification rates with a varying number of sensors.     

WEIS wheel speed real-time measuring method for VOSM

Wheel speed is one of the key parameters of vehicle operating attitude. To solve the problems in traditional wheel speed measuring methods, such as low measurement precision and the lack of real-time monitoring of the vehicle’s operating attitude, a wheel embedded intelligent sensors (WEIS) wheel speed measuring method for vehicle operating safety states monitoring (VOSM) is innovatively proposed. Radial acceleration signal is obtained through a WEIS module embedded in the hub. Using wavelet packet to implement wavelet de-noising for the non-stationary acceleration signals, and adopting short-time Fourier transform (STFT) algorithm to extract the signal characteristics, the wheel speed measurement can be achieved. The experimental result shows that under experimental conditions the speed measurement error is − 2.05%, and the speed measuring response time is 0.45 s.