In-Situ Structural Health Monitoring of a Reinforced Concrete Frame Embedded with Cement-Based Piezoelectric Smart Composites

ABSTRACT

The application of a novel cement-based piezoelectric (PZT) ceramic sensor to the in-situ stress-time history monitoring of a reinforced concrete frame structure is described in this article. Smart frame composite structures were produced and characterized by a range of experimental methods. ADINA, a finite element analysis program, was used to analyze the mechanical response of the concrete frame under static loading. The results show that the mechanical-electrical response of sensors embedded in a reinforced concrete frame structure follows a linear relationship under various loading conditions. The sensors are able to record the stress history of the frame under static loads. Moreover, the measured stress maxima agree well with the simulated results, and the smart structure is found to be capable of reliably monitoring the response of a frame structure during stress testing for different loading modes to real concrete structures. The study indicates that such cement-based PZT composites have a high feasibility and applicability to the in-situ stress-time history monitoring of reinforced concrete structures.     

Monitoring of Impacted Aramid-Reinforced Composites by Embedded PVDF Acoustic Emission Sensors

Abstract:  An embedded piezoelectric [poly(vinylidene fluoride) (PVDF)] thin film sensors system for acoustic emission (AE) was realized to investigate the possibility of monitoring, in real time, the post-impact damage in aramid woven fabric-reinforced epoxy. The same sensors have been used in a previous work on similar specimens tested in flexure but not previously impacted, with the aim of verifying the suitability of these sensors to be embedded and their ability to detect AE signals under loading. This work is a continuation of the previous one aiming at evaluating the ability of these embedded PVDF sensors to point out the presence of impact damage, issue widely studied in literature. Aramid fibre/epoxy composite specimens with embedded PVDFs, previously impacted at different energies, namely 5, 10 and 15 J, were tested using three-point bending tests. It appeared from mechanical tests that the flexural strength decreased passing from non-impacted specimens to those impacted with the highest energy and that the embedment of PVDFs in the laminates did not markedly affect the structural integrity of the impacted composites. The degree of impact damage, represented by the decrease in mechanical properties, has been correlated with the AE activity by means of a parametric analysis of the AE signals detected during post-impact mechanical tests.     

传感器测试FRP约束混凝土轴压短柱的核心区应力

提出了一种使用水泥基压电陶瓷传感器测试混凝土轴压短柱应力的新方法。将压电传感器埋入混凝土矩形短柱核心区,测试了纤维增强复合材料约束前后混凝土短柱的轴向动态疲劳载荷,建立了传感器输出信号与混凝土短柱核心区应力之间的数值模型,并将理论计算应力值与由模型推导出的应力值进行对比。结果表明:模型推导应力值与理论计算应力值基本吻合,验证了使用压电传感器测试动态载荷作用下混凝土短柱应力这一新方法的可行性。     

互易法校准压电型声发射传感器的研究与实现

声发射传感器的校准是实现声发射定量技术的前提,依据电声换能器互易原理,在计算互易常数的基础 上,建立了适用于压电型声发射传感器表面波和纵波互易的校准系统。通过设置特定的激励信号波形,依据接收 电压信号与激励电流信号之间的时间延迟,准确获取电流信号与电压信号对应的特征值,实现了声发射传感器的表面波和纵波互易校准。由于传感器的尺寸效应,传感器在高频时的表面波速度灵敏度低于纵波灵敏度,不确定度评定结果表明,声发射传感器速度灵敏度的互易法校准不确定度为1. 2 dB。     

基于声发射信号的三维针刺C/SiC复合材料拉伸损伤演化研究

本研究对三维针刺C/SiC(3-dimension needled C/SiC, 3D-N C/SiC)复合材料进行室温单调拉伸和拉伸加载-卸载试验, 利用声发射技术对试样损伤演化进行动态监测。采用K-均值聚类分析方法对小波降噪后的声发射信号进行了损伤模式识别, 结合试样断口扫描电镜观测, 发现3D-N C/SiC复合材料在拉伸载荷作用下主要存在五类损伤模式: 基体开裂、界面脱粘、界面滑移、纤维断裂和纤维束断裂。通过快速傅里叶变换(FFT)方法对小波降噪后的信号进行频谱分析得出: 3D-N C/SiC复合材料在拉伸载荷作用下主要存在240、370和455 kHz三种频率的损伤信号, 分别对应于界面损伤、基体损伤和纤维损伤。结合单调拉伸试验过程声发射信号能量柱分布和加卸载过程累积能量曲线特征, 分析了试样损伤演化机理。     

Effect of electric cyclic loading on fatigue cracking of a bending piezoelectric hybrid composite actuator

Fatigue damage development in bending piezoelectric hybrid composite actuators with different lay-up configurations under electrical loading cycles is addressed in this work with the aid of an acoustic emission (AE) technique. Electric cyclic fatigue tests have been performed up to 10⁷ cycles on the fabricated bending piezoelectric hybrid composite actuators. The applied electric loading range is from ?150 voltage to +150 voltage. To confirm the fatigue damage onset and its pathway, the source location and distributions of the AE behavior over the fatigue range are analyzed. In conclusion, electric cyclic loading leads to piezoelectric fatigue damage such as trans- and intergranular micro-damage and long path main cracking on the surface of the PZT ceramic layer, thereby degrading the displacement performance. However, this fatigue damage and cracking do not result in final failure of the bending piezoelectric hybrid composite actuator loaded up to 10⁷ cycles. In particular, investigation of the AE behavior and the linear AE source location reveals that the onset time of the fatigue damage varies considerably depending on the existence of a GFRP protecting bottom layer.     

Acoustic emission analysis of composite pressure vessels under constant and cyclic pressure

The use of acoustic emission (AE) for the detection of damage in carbon fibre composite pressure vessels was evaluated for constant and cyclic internal gas pressure loading conditions. AE was capable of monitoring the initiation and accumulation of damage events in a composite pressure vessel (CPVs), although it was not possible to reliably distinguish carbon fibre breakage from other microscopic damage events (e.g. matrix cracks, fibre/matrix interfacial cracks). AE tests performed on the carbon fibre laminate used as the skin of pressure vessels revealed that the development of damage is highly variable under constant pressure, with large differences in the rupture life and acoustic emission events at final failure. Numerical analysis of the skin laminate under constant tensile stress revealed that the high variability in the stress rupture life is due mainly to the stochastic behaviour of the carbon fibre rupture process.     

Diagnostic of fatigue damage severity on reinforced concrete beam using acoustic emission technique

Fatigue damage assessment using non-destructive testing on structures as well as reinforced concrete (RC) beam has become an attention for recent decades. In this paper, diagnostic of fatigue damage in RC beams using acoustic emission (AE) technique was investigated. Based on severity analysis of AE signal strength during service life of the beams, bath–tub curves derived from AE signal are presented and divided into three stages; burn-in, steady state and burn-out. At the same time, deflection in the RC beams also has been analyzed.     

Effectiveness of nonlinear ultrasonic and acoustic emission evaluation of concrete with distributed damages

Nonlinear ultrasonic (NLU) and acoustic emission (AE) techniques are used for nondestructive evaluation of concrete, damaged under compression loading. Experiments were carried out in 18 cubic specimens (150 × 150 × 150 mm) cast with three different w/c (six specimens for each w/c). Three specimens at each w/c were used for AE monitoring and three others for NLU evaluation. The NLU evaluation is based on measuring the change in fundamental amplitude with increasing damage and output power level. In acoustic emission testing technique four sensors were used to listen to the wide range of events under various loading and unloading cycles. An increase in AE hits was observed with increasing damage. Each loading and unloading stage was carefully examined for Kaiser and Felicity effects in order to assess the concrete deterioration. It was proposed to measure Felicity ratio at three different loading levels, corresponding to AE hits at 3%, 5%, and 10% of the AE hits at the previous maximum load, respectively. Normalized values of Felicity ratio were plotted and compared with the NLU test data. Correlation between acoustic emission and nonlinear ultrasonic techniques in assessing damage growth in concrete was investigated.     

Use of piezoelectric as acoustic emission sensor for in situ monitoring of composite structures

In this paper, the influence of the integration of several sensors in composite structures is investigated. The plates and the structures in simple shapes, composed of laminated and sandwich materials, are considered. The mechanical behaviour, the acoustics activity and the location of damage sources in various structures with and without piezoelectric implant are compared. The analysis of results allowed a better identification of the influence of the impact of piezoelectric implant on the mechanical behaviour of different structures under different loads. Then, the analysis and the observation of Acoustic Emission (AE) signals led to the identification of the main acoustic signatures of different damage modes dominant in each type of composite materials (laminates and sandwich). Viewpoint comparison between integrated and non-integrated structures, acoustic activity is more significant in the case of integrated material. The location of the sources of damage has shown that acoustic events occurred far from the positions of integrated sensors.     

Acoustic emission detection of fatigue cracks in wind turbine blades based on blind deconvolution separation

The occurrence and expansion of fatigue cracks in large wind turbine blades may lead to catastrophic blade failure. Each fatigue phase of a material has been associated with a typical set of acoustic emission (AE) signal frequency components, providing a logical base for establishing a clear connection between AE signals and the fatigue condition of a material. The relevance of efforts to relate recorded AE signals to a material's mechanical behaviour relies heavily on accurate AE signal processing. The main objective of the present study is to establish a direct correlation between the fatigue condition of a material and recorded AE signals. We introduce the blind deconvolution separation (BDS) approach because the result of AE monitoring is usually a convoluted mixture of signals from multiple sources. The method is implemented on data acquired from a fatigue test rig employing a wind turbine blade with an artificial transverse crack seeded in the surface at the base of the blade. Two different sets of fatigue loading were conducted. The convoluted signals are collected from the AE acquisition system, and the weak crack feature is extracted and analysed based on the BDS algorithm. The study reveals that the application of BDS‐based AE signal analysis is an appropriate approach for distinguishing and interpreting the different fatigue damage states of a wind turbine blade. The novel methodology proposed for fatigue crack identification will allow for improved predictive maintenance strategies for the glass‐epoxy blades of wind turbines. The experimental results clearly demonstrate that the AE signals generated by a fatigue crack on a wind turbine blade can be synchronously separated and identified. Characterizing and assessing fatigue conditions by AE monitoring based on BDS can prevent catastrophic failure and the development of secondary defects, as well as reduce unscheduled downtime and costs. The possibility of using AE monitoring to assess the fatigue condition of fibre composite blades is also considered.     

Dynamic analysis of sandwich cement-based piezoelectric composites

Theoretical analysis of a sandwich cement-based piezoelectric composite is presented based on the theory of piezo-elasticity. The steady-state responses of two kinds of this composite under different loading cases are obtained by the use of displacement method. The effects of piezoelectric phases on the performance of this kind of devices are simulated and discussed. The solutions are compared with both the numerical and experimental results, and good agreements are found. Sandwich cement-based piezoelectric composites have great application potential in civil structure health monitoring. The results obtained in this paper are beneficial to the design of this kind of smart devices.     

Modified Gutenberg–Richter Coefficient for Damage Evaluation in Reinforced Concrete Structures Subjected to Seismic Simulations on a Shaking Table

This paper presents analysis and discussion of the \(b\) - and ib-values calculated from the acoustic emission (AE) signals recorded during dynamic shake-table tests conducted on a reinforced concrete (RC) frame subjected to several uniaxial seismic simulations of increasing intensity until collapse. The intensity of shaking was controlled by the peak acceleration applied to the shake-table in each seismic simulation, and it ranged from 0.08 to 0.47 times the acceleration of gravity. The numerous spurious signals not related to concrete damage that inevitably contaminate AE measurements obtained from complex dynamic shake-table tests were properly filtered with an RMS filter and the use of guard sensors. Comparing the \(b\) - and ib-values calculated through the tests with the actual level of macro-cracking and damage observed during testing, it was concluded that the limit value of 0.05 proposed in previous research to determine the onset of macro-cracks should be revised in the case of earthquake-type dynamic loading. Finally, the \(b\) - and ib-values were compared with the damage endured by the RC frame evaluated both visually and quantitatively in terms of the inter-story drift index.     

基于声发射检测技术的PE/PE自增强复合材料破损机理分析

用声发射(AE)技术研究了聚乙烯自增强复合材料的拉伸损伤与断裂行为.宽带传感器记录了不同角度纤维铺层的复合材料试样在拉伸破坏过程中的声发射信号,用扫描电子显微镜(SEM)观察了试样的几种典型的损伤破坏断面,对比分析了不同类型的损伤机制.实验分析表明,拉伸过程中破坏机制对声发射信号的特征具有显著影响,不同损伤模式的信号频谱特征存在明显的差异.声发射检测能有效提取热塑性复合材料损伤破坏信息,在材料的结构损伤主动监测中有良好的应用潜力.     

汶川地震下框架结构的抗倒塌能力分析

从震害统计和数值模拟两个方面研究了按现行抗震规范设计的钢筋混凝土框架结构的抗倒塌能力。汶川地震大量钢筋混凝土框架结构震害统计表明,按7度抗震设防的结构在地震烈度达到9度或加速度峰值达到400gal,开始出现倒塌破坏(占1%~2%);当地震烈度达到11度或加速度峰值达到800gal以上时,出现大量的倒塌破坏(占60%以上)。进一步以汶川强震记录为输入,对两个典型的钢筋混凝土框架结构进行了增量动力分析。结果表明:7度抗震设防时可抵御300gal~500gal加速度峰值作用(地震烈度近似9度);按8度抗震设防时可抵御400gal~600gal加速度峰值作用(地震烈度近似10度)。总体上看按现行抗震规范设计的钢筋混凝土框架的超强系数基本大于2。     

基于多维阵列和空间滤波器的损伤无波速成像定位方法

随着复合材料在航空结构中的广泛应用,基于压电传感器（PZTs）阵列和Lamb波的结构健康监测成像方法已经成为复合材料结构健康监测技术的研究热点,但是复合材料的各向异性特点导致依赖于信号传播速度的延迟-累加、相控阵等成像方法难以实现其损伤的准确监测。鉴于此,研究了一种与信号传播速度无关的空间滤波器损伤成像定位方法,该方法利用Lamb波在结构中传播时的空间-波数域特征,通过设置空间权重函数使压电传感器阵列形成波数带宽为[k_min,k_max]的空间-波数域滤波器对特定空间方位的Lamb波进行滤波,得到损伤的角度图像; 然后,利用多维线性压电传感器阵列各自针对损伤得到的角度图像进行融合,得到损伤的坐标图像,从而实现了在不依赖传播速度的情况下对损伤的成像定位。在碳纤维层合板上对该方法进行了实验验证。实验结果表明：基于多维线性压电传感器阵列和空间-波数域滤波算法的无波速成像定位方法可以对复合材料结构损伤进行不依赖信号传播速度的成像定位,定位误差在1 cm以内。     

Optimization of piezoelectric sensor location for delamination detection in composite laminates

The optimal placement of sensors is a critical issue in detecting damage in laminated composite structures. The aim is to use a minimum number of sensors, placed at the correct locations, so that the voltage signals received from the sensor set can be used to detect both the presence and the extent of damage. In this study, an optimization procedure is developed to detect arbitrarily located discrete delamination in composite plates using distributed piezoelectric sensors. The probability of damage distribution in the plate is determined using a statistical model. A genetic algorithm (GA) is used to detect the number and location of the sensors. The analysis uses a Monte Carlo method to generate the initial population. The simulation and signal processing is performed using a finite element procedure based on the refined layer-wise theory, which is capable of modelling ply-level stresses, and seeded delaminations are modelled with Heaviside step functions. A two-way electromechanical coupled field formulation is used to describe the induced strain. The objective function is a damage index which compares the voltage signals from a healthy (no delamination) and a statistically determined delaminated model. The voltage signals are affected by the local changes in the strain induced by the presence of delamination. The optimization solutions are verified by numerical simulation as well as with experiments conducted using customized piezoelectric sensors and a laser scanning vibrometer. The results presented show that the optimum sensor pattern is capable of detecting discrete seeded delaminations in moderately thick composite plates.     

Detection of Damaged Tool in Injection Molding Process with Acoustic Emission

ABSTRACT

The measurement of acoustic emission (AE) signals during injection molding of polypropylene with new and damaged mold is presented. The damaged injection mold was fitted with a steel insert with cracks induced by laser surface heat treatment. Two resonant piezoelectric AE sensors were attached to the mold via AE waveguides. To improve the mold integrity prediction with smaller defects, AE signal frequency characteristics and a measure of AE signal amplitude probability distribution are implemented. A 5-dimensional feature vector with real-valued explanatory variables is proposed, providing the defining points in an appropriate multidimensional space to characterize the state of injection molding tool. Feature vectors are classified with neural network pattern recognition. The results confirm that presented AE technique offers characterizing the integrity of molds also with resonant sensors.     

基于Shannon 复数小波的复合材料结构时间反转聚焦多损伤成像方法

研究了一种基于压电传感器阵列和主动Lamb 波的结构损伤成像方法,有助于克服Lamb 波在板结构中、特别是在复合材料板结构中存在的频散、多种模式及模式转换的现象给结构健康监测带来的困难。分析了结构多损伤散射信号的时间反转聚焦原理,在此基础上提出了一种基于Shannon 复数小波和时间反转聚焦的信号合成成像方法。该方法中,确定Lamb 波响应信号的到达时刻是信号能够准确聚焦的关键因素之一。提出了利用Shannon 复数小波变换计算Lamb 波响应信号到达时刻的方法。在碳纤维复合材料板结构上对整套信号合成成像方法进行了验证。研究结果表明,该方法能够有效地对同一个监测区域中的多个损伤进行成像定位。相对于30 cm ×30 cm 的监测区域,定位误差不超过2 cm。该方法有助于结构健康监测技术的工程应用。      

Characterisation of Damaged Tubular Composites by Acoustic Emission,Thermal Diffusivity Mapping and TSR-RGB Projection Technique

An increase in the use of composite materials, owing to improved design and fabrication processes, has led to cost reductions in many industries. Resistance to corrosion, high specific strength, and stiffness are just a few of their many attractive properties. However, damage tolerance remains a major concern in the implementation of composites and uncertainty regarding component lifetimes can lead to over-design and under-use of such materials. A combination of non-destructive evaluation (NDE) and structural health monitoring (SHM) have shown promise in improving confidence by enabling data collection in-situ and in real time. In this work, infrared thermography (IRT) is employed for NDE of tubular composite specimens before and after impact. Four samples are impacted with energies of 5 J, 7.5 J, and 10 J by an un-instrumented falling weight set-up. Acoustic emissions (AE) are monitored using bonded piezoelectric sensors during one of the four impact tests. IRT data is used to generate diffusivity and thermal depth mappings of each sample using the thermographic signal reconstruction (TSR) red green blue (RGB) projection technique. Analysis of AE data alone for a 10 J impact suggest significant damage to the fibres and matrix; this is in good agreement with the generated thermal depth mappings for each sample, which indicate damage through multiple fibre layers. IRT and AE data are correlated and validated by optical micrographs taken along the cross section of damage.