Piezoelectric Acoustic Emission Research Articles

ACOUSTIC EMISSION CONTROL OF DEFECTS IN THE AIRCRAFT WING ATTACHMENT ZONE IN FLIGHT

The results of studies obtained while monitoring the structure of the Tu-134A aircraft in flight are presented. On board the aircraft were installed two four-channel blocks of the microprocessor acoustic-emission (AE) system STsAD-16.12 and two antennas, each of which was connected to one of the system blocks. One of the antennas consisted of four piezoelectric acoustic emission transducers (PAEs), and the other antenna used two PAE sensors and two fiber optic sensors (FOS). Signals from the PAE and FOS sensors were received at the input of the measuring channels of each block of the system, processed and digitally entered into the computer. Then a linear location was built, carried out by two AE sensors installed on the frame, and a total count of AE signals over time, recorded during the takeoff of the aircraft, during its flight and landing.

Falling Damage Behavior Analysis and Degree Prediction for Wooden Pallet Based on Piezoelectric Effect and Acoustic Emission

Falling Damage Behavior Analysis and Degree Prediction for Wooden Pallet Based on Piezoelectric Effect and Acoustic Emission

A Review on Acoustic Emission Testing for Structural Health Monitoring of Polymer-Based Composites.

Acoustic emission (AE) has received increased interest as a structural health monitoring (SHM) technique for various materials, including laminated polymer composites. Piezoelectric sensors, including PZT (piezoelectric ceramic) and PVDF (piezoelectric polymer), can monitor AE in materials. The thickness of the piezoelectric sensors (as low as 28 µm-PVDF) allows embedding the sensors within the laminated composite, creating a smart material. Incorporating piezoelectric sensors within composites has several benefits but presents numerous difficulties and challenges. This paper provides an overview of acoustic emission testing, concluding with a discussion on embedding piezoelectric AE sensors within fibre-polymer composites. Various aspects are covered, including the underlying AE principles in fibre-based composites, factors that influence the reliability and accuracy of AE measurements, methods to artificially induce acoustic emission, and the correlation between AE events and damage in polymer composites.

Investigation of Acoustic Emission Wave Propagation Pattern with Defect Locations in a Multilayer Structure

Acoustic emission (AE) is used to monitor conditions of various structures across many industrial sectors, including containment vessel or storage tank of nuclear materials. Periodic monitoring, inspection, and analysis of structure conditions can help prevent failure and accidents. Understanding the transient elastic waves in multi-layered structures (planar or rounded types) has long been of great interest. This paper experimentally investigates changes in AE wave propagation patterns in multilayer planar structures (detecting and assessing the effect of coating layers, assumed surrogate of deposits or protective layer). Epoxy phenolic coated two mild steel plates were assembled (without any adhesion), and two piezoelectric AE sensors were placed on the coating layer. The pencil lead break (PLB) test was used to initiate the AE waves from the surface and cross-section of different layers. From wavelet transforms (WT) analysis, significant energy zone changes were observed up to the 450 kHz frequency level with PLB on the surface and cross-section of different layers. Love wave propagation on the coated plate structure resulted in wave pattern changes with PLB locations and layers. Wave duration, energy, energy ratio, and peak amplitude levels were also analysed to characterise the AE wave pattern relationship with defect location in a multilayer plate-like (planar) structure. The approaches used in this work could potentially be useful in providing a greater understanding of defects within multilayer nuclear containment structures, and also offering an alternative way to monitor corrosion related degradation of structures with insulations.

Preparation and acoustic properties of high-temperature acoustic emission sensor based on La3Ga5SiO14 crystal

With the rapid development of modern industries, the high-temperature piezoelectric sensors that can work in extreme environments are in great demand. In this work, langasite (La3Ga5SiO[Formula: see text], LGS), as a high-temperature piezoelectric crystal with stable electro-elastic performance, is used as core element, and air and porous Al2O3 are selected as backing layers respectively to prepare two kinds of high-temperature acoustic emission (AE) sensors. The detection sensitivities at 25-500[Formula: see text]C are analyzed by the ball falling test and Hsu–Nielsen experiment. Under the condition of 25–500[Formula: see text]C, the received amplitude signals by both sensors are maintained above 90 dB stimulated by the ZrO2 ceramic ball dropping. In the Hsu–Nielsen experiment, as the temperature rising from 25[Formula: see text]C to 500[Formula: see text]C, the signal amplitude of sensor with air backing layer decays from 447 mV to 365 mV, while the signal amplitude varies from 270 mV to 203 mV for the sensor with porous Al2O3 backing layer. Significantly, compared with the bandwidth of the air-backing sensor (37–183 kHz), the sensor with porous Al2O3 backing layer broadens bandwidth to 28–273 kHz. These results show that both these AE sensors have strong and stable response ability to AE signals at high-temperature of 500[Formula: see text]C. Therefore, piezoelectric AE sensor based on LGS has great potential application in the field of high-temperature structural health monitoring.

Modeling of Acoustic Emission Wave and Its Parametric Characterization Based on Peak Sensor Sensitivity on an Aluminum Block

In this paper an acoustic emission (AE) signal has been generated analytically for a homogenous material with a surface load. For the validation of the AE theory, a simulation for a developed AE wave has been conducted with computational algorithms. Experimental validation for the AE wave generation and propagation have also been performed under similar conditions. Aluminum metal block has been selected as the homogenous propagation medium for both simulation and the experiment. A function generator has been used for the excitation of a burst sine signal on the surface. A piezoelectric AE resonance sensor receives the vertical response due to the vertical load of the function generator. The algorithm of Lamb's solution has been employed in the generation of a simulated AE wave. As the transfer function, the peak sensor sensitivity of the AE sensor (R15alpha) has been incorporated along with the acoustic impedance of the metal surface and sensor. For both detected and simulated AE waves, the signal parametric characterizations have been performed based on the rise time and the maximum amplitude. The attenuation properties of the maximum amplitude and the increase of rise time with the increment of source to sensor distance has been evaluated to validate the proposed method.

A novel acoustic emission sensor design and modeling method for monitoring the status of high-speed train bearings

Acoustic emission (AE) technology is suitable for monitoring the status of high-speed train bearings owing to its high sensitivity and real-time dynamic monitoring capabilities. However, a complete theoretical model of the AE sensor, which is the core component of AE signal sensing equipment, has not yet been reported. The existing matching layer models do not account for wave attenuation in the matching layer. To address these shortcomings, we established a novel piezoelectric AE sensor design and modeling method. First, a rough contact model is established for piezoelectric ceramics, and the influence of roughness on size selection of piezoelectric ceramics is analyzed. Second, the sound intensity transmission coefficient (SITC) model of the matching layer is established considering the attenuation of AE waves, and the corresponding relationship between the attenuation coefficient and the optimum thickness of the matching layer is derived. Then a complete finite element (FE) model of an AE sensor is established, and the electroacoustic properties of the AE sensor are numerically simulated based on acoustic and piezoelectric coupling. Furthermore, AE sensors with different thicknesses of matching layers are constructed, and the validity of the mathematical model of the matching layer is verified through a lead-breaking experiment. Thereafter, a novel comprehensive performance evaluation index (CPEI) is designed through principal component analysis (PCA) based on hit parameters of AE sensors. Finally, the effectiveness and environmental adaptability of the AE sensor is verified by performance testing under complex conditions near an actual high-speed train line. The proposed method can provide a valuable theoretical framework for AE sensor design and status monitoring of high-speed train bearings.

Flexible Pb(Zr0.52,Ti0.48)O3 thin film acoustic emission sensor for monitoring partial discharge in power cable

Piezoelectric acoustic emission sensors can be used detect the sound emitted by the target structure when it is damaged and have important applications in the field of structure health monitoring. However, due to the mismatch of the interface acoustic impedance, it is hard for the conventional ultrasonic sensor to monitor the acoustic emission in a pipe structure. In this work, a flexible sensor by the deposition of a Pb(Zr0.52,Ti0.48)O3 thin film on a mica substrate was fabricated, and the acoustic emission generated by the partial discharge of a 110 kV power cable was detected by using the flexible sensor. The flexible sensor was designed with an electromagnetic shielding structure and, therefore, can screen most of the electromagnetic interference. The flexible sensor shows a relatively flat response in the frequency range from 100 to 1000 kHz with a sensitivity over 47.5 dB, which is beneficial for pattern recognition studies of acoustic emission. This work not only provides a flexible, anti-electromagnetic interference and broadband sensor for acoustic emission detection but also promotes the development and application of flexible ferroelectric materials.

Theoretical and experimental analysis of acoustic emission signal for resonant sensor on homogenous material

The modelling of AE signal has been conducted for AE resonant sensor. For surface loading, the generation of acoustic emission (AE) signal has been developed and simulated in this paper for two homogenous materials. The simulated results have been verified by executing AE model experiments under similar considerations. Aluminum and steel have been selected as the wave propagation media for both modelling and experiment. A sine load at source point has been implemented by a function generator. A piezoelectric AE resonant sensor has been utilized to collect the vertical response due to the vertical load on the material surface. It converts the dynamic displacement of the AE wave into electrical signal. As the transfer function of the sensor, the sensor sensitivity characteristics of the AE sensor (R15α) has been calculated and incorporated in the model. The acoustic impedance of the metal surface and sensor has been utilized to determine the transfer loss due to the signal travelling from the sensor to the material. For both the experimental and simulated AE waves, the rise time and the maximum amplitude have been evaluated and the signal parametric characterizations have been performed. The attenuation property of maximum amplitude and the increase of rise time with the increment of source to receiver distance has been determined for the verification of the proposed model.

A multifunctional rock testing system for rock failure analysis under different stress states: Development and application

The stress state in a rock mass is complex. Stress redistribution around underground excavation may lead to various failure modes, including compressive-shear, tensile-shear, and tensile failures. The ability to perform laboratory tests with these complex stress states is significant for establishing new strength criteria. The present paper introduces a new rock testing system with “tensile-compressive-shear” loading functions. The device includes bi-directional and double-range hydraulic cylinders, auxiliary loading equipment, and roller rows that can perform direct compressive-shear tests, direct tensile tests, and direct tensile-shear tests. The testing system provides maximum vertical and lateral loading forces of 2000 kN and allows testing cubical rock specimens with dimensions of 0.5 m × 0.5 m × 0.5 m. The performance of the testing machine was evaluated by testing a rock-like material based on cement mortar under compressive-shear, tensile, and tensile-shear stress states. The failure process and deformation characteristics were monitored during loading using acoustic emission (AE) transient recorder, piezoelectric AE sensors, a high-speed camera, and a thermal infrared camera. The failure mechanism was investigated by analyzing AE counts, AE amplitude, strain, and temperature changes on the rock specimen surface. The test results confirmed that the testing system could successfully simulate the abovementioned stress path. The AE counts and amplitude responses were influenced by different failure modes. The temperature response during the compressive-shear test indicated the development of a high-temperature band on the rock specimen surface. In contrast, a negligible temperature change was observed during the tensile and tensile-shear tests. The newly developed multifunctional rock testing system allows laboratory tests under various failure modes. The monitoring results of multiple variables during rock failure tests provide valuable information on failure characteristics. • Develop a novel rock testing system with tensile-compressive-shear loading function. • Investigate the failure behavior of rock-like specimens under different stress states. • Analyze the various attributes response characteristics in different failure modes.

TESTING OF CFRP SPECIMENS WITH IMPACT DAMAGE USING THE ACOUSTIC EMISSION METHOD AND TENSOMETRY

Samples of carbon fiber T 700 were researched. They were subjected to impact damage, after which they were loaded with a static load until failure. Registration of defects was carried out using the method of acoustic emission (AE) and tensometry. In the process of loading the samples, the deformation and load were determined, at which the AE signals were located. An antenna consisting of piezoelectric acoustic emission transducers (PAE) and fiber optic sensors (FOS) was used to monitor defects. When the load changed from 80 to 100 kN, a jump in mechanical stresses was observed in the samples from 338 to 432 MPa, registered by the certified microprocessor-based high-speed tensometic system “Dynamics-3”. In this case, the average amplitude of the AE signals significantly decreased, starting from the load P = 80 kN, after which it increased at the load P = 110 kN. For sensors PAE 3 and VOD 2, located on the opposite side of the sample, where impact damage was absent, these changes in the amplitudes of the AE signals were less pronounced.

Using acoustic emission technique for detecting checks on industrial-size beech wood disks during drying

Wood disks are very susceptible to checking during drying. The present study was aimed to determine a suitable transducer mounting configuration to detect the drying checks with acoustic emission (AE) technique. AE generated during drying of 30-mm-thick beech (Fagus orientalis L.) wood disk with a diameter of 300 mm were monitored using piezoelectric AE transducers operating at frequency of 50-200 kHz. The transducers were directly attached on the disks with four combinations depending on the sensor number and grain direction. Total number of AE events and event rate were associated with drying time and checking features. The successive formation of near-bark radial checks was detected due to fluctuations in the AE event rate. Results showed that if the transducers are attached to the disk lateral surfaces, the formation of pith checks cannot be detected in the early stages of the check formation. The V-shaped cracks can be only detected when the transducer is mounted very close to the crack location. Overall, our results showed that more than two transducers are required to detect all types of checks occurred during drying of wood disks of this size. They should be attached parallel to the grain, one near to the pith and the rest at a suitable distance around periphery of the disk.

Locating Acoustic Emission Signals Due to Shock Impacts on a Carbon Fiber Sample Using Piezoelectric and Fiber Optic Sensors

Comparative tests related to locating acoustic emission (AE) signals due to shock impacts on a T700 carbon fiber sample were carried out. Piezoelectric acoustic emission transducers (AETs) and fiber-optic sensors (FOSs) were installed on the sample, forming rectangular location antennas measuring 360 times 280 mm. Strikes were delivered with balls weighing 10 and 18.5 g. Antennas consisting of four AET sensors and four FOS sensors and an antenna consisting of two AET sensors and two FOS sensors were organized. When using the antenna containing four FOS sensors, the impact on the sample was produced by a load weighing 530 g dropped from a height of 400 mm. AE signals were recorded by the SCAD-16.10 system with “floating” selection thresholds when the ball was dropped and during its repeated bounces. Then AE signal clusters were formed and recorded during the impact of loads. The arrival times of AE signals to the antenna sensors were calculated using the threshold method, the root mean square (RMS) deviation method and the two-interval method. It is shown that the maximum error in locating AE signals is observed when a steel ball with a diameter of 16 mm is dropped from a height of 300 mm and the minimum error is when using an electronic simulator.

Acoustic emission data based deep learning approach for classification and detection of damage-sources in a composite panel

Structural health monitoring for lightweight complex composite structures is being investigated in this paper with a data-driven deep learning approach to facilitate automated learning of the map of transformed signal features to damage classes. Towards this, a series of acoustic emission (AE) based laboratory experiments have been carried out on a composite sample using a piezoelectric AE sensor network. The registered time-domain AE signals from the assigned sensor networks on the composite panel are processed with the continuous wavelet transform to extract time-frequency scalograms . A convolutional neural network based deep learning architecture is proposed to automatically extract the discrete damage features from the scalogram images and use them to classify damage-source regions in the composite panel. The proposed deep-learning approach has shown an effective damage monitoring potential with high training, validation and test accuracy for unseen datasets as well as for entirely new neighboring damage datasets. Further, the proposed network is trained, validated and tested only for the peak-signal data extracted from the raw AE data. The application of peak-signal scalogram data has shown a significant improvement in damage-source classification performance with high training, validation and test accuracy.

Study of the Use of Piezoelectric Diaphragm as a Low-Cost Alternative to the Acoustic Emission Sensor in Dressing Operation of Aluminum Oxide Wheels

Acoustic emission (AE) sensors have been widely used for tool condition monitoring in the grinding process. Recently, the piezoelectric diaphragm (piezoelectric buzzer) was introduced as a low-cost alternative for the same purpose. In this context, the present research work aims to study the efficiency of the piezoelectric diaphragm as a viable substitute to AE sensors in monitoring the dressing of structurally distinct aluminum oxide grinding wheels. Dressing tests were conducted using two industrial wheels, which were subjected to various dressing conditions. The signals generated by the AE and piezoelectric diaphragm sensors were collected simultaneously and subsequently analyzed in both time and frequency domains. The most relevant features related to the dressing were extracted through the following metrics: energy criterion, Pearson correlation coefficient, power spectral density (PSD), fast Fourier transform (FFT), and magnitude-squared coherence (MSC). Correlation greater than 80% was found between the piezoelectric diaphragm and AE sensor signals for determining the actual grinding wheel condition, which indicates the piezoelectric diaphragm as a viable alternative to the commercial AE sensors in dressing operation monitoring.

Effects of periodic cavitation on steam–water flow regime transition and mixing near steam nozzle exit

Abstract Supersonic steam injection from underwater vehicles into surrounding bulk water exhibits the formation of coherent structures due to the interfacial interaction between the steam and water. The mixing between the two is a function of the rate of growth of shear layer. In present work, experimental study is conducted with minor contribution from the CFD, to highlight the phenomena associated to the high-pressure steam injection into a pool of water under the influence of periodic cavitation which occurs near the steam's nozzle exit with its opening being at right angle to the opening of the exit nozzle. PIV setup along with piezoelectric acoustic emission sensors as well as LM35 temperature sensors and pitot tubes were applied to characterize the growth of the shear layer as a function of periodic cavitation with a range of steam's operating pressure. Based on the normalized shear growth rate as well as the Strouhal number and the normalized pitot thickness, the effect of rising in the cavitation on the variations of the thickness of the shear layer was studied. It was observed that higher area under the influence of the shear layer was due to the domination of the coherent flow structures, which influenced improved mixing between the steam and water. Comparison of our data with the available shear growth rate in literature shows good agreement when compared as a function of Mach number.

All-Fiber Laser-Self-Mixing Sensor for Acoustic Emission Measurement

Self-mixing interferometry (SMI) is a promising non-destructive sensing technology with advantages of simplicity in system structure, low cost in implementation, ease in optical alignment, and high resolution in measurement. It consists of a laser diode, a photodiode packaged at the rear of the laser diode, a lens, and a target to be measured. Typically, SMI-based sensing is to measure the phase change in an SMI signal with a fringe pattern as sinusoidal or saw-tooth like. The phase is called optical phase in external cavity that is linked to the quantity to be measured, e.g., displacement, velocity, and vibration. Each SMI fringe maps to a half-laser-wavelength displacement of the target. With increasing feedback level in an SMI system, some fringes may lost or even totally disappear. In this case, the laser output from an SMI system can trace the optical phase to achieve a linear sensing relationship. In this article, we design an all-fiber SMI linear sensor for real-time and fast tracking acoustic emission (AE) signals. Firstly, a system design in terms of selection of operating parameters is presented. Then, a proof of concept experimental system was built for detecting AE signals. The results show that the proposed SMI sensor has comparable AE detection capability to piezoelectric sensor, providing a compact and cost-effective optical AE sensing solution without need of extra signal processing, which can be considered as a viable alternative to the well-established piezoelectric AE sensor.

Monitoring of the High-Technology Nailing of CFRTP Material under Ultrasonic Vibration by Acoustic Emission Method

In this study, the potential to monitor the high-technology nailing of carbon fiber reinforced thermoplastic material (CFRTP) under ultrasonic vibration was investigated by acoustic emission (AE) method. AE signals were detected by a piezoelectric AE sensor during high-technology nailing under ultrasonic vibration. This paper describes some experimental results on AE signal characteristics and observation of the high-technology nailing. In order to investigate the effects of machining condition, we focused on RMS voltage, which is dependent on the energy parameter of the AE signal. It was found that the AE method is a useful method of monitoring high-technology nailing.

Multichannel fiber laser acoustic emission sensor system for crack detection and location in accelerated fatigue testing of aluminum panels

Detection and location of the source of acoustic emission in a thin aluminum panel is demonstrated using a multichannel fiber laser sensor system. Acoustic emission generated by a crack in an aluminum panel used as a test coupon in an accelerated fatigue experiment is detected and the location of the crack identified. Acoustic emission is detected over a bandwidth of around 0.5 MHz from a serially multiplexed array of four laser sensors and compared with measurements taken from four piezo-electric sensors co-located with the fiber laser sensors. The location of the crack is determined by first estimating time difference of arrival of signals at each sensor using a novel algorithm based on the cumulative distribution transform method with hyperbolic positioning. The fiber laser sensor is shown to match the signal-to-noise ratio of the industry standard (Mistras S9225) piezo-electric acoustic emission sensor.

Magnetic-repulsion-coupled piezoelectric-film-based stretchable and flexible acoustic emission sensor

This paper presents a stretchable and flexible acoustic emission (AE) sensor composed of patterned upper, lower piezoelectric film foils, magnets and stereolithographic structures. The proposed device possesses the following novelties. The piezoelectric sensing structures with magnetic repulsion is effective for AE signal coupling. The lower piezoelectric serpentine-shaped AE detection structure with stretchable and flexible characteristics allows sensing various curved surfaces. Additionally, the contact force between the sensing target and AE sensor can be evaluated by monitoring the structural characteristic change of the upper piezoelectric structure of the AE sensor. The magnetic-repulsion-enhanced AE sensor exhibits a better bandwidth compared to that with only a lower AE sensing structure. Also, the fabricated sensor subjected to a sensing target force ranging from 4.98 to 14.85 mN resulting in a frequency change of the piezoelectric sensing beam of the upper foil from 20.073 to 20.135 kHz is verified. The developed AE sensor can open a new field for various applications. For instance, AE waves can be monitored without contacting the target (e.g. interfacing with air). The detection mechanism of AE waves by an action at a distance is successfully demonstrated.