Acoustic emission from superconducting magnets

We have shown experimentally that the acoustic emission (AE) is an effective means of monitoring the operating conditions of superconducting magnets and can be used to prevent catastrophic quenching. the signal-to-noise ratio of AE transducers at liquid helium temperature has been found to be about 18 dB higher than that at room temperature; AE originating from a superconducting magnet and those from the liquid helium shower can be clearly discriminated by observing their wave forms and frequency spectra. These results are also discussed from a theoretical view point based on an elastic medium model for the superconducting magnet.     

Stability of the vertical bearing structures of the Syracuse Cathedral: experimental and numerical evaluation

In the present paper the results from a recent monitoring campaign and numerical analysis performed on the ancient Cathedral of Syracuse in Sicily are presented. The acoustic emission (AE) technique is adopted to assess the damage pattern evolution. The localization of the propagating cracks is obtained using six synchronized AE sensors. A clear correlation between the regional seismic activity and the AE acquisition data is shown. In fact the AE count rate presents peaks corresponding to the main seismic events. In addition, a numerical analysis of the vertical bearing structures of the Cathedral is presented. The nonlinear Finite Element model is particularly refined to account for the cracking in the most damaged pillar. Some recent seismic events in the area acted as crack propagators. The crack occurrence obtained from the numerical analysis agrees quite well with the crack localization provided by the AE monitoring.     

Acoustic emission during quench training of superconducting accelerator magnets

Acoustic emission (AE) sensing is a viable tool for superconducting magnet diagnostics. Using in-house developed cryogenic amplified piezoelectric sensors, we conducted AE studies during quench training of the US LARP’s high-field quadrupole HQ02 and the LBNL’s high-field dipole HD3. For both magnets, AE bursts were observed, with spike amplitude and frequency increasing toward the quench current during current up-ramps. In the HQ02, the AE onset upon current ramping is distinct and exhibits a clear memory of the previously-reached quench current (Kaiser effect). On the other hand, in the HD3 magnet the AE amplitude begins to increase well before the previously-reached quench current (felicity effect), suggesting an ongoing progressive mechanical motion in the coils. A clear difference in the AE signature exists between the untrained and trained mechanical states in HD3. Time intervals between the AE signals detected at the opposite ends of HD3 coils were processed using a combination of narrow-band pass filtering; threshold crossing and correlation algorithms, and the spatial distributions of AE sources and the mechanical energy release were calculated. Both distributions appear to be consistent with the quench location distribution. Energy statistics of the AE spikes exhibits a power-law scaling typical for the self-organized critical state.     

基于聚类分析的罐底声发射检测信号融合方法

采用声发射技术进行罐底腐蚀与泄漏检测过程中,需要对多个传感器的检测到的声发射信号进行融合处理,将属于同一声发射源的声发射信号判定为一个声发射事件。但是在现场检测过程中,由于噪声的存在,使得在声发射信号融合处理时容易对声发射源产生误判。针对该问题,提出了一种基于聚类分析的罐底声发射信号融合方法,其基本原理是先根据事件定义时间进行初始声发射事件判定,然后采用聚类分析方法对初始声发射事件中的信号进行分类,将每一类信号分别判定为一个声发射源。现场实验表明采用该方法抗噪声干扰能力强、误判概率低,能准确反应罐底腐蚀的实际情况。     

Acoustic Emission Sensor Calibration for Absolute Source Measurements

This paper describes sensor calibration and signal analysis techniques applicable to the method of acoustic emission (AE) and ultrasonic testing. They are particularly useful for obtaining absolute measurements of AE wave amplitude and shape, which can be used to constrain the physics and mechanics of the AE source. We illustrate how to perform calibration tests on a thick plate and how to implement two different mechanical calibration sources: ball impact and glass capillary fracture. In this way, the instrument response function can be estimated from theory, without the need for a reference transducer. We demonstrate the methodology by comparing calibration results for four different piezoelectric acoustic emission sensors: Physical Acoustics (PAC) PAC R15, PAC NANO30, DigitalWave B1025, and the Glaser-type conical sensor. From the results of these tests, sensor aperture effects are quantified and the accuracy of calibration source models is verified. Finally, this paper describes how the effects of the sensor can be modeled using an autoregressive-moving average (ARMA) model, and how this technique can be used to effectively remove sensor-induced distortion so that a displacement time history can be retrieved from recorded signals.     

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.     

Acoustic emission and disturbances in central solenoid model coil for International Thermonuclear Experimental Reactor

This paper presents acoustic emission (AE) signals induced from the Central Solenoid (CS) model coil of the International Thermonuclear Experimental Reactor (ITER) program. Envelopes of the AE signals were quasi-continuously measured with high-time resolution of 100 μs using six multi-channel AE sensors in order to detect the disturbances in the CS model coil during the process of the series of direct current (DC) operations. The AE signals were considered to be originally induced by motion of superconducting cables in cable-in-conduit (CIC) conductors and local motion of the conductors, judging from the close correlation between the AE signals and voltage spikes in the coil, especially during the virgin current operation. The multi-channel measurements provide us with information about the distribution of disturbances that could be detected acoustically by the AE sensors installed at each point of the CS model coil. The observation of AE envelopes with high-time resolution showed that the disturbances at each location of the CS model coil decreased by repeatedly charging-up the coil, judging from instantaneous AE levels, AE energy and the number of AE events. Direct measurements of the number of AE events that were carried out at another point on the coil confirmed that the disturbance dependence on the number of operations was similar to that mentioned above. The transfer function methods using one pair of AE sensors enabled us to analyze changes that might occur in either the coil structure or in the disturbance in frequency region during the repeating of the charging-up processes of the coil.     

Transient slip behaviour of metal/insulator pairs at 4.2 K

Experiments have been conducted to observe the sliding behaviour, at 4.2 K, of freshly prepared metal/insulator combinations during a set of sequential slip tests. Measurements of the tangential force versus displacement, as well as displacement and acoustic emission rate versus time, were recorded. A triboelectric effect was also monitored.Depending on the particular metal/insulator pair tested, completely stable (slow velocity), completely unstable (rapid velocity), or a transition from unstable to stable sliting behaviour was observed. This transition behaviour was noticed for several metal/insulator combinations commonly used in superconducting magnet windings. An asperity plowing model is proposed to account for this behaviour, and is based upon the abrasive action of rubbing materials poorly matched in hardness against each other.The training phenomenon in unimpregnated superconducting magnet windings may be attributable to this wearing-in of frictional surfaces. A simple epoxy coating technique was successful in eliminating initial rapid slip events, thereby completely stabilizing the sliding behaviour of a conductor/insulator combination.     

Acoustic emission monitoring results from a fermi dipole

Acoustic emission (AE) techniques have been used to monitor a Fermi dipole magnet during quench current experiments. The dipole data show that conductor motion is the principal source of AE and the primary cause of quenches, as is the case for most high-performance superconducting magnets. The middle of the dipole was found to be more susceptible to quenches with motion than either end. This result is consistent with the field distribution along the magnet. There is good correlation between quench current and AE history. The experimental data can be satisfactorily explained by a model relating AE energy and frictional motion. Acoustic emission was used in conjunction with voltage data to quantify the average frictional dissipation in the windings, estimated to be ≈ 10 μW cm⁻³.     

Damage monitoring of reinforced concrete frames under seismic loading using cement-based piezoelectric sensor

Damage process monitoring of concrete structures using acoustic emission (AE) technology has been drawn more and more attention due to its powerful capability. In this paper, a brand new cement-based piezoelectric composite sensor was introduced with improved performance, particularly concerning its AE signals detection capacity in the high frequency domain. Such sensors were embedded into the foundation of reinforced concrete (RC) frames during construction, and appointed to monitor concrete damage due to shake table excitation. A standard ground motion record of 1999 Taiwan earthquake with 840 gal and 1300 gal peak ground accelerations were employed in the tests as the excitation inputs. The signals detected by the sensors were stored and analyzed by commercial available data acquisition devices. Advanced stochastic signal analysis methods were adopted to effectively interpret the frequency domain components and identify the useful information representing the damage processes of the RC frames. The results were compared with the eye observations of structural damage and corresponding cyclic loading tests results. It is shown that the health monitoring method using cement-based piezoelectric composite sensors and advanced stochastic signal analysis are capable of detecting and evaluating the damage process of RC frames due to seismic loading. An effective damage indicator of the RC frames is possible to be evaluated from extracted AE information.     

APMOC/环氧复合材料层板破坏过程声发射特征

本文利用声发射测试技术,对APMOC/环氧复合材料各种铺层的单层板、层合板的损伤机理和破坏过程进行了详细的研究。结果表明,在不同的声发射信号参量特征与不同的损伤机理之间存在对应关系。声发射信号参量的变化过程能够描述层板的动态损伤过程,不同的声发射参量表征层板的不同损伤过程与机理。     

Evaluation of the use of envelope analysis and DWT on AE signals generated from degrading shafts

Vibration analysis is widely used in machinery diagnosis. Wavelet transforms and envelope analysis, which have been implemented in many applications in the condition monitoring of machinery, are applied in the development of a condition monitoring system for early detection of faults generated in several key components of machinery. Early fault detection is a very important factor in condition monitoring and a basic component for the application of condition-based maintenance (CBM) and predictive maintenance (PM). In addition, acoustic emission (AE) sensors have specific characteristics that are highly sensitive to high-frequency and low-energy signals. Therefore, the AE technique has been applied recently in studies on the early detection of failure. In this paper, AE signals caused by crack growth on a rotating shaft were captured through an AE sensor. The AE signatures were pre-processed using the proposed signal processing method, after which power spectrums were generated from the FFT results. In the power spectrum, some peaks from fault frequencies were presented. According to the results, crack growth in rotating machinery can be considered and detected using an AE sensor and the signal processing method.     

Optimization of Positioning of an Acoustic Emission Sensor for Monitoring Hot Forging

Optimization of a sensor location for effective characterization of a hot forging process using acoustic emission (AE) signals is discussed in this paper. Acoustic emission signals generated during forging operations on an aluminium alloy were recorded using three sensors simultaneously by mounting them on the top bolster, bottom bolster, and bottom die of the press. The AE signals with maximum sensitivity could be detected with a sensor attached to the bottom die in preference to the other positions. Using AE parameters, the forging process could be differentiated into three regions, i.e., 1) yielding of the workpiece material, 2) intermediate deformation region, and 3) filling of the die. The results show that the optimum position of the AE sensor for monitoring hot forging is found to be the bottom die of the forging press.     

Evaluation of the repair on multiple leaf stone masonry by acoustic emission

Aim of this research was to evaluate the possible application of the AE technique to study the response of multiple leaf masonry repaired with different techniques. The results of shear tests carried out on three specimens repaired after failure are presented on an explorative basis; on two of them the acoustic emission (AE) technique was also used. Through a number of sensors and by triangulation, this technique makes it possible to identify the location of the damage, unknown initially, and subsequently to assess the stability of its evolution. Using the AE technique the area of the material where the cracks propagated during shear tests was identified. These analyses made it possible to evaluate the effectiveness of repair interventions through parameters other than stress and strain, and contributed to the identification of the most suitable methodology for their optimisation.     

Damage monitoring of carbon fiber-reinforced plastics with Michelson interferometric fiber-optic sensors

This paper presents the application of a Michelson interferometric fiber-optic sensor for monitoring the damage of fiber-reinforced plastics. A Michelson interferometric fiber-optic sensor was mounted on the surface of unidirectionally aligned carbon fiber-reinforced epoxy composites. Response of the interference signal to either dynamic or static loading was investigated. Specimen being impacted, the optical interference signal dropped suddenly and then oscillated. The tensile test was performed with the measurement of optical interference signal, strain as well as acoustic emission. Both fast Fourier transform and digital filter processing of the optical interference signal were carried out to characterize the damage signal from the fiber-optic sensor. The optical interference signal whose frequency ranged from tens to hundreds Hz occurred when the specimen was damaged. It was shown that real-time information comparable to acoustic emission (AE) data could be obtained from Michelson interferometric fiber-optic sensor through a digital filtering technique. The Michelson interferometric fiber-optic sensor proved to be effective for monitoring the damage processes of the material studied.     

Acoustic emission for in situ monitoring in metal-matrix composite processing

The attractive elevated-temperature properties of metal-matrix composities (MMCs) have not been exploited in commercial applications partly because of the high processing cost and lack of reliability in fabrication. In this exploratory study, the feasibility of using acoustic emission (AE) as an in-process, non-destructive quality control technique is examined. A variation of the squeeze casting technique is selected for investigation. Acoustic emission is employed with the intent of non-intrusively establishing whether complete infiltration has occurred during composite fabrication. The problems due to the background noise during AE monitoring are overcome by using transducers with different frequency responses. The acoustic signatures of machine noise, preform crushing and metal solidification are obtained by employing suitable transducers in a series of tests that systematically evaluate the individual processes that comprise infiltration casting. The results form a strong basis for the development of an in situ AE sensor for the infiltration process.     

Monitoring pitting corrosion of AISI 316L austenitic stainless steel by acoustic emission technique: Choice of representative acoustic parameters

This experimental work was aimed at investigating the monitoring of pitting corrosion by the acoustic emission (AE) technique, for pits developed by potentiostatic or galvanostatic polarization on two types of 316L austenitic stainless steels, in a 3% NaCl solution acidified to pH 2. The study of the evolution of AE global activity during the test showed the existence of a time delay before pits became emissive. This time delay and the AE events number rate measured during the propagation step of the pits are closely correlated with the sensitivity of the material towards pitting and with the polarization procedure. Moreover, the evolution of cumulative % of AE signals number versus selected acoustic parameters shows that rise time and counts number of signals appear to be discriminating acoustic parameters for monitoring pitting corrosion of austenitic stainless steels by acoustic emission technique in our experimental conditions, whatever the polarization procedure and the type of tested steel.     

Study of Acoustic Surface Waveguides on Reinforced Concrete Slabs

This paper describes the development of a two-dimensional acoustic surface waveguide system to enhance the transmission of Acoustic Emission (AE) signals in high attenuation concrete materials. The design of the surface waveguide system and the AE source location results are described. In this study, steel wires were selected as a waveguide material and were attached on the surface area of reinforced concrete structures. AE sensors were mounted at the end of the waveguides. The waveguides were connected to a concrete slab at joints with small contact areas using epoxy. This minimizes the amount of AE energy that could dissipate back to concrete. Thus, AE signals can be transmitted a longer distance. Experiments using standard pencil-lead breaks were conducted at 49 locations on a surface of a reinforced concrete floor slab to provide artificial AE signals. High transmission efficiencies were experimentally determined for the epoxy joints developed to attach the waveguides on the concrete surface. Results confirm that the use of the two-dimensional surface waveguides can significantly increase the AE monitoring range. A multi-layer Neural Network (NN) system was employed to predict locations of the AE sources. Four data sets of AE parameters and their corresponding 49 source locations in each data set were used to train the NN system. A testing data set was then used to demonstrate the ability of the NN in identifying the locations of the AE sources. Satisfactory prediction results from the NN were obtained.     

Discrete failure mode detection in a woven SiC cloth reinforced glass composite

Single layer silicon carbide cloth reinforced glass composites were fabricated and subjected to three-point bending in order to develop better models of failure mechanisms. Acoustic emission (AE) monitoring was also performed during the bend tests to help isolate these mechanisms. During the basic flexural tests, discrete failure modes, which were often not visible from specimen surfaces, displayed their existence through characteristic load-deflection curve unloading regions and abrupt changes in acoustic activity. Microscopic three-point bend tests were then performed to elaborate on the results of the conventional bend tests. Observations made during the microscopic bend tests provided a one-to-one correlation with load-deflection curve anomalies and acoustic emission activity. As a result of the different mechanical, optical and acoustical techniques used, discrete failure mechanisms for the cloth reinforced ceramic matrix composite (CMC) were conclusively established.     

Some Applications of Acoustic Emission in Particle Science and Technology

Acoustic emission (AE) has been used in many applications in the field of particle science and technology. AE sensors have been used in particle concentration measurements both in gas-continuous and oil-continuous flows in the oil and gas industry. To avoid formation sand flowing into pipelines, leading to erosion of valves and in many cases even to complete blockage of the flow of oil and gas, AE sensors are almost exclusively used in sand monitoring and control. These are very often among standard sensors stipulated by the operators of oil and gas production facilities in offshore, on shore, and subsea applications. Special types of sensor design have led to easy mounting of these AE sensors, which are very often clamp-on devices. This article presents a brief overview of AE-based particle monitoring in general and focuses on flange-mounted sensors in the monitoring of particle flow. By using two or more AE sensors located suitably in the process line, the particle velocity can also be evaluated, as is shown in examples using correlation in this article. The AE sensors can easily be adapted to detect malfunctioning of the process line, whether pneumatic lines or silos, just by analyzing the time series of signals from strategically based AE sensors along the process lines. Some examples are given based on recent measurement data. Finally, the article presents an overview of possibilities for improved particle flow monitoring using a multisensor suite incorporating AE sensors with other sensors/detectors such as those derived from capacitance, resistance, gamma ray, microwave, and optical devices. Artificial intelligence (AI) techniques, such as fuzzy logic and neural network algorithms, used in handling the data from these sensors lead to faster and more reliable control. Some of these topics are addressed also.