Acoustic emission study on corona discharge using FDTD model

This paper attempts to study the propagating characteristics of acoustic signals emitted from the breakdown of air using time domain numerical model. Acoustic emissions are produced by high voltage faults such as partial discharge and surface discharge. Study of such emissions has become popular among researchers because of the promising correlation between partial and surface discharges and its byproduct, acoustic signal emission. In this paper, propagation characteristics of acoustic signals are studied using finite difference time domain (FDTD) method. Multiple monitoring points are placed within a designated computation space at different distance away from a source.

Study of acoustic emission (AE) caused by high voltage insulators

Acoustic emission (AE) study based on the acoustic signal ranges from 30MHz to 300MHz has been performed to diagnose the deterioration of insulation level in outdoor ceramic insulator. Different weather conditions combining with artificially created pollution were produced in laboratory and measurements were recorded over a fixed period of time. Pollution due to fine dust particles has been created according to IEC standard under wet and dry conditions. Samples that exhibit internal cracks and fracture were used in this study. The collected AE signals were sampled and analysed using fractal theory. The results of this study have clearly demonstrated the prospect of using AE technique to monitor the working condition of outdoor insulator.

Combined in situ neutron diffraction and acoustic emission of twin nucleation & twin growth in extruded ZM20 Mg alloy

In the present work in situ neutron diffraction and acoustic emission were used concurrently to study deformation twinning in two ZM20 Mg alloys with significantly different grain sizes at room temperature. The combination of these techniques allows differentionation between the twin nucleation and the twin growth mechanisms. It is shown, that yielding and immediate post-yielding plasticity in compression is governed primarily by twin nucleation, whereas the plasticity at higher strains is governed by twin growth. The current results further suggest that yielding by twinning happens in a slightly different manner in the fine-grained as compared to the coarse-grained alloy.

Investigation of hydraulic fracture propagation using a post-peak control system coupled with acoustic emission

This study investigates the fracture mechanism of fluid coupled with a solid resulting from hydraulic fracture. A new loading machine was designed to improve upon conventional laboratory hydraulic fracture testing and to provide a means of better understanding fracture behavior of solid media. Test specimens were made of cement mortar. An extensometer and acoustic emission (AE) monitoring system recorded the circumferential deformation and crack growth location/number during the test. To control the crack growth at the post-peak stage the input fluid rate can be adjusted automatically according to feedback from the extensometer. The complete stress-deformation curve, including pre- and post-peak stages, was therefore obtained. The crack extension/growth developed intensively after the applied stress reached the breakdown pressure. The number of cracks recorded by the AE monitoring system was in good agreement with the amount of deformation (expansion) recorded by the extensometer. The results obtained in this paper provide a better understanding of the hydraulic fracture mechanism which is useful for underground injection projects. © 2014 Springer-Verlag Wien.

Acoustic condition monitoring for cold metal forming

One of the most important objectives of cold metal forming research is to develop techniques that enable better manufacturing efficiencies. Within this monitoring of tooling condition is vital to providing high quality manufacturing. The objective of this research is to determine the signature derived from Acoustic Emission (AE) sensors, in order to establish the current condition of a machine tool, as applied to bolt-making. From here we aim to develop and implement an on-line condition monitoring tool for the cold forming process. A review of the literature has shown that much research into AE has been successfully applied in metal cutting operations; such as milling, drilling and turning, but little research has been done related to metal forming. This appears to be due to the complexity of obtaining consistent signals using Acoustic Emission systems, because the presence of noise in many forms. This paper will detail many of the AE signals acquired and analysed through our research. The extensive results indicate this form of condition monitoring is not suitable for metal forming in its current configuration. Further tests are proposed to enable such research to move forward, so a condition monitoring system can be established.

On-line tool condition monitoring and control system in forging processes

Cold bulk metal forming has made large-scale production of small complex solid parts economically feasible. Tooling used in metal forming poses many uncertainties in the preliminary cost estimation and production process and continual tool replacement and maintenance dramatically reduces productivity and raises manufacturing cost. In order to tackle this, an on-line tool condition monitoring system using artificial neural network (ANN) to integrate information from multiple sensors for forging process has been developed. Together with the force, acoustic emission signals and process conditions, information developed from theoretical models is integrated into the ANN tool monitoring system to predict tool life and provide the maintenance schedule.

Integrated health monitoring for reinforced concrete beams: an experimental study

Civil infrastructures begin to deteriorate once they are built and used. Detecting the damages in a structure to maintain its safety is a topic that has received considerable attention in the literature in recent years. In vibration-based methods, the first few modes are used to assess the locations and the amount of damage. However, a small number of the global modes are not sufficient to reliably detect minor damage in the structure. Also, a common limitation of these techniques is that they require a high-fidelity model of the structure to start with, which is usually not available. Recently, guided waves (GW) have been found as an effective and efficient way to detect incipient damages due to its capacity of relatively long propagation range as well as its flexibility in selecting sensitive mode-frequency combinations. In this paper, an integrated structural health monitoring test scheme is developed to detect damages in reinforced concrete (RC) beams. Each beam is loaded at the middle span progressively to damage. During each loading step, acoustic emission (AE) method is used as a passive monitoring method to catch the AE signals caused by the crack opening and propagation. After each loading step, vibration tests and guided wave tests are conducted as a combined active monitoring measure. The modal parameters and wave propagation results are used to derive the damage information. Experimental results show that the integrated method is efficient to detect incipient damages in RC structures.

High-sensitivity acoustic sensors from nanofibre webs

Considerable interest has been devoted to converting mechanical energy into electricity using polymer nanofibres. In particular, piezoelectric nanofibres produced by electrospinning have shown remarkable mechanical energy-to-electricity conversion ability. However, there is little data for the acoustic-to-electric conversion of electrospun nanofibres. Here we show that electrospun piezoelectric nanofibre webs have a strong acoustic-to-electric conversion ability. Using poly(vinylidene fluoride) as a model polymer and a sensor device that transfers sound directly to the nanofibre layer, we show that the sensor devices can detect low-frequency sound with a sensitivity as high as 266 mV Pa(-1). They can precisely distinguish sound waves in low to middle frequency region. These features make them especially suitable for noise detection. Our nanofibre device has more than five times higher sensitivity than a commercial piezoelectric poly(vinylidene fluoride) film device. Electrospun piezoelectric nanofibres may be useful for developing high-performance acoustic sensors.

Location based power control for energy critical sensors in a disconnected network

This paper provides a location based power control strategy for disconnected sensory nodes deployed for long term service. Power conservation is of importance particularly when sensors communicate with a mobile robot used for data collection. The proposed algorithm uses estimations from a Robust Extended Kalman Filter (REKF) with RSSI measurements, in implementing a sigmoid function based power control algorithm which essentially approaches a desired power emission trajectory based on carrier-to-interference ratios(CIR) to ensure interferenceless reception. The more realistic modelling we use incorporates physical dynamics between the mobile robot and the sensors together with the wireless propagation parameters between the transmitter and receiver to formulate a sophisticated and effective power control strategy for the exclusive usage of energy critical disconnected nodes in a sensory network increasing their life span.