Papers by Keyword: Source Location

Abstract: This work presents the analysis of damage assessment for dangerous industrial objects of acoustic emission method. Samples of low carbon and low alloy steels were researched. The aim of this work is to experimentally determine damage assessment for the state of developed and unacceptable sources of acoustic emission. Cracks of various lengths have been obtained by low-cycle loading. According to research, it is necessary to use several criteria simultaneously to increase the reliability of inspection of each growing crack.

Abstract: The deviation of microseismic station location will affect the microseismic source location accuracy in microseismic monitoring. The relationship between microseismic station location deviation and source location accuracy is studied in the paper. A global optimization algorithm, particle swarm optimization (PSO), is used to search for the source location. Results show that PSO method is good. The source location error increases with the microseismic station location error. The relationship between them is nonlinear. The microseismic sources outside the microseismic station array are more sensitive to the microseismic station location deviation than inside the microseismic station array. The bigger the microseismic station location error, the greater the difference. Therefore, when the microseismic source is outside the microseismic station array, it is more necessary to ensure the accuracy of microseismic station location.

Abstract: This paper presents a method for multi-point vibration location near-surface. Unlike traditional source location technologies, it is not using travel times of seismic waves for positioning calculation, but according to the entire seismic data record, using the wave equation migration method to calculate the source location. Similar to exploration seismic, the records from a survey line within a certain period of time are data volumes with dimensions of time and ground coordinates. Based on the data, combined with surface seismic wave propagation characteristics, by using the improved seismic depth migration algorithm, the vibration energy will return to the starting position where exactly the source location is. The method can solve the problem of location calculation error by using traditional method when several vibration at the same time or continuous vibration occurs at some point.

Abstract: In recent years, acoustic emission (AE) testing technology is the one of the most important non-destructive testing (NDT) methods. The characteristics can be described by AE signals, including the location, nature and severity. In order to obtain the basic data for monitoring the wind turbine blade composite structure, the experiment adopted Φ0.5 mm lead pencil as artificial acoustic emission source and measured AE parameters, attenuation and source location of resin matrix for wind turbine blade. This paper introduced linear location and two-dimensional positioning technology of time arrival location method about the burst AE signal. The result shows that the location of AE source basically reflects the location of stimulation AE source, the location of AE source for resin matrix can agree well with the simulated location of AE source, the more close to the middle area, the more accurate location.

Abstract: In acoustic emission (AE) testing for steel structures, location of AE source is an important problem because the source is often related to micro-structure change or defects. In the paper, an activity detector was proposed to locate AE sources based on clustering analysis and AE statistical parameters. Firstly, a location plane, which may contain AE sources, was obtained by the technique of time difference of arrival (TDOA). And the plane was divided into some sub-planes base on clustering analysis. Then, the activity detector was established based on two AE statistical parameters of energy counts and ring-down counts. Finally, the detector value in each sub-plane was calculated and the sub-plane with the maximum value was identified the position of AE sources. Further, by applying the method to test crack sources in a steel structure experiment, the crack position was located correctly compared with actual crack sources. The results demonstrated that the method based on the AE activity detector can reduce ambiguity and locate AE sources accurately and effectively.

Abstract: The corrosion acoustic emission (AE) source location is one of the main purposes of acoustic emission testing (AET), corrosion detection and location can guarantee the safety and integrity of pipeline, storage tank and other equipment in the petrochemical industry. The computed source location and zonal location methods are reviewed in this paper, and also new source location method based on modal acoustic emission (MAE) is introduced and this new method will be more widely used in the field of corrosion detection in future.

Abstract: Different experimental procedures for the location of sources of Acoustic Emission (AE) avalanches during Martensitic Transformations are discussed. A first example corresponds to the 1D location of AE events during stress-induced martensitic transitions in a Cu-Zn-Al shape memory alloy (3.5 cm length). The obtained data allows monitoring of the interface advancement with a spatial resolution of less than 1 mm. Secondly, we discuss two different ideas that have significant potential for improving this resolution in the case of thermally induced transitions in small single crystalline samples (~1 cm): the use of elastodynamic simulations based on finite element methods and the simultaneous detection of AE and Barkhausen noise in ferromagnetic samples.

Abstract:
A novel optical fiber acoustic emission (AE) system with multi-sensing function in single long fiber was developed and utilized for the estimation of AE sources of model steel plate and jointed pipes. Multi-sensing function was achieved by dividing the single sensing fiber into several sensor portions with different resonance frequencies. The resonance frequencies were provided by winding the sensing fiber around the solid rods (sensor holders) with different diameters. The monitoring system with three sensors in a 10 m long fiber was demonstrated to detect three wave packets with different frequencies and correctly estimate the source locations of AEs from artificial (Nelson-Sue) sources on a 0.9 wide x 1.8 m long steel plate. Here the arrival times of AEs for the source location were determined by the continuous wavelet transform. Source locations on the steel plate were determined within a distance error of 53 mm. The system also makes the location of the pipe with damage possible.

Abstract: Conventional methods of acquiring and using acoustic emission (AE) discard the raw signal waveform after extracting signal features from it. The main reason for this is the number of bytes required to save hundreds of thousands of AE waveforms, using a modern high speed multichannel system the hard-drive may be quickly filled. One side effect of this “feature extraction” approach is that information is thrown away with the wave-form. The advent of systems capable of acquiring AE waveforms on all channels has opened up the opportunity to use this extra data to get more information about the source and the transmission path. This paper describes the use of acoustic emission waveforms to aid source discrimination, and presents data acquired during pressure testing of a slug-catcher.

Abstract: Good knowledge of acoustic emission (AE) source location is the basic requirement for further damage mechanism characterization. Calculation of the AE source location is mostly based on arrival time differences of the signals recorded by different transducers. Error free arrival time determination is the crucial factor for the localization results accuracy together with the exact elastic wave velocity measurement. In the paper difficulties and limitations of the elastic wave velocity computation are shown. To solve the velocity and the time differences problems, new approach to AE source localization is described. The new method estimates the AE source coordinates using artificial neural network (ANN) processing extracted signal parameters. The ANN do not uses neither arrival time differences nor elastic wave velocities as input data. The new approach advantages are discussed in cases of both numerical and practical experiments. The experiments results are promising for the use of designed localization method in praxis.