An Apparatus for the Acoustic Emission Technique
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Author(s):
G. Muciaccia - DIPARTIMENTO DI INGEGNERIA STRUTTURALE – POLITECNICO DI MILANO
Industry:
Research
Products:
LabVIEW, Modular Instruments
The Challenge:
Creating an automated system that detects and locates acoustic events generated in a quasibrittle material when testing a generic structural element.
The Solution:
Setting up a net of piezoelectric sensors, amplifying their signal by an external device, acquiring the signals using NI PCI-5112 digitizers ,and detecting the events with NI LabVIEW graphical programming software, which also stores the data.
"With National Instruments software and hardware, we detected the microseismic signals in the material generated by fracture propagation using the acoustic emission technique."
In experimental fracture mechanics of quasibrittle materials it is crucial to determine the area affected by crack propagation. This can be done with the acoustic emission technique that uses sensors to detect microseismic signals generated in the material by the fracture propagation. These signals can be amplified, properly detected, and then stored. This is done using hardware and software from National Instruments.
When evaluating the load-bearing capacity of structural elements, failure indicates the maximum load achievable by an element under given conditions of restraint and load. The failure point is established using microseismic events that propagate waves that cause structural damage.
Quasibrittle materials are characterized by pores and microcracks referred to as damage, which nucleate at the failure point to form a major propagated crack. It is generally accepted that crack propagation involves a restricted zone in the element called the front propagation zone (FPZ). Many theories try to explain the nature of this zone by estimating the extension of the FPZ. From an experimental point of view, it is critical to be able to measure this extension. This can be done by applying the acoustic emission technique.
The creation and coalescence of damage within these materials generates microseismic signals called acoustic emission (AE). Thus the acoustic emission technique attempts to detect the energy released from localized sources within the specimen using a network of AE sensors positioned at different points around the structure.
In the source location technique, a network of sensors detects changes in stress or environment from microseismic activity, especially the P-wave. The P-wave is the component of the microseismic signal that propagates first. By knowing the velocity of the P-wave traveling through the material and the coordinates of each sensor, the microseismic event hypocenter can be estimated with a minimum of four sensors, because the problem contains four unknowns: the spatial coordinates x, y, and z of the event and the time at which the event occurred. Additional sensors can be used to eliminate ambiguities arising from the quadratic nature of the distance equation overcome errors associated with arrival-time detection and with the P-wave velocity. To identify the features of the localized zone through the location of AE, we record a large number of events without interruption. This requires a system with the proper software and sufficient memory to store the experimental data.
The sensors have a reasonably flat frequency response from 0.1 MHz to 1 MHz and a sensor diameter of about 3 mm. A preamplifier (40 dB gain) is provided for each sensor. A single, 8-channel amplifier simultaneously amplifies the signals coming from the eight preamplifiers, and then the signal is delivered to the NI PCI-5112 digitizers mounted on a standard P4 PC. For each digitizer, two channels are used, and all digitizers are linked together by an RTSI cable, which synchronizes the four devices. The detection of the event and the acquisition of the data are operated simultaneously by a LabVIEW program we developed in collaboration with The University of Minnesota using NI-SCOPE libraries.
One of the sensors is also used as a trigger, and it is generally positioned near the expected point of the first crack formation. The principal parameters are the voltage required to acquire data and the input range of the digitizer. Depending on the signal, other parameters include the sample rate, the duration of each data acquisition period, and the sleep time between data acquisition periods. Using the NI PCI-5112 digitzers in this configuration, we could record up to 100 events per seconds.
A pretrigger examines the signal before the trigger point to identify the first arrival of a wave. By knowing these relative arrival times, the P-wave velocity of the material, and the coordinates of each sensor, the event hypocenter is estimated using a tool developed in The MathWorks MatLab® software environment.
©2008 National Instruments Corporation. All rights reserved. LabVIEW, National Instruments, NI, and ni.com are trademarks of National Instruments. MATLAB® is a registered trademark of The MathWorks, Inc. Other product and company names listed are trademarks or trade names of their respective companies.
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