High-frequency impulse-measurement
Structure-borne sound signal in the conventional
2-dimensional diagram "amplitude vs. time" (1) and the same signal as
3-dimensional HFIM process landscape (2). The enhanced signal-to-noise ratio
becomes obvious while an impulse-like signal (3) becomes directly evident in
the HFIM picture whereas it is not visible in the 2-dimensional diagram.
HFIM, acronym for high-frequency-impulse-measurement,
is a type of measurement technique in acoustics, where structure-borne
sound signals are detected and processed with certain emphasis on short-lived
signals as they are indicative for crack formation in a solid body,
mostly steel. The basic idea is to use mathematical signal processing
methods such as Fourier analysis in combination with suitable
computer hardware to allow for real-time measurements of acoustic signal
amplitudes as well as their distribution in frequency space. The main benefit
of this technique is the enhanced signal-to-noise ratio when it comes
to the separation of acoustic emission from a certain source and other,
unwanted contamination by any kinds of noise. The technique is therefore mostly
applied in industrial production processes, e.g. cold forming or machining,
where a 100 percent quality control is required or in condition
monitoring for e.g. quantifying tool wear.
Contents
- 1Physical
basics
- 2Applications
- 3References
- 4External
links and further reading
Physical basics
High-frequency-impulse measurement is an algorithm for
obtaining frequency information of any structure- or air-borne sound source on
the basis of discrete signal transformations. This is mostly done using
[Fourier series] to quantify the distribution of the energy content of a sound signal
in frequency space. On the software side, the tool used for this is the fast
Fourier transform (FFT) implementation of this mathematical transformation.
This allows, in combination with specific hardware, to directly obtain
frequency information so that this is accessible in-line, e.g. during a
production process. Contrary to classical, off-line frequency analysis methods,
the signal is not unfolded before transformation but is directly fed into the
FFT computation. Single events, such as cracks, are hence depicted as extremely
short-lived signals covering the entire frequency range (the Fourier transform
of a single impulse is a signal covering the entire observed frequency space).
Therefore, such single events are easily separable from other noises, even if
they are much more energetic.
Applications
Because of its in-line capabilities, HFIM is mostly applied
in industrial production processes when it comes to high quality standards e.g.
for auto parts that are relevant for crash behavior of a car:
- Cold
forming: In cold forming applications, HFIM is mostly used to detect
cracks during the forming process. Since such cracks are vastly due to
stress in the manufactured part, the spontaneous formation of a crack is
accompanied by a very sharp, impulse-like signal in the HFIM process
landscape which can easily be separated from other noise. Therefore, HFIM
is the standard technology for crack detection in the automotive sector
all over the world.
- Machining:
In many machining applications, HFIM is used to either monitor the status
of tool wear and hence enable pedicitive maintenance or to
prevent chatter.
- Plastic injection
molding: Here, HFIM is used to monitor the status of the molds which are
usually very complex. In particular, breaking off of small pins or other
parts of the mold can be detected in-line.
- Welding:
In contrast to most classical monitoring systems for the welding process
which usually measure currents or voltages on the welding device, HFIM
measures the energy acting directly on the welded workpiece. That allows
for detection of various weld imperfactions such as burn-through.
There are also several applications of HFIM devices in
materials science laboratories where the exact timing of crack formation is
relevant, for instance when determining the plasticity of a new kind
of steel.
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