Page 240 - Advances In Productive, Safe, and Responsible Coal Mining

Engineered noise controls for miner safety and environmental responsibility 219

the assumed source location, the shifted microphone signals will be in-phase and the
summation of the signals divided by the number of microphones will represent the
acoustic signal at the center of the microphone array. However, if no actual noise
source exists at the assumed source location, the summation of the time-shifted signals
will diminish.
Most beamforming algorithms take advantage of the computational efficiency of
the fast Fourier transform (FFT) and thus process the data in the frequency domain [9].
However, for moving noise sources, time domain beamforming algorithms have been
traditionally used. Nevertheless, a new technique has been developed to conduct
beamforming on moving sources of sound that process the data in the frequency
domain and is therefore significantly less computationally intensive than traditional
time domain beamforming [10,11]. This technology has been demonstrated to be a
very effective tool to identify noise sources in mid- and high-frequency ranges (above
1000Hz). It can be used at frequencies below 1000Hz; however, the resolution of the
acoustic maps decreases significantly requiring additional postprocessing algorithms.
Some of these algorithms involve deconvolution methods [12] while others take
advantage of the spatial coherence characteristic of noise sources [13].

12.3.3 Source path contribution analysis

There are many cases where due to the complex machine geometry, large dimensions
of a machine, and the presence of different noise sources, it is not clear through what
paths noise is being transmitted from source to receiver. In general, sound can be
transmitted via structure-borne and/or airborne paths. In this context, a test-based
approach known as source path contribution (SPC) analysis has been shown to be very
helpful.
Several SPC methods are available and they all fall into one of two categories:
(1) the synthesis approach; or (2) the decomposition approach. In the synthesis
approach, noise arriving at the receiver is calculated as a sum of the contributions from
each source; i.e., source strength multiplied by the transfer function between that par-
ticular source and the receiver. These transfer functions are measured experimentally
using a volume velocity source at the receiver and microphones at the assumed source
locations. Since source strengths cannot be measured directly, they are estimated from
measurements at so-called indicator locations; i.e., locations in close proximity
(within 2–5cm) to the assumed source locations. Using the volume velocity source,
transfer functions between indicator locations and assumed source locations are mea-
sured. Next, this matrix of transfer functions is inverted and multiplied by the vector of
acoustic responses measured at indicator locations when the machine is in operation.
This product yields a vector of estimated source strengths.
In contrast, the decomposition approach separates the sound arriving at the receiver
into a number of components according to some criteria based on a reference signal
[14]. Once sources are identified and critical transmission paths determined, then
noise controls can be developed to reduce noise levels at the receiver; i.e., the operator
location.