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Weighting Curves

Let's say that you're hired to go measure the level of background noise in an office building. So, you wait until everyone has gone home, you set up your band-new and very expensive sound pressure level meter and you'll find out that the noise level is really high - something like 90 dBspl or more.

This is a very strange number, because it doesn't sound like the background noise is 90 dBspl... so why is the meter giving you such a high number? The answer lies in the quality of your meter's microphone. Basically, the meter can hear better than you can - particularly at very low frequencies. You see, the air conditioning system in an office building makes a lot of noise at very low frequencies, but as we saw earlier, you aren't very good at hearing very low frequencies.

The result is that the sound pressure level meter is giving you a very accurate reading, but it's pretty useless at representing what you hear. So, how do we fix this? Easy! We just make the meter's ``hearing'' as bad as yours.

So, what we have to do is to introduce a filter in between the microphone output and the measuring part of the meter. This filter should simulate your hearing abilities.

There's a problem, however. As we saw in Section 5.4, the ``EQ curve'' of your hearing changes with level. Remember, the louder the sound, the flatter your personal frequency response. This means that we're going to need a different filter in our sound pressure level meter according to the sound pressure of the signal that we're measuring.

The filter that we use to simulate human hearing is called a weighting filter (sometimes called a weighting network) because it applies different weights (or levels of importance) to different frequencies. The frequency response characteristics of the filter is usually called a weighting curve.

There are three standard weighting curves, although we typically only use two of them in most situations. These three curves are shown in Figure 5.9 and are called the A-weighting, B-weighting, and C-weighting curves.

Figure 5.9: Frequency response curves for the A, B and C weighting filters. [Ballou, 1987]

These curves show the frequency response characteristics of the three weighting filters. The question then is, how do you know which filter to use for a given measurement? As you can see in Figure 5.9, the A-weighting curve has the most attenuation in the low and high frequency bands. Therefore, of the three, it most closely matches your hearing at low levels. The B- and C-weighting curves have less attenuation in high frequencies than the A-weighting curve. The B-weighting curve has more attenuation in the low frequencies than the C-curve. Therefore, if your measuring a sound with a higher sound pressure level, you use the B-weighting curve. Even higher sound pressure levels require the C-weighting curve. Table 5.2 shows a list of suggestions for which weighting curve to use based on the sound pressure level.

Table 5.2: Suggested weighting network according to the measured sound pressure level [Ballou, 1987].

Sound Level	Weighting
Range (dBspl)	Network
20 - 55	A
55 - 85	B
85 - 140	C

Notice that the A-weighting curve has a great deal of attenuation in the low and high frequencies. Therefore, if you have a piece of equipment that is noisy, and you want to make its specifications look better than they really are, you can use an A-weighting curve to reduce the noise level. Manufacturers who want to make their gear have better specifications will use an A-weighting curve to improve the looks of their noise specifications.

You may also see instances where people use an A-weighting curve to measure acoustical noise floors even when the sound pressure level of the noise is much higher than 55 dBspl. This really doesn't make much sense, since the frequency response of your hearing is better than an A-weighting filter at higher levels. Again, this is used to make you believe that things aren't as loud as they appear to be.