This is why I no longer recommend turning one sub off to fight power alley
Takeaway
Leave both subs on. Turning one sub off in an uncoupled array will create a greater F2B contrast.
You can use standard deviation to help you decide between two design decisions.
Intro
For better or for worse, many of the sound systems that we encounter today still use uncoupled subwoofer arrays placed to the left and right sides of the stage and there’s nothing we can do about it. This creates peaks and valleys of summation and cancellation through the room (power alley). For many years I have used and recommended a trick in these scenarios – turn one sub off.
Audio myth?
In this article I will attempt to prove its viability.
How did we end up here?
If you are now asking why I would ever use an upcoupled sub array, then this article is not for you. This article is for the people who get stuck in this challenging situation because they walk into a room where the subs are either nailed to the floor or are physically supporting the mains and therefore, cannot be moved without moving the mains.
If you regularly work in small spaces, trying to fight this is a losing battle. The client and artist want to see symmetry and you want to keep your job. So how do you give everyone what they want?
Turn one sub off? Let’s find out.
Goal
Why would we ever want to turn one subwoofer off? Won’t that always give us less power?
Yes and no. Less subwoofers will give you less potential for power through summation, but it will also give you less potential for power loss through cancellation. We’re talking about the famous power alley.
But our goal is not potential power. Our goal is minimum variance. Power can be scaled with our amplifiers or system processors. So as long as our SPL requirements and frequency response targets can be met with either two or one subwoofer playing, we are free to pursue a solution with less level variation over frequency.
Research method
How will we figure this out?
Eventually, I would like to experiment this in many different rooms, but for efficiency, I will use a MAPP XT to run predictions.
My first thought was that I could simply compare different prediction plots and see which one had less color variation. When I enabled the wall reflections, this method quickly proved inadequate. I couldn’t tell which had less variation. So I asked my dad for help.
Craig is an expert in machine vision and pattern recognition and is working on a project for EyeLock around iris-based identity authentication. With the exported images from MAPP XT, he showed me how to generate a single number representing standard color deviation from each image.
What is standard deviation?
Standard deviation is a measure that is used to quantify the amount of variation or dispersion of a set of data values.[1] A low standard deviation indicates that the data points tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the data points are spread out over a wider range of values. –wikipedia
Low standard deviation = Minimum variance.
After running a few tests, I realized that this method was inadequate because it only tested the designs at a single frequency. I could export more prediction images at more frequencies, but that would take forever. Craig suggested that I turn all of those colors into numbers to make them easier to analyze. That’s when I realized that MAPP XT can export the measurement of a microphone position as an Excel file, which I could then analyze for standard deviation.
Brilliant!
Here is my first, completely fictional design. But one I believe represents the dimensions of many small spaces.
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Here is a prediction with both subs on at 63Hz.
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Here is a prediction with one sub off. I want the prediction to include as many real world complexities as possible so I have enabled the walls.
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Which one is better? How will you choose? To me, the answer is unclear. With both subs on there is less blue, but with one sub on there are less hot spots of red.
Wouldn’t it be easier if we could apply a value to each for a more objective approach?
First, I’ll use a 20 microphone approach, export each measurement, and compare the standard deviation between 30Hz and 80Hz. In the image below you can see the standard deviation by frequency with both subs on in orange (AB), one sub off in blue (A), and a single center sub in gray (Mono).
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Here is the same graph with a few more symbols to help explain what’s going on. The Y-axis is standard deviation from low
