Cheap DC-DC converters have been a boon on the hobbyist bench for a while now, but they can wreak havoc with sensitive circuits if you’re not careful. The problem: noise generated by the switch-mode supply buried within them. Is there anything you can do about the noise?
As it turns out, yes there is, and [Shahriar] at The Signal Path walks us through a basic circuit to reduce noise from DC-DC converters. The module under the knife is a popular buck-boost converter with a wide input range, 0-32 VDC output at up to 5 amps, and a fancy controller with an LCD display. But putting the stock $32 supply on a scope reveals tons of harmonics across a 1 MHz band and overall ripple of about 66 mV. But a simple voltage follower built from a power op-amp and a Zener diode does a great job of reducing the spikes and halving the ripple. The circuit is just a prototype and is meant more as a proof of principle and launching point for further development, and as such it’s far from perfect. The main downside is the four-volt offset from the input voltage; there’s also a broad smear of noise at the high end of the spectrum that persists even with the circuit in place. Centered around 900 MHz as it is, we suspect a cell signal of some sort is getting in. 900 kHz.
Like any Moore’s Law-inspired race, the megapixel race in digital cameras in the late 1990s and into the 2000s was a harsh battleground for every manufacturer. With the development of the smartphone, it became a war on two fronts, with Samsung eventually cramming twenty megapixels into a handheld. Although no clear winner of consumer-grade cameras was ever announced (and Samsung ended up reducing their flagship phone’s cameras to sixteen megapixels for reasons we’ll discuss) it seems as though this race is over, fizzling out into a void where even marketing and advertising groups don’t readily venture. What happened?
A brief overview of Moore’s Law predicts that transistor density on a given computer chip should double about every two years. A digital camera’s sensor is remarkably similar, using the same silicon to form charge-coupled devices or CMOS sensors (the same CMOS technology used in some RAM and other digital logic technology) to detect photons that hit it. It’s not too far of a leap to realize how Moore’s Law would apply to the number of photo detectors on a digital camera’s image sensor. Like transistor density, however, there’s also a limit to how many photo detectors will fit in a given area before undesirable effects start to appear.
Image sensors have come a long way since video camera tubes. In the ’70s, the charge-coupled device (CCD) replaced the cathode ray tube as the dominant video capturing technology. A CCD works by arranging capacitors into an array and biasing them with a small voltage. When a photon hits one of the capacitors, it is converted into an electrical charge which can then be stored as digital information. While there are still specialty CCD sensors for some niche applications, most image sensors are now of the CMOS variety. CMOS uses photodiodes, rather than capacitors, along with a few other transistors for every pixel. CMOS sensors perform better than CCD sensors because each pixel has an amplifier which results in more accurate capturing of data. They are also faster, scale more readily, use fewer components in general, and use less power than a comparably sized CCD. Despite all of these advantages, however, there are still many limitations to modern sensors when more and more of them get packed onto a single piece of silicon.
While transistor density tends to be limited by quantum effects, image sensor density is limited by what is effectively a “noisy” picture. Noise can be introduced in an image as a result of thermal fluctuations within the material, so if the voltage threshold for a single pixel is so low that it falsely registers a photon when it shouldn’t, the image quality will be greatly reduced. This is more noticeable in CCD sensors (one effect is called “blooming“) but similar defects can happen in CMOS sensors as well. There are a few ways to solve these problems, though.
First, the voltage threshold can be raised so that random thermal fluctuations don’t rise above the threshold to trigger the pixels. In a DSLR, this typically means changing the ISO setting of a camera, where a lower ISO setting means more light is required to trigger a pixel, but that random fluctuations are less likely to happen. From a camera designer’s point-of-view, however, a higher voltage generally implies greater power consumption and some speed considerations, so there are some tradeoffs to make in this area.
Another reason that thermal fluctuations cause noise in image sensors is that the pixels themselves are so close together that they influence their neighbors. The answer here seems obvious: simply increase the area of the sensor, make the pixels of the sensor bigger, or both. This is a good solution if you have unlimited area, but in something like a cell phone this isn’t practical. This gets to the core of the reason that most modern cell phones seem to be practically limited somewhere in the sixteen-to-twenty megapixel range. If the pixels are made too small to increase megapixel count, the noise will start to ruin the images. If the pixels are too big, the picture will have a low resolution.
There are some non-technological ways of increasing megapixel count for an image as well. For example, a panoramic image will have a megapixel count much higher than that of the camera that took the picture simply because each part of the panorama has the full mexapixel count. It’s also possible to reduce noise in a single frame of any picture by using lenses that collect more light (lenses with a lower f-number) which allows the photographer to use a lower ISO setting to reduce the camera’s sensitivity.
Of course, if you have unlimited area you can make image sensors of virtually any size. There are some extremely large, expensive cameras called gigapixel cameras that can take pictures of unimaginable detail. Their size and cost is a limiting factor for consumer devices, though, and as such are generally used for specialty purposes only. The largest image sensor ever built has a surface of almost five square meters and is the size of a car. The camera will be put to use in 2019 in the Large Synoptic Survey Telescope in South America where it will capture images of the night sky with its 8.4 meter primary mirror. If this was part of the megapixel race in consumer goods, it would certainly be the winner.
With all of this being said, it becomes obvious that there are many more considerations in a digital camera than just the megapixel count. With so many facets of a camera such as physical sensor size, lenses, camera settings, post-processing capabilities, filters, etc., the megapixel number was essentially an easy way for marketers to advertise the claimed superiority of their products until the practical limits of image sensors was reached. Beyond a certain limit, more megapixels doesn’t automatically translate into a better picture. As already mentioned, however, the megapixel count can be important, but there are so many ways to make up for a lower megapixel count if you have to. For example, images with high dynamic range are becoming the norm even in cell phones, which also helps eliminate the need for a flash. Whatever you decide, though, if you want to start taking great pictures don’t worry about specs; just go out and take some photographs!
(Title image: VISTA gigapixel mosaic of the central parts of the Milky Way, produced by European Southern Observatory (ESO) and released under Creative Commons Attribution 4.0 International License. This is a scaled version of the original 108,500 x 81,500, 9-gigapixel image.)
The police force in Evanston, Illinois had a problem on their hands. A mystery transmitter was blocking legal use of radio devices, car key fobs, cellphones, and other transmitters in an area of their city, and since it was also blocking 911 calls they decided to investigate it. Their first call for help went to the FCC who weren’t much use, telling them to talk to the manufacturers of the devices affected.
The ARRL are highlighting this otherwise fairly unremarkable case to draw attention to the problem of devices appearing on the market with little or no pretence of electromagnetic compatibility compliance. In particular they are critical of the FCC’s lacklustre enforcement response in cases like this one. It’s a significant problem worldwide as huge numbers of very cheap switch-mode mains power supplies have replaced transformers in mains power applications, and in any center of population its effects can be readily seen with an HF radio in the form of a significantly raised RF noise floor. Though we have reported before on the FCC’s investigation of the noise floor problem we’d be inclined to agree with the ARRL that it is effective enforcement of EMC regulations that is key to the solution.
City of Evanston police vehicle picture, [Inventorchris] (CC BY-NC 2.0) via Flickr.
In part one, I compared the different Analog to Digital Converters (ADC) and the roles and properties of Delta Sigma ADC’s. I covered a lot of the theory behind these devices, so in this installment, I set out to find a design or two that would help me demonstrate the important points like oversampling, noise shaping and the relationship between the signal-to-noise ratio and resolution.
Check out part one to see the block diagrams of what what got us to here. The schematics shown below are of a couple of implementations that I played with depicting a single-order and a dual-order Delta Sigma modulators.
Basically I used a clock enabled, high speed comparator, with two polarities in case I got it the logic backwards in my current state of burn out to grey matter ratio. The video includes the actual schematic used.
Since I wasn’t designing for production I accepted the need for three voltages since my bench supply was capable of providing them and this widget is destined for the drawer with the other widgets made for just a few minutes of video time anyway. Continue reading “Tearing into Delta Sigma ADCs Part 2”→
It’s not surprising that Analog to Digital Converters (ADC’s) now employ several techniques to accomplish higher speeds and resolutions than their simpler counterparts. Enter the Delta-Sigma (Δ∑) ADC which combines a couple of techniques including oversampling, noise shaping and digital filtering. That’s not to say that you need several chips to accomplish this, these days single chip Delta-Sigma ADCs and very small and available for a few dollars. Sometimes they are called Sigma-Delta (∑Δ) just to confuse things, a measure I applaud as there aren’t enough sources of confusion in the engineering world already.
I’m making this a two-parter. I will be talking about some theory and show the builds that demonstrate Delta-Sigma properties and when you might want to use them.
If you stand outside on a clear night, can you see the Milky Way? If you live too close to a conurbation the chances are all you’ll see are a few of the brighter stars, the full picture is only seen by those who live in isolated places. The problem is light pollution, scattered light from street lighting and other sources hiding the stars.
The view of the Milky Way is a good analogy for the state of the radio spectrum. If you turn on a radio receiver and tune to a spot between stations, you’ll find a huge amount more noise in areas of human habitation than you will if you do the same thing in the middle of the countryside. The RF noise emitted by a significant amount of cheaper modern electronics is blanketing the airwaves and is in danger of rendering some frequencies unusable.
If you have ever designed a piece of electronics to comply with regulations for sale you might now point out that the requirements for RF interference imposed by codes from the FCC, CE mark etc. are very stringent, and therefore this should not be a significant problem. The unfortunate truth is though that a huge amount of equipment is finding its way into the hands of consumers which may bear an FCC logo or a CE mark but which has plainly had its bill-of-materials cost cut to the point at which its compliance with those rules is only notional. Next to the computer on which this is being written for example is a digital TV box from a well-known online retailer which has all the appropriate marks, but blankets tens of megahertz of spectrum with RF when it is in operation. It’s not faulty but badly designed, and if you pause to imagine hundreds or thousands of such devices across your city you may begin to see the scale of the problem.
We hope that quantifying the scale of the RF noise problem will result in some action to reduce its ill-effects. It is also to be hoped though that the response will not be an ever-tighter set of regulations but greater enforcement of those that already exist. It has become too easy to make, import, or sell equipment made with scant regard to RF emissions, and simply making the requirements tougher for those designers who make the effort to comply will not change anything.
This is the first time we’ve raised the problem of the ever-rising radio noise floor here at Hackaday. We have covered a possible solution though, if stray RF is really getting to you perhaps you’d like to move to the National Radio Quiet Zone.
No surprise there, but rather than give up, he decided to see what he could do about the noise. So, he took the projector apart. After some excavation, he realized that the main source of noise was the input fan, which was small and partly covered. That’s a recipe for noise, so he cut out the plastic grille over it and mounted a larger, quieter fan on the outside. He also designed and 3D printed an external hood for this larger fan. The result, he says, is much quieter than the original, and still keeps the LED light source fairly cool. It’s a neat hack that shows how a few hours and a bit of ingenuity can sometimes make a cheap device better.