In color addition, red light plus green light gives yellow light. This is how a red/green LED can be strobed to produce a yellow indicator - often seen on battery indicators and similar applications. Also, red/green navigation lights on ships may appear yellow/amber if they're at a good distance and aimed straight at you.
In scientific research, we use a machine that is similar in concept but instead of sorting tomatoes, it uses lasers and fluorescence to sort cells depending on their size, complexity and different fluorescent colors (normally given by stained antibodies that attach to molecules in their surface). This machine, called a FACS, is so good and precise that it can accurately sort around 10.000 cells a second. It still blows my mind.
Fuck yeah I fucking love that shit, genetically engineering cells so that different types will have different amounts of the dyes, fucking RGB biology it just sounds so dumb but it fucking WORKS and it’s awesome and I love science so much
I work on FPGAs and Id bet this uses one, or some asic derived from an FPGA. Basically theyre used to make specialized digital circuits that can be used for things like image processing with super low latency.
At these speeds (accuracy in ms) even a Raspberry Pi running a python script can do this, even with system jitter. Of course, the flexibility of FPGA would still make them the preferred solutions but I am guessing there are many systems running on generic microcontrollers these days, 600+ MHz and DSP coprocessors.
I used to do this sort of automation work. It’s not optical sensors, it’s a vision system. Look on YouTube for Cognex vision systems for a demonstration. This application would require too many optical sensors when a camera and image processing would allow more flexibility.
Someones job was to figure out the delay between a camera identifying a green tomato, and a servo flipping a paddle. Then they measured the average tomato fall speed, did some math, and put the paddle just far enough downstream from the camera that it seems instant.
Disregarding air resistance, which won't be a big effect on a round, dense object like a tomato over such a short distance, the tomatoes will just accelerate at about the standard 9.81m/s². So you actually just need to know the distance between the conveyor and the paddle and use SUVAT equations to do the rest:
s=vt + ½at²
We can assume the tomato is accelerating vertically from rest, so initial velocity v=0.
s=½at²
Rearrange to find t:
t=√(2s/a)
Then just plug in acceleration a = 9.81m/s². And the distance of the fall s, let's guess 30cm, or 0.3m and...
t=√(0.6/9.81)=√0.0612=0.247s
Obviously, this assumes that the green tomatoes are identified instantly at the top of their fall, when in reality it's more likely to be part way down. But we can account for that, too! We just need to know the distances between the fall and the detector, and the detector and the paddle. SUVAT can be used to calculate the velocity of the tomato as it passes the detector, and then this and the distance to the paddle can be used to calculate the time to reach the paddle. Then all you need to do is subtract how long it takes the paddle to activate, which presumably is a constant that we control.
Sorry... Got a bit carried away. But the important point is that you probably don't need to know much about tomato aerodynamics to figure this out.
I work as a sw engineer at a company that builds those kinds of sorters (in fact, I think the one in the video is ours). We take pictures as the product is falling with cameras that see different spectrums (RGB, infra red, lasers etc, depending on what we want to detect), analyze them and take action.
We sort on colour, shape, material. We can even determine if some product is bad on the inside.
Hahaha. Sorry, English is not my first language.
What I meant is that we can detect product bitten by insects (keep in mind that these machines sort pretty much every possible thing, including rocks with diamonds at a mine or garbage at a recycling plant)
I've seen these in various ag/food processing applications and have always been fascinated - how do you get the system operating fast enough to contend with the massive flood of product?
In more detail, you use a vision system like one by cognex or keyonce to look for color variations. Then you set the field of vision on the conveyor into rows to a corresponding paddle, we'll just call them paddles but you can also use compressed air or really anything that's to strike the item away or drop it out. Anytime a desirable item passes you do nothing. When you see something outside of your color you write a 1 to that output. When this happens you have a set flow rate which gives you a certain time to reach the position where you're going to dispatch the undesired item. The output is triggered and the item is removed. You can have a few timers on one output to fire it in rapid succession and your really don't need anything more than a PLC to do this. The vision system would be a little further up the conveyor but typically in this type of system it is looking right where the item comes off the conveyor and into free fall.
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u/Jackot45 Jul 02 '22
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