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BrokeInBendigo

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  1. That intro video is hilarious. Like comically overblown hype with similarly comically bad CGI. Lol! Guess the coin and relic crowd is a bit different than the gold crowd.
  2. Maybe a tiny amount of material would leach out but only the outermost molecules in the nugget would be exposed to the environment. I'm more referring to the depositional environment - the bedrock or clay or whatever acts just like a sluice to catch gold particles. It also catches heavy materials like iron-rich minerals. Those other materials are concentrated along with the gold contribute to the response. When you dig, you disperse all the other stuff and the response is no longer the both gold + nearby concentrated minerals, it's mostly just the gold, hence a lesser response.
  3. Nugget halo makes sense to me. You'd expect iron-containing heavy minerals (ground noise) to settle in along with nuggets. It's not that the gold itself is interacting with its environment, but that the process that guides nuggets to their resting place also accumulates materials that give a bit of a signal. When digging, you break up the previously concentrated and defined volumes of metalliferous material which surrounded the gold. I'd be confused if a nugget in its "original" spot *didn't* sound different than the same nugget buried at the same depth, with same orientation, in the same now-disturbed ground.
  4. That soft, low-pitched whomp is just screaming "dig me"!
  5. Talk about Real Hard Yakka™️ country! I suppose prospecting style picks will do pretty well on ice.
  6. A major lesson learned after moving to Australia is that friends here use words that, in the states, you don’t even use for enemies (much less suitable for this forum). JP’s post was actually quite warm and fluffy relative to the usual vernacular.
  7. Gerry, Might wanna slow down there buddy. There are some older folks on this board that need to watch their blood pressure.
  8. Great results Simon. I expect ML will replace the 11" coil. Hopefully they take responsibility on a larger scale for the apparently quality issues with the coil and detector.
  9. I’m sure the individual employees are decent people, just the company policies which are lacking
  10. Yeah the 6000 & its headphones use aptX low-latency. Best case scenario with aptX LL is 40 ms latency. Not many devices implement this codec and few do it well, many are closer to 100ms latency than 40ms (50+ ms is unusable for realtime anything IMO). Non-LL aptX bluetooth latency is usually ~200ms, definitely unusable and laggy as hell. The 6000 headphones implement this codec properly so they aren't laggy. This is a rarity, kudos to ML for doing it right. Miners Den has clearly just made a deal on Alibaba for this product with no design input. Compare to the Quest wire-free kits. They use a totally different, lag-free wireless technology, good build quality and retail for less than this Miners Den kit. They also offer kits for 40% less that let you use your own headphones. Their devices are clearly designed by them for metal detecting, though I'm sure manufactured in Asia. Miners Den has a reputation here for poor customer service and cash grabs like what this BT setup looks to be. I don't know anybody who has had a good experience with Miners Den.
  11. Thanks JP. I have a stock 14” and month-old 17” CC x-coil, believe it is bundle wound (edit: tis spiral, thanks Simon). Out bush in reefy country with a lot of ironstone or red mudstone type bedrock I often get a fairly loud signal on the ferrite but on alluvial gravels or paddocks it’s less intense. I’ve been running auto but understand the advantage of semi auto - I’ll try that and your suggestion about elevating the ferrite today.
  12. I can "balance" the ferrite out in Difficult using the QT button but cannot balance it out in Normal. I've done the octopus (as described by @Jonathan Porter ) manoeuvre for 1 to 2 minutes over the ferrite, still hear it. Especially if the ground is hot. Am I doing it wrong?
  13. This is the big shift with machine learning (what we are, for convenience, referring to as "AI"). Computers are no longer only as good as the programmer. Computers are better than the programmer - much, much better. Perhaps disturbingly, the programmer has no functional access to the logical process an AI uses to make a given decision. It is too complex and abstract, humans generally cannot understand it, despite being able to analyse that decision-making process. Put a coil on an AI and you could have a detector that rivals and even surpasses the work of human genius. Just one example of machine learning revolutionising a data analysis problem (which humans have spent a very significant amount of time and money on): https://www.escardio.org/The-ESC/Press-Office/Press-releases/machine-learning-overtakes-humans-in-predicting-death-or-heart-attack
  14. Here's a moderately technical paper from Minelab (who, at this time, makes the best pulse induction prospecting detectors): https://www.minelab.com/__files/f/11043/KBA_METAL_DETECTOR_BASICS_&_THEORY.pdf More basics (see Multi Period Fast, Multi Period Sensing, Smart Electronic Timing Alignment, Zero Voltage Transmission): https://www.minelab.com/anzea/knowledge-base/key-technologies Some good info in there. Minelab does use multi-frequency TX and RX but their analysis is magic sauce. Imagine they have some sophisticated analysis. As you well know, if there was AI involved anywhere, their marketing would ensure we know allll about it. Alternative avenues of improvement include ZVT (as mentioned above, this was the main innovation in the GPZ 7000, released 2015, new updated model on same platform expected in the relatively near future) and innovative coil design (for example, the recent rise of concentric coils for the GPZ, some recent patents for coils in which a flat-wound coil is twisted at front and rear to be vertically oriented, to reduce saturation from ground mineralisation and other designs).
  15. Exactly. Your experiencing running with GB off illustrates how much detecting depth depends on the ground handling. Think I’d still rather have our Aussie sized nuggets and hotter ground than your mild soils and fine gold 😅 hope you can make it over here some time for a prospecting adventure and smash some personal bests!
  16. Simon’s referring to no ground balance at all - not fixed/manual GB - which is a setting I’d wager nobody uses on Australian goldfields.
  17. Meant stable threshold not silent. Almost all of the tech in a PI detector is there to separate of signal from noise. When you run your detector at anything besides the highest sensitivity settings (so on a GPZ, that'd be Sens 20, all smoothing off, Normal - on a GPX 5000, that'd be Sharp timing, gain 20, stab 0), you are sacrificing depth for stability. Every setting under those max settings is there to help filter out ground and EMI so you can actually distinguish real targets. Even those max settings have some amount of ground and EMI mitigation built in. If you can run balls to the wall settings where you are and still not ever be affected by ground noise or EMI, have zero false targets, well I would love to be there! But I suspect that you do not run your GPZ or GPX full-bore all the time, and therefore you are missing targets. I think there is a lot of blood still to squeeze out. The QED is one detector that has a no GB mode - not aware of any others - and it is unusable in that mode in even marginally mineralised ground. Of course, the detector manufacturers and engineers are the ones who will improve the tech. The prospectors are doing what you want to be doing - prospecting. Machine learning can do things today that only the most visionary humans dreamt of in the past. There's massive potential for a new era that dwarfs previous technological generations in terms of scope and capability. It's hard to overstate the potential, but very easy to dismiss it as incremental. It can and should be applied to detector technology and will likely have a massive impact.
  18. You're most welcome. I've a keen interest in this, so please excuse if I go on a bit long about this stuff. Balancing and EMI It's most important to balance the ground mineralisation because a target on the edge of detection cannot be differentiated by the detector operator from the response from the ground. To elaborate, I'll just describe a bit of how pulse induction detectors work. The coil is energised with varied intensity and at varied intervals. The pattern constitutes the "timing" involved. The detector transmits a pulse or pattern of pulses and then is set to a receive mode to get a response. TX/RX cycles are very fast. The timing you select is largely dependent on the ground type. Some timings are higher-energy than others. The more energy you put into the coil, the better the response on gold/metal, so you want the highest-energy timing that will work in the area. Problem is, different ground responds to different timings in different ways. For example, the ground may be saturated to a significant degree with iron-rich minerals (generally in an area where quartz reefs occur) or salt (dry salt lakes), or have far less mineralisation (granitic sands). Some ground types will produce responses very similar to a piece of gold with a certain timing. The higher-energy timings may be unusable in these areas because the ground looks more or less the same as a metal object at depth. In other words, it sounds like there are targets everywhere (on current detectors). You then switch to a lower-energy timing, or perhaps a timing with a different pattern of pulses, which does not produce as much of a response for that particular ground type. In doing so, you lose detection depth. Regarding EMI, it is a similar situation. When near sources of EMI (e.g. power lines) at frequencies and amplitudes such that they energise the coil, again you get a response that is very similar to a real target. In both cases, there are a variety of settings on the detector, some of which process the data stream before it is converted into audio and some afterwards. You could use a higher-energy timing but reduce the gain at a particular point a the processing chain, or apply whatever kind of DSP method. A common one is "stabilisation", where you ignore low-amplitude variations in the signal. Reducing the amount of data being converted to audio reduces audible responses of course. Sometimes it's better to have a quiet detector with less sensitivity, other times a noisier detector with more sensitivity. The operator and their experience is a major factor in setting choice. So what we need to improve in current detectors is the handling of the ground response, when using the highest-energy timings. We need to separate the signal from noise, which I believe is a task very well-suited to an AI. Ground Conditions Ground conditions can be and very often is variable in very small areas. For example, you may have an iron rich area of bedrock that is visible at the surface and then slopes downward, at which point it is covered in a mostly organic soil. Swinging the detector across this boundary of soil to ironstone will induce a response. Another example is a quantity of soil which has higher capacity to retain water than an adjacent area (again, this could be within a square metre) - this will cause a response. Of course, across larger regions you have trends as well. The timing used can reduce/eliminate the response at these boundaries, at the cost of detection depth. Training/implementation Your idea is fine, but I'll reiterate that you absolutely need an existing algorithm processing the ground for this to work. Nobody wants to dig X holes just to get started in a particular spot, it's not feasible. You'll understand when you recover 30 targets 🙂 Burying targets Not gonna work. Metal objects in the ground have been there from a few decades to literally millions of years. The presence of the objects in addition to all that time create profoundly different conditions than what you'd get if you buried something. A common technique to somewhat obviate this is to drill holes from below the desired target depth and insert a test target. This allows the ground above the target to be undisturbed and provides a more realistic testing scenario. Still, it won't really work because of the extremely diverse range of ground conditions in which gold is found. The only real use of testing on buried targets is comparing different detectors relative detection depths, and even then it's a very smooshy, vague kind of testing. Waveforms to Images Sounds like a reasonable method. I had a lot of fun coding an app to interpret an image as raw audio, then apply audio effects to it, and finally re-interpret it back to an image. I mean, a waveform is just a 1 by X image, right? Yes - In Bendigo at the moment. I think the majority of this site is focused on the US but plenty of Australian fossickers and prospectors here. Hard disagree. The increase in targets recovered if we could use the highest-energy timings in all areas, with perfect ground and EMI handling (meaning silent threshold), would be IMMENSE. Hot rocks are metal-rich rocks (sometimes also mineralised with gold!) which sound like a nugget. Some areas are covered in hot rocks and your options are to either tune down your detector to ignore them (and necessarily miss some gold) or dig them all (and spend a lot more time digging). I've suggested this a few times, and there are other applications - an accelerometer could be used to know the detector is in a "target recovery" mode and it should not do any ground tracking. It could also be used with an AI to recognise small-scale geological boundaries and not give one-way responses when crossing them. Would I want this? No, I'd rather hear the ground changes. But still interesting. I absolutely want my detector to handle as much extraneous information processing as possible. I want to use my prospecting knowledge to determine where to swing and turn my detector sensitivity as high as it can go. You may be interested in looking up geophysical interpretations. I don't know if AI is being used in this area but such datasets are extremely interesting.
  19. Recent Apple iPhones have a dedicated processor for machine learning tasks. You don't need crazy hardware. Well, modern smartphones are kinda crazy with how much power they have, but still, it's nothing exotic. Another idea is to simply update the ground and EMI handling on a regular basis via software updates. While the detector is in testing/development, a lot of training data is acquired. The detector/app doesn't need to be sophisticated at this point, the app would just record all raw data from the coil and your beta testers press a button on the app when they believe they have a target, then press another button after it has been investigated to confirm if it was metal (and what exactly it was perhaps), or if it was just ground noise/EMI. You'd also have some people going out in various goldfields to very carefully and methodically generate high quality training data. After your testers gather ground responses from all over the world and have timestamps for targets, you give this to a NN to figure out a model. You'll need some slack in the model of course, as humans aren't perfect. Afterwards, you have a pretty good model. This is implemented to the detector on release. People who agree to continue helping to develop the model continue to mark targets as real when found as described. This data is given back to the developer who continues training the NN with this updated data. Unless a large number of people poison the well, your model will only improve as time goes on. You'd have two release channels for the model, stable and testing, which you could select in the app. Testing would be the latest changes, which may or may not be better than the stable model. Major takeaway: You don't need to engineer or even understand your signal processing pipeline if you let a NN do it. In other words, you don't need to really understand how a metal detector works to make a very, very effective machine. Edit: You could have different NN for different regions. For example, you could have a Pilbara model, a Ballarat model, a Clermont model, a Nevada model, etc... You could give GPS coordinates to the algorithm and have extremely specified ground balancing... The possibilities are mind-boggling. If you want to see how paradigm shifting AI can be, have a look at DALL-E 2, an imagine generation model. Here's a mind-blower of a PDF giving a lot of examples: http://dallery.gallery/wp-content/uploads/2022/07/The-DALL·E-2-prompt-book-v1.02.pdf
  20. Hi Ben, I've thought about this quite a bit. I think would be trivial for a neural network to sort it out. There are only a few primary dimensions to the data - it's just electrical current from the coil, that is the only sensor detectors use. However, I think you are slightly misguided in where to apply the AI. Metal target differentiation may yield some interesting results but you can make NO assumptions about the mass, volume, shape, texture, and mineral inclusions in samples of native gold. Gold often contains silver, copper, and iron, among other metals. I have a gold nugget that is over 1% palladium (not platinum!). Gold is present as jaggedy, branching crystals as well as smooth and solid nuggets. It is found distributed through quartz and ironstone. I am deeply sceptical that any algorithm could accurately differentiate gold from not-gold. Where a neural network would do wonders is with ground balancing and EMI cancellation - that is, the capacity of the detector to ignore everything except a solid metal object. This is what holds detector technology back far more than lack of target identification. Such a NN-developed algorithm couldn't simply be static. You can't train it and then code it into the machine's software, because ground types are *incredibly* variable. EMI is *incredibly* variable. There is no way in hell you can get enough training data to do this perfectly, but you could (and should) ship a good-enough algorithm with the detector. So you start your detecting with a passable (meaning, as good as current detectors) handling algorithm, but a processor on the detector (or your mobile phone, paired to the detector) then continually modifies, in near-real-time, a ground and EMI handling algorithm to be used in that session. So as you detect, the detector gets better and better at handling the ground and EMI characteristics of that area. I'm not sure what would need to happen to modify this algorithm, I don't know this area of computer science. My vision for such a detector would be pretty simply, hardware-wise. A phone connects (via Apple lightning or USB cable - bluetooth is too slow) to the detector. All processing happens on the phone. The detector has a battery which powers both the coil and the phone. A hardware interface on the detector handles the analog-to-digital conversion of the coil response, data transfer to and from the phone, and digital-to-analog conversion of the audio output (along with a headphone output). The phone screen is used to change settings and get visual feedback from the detector (something that is sorely missing on current detectors). A real-time waveform display would be excellent. Imagine, detector operators, that you can see an oscilloscope type view of the raw coil data alongside processed audio waveform, in real-time. You hear the response, and see it. How incredibly useful would that be! Imagine almost infinitely fine variability of all parameters. Imagine custom timings. Regular, over-the-air software updates for the phone app and firmware updates for the detector hardware. I believe that the company who does this first will make bank if it is implemented well. Edit: I'm aware of Air Metal Detectors, a kickstarter project which seemed very promising at the start but seems to have flopped. It uses a phone for the processing as I suggested, but I don't think it uses AI or anything fancy internally. Just standard VLF processing.
  21. My favourite gold-related YouTube channel is WilTube Prospecting. Young lad, not sure if he's even a teenager yet. Give him a follow!
  22. It’s not like the infection is a binary thing; you can have a small viral load or a substantial load. There are also many known genetic variants of the virus. Its very well established that vaccinated individuals are affected less than unvaccinated (the vaccine works). Back on topic: I’ve noticed American users are clambering for DD coils, especially small ones. Over here in Australia, I don’t see so much use for a small DD coil, except for near EMI sources, despite our ground being far hotter than yours (as far as I know at least). I’d rather user a small mono any day if the week. Why do you USA-based operators want small DD coils over small monos?
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