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Device for Seismic Noise Analysis

A device that monitors the statistics of the magnitude and the 3-D direction of seismic noise might detect earthquakes before they happen.

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Building collapse is what actually kills people when major earthquakes hit impoverished urban areas with substandard housing. There are 7 earthquakes that have each killed over 100,000 people in the past century. 223,000 people died in Haiti ten years ago - now forgotten. A reliable warning on the order of tens of seconds or more would let people move to safer places, but such a system does not yet exist.

The earth is always in motion. This motion is "seismic noise." A new femtoampere amplifier IC now allows the precise measurement of the vector magnitude and 3 dimensional origin of this noise and determination of the statistics of these values in real time. The project reports a new, unique, ultra-sensitive and easily networked digital seismic device built with off the shelf components. It outputs seismic data in vector format and statistical data. Small local seismic signals that were previously lost in the seismic noise can be readily identified.

This completely open source project breaks down into four main parts.

1) Part 1 -Seismic sensor

From Wikipedia, the free encyclopedia -

"In geology and other related disciplines, seismic noise is a generic name for a relatively persistent vibration of the ground, due to a multitude of causes, that is a non-interpretable or unwanted component of signals recorded by seismometers."

The role of the hacker here might be to challenge that bit of conventional wisdom. Let's see where it goes if we put the magnifying glass on seismic noise instead of intentionally ignoring it.

The hypothesis behind this project was that if we really study the seismic noise and mathematically get to know its behavior in seismically active locations, we will be able to tell the difference between this noise and the telltale snaps, crackles and pops that must happen locally right before a geological fault line lets loose.

Basically, I am reporting a new kind of design for a seismic device for the purpose of responding to the low frequency ( <1.5 Hz ) baseline noise movements of the earth's crust. Seismic noise is present everywhere on earth. Some of it is local and some of it arrives from far away. Ocean waves are a one cause of distant noise.

Most useful sensitive seismometers utilize a mechanical moving element with a fixed resonant frequency. Because noise by definition is a composite of a wide range of frequencies, for our purposes this device must not have any significant frequency biases. It must be relatively neutral to all the frequencies in its band. Mechanical designs therefore can't be used for this purpose. Piezoelectic seismic accelerometers are practically frequency independent for seismic purposes and these "geophones" are commercially available, but they are usually very insensitive and they are best used for strong man-made signals in geological exploration. However, piezoelectric pressure sensors still have the theoretical potential for extremely high sensitivity. They have no moving parts or resonant frequencies in the seismic range, they have minimal frequency biases and are widely avaiable in the form of extremely inexpensive but high quality microphone elements. Because of the need for frequency independent noise floor analysis, I needed to design an ultrasensitive inertial piezo instument that pushes its seismic sensitivity to the very limit of what is possible. The other goal is to extract 3D directional information - in other words, to be able to ask "where is the noise (mostly) coming from?" in addition to "How loud is it?" in real time. This has not been done before.

The design is fixed to a wooden base on rubber feet. A stainless steel or mineral sphere is supported by 3 hard insulating plastic beads resting directly on 3 inexpensive piezoelectric buzzer elements. These elements are themselves symmetrically arranged 120 degrees apart and precisely tilted at a 45 degree angle around the center ball. The buzzer elements are mounted on adjustable supports, like magnetic doorstops available in hardware stores or inexpensive camera tripod heads. Each piezo element provides equal support to the central ball. Movement of the base in any vertical or horizontal direction accelerates the mass and changes the compression force of the ball against its sensors. One of the sensors is aligned to true north as a direction reference. The precise geometry of the device allows for the mathematical calculation of the vector magnitude and spatial origin of the seismic noise in real time.

The base of the device is leveled with a bubble inclinometer or with an iPhone. An enclosure provides protection against short term temperature changes and air currents. The device can be placed under a glass bell jar or withinin an airtight styrofoam cooler box, for example. The electronics are either housed in a closed box or within the styrofoam cooler box. To be useful, the devices need a very sturdy foundation. The devices either rest on a thick...

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EXXXP62.ino

Arduino Yun program file

ino - 62.39 kB - 02/23/2020 at 16:28

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IMG_2575 (1).JPG

A photograph of the basic schematic for one channel of the TI op amp based charge amplifier. I can't add any more photographs to the build instructions section for some reason!

JPEG Image - 381.72 kB - 09/18/2017 at 22:43

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newground.pcb

The Pad2Pad.com design file that contains all needed instructions for manufacture of the PCB. It also contains its own version of the BOM.

pcb - 147.48 kB - 04/28/2017 at 19:30

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BOM.ods

Bill of materials

application/vnd.oasis.opendocument.spreadsheet - 13.39 kB - 04/28/2017 at 03:13

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  • 1 × Wooden base - see instructions 2 inch thick 8 inch diameter hardwood bowl blank from woodworking store.
  • 1 × Center mass - 3 inch chromium steel or mineral ball Available on Amazon and eBay. See instructions.
  • 3 × Piezo crystal microphone or buzzer elements - see instructions Available on Amazon and eBay.
  • 1 × Assembled 3 channel charge amplifier circuit board - see instructions Pad2Pad, per custom specs- schematic & bill of materials free on request
  • 3 × Texas Instruments LMC662 femtoampere op amplifier And passive surface mount componetns - from Digikey. See Pad2Pad BOM.

View all 9 components

  • "Fingerprinting" the local seismic noise in the Yellowstone area

    Michael Doody02/06/2020 at 01:53 0 comments

    The data from the last log entry was collected on Feb. 3, 2020. This log shows about 19 hours of data from today, Feb. 5, 2020. The unusual features of the last plot are highlighted again to show the similarities from day to day.

    First, the plot of the angular depth vs. combined probability statistic -

    Next, the plot of the compass direction vs. the combined probability statistic -

    Finally, the plot of 3D magnitude vs. the combined probability statistic. 

    Lots of persistence of the unique features of this noise data. Now - how to use this?

    There was a request for a graph of what the 3D magnitude and angular location probability arrays look like. The following two graphs show how 102,000 data points sort out into their 100 respective probability "bins." 

    First, the 3D magnitude probability array -

    Next, the angular location probability array -

  • Looking at the fine points

    Michael Doody02/03/2020 at 14:25 0 comments

    The probability data really shows some interesting features. Again, the probability parameter of each 1 second data point is affected by the 3D magnitude, the averaged compass direction and the angular depth of that data point. It is clear that these 3 parameters are inter-related as well. The display of these individual data parameters against the probability statistic shows an interesting subpopulation of noise events. 

    This is a plot of angular depth (X axis) vs. probability statistic for Yellowstone data from the last 9 1/2 hours. There is a clustering of data points at around -1 radians of depth that is clearly separate from the rest of the data.

    The "steps" in the combined probability data relate to the fact that the magnitude and vector origin probabilities are stored in discrete "bins" that are not continuous.

    Next is the same data set showing compass direction - another cluster of points is seen, but their compass locations do not seem to be out of the ordinary. The discrepancy must therefore be related to magnitude or angular depth.

    Next is a plot of 3D magnitude vs. the overall probability statistic. There is a break in the data at the higher magnitudes. Something seems to be  "pushing down" the probabilities of points that "should have been" in the -6 to -7 range. If these are the same misplaced points as in the plot immediately above, it sounds like the data points with anomalous angular depth (from the first plot)  may explain the  discrepancies.

    What does all of this mean? More to follow as I try to figure it all out!

  • Data from the Yellowstone area - FINALLY

    Michael Doody02/02/2020 at 15:24 0 comments

    The seismic noise device placed in the Madison Valley East-Northeast from the Yellowstone caldera has been turning out reams of data. The amount of seismic noise in this area is astounding. It is 4 or 5 times as intense as the noise recorded by the same machine in East Tennessee. Much of the noise seems to be coming from the West, interestingly. The stronger noise is originating closer to the horizon and the less intense noise is deeper. Several strong local events have been recorded. The device is indoors in a climate controlled environment and it is possible that there may be data artefacts from the vibrations from the heating system. A future visit to Montana will be needed to eliminate this issue. Another source of noise may be the Madison river itself - it is about 200 yards to the East of the current location of the device.

    Here is a representative 24 hour plot of the vector magnitude data showing a local event. Full scale for vector magnitude would be about 650.

    This is the same data, expressed as a scatter plot. I believe that he small blips along the bottom of the plot may be related to the indoor heater coming on and off.

     Next is the 3D vector magnitude data expressed as a histogram. The nice Gaussian-like distribution seen in Tennessee is not seen! This data seems to reflect at least 2 independent sources of the noise.

    Here is a plot of the combined (multiplied) vector magnitude probability and 3D location probability (Y axis) of each time point during the same time interval. 10^-8 is one in 100 million. 

    Next is a plot of angular depth vs. vector magnitude over a 24 hour period. Depth is expressed in radians from the horizon. Zero is at the horizon. - Pi/2 would be straight down. Higher intensity time points tend (seem) to come from a direction near the horizon. At this point, the device is not fully calibrated and the angular depth cannot be considered to be precise. 

    Next is a plot of averaged compass direction vs. angular depth. The compass direction (in radians, with North = 0) calculation is compressed to the north by the averaging process. The direction does not extend all the way from -pi to +pi. A faster processor and memory will be needed in the future to do this without averaging. Each one second time point is the result of 50 measurements of each sensor. The device has a low band cutoff in the range of 15 Hz, so when the processor is capable of calculating and recording 30 time points per second, the averaging can be effectively eliminated.

    Here is a plot of direction vs. magnitude. West is to the left on this plot. Again, compass direction is averaged. This plot is interesting, because the caldera is to the Southeast. It is possible that deeper seismic noise from the caldera on the Southeast is being reflected back to our machine by the Gravelly range mountains located immediately to the west of our site. 

    This is a video of the 3D plot of compass direction vs. angular depth vs. 3D vector magnitude for a 24 hour period.

    The next video is the 3D plot of compass direction vs. angular depth vs. combined probability parameter for a 24 hour period. 

  • New Location Near the Yellowstone Caldera

    Michael Doody01/06/2020 at 06:36 0 comments

    I have placed a machine in the Madison Valley of Montana! It is near the Yellowstone caldera and is putting out data. I'll update with more information soon!

  • Yun program now added to downloaded files

    Michael Doody09/15/2017 at 14:24 0 comments

    I just added the "noisemachine.ino" program to the files section, so that the entire project is completely available to anyone who wants to replicate it.  I also added noisemachine.txt so that the program can be viewed without the arduino IDE.

  • Mexico Earthquake last week

    Michael Doody09/14/2017 at 11:53 0 comments

    People have been asking me if my device registered the magnitude 8+  earthquake that happened near Guatemala, off the West coast of southern Mexico on  September 8. There were at least 96 fatalities and thousands were left homeless. Here is a picture to keep a focus on the human cost of these events. Note the total collapse of this residence.  It is not clear from the news report whether anyone died in this house. There was  no warning whatsoever before this earthquake from traditional seismometer monitoring stations.


     Detection of distant quakes is not what this device is for, but the "big one" registered very well on our machine  here in Knoxville. The peak is about half full scale on our machine. Here is the vector magnitude data - this quake was about 1600 miles from the Knoxville machine.

    Here's the probability statistic data, log scale, running averaged - 

    Here's the vector location data (radians ) pointing at the quake  toward the Southwest. I am not sure, but the later vibrations appearing to come from the Northeast may be S-waves  (transverse waves)  travelling at about half the speed of the initial P-waves (compression waves).  This is a nice illustration of the fact that transverse waves vibrate at a 90 degree angle to the compression waves.

  • Another small quake 413 miles away

    Michael Doody09/14/2017 at 00:57 0 comments

    A minor earthquake occurred on Wed Sep 13, 2017 at about 12:33:10 CDT (Sep 13, 2017 17:33:10 UTC) 11.43 km northeast of Peterstown, WV. The magnitude was 3.1.

    Our main machine recorded this event 23 seconds later. The vector magnitude plot for that hour  is:

    The brief event early in the hour appears to be something very local. It showed up the local USGS affiliated "strong motion" machine 7 miles or so away even though the West Virginia event did not show up well (see below). Here is an isolated view of the vector magnitude data from the West Virginia event:

    There appears to be no advance vibration from this distant event whatsoever.  Here is the combined probability statistic data from the entire hour.

    This shows a substantial deviation from normal statistics for about 1000 seconds after the main front of the West Virginia tremor, a hint of which can be seen in the actual vector magnitude data. I speculate that the deviation from normal statistics may be due to echoes from the nearby Smoky mountains to our South and from the Appalachian mountains farther away to the East. 

    This graph shows the horizontal location in radians of the data points for the hour, indicating a persistent Eastward trend in  the average location of the noise for about 1000 seconds:

    Here is the data from the Knoxville USGS machine, by way of comparison. It records (in black) the event early in the hour that showed up on my machine, but there is only the barest hint of the West Virginia event at 1:33 PM EST. Here is the data from all of this afternoon on that machine:

    Here is a cutout view of this data showing the local early event (in black) and the barely perceptible West Virginia event. I added the time labels.

    The take home message that seems to be evolving is that distant events are not associated with detectable anomalies of the noise before the event, but local events do seem to be associated with anomalies. More data points (and lots of them!) are needed.

  • Nearby Tremor in Knoxville

    Michael Doody08/25/2017 at 21:40 0 comments

    About an hour ago, a small 2.5 magnitude tremor event happened several miles to the Northwest of our machine. I felt and heard it - it seemed like thunder some distance away. The rumbling persisted for quite a while. Here is the recording from the local USGS machine - there was no significant activity prior to the event on the local machines.


    Here is the location of the event, according to the University of Memphis earthquake center, in relation to our machine - I have added text to the Memphis center image to indicate the two locations.


    Here is the vector intensity data from our machine - X axis is in seconds.

    Here is a close up view of the seismic noise during the 500 seconds before the main tremor.

    Here is the apparent location data, in radians, including the tremor itself  - it starts at 500 on the X axis. Positive values are westerly, consistent with the Northwest location of the quake from our machine. Because of the processing limitations of the Arduino Yun, the location calculations are less sensitive to tremors arriving from the North and South.


    Here  is the log scale of the combined probability data, without averaging.  The combined probability is the product of the probability of the location data and the vector magnitude data. There are definite statistical aberrations noted in the minutes preceding the main event. The lowest probability point in the precursor data is in the one-in-a-billion range! Because of the size of the initial data set after start up, the minimum possible combined log probability is -10.3. This explains the bottoming out of the data during the actual earthquake. 


    Here is the same data, with running averaging.


    Once again, VERY interesting data. We need to profile dozens of tremors before any conclusions can be drawn about the statistical prediction of local earthquakes, but this is another confirmatory event that seems to say we are on the right track! The placement of a machine to the west of Yellowstone park will happen sometime in late fall if everything goes well.

  • Adding a little cool factor

    Michael Doody07/11/2017 at 02:44 1 comment

    Earthquakes don't happen very often in East Tennessee, so while waiting to get a device installed near Yellowstone I have a little extra time on my hands at this stage in the project. Just to add a little somethin' to my "indoor" seismometer, I bought a inexpensive little solid state ultraviolet laser module and an inexpensive laser control module on eBay, Total cost about $20.

    Fluorite contains yttrium, europium and samarium in a calcium fluoride matrix. The first three elements absorb ultraviolet light, hold on to the energy for a while and emit it later as visible light. This type of photoluminescence is a combination of fluorescence and phosphorescence. The entire ball glows nicely when illuminated from below by the laser through a small hole in the seismometer base - the laser light itself is invisible.

    It's aliiiive!

    The Arduino code to make it dim and brighten is bone simple:

    ******************************************************************************************************

    int laserPin = 5;

    void setup() {

    pinMode (laserPin, OUTPUT); //actual pin is 5

    pinMode(6, OUTPUT); //we will use pin 6 as a ground for the electrodes in digital pin 5

    digitalWrite(6, LOW); //pin 6 is used as ground for the electrodes, so the program never changes this.

    }

    void loop() {

    int x = 1;

    for (int i = 0; i > -1; i = i + x) {

    digitalWrite(laserPin, HIGH);

    delayMicroseconds(i * 20); // vary the brightness of the fluorite ball

    // with this number; 20 is "subtle" in the daytime

    digitalWrite(laserPin, LOW);

    if (i == 255) x = -1; // switch direction at peak

    delay(10);

    }

    }

    ********************************************************************************************************

    The code can be added on to the main seismic noise program as well, so that the ball also changes intensity in response to vibrations in the home, but that delay(10) statement makes it a time hog. It is best to have a separate Arduino Uno controller for the laser and the Yun for the seismic noise device.

  • Aberrant noise detected 32 minutes before local quake

    Michael Doody06/25/2017 at 21:05 2 comments

    This morning at 10:00:57 UTC (6:00:57 Eastern), a magnitude 2.6 tremor originating near Lenoir City, TN was recorded on all regional seismometers in the USGS networks.

    Here is the USGS summary page of that event.

    This event was 21 km in depth and was approximately 20 miles from our seismic noise device. Here is the signal as recorded on the Knoxville strong motion machine - a few miles from here. Note the absence of any signal before or after the event.

    Here is the event as recorded on our machine - the data shown is from 4:00 to 7:00 AM. with data points every 1000 milliseconds. The x-axis is number of seconds from 4 AM and the Y axis is vector magnitude units (in machine voltage units, not the magnitude units used to refer to earthquake strength). This data is from the <15 Hz device. Unfortunately, the low frequency machine was not recording data during this event due to a bad clock module.

    32 minutes before the main event, small increases in noise magnitude, associated with directional anomalies were noted. After-tremors were recorded on our device which did not show up on the Knoxville machine, but which did show up on some of the more sensitive regional machines.

    Here is a zoomed in view of a scatter plot of the vector magnitude data from the aberrant noise precursor before the main event. Once above 33 units, the data is outside the normal bell curve of the noise.

    Here is a line plot of the 5 second running average of the logarithm of the combined (magnitude and location) probability parameter. There is strong evidence of a prolonged statistical anomaly beginning about 32 minutes before the main event (red arrow), although of course it cannot be certain that the anomaly is actually related to the following event.

    Here is the same data without the running averaging.

    Notice that the lowest point in the precursor is around 10^-7. In other words, there is about a one in ten million chance that the magnitude and direction of that time point's data is part of the usual seismic noise. This is not even taking into account the tremendous improbability of having a cluster of "unlikely" measurements closely related to one another in a short time period. One of the time points for the actual quake reaches a peak at about a one in 10 billion chance.

    These numbers are all the more impressive if one takes into account the meaning of the logarithmic data. If 50-50 odds was a line one inch long as on this graph, one in 10 million odds would be a line 158 miles long and one in 10 billion odds would be a line 158,000 miles long. That's almost a light second!

    Seismic events are happening across the globe constantly. These far away events are what make up the majority of seismic noise. It's clear that some kind of cluster analysis will be helpful to deal with random and isolated (one point only) deviations from normal statistics and will allow a machine to identify local precursor events with extreme clarity. Far-away (weak intensity and brief apparent duration) seismic events would be experienced almost equally by the individual members of a local network of machines, while the machines will give very different responses to nearby precursor events.

    A central computer responding to data from a local network will then need to quantify the heterogeneity of the probability data coming in from its individual machines in response to weak intensity signals. If the local devices are seeing a weak (low amplitude) but real ( a cluster of very low probability time points) event in widely different ways, it then can assume that a local seismic event may be happening.

    Then decide whether to issue a warning.

View all 15 project logs

  • 1
    Instructions for build

    This picture is of my "indoor" seismometer, with its electronics in an antique wooden box next to it. It is networked and completely functional, but because of its noisy indoor location, it is not useful for any serious seismology. It is never quiet, even at night, because of vibrations related to air conditioning or heating fans, dog activity, weather, etc. Things DO go bump in the night, a lot, and I have proof... The center mass is an agate sphere, in keeping with the geological aspect of this project.

    The basic device design consists of a heavy and rigid wooden base, mechanical supports for piezoelectric sensors, a spherical center mass, the sensors themselves, a high quality but very simple 3 channel charge amplifier based on an ultrasensitive Texas Instruments femtoampere op amp, a clock module, the Arduino YUN microcontroller and its program and an enclosure. Because the YUN has built in wireless networking, the data stored on its SD card can be accessed for processing externally, even remotely from the web. The "indoor" seismometer is enclosed in a glass display cloche, to minimize temperature and air current variations. "Working" seismometers are enclosed in weighted styrofoam coolers.

    The photograph above shows one of the devices, the Yun board (left), the clock module (middle, with the LED) and the three channel charge amplifier (right).

    The next photograph shows another device with a heavy 4" walnut base, a 4 pound chromium steel ball and rubber feet. The device behind it is the last version of an earlier design that used 3 steel balls suspended from a center post. It is no longer in use. The single mass design makes fewer assumptions about the vertical component of the seismic noise. It would also be much more stable in case of a strong seismic event.

    Two of the noise vector devices in their styrofoam containers rest directly on a massive 2-car garage concrete slab. The containers are weighted on top.

    One device is bolted through its styrofoam container to a 300 pound poured concrete base outdoors, under a weatherproof "fake rock" fiberglass housing. As with the others, it is connected to the home network through a wireless router.

    I have used several different hardwood bases - walnut, spalted maple and cherry. Different sizes and shapes are possible, but a circular base 2 inches thick and 8 inches diameter seems to work well. Beautiful pieces of wood can be purchased on Amazon - look for "bowl blank". Rubber stoppers (hardware store, usually next to the corks) work well as pedestal bases.

    The sensor elements are basically piezelectric buzzers in plastic cases similar to this

    http://www.ebay.com/itm/Lot-of-2-Piezo-Buzzer-70dB-2kHz-Supply-1-to-25v-Square-waves-/112066085579?hash=item1a17a8c2cb .

    The center hole of the piezo casing is drilled out to allow a hard plastic bead (JoAnn fabric store) to contact the piezo element directly.

    The sensor elements are glued directly to adjustable supports. Magnetic door stops (Lowe's, Home Depot) work well like those used for the "indoor" machine above, as do inexpensive mini tripod mounts like these on eBay.

    The adjustable supports are bolted to the wooden base by 1/4" threaded bolts (hardware store) that have been cut to size with a Dremmel tool.

    The center mass ball is supported by the 3 beads in the center holes of the sensors and the sensors are tilted at a 45 degree angle with respect to the horizontal. Beautiful minerals and rocks are easily available from multiple sources on the web as 3 inch spheres, as are chromium steel balls.

     The sensors themselves must be precisely angled and leveled - this is extremely important, as the acceleration of gravity is a very significant part of the program's vector calculations. The gravitational acceleration of the center mass must affect all three sensors equally. Smart phone apps like iLevel (for the iphone) can provide highly accurate leveling and tilting information. A bubble level or smartphone is used to level the wooden base.

    Inexpensive large scale manufacture is needed to produce a device for use in the third world. A molded plastic base incorporating all the necessary angles and distances without the need for adjustable elements would be the way to go. Glue the sensors in place, drop a lead or steel ball in and it would be done. Someone with a 3D printer could produce a prototype - anybody interested?

    Pad2Pad is a company that will custom produce circuit boards at rock bottom prices from designs produced on their own proprietary software or other professional software. 

    The circuit board plan  designed by me (in the files section of this project)  can be ordered by any interested party through Pad2Pad - contact me for further instructions if there is difficulty ordering it or Pad2Pad requires further permission from me. I have spoken with them and this should not be a problem. The design is based on ideas from a Texas Instruments white paper on piezoelectric sensor instrumentation.

    The need for soldering might be a barrier to makers interested in building these devices. I am looking into the possibility of selling the charge amplifier PCB board and all of its components on Tindie.com. It will be sold either as a kit with the DigiKey bill of materials or as a pre -assembled board.

    Newground.pcb is the Pad2Pad.com project file and it has been uploaded to the uploaded files section of this project. The Pad2Pad design program itself is free and downloadable from their website - it is needed to work with, view or modify the Newground.pcb file.


    The Pad2Pad.com BOM is also included in the uploaded files section of this project and it is also part of the Newground.pcb file. The Findchips.com web page suggested by Hackaday will not accept the BOM in the Pad2Pad format or open source Open Office format, unfortunately. I tried!

    The PCB is a surface mount design but uses fairly large (well, large for surface mount, anyway!) SMT 1206 components for the most part. Some soldering skills (or patience and willingness to learn!) are required for assembly.

    The 3 channel charge amplifier and low-pass filter electronics are based on the following simple design. Shown is one channel only, but they are identical. The TI op amp is a dual design, so only 3 relatively inexpensive op amps are needed.

    The Arduino YUN program (906 lines, including spaces and comments) is open source and it is available in the downloaded files section of this project description.

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RichardCollins wrote 04/06/2019 at 22:58 point

Keep up the great work!  Very interesting.  I love the use of wood and stone.

I have a project to use sensitive accelerometers to track the sun and moon.  Essentially, a seismometer or accelerometers, becomes a "gravimeter", when it is able to be continuously calibrated against the sun moon vector tidal acceleration signal at the station.  If you have been collecting data continously, I can help you to calibrate it, or show you how to do it yourself.

I started about 15 years ago, using data from the superconducting gravimeter (SG) network.  Their signal is about 95% sun moon tidal acceleration.  The remainder comes from the earth.  Then I tackled the seismometer network because I needed three axis machines so I could invert to report positions of the sun and moon (one at a time holding the other as known).

I know of about 30 technologies which have produced instruments that either detect the tidal signal, can be pushed to do so, or have to correct for it, and really ought to be measuring it.

You should probably accept Peter Walsh's offer to help upgrade the amplifiers.  If you have a nice noisy seismic environment, that will provide the variation in the output of the piezo's -- if you can get enough natural noise to drive keep the mass moving continously.  If you have a way to ping the mass randomly (in three independent directions) , so that the impulses are not correlatied, that will cause greater output in the piezos, that will be correlated with the stress, and the weight of the mass.  The greater the mass, and the greater the random driver, the stronger the signal.  Up until you break it.  I have not tried this, but I think it should work.  His ampliers might be generally useful for many projects, but it would be worth trying it on yours.  If you drive the mass randomly, or use the natural noise, you will probably have to carefully model the acoustic and vibrational modes of the mass.  That might mean using very uniform and hard spheres. But then the agate ones might damp noise internally more effectively. 

You could also just drive the piezos with another piezo. but off the frequency of the detector piezo. That would provide a modulated signal in a steady mass that would be easier to amplify than the static piezo output.  I think that is probably easier and cleaner.  I love noise, but you don't have to use random, if there is an off-the-sheld technology that can do as well or much better.  I can't build these things, but I know what I have seen and others have tried.

I looked into a tripod supporting a heavy mass, where the "feet" of the tripod rest on piezo sensors.  That should be equivalent using piezos.  If you hang a heavy mass on the tripod, the shifting weight will give a signal correlated with the local vertical gravitational acceleration, and on a finer scale with the sun moon accelerations.  You can track the position of the sphere and get a boost from two indendent measures.

If you mount opposing small but strong magnets, it should allow you to float the mass, but you would need an interferometer or noncontact atomic force sensor or other.  

To get the same sensitivity as an SG means 0.1 nanometer/secondSquared (nm/s2) measurements once per second. And high stablility, which you can get by using the sun and moon as continous references.

You mentioned you did not get early warning for the earthquake.  The networks found they can "see" the gravitational field changes from large earthquakes in the the seismometer and superconducting gravimeter records.  These changes propagate at the speed of gravity, which is identical to the speed of light.  I have been trying for over a year to get people interested in building high sensitivty, three axis, Gsps gravimeters, which are what you need to track and image such gravitational field change sources.  A giga sample per second gravimeter is recording data coming in at the speed of light|gravity.  The corresponds to about 30 cm resolution at the source.  Most of the time-of-flight methods from lightning location and imaging apply. There are many resources, if you can get the acceleration data captured and into the existing data streams. They have a funny catchword, "elastogravity".  It is actually density changes in the source voxels, generating changes in the gravitational potential, which diffuse at the speed of light (they are incoherent from natural sources), and cause changes in the gradient of the potential (accelerations) at the detector.  The potential is fundamental, not the accelerations.

Very nice.  I would carve a statue and set it on three supports.  My small statues weigh about a hundred pounds. Some of the larger ones close to 500.  Would probably have to go old school and use quartz.  I don't know if the new piezos could handle that much weight. So much to learn.

Getting too old to carve marble and limestone.  Maybe someone will help me build a hand controlled robot carving machine.  :)

Richard Collins, The Internet Foundation

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senorblasto wrote 02/02/2020 at 19:22 point

Thank you for sharing your knowledge and experience. 

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mr.jb wrote 06/29/2017 at 08:44 point

Hi,

I'm researching for a similar project with a MiniSense 100

I have tried to understand your first stage  : "it really responds to the derivative of the squeeze,"

I'm interested why you put the 500 Mohm at that particular spot.

( guess it's a filter as described  from  Charge amplifier 3.2 )
http://www.ti.com/lit/an/sloa033a/sloa033a.pdf

FL = 1/(2*pi*500E6*22E-12) = 14.5Hz   ( start of passband !? ...guess it's FH )

Low pass filter at end of handwritten figure :
F = 1/(2*pi*1E3*10E-6)= 15.9Hz

hmm looks like  FL,FH is swapped in Texas instruments pdf

http://metrology.hut.fi/courses/s108-180/Luento3/varvah.pdf

Since you probably has 14.5Hz  as FH, what about FL ?

A big input resistor missing ??

--------------

My plan before seeing your project,   using 250 Mohm in parallel at the input stage, described here....  ( just another way to achieve same type of filter ? )

http://www.scienceprog.com/thoughts-on-interfacing-piezo-vibration-sensor/

What is your opinion about sensitivity ( noise problems ) compared to a geophone ?
http://www.experiencingphysics.com/?p=87

Any suggestions about overvoltage protection ( that does not interfere with the circuit ) ?

zener or schottky  ?

Did you connect the piezo to the voltage divider ( x2 - 10k ohm ) to achieve vcc/2  ( any problems with such low resistance !?)

/JB

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Tillo wrote 06/29/2017 at 06:39 point

Congrats on that sleek look, it already looks like a object to put somewere in the living room. It's actually well too beautiful designed to be a hackaday project ;).

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David H Haffner Sr wrote 06/26/2017 at 20:31 point

I see UR are on the "feature" page...This project deserves it :)

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Tindie wrote 06/23/2017 at 00:27 point

Congratulations on being one of the Internet of Useful Things Hackaday Prize Finalists!

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Peter Walsh wrote 05/07/2017 at 00:10 point

1) That "not a gaussian" curve looks suspiciously like a Levy distribution. It's one of the three known stable distributions (others being Gaussian and Cauchy). It's what you get when the variation is proportional to the offset from the mean, and comes up occasionally IRL for things such as annual flooding and geomagnetic reversals.

http://www.gummy-stuff.org/Levy.htm

2) I don't know what amplification you're actually getting, but a quick back-of-the-envelope estimate guessing the parameters of the piezoelectric sensor indicates that the output of your amplifier is 1,000x the input signal.

I have a project with a charge amplifier circuit that I've been working on for awhile, and I'm getting a factor of 1,000,000x the input signal, which are 3MHz pulses. (Measuring individual alpha particles.) I'm accurately measuring 6uV pulses that are 1/3uS long, which is about 3x the noise floor.

If you think higher amplification would benefit your project and want to compare notes or try a different circuit, send me a PM.

3) Kickass project, looking forward to future posts.

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Michael Doody wrote 05/09/2017 at 00:48 point

Peter - 

Thanks for the comments.

Your project page looks really interesting. I would really like to look at your charge amplifier circuit out of sheer curiosity about what it looks like. Sounds like you have a great project there too. You are looking at transient pulses whereas I am looking at ultra-slow seismic waves affecting the behavior of piezo crystals, so we are optimizing for different things.

The amplification in this piezo charge amplifier first stage is somewhat difficult to define because of the huge but necessary (500 megaOhm) resistor, the ultra-low femtoampere leakage current of the TI op amp inverting input, the high resistance of the piezo crystal and the very nature of "charge " vs. "voltage". 

This is not at all a perfect analogy, but you can think of a piezo crystal as a sponge - you squeeze it and electrons get squeezed out - when you un-squeeze it they go back in. Unlike a sponge, though, if you stop squeezing the electrons go back in too, even if you haven't un-squeezed it yet. Therefore, it really responds to the derivative of the squeeze, so to speak. The electrons go "out" of the sponge/crystal in a charge amplifier circuit but not "around the block" as in a typical circuit. The charge amplifier first stage is then followed by a classic 10X voltage amplifying second stage. The second stage could be arbitrarily high, but 10X is just fine for our data collection purposes and it keeps the electronic noise down to a minimum.

To summarize, the first stage charge amplifier is very sensitive to the static electric field produced by the piezo element's charge output and the second stage amp gives us tens of millivolts of output in response to the acceleration of the center mass caused by the seismic noise. 

Mike

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David H Haffner Sr wrote 04/29/2017 at 22:17 point

This is another fantastic project here, and I truly wish you luck on this, what a breakthrough it would be!

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Thomas wrote 04/28/2017 at 18:39 point

Did you try using ordinary TL072 for the charge amplifiers? The bias current is a bit higher, but I don't expect the offset to be higher than 0.5V (which can be canceled out with a floating average). 

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Michael Doody wrote 04/29/2017 at 01:49 point

The original design used TL082 op amps - it  "worked", but was not nearly as sensitive. The standard deviation of the noise increased significantly when we swapped the op amps (that's a good thing).  The idea for the change came out of a Hackaday discussion (!). This project depends on resolving the noise into the widest possible noise distribution. The wider it is, the more the program can detect subtle changes in what is happening down there!!

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Thomas wrote 04/29/2017 at 03:01 point

Thanks, now it's clear :-)

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Andrew Bolin wrote 03/31/2017 at 02:14 point

Great write-up, I'm interested to see how your results come out!

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