Earthquake early warning for mitigation and energy harvesting, atomic scale computing
Signal Decomposition and Feature Extraction Techniques: Application to Seismic Mitigation of Vibration-sensitive Eq
This is very informative. I will only suggest a few things.
Vibration isolation is now needed for buildings, as an integral part of energy harvesting, to allow orders of magnitude improvement in seismometers and gravimeters, and for gravitational wave detection.
I will have to look more closely at the needs of wafer processes.
In terms of earthquake early warning, the best are two strategies. First to instrument active regions known to produces earthquakes and then in real time provide global awareness and real time tracking of the seismic waves and their detailed shapes. If you know what is coming and its precise wave shape, then better control strategies are possible. That also applies to tidal energy harvesting, wind and other energy harvesting.
The other part is gravitational and electromagnetic tracking of earthquakes. It is possible (using vibration isolated sensors in arrays) to track, image and follow the seismic waves from emerging earthquake events. The seismic waves modify the geopotential and magnetic potential and electric potential (it is just harder to work with), the potential change diffuse at the speed of light and gravity, the local potential changes, and the gradients of the local potential are measurable.
But that requires time of flight (at the speed of light and gravity) sampling rates, so Gsps and higher. These sampling rates at bits per reading are more and more readily available now for a lot of reasons and in many industries and new technologies.
It might not be obvious, but lidar and radar both now allow real time monitoring of atmospheric events, including infrasound and flows. So “early warning” for control systems in wind harvesters takes on new meaning when you can look upstream. The same is true of clear air turbulence monitoring ahead of airplanes, especially supersonic and hypersonic vehicles.
ALL of these methods will require stages of vibration isolation to get many orders of magnitude less noisy baselines for measurement. I expect that will have a direct impact on atomic scale computing devices, quantum devices, mixed electron photon computing devices and sensors of all sorts.
Richard Collins, The Internet Foundation
Shieh-Kung Huang One other thing. Your method seems to be almost identical to machine learning. The advantage of following machine learning methods is they make use of hardware acceleration for speed in following real time changes needed for picosecond resolution control systems and energy harvesting methods.