Processing Sensit Field Data

Publications | Data Logger Programming

References

Sensit data

   Data Processing and Calibration document - View DPC.pdf

The "Data Processing and Calibration" document contains theory of operation, catcher information and technical information about the eroding mass sensor. Last update Feb 10, 2005.

  Movie of Owen's Dry Lake data. Animation of actual girded erosion data covering a dry lake area. Data was taken by the California Great Basin Unified Air Pollution Control District (GBAPCD). High speed internet connection preferable.

The large grid (lake bed is approximately 12mi x 23mi) of meteorological towers collecting Sensit data (one kilometer gird locations) is shown in the adjacent image.  This monumental effort undertaken by GBAPCD is the largest erosion monitoring effort ever undertaken. The project is currently on-going with remarkable success controlling saltation,  migration and decreasing airborne particulates.

Understanding Sensit raw data

Understanding Sensit data is the key to success.

Raw data - A charge is produced by the crystal as particles impact the sensor. The charge produced by the crystal charges an integrator capacitor. When the voltage across the capacitor reaches a predetermined value, the capacitor is reset. This reset pulse becomes the kinetic energy output. One pulse represents a fixed amount of kinetic energy.

Mass flux - The sensor's true response is kinetic energy.  This response has empirically been found to correlate to mass flux (r^2+0.997) by several independent researchers. The physical mechanism responsible for this correlation is unknown to date.

The dynamic range  - Consider the following; The sensor's primary output is linear response to kinetic energy. Considering the simple equation for kinetic energy as 1/2mv^2, it can be seen that particle velocity is a powerful influence. Also, mass (depicted as a sphere) varies as the cube of particle diameter (volume of a sphere as 4/3 pi r^3).

Now consider the characteristics of typical saltation. Saltating particle diameters are typically 100 microns to 1 millimeter. Particle velocities range  from 5 m/s to 50 m/s. This represents a kinetic energy dynamic range of 10^5. It is a difficult for linear electronic measurement devices to operate over a dynamic range of 10^5 without changing ranges.

The Sensit accommodates this dynamic range by increasing the maximum signal resolution through the use of time integration. This technique is  common for very sensitive measurements where the signal is comprised of individual pulses such as photon counting or radiation counting.

Near-zero data resolution is accomplished by taking a measurement of background noise. To make sure this background signal occurs often enough for a data logger to count it within its sampling period, we add a small amount of artificial background. This background signal is subtracted from the final signal. 

Maximum signal resolution is extended by the inherent nature of integration. The output format is in the form of pulses.  The largest number you record (for a typical event) is determined by length of time (i.e., integration) you count these pulses. This is set by the sampling period of the data logger. A longer integration period will naturally improve the minimum signal resolution.

This graph of Sensit response vs. mass data from a prototype real-time weighing sampler made by Charles Yates (USDA technical engineer) demonstrated the sensor's response to true mass was better than expected (r^2=0.997).

The scale-type weighing sampler used as a saltation sensor was abandon due to un-resolvable scatter caused by wind buffeting of the scale mechanism, long term drift, corrosion problems and limited sampler volume. But this rare data set was the first demonstration of the sensors ability to measure saltation.

Relationship between Sensit response vs. BSNE Catcher