Auto-zero/Auto-calibration
From Wikimization
Contents |
Motivation
In instrumentation, both in a supporting role and as a prime objective, measurements are taken that are subject to systematic errors. Routes to minimizing the effects of these errors are:
- Spend more money on the hardware. This is valid but hits areas of diminishing returns; the price rises disproportionately with respect to increased accuracy.
- Apparently, in the industrial processing industry, various measurement points are implemented and regressed to find "subspaces" that the process has to be operating on. Due to lack of experience I (RR) will not be covering that here; although others are welcome to (and replace this statement). This is apparently called "data reconciliation".
- Calibrations are done and incorporated into the instrument. This can be done by analog adjustments or written into storage mediums for subsequent use by operators or software.
- Runtime Auto-calibrations done at regular intervals. These are done at a variety of time intervals: every .01 seconds to 30 minutes. I can speak to these most directly; but I consider the "Calibrations" to be a special case.
Mathematical Formulation
Let
- a vector of some environmental or control variables that need to be estimated
- a vector of calibration points
- be the estimate of
- a vector of nominal values of uncertain parameters affecting the measurement
- Assumed constant or designed in
- be the errors in
- Assumed to vary but constant in the intervals between calibrations and real measurements
- be the results of a measurement processes attempting to measure
- where might be additive, multiplicative, or some other form.
- the reading values at the calibration points
- Subsequently will be assumed fixed for the problem realm; and dropped from notation
- be estimates of derived from
- be a quality measure of resulting estimation; for example
- Where is allowed to vary over a domain for fixed
- The example is oversimplified as will be demonstrated below.
- is typically decomposed into a chain using
Then the problem can be formulated as:
- Given
- Find a formula or process to select so as to minimize
- The reason for the process term is that many correction schemes are feedback controlled; is never computed, internally, although it might be necessary in design or analysis.
Examples
Biochemical temperature control where multiple temperature sensors are multiplexed into a data stream and one or more channels are set aside for Auto-calibration. Expected final systems accuracies of .05 degC are needed because mammalian temperature regulation has resulting in processes and diseases that are "tuned" to particular temperatures.
- A simplified equation only evaluating one calibration channel and one reading channel
- can be either the calibration resistor or the unknown resistance of the thermistor
- is the corresponding voltage read:
- is the reading offset value, an error
- the bias voltage
- the bias resistor
- With errors
- Calibration reading
- Thermistor (real) reading.
- The problem is to optimally, an ambiguous term during design, estimate based upon and
- The direct inversion formula illustrates the utility of mathematically using the error space, . during design and analysis. The direct inversion of for naturally invokes the error space as a link to .
- Inversion for
Infrared Gas analysers with either multiple stationary filters or a rotating filter wheel. In either case the components, sensors, and physical structures are subject to significant variation.
Various forms of
- Weighted least squares of over the range of
- Minimize mode of with respect to the range of and the measurements
- Minimize the mean of with respect to the range of and the measurements
- Minimize the worst case of over the range of
- Some weighting of the error interval with respect to
Areas of optimization
Design
Runtime
Calibration usage