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The static characteristics of sensors refer to the relationship between the static input signal and the output and input of the sensor. Because the input and output are all independent of time, the relationship between them, that is, the static characteristic of the sensor can be used as an algebraic equation without time variables, or as a horizontal coordinate with the input quantity, and describes the characteristic curve drawn with its corresponding output as a longitudinal coordinate. The main parameters that characterize the static characteristics of sensors include linearity, sensitivity, hysteresis, repeatability, drift and so on.
The so-called dynamic characteristic refers to the output characteristics of the sensor when it changes. In practice, the dynamic characteristics of sensors are often expressed in response to some standard input signals. This is because the sensor's response to the standard input signal is easily obtained by the experimental method, and there is a certain relationship between the response of the standard input signal and its response to any input signal, and it is often known that the former can be presumed to be the latter. The most commonly used standard input signals are two kinds of step signals and sinusoidal signals, so the dynamic characteristics of sensors are also represented by step response and frequency response.
Usually, the output of the sensor's static characteristic is a bar curve instead of a straight line. In practical work, in order to make the instrument have uniform scale reading, a fitting line is often used to approximate the actual characteristic curve and the linearity (the nonlinear error) is a performance index of the approximate degree.
There are many methods for the selection of fitting lines. For example, the theoretical line connected by the zero input and the full range output point is used as a fitting line, or a straight line is used as the least theoretical line, which is the least square of the deviations of the points on the characteristic curve, and the fitting line is called the least square method to fit the straight line.
Sensitivity refers to the ratio of the output of the sensor under steady state operation to the ratio of input y to X. It is the slope of the output of an input characteristic curve. If there is a linear relationship between the output and input of the sensor, the sensitivity S is a constant. Otherwise, it will change with the change of the input. The dimension of sensitivity is the ratio of output to the dimension of input. For example, when a displacement sensor changes the output voltage to 200mV when the displacement changes 1mm, its sensitivity should be expressed as 200mV/mm. When the output of the sensor is equal to the dimension of the input, sensitivity can be understood as magnification. Higher sensitivity can be obtained and higher measurement accuracy can be obtained. However, the higher the sensitivity, the narrower the measuring range is, the worse the stability is.
Resolution refers to the ability of a sensor to sense the smallest change being measured. That is to say, if the input quantity changes slowly from a non zero value. When the input change value does not exceed a certain value, the output of the sensor will not change, that is, the sensor can not distinguish the change of input quantity. The output will change only when the amount of input exceeds resolution.
Usually, the resolution of the sensors in the full range is different, so the maximum variation in the input amount that can produce the step change in the full range is used as an indicator of the resolution. If the above index is expressed in percentage of full scale, it is called resolution. The resolution is negatively correlated with the stability of the sensor.
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