The factors that affect the stability of the sensor are those two

The characteristics of a sensor refer to the general term for the properties that are unique to the sensor. The input-output characteristics of the sensor are its basic characteristics, and when the sensor is generally studied as a two-terminal network, the input-output characteristics are the external characteristics of the two-terminal network, that is, the correspondence between the input and the output. Since the state of the input action (static and dynamic) is different, the input-output characteristics expressed by the same j sensors are also different, so there are static characteristics and dynamic characteristics.

Since the internal parameters of different sensors are different, the static and dynamic characteristics also exhibit different characteristics and have different effects on the measurement results. Therefore, starting from the analysis of the external characteristics of the sensor, it is important to analyze the working principle, the relationship between the input-output characteristics and the internal parameters, the causes and rules of errors, and the range relationship. This chapter focuses on the input-output characteristics from both static and dynamic perspectives.

Static properties

The static characteristics of a sensor refer to the correlation between the output and input of the sensor for the static input signal. Because the input quantity and the output quantity are independent of time, the relationship between them, i.e., the static characteristics of the sensor, can be described by an algebraic equation without time variables, or by drawing a characteristic curve with the input quantity as the abscissa and the corresponding output quantity as the ordinate. The main parameters that characterize the static characteristics of a sensor are:

linearity, sensitivity, resolution, hysteresis, etc.

Static characteristics refer to the input-output characteristics of a sensor when the input quantity is constant or changes very slowly. Dynamic characteristics refer to the input-output characteristics of a sensor as the input changes over time.

The main indicators to measure the static characteristics of the sensor are linearity, hysteresis, repeatability, resolution, stability, temperature stability, and various anti-interference capabilities. Static characteristic curves can be obtained from actual testing, and after obtaining them, it can be said that the problem has been solved. However, for the convenience of calibration and data processing, it is desirable to obtain a linear relationship, and various methods, including computer hardware and software compensation, can be used to linearize the relationship.

Generally speaking, these methods are more complex, so when the nonlinearity error is not too large, the linearization method is always used to linearize.

Dynamic properties

The so-called dynamic characteristics refer to the characteristics of the output of the sensor when the input changes. In practice, the dynamic characteristics of a sensor are often expressed in terms of its response to some standard input signal. This is because the sensor's response to the standard input signal is easy to find experimentally, and there is a certain relationship between its response to the standard input signal and its response to any input signal.

The most commonly used standard input signals are step signal and sinusoidal signal, so the dynamic characteristics of the sensor are also expressed in step response and frequency response.

It's a grating sensor. First of all, the stability is whether the elastic modulus of the quartz material itself is stable in the process of vibration, you have to prove through experiments, we have proved that it is unstable, and the calibration interval of the sensor is very short. The second is the encapsulation material, because the coefficient of thermal expansion of quartz is very small, it is difficult to encapsulate with other materials, you can see the relevant information.

If the sensor itself is unstable, let's not talk about accuracy. There are too many academic fools now, so be careful not to be fooled. Xi'an Shiyou University is a leader in this research and has won the second prize of the National Science and Technology Invention Award, you can consult them.

Linearity, sensitivity, hysteresis, repeatability, drift, etc.

1. Linearity: refers to the degree to which the actual relationship curve between the output and the input of the sensor deviates from the fitting straight line. Defined as the ratio of the maximum deviation between the actual characteristic curve and the fitted line over the full scale range to the full-scale output.

2. Sensitivity: Sensitivity is an important indicator of the static characteristics of the sensor. It is defined as the ratio of the increment of the output to the corresponding increment of the input that caused the increment. S is used to indicate sensitivity.

3. Hysteresis: The phenomenon that the input and output characteristic curves of the sensor do not coincide during the change of the input amount from small to large (positive stroke) and input quantity from large to small (reverse stroke) becomes hysteresis. For the input signal of the same size, the positive and negative 4 of the sensor and the stroke output signal are not equal, and this difference is called the hysteresis difference.

5. Repeatability: Repeatability refers to the degree of inconsistency of the characteristic curve obtained when the input quantity of the sensor changes continuously in the full scale in the same direction.

6. Drift: The drift of the sensor refers to the change of the output of the sensor with time under the condition that the input amount remains unchanged, which is called drift. There are two reasons for drift: one is the structural parameters of the sensor itself; The second is the surrounding environment (such as temperature, humidity, etc.).

Hello dear, it is a pleasure to serve you. According to your description, the stability of the sensor can usually be divided into two types: short-term stability and long-term stability.

Short-term stability refers to how the measurement results of a sensor change over a time frame. This time frame is generally shorter, such as a few seconds or minutes. Due to the influence of temperature, humidity, voltage and other factors, the measurement results of the sensor may fluctuate to a certain extent.

A better sensor should have less short-term stability, i.e., the results of multiple consecutive measurements should have a small differential hypoosmotic deficiency in the same environment. Long-term stability refers to the change in the measurement results of the sensor over a long period of time. During long-term use, the sensor may be affected by mechanical wear, aging, corrosion and other factors, resulting in deviations in the measurement results.

A good sensor should have good long-term stability, that is, the deviation of the measurement results should be as small as possible during long-term use. Therefore, when selecting and using sensors, it is necessary to consider both short-term and long-term stability to ensure that the sensor can accurately measure and maintain stable performance.

There are two basic characteristics of a sensor:

1.Static characteristics: linearity, sensitivity, repeatability, hysteresis, stability, drift, static error, etc.

2.Dynamic properties

Step response: maximum overshoot, hysteresis time, rise time, peak orange closure time, response time, etc.

Frequency response: circular crack frequency characteristics, amplitude-frequency characteristics, phase frequency characteristics, etc.

The dynamic characteristics of the sensor depend first and foremost on the sensor itself. Sensors are generally made up of several steps. These links may be analog or digital.

The simulation link can be divided into contact link and non-contact link. The former refers to the transmission of information in the form of rigid contact, while the latter does not. Due to their different dynamic characteristics and their research methods, it is necessary to separate the contact link from the simulation link and put it in a separate category.

In this way, the components of the sensor are divided into the following three categories: contact link; Simulation session; Digital link. The dynamic characteristics of a sensor composed of a certain link depend on the dynamic characteristics of such a link.

Some sensors have several links, so it is necessary to study the dynamic characteristics of these links separately, and the main actor determines the dynamic characteristics of the entire sensor.