How to choose the measurement accuracy of instruments

In daily work, different error calibration methods have different actual measurement accuracy for different measurement values. When choosing, we should analyze the measurement situation and the allowable error of the instrument at the measurement point. It is not necessarily the case that low-grade instruments have the best measurement effect. We should choose the appropriate instrument and range according to the specific situation to minimize the measurement error. Therefore, what we are going to talk about today is how to choose the measurement accuracy of instruments. Definition

        of measurement error
        Measurement error is the difference between the measurement result and the true value of the measured value, referred to as error. Because the true value cannot be accurately obtained, the agreed true value is actually used. The agreed true value needs to be characterized by the measurement uncertainty to characterize its range, so the measurement error cannot actually be accurately obtained. Measurement uncertainty: indicates the dispersion of the value reasonably assigned to the measured value. It is related to people's understanding of the measured value and is an interval obtained through analysis and evaluation.
　　Measurement error: It is the difference indicating that the measurement result deviates from the true value. It exists objectively but people cannot determine it. The measurement result may be very close to the true value, but due to insufficient understanding, the value assigned by people falls within a larger area; it may also be that the actual measurement error is large, but due to insufficient analysis and estimation, the uncertainty given is too small. Therefore, when evaluating the measurement uncertainty, various influencing factors should be fully considered, and the uncertainty evaluation should be verified as necessary.

        Generation of Errors
　　Errors are divided into random errors and systematic errors. Errors can be expressed as: error = measurement result - true value = random error + systematic error. Therefore, any error can be decomposed into the algebraic sum of systematic error and random error.
　　Systematic error: The measurement error caused by the inherent error of the measuring tool (or measuring instrument), the defects of the measurement principle or the measurement method itself, the experimental operation and the psychological and physiological conditions of the experimenter are called systematic errors.
　　Random error: Random error is also called accidental error. Even in the ideal case of completely eliminating the systematic error, repeated measurements of the same measurement object will still cause measurement errors due to various accidental and unpredictable uncertain factors, which are called random errors. From the distribution law of random errors, it can be seen that increasing the number of measurements and processing the measurement results according to statistical theory can reduce random errors.

        Precision, Accuracy and Accuracy
　　If the same measuring tool and method are used for multiple measurements under the same conditions, if the random error of the measured value is small, that is, the fluctuation of each measurement result is small, it means that the measurement repeatability is good, which is called good measurement precision or good stability. Therefore, the size of the accidental measurement error reflects the precision of the measurement.
　　Accuracy is a general term for the accuracy and precision of the measurement. In actual measurement, the main factor affecting the accuracy may be the systematic error or the random error. Of course, it is also possible that the influence of both on the measurement accuracy cannot be ignored. In some measuring instruments, the concept of commonly used accuracy actually includes two aspects: systematic error and random error. For example, commonly used instruments often divide the instrument grades according to accuracy.
　　Instrument accuracy is referred to as precision, also known as accuracy. The accuracy and error of digital pressure gauges can be said to be twin brothers, because there is an error, there is the concept of accuracy. In short, instrument accuracy is the accuracy of the instrument measurement value close to the true value, usually expressed as relative percentage error (also called relative reduced error).

　　In the actual application process, the range and accuracy of the instrument should be selected according to the actual situation of the measurement. It is not necessarily the case that the instrument with a small accuracy level will have the best measurement effect. Taking the application of multimeter as an example, the error caused by measuring the same voltage with multimeters of different accuracy. Comparing △X1 and △X2, it can be seen that: although the accuracy of the first meter is higher than that of the second meter, the error caused by measuring with the first meter is larger than that of measuring with the second meter. Therefore, it can be seen that when selecting an instrument, the higher the accuracy, the better. It is also necessary to select the appropriate range. Only by selecting the range correctly can the potential accuracy of the multimeter be brought into play.
　　How to choose the measurement accuracy of instruments and meters Explosion-proof electric contact pressure gauge-the above four points have been described for this problem. I hope that seeing these selection methods and definitions can help you use them in your daily work.