Relationship between standard weight error and uncertainty

Error and uncertainty not only have different definitions, but also different concepts. The two cannot be confused, but they are closely related. Error analysis is still the theoretical basis of measurement uncertainty evaluation, and it is even more inseparable when estimating type B components. Open error analysis, the concept of uncertainty is the application and expansion of error theory.

The error and uncertainty of standard weights are one of the important issues that metrology testers care about, and they are also the basic propositions studied in metrology. It is directly related to the reliability of the measurement results and the accuracy of the national value. The same is true in quality measurement, which is divided into four aspects as follows:

The relationship between standard weight error and uncertainty

1. Error

In most cases, it refers to the measurement error, and its traditional definition is the difference between the measurement result and the measured true value. Usually can be divided into two categories: systematic errors and accidental errors. Since in most cases, the true value is unknown, the true error cannot be known either. We only seek a good approximation of the truth value under certain conditions, and call it the agreed truth value. But this good value is only relative to a specific condition. Actual conditions and true values are constantly changing, so the measurement results will also change within a certain range, not to mention the measurement methods are not perfect. At present, measurement testers at home and abroad tend to use measurement uncertainty to characterize the range of measurement results.

2. Definition of measurement uncertainty

Characterize the evaluation of the range of the measured true value. It gives the interval in which the true value may fall according to a certain confidence probability. But it is not specific

The true error, it only quantitatively expresses the part of the error range that cannot be corrected in the form of parameters. It comes from the imperfect correction of accidental effects and system effects. It is used to characterize the dispersion parameter of the measured value that is reasonably assigned. Uncertainty can be divided into type A scoring amount and type scoring component according to its obtaining method. Type A evaluation component is the uncertainty evaluation made by statistical analysis of observation series, also called experimental standard uncertainty or standard deviation. The category B evaluation component is estimated based on experience or other information, and it is assumed that there is an approximate "standard deviation" represented by the uncertainty (component). The (total) synthetic uncertainty in the measurement process may contain the above two types of components at the same time.