In the process of glass thermometer calibration, accurate data processing and scientific uncertainty evaluation are key links in evaluating the quality of calibration results.
Data processing first needs to ensure the accuracy and integrity of the data. When reading the thermometer readings, it should be carried out strictly in accordance with the operating procedures to avoid reading errors. For the data of multiple measurements, statistical methods are used for processing. For example, calculate the arithmetic mean as the best estimated value of the measurement result, and evaluate the degree of dispersion of the measurement data by calculating the standard deviation. During the processing, abnormal data should be judged and eliminated. Abnormal data may be caused by accidental factors or equipment failures during the measurement process. Common methods for judging abnormal data include the Grubbs criterion, etc. Once abnormal data is found, the measurement process needs to be checked, and the measurement is carried out again after troubleshooting.
Uncertainty evaluation is a quantitative characterization of the credibility of the measurement result. The sources of uncertainty in glass thermometer calibration mainly include the uncertainty of the standard thermometer, the uncertainty introduced by the temperature fluctuation of the constant temperature bath, the uncertainty introduced by the reading error, etc. For each source of uncertainty, it is necessary to carry out quantitative calculations through reasonable methods. For example, the uncertainty of the standard thermometer can be directly obtained according to the information provided in its calibration certificate; the uncertainty introduced by the temperature fluctuation of the constant temperature bath can be evaluated by measuring the temperature of the constant temperature bath multiple times and calculating its standard deviation; the uncertainty introduced by the reading error can be estimated according to the reading repeatability of the operator and the minimum scale value of the thermometer. Synthesize each uncertainty component according to certain mathematical methods to obtain the combined uncertainty, and then determine the expanded uncertainty as needed. Through uncertainty evaluation, users can clearly understand the reliability range of the calibration results and provide a scientific basis for subsequent measurement applications.
