Measurement Accuracy and Calibration Method

Abstract: Information on measurement accuracy and calibration methods is provided by excellent flowmeter and flowmeter manufacturers and quotation manufacturers. The accuracy that can be achieved by measurement is an important indicator for selecting an instrument. This article describes in detail the methods of error generation, calculation and calibration under several different situations. Hope it will be helpful for you to choose the right measuring instrument. 1. Determination of measurement error. More flowmeter manufacturers choose models and price quotations. You are welcome to inquire. The following is the details of the measurement accuracy and calibration methods. The accuracy that can be achieved by measurement is an important indicator for selecting an instrument. This article describes in detail the methods of error generation, calculation and calibration under several different situations. Hope it will be helpful for you to choose the right measuring instrument. First, the definition of measurement error Measurement error is the difference between the measurement result minus the true value of the measured value, referred to as error. Because the true value (also known as the theoretical value) cannot be obtained accurately, the conventional true value is actually used. The conventional true value needs to be characterized by the measurement uncertainty, so the measurement error cannot be obtained accurately. Measurement uncertainty: It indicates the dispersion of the value reasonably assigned to the measurand, which is related to the degree of people's understanding of the measurand, and is an interval obtained through analysis and evaluation. Measurement error: It is the difference that indicates that the measurement result deviates from the true value, which exists objectively but cannot be determined by people. For example: the measurement result may be very close to the true value (that is, the error is small), but due to lack of knowledge, the value assigned by people falls within a larger area (that is, the measurement uncertainty is large); However, due to insufficient analytical estimation, the given uncertainty is small. Therefore, various influencing factors should be fully considered when evaluating the measurement uncertainty, and the necessary verification should be carried out for the evaluation of the uncertainty. Second, the 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 algebraic and systematic errors of systematic error and random error: The measurement error caused by the inherent error of the measurement tool (or measurement instrument) itself, the defect of the measurement principle or the theory of the measurement method, the experimental operation and the restriction of the psychological and physiological conditions of the experimenter is called the systematic error. The characteristic of systematic error is in Under the same measurement conditions, the measurement results obtained by repeated measurement are always too large or too small, and the error value is constant or changes according to a certain rule. The method of reducing the systematic error can usually change the measurement tool or measurement method, and can also consider the correction of the measurement results. Value. Random error: Random error is also called accidental error. Even if the systematic error is completely eliminated, the same measurement object is repeatedly measured many times, and the measurement will still occur due to the interference of various accidental and unpredictable uncertain factors. Error, called random error. Random error is characterized by repeated measurement of the same measurement object, and the error of the obtained measurement result shows irregular fluctuations, which may be positive (the measurement result is too large) or negative (the measurement result is too large). However, the distribution of errors obeys the statistical law, showing the following three characteristics: unimodal, that is, the error is smaller than the error is larger; symmetry, that is, the positive error and the negative error The probability is equal; bounded, that is, the probability of a large error is almost zero. 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. 3. Precision, precision If the random error of the measurement 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 and good stability. , therefore, the size of the measurement accidental error reflects the precision of the measurement. According to the error theory, when the number of measurements increases infinitely, the random error can be made to tend to zero, and the obtained measurement result deviates from the true value.——The measurement accuracy will fundamentally depend on the size of the systematic error, so the size of the systematic error reflects the possible accuracy of the measurement. Accuracy is the general term for the accuracy and precision of the measurement. It may be mainly systematic error, or it may be mainly random error. Of course, the influence of both on measurement accuracy cannot be ignored. In some measuring instruments, the concept of commonly used accuracy actually includes both systematic error and random error. In one aspect, for example, commonly used instruments are often divided into instrument grades by accuracy. Instrument accuracy is referred to as accuracy, also known as accuracy. Accuracy and error can be said to be twin brothers. Because of the existence of error, there is the concept of accuracy. In short, the accuracy of the instrument is the accuracy of the measurement value of the instrument close to the true value, usually expressed in relative percentage error (also called relative reduced error).

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