In scientific experiments and daily work, we often hear the term "precise measurement", but in reality, no matter how careful we are, there is a certain margin of error for each measurement. This error is called "measurement uncertainty", which is an important concept for characterizing the accuracy of measured values, and is of great significance for the reliability and reliability of engineering design, product development, and scientific research results.
From delicate mechanical equipment to measurements on large aerospace vehicles, uncertainty is quietly affecting the accuracy of results. In this article, we will demystify measurement uncertainty and explore its role in scientific research and work, helping us to properly evaluate measurement results.
When making measurements, it is inevitable that the measurement results will be inaccurate due to some factors, such as the accuracy of the instrument itself, the instability of human operation, the influence of the environment, etc., which indicates the uncertainty of the measured value is the measurement uncertainty.
For example, let's say you want to measure the length of a piece of paper with a scale, and the actual length of the paper is 10mm. However, due to the limited accuracy of the scale, you may not be able to accurately see the alignment between the edges of the paper and the scale. In this way, your measurement could be 98mm or 102mm, instead of 10mm, which is completely accurate.
In this example, the uncertainty of the measurement** is compared to factors such as the accuracy of the scale, your ability to visualize, and so on. Therefore, we cannot simply say that the length of this paper is 10mm, but we need to attach an uncertainty, such as (10 0.).2) mm, which means that the range of the measurement result is 02mm。
Measurement uncertainty is an important indicator of the reliability and accuracy of the measurement results, it tells us the possible margin of error in the measurement results, and helps us better understand and interpret the experimental or measurement data.
When making measurements, we are often not completely sure of the accuracy of the measurement results, so we need to pay attention to how much error is possible. To quantify this uncertainty, we need to be clear about two numbers: 1The range of error can also be said to be the upper and lower limits of the measurement results;2.Confidence probability, which is used to illustrate how sure we are of the "true value" within this range.
Typically, we estimate the total measurement error using a range containing the factor k=2 while giving a confidence probability of about 95%. This allows us to describe the uncertainty of the measurement results with the smallest margin of error and a high degree of confidence, helping us to better understand the measurement results and evaluate their reliability.
The following is the certificate obtained by the 3D scanner after calibration in the Scancan calibration center, using the 3D scanner to perform multiple repeated measurements on the standard, combined with the certificate of the standard plate and the calibration environmental conditions and other factors, and finally calculated the extended uncertainty of u=0010mm，k=2。
There are many factors that can contribute to the increase in measurement uncertainty during the measurement process. One is the ability of the instrument itself to measure the object, such as resolution, accuracy, stability and calibration statusSecond, changes in environmental factors, such as temperature, humidity, noise, etc., will affect the measurement results;The third is human factors, such as human operation skills and visual judgment limitations, which will also cause errors in measurement results.
While measurement uncertainty cannot be eliminated entirely, there are a few things we can do to reduce it.
Choosing the right measurement method: Choosing the right measurement method is key to reducing uncertainty. Select the appropriate instrument and measurement method for different measurement purposes, as well as the size, shape, and material properties of the measurement object.
Instrument calibration and maintenance: Ensure that the equipment is calibrated and maintained regularly to maintain its optimal performance.
Get the most out of your software: High-quality data processing and analysis software can help reduce errors in the data processing process.
Improve operational skills: Train operators to improve their skills and experience and reduce human error in operation.
Environmental control: control the measurement environment, such as humidity, temperature, etc., to avoid the influence of environmental factors on the measurement results.
Scantech's 3D scanner can greatly reduce the measurement uncertainty and meet the 3D measurement needs of most application scenarios.
1.High accuracy and resolution
The ability of 3D scanners to provide high-resolution images and data means that they can capture even the smallest details and the results have little error, helping to reduce measurement uncertainty.
2.Non-contact measurement
3D scanners typically use non-contact measurement to measure fragile or complex surfaces, eliminating the errors that can occur with physical contact.
3.Get data fast
Compared to conventional measuring equipment, 3D scanners can quickly acquire data on the surface of the object being measured, which helps to improve efficiency and reduce errors that can occur during the waiting process of the measurement process.
4.Advanced data processing capabilities
3D scanners are often equipped with advanced data processing software that can automatically process and analyze the data, thereby reducing the uncertainty that can arise from manual data processing.
5.Flexible and adaptable
3D scanners are usually highly adaptable to materials and can flexibly measure objects of different sizes and materials.
Measurement uncertainty is a quantitative index to measure the accuracy of measurement results, and the measurement uncertainty is used instead of error to represent the measurement results, which is easy to understand and evaluate, and has strong rationality and practicability. Xi and understand the relevant knowledge of measurement uncertainty is of positive significance for improving the measurement level.
In the process of quantifying the measurement uncertainty, the measurement uncertainty can be continuously reduced by selecting the appropriate measuring instrument, the measurement environmental conditions and the operation skills, etc., and the accuracy of the measurement and the reliability of the measurement results can be improved.
Learn more about 3D scanners.