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Analyze the Reasons of Measurement Errors in Vision Measuring Machine, and Try to Avoid Them


The Vision Measuring Machine is a new type of precision measuring instrument based on image analysis and recognition. It is widely used due to its strong universality, large measurement range, high efficiency, high accuracy, good performance, and strong real-time capabilities. However, even precision measuring instruments like Vision Measuring Machines can produce errors during using. Therefore, instead of worrying too much, it is important to analyze the reasons behind the errors and avoid them.

The reasons for measurement errors in Vision Measuring Machines are multifaceted and can occur during various stages of the instrument's design, manufacture, and use. They can be divided into design errors, manufacturing errors, and operational errors.

I. Design Errors

Errors may cause by CCD camera distortion and measurement method differences fall under the category of design errors in Vision Measuring Machines.

1. Due to reasons such as camera manufacturing and processes, refraction errors of incident light passing through various lenses, and CCD lattice position errors, the actual optical system has nonlinear geometric distortion, resulting in various types of geometric distortion between target image points and theoretical image points, such as radial distortion, eccentric distortion, and prism distortion.

Using high-quality Zoom Lens can reduce the impact of distortion errors. However, in precision measurement, the influence of distortion on the measurement results needs to be considered and corrected.


2. Measurement method differences refer to recognition and quantification errors caused by different image processing techniques.

During image processing, edge extraction is required, and there are many different methods for edge extraction in digital image processing. Choosing different extraction methods can cause significant changes in the edge position of the same measured part, thus affecting the final measurement result.

For example, when measuring the radius and center of a circular workpiece, changes in the contour of the circle will cause corresponding changes in the radius value and center position.

Therefore, it is important to note that the image processing algorithm has a significant impact on the measurement accuracy of the instrument and is a focal point of concern in image measurement.

II. Manufacturing Errors

Errors caused by guiding mechanisms and installation errors fall under the category of manufacturing errors in Vision Measuring Machines.

1. The error caused by guiding mechanisms in Vision Measuring Machines is mainly the linear motion positioning error in the mechanism error. Vision Measuring Machines are orthogonal coordinate measuring instruments. Orthogonal coordinate measuring instruments have three mutually perpendicular axis lines: X, Y, and Z. Three moving parts move along these three axis lines to make the CCD perform three-dimensional linear motion relative to the measured workpiece.

Using high-quality motion guiding mechanisms can reduce the impact of such errors.


2. Installation errors mainly refer to the relative relationship between the camera and the worktable. When the measuring platform and the lens of the CCD camera have a certain angle H, according to geometric knowledge, the error calculation formula can be obtained as follows: D=L(1-cosH).

If the leveling performance of the measuring platform and the installation of the CCD camera are excellent, and their angle is within a certain range, this error is very small.

III. Operational Errors

Errors caused by changes in measurement environment and conditions (such as temperature changes, voltage fluctuations, changes in lighting conditions, and mechanism wear) and dynamic errors fall under the category of operational errors in optical Vision Measuring Machines. Improving measurement operating conditions can effectively reduce such errors.

1. Temperature changes can cause changes in the size, shape, mutual position relationship, and some important characteristic parameters of the components of the image measuring instrument, thereby affecting the instrument's accuracy.

Temperature changes can also cause changes in electrical parameters and instrument characteristics, causing temperature sensitivity drift and temperature zero drift.


2. Changes in voltage and lighting conditions can affect the brightness of the upper and lower light sources of the image measuring instrument, causing uneven system illumination, leaving shadows when collecting image edges, and causing errors in edge extraction.


3. Wear causes dimensional, shape, and position errors in the components of the image measuring instrument, increases clearance, and reduces the stability of the instrument's working accuracy. 


The above is an analysis of measurement errors in Vision Measuring Machines. Understanding the reasons behind the errors and taking corresponding measures can effectively avoid and reduce errors, resulting in more accurate measurement data.

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