Development and Application of Standard Device for Calibrating Steel Measuring Tape Based on Machine Vision

Abstract

Aiming to address the disadvantages of the low automation degree of the traditional steel measuring tape verification device, as well as the high labor intensity of metrologists, high time costs, and low measurement accuracy, this paper develops a new automatic steel measuring tape calibration device based on machine vision technology. In this study, the key components, such as the tape-winding mechanism, machine vision system, force measuring device, and tape-retracting device, were designed. Three different scribed line identification and location algorithms, processing the longest line, the closest to the starting line, the highest line, etc., were designed to adapt to different types of steel measuring tape. Lastly, indication error and measurement repeatability tests were carried out. The results showed that the standard device can carry out the verification and calibration of steel measuring tape, and the maximum repeatability of the indication error of the test objects was 0.025 mm, 0.038 mm, and 0.030 mm, respectively, and the indication error of each object was within the allowable error limits. The uncertainty evaluation of the indication error of each test object was 0.16 mm, 0.54 mm, 0.78 mm, which was not more than one third of the maximum permissible error value. Hence, the measuring principle, method, and procedure of the calibration device are shown to be scientific and feasible.

Design and Experimentation of a Residual-Input Tube-End Cutting System for Plasma Bags Based on Machine Vision

“…After the coordinate system was established, we used the floating coordinate method to design and analyze it. The endpoint position of the end input tube was point A, and its position in the global coordinate system [X 1 , Y 1 , Z 1 ] was calculated using Equation (1), where D is the direction cosine matrix C A A 1 of the relative coordinate system with respect to the global coordinate system; u 0 is the position of the input tube endpoint A in the relative coordinate system before deformation; A1 x 1 1 , y 1 1 , z 1 1 is the position of the deformed input tube endpoint in the relative coordinate system, as shown in Figure 3; u f is the deformation displacement of the input tube; and R is the position of point A when the input tube is undeformed in the global coordinate system. We then differentiated Equation ( 1) to obtain the motion velocity of point A, as shown in Equation (3), and differentiated Equation (3) again to obtain the motion acceleration of point A, as shown in Equation ( 4).…”

“…Based on machine vision, processing equipment has been widely used, providing a new approach for accurate identification of the cutting position of the input tube of the plasma bag. Peng Wang et al [1] addressed the problem of inaccurate positioning of traditional steel tapes by designing an automatic calibration device for steel tapes, simplifying the recognition process with a mechanical structure, and designing three different recognition algorithms based on the pictures of different types of tapes to adapt to different types of steel tapes. The errors of the three algorithms were within the allowable range after testing.…”

Study on high-speed wire diameter measurement based on improved Zernike moment

“…If the product quality is found to be unqualified, due to the high speed of its production, a large number of defective products will be produced, so the use of non-contact real-time measurement is particularly important [1][2] . As a common method of non-contact measurement, vision technology has a wide range of applications in industrial dimensional measurement [3][4] , and its edge extraction technology is very suitable for wire diameter identification. Pixel-level edge detection algorithms are currently the most widely used, and the commonly used ones are Sobel operator, Canny operator, Laplacian operator, etc [5][6] .…”

Research on the Measurement Technology of Rotational Inertia of Rigid Body Based on the Principles of Monocular Vision and Torsion Pendulum

“…Vision measurement technology utilizes high-precision industrial cameras to capture images of a measured object and obtains the dimensional parameters of the object through the object–image relationship of the imaging system. When combined with artificial intelligence algorithms, it forms machine vision technology, which plays an irreplaceable role in an increasing number of dimensional measurement applications [ 31 , 32 , 33 , 34 ]. In this paper, monocular vision technology is introduced into the measurement of rigid bodies’ rotational inertia and is used to realize the real-time recording of the torsion vibration angle displacement and to obtain the torsion pendulum curve.…”