On-machine measurement method for the geometric error of shafts with a large ratio of length to diameter

Liu, Yunlong; Li, Guochao; Zhou, Honggen; Xie, Zhancheng; Feng, Feng; Wen, Guangwu

doi:10.1016/j.measurement.2021.109194

Cited by 21 publications

(6 citation statements)

References 19 publications

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“…Che J K et al [13] developed a method to measure the diameter of the workpiece during turning in real-time without stopping the lathe, using a visual monitoring method. Liu Y et al [14] proposed a non-contact measurement method based on the theory of spatially resolved geometry by combining a line laser measuring instrument and a laser displacement sensor to achieve the measurement of shape and position tolerances of shafts.…”

Section: Introductionmentioning

confidence: 99%

Machine vision-based measurement of air compressor crankshaft journal dimensions

Xi,

Ruan,

Liu

2023

Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023)

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For the problems of slow speed, low efficiency, and labor intensity of manual measurement of crankshaft structure size of air compressor, a machine vision-based method for measuring crankshaft size of air compressor was proposed. Firstly, a bilateral retention filter was used to filter the grayscale image to ensure the crankshaft edge while smoothing the image. Then the smoothed image was binarized by an automatic threshold segmentation algorithm to segment the crankshaft and the background region. Finally, the sub-pixel edge contours of the image were extracted using canny as the localization function, and the edge contours of the crankshaft were obtained after segmentation, screening, and combination. Based on the extracted contour lines, the edge line regions were drawn, and the pixel distance between the two linear regions was calculated to obtain the diameter size of the crankshaft. The experimental results show that the accuracy of the diameter dimension calculated by this algorithm can reach 99.898% compared with the measured dimension, and the error was less than 0.03mm.

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Section: Introductionmentioning

confidence: 99%

Machine vision-based measurement of air compressor crankshaft journal dimensions

Xi,

Ruan,

Liu

2023

Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023)

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“…Being the core technology of intelligent manufacturing, measurement technology based on machine vision has been widely used in the measurement of geometric accuracy of mechanical parts [ 13 , 14 , 15 , 16 , 17 ], as it has the characteristics of non-contact, non-destructive, high precision, and fast speed.…”

Section: Introductionmentioning

confidence: 99%

Precision Measurement Method of Large Shaft Diameter Based on Dual Camera System

Wang

2022

Sensors

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At present, there is a problem that the measurement accuracy and measurement range cannot be balanced in the measurement of shaft diameter by the machine vision method. In this paper, we propose a large-scale shaft diameter precision measurement method based on a dual camera measurement system. The unified world coordinate system of the two cameras is established by analyzing the dual camera imaging model and obtaining the measurement formula. In order to verify the validity of the proposed method, two black blocks in the calibration plate with a known center distance of 100 mm were measured. The mean value was 100.001 mm and the standard deviation was 0.00039 in 10 measurements. Finally, the proposed system was applied to the diameter measurement of a complexed crankshaft. The mean μ95 values of CMM and the proposed method were ±1.02 μm and ±1.07 μm, respectively, indicating that the measurement accuracy of the proposed method is roughly equal to the CMM.

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“…In measuring the form and position tolerances, the measurement methods based on laser sensors are proposed to measure the roundness and rotation errors of a rotor [13,14]. Moreover, the laser sensor was used to build the on-machine measurement system for the geometric parameters of shaft part [15,16]. As the measurement accuracy is easily disturbed by various factors using the 1D laser sensor [17], Li et al [18] proposed an error compensation method based on the least squares method and function-library compensation method to reduce the tilt error.…”

Section: Introductionmentioning

confidence: 99%

Measurement and evaluation of wheel profiles of a rail vehicle on an underfloor wheelset lathe

Liu¹,

Li²,

Hou³

et al. 2022

Meas. Sci. Technol.

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Wheel profile form directly affects the dynamic behaviour of rail vehicles. Moreover, it is an important factor to ensure the safe running of a high–speed vehicle. As off–line measurements do not provide high–efficiency and high–accuracy wheel profile measurements, we focused on on–machine measurement and evaluation for obtaining the wheel profiles of a rail vehicle in this study. By combining the wheel machining with the wheel measurement, the measurement and evaluation of radial and axial wheel profiles on the underfloor wheelset lathe were proposed. The measurement of radial wheel profile based on two laser sensors was introduced, and the corresponding error models of on–machine measurement were established. The error models were used to separate the measurement errors from the measurement data. This can improve the accuracy of measuring the radial wheel profile effectively. For measuring the axial wheel profile, an adaptive correction method of profile error was proposed to suppress the measurement error, which was the basis for obtaining an accurate equivalent conicity. By measuring radial and axial wheel profiles, polygonisation evaluation and equivalent conicity were obtained to evaluate the radial and axial dynamic behaviours of a wheelset, respectively. Finally, the measurements were applied to an underfloor wheelset lathe to verify the effectiveness of measuring wheel profiles. In this study, we not only improved working efficiency for the machine tools, but also provided a high–accuracy measurement method for the wheel profiles of rail vehicle.

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On-machine measurement method for the geometric error of shafts with a large ratio of length to diameter

Cited by 21 publications

References 19 publications

Machine vision-based measurement of air compressor crankshaft journal dimensions

Machine vision-based measurement of air compressor crankshaft journal dimensions

Precision Measurement Method of Large Shaft Diameter Based on Dual Camera System

Measurement and evaluation of wheel profiles of a rail vehicle on an underfloor wheelset lathe

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