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The pipeline robot will encounter complex conditions of turning, obstacles and pipe diameter changes when it works. Therefore, cornering performance, obstacle crossing performance, and diameter changing ability are important indicators of the pipeline robot performance. A multi-axis differential adaptive pipeline robot is designed. The multi-axis differential mechanism is used to realize the smooth turning of the robot. The pre-tightening and reducing mechanism is used to achieve the obstacle crossing of the robot and the ability to adapt to different pipe diameters. The overall structure of the pipeline robot, the transmission mechanism, and the pre-tightening and reducing mechanism are introduced. The kinematics model of the robot is studied when it crosses obstacles. Using the maximum height of the pipeline robot passing through obstacles as an indicator, an equation of the pipeline robot obstacle crossing is established. The ADAMS software is used to simulate the kinematics of the turning process of the pipeline robot. Through the simulation experiments, the following conclusions are obtained: (1) The larger the adhesion coefficient between the pipe wall and the wheel, the stronger the obstacle crossing ability of the pipeline robot. The larger the diameter of the wheel, the stronger the ability to overcome obstacles. (2) By tracking the changes in the angular velocity of the three driving wheels, it is shown that the pipeline robot can pass through the curve smoothly and has anti-motion interference performance.

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Aiming to solve the problems of identifying the over-brightness and over-dark parts in the reflected light wear debris image, this paper proposed a new OLVF (on-line visual ferrgraph) reflected light wear debris segmentation algorithm. If the wear debris image is bright and dark, the morphological black-hat operation is used to eliminate these interferences. Then the H-minima transform is applied to corrected image local extreme value interference and the threshold is obtain through Otsu algorithm. The watershed algorithm is adopted to separate over-bright and over-dark wear debris. Eventually the morphological dilate corrosion of opening and closing reconstruction is applied to filled holes and connected wear debris profile. On the basis of the above-mentioned method, the OLVF reflected light wear debris are accurate shape and continuous profile in the final result. Compared with other wear debris divide algorithms, the proposed method effectively suppresses the influence of reflected light, and better retain the information of wear debris image. At the same time, the signal-to-noise ratio is 12dB higher than others at the maximum, and the root mean square error is reduced by 0.051 at the maximum.

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