In the robotic welding process with thick steel plates,laser vision sensors are widely used to profile the weld seam to implement automatic seam tracking.The weld seam profile extraction(WSPE)result is a crucial step ...In the robotic welding process with thick steel plates,laser vision sensors are widely used to profile the weld seam to implement automatic seam tracking.The weld seam profile extraction(WSPE)result is a crucial step for identifying the feature points of the extracted profile to guide the welding torch in real time.The visual information processing system may collapse when interference data points in the image survive during the phase of feature point identification,which results in low tracking accuracy and poor welding quality.This paper presents a visual attention featurebased method to extract the weld seam profile(WSP)from the strong arc background using clustering results.First,a binary image is obtained through the preprocessing stage.Second,all data points with a gray value 255 are clustered with the nearest neighborhood clustering algorithm.Third,a strategy is developed to discern one cluster belonging to the WSP from the appointed candidate clusters in each loop,and a scheme is proposed to extract the entire WSP using visual continuity.Compared with the previous methods the proposed method in this paper can extract more useful details of the WSP and has better stability in terms of removing the interference data.Considerable WSPE tests with butt joints and T-joints show the anti-interference ability of the proposed method,which contributes to smoothing the welding process and shows its practical value in robotic automated welding with thick steel plates.展开更多
A short survey on researching and developing status of intelligenttechnologies in modem welding manufacturing is given. According to the developing trend of advancedmanufacturing technology, a concept on intelligentiz...A short survey on researching and developing status of intelligenttechnologies in modem welding manufacturing is given. According to the developing trend of advancedmanufacturing technology, a concept on intelligentized welding manufacturing engineering (IWME), ispresented for systematization of researching and developing domains on welding automation,intelligentized welding, robotic and flexible welding and advanced welding manufacturingtechnologies. And key technologies of welding intelligent manufacturing and its developing trend inthe future are investigated.展开更多
The real-time detection of porosity in welding process is an important problem to be solved in intelligent welding manufacturing.A new on-line detection method for porosity of aluminum alloy in robotic arc welding bas...The real-time detection of porosity in welding process is an important problem to be solved in intelligent welding manufacturing.A new on-line detection method for porosity of aluminum alloy in robotic arc welding based on arc spectrum is proposed in this paper.First,k-shape and the improved k-means were used for the initial feature selection of the preprocessed arc spectrum to reduce the data dimension.Second,the secondary feature selection was carried out based on the importance of features to further reduce feature redundancy.Then,the optimal sample label library was established by combining the final characteristic parameters and the X-ray pictures of welds.Finally,an on-line detection method of porosity in gas tungsten arc welding of aluminum alloy based on light gradient boosting machine(LightGBM)was proposed.Compared with extreme gradient boosting(XGBoost)and categorical boosting(CatBoost),this method can achieve better detection performance.The new method proposed in this paper can be used to detect other welding defects,which is helpful to the development of intelligent welding technology.展开更多
3D reconstruction of worn parts is the foundation for remanufacturing system based on robotic arc welding, because it can provide 3D geometric information for robot task plan. In this investigation, a novel 3D reconst...3D reconstruction of worn parts is the foundation for remanufacturing system based on robotic arc welding, because it can provide 3D geometric information for robot task plan. In this investigation, a novel 3D reconstruction system based on linear structured light vision sensing is developed. This system hardware consists of a MTC368-CB CCD camera, a MLH-645 laser projector and a DH-CG300 image grabbing card. This system software is developed to control the image data capture. In order to reconstruct the 3D geometric information from the captured image, a two steps rapid calibration algorithm is proposed. The 3D reconstruction experiment shows a satisfactory result.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.51575349,51665037,51575348)State Key Laboratory of Smart Manufacturing for Special Vehicles and Transmission System(Grant No.GZ2016KF002).
文摘In the robotic welding process with thick steel plates,laser vision sensors are widely used to profile the weld seam to implement automatic seam tracking.The weld seam profile extraction(WSPE)result is a crucial step for identifying the feature points of the extracted profile to guide the welding torch in real time.The visual information processing system may collapse when interference data points in the image survive during the phase of feature point identification,which results in low tracking accuracy and poor welding quality.This paper presents a visual attention featurebased method to extract the weld seam profile(WSP)from the strong arc background using clustering results.First,a binary image is obtained through the preprocessing stage.Second,all data points with a gray value 255 are clustered with the nearest neighborhood clustering algorithm.Third,a strategy is developed to discern one cluster belonging to the WSP from the appointed candidate clusters in each loop,and a scheme is proposed to extract the entire WSP using visual continuity.Compared with the previous methods the proposed method in this paper can extract more useful details of the WSP and has better stability in terms of removing the interference data.Considerable WSPE tests with butt joints and T-joints show the anti-interference ability of the proposed method,which contributes to smoothing the welding process and shows its practical value in robotic automated welding with thick steel plates.
基金Provincial Science and Technology Committee of Shanghai,China(No.021111116)Doctoral Program Foundation of Education Ministry of China(No.20020248015)
文摘A short survey on researching and developing status of intelligenttechnologies in modem welding manufacturing is given. According to the developing trend of advancedmanufacturing technology, a concept on intelligentized welding manufacturing engineering (IWME), ispresented for systematization of researching and developing domains on welding automation,intelligentized welding, robotic and flexible welding and advanced welding manufacturingtechnologies. And key technologies of welding intelligent manufacturing and its developing trend inthe future are investigated.
基金the National Natural Science Foundation of China(Nos.61873164 and 51575349)。
文摘The real-time detection of porosity in welding process is an important problem to be solved in intelligent welding manufacturing.A new on-line detection method for porosity of aluminum alloy in robotic arc welding based on arc spectrum is proposed in this paper.First,k-shape and the improved k-means were used for the initial feature selection of the preprocessed arc spectrum to reduce the data dimension.Second,the secondary feature selection was carried out based on the importance of features to further reduce feature redundancy.Then,the optimal sample label library was established by combining the final characteristic parameters and the X-ray pictures of welds.Finally,an on-line detection method of porosity in gas tungsten arc welding of aluminum alloy based on light gradient boosting machine(LightGBM)was proposed.Compared with extreme gradient boosting(XGBoost)and categorical boosting(CatBoost),this method can achieve better detection performance.The new method proposed in this paper can be used to detect other welding defects,which is helpful to the development of intelligent welding technology.
文摘3D reconstruction of worn parts is the foundation for remanufacturing system based on robotic arc welding, because it can provide 3D geometric information for robot task plan. In this investigation, a novel 3D reconstruction system based on linear structured light vision sensing is developed. This system hardware consists of a MTC368-CB CCD camera, a MLH-645 laser projector and a DH-CG300 image grabbing card. This system software is developed to control the image data capture. In order to reconstruct the 3D geometric information from the captured image, a two steps rapid calibration algorithm is proposed. The 3D reconstruction experiment shows a satisfactory result.
