Yanling Xu

Research on the Real-time Tracking Information of Three-dimension Welding Seam in Robotic GTAW Process Based on Composite Sensor Technology

Aiming at the shortcomings of teaching-playback robot that can’t track the three-dimensional welding seam in real time during GTAW process, this paper designed a set of composite sensor system for tracking the three-dimensional welding seam based on visual sensor and arc sensor technology, which can effectively acquire three-dimensional welding seam information, such as clear images of seam and pool and stable arc voltage signals. The characteristic values of weld image and arc voltage signals were accurately extracted by using proper processing algorithm, and the experiments have been done to verify the precision of processing algorithms. The results demonstrate that the error is very small, which is accurate enough to meet the requirements of the subsequent real-time tracking and controlling during the welding robot GTAW process.

Autonomous Detection of Weld Seam Profiles via a Model of Saliency-Based Visual Attention for Robotic Arc Welding

This paper presents a method of autonomously detecting weld seam profiles from molten pool background in metal active gas (MAG) arc welding using a novel model of saliency-based visual attention. First, a vision sensor based on structured light is employed to capture laser stripes and molten pools simultaneously in the same frame. Second, to effectively detect the weld seam profile from molten pool background for next autonomous guidance of initial welding positions and seam tracking, a model of visual attention based on saliency is proposed. With respect to the enhanced effect of saliency, the proposed model is much better than the classic models in the field. According to the comprehensive saliency map created by the proposed model, the weld seam profile can be extracted after threshold segmentation and clustering are applied to it in turn. Third, different weld seam images are used to demonstrate the robustness of the proposed methodology and last, to evaluate the performance of the proposed method, a measure called profile extraction rate (PER) is computed, which shows that the extracted weld seam profile can basically meet the requirements of seam tracking and the guidance of welding torches.

Audio sensing and modeling of arc dynamic characteristic during pulsed Al alloy GTAW process

Purpose – The purpose of this paper is to study the relationship between arc sound signal and arc height through arc sound features of GTAW welding, which is aimed at laying foundation work for monitoring the welding penetration and quality by using the arc sound signal in the future.Design/methodology/approach – The experiment system is based on GTAW welding with acoustic sensor and signal conditioner on it. The arc sound signal was first processed by wavelet analysis and wavelet packet analysis designed in this research. Then the features of arc sound signal were extracted in time domain, frequency domain, for example, short‐term energy, AMDF, mean strength, log energy, dynamic variation intensity, short‐term zero rate and the frequency features of DCT coefficient, also the wavelet packet coefficient. Finally, a ANN (artificial neural networks) prediction model was built up to recognize different arc height through arc sound signal.Findings – The statistic features and DCT coefficient can be absolutely ...

Real‐time image capturing and processing of seam and pool during robotic welding process

Purpose – The purpose of this paper is to analyze the technology of capturing and processing weld images in real‐time, which is very important to the seam tracking and the weld quality control during the robotic gas tungsten arc welding (GTAW) process.Design/methodology/approach – By analyzing some main parameters on the effect of image capturing, a passive vision sensor for welding robot was designed in order to capture clear and steady welding images. Based on the analysis of the characteristic of the welding images, a new improved Canny algorithm was proposed to detect the edges of seam and pool, and extract the seam and pool characteristic parameters. Finally, the image processing precision was verified by the random welding experiments.Findings – It was found that the seam and pool images can be clearly acquired by using the passive vision system, and the welding image characteristic parameters were accurately extracted through processing. The experiment results show that the precision range of the i...

Research on detection of welding penetration state during robotic GTAW process based on audible arc sound

– Penetration state is one of the most important factors for judging the quality of a gas tungsten arc welding (GTAW) joint. The purpose of this paper is to identify and classify the penetration state and welding quality through the features of arc sound signal during robotic GTAW process., – This paper tried to make a foundation work to achieve on‐line monitoring of penetration state to weld pool through arc sound signal. The statistic features of arc sound under different penetration states like partial penetration, full penetration and excessive penetration were extracted and analysed, and wavelet packet analysis was used to extract frequency energy at different frequency bands. The prediction models were established by artificial neural networks based on different features combination., – The experiment results demonstrated that each feature in time and frequency domain could react the penetration behaviour, arc sound in different frequency band had different performance at different penetration states and the prediction model established by 23 features in time domain and frequency domain got the best prediction effect to recognize different penetration states and welding quality through arc sound signal., – This paper tried to make a foundation work to achieve identifying penetration state and welding quality through the features of arc sound signal during robotic GTAW process. A total of 23 features in time domain and frequency domain were extracted at different penetration states. And energy at different frequency bands was proved to be an effective factor for identifying different penetration states. Finally, a prediction model built by 23 features was proved to have the best prediction effect of welding quality.

Research on the key technology of vision sensor in robotic welding

With the popularization and development of welding robot, robotic intellectualized welding technology will be the main trend of future development. This paper mainly introduces some sensor technology of robotic welding intellectualization in Shanghai Jiao Tong University of China, especially the vision sensor, such as passive vision, active vision and active-passive vision technology, etc. All these studies are just the beginning, and deeper research is still needed.

Sensing Technology for Intelligentized Robotic Welding in Arc Welding Processes

As more and more extensive application of welding robot, intelligentized robotic welding technology will become the main development trend. This paper introduces some sensing technique of research works about welding robot, such as computer vision sensing technology, arc sensing technology, arc sound sensing technology and welding arc spectral technology. All of which will attempted to address some key problem and provide the scientific basis and the technology realistic way for welding quality controlling in robotic welding intellectualization.

Spectroscopic Diagnostics of Pulsed Gas Tungsten Arc Welding Plasma and Its Effect on Weld Formation of Aluminum-Magnesium Alloy

ABSTRACT Welding arc properties have been studied by means of spectroscopic and optical techniques to optimize the effective arc heat in a pulsed gas tungsten arc welding. A spectral line fitting algorithm was developed for plasma diagnostics. The relationships among arc length, weld pool size, vaporization of weld metal associated with arc temperature, and electron density were discussed in terms of thermal equilibrium. Results showed that arc length and alloying vapor had important effects on the effective arc heat. With an increasing arc length from 2 to 4 mm, both arc temperature and electron density first increased and then decreased, showing good agreement with the weld pool width. An optimum arc length with the maximum of effective arc heat has been found, which was particular for the selected welding conditions but easy to generalize.

Research on Reconstruction of Weld Pool Surface Based on Shape from Shading During Robot Aluminum Alloy Pulse GTAW

In the interest of controlling the weld bead formation quality during robot aluminum alloy gas tungsten arc welding (GTAW) process, it’s necessary to monitor the shape and surface height information of the weld pool in real-time, which can indicate the penetration and formation. This paper presents an algorithm of shape from shading (SFS) based on single image for weld pool surface reconstruction. Two classic SFS algorithms are analyzed with the results of reconstruction from the synthetic half sphere image. Based on the Zheng and Chellapa algorithm, this paper proposes some measures for the improvement, such as smoothing process, strengthening the boundary constraints, using the known characteristics of the object surface and weighting error functions. And the improved algorithm is used to reconstruct the aluminum alloy weld pool surface during the robot pulse GTAW process. The result shows that the algorithm can successfully reconstruct the weld pool surface with effectiveness and accuracy and the computation of the surface height can be applied in real-time.

Mechanism Analysis and Feature Extraction of Arc Sound Channel for Pulse GTAW Welding Dynamic Process

Arc sound signal has been proved to be an effective information for on-line monitoring and control for the quality of GTAW welding. Lots of studies focused on the sound source analysis. In this paper, an analysis of the generation and mechanism of sound channel during GTAW welding is completed, a method of establishing the equivalent model based on cepstral coefficient is proposed. The sound channel is expressed by complex cepstral coefficient through Z transform. The cepstral coefficient and spectral envelope of three different penetration states have been identified. Results show that the models of sound channel for full penetration, partial penetration and excessive penetration are clearly distinguishing the different fusion state of welding process. The sound channel for normal weld is more stable and balanceable than the abnormal weld. Thus, the cepstral coefficient for sound channel is proved to be an effective feature for the identification of dynamic welding process.