Several digital signal processing (DSP) methods are analyzed and compared with respect to the expected errors for an ultrasonic range measurement arrangement. These include L1, L2 norms and correlation with different approaches for envelope extraction. The influence of different factors such as signal-to-noise ratio (SNR), sampling frequency, and digitizing resolution on measurement errors is analyzed using a synthetic approach through nearly 40000 simulations. Results show different performance levels involving accuracy, computing time, and cost for the studied methods, although all of them allow reduction of errors by several orders of magnitude. >

Digital signal processing techniques for high accuracy ultrasonic range measurements

In the automatic welding process on mid/thick plates, the precision of the welding position has an important effect on welding quality, which mainly relies on the identification of the welding seam. However, due to some possible disturbances in complex unstructured welding environments, e.g., strong arc lights, welding splashes, thermal-induced deformations, etc., it is a great challenge to identify the welding seam. In this paper, we propose a robust automatic welding seam identification and tracking method by utilizing structured-light vision. First, after the preprocessing of the welding image, the gray distribution of the laser stripe is tracked and the profile of the welding seam is searched in a small area by using the Kalman filter, with the aim to avoid some disturbances. Second, in order to extract the welding seam profile, a series of centroids obtained by scanning the columns in the rectangular window are fitted using the least-squares method. Third, a character string method is proposed to qualitatively describe the welding seam profile, which might consist of different segment and junction relationship elements. And then, these character strings acquired from the object image are matched with those from the model, so that the position of the welding seam can be determined. Finally, the advantages of the new algorithm are testified and compared through several experiments.

Automatic Welding Seam Tracking and Identification

In this paper, an intelligent seam-tracking system is developed for fillet weld workpiece. Structured light vision is employed to detect the deviation of the welding torch. Two stripe lines are formed on the surface of the fillet weld workpiece by the structured laser light. Their intercepts are selected as the image feature, which can result in an approximately uncoupled relationship between the image feature and the movement of adjustment mechanism. A two-step feature-extraction method is designed to robustly detect the two lines in image. In order to get a favorable tracking precision in the welding process, a new self-tuning fuzzy controller is designed. Its input and output scaling factors are tuned according to its active working region. Moreover, a supervisory level is introduced into the control system to limit the output pulses in order to guarantee steady and safe tracking. Finally, experiments are well conducted to verify the performance of the proposed system and methods.

A Vision-Based Self-Tuning Fuzzy Controller for Fillet Weld Seam Tracking

Robust measurement of the specular weld pool surface can help better understand the complex welding processes and provide feedback for robotic welding. The strong arc light and the specular surface of the weld pool make it difficult for the direct sensing measurement. In this paper, a novel imaging and measurement system is proposed, and it makes use of the strong penetrability of the laser to avoid the interference of arc light and obtain the surface information of the weld pool. By intercepting the reflection of a projected laser pattern twice, the proposed system gives a closed-form solution for each reflected ray and a closed-form solution for the corresponding point on the weld pool surface. The weld pool surface can be thus reconstructed by one-shot structured light projection. To increase the robustness of the measurement system, the least deformation principle is proposed to rectify the coefficient errors of the computed plane equation. Finally, a sequence of 3-D weld pools is reconstructed and compared with state-of-art literature. The comparison verifies that our method is significantly better than all the other methods in measuring the 3-D weld pool shapes.

An Imaging and Measurement System for Robust Reconstruction of Weld Pool During Arc Welding

This paper presents a tactile sensor system for a robot manipulator and an active-sensing technique to realize 3-D object recognitions concerning object shape, object surface normal, and object edge tracing with experimental results. The proposed tactile sensor units implemented on the robot hand consist of three thin sheets of force-sensitive resistors arranged triangularly with the peripheral circuits. One potential application of the proposed techniques is to realize an effective human-robot cooperation to move an object together by utilizing the control of a hand pose to keep the direction of the hand normal to the object surface in three dimensions, which is often necessary when pushing an object. Another is a 3-D object edge tracing. The proposed techniques can be employed in industrial processes such as welding and inspection to eliminate manual teaching procedures for searching the object edge automatically before doing the welding process. In these applications, information about the object shape or orientation is not required in advance.

Robotic Tactile Sensor System and Applications

The description of an ultrasonic-based seam-tracking robotic system that guides a nonwelding torch along different welding grooves is presented. A 100 kHz airborne transducer is used to inspect the workpiece ahead of a welding torch and measures the joint orientation and lateral deviation caused by curvature or discontinuities in the joint part. Data pertaining to the joint orientation and lateral deviation (echo pulse amplitude and time of flight) are obtained periodically by sampling equi-spaced points along the joint as the torch advances. A trajectory-generating algorithm uses this data to calculate the x, y, theta coordinates of the torch-tip trajectory needed to meet the tracking requirements. The experimental results from a feasibility study conducted to determine if this system could be used for tracking during live welding are also presented. >

Robotic acoustic seam tracking: system development and application

A noncontact optical preview sensing technique for possible application to a robotic seam tracking system is presented. This technique uses a structured laser illumination source: a SELFOC lens array (SLA) coupled to a fiberoptic and a phototransistor (photodetector) array. The experimental results with the SLA and fiberoptic array demonstrate the feasibility of linear fiberoptic array sensing of the weld joint. The intensity profiles acquired by the array were such that when combined with suitable data processing software routines, the sensing technique was able to provide satisfactory measurements of joint width and location of the centerline. An experiment demonstrates the viability of the approach for tracking of a weld seam. A clear profile containing the expected features was obtained at each cross-sectional location as the joint was traversed. >

C. Umeagukwu

Papers

Robotic acoustic seam tracking: system development and application

Investigation of an array technique for robotic seam tracking of weld joints