Recognition of initial welding position for large diameter pipeline based on pulse coupled neural network

Abstract

Purpose

The main purpose of this paper is to develop a method to recognize the initial welding position for large-diameter pipeline automatically, and introduce the image processing based on pulse-coupled neural network (PCNN) which is adopted by the proposed method.

Design/methodology/approach

In this paper, a passive vision sensor is designed to capture weld seam images in real time. The proposed method contains two steps. The first step is to detect the rough position of the weld seam, and the second step is to recognize one of the solder joints from the local image and extract its centroid, which is regarded as the initial welding position. In each step, image segmentation and removal of small false regions based on PCNN are adopted to obtain the object regions; then, the traditional image processing theory is used for the subsequent processing.

Findings

The experimental results show the feasibility and real time of the proposed method. Based on vision sensing technology and PCNN, it is able to achieve the autonomous recognition of initial welding position in large-diameter pipeline welding.

Practical implications

The proposed method can greatly shorten the time of positioning the initial welding position and satisfy the automatic welding for large-diameter pipeline.

Originality/value

In the proposed method, the image pre-processing is based on PCNN, which is more robust and flexible in the complex welding environment. After that, traditional image processing theory is adopted for the subsequent processing, of which the processing speed is faster.

Citation

Yang, L.J., Lou, P.H. and Qian, X.M. (2015), "Recognition of initial welding position for large diameter pipeline based on pulse coupled neural network", Industrial Robot, Vol. 42 No. 4, pp. 339-346. https://doi.org/10.1108/IR-01-2015-0011