Proceedings of the Thirty-second (2022) International Ocean and Polar Engineering Conference
Shanghai, China, June 5–10, 2022
Copyright © 2022 by the International Society of Offshore and Polar Engineers (ISOPE)
ISBN 978-1-880653-81-4; ISSN 1098-6189

www.isope.org

Application of Fuzzy Interpolation Reasoning in Welding Process Decision
Zufu Pan1, Zhiqiang Feng2,3,*, Haijian Qin2, Ziquan Jiao2, Hao Yuan2, Xin Li2
1.School of Mechamical Engineering, Guangxi University, Nanning, Guangxi, China
2. Guangxi Engineering Technology Research Center of Ship Digital Design and Advanced Manufacturing,Beibu Gulf University, Qinzhou, Guangxi, China
3.State Key Laboratory of Hydraulic Engineering Simulation & Safety, Tianjin University, Tianjin, China

ABSTRACT: Welding is a highly nonlinear, time-varying and multi
coupling typical complex process. When using the traditional fuzzy
reasoning method to make decision on welding parameters, it is difficult
to build an accurate and complete welding process parameter rule basedue to the uncertainty and complexity of the welding process. When thegiven input value cannot match the rules in the rule base, the reasoning
conclusion cannot be drawn. In order to solve this limitation, this paper
proposes a welding process parameter decision-making method, whichis achieved by fuzzy rule interpolation. It can predict and decide welding
parameters when the welding process parameter rule base is sparse. The
experimental results show that the model can achieve high accuracy.

KEY WORDS: Welding specification parameters; fuzzy interpolation
reasoning; process decision-making.

INTRODUCTION
Welding technology is an important part of modern industry. It is
widely used in the connection of various metal components due to its
low cost, high efficiency and reliable connection. During shipconstruction, welding occupies an important position in ship production.
The welding time for ship hull accounts for 30% ~ 40% of the total
construction time for ship (Zhou Guosheng, 2003). However, welding isa highly non-linear, time-varying and multi-coupling typical complex
process, and the actual welding conditions and environment are
constantly changing, which hinders the automation, intelligence andscale of ship welding production to a large extent. With the developmentof automatic welding technology, it has been widely used in themanufacturing industry, improving the efficiency of welding production.
Forming quality of weld is one of the factors affecting the performanceof welded joint. There are many factors affecting the forming of weld.
Under the condition that other process conditions remain unchanged,
welding current, welding voltage and welding speed are the key factors
affecting the forming quality of weld. Selecting reasonable welding
process parameters is very important to improve the welding quality andproduction efficiency. Because welding is a complicated thermal process,2915

it is difficult to establish an accurate mathematical model of weld size
and welding process parameters. It is difficult to describe it accurately
using binary logic or multivalued logic.
The selection of welding process parameters is an important segmentin the welding process. The selection of welding process parameters not
only affects the quality of welding, but also affects the production
efficiency of welding. Under the same welding process conditions,welding current, voltage and welding speed have a greater influence on
the quality of weld formation. Reasonable selection of welding processparameters is the precondition of ensuring welding quality, which canreduce the occurrence of welding defects and improve production
efficiency. In actual welding operations, the setting of welding processparameters is usually determined by referring to relevant welding
process manuals and through several process tests, which requires a lotof effort. However, this does not ensure that the selected welding
parameters can achieve the best welding performance, so it is necessary
to explore other methods to assist in determining the welding processparameters.
Fuzzy reasoning is an important part of intelligent systems such as
fuzzy control, fuzzy expert system and fuzzy decision support system,and has been successfully applied in industry. In literature (Pei Daminget al., 2016) proposed a hull welding process design method based on
fuzzy rule reasoning, which applies fuzzy logic to welding processplanning process. In literature (Tarng Y S et al., 2000) fuzzy reasoning
is applied to the optimization of multi-performance of submerged arc
welding. Literature (Liao T.W, 2003) proposed different types of expert
system for welding defect diagnosis based on fuzzy rules. Traditionalfuzzy reasoning method needs complete rule base covering the whole
input field, but it is difficult to obtain a close rule base in reality. Whenthe rule base is sparse and the observation value does not overlap withthe precondition part of the rule base, the reasoning conclusion can not
be reached by traditional reasoning method. The interpolation reasoningof fuzzy rules put forward by Kóczy and Hirota can reason under thesparse rule base and draw inference conclusions, thus starting theresearch on the sparse rule base (Kóczy L T and Hirota K, 1993). Fuzzyrule interpolation (FRI) is very important for reasoning under thecondition of insufficient knowledge or sparse rule base.
In this paper, a decision-making method for welding process