In recent years, global warming has accelerated significantly, resulting in accelerated melting of the Arctic Ocean’s ice. Once the Arctic Channel is fully opened, it will directly change the maritime transportation structure. There will be a significant impact on international trade and energy development. However, there is a higher strength requirement for hull plates for polar navigation. So, higher-strength materials are needed for hull plates. In addition, the Initial IMO Strategy for the reduction of greenhouse gas (GHG) emissions from ships was proposed by the International Maritime Organization (IMO) in 2018. The average CO
2 emissions of international shipping will be reduced by at least 40% compared with 2008 and reduced by 70% by 2050 via this strategy [
1]. The lightweight construction of ships is one of the ways to achieve CO
2 emission reduction. On the premise of ensuring sufficient strength, the thickness of high-strength steel is lower than that of traditional ordinary steel plates. The weight of an empty ship can be reduced effectively by applying high-strength steel, which not only reduces the emissions of CO
2 but also reduces the transportation cost [
2]. High-strength steel is becoming a hot research topic regarding ship structural materials due to polar and green navigation. In order to research the influence of the low-temperature Arctic environment on the properties of high-strength steel materials, Chen, M. et al. [
3] carried out tensile tests on steel Q890 and steel Q960 in a liquid nitrogen chamber. The mechanical properties, such as the yield stress of high-strength steel at low Arctic temperatures, were obtained, and the prediction equation was proposed. Li, J. et al. [
4] researched the deformation mechanism of AH36 L-beams under air cooling by numerical simulation. The deformation of L-beams is caused by the combined action of the transformation strain and the cooling shrinkage strain. Netto, A. et al. [
5] established a numerical calculation model for the welding of high-strength steel and optimized the process parameters. Obers, S. et al. [
6] proposed a finite element simulation model for nonlinear plastic materials to analyze the effect of the yield-to-tensile strength ratio on the plastic stress concentration factor. Ramírez-Ramírez, J. et al. [
7] analyzed the causes of cracks in high-strength steel and evaluated these causes through numerical calculation models. Sorger, G. et al. [
8] studied the fatigue performance of high-strength steel in welding and concluded that the fatigue strength of welded joints in friction stir welding was higher than that in electric arc welding. Most of the existing studies on high-strength steel have focused on welding, material properties, and fatigue strength. However, few scholars have paid attention to the study of the plate forming of high-strength steel.
The hull plate is an important part of the ship structure, in which a large number of double-curved hull plates are used to form the complex shape of the bow and stern to meet the hydrodynamic requirements of the ship. At present, the main method of double-curved hull plate forming is line heating [
9]. The equipment cost of line heating is relatively low, which has high economic benefits in the process of ship construction. However, at present, the automation degree of line heating is not high. Dependence on the experience of workers is strong [
10]. Therefore, many scholars have performed further research on the mechanism of line heating. Vega, A. et al. [
11] researched the effect of overlapping heating on the inherent strain in line heating by finite element analysis. The results showed that the inherent strain was caused by the residual stress generated by the previous heating line. Focusing on the line heating of a single-curved plate, Yona, D. et al. [
12] researched the influence of plate thickness, heating times, and heating velocity on deformation by combining numerical calculation and experimentation. It was considered that plate thickness was the most important factor affecting deformation. Shibahara M et al. [
13] combined the finite element method with deep reinforcement learning to obtain process plans for line heating. Thomas K. et al. [
14] established a computer simulation model for line heating, which could predict the deformation of flat plates. Lim H. et al. [
15] studied the effect of line heating on the material properties of steel plates, and the experimental results showed that the steel plates formed by line heating had greater yield strength and tensile strength. Wang, J. et al. [
16] carried out induction heating experiments on steel sail plate Q235 and steel saddle plate AH36. A numerical calculation model of induction heating in curved plate forming was established, which matched the experimental results. Zhou, H. et al. [
17] researched the influence of heating velocity on the maximum temperature of the plate surface in induction heating and proved the feasibility of numerical calculation using elastic finite element analysis combined with experiments. Zhang, S. et al. [
18] optimized the shape parameters of the inductor in induction heating and found that the deformation of the curved plate significantly increased through optimization. Wang, S. et al. [
19] established a numerical calculation model for high-strength steel saddle plates through experiments and studied the influence of geometric and process parameters on the deformation of the plates. Lee, J. et al. [
20] derived a formula for calculating the transverse shrinkage and angular deformation of curved plates by using plate thickness, heating velocity, and heating line spacing based on the results of multi-heating line forming experiments and numerical analysis. The formula could also be used to calculate the minimum distance between two heating lines that do not interact with each other. Zhao, Z. et al. [
21] researched the influence of forming parameters on plastic strain in induction heating and established a database of the relationship between forming parameters and plastic strain under a single heating line condition. At present, scholars’ research on line heating has mainly been about low-carbon steel materials, and the types of plates studied have mainly been sail-shaped plates and single-curved plates. Therefore, there is a lack of research on the forming of high-strength steel saddle plates.
The saddle plate is one of the most common types of double-curved hull plate, which is applied to the outer hull to reduce navigation resistance. Deflection is an important parameter to express the overall deformation of the saddle plate. To fill the research gap in the forming of high-strength steel saddle plates, the intelligent prediction model is established in this paper based on the numerical calculation model of high-strength steel saddle plates in previous research [
19]. Firstly, the influence of forming parameters and plate geometric parameters of the plate on the deflection is researched. Secondly, a multiple regression deflection prediction model of high-strength steel saddle plate suitable for data interpolation is established. Finally, in order to realize the deflection prediction during data extrapolation, an intelligent prediction model for deflection based on a support vector machine (SVM) is established. The deflection can be quickly calculated by inputting geometric parameters and forming parameters into the model. The research in this paper belongs to the application of artificial intelligence in the shipbuilding industry, which can provide data support for the automatic forming of curved plates in the fields of chemistry, aerospace, and so on.