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

A Method of Recognizing Ship Vibration Mode based on CNN
Qingchun Zhu, Heqi Fu, Wei Wang, Haixin Cui, Cong Li, Wei Xia
Marine Design and Research Institute of China
Shanghai, China

ABSTRACTnatural frequency of grillage is significant for equipment’s function andthe vibration and noise control of hull structure.

This paper attempts to solve the mode recognition problem using theCNN (convolutional neural network) algorithm. A program is designed
by Pytorch and PCL (Patran command language) to recognize both thenatural frequency of ship hull and grillage. After building a training set
with pictures of ship vibration mode, the VGG model is built to acquirefeatures of the model. Meanwhile, automatic screenshots of the modal
analysis results in Patran are captured and sent to the recognition
program. Derived from multiple sets of test cases, the results show thatmode recognition accuracy and efficiency are satisfactory. The practiceof this paper has provided a new method for the fast evaluation of shipvibration.

However, it is quite difficult to obtain the vibration mode of a grillage.
On one hand, the vibration modes of small panels are also caught aseigenvalue in mode analysis, so that many more orders of eigenvalues
would be calculated to obtain the grillage’s mode. On the other hand, if
the FEM model consists of small mesh, or even with modeling error,
for instance lacking stiffness, the whole mode analysis would be stuck
in local-panel modes or unreal modes. In this case, it may takehundreds of eigenvalues to obtain the suitable grillage mode.
At the earlier stage of ship design, it is required to evaluate generalvibration and grillage vibration of concerning area quickly whenarrangement plan is uncertain. Besides, at the same stage, generalstrength should also be evaluated to make sure the design is under key
constraints. The mesh size of the FEM model for general strength
evaluation is much smaller than that of vibration evaluation. As
mentioned above, a small-size mesh model induces more eigenvalues
so that mode visual recognition would be much more difficult
inevitably. Since the design plan may change completely, building
FEM model for each plan and making analysis for multi-evaluations
would be a huge waste of human resources. It is advisable to evaluate
strength and vibration with the same FEM model.

KEY WORDS:

Convolutional Neural Networks (CNN); VGG
Model; Mode Recognition; Deep Learning.

INTRODUCTION
To control design direction at a primitive stage, it is repeatedly required
to calculate the natural frequency of ship hull or grillage during thestructural design process. Normally, mode analysis is conducted in
FEM (finite element method) software with results spotted by visual
recognition and it takes a great deal of time and human resources toobtain proper vibration mode. Designers pick out the required vibration
modes and their eigenvalues are the natural frequency.

In recent years, with the development of neural network algorithms andthe rapid development of hardware, artificial intelligence, especiallydeep learning techniques specializing in visual processing problems has
advanced by leaps and bounds. Characterized by the neural network,
deep learning techniques have been applied in structural design andanalysis. Guo, Wang, Kang et al. (2019) explored the prediction of
cabin noise with RBF neural network and received good accuracy
overall. Li, Ma, Lin (2019) attempted to solve the problem of structural
damage identification with CNN and proved that CNN was not only
feasible but also had more advantages in automatically extracting
features than traditional methods. From 2015, the ILSVRC champion
model has achieved a lower error rate than human eyes, which marks
the convolutional neural network (CNN) algorithm has surpassed

The first and the second order of vertical and horizontal vibration
frequency of ship hull should be obtained and compared with theprimary vibration source which is the main engine, to avoid resonance.
General vibration modes are more obviously acquired than local
grillage modes. As for grillage, the range we are concerned with is thestiffened plates between two bulkheads. The natural frequency ofgrillage is a vital design parameter that instructs the designer tomismatch the incentive source in the vicinity. Meanwhile, a lot of ship
equipment has requirements for grillage stiffness, so knowing the3614