Because of the long propulsion shafting of special ships, the number of bearings is large and the number of measured bearing reaction data is small, which makes the installation of shafting difficult. To apply a small amount of measured data to the process of ship installation so as to accurately calculate the displacement value in the actual installation, this article proposes a method to calculate the displacement value of shafting intermediate bearing based on different confidence-level training samples. Taking a ro-ro ship as the research object, this research simulates the actual installation process, gives a higher confidence level to a small amount of measured data, constructs a new training sample set for machine learning, and finally obtains the genetic algorithm-backpropagation(GABP) neural network reflecting the actual installation process. At the same time, this research compares the accuracy between different confidence-level training sample shafting neural network and the shafting neural network without measured data, and the results show that the accuracy of shafting neural network with different confidence-level training samples is higher. Although as the adjustment times and the number of measured data increase, the network accuracy is significantly improved. After adding four measured data, the maximum error is within 1%, which can play a guiding role in the ship propulsion shafting alignment.
Introduction
With the rapid development of science and technology in the world, special ships such as engineering ships, official ships, and warships play an important role (Carrasco et al. 2020; Prill et al. 2020). Some ships of this special type are limited by various factors such as the stern line of engine room, hull stability, and operation requirements. They usually adopt the layout of middle or front engine room, which causes the propulsion system to have a longer shaft and the number of intermediate shafts and intermediate bearings exceeds two. This forms a so-called multisupport shafting (Lee et al. 2019) and it increases the difficulty of shafting alignment because of the force-coupling between the bearings (Lai et al. 2018a, 2018b). The process of the existing methods for calculating the displacement value is complex, and because of the influence of installation error and other factors, it is necessary to adjust the bearing height several times to make the bearing reaction meet the specification requirements(Kim et al. 2017, Ko et al. 2017). So how to predict the accurate displacement value of each intermediate bearing is the key to solving the problem of multisupport shafting intermediate bearing installation and calibration (Zhou et al. 2005, Xiao-fei et al. 2017).
AIRBORNE HYPERSPECTRAL REMOTE SENSING FOR IDENTIFICATION GRASSLAND VEGETATION
