Abstract
Stick-slip vibration images of water-lubricated rubber stern bearing are collected by using machine vision technology. Then these images are analyzed by the methods of persistent homology-based machine learning (PHML). During this analysis, the corresponding barcode is obtained by calculating the homology of the simplicial complex of the vibration images, and the topological characteristics of the vibration images are obtained based on the barcode images, then the support vector machine (SVM) learning is used to study the topological features, and finally the classification and identification of the stick-slip vibration of water-lubricated rubber stern tube bearing are completed. The results have shown that the length of the longest 1D Betti number is closely related to vibration value. Based on these data, it is possible to use the warning beep effectively, create an intelligent description of the beep process, and provide a new idea for simulating stick-slip vibration in the stern bearing.
Highlights
IntroductionThe frictional vibration and noise of water-lubricated rubber stern bearings (hereinafter referred to as stern bearing) affect the concealment, safety, and reliability of underwater vehicles, as well as the comfort of their passengers [1, 2]
The frictional vibration and noise of water-lubricated rubber stern bearings affect the concealment, safety, and reliability of underwater vehicles, as well as the comfort of their passengers [1, 2]
The contact between water-lubricated rubber stern bearing and shaft during operation leads to stick-slip vibration and “whistling” noise, which seriously affects the concealment of the underwater vehicle and is one of the bottlenecks for the underwater vehicle to achieve the level of silence
Summary
The frictional vibration and noise of water-lubricated rubber stern bearings (hereinafter referred to as stern bearing) affect the concealment, safety, and reliability of underwater vehicles, as well as the comfort of their passengers [1, 2]. Friction vibration noise is a very complex natural phenomenon, which mainly occurs in low speed and heavy load conditions [3,4,5] At this time, stern bearings have boundary lubrication or mixed lubrication, and it is difficult to build a water film [6,7,8,9]. Stern bearings have boundary lubrication or mixed lubrication, and it is difficult to build a water film [6,7,8,9] This causes direct contact between the shaft/rubber bearing friction pair thereby generating vibration in the bearing-shaft system [10]. STICK-SLIP VIBRATION IN WATER-LUBRICATED BEARING-SHAFT SYSTEM SIMULATED IN PERSISTENT HOMOLOGY-BASED MACHINE LEARNING MODEL. PH and machine learning (ML) for data analysis are to be combined [30], but there are little researches on the stick-slip analysis of stern bearing based on the PHML
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