Study on Ship Structural Health Monitoring System Based on Computer Artificial Intelligence Vibration Technology

This paper introduces the principle and method of condition monitoring for ship electrical equipment. A prototype of a field contact intelligent sensor is designed at the monitored system. In this way, people can collect and analyze the monitored information and upload it to the server. A layered and multi-agent health monitoring system is proposed. The machine learning-based theory and algorithm are integrated to realize automatic analysis of existing detection results to reduce the computational load of subsequent analysis and improve the accuracy of analysis. The feature vector which is easy to identify is obtained by single parameter selection. The advantages and disadvantages of support vector machine algorithm in structural health monitoring are compared, and the advantages of various SVMS are comprehensively utilized to reduce the rate of missed detection and error detection. Finally, by developing a portable mobile terminal, inspectors can know the current operating status at any location, so as to carry out effective maintenance.