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- W4387006023 abstract "The improvement of ship machinery manufacturing level has promoted the development of China’s shipping industry. While the ship performance is improved, the structure and operating conditions of ship machinery are becoming more and more complex, which has brought some challenges to the maintenance of ship machinery. Therefore, it is necessary to strengthen the fault maintenance and condition monitoring and evaluation of ship machinery and equipment. Firstly, this paper summarizes and analyzes the common faults of marine mechanical equipment, then explains and introduces the commonly used SVM algorithm, evaluates the health status of marine mechanical equipment based on the monitoring data, identifies the possible fault conditions and various possible fault categories, and uses the SVM algorithm for model training and classification. It can effectively reduce the maintenance cost of ship machinery, improve the operation safety and reliability of ship machinery and equipment, improve the intelligent level of ship equipment, monitor and evaluate the condition of ship equipment, and create favorable conditions for the long-term development of China’s maritime industry." @default.
- W4387006023 created "2023-09-26" @default.
- W4387006023 creator A5049949859 @default.
- W4387006023 date "2023-06-01" @default.
- W4387006023 modified "2023-09-26" @default.
- W4387006023 title "Condition Monitoring and Evaluation of Marine Machinery Based on Support Vector Machine Algorithm" @default.
- W4387006023 doi "https://doi.org/10.1109/icmiii58949.2023.00058" @default.
- W4387006023 hasPublicationYear "2023" @default.
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