Journal
IEEE-ASME TRANSACTIONS ON MECHATRONICS
Volume 27, Issue 2, Pages 1150-1161Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMECH.2021.3082631
Keywords
Valves; Pipelines; Marine vehicles; Support vector machines; Supervisory control; Reliability engineering; Principal component analysis; Autonomous piping system; autonomous valve; damage recovery algorithm; multistage control (MSC); naval ship survivability; support vector machine (SVM)
Categories
Funding
- Basic Research Project of National Research Foundation of Korea [NRF-2020R1F1A1070300]
- BK21
- Main Project of Korea Institute of Machinery and Materials [NK232B]
- National Research Council of Science & Technology (NST), Republic of Korea [NK232B] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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This study proposes an autonomous recovery system for pipeline systems in naval ships to quickly detect and isolate unexpected damage. By using a multistage control algorithm and support vector machine design procedure, the reliability of the system is enhanced. The effectiveness of the algorithm is demonstrated through flow simulations and experiments.
Pipeline systems in naval ships with special combat purposes (such as warships) are frequently exposed to the risk of damage. It is necessary to detect and isolate such unexpected damage quickly via an autonomous recovery system in the pipelines to ensure the ship's survivability. This recovery system employs an autonomously controlled valve, which consists of a valve body, two pressure sensors, an actuator to open/close the valve, and a controller equipped with damage detection capability and a control algorithm. To enhance the reliability of the autonomous recovery system, this study first proposes a multistage control algorithm that can comprehensively consider the various damage scenarios in a naval ship and then suggests the design procedure for the autonomous piping system based on support vector machine (SVM). To design the suggested algorithm, a simulation model for the 1-D real-time flow analysis is first established, and its results for possible damage scenarios are used as training data for the SVM with the valve operation information for recovery of the piping system and to minimize the damaged area. A performance comparison of the representative control algorithms for the autonomous piping system is conducted via flow simulations under three representative damage scenarios. Finally, a real-scale testbed of the firemain in a naval ship is designed and constructed, and the effectiveness of the algorithm is demonstrated through experiments.
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