Ship power equipment fault identification method

A technology for fault identification and power equipment, applied in character and pattern recognition, instruments, calculation models, etc., can solve the problems of slow convergence speed, easy to fall into local optimum, etc., to avoid blindness, improve convergence speed and recognition accuracy, reduce The effect of small ineffective optimization

Pending Publication Date: 2020-08-11
JIANGSU UNIV OF SCI & TECH +1
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  • Abstract
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Problems solved by technology

The artificial fish swarm algorithm can be used to optimize the parameters of SVM, but the traditional AFSA algorithm has problems such as slow convergence speed and easy to fall into local optimum, so it needs to be further improved

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  • Ship power equipment fault identification method
  • Ship power equipment fault identification method
  • Ship power equipment fault identification method

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Embodiment Construction

[0037] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. The components of the embodiments of the invention generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations.

[0038] Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art wi...

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Abstract

The invention relates to a ship power equipment fault identification method. The method is characterized by comprising the following specific steps: S1, collecting and classifying monitoring data samples; s2, establishing and training a classifier; s3, applying a model. According to the method, a fault of ship power equipment is recognized through a support vector machine, so that a fault recognition result under small sample data is more accurate; random behaviors in an AFSA algorithm are improved, blindness generated by artificial fish through a traditional random behavior optimization process is avoided, and the phenomenon of invalid optimization in the optimization process is reduced; a GWO-AFSA algorithm is optimized, so that the convergence rate and the recognition precision are improved, and the defect that traditional AFSA is easy to fall into local optimum is overcome; and SVM parameters are optimized by using the improved GWO-AFSA, so that the fault identification precision of the ship power equipment is improved.

Description

technical field [0001] The invention relates to the technical field of fault identification of ship power equipment, in particular to a method for fault identification of ship power equipment. Background technique [0002] The ship power system is the key system to ensure the sailing ability, maneuverability and safety of the ship, and it is called the heart of the ship. The performance of the ship's power system and the reliability of the equipment directly affect a series of performance indicators such as the rapidity, speed adaptability, vitality, endurance, and concealment of the ship. The ship power system is composed of multiple devices, with many parts and complicated structure. During the long-term operation, failures and problems are prone to occur. As the main facilities and equipment for providing ship power, once the ship's power equipment fails, it will affect the operating state of the ship, resulting in unstable navigation or even suspension of the ship. In s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/00
CPCG06N3/006G06F18/2411G06F18/214
Inventor 杨奕飞于晓琳何祖军苏贞徐江敏
Owner JIANGSU UNIV OF SCI & TECH
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