Application of Particle Swarm Optimizer Neural Network in Fault Diagnosis for Marine Auxiliary Boiler

WANG Shiwei; GAN Huibing; HU Guotong; ZHONG Zhenyu

doi:10.3969/j.issn.1000-4653.2022.02.007

Navigation of China > 2022 > 45(2): 37-42,55. > DOI: 10.3969/j.issn.1000-4653.2022.02.007

WANG Shiwei, GAN Huibing, HU Guotong, ZHONG Zhenyu. Application of Particle Swarm Optimizer Neural Network in Fault Diagnosis for Marine Auxiliary Boiler[J]. Navigation of China, 2022, 45(2): 37-42,55. DOI: 10.3969/j.issn.1000-4653.2022.02.007

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Application of Particle Swarm Optimizer Neural Network in Fault Diagnosis for Marine Auxiliary Boiler

Marine Engineering College, Dalian Maritime University, Dalian 116026, China

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Received Date: December 24, 2020
Available Online: June 13, 2024

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Abstract

A mixed neural network diagnose model is constructed by integrating the self-organizing feature map network with a BP neural network in cascade.Meantime, the particle swarm optimizer is used to improve the initial connecting weighting and node dependent thresholding.An ALFA LAVAL D-type water tube boiler is taken as the objective machine for verification of the diagnosis model.The diagnosis model is tested with the data from the DMS VLCC marine engine room simulator.Same experiments are carried out with the sole BP neural network and the SOM-BP network for comparison.The advantage of the development is demonstrated.
- marine auxiliary boiler,
- fault diagnosis,
- mixed neural network,
- particle swam optimizer

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