Researching | Fault diagnosis of steam power system based on convolutional neural network

Chinese Journal of Ship Research, Volume. 17, Issue 6, 96(2022)

Fault diagnosis of steam power system based on convolutional neural network

Jian SU¹, Hanjiang SONG², Fuyuan SONG¹, and Guolei ZHANG¹

Author Affiliations

¹College of Power and Energy Engineering, Harbin Engineering University, Harbin 150001, China

²The 92942 Unit of PLA, Beijing 100161, China

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Table 1. Comparison of steady-state dimensionless parameters under ahead condition

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Table 1. Comparison of steady-state dimensionless parameters under ahead condition

参数	仿真值	试验值	误差/%
过热蒸汽温度	1.009	1	0.93
汽包压力	0.993	1	−0.65
过热蒸汽压力	0.997	1	−0.34
锅炉给水温度	0.962	1	−3.80
过热蒸汽总管温度	1.002	1	0.19
除氧器压力	0.984	1	−1.59
辅过热蒸汽总管温度	1.007	1	0.74
辅过热蒸汽总管压力	1.005	1	0.52
微过热蒸汽温度	1.001	1	0.06
微过热蒸汽压力	0.953	1	−4.67
主机阀前蒸汽压力	1.000	1	0
螺旋桨转速	0.982	1	−1.75

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Jian SU, Hanjiang SONG, Fuyuan SONG, Guolei ZHANG. Fault diagnosis of steam power system based on convolutional neural network[J]. Chinese Journal of Ship Research, 2022, 17(6): 96

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Paper Information

Category: Intelligent Engine Room, Intelligent Energy Efficiency and Intelligent Platform

Received: Nov. 24, 2021

Accepted: --

Published Online: Mar. 26, 2025

The Author Email:

DOI:10.19693/j.issn.1673-3185.02616

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