为了提升船用高频开关电源的运行可靠性，提出基于深度学习算法的船用高频电路工作状态检测方法。采集船用高频电路工作状态信号，作为深度受限波尔兹曼机的输入，深度受限波尔兹曼机利用2层受限玻尔兹曼机，通过2次非线性映射，提取船用高频电路工作状态特征。设置所提取的高频电路工作状态特征，作为支持向量数据描述方法的输入，将输入样本映射至高维内积空间，判定样本是否存在于高维内积空间的最优超球体内，检测船用高频电路工作状态为正常或异常状态。实验结果表明，该方法可以精准检测船用高频电路工作状态，满足船舶高频开关电源的运行可靠性需求。
A deep learning algorithm based working state detection method for marine high frequency circuit is studied to improve the operational reliability of marine high frequency switching power supply. The working state signals of Marine high frequency circuits are collected and used as input of the depth limited Boltzmann machine. The depth limited Boltzmann machine uses the two-layer limited Boltzmann machine to extract the working state characteristics of marine high frequency circuits through two nonlinear mapping. The extracted working state characteristics of the high-frequency circuit are set as the input of the support vector data description method, which maps the input sample to the high-dimensional inner product space, determines whether the sample exists in the optimal hypersphere of the high-dimensional inner product space, and detects whether the working state of the marine high-frequency circuit is normal or abnormal. Experimental results show that the proposed method can accurately detect the working state of marine high-frequency circuit and meet the operational reliability requirements of marine high-frequency switching power supply.
2023,45(12): 156-159 收稿日期：2022-11-14
DOI：10.3404/j.issn.1672-7619.2023.12.031
分类号：U665
基金项目：湖北省教育科学规划重点课题（2022GA089）
作者简介：何一芥(1984-),女,硕士,副教授,主要研究方向为电子信息技术
参考文献：
[1] 牟红宇, 赵世舟, 白钰, 等. 船用增压锅炉燃烧系统燃油压差控制电路设计[J]. 热能动力工程, 2020, 35(12): 154–161
MOU Hong-yu, ZHAO Shi-zhou, BAI Yu, et al. Design of fuel oil pressure difference control circuit for combustion system of marine supercharged boiler[J]. Journal of Engineering for Thermal Energy and Power, 2020, 35(12): 154–161
[2] 李涛, 乔鸣忠, 宋庆国. 船用逆变电源两级死区补偿控制策略[J]. 船舶工程, 2022, 44(S1): 398–402
LI Tao, QIAO Ming-zhong, SONG Qing-guo. Two-stage dead zone compensation control strategy for Marine inverter power supply[J]. Ship engineering, 2022, 44(S1): 398–402
[3] 吴希杰, 周方明. 船舶控制设备用微连接器激光软钎焊电路设计[J]. 船海工程, 2021, 50(1): 64–67
[4] 汪洋, 黎恒烜, 鄂士平, 等. 基于深度学习的变电站硬压板状态检测与识别算法[J]. 沈阳工业大学学报, 2020, 42(6): 676–680
WANG Yang, LI Hengxuan, E Shiping, et al. State detection and recognition algorithm for hard platens of substation based on deep learning[J]. Journal of Shenyang University of Technology, 2020, 42(6): 676–680
[5] 吴健, 尹泽, 李豪, 等. 基于分数阶理论的锂离子电池高频等效电路模型[J]. 电工技术学报, 2021, 36(18): 3902–3910
[6] 岳改丽, 向付伟, 李忠. Cascode GaN高电子迁移率晶体管高频驱动电路及损耗分析[J]. 电工技术学报, 2021, 36(20): 4194–4203
YUE Gai-li, XIANG Fu-wei, LI Zhong. High-frequency drive circuit and its loss analysis of cascode GaN high electron mobility transistor[J]. Transactions of China Electro technical Society, 2021, 36(20): 4194–4203
