流体机械

2020, v.48;No.579(09) 65-70+82

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基于人工智能的往复式压缩机故障诊断研究综述
Research Review on Fault Diagnosis of Reciprocating Compressor Based on Artificial Intelligence

刘华敏;吕倩;余小玲;叶君超;杨长华;万辰咏;
Liu Huamin;Lyu Qian;Yu Xiaoling;Ye Junchao;Yang Changhua;Wan Chenyong;SINOPEC Jianghan Oilfield Company;Xi'an Jiaotong University,School of Energy and Power Engineering;Sinopec Chongqing Fuling Shale Gas Exploration and Development Co.,Ltd.;

摘要(Abstract):

往复式压缩机因其机构和运动复杂导致其故障形式繁多,给人工的诊断过程带来了困难。本文较为全面地综述了人工智能用于故障诊断的现状和发展趋势,分析了各种人工智能技术的特点及适用性,提出了今后往复式压缩机故障诊断和人工智能方法结合的发展方向。对于压缩机人工智能诊断方法选择,促进压缩机智能化发展有重要意义。
Reciprocating compressors play an important role in industrial production.Complicated construction and movement can lead to diverse fault modes,which imposes a burden on manual diagnosis.In present study,the current status and development trend of artificial intelligence for fault diagnosis were comprehensively summarized,the characteristics and applicability of various artificial intelligence technologies were analyzed.and the future development direction of fault diagnosis and artificial intelligence methods of reciprocating compressor were proposed.Besides,the selection of compressor artificial intelligence diagnostic methods is significant for promoting compressor intelligentization development.

关键词(KeyWords): 往复式压缩机;故障诊断;人工智能
reciprocating compressor;fault diagnosis;artificial intelligence

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作者(Author): 刘华敏;吕倩;余小玲;叶君超;杨长华;万辰咏;
Liu Huamin;Lyu Qian;Yu Xiaoling;Ye Junchao;Yang Changhua;Wan Chenyong;SINOPEC Jianghan Oilfield Company;Xi'an Jiaotong University,School of Energy and Power Engineering;Sinopec Chongqing Fuling Shale Gas Exploration and Development Co.,Ltd.;

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