大数据下机械智能故障诊断的机遇与挑战

被引：395

作者：

雷亚国 ^{[1
]}

贾峰 ^{[1
]}

孔德同 ^{[2
]}

林京 ^{[1
]}

邢赛博 ^{[1
]}

机构：

[1] 西安交通大学机械制造系统工程国家重点实验室

[2] 华电电力科学研究院

来源：

机械工程学报 | 2018年 / 54卷 / 05期

关键词：

机械装备; 智能故障诊断; 大数据;

D O I：

暂无

中图分类号：

TH17 [机械运行与维修];

学科分类号：

摘要：

机械故障是风力发电设备、航空发动机、高档数控机床等大型机械装备安全可靠运行的"潜在杀手"。故障诊断是保障机械装备安全运行的"杀手锏"。由于诊断的装备量大面广、每台装备测点多、数据采样频率高、装备服役历时长,所以获取了海量的诊断数据,推动故障诊断领域进入了"大数据"时代。而机械智能故障诊断有望成为大数据下诊断机械装备故障的"一把利器"。与此同时,大数据给机械智能故障诊断的深入研究和应用提供了新的机遇:"数据为王"的学术思想有望成为主流、诊断整机或系统级对象成为可能、全面解析故障演化过程成为趋势等;但也遇到了新的挑战:数据大而不全呈"碎片化"、故障特征提取受制于人为经验、浅层诊断模型诊断精度低等。阐述了机械智能故障诊断大数据的特点;从信号获取、特征提取、故障识别与预测三个环节,综述了机械智能故障诊断的国内外研究进展和发展动态;指出了机械智能故障诊断理论与方法在大数据背景下的挑战;最后讨论了应对这些挑战的解决途径与发展趋势。

引用

页码：94 / 104

页数：11

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