Research status and prospect of prognostics health management technology for mine inverter power devices
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摘要: 矿用逆变器功率器件故障预测与健康管理(PHM)技术通过对监测数据分析处理,能够提取信号特征、定位功率器件开路故障位置、预测功率器件寿命,提高矿用逆变器安全性和可靠性。详细介绍了PHM技术中信号特征提取方法(主要包括坐标变换法、频谱分析法、小波分析法、经验模态分解法)、功率器件开路故障诊断方法(主要包括状态估计法、神经网络法、支持向量机法)、功率器件寿命预测方法(主要包括解析模型法、物理模型法、数据驱动法)的原理及研究现状。分别从实现难度、时效、抗扰性、准确度和数据需求量5个方面对上述各方法进行了比较。针对目前信号特征提取方法单一、矿用逆变器多功率器件开路故障、基于数据驱动法的功率器件寿命预测未能考虑逆变器变工况条件等问题,提出了矿用逆变器功率器件PHM技术的研究方向,包括多方法融合的信号特征提取、基于智能算法的多功率器件开路故障诊断、容错控制和健康管理、变工况下功率器件寿命预测。
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关键词:
- 矿用逆变器;功率器件 /
- 故障预测与健康管理 /
- 信号特征提取 /
- 开路故障诊断 /
- 寿命预测
Abstract: Through the analysis and processing of monitoring data, the prognostics health management (PHM) technology for mine inverter power devices can extract signal characteristics, locate the open circuit fault position of power devices, predict the life of power devices and improve the safety and reliability of mine inverter. This paper introduces the principle and research status of signal characteristics extraction method in PHM technology, including coordinate transformation method, spectrum analysis method, wavelet analysis method, empirical mode decomposition method. This paper introduces the principle and research status of power device open circuit fault diagnosis method in PHM technology, including state estimation method, neural network method, support vector machine method. This paper introduces the principle and research status of power device life prediction method in PHM technology, including analytical model method, physical model method, data-driven method. The above methods are compared from five aspects, including implementation difficulty, timeliness, immunity, accuracy and data demand. The signal characteristic extraction method is single. There is open-circuit fault of multiple power devices of mine inverter. The life prediction of power devices based on data-driven method fails to consider the variable working conditions of inverter. In order to solve the above problems, the research directions of PHM technology for mine inverter power devices are proposed. The directions include signal characteristic extraction based on multi-method fusion, open-circuit fault diagnosis of multiple power devices based on intelligent algorithm, fault-tolerant control and health management, and power device life prediction under variable working conditions. -
表 1 信号特征提取方法比较
Table 1. Comparison of signal characteristic extraction methods
信号特征提取方法 实现难度 时效 抗扰性 准确度 数据需求量 坐标变换法 难 快 弱 低 少 频谱分析法 易 慢 弱 低 少 小波分析法 易 慢 强 高 少 模态分解法 难 慢 强 高 多 表 2 功率器件开路故障诊断方法比较
Table 2. Comparison of open-circuit fault diagnosis methods for power device
功率器件开路
故障诊断方法实现难度 时效 抗扰性 准确度 数据需求量 状态估计法 难 快 强 低 少 神经网络法 易 慢 弱 高 多 支持向量机法 易 快 强 高 少 表 3 功率器件寿命预测方法比较
Table 3. Comparison of power device life prediction methods
功率器件寿命
预测方法实现难度 时效 抗扰性 准确度 数据需求量 解析模型法 难 慢 弱 低 多 物理模型法 难 慢 强 高 多 数据驱动法 易 快 弱 高 少 -
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