Integrated On-line Condition Monitoring and Failure Diagnosis in Induction Motors

感应电机的集成在线状态监测和故障诊断

• 批准号: LP0453951
• 负责人: A/Prof Nesimi Ertugrul
• 金额: $ 13.85万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2004
• 资助国家: 澳大利亚
• 起止时间: 2004-04-18 至 2010-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP0453951
• 关键词: Integrated; line; Condition; Monitoring; Failure

Electric motors are widely used in industry. Traditional maintenance approaches have involved regular overhauls/inspections and replacement after a fixed period. On-line condition monitoring involves taking non-invasive measurements to determine the motor's "health" and only scheduling maintenance when required. The benefits are reduced unexpected failures and reduced maintenance costs due to the greater maintenance intervals. The majority of existing work on condition monitoring has looked at using a single sensor type (eg. vibration) for fault prediction. The proposed work seeks to improve the reliability and accuracy of fault diagnosis by correlating information from multiple sensor types, which can be accessed remotely.

电动机在工业上被广泛使用。传统的维护方法涉及定期检修/检查和固定时间后的更换。 在线状态监测涉及采取非侵入性测量来确定电机的“健康状况”，并仅在需要时安排维护。其好处是减少了意外故障，并由于更长的维护间隔而降低了维护成本。大多数关于状态监测的现有工作都着眼于使用单一传感器类型（例如，振动）进行故障预测。 所提出的工作旨在通过关联来自多个传感器类型的信息来提高故障诊断的可靠性和准确性，这些信息可以远程访问。