Characterization and Control of Non-Steady State Machine Vibration

非稳态机器振动的表征和控制

• 批准号: RGPIN-2014-05922
• 负责人: Mechefske, Christopher
• 金额: $ 2.84万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=659463
• 关键词: Characterization; Control; Non; Steady; State

Non-steady state operating conditions are commonplace in a wide range of machinery from wind turbines to airplanes. However the system response dynamics in these situations remain poorly characterized and not well understood. The changing operating conditions that generate non-steady state responses are due to a variety of factors such as unpredictable machine speed (planetary gear systems in wind turbines), fluctuating mass (loading and emptying of mining skips) or variable excitation (aircraft flight envelopes, MRI scanner imaging excitation). In all cases it is extremely important to fully understand the system response in order to control mechanical vibration and mitigate potentially harmful effects.**The broad class of non-steady state machine response applications has a wide and variable time scale (potentially ranging from minutes to months) defining the different operational regimes. The many different parameters that define the operating conditions of these systems may also combine in unpredictable ways. In these cases it remains challenging to characterize, predict and control the mechanical vibration.*Non-steady state system characterization has followed an ad-hoc development path to date. Most work has focused on particular applications where the non-steady state system behaviour is unique. A more structured approach will be followed in the proposed research work. This approach will begin with a set of characterization criteria that are traditionally used in steady state system identification and characterization and develop new and/or hybrid methods for characterization of non-steady state operation. Preliminary work by myself and others has revealed several new signal analysis methods that show significant promise in this regard.**Recent research has begun to produce tools that allow system condition monitoring, fault diagnosis, vibration control and system performance optimization. Most of this work requires fixed time scales, prior knowledge of the expected system operating conditions and a reasonable history of sample data representing those operating conditions. My past research work has been directly related to this research area and was focused on methods that do not require detailed prior system knowledge nor sample data for training of analysis algorithms. Other closely related work that I have completed recently includes noise and vibration reduction in MRI scanners and vibration control in mining skips. Solutions to the vibration and noise problems in both of these applications relied on development of a clearer understanding of the system performance during non-steady state operational situations.**The research work proposed in my Discovery Grant application will be focused on the further understanding of non-steady state system performance through system characterization. Application of the results of this work will lead directly to new methods for machine/structure condition monitoring, fault detection and diagnosis, vibration control, and system performance and design optimization. In my research program I will be focusing on the application of these results as they apply to fault detection and diagnosis in planetary gearboxes, noise reduction in MRI scanners and vibration control in mining skips. While these applications may seem relatively specific they have common aspects and represent a broad field of study of interest to a range of important resource based industries in Canada. My expertise and experience uniquely position me to address these topics.

非稳态操作条件在从风力涡轮机到飞机的各种机械中是常见的。然而，在这些情况下的系统响应动力学仍然很差的特点和没有很好地理解。产生非稳态响应的不断变化的操作条件是由于各种因素造成的，例如不可预测的机器速度（风力涡轮机中的行星齿轮系统）、波动的质量（采矿箕斗的装载和清空）或可变激励（飞机飞行包线、MRI扫描仪成像激励）。在所有情况下，为了控制机械振动和减轻潜在的有害影响，充分了解系统响应是非常重要的。**非稳态机器响应应用的广泛类别具有广泛且可变的时间尺度（可能从几分钟到几个月），其定义了不同的操作状态。定义这些系统的操作条件的许多不同参数也可能以不可预测的方式组合联合收割机。在这些情况下，表征、预测和控制机械振动仍然具有挑战性。*迄今为止，非稳态系统表征一直遵循特定的发展路径。大多数工作都集中在特定的应用程序中的非稳态系统的行为是独特的。在拟议的研究工作中，将采用一种更有条理的方法。这种方法将开始与传统上用于稳态系统识别和表征的一组表征标准，并开发新的和/或混合的方法，用于表征非稳态操作。我和其他人的初步工作揭示了几种新的信号分析方法，在这方面显示出重大的希望。最近的研究已经开始产生允许系统状态监测、故障诊断、振动控制和系统性能优化的工具。这项工作的大部分需要固定的时间尺度，预期的系统操作条件的先验知识和代表这些操作条件的样本数据的合理历史。我过去的研究工作与这一研究领域直接相关，并专注于不需要详细的先验系统知识或样本数据来训练分析算法的方法。我最近完成的其他密切相关的工作包括MRI扫描仪的噪音和振动减少以及采矿箕斗的振动控制。这两种应用中振动和噪声问题的解决方案都依赖于对非稳态运行情况下系统性能的更清晰理解。**我的发现资助申请中提出的研究工作将重点关注通过系统表征进一步了解非稳态系统性能。这项工作的结果的应用将直接导致新的方法，机器/结构的状态监测，故障检测和诊断，振动控制，系统性能和设计优化。在我的研究计划中，我将专注于这些结果的应用，因为它们适用于行星齿轮箱的故障检测和诊断，MRI扫描仪的降噪和采矿箕斗的振动控制。虽然这些应用可能看起来相对具体，但它们具有共同的方面，代表了加拿大一系列重要资源型行业感兴趣的广泛研究领域。我的专业知识和经验使我能够解决这些问题。