ERI: Hydraulic Cylinder Diagnostics Using Nonlinear Inverse Model Estimation and Frequency Domain Analysis

ERI：使用非线性逆模型估计和频域分析进行液压缸诊断

• 批准号: 2301535
• 负责人: Yongsoon Yoon
• 金额: $ 19.99万
• 依托单位: Oakland University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2301535&HistoricalAwards=false
• 关键词: ERI; Hydraulic; Cylinder; Diagnostics; Using

This Engineering Research Initiation (ERI) grant will fund research that enables reliable operation and cost-effective maintenance of machinery in which hydraulic cylinder actuators play a central role—of critical importance to the transportation, manufacturing, construction, and agricultural industries—thereby promoting the progress of science and advancing the national prosperity. Given its high power density and large force capacity, the hydraulic cylinder is a trusted workhorse across many industrial applications. By its design, it is also vulnerable to a variety of critical faults, such as seal failures, leakage, fluid contamination, and reduced load-carrying capacity, that may negatively affect performance and efficiency, and result in high costs from downtime, permanent damage, or operator injury. To ensure that such faults can be accurately detected and identified, this project relies on a combination of physics-based modeling and innovative frequency domain analysis to develop a novel diagnostic methodology that accounts for system nonlinearities and closed-loop operation. Such a diagnostic paradigm is also anticipated to find application in a variety of energy and power transmission systems, including electric vehicles. Efforts to disseminate research outcomes to local industry in Southeast Michigan, undergraduate research opportunities, and integration of modeling and systems diagnostics principles in coursework will produce broader societal impact.This research aims to develop the foundations for a comprehensive systems diagnostics methodology for hydraulic cylinders that relies on physics-based modeling rather than statistics and machine learning techniques, as has been common in recent years. Such foundational contributions will be made through the design of a new residual generator that extracts faulty features from sensor measurements, as well as of a residual evaluator that makes a diagnostic decision by comparing the residual with the prescribed threshold under a certain operating condition. Several tasks will be pursued through a combination of theoretical modeling, numerical simulations, and physical experiments, including comprehensive fault analysis using a nonlinear, inverse, frequency domain representation of the system dynamics, and formulation and testing of a parameter estimation algorithm for such a nonlinear inverse model under closed-loop operation using an adaptive digital twin. Hardware-in-the-loop simulations will be performed to validate the methodology and investigate its robustness also in the presence of multiple simultaneous faults.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项工程研究启动（ERI）赠款将资助研究，使可靠的操作和具有成本效益的维护机械，其中液压缸执行器发挥核心作用，至关重要的运输，制造业，建筑业和农业产业，从而促进科学的进步和推进国家的繁荣。由于其高功率密度和大的力容量，液压缸是许多工业应用中值得信赖的主力。根据其设计，它也容易受到各种严重故障的影响，例如密封失效、泄漏、流体污染和承载能力降低，这些可能会对性能和效率产生负面影响，并导致停机、永久性损坏或操作员受伤的高成本。为了确保这些故障可以被准确地检测和识别，该项目依赖于基于物理的建模和创新的频域分析相结合，以开发一种新的诊断方法，该方法考虑了系统的非线性和闭环操作。这样的诊断范例也被期望在包括电动车辆在内的各种能量和动力传输系统中找到应用。努力将研究成果传播给密歇根州东南部的当地工业，本科生研究机会，以及在课程中整合建模和系统诊断原理将产生更广泛的社会影响。这项研究旨在为液压缸的综合系统诊断方法奠定基础，该方法依赖于基于物理的建模，而不是统计和机器学习技术，这在近年来很常见。这种基础性的贡献将通过一个新的残差发生器，从传感器测量提取故障特征的设计，以及残差评估器，通过比较残差与规定的阈值在一定的操作条件下作出诊断决定。几项任务将通过理论建模，数值模拟和物理实验，包括全面的故障分析，使用非线性，逆，频域表示的系统动态，和制定和测试的参数估计算法，这样一个非线性逆模型下的闭环操作使用自适应数字孪生相结合的追求。硬件在环仿真将被执行，以验证该方法，并调查其鲁棒性，也存在多个并发故障。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。