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SBIR Phase I: Intelligent Tool Wear Monitoring

SBIR Phase I: Intelligent Tool Wear Monitoring
SBIR 第一阶段:智能刀具磨损监测
批准号:
0810434
负责人:
Donald Esterling
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-07-01 至 2009-06-30

项目摘要

项目成果

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中文摘要
翻译
这个小企业创新研究第一阶段项目将调查过程验证和工具磨损技术的融合。过程验证——基于物理的加工过程分析和优化,是纯几何数控验证的后续——可以显著提高21世纪制造业的可靠性和生产率。基于物理的系统以刀具力建模为基础,主要依赖于称为切削能量的输入过程模型参数。随着刀具的磨损,这些切削能量和相关的刀具力可能会增加一倍或三倍,从而使基于锋利刀具参数的推荐切削条件失效,从而导致刀具损坏和制造中断。该项目将监测主轴功率以确定原位切削能量,提供准确的更新模型参数和刀具力。最重要的是,除了提供可靠的刀具力外,更新的切削能量可以提供有价值的刀具磨损信息。与当前的商业工具监控系统相比,该系统不需要费力的用户导向学习实验。在一些初步实验之后,这项工作将研究是否可以使用切削能量的绝对值和时间依赖性来告知用户主要磨损机制,刀具磨损程度和预期的剩余刀具寿命。数控验证(对零件几何形状进行虚拟加工验证)已成为一项普遍存在的技术。基于刀具力建模的工艺验证基本上可以为确定最佳加工条件提供有价值的指导。实际上,这样的系统很少被出售,原因有三。现有的系统侧重于刀具力,很少有机械师知道如何选择最佳的力廓形。这些刀具力,如果基于锋利的刀具模型参数,是不可靠的,因为刀具不可避免地会磨损。主要市场竞争者的直接销售力量很小,只能到达有限的市场。相比之下,1提出的工艺验证系统将与机械师友好的术语,如CNC性能限制和所需的表面精度接口。本项目下开发的技术解决方案将与现有的纯软件过程验证产品集成,以在工具磨损时提供可靠的、更新的工具力。集成产品将帮助机械师选择切削条件,其中更理想的磨损机制(侧面磨损)占主导地位,如果技术方案成功,则提供有价值的剩余刀具寿命估计。如果成功,该项目将对21世纪的全球制造业运营产生重大的商业影响。
英文摘要
This Small Business Innovative Research Phase 1 project will investigate the confluence of process verification and tool wear technologies. Process verification - physics-based analysis and optimization of the machining process and sequel to purely geometric NC verification - can significantly improve the reliability and productivity of 21st Century manufacturing. Physics-based systems are based on tool force modeling and depend critically on input process model parameters called cutting energies. As the tool wears, these cutting energies and associated tool forces can double or triple, invalidating recommended cutting conditions based on sharp tool parameters, leading to broken tooling and disruptions in manufacture. This project will monitor spindle power to determine the cutting energies in situ, providing accurate updated model parameters and tool forces. Most importantly, in addition to providing reliable tool forces, the updated cutting energies may provide valuable tool wear information. In contrast to current commercial tool monitoring systems, the proposed system does not require laborious user-directed learning experiments. Following on some preliminary experiments, this effort will investigate whether the absolute value and time dependence of the cutting energies can be used to inform the user of the dominant wear mechanism, the extent of the tool wear and the expected remaining tool life. NC verification (virtual machining validating the part geometry) has become an ubiquitous technology. Process verification, based on tool force modeling, in principal can provide valuable guidance in setting optimal machining conditions. In practice, very few such systems have been sold, for three reasons. 1 The available systems focus on tool forces and few, if any, machinists know how to choose optimal force profiles. 2 Those tool forces, if based on sharp tool model parameters, are not reliable as the tool inevitably wears. 3 The primary market competitors have a small direct sales force, reaching only a limited market. In contrast, 1 the proposed process verification system will interface with machinist-friendly terms such as CNC performance limits and desired surface accuracy. 2 The technical solutions developed under this project will integrate with existing software-only process verification products to include reliable, updated tool forces as the tool wears. The integrated products will assist the machinist in selecting cutting conditions where more desirable wear mechanisms (flank wear) dominate and, if the technical program is successful, provide valuable estimates of the remaining tool life. If successful, this project could have a significant commercial impact on global 21st century manufacturing operations.
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SBIR Phase II: Intelligent Tool Wear Monitoring
  • 批准号:
    0923900
  • 项目类别:
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  • 资助金额:
    $0.0万
  • 财政年份:
    2009
  • 负责人:
    Donald Esterling
  • 依托单位:
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  • 项目类别:
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  • 资助金额:
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