ASAP - Advanced electromagnetic Sensors for Assessing Property scatter in high value steels

ASAP - 用于评估高价值钢材性能分散的先进电磁传感器

• 批准号: EP/K027700/1
• 负责人: Anthony Peyton
• 金额: $ 40.63万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FK027700%2F1
• 关键词: ASAP; Advanced; electromagnetic; Sensors; Assessing

The development of new techniques to measure the microstructure of a material in a non-contact non-destructive fashion can lead to a dramatic improvement in the understanding of the material and its behaviour during processing and in-service. This, in turn, can lead to a greater ability to control the material properties and predict the evolution of these properties. At present, the majority of microstructural analysis techniques are destructive and / or require small samples. Consequently, existing techniques are limited in applicability especially if dynamic microstructural control during commercial processing is of interest. Several techniques have been proposed to directly measure microstructures in these situations but, as yet, no single technique offers a full solution. It is well known that the microstructure is directly related to the mechanical properties of steel, therefore if the microstructure can be measured on-line during processing, and the inherent variability in microstructure can be assessed (on-line or off-line), then the mechanical properties (including any scatter) can be inferred. This could provide enormous saving to the manufacturing industry as product quality can be improved through real-time feedback for processing control and / or reduction (or better still elimination) of the off-line destructive mechanical testing for release specifications. In this context, our proposal focuses directly on advanced sensors for measuring the key microstructural parameters that are directly linked to mechanical properties in high value steels.Our ambition is to exploit novel electromagnetic (EM) techniques to analyse microstructure directly, and therefore to infer mechanical properties, for a range of advanced steel types during and after processing. Typically these EM techniques have included multi-frequency interrogation combined with advanced signal and data processing and modelling. Both the UK and Indian teams have successfully considered the electromagnetic response, using different sensor types, to component phase fractions (such as ferrite), which in the UK has been supported by 3D modelling of both idealised and realistic microstructures. In parallel, the problem of inverting the complex inductance spectra acquired by the sensor systems to yield parameters of metallurgical significance has been addressed, and in India a link between sensor output and mechanical properties for relatively simple steels has been established. In the EU sensor configurations that can be deployed on-line for phase transformation monitoring by measuring the mutual inductance have been successfully tested, in collaboration with Tata Steel Europe, and are now in the process of being commercially exploited via a licensing agreement with an external company. The natural next step in the research is to combine EM sensor techniques to exploit the full electromagnetic characteristics of steel (for example using sensors that measure coercivity, saturation and incremental permeability) to characterise the more complex microstructures, and their spatial inhomogeneity, in advanced steels. This requires collaboration between the leading international groups on sensor design, implementation and microstructure-signal relationships. On-line deployment of these systems will allow greater feedback control during processing to enable these advanced steels to be produced on older as well as new mills. Mechanical property determination, through the microstructure-property relationships, provides the potential to reduce or eliminate the off-line property release tests that are currently performed with a significant saving to the industry.

以非接触非破坏性方式测量材料微观结构的新技术的发展可以大大提高对材料及其在加工和使用过程中的行为的理解。这反过来又可以提高控制材料性能和预测这些性能演变的能力。目前，大多数显微结构分析技术是破坏性的和/或需要小样品。因此，现有技术的适用性有限，特别是如果在商业加工过程中的动态微观结构控制是感兴趣的。已经提出了几种技术来直接测量这些情况下的微观结构，但到目前为止，没有一种技术提供了完整的解决方案。众所周知，微观结构与钢的机械性能直接相关，因此，如果可以在加工过程中在线测量微观结构，并且可以评估微观结构的固有可变性（在线或离线），则可以推断机械性能（包括任何分散）。这可以为制造业提供巨大的节省，因为可以通过用于处理控制的实时反馈和/或减少（或更好地消除）用于发布规范的离线破坏性机械测试来提高产品质量。在这种情况下，我们的建议直接集中在先进的传感器上，用于测量与高价值钢的机械性能直接相关的关键微观结构参数。我们的目标是利用新的电磁（EM）技术直接分析微观结构，从而推断加工过程中和加工后的一系列先进钢类型的机械性能。通常，这些EM技术包括与先进的信号和数据处理和建模相结合的多频询问。英国和印度的团队都成功地考虑了电磁响应，使用不同的传感器类型，成分相分数（如铁氧体），这在英国得到了理想化和现实微观结构的3D建模的支持。与此同时，已经解决了将传感器系统获得的复杂电感谱反转以产生具有冶金意义的参数的问题，并且在印度已经建立了传感器输出与相对简单的钢的机械性能之间的联系。在欧盟，与Tata Steel Europe合作成功测试了可通过测量互感在线部署用于相变监测的传感器配置，目前正通过与外部公司的许可协议进行商业开发。研究的下一步自然是将联合收割机EM传感器技术结合起来，利用钢的全部电磁特性（例如使用测量磁导率、饱和度和增量磁导率的传感器），以消除先进钢中更复杂的微观结构及其空间不均匀性。这需要在传感器设计、实施和微结构-信号关系方面的领先国际团体之间进行合作。这些系统的在线部署将允许在加工期间进行更大的反馈控制，以使这些先进的钢能够在旧的和新的米尔斯上生产。通过微观结构-性能关系的机械性能测定提供了减少或消除离线性能释放测试的可能性，该离线性能释放测试目前在显著节省工业成本的情况下进行。

项目成果

Magnetic characterisation of grain size and precipitate distribution by major and minor BH loop measurements

• DOI: 10.1016/j.jmmm.2019.02.088
• 发表时间: 2019-07-01
• 期刊: JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS
• 影响因子: 2.7
• 作者: Liu，Jun;Wilson，John;Peyton，Anthony
• 通讯作者: Peyton，Anthony

Magnetic characterisation of microstructural feature distribution in P9 and T22 steels by major and minor BH loop measurements

• DOI: 10.1016/j.jmmm.2015.10.075
• 发表时间: 2016-03-01
• 期刊: JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS
• 影响因子: 2.7
• 作者: Liu, Jun;Wilson, John;Peyton, Anthony
• 通讯作者: Peyton, Anthony

Reducing the Lift-Off Effect on Permeability Measurement for Magnetic Plates From Multifrequency Induction Data

• DOI: 10.1109/tim.2017.2728338
• 发表时间: 2018-01-01
• 期刊: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
• 影响因子: 5.6
• 作者: Lu, Mingyang;Zhu, Wenqian;Qu, Zhigang
• 通讯作者: Qu, Zhigang

Monitoring of power station steels using electromagnetic sensors

使用电磁传感器监测电站钢材

• 发表时间: 2014
• 作者: Karimian Noushin

Non-destructive characterisation of N/Al level in P91 steels using electromagnetic sensors

使用电磁传感器无损表征 P91 钢中的 N/Al 水平

• DOI: 10.1179/1743284714y.0000000642
• 发表时间: 2014
• 期刊: Materials Science and Technology
• 影响因子: 1.8
• 作者: Liu J