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- 摘要
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Hyperspectral and thermal temperature estimation during laser cladding
摘要： Although there is no doubt about the tremendous industrial potential of metal additive manufacturing techniques such as laser metal deposition, the technology still has some intrinsic quality challenges to overcome before reaching its industrial maturity. Noncontact in situ monitoring of the temperature evolution of the workpiece could provide the necessary information to implement an automated closed-loop process control system and optimize the manufacturing process, providing a robust solution to these issues. However, measuring absolute temperatures is not self-evident: wavelength-dependent emissivity values vary between solid, liquid, and mushy metallic regions, requiring spectral information and dedicated postprocessing to relate the amount of emitted infrared radiation to the material temperature. This paper compares the temperature estimation results obtained from a visible and near-infrared hyperspectral line camera and a conventional short-wave infrared (SWIR) thermal camera during the laser melting and cladding of a 316L steel sample. Both methods show agreeing results for the temperature distribution inside the melt pool, with the SWIR camera extending the temperature measurements beyond the melt pool boundaries into the solid region.
关键词： temperature estimation,laser cladding,hyperspectral imaging,additive manufacturing,thermal monitoring
更新于2025-11-28 14:24:20
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[IEEE 2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW) - YILAN, Taiwan (2019.5.20-2019.5.22)] 2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW) - Maximum Power Point Tracking of Photovoltaic System Based on Reinforcement Learning
摘要： Chip designers place on-chip thermal sensors to measure local temperatures, thus preventing thermal runaway situations in many-core processing architectures. However, the quality of the thermal reconstruction is directly dependent on the number of placed sensors, which should be minimized, while guaranteeing full detection of all the worst case temperature gradient. In this paper, we present an entire framework for the thermal management of complex many-core architectures, such that we can precisely recover the thermal distribution from a minimal number of sensors. The proposed sensor placement algorithm is guaranteed to reduce the impact of noisy measurements on the reconstructed thermal distribution. We achieve signi?cant improvements compared to the state of the art, in terms of both computational complexity and reconstruction precision. For example, if we consider a 64 cores systems-on-chip with 64 noisy sensors (s2 ? 4), we achieve an average reconstruction error of 1:5(cid:2) C, that is less than half of what previous state-of-the-art methods achieve. We also study the practical limits of the proposed method and show that we do not need realistic workloads to learn the model and ef?ciently place the sensors. In fact, we show that the reconstruction error is not significantly increased if we randomly generate the power-traces of the components or if we have just a part of the correct workload.
关键词： thermal monitoring,thermal management,Sensor placement
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Can Bad Solar Cells Make a PV Module More Efficient?
摘要： Chip designers place on-chip thermal sensors to measure local temperatures, thus preventing thermal runaway situations in many-core processing architectures. However, the quality of the thermal reconstruction is directly dependent on the number of placed sensors, which should be minimized, while guaranteeing full detection of all the worst case temperature gradient. In this paper, we present an entire framework for the thermal management of complex many-core architectures, such that we can precisely recover the thermal distribution from a minimal number of sensors. The proposed sensor placement algorithm is guaranteed to reduce the impact of noisy measurements on the reconstructed thermal distribution. We achieve signi?cant improvements compared to the state of the art, in terms of both computational complexity and reconstruction precision. For example, if we consider a 64 cores systems-on-chip with 64 noisy sensors (s2 ? 4), we achieve an average reconstruction error of 1:5(cid:2) C, that is less than half of what previous state-of-the-art methods achieve. We also study the practical limits of the proposed method and show that we do not need realistic workloads to learn the model and ef?ciently place the sensors. In fact, we show that the reconstruction error is not signi?cantly increased if we randomly generate the power-traces of the components or if we have just a part of the correct workload.
关键词： thermal management,thermal monitoring,Sensor placement
更新于2025-09-19 17:13:59
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[IEEE 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS) - Gold Coast, Australia (2019.12.16-2019.12.18)] 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS) - Comparison of Modulation Methods for Visible Light Communication System Using Organic LED
摘要： Chip designers place on-chip thermal sensors to measure local temperatures, thus preventing thermal runaway situations in many-core processing architectures. However, the quality of the thermal reconstruction is directly dependent on the number of placed sensors, which should be minimized, while guaranteeing full detection of all the worst case temperature gradient. In this paper, we present an entire framework for the thermal management of complex many-core architectures, such that we can precisely recover the thermal distribution from a minimal number of sensors. The proposed sensor placement algorithm is guaranteed to reduce the impact of noisy measurements on the reconstructed thermal distribution. We achieve signi?cant improvements compared to the state of the art, in terms of both computational complexity and reconstruction precision. For example, if we consider a 64 cores systems-on-chip with 64 noisy sensors (s2 ? 4), we achieve an average reconstruction error of 1:5(cid:2) C, that is less than half of what previous state-of-the-art methods achieve. We also study the practical limits of the proposed method and show that we do not need realistic workloads to learn the model and ef?ciently place the sensors. In fact, we show that the reconstruction error is not significantly increased if we randomly generate the power-traces of the components or if we have just a part of the correct workload.
关键词： thermal monitoring,thermal management,Sensor placement
更新于2025-09-16 10:30:52