Thermal vulnerability detection in integrated electronic and photonic circuits using IR thermography

• URL: http://arxiv.org/abs/2006.12201v1
• Date: Fri, 1 May 2020 09:25:55 GMT
• Title: Thermal vulnerability detection in integrated electronic and photonic circuits using IR thermography
• Authors: Bilal Hussain, Bushra Jalil, Maria Antonietta Pascali, Muhammad Imran, Giovanni Serafino, Davide Moroni and Paolo Ghelfi
• Abstract summary: This work presents an IR-assisted thermal vulnerability detection technique suitable for photonic as well as electronic components. For the first time, the reliability testing is extended to a fully functional microwave photonic system using conventional IR thermography.
• Score: 1.8809094132625916
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Failure prediction of any electrical/optical component is crucial for estimating its operating life. Using high temperature operating life (HTOL) tests, it is possible to model the failure mechanisms for integrated circuits. Conventional HTOL standards are not suitable for operating life prediction of photonic components owing to their functional dependence on thermo-optic effect. This work presents an IR-assisted thermal vulnerability detection technique suitable for photonic as well as electronic components. By accurately mapping the thermal profile of an integrated circuit under a stress condition, it is possible to precisely locate the heat center for predicting the long-term operational failures within the device under test. For the first time, the reliability testing is extended to a fully functional microwave photonic system using conventional IR thermography. By applying image fusion using affine transformation on multimodal acquisition, it was demonstrated that by comparing the IR profile and GDSII layout, it is possible to accurately locate the heat centers along with spatial information on the type of component. Multiple IR profiles of optical as well as electrical components/circuits were acquired and mapped onto the layout files. In order to ascertain the degree of effectiveness of the proposed technique, IR profiles of CMOS RF and digital circuits were also analyzed. The presented technique offers a reliable automated identification of heat spots within a circuit/system.

Related papers

• In-Situ Infrared Camera Monitoring for Defect and Anomaly Detection in Laser Powder Bed Fusion: Calibration, Data Mapping, and Feature Extraction [0.26999000177990923]
  Laser powder bed fusion (LPBF) process can incur defects due to melt pool instabilities, spattering, temperature increase, and powder spread anomalies. Identifying defects through in-situ monitoring typically requires collecting, storing, and analyzing large amounts of data generated.
  arXiv  Detail & Related papers  (2024-07-17T16:02:22Z)
• Enhanced Imaging of Electronic Hot Spots Using Quantum Squeezed Light [0.0]
  thermoreflective imaging is being used to perform precise temporal and spatial imaging of heat on wires and semiconductor materials. We apply quantum squeezed light to perform thermoreflective imaging on micro-wires, surpassing the shot-noise limit of classical approaches.
  arXiv  Detail & Related papers  (2024-03-22T16:55:46Z)
• Thermal Crosstalk Modelling and Compensation Methods for Programmable Photonic Integrated Circuits [0.0]
  We train and experimentally evaluate three models to predict the effect of thermal crosstalk in different locations of an integrated programmable photonic mesh. We experimentally validate the models through compensation of the crosstalk-induced wavelength shift. We evaluate the generalization capabilities of one of the models by employing it to predict and compensate for the effect of thermal crosstalk for parts of the chip it was not trained on.
  arXiv  Detail & Related papers  (2024-03-19T21:19:54Z)
• TCI-Former: Thermal Conduction-Inspired Transformer for Infrared Small Target Detection [58.00308680221481]
  Infrared small target detection (ISTD) is critical to national security and has been extensively applied in military areas. Most ISTD networks focus on designing feature extraction blocks or feature fusion modules, but rarely describe the ISTD process from the feature map evolution perspective. We propose Thermal Conduction-Inspired Transformer (TCI-Former) based on the theoretical principles of thermal conduction.
  arXiv  Detail & Related papers  (2024-02-03T05:51:22Z)
• Critical heat flux diagnosis using conditional generative adversarial networks [0.0]
  The critical heat flux (CHF) is an essential safety boundary in boiling heat transfer processes employed in high heat flux thermal-hydraulic systems. This study presents a data-driven, image-to-image translation method for reconstructing thermal data of a boiling system at CHF.
  arXiv  Detail & Related papers  (2023-05-04T07:53:04Z)
• Does Thermal Really Always Matter for RGB-T Salient Object Detection? [153.17156598262656]
  This paper proposes a network named TNet to solve the RGB-T salient object detection (SOD) task. In this paper, we introduce a global illumination estimation module to predict the global illuminance score of the image. On the other hand, we introduce a two-stage localization and complementation module in the decoding phase to transfer object localization cue and internal integrity cue in thermal features to the RGB modality.
  arXiv  Detail & Related papers  (2022-10-09T13:50:12Z)
• Weak Thermal State Quadrature-Noise Shadow Imaging [0.0]
  We demonstrate the possibility to create an image of an opaque object using a few-photon thermal optical field. We show that such thermal QSI scheme has an advantage over the classical differential imaging when the effect of dark counts is considered.
  arXiv  Detail & Related papers  (2022-02-04T16:57:15Z)
• Meta-UDA: Unsupervised Domain Adaptive Thermal Object Detection using Meta-Learning [64.92447072894055]
  Infrared (IR) cameras are robust under adverse illumination and lighting conditions. We propose an algorithm meta-learning framework to improve existing UDA methods. We produce a state-of-the-art thermal detector for the KAIST and DSIAC datasets.
  arXiv  Detail & Related papers  (2021-10-07T02:28:18Z)
• Adiabatic Sensing Technique for Optimal Temperature Estimation using Trapped Ions [64.31011847952006]
  We propose an adiabatic method for optimal phonon temperature estimation using trapped ions. The relevant information of the phonon thermal distributions can be transferred to the collective spin-degree of freedom. We show that each of the thermal state probabilities is adiabatically mapped onto the respective collective spin-excitation configuration.
  arXiv  Detail & Related papers  (2020-12-16T12:58:08Z)
• Exploring Thermal Images for Object Detection in Underexposure Regions for Autonomous Driving [67.69430435482127]
  Underexposure regions are vital to construct a complete perception of the surroundings for safe autonomous driving. The availability of thermal cameras has provided an essential alternate to explore regions where other optical sensors lack in capturing interpretable signals. This work proposes a domain adaptation framework which employs a style transfer technique for transfer learning from visible spectrum images to thermal images.
  arXiv  Detail & Related papers  (2020-06-01T09:59:09Z)
• Thermal phase shifters for femtosecond laser written photonic integrated circuits [58.720142291102135]
  Photonic integrated circuits (PICs) are acknowledged as an effective solution to fulfill the demanding requirements of many practical applications in both classical and quantum optics. Phase shifters integrated in the photonic circuit offer the possibility to dynamically reconfigure its properties in order to fine tune its operation or to produce adaptive circuits. We show how thermal shifters to reconfigure photonic circuits can be solved by a careful design of the thermal shifters and by choosing the most appropriate way to drive them.
  arXiv  Detail & Related papers  (2020-04-23T20:09:56Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.