Thermal vulnerability detection in integrated electronic and photonic circuits using infrared thermography.

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 the thermo-optic effect. This work presents an infrared (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 complementary metal-oxide semiconductor RF and digital circuits were also analyzed. The presented technique offers a reliable automated identification of heat spots within a circuit/system.

Fault Detection in Power Equipment via an Unmanned Aerial System Using Multi Modal Data.

The power transmission lines are the link between power plants and the points of consumption, through substations. Most importantly, the assessment of damaged aerial power lines and rusted conductors is of extreme importance for public safety; hence, power lines and associated components must be periodically inspected to ensure a continuous supply and to identify any fault and defect. To achieve these objectives, recently, Unmanned Aerial Vehicles (UAVs) have been widely used; in fact, they provide a safe way to bring sensors close to the power transmission lines and their associated components without halting the equipment during the inspection, and reducing operational cost and risk. In this work, a drone, equipped with multi-modal sensors, captures images in the visible and infrared domain and transmits them to the ground station. We used state-of-the-art computer vision methods to highlight expected faults (i.e., hot spots) or damaged components of the electrical infrastructure (i.e., damaged insulators). Infrared imaging, which is invariant to large scale and illumination changes in the real operating environment, supported the identification of faults in power transmission lines; while a neural network is adapted and trained to detect and classify insulators from an optical video stream. We demonstrate our approach on data captured by a drone in Parma, Italy.

A Pilot Study of Infrared Thermography Based Assessment of Local Skin Temperature Response in Overweight and Lean Women during Oral Glucose Tolerance Test.

Obesity is recognized as a major public health issue, as it is linked to the increased risk of severe pathological conditions. The aim of this pilot study is to evaluate the relations between adiposity (and biophysical characteristics) and temperature profiles under thermoneutral conditions in normal and overweight females, investigating the potential role of heat production/dissipation alteration in obesity. We used Infrared Thermography (IRT) to evaluate the thermogenic response to a metabolic stimulus performed with an oral glucose tolerance test (OGTT). Thermographic images of the right hand and of the central abdomen (regions of interests) were obtained basally and during the oral glucose tolerance test (3 h OGTT with the ingestion of 75 g of oral glucose) in normal and overweight females. Regional temperature vs BMI, % of body fat and abdominal skinfold were statistically compared between two groups. The study showed that mean abdominal temperature was significantly greater in lean than overweight participants (34.11 ± 0.70 °C compared with 32.92 ± 1.24 °C, p < 0.05). Mean hand temperature was significantly greater in overweight than lean subjects (31.87 ± 3.06 °C compared with 28.22 ± 3.11 °C, p < 0.05). We observed differences in temperature profiles during OGTT between lean and overweight subjects: The overweight individuals depict a flat response as compared to the physiological rise observed in lean individuals. This observed difference in thermal pattern suggests an energy rate imbalance towards nutrients storage of the overweight subjects.

Assessment of hand superficial oxygenation during ischemia/reperfusion in healthy subjects versus systemic sclerosis patients by 2D near infrared spectroscopic imaging.

BACKGROUND AND OBJECTIVE: Patients affected by systemic sclerosis (SSc) develop functional and structural microcirculatory dysfunction, which progressively evolves towards systemic tissue fibrosis (sclerosis). Disease initially affects distal extremities, which become preferential sites of diagnostic scrutiny. This pilot investigation tested the hypothesis that peripheral microcirculatory dysfunction in SSc could be non-invasively assessed by 2D Near Infrared Spectroscopic (NIRS) imaging of the hand associated with Vascular Occlusion Testing (VOT). NIRS allows measurement of hemoglobin oxygen saturation (StO2) in the blood perfusing the volume tissue under scrutiny. METHODS: In five normal volunteers and five SSc patients we applied a multispectral oximetry imaging device (Kent camera, Kent Imaging, Calgary, Canada) to acquire StO2 2D maps of the whole hand palm during baseline, ischemia and reperfusion phase. RESULTS: We found significant differences between controls and SSc patients in basal StO2 (82.80 ±â€¯2.51 vs 65.44 ±â€¯7.96%, p = 0.0016), minimum StO2 (59.35 ±â€¯4.29 vs 40.73 ±â€¯6.47%, p = 0.0007), final StO2 (83.83 ±â€¯4.09 vs 68.84 ±â€¯11.41%, p = 0.02) and time to maximum StO2 (40 ±â€¯12.25 vs 62 ±â€¯4.47 s, p = 0.005). CONCLUSIONS: This is, to our knowledge, the first application of 2D NIRS imaging of the whole hand to the investigation of microvascular dysfunction in systemic sclerosis. The image processing presented here considered the StO2 in the entire hand allowing a comprehensive view of the spatial heterogeneity of microvascular dysfunction.