Real-time detection of grip length deviation for fastening operations: a Mahalanobis-Taguchi system (MTS) based approach

Hand-held fastening tools are extensively used in manufacturing, especially in aerospace industry. Typically, the process is monitored by the operator and joints are visually inspected after the process is completed. When complex products, such as an aircraft, are considered, fastening process and its inspection can be very time consuming. In addition, no inspection data is typically collected during the process unless a major problem is encountered. Real-time monitoring and verification of the fastening process of joint quality are two important advancements to reduce the manufacturing lead time while ensuring safety and quality --Abstract, page iv

Neonatal non-contact respiratory monitoring based on real-time infrared thermography

<p>Abstract</p> <p>Background</p> <p>Monitoring of vital parameters is an important topic in neonatal daily care. Progress in computational intelligence and medical sensors has facilitated the development of smart bedside monitors that can integrate multiple parameters into a single monitoring system. This paper describes non-contact monitoring of neonatal vital signals based on infrared thermography as a new biomedical engineering application. One signal of clinical interest is the spontaneous respiration rate of the neonate. It will be shown that the respiration rate of neonates can be monitored based on analysis of the anterior naris (nostrils) temperature profile associated with the inspiration and expiration phases successively.</p> <p>Objective</p> <p>The aim of this study is to develop and investigate a new non-contact respiration monitoring modality for neonatal intensive care unit (NICU) using infrared thermography imaging. This development includes subsequent image processing (region of interest (ROI) detection) and optimization. Moreover, it includes further optimization of this non-contact respiration monitoring to be considered as physiological measurement inside NICU wards.</p> <p>Results</p> <p>Continuous wavelet transformation based on Debauches wavelet function was applied to detect the breathing signal within an image stream. Respiration was successfully monitored based on a 0.3°C to 0.5°C temperature difference between the inspiration and expiration phases.</p> <p>Conclusions</p> <p>Although this method has been applied to adults before, this is the first time it was used in a newborn infant population inside the neonatal intensive care unit (NICU). The promising results suggest to include this technology into advanced NICU monitors.</p

Artificial intelligence and machine learning: changing paradigm in diagnostics and imaging

Healthcare industry is currently undergoing a digital transformation, and Artificial Intelligence (AI) is the latest buzzword in the healthcare domain. The accuracy and efficiency of AI-based decisions are already been heard across countries. Moreover, the increasing availability of electronic clinical data can be combined with big data analytics to harness the power of AI applications in healthcare. Like other countries, the Indian healthcare industry has also witnessed the growth of AI-based applications. A review of the literature for data on AI and machine learning was conducted. In this article, we discuss AI, the need for AI in healthcare, and its current status. An overview of AI in the Indian healthcare setting has also been discussed

Digital Infrared Thermal Imaging and its use in Domestic and Non-Domestic Species

Digital infrared thermal imaging (DITI) is a non-invasive diagnostic technique that is used to detect symmetry and asymmetry of surface temperature gradients. DITI can examine many different aspects of thermal physiology and diagnose injury and disease. The objectives of this study were (1) to investigate the use of DITI to determine whether differences in temperature gradients exist between late gestation and non-pregnant mares, (2) to evaluate whether velvet antler (VA) temperature gradients, as measured by DITI would pattern VA growth, and (3) to determine if “normal” temperature gradients of the foot exist among elephants as detected using DITI. To investigate these objectives, three experiments were conducted to determine the value of DITI for research on mammals. Results obtained from the first study indicate DITI was able to detect pregnancy in the horse during late gestation. In the second study DITI successfully patterned the growth and hardening of VA. While in the third study DITI demonstrated its value as a tool to increase overall welfare for captive elephants. In summary these studies suggests that DITI may have value in conducting research with domestic and non-domestic species that are not able to be restrained

Digital Infrared Thermal Imaging and its use in Domestic and Non-Domestic Species

Digital infrared thermal imaging (DITI) is a non-invasive diagnostic technique that is used to detect symmetry and asymmetry of surface temperature gradients. DITI can examine many different aspects of thermal physiology and diagnose injury and disease. The objectives of this study were (1) to investigate the use of DITI to determine whether differences in temperature gradients exist between late gestation and non-pregnant mares, (2) to evaluate whether velvet antler (VA) temperature gradients, as measured by DITI would pattern VA growth, and (3) to determine if “normal” temperature gradients of the foot exist among elephants as detected using DITI. To investigate these objectives, three experiments were conducted to determine the value of DITI for research on mammals. Results obtained from the first study indicate DITI was able to detect pregnancy in the horse during late gestation. In the second study DITI successfully patterned the growth and hardening of VA. While in the third study DITI demonstrated its value as a tool to increase overall welfare for captive elephants. In summary these studies suggests that DITI may have value in conducting research with domestic and non-domestic species that are not able to be restrained

The use of multispectral sensing techniques to detect ponderosa pine trees under stress from insect or pathogenic organisms Annual progress report

Ground and aerial imaging techniques to detect tree damage caused by bark beetles in forested area

An Assessment on the Non-Invasive Methods for Condition Monitoring of Induction Motors

The ability to forecast motor mechanical faults at incipient stages is vital to reducing maintenance costs, operation downtime and safety hazards. This paper synthesized the progress in the research and development in condition monitoring and fault diagnosis of induction motors. The motor condition monitoring techniques are mainly classified into two categories that are invasive and non-invasive techniques. The invasive techniques are very basic, but they have some implementation difficulties and high cost. The non-invasive methods, namely MCSA, PVA and IPA, overcome the disadvantages associated to invasive methods. This book chapter reviews the various non-invasive condition monitoring methods for diagnosis of mechanical faults in induction motor and concludes that the instantaneous power analysis (IPA) and Park vector analysis (PVA) methods are best suitable for the diagnosis of small fault signatures associated to mechanical faults. Recommendations for the future research in these areas are also presented