Using Capacitance Sensor to Extract Characteristic Signals of Dozing from Skin Surface

Skin is the largest organ of the human body and a physiological structure that is directly exposed to the environment. From a theoretical perspective, numerous physiological and psychological signals use the skin as a medium for input and output with the outside world. Therefore, the skin is considered an optimal signal interception point when developing noninvasive, direct, and rapid signal exploration devices. To date, skin signal interceptions are predominantly performed by measuring skin impedance. However, this method is prone to interference such as sweat secretion, salt accumulation on the skin, and muscle contractions, which may result in a substantial amount of interference and erroneous results. The present study proposes novel and effective methods for skin signal interception, such as using a nested probe as a sensor to measure capacitance to be further processed as physiological and psychological signals. The experimental results indicate that the capacitance curve for the transition between wakefulness and dozing exhibits significant changes. This change in the curve can be analyzed by computer programs to clearly and rapidly determine whether the subject has entered the initial phases of sleep

Monitoring of Biodiesel Transesterification Process Using Impedance Measurement

Alternative diesel fuels have been the subject of extensive investigation. Fatty acid methyl ester (FAME) based Biodiesel manufactured from vegetable oils or animal fats is an excellent candidate to replace common diesel fuel being renewable, non-toxic and often giving rise to reduced exhaust gas emissions. The transesterification process has been commonly and widely used to produce biodiesel from vegetable oil or animal fat. Vegetable oils or animal fats generally have viscosities higher than standard diesel oil. This means that it is necessary to reduce the viscosity by means of reacting vegetable oil with alcohol in the presence of a suitable catalyst. The target product for this reaction is methyl ester, with glycerol and potentially soap produced as by products with the process of transesterification. Methylester (Biodiesel) is produced by converting triglycerides to alkylesters. A batch transesterification process has two significant mechanisms, and exhibits a mass transfer controlled region that precedes a second order kinetically controlled region. In order to control the conversion process it is useful to employ process monitoring. In particular monitoring of the mass transfer processes that limits the initial reaction rates could prove to be beneficial in allowing for process optimization and control. This thesis proposes the use of a new method of biodiesel process monitoring using low frequency (15kHz) impedance sensing which is able to provide information regarding the progress of mass transfer and chemical reaction during biodiesel production. An interdigitated (ID) sensor has been used to monitoring the biodiesel process The ID sensor is of simple construction and consists of two sets of interleaved electrodes (fingers). The two sets of electrodes are separated by a gap and when an AC excitation voltage is applied across the interleaved electrodes an oscillating electric field is developed. The response of the fluid surrounding the sensor to the applied excitation was then used to determine progress of the chemical reaction by evaluating the real and complex impedance. A significant and unambiguous change in the components of impedance has been shown to occur during mixing (mass transfer) and transesterification. The impedance measurements gained during transesterification were then used for the development of a system model. A systematic approach was used to select mathematical models and system identification techniques were evaluated. The system identification investigation used real process measurement data in conjunction with the Matlab system identification toolbox

SUSTAINABLE AND MOBILITY TECHNOLOGIES FOR ASSISTIVE HEALTHCARE AND MONITORING

Ph.DDOCTOR OF PHILOSOPH

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 122, December 1973

This special bibliography lists 343 reports, articles, and other documents introduced into the NASA scientific and technical information system in November 1973

Advanced Automation for Space Missions

The feasibility of using machine intelligence, including automation and robotics, in future space missions was studied

Commissioning adiabatic oven testing - an inter-laboratory comparison

Adiabatic oven testing for spontaneous combustion assessment has been a primary method used by the Australian and New Zealand coal industries for input to the development of Principal Hazard Management Plans for mining operations. Consistency of results is important to ensure that the ratings obtained are accurate and reliable for maintaining the integrity of the database used to compare between mines and for obtaining site specific relationships. This paper presents the results from commissioning tests of four new adiabatic ovens at two different laboratories, which show the high level of reproducibility and repeatability needed for confidence in planning of future mining operations. The results cover a range of coal self-heating rates to show the validity of the testing and the reliability of the adiabatic ovens

RISKGATE and Australian coal operations

The major Australian Coal Association Research Program (ACARP) project, RISKGATE has now completed three years of knowledge capture and system development. The body of knowledge for risk management of tyres, collisions, fires, isolation, strata underground, ground control open cut, explosions, explosives underground, explosives open cut, manual tasks and slips/trips/falls was launched in December 2012. Recently, the project added knowledge about outbursts, coal bumps and bursts, human-machine interface, tailings dams, occupational hygiene and inrush to the original 11 topics. In 2014, the project plans (pending ACARP funding approval) to focus on issues around Fitness for Work. RISKGATE provides an environment for knowledge capture and knowledge exchange to drive innovation and cross industry sharing of current practice in the identification, assessment and management of risk. By capturing operational knowledge from industry experts, RISKGATE provides a cumulative corporate memory at a time of high personnel turnover in the coal industry. RISKGATE is the largest single ACARP Occupational Health and Safety (OHS) initiative to date. This paper presents an overview of the first seventeen topics, topic structures, and contrasts and inter-relationships between topics. The second part of the paper discusses some early steps that companies are taking to integrate RISKGATE into their operations; and conclude with some thoughts on where RISKGATE can go in the future

Comparative analysis of coal fatalities in Australia, South Africa, India, China and USA, 2006-2010

Coal mining (especially underground) is considered one of the most hazardous industries, and as a result considerable focus is applied to eliminating or mitigating hazards through careful mine planning, equipment selection and certification, and development of management systems and procedures. Regulatory agencies have developed in-house methods for reporting, classification and tracking of fatalities and other incidents according to the type of event, often including consideration of different hazard types. Unfortunately, direct comparison of mining safety statistics between countries is confounded by considerable differences in the way that individual countries classify specific fatalities or incidents. This paper presents a comparative analysis of coal mining fatality data in Australia, South Africa, India, China and the United States from 2006 to 2010. Individual classification definitions are compared between the five countries, and methods presented to normalise each country’s hazard definitions and reporting regimes around the RISKGATE framework of seventeen different priority unwanted events (or topics). Fatality data from individual countries is then re-classified according to the different RISKGATE topics, thereby enabling a comparative analysis between all five countries. This paper demonstrates the utility and value of a standard classification approach, and submits the RISKGATE framework as a model for classification that could be applied globally in coal mining. RISKGATE is the largest health and safety project ever funded by the Australian coal industry (http://www.riskgate.org) to build an industry body of knowledge to assist in managing common industry hazards. A comprehensive knowledge base has been captured for risk management of tyres, collisions, fires, isolation, strata underground, ground control open cut, explosions, explosives, manual tasks and slips/trips/falls. This has been extended to outburst, coal burst and bumps, interface displays and controls, tailings dams and inrush

Is carbon monoxide sensing an effective early fire detection option for underground coal mines?

The ability of carbon monoxide (CO) sensing to detect early stage smouldering of fixed plant fires in underground coal mines was recently assessed as part of an ongoing fire detection research project. Experiments were carried out to record the level of CO concurrent at the time of alarm activation of a Video Based Fire Detection (VBFD) system. The tests were carried out under simulated mine conditions within the SIMTARS facility at Redbank, Queensland. The experimental setup initially located the CO sensors in the positions at where they would typically be installed underground. On testing the experimental setup, it was found that the amount of CO produced from simulated overheating conveyor belt bearing housings did not display a reading on the CO sensors. The VBFD system however detected smoke and alarmed on each of the trial tests. To enable the experiments to proceed and a comparison to be made, the CO sensors were moved considerably closer to the weak pyrolysis fire source. The question of CO sensor capability in typical operational mine positions was highlighted as a result of this experiment. Computational Fluid Dynamics (CFD) modelling was used to estimate the fire size required to activate CO sensors under typical mining conditions. This modelling reinforced the limitations in using CO detectors on fixed plant. As such, the study presented here indicates that CO sensing may not be the most effective early fire detection option available, and that further research and development work with VBFD should be undertaken