Fiber Bragg Grating Sensors for Real Time Monitoring of Evacuation Process

Fiber bragg grating (FBG) sensors have been widely used for number of sensing applications like temperature, pressure, acousto-ultrasonic, static and dynamic strain, refractive index change measurements and so on. Present work demonstrates the use of FBG sensors in in-situ measurement of vacuum process with simultaneous leak detection capability. Experiments were conducted in a bell jar vacuum chamber facilitated with conventional Pirani gauge for vacuum measurement. Three different experiments have been conducted to validate the performance of FBG sensor in monitoring vacuum creating process and air bleeding. The preliminary results of FBG sensors in vacuum monitoring have been compared with that of commercial Pirani gauge sensor. This novel technique offers a simple alternative to conventional method for real time monitoring of evacuation process. Proposed FBG based vacuum sensor has potential applications in vacuum systems involving hazardous environment such as chemical and gas plants, automobile industries, aeronautical establishments and leak monitoring in process industries, where the electrical or MEMS based sensors are prone to explosion and corrosion.

Solid state electrochemical sensor for monitoring Mg in Al refining process

Novel solid-state electrochemical sensors have been designed using the Mg2+ cation conductors incorporating novel solid-state reference electrodes for in-line monitoring of Mg in molten Al during the refining process and also for in-line monitoring of Mg content in molten Al in the alloying process. In this paper we report the preparation of Mg2+ ion conductors, MgAl2O4 and MgZr4(PO4)6, by the solid state ceramic synthesis route, measurement of their electrical properties using ac-impedance spectroscopy and application of the above cation conductors for designing novel electrochemical sensors for monitoring Mg dissolved in molten Al. The activation energy for Mg2+ ion conduction in MgAl2O4 is 2.08 eV and in MgZr4(PO4)6 is 1.7 eV, respectively. The sensors have been found to respond rapidly to change in Mg content in molten aluminium around 1000 K.

Monitoring A Micromechanical Process In Macroscale Carbon Nanotube Films And Fibers

The evaluation of mechanical properties of carbon nanotube (CNT) fibers is inherently difficult. Here, Raman scattering-a generic methodology independent of mechanical measurements-is used to determine the interbundle strength and microscopic failure process for various CNT macroarchitectures. Raman data are used to predict the moduli of CNT films and fibers, and to illustrate the influences of the twisting geometries on the fibers' mechanical performances.

Wind-driven desertification: process modeling, remote monitoring, and forecasting

Arid and semiarid landscapes comprise nearly a third of the Earth's total land surface. These areas are coming under increasing land use pressures. Despite their low productivity these lands are not barren. Rather, they consist of fragile ecosystems vulnerable to anthropogenic disturbance.

The purpose of this thesis is threefold: (I) to develop and test a process model of wind-driven desertification, (II) to evaluate next-generation process-relevant remote monitoring strategies for use in arid and semiarid regions, and (III) to identify elements for effective management of the world's drylands.

In developing the process model of wind-driven desertification in arid and semiarid lands, field, remote sensing, and modeling observations from a degraded Mojave Desert shrubland are used. This model focuses on aeolian removal and transport of dust, sand, and litter as the primary mechanisms of degradation: killing plants by burial and abrasion, interrupting natural processes of nutrient accumulation, and allowing the loss of soil resources by abiotic transport. This model is tested in field sampling experiments at two sites and is extended by Fourier Transform and geostatistical analysis of high-resolution imagery from one site.

Next, the use of hyperspectral remote sensing data is evaluated as a substantive input to dryland remote monitoring strategies. In particular, the efficacy of spectral mixture analysis (SMA) in discriminating vegetation and soil types and detennining vegetation cover is investigated. The results indicate that hyperspectral data may be less useful than often thought in determining vegetation parameters. Its usefulness in determining soil parameters, however, may be leveraged by developing simple multispectral classification tools that can be used to monitor desertification.

Finally, the elements required for effective monitoring and management of arid and semiarid lands are discussed. Several large-scale multi-site field experiments are proposed to clarify the role of wind as a landscape and degradation process in dry lands. The role of remote sensing in monitoring the world's drylands is discussed in terms of optimal remote sensing platform characteristics and surface phenomena which may be monitored in order to identify areas at risk of desertification. A desertification indicator is proposed that unifies consideration of environmental and human variables.

Rapid automated in-situ monitoring of total dissolved iron and total dissolved manganese in underground water by reverse-flow injection with chemiluminescence detection during the process of water treatment

Measurement of iron and manganese is very important in evaluating the quality of natural waters. We have constructed an automated Fe(II), total dissolved iron(TDI), Mn(II), and total dissolved manganese(TDM) analysis system for the quality control of underground drinking water by reverse flow injection analysis and chemiluminescence detection(rFIA-CL), The method is based on the measurement of the metal-catalyzed light emission from luminol oxidation by potassium periodate. The typical signal is a narrow peak, in which the height is proportional to light emitted and hence to the concentration of metal ions. The detection limits were 3 x 10(-6) mu g ml(-1) for Fe(II) and the linear range extents up to 1.0 x 10(-4) and 5 x 10(-6) mu g ml(-1) for Mn(II) cover a linear range to 1.0 x 10(-4) mu g ml(-1). This method was used for automated in-situ monitoring of total dissolved iron and total dissolved in underground water during water treatment. (C) 1997 Elsevier Science B.V.

Plug Force Monitoring for the Control and Optimisation of the Thermoforming Process

Thermoforming processes generally employ sheet temperature monitoring as the primary means of process control. In this paper the development of an alternative system that monitors plug force is described. Tests using a prototype device have shown that the force record over a forming cycle creates a unique map of the process operation. Key process features such as the sheet modulus, sheet sag and the timing of the process stages may be readily observed, and the effects of changes in all of the major processing parameters are easily distinguished. Continuous, cycle-to-cycle tests show that the output is consistent and repeatable over a longer time frame, providing the opportunity for development of an on-line process control system. Further testing of the system is proposed.

Development of remote monitoring process tools for biomass fired bubbling fluidized bed boilers

Remote monitoring of a power boiler allows the supplying company to make sure that equipment is used as supposed to and gives a good chance for process optimization. This improves co-operation between the supplier and the customer and creates an aura of trust that helps securing future contracts. Remote monitoring is already in use with recovery boilers but the goal is to expand especially to biomass-fired BFB-boilers. To make remote monitoring possible, data has to be measured reliably on site and the link between the power plant and supplying company’s server has to work reliably. Data can be gathered either with the supplier’s sensors or with measurements originally installed in the power plant if the plant in question is not originally built by the supplying company. Main goal in remote monitoring is process optimization and avoiding unnecessary accidents. This can be achieved for instance by following the efficiency curves and fouling in different parts of the process and comparing them to past values. The final amount of calculations depends on the amount of data gathered. Sudden changes in efficiency or fouling require further notice and in such a case it’s important that dialogue toward the power plant in question also works.

In-situ confocal Raman monitoring of evaporation process during protein crystallization

We have introduced an in-situ Raman monitoring technique to investigate the crystallization process inside protein drops. In addition to a conventional vapour-diffusion process, a novel procedure which actively stimulates the evaporation from a protein drop during crystallization was also evaluated, with lysozyme as a model protein. In contrast to the conventional vapour-diffusion condition, the evaporation-stimulated growth of crystals was initiated in a simple dehydration scheme and completed within a significantly shorter time. To gain an understanding of crystallization behaviours under the conditions with and without such evaporation stimulation, confocal Raman spectroscopy combined with linear regression analysis was used to monitor both lysozyme and HEPES buffer concentrations in real time. The confocal measurements having a high spatial resolution and good linear response revealed areas of local inhomogeneity in protein concentration when the crystallization started. The acquired concentration profiles indicated that (1)ÿthe evaporation-stimulated crystallization proceeded with protein concentrations lower than those under conventional vapour diffusion, and (2)ÿcrystals under the evaporation-stimulated condition were noticeable within an early stage of crystallization before the protein concentration approached its maximum value. The HEPES concentration profiles, on the other hand, increased steadily towards the end of the process regardless of the conditions used for crystallization. In particular, the observed local inhomogeneities specific to protein distribution suggested an accumulation mechanism of protein molecules that initiates the nucleation of crystals.

In-line shape compensation for roll forming through process parameter monitoring

Buddhika’s Phd topic is In-line shape compensation for roll forming through process parameter monitoring. It mainly discussed about defects monitoring and compensation in high strength steel roll forming for automotive applications.

An audio signal based model for condition monitoring of sheet metal stamping process

Tool condition monitoring is an important factor in ensuring manufacturing efficiency and product quality. Audio signal based methods are a promising technique for condition monitoring. However, the influence of interfering signals and background noise has hindered the use of this technique in production sites. Blind signal separation (BSS) has the potential to solve this problem by recovering the signal of interest out of the observed mixtures, given that the knowledge about the BSS model is available. In this paper, we discuss the development of the BSS model for sheet metal stamping with a mechanical press system, so that the BSS techniques based on this model can be developed in future. This involves conducting a set of specially designed machine operations and developing a novel signal extraction technique. Also, the link between stamping process conditions and the extracted audio signal associated with stamping was successfully demonstrated by conducting a series of trials with different lubrication conditions and levels of tool wear.

In-process grinding monitoring by acoustic emission

This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. Many statistics have shown effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS.