In-process grinding monitoring through 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 processes. 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 Steel as work material. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system working at 2.5 MHz was used to collect the raw acoustic emission instead of the root mean square value usually employed. Many statistical analyses have shown to be effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm rate (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. Copyright © 2006 by ABCM.

Automatic system for thermal damage detection in manufacturing process with Internet monitoring

This work involved the development of a smart system dedicated to surface burning detection in the grinding process through constant monitoring of the process by acoustic emission and electrical power signals. A program in Visual Basic® for Windows® was developed, which collects the signals through an analog-digital converter and further processes them using burning detection algorithms already known. Three other parameters are proposed here and a comparative study carried out. When burning occurs, the newly developed software program sends a control signal warning the operator or interrupting the process, and delivers process information via the Internet. Parallel to this, the user can also interfere in the process via Internet, changing parameters and/or monitoring the grinding process. The findings of a comparative study of the various parameters are also discussed here. Copyright © 2006 by ABCM.

Monitoring the dressing operation in the grinding process

This work was based on a methodology of development and experimentation, and involved monitoring the dressing operation by processing the acoustic emission and electric power signals to detect the optimal dressing moment. Dressing tests were performed in a surface grinding machine with an aluminium grinding wheel. Dressing analysis software was developed and used to process the signals collected earlier in order to analyse not only the dressing parameters but also the software's ability to indicate the instant when the dressing operation could be concluded. Parameters used in the study of burn in grinding were implemented in order to ascertain if they would also prove efficient in monitoring dressing. A comparative study revealed that some parameters are capable of monitoring the dressing operation. It was possible to verify the parameters effectiveness that today are utilised in burning to monitor dressing as well as to create new parameters for monitoring this operation. Copyright © 2009, Inderscience Publishers.

Radon emissions related to the granitic Precambrian shield in southern Brazil

The equivalent uranium (eU) activity concentration was analysed in selected granite samples at several sites in Porto Alegre, Southern Brazil, to obtain information on the radon (222Rn) generation by the aquifer rock matrices. Radon analyses of ground water and soil samples were also performed. Several samples exhibited a dissolved 222Rn activity concentration exceeding the World Health Organization maximum limit of 100 Bq l-1. The dissolved radon content in ground waters from the Fractured Precambrian Aquifer System exhibited a direct significant correlation with the eU in the rock matrices, which is a typical result of water-rock interactions. Variation in the soil's porosity was confirmed as an important factor for 222Rn release, as expected, due to its gaseous nature. Thus, although the calcic-alkaline to alkaline Precambrian granitoid rocks of the study area are important reservoirs for underground resources, they can release high amounts of radon gas into the liquid phase. © 2013 Copyright Taylor and Francis Group, LLC.

Study of combustion of different biomass and its atmospheric emissions

One of the energy alternatives that provide utility, flexibility, cleanliness and economy is biomass, such as forest waste (wood) and agricultural (sugarcane bagasse, rice husks, coffee pods, etc.). However, with its increasing supply and use grows also the concern of industries to invest in monitoring and control of emissions into the atmosphere, because during biomass burning are emitted as exhaust gases, fine particles known as particulates, which greatly contribute to the triggering of serious health problems to humans, in addition to the environmental damage. With that, this work aimed to conduct a monitoring of particulate and gaseous pollutants emissions to the atmosphere from the burning of various types of biomass used by industries. The equipment used for sampling were the optical monitor DataRAM 4 and the Unigas3000 + gas sampler. The results showed that biomass coffee pods presented the greatest concentration of particulates (485119 μg m-3) with particle diameters between 0.0602 μm and 0.3502 μm, i.e. the most ultrafine particles, harmful to human health and the environment. The largest emissions of CO and NOx were observed, respectively, for the coffee pods (3500 ppm) and for the rice husk (48 ppm). As for the superior calorific value (PCS), the best of fuel, with higher PCS, was the Eucalyptus grandis.

Continuous geochemical monitoring by mass-spectometer in the Campi Flegrei geothermal area. An application at Pisciarelli-Solfatara (diffuse and fumarolic gases) and at the mud gases during drilling of the CFDDP pilot hole

During this work has been developed an innovative methodology for continuous and in situ gas monitoring (24/24 h) of fumarolic and soil diffusive emissions applied to the geothermal and volcanic area of Pisciarelli near Agnano inside the Campi Flegrei caldera (CFc). In literature there are only scattered and in discrete data of the geochemical gas composition of fumarole at Campi Flegrei; it is only since the early ’80 that exist a systematic record of fumaroles with discrete sampling at Solfatara (Bocca Grande and Bocca Nuova fumaroles) and since 1999, even at the degassing areas of Pisciarelli. This type of sampling has resulted in a time series of geochemical analysis with discontinuous periods of time set (in average 2-3 measurements per month) completely inadequate for the purposes of Civil Defence in such high volcanic risk and densely populated areas. For this purpose, and to remedy this lack of data, during this study was introduced a new methodology of continuous and in situ sampling able to continuously detect data related and from its soil diffusive degassing. Due to its high sampling density (about one measurement per minute therefore producing 1440 data daily) and numerous species detected (CO2, Ar, 36Ar, CH4, He, H2S, N2, O2) allowing a good statistic record and the reconstruction of the gas composition evolution of the investigated area. This methodology is based on continuous sampling of fumaroles gases and soil degassing using an extraction line, which after undergoing a series of condensation processes of the water vapour content - better described hereinafter - is analyzed through using a quadrupole mass spectrometer

Extended frequency range hearing thresholds and otoacoustic emissions in acute acoustic trauma

We sought to evaluate the relative value of pure tone audiometry (PTA), extended high-frequency audiometry (EFA) and transiently evoked otoacoustic emissions (OAE) and distortion products when monitoring acute acoustic trauma (AAT).

Estimating greenhouse gas emissions of highway construction and rehabilitation to support pavement life cycle assessment

Highway infrastructure plays a significant role in society. The building and upkeep of America’s highways provide society the necessary means of transportation for goods and services needed to develop as a nation. However, as a result of economic and social development, vast amounts of greenhouse gas emissions (GHG) are emitted into the atmosphere contributing to global climate change. In recognizing this, future policies may mandate the monitoring of GHG emissions from public agencies and private industries in order to reduce the effects of global climate change. To effectively reduce these emissions, there must be methods that agencies can use to quantify the GHG emissions associated with constructing and maintaining the nation’s highway infrastructure. Current methods for assessing the impacts of highway infrastructure include methodologies that look at the economic impacts (costs) of constructing and maintaining highway infrastructure over its life cycle. This is known as Life Cycle Cost Analysis (LCCA). With the recognition of global climate change, transportation agencies and contractors are also investigating the environmental impacts that are associated with highway infrastructure construction and rehabilitation. A common tool in doing so is the use of Life Cycle Assessment (LCA). Traditionally, LCA is used to assess the environmental impacts of products or processes. LCA is an emerging concept in highway infrastructure assessment and is now being implemented and applied to transportation systems. This research focuses on life cycle GHG emissions associated with the construction and rehabilitation of highway infrastructure using a LCA approach. Life cycle phases of the highway section include; the material acquisition and extraction, construction and rehabilitation, and service phases. Departing from traditional approaches that tend to use LCA as a way to compare alternative pavement materials or designs based on estimated inventories, this research proposes a shift to a context sensitive process-based approach that uses actual observed construction and performance data to calculate greenhouse gas emissions associated with highway construction and rehabilitation. The goal is to support strategies that reduce long-term environmental impacts. Ultimately, this thesis outlines techniques that can be used to assess GHG emissions associated with construction and rehabilitation operations to support the overall pavement LCA.

Observations of volcanic emissions using satellite remote sensing

Volcanoes pose a threat to the human population at regional and global scales and so efficient monitoring is essential in order to effectively manage and mitigate the risks that they pose. Volcano monitoring from space has been possible for over thirty years and now, more than ever, a suite of instruments exists with the capability to observe emissions of gas and ash from a unique perspective. The goal of this research is to demonstrate the use of a range of satellite-based sensors in order to detect and quantify volcanic sulphur dioxide, and to assess the relative performances of each sensor against one another. Such comparisons are important in order to standardise retrievals and permit better estimations of the global contribution of sulphur dioxide to the atmosphere from volcanoes for climate modelling. In this work, retrievals of volcanic sulphur dioxide from a number of instruments are compared, and the individual performances at quantifying emissions from large, explosive volcanic eruptions are assessed. Retrievals vary widely from sensor to sensor, and often the use of a number of sensors in synergy can provide the most complete picture, rather than just one instrument alone. Volcanic emissions have the ability to result significant economic loses by grounding aircraft due to the high risk associated with ash encountering aircraft. As sulphur dioxide is often easier to measure than ash, it is often used as a proxy. This work examines whether this is a reasonable assumption, using the Icelandic eruption in early 2010 as a case study. Results indicate that although the two species are for the most part collocated, separation can occur under some conditions, meaning that it is essential to accurately measure both species in order to provide effective hazard mitigation. Finally, the usefulness of satellite remote sensing in quantifying the passive degassing from Turrialba, Costa Rica is demonstrated. The increase in activity from 2005 – 2010 can be observed in satellite data prior to the phreatic phase of early 2010, and can therefore potentially provide a useful indication of changing activity at some volcanoes.

EXPLORATION OF THE MTSAT2 SATELLITE CAPABILITIES FOR REAL TIME DETECTION AND CHARACTERIZATION OF VOLCANIC EMISSIONS

In this report, we attempt to define the capabilities of the infrared satellite remote sensor, Multifunctional Transport Satellite-2 (MTSAT-2) (i.e. a geosynchronous instrument), in characterizing volcanic eruptive behavior in the highly active region of Indonesia. Sulfur dioxide data from NASA's Ozone Monitoring Instrument (OMI) (i.e. a polar orbiting instrument) are presented here for validation of the processes interpreted using the thermal infrared datasets. Data provided from two case studies are analyzed specifically for eruptive products producing large thermal anomalies (i.e. lava flows, lava domes, etc.), volcanic ash and SO2 clouds; three distinctly characteristic and abundant volcanic emissions. Two primary methods used for detection of heat signatures are used and compared in this report including, single-channel thermal radiance (4-µm) and the normalized thermal index (NTI) algorithm. For automated purposes, fixed thresholds must be determined for these methods. A base minimum detection limit (MDL) for single-channel thermal radiance of 2.30E+05 Wm- 2sr-1m-1 and -0.925 for NTI generate false alarm rates of 35.78% and 34.16%, respectively. A spatial comparison method, developed here specifically for use in Indonesia and used as a second parameter for detection, is implemented to address the high false alarm rate. For the single-channel thermal radiance method, the utilization of the spatial comparison method eliminated 100% of the false alarms while maintaining every true anomaly. The NTI algorithm showed similar results with only 2 false alarms remaining. No definitive difference is observed between the two thermal detection methods for automated use; however, the single-channel thermal radiance method coupled with the SO2 mass abundance data can be used to interpret volcanic processes including the identification of lava dome activity at Sinabung as well as the mechanism for the dome emplacement (i.e. endogenous or exogenous). Only one technique, the brightness temperature difference (BTD) method, is used for the detection of ash. Trends of ash area, water/ice area, and their respective concentrations yield interpretations of increased ice formation, aggregation, and sedimentation processes that only a high-temporal resolution instrument like the MTSAT-2 can analyze. A conceptual model of a secondary zone of aggregation occurring in the migrating Kelut ash cloud, which decreases the distal fine-ash component and hazards to flight paths, is presented in this report. Unfortunately, SO2 data was unable to definitively reinforce the concept of a secondary zone of aggregation due to the lack of a sufficient temporal resolution. However, a detailed study of the Kelut SO2 cloud is used to determine that there was no climatic impacts generated from this eruption due to the atmospheric residence times and e-folding rate of ~14 days for the SO2. This report applies the complementary assets offered by utilizing a high-temporal and a high-spatial resolution satellite, and it demonstrates that these two instruments can provide unparalleled observations of dynamic volcanic processes.

Seasonal Geophysical Monitoring of Biogenic Gases in a Northern Peatland: Implications for Temporal and Spatial Variability in Free Phase Gas Production Rates

A set of high resolution surface ground penetrating radar (GPR) surveys, combined with elevation rod ( to monitor surface deformation) and gas flux measurements, were used to investigate in situ biogenic gas dynamics within a northern peatland (Caribou Bog, Maine). Gas production rates were directly estimated from the time series of GPR measurements. Spatial variability in gas production was also investigated by comparing two sites with different geological and ecological attributes, showing differences and/or similarities depending on season. One site characterized by thick highly humified peat deposits (5-6 m), wooded heath vegetation and open pools showed large ebullition events during the summer season, with estimated emissions (based on an assumed range of CH(4) concentration) between 100 and 172 g CH(4) m(-2) during a single event. The other site characterized by thinner less humified peat deposits (2-3 m) and shrub vegetation showed much smaller ebullition events during the same season (between 13 and 23 g CH(4) m(-2)). A consistent period of free-phase gas (FPG) accumulation during the fall and winter, enhanced by the frozen surficial peat acting as a confining layer, was followed by a decrease in FPG after the snow/ice melt that released estimated fluxes between 100 and 200 g CH(4) m(-2) from both sites. Estimated FPG production rates during periods of biogenic gas accumulation ranged between 0.22 and 2.00 g CH(4) m(3) d(-1) and reflected strong seasonal and spatial variability associated with differences in temperature, peat soil properties, and/or depositional attributes (e. g., stratigraphy). Periods of decreased atmospheric pressure coincided with short-period increases in biogenic gas flux, including a very rapid decrease in FPG content associated with an ebullition event that released an estimated 39 and 67 g CH(4) m(-2) in less than 3.5 hours. These results provide insights into the spatial and seasonal variability in production and emission of biogenic gases from northern peatlands.

Measurement of isotopic uranium in water for compliance monitoring by liquid scintillation counting with alpha/beta discrimination

A simple and inexpensive method is described for analysis of uranium (U) activity and mass in water by liquid scintillation counting using $\alpha$/$\beta$ discrimination. This method appears to offer a solution to the need for an inexpensive protocol for monitoring U activity and mass simultaneously and an alternative to the potential inaccuracy involved when depending on the mass-to-activity conversion factor or activity screen.^ U is extracted virtually quantitatively into 20 ml extractive scintillator from a 1-$\ell$ aliquot of water acidified to less than pH 2. After phase separation, the sample is counted for a 20-minute screening count with a minimum detection level of 0.27 pCi $\ell\sp{-1}$. $\alpha$-particle emissions from the extracted U are counted with close to 100% efficiency with a Beckman LS6000 LL liquid scintillation counter equipped with pulse-shape discrimination electronics. Samples with activities higher than 10 pCi $\ell\sp-1$ are recounted for 500-1000 minutes for isotopic analysis. Isotopic analysis uses events that are automatically stored in spectral files and transferred to a computer during assay. The data can be transferred to a commercially available spreadsheet and retrieved for examination or data manipulation. Values for three readily observable spectral features can be rapidly identified by data examination and substituted into a simple formula to obtain $\sp{234}$U/$\sp{238}$U ratio for most samples. U mass is calculated by substituting the isotopic ratio value into a simple equation.^ The utility of this method for the proposed compliance monitoring of U in public drinking water supplies was field tested with a survey of drinking water from Texas supplies that had previously been known to contain elevated levels of gross $\alpha$ activity. U concentrations in 32 samples from 27 drinking water supplies ranged from 0.26 to 65.5 pCi $\ell\sp{-1}$, with seven samples exceeding the proposed Maximum Contaminant Level of 20 $\mu$g $\ell\sp{-1}$. Four exceeded the proposed activity screening level of 30 pCi $\ell\sp{-1}$. Isotopic ratios ranged from 0.87 to 41.8, while one sample contained $\sp{234}$U activity of 34.6 pCi $\ell\sp{-1}$ in the complete absence of its parent, $\sp{238}$U. U mass in the samples with elevated activity ranged from 0.0 to 103 $\mu$g $\ell\sp{-1}$. A limited test of screening surface and groundwaters for contamination by U from waste sites and natural processes was also successful. ^

Design of a solar incubator. Part 1: Monitoring temperature and enthalpy gradients under commercial production

The real increase in energy prices and the intention of reducing pollutant emissions in developed countries makes interesting to use solar energy in all the processes where its application is possible. As it is demonstrated in countries sited at latitudes with optimal conditions of solar radiation and temperature, it is possible to use solar energy as heat source for small-scale hatchery [1,2], but beyond, making a design for proper installation; it is possible to use solar energy as main or support energy source in medium and large size incubators . Monitoring of a normal actual process using temperature and relative humidity sensors is necessary to know the actual operating conditions that the solar heating system must be designed and sized for. Moreover, the identification and analysis of temperature and enthalpy gradients inside the incubator is of major importance.

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.