279 resultados para acoustic emission sensors
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This thesis is concerned with the detection and prediction of rain in environmental recordings using different machine learning algorithms. The results obtained in this research will help ecologists to efficiently analyse environmental data and monitor biodiversity.
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A simple modular strategy for the synthesis of profluorescent nitroxide containing polymers is described. The incorporation of an epoxide as a pendant functionality on a polymer backbone synthesized using ATRP and subsequent nucleophilic ring-opening with sodium azide gave hydroxyl and azide functionality within a 3-bond radius. Orthogonal coupling chemistry then allowed the independent attachment of fluorophore and nitroxide groups in close proximity, giving rise to a profluorescent polymer. Validation of the viability of these materials as fluorescent sensors is demonstrated through efficient fluorescence switch-on observed when the materials are exposed to a model reductant or carbon-centred radical source.
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This study is seeking to investigate the effect of non-thermal plasma technology in the abatement of particulate matter (PM) from the actual diesel exhaust. Ozone (O3) strongly promotes PM oxidation, the main product of which is carbon dioxide (CO2). PM oxidation into the less harmful product (CO2) is the main objective whiles the correlation between PM, O3 and CO2 is considered. A dielectric barrier discharge reactor has been designed with pulsed power technology to produce plasma inside the diesel exhaust. To characterise the system under varied conditions, a range of applied voltages from 11 kVPP to 21kVPP at repetition rates of 2.5, 5, 7.5 and 10 kHz, have been experimentally investigated. The results show that by increasing the applied voltage and repetition rate, higher discharge power and CO2 dissociation can be achieved. The PM removal efficiency of more than 50% has been achieved during the experiments and high concentrations of ozone on the order of a few hundreds of ppm have been observed at high discharge powers. Furthermore, O3, CO2 and PM concentrations at different plasma states have been analysed for time dependence. Based on this analysis, an inverse relationship between ozone concentration and PM removal has been found and the role of ozone in PM removal in plasma treatment of diesel exhaust has been highlighted.
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On the basis of the growing interest on the impact of airborne particles on human exposure as well as the strong debate in Western countries on the emissions of waste incinerators, this work reviewed existing literature to: (i) show the emission factors of ultrafine particles (particles with a diameter less than 100 nm) of waste incinerators, and; (ii) assess the contribution of waste incinerators in terms of ultrafine particles to exposure and dose of people living in the surrounding areas of the plants in order to estimate eventual risks. The review identified only a limited number of studies measuring ultrafine particle emissions, and in general they report low particle number concentrations at the stack (the median value was equal to 5.5×103 part cm-3), in most cases higher than the outdoor background value. The lowest emissions were achieved by utilization of the bag-house filter which has an overall number-based filtration efficiency higher than 99%. Referring to reference case, the corresponding emission factor is equal to 9.1×1012 part min-1, that is lower than one single high-duty vehicle. Since the higher particle number concentrations found in the most contributing microenvironments to the exposure (indoor home, transportation, urban outdoor), the contribution of the waste incinerators to the daily dose can be considered as negligible.
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Background Balance dysfunction is one of the most common problems in people who suffer stroke. To parameterize functional tests standardized by inertial sensors have been promoted in applied medicine. The aim of this study was to compare the kinematic variables of the Functional Reach Test (FRT) obtained by two inertial sensors placed on the trunk and lumbar region between stroke survivors (SS) and healthy older adults (HOA) and to analyze the reliability of the kinematic measurements obtained. Methods Cross-sectional study. Five SS and five HOA over 65. A descriptive analysis of the average range as well as all kinematic variables recorded was developed. The intrasubject and intersubject reliability of the measured variables was directly calculated. Results In the same intervals, the angular displacement was greater in the HOA group; however, they were completed at similar times for both groups, and HOA conducted the test at a higher speed and greater acceleration in each of the intervals. The SS values were higher than HOA values in the maximum and minimum acceleration in the trunk and in the lumbar region. Conclusions The SS show less functional reach, a narrower, slower and less accelerated movement during the FRT execution, but with higher peaks of acceleration and speed when they are compared with HOA.
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This paper discusses some of the sensing technologies and control approaches available for guiding robot manipulators for a class of underground mining tasks including drilling jumbos, bolting arms, shotcreters or explosive chargers. Data acquired with such sensors, in the laboratory and underground, is presented.
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Background and purpose There are no published studies on the parameterisation and reliability of the single-leg stance (SLS) test with inertial sensors in stroke patients. Purpose: to analyse the reliability (intra-observer/inter-observer) and sensitivity of inertial sensors used for the SLS test in stroke patients. Secondary objective: to compare the records of the two inertial sensors (trunk and lumbar) to detect any significant differences in the kinematic data obtained in the SLS test. Methods Design: cross-sectional study. While performing the SLS test, two inertial sensors were placed at lumbar (L5-S1) and trunk regions (T7–T8). Setting: Laboratory of Biomechanics (Health Science Faculty - University of Málaga). Participants: Four chronic stroke survivors (over 65 yrs old). Measurement: displacement and velocity, Rotation (X-axis), Flexion/Extension (Y-axis), Inclination (Z-axis); Resultant displacement and velocity (V): RV=(Vx2+Vy2+Vz2)−−−−−−−−−−−−−−−−−√ Along with SLS kinematic variables, descriptive analyses, differences between sensors locations and intra-observer and inter-observer reliability were also calculated. Results Differences between the sensors were significant only for left inclination velocity (p = 0.036) and extension displacement in the non-affected leg with eyes open (p = 0.038). Intra-observer reliability of the trunk sensor ranged from 0.889-0.921 for the displacement and 0.849-0.892 for velocity. Intra-observer reliability of the lumbar sensor was between 0.896-0.949 for the displacement and 0.873-0.894 for velocity. Inter-observer reliability of the trunk sensor was between 0.878-0.917 for the displacement and 0.847-0.884 for velocity. Inter-observer reliability of the lumbar sensor ranged from 0.870-0.940 for the displacement and 0.863-0.884 for velocity. Conclusion There were no significant differences between the kinematic records made by an inertial sensor during the development of the SLS testing between two inertial sensors placed in the lumbar and thoracic regions. In addition, inertial sensors. Have the potential to be reliable, valid and sensitive instruments for kinematic measurements during SLS testing but further research is needed.
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Visual information in the form of lip movements of the speaker has been shown to improve the performance of speech recognition and search applications. In our previous work, we proposed cross database training of synchronous hidden Markov models (SHMMs) to make use of external large and publicly available audio databases in addition to the relatively small given audio visual database. In this work, the cross database training approach is improved by performing an additional audio adaptation step, which enables audio visual SHMMs to benefit from audio observations of the external audio models before adding visual modality to them. The proposed approach outperforms the baseline cross database training approach in clean and noisy environments in terms of phone recognition accuracy as well as spoken term detection (STD) accuracy.
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Soundscape assessment has been proposed as a remote ecological monitoring tool for measuring biodiversity, but few studies have examined how soundscape patterns vary with landscape configuration and condition. The goal of our study was to examine a suite of published acoustic indices to determine whether they provide comparable results relative to varying levels of landscape fragmentation and ecological condition in nineteen forest sites in eastern Australia. Our comparison of six acoustic indices according to time of day revealed that two indices, the acoustic complexity and the bioacoustic index, presented a similar pattern that was linked to avian song intensity, but was not related to landscape and biodiversity attributes. The diversity indices, acoustic entropy and acoustic diversity, and the normalized difference soundscape index revealed high nighttime sound, as well as a dawn and dusk chorus. These indices appear to be sensitive to nocturnal biodiversity which is abundant at night in warm, subtropical environments. We argue that there is need to better understand temporal partitioning of the soundscape by specific taxonomic groups, and this should involve integrated research on amphibians, insects and birds during a 24 h cycle. The three indices that best connected the soundscape with landscape characteristics, ecological condition and bird species richness were acoustic entropy, acoustic evenness and the normalized difference soundscape index. This study has demonstrated that remote soundscape assessment can be implemented as an ecological monitoring tool in fragmented Australian forest landscapes. However, further investigation should be dedicated to refining and/or combining existing acoustic indices and also to determine if these indices are appropriate in other landscapes and for other survey purposes.
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Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers of fixed sampling locations to validate a complex fluid environment and collect sufficient data to confirm model effectiveness. This paper describes the development of a methodology to address the need of a more precise approach that is capable of characterizing blasting plumes in near-real time. The integration of the system required the modification and integration of an opto-electrical dust sensor, SHARP GP2Y10, into a small fixed-wing and multi-rotor copter, resulting in the collection of data streamed during flight. The paper also describes the calibration of the optical sensor with an industry grade dust-monitoring device, Dusttrak 8520, demonstrating a high correlation between them, with correlation coefficients (R2) greater than 0.9. The laboratory and field tests demonstrate the feasibility of coupling the sensor with the UAVs. However, further work must be done in the areas of sensor selection and calibration as well as flight planning.
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Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.
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Acoustic recordings of the environment provide an effective means to monitor bird species diversity. To facilitate exploration of acoustic recordings, we describe a content-based birdcall retrieval algorithm. A query birdcall is a region of spectrogram bounded by frequency and time. Retrieval depends on a similarity measure derived from the orientation and distribution of spectral ridges. The spectral ridge detection method caters for a broad range of birdcall structures. In this paper, we extend previous work by incorporating a spectrogram scaling step in order to improve the detection of spectral ridges. Compared to an existing approach based on MFCC features, our feature representation achieves better retrieval performance for multiple bird species in noisy recordings.
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Greenhouse gas (GHG) emissions are simultaneously exhausting the world's supply of fossil fuels and threatening the global climate. In many developing countries, significant improvement in living standards in recent years due to the accelerating development of their economies has resulted in a disproportionate increase in household energy consumption. Therefore, a major reduction in household carbon emissions (HCEs) is essential if global carbon reduction targets are to be met. To do this, major Organisation for Economic Co-operation and Development (OECD) states have already implemented policies to alleviate the negative environmental effects of household behaviors and less carbon-intensive technologies are also proposed to promote energy efficiency and reduce carbon emissions. However, before any further remedial actions can be contemplated, though, it is important to fully understand the actual causes of such large HCEs and help researchers both gain deep insights into the development of the research domain and identify valuable research topics for future study. This paper reviews existing literature focusing on the domain of HCEs. This critical review provides a systematic understanding of current work in the field, describing the factors influencing HCEs under the themes of household income, household size, age, education level, location, gender and rebound effects. The main quantification methodologies of input–output models, life cycle assessment and emission coefficient methods are also presented, and the proposed measures to mitigate HCEs at the policy, technology and consumer levels. Finally, the limitations of work done to date and further research directions are identified for the benefit of future studies.
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Acoustic recordings play an increasingly important role in monitoring terrestrial environments. However, due to rapid advances in technology, ecologists are accumulating more audio than they can listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings by calculating acoustic indices. These are statistics which describe the temporal-spectral distribution of acoustic energy and reflect content of ecological interest. We combine spectral indices to produce false-color spectrogram images. These not only reveal acoustic content but also facilitate navigation. An additional analytic challenge is to find appropriate descriptors to summarize the content of 24-hour recordings, so that it becomes possible to monitor long-term changes in the acoustic environment at a single location and to compare the acoustic environments of different locations. We describe a 24-hour ‘acoustic-fingerprint’ which shows some preliminary promise.
Development of multi-rotor localised surveillance using multi-spectral sensors for plant biosecurity
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This report describes a proof of concept for multi-rotor localised surveillance using a multi-spectral sensor for plant biosecurity applications. A literature review was conducted on previous applications using airborne multispectral imaging for plant biosecurity purposes. A ready built platform was purchased and modified in order to fit and provide suitable clearance for a Tetracam Mini-MCA multispectral camera. The appropriate risk management documents were developed allowing the platform and the multi-spectral camera to be tested extensively. However, due to technical difficulties with the platform the Mini- MCA was not mounted to the platform. Once a suitable platform is developed, future extensions can be conducted into the suitability of the Mini-MCA for airborne surveillance of Australian crops.