486 resultados para acoustic properties


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Pedestrians’ use of mp3 players or mobile phones can pose the risk of being hit by motor vehicles. We present an approach for detecting a crash risk level using the computing power and the microphone of mobile devices that can be used to alert the user in advance of an approaching vehicle so as to avoid a crash. A single feature extractor classifier is not usually able to deal with the diversity of risky acoustic scenarios. In this paper, we address the problem of detection of vehicles approaching a pedestrian by a novel, simple, non resource intensive acoustic method. The method uses a set of existing statistical tools to mine signal features. Audio features are adaptively thresholded for relevance and classified with a three component heuristic. The resulting Acoustic Hazard Detection (AHD) system has a very low false positive detection rate. The results of this study could help mobile device manufacturers to embed the presented features into future potable devices and contribute to road safety.

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The main constituents of red mud produced in Aluminio city (S.P. – Brazil) are iron, aluminium and silicon oxides. It has been determined that the average particle diameter for this red mud is between 0.05 and 0.002mm. It is observed that a decrease in the percentage of smaller particles occurs at temperatures greater than 400°C. This observation corresponds with the thermal analysis and X-ray diffraction (XRD) data, which illustrate the phase transition of goethite to hematite. A 10% mass loss is observed in the thermal analysis patterns due to the hydroxide – oxide phase transitions of iron (primary phase transition) and aluminium (to a lesser extent). The disappearance and appearance of the different phases of iron and aluminium confirms the decomposition reactions proposed by the thermal analysis data. This Brazilian red mud has been classified as mesoporous at all temperatures except between 400 and 500°C where the classification changes to micro/mesoporous.

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This paper presents techniques which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outline, including time-frequency analysis and selection of optimum frequency band.The results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals and the effects of changing parameter values are also outlined. The results on separation of RMS signals show thsi technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events within the combustion process of multi-cylinder diesel engines.

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Vibration analysis has been a prime tool in condition monitoring of rotating machines, however, its application to internal combustion engines remains a challenge because engine vibration signatures are highly non-stationary that are not suitable for popular spectrum-based analysis. Signal-to-noise ratio is a main concern in engine signature analysis due to severe background noise being generated by consecutive mechanical events, such as combustion, valve opening and closing, especially in multi-cylinder engines. Acoustic Emission (AE) has been found to give excellent signal-to-noise ratio allowing discrimination of fine detail of normal or abnormal events during a given cycle. AE has been used to detect faults, such as exhaust valve leakage, fuel injection behaviour, and aspects of the combustion process. This paper presents a review of AE application to diesel engine monitoring and preliminary investigation of AE signature measured on an 18-cylinder diesel engine. AE is compared with vibration acceleration for varying operating conditions: load and speed. Frequency characteristics of AE from those events are analysed in time-frequency domain via short time Fourier trasform. The result shows a great potential of AE analysis for detection of various defects in diesel engines.

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As civil infrastructures such as bridges age, there is a concern for safety and a need for cost-effective and reliable monitoring tool. Different diagnostic techniques are available nowadays for structural health monitoring (SHM) of bridges. Acoustic emission is one such technique with potential of predicting failure. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). AEtechnique involves recording the stress waves bymeans of sensors and subsequent analysis of the recorded signals,which then convey information about the nature of the source. AE can be used as a local SHM technique to monitor specific regions with visible presence of cracks or crack prone areas such as welded regions and joints with bolted connection or as a global technique to monitor the whole structure. Strength of AE technique lies in its ability to detect active crack activity, thus helping in prioritising maintenance work by helping focus on active cracks rather than dormant cracks. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. One is the generation of large amount of data during the testing; hence an effective data analysis and management is necessary, especially for long term monitoring uses. Complications also arise as a number of spurious sources can giveAEsignals, therefore, different source discrimination strategies are necessary to identify genuine signals from spurious ones. Another major challenge is the quantification of damage level by appropriate analysis of data. Intensity analysis using severity and historic indices as well as b-value analysis are some important methods and will be discussed and applied for analysis of laboratory experimental data in this paper.

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Global warming can have a significant impact on building energy performance and indoor thermal environment, as well as the health and productivity of people living and working inside them. Through the building simulation technique, this paper investigates the adaptation potential of different selections of building physical properties to increased outdoor temperature in Australia. It is found that overall, an office building with lower insulation level, smaller window to wall ratio and/or a glass type with lower shading coefficient, and lower internal load density will have the effect of lowering building cooling load and total energy use, and therefore have a better potential to adapt to the warming external climate. Compared with clear glass, it is shown that the use of reflective glass for the sample building with WWR being 0.5 reduces the building cooling load by more than 12%. A lower internal load can also have a significant impact on the reduction of building cooling load, as well as the building energy use. Through the comparison of results between current and future weather scenarios, it is found that the patterns found in the current weather scenario also exist in the future weather scenarios, but to a smaller extent.

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Early-stage treatments for osteoarthritis are attracting considerable interest as a means to delay, or avoid altogether, the pain and lack of mobility associated with late-stage disease, and the considerable burden that it places on the community. With the development of these treatments comes a need to assess the tissue to which they are applied, both in trialling of new treatments and as an aid to clinical decision making. Here, we measure a range of mechanical indentation, ultrasound and near-infrared spectroscopy parameters in normal and osteoarthritic bovine joints in vitro to describe the role of different physical phenomena in disease progression, using this as a basis to investigate the potential value of the techniques as clinical tools. Based on 72 samples we found that mechanical and ultrasound parameters showed differences between fibrillated tissue, macroscopically normal tissue in osteoarthritic joints, and normal tissue, yet did were unable to differentiate degradation beyond that which was visible to the naked eye. Near-infrared spectroscopy showed a clear progression of degradation across the visibly normal osteoarthritic joint surface and as such, was the only technique considered useful for clinical application.

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Several studies of the surface effect on bending properties of a nanowire (NW) have been conducted. However, these analyses are mainly based on theoretical predictions, and there is seldom integration study in combination between theoretical predictions and simulation results. Thus, based on the molecular dynamics (MD) simulation and different modified beam theories, a comprehensive theoretical and numerical study for bending properties of nanowires considering surface/intrinsic stress effects and axial extension effect is conducted in this work. The discussion begins from the Euler-Bernoulli beam theory and Timoshenko beam theory augmented with surface effect. It is found that when the NW possesses a relatively small cross-sectional size, these two theories cannot accurately interpret the true surface effect. The incorporation of axial extension effect into Euler-Bernoulli beam theory provides a nonlinear solution that agrees with the nonlinear-elastic experimental and MD results. However, it is still found inaccurate when the NW cross-sectional size is relatively small. Such inaccuracy is also observed for the Euler-Bernoulli beam theory augmented with both contributions from surface effect and axial extension effect. A comprehensive model for completely considering influences from surface stress, intrinsic stress, and axial extension is then proposed, which leads to good agreement with MD simulation results. It is thus concluded that, for NWs with a relatively small cross-sectional size, a simple consideration of surface stress effect is inappropriate, and a comprehensive consideration of the intrinsic stress effect is required.

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Based on the molecular dynamics (MD) method, the single-crystalline copper nanowire with different surface defects is investigated through tension simulation. For comparison, the MD tension simulations of perfect nanowire are firstly carried out under different temperatures, strain rates, and sizes. It has concluded that the surface-volume ratio significantly affects the mechanical properties of nanowire. The surface defects on nanowires are then systematically studied in considering different defect orientation and distribution. It is found that the Young’s modulus is insensitive of surface defects. However, the yield strength and yield point show a significant decrease due to the different defects. Different defects are observed to serve as a dislocation source.

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20 and 26 S proteasomes were isolated from rat liver. The procedure developed for the 26 S proteasome resulted in greatly improved yields compared with previously published methods. A comparison of the kinetic properties of 20 and 26 S proteasomes showed significant differences in the kinetic characteristics with certain substrates and differences in the effects of a protein substrate on peptidase activity. Observed differences in the kinetics of peptidylglutamyl peptide hydrolase activity suggest that the 26 S complex cannot undergo the conformational changes of 20 S proteasomes at high concentrations of the substrate benzyloxycarbonyl (Z) -Leu-Leu-Glu-b-naphthylamide. Various inhibitors that differentially affect the trypsin-like and chymotrypsin-like activities have been identified. Ala-Ala-Phe-chloromethyl (CH2Cl) inhibits chymotrypsin-like activity assayed with succinyl (Suc) -Leu-Leu-Val-Tyr-AMC, but surprisingly not hydrolysis of Ala-Ala-Phe-7-amido-4-methylcoumarin (AMC). Tyr-Gly-Arg-CH2Cl inhibits Suc-Leu-Leu-Val-Tyr-AMC hydrolysis as well as trypsinlike activity measured with t-butoxycarbonyl (Boc) -Leu-Ser-Thr-Arg-AMC, while Z-Phe-Gly-Tyr-diazomethyl (CHN2) was found to inhibit only the two chymotrypsin- like activities. Radiolabeled forms of peptidyl chloromethane and peptidyl diazomethane inhibitors, [3H]acetyl-Ala-Ala-Phe-CH2Cl, [3H]acetyland radioiodinated Tyr-Gly-Arg-CH2Cl, and Z-Phe-Gly- Tyr-(125I-CHN2), have been used to identify catalytic components associated with each of the three peptidase activities. In each case, incorporation of the label could be blocked by prior treatment of the proteasomes with known active site-directed inhibitors, calpain inhibitor 1 or 3,4-dichloroisocoumarin. Subunits of labeled proteasomes were separated either by reverse phase-HPLC and SDS-polyacrylamide gel electrophoresis or by twodimensional polyacrylamide gel electrophoresis followed by autoradiography/fluorography and immunoblotting with subunit-specific antibodies. In each case, label was found to be incorporated into subunits C7, MB1, and LMP7 but in different relative amounts depending on the inhibitor used, consistent with the observed effects on the different peptidase activities. The results strongly suggest a relationship between trypsin-like activity and chymotrypsin-like activity. They also help to relate the different subunits of the complex to the assayed multicatalytic endopeptidase activities

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This paper presents an experimental investigation into the detection of excessive Diesel knock using acoustic emission signals. Three different dual-fuel Diesel engine operating regimes were induced into a compression ignition (Diesel) engine operating on both straight Diesel fuel and two different mixtures of fumigated ethanol and Diesel. The experimentally induced engine operating regimes were; normal, or Diesel only operation, acceptable dual-fuel operation and dual-fuel operation with excessive Diesel knock. During the excessive Diesel knock operating regime, high rates of ethanol substitution induced potentially damaging levels of Diesel knock. Acoustic emission data was captured along with cylinder pressure, crank-angle encoder, and top-dead centre signals for the different engine operating regimes. Using these signals, it was found that acoustic emission signals clearly distinguished between the two acceptable operating regimes and the operating regime experiencing excessive Diesel knock. It was also found that acoustic emission sensor position is critical. The acoustic emission sensor positioned on the block of the engine clearly related information concerning the level of Diesel knock occurring in the engine whist the sensor positioned on the head of the engine gave no indication concerning Diesel knock severity levels.

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This paper discusses commonly encountered diesel engine problems and the underlying combustion related faults. Also discussed are the methods used in previous studies to simulate diesel engine faults and the initial results of an experimental simulation of a common combustion related diesel engine fault, namely diesel engine misfire. This experimental fault simulation represents the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank-angle encoder and top-dead centre signals. Using these signals, it was possible to characterise the diesel engine in-cylinder pressure profiles and the effect of different combustion conditions on both vibration and acoustic emission signals.

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Acoustic emission (AE) analysis is one of the several diagnostic techniques available nowadays for structural health monitoring (SHM) of engineering structures. Some of its advantages over other techniques include high sensitivity to crack growth and capability of monitoring a structure in real time. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). In AE technique, these stress waves are recorded by means of suitable sensors placed on the surface of a structure. Recorded signals are subsequently analysed to gather information about the nature of the source. By enabling early detection of crack growth, AE technique helps in planning timely retrofitting or other maintenance jobs or even replacement of the structure if required. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. Large amount of data is generated during AE testing, hence effective data analysis is necessary, especially for long term monitoring uses. Appropriate analysis of AE data for quantification of damage level is an area that has received considerable attention. Various approaches available for damage quantification for severity assessment are discussed in this paper, with special focus on civil infrastructure such as bridges. One method called improved b-value analysis is used to analyse data collected from laboratory testing.

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THERE is an increasing need for biodegradable plastics because they are environmentally friendly and can replace petroleum-based non-degradable plastics which pollute the environment. Starch-derived films reinforced with sugar cane bagasse fibre, which are biodegradable, have been prepared and characterised by gravimetric analysis for moisture uptake, X-ray powder diffraction for crystallinity, and tensile testing for mechanical properties. Results have shown that the addition of bagasse fibre (5 wt%, 10 wt% or 20 wt%) to either (modified) potato starch (Soluble starch) or hydroxypropylated maize starch reduced moisture uptake by up to 30% at 58% relative humidity (RH). Also, the tensile strength and the Young’s Modulus increased up to 63% and 80% respectively, with the maximum value obtained with 5 wt% fibre at 58% RH. However, the tensile strain of the films significantly decreased by up to 84%. The results have been explained based on the crystallinity of the films and the intrinsic properties of starch and bagasse fibres.

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Monitoring environmental health is becoming increasingly important as human activity and climate change place greater pressure on global biodiversity. Acoustic sensors provide the ability to collect data passively, objectively and continuously across large areas for extended periods. While these factors make acoustic sensors attractive as autonomous data collectors, there are significant issues associated with large-scale data manipulation and analysis. We present our current research into techniques for analysing large volumes of acoustic data efficiently. We provide an overview of a novel online acoustic environmental workbench and discuss a number of approaches to scaling analysis of acoustic data; online collaboration, manual, automatic and human-in-the loop analysis.