960 resultados para Noise control


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Bibliography: p. 12.

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Project officer: William Murphy.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

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The work described in this thesis is directed towards the reduction of noise levels in the Hoover Turbopower upright vacuum cleaner. The experimental work embodies a study of such factors as the application of noise source identification techniques, investigation of the noise generating principles for each major source and evaluation of the noise reducing treatments. It was found that the design of the vacuum cleaner had not been optimised from the standpoint of noise emission. Important factors such as noise `windows', isolation of vibration at the source, panel rattle, resonances and critical speeds had not been considered. Therefore, a number of experimentally validated treatments are proposed. Their noise reduction benefit together with material and tooling costs are presented. The solutions to the noise problems were evaluated on a standard Turbopower and the sound power level of the cleaner was reduced from 87.5 dB(A) to 80.4 db(A) at a cost of 93.6 pence per cleaner.The designers' lack of experience in noise reduction was identified as one of the factors for the low priority given to noise during design of the cleaner. Consequently, the fundamentals of acoustics, principles of noise prediction and absorption and guidelines for good acoustical design were collated into a Handbook and circulated at Hoover plc.Mechanical variations during production of the motor and the cleaner were found to be important. These caused a vast spread in the noise levels of the cleaners. Subsequently, the manufacturing processes were briefly studied to identify their source and recommendations for improvement are made.Noise of a product is quality related and a high level of noise is considered to be a bad feature. This project suggested that the noise level be used constructively both as a test on the production line to identify cleaners above a certain noise level and also to promote the product by `designing' the characteristics of the sound so that the appliance is pleasant to the user. This project showed that good noise control principles should be implemented early in the design stage.As yet there are no mandatory noise limits or noise-labelling requirements for household appliances. However, the literature suggests that noise-labelling is likely in the near future and the requirement will be to display the A-weighted sound power level. However, the `noys' scale of perceived noisiness was found more appropriate to the rating of appliance noise both as it is linear and therefore, a sound level that seems twice as loud is twice the value in noys and also takes into consideration the presence of pure tones, which even in the absence of a high noise level can lead to annoyance.

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Acoustic emission (AE) technique is one of the popular diagnostic techniques used for structural health monitoring of mechanical, aerospace and civil structures. But several challenges still exist in successful application of AE technique. This paper explores various tools for analysis of recorded AE data to address two primary challenges: discriminating spurious signals from genuine signals and devising ways to quantify damage levels.

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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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This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the proposed system there is no need for using offline estimation. The proposed method consists of two steps: a noise controller which is based on an FxLMS algorithm, and a variable step size (VSS) LMS algorithm which is used to adapt the modeling filter with the secondary path. In order to increase performance of the algorithm in a faster convergence and accurate performance, we stop the VSS-LMS algorithm at the optimum point. The results of computer simulation shown in this paper indicate effectiveness of the proposed method.