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Published Articles


The Volume 14, No 2, June 2009




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Noise and Blood Pressure: a Cross Sectional and Longitudinal Study of the Effects of Exposure to Loud Noise on Residents in Calabar, Cross River State, Nigeria

Ubon E. Asuquo, Michael U. Onuu and Aniefiok O. Akpan, Affiong U. Asuquo


https://doi.org/10.20855/ijav.2009.14.2238


A cross-sectional and longitudinal study of the effects of loud noise on residents of Calabar, Nigeria, has been carried out using subjective and objective measures. For the cross-sectional study, a 39-item questionnaire was used for the subjective measure. A sample size of 1000 people in the high noise zones with equivalent continuous A-weighted sound pressure levels over 80 dB was randomly selected and used as the study group. In the low noise zone with equivalent continuous A-weighted sound pressure levels under 80 dB, 1000 people were also randomly selected and used as the control group. For the longitudinal study, a sample size of 15 persons who had worked in the Calabar Timber Market from July 2002 (when the first blood pressure assessment was carried out) to July 2006 (when the second blood pressure assessment was carried out) was used. Findings show that exposure to loud noise may not have an immediate effect on blood pressure, but, when individuals are exposed for a long period of time (4 years in this study), it leads to a significant rise in blood pressure.


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Fuzzy-Neuro Controler for Smart Fault Detection of a Beam

Harish Ch. Das, Dayal R. Parhi


https://doi.org/10.20855/ijav.2009.14.2239


This paper addresses the fault detection of a cracked cantilever beam using a hybrid artificial intelligence tech- nique. The hybrid technique used here uses a fuzzy-neuro controller. The fuzzy-neuro controller has two parts. The first part is comprised of the fuzzy controller, and the second part is comprised of the neural controller. The input parameters of the fuzzy controller are relative deviation of the first three natural frequencies and the relative values of the percentage deviation for the first three mode shapes. The output parameters of the fuzzy controller are initial relative crack depth and initial relative crack location. The input parameters of the neural segment of the fuzzy-neurocontroller are relative deviation of the first three natural frequencies and relative values of percentage deviation for the first three mode shapes, along with the initial outputs of the fuzzy controller. The output param- eters of the fuzzy-neuro controller are final relative crack depth and final relative crack location. For deriving the fuzzy rules and training patterns of natural frequencies, mode shapes, crack depths and crack locations, theoretical expressions have been developed. Several fuzzy rules and training patterns for the fuzzy controller and neural controller of fuzzy-neuro controller are derived respectively. Experimental set-up has been developed for verifying the robustness of the fuzzy-neuro controller. The results of the developed fuzzy-neuro controller and experimental method are in good agreement.


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The Application of Fault Simulation to Machine Diagnostics and Prognostics

Robert B. Randall


https://doi.org/10.20855/ijav.2009.14.2240


The early development of machine diagnostics and condition monitoring was based on measurements from actual failures, but these cannot be predicted or arranged to occur when and where desired. In recent years it has become possible to make simulation models of a machine, such as a gearbox or engine, including the simulation of various faults of different types, severity, and location. There are a number of benefits from doing this, the first being to be able to produce sufficient representative signals to train automated fault recognition algorithms, such as artificial neural networks, as it is not economically viable to experience the number of actual failures required. Being able to produce signals from faults of different sizes and locations can be useful in the development of diagnostic and prognostic procedures ? the latter, for example, by being able to develop appropriate trend parameters. Finally, the effects of faults in complex machines are often based on nonlinear interactions, which are difficult to foresee, and the simulation modelling of the whole machine can be very useful to obtain a physical understanding of these complex interactions. This paper illustrates these principles using examples of rolling element bearings, gears, geared systems (including bearings), and internal combustion engines, with favourable results in all aspects.


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Source Identification and Noise Reduction of a Reciprocating Compressor; a Case History

N. Bert Roozen, Jozef van den Oetelaar, Alex Geerlings, Theon Vliegenthart


https://doi.org/10.20855/ijav.2009.14.2241


A noise source can be very complex in nature. In noise control engineering an essential first step is to identify the strongest contributing noise sources. This paper discusses a practical case history, in which a series of measurement techniques was applied to a reciprocating compressor to identify the strongest sound source. In addition numerical prediction methods were used to give direction towards a lower noise design of the compressor. Structural modifications to the compressor are discussed, leading to a significant reduction of the noise levels. The sound power level of the reciprocating compressor was reduced by 5 dB. Moreover, from a perceptual point of view, customers experience the sound as more robust and more pleasant as well, probably because of shifting frequencies.


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Gearbox Noise and Vibration Prediction and Control

Jiri Tuma


https://doi.org/10.20855/ijav.2009.14.2242


This paper will review practical techniques and procedures employed to quiet gearboxes and transmission units. The author prefers solving the gear noise problem at the very source to introduce an enclosure as a means to reduce radiated noise, which seems to be easy but its effect on the sound pressure level is small. The gearbox noise problem solution is focused on the improvement of gear design; on the verification of its effect on the radiated noise and the determination of the gears? contribution to the truck?s or car?s overall noise levels and on the analytical and/or numerical computer-based tools needed to perform the signal processing and diagnostics of geared axis systems. All of the analytical methods are based on the time and frequency domain approach. Special care is addressed to the smoothness of the drive resulting from the transmission error variation during a mesh cycle. This paper will review the progress in technique of the gear angular vibration analysis and its effect on gear noise due to the self excited vibration. This presentation will include some examples of the use of such approaches in practical engineering problems.


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