Initial Study of Converting Sound Energy into Electrical Energy

This study concerns on finding alternative source of energy by finding out the method of converting available and unused sound energy into electrical energy. The purpose of this study includes to investigate the possibility of converting sound wave in a range between 70 dB to 80 dB into electrical energy by determining the effectiveness of the method to transform sound wave into electrical energy and study the percentage error between the theoretical and experimental output voltage produced. An electronic circuit-based experiment was conducted to fulfill the objectives of the study. Sound energy was converted into electrical energy by using microphone transducer, then the brightness of bulb and the voltage reading was observed and tabulated. Theoretical and experimental voltage value were compared and being represented in percentage error value. The data shows that there is potential of converting sound into electricity through the suitable electrical circuit and the output voltage increase linearly with the sound pressure levels (SPL) of the sound sources. Further research should include the study of relationship between distance of sound sources and the transducer, and the output voltage produce

Hand-arm vibration disorder among grass-cutter workers in Malaysia

Prolonged exposure to hand-transmitted vibration from grass-cutting machines has been associated with increasing occurrences of symptoms and signs of occupational diseases related to hand-arm vibration syndrome (HAVS). Methods. A cross-sectional study was carried out using an adopted HAVS questionnaire on hand-arm vibration exposure and symptoms distributed to 168 male workers from the grass and turf maintenance industry who use hand-held grass-cutting machines as part of their work. The prevalence ratio and symptom correlation to HAVS between high and low–moderate exposure risk groups were evaluated. Results. There were positive HAVS symptoms relationships between the low–moderate exposure group and the high exposure group among hand-held grass-cutting workers. The prevalence ratio was considered high because there were indicators that fingers turned white and felt numb, 3.63, 95% CI [1.41, 9.39] and 4.24, 95% CI [2.18, 8.27], respectively. Less than 14.3% of workers stated that they were aware of the occupational hand-arm vibration, and it seemed to be related to the finger blanching and numbness. Conclusion. The results suggest that HAVS is under-diagnosed in Malaysia, especially in the agricultural sectors. More information related to safety and health awareness programmes for HAVS exposure is required among hand-held grass-cutting workers

Investigation the Capability of Neural Network in Predicting Reverberation Time on Classroom

The purpose of this paper is to investigate the capability of neural network in predicting a classroom’s reverberation time. A classroom in Oita University was chosen as a sample to obtain the virtual data (reverberation time) based on 20 types of sound absorptions coefficients using Finite Element Method (FEM) and Sabine equation. The capability of FEM has shown that it is able to simulate virtual data in each location of a classroom. To develop a neural network model, virtual data (721 data) was taken from FEM for the learning process. The assessment was made by using testing subset (20% from 721 data) to verify the performance. The testing’s means square error (MSE) was 3.7751×10-4 and correlation coefficient (R2) was 0.992 approximately to 1. The optimum network used was 4 hidden nodes. Extended assessment was made using the unseen data (35 data) and it showed that neural network prediction was approximately close to the actual data with MSE is 4.154×10-4. Basically, the capability of reverberation time prediction using neural network is shown in this paper.&nbsp

An Initial Study of Finite Element Analysis on Sound Pressure and Pressure Drop on a Diesel Generator Sets

This study is concern about the behavior of a diesel generator sets in terms of sound pressure level and pressure drop. Numerical study had been carried out by using simulation from the ANSYS software to obtain the sound pressure level and pressure drop across a duct silencer of a diesel generator sets. ANSYS Fluent and ANSYS Harmonic Responses was used to perform the simulation on the sound pressure level and pressure drop of the duct silencer. The design of the 3-dimensional model consists of splitter and rockwool as its porous medium. Observation was focused along the simulation process and detailed investigation has been carried out on the duct silencer. From the results obtained, there is noise reduction and pressure drop occur across the duct silencer and contour were observed clearly

Prediction of classroom reverberation time using neural network

In this paper, an alternative method for predicting the reverberation time (RT) using neural network (NN) for classroom was designed and explored. Classroom models were created using Google SketchUp software. The NN applied training dataset from the classroom models with RT values that were computed from ODEON 12.10 software. The NN was conducted separately for 500Hz, 1000Hz, and 2000Hz as absorption coefficient that is one of the prominent input variable is frequency dependent. Mean squared error (MSE) and regression (R) values were obtained to examine the NN efficiency. Overall, the NN shows a good result with MSE 0.9. The NN also managed to achieve a percentage of accuracy of 92.53% for 500Hz, 93.66% for 1000Hz, and 93.18% for 2000Hz and thus displays a good and efficient performance. Nevertheless, the optimum RT value is range between 0.75 – 0.9 seconds

Acoustic properties of biodegradable composite micro-perforated panel (BC-MPP) made from kenaf fibre and polylactic acid (PLA)

This paper investigates the sound absorption of biodegradable composite micro-perforated panel (BC-MPP) made from kenaf fibre and biodegradable polymer known as polylactic acid (PLA). BC-MPP samples were made through conventional machining method such as mixing, drilling, and hot pressing process. Sound absorption of BC-MPP samples were measured by using impedance tube. The porosity and tensile strength of BC-MPP samples were determined by using porosity tester and universal testing machine respectively. The effects of material composition and air gap thickness behind the panel towards the sound absorption coefficient of BC-MPP samples along with the porosity and tensile strength of BC-MPP samples will be presented in this paper. Results indicate that the sound absorption coefficient of BC-MPP samples could be affected by the difference of composition percentage of kenaf fibre and PLA. The porosity of BC-MPP sample increases along with the increment of kenaf fibre composition. However, the increment of kenaf fibre composition causes the reduction of tensile strength of BC-MPP sample. As the air gap thickness behind the panel increases, the peak absorption of BC-MPP sample shifts nearer to lower frequency range. The maximum sound absorption coefficient of BC-MPP sample can be varied as well by altering the air gap thickness behind the panel

Prediction on hand arm vibration exposure cause-effect among grass-cutting workers in Malaysia

Prolonged exposures to hand-transmitted vibrations from grass-cutting machines have been associated with increasing occurrences of signs of occupational diseases related to the hand-arm vibration syndrome (HAVS). However, there are no specific processes available that cover the subjective and objective health cause-effects of the hand arm vibration risk factors during onsite operations. The objectives are (1) to measure the health subjective and objective risks during normal working conditions among hand-held grass-cutting workers and (2) to determine the significant correlation of the subjective and objective measurement variables of the Hand Arm Vibration Exposure Risk Assessment (HAVERA) on hand arm vibration symptoms and disorders. The study was conducted in two stages: evaluation of the HAVERA variables and development of the health prediction cause-effect model of the HAVERA process using multiple linear regressions and feed forward neural network programming. In the onsite measurement, the daily vibration value depicted an exceeded exposure action value of 2.5 m/s2 for both hands; and experiences of any finger colour change were claimed by 80% of the 204 subjects. This shows that HAVERA process provided a good indication of HAVS which are reported as vascular, neurological and musculoskeletal disorders. In the right and left hand prediction model development, the results demonstrated a higher reliability performance as compared to the linear model for hand grip strength and hand numerical scoring assessment. The prediction of the HAVERA model using the neural network method has been developed for monitoring health conditions due to hand-transmitted vibrations among hand-held grasscutting workers in Malaysia

Comparison between GLCM and modified Zernike moments for material surfaces identification from photo images

Types of materials are one of an important data for research in acoustic engineering. This paper compares methods for extracting texture data of material surfaces for classification. Gray Level Co-occurrence Matrix (GLCM) and modified Zernike moments that is applied for image extraction are tested and compared with back propagation neural network used for classification. These methods are also applied to the Brodatz texture database as a general comparison. The GLCM method shows a good performance and regression, R>0.9 for the Brodatz database while the collected surfaces datasets using GLCM and modified Zernike moments as well as the Brodatz datasets using modified Zernike moments method had only managed an acceptable performance and regression of R>0.8

Conceptual framework on noise ranking classification in eatery places for human psycho-acoustics preferences towards acoustic comfort

One of the important dining interests for focusing on smelling and tasting during dining in eatery places is having concentration or attention perceived of what we eat or drink. The dining satisfaction influenced positive behavior of return intent and recommending the eatery places to others. Higher noise level may distract the concentration for having a fine dining experience and could interrupt the ability of smelling and tasting senses. Settings in the noisy atmosphere of eatery places such as located near to a busy road, open kitchen, table layout and inappropriate decoration as well as the patrons’ conversation behavior may affect speech intelligibility. Ultimately, the long period exposure towards high decibel sound and noise affecting not only the health and wellbeing but also the social interactions and communications. It is also having a direct significant impact to human preferences on acoustic comfort during their dining. However, there is no specific classification or rating system established in Malaysia to assist the information on acoustic environment obtained in the eatery place. The aim of this paper is to identify the framework of eatery places classification in Malaysia within the context of the acoustic comfort and its performance. The main concern is to elucidate clearly different categorization of eatery places which might have significant on human psychoacoustics. Based on ongoing research, this paper will discuss on the critical literature reviews to develop a conceptual framework in classifying eatery places typologies and diners’ acoustical preferences

Prediction of sound absorption coefficient for double layer rubberised concrete blocks

Nowadays rubberised concrete is used to support construction sustainability and contribute to a better development of efficient construction material, in particular by using waste rubber tyre. The use of rubber in block pavement is one of the actions in order to reduce the noise from tyre-road interaction and hence able to reduce pass by noise pollution. In this paper, the influence of waste rubber tyre as the replacement for aggregate on the sound absorption coefficient of double layer rubberised concrete blocks was investigated. Non acoustics and acoustics experimental investigations were carried out on a series of block with thickness of 80 mm with facing layer (FL) of block varies in thickness from 10 to 40 mm. FL and bottom layer consist of concrete mixture containing waste tyre rubber granules (RG) of 5 mm to 8 mm and 1 mm to 4 mm, respectively as replacement of natural aggregate within the range of 10-40%. The ratio for cement: aggregate: sand was 1: 1.7:1.5 and water to cement (w/c) ratio of 0.47. Noun acoustics parameters include density, compressive strength, water absorption and porosity. Acoustic parameters investigation of specimens of double layer block showed that concrete pavement blocks have maximum sound absorption located at low frequency of 500 to 700 Hz. This indicates that it is suitable for application of mitigation of low speed traffic condition. A model was developed to predict the maximum sound absorption coefficient of the double layer block pavements which included the percentage of rubber content, thickness of FL and porosity as statistically significant predictor (p < 0.05). This would benefit the road engineers in managing traffic noise management as the sound absorption coefficient is the key important element in reducing tyre/road interaction noise