A number of studies have been conducted on the improvement of the sound quality of electrical artificial laryngeal speech, the speech produced has been difficult to hear compared to a natural voice. For this reason, it is necessary to effectively improve the frequency characteristics of the input signal. In the present study, to improve the sound quality of vocalization using an electrical artificial larynx, first, a comparison of the frequency characteristics between the real and artificial voices was conducted, and three filters that can make the frequency characteristics of the artificial voice closer to those of a real voice were generated. Then, the influence of these filters on the quality of the artificial voice was investigated via physical measurement and a subjective evaluation experiment targeted at Japanese five vowels. It was found that the intelligibility of artificial /a/ and /o/ sounds was improved, whereas little improvement was observed in the case of /i/, /u/, and /e/. The obtained results confirmed the effect of optimizing the input signal into the vibration speaker and indicated areas for further improvement.
{"title":"Effect of Input Waveform to Vibration Speaker on Sound Quality of\u0000Electric Artificial Voice","authors":"T. Asakura, K. Shindo","doi":"10.32604/sv.2020.08119","DOIUrl":"https://doi.org/10.32604/sv.2020.08119","url":null,"abstract":"A number of studies have been conducted on the improvement of the sound quality of electrical artificial laryngeal speech, the speech produced has been difficult to hear compared to a natural voice. For this reason, it is necessary to effectively improve the frequency characteristics of the input signal. In the present study, to improve the sound quality of vocalization using an electrical artificial larynx, first, a comparison of the frequency characteristics between the real and artificial voices was conducted, and three filters that can make the frequency characteristics of the artificial voice closer to those of a real voice were generated. Then, the influence of these filters on the quality of the artificial voice was investigated via physical measurement and a subjective evaluation experiment targeted at Japanese five vowels. It was found that the intelligibility of artificial /a/ and /o/ sounds was improved, whereas little improvement was observed in the case of /i/, /u/, and /e/. The obtained results confirmed the effect of optimizing the input signal into the vibration speaker and indicated areas for further improvement.","PeriodicalId":49496,"journal":{"name":"Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90833161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hossein ElahiShirvan, M. Ghotbi-Ravandi, S. Zare, M. G. Ahsaee
Workers’ exposure to excessive noise is a big universal work-related challenges. One of the major consequences of exposure to noise is permanent or transient hearing loss. The current study sought to utilize audiometric data to weigh and prioritize the factors affecting workers’ hearing loss based using the Support Vector Machine (SVM) algorithm. This cross sectional-descriptive study was conducted in 2017 in a mining industry in southeast Iran. The participating workers (n = 150) were divided into three groups of 50 based on the sound pressure level to which they were exposed (two experimental groups and one control group). Audiometric tests were carried out for all members of each group. The study generally entailed the following steps: (1) selecting predicting variables to weigh and prioritize factors affecting hearing loss; (2) conducting audiometric tests and assessing permanent hearing loss in each ear and then evaluating total hearing loss; (3) categorizing different types of hearing loss; (4) weighing and prioritizing factors that affect hearing loss based on the SVM algorithm; and (5) assessing the error rate and accuracy of the models. The collected data were fed into SPSS 18, followed by conducting linear regression and paired samples t-test. It was revealed that, in the first model (SPL < 70 dBA), the frequency of 8 KHz had the greatest impact (with a weight of 33%), while noise had the smallest influence (with a weight of 5%). The accuracy of this model was 100%. In the second model (70 < SPL < 80 dBA), the frequency of 4 KHz had the most profound effect (with a weight of 21%), whereas the frequency of 250 Hz had the lowest impact (with a weight of 6%). The accuracy of this model was 100% too. In the third model (SPL > 85 dBA), the frequency of 4 KHz had the highest impact (with a weight of 22%), while the frequency of 250 Hz had the smallest influence (with a weight of 3%). The accuracy of this model was 100% too. In the fourth model, the frequency of 4 KHz had the greatest effect (with a weight of 24%), while the frequency of 500 Hz had the smallest effect (with a weight of 4%). The accuracy of this model was found to be 94%. According to the modeling conducted using the This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Sound & Vibration DOI:10.32604/sv.2020.08839 Article ech T Press Science
{"title":"Using Audiometric Data to Weigh and Prioritize Factors that Affect Workers’\u0000Hearing Loss through Support Vector Machine (SVM) Algorithm","authors":"Hossein ElahiShirvan, M. Ghotbi-Ravandi, S. Zare, M. G. Ahsaee","doi":"10.32604/sv.2020.08839","DOIUrl":"https://doi.org/10.32604/sv.2020.08839","url":null,"abstract":"Workers’ exposure to excessive noise is a big universal work-related challenges. One of the major consequences of exposure to noise is permanent or transient hearing loss. The current study sought to utilize audiometric data to weigh and prioritize the factors affecting workers’ hearing loss based using the Support Vector Machine (SVM) algorithm. This cross sectional-descriptive study was conducted in 2017 in a mining industry in southeast Iran. The participating workers (n = 150) were divided into three groups of 50 based on the sound pressure level to which they were exposed (two experimental groups and one control group). Audiometric tests were carried out for all members of each group. The study generally entailed the following steps: (1) selecting predicting variables to weigh and prioritize factors affecting hearing loss; (2) conducting audiometric tests and assessing permanent hearing loss in each ear and then evaluating total hearing loss; (3) categorizing different types of hearing loss; (4) weighing and prioritizing factors that affect hearing loss based on the SVM algorithm; and (5) assessing the error rate and accuracy of the models. The collected data were fed into SPSS 18, followed by conducting linear regression and paired samples t-test. It was revealed that, in the first model (SPL < 70 dBA), the frequency of 8 KHz had the greatest impact (with a weight of 33%), while noise had the smallest influence (with a weight of 5%). The accuracy of this model was 100%. In the second model (70 < SPL < 80 dBA), the frequency of 4 KHz had the most profound effect (with a weight of 21%), whereas the frequency of 250 Hz had the lowest impact (with a weight of 6%). The accuracy of this model was 100% too. In the third model (SPL > 85 dBA), the frequency of 4 KHz had the highest impact (with a weight of 22%), while the frequency of 250 Hz had the smallest influence (with a weight of 3%). The accuracy of this model was 100% too. In the fourth model, the frequency of 4 KHz had the greatest effect (with a weight of 24%), while the frequency of 500 Hz had the smallest effect (with a weight of 4%). The accuracy of this model was found to be 94%. According to the modeling conducted using the This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Sound & Vibration DOI:10.32604/sv.2020.08839 Article ech T Press Science","PeriodicalId":49496,"journal":{"name":"Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89467498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Wu, Kuan Lu, Yulin Jin, Haopeng Zhang, Yushu Chen
Two different order reduction methods of the deterministic and stochastic systems are discussed in this paper. First, the transient proper orthogonal decomposition (T-POD) method is introduced based on the high-dimensional nonlinear dynamic system. The optimal order reduction conditions of the T-POD method are provided by analyzing the rotor-bearing system with pedestal looseness fault at both ends. The efficiency of the T-POD method is verified via comparing with the results of the original system. Second, the polynomial dimensional decomposition (PDD) method is applied to the 2 DOFs spring system considering the uncertain stiffness to study the amplitude-frequency response. The numerical results obtained by the PDD method agree well with the Monte Carlo simulation (MCS) method. The results of the PDD method can approximate to MCS better with the increasing of the polynomial order. Meanwhile, the Uniform-Legendre polynomials can eliminate perturbation of the PDD method to a certain extent via comparing it with the Gaussian-Hermite polynomials.
{"title":"The Applications of Order Reduction Methods in Nonlinear Dynamic Systems","authors":"N. Wu, Kuan Lu, Yulin Jin, Haopeng Zhang, Yushu Chen","doi":"10.32604/sv.2020.09783","DOIUrl":"https://doi.org/10.32604/sv.2020.09783","url":null,"abstract":"Two different order reduction methods of the deterministic and stochastic systems are discussed in this paper. First, the transient proper orthogonal decomposition (T-POD) method is introduced based on the high-dimensional nonlinear dynamic system. The optimal order reduction conditions of the T-POD method are provided by analyzing the rotor-bearing system with pedestal looseness fault at both ends. The efficiency of the T-POD method is verified via comparing with the results of the original system. Second, the polynomial dimensional decomposition (PDD) method is applied to the 2 DOFs spring system considering the uncertain stiffness to study the amplitude-frequency response. The numerical results obtained by the PDD method agree well with the Monte Carlo simulation (MCS) method. The results of the PDD method can approximate to MCS better with the increasing of the polynomial order. Meanwhile, the Uniform-Legendre polynomials can eliminate perturbation of the PDD method to a certain extent via comparing it with the Gaussian-Hermite polynomials.","PeriodicalId":49496,"journal":{"name":"Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90534854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. F. Madvari, M. Monazzam, M. N. Sharak, Mohsen Mosa Farkhani
Honeycomb structures have recently, replaced with conventional homogeneous materials. Given the fact that sandwich panels containing a honeycomb core are able to adjust geometric parameters, including internal angles, they are suitable for acoustic control applications. The main objective of this study was to obtain a transmission loss curve in a specific honeycomb frequency range along with same overall dimensions and weight. In this study, a finite element model (FEM) in ABAQUS software was used to simulate honeycomb panels, evaluate resonant frequencies, and for acoustic analysis. This model was used to obtain acoustic pressure and then to calculate the sound transmission loss (STL) in MATLAB software. Vibration and acoustic analysis of panels were performed in the frequency range of 1 to 1000 Hz. The models analyzed in this design includes 14-single row-honeycomb designs with angles of −45°, −30°, −15°, 0°, +15°, +30°, +45°. The results showed that a-single row and −45°cell angle honeycomb panel in the frequency range of 1 to 1000 Hz had the highest STL as well as the highest number of frequency modes (90 mods). Furthermore, the panel had the highest STL regarding the area under the STL curve (dB∙Hz). The panels containing more frequency mods, have a higher transmission loss. Moreover, the sound transmission loss is more sensitive to the cell angle variable (θ). In other studies, the STL was more sensitive to the number of honeycomb cells in the horizontal and vertical directions, as well as the angle of cells.
{"title":"Analytical Study on the Rate of Sound Transmission Loss in Single Row\u0000Honeycomb Sandwich Panel Using a Numerical Method","authors":"R. F. Madvari, M. Monazzam, M. N. Sharak, Mohsen Mosa Farkhani","doi":"10.32604/sv.2020.08158","DOIUrl":"https://doi.org/10.32604/sv.2020.08158","url":null,"abstract":"Honeycomb structures have recently, replaced with conventional homogeneous materials. Given the fact that sandwich panels containing a honeycomb core are able to adjust geometric parameters, including internal angles, they are suitable for acoustic control applications. The main objective of this study was to obtain a transmission loss curve in a specific honeycomb frequency range along with same overall dimensions and weight. In this study, a finite element model (FEM) in ABAQUS software was used to simulate honeycomb panels, evaluate resonant frequencies, and for acoustic analysis. This model was used to obtain acoustic pressure and then to calculate the sound transmission loss (STL) in MATLAB software. Vibration and acoustic analysis of panels were performed in the frequency range of 1 to 1000 Hz. The models analyzed in this design includes 14-single row-honeycomb designs with angles of −45°, −30°, −15°, 0°, +15°, +30°, +45°. The results showed that a-single row and −45°cell angle honeycomb panel in the frequency range of 1 to 1000 Hz had the highest STL as well as the highest number of frequency modes (90 mods). Furthermore, the panel had the highest STL regarding the area under the STL curve (dB∙Hz). The panels containing more frequency mods, have a higher transmission loss. Moreover, the sound transmission loss is more sensitive to the cell angle variable (θ). In other studies, the STL was more sensitive to the number of honeycomb cells in the horizontal and vertical directions, as well as the angle of cells.","PeriodicalId":49496,"journal":{"name":"Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90649764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Today, analyzing of sound pressure level and frequency is considered as an important index in human society. Sound experts believe that analyzing of these parameters can help us to better understanding of work environments. Sound measurements and frequency analysis did to fi x the harmful frequency in all sections in Shiraz gas power plant with sound analyzer model BSWA 308. The sound pressure levels (L P ) and the one and one-third octave band were continuously measured in A and C weighting networks and slow mode for time response. Excel 2013 and Minitab 18.1 software used for statistical calculations. Results analyzed by Minitab 18.1 software. The highest harmful frequency in Shiraz Gas Power Plant (SGPP) was 50 Hz with 115 dB. The sound pressure level (SPL) ranged from 45 dB to 120 dB in one-third octave band and weighting net-work C. The maximum sound pressure level was in Craft electricity generator with 105.3 dB and 67 Hz. Sound pressure level in surrounded environment was 120 dB. According to the results, in this industry the sound pressure level exceeded the Occupational Exposure Level of Iran (OEL). The value of sound pressure level were higher than the Standard of occupational health. SGPP con-sumes 47000 cubic meters of natural gas per hour to produce 100 MW (Mega Watt) of electricity. It is very high and it is not economical and cost effec-tive. These numbers indicate that the power plant ’ s ef fi ciency is low. It could be concluded that the noise pollution is an important issue in these industries. More-over, SGPP produce noise with loss energy. Frequencies rotation at high sound pressure levels toward low frequencies were happened.
{"title":"Frequencies Rotation at High Sound Pressure Levels Toward Low Frequencies","authors":"Hadi Negahdari, S. Javadpour, F. Moattar","doi":"10.32604/sv.2020.011086","DOIUrl":"https://doi.org/10.32604/sv.2020.011086","url":null,"abstract":": Today, analyzing of sound pressure level and frequency is considered as an important index in human society. Sound experts believe that analyzing of these parameters can help us to better understanding of work environments. Sound measurements and frequency analysis did to fi x the harmful frequency in all sections in Shiraz gas power plant with sound analyzer model BSWA 308. The sound pressure levels (L P ) and the one and one-third octave band were continuously measured in A and C weighting networks and slow mode for time response. Excel 2013 and Minitab 18.1 software used for statistical calculations. Results analyzed by Minitab 18.1 software. The highest harmful frequency in Shiraz Gas Power Plant (SGPP) was 50 Hz with 115 dB. The sound pressure level (SPL) ranged from 45 dB to 120 dB in one-third octave band and weighting net-work C. The maximum sound pressure level was in Craft electricity generator with 105.3 dB and 67 Hz. Sound pressure level in surrounded environment was 120 dB. According to the results, in this industry the sound pressure level exceeded the Occupational Exposure Level of Iran (OEL). The value of sound pressure level were higher than the Standard of occupational health. SGPP con-sumes 47000 cubic meters of natural gas per hour to produce 100 MW (Mega Watt) of electricity. It is very high and it is not economical and cost effec-tive. These numbers indicate that the power plant ’ s ef fi ciency is low. It could be concluded that the noise pollution is an important issue in these industries. More-over, SGPP produce noise with loss energy. Frequencies rotation at high sound pressure levels toward low frequencies were happened.","PeriodicalId":49496,"journal":{"name":"Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89918272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hossein Molaeifar, F. Khajehnasiri, Kiana Nikeghbal, Z. Zamanian
Exposure to sound, heat, and increased physical workload can change physiological parameters. This study was conducted to evaluate the effect of concomitant exposure to sound, heat, and physical workload changes on physiological parameters in controlled laboratory conditions. This experimental crosssectional study was conducted in 35 male university students with a mean age of 25.75 years and a mean BMI of 22.69 kg/m. Systolic and diastolic blood pressure and heart rate were measured after 15 min rest in the laboratory, 5 and 10 min after starting the experiment, and then after 20 min in controlled laboratory conditions in five combination modes. The combination modes were (Sound: 65 dB, WBGT: 22°C, Speed: 1.7, Slope: 10%), (Sound: 65 dB, WBGT: 22°C, Speed: 3.4, Slope: 14%), (Sound: 95 dB, WBGT: 22°C, Speed: 1.7, Slope: 10%), (Sound: 65 dB, WBGT: 32°C, Speed: 1.7, Slope: 10%), and (Sound: 95 dB, WBGT: 32°C, Speed: 3.4, Slope: 14%). Mixed model analysis and paired t-test were applied for analysis. The results showed that the mean physiological parameters (Systolic and diastolic blood pressure and heart rate) increased when different combination modes worsened (Sound from 65 to 95 dB, WBGT from 22°C to 32°C, speed from 1.7 to 3.4, and slope from 10% to 14%, and when sound: 95 dB, WBGT: 32°C, Speed: 3.4, and Slope: 14%). Moreover, the mean changes of systolic and diastolic blood pressure were significant in all conditions when compared with the reference condition (Sound: 65 dB, WBGT: 22°C, Speed: 1.7, and Slope: 10%). The mean heart rate changes were also significant except for exposure to the second condition (Sound: 65 dB, WBGT: 22°C, Speed: 3.4, Slope: 14%) and the third condition (Sound: 95 dB, WBGT: 22°C, Speed: 1.7, Slope: 10%). Exposure to hazardous levels of sound, heat, and workload has adverse effects on physiological parameters. Concomitant exposure to all three hazards has a synergistic effect and increases the adverse effect.
{"title":"Assessment of Effects of Concomitant Exposure to Sound, Heat, and Physical\u0000Workload Changes on Physiological Parameters in Five Different Combination\u0000Modes, a Controlled Laboratory Study","authors":"Hossein Molaeifar, F. Khajehnasiri, Kiana Nikeghbal, Z. Zamanian","doi":"10.32604/sv.2020.08810","DOIUrl":"https://doi.org/10.32604/sv.2020.08810","url":null,"abstract":"Exposure to sound, heat, and increased physical workload can change physiological parameters. This study was conducted to evaluate the effect of concomitant exposure to sound, heat, and physical workload changes on physiological parameters in controlled laboratory conditions. This experimental crosssectional study was conducted in 35 male university students with a mean age of 25.75 years and a mean BMI of 22.69 kg/m. Systolic and diastolic blood pressure and heart rate were measured after 15 min rest in the laboratory, 5 and 10 min after starting the experiment, and then after 20 min in controlled laboratory conditions in five combination modes. The combination modes were (Sound: 65 dB, WBGT: 22°C, Speed: 1.7, Slope: 10%), (Sound: 65 dB, WBGT: 22°C, Speed: 3.4, Slope: 14%), (Sound: 95 dB, WBGT: 22°C, Speed: 1.7, Slope: 10%), (Sound: 65 dB, WBGT: 32°C, Speed: 1.7, Slope: 10%), and (Sound: 95 dB, WBGT: 32°C, Speed: 3.4, Slope: 14%). Mixed model analysis and paired t-test were applied for analysis. The results showed that the mean physiological parameters (Systolic and diastolic blood pressure and heart rate) increased when different combination modes worsened (Sound from 65 to 95 dB, WBGT from 22°C to 32°C, speed from 1.7 to 3.4, and slope from 10% to 14%, and when sound: 95 dB, WBGT: 32°C, Speed: 3.4, and Slope: 14%). Moreover, the mean changes of systolic and diastolic blood pressure were significant in all conditions when compared with the reference condition (Sound: 65 dB, WBGT: 22°C, Speed: 1.7, and Slope: 10%). The mean heart rate changes were also significant except for exposure to the second condition (Sound: 65 dB, WBGT: 22°C, Speed: 3.4, Slope: 14%) and the third condition (Sound: 95 dB, WBGT: 22°C, Speed: 1.7, Slope: 10%). Exposure to hazardous levels of sound, heat, and workload has adverse effects on physiological parameters. Concomitant exposure to all three hazards has a synergistic effect and increases the adverse effect.","PeriodicalId":49496,"journal":{"name":"Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89190188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Vehicles generate dissimilar sound patterns under different working environments. These generated sound patterns signify the condition of the engines, which in turn is used for diagnosing various faults. In this paper, the sound signals produced by motorcycles are analyzed to locate various faults. The important attributes are extracted from the generated sound signals based on time, frequency and wavelet domains which clearly describe the statistical behavior of the signals. Further, various types of faults are classi fi ed using the Extreme Learning Machine (ELM) classi fi er from the extracted features. More-over, the improved classi fi cation performance is obtained by the combination of feature sets in different domains. The simulation results clearly demonstrate that the proposed hybrid feature set together with the ELM classi fi er gives more promising results with higher classi fi cation accuracy when compared with the other conventional methods.
{"title":"Sound Signal Based Fault Classification System in Motorcycles Using Hybrid Feature Sets and Extreme Learning Machine Classifiers","authors":"T. Jayasree, R. Ananth","doi":"10.32604/sv.2020.08573","DOIUrl":"https://doi.org/10.32604/sv.2020.08573","url":null,"abstract":": Vehicles generate dissimilar sound patterns under different working environments. These generated sound patterns signify the condition of the engines, which in turn is used for diagnosing various faults. In this paper, the sound signals produced by motorcycles are analyzed to locate various faults. The important attributes are extracted from the generated sound signals based on time, frequency and wavelet domains which clearly describe the statistical behavior of the signals. Further, various types of faults are classi fi ed using the Extreme Learning Machine (ELM) classi fi er from the extracted features. More-over, the improved classi fi cation performance is obtained by the combination of feature sets in different domains. The simulation results clearly demonstrate that the proposed hybrid feature set together with the ELM classi fi er gives more promising results with higher classi fi cation accuracy when compared with the other conventional methods.","PeriodicalId":49496,"journal":{"name":"Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73978397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Variani, Ali Dastamoz, S. Zare, A. Nikpey, Saeid Ahmadi
This work investigated multiple jet nozzles with various geometrical shape, number of exits, and material on reducing noise radiated from jet flows. Nozzles are categorized in two groups with few and many exit numbers, each with various exit shapes, slot and circular, and geometry. Firstly, nozzles are designed and then fabricated by a 3D printer, Form Labs, Form2USA, with polymeric resin. Also, the nozzle with the most noise reduction made of stainless steel. Noise and air thrust were measured at three air pressure gauges, 3, 5, 7 BAR and directions from nozzle apex, 30°, 90°, 135°. Nozzles with slot exit shape made of both plastic and stainless steel revealed the most noise reduction among all nozzles with few exit numbers, nearly 11–14 dB(A) and 11.5–15 dB(A), respectively. On average, slotted nozzle noise reduction was nearly 5–6 dB(A) more than finned nozzle. However, nozzles with more exit numbers, finned and finned-central exit, illustrated much more noise reduction than nozzles with few exit numbers, by almost 16–18 dB(A), they represented similar sound. All tested nozzles and open pipe demonstrated equal air thrust at each pressure gauges. The nozzles with slotted exit shape, either plastic or stainless steel, can provide reasonable noise reduction in comparison to other configuration with few exit numbers. In contrast, nozzles with more exit numbers demonstrated the most noise reduction.
{"title":"The Acoustic Performance of 3D Printed Multiple Jet Nozzles with Different Configurations","authors":"A. Variani, Ali Dastamoz, S. Zare, A. Nikpey, Saeid Ahmadi","doi":"10.32604/sv.2020.08636","DOIUrl":"https://doi.org/10.32604/sv.2020.08636","url":null,"abstract":"This work investigated multiple jet nozzles with various geometrical shape, number of exits, and material on reducing noise radiated from jet flows. Nozzles are categorized in two groups with few and many exit numbers, each with various exit shapes, slot and circular, and geometry. Firstly, nozzles are designed and then fabricated by a 3D printer, Form Labs, Form2USA, with polymeric resin. Also, the nozzle with the most noise reduction made of stainless steel. Noise and air thrust were measured at three air pressure gauges, 3, 5, 7 BAR and directions from nozzle apex, 30°, 90°, 135°. Nozzles with slot exit shape made of both plastic and stainless steel revealed the most noise reduction among all nozzles with few exit numbers, nearly 11–14 dB(A) and 11.5–15 dB(A), respectively. On average, slotted nozzle noise reduction was nearly 5–6 dB(A) more than finned nozzle. However, nozzles with more exit numbers, finned and finned-central exit, illustrated much more noise reduction than nozzles with few exit numbers, by almost 16–18 dB(A), they represented similar sound. All tested nozzles and open pipe demonstrated equal air thrust at each pressure gauges. The nozzles with slotted exit shape, either plastic or stainless steel, can provide reasonable noise reduction in comparison to other configuration with few exit numbers. In contrast, nozzles with more exit numbers demonstrated the most noise reduction.","PeriodicalId":49496,"journal":{"name":"Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72380645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Parvane Mahdi, A. Pourbakht, V. Mahabadi, A. Yazdi, M. Anari, M. Kamali
Exposure to high level of noise, may cause the permanent cochlear synaptic degeneration. In present study, a model of noise induced cochlear synaptopathy was established and the electrophysiological and histological metrics for its assessment was designed. 6 guinea pigs were subjected to a synaptopathic noise (octave band of 4 kHz at 104 dB SPL, for 2-h). The amplitude growth curve of Auditory Brainstem Response (ABR) wave-I and wave-III latency shift in presence of noise were calculated. These indexes were considered in pre-exposure, 1 day post exposure (1DPE), 1 week post exposure (1WPE) and 1 month post exposure (1MPE) to noise. Finally, the samples were histologically analyzed. ABR wave-I amplitude was different between pre and 1DPE (p-value ≤ 0.05). However, at 1WPE, it was recovered at low intensities but at 70 dB SPL and above, the differences persisted even till 1MPE. In masked ABR, the latency shift of wave-III was different between pre and 3 post exposure assessments (p-value ≤ 0.05). Electro-microscopic analysis confirmed the synaptic degeneration, as the ribbons were larger than normal, hollow inside, and spherical and irregular in shape, also, the post synaptic density was abnormally thick and missed its flat orientation. These data revealed that noise at level below that can produce permanent hearing loss, can incur synaptic injury. So, noise is considered to be more damaging than previously thought. Accordingly, designing tools for clinical assessment of synaptopathy is beneficial in comprehensive auditory evaluation of those with history of noise exposure and also in hearing protection planning.
暴露在高水平的噪音中，可能导致永久性的耳蜗突触变性。本研究建立了噪声性耳蜗突触病模型，并设计了评价噪声性耳蜗突触病的电生理和组织学指标。将6只豚鼠置于突触病变噪声(4 kHz, 104 dB SPL，倍频带)下2小时。计算噪声存在下听觉脑干反应(ABR)波i和波iii潜伏期移位的振幅增长曲线。这些指标分别在噪声暴露前、暴露后1天(1DPE)、暴露后1周(1WPE)和暴露后1个月(1MPE)进行考虑。最后，对样本进行组织学分析。ABR波i幅值与dpe前后存在差异(p值≤0.05)。然而，在1WPE时，它在低强度下恢复，但在70 dB SPL及以上，差异甚至持续到1MPE。在隐蔽性ABR中，暴露前和暴露后3次评估中，iii波的潜伏期移位有差异(p值≤0.05)。电镜分析证实突触变性，突触带比正常大，内部空心，形状呈球形不规则，突触后密度异常增厚，失去了其平面取向。这些数据表明，低于这个水平的噪音会导致永久性听力丧失，会导致突触损伤。因此，噪音被认为比之前认为的更具破坏性。因此，设计突触病的临床评估工具，有利于噪声暴露史患者的综合听觉评估和听力保护规划。
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This work aims to improve the setup of an electrodynamic triaxial shaker prototype with respect to its usability for the automotive industry. Triaxial shakers being capable of meeting the corresponding requirements are not available as standard test equipment. Modifications on the fixture have to be conducted in order to ensure an effective control. The first part of the work is the qualitative description of the system behavior. Therefore, the shaker is treated as a black box. The second part is the modification of the test fixture in order to handle the resonances of the shaker, which is elementary for its usage. A setup is found, that improves testing within the desired frequency range. Thereby, acceleration levels are considered as well as excitation phases and coherences. The proposed setup is used for an exemplary specimen with two different control scenarios. Conclusions are then drawn about the usage of triaxial shakers.
{"title":"Fixture Modifications for Effective Control of an Electrodynamic\u00003D-Shaker System","authors":"K. Kersch, E. Woschke","doi":"10.32604/sv.2020.08909","DOIUrl":"https://doi.org/10.32604/sv.2020.08909","url":null,"abstract":"This work aims to improve the setup of an electrodynamic triaxial shaker prototype with respect to its usability for the automotive industry. Triaxial shakers being capable of meeting the corresponding requirements are not available as standard test equipment. Modifications on the fixture have to be conducted in order to ensure an effective control. The first part of the work is the qualitative description of the system behavior. Therefore, the shaker is treated as a black box. The second part is the modification of the test fixture in order to handle the resonances of the shaker, which is elementary for its usage. A setup is found, that improves testing within the desired frequency range. Thereby, acceleration levels are considered as well as excitation phases and coherences. The proposed setup is used for an exemplary specimen with two different control scenarios. Conclusions are then drawn about the usage of triaxial shakers.","PeriodicalId":49496,"journal":{"name":"Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83185248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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