A Study on the Sound Quality Evaluation Model of Mechanical Air-Cleaners

2009 ◽  
Vol 131 (3) ◽  
Author(s):  
Jeong-Guon Ih ◽  
Su-Won Jang ◽  
Cheol-Ho Jeong ◽  
Youn-Young Jeung
Keyword(s):  
High Frequency ◽  
Quality Evaluation ◽  
Principal Component ◽  
Sound Quality ◽  
Subjective Feeling ◽  
Subjective Data ◽  
Frequency Bands ◽  
Air Cleaner ◽  
Air Cleaners

In operating the air-cleaner for a long time, people in a quiet enclosed space expect low sound at low operational levels for a routine cleaning of air. However, in the condition of high operational levels of the cleaner, a powerful yet nonannoying sound is desired, which is connected to a feeling of an immediate cleaning of pollutants. In this context, it is important to evaluate and design the air-cleaner noise to satisfy such contradictory expectations from the customers. In this study, a model for evaluating the sound quality of air-cleaners of mechanical type was developed based on objective and subjective analyses. Sound signals from various air-cleaners were recorded and they were edited by increasing or decreasing the loudness at three wide specific-loudness bands: 20–400 Hz (0–3.8 barks), 400–1250 Hz (3.8–10 barks), and 1.25–12.5 kHz bands (10–22.8 barks). Subjective tests using the edited sounds were conducted by the semantic differential method (SDM) and the method of successive intervals (MSI). SDM tests for seven adjective pairs were conducted to find the relation between subjective feeling and frequency bands. Two major feelings, performance and annoyance, were factored out from the principal component analysis. We found that the performance feeling was related to both low and high frequency bands, whereas the annoyance feeling was related to high frequency bands. MSI tests using the seven scales were conducted to derive the sound quality index to express the severity of each perceptive descriptor. Annoyance and performance indices of air-cleaners were modeled from the subjective responses of the juries and the measured sound quality metrics: loudness, sharpness, roughness, and fluctuation strength. The multiple regression method was employed to generate sound quality evaluation models. Using the developed indices, sound quality of the measured data was evaluated and compared with the subjective data. The difference between predicted and tested scores was less than 0.5 points.

A Study on the Sound Quality Evaluation Model of the Air Cleaner

2007 ◽  
Author(s):  
Jeong-Guon Ih ◽  
Su-Won Jang ◽  
Cheol-Ho Jeong ◽  
Youn-Young Jeung ◽  
Kye-Sup Jun
Keyword(s):  
High Frequency ◽  
Quality Evaluation ◽  
Principal Component ◽  
Sound Quality ◽  
Differential Method ◽  
Subjective Feeling ◽  
Subjective Data ◽  
Frequency Bands ◽  
Air Cleaner ◽  
Air Cleaners

In operating the air cleaner for a long time, people in a quiet enclosed space expect calm sound at low operational levels for a routine cleaning of air; in contrast, a powerful, yet not-annoying, sound is expected at high operational levels for an immediate cleaning of pollutants. In this context, it is important to evaluate and design the air cleaner noise to satisfy such contradictory expectation from the customers. In this study, a model for evaluating the air cleaner sound quality was developed based on the objective and subjective analyses. Sound signals from various air cleaners were recorded and they were edited by increasing or decreasing the loudness at three wide specific-loudness bands: 20–400 Hz (0–3.8 Bark), 400–1250 Hz (3.8–10 Bark), 1.25k–12.5k Hz bands (10–22.8 Bark). Subjective tests using the edited sounds were conducted by the semantic differential method (SDM) and the method of successive intervals (MSI). SDM test for 7 adjective pairs was conducted to find the relation between subjective feeling and frequency bands. Two major feelings, performance and annoyance, were factored out from the principal component analysis. We found that the performance feeling was related to both low and high frequency bands; whereas the annoyance feeling was related to high frequency bands. MSI test using the 7 scales was conducted to derive the sound quality index to express the severity of each perceptive descriptor. Annoyance and performance indices of air cleaners were modeled from the subjective responses of the juries and the measured sound quality metrics: loudness, sharpness, roughness, and fluctuation strength. Multiple regression method was employed to generate sound quality evaluation models. Using the developed indices, sound quality of the measured data were evaluated and compared with the subjective data. The difference between predicted and tested scores was less than 0.5 point.

A Semantic Differential for Evaluating the Sound Quality of Fan Systems

2017 ◽  
Author(s):  
Carolin Feldmann ◽  
Thomas Carolus ◽  
Marc Schneider
Keyword(s):  
Principal Component ◽  
Semantic Differential ◽  
Sound Quality ◽  
Heat Pumps ◽  
First Case ◽  
Objective Metrics ◽  
Main Components ◽  
Air Conditioning Systems ◽  
The University

Fans are main components e.g. in heating, ventilating and air conditioning systems for vehicles or buildings, cooling units of engines and electronic circuits, and household appliances such as kitchen exhaust hoods or vacuum cleaners. End-users increasingly demand a high sound quality of their system or device. The overall objective of a recent research project at the University of Siegen is a multidimensional assessment of fan sound quality. In a first step an advanced novel semantic differential for the assessment of fan-related sounds is established with the aid of carefully designed jury tests. Eventually, this semantic differential is employed for sound quality jury tests of fans in kitchen exhaust hoods, heat pumps and air purifiers as a first case. Finally, a prediction model is suggested, which relates the outcome from the jury tests to objective metrics. A principal component analysis is carried out and yields five main assessment criteria with 23 relevant adjective scales. The results show that the perceived sound quality of fan systems is mainly determined by the loudness and tonality of the sound. The spectral content (represented by the sharpness) as well as the time structure (represented by the roughness) have no significant impact on perceived sound quality of the fan systems investigated.

scholarly journals A New Strategy for Quality Evaluation and Identification of Representative Chemical Components in Polygonum multiflorum Thunb.

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yun-xia Li ◽  
Xiao-hong Gong ◽  
Mei-chen Liu ◽  
Cheng Peng ◽  
Peng Li ◽  
...  
Keyword(s):  
Quality Evaluation ◽  
Comprehensive Evaluation ◽  
Principal Component ◽  
Chemical Compounds ◽  
Chemical Components ◽  
Health Food ◽  
Polygonum Multiflorum ◽  
New Strategy ◽  
Novel Method

Polygonum multiflorum Thunb. (HSW) is widely used as herb medicine and health food additive. Recently, a series of HSW-induced hepatotoxicities have been reported and many studies have been carried out to investigate it. But contradictory conclusions were drawn that might be caused by the inconsistent quality of market decoction pieces. Therefore, the HSW decoction pieces quality was evaluated with a developed novel method in the paper. 25 batches of raw HSW (RHSW) and 21 batches of processed HSW (PHSW) samples were purchased from different provinces of China. HPLC determination was performed to identify and detect the contents of 16 chemical compounds in herbal material. Fingerprint similarity was analyzed using chromatography information and the results showed that most herbs were in good similarity. Then, a comprehensive evaluation strategy based on principal component analysis with representative quality control indicators was developed to evaluate the quality of HSW samples. And the rationality of the developed method was verified by HCA analysis. The results showed that the herb from Dabashan, Sichuan Province, no matter RHSW or PHSW had the best quality. Different representative components were selected for RHSW or PHSW decoction pieces which might be caused by the chemical reaction during processing. And most PHSW were unqualified according to the requirement of Chinese Pharmacopeia which might take the responsibility for the toxicity of HSW.

An Initial-Fit Comparison of Two Generic Hearing Aid Prescriptive Methods (NAL-NL2 and CAM2) to Individuals Having Mild to Moderately Severe High-Frequency Hearing Loss

2013 ◽  
Vol 24 (02) ◽  
pp. 138-150 ◽  
Author(s):  
Earl E. Johnson
Keyword(s):  
Hearing Loss ◽  
High Frequency ◽  
Speech Intelligibility ◽  
Paired Comparison ◽  
Hearing Aid ◽  
Sound Quality ◽  
Individual Subject ◽  
Model Calculations ◽  
High Frequency Hearing Loss

Background: Johnson and Dillon (2011) provided a model-based comparison of current generic hearing aid prescriptive methods for adults with hearing loss based on the attributes of speech intelligibility, loudness, and bandwidth. Purpose: This study compared the National Acoustic Laboratories—Non-linear 2 (NAL-NL2) and Cambridge Method for Loudness Equalization 2—High-Frequency (CAM2) prescriptive methods using adult participants with less high-frequency hearing loss than Johnson and Dillon (2011). Of study interest was quantification of prescribed audibility, speech intelligibility, and loudness. The preferences of participants for either NAL-NL2 or CAM2 and preferred deviations from prescribed settings are also reported. Research Design: Using a single-blind, counter-balanced, randomized design, preference judgments for the prescriptive methods with regard to sound quality of speech and music stimuli were obtained. Preferred gain adjustments from the prescription within the 4–10 kHz frequency range were also obtained from each participant. Speech intelligibility and loudness model calculations were completed on the prescribed and adjusted amplification. Study Sample: Fourteen male Veterans, whose average age was 65 yr and whose hearing sensitivity averaged normal to borderline normal through 1000 Hz sloping to a moderately severe sensorineural loss, served as participants. Data Collection and Analysis: Following a brief listening time (˜10 min), typical of an initial fitting visit, the participants made paired comparison of sound quality between the NAL-NL2 and CAM2 prescriptive settings. Participants were also asked to modify each prescription in the range of 4–10 kHz using an overall gain control and make subsequent comparisons of sound quality preference between prescriptive and adjusted settings. Participant preferences were examined with respect to quantitative analysis of loudness modeling, speech intelligibility modeling, and measured high-frequency bandwidth audibility. Results: Consistent with the lack of difference in predicted speech intelligibility between the two prescriptions, sound quality preferences on the basis of clarity were split across participants while some participants did not have a discernable preference. Considering sound quality judgments of pleasantness, the majority of participants preferred the sound quality of the NAL-NL2 (8 of 14) prescription instead of the CAM2 prescription (2 of 14). Four of the 14 participants showed no preference on the basis of pleasantness for either prescription. Individual subject preferences were supported by loudness modeling that indicated NAL-NL2 was the softer of the two prescriptions and CAM2 was the louder. CAM2 did provide more audibility to the higher frequencies (5–8 kHz) than NAL-NL2. Participants turned the 4–10 kHz gain recommendation of CAM2 lower, on average, by a significant amount of 4 dB when making adjustments while no significant adjustment was made to the initial NAL-NL2 recommendation. Conclusions: NAL-NL2 prescribed gains were more often preferred at the initial fitting by the majority of participating veterans. For those patients with preference for a louder fitting than NAL-NL2, CAM2 is a good alternative. When the participant adjustment from the prescription between 4 and 10 kHz exceeded 4 dB from either NAL-NL2 (2 of 14) or CAM2 (11 of 14), the participants demonstrated a later preference for that adjustment 69% of the time. These findings are viewed as limited evidence that some individuals may have a preference for high-frequency gain that differs from the starting prescription.

Quality Evaluation of Strawberries Packed with Perforated Film

2012 ◽  
Vol 200 ◽  
pp. 451-454
Author(s):  
Zu Ju Shu ◽  
Sheng Quan Liu ◽  
Yan Yuan ◽  
Ye Bao Xia
Keyword(s):  
Carbon Dioxide ◽  
Quality Evaluation ◽  
Carbon Dioxide Concentration ◽  
Principal Component ◽  
Quality Parameters ◽  
Low Oxygen ◽  
High Carbon ◽  
Perforated Film ◽  
High Carbon Dioxide

Strawberries were stored in perforated film packages with different number and diameter of perforation for 5 days at 18°C simulating the ordinary logistics in Hefei. The non-perforated film packages were used as the control. Several quality parameters of strawberries were determined and analyzed everyday during storage. The principal component analysis was applied to the comprehensive assessment of strawberry quality. The results showed that suitable diameter and number of perforation could maintain strawberry quality. The comprehensive quality of strawberries packed in perforated film with 36 perforations of diameter 0.5mm was the best, followed by the ones packed in non-perforated film with internal atmosphere of low oxygen and high carbon dioxide concentration.

EVALUATION OF NONSTATIONARY VEHICLE PASSING LOUDNESS BASED ON AN ANTINOISE WAVELET PRE-PROCESSING NEURAL NETWORK MODEL

2009 ◽  
Vol 07 (04) ◽  
pp. 459-480 ◽  
Author(s):  
Y. S. WANG ◽  
C.-M. LEE
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Neural Network Model ◽  
Quality Evaluation ◽  
Sound Quality ◽  
Point Model ◽  
Vehicle Noise ◽  
A New Technique ◽  
Loudness Model

A new technique for sound loudness evaluation, the so-called antinoise wavelet pre-processing neural network (ANWT-NN) model, is presented in this paper. Based on passing vehicle noise, the ANWT-NN loudness model combines the techniques of wavelet analysis and neural network regression and classification. A wavelet-based, 21-point model for vehicle noise feature extraction is established. Verification shows that the trained ANWT-NN models are more accurate and effective than the WT-NN models for sound quality evaluation of nonstationary vehicle noises. The newly proposed ANWT-NN model can be applied to both the stationary and nonstationary sound signals and even to the transient ones. The ANWT-NN technique is suggested not only for the prediction, classification, and comparison of the sound quality of passing vehicle noise, but also for applications in other sound-related engineering fields, in place of the conventional psychoacoustical models.

A Comparison of Psychoacoustical Evaluation Methods for Vehicle Engine Noises Based on Wavelet Shrinkage Denoising Technique

2011 ◽  
Vol 219-220 ◽  
pp. 93-97 ◽  
Author(s):  
Yan Song Wang ◽  
Yue Yan ◽  
Zhi Qiu ◽  
Jin Zhang
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Quality Evaluation ◽  
Sound Quality ◽  
Pressure Level ◽  
Signal Denoising ◽  
Subjective Feeling ◽  
Wavelet Shrinkage ◽  
Vehicle Engine ◽  
Shrinkage Method

Based on the measured and denoised vehicle engine noises, the sound quality evaluation (SQE) techniques in common use for A-weighting sound pressure level (SPL) and psychoacoustical parameters, such as loudness, sharpness and roughness, are performed and compared in this paper. The wavelet threshold shrinkage method is adopted for sound signal denoising. The comparisons suggest that the A-weighting SPL is not sufficient and can only be used as a reference in vehicle SQE, the psychoacoustical parameters can provide a complete description and more exactly reflect to the subjective feeling of vehicle noises, should be considered in vehicle designs.

Sound quality evaluation for luxury refrigerator door closing sound

2021 ◽  
Vol 263 (5) ◽  
pp. 1845-1854
Author(s):  
Kanta Imamori ◽  
Atsuya Yoshiga ◽  
Junji Yoshida
Keyword(s):  
Regression Analysis ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Subjective Evaluation ◽  
Low Frequency ◽  
Sound Quality ◽  
Subjective Test ◽  
Two Factors

In this study, we carried out subjective evaluation tests employing 19 refrigerator door closing sounds to quantify the luxury feeling. By applying factor analysis to the subjective evaluation results, the sound quality of the refrigerator door closing sound was found to be expressed by the following two factors: overall loudness and the pitch of the sound. Subsequently, luxury feeling evaluation model was obtained through multiple regression analysis. As the result, the luxury feeling of the door closing sound was evaluated to be high when the sound was softer and had lower pitch. Then, we prepared several luxury door closing sounds according to the obtained evaluation model through a filter processing and conducted subjective evaluation tests again to verify the evaluation model. The result shows that the amplitude increased sound at low frequency band under 100 Hz, which was calculated to be high luxury by the evaluation model, was actually evaluated as the best among the presented sounds through the subjective test. And the luxury sound quality evaluation method was confirmed to be useful to quantify and estimate the sound quality of the refrigerator door closing sound.

Catch a Rising Tone: Selecting a Tone for a New Calling Service

1992 ◽  
Vol 36 (3) ◽  
pp. 227-231 ◽  
Author(s):  
Marc E. Fusco ◽  
Robert B. Katz
Keyword(s):  
High Frequency ◽  
Sound Quality ◽  
To Receive

The tone used in the new service Caller ID on Call Waiting (CIDCW) must be reliably detected by customer premises equipment (CPE), so that it can prepare to receive caller ID data, and it should alert customers to new calls but without being annoying. To help select a tone, the first experiment of this study examined the acceptability of a series of high-frequency dual tones that might be able to perform the required CPE signaling. Subjects were presented with the tones under circumstances in which they would typically be heard (while talking and listening over the telephone) and rated the sound quality of the tones. Long bursts of tones were presented as well as short bursts prepended or appended to the 440-Hz tone used in Call Waiting service. The results suggested that customers may find high-frequency dual tones acceptable. To determine acceptable parameters of tones, in the second experiment, subjects rated the loudness of selected tones as their length and power were varied.

Evaluation of English interpretation teaching quality based on GA optimized RBF neural network

2020 ◽  
pp. 1-8
Author(s):  
Lu Chen ◽  
He Being
Keyword(s):  
Neural Network ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Rbf Neural Network ◽  
Evaluation Model ◽  
Principal Component ◽  
Teaching Quality ◽  
Network Teaching ◽  
Time Performance

Aiming at the problem of low accuracy of the current English interpretation teaching quality evaluation, a teaching quality evaluation method based on a genetic algorithm (GA) optimized RBF neural network is proposed. First, the principal component analysis is used to select the teaching quality evaluation index, and then design The RBF neural network teaching evaluation model is used, and GA is used to optimize the initial weights of the RBF neural network. Experimental results show that this method can effectively evaluate the quality of English interpretation teaching, and has high accuracy and real-time performance.

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