Experimental investigations of psychoacoustic characteristics of household vacuum cleaners
11 Experimental investigations of psychoacoustic characteristics of household vacuum cleaners
Sanjay Kumar (a) , Wong Sze Wing, Teng Mingbang, and Heow Pueh Lee (b)
Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117575, Singapore
Corresponding authorโs email: a) [email protected], b) [email protected]
Abstract
Vacuum cleaners are one of the most widely used household appliances associated with unpleasant noises. Previous studies have indicated the severity of vacuum cleaner noise and its impact on the users nearby. The quantified measurements of the generated noise standalone are not sufficient for the selection or designing of vacuum cleaners. The human perception must also be included for a better assessment of the quality of sound. A hybrid approach known as psychoacoustics, which comprises subjective and objective evaluations of sounds, is widely used in recent times. This paper focuses on the experimental assessment of psychoacoustical matrices for household vacuum cleaners. Three vacuum cleaners with different specifications have been selected as test candidates, and their sound qualities have been analyzed. Besides, the annoyance index has been assessed for these vacuum cleaners. Introduction
In almost every house, several electromechanical home appliances are used, such as fans, hair driers, grinders, juicers, microwave ovens, and vacuum cleaners. Among these, the vacuum cleaner is one of the most frequently used home appliances which generates unpleasant noise during the operations. Many people ignore one crucial aspect, namely the noise level when buying a vacuum cleaner. The noise is mostly emitted from the built-in suction units of the vacuum cleaners, exhaust fan, the airflow, and the surface vibrations during the operation [1]. The suction unit generally consists of a driving electric motor and a centrifugal blower. In some equipment, a vanned diffuser is installed in the hose to achieve high-pressure rise during the operation. A detailed description of noise generation source(s) of typical vacuum cleaners can be found in various publications [2-6]. The sound pressure level of working vacuum cleaners is varied from 65 dB(A) to 90 dB(A). A long-term exposure to excessive levels of noise ( โฅ
80 dBA) can lead to several adverse human health issues such as, stress, fatigue, psychological disorders, hearing loss, high blood pressure, coronary heart disease, sleeping disorder, hypertension, obesity, cognitive impairment in children, and diabetic type I and II, hence making it imperative to reduce the noise levels [7-9]. The risk is typically low for normal usage but extended usage for professional cleaners will be exposed to higher risk. Recently, the European Union released eco-design regulation guidelines related to energy consumptions and noise levels for vacuum cleaners. The maximum motor size and the peak noise level for any vacuum cleaners in operation are limited to 900 W and 80 dB(A), respectively [10, 11]. However, manufacturers have reported their concerns for the full implementation of those directives, because the noise levels are sometimes psychologically misinterpreted by the users as the cleaning capacity of the vacuum cleaners. Symanczyk [12] pointed out the paradox with vacuum cleaner sounds: โ you can make them very silent, but then they will not be perceived as very powerful โ . Some vacuum cleaners which fail to meet EU guidelines are still available in the market for sale [13]. In recent times, the European Union has released strict directives to the vacuum cleaner manufacturers for further reduction in operating noise. Owing to these international regulations, a comprehensive assessment of sound qualities for the commercial vacuum cleaners is necessary. In this regard, several research studies have been reported [14]. Researchers started from the measurement of sound pressure levels of the generated noise and assessed the performance of the equipment as per international regulations ( ๐ฟ๐ด ๐๐ < 80 dBA of the 8-hour daily occupational noise exposure). However, the sound pressure level data stand-alone is not sufficient for any conclusion made for the noise source because human perception towards the surrounding noise is different from the quantified sound levels. The human perception for the sound considers subjective and objective elements and may vary from person-to-person. Apart from the sound intensity of the noise, other subjective parameters like environmental conditions, psychological factors (pleasantness), psychoacoustical parameters (loudness, sharpness, roughness, fluctuation strength, and tonality) need to be incorporated in the sound quality assessments [15-19]. In recent years, several psychoacoustical studies have been reported for household appliances. Ih et al. [20] experimentally investigated the product sound quality of the vacuum cleaner. First, the Taguchi orthogonal array method, an experimental design technique was utilized to assess the frequency range that described the sound quality of the vacuum cleaners. Then, a psychoacoustic model โannoyance indexโ was developed by using linear regression analysis. The developed model was further validated by the artificial intelligence-based technique, artificial neural network (ANN). Takada et al. [21] conducted a psychoacoustic assessment for the economic evaluation of the sound quality index for vacuum cleaners and hair dryers. Conjoint analysis was used to evaluate the buying willingness of these items based on generated noise. It was reported that the personโs purchasing willingness increased for the equipment with the lower values of sound pressure level and sharpness. Rukat et al. [6] investigated the effect of operating conditions on vacuum cleaner noise. They reported that the vacuum cleaner emitted a higher level of noise while working on a flat surface like terracotta as compared to working on the carpet. Their conclusion was based on the measurement of A-weighted sound pressure levels of the tested vacuum cleaners. Moravec et al. [22] developed a sound quality index for automatic washing machine noise. Their psychoacoustic model was based on the correlation between subjective and objective sound quality assessment. Novakovic et al. [23] experimentally validated the previously correlation models proposed by Lipar et al. [16] and Di et al. [24]. Their findings suggested that both models were appropriate for quick assessment of sound quality index. Ma et al. [25] investigated the influence of the dental equipment noise on the perceptions and behaviors of dental professionals. More recently, Murovec et al. [26] conducted psychoacoustic analysis for cavitation detection in centrifugal pumps. These reported works confirm the broad applications of psychoacoustic assessment of noise. In this work, we have performed an experimental assessment on the psychoacoustic characteristics of commercially available household vacuum cleaners. Three dry-type vacuum cleaners from different manufacturers are selected, and their acoustical performances have been investigated. In the study, first, we measured the noise levels generated from the selected vacuum cleaners, and the recorded data is used in the evaluation of psychoacoustic parameters, namely, loudness, sharpness, roughness, and fluctuation strength. Furthermore, the Annoyance index, a psychological attribute of psychoacoustics, has been evaluated for these vacuum cleaners. The annoyance index was based on the previously developed annoyance index equation by Altmsoy et al. [27] for dry type vacuum cleaners. Psychoacoustic parameters
Loudness
Loudness is one of the most important subjective parameters of the psychoacoustic analysis. The loudness is slightly different from the sound amplitude. The sound amplitude is a measured sound intensity in decibel value whereas loudness is the psychological aspects of the measured sound pressure level. The former is quantified by the microphone perceived sound, and the later involves the human perception of the sound. It is interesting to note that the human ear can perceive sounds of different frequencies at different sound pressure levels as equally loud. This is due to the differing sensitivity of the human ear within the hearing domain. In 1933, Fletcher-Munson developed the curves of equal loudness to accurately define perceived loudness across all frequency spectrums within the human hearing domain. The calculation of loudness (L) is made by several approved standards such as ISO532B and DIN 45631 which are also available in various sound processing software. Loudness level is expressed in phons (P) or sones (S). The ๐โ๐๐ is a unit of loudness that represents equal loudness to a 1000Hz pure tone, whereas sones is defined as the loudness perceived by typical listeners when confronted with a 1000 Hz tone at a sound pressure level of 40 phons. The loudness level in sones can be calculated from the relation ๐ = 2 (๐โ40) 10โ .[28]
Sharpness
Sharpness delineates the human sensation caused by high frequency components of the noise. The units of sharpness (SH) is ๐๐๐ข๐ . A narrow band noise at 1 kHz with a bandwidth of < 150 Hz and a sound level of 60 dB is defined as 1 ๐๐๐ข๐ . The variability of sharpness depends upon the specific loudness distribution of the sound. It is calculated as a weighted area of loudness from the relation
๐๐ป = 0.11 โซ ๐ โฒ ๐(๐ง)๐ง๐๐ง
24 ๐ต๐๐๐0 โซ ๐ โฒ ๐๐ง
24 ๐ต๐๐๐0 , where ๐ โฒ is the specific loudness that exhibits the loudness distribution across the critical-bands, ๐(๐ง) ={ 1; ๐๐๐ ๐ < 3๐๐ป๐ง4; ๐๐๐ 3 ๐๐ป๐ง < ๐ < 20 ๐๐ป๐ง is the weighting function, and ๐ง is the critical-band rate defined by Zwicker.[17] Fluctuation Strength and Roughness
When multiple tones are modulated or combined to form a single sound, the sound level rises and falls over time. These sound level fluctuations arise from the constructive and destructive interferences of the tones for different frequency. Examples of such sounds could be the siren from an ambulance or the rumbling of a car engine. The amount of sound modulation determines the sensation that is perceived by the human ear. This sensation can be modeled by two analytical parameters, namely, fluctuation strength and roughness [14]. These psychoacoustic matrices quantify the amount of sound modulation based on the following aspects: modulation frequency โ the number of rises and falls in the sound per sound, and modulation Level โ the perceived magnitude level change over time. The fluctuation Strength describes with 20 modulations per second or less (between 0.5 and 20 Hz), and the roughness is perceived as the sensation of rapidly modulated sound or vibration in the modulation range between 20 and 300 times per second (20 โ
300 Hz). In terms of the human hearing domain, the ear can pick up modulations below 20 Hz, and anything beyond it, perceived as a stationary and rough tone. These two metrics can invoke individual sensory perceptions. For instance, a tone with high fluctuation strength is regarded as an alert (fire alarms, sirens) while high roughness has been used in automotive industries to accentuate the sportiness of the vehicle. The units to describe fluctuation strength (F) and roughness (R) is ๐ฃ๐๐๐๐ and ๐๐ ๐๐๐ , respectively. 1 ๐ฃ๐๐๐๐ is defined as a tone with sound pressure level of 60 dB at 1 kHz modulated by 100 % at modulation frequency of 4 Hz. While, 1 ๐๐ ๐๐๐ represents the roughness produced by a pure tone at 1000 Hz and with SPL of 60 dB which is modulated by 100 % modulation depth and modulation frequency ( ๐ ๐๐๐ ) of 70 Hz. The roughness of sound can be estimated from the equation, ๐ = ๐๐๐ ร โซ ๐ ๐๐๐ โ๐ฟ ๐๐ง
24 ๐ต๐๐๐0 , and the fluctuation strength is determined from the equation,
๐น = ๐๐๐ โ๐ฟ ๐๐ง
24 ๐ต๐๐๐0 ( ๐๐๐๐4 ๐ป๐ง )+( ) , where โ๐ฟ is the perceived masking depth, ๐๐๐ is the calibration factor [17]. Annoyance Index
The annoyance index is one of the most important attributes for the psychoacoustical assessment. It describes the human sentiments towards the incoming sound waves. In the annoyance index analysis, the combination of the psychological parameters and the psychoacoustical matrices are included. The physical parameters can be collected through jury testing in which data are collected from the persons directly. In the process, the recorded sound generated from appliances such as vacuum cleaners are played for a short period in front of listeners, and some psychological questions are asked, and their responses are rated on a point scale. The results of the subjective judgments are used to generate a value of perceived annoyance factor for each vacuum cleaner. The collected data are then correlated using regression analysis with the psychoacoustic parameters measured from the same vacuum cleaners. The study gives rise to an Annoyance index (AI), which can be used to determine the sound quality of equipment. Altmsoy et al. [27] developed a general annoyance index equation for assessment of the sound qualities of vacuum cleaners. The annoyance index (AI) for a vacuum cleaner can be expressed as a linear combination of psychoacoustics metrics,
๐ด๐ผ = 0.1(๐ฟ + ๐๐ป + 15๐ + 5๐น) , where ๐ฟ is loudness, ๐๐ป is sharpness, ๐ is roughness, and ๐น is fluctuation strength [27]. Experimental design and methods
Test Environment
The experiment was carried out in a room of the Vibration/Dynamics Laboratory located in the National University of Singapore. The room was 5.9 m x 8.3 m in size with 2 doors and several cabinets surrounding 3 sides of the walls. There were 4 tables in the room and various equipment was placed onto them.
Figure 1 (a) shows the floor plan and the photo of the test room. The room was selected to perform the experiment since it had similar size and obstructions to a living room, which was a common operating environment for a vacuum cleaner.
Figure 1. (a)
Schematics of experimental setup plan. (b)
Photographs of the three different vacuum cleaners. LG V-CP243NB (model type 1), Dyson Cyclone V10 (model type 2), and Xiaomi Cleanfly Gen2 (model type 3). (c)
Photographs of the testing room displaying the vacuum cleaner positions.
Test appliances
Three different makers of dry-type vacuum cleaners were selected for the psychoacoustic studies. The manufacturers launched the selected vacuum cleaners in three different periods. The LG V-CP243NB is the oldest model, while the Dyson Cyclone V10 and Xiaomi models are recently launched.
Figure 1 (b) shows photographs of the selected models. LG V-CP243NB is a traditional vacuum cleaner that includes a suction unit on the sled and a flexible hose for transporting the dust. The power consumption is 1400 W with a single power setting. Dyson Cyclone V10 is an upright vacuum cleaner that is well known for its fourteen patented concentric cyclones feature to allow efficient and accelerated airflows for capturing the microscopic particles as small as 0.3 microns. Their digital motor consumes 525 W to generate 125,000 rpm motor speed for 151 air watts suction power. It comes with three power settings to suit different tasks, and the running time is up to 60 mins. The overall weight of the device is 2.5kg. Xiaomi Cleanfly Gen 2 is a portable wireless handheld vacuum cleaner. It consists of a brushless DC motor with a maximum rotation speed of 100,000 rpm with a total power consumption of 120W. Xiaomi Cleanfly comes with two-speed settings for different applications. It is capable of developing a maximum suction pressure of 16.8 kPa and comes with a compact design with an overall weight of 560g. The product specifications of these three vacuum cleaners are listed in
Table 1 . Table 1.
Product specifications of the used vacuum cleaners.
Specifications
LG V-CP243NB
Dyson Cyclone V10
Xiaomi Cleanfly Gen2
Annotation used Model type 1 Model type 2 Model type 3 Power rating (Watt) 1400 525 120 Suction pressure N.A.* 151 air Watt 16.8 kPa Motor speed (R.P.M.) N.A.* 1,25,000 1,00,000 Overall weight (kg) 3.5 2.5 0.56 *N.A. = Not available.
Test equipment and signal processing
The ambient and vacuum cleaner noise was recorded by a handheld data acquisition system (The Simcenter SCADAS XS-Siemensยฎ) [29]. It is capable of acquiring dynamic data simultaneously at 50,000 samples per second on up to 12 dynamic channels. The portable hardware was connected with a binaural headset and a central microphone. This headset is equipped with two microphones positioned at both ears to make binaural recordings.
A ยผโ pressure field central microphone (PCB) was also connected with the data acquisition system. The data recorded from the binaural headset reflected the noise influence to the vacuum cleaner user whilst the regular microphone was used to capture the noise effect from the vacuum cleaner to the surrounding occupants. The SCADAS system was remotely controlled by the Simcenter Testlab Scope App software installed on an Android-based Samsung tablet. The recorded data was post-processed in the LMS test lab software (Siemensยฎ), and several psychoacoustic parametric values were extracted.
Noise measurement methods
For noise measurements of the vacuum cleaners, the walking test was preferred over the static test. Because, in the walking test methods, suction noise, and the noise generated from the interaction between the vacuum cleaner and the floor, are both considered. While in the static test, only suction noise is measured. In the test procedure, SCADAS XS and a central microphone were placed on the table (
Figure 1 a). The central microphone was used to investigate the noise annoyance towards the surrounding occupants. Also, a set of binaural headphones was placed on the test personnelโs shoulder for recreation of the sound disturbance perceived by the user. The central microphone was kept at a distance of 1 m away from the walkway, and the walking distance was limited to 3 m as well. The microphones were calibrated by using a standard sound calibrator. The test personnel operated the vacuum cleaners while walking for a linear distance of 3 m, and the generated noise was recorded. Prior to this, background noise was first recorded in the same experimental condition, and the results were used for comparison with the acoustic characteristics for a vacuum cleaner noise.
Table 2 enlists the annotations used to represent the microphones and motor speed settings. For equivalent sound pressure level calculations, 32 readings of sound pressure level (SPL) were recorded at an interval of 30 seconds in a period of 10 minutes, and their minimum and maximum SPL were extracted. From these data, the equivalent noise level calculated by using the following expressions, ๐ฟ๐ด ๐๐ = 10 log (โ ๐ผ๐ร10ร๐ฟ10๐๐=1 ) , where ๐ is the number of observations, ๐ผ is the fraction of time for which SPL persists, ๐ is the time interval, ๐ฟ is the sound intensity. In this study, we have taken ๐ผ = 0.9 for calculation of equivalent sound pressure levels. Table 2.
Annotations used in the study.
Annotations Descriptions
C1 Centre Microphone C2 Right Ear Microphone (from the headphones) C3 Left Ear Microphone (from the headphones) S1 Minimum motor speed setting of vacuum cleaners S2 Maximum motor speed setting of vacuum cleaners Results and discussion
Acoustical performances
Figure 2 (a-c) depicts the measured A-weighted sound levels spectra (one-third octave) for the three different vacuum cleaners; model type 1, model type 2, and model type 3, respectively. All measurements were performed at the same venue, under similar environmental conditions, and by the same person. Each experiment has repeated ten times, and their average values have considered in the study. As shown in
Figure 2 (a), the noise level of the model type 1 vacuum cleaner is maximum in the mid-range frequencies (500-2000 Hz). The Equivalent pressure level ๐ฟ๐ด ๐๐ for C1, C2, and C3 are 77.4 dBA, 90.4 dBA, and 80.6 dBA, respectively. In the case of model type 2, the maximum noise level is observed in the mid-frequency range at both speed settings. Also, the equivalent pressure level is measured to be 69.8 dBA, 86.2 dBA, and 70.7 dBA for C1, C2, and C3 in the minimum setting while the ๐ฟ๐ด ๐๐ is 75.4 dBA, 94.8 dBA and 76.3 dBA for C1, C2, and C3 in the maximum setting. Figure 2 (c) shows the sound pressure level spectrum obtained from the model type 3 vacuum cleaner. It is observed that the maximum sound level values lie in mid-range frequencies in both speed settings S1 and S2. The ๐ฟ๐ด ๐๐ is 64.1 dBA, 79.6 dBA, and 70.4 dBA for C1, C2, and C3 in the minimum setting while the ๐ฟ๐ด ๐๐ is 71.2 dBA, 90.0 dBA, and 79.2 dBA for C1, C2 and C3 in the maximum setting. Figure 2.
Sound pressure level spectra of three different vacuum cleaners (a) Model type 1, (b) Model type 2, (c) Model type 3. All data are plotted on log2 scale. The equivalent sound pressure levels presented in the figure is LA eq(90) . Psychoacoustic performance
Figure 3 to Figure 5 shows the results of psychoacoustic metrics (loudness, sharpness, fluctuation strength, and roughness) obtained from the recorded sound levels of vacuum cleaner units. As shown in
Figure 3 (a), the maximum perceived sound intensity is at the user โs right ear and is about 109 sone as it is nearest to the vacuum cleaner (model type 1). Moreover, t he userโs left ear C3 experiences slightly higher loudness than the surrounding occupants C1. Also, C1 has larger sharpness values than C2 and C3, implying the sharpness is the highest for the surrounding occupants (
Figure 3 b). In
Figure 3 (c), the u serโs right ear (C2) encounters the highest roughness value, in the modulation frequency of 30-300 Hz. Furthermore, the fluctuation strengths captured are nearly identical in all microphones. The model type 2 surprisingly revealed a maximum loudness value of 118 sones to the userโs right ear at the maximum speed setting S2, and a second highest perceived sound intensity was observed to the userโs right ear but in minimum rotation speed setting S1 (
Figure 4 a). The other two microphones C1 and C3, have a slight variation in their loudness values in both speed settings. Furthermore, as shown in
Figure 4 (b), at lower speed setting S1, the sharpness value for C3 microphone was lowest over the period, while for the right ear microphone C2, the sharpness value was higher than that for C1 except for few values. A
128 256 512 1024 2048 4096 8192 1638420406080100 S ound P r e ss u r e Le v e l ( d B ( A )) Frequency (Hz)
C1: LA eq = 77.4 dBA C2: LA eq = 90.4 dBA C3: LA eq = 80.6 dBA Model Type 1
128 256 512 1024 2048 4096 8192 1638420406080100 S ound P r e ss u r e Le v e l ( d B ( A )) Frequency (Hz)
C1 S1: LA eq = 69.8 dBA C2 S1: LA eq = 86.2 dBA C3 S1: LA eq = 70.7 dBA C1 S2: LA eq = 75.4 dBA C2 S2: LA eq = 94.8 dBA C3 S2: LA eq = 76.3 dBA (a)(c) (b) Model Type 2
128 256 512 1024 2048 4096 8192 1638420406080100 S ound P r e ss u r e Le v e l ( d B ( A )) Frequency (Hz)
C1 S1: LA eq = 64.1 dBA C2 S1: LA eq = 79.6 dBA C3 S1: LA eq = 70.4 dBA C1 S2: LA eq = 71.2 dBA C2 S2: LA eq = 90.0 dBA C3 S2: LA eq = 79.2 dBA Model Type 3 similar trend was observed at higher speed setting S2. Since the user had kept the vacuum cleaners on the right hand during the operation, that may be attributed to the lower sharpness value for the left ear โs C3 microphone. Also, there was no statistically significant difference in roughness values between each configuration (
Figure 4 c).
The userโs right ear microphone attained the slightly higher roughness value of recorded sound at both speed settings. Since the roughness varies with time, it may be possible that the variation with time had a more significant effect than the difference in motor speed and recording position (listening position) compared to other psychoacoustic parameters. Similarly, as shown in
Figure 4 (d), the fluctuation strength values were not significantly dependent on the microphone positions. However, some variations in measured values were observed with the time. Their difference in fluctuation strength was within 0.25 vacil. For the third vacuum cleaner systems (model type 3), the highest loudness value of 78 sones is recorded in C2 for both speed settings (
Figure 5 a). It can be observed that the sound intensity perceived by the userโs right ear
C2 is higher than by the left ear C3 and surrounding occupants C1 regardless of the equipment types and speed settings. For sharpness values, the occupantโs microphone C1 was perceived to be the highest among all microphones at each setting (
Figure 5 b). While for the right and left earโs microphones, the sharpness values were not significantly different. However, some significant peaks could be observed at several time periods. Similar to the model type 2 vacuum cleaners, the roughness (
Figure 5 c) and fluctuation strength (
Figure 5 d) were dependent on the operation time for the model type 3 system. These parameters didnโt not deviate much between different locations and different speeds, indicating they have close amplitude variations. 0
Figure 3.
Psychoacoustic parametric values for the vacuum cleaner (model type 1). (a) loudness, (b) sharpness, (c) roughness, and (d) fluctuation strength. S one Time (s) C1 C2 C3
Loudness A c u m Time (s) C1 C2 C3
Sharpness
Model Type 1 A s pe r Time (s) C1 C2 C3
Roughness Fluctuation strength (a) (b)(c) (d) V a c il Time (s) C1 C2 C3 Figure 4.
Psychoacoustic parametric values for the vacuum cleaner (model type 2). (a) loudness, (b) sharpness, (c) roughness, and (d) fluctuation strength. S one Time (s)
C1 S1 C2 S1 C3 S1 C1 S2 C2 S2 C3 S2
Loudness (a) (b)(d)(c)
Model Type 2 A c u m Time (s)
C1 S1 C2 S1 C3 S1 C1 S2 C2 S2 C3 S2
Sharpness A s pe r Time (s)
C1 S1 C2 S1 C3 S1 C1 S2 C2 S2 C3 S2
Roughness V a c il Time (s)
C1 S1 C2 S1 C3 S1 C1 S2 C2 S2 C3 S2
Fluctuation strength Figure 5.
Psychoacoustic parametric values for the vacuum cleaner (model type 3). (a) loudness, (b) sharpness, (c) roughness, and (d) fluctuation strength.
Comparative analysis
Figure 6 presents the comparative results of psychoacoustics parameters for three vacuum cleaners. As shown in
Figure 6 (a), model type 1 produces the highest loudness to the surrounding occupants C1, followed by model type 2 and model type 3 at the maximum and the minimum settings. Besides, the loudness captured at right ear mic C2 is higher than the left ear mic C3. Because the vacuum cleaner was hold on right hand of the user (
Figure 1 a) , and the personโs body may cause the obstruction into the sound wave path to reach the left ear. The most substantial loudness impact towards the right ear of the user has resulted from model type 2 at the maximum setting (C2S2). Figure 6 (b) shows the average sharpness values perceived by surrounding occupants as well as the userโs ears. As shown, the average sharpness values perceived by surrounding occupants C1 in the case of model type 1 system was the lowest and model type 2 and model type 3 produced higher sharpness. Moreover, contrary to loudness, the sharpness measurements did not show a clear differentiation between the left and right ears. The average sharpness values measured by C2 and C3 for model type 1 and model type 3 vacuum cleaners at both settings were approximately the same. However, the average S one Time (s)
C1 S1 C2 S1 C3 S1 C1 S2 C2 S2 C3 S2
Loudness Fluctuation strengthSharpnessRoughness (a) (b)(c) (d)
Model Type 3 A c u m Time (s)
C1 S1 C2 S1 C3 S1 C1 S2 C2 S2 C3 S20 2 4 6 8 10 12 140.080.100.120.140.160.180.200.220.240.260.280.300.320.34 A s pe r Time (s)
C1 S1 C2 S1 C3 S1 C1 S2 C2 S2 C3 S2 0 2 4 6 8 10 12 140.40.60.81.01.2 V a c il Time (s)
C1 S1 C2 S1 C3 S1 C1 S2 C2 S2 C3 S2
3 sharpness value in C2 for the model type 2 vacuum cleaner (C2S2) was more significant than that of C3. Right ears received the highest sharpness values for model type 2 vacuum cleaner at both settings.
Figure 6 (c) shows the average roughness values obtained from the different vacuum cleaners. As shown, roughness values for the model type 3 were almost constant despite different settings across different microphones. The model type 2, however, has shown larger roughness values when operating at the minimum settings across all microphones. Overall, model type 2, at the minimum setting, has the highest roughness values (C1S1 and C2S1). The observations across the left and right ears remained similar across all three devices where the right ear registered the larger roughness values. The fluctuation strength of the vacuum cleaners exhibited small variations across each microphone (
Figure 6 d). The values range from 0.9 to 1.1 vacil for all microphones.
Figure 6.
Comparative psychoacoustic parametric values for different vacuum cleaners with corresponding standard deviations. (a) loudness (b) sharpness (c) roughness, and (d) fluctuation strength.
Model type 1 (C1) Model type 2 (C1S1) Model type 2 (C1S2) Model type 3 (C1S1) Model type 3 (C1S2)16202428323640444852 S one Modeltype 1(C2) Modeltype 2(C2S1) Modeltype 2(C2S2) Modeltype 3(C2S1) Modeltype 3(C2S2) Modeltype 1(C3) Modeltype 2(C3S1) Modeltype 2(C3S2) Modeltype 3(C3S1) Modeltype 3(C3S2)20406080100120 S one Model type 1 (C1) Model type 2 (C1S1) Model type 2 (C1S2) Model type 3 (C1S1) Model type 3 (C1S2)1.92.02.12.22.32.42.52.6 A c u m Modeltype 1(C2) Modeltype 2(C2S1) Modeltype 2(C2S2) Modeltype 3(C2S1) Modeltype 3(C2S2) Modeltype 1(C3) Modeltype 2(C3S1) Modeltype 2(C3S2) Modeltype 3(C3S1) Modeltype 3(C3S2)1.82.02.22.42.6 A c u m Model type 1 (C1) Model type 2 (C1S1) Model type 2 (C1S2) Model type 3 (C1S1) Model type 3 (C1S2)0.050.100.150.200.250.300.350.400.450.50 A s pe r Modeltype 1(C2) Modeltype 2(C2S1) Modeltype 2(C2S2) Modeltype 3(C2S1) Modeltype 3(C2S2) Modeltype 1(C3) Modeltype 2(C3S1) Modeltype 2(C3S2) Modeltype 3(C3S1) Modeltype 3(C3S2)0.00.10.20.30.40.50.60.70.8 A s pe r P (6)
Model type 1 (C1) Model type 2 (C1S1) Model type 2 (C1S2) Model type 3 (C1S1) Model type 3 (C1S2)0.70.80.91.01.11.21.31.41.5 V a c il Modeltype 1(C2) Modeltype 2(C2S1) Modeltype 2(C2S2) Modeltype 3(C2S1) Modeltype 3(C2S2) Modeltype 1(C3) Modeltype 2(C3S1) Modeltype 2(C3S2) Modeltype 3(C3S1) Modeltype 3(C3S2)0.60.70.80.91.01.11.21.31.41.5 V a c il (a)(b)(c)(d) Annoyance Index analysis
As described in the aforementioned section 2.4, the relative annoyance index (AI) score for the central, left, and the right microphones are calculated by using the relation proposed by Altmsoy et al. [27]. The central microphone C1 is analogous to individuals present nearby. The C2 and C3 mics are the sensory perceptions of the vacuum noise comparable to the right and left ears of the user.
Figure 7 shows the calculated annoyance index for the recorded sound perceived from these microphones. As shown in
Figure 7 (a), the AI index was found to be highest in the central microphone for the model type 1 system followed by the model type 3. Also, no significant difference in AI index was found for model type 2. The annoyance index for other microphones for three vacuum cleaners are shown in
Figure 7 (b), model type 2 vacuum cleaners have registered the highest annoyance at its high-speed settings (C2S2). It was expected as vacuum cleaner operated at higher speed settings produced noise with a high sound level. Moreover, the right ear side microphone showed higher annoyance than the left ear microphone for each vacuum cleaner. The possible reason for this trend might be the experimental conditions. During the vacuum cleaning operation, the device was held consistently on the right hand. Hence the right ear was in closer vicinity to the device. As such, this could be the reason for a higher annoyance index values in the right ear. The left and right ear may not perceive the similar quality of sound, and other factors such as the distance of the sound source from each ear can influence the evaluated level of annoyance.
Figure 7.
Annoyance index for (a) center mic C1, and (b) right mic C2 and left mic C3 for different types of vacuum cleaners. The minimum and maximum motor speed settings are represented by S1 and S2, respectively.
Type 1 (C1) Type 2 (C1S1) Type 2 (C1S2) Type 3 (C1S1) Type 3 (C1S2)
Type 1(C3) Type 1(C2) Type 2(C3S1) Type 2(C2S1) Type 2(C3S2) Type 2(C2S2) Type 3(C3S1) Type 3(C2S1) Type 3(C3S2) Type 3(C2S2) Conclusions
The presented experimental investigations provide exciting information related to the sound quality index of vacuum cleaners (LG V-CP243NB (model type 1), Dyson Cyclone V10 (model type 2), and Xiaomi Cleanfly Gen 2 (model type 3)). A series of the experiment is carried out to measure the noise produced by each vacuum cleaner. Binaural headphones and a condense microphone are used to emulate the psychoacoustic effect towards the user and the surrounding occupants. Annoyance level index is determined for each vacuum cleaner by using the subjective and objective factors. The analysis of the annoyance level index would result in a better understanding of the human perception of the emitted noise. Moreover, based on the estimated values, the following observations are made. It is observed that the loudness produced by the device has a more significant effect on its annoyance level, which complies with the previously published works. At the same time, it is also noted that the level of annoyance perceived by the user of the device can be different from those that are within proximity of to the appliance. From the psychoacoustic analysis, the annoyance index of model type 2 at the maximum speed setting is the highest, while the annoyance index of model type 1 is the largest to the surrounding people. The presented investigations may add a valuable contribution to the assessment of vacuum cleaner noise and may help in the development of a better appliance with the permissible noise level. The studies could be extended to different models of vacuum cleaners and also wet type vacuum cleaners.
Author contributions
All authors have made valuable contributions to the presented work. S.K. has written the manuscript and helped in experimental planning. W.S.W. and T.M. have conducted the experiments and performed psychoacoustic analysis. H.P.L. conceived the idea and monitored the overall project at every stage.
References [1] E. Altmsoy, H. Erol, An experimental study on vibro-acoustic characteristics of a wet and dry type vacuum cleaner, in: Seventh international congress on sound and vibration, Citeseer, 2000, pp. 667-674. [2] M. ฤudina, J. Prezelj, Noise generation by vacuum c leaner suction units: Part I. Noise generating mechanisms โ An overview, ApAc., 68 (2007) 491-502. [3] M. ฤudina, J. Prezelj, Noise generation by vacuum cleaner suction units: Part II. Effect of vaned diffuser on noise characteristics, ApAc., 68 (2007) 503-520. [4] M. ฤudina, J. Prezelj, Noise generation by vacuum cleaner suction units. Part III. Contribution of structure-borne noise to total sound pressure level, ApAc., 68 (2007) 521-537. [5] M. ฤudina, J. Prezelj, Noise generation by vacuum cleaner suction units, Noise & Vibration Worldwide, 39 (2008) 12-27. [6] W. Rukat, B. Jakubek, A. Madej, The noise emitted by a vacuum cleaner treated as a device with extensive sound sources, Vibrations in Physical Systems, 29 (2018). [7] K. Jensen, N.E. Hahn, R. Palme, K. Saxton, D.D. Francis, Vacuum-cleaner noise and acute stress responses in female C57BL/6 mice (Mus musculus), Journal of the American Association for Laboratory Animal Science, 49 (2010) 300-306. 6 [8] A. Seidler, J. Hegewald, A.L. Seidler, M. Schubert, M. Wagner, P. Drรถge, E. Haufe, J. Schmitt, E. Swart, H. Zeeb, Association between aircraft, road and railway traffic noise and depression in a large case-control study based on secondary data, Environmental research, 152 (2017) 263-271. [9] S. Kumar, H.P. Lee, The Present and Future Role of Acoustic Metamaterials for Architectural and Urban Noise Mitigations, Acoustics, 3 (2019) 590-607. [10] C.D.R. (EU), Ecodesign Requirements for Vacuum Cleaners, in: C.D.R. (EU) (Ed.) 518/2014, 2014. [11] M. Knight, Noisy vacuum cleaners flout EU rules, in, Which?, UK, 2018. [12] A. Symanczyk, The Sound of Stuff โ Archetypical Sound in Product Sound Design, Journal of Sonic Studies, 10 (2015). [13] Will, Vacuum Cleaners Are Failing To Meet New EU Regulations, in, TopTenVacuums, UK, 2018. [14] H. Fastl, The psychoacoustics of sound-quality evaluation, Acta Acust. united Ac., 83 (1997) 754-764. [15] R. Jurc, O. Jiลรญฤek, M. Brothรกnek, Methods for the assessment of pleasantness in sound quality,
Noise Control Engineering Journal, 58 (2010) 62-66. [16] P. Lipar, J. Prezelj, P. Steblaj, J. Rejec, M. Cudina, Psychoacoustic approach used for developing the model of sound pleasantness of vacuum cleaners and suction units based on objective and subjective analysis, in: 5th Congress of Alps-Adria Acoustics Association, 2012. [17] E. Zwicker, H. Fastl, Psychoacoustics: Facts and models, Springer Science & Business Media, 2013. [18] S. Atamer, M.E. Altinsoy, Effect of tonality in loudness perception: Vacuum cleaner and shaver examples, Acoustical Science and Technology, 41 (2020) 369-372. [19] J. Kunio, Using sound quality to improve your product, in: International Appliance Technical Conference & Exhibition, Brรผel & Kjรฆr, 2006. [20] J.-G. Ih, D.-H. Lim, S.-H. Shin, Y. Park, Experimental design and assessment of product sound quality: application to a vacuum cleaner, Noise control engineering journal, 51 (2003) 244-252. [21] M. Takada, S. Arase, K. Tanaka, S.-i. Iwamiya, Economic valuation of the sound quality of noise emitted from vacuum cleaners and hairdryers by conjoint analysis, Noise Control Engineering Journal, 57 (2009) 263-278. [22] M. Moravec, G. Iลพarรญkovรก, P. Liptai, M. Badida, A. Badidovรก, Development of psychoacoustic model based on the correlation of the subjective and objective sound quality assessment of automatic washing machines, ApAc., 140 (2018) 178-182. [23] T. Novakoviฤ, M. Ogris, J. Prezelj, Validating impeller geometry optimization for sound quality based on psychoacoustics metrics, ApAc., 157 (2020) 107013. [24] G. Di, An improved psychoacoustic annoyance model based on tonal noises, in: INTER-NOISE and NOISE-CON Congress and Conference Proceedings, Institute of Noise Control Engineering, 2016, pp. 540-549. [25] K.W. Ma, C.M. Mak, H.M. Wong, The perceptual and behavioral influence on dental professionals from the noise in their workplace, ApAc., 161 (2020) 107164. [26] J. Murovec, L. ฤuroviฤ, T. Novakoviฤ, J. Prezelj, Psychoacoustic approach for cavitation detection in centrifugal pumps, ApAc., 165 (2020) 107323. [27] E. Altmsoy, G. Kanca, H. Belek, A Comparative on the Study Sound Quality of Wet-And-Dry Type Vacuum Cleaners, in: Sixth international congress on sound and vibration, Copenhagen, Denmark, 1999, pp. 3079-3086. [28] H.F. Olson, The measurement of loudness, Audio Magazine, 56 (1972) 18-22. [29] Simcenter SCADAS XS: Everything you need to know!, in: S.D.I.S. Inc. (Ed.), Siemens Digital Industry Software Inc., 2019.centrifugal pumps, ApAc., 165 (2020) 107323. [27] E. Altmsoy, G. Kanca, H. Belek, A Comparative on the Study Sound Quality of Wet-And-Dry Type Vacuum Cleaners, in: Sixth international congress on sound and vibration, Copenhagen, Denmark, 1999, pp. 3079-3086. [28] H.F. Olson, The measurement of loudness, Audio Magazine, 56 (1972) 18-22. [29] Simcenter SCADAS XS: Everything you need to know!, in: S.D.I.S. Inc. (Ed.), Siemens Digital Industry Software Inc., 2019.