ISO/PAS 20065:2016 音響学 — 騒音中の音の可聴性を評価するための客観的な方法 — 工学的方法 | ページ 5

3.1

tonality

presence of a tone in a noise, the level of which is below that of the remaining noise components in the critical band (3.5) about the tone frequency (3.2) by less than the value of the masking index (3.16) , a_v

3.2

tone frequency

f_T

frequency of the spectral line (3.23) (or mid-band frequency of the narrow-band filter), to the level of which the tone contributes most strongly

3.3

tone level

L_T

energy summation of the narrow-band level (3.22) with the tone frequency (3.2) , f_T, and the lateral lines about f_T, assignable to this tone

Note 1 to entry: If the critical band (3.5) for the frequency, f_T, under consideration contains a number of tones, then the tone level, L_T, is the energy sum of these tones. This level, L_T, is then assigned to the frequency of the participating tone that has the maximal value of audibility (3.4) , ΔL.

Note 2 to entry: The method for the determination of the tone level, L_T, of a tone in a critical band is described in 5.3.3.

3.4

audibility

ΔL

difference between the tone level (3.3) , L_T, and the masking threshold (3.15) ,

Note 1 to entry: The method for the determination of the decisive audibility (3.24) , ΔL_j , of a narrow-band spectrum (3.12) is described in 5.3.8.

3.5

critical band

frequency band with a bandwidth (3.17) , ∆f_c, within which the auditory system integrates the sound intensity in the formation of loudness and within which it integrates the sound intensity in the formation of the masking threshold (3.15)

Note 1 to entry: This characteristic of a critical band (see also References [3] and [4]) holds only for a restricted sound level range. This dependence is neglected here.

3.6

mean narrow-band level of the critical band

L_S

energy mean value of all narrow-band levels (3.22) in a critical band (3.5) that (as a rule) does not exceed this mean value by more than 6 dB

Note 1 to entry: The method for the determination of the mean narrow-band level L_S of the masking noise is described in 5.3.2 and Annex D (iterative method).

3.7

critical band level

L_G

level of noise that is assigned to the critical band (3.5) that describes the masking characteristic of the noise for one or more tones of the noise in this critical band

Note 1 to entry: See narrow-band level (3.22) and Annex C for masking.

Note 2 to entry: For the definition formula for L_G, see Formula (12).

3.8

sampling frequency

f_S

number of samples taken per second

Note 1 to entry: The analogue data provided continuously are converted into samples through sampling at discrete time intervals for digital processing.

Note 2 to entry: To ensure the reproducibility of a digitized signal, the Shannon theorem requires that the sampling frequency, f_S, is at least 2 times the highest frequency of the signal components used for evaluation in the time signal [f_S ≥ 2 f_N , see also aliasing (3.9) , antialiasing filter (3.10) and useable frequency (3.20) ]. The algorithm of a Fast Fourier Transform analysis (the variant of a discrete Fourier Transform used typically and optimized for calculation) only permits block lengths (3.11) , N, that correspond to a power of two. FFT analyzers thus need a sampling frequency that is at least 2,56 times the maximum frequency to be analysed.

3.9

aliasing

reflection in the line spectrum (3.12) of frequency components from the range above the sampling frequency (3.8) divided by two (f_S/2) in the range below f_S/2

Note 1 to entry: Antialiasing filters (3.10) are used to avoid errors through such reflections.

Note 2 to entry: Half the sampling frequency (f_S/2) is also known as the Nyquist frequency.

3.10

antialiasing filter

low-pass filter

ideal filter that allow frequencies below half the sampling frequency (3.8) to pass through completely (without influencing the signal), but completely block all higher frequencies

Note 1 to entry: To prevent aliasing (3.9) , the noise under investigation shall be filtered using an antialiasing filter before analogue-to-digital conversion.

Note 2 to entry: Real aliasing filters have a final damping (generally 120 dB/octave) within the blocking range, i.e. signal components in this transition range are reflected (damped). For example, in the transformation of 2 048 (2 k) data points, 1 024 frequency lines are calculated and 800 lines shown. A component in the line number 1 248 is folded back into the line number 800. With a low-pass filter of 120 dB/octave the damping of these components is approximately 75 dB.

Note 3 to entry: The usual commercial FFT analyzers have an antialiasing filter, the limit frequency of which can be switched automatically with the selectable sampling frequency. The reflection of simulated narrow-band levels (3.22) is suppressed.

3.11

block length

N

block of sampling values that in discrete form represents a time-limited range of the time signal to be analysed

Note 1 to entry: In contrast to frequency analysis with analogue and digital filters, the noise with the Fast Fourier Transform is processed in data blocks. In general, these blocks embrace only a part of the noise recording. The block length, N, expresses the number of data points processed at the same time. Due to the nature of the Fast Fourier Transform, the value of N has the integer of power of 2. It has a value, for example, of N = 2¹⁰ = 1 024 data points.

3.12

line spectrum

narrow-band spectrum

frequency spectrum

plot of the sound pressure level (narrow-band level) (3.22) as a function of the frequency in frequency bands of constant bandwidth (3.17) (line spacing, ∆f) (3.13)

Note 1 to entry: A-weighting of the level is assumed in this Publicly Available Specification.

Note 2 to entry: Frequency analysis delivers a line spectrum, in which each line represents the output of a filter, the mid-frequency of which corresponds to the frequency of the spectral line (3.23) .

3.13

line spacing

frequency resolution

Note 1 to entry: In this Publicly Available Specification, the line spacing is 1,9 Hz ≤ Δf ≤ 4,0 Hz.

3.14

time window

time data set of the signal segment (block length) (3.11) that is multiplied by a weighting function (window function)

Note 1 to entry: In accordance with the definition of the Fourier integral, a prerequisite of the FFT analysis is that the time data set is periodic. If this is not the case (as with stochastic signals), cut-off effects at the edges of the time window will lead to distortion of the spectrum. These distortions are avoided through weighting functions such as the Hanning Function.

Note 2 to entry: For more information on window and weighting functions, see, for example, Reference [5] and Annex A.

3.15

masking threshold

audibility (3.4) threshold for a specific sound in the presence of a masking sound (masker)

Note 1 to entry: See Annex C for more information on the audibility threshold and the masking noise.

3.16

masking index

a_v

difference between the masking threshold (3.15) , , and the critical band level (3.7) , L_G, of the masking noise

Note 1 to entry: For frequency-dependent masking index, a_v, masking and masking noise, see Annex C.

3.17

bandwidth

frequency bandwidth

frequency range of a number of neighbouring spectral lines (3.23)

Note 1 to entry: If the width of a frequency band is calculated for which its beginning or end does not correspond to the boundary between two spectral lines, then only the spectral lines that lie in their full width within the calculated frequency range are assigned to the frequency band.

3.18

distinctness

clarity

ratio of the conspicuousness of a tone based on a bandpass noise to the conspicuousness of a sinusoidal tone of the same tone frequency (3.2) , f_T, and same tone level (3.3) , L_T

3.19

edge steepness

ratio of the level difference between the maximum narrow-band level (3.22) of a tone, L_Tmax, and the narrow-band levels of the first line below/above the tone to the corresponding frequency difference

3.20

useable frequency

f_N

upper limit frequency of the signal components used for evaluation

3.21

investigation range

range within which tones are investigated in the line spectrum (3.12)

3.22

narrow-band level

averaged level within a spectral line (3.23)

3.23

spectral line

frequency band of bandwidth (3.17) , ∆f (line spacing) (3.13), in a line spectrum (3.12)

3.24

decisive audibility

ΔL_j

maximum audibility (3.4) , ∆L, in the individual spectrum, j