JP2016045129A - Frequency characteristic prediction calculation device and frequency characteristic prediction calculation program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a frequency characteristic prediction calculation device and a frequency characteristic prediction calculation program applying an acoustical theoretical analysis to a mobile body passage time pressure fluctuation and capable of correctly predicting a frequency characteristic of the mobile body passage time pressure fluctuation.SOLUTION: A low frequency sound separation part separates a low frequency sound p occurred when a train 1 passes through a bright section into a component of train passage time pressure fluctuations p, pand a component of an acoustic low frequency sound Pbased on the calculation result of a prediction spectrum density calculation part. The low frequency sound separation part, separates the low frequency sound P into the component of train passage time pressure fluctuations P, Pand the component of an acoustic low frequency sound Pbased on a cut-off frequency fset by a cut-off frequency setting part. The low frequency sound separation part reduces the component of the train passage time pressure fluctuations P, Plower in frequency than the cut-off frequency f, for example, among the low frequency sounds P as shown in (A), and allows the component of the acoustic low frequency sound Phigher in frequency than the cut-off frequency fto pass through as shown in (B).SELECTED DRAWING: Figure 7

Description

  The present invention relates to a frequency characteristic prediction calculation device and a frequency characteristic prediction calculation program for predicting and calculating a frequency characteristic of pressure fluctuation at the time of movement of a moving body that occurs when the moving body passes through a light section other than a tunnel section.

  When a train passes through a light section other than the tunnel section at high speed, two types of low-frequency sound (light and low-frequency sound) are observed along the line, including pressure fluctuations (pseudo-sound) and acoustic low-frequency sound when the train passes. (For example, refer nonpatent literature 1). Here, the pressure fluctuation at the time of passing the train is a pseudo sound generated mainly by the pressure field around the head and tail of the train moving with the train as the train travels at high speed. It is inversely proportional to the square of the distance. Acoustic low-frequency sound is an acoustic wave phenomenon (low-frequency sound wave) with a propagating property that is continuously observed while a train is passing. Sound pressure is observed when modeled with a linear sound source. It is inversely proportional to the square root of the point distance. Such pressure fluctuation and acoustic low-frequency sound when passing through the train are observed almost simultaneously. Although the pressure fluctuation at the time of passing through the train is observed corresponding to the head and tail of the train, the acoustic low frequency sound generated from the middle part of the train is very small, so the pressure fluctuation waveform is not clear . For this reason, acoustic low-frequency sound rarely becomes a problem along the current Shinkansen, but acoustic low-frequency sound is observed even relatively far away. There is also a demand to do it.

  Pressure fluctuations and acoustic low-frequency sound when passing through the train are observed superimposed. Conventionally, in order to investigate in detail the phenomenon of pressure fluctuation at the time of passing through a train and the phenomenon of acoustic low-frequency sound, there is a method of separating both by a bandpass filter. This is based on the fact that the frequency band of the pressure fluctuation when passing through the train is 10 Hz or less and the acoustic low frequency sound is 10 to 100 Hz. It has been confirmed by field tests, model tests, and numerical calculation results that this separation method is effective when the observation point is far away.

Satoshi Takami et al., “Low-frequency sound analysis of high-speed trains when driving in light sections”, Railway Research Institute report, Kenyusha Co., Ltd., 2009, Vol.23, No.7, p.5-10

  The conventional bandpass filter design method that separates pressure fluctuations and acoustic low-frequency sound when passing through a train is largely based on empirical rules based on past field tests and numerical results. For example, the pressure fluctuation when passing through the train is lower in the frequency band as the observation point is farther, the distance attenuation is larger than the acoustic low frequency sound, and varies depending on the shape of the train head, the knitting growth, and the shape of the tail. There are features such as. However, such a characteristic point is not reflected in the conventional design method of the band filter for separating the pressure fluctuation at the time of passing through the train and the acoustic low frequency sound. In addition, by analyzing the spectral distribution of pressure fluctuations when passing through trains and clarifying the effects of pressure fluctuations when passing through trains included in the 10 Hz and higher band, the phenomenon of acoustic low-frequency sound is indirectly clarified. Contribute.

  An object of the present invention is to apply an acoustic theoretical analysis to the pressure fluctuation at the time of passing through the moving body, and to accurately predict the frequency characteristic of the pressure fluctuation at the time of moving through the moving body and the frequency characteristic prediction calculation. Is to provide a program.

The present invention solves the above-mentioned problems by the solving means described below.
In addition, although the code | symbol corresponding to embodiment of this invention is attached | subjected and demonstrated, it is not limited to this embodiment.
As shown in FIGS. 1 and 4, the invention of claim 1 is a method for detecting pressure fluctuations (p _A , p _B ) during passage of a moving body that occurs when the moving body (1) passes through a light section other than a tunnel section. A frequency characteristic prediction calculation apparatus for predicting and calculating a frequency characteristic, comprising: a predicted spectral density calculation unit (12) for calculating a predicted spectral density (S _ref ) of the pressure fluctuation during passage through the moving body. It is a prediction arithmetic unit (5).

を特徴とする周波数特性予測演算装置である。 According to a second aspect of the present invention, in the frequency characteristic prediction calculation device according to the first aspect, the predicted spectral density calculation unit includes an air density ρ ₀ , a moving body speed U, a maximum cross-sectional area A _{0 of} the moving body, Cross-sectional area distribution A of the entire length, the distance r ₀ from the center of the path along which the moving body moves, the second type modified Bessel function K ₀ , the angular frequency ω ^* , and this moving body when the origin is taken as the tip of the moving body Calculating the predicted spectral density according to the following formula when the coordinate axis x in the length direction is:

Is a frequency characteristic prediction arithmetic device characterized by

According to a third aspect of the present invention, in the frequency characteristic prediction calculation device according to the first or second aspect, as shown in FIG. 7, the light section is moved based on the calculation result of the predicted spectral density calculation unit. Low frequency sound that separates the low frequency sound (p) generated when the body passes through into a component of pressure fluctuation (p _A , p _B ) and a component of acoustic low frequency sound (p _C ) It is a frequency characteristic prediction calculation device characterized by including a wave sound separation unit (18).

According to a fourth aspect of the present invention, in the frequency characteristic prediction calculation apparatus according to the third aspect, as shown in FIG. 6, an actual measurement spectral density calculation unit (10) for calculating an actual measurement spectral density (S) of the low frequency sound; A cutoff frequency setting unit (16) for setting a frequency when the difference between the measured spectral density and the predicted spectral density is a predetermined value (Th ₁ ) as a cutoff frequency (f _C ), The frequency sound separation unit separates the low frequency sound into a pressure fluctuation component and an acoustic low frequency sound component when passing through the moving body based on the cut-off frequency. Device.

According to a fifth aspect of the present invention, in the frequency characteristic prediction calculation apparatus according to the third aspect, as shown in FIG. 10, the spectral ratio is a predetermined value (Th ₂ ) with respect to the peak frequency (f _P ) of the predicted spectral density. A cut-off frequency setting unit (16) for setting a frequency at which to become a cut-off frequency (f _C ), and the low-frequency sound separation unit moves the low-frequency sound based on the cut-off frequency A frequency characteristic prediction calculation device that separates into a component of pressure fluctuation during body passage and a component of acoustic low frequency sound.

As shown in FIG. 4 and FIG. 8, the invention of claim 6 is a method for measuring pressure fluctuations (p _A , p _B ) during passage of the moving body that occurs when the moving body (1) passes through a light section other than the tunnel section. A frequency characteristic prediction calculation program for predicting and calculating a frequency characteristic, wherein the computer executes a predicted spectral density calculation procedure (S160) for calculating a predicted spectral density (S _ref ) of the pressure fluctuation during passage through the moving body. This is a frequency characteristic prediction calculation program.

を特徴とする周波数特性予測演算プログラムである。 According to a seventh aspect of the present invention, in the frequency characteristic prediction calculation program according to the sixth aspect, the predicted spectral density calculation procedure includes an air density ρ ₀ , a moving body speed U, a maximum cross-sectional area A _{0 of} the moving body, Cross-sectional area distribution A of the entire length, the distance r ₀ from the center of the path along which the moving body moves, the second type modified Bessel function K ₀ , the angular frequency ω ^* , and this moving body when the origin is taken as the tip of the moving body Including the step of calculating the predicted spectral density by the following formula when the coordinate axis x in the length direction of

Is a frequency characteristic prediction calculation program characterized by

According to an eighth aspect of the present invention, in the frequency characteristic prediction calculation program according to the sixth or seventh aspect, as shown in FIGS. 7 and 8, the light section is based on a calculation result in the predicted spectral density calculation procedure. Is separated into a component of pressure fluctuation (p _A , p _B ) and a component of acoustic low frequency sound (p _C ) when passing through the moving body. A frequency characteristic prediction calculation program including a low frequency sound separation procedure (S200).

According to the ninth aspect of the present invention, in the frequency characteristic prediction calculation program according to the eighth aspect, as shown in FIG. 6, an actual measurement spectral density calculation procedure (S140) for calculating the actual measurement spectral density (S) of the low frequency sound; A cutoff frequency setting procedure (S180) for setting a frequency at which a difference between the measured spectral density and the predicted spectral density becomes a predetermined value (Th ₁ ) as a cutoff frequency (f _C ), The frequency sound separation procedure includes a step of separating the low frequency sound into a component of pressure fluctuation when passing through the moving body and a component of acoustic low frequency sound based on the cutoff frequency. This is a characteristic prediction calculation program.

According to a tenth aspect of the present invention, in the frequency characteristic prediction calculation program according to the eighth aspect, as shown in FIGS. 8 and 10, the spectral ratio is a predetermined value with respect to the peak frequency (f _P ) of the predicted spectral density. Including a cut-off frequency setting procedure (S180) for setting a frequency at which Th ₂ ) is obtained as a cut-off frequency (f _C ), and the low-frequency sound separation procedure is based on the cut-off frequency. Is a frequency characteristic prediction calculation program characterized by including a procedure for separating the pressure fluctuation component when passing through the moving body and the acoustic low frequency sound component.

  According to the present invention, an acoustic theoretical analysis is applied to the pressure fluctuation when passing through the moving body, and the frequency characteristic of the pressure fluctuation when passing through the moving body can be accurately predicted.

It is a block diagram of the frequency characteristic prediction calculating apparatus which concerns on 1st Embodiment of this invention. It is a graph which shows typically the pressure fluctuation waveform which the low frequency sound wave generation part of the frequency characteristic prediction arithmetic unit concerning a 1st embodiment of this invention generates. It is a graph which shows typically the measured spectrum density which the measured spectrum density calculating part of the frequency characteristic prediction calculating device concerning a 1st embodiment of this invention calculates. It is a graph which shows typically the prediction spectrum density which the prediction spectrum density calculation part of the frequency characteristic prediction calculation apparatus which concerns on 1st Embodiment of this invention calculates. It is a conceptual diagram which shows the calculation process by the estimated spectrum density calculating part of the frequency characteristic prediction calculating apparatus which concerns on 1st Embodiment of this invention, (A) is a side view which shows an actual mobile body typically, (B ) Is a graph schematically showing a pressure field formed around an actual moving body. It is a graph which shows typically the setting procedure of the cutoff frequency by the cutoff frequency setting part of the frequency characteristic prediction arithmetic unit which concerns on 1st Embodiment of this invention. It is a graph which shows typically the separation effect of the low frequency sound separation part of the frequency characteristic prediction arithmetic unit concerning a 1st embodiment of this invention, and (A) shows typically the pressure fluctuation waveform of the low frequency sound before separation. (B) is a graph which shows typically the pressure fluctuation waveform of the acoustic low frequency sound after isolation | separation. It is a flowchart for demonstrating operation | movement of the frequency characteristic prediction calculating apparatus which concerns on 1st Embodiment of this invention. It is a block diagram of the frequency characteristic prediction calculating apparatus which concerns on 2nd Embodiment of this invention. It is a graph which shows typically the setting procedure of the cutoff frequency by the cutoff frequency setting part of the frequency characteristic prediction arithmetic unit which concerns on 1st Embodiment of this invention.

(First embodiment)
Hereinafter, a first embodiment of the present invention will be described in detail with reference to the drawings.
A train 1 shown in FIG. 1 is a moving body that moves along a track 2. The train 1 is, for example, a Shinkansen train formed by rail cars that travel at a high speed of 300 km / h or higher. The train 1 includes a leading portion 1a that forms the front portion of the leading vehicle of the train 1, a trailing portion 1b that forms the trailing portion of the trailing vehicle of the train 1, and a leading portion 1a and a trailing portion 1b of the train 1. The intermediate part 1c which comprises the part of between is provided. The train 1 includes a long streamlined head portion 1a and a tail portion 1b, and the head portion 1a and the tail portion 1b are formed in a predetermined shape in order to reduce air resistance and micro-pressure waves.

  The track 2 is a passage (movement route) on which the train 1 travels. As shown in FIG. 1, the track 2 is a double line composed of two main lines, and includes a line 2 a serving as an up main line and a line 2 b serving as a down main line. The structure 3 is a fixed structure through which the train 1 passes. The structure 3 is a fixed structure such as a tunnel that passes through the ground such as a mountainside and passes the train 1. The structure 3 includes a structure entrance / exit (tunnel wellhead) 3a serving as an entrance / exit from which the train 1 enters and exits.

  The low frequency sound measuring device 4 is a means for measuring the low frequency sound p generated when the train 1 passes. One low-frequency sound measuring device 4 is installed on the track 2 in the light section other than the inside of the structure 3 (tunnel section). The low frequency sound measuring device 4 is a pressure sensor (pressure gauge) or a microphone that measures the low frequency sound (light low frequency sound) p shown in FIG. 2 generated when the train 1 shown in FIG. Etc. As shown in FIG. 1, the low-frequency sound measuring device 4 is arranged near the orbit 2 at a predetermined distance from the orbit 2. The low frequency sound measuring device 4 outputs a low frequency sound signal (low frequency sound information) corresponding to the low frequency sound p generated when the train 1 passes the passing point P to the frequency characteristic prediction calculating device 5.

The frequency characteristic prediction calculation device 5 is a device that predicts and calculates frequency characteristics of the train passage pressure fluctuations p _A and p _B that occur when the train 1 passes through a light section other than the tunnel section. The frequency characteristic prediction calculation device 5 predicts and calculates the predicted spectral density S _ref of the pressure fluctuations p _A and p _B when passing through the train based on the low frequency sound p generated when the train 1 passes through the light section. Based on the predicted spectral density S _ref after the prediction calculation, the frequency characteristic prediction calculation device 5 generates the low frequency sound p generated when the train 1 passes through the light section, and the pressure fluctuations p _A and p _B when passing through the train. The component is separated into the component of the acoustic low frequency sound p _C. As shown in FIG. 1, the frequency characteristic prediction calculation device 5 includes a signal processing unit 6, a low-frequency sound information storage unit 7, a low-frequency sound waveform generation unit 8, a low-frequency sound waveform information storage unit 9, an actual measurement. Spectral density calculation unit 10, actual measurement spectral density information storage unit 11, predicted spectral density calculation unit 12, predicted spectral density information storage unit 13, prediction calculation information storage unit 14, prediction calculation information input unit 15, cut Off-frequency setting unit 16, cut-off frequency information storage unit 17, low-frequency sound separation unit 18, acoustic low-frequency sound information storage unit 19, acoustic low-frequency sound waveform generation unit 20, acoustics A low-frequency acoustic wave shape information storage unit 21, a program storage unit 22, a display unit 23, a control unit 24, and the like are provided. The frequency characteristic prediction calculation device 5 is constituted by, for example, a personal computer and executes predetermined processing according to a frequency characteristic prediction calculation program.

  The signal processing unit 6 is a means for processing the output signal of the low frequency sound measuring device 4. The signal processing unit 6 includes an amplifier circuit that amplifies the low-frequency sound signal output from the low-frequency sound measurement device 4, an A / D converter that converts the amplified analog signal into a digital signal, and the like. The signal processing unit 6 outputs the low frequency sound signal (low frequency sound information) after A / D conversion to the control unit 24.

  The low frequency sound information storage unit 7 is means for storing low frequency sound information output from the signal processing unit 6. For example, as shown in FIG. 1, the low-frequency sound information storage unit 7 is a memory that stores low-frequency sound p generated when the train 1 passes the passing point P as low-frequency sound information.

The low frequency sound waveform generation unit 8 is a means for generating the pressure fluctuation waveform W of the low frequency sound p based on the low frequency sound signal output from the low frequency sound measurement device 4. As shown in FIG. 2, the low frequency sound waveform generator 8 generates a pressure fluctuation waveform W that represents a temporal change in the pressure of the low frequency sound p based on the low frequency sound signal output from the low frequency sound measurement device 4. To do. Here, the vertical axis shown in FIG. 2 is pressure, and the horizontal axis is time. The low-frequency sound wave generator 8 is, for example, a pressure fluctuation waveform (plus or minus waveform) W of a train passage pressure fluctuation p _A that occurs when the leading portion 1a of the train 1 shown in FIG. and _a, the pressure fluctuation waveform (plus or minus of the waveform) W _B of the train pass during pressure fluctuations p _B that occurs when the tail portion 1b of the train 1 has passed the pass point P, the middle portion 1c passing point of the train 1 A pressure fluctuation waveform W _{C of} an acoustic low frequency sound p _C generated while passing through P is generated. The low frequency sound waveform generation unit 8 outputs the pressure fluctuation waveform W of the generated low frequency sound p to the control unit 24 as a low frequency sound waveform signal (low frequency sound waveform information).

  The low frequency sound waveform information storage unit 9 shown in FIG. 1 is means for storing the low frequency sound waveform information output from the low frequency sound waveform generation unit 8. For example, as shown in FIG. 1, the low-frequency sound waveform information storage unit 9 generates a low-frequency sound waveform of the pressure fluctuation waveform W of the low-frequency sound p while the intermediate part 1 c of the train 1 passes through the passing point P. It is a memory that stores information.

The measured spectral density calculation unit 10 is a means for calculating the measured spectral density S of the low frequency sound p generated when the train 1 passes through the light section. Based on the low frequency sound signal output from the low frequency sound measuring device 4, the measured spectral density calculation unit 10 generates frequency distributions (low frequency) of the train passage pressure fluctuations p _A and p _B and the acoustic low frequency sound p _C. A measured spectral density (measured frequency characteristic) S representing a distribution of energy of the wave sound signal with respect to the frequency) is calculated. Here, the vertical axis shown in FIG. 3 is energy spectral density (ESD), and the horizontal axis is frequency (Hz). For example, as shown in FIG. 3, the measured spectral density calculation unit 10 is used when the head 1 a of the train 1 shown in FIG. 1 passes the passing point P and the tail 1 b of the train 1 passes the passing point P. The actual measured spectral density S is calculated by the train-passing pressure fluctuations p _A and p _B generated at 1 and the acoustic low-frequency sound p _C generated while the intermediate portion 1c of the train 1 passes through the passing point P. The measured spectral density calculation unit 10 outputs the calculated measured spectral density S to the control unit 24 as a measured spectral density signal (measured spectral density information).

  The measured spectral density information storage unit 11 shown in FIG. 1 is means for storing the measured spectral density information output from the measured spectral density calculation unit 10. The measured spectral density information storage unit 11 is a memory that stores, for example, the measured spectral density S when the train 1 as shown in FIG.

The predicted spectral density calculation unit 12 is a means for calculating the predicted spectral density S _ref of the pressure fluctuations p _A and p _B when passing through the train. Based on the low frequency sound signal output from the low frequency sound measurement device 4, the predicted spectral density calculation unit 12 distributes the frequency distribution of the pressure fluctuations p _A and p _B when passing through the train (distribution of the energy of the low frequency sound signal with respect to the frequency). A predicted spectral density (predicted frequency characteristic) S _ref is calculated. Here, the vertical axis shown in FIG. 4 is energy spectral density (ESD), and the horizontal axis is frequency (Hz). For example, as shown in FIG. 4, the predicted spectral density calculation unit 12 is configured such that when the leading portion 1 a of the train 1 shown in FIG. 1 passes the passing point P and when the trailing portion 1 b of the train 1 passes the passing point P. The predicted spectral density S _raf is calculated from the pressure fluctuations p _A and p _B when the train passes.

Assume that the origin of the coordinate system shown in FIG. 5 is placed on the ground surface, and the leading portion 1a of the train 1 is at the coordinate origin at time t = 0. The train 1 shown in FIG. 5 travels at a constant speed U in the negative direction of the x ₁ axis at a position of x ₂ = 0 and x ₃ = h. When ignoring the influence of the shape of the head part 1a of the train 1 and approximating the influence of the train 1 by a point spring, the spring strength q is given by the following equation (1).

Here, A ₀ shown in Equation 1 is a cross-sectional area of the train 1, and δ is a delta function. When the train Mach number M = U / c ₀ (c ₀ is the speed of sound) is sufficiently small, the pressure fluctuations p _A and p _B when passing through the train approximate to the low Mach number are calculated using the Green function of the incompressible potential flow. be able to. The Green function of the incompressible fluid considering the ground effect is given by the following equations (2) and (3).

  The pressure fluctuation p due to springing is expressed by the following equation 4 using the Green function.

Here, ρ ₀ shown in Equation 4 is the atmospheric density. Considering the influence of the shape of the entire train 1, the spring strength q is expressed by the following formula 5.

  Here, A shown in Equation 5 is a cross-sectional area distribution of the entire length of the train 1 including the leading portion 1a and the trailing portion 1b of the train 1. Substituting equation 5 into equation 4 and setting h = 0, the following equation 6 is obtained.

Even if x ₁ = 0 in Equation 6, generality is not lost. When Fourier transform is performed with x ₁ = 0, b = A / A ₀ , and Y = y ₁ / r ₀ , the energy of the pressure fluctuations p _A and p _B when passing through the train considering the influence of the shape of the leading portion 1a of the entire train 1 Spectral density (ESD) is obtained by Equation 7 below.

Here, ρ ₀ shown in Equation 7 is the air density, U is the speed of the train 1, A ₀ is the maximum cross-sectional area of the train 1, A is the cross-sectional area distribution of the entire length of the train 1, and r _0. Is the distance from the center of the track 2a on which the train 1 moves, K ₀ is the second type modified Bessel function, ω ^* is the angular frequency, and x is this when the origin is at the tip of the train 1 It is a coordinate axis in the length direction of the train 1 (distance from the tip of the leading portion 1a of the train 1).

The predicted spectral density calculation unit 12 illustrated in FIG. 1 calculates the predicted spectral density S _{ref according} to _Equation 7 based on the predicted calculation information stored in the predicted calculation information storage unit 14. The predicted spectral density calculation unit 12 outputs the calculated predicted spectral density S _ref to the control unit 24 as a predicted spectral density signal (predicted spectral density information).

The predicted spectral density information storage unit 13 is means for storing predicted spectral density information output by the predicted spectral density calculation unit 12. The predicted spectral density information storage unit 13 stores, for example, the predicted spectral density S _ref when the leading part 1a and the trailing part 1b of the train 1 pass through the passing point P as shown in FIG. 4 as predicted spectral density information. It is.

The prediction calculation information storage unit 14 is a means for storing information necessary for calculation of the predicted spectral density S _ref as prediction calculation information. The prediction calculation information storage unit 14 includes the air density ρ ₀ shown in Equation 7, the speed U of the train 1, the maximum cross-sectional area A _{0 of} the train 1, the cross-sectional area distribution A of the entire length of the train 1, and the track 2a on which the train 1 moves. Prediction calculation information relating to the distance r ₀ from the center, the second type modified Bessel function K _{0, the} angular frequency ω ^*, etc. is stored. The prediction calculation information storage unit 14 is a memory that stores, for example, prediction calculation information output from the prediction calculation information input unit 15.

The prediction calculation information input unit 15 is a means for inputting information necessary for calculation of the predicted spectral density S _ref . For example, when the operator operates an input device such as a keyboard or an auxiliary input device such as a mouse to input prediction calculation information necessary for calculating the predicted spectral density S _ref , the prediction calculation information input unit 15 It is an interface (I / F) circuit or the like that inputs prediction calculation information to the frequency characteristic prediction calculation device 5.

Cutoff frequency setting unit 16 is means for setting a cut-off frequency f _c of the time separating a predetermined frequency component from the low-frequency sound p generated when the lights interval train 1 passes. Here, the vertical axis shown in FIG. 6 is energy spectral density (ESD), and the horizontal axis is frequency (Hz). The solid line shown in FIG. 6 is the measured spectral density S, and the two-dot chain line is the predicted spectral density S _ref . The cut-off frequency setting unit 16 sets the frequency at which the difference between the measured spectral density S and the predicted spectral density S _ref becomes a predetermined value (threshold value) Th ₁ as the cut-off frequency f _C. For example, as shown in FIG. 6, the cut-off frequency setting unit 16 includes the train passing pressure fluctuations p _A and p _B and the actually measured spectral density S of the acoustic low frequency sound p _C and the train passing pressure fluctuation p _A , The frequency at which the difference between the predicted spectral density S _ref of p _B reaches the predetermined value Th ₁ is set as the cutoff frequency (cutoff frequency) f _C. The cut-off frequency setting unit 16 _{modifies the} predicted spectral density S _ref shown in Equation 7 as shown in _Equation 8 below.

Here, a shown in Equation 8 is a coefficient. The cut-off frequency setting unit 16 sets the coefficient a according to various local conditions. For example, as shown in FIG. 6, the cutoff frequency setting unit 16 makes the peak frequency of the measured spectral density S shown in FIG. 3 substantially coincide with the peak frequency f _P of the predicted spectral density S _ref shown in FIG. , Coefficient a is set. For example, as shown in FIG. 6, the cutoff frequency setting unit 16 collates the measured spectral density S shown in FIG. 3 with the corrected predicted spectral density S _ref shown in FIG. The frequency at which the difference from the predicted spectral density S _ref becomes the predetermined value Th ₁ is set as the cutoff frequency f _C. The cut-off frequency setting unit 16 outputs the set cut-off frequency f _C to the control unit 24 as a cut-off frequency signal (cut-off frequency information).

The cut-off frequency information storage unit 17 shown in FIG. 1 is means for storing the cut-off frequency f _C set by the cut-off frequency setting unit 16 as cut-off frequency information. The cut-off frequency information storage unit 17 is a memory that stores, for example, cut-off frequency information output from the cut-off frequency setting unit 16.

Low frequency sound separation section 18 shown in FIG. 1, according to the result of the prediction spectral density calculation unit 12, the low-frequency sound p generated when the lights interval train 1 passes, train passes when the pressure variation p _A , P _B component and acoustic low frequency sound p _C component. Here, the vertical axis shown in FIG. 7 is pressure, and the horizontal axis is time. Based on the cutoff frequency f _C set by the cutoff frequency setting unit 16, the low frequency sound separation unit 18 converts the low frequency sound p into the components of the pressure fluctuations p _A and p _B when passing through the train and the acoustic low frequency sound. Separated into p _C components. The low frequency sound separation unit 18 extracts a component of the acoustic low frequency sound p _C from the low frequency sound p based on the low frequency sound information stored in the low frequency sound information storage unit 7. The low frequency sound separation unit 18 reduces, for example, the components of the pressure fluctuations p _A and p _B when passing through the train having a frequency lower than the cut-off frequency f _{C in the} low frequency sound p shown in FIG. 7 (B), a high-pass filter that passes a component of an acoustic low-frequency sound p _C higher than the cutoff frequency f _C or the like. The low frequency sound separation unit 18 outputs the component of the acoustic low frequency sound p _C separated from the low frequency sound p to the control unit 24 as an acoustic low frequency sound signal (acoustic low frequency sound information).

The acoustic low frequency sound information storage unit 19 shown in FIG. 1 is means for storing the acoustic low frequency sound p _C separated by the low frequency sound separation unit 18 as acoustic low frequency sound information. The acoustic low frequency sound information storage unit 19 is a memory that stores, for example, acoustic low frequency sound information output from the low frequency sound separation unit 18.

The acoustic low frequency sound wave generator 20 is a means for generating the pressure fluctuation waveform W _C of the acoustic low frequency sound p _C based on the acoustic low frequency sound signal output from the low frequency sound separation unit 18. is there. As shown in FIG. 7B, the acoustic low-frequency sound waveform generator 20 generates the acoustic low-frequency sound p _C based on the acoustic low-frequency sound signal output from the low-frequency sound separator 18. A pressure fluctuation waveform W _C representing the time change of the pressure is generated. The acoustic low-frequency sound waveform generator 20 generates a pressure fluctuation waveform W _C of the acoustic low-frequency sound p _C generated while the intermediate part 1c of the train 1 passes the passing point P, for example. The acoustic low frequency sound waveform generation unit 20 controls the pressure fluctuation waveform W _C of the generated acoustic low frequency sound p _C as an acoustic low frequency sound waveform signal (acoustic low frequency sound waveform information). To the unit 24.

The acoustic low frequency sound waveform information storage unit 21 shown in FIG. 1 is means for storing the acoustic low frequency sound waveform information output from the acoustic low frequency sound waveform generation unit 20. For example, as shown in FIG. 7B, the acoustic low frequency sound waveform information storage unit 21 stores the pressure fluctuation waveform W _C of the acoustic low frequency sound p _C as acoustic low frequency sound waveform information. Memory.

The program storage unit 22 is a means for storing a frequency characteristic prediction calculation program for predicting and calculating the frequency characteristics of the train passage pressure fluctuations p _A and p _B that occur when the train 1 passes through a light section other than the tunnel section. . The program storage unit 22 is a memory that stores the frequency characteristic prediction calculation program read from, for example, an information recording medium that records the frequency characteristic prediction calculation program or a telecommunication line that transmits the frequency characteristic prediction calculation program.

The display unit 23 is a means for displaying various information related to the frequency characteristic prediction calculation device 5. The display unit 23 displays, for example, the pressure fluctuation waveform W of the low frequency sound p as shown in FIGS. 2 and 7A, the measured spectral density S as shown in FIG. and it displays the predicted spectral density S _ref as shown in, the display device having a liquid crystal screen and displays the pressure fluctuation waveform W _C of acoustical low-frequency sound p _C as shown in FIG. 7 (B) is there.

  The control unit 24 is a central processing unit (CPU) that controls various operations of the frequency characteristic prediction calculation device 5. The control unit 24 reads the frequency characteristic prediction calculation program from the program storage unit 22 and executes a series of frequency characteristic prediction calculation processes. For example, the control unit 24 outputs the low frequency sound information output from the signal processing unit 6 to the low frequency sound information storage unit 7 or instructs the low frequency sound information storage unit 7 to store the low frequency sound information. Low-frequency sound information is read from the low-frequency sound information storage unit 7 and output to the low-frequency sound waveform generation unit 8, the measured spectral density calculation unit 10 and the low-frequency sound separation unit 18, or the low-frequency sound waveform generation unit 8 Instructs the generation of the pressure fluctuation waveform W of the frequency sound p, outputs the low frequency sound waveform information output from the low frequency sound waveform generation unit 8 to the low frequency sound waveform information storage unit 9, or stores the low frequency sound waveform information The unit 9 is instructed to store low-frequency sound waveform information.

The control unit 24 instructs the measured spectral density calculation unit 10 to calculate the measured spectral density S, outputs the measured spectral density information output from the measured spectral density calculation unit 10 to the measured spectral density information storage unit 11, or instructs the storing of the measured spectral density information on spectral density information storage unit 11, the prediction spectral density information or command calculation of predicted spectral density S _ref to the prediction spectral density calculation unit 12, and outputs the prediction spectral density calculation unit 12 Is output to the predicted spectral density information storage unit 13, the predicted spectral density information storage unit 13 is instructed to store predicted spectral density information, or the predicted calculation information stored in the predicted calculation information storage unit 14 is read out to be predicted spectral density Prediction calculation information output to the calculation unit 12 or output by the prediction calculation information input unit 15 Is output to the prediction calculation information storage unit 14 or the prediction calculation information storage unit 14 is instructed to store the prediction calculation information.

The control unit 24 commands the cutoff frequency setting unit 16 to set the cutoff frequency f _C , outputs the cutoff frequency information output by the cutoff frequency setting unit 16 to the cutoff frequency information storage unit 17, The cut-off frequency information storage unit 17 is instructed to store cut-off frequency information, the low-frequency sound separation unit 18 is instructed to separate the low-frequency sound p, and the low-frequency sound separation unit 18 outputs an acoustic low The frequency sound information is output to the acoustic low frequency sound information storage unit 19, the acoustic low frequency sound information storage unit 19 is instructed to store the acoustic low frequency sound information, or the acoustic low frequency sound information is stored. The waveform generator 20 is instructed to generate a pressure fluctuation waveform W _C of the acoustic low-frequency sound p _C , and the acoustic low-frequency sound waveform information output by the acoustic low-frequency sound waveform generator 20 is acoustically Output to the low frequency sound wave information storage unit 21 Or the acoustic low-frequency sound waveform information storage unit 21 is instructed to store the acoustic low-frequency sound waveform information, the length correction program is read from the program storage unit 22, and various information is stored in the display unit 23. Command display.

  The control unit 24 includes a signal processing unit 6, a low frequency sound information storage unit 7, a low frequency sound waveform generation unit 8, a low frequency sound waveform information storage unit 9, an actual measurement spectral density calculation unit 10, and an actual measurement spectral density information storage unit 11. , Predicted spectrum density calculation unit 12, predicted spectrum density information storage unit 13, prediction calculation information storage unit 14, prediction calculation information input unit 15, cut-off frequency setting unit 16, cut-off frequency information storage unit 17, low-frequency sound separation unit 18. Acoustic low frequency sound information storage unit 19, acoustic low frequency sound waveform generation unit 20, acoustic low frequency sound waveform information storage unit 21, program storage unit 22, display unit 23, and the like can communicate with each other. As such, they are connected by communication means such as a bus.

Next, the operation of the frequency characteristic prediction calculation apparatus according to the first embodiment of the present invention will be described.
Below, it demonstrates centering around operation | movement of the control part 24 shown in FIG.
In step (hereinafter referred to as S) 100 shown in FIG. 8, the control unit 24 reads the frequency characteristic prediction calculation program. When the power supply of the frequency characteristic prediction calculation device 5 shown in FIG. 1 is turned on, the control unit 24 reads a frequency characteristic prediction calculation program from the program storage unit 22 and the control unit 24 executes a series of frequency characteristic prediction calculation processes.

In S110, the control unit 24 instructs the low frequency sound information storage unit 7 to store the low frequency sound information. As shown in FIGS. 1 and 2, the low-frequency sound measuring device 4 uses the train passage pressure fluctuations p _A and p _B and the acoustic low-frequency sound p _C generated when the train 1 passes the passing point P. The low frequency sound measurement device 4 measures the low frequency sound signal corresponding to the pressure fluctuations p _A and p _B and the acoustic low frequency sound p _C when passing through the train to the signal processing unit 6 of the frequency characteristic prediction calculation device 5. Output. As a result, the signal processing unit 6 processes the low frequency sound signal output from the low frequency sound measuring device 4, and the signal processing unit 6 outputs the low frequency sound signal to the control unit 24. When the control unit 24 outputs the low frequency sound signal to the low frequency sound information storage unit 7 and the control unit 24 instructs the low frequency sound information storage unit 7 to store the low frequency sound information, the low frequency sound information storage unit 7 Stores low frequency sound information.

  In S120, the control unit 24 instructs the low-frequency sound waveform generation unit 8 to generate the pressure fluctuation waveform W of the low-frequency sound p. The control unit 24 reads the low frequency sound information from the low frequency sound information storage unit 7, and the control unit 24 outputs the low frequency sound information to the low frequency sound waveform generation unit 8. When the control unit 24 instructs the low-frequency sound waveform generator 8 to generate the pressure fluctuation waveform W of the low-frequency sound p, the pressure fluctuation waveform W of the low-frequency sound p as shown in FIGS. 2 and 7A is reduced. The low frequency sound waveform generation unit 8 generates the low frequency sound waveform information and outputs the low frequency sound waveform information to the control unit 24.

  In S130, the control unit 24 instructs the low-frequency sound waveform information storage unit 9 to store the low-frequency sound waveform information. When the control unit 24 outputs the low frequency sound waveform information to the low frequency sound waveform information storage unit 9 and the control unit 24 instructs the low frequency sound waveform information storage unit 9 to store the low frequency sound waveform information, the low frequency sound waveform information is stored. The information storage unit 9 stores low frequency sound waveform information.

  In S <b> 140, the control unit 24 instructs the measured spectral density calculation unit 10 to calculate the measured spectral density S. The control unit 24 reads the low frequency sound information from the low frequency sound information storage unit 7, and the control unit 24 outputs the low frequency sound information to the measured spectral density calculation unit 10, and calculates the measured spectral density S. The control unit 24 instructs the calculation unit 10. As a result, the actually measured spectrum density S as shown in FIG. 3 is calculated by the actually measured spectrum density calculation unit 10, and the actually measured spectrum density information is output to the control unit 24.

  In S150, the control unit 24 instructs the measured spectral density information storage unit 11 to store the measured spectral density information. When the control unit 24 outputs the measured spectral density information to the measured spectral density information storage unit 11 and the control unit 24 instructs the measured spectral density information storage unit 11 to store the measured spectral density information, the measured spectral density information is converted into the measured spectral density information. The information storage unit 11 stores the information.

In S160, the control unit 24 instructs the predicted spectral density calculation unit 12 to calculate the predicted spectral density _Sref . The control unit 24 reads the low frequency sound information from the low frequency sound information storage unit 7, and the control unit 24 outputs the low frequency sound information to the predicted spectrum density calculation unit 12. Further, the control unit 24 reads the prediction calculation information from the prediction calculation information storage unit 14, and the control unit 24 outputs the prediction calculation information to the prediction spectrum density calculation unit 12. When the control unit 24 calculates the prediction spectral density S _ref to the prediction spectral density calculation unit 12 instructs the prediction spectral density S _ref as shown FIG. 4 calculates the prediction spectral density calculation unit 12, the prediction spectral prediction spectral density information The density calculation unit 12 outputs to the control unit 24.

  In S <b> 170, the control unit 24 instructs the predicted spectral density information storage unit 13 to store the predicted spectral density information. When the control unit 24 outputs the predicted spectral density information to the predicted spectral density information storage unit 13 and the control unit 24 instructs the predicted spectral density information storage unit 13 to store the predicted spectral density information, the predicted spectral density information is converted into the predicted spectral density information. The information storage unit 13 stores it.

In S180, the control unit 24 instructs the cutoff frequency setting unit 16 to set the cutoff frequency f _C. The control unit 24 reads the measured spectral density information stored in the measured spectral density information storage unit 11, and the control unit 24 reads the predicted spectral density information from the predicted spectral density information storage unit 13. When the control unit 24 outputs the measured spectral density information and the predicted spectral density information to the cutoff frequency setting unit 16, the control unit 24 instructs the cutoff frequency setting unit 16 to set the cutoff frequency f _C. As a result, as shown in FIG. 6, when the cutoff frequency setting unit 16 sets the frequency at which the difference between the measured spectral density S and the predicted spectral density S _ref is a predetermined value Th ₁ as the cutoff frequency f _C , the cutoff frequency The cut-off frequency setting unit 16 outputs the information to the control unit 24.

  In S190, the control unit 24 instructs the cutoff frequency information storage unit 17 to store the cutoff frequency information. When the control unit 24 outputs the cut-off frequency information to the cut-off frequency information storage unit 17 and the control unit 24 instructs the cut-off frequency information storage unit 17 to store the cut-off frequency information, the cut-off frequency information is converted into the cut-off frequency information. The information storage unit 17 stores it.

In S200, the control unit 24 instructs the low frequency sound separation unit 18 to separate the low frequency sound p. The control unit 24 reads the low frequency sound information from the low frequency sound information storage unit 7, and the control unit 24 outputs the low frequency sound information to the low frequency sound separation unit 18, and the cut frequency information is stored in the cutoff frequency information storage unit 17. The control unit 24 reads off frequency information, and the control unit 24 outputs this cutoff frequency information to the low frequency sound separation unit 18. When the control unit 24 instructs the low frequency sound separation unit 18 to separate the low frequency sound p, the low frequency sound separation unit 18 separates the acoustic low frequency sound p _C from the low frequency sound p shown in FIG. The low frequency sound separation unit 18 outputs the scientific low frequency sound information to the control unit 24.

  In S210, the control unit 24 instructs the acoustic low frequency sound information storage unit 19 to store the acoustic low frequency sound information. The control unit 24 outputs the acoustic low frequency sound information to the acoustic low frequency sound information storage unit 19, and stores the acoustic low frequency sound information in the acoustic low frequency sound information storage unit 19. , The acoustic low frequency sound information storage unit 19 stores the acoustic low frequency sound information.

In S220, the control unit 24 instructs the acoustic low-frequency sound waveform generator 20 to generate the pressure fluctuation waveform W _C of the acoustic low-frequency sound p _C. The control unit 24 reads the acoustic low frequency sound information from the acoustic low frequency sound information storage unit 19, and the control unit 24 sends the acoustic low frequency sound information to the acoustic low frequency sound waveform generation unit 20. Output. When the control unit 24 instructs the acoustic low-frequency sound waveform generator 20 to generate the pressure fluctuation waveform W _C of the acoustic low-frequency sound p _C, the acoustics as shown in FIG. 2 and FIG. the pressure fluctuation waveform W _C of the low-frequency sound p _C generated by acoustical low-frequency sound wave generating unit 20, an acoustical low-frequency sound information acoustical low-frequency sound wave information storage unit 21 the control unit 24 Output.

  In S230, the control unit 24 instructs the acoustic low-frequency sound waveform information storage unit 21 to store the acoustic low-frequency sound waveform information. The controller 24 outputs the acoustic low frequency sound waveform information to the acoustic low frequency sound waveform information storage unit 21, and stores the acoustic low frequency sound waveform information storage unit 21. When the control unit 24 instructs, the acoustic low-frequency sound waveform information storage unit 21 stores the acoustic low-frequency sound waveform information.

The frequency characteristic prediction calculation device and the frequency characteristic prediction calculation program according to the first embodiment of the present invention have the following effects.
(1) In the first embodiment, the predicted spectral density calculation unit 12 calculates the predicted spectral density S _ref of the train passing pressure fluctuations p _A and p _B. For this reason, the frequency characteristics of the pressure fluctuations p _A and p _B when passing through the train can be accurately predicted. As a result, it is possible to analyze the pressure fluctuation in the vicinity of the high-speed railway line.

(2) In the first embodiment, the air density ρ ₀ , the speed U of the train 1, the maximum cross-sectional area A _{0 of} the train 1, the cross-sectional area distribution A of the entire length of the train 1, and the center of the track 2a on which the train 1 moves The estimated spectral density calculation when the distance r ₀ , the second type modified Bessel function K ₀ , the angular frequency ω ^* , and the coordinate axis x in the length direction of the train 1 when the origin is taken at the tip of the train 1 The unit 12 calculates the predicted spectral density S _{ref according} to _Equation 7. Therefore, the train passes during pressure fluctuations p _A, by applying acoustic theory analysis p _B, the train passes during pressure fluctuations p _A, the frequency characteristic of the p _B can be accurately predicted by the prediction equation .

(3) In the first embodiment, based on the calculation result of the predicted spectral density calculation unit 12, the low-frequency sound p generated when the train 1 passes through the light section is converted into the pressure fluctuation p _A , p when the train passes. _The low frequency sound separation unit 18 separates the _B component and the acoustic low frequency sound p _C component. For this reason, components other than the pressure fluctuations p _A and p _B when passing through the train can be extracted from the low frequency sound p with high accuracy.

(4) In the first embodiment, the measured spectral density calculation unit 10 calculates the measured spectral density S of the low-frequency sound p, and the difference between the measured spectral density S and the predicted spectral density S _ref becomes a predetermined value Th ₁ . The cutoff frequency setting unit 16 sets the frequency at the time as the cutoff frequency f _C. In the first embodiment, based on the cut-off frequency f _C , the low-frequency sound p is converted into the components of the pressure fluctuations p _A and p _B when passing through the train and the acoustic low-frequency sound p _C. The separation unit 18 is separated. Therefore, the cut-off frequency f _C for removing the influence of the pressure fluctuations p _A and p _B when passing through the train can be designed and determined according to the position of the observation point, the situation and conditions of the train 1. For example, by setting the cutoff frequency f _C to about 10 Hz, the influence of the pressure fluctuations p _A and p _B when passing through the train can be reduced to 1/100 or less.

(Second Embodiment)
In the following, the same parts as those shown in FIGS. 1 to 7 are denoted by the same reference numerals and detailed description thereof is omitted.
Unlike the frequency characteristic prediction calculation device 5 shown in FIG. 1, the frequency characteristic prediction calculation device 5 shown in FIG. 9 does not include the measured spectrum density calculation unit 10 and the measured spectrum density information storage unit 11, and is shown in FIG. The method of determining the cut-off frequency f _C by the cut-off frequency setting unit 16 is different from that of the cut-off frequency setting unit 16 shown in FIG.

The cut-off frequency setting unit 16 shown in FIG. 9 is means for setting the frequency at which the spectrum ratio is a predetermined value Th ₂ with respect to the peak frequency f _P of the predicted spectral density S _ref as the cut-off frequency f _C. For example, as shown in FIG. 10, the cutoff frequency setting unit 16 sets the peak frequency f _P as the frequency when the predicted spectral density S _{ref of the} pressure fluctuations p _A and p _B when passing through the train shows the maximum value. The frequency at which the spectrum ratio at the frequency f _P becomes a predetermined value (threshold value) Th ₂ is set as the cutoff frequency f _C.

The frequency characteristic prediction calculation device and the frequency characteristic prediction calculation program according to the second embodiment of the present invention have the following effects in addition to the effects of the first embodiment.
In the second embodiment, the cutoff frequency setting unit 16 sets the frequency at which the spectrum ratio is a predetermined value Th ₂ with respect to the peak frequency f _P of the predicted spectral density S _ref as the cutoff frequency f _C , Based on the off-frequency f _C , the low-frequency sound p is separated by the low-frequency sound separation unit 18 into components of the pressure fluctuations p _A and p _B when passing through the train and a component of the acoustic low-frequency sound p _C. For this reason, by setting the frequency at which the spectral ratio becomes the predetermined value Th ₂ inputted in advance as the cutoff frequency f _C , it is possible to remove the influence of the train passing pressure fluctuations p _A and p _B. For example, by setting the spectral ratio to about 1/100, the influence of the pressure fluctuations p _A and p _B when passing through the train can be reduced.

(Other embodiments)
The present invention is not limited to the embodiment described above, and various modifications or changes can be made as described below, and these are also within the scope of the present invention.
In this embodiment, the train 1 is described as an example of the moving body, but the present invention is not limited to this. For example, the present invention can be applied to a moving body such as a magnetic levitation railway, an automobile, an aircraft, or a flying object that travels at a high speed. In this embodiment, the case where the track 2 is a double line has been described as an example. However, the present invention can also be applied to a case where the track 2 is a single line or a double line. Furthermore, in this embodiment, the tunnel is taken as an example of the structure 3, but the tunnel buffer covering the tunnel wellhead to reduce the tunnel micro-pressure wave, the bridge bridge over the track 2, the track 2 The present invention can also be applied to structures such as Hashigami Station where the station bookstore is located.

1 train (mobile)
1a First part (front part)
1b Tail (rear)
DESCRIPTION OF SYMBOLS 1c Intermediate part 2 Orbit 3 Structure 4 Low frequency sound measuring device 5 Frequency characteristic prediction computing device 6 Signal processing part 7 Low frequency sound information storage part 8 Low frequency sound wave generation part 9 Low frequency sound wave form information storage part 10 Measured spectral density Calculation unit 11 Measured spectral density information storage unit 12 Predicted spectral density calculation unit 13 Predicted spectral density information storage unit 14 Prediction calculation information storage unit 15 Prediction calculation information input unit 16 Cutoff frequency setting unit 17 Cutoff frequency information storage unit 18 Low frequency Wave sound separation unit 19 Acoustic low frequency sound information storage unit 20 Acoustic low frequency sound waveform generation unit 21 Acoustic low frequency sound waveform information storage unit 22 Program storage unit 23 Display unit 24 Control unit P Passing point p Low frequency Wave sound (light low frequency sound)
p _A , p _B pressure fluctuation when passing through train (pressure fluctuation when passing through moving body)
p _C acoustical low frequency sound W, W _A , W _B , W _C pressure fluctuation waveform S measured spectral density S _ref predicted spectral density (frequency characteristics)
Th ₁ and Th ₂ predetermined values (threshold)
f _C cutoff frequency f _P peak frequency

Claims (10)

A frequency characteristic prediction calculation device that predicts and calculates a frequency characteristic of pressure fluctuation at the time of moving through a moving body that occurs when the moving body passes through a light section other than a tunnel section,
A predicted spectral density calculation unit for calculating a predicted spectral density of pressure fluctuations when passing through the moving body;
A frequency characteristic prediction calculation device characterized by the above. In the frequency characteristic prediction calculation apparatus according to claim 1,
The predicted spectral density calculation unit includes an air density ρ ₀ , a moving body speed U, a maximum cross sectional area A _{0 of} the moving body, a cross sectional area distribution A of the entire length of the moving body, and a distance r ₀ from the center of the path along which the moving body moves. , The second type modified Bessel function K ₀ , the angular frequency ω ^* , and the coordinate axis x in the length direction of the moving body when the origin is taken at the tip of the moving body, Computing

A frequency characteristic prediction calculation device characterized by the above. In the frequency characteristic prediction calculation device according to claim 1 or 2,
Based on the calculation result of the predicted spectral density calculation unit, the low frequency sound generated when the moving body passes through the light section, the component of the pressure fluctuation when passing the moving body and the component of acoustic low frequency sound A low-frequency sound separation unit that separates into
A frequency characteristic prediction calculation device characterized by the above. In the frequency characteristic prediction calculation apparatus according to claim 3,
An actual spectral density calculation unit for calculating an actual spectral density of the low-frequency sound;
A cutoff frequency setting unit that sets a frequency when the difference between the measured spectral density and the predicted spectral density is a predetermined value as a cutoff frequency;
The low-frequency sound separation unit separates the low-frequency sound into a component of pressure fluctuation when passing through the moving body and a component of acoustic low-frequency sound based on the cutoff frequency;
A frequency characteristic prediction calculation device characterized by the above. In the frequency characteristic prediction calculation apparatus according to claim 3,
A cutoff frequency setting unit that sets a frequency when a spectral ratio is a predetermined value with respect to a peak frequency of the predicted spectral density as a cutoff frequency;
The low-frequency sound separation unit separates the low-frequency sound into a component of pressure fluctuation when passing through the moving body and a component of acoustic low-frequency sound based on the cutoff frequency;
A frequency characteristic prediction calculation device characterized by the above. A frequency characteristic prediction calculation program for predicting and calculating a frequency characteristic of pressure fluctuation at the time of moving through a moving body that occurs when the moving body passes through a light section other than a tunnel section,
Causing a computer to execute a predicted spectral density calculation procedure for calculating a predicted spectral density of pressure fluctuation during passage through the moving body;
A frequency characteristic prediction calculation program characterized by In the frequency characteristic prediction calculation program according to claim 6,
The predicted spectral density calculation procedure includes air density ρ ₀ , moving body speed U, maximum cross sectional area A _{0 of} the moving body, cross sectional area distribution A of the entire length of the moving body, and distance r ₀ from the center of the path along which the moving body moves. , The second type modified Bessel function K ₀ , the angular frequency ω ^* , and the coordinate axis x in the length direction of the moving body when the origin is taken at the tip of the moving body, Including a procedure for computing

A frequency characteristic prediction calculation program characterized by In the frequency characteristic prediction calculation program according to claim 6 or 7,
Based on the calculation result in the predicted spectral density calculation procedure, the low frequency sound generated when the moving body passes through the light section, the pressure fluctuation component and the acoustic low frequency sound component when the moving body passes Including a low frequency sound separation procedure,
A frequency characteristic prediction calculation program characterized by In the frequency characteristic prediction calculation program according to claim 8,
Actual spectral density calculation procedure for calculating the actual spectral density of the low frequency sound,
A cutoff frequency setting procedure for setting a frequency when the difference between the measured spectral density and the predicted spectral density is a predetermined value as a cutoff frequency;
The low frequency sound separation procedure includes a procedure of separating the low frequency sound into a component of pressure fluctuation when passing through the moving body and a component of acoustic low frequency sound based on the cutoff frequency.
A frequency characteristic prediction calculation program characterized by In the frequency characteristic prediction calculation program according to claim 8,
A cutoff frequency setting procedure for setting a frequency when a spectral ratio is a predetermined value with respect to a peak frequency of the predicted spectral density as a cutoff frequency;
The low frequency sound separation procedure includes a procedure of separating the low frequency sound into a component of pressure fluctuation when passing through the moving body and a component of acoustic low frequency sound based on the cutoff frequency.
A frequency characteristic prediction calculation program characterized by

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