JPH0288928A - Device for discriminating noise of aircraft - Google Patents

Abstract

PURPOSE:To surely discriminate the noise of aircraft without receiving any influences of periodic high-level noise components by performing white noising calculating processes on noise detecting signals obtained from a pair of microphones and at the same time, executing a mutually correlating process on the signals. CONSTITUTION:Difference data S5A and S5B from which periodic noise components contained in noise detecting data S4A and S4B are removed are found by performing difference calculating processes on the noise detecting data S4A and S4B obtained from two microphones 2A and 2B by means of white noising calculating means 15 and mutually correlating processes are performed on the difference data S5A and S5B. Therefore, wrong discrimination based on a periodic high-level noise component can be avoided and the aircraft noise discriminating ability of this device can be improved further.

Description

Detailed Description of the Invention [Summary of the Invention] The present invention provides an aircraft noise identification device using a cross-correlation calculation method, in which a cross-correlation calculation is executed after noise detection data is subjected to differential calculation processing. It is possible to make the peak representing the value even steeper.

[Conventional technology]

As a standard for evaluating aircraft noise, [Environmental standards related to aircraft noise (Environment Agency Notification 154 of December 27, 1970)]
J, and automatic aircraft noise measurement devices manufactured in accordance with this standard have been used in the past.

However, in this type of automatic aircraft noise measurement device,
In practice, it is difficult to distinguish aircraft noise from ambient noise such as city noise and evaluate only aircraft noise.
The second method is to evaluate the noise as aircraft noise when the noise received by microphone 0 exceeds a predetermined set level (Japanese Patent Publication No. 15143/1983), and A method for determining the cross-correlation value of the microphone output signal and identifying aircraft noise based on the position of the peak of the cross-correlation value (Special Publication No. 61-1
3169), etc. have been proposed.

[Problem that the invention seeks to solve]

However, with the first identification method, if the level of noise other than aircraft noise is higher than aircraft noise, there is a risk that the noise other than aircraft noise may be mistakenly identified as aircraft noise.This problem can be solved by the second identification method. Improvements are being made by using methods in combination. However, if the frequency spectrum of the noise to be measured contains noise components with strong periodicity, the second identification method may malfunction due to the noise based on the periodicity being mixed into the cross-correlation value. There is.

The second method for calculating the cross-correlation value between two measurement signals is to calculate the time of the peak position of the cross-correlation value for the total volume of the noise, assuming that the noise has the characteristics of white noise. Aircraft noise is identified by focusing on the fact that the change in position represents the flight position of the aircraft.

However, in reality, for example, aircraft with propellers contain noise components with strong periodicity and high noise levels in the frequency range of about 100 to 200 ([2)].
Furthermore, when sirens, horns, etc. are mixed into city noise, a noise component having a frequency between 250 (Hz) and 1 (kHz) with strong periodicity and a high noise level is generated.

In this way, when a noise component with a high noise level for some frequencies in the frequency spectrum is mixed, if the fluctuation period of the noise level of the noise component is sufficiently longer than the cross-correlation calculation period, the cross-correlation value of the aircraft At the same time as it changes based on movement, it also changes with the period of the noise component, and this results in being mixed in as noise in the aircraft noise identification result.

It is extremely difficult in practice to determine whether or not it is aircraft noise based on identification results that include such noise, and it is desirable to improve this.

The present invention has been made in consideration of the above points, and it is possible to obtain a cross-correlation value that is not affected by periodic noise components even if the noise signal detected by the microphone is mixed with periodic noise components. This paper attempts to propose an aircraft noise identification method that can further improve aircraft noise identification performance.

[Means for solving problems]

In order to solve this problem, in the present invention, the first and second microphones 2A and 2B have first and second noise detection signals SIA and sl obtained from the first and second microphones 2A and 2B, which are made up of sampling data that are sequentially arranged in accordance with the passage of time. Second noise detection data S4. and a noise detection data forming means 9 forming the first and second noise detection data S4A and S4. a white noise conversion calculation means 15 for detecting the difference between the sequentially arranged sampling data to form first and second difference data S5A and S5++; Calculate the cross-correlation and obtain the cross-correlation calculation signal S
A cross-correlation determining means 2° for identifying aircraft noise based on peaks occurring at ll is provided.

[Effect]

Prior to the cross-correlation calculation performed by the cross-correlation determining means, the noise detection data S4A and S4° are subjected to differential calculation processing by the white noise conversion calculation means 15.

As a result, the difference data S5A and 55 from which periodic noise components included in the noise detection data S4A and 34m are removed
11 can be obtained, and by performing cross-correlation calculation processing on this, it is possible to realize an aircraft noise identification device that can effectively avoid the possibility of misjudgment based on noise components with different periodicity and a high noise level.

〔Example〕

An embodiment of the present invention will be described in detail below with reference to the drawings.

(1) First Embodiment In FIG. 1, l indicates an aircraft noise identification device as a whole, and noise detection signals Sla and SIm obtained from upper and lower microphones 2A and 2B are transmitted to amplifier circuits 3A and 3.
Analog/digital conversion circuits 4A and 4B via B
is input.

In this embodiment, upper and lower microphones 2A and 2
As shown in FIG. 2, B is placed on the same vertical line Lv by arms 7A and 7B at heights HA and H3 from the ground surface 5, respectively, on a stand 6 that stands vertically on the ground surface 5. Thus, when the noise from the aircraft 8 reaches the upper and lower microphones 2A and 2B through the paths WA and WB connecting the aircraft 8 and the upper and lower microphones 2A and 2B, respectively. , a noise detection signal that changes over time with a time delay corresponding to the path difference between the paths WA and WB (therefore, the difference in elevation angles θ and θ8 of the paths WA and WB at the upper and lower microphone positions 2A and 2B). S1
m and S1m can be taken into the noise detection data forming means 9.

The analog/digital conversion circuits 4A and 4B receive the sampling signal S3 from the system controller 11.
, the amplifier circuits 3A and 3 at that sampling period.
B's output S2. and 32m instantaneous values were sampled to obtain noise detection data S4A and S4. After converting the data into , it is supplied as the output of the noise detection data forming means 9 to the difference detection circuits 12A and 12B.

The difference detection circuit 12A (and 12B) is connected to the immediately preceding data latch circuit 13A (and 13B) and the subtraction circuit 14A (and 1
4B) and noise detection data 54m (and S4.) sent from the analog/digital conversion circuit 4A (and 4B) every time the sampling signal S3 is given.
is received by the subtraction circuit 14A (and 14B), and the immediately preceding data S is received by the immediately preceding data latch circuit 13A (and 13B).
4^8 (and 3411X), thus forming the white noise conversion calculation means 15.

The subtraction circuit 14A (and 14B) inputs the immediately preceding data S4^X (and 3
4ax) as a subtraction input, and as shown in FIG. 3(A) (and FIG. 3(B)), the immediately preceding data 5 is obtained from the noise detection data 34A (and 54R) at the current time point 1fi.
The difference data S5A (and S5.) obtained by subtracting 4ax (and 341X) is supplied to the cross-correlation determination circuit 20.

Thus, the difference detection circuit 12A (and 12B) sequentially detects the successive sampling points... ta-1, tn, t7.
Noise detection data 34m at ゜,...
The difference data 35m (and S5,
) is supplied to the cross-correlation determining circuit 20.

The cross-correlation determination circuit 20 includes a cross-correlation calculation circuit section 21 and a determination a-step section 22.

The cross-correlation calculation circuit section 21 calculates the difference data S5A and S5.
It has time data memories 25A and 25B which sequentially take in data 35m and S5. are sequentially read out as correlation data 512A and 512B under the control of the control signal Sll given from the system controller 11, multiplied in the multiplication circuit 26, and the average value of the multiplied data 313 is calculated in the average value circuit 27, thus obtaining the cross-correlation value. A signal 514 is sent out as the output of the cross-correlation calculation circuit section 21.

In this embodiment, the upper time data memory 25A is the fourth
As shown in Figure (A), difference data 35. For example, a simultaneous data area Ms1.Ms1. A in the center and the previous time, for example, 32
a previous time data area M for storing data for each item; , and a later time data area MAF? that stores 32 pieces of data regarding later times. It has A.

Similarly, the lower time data memory 25B also stores the same time data areas Ms, 14. and previous time data area M@E□
and a later time data area M @ y y @.

Each data in the upper time data memory 25A and the lower time data memory 25B is read out as cross-correlation data 512A and 312B and multiplied by the following procedure while maintaining a synchronized relationship with each other by the control signal Sll of the system controller 11. It is output to the circuit 26.

That is, the 33rd, 34th, . . . stored in the same time data area Ms1Mm of the lower time data memory 25B.
...The 1032nd data is read out repeatedly 32 times in response to the previous time data, then read out once in response to the same time data, and then repeatedly read out 32 times in response to the later time data. Read out. Here, the same time data area M□. is read out once, 1000 pieces of data are sequentially read out from the upper time data memory 25A while being shifted one data at a time.

For example, previous time data area Ml! , 1st to 100th
The 33rd to 1032nd data of the lower time data memory 25B are sequentially read out at the timing when the 0th data is sequentially read out, multiplied by each other in the multiplication circuit 26, and then outputted to the average value circuit 27 as multiplication data S13. be done.

The average value circuit 27 calculates an average value from the 1000 multiplication data S13 that are sequentially output, and outputs it as a cross-correlation value signal S14 representing the correlation degree of the first sampling point.

When the cross-correlation calculation for the first sampling point of the previous time is completed in this way, the 2nd to 1001st data (that is, the data shifted by 1 day and 5 minutes) are subsequently transferred from the upper time data memory 25A. The data is sequentially multiplied by the 33rd to 1032nd data read out and repeatedly read out from the lower time data memory 25B, and outputted to the average value circuit 27 as multiplied data S13.

At this time, the average value circuit 27 sequentially outputs 1000
An average value is calculated from the multiplied data S13 and sent as a cross-correlation value signal S14 representing the correlation degree of the second sampling point.

Thereafter, in the same manner, the 32nd
The cross-correlation value signal S14 for the 32nd sampling point is sent out based on the data from the 1031st to the 1031st, thereby ending the cross-correlation calculation related to the previous time data area M0.

Thereafter, the upper time data memory 25A stores the same time data areas Ms and M, as shown in FIG. 4(B).

The 33rd to 1032nd data stored in are read out and supplied to the multiplication circuit 26. At this time, the average value circuit 27 calculates the average value from the 1000 multiplication data 313 and sends out a cross-correlation value signal S14 representing the degree of correlation of the 33rd sampling point, thereby causing the same-time data area M84. Finish the cross-correlation operation related to .

Subsequently, the upper time data memory 25A is stored in the upper time data memory 25A as shown in FIG.
As shown in C), in relation to the later time data area M A gate A, the 34th, 35th, 66th, etc. Cross-correlation value signal S1 representing the correlation degree of the th sampling point
Send 4.

The cross-correlation value signal 514 obtained from the average value circuit 27 in this way represents the correlation degree for 65 sampling points as shown in FIG. 5, but among these data, the 33rd data is This data represents the degree of correlation in a state where aircraft noise reaches the upper microphone 2A and the lower microphone 2B at the same time, and a sampling point number "0" is assigned to this data.

Further, the 32nd, 31st, etc., first data is data representing that the time when the aircraft noise reaches the upper microphone 2A is before the time when the aircraft noise reaches the lower microphone 2B, Sampling point numbers "+1", "+2", . . . "+32" are assigned to this data.

Furthermore, the 34th, 35th, . . . , 65th data are data representing that the time point at which the aircraft noise reaches the upper microphone 2A is later than the time point at which it reaches the lower microphone 2B, Sampling point numbers "-1", "-2", . . . "-32" are assigned to this data.

Thus, as shown in FIG.
2"..."-1", "0", "+1"...
...If we form a cross-correlation value signal 514 in which r+324 data are arranged in that order and display this on a monitor graph, the correlation degree peak will change from the sampling point number "0" to the right sampling point number "+IJ, "+2"...
... As we move to r+32J, this means that the aircraft is far from the upper and lower microphones 2A and 2B (thus, the lengths of paths WA and WB are approximately equal (elevation angles θ1 and θ , are almost equal)) to a state that is approaching the position directly above (therefore, the path WA
This represents a state in which the length of the route WB becomes shorter than the length of the route WB.

On the other hand, the peak of the correlation degree is the sampling point number “0”.
” to the left sampling point number “-1”, “-2”.
...Moving to r-32J, this means that the upper and lower microphones 2
This indicates that the aircraft noise is reflected from the ground surface 5 (FIG. 2) and arrives from the lower microphone 2B side when it approaches the position directly above A and 2B.

The cross-correlation value signal 314 is given to the peak detection circuit 28 of the determination circuit section 22, and when the cross-correlation value signal S14 reaches the maximum value, the peak detection circuit 28 outputs the peak detection signal S1.
5 to the peak address memory 29.

The peak address memory 29 stores and updates the sampling point number at that timing every time the peak detection signal S15 is obtained, and thus the sampling point number "
For the cross-correlation value signal S14 ranging from "+32" to r-32J (FIG. 5), the sampling point number JDG having the maximum correlation degree is sent to the determination circuit 30 as the peak address detection signal S16.

Based on the sampling point number JDG of the peak value, the determination circuit 30 sends out an aircraft noise identification signal 5174 representing the flight position of the aircraft as an output of the cross-correlation determination circuit 20.

In this embodiment, the cross-correlation value signal S14 sent out from the cross-correlation calculation circuit section 21 is converted into an analog signal in the digital/analog conversion circuit 31, and then sent out from the cross-correlation determination circuit 20 as a monitor signal 818. By applying this monitor signal 818 to a monitor such as an oscilloscope, a correlation curve as shown in FIG. is being done.

In the above configuration, the noise detection signals SIA and S obtained from the upper microphone 2A and the lower microphone 2B are
1m is sampled in analog/digital conversion circuits 4A and 4B and noise detection data S4. and S41
When the noise detection data S4A and S41 are obtained, the difference detection circuits 12A and 12B convert the noise detection data S4A and S41 into difference data S5A.
and S5, the cross-correlation determination circuit 20 calculates the cross-correlation and obtains the aircraft noise identification signal 317 representing the sampling point number corresponding to the peak position of the cross-correlation value signal S14.

Therefore, the difference detection circuits 12A and 12B detect the noise detection data S4A and 3 at each sampling point.
4. Only the information representing the change in difference data S5A and s
5m, even if the noise detection signals SIA and S1m contain noise components with periodicity and a large noise level, the noise components can be excluded and a nearly -like frequency spectrum can be obtained. In this way, the cross-correlation value signal S14 having a stable signal level can be supplied to the cross-correlation determination circuit 20.

For example, the noise of an aircraft with a propeller is 100~
If a periodic noise component of about 200 (Hz) is mixed, the period of the periodic noise component is sufficiently longer than the difference calculation period of the difference detection circuits 12A and 12B, so the difference data S5A and Since the signal levels of the aircraft noise components included in S5m are almost equal, they are canceled out by the subtraction operations in the subtraction circuits 14A and 14B, and can be made not to be included in the difference data 35A and s5g.

Similarly, city noise other than aircraft noise, for example, 250
Similarly, regarding noise components such as sirens and horns with a frequency of approximately (Hz) to 1 (k)lx), the influence of noise components is affected by the fact that the period of the noise component is sufficiently longer than the period of the difference calculation in the difference detection circuits 12A and 12B. can be removed.

Therefore, according to the above configuration, even if the noise detection signals SIA and Sim of the upper and lower microphones 2A and 2B
Even if a noise component having periodicity and a high noise level is mixed into the noise component, the flight position of the aircraft can be reliably detected without being substantially affected by the noise component.

Incidentally, regarding aircraft noise having noise components with periodicity of about 100 to 200 (Hz), the difference detection circuit 12A
If the cross-correlation determination circuit 20 determines the cross-correlation without executing the difference calculation processing of If the degree of correlation changes greatly to correspond to the period of the noise component, multiple peaks may occur or the peak waveform may become ambiguous. As shown by the maximum peak sampling point number JDG in FIG. 5, a cross-correlation value signal with a steep peak waveform can be obtained as information representing the flight position of the aircraft.

According to experiments, as shown in Fig. 7, the cross-correlation value signal S14 of aircraft noise when an aircraft with a propeller passes overhead is measured, and the result is shown in Fig. 7 (B).
As shown in , the peak waveform representing the flight position of the aircraft was near sampling point number "0" at the start, but when the aircraft passed overhead 3.5 seconds later, the peak waveform representing the flight position of the aircraft was located near sampling point number "0". It is possible to obtain measurement information exhibiting a waveform change in which the aircraft moves largely in the direction of number r+32J and then returns to the direction of sampling point number "0" as the aircraft moves away from it until 7.5 seconds later. did it.

On the other hand, when similar measurements were made using a configuration in which the difference detection circuits 12A and 12B were omitted, the results were as shown in FIG.
), a periodic noise component based on propeller noise appears in the cross-correlation value signal 514
By converging on )
The result was that two peak waveforms were generated.

From these experimental results, it has been confirmed that the difference detection circuits 12A and 12B can form a cross-correlation value signal 314 that is not affected by periodic noise components included in aircraft noise.

[2] Other embodiments (1) In the above embodiment, the white noise conversion calculation means 15
Although an embodiment using a first-order difference calculation circuit has been described, instead of this, various configurations such as an n-order difference calculation circuit, a linear prediction filter, a partial autocorrelation calculation circuit, and a combination thereof may be applied. In short, it is sufficient to apply a white noise processing means.

(2) In the above embodiment, two microphones 2A
We have described the case where 2B and 2B are arranged vertically,
The arrangement direction is not limited to this, and the same effect as described above can be obtained by arranging in various directions, such as the horizontal direction.

(3) In the above-described embodiments, the case where the aircraft noise identification device according to the present invention is configured using hardware circuit means has been described, but instead of this, it may be configured using software calculation means as well. You can get the same effect as in the case.

〔Effect of the invention〕

As described above, according to the present invention, the noise output signals obtained from a pair of microphones are converted into digital data, and then subjected to white noise calculation processing and cross-correlation processing. Even if a noise component with a strong noise level having periodicity is mixed in, aircraft noise can be reliably identified without being affected by the noise component.

Stage, 20... Cross correlation determination circuit, 21...
. . . Cross-correlation calculation circuit section, 22 . . . Determination circuit section.

[Brief explanation of drawings]

FIG. 1 is a block diagram showing an embodiment of the aircraft noise identification device according to the present invention, FIG. 2 is a line side view showing the configuration of the microphone device, FIG. 3 is a curve diagram for explaining the difference calculation, and FIG. Figure 4 is a route map for explaining the cross-correlation calculation.
5 and 6 are signal waveform diagrams for explaining the cross-correlation calculation results, and FIG. 7 is a signal waveform diagram showing the experimental results.

Claims (1)

[Scope of Claims] Noise detection that forms first and second noise detection data consisting of sampling data that samples noise detection signals obtained from first and second microphones and sequentially arranges them over time. a data forming means, and each of the first and second noise detection data;
white noise conversion calculation means for detecting the difference between the sequentially arranged sampling data to form first and second difference data; and calculating a cross-correlation between the first and second difference data; 1. An aircraft noise identification device comprising: cross-correlation determination means for identifying aircraft noise based on peaks occurring in a calculated signal.