CN105488260B - A kind of aircraft noise identification and non-aircraft noise filter method - Google Patents
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Abstract
The invention discloses a kind of identification of aircraft noise and non-aircraft noise filter methods, premised on the Ubiquitous network formats airport noise perception, intensive, equally distributed noise measuring equipment is arranged in monitoring region, according to the real-time noise monitor value that the position correlation between each monitoring device is generated with it, realize that the Ubiquitous network is formatted the aircraft noise identification and the filtering of non-aircraft noise of airport noise perception.
Description
Technical field
The present invention relates to a kind of identification of aircraft noise and non-aircraft noise filter methods, belong to noise monitoring technical field.
Background technique
In recent years, although the career development of civil aviaton of China is very swift and violent, air transportion resource is still very nervous.Either base
Infrastructure aspect or airport quantity and capacity have all been in the state of wretched insufficiency.According to statistics, 2010 end of the year whole nations are handled up
Before amount ranking in 50 airports, there are 26 aerodrome capacities saturations, it is contemplated that other 24 airports were also up to saturation in 2015.
In order to solve the problems, such as that air transportion resource is nervous, the whole nation be planned for " 12th Five-Year Plan " latter stage civil transport number reach 230 with
On.And 2011 actually newly-increased airport there was only 5,2012 3,2013 beginning of the years estimated newly-increased 14 airports, but real
Border only builds up 10.To find out its cause, being the construction speed for affecting China's civil airport since airport noise is seriously polluted.In
The research report of Economic Growth of Civil Aviation Transportation general bureau counts: in China, having more than 150 civil airports, there are problem of noise pollution, among these will
The airport noise pollution problem of nearly one third is extremely serious.As the people increasingly mentions to what living environment quality required
Height, the airport noise pollution problem got worse caused it is civil oppose airport construction tide, make airport operator gradually by
Dynamic, the pressure from public opinion born is also increasing, seriously affects and restrict the sustainable development of China's Civil Aviation Industry.
The main airports of most of developed country have all been installed and have applied airport noise monitoring system, such as moral in the world at present
State Frankfurt Airport (Fraport) increases two monitoring stations and some mobile detection apparatus around airport, to monitor
Aircraft noise situation；Belgian Brussels airport is provided with 21 noise monitoring devices and provides the noise of surrounding incessantly
One day average noise size distribution ratio and isogram can be generated in situation.The Beijing Capital International Airport of the country, Hong Kong
The main airports such as International airport, Taiwan Taoyuan International Airport also use similar monitoring system.Airport noise monitors system can
To realize that the whole day to airport noise monitors, the reliable basis that monitoring data are polluted as airport noise is greatly facilitated
Airport administrator implements integrated control to noise.But existing airport noise monitoring system is all made of traditional monitoring mode, monitors
Node it is with high costs, node is high to arrangement environmental requirement, and system stability is poor, and data-transmission mode is fixed, transmission line paving
If the cost with later maintenance is very high.Traditional monitoring mode can not be achieved airport noise monitoring node due to the above reasons,
Extensive dense deployment can not realize the overall measure to airport and its circumference noise.
For comprehensive real-time perception demand of airport noise perception, existing Internet of Things theoretical result is airport noise perception
Research provide theoretical basis and practical experience.But these researchs are directed to general technology of Internet of things or specific application mostly
Precedent is studied and applied not yet to scene in airport noise perceptible aspect.Based on Internet of Things theory, set with a large amount of noise monitoring
It is standby uniformly, intensive, extensive layout around airport environment, the layout that the Ubiquitous network is formatted is formed, to providing in all directions around airport
Real-time noise perception data.
Current universal noise recognizing method is to carry out analysis and distinguishing to the frequency of noise, mainly have by wavelet decomposition,
The methods of noise reduction isolates the noise signal for needing to identify with this, and it is identified and is determined；Or on this basis,
By using the methods of classification, cluster in data mining, noise situations are identified and are classified.But above-mentioned Noise Identification side
The noise data that method only used single noise monitoring point is analyzed, and monitoring point numerous under general grid environment is not only had ignored
Characteristic, do not account for the correlation between each data of monitoring point yet.If considering more data of monitoring point, to the noise number of each monitoring point
According to being analyzed, it will greatly increase its calculation amount, but due to similar in frequency after the transformation of each test point noise data
Spend identification level higher, thus that its noise can not be significantly improved.
Summary of the invention
Technical problem to be solved by the invention is to provide a kind of aircraft noise identification and non-aircraft noise filter method,
Uniform, intensive, extensive noise monitoring device is laid out around airport, and each monitoring point can generate noise figure in real time, with
This obtains real-time Ubiquitous network and formats airport noise monitoring data.Since non-aircraft noise is smaller with respect to the sound intensity for aircraft noise,
Its influence of noise obvious decaying and is eliminated with becoming larger for distance, and influence of noise radius is shorter, the monitoring point number that can be influenced compared with
It is few, therefore the phase of noise between adjacent monitoring point can be calculated according to target monitoring point and the noise figure difference of neighbouring monitoring point
Like degree relationship, discriminate whether to belong to non-aircraft noise covering, and then be filtered operation.And the radius of influence of aircraft noise compared with
Far, it tends to reach as many as several kilometers.Thus in the case where aircraft noise, enough widely distributed noise monitoring point meetings
It is affected, the presence of aircraft noise is differentiated with this.According to the distribution situation of monitoring spot noise, calculate between each monitoring point
Noise rise vector, differentiates whether noise rise direction is directed toward same direction or whether is gathered in same position, calculates its aviation
Noise possibility size discriminates whether that there are aircraft noises with this, probably estimates its range.
The present invention uses following technical scheme to solve above-mentioned technical problem:
On the one hand, the present invention provides a kind of non-aircraft noise filter method, by target monitoring point and close on monitoring point it
Between noise figure size, establish noise monitoring grid, and calculate separately horizontal direction, vertical direction and two diagonals
On noise fluctuations situation；Based on the isolatism of interference noise point, pretreatment is amplified to noise fluctuations situation, selection is most closed
Suitable direction simultaneously carries out similarity analysis to noise situations in this direction, if similarity is lower than given threshold, there are non-aviations to make an uproar
Acoustic jamming is filtered operation to it, is not otherwise filtered to it.
As a further optimization solution of the present invention, it target monitoring point and closes on monitoring point and constitutes with target monitoring point and be
3 × 3 noise monitoring grids of the heart.
On the other hand, the present invention provides a kind of aircraft noise recognition methods, by entirely monitoring noise monitoring point in region
Noise figure, calculate each target monitoring point relative to closing on the noise figure difference of monitoring point, and calculate its noise rise vector；
It calculates entire monitoring region monitoring point noise rise vector and any arrives the inner product of the distance vector of the monitoring location, and find out
For its maximum value as there are aircraft noise source, there are degree sizes, degree size is greater than given threshold if it exists, then shows to supervise
Surveying region, there are aircraft noise sources, and the point is then the estimated location of floor projection where aircraft noise source.
On the other hand, the present invention provides a kind of aircraft noise identification and non-aircraft noise filter method, firstly, using as weighed
Benefit require 1 described in a kind of non-aircraft noise filter method, filter non-aircraft noise；Secondly, using as claimed in claim 3
The position in aircraft noise source is estimated in a kind of aircraft noise recognition methods.
As a further optimization solution of the present invention, if lacking noise figure at certain monitoring point in monitoring region, most with it
The inverse distance-weighting mean value substitution of nearly N number of spot noise figure, N is positive integer.
The invention adopts the above technical scheme compared with prior art, has following technical effect that
1, the present invention according to the real-time noise monitor value that is generated with it of mutual alignment relation between each monitoring point device into
The aircraft noise identification perceived based on airport noise and the filtering of non-aircraft noise may be implemented in row analysis.The present invention greatly improves
The recognition correct rate of aircraft noise, for the reasonable management of aircraft noise provides important evidence；
2, the non-aircraft noise source that the present invention can generate airport periphery monitoring region identify while to non-aviation
Noise source is filtered；Identification decision is carried out to the aircraft noise source in monitoring region, whether determines airport periphery monitoring range
There are takeoff and landing；Estimate aircraft Position Approximate.The present invention not only can effectively filter non-aircraft noise, position approximate big for aircraft
The flight course planning estimated or taken off set provides reliable basis；
3, the present invention can be to further realize the real-time isoplethes drawing of airport noise, provide and sentence for aircraft track reproduction etc.
Other condition and theoretical foundation are of great significance to China's aviation development to make tremendous contribution to China's airport construction.
Specific embodiment
Technical solution of the present invention is described in further detail below:
The noise General Influence range of aircraft is wider, when aircraft enters airport noise monitoring range, due to Internet of Things
The characteristic that net perceives on a large scale, multiple noise monitoring points can monitor the fluctuation of noise, and noise profile has significantly to become
Gesture.And called if it is general vehicle whistle or animal etc., because of more, the noise attentuation small compared with aircraft noise of its intensity of sound
The range that will affect in the process is smaller, and the noise figure that often 2,3 monitoring points monitor around sound source can change, and its
He will not then generate apparent variation by noise monitoring point.
Non- aircraft noise filter algorithm
By the association similarity analysis of monitor value between neighbouring monitoring point, the interference noise that regional area can be monitored
Source filters out, and can be improved the accuracy of aircraft noise identification.Detailed process is as follows for algorithm:
In the layout of the monitoring point that the Ubiquitous network is formatted, monitoring point is distributed according to grid situation, but the position of monitoring point is allowed to deposit
In deviation and the missing of monitoring point etc..If lacking noise figure situation at certain point, first added with the anti-distance of its nearest N number of spot noise figure
Weigh mean value substitution.
When to judge certain point P (x, y) with the presence or absence of non-aircraft noise, 3 × 3 noises put centered on P (x, y) prison is selected
Survey grid lattice W,
W={ P (i-1, j-1), P (i-1, j), P (i-1, j+1), P (i, j-1), P (i, j), P (i, j+1), P (i+1, j-
1),P(i+1,j),P(i+1,j+1)}
Wherein, i indicates that the abscissa of noise monitoring grid, j indicate the ordinate of grid.To in noise monitoring grid W
Monitoring node by table 1 carry out bearing mark.
1 noise monitoring grid W of table
| NW | N | NE |
| W | P(x,y) | E |
| SW | S | SE |
Take 4 subset (i in the griddIt is each side in monitoring grid upwardly adjacent to the noise figure of monitoring point, d indicates prison
8 represented directions in survey grid lattice):
W1={ iNW, P (x, y), iSE}
W2={ iW, P (x, y), iE}
W3={ iSW, P (x, y), iNE}
W4={ iN, P (x, y), iS}
The standard deviation for 4 subsets sought, and that the smallest group is found out, it is denoted as Wmin.Standard deviation is smaller, then explanation should
The fluctuation of group data is smaller, their noise monitoring value is with regard to closer.
Reinforcement processing, i.e. Wmin*L are carried out to the noise figure of the central point of that the smallest group, wherein [- 1,3, -1] L=,
Obtain new central point monitor value P (x, y) '.If central point is interference noise source, handled, can be incited somebody to action by above-mentioned weighting
The noise figure of the monitoring point further protrudes, and increases the difference between the monitoring point and surrounding normal monitoring point, in conjunction with hereinafter
Similarity measures can preferably detect the presence of interference noise source.If center monitors point is normal noise, i.e., nearby not
There are non-aircraft noise sources, then its noise figure detected should be very close with the noise figure of neighbouring monitoring point, reinforce rear center
Spot noise figure is almost unchanged, therefore will not impact to Similarity measures hereinafter, will not be mistaken for interference noise
Point.
By above-mentioned processing, grid element center point becomes P (x, y) ', other outer prisons of central point P (x, y) ' will be removed in grid W
Measured value forms new sequence, obtains new sequence B={ B (1), B (2), B (3), B (4), B (5), B (6), B (7), B (8) }, and by its
In each element and P (x, y) ' subtracted each other, all differences are taken absolute value to obtain
Dj=| B (j)-P (x, y) ' |
Wherein 1≤j≤8.Consider to consider the non-aircraft noise source that is not present around the fault-tolerance and center monitors point of algorithm, and
There are when non-aircraft noise source around the monitoring point of surrounding, the noise spot is impacted, and other 7 noise monitoring points and center are made an uproar
Sound monitoring point is then impacted smaller, and therefore, we are from DjIn select the smallest 4 values and constitute new one-dimensional matrix, can be with this
It removes by influencing noise spot on side.
D={ Di, wherein 1≤i≤4.
For monitoring grid W, if central point is interference noise point, the isolatism based on noise spot, 4 members in D
The value of element will be bigger；, whereas if central point is normal monitoring point, then the value of 4 in D element is smaller.In order to indicate
Degree of similarity between central point and neighbouring monitoring point, defines a new function T, is expressed as follows shown in formula:
Wherein: DiIndicate that the element in above-mentioned new matrix D, t are the threshold value for judging noise.If T < t, P (x, y) are positive
Normal monitoring point, otherwise P (x, y) is interference noise point, it is believed that the noise that the point monitors is not aircraft noise, in aviation
In device noise monitoring and treatment process, the monitor value of the point can be ignored, mark the noise figure by non-aircraft influence of noise.
Aircraft noise recognizer
Identical as non-aircraft noise filter algorithm, the identification of aircraft noise needs to calculate itself and week to each target monitoring point
Enclose the similarity of monitoring point.Since the coverage of aircraft noise is wider, between noise attentuation and noise monitoring point and noise source
The logarithm of distance is related, and aircraft noise source and monitoring point distance will not be too close, at least hundred meters of distance, therefore, mutually
The noise figure of the several noise monitoring points closed on is not much different, and will not be misidentified by non-aircraft noise filter algorithm.Meanwhile each prison
The distance of distance between measuring point and noise source, will affect the size on noise figure.W1={ iNW, P (x, y), iSE, W2={ iW,P
(x, y), iE, W3={ iSW, P (x, y), iNE, W4={ iN, P (x, y), iSIn, each monitoring point is due to its range noise source position
Distance, unless noise source just near P point or these monitoring points apart from aircraft noise source apart from too far, these monitoring points
The distance between the opposite distance to aircraft noise source it is too small, cause its noise figure to be all not much different；Otherwise W1, W2, W3, W4Sequence
Column will form increasing or decreasing sequence.According to the degree that noise figure in all directions increases or decreases, noise rise can be differentiated
Direction or the direction of noise source.Steps are as follows for specific algorithm:
Assuming that airport periphery monitoring point layout is the general meshed network of a M*N.For each, nearby there are noises
The mesh point of detection device calculates it non-aircraft noise and differentiates and filter algorithm, by filtered grid be set as matrix A=
[aij], (1≤i≤M, 1≤j≤N), wherein aijThe noise figure of corresponding mesh point.
When there are aircraft noise, the overlay area of aircraft noise is using aircraft noise source as the center of circle, and the radius of influence is in 1Km
Above border circular areas.The noise figure that monitoring point monitors in a wide range of all can be by the influence of aircraft noise, and its noise
The size of value relies primarily on monitoring point to the distance in aircraft noise source.Therefore we use matrixFor indicating each net
The corresponding noise rise vector of lattice point.
For each mesh point filtered in A, to the W of the 3*3 grid centered on it1, W2, W3, W4Sentenced
It is disconnected, if Wi(1≤i≤4) are an increasing or decreasing sequences, then mark its noise rise direction, otherwise do not mark to it
Note.To W1, W2, W3, W4Noise rise direction carry out addition of vectors,WhereinIt is WtNoise rise to
Amount.
Each noise rise vector is directed toward the degree of the same area in calculating matrix B:
((xi,yj)) indicate that the coordinate of the i-th row jth column mesh point, α indicate that apart from balance weight, mesh point distance (a, b) distance is remoter,
Weight is smaller, to indicate that it is directed toward the degree size of the same area, that is, the size that aircraft noise there is a possibility that.T is indicated
There are the threshold value of aircraft noise, i.e. T>t shows there are aircraft noise for it, and T<t shows that there is no aircraft noises.There are aviations to make an uproar
In the case where sound source, (a, b) is then the estimated location of floor projection where aircraft noise source.
The above, the only specific embodiment in the present invention, but scope of protection of the present invention is not limited thereto, appoints
What is familiar with the people of the technology within the technical scope disclosed by the invention, it will be appreciated that expects transforms or replaces, and should all cover
Within scope of the invention, therefore, the scope of protection of the invention shall be subject to the scope of protection specified in the patent claim.
Claims (3)
1. a kind of aircraft noise identification and non-aircraft noise filter method, which is characterized in that firstly, using a kind of non-aircraft noise
Filter method filters non-aircraft noise；Secondly, estimating the position in aircraft noise source using a kind of aircraft noise recognition methods；
A kind of non-aircraft noise filter method by target monitoring point and closes on the noise figure size between monitoring point, builds
Vertical noise monitoring grid, and calculate separately horizontal direction, vertical direction and two diagonally adjacent noise fluctuations situations；
Based on the isolatism of interference noise point, pretreatment is amplified to noise fluctuations situation, chooses most suitable direction and to the direction
Upper noise situations carry out similarity analysis, and the most suitable direction is that four sons concentrate the smallest that of standard deviation to organize corresponding side
To if similarity is lower than given threshold, there are the interference of non-aircraft noise, and operation is filtered to it, is not otherwise carried out to it
Filtering；
A kind of aircraft noise recognition methods calculates each mesh by entirely monitoring the noise figure of noise monitoring point in region
Mark monitoring point calculates its noise rise vector relative to closing on the noise figure difference of monitoring point；Calculate entire monitoring region prison
Measuring point noise rise vector arrives the inner product of the distance vector of the monitoring location with a bit, and finds out its maximum value and be used as and there is boat
Empty noise source there are degree size, degree size is greater than given threshold if it exists, then shows to monitor region that there are aircraft noises
Source, and the target monitoring point is then the estimated location of floor projection where aircraft noise source.
2. a kind of aircraft noise identification according to claim 1 and non-aircraft noise filter method, which is characterized in that target
Monitoring point constitutes 3 × 3 noise monitoring grids centered on target monitoring point with monitoring point is closed on.
3. a kind of aircraft noise identification according to claim 1 and non-aircraft noise filter method, which is characterized in that if prison
It surveys and lacks noise figure in region at certain monitoring point, then with the inverse distance-weighting mean value substitution of its nearest N number of spot noise figure, N is positive
Integer.
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| CN112179487A (en) * | 2020-11-17 | 2021-01-05 | 天津市生态环境监测中心 | Airport environment noise automatic detection system and monitoring method |
| CN113295265B (en) * | 2021-03-31 | 2022-06-14 | 国网河北省电力有限公司电力科学研究院 | Transformer noise detection method |
| CN113887590B (en) * | 2021-09-22 | 2023-06-09 | 中国电子科技集团公司第二十九研究所 | Target typical track and area analysis method |
| CN115326193B (en) * | 2022-10-12 | 2023-08-25 | 江苏泰洁检测技术股份有限公司 | Intelligent monitoring and evaluating method for factory operation environment |
| CN115638876B (en) * | 2022-12-14 | 2023-04-11 | 北京英视睿达科技股份有限公司 | Noise calculation method, device, equipment and storage medium based on high-density grid |
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| US4114135A (en) * | 1975-06-20 | 1978-09-12 | The United States Of America As Represented By The Secretary Of The Navy | Acoustic device |
| US20100079342A1 (en) * | 1999-03-05 | 2010-04-01 | Smith Alexander E | Multilateration enhancements for noise and operations management |
| US6885340B2 (en) * | 2000-02-29 | 2005-04-26 | Rannoch Corporation | Correlation of flight track data with other data sources |
| US7092853B2 (en) * | 2001-10-25 | 2006-08-15 | The Trustees Of Dartmouth College | Environmental noise monitoring system |
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