CN110907895A - Noise monitoring, identifying and positioning method and system and computer readable storage medium - Google Patents
Noise monitoring, identifying and positioning method and system and computer readable storage medium Download PDFInfo
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- CN110907895A CN110907895A CN201911234678.5A CN201911234678A CN110907895A CN 110907895 A CN110907895 A CN 110907895A CN 201911234678 A CN201911234678 A CN 201911234678A CN 110907895 A CN110907895 A CN 110907895A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
- G01S5/22—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
- G01S5/20—Position of source determined by a plurality of spaced direction-finders
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
- G01S5/30—Determining absolute distances from a plurality of spaced points of known location
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- Engineering & Computer Science (AREA)
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- Radar, Positioning & Navigation (AREA)
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- Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)
Abstract
The invention provides a noise monitoring, identifying and positioning method, a system and a computer readable storage medium, wherein the noise monitoring equipment arranged at different positions detects noise signals and transmission directions thereof, and detects initial time information of the noise signals; calculating the sound similarity between two groups of noise signals detected in the same time period; when the sound similarity reaches a set threshold value, determining that the sound similarity and the threshold value belong to the same noise source; determining a target space position corresponding to a noise source by combining the space positions of two noise monitoring devices which detect two groups of noise signals and the transmission directions of the two groups of noise signals by utilizing a triangulation positioning principle; the method realizes the quick identification and positioning of the noise source, is favorable for eliminating the noise influence in time, and avoids the influence on the work, study and life of people.
Description
Technical Field
The present invention relates to the field of noise monitoring technologies, and in particular, to a noise monitoring, identifying and positioning method and system, and a computer readable storage medium.
Background
Nowadays, society develops rapidly, and a lot of noises are inevitably generated in life. However, the noise cannot be found and reported at the first time, so that many people are seriously troubled by the noise in life, and the source of the noise cannot be found, thereby bringing great influence to the life of people.
In order to solve the problem, the scheme is combined with monitoring equipment arranged in an urban area, and a noise source and a noise type can be found at the first time so as to be reported in time and solve the noise problem.
Disclosure of Invention
The invention provides a noise monitoring, identifying and positioning method, a system and a computer readable storage medium, which mainly solve the technical problems that: how to implement noise identification localization.
In order to solve the above technical problem, the present invention provides a noise monitoring, identifying and positioning method, which comprises:
receiving noise signals detected by noise monitoring equipment arranged at different positions and transmission directions thereof, and detecting initial time information of the noise signals;
calculating the sound similarity between two groups of noise signals detected in the same time period;
when the sound similarity reaches a set threshold value, determining that the sound similarity and the threshold value belong to the same noise source;
and determining the target space position corresponding to the noise source by combining the space positions of two noise monitoring devices which detect the two groups of noise signals and the transmission directions of the two groups of noise signals by utilizing a triangulation positioning principle.
Optionally, the method further includes: and mapping the target space position to a map, and positioning and alarming the noise source.
Optionally, the method further includes determining a noise type of the noise source, and prompting the noise type of the noise source when performing a positioning alarm on the noise source.
Optionally, the determining the noise type of the noise source includes: and comparing the two groups of noise signals with various noises with different noise types in a noise library by utilizing a sound monitoring and matching application program interface to determine the noise type of the noise source.
Optionally, the determining the noise type of the noise source includes: and determining the noise type of the noise source by using a deep learning model, wherein the deep learning model is obtained by training and learning based on an AudioSet audio data set.
The invention also provides a noise monitoring, identifying and positioning system, which comprises:
the noise monitoring equipment is arranged at different positions and used for detecting noise signals and the transmission direction thereof and recording the initial time information of the detected noise signals; sending the noise signal, the transmission direction of the noise signal and the initial time information of the noise signal to a noise analysis server;
the noise analysis server is used for receiving the noise signal and the transmission direction thereof as well as the starting time information of the noise signal; calculating the sound similarity between two groups of noise signals detected in the same time period; when the sound similarity reaches a set threshold value, determining that the sound similarity and the threshold value belong to the same noise source; and determining the target space position corresponding to the noise source by combining the space positions of two noise monitoring devices which detect the two groups of noise signals and the transmission directions of the two groups of noise signals by utilizing a triangulation positioning principle.
Optionally, the noise monitoring device includes eight noise receivers, and the noise receivers are respectively and evenly arranged on eight directions on the horizontal plane of the noise monitoring device at intervals.
Optionally, the noise analysis server is further configured to map the target spatial position onto a map, and perform positioning alarm to a background monitoring center for the noise source.
Optionally, the noise analysis server is further configured to determine a noise type of the noise source, and prompt the noise type of the noise source when the positioning alarm is performed on the noise source.
The present invention also provides a computer readable storage medium having one or more programs stored thereon that are executable by one or more processors to perform the steps of the noise monitoring, identifying and locating method as described above.
The invention has the beneficial effects that:
according to the noise monitoring, identifying and positioning method, system and computer readable storage medium provided by the invention, the noise signals detected by noise monitoring equipment arranged at different positions and the transmission directions thereof are received, and the initial time information of the noise signals is detected; calculating the sound similarity between two groups of noise signals detected in the same time period; when the sound similarity reaches a set threshold value, determining that the sound similarity and the threshold value belong to the same noise source; determining a target space position corresponding to a noise source by combining the space positions of two noise monitoring devices which detect two groups of noise signals and the transmission directions of the two groups of noise signals by utilizing a triangulation positioning principle; the method realizes the quick identification and positioning of the noise source, is favorable for eliminating the noise influence in time, and avoids the influence on the work, study and life of people.
Drawings
Fig. 1 is a schematic flow chart of a noise monitoring, identifying and positioning method according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of a noise receiver of a noise monitoring device according to a first embodiment of the present invention;
FIG. 3 is a schematic view of triangulation according to a first embodiment of the present invention;
fig. 4 is a schematic structural diagram of a noise monitoring, identifying and positioning system according to a second embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following detailed description and accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The first embodiment is as follows:
in order to realize quick identification and positioning of urban noise, improve law enforcement efficiency and practically guarantee the benefits of civilians, the embodiment of the invention provides a noise monitoring, identification and positioning method.
Referring to fig. 1, the method mainly includes the following steps:
s101, receiving noise signals detected by noise monitoring equipment arranged at different positions and transmission directions thereof, and detecting initial time information of the noise signals.
Urban resident living residential areas, school areas, comprehensive office areas and the like belong to urban noise forbidden areas so as to practically guarantee the normal living, working and learning environment requirements of people in the residential areas. Noise monitoring devices are arranged at different positions in the residential areas, and the noise monitoring devices with different densities can be flexibly erected according to the severity of noise pollution. Aiming at the noise pollution serious disaster area, a larger number of noise monitoring devices can be arranged; for the region with occasional noise pollution, a certain number of noise monitoring devices can be arranged.
A noise monitoring device includes a plurality of noise receivers, see fig. 2, for example, eight noise receivers, which are uniformly spaced in eight directions on a horizontal plane of the noise monitoring device, namely, eight directions, namely, true south, true north, true west, true east, west north, east, and south east.
In this embodiment, the direction indicated by the noise receiver with the highest sound intensity may be selected as the transmission direction of the noise. Of course, other existing ways of detecting the noise transmission direction may be fully employed. Optionally, the transmission direction may also be verified by using the time of reception of the noise, and the receiver with the highest sound intensity usually receives the noise signal at the earliest.
S102, aiming at two groups of noise signals detected in the same time period, the sound similarity between the two groups of noise signals is calculated.
The same noise source may be monitored by a plurality of noise monitoring devices nearby at the same time, and in this embodiment, for the noise signals detected by each noise monitoring device within the set range, if two or more sets of noise signals exist in the same time period, the sound similarity between every two sets of noise signals is calculated. The method for calculating the sound similarity may adopt any existing method, which is not limited in this embodiment.
It should be noted that the same time period is not the same as the start time and the end time, as long as the detection times of the two sets of noise signals at least partially overlap, and of course, the complete overlap can be regarded as the same time period.
In this embodiment, the collected noise time duration may be predefined, for example, 10 seconds, 20 seconds, one minute, and the like. The method avoids the problem that the duration of some noise sources is too long and the noise sources possibly overlap with other noise sources in time, so that the system needs to perform identification processing on whether the noise sources are the same noise source for multiple times.
And S103, when the sound similarity reaches a set threshold value, determining that the sound similarity and the noise similarity belong to the same noise source.
The set threshold value can be flexibly set according to the actual situation.
Optionally, the noise signals detected by the Monitoring devices at the same time interval are subjected to Sound filtering and noise reduction by using Sound Monitoring and matching Application Program Interface (API), and Sound similarity calculation is performed, and when the similarity is higher than 90%, the noise signals are regarded as the same noise source.
And S104, determining the target space position corresponding to the noise source by combining the space positions of the two noise monitoring devices which detect the two groups of noise signals and the transmission directions of the two groups of noise signals by utilizing a triangulation positioning principle.
Referring to fig. 3, the spatial coordinate positions of the noise monitoring device B and the noise monitoring device C are known and can be marked on the map in advance, so that the distance a between the two is clear; for the same noise source, the noise monitoring device B can detect the transmission direction relative to itself
The noise monitoring device C can detect the transmission direction relative to itself
Based on the direction of transmission
And
angle ∠ B between, direction of travel
And
the included angle ∠ C between them, and the distance a between the noise monitoring device B and the noise monitoring device C, are according to the following formula (1):
the target spatial position a of the noise source can be calculated.
In other embodiments of the invention, in order to facilitate the urban management law enforcement officers to accurately find the noise source and process the noise source in time, the system can map the target space position to a map and perform positioning and alarming on the noise source.
Optionally, the method further comprises determining a noise type of the noise source, and prompting the noise type of the noise source when the positioning alarm is performed on the noise source.
Wherein determining the noise type of the noise source comprises: and comparing the noise signal with various noises of different noise types in a noise library by utilizing a sound monitoring and matching application program interface to determine the noise type of the noise source.
Optionally, the noise type of the noise source is determined by using a deep learning model, wherein the deep learning model can be obtained by training and learning based on an AudioSet audio data.
According to the noise monitoring, identifying and positioning method provided by the invention, the noise signals detected by noise monitoring equipment arranged at different positions and the transmission directions thereof are received, and the initial time information of the noise signals is detected; calculating the sound similarity between two groups of noise signals detected in the same time period; when the sound similarity reaches a set threshold value, determining that the sound similarity and the threshold value belong to the same noise source; determining a target space position corresponding to a noise source by combining the space positions of two noise monitoring devices which detect two groups of noise signals and the transmission directions of the two groups of noise signals by utilizing a triangulation positioning principle; the method realizes the quick identification and positioning of the noise source, is favorable for eliminating the noise influence in time, and avoids the influence on the work, study and life of people.
Example two:
in this embodiment, on the basis of the first embodiment, a noise monitoring, identifying and positioning system is provided, which is mainly used for implementing the steps of the noise monitoring, identifying and positioning method in the first embodiment, please refer to fig. 4, and the system mainly includes:
a plurality of noise monitoring devices 41 disposed at different positions for detecting a noise signal and a transmission direction thereof, and recording start time information of the detected noise signal; and transmitting the noise signal and the transmission direction thereof, and the start time information of the noise signal to the noise analysis server.
Optionally, the noise monitoring device 41 includes eight noise receivers, which are respectively and evenly spaced in eight directions on the horizontal plane of the noise monitoring device.
A noise analysis server 42 for receiving the noise signal and its transmission direction, and the start time information of the noise signal; calculating the sound similarity between two groups of noise signals detected in the same time period; when the sound similarity reaches a set threshold value, determining that the sound similarity and the threshold value belong to the same noise source; and determining the target space position corresponding to the noise source by combining the space positions of two noise monitoring devices which detect the two groups of noise signals and the transmission directions of the two groups of noise signals by utilizing the triangulation positioning principle.
The noise analysis server 42 is also used for mapping the target space position on a map and performing positioning alarm to a background monitoring center aiming at the noise source.
Optionally, the noise analysis server 42 is further configured to determine a noise type of the noise source, and prompt the noise type of the noise source when a positioning alarm is performed on the noise source.
Wherein determining the noise type of the noise source comprises: and comparing the noise signal with various noises of different noise types in a noise library by utilizing a sound monitoring and matching application program interface to determine the noise type of the noise source.
Optionally, the noise type of the noise source is determined by using a deep learning model, wherein the deep learning model can be obtained by training and learning based on an AudioSet audio data.
The present embodiments also provide a computer readable storage medium storing one or more programs, which are executable by one or more processors to implement the steps of the noise monitoring, identifying and locating method as described in the first embodiment. For details, please refer to the description in the first embodiment, which is not repeated herein.
It will be apparent to those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and optionally they may be implemented in program code executable by a computing device, such that they may be stored on a computer storage medium (ROM/RAM, magnetic disks, optical disks) and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The foregoing is a more detailed description of the present invention that is presented in conjunction with specific embodiments, and the practice of the invention is not to be considered limited to those descriptions. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (10)
1. A noise monitoring, identifying and positioning method is characterized by comprising the following steps:
receiving noise signals detected by noise monitoring equipment arranged at different positions and transmission directions thereof, and detecting initial time information of the noise signals;
calculating the sound similarity between two groups of noise signals detected in the same time period;
when the sound similarity reaches a set threshold value, determining that the sound similarity and the threshold value belong to the same noise source;
and determining the target space position corresponding to the noise source by combining the space positions of two noise monitoring devices which detect the two groups of noise signals and the transmission directions of the two groups of noise signals by utilizing a triangulation positioning principle.
2. The noise monitoring, identifying and locating method of claim 1, further comprising: and mapping the target space position to a map, and positioning and alarming the noise source.
3. The noise monitoring, identifying and locating method according to claim 2, further comprising determining a noise type of the noise source and prompting the noise type of the noise source when a location alarm is made for the noise source.
4. The noise monitoring, identifying and locating method of claim 3, wherein said determining the noise type of the noise source comprises: and comparing the two groups of noise signals with various noises with different noise types in a noise library by utilizing a sound monitoring and matching application program interface to determine the noise type of the noise source.
5. The noise monitoring, identifying and locating method of claim 3, wherein said determining the noise type of the noise source comprises: and determining the noise type of the noise source by using a deep learning model, wherein the deep learning model is obtained by training and learning based on an AudioSet audio data set.
6. A noise monitoring, identification and location system, comprising:
the noise monitoring equipment is arranged at different positions and used for detecting noise signals and the transmission direction thereof and recording the initial time information of the detected noise signals; sending the noise signal, the transmission direction of the noise signal and the initial time information of the noise signal to a noise analysis server;
the noise analysis server is used for receiving the noise signal and the transmission direction thereof as well as the starting time information of the noise signal; calculating the sound similarity between two groups of noise signals detected in the same time period; when the sound similarity reaches a set threshold value, determining that the sound similarity and the threshold value belong to the same noise source; and determining the target space position corresponding to the noise source by combining the space positions of two noise monitoring devices which detect the two groups of noise signals and the transmission directions of the two groups of noise signals by utilizing a triangulation positioning principle.
7. The noise-monitoring, identification and location system of claim 6 wherein the noise-monitoring device includes eight noise receivers, each of which is evenly spaced in eight directions above the horizontal plane of the noise-monitoring device.
8. The noise monitoring, identifying and positioning system of claim 6, wherein the noise analysis server is further configured to map the target spatial location onto a map and perform a positioning alarm to a background monitoring center for the noise source.
9. The noise monitoring, identifying and locating system of claim 7, wherein the noise analysis server is further configured to determine a noise type of the noise source and prompt the noise type of the noise source when a location alarm is performed for the noise source.
10. A computer readable storage medium, having one or more programs stored thereon which are executable by one or more processors to perform the steps of the noise monitoring, identifying and locating method of any one of claims 1 to 5.
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| CN111829771A (en) * | 2020-07-27 | 2020-10-27 | 盐城工学院 | Electromagnetic valve noise monitoring system and method for electro-hydraulic composite braking system |
| CN112098939A (en) * | 2020-09-18 | 2020-12-18 | 广东电网有限责任公司电力科学研究院 | Method and device for identifying and evaluating noise pollution source |
| CN112420077A (en) * | 2020-11-19 | 2021-02-26 | 展讯通信（上海）有限公司 | Sound positioning method and device, testing method and system, equipment and storage medium |
| CN113267249A (en) * | 2021-05-12 | 2021-08-17 | 杭州仁牧科技有限公司 | Multi-channel noise analysis system and analysis method based on big data |
| CN114509162A (en) * | 2022-04-18 | 2022-05-17 | 四川三元环境治理股份有限公司 | Sound environment data monitoring method and system |
| CN115273850A (en) * | 2022-09-28 | 2022-11-01 | 科大讯飞股份有限公司 | Autonomous mobile equipment voice control method and system |
| CN117935789A (en) * | 2024-01-17 | 2024-04-26 | 联通(广东)产业互联网有限公司 | Speech recognition method, system, equipment and storage medium |
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| CN111829771A (en) * | 2020-07-27 | 2020-10-27 | 盐城工学院 | Electromagnetic valve noise monitoring system and method for electro-hydraulic composite braking system |
| CN112098939A (en) * | 2020-09-18 | 2020-12-18 | 广东电网有限责任公司电力科学研究院 | Method and device for identifying and evaluating noise pollution source |
| CN112098939B (en) * | 2020-09-18 | 2021-09-24 | 广东电网有限责任公司电力科学研究院 | Method and device for identifying and evaluating noise pollution source |
| CN112420077A (en) * | 2020-11-19 | 2021-02-26 | 展讯通信（上海）有限公司 | Sound positioning method and device, testing method and system, equipment and storage medium |
| CN112420077B (en) * | 2020-11-19 | 2022-08-16 | 展讯通信（上海）有限公司 | Sound positioning method and device, testing method and system, equipment and storage medium |
| CN113267249A (en) * | 2021-05-12 | 2021-08-17 | 杭州仁牧科技有限公司 | Multi-channel noise analysis system and analysis method based on big data |
| CN114509162A (en) * | 2022-04-18 | 2022-05-17 | 四川三元环境治理股份有限公司 | Sound environment data monitoring method and system |
| CN114509162B (en) * | 2022-04-18 | 2022-06-21 | 四川三元环境治理股份有限公司 | Sound environment data monitoring method and system |
| CN115273850A (en) * | 2022-09-28 | 2022-11-01 | 科大讯飞股份有限公司 | Autonomous mobile equipment voice control method and system |
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