Automatic detection system and monitoring method for airport environmental noise

Abstract

The present invention discloses an automatic detection system and monitoring method for airport environmental noise. An acoustic sensor and a vector determination module, a noise feature extraction and discrimination module, a monitoring and recording module, a meteorological collection unit, etc. are connected in parallel, and then connected to a main control computer through a bus to form a noise detection system. M×N acoustic sensors and vector determination modules with uniform grid arrays are arranged on both sides of the airport runway, and the take-off or landing state of the aircraft is discriminated according to the feedback sound field signal changes. The noise intensity distribution within the detection time period is obtained by noise feature extraction and discrimination, and the attenuation characteristics, direction, experience time, and model characteristics of the noise source in the monitoring area are obtained and recorded at the same time. The radar signal collector in the monitoring and recording module is used to quantitatively judge the aircraft model and flight status. The detection results are calculated and analyzed by the main control computer, and the airport environmental noise data information is sent in real time. The adopted technical method can be transplanted to the high-speed rail line to implement noise monitoring in specific areas.

Description

Technical Field

[0001] The invention belongs to the field of environmental protection noise monitoring, and mainly relates to an automatic identification and monitoring technology for airport environmental noise. Background Art

[0002] As people's requirements for quality of life and physical and mental health are increasing day by day, with the rapid development of air transportation and high-speed railways, the noise brought by these transportation tools has also become an invisible killer, which has caused varying degrees of impact on people's mental state of work and life. Therefore, noise has been listed as one of the public hazards that pollute the environment internationally. In particular, the reconstruction and expansion of airports in recent years have further increased the number of runways, aggravating the pollution of the noise environment and the corresponding governance issues. As the impact of noise becomes increasingly prominent, group complaints around airports are also increasing. How to strengthen the monitoring and control of aircraft noise has become an international issue.

[0003] At present, most aircraft noise monitoring technologies are manual monitoring, which requires 24-hour manual monitoring, flight status judgment and data recording. In addition to excessive physical burden, the resulting problems also cause data omissions. At the same time, the monitoring time is long and the amount of data processing is large. The data obtained in a short time is difficult to accurately reflect the airport's full-time noise emissions. Therefore, automatic monitoring of airport environmental noise has become a current difficulty and focus issue. Summary of the invention

[0004] The purpose of the present invention is to propose an automatic aircraft noise monitoring system to address the defects in the current airport environmental noise monitoring, which can obtain airport noise data in real time and facilitate the development of monitoring work.

[0005] The technical solution adopted to achieve the purpose of the present invention is: an automatic detection system and monitoring method for airport environmental noise. The system includes: an acoustic sensor and vector determination module, a noise feature extraction and discrimination module, a monitoring and recording module, a meteorological collection unit, a storage module, a transmission module, a power supply unit, a main control computer, a sound source array receiver, a radar signal collector, a solar photovoltaic panel and a battery, and a noise analyzer. Its composition scheme is: the acoustic sensor and vector determination module is connected to the Internet of Things; the noise feature extraction and discrimination module is connected to the sound source array receiver and the radar signal collector; the meteorological collection unit is connected to the precipitation detection device and the wind direction monitoring device. Among them: the acoustic sensor and vector determination module, the noise feature extraction and discrimination module, the monitoring and recording module, the meteorological collection unit, the storage module, and the power supply unit are connected in parallel, and then connected to the main control computer through the bus and the transmission module to form a noise detection system. The power supply unit supplies power to all devices. The noise monitoring method is as follows:

[0006] (1) In the monitoring area on both sides of the airport runway, M×N acoustic sensors and vector judgment modules are arranged in a uniform grid array to detect the noise and direction at the locations of the acoustic sensors and vector judgment modules. The take-off or landing status of the aircraft is judged according to the feedback of the sound field signal changes, and the monitoring area is determined; the noise spectrum, intensity and sound source attenuation direction within the set detection time period at the locations of the N acoustic sensors and vector judgment modules are obtained through the noise feature extraction and judgment module.

[0007] (2) Based on the noise spectrum, intensity and sound source attenuation direction, the monitoring and recording module obtains and records the noise source intensity, attenuation characteristics, direction and elapsed time in the monitoring area, and then uses the radar signal collector in the monitoring and recording module to quantitatively determine the aircraft model and flight status.

[0008] (3) The meteorological data collection unit obtains the airport's wind speed, wind direction and precipitation data in real time as meteorological condition data for airport noise detection.

[0009] The data transmitted by the acoustic sensor and vector determination module, as well as the noise feature extraction and discrimination module, are used to determine whether the noise source is aircraft noise. The judgment result is used as a new signal directional recognition, and the monitoring and recording module and meteorological condition data information are simultaneously collected and pushed to the main control computer in real time. The main control computer calculates and analyzes the data and sends the airport environmental noise data information in real time.

[0010] The present invention combines three methods, namely, grid point distribution method, sound source identification and radar signal analysis, to perform the work of distinguishing the true from the false in aircraft flight events.

[0011] When the single grid method is used to determine aircraft noise events, the interference caused by the surrounding mobile noise sources may lead to misjudgment of flight events. For example, the traffic noise generated by the passage of vehicles may be considered as a flight event, and the time-series sound sources that occur accidentally in different grid points may also be considered as flight events. In order to more accurately record flight events, the present invention proposes this monitoring point layout method, adds sound source identification and radar analysis devices to achieve the true and false identification of flight events and accurate collection of monitoring data.

[0012] The innovation of the invention is reflected in:

[0013] 1. Use the grid method to realize the fuzzy capture of aircraft noise events, preliminarily determine the important nodes for noise monitoring and early warning based on the fuzzy capture results, and set noise monitoring instruments or sound source identification devices at the node locations.

[0014] The implemented device is: the acoustic sensor and vector determination module have 5G communication function, and the main control module is the main control computer.

[0015] 2. Use the sound source identification device to capture aircraft noise events, combine the aircraft heading and grid method fuzzy judgment results, remotely start the noise monitoring equipment, and capture noise data.

[0016] The device implemented is: a noise feature extraction and discrimination module (composed of multiple sound source array receiving devices), and the main control module is still the main control computer.

[0017] 3. Utilizing the working mode of transmitting radar signals between the aircraft and the tower, the sound source identification device is equipped with a built-in radar signal receiving device to collect information such as the aircraft model and number, thereby realizing the rapid recording of basic aircraft information.

[0018] The implemented device is: noise feature extraction and discrimination module.

[0019] 4. Utilize the fuzzy capture function of the grid method, integrate the sound source identification and radar signal analysis functions, and realize efficient, real-time and accurate capture of aircraft noise events within the airspace of the airport runway and its extension line; when the airport adjusts the take-off and landing runways due to the influence of wind direction, remotely and dynamically start the noise monitor, adjust the position of the monitoring point, and capture data in real time.

[0020] The device is composed of a noise feature extraction and discrimination module and multiple sound source array receiving devices, and also includes a main control computer and a monitoring and recording module (multiple noise analyzers).

[0021] The main points of the invention are also reflected in:

[0022] The acoustic sensor and vector determination module, noise feature extraction and discrimination module obtain feature vectors by densely sampling points in the monitoring area, and determine the location of the monitoring point based on the feature vector results. The acoustic sensor grid point method is combined with the sound source array identification method and radar signal analysis method to achieve quantitative judgment of airport environmental noise.

[0023] According to the detection data of the acoustic sensor and vector judgment module and the acoustic feature extraction and discrimination module, the logical judgment results are used as new signal directional identification, and the data information of each module is dynamically captured, which saves work space and improves work efficiency.

[0024] The transmission module adopts 5G technology to transmit collected data to the terminal device in real time, facilitating timely data analysis and correction of deviant data.

[0025] Solar photovoltaic panels and batteries are used as system power sources to reduce wiring difficulties and improve layout efficiency.

[0026] Adopting flash memory storage technology, it can realize the functions of ultra-large data storage, quick access and data rolling overwrite.

[0027] The characteristics and beneficial effects of the present invention are: large amount of data collection, covering both sides of the airport runway, and this area is the main source of airport environmental noise. The acoustic sensor and vector determination module, the noise feature extraction and discrimination module obtain the feature vector through detection and analysis to accurately determine the location area of ​​the monitoring point. The present invention combines the sound source array recognition method, radar signal analysis, etc., can obtain noise data 24 hours a day, obtain quantitative data information of airport environmental noise, and publish it in time. At the same time, the technical method adopted by the present invention can be transplanted to the high-speed railway line to implement noise monitoring in specific areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 Shown is a system diagram of the logical connection structure of each component of the invention. DETAILED DESCRIPTION

[0029] The system and detection method of the present invention are further described below with reference to the accompanying drawings and examples.

[0030] The automatic detection system and monitoring method of airport environmental noise include: an acoustic sensor and vector determination module 1, a noise feature extraction and discrimination module 2, a monitoring and recording module 3, a meteorological collection unit 4, a storage module 5, a power supply unit 6, a transmission module 7, a main control computer 8, a sound source array receiver 9, a radar signal collector 10, a solar photovoltaic panel and a battery, and a noise analyzer. Among them: the acoustic sensor and vector determination module is connected to the Internet of Things 11; the noise feature extraction and discrimination module is connected to the sound source array receiver and the radar signal collector; the meteorological collection unit is connected to the precipitation detection device 12 and the wind direction monitoring device 13. Its composition structure is: the acoustic sensor and vector determination module, the noise feature extraction and discrimination module, the monitoring and recording module, the meteorological collection unit, the storage module, and the power supply unit are connected in parallel, and then connected to the main control computer through the bus and the transmission module to form a noise detection system, and the power supply unit supplies power to all devices. The monitoring method is as follows:

[0031] (1) In the monitoring area on both sides of the airport runway, M×N acoustic sensors and vector judgment modules are arranged in a uniform grid array to detect the noise and direction at the locations of the acoustic sensors and vector judgment modules, and the take-off or landing status of the aircraft is judged according to the feedback of the sound field signal changes; the noise intensity distribution within the set detection time period at the locations of the N acoustic sensors and vector judgment modules is obtained through the noise feature extraction and judgment module.

[0032] (2) Based on the frequency spectrum of the noise intensity distribution, the monitoring and recording module obtains and records the attenuation characteristics, direction, experience time, and aircraft type characteristics of the noise source in the monitoring area, and then uses the radar signal collector in the monitoring and recording module to quantitatively determine the aircraft type and flight status.

[0033] (3) The meteorological data collection unit obtains the airport's wind speed, wind direction, and precipitation data in real time as meteorological condition data for airport noise detection.

[0034] The data transmitted by the acoustic sensor and vector determination module, and the noise feature extraction and discrimination module are used to determine whether the noise source is aircraft noise. The judgment result is used as a new signal directional identification. The monitoring and recording module and meteorological condition data information are simultaneously collected and pushed to the main control computer in real time. The main control computer calculates and analyzes and sends the airport environmental noise data information in real time.

[0035] M×N uniform grid arrays, where M is the number of rows and N is the number of columns, each acoustic sensor and vector determination module has its own number according to the distribution points in the monitoring area.

[0036] The monitoring and recording module contains a noise analyzer with 5G function, which can continuously record noise detection data for one week.

[0037] The transmission module incorporates 5G transmission speed, and transmits collected data in real time for timely data analysis and correction of deviated data.

[0038] The power supply unit uses solar photovoltaic panels and batteries as the power supply of the noise detection system. The detection system also has an external power supply. The battery is a 12V or 24V lead-acid battery, which can be used in combination as needed.

[0039] The storage module uses flash memory technology to store and access excessive data in real time.

[0040] The acoustic sensor and vector determination module is responsible for determining the location of the aircraft noise monitoring point and the prediction of flight events. As an example, within 5 kilometers on both sides of the airport runway and 1 kilometer within the vertical channel, there are 10×10 uniform grid arrays, that is, the number of rows is 10; the number of columns is 10. The collected noise information is filtered, and the sound information with a decibel value lower than the set value is filtered out, and the sound information with a decibel value higher than the set value is regarded as aircraft noise. The effective sound information is collected to determine the sound level time vector.

[0041] The noise feature extraction and discrimination module uses a multi-microphone sound source array method to deploy the sound source array equipment at the aircraft noise monitoring point and set the detection time period in advance. One or more noise feature extraction and discrimination module devices equipped with radar signal analysis can be deployed to realize the recognition of sound source spectrum and aircraft flight information (take-off or landing flight status), experience time and model characteristics, and combine the results of the acoustic sensor module and the vector discrimination module to determine whether the flight event is established.

[0042] The monitoring and recording module places the sound data collector or noise analyzer at the predetermined point to continuously record the noise data and is equipped with short-term (one week) storage and review functions.

[0043] The transmission modules all adopt the Internet of Things and 5G technologies to realize real-time data interaction between the main control computer and sensors, noise analyzers and sound source array identification systems.

[0044] The main control computer is a processor that compares the vector with the characteristic vector of the experimental monitoring phase, identifies the aircraft event, and transmits the logical judgment results to each monitoring module to dynamically retrieve data.

[0045] The noise feature extraction and discrimination module is composed of a digital signal processing integrated circuit and a field programmable gate array integrated circuit, wherein the model of the digital signal processing integrated circuit is DSP TMS320F2812PGFA, the digital signal processing integrated circuit and the field programmable gate array integrated circuit are connected, the asynchronous serial port of the processor is electrically connected to the synchronous serial port of the digital signal processing integrated circuit, and the digital signal processing integrated circuit is also provided with multiple peripheral interfaces such as a clock pulse, a reset port, an expansion interface, and a flash memory interface.

[0046] The steps are as follows:

[0047] (1) By densely sampling sensors in the monitoring area, characteristic vectors are obtained through analysis, and the location of the monitoring points is determined based on the characteristic vector results;

[0048] (2) Determine the vector feature index, form a feature vector, and record the feature vector to the discrimination module for later detection of aircraft take-off and landing status;

[0049] (3) According to the monitoring point locations determined in step (1), sound source identification equipment is installed in the take-off and landing directions to collect aircraft flight radar signals and aircraft noise at the same time. The characteristic spectrum of the aircraft noise is collected and analyzed through array technology to obtain characteristic spectrum data and flight direction arrays, which are used as the discrimination conditions for determining whether an aircraft noise event has occurred.

[0050] (4) The feature vector described in step (1) and the judgment condition described in step (2) are transmitted to the background computing system, the logical judgment result is used as the new signal for directional identification, and the data information of each module is collected synchronously.

[0051] (5) Analyze monitoring data in real time and publish corresponding results.

[0052] Wherein step (1) comprises the following process:

[0053] ① Collect the acoustic sensor information of the grid point method for a period of time without interference from other sound sources;

[0054] ② Filter the sound information, filter out the sound information with decibel value lower than the set value, and retain the sound information with decibel value higher than the set value as aircraft noise;

[0055] ③ Combined with the Internet of Things technology, the sensor data and sensor location information are uploaded to the main control computer, and a noise map using the grid point method is drawn. After calculation and analysis, the main noise propagation vector is obtained to determine the location of the monitoring point.

[0056] The sound source array recognition system in step (3) is used to automatically identify the flight status of the aircraft and transmit it to the main control computer to assist in determining the flight status of the aircraft taking off or about to land, and whether the aircraft event is true.

[0057] Step (3) also includes the following process:

[0058] ① Using the monitoring point locations measured in step (1), deploy a sound source array identification instrument on the runway on the take-off and landing sides of the aircraft;

[0059] ② Identify the noise source through the sound source array recognition device to assist in determining whether the aircraft event is true and the characteristics of the sound source.

[0060] Step (4) is implemented by using digital signal processing integrated circuits and field programmable gate array integrated circuits. Grid point distribution, sound source array identification method and radar signal analysis technology are used to comprehensively judge whether the aircraft event is true. If true, the monitoring data information in each module is collected and uploaded to the main control computer for calculation, and the quantitative data information of the airport environmental noise is obtained and published in a timely manner.

[0061] This embodiment cannot be considered to limit the scope of implementation of the present invention. All changes and improvements made within the technical features of the present invention should fall within the scope of the present invention.

Claims

1. Monitoring method of the airport environmental noise automatic detection system, the system comprising: The invention relates to an acoustic sensor and vector determination module (1), a noise feature extraction and discrimination module (2), a monitoring and recording module (3), a meteorological collection unit (4), a storage module (5), a power supply unit (6), a transmission module (7), a main control computer (8), a sound source array receiver (9), a radar signal collector (10), a solar photovoltaic panel and a storage battery, and a noise analyzer. The invention is characterized in that the acoustic sensor and vector determination module is connected to an Internet of Things (11); the noise feature extraction and discrimination module is connected to a sound source array receiver and a radar signal collector; the meteorological collection unit is connected to a precipitation detection device (12) and a wind direction monitoring device (13), wherein the acoustic sensor and vector determination module, the noise feature extraction and discrimination module, the monitoring and recording module, the meteorological collection unit, the storage module, and the power supply unit are connected in parallel and then connected to the main control computer through a bus and the transmission module to form a noise detection system. The power supply unit supplies power to all devices. The noise monitoring method is as follows: (1) In the monitoring area on both sides of the airport runway, M×N acoustic sensors and vector determination modules are arranged in a uniform grid array to detect the noise and direction at the locations of the acoustic sensors and vector determination modules, and the take-off or landing state of the aircraft is judged according to the feedback sound field signal changes to determine the monitoring area; the noise spectrum, intensity and sound source attenuation direction within the detection time period set at the locations of the N acoustic sensors and vector determination modules are obtained through the noise feature extraction and discrimination module; (2) Based on the noise spectrum, intensity and sound source attenuation direction, the monitoring and recording module obtains and records the noise source intensity, attenuation characteristics, direction and elapsed time in the monitoring area, and then uses the radar signal collector in the monitoring and recording module to quantitatively determine the aircraft model and flight status; (3) The meteorological data collection unit obtains the airport's wind speed, wind direction and precipitation data in real time as meteorological condition data for airport noise detection; The data transmitted by the acoustic sensor and vector determination module, as well as the noise feature extraction and discrimination module, are used to determine whether the noise source is aircraft noise. The judgment result is used as a new signal directional recognition, and the monitoring and recording module and meteorological condition data information are simultaneously collected and pushed to the main control computer in real time. The main control computer calculates and analyzes the data and sends the airport environmental noise data information in real time.

2. The monitoring method of the airport environmental noise automatic detection system according to claim 1 is characterized by: The M×N uniform grid arrays, where M is the number of rows and N is the number of columns, each acoustic sensor and vector determination module is provided with its own number according to the distribution points in the monitoring area.

3. The monitoring method of the airport environmental noise automatic detection system according to claim 1 is characterized by: The monitoring and recording module includes a noise analyzer with 5G function, and the monitoring and recording module can continuously record noise detection data for one week.

4. The monitoring method of the airport environmental noise automatic detection system according to claim 1 is characterized by: The transmission module incorporates 5G transmission speed and transmits collected data in real time for timely analysis of data and correction of deviated data.

5. The monitoring method of the airport environmental noise automatic detection system according to claim 1 is characterized by: The power supply unit adopts solar photovoltaic panels and batteries as the power supply of the noise detection system, and the detection system is also equipped with an external power supply.

6. The monitoring method of the airport environmental noise automatic detection system according to claim 1 is characterized by: The storage module adopts flash memory technology to access excess data in real time.

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