A grid-based noise monitoring system for sound source localization based on WSN technology

Abstract

This invention proposes a gridded noise monitoring system for sound source localization based on WSN technology, addressing the technical problems of high hardware cost, limited application, and susceptibility to interference in existing sound source localization methods. The invention includes multiple wireless noise sensor nodes arranged in a grid, all communicatively connected to a convergence node, which in turn connects to a remote server. This invention utilizes wireless sensor network technology for the gridded layout of the wireless noise sensor nodes, enabling the monitoring of noise sources over a wide area. Furthermore, the localization method is simple, requiring no complex algorithm calculations; only the convergence node needs to interface with the remote server, reducing the load on the remote server; and in addition to sound source localization, it can also calculate the path of moving noise.

Description

Technical Field

[0001] This invention relates to the technical field of noise monitoring, and in particular to a gridded noise monitoring system based on WSN technology for sound source localization. Background Technology

[0002] In the field of noise monitoring, sound source localization is an important function, mainly used for fault diagnosis of mechanical systems, abnormal noise location, status monitoring of power equipment, and leak detection in chemical plant pipelines. Currently, sound source localization is achieved by using a microphone array to pick up sound signals. By analyzing and processing the received output information from each channel, and combining algorithms such as controllable beamforming localization algorithms based on maximum output power, high-resolution spectrum estimation localization algorithms, and time delay difference of arrival estimation localization algorithms, the location information of one or more sound sources can be obtained. This method of sound source localization has drawbacks such as short localization distance (sound sources will refract beyond a certain range) (150 meters), high cost, and high sensitivity to the surrounding environment.

[0003] With the development of noise monitoring technology, especially in the field of sound source localization, it has become increasingly important. Major application areas include fault point monitoring in ships, vehicles, and chemical plant pipelines, as well as security systems, teleconferencing, smart homes, navigation, and related cinema systems.

[0004] Currently, the main principle of sound source localization is based on collecting sound signals using a certain number of microphone arrays, processing them using relevant localization algorithms, and then determining the location of the sound source. The microphone arrays are integrated onto a substrate or camera, and their arrangement includes linear, circular, spherical, and spiral arrays. Various localization algorithms exist, but are not limited to, TDOA (Time Delay of Arrival), controlled beamforming, and high-resolution spectral estimation. This microphone array-based sound source localization technology is characterized by high hardware costs, significant limitations, susceptibility to interference, and short localization distance.

[0005] Wireless Sensor Networks (WSNs) are distributed sensor networks composed of multiple sensor nodes (including aggregation nodes and individual sensor nodes) that communicate wirelessly to form a network. The network configuration is flexible and can form multi-hop self-organizing networks. WSN networks are characterized by their large scale, self-organization, and dynamism. They have a wide range of applications, including military, healthcare, and environmental monitoring.

[0006] Existing patents for wireless noise monitoring systems are relatively simple and are only applied to simple, specific locations, such as noise monitoring of water pumps in water plants. They feature single-point and disordered monitoring, and are simply wireless and miniaturized versions of wired / wireless noise monitoring systems.

[0007] Currently, the existing sound source localization method uses a microphone array combined with a localization algorithm. Analysis shows the following drawbacks: (1) High hardware cost, requiring at least 8 noise sensors, and the localization distance is limited to within 150 meters, making it unsuitable for large-scale road traffic, residential areas, and factories. (2) Limited application, generally used in specific locations such as monitoring mechanical faults, monitoring factory pipeline operations, and localizing sound sources in small, specific areas. (3) Susceptible to interference, especially in noisy environments; if there are other obstructions, sound refraction and scattering will affect the localization accuracy. Existing noise monitoring requires interaction between each device and the server via a 4G network; too many devices will increase the server load. Summary of the Invention

[0008] To address the technical problems of high hardware cost, limited application, and susceptibility to interference in existing sound source localization methods, this invention proposes a gridded noise monitoring system for sound source localization based on WSN technology. By combining WSN and wireless noise sensor technology, it can achieve large-scale sound source localization with low hardware cost, low sensitivity to the environment, and applicability to multiple scenarios and large-scale sound source localization.

[0009] To achieve the above objectives, the technical solution of the present invention is as follows: a gridded noise monitoring system for sound source localization based on WSN technology, comprising multiple wireless noise sensor nodes, the multiple wireless noise sensor nodes being arranged in a gridded manner, the multiple wireless noise sensor nodes being communicatively connected to a convergence node, and the convergence node being connected to a remote server.

[0010] Preferably, the distance between the wireless noise sensor nodes is 20-50m; the wireless noise sensor nodes and the aggregation node are installed on the streetlights.

[0011] Preferably, both the wireless noise sensor node and the aggregation node include a package structure, on which a microphone and an antenna are provided, and inside the package structure are a circuit board, a battery, and a power management module. The microphone, antenna, battery, and power management module are all connected to the circuit board.

[0012] Preferably, the circuit board is equipped with a controller, which is connected to a signal processing circuit and a wireless transceiver module. The wireless transceiver module is matched with an antenna, and the signal processing circuit is connected to a microphone.

[0013] Preferably, the microphone is connected to a preamplifier, which is located on the outside of the package structure; the preamplifier is connected to a signal processing circuit, which is connected to an analog-to-digital converter.

[0014] Preferably, the circuit board is further provided with a memory and an expandable interface, both of which are connected to the controller.

[0015] Preferably, the circuit board of the aggregation node is also equipped with a 4G module, which is connected to the controller and to a remote server or mobile terminal.

[0016] Preferably, the wireless transceiver modules of the wireless noise sensor nodes and the aggregation node use a unique frequency of 433MHz for data transmission; the aggregation node stores the values ​​monitored by the wireless noise sensor nodes in a table format in the memory according to the wireless noise sensor node numbers and transmits them to the remote server through a 4G module. The remote server knows the instantaneous noise values ​​of the noise nodes arranged in a grid in a certain area according to the numbers.

[0017] Preferably, the controller of the aggregation node performs a row-column scan at a certain period to find the maximum and minimum instantaneous noise values ​​of multiple wireless noise sensor nodes arranged in a grid pattern. Before installation, the code of all noise nodes is fixed, and the location information of all nodes in the area can be determined by the aggregation node scanning all noise nodes to determine which grid the maximum / minimum value is located in, thereby realizing the location of abnormal wireless noise sensor nodes.

[0018] Preferably, the controller of the aggregation node calculates the distance the noise source has moved based on the time it takes for the instantaneous noise value of the wireless noise sensor node to change from normal to abnormal.

[0019] The beneficial effects of this invention are as follows: This invention combines WSN and wireless noise monitoring technologies to propose a novel positioning system, primarily for sound source localization in road traffic, especially at night. This invention is not limited to urban roads but can also be applied to residential areas, factories, and other locations. This invention uses Wireless Sensor Network (WSN) technology to create a gridded layout of wireless noise sensor nodes, enabling the monitoring of noise sources over a large area. This invention only requires connecting the data from the noise nodes to a aggregation node, and then transmitting it to a remote server, effectively reducing the load on the remote server. In addition to sound source localization, this invention can also calculate the sound source's movement path based on changes in the sound source's noise level.

[0020] This invention abandons the traditional microphone array and adopts WSN technology combined with a grid layout to achieve sound source localization; this sound source localization technology is applicable to a large area; and the localization method is simple and does not require complex algorithm calculations; only the aggregation node needs to be connected to the remote server, reducing the pressure on the remote server; in addition to sound source localization, it can also calculate the path of moving noise. Attached Figure Description

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 This is a schematic diagram of the structure of the present invention.

[0023] Figure 2 This is a schematic diagram of the gridded layout of the wireless noise sensor nodes and aggregation nodes of the present invention.

[0024] Figure 3 This is a structural diagram of the wireless noise sensor node of the present invention.

[0025] Figure 4 This is a structural diagram of the convergence node of the present invention.

[0026] Figure 5 This is a flowchart of the process of the present invention.

[0027] Figure 6 This is a distribution diagram of the instantaneous minimum noise value after the mobile noise source of the present invention stops.

[0028] Figure 7 This is a distribution diagram of the instantaneous noise maxima of the fixed noise source of the present invention.

[0029] Figure 8 This is a schematic diagram illustrating the calculation of the noise source movement distance according to the present invention.

[0030] In the diagram, 1 is the packaging structure, 2 is the circuit board, 3 is the antenna, 4 is the battery and power management module, 5 is the microphone, and 6 is the preamplifier. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] like Figure 1As shown, a gridded noise monitoring system based on WSN technology for sound source localization includes multiple wireless noise sensor nodes arranged in a grid. These nodes are communicatively connected to a aggregation node. In addition to communicating with the aggregation node, the wireless noise sensor nodes can also communicate with each other. The aggregation node is connected to a remote server. A single aggregation node can receive data from multiple wireless noise sensor nodes, and the system is not limited to a single aggregation node. The wireless noise sensor nodes are used to detect noise at their location in real time. The aggregation node collects the noise data from the multiple wireless noise sensor nodes and transmits it to the remote server. The remote server processes the collected noise data to locate the grid where the noise is located. Mobile terminals connect to the remote service platform via a wireless network, allowing users to view the data from the remote server more conveniently.

[0033] like Figure 2 As shown, the distance between the wireless noise sensor nodes is 20-50m; the wireless noise sensor nodes and the convergence node are installed on streetlights. Since the specific location of the sound source needs to be calculated, the sensor nodes need to be laid out in a grid pattern. The distance between each sensor is set to 30m. In actual on-site deployment, if the municipal road plan is gridded or quasi-grid, streetlights can be used as carriers, as the distance between streetlights is between 25-50m, facilitating the location of the sound grid.

[0034] like Figure 3 As shown, the wireless noise sensor node includes a package structure 1, on which a microphone 5 and an antenna 3 are mounted. Inside the package structure 1 are a circuit board 2 and a battery and power management module 4. The microphone 5, antenna 3, and battery and power management module 4 are all connected to the circuit board 2. The circuit board 2 is the central control unit of the wireless noise sensor node. The battery and power management module 4 contains a battery and a power management unit. The battery provides power to the entire sensor node, and the power management unit is a power management chip LMG3410R050, which manages the charging and discharging functions of the battery to ensure its normal operation. The microphone 5, also known as a condenser microphone, is an energy conversion device that converts sound signals into electrical signals. The microphone 5 is generally a condenser microphone. The antenna 3 works with the wireless transceiver module to transmit and receive data.

[0035] The circuit board 2 is equipped with a controller, which is connected to the signal processing circuit and the wireless transceiver module. The wireless transceiver module is matched with the antenna 3, and the signal processing circuit is connected to the microphone 5. The controller is an MCU, which performs noise acquisition and preliminary processing, as well as control of the wireless transmission and reception of noise. The signal processing circuit processes the electrical signals acquired by the microphone 5. The microphone is generally a condenser microphone, used to convert sound signals into electrical signals. The function of the signal processing circuit is to convert the electrical signals into reasonable analog quantities as inputs for A / D (analog-to-digital) conversion. The signal processing circuit generally consists of attenuators, overload detection, weighting amplifiers, filters, detectors, etc. The wireless transceiver module performs wireless transmission and reception of measurement data and transmits the data through the antenna. The wireless transceiver module is a 433Hz wireless transceiver device used for data transmission between different nodes, and the antenna 3 is an accessory of the wireless transceiver module.

[0036] The microphone 5 is connected to the preamplifier 6, which is located on the outside of the package structure 1. The preamplifier 6 is connected to the signal processing circuit, which in turn is connected to the analog-to-digital converter (ADC). The microphone and preamplifier are connected via threads, and the preamplifier is connected to the signal processing circuit on the circuit board via a BNC interface. The preamplifier 6 is generally composed of a source follower made of a field-effect transistor combined with a bootstrap circuit, which can realize impedance transformation between the microphone 5 and the back-end detection module. The preamplifier 6 is added because the internal resistance of the microphone (capacitor) is very high, generally 10¹²Ω. However, the impedance of the subsequent attenuator and amplifier is generally not too high. The function of the preamplifier 6 is impedance matching, because the capacitance of the microphone is very small and the internal resistance is very high, while the impedance of the subsequent circuit is generally not too high. The analog-to-digital converter converts the analog signal of the electrical signal collected by the microphone 5 and amplified by the preamplifier 6 into a digital signal for processing by the signal processing circuit.

[0037] The circuit board 2 also includes a memory and an expandable interface, both of which are connected to the controller. The expandable interface primarily provides more human-machine interface functions and includes at least one of USB, RS232, RS485, RJ45, or DP interfaces. The expandable interface is added to better realize data transmission and human-machine interaction functions. The memory is a FLASH memory used to store the acquired noise data.

[0038] like Figure 4 As shown, in addition to the functions of a noise node, the aggregation node is also responsible for data processing and interfacing with remote servers and cloud servers. The circuit board 2 of the aggregation node is also equipped with a 4G module, which is connected to the controller and the remote server. At the same time, the remote server can push data to the mobile terminal (phone) for convenient viewing by users.

[0039] The wireless transceiver modules of the wireless noise sensor nodes and the aggregation node use a unique 433MHz frequency for data transmission. The aggregation node stores the values ​​monitored by the wireless noise sensor nodes in a table format in its memory according to the node numbers and transmits them to a remote server via a 4G module. The remote server knows the instantaneous noise values ​​of the gridded noise nodes in a certain area based on the node numbers. The wireless noise sensor nodes and the aggregation node are arranged as follows: Figure 2 As shown, suppose there are 35 wireless noise sensor nodes and 1 aggregation node in an area. The function of the wireless noise sensor nodes is to collect instantaneous noise values ​​when noise occurs. The aggregation node, in addition to the functions of the wireless noise sensor nodes (i.e., noise nodes), also needs to store the values ​​monitored by these noise nodes in a FLASH memory according to their numbers, and then transmit them to a remote server via a 4G module. Since both the noise nodes and the aggregation node are installed according to their corresponding geographical locations, when the aggregation node transmits data to the remote server via a specific IP address and port number, the remote server can know the instantaneous noise values ​​of the gridded noise nodes in a certain area based on their numbers. The data packet structure is frame header + address + function code + data packet + checksum + frame trailer. This design ensures data reliability and prevents the noise nodes from becoming disordered.

[0040] like Figure 5 As shown, the basic operating flow of this invention is as follows: Power-on system initialization: initialization of noise nodes and aggregation nodes (power supply, crystal oscillator, network on the circuit board); noise nodes and aggregation nodes are numbered to determine their location information. Before installation, noise nodes and aggregation nodes are numbered according to GPS geographical location information. For example, in a grid layout in a city, the location of noise node number 1 corresponds to latitude and longitude of 116.38, 39.9, etc. Each module of the noise node and aggregation node starts measurement mode (i.e., begins detecting the instantaneous noise value of the surrounding environment), and the instantaneous noise values ​​collected by the noise nodes are transmitted to the aggregation node. Because the 433MHz wireless band has strong penetration, long propagation distance, and strong anti-interference capability, with an effective transmission distance of up to 100m, the transmission between the noise nodes and aggregation nodes uses the unique 433MHz frequency. The aggregation node summarizes all the data collected by the noise nodes and stores it in a table format in its internal FLASH memory. The table format uses number and time as the main index, which is a conventional storage method.

[0041] The controller of the aggregation node performs a row-and-column scan at regular intervals to find the maximum and minimum instantaneous noise values ​​of multiple wireless noise sensor nodes arranged in a grid pattern. Since the installation area of ​​the noise nodes is fixed, and each noise node is numbered, the grid containing the maximum or minimum noise value can be identified based on the number, thus locating abnormal wireless noise sensor nodes. Specifically, a row-and-column scan method is used once per second to find the maximum or minimum values ​​s1max, s2max, s3max, s4max, or s1min, s2min, s3min, s4min within a specific grid. Because the noise nodes are arranged in a grid pattern, it is easy to locate the grid cell where noise is occurring. This location principle, based on sound intensity, can calculate the distance the noise has traveled, especially for large areas, such as nighttime street noise pollution in urban areas, enabling environmental protection bureaus to trace noise phenomena.

[0042] In actual testing, the noise level within a region tends to remain at a certain level, but it will exceed this average when a noise source is present. By transmitting noise data to a remote server, a noise variation curve for a specific region can be obtained, allowing the identification of extreme values. If the maximum / minimum noise value remains at a certain level for 10 seconds during the measurement process, it is considered a fixed noise source.

[0043] The controller at the aggregation node calculates the distance the noise source has moved based on the time it takes for the instantaneous noise value from the wireless noise sensor node to change from normal to abnormal. For example... Figure 8 As shown, the noise source's moving distance s = vt, the speed of sound in air is 340 m / s, and t is the time it takes for the sound intensity to change from normal to abnormal. The normal-to-abnormal data can be distinguished based on the curve generated from the noise data transmitted to the remote server, allowing for a very intuitive differentiation between normal and abnormal values.

[0044] Noise movement path calculation: The movement path is calculated based on changes in sound intensity. For example, under normal circumstances, the monitored noise level at all noise nodes is 40 dB. When noise occurs, it causes fluctuations in the monitored value, such as changing from the normal value of 40 dB to 50 dB, indicating that a noisy object has passed by. The recording time starts from this point and continues until the noise source stops moving. This time period is the movement time of the noise object. Then, based on the speed of sound in air being 340 m / s, the distance the noise source has moved can be calculated using s=vt.

[0045] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A gridded noise monitoring system for sound source localization based on WSN technology, characterized in that, It includes multiple wireless noise sensor nodes, which are arranged in a grid pattern. The multiple wireless noise sensor nodes are connected to a convergence node, which is connected to a remote server. The mobile terminal is connected to the remote service platform through a wireless network. The distance between the wireless noise sensor nodes is 20-50m; The aggregation node stores the values ​​monitored by the wireless noise sensor nodes in a table format in the memory according to the wireless noise sensor node numbers, and transmits them to the remote server through the 4G module. The remote server knows the instantaneous noise value of the noise nodes arranged in a grid in a certain area according to the numbers. The controller of the aggregation node performs a row-column scan at a certain period to find the maximum and minimum instantaneous noise values ​​of multiple wireless noise sensor nodes arranged in a grid, thereby locating abnormal wireless noise sensor nodes.

2. The gridded noise monitoring system based on WSN technology for sound source localization according to claim 1, characterized in that, The wireless noise sensor nodes and aggregation nodes are installed on the streetlights.

3. The gridded noise monitoring system for sound source localization based on WSN technology according to claim 1 or 2, characterized in that, Both the wireless noise sensor node and the aggregation node include a package structure, on which a microphone and an antenna are provided. Inside the package structure, there is a circuit board, a battery, and a power management module. The microphone, antenna, battery, and power management module are all connected to the circuit board.

4. The gridded noise monitoring system based on WSN technology for sound source localization according to claim 3, characterized in that, The circuit board is equipped with a controller, which is connected to a signal processing circuit and a wireless transceiver module. The wireless transceiver module is matched with an antenna, and the signal processing circuit is connected to a microphone.

5. The gridded noise monitoring system based on WSN technology for sound source localization according to claim 4, characterized in that, The microphone is connected to a preamplifier, which is located on the outside of the package structure; the preamplifier is connected to a signal processing circuit, which is connected to an analog-to-digital converter.

6. The gridded noise monitoring system for sound source localization based on WSN technology according to claim 4 or 5, characterized in that, The circuit board is also equipped with a memory and an expansion interface, both of which are connected to the controller.

7. The gridded noise monitoring system for sound source localization based on WSN technology according to claim 6, characterized in that, The circuit board of the aggregation node is also equipped with a 4G module, which is connected to the controller and to a remote server or mobile terminal.

8. The gridded noise monitoring system for sound source localization based on WSN technology according to claim 7, characterized in that, The wireless transceiver modules of the wireless noise sensor node and the aggregation node use a unique frequency of 433MHz for data transmission.

9. The gridded noise monitoring system for sound source localization based on WSN technology according to claim 1 or 8, characterized in that, The controller of the aggregation node calculates the distance the noise source moves based on the time it takes for the instantaneous noise value of the wireless noise sensor node to change from normal to abnormal.

Images