Automatic noise source scanning and positioning system and method

Abstract

The invention discloses an automatic noise source scanning and positioning system and method, and belongs to the technical field of noise source localization. A camera is used for obtaining a measurement image of a measurement area in an image, and a moving mechanism drives a detection device to move according to a scanning path and detect the measurement area; according to the method, a noise signal corresponding to each position on a scanning path can be determined, so that a visual positioning image of a noise source can be obtained by combining the corresponding relationship between the position information of the detection device and the noise signal into a measurement image, and the actual position of the noise source can be visually displayed on the visual positioning image; as the moving mechanism drives the detection device to move according to the scanning path, the scanning speed of the detection device is stable, the scanning range is uniform, and the measurement precision is high.

Description

Technical Field

[0001] The present invention relates to the technical field of noise source localization, and particularly to an automatic scanning and localization system and method for a noise source. Background Art

[0002] The noise source localization method can adopt the sound intensity detection technology. The sound intensity detection technology determines the azimuth of the noise source by analyzing the magnitude change of the sound intensity. At present, the sound intensity detection technology obtains the sound intensity data of the noise source at different positions through a sound intensity probe, and analyzes all the sound intensity data to locate the specific position of the noise source. However, the above-mentioned schemes all require manual scanning, which is time-consuming and laborious, and the scanning speed of the probe is unstable, and the scanning range is uneven, affecting the measurement accuracy. Summary of the Invention

[0003] The present invention aims to solve at least one of the technical problems existing in the prior art. For this purpose, the present invention proposes an automatic scanning and localization system and method for a noise source, so that the actual position of the noise source can be intuitively displayed in the visual localization image. Since the moving mechanism drives the detection device to move along the scanning path, the scanning speed of the detection device is stable, the scanning range is uniform, and the measurement accuracy is relatively high.

[0004] The automatic scanning and localization system for a noise source according to the first aspect embodiment of the present invention includes: A camera; A moving mechanism, the position of the moving mechanism is relatively fixed with respect to the position of the camera; A detection device, connected to the moving mechanism, and the moving mechanism drives the detection device to move; A controller, configured to set a measurement area and plan a scanning path, and the controller controls the moving mechanism to drive the detection device to move along the scanning path.

[0005] The automatic scanning and localization system for a noise source according to the embodiment of the present invention has at least the following beneficial effects: The camera is used to obtain the measurement image of the measurement area in the image. The moving mechanism drives the detection device to move along the scanning path and detect the measurement area, so that the noise signal corresponding to each position on the scanning path can be determined. Therefore, according to the correspondence between the position information of the detection device and the noise signal and combined with the measurement image, the visual localization image of the noise source can be obtained, and the actual position of the noise source can be intuitively displayed in the visual localization image; Since the moving mechanism drives the detection device to move along the scanning path, the scanning speed of the detection device is stable, the scanning range is uniform, and the measurement accuracy is relatively high.

[0006] According to some embodiments of the present invention, the moving mechanism is a three-axis moving platform.

[0007] The noise source automatic scanning and positioning method according to the second aspect embodiment of the present invention is applied to the noise source automatic scanning and positioning system described in the above embodiment. The noise source automatic scanning and positioning method includes: Controlling the camera to acquire an image and setting a measurement area according to the image; Acquiring a measurement image of the measurement area, and the controller designing a scanning path according to the measurement area; The controller controls the moving mechanism to drive the detection device to move and detect according to the scanning path, acquires the position information of the detection device, and controls the detection device to acquire the noise signal of the noise source; Generating a visual positioning image of the noise source according to the measurement image, the position information, and the noise signal.

[0008] The noise source automatic scanning and positioning method according to the embodiment of the present invention has at least the following beneficial effects: By using the camera to acquire a measurement image of the measurement area in the image, the moving mechanism drives the detection device to move and detect the measurement area according to the scanning path, and the noise signal corresponding to each position on the scanning path can be determined. Therefore, according to the correspondence between the position information of the detection device and the noise signal and combined with the measurement image, a visual positioning image of the noise source can be obtained, so that the actual position of the noise source can be intuitively displayed in the visual positioning image; Since the moving mechanism is used to drive the detection device to move according to the scanning path, the scanning speed of the detection device is stable, the scanning range is uniform, and the measurement accuracy is relatively high.

[0009] According to some embodiments of the present invention, the setting of the measurement area according to the image includes: Framing a measurement surface according to the image, and the noise source is located in the measurement surface; Obtaining boundary data according to the position of the measurement surface in the image, and determining the measurement area according to the boundary data.

[0010] According to some embodiments of the present invention, the controller controls the moving mechanism to drive the detection device to move and detect according to the scanning path, including: Controlling the moving mechanism to drive the detection device to move at a preset speed and controlling the detection device to sample at a preset frequency.

[0011] According to some embodiments of the present invention, the controller designing the scanning path according to the measurement area includes: Obtaining the area of the measurement area and obtaining the preset scanning spacing of the detection device; Calculating the row spacing according to the area and the preset scanning spacing; Setting the scanning path according to the measurement area and the row spacing.

[0012] According to some embodiments of the present invention, obtaining the position information of the detection device and controlling the detection device to obtain the noise signal of the noise source includes: Obtaining the position information of the detection device according to the position signal of the moving mechanism; Controlling the detection device to obtain the sound pressure data and particle velocity data of the noise source, and the sound pressure data and particle velocity data form the noise signal; Making the noise signal correspond one-to-one with the position information.

[0013] According to some embodiments of the present invention, obtaining the position information of the detection device and controlling the detection device to obtain the noise signal of the noise source further includes: Calculating sound intensity data according to the sound pressure data and the particle velocity data; Establishing a coordinate system with the position information and the measurement area, and combining the sound intensity data into the coordinate system to form a sound intensity distribution map.

[0014] According to some embodiments of the present invention, obtaining the position information of the detection device and controlling the detection device to obtain the noise signal of the noise source further includes: Performing sound pressure analysis on the sound pressure data and the particle velocity to obtain sound pressure data; Establishing a coordinate system with the position information and the measurement area, and combining the sound pressure data into the coordinate system to form a sound pressure distribution map.

[0015] According to some embodiments of the present invention, obtaining the position information of the detection device and controlling the detection device to obtain the noise signal of the noise source further includes: Performing spectrum analysis on the sound pressure data and the particle velocity to obtain spectrum data; Establishing a coordinate system with the position information and the measurement area, and combining the spectrum data into the coordinate system to form a spectrum analysis map. Description of the Drawings

[0016] Figure 1 is a schematic structural diagram of a noise source automatic scanning and positioning system according to an embodiment of the present invention; Figure 2 is a flowchart of a noise source automatic scanning and positioning method according to an embodiment of the present invention; Figure 3 is a flowchart of setting a measurement area in an embodiment of the present invention; Figure 4 is a flowchart of setting a scanning path in an embodiment of the present invention; Figure 5 is a flowchart of obtaining a noise signal in an embodiment of the present invention; Figure 6 It is a flowchart for forming a sound intensity distribution diagram in an embodiment of the present invention; Figure 7 It is a flowchart for forming a sound pressure distribution diagram in an embodiment of the present invention; Figure 8 It is a flowchart for forming a frequency spectrum distribution diagram in an embodiment of the present invention; Figure 9 It is a schematic diagram of the scanning path of the scanning device in an embodiment of the present invention; Figure 10 It is a sound intensity distribution diagram of different frequency noise sources in an embodiment of the present invention; Figure 11 It is a frequency spectrum analysis diagram of different frequency noise sources in an embodiment of the present invention.

[0017] Description of the drawings: Moving mechanism 100, detection device 200. Detailed implementation manners

[0018] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation of the present invention.

[0019] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as front, back, up, down, axial direction, circumferential direction, etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0020] In the description of the present invention, the meaning of "a plurality of" is more than two. Understandings such as greater than, less than, exceeding, etc. do not include the present number, and understandings such as above, below, within, etc. include the present number. If there is a description of first and second, it is only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0021] In the description of the present invention, it should be noted that terms such as setting, installation, connection, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific content of the technical solution.

[0022] The technical solutions of the present invention will be described clearly and completely below with reference to the drawings. Obviously, the following described embodiments are some embodiments of the present invention, not all embodiments.

[0023] Referring to Figure 1 as shown, an embodiment of the present invention provides an automatic scanning and positioning system for a noise source.

[0024] The automatic scanning and positioning system for a noise source includes a camera, a moving mechanism 100, a detection device 200, and a controller.

[0025] The position of the camera is relatively fixed with respect to the position of the moving mechanism 100, so that the relative position between the image captured by the camera and the moving mechanism 100 is fixed. The detection device 200 is connected to the moving mechanism 100, and the moving mechanism 100 drives the detection device 200 to move, thereby realizing that the moving mechanism 100 drives the detection device 200 to move relative to the image captured by the camera, ensuring that the detection device 200 can scan the area corresponding to the image and detect the noise situation.

[0026] The controller is electrically connected to the moving mechanism 100. The user can set a measurement area in the image captured by the camera through the controller. Then, the controller automatically plans a scanning route according to the measurement area set by the user, so that the moving mechanism 100 drives the detection device 200 to move along the scanning path.

[0027] Among them, since the position of the moving mechanism 100 is relatively fixed with respect to the camera, a detection range is obtained based on the moving stroke of the moving mechanism 100 driving the detection device 200 and the detection area of the detection device 200. Combining the detection range into the image captured by the camera can define an effective measurement range, and it is necessary to ensure that the noise source is within the effective measurement range.

[0028] Therefore, setting a measurement area within the effective measurement range can ensure that the detection device 200 can scan and detect the noise at each position in the measurement area. To further improve the detection efficiency and detection accuracy, the measurement area can be reduced and include the area where the noise source is located.

[0029] After setting the measurement area in the image, the area of the image corresponding to the measurement area forms a measurement image. The controller can plan and design a scanning path according to the boundary of the measurement area, so that after the detection device 200 moves along the scanning path and detects, the detected area can cover the entire measurement area.

[0030] The measurement image of the measurement area is obtained from the image by using a camera. The moving mechanism 100 drives the detection device 200 to move along the scanning path and detect the measurement area, and the noise signal corresponding to each position on the scanning path can be determined. Therefore, according to the corresponding relationship between the position information of the detection device 200 and the noise signal and combined into the measurement image, a visual positioning image of the noise source can be obtained, so that the actual position of the noise source can be intuitively displayed in the visual positioning image. Since the moving mechanism 100 drives the detection device 200 to move along the scanning path, the scanning speed of the detection device is stable, the scanning range is uniform, and the measurement accuracy is relatively high.

[0031] In some embodiments, referring to Figure 1 as shown, the moving mechanism 100 is a precision three-axis moving platform.

[0032] The detection device 200 is driven by an X-axis moving mechanism, a Y-axis moving mechanism, and a Z-axis moving mechanism. The X-axis moving mechanism drives the Y-axis moving mechanism to move along the X-axis, the Y-axis moving mechanism drives the Z-axis moving mechanism to move along the Y-axis, and the Z-axis moving mechanism drives the detection device 200 to move along the Z-axis. Thus, the detection device 200 can be moved along the scanning path, and it is ensured that the moving speeds of the X-axis, Y-axis, and Z-axis are all equal to the preset speed. Moreover, the X-axis moving mechanism, Y-axis moving mechanism, and Z-axis moving mechanism can record the real-time position of the detection device 200, and thus obtain the position information of the detection device 200.

[0033] The three-axis moving platform is set to be able to call the moving mechanisms of any two axes according to the position of the noise source to realize the movement of the detection device 200.

[0034] Referring to Figures 2 to 11 as shown, an embodiment of the present invention provides a method for automatically scanning and positioning a noise source.

[0035] Referring to Figure 2 as shown, the method for automatically scanning and positioning a noise source includes the following steps.

[0036] Step S100, controlling the camera to obtain an image and setting the measurement area according to the image.

[0037] Since the positions of the moving mechanism 100 and the camera are relatively fixed, the detection range is obtained based on the moving stroke of the moving mechanism 100 driving the detection device 200 and the detection area of the detection device 200. Combining the detection range into the image captured by the camera can define the effective measurement range, and it is necessary to ensure that the noise source is within the effective measurement range.

[0038] Setting the measurement area within the effective measurement range can ensure that the detection device 200 can scan and detect the noise at each position in the measurement area. In order to further improve the detection efficiency and detection accuracy, the measurement area can be reduced and include the area where the noise source is located.

[0039] Step S200: Obtain the measurement image of the measurement area, and the controller designs the scanning path according to the measurement area.

[0040] After setting the measurement area in the image, the area of the image corresponding to the measurement area forms the measurement image. The controller can plan and design the scanning path according to the boundary of the measurement area, so that after the detection device 200 moves along the scanning path and detects, the detected area can cover the entire measurement area.

[0041] Step S300: The controller controls the moving mechanism 100 to drive the detection device 200 to move and detect according to the scanning path, obtains the position information of the detection device 200, and controls the detection device 200 to obtain the noise signal of the noise source.

[0042] The moving mechanism 100 is equipped with a position monitoring device, which can monitor the real-time position information of the detection device 200, and the detection device 200 detects synchronously during the movement process to obtain the noise signal of the noise source.

[0043] Step S400: Generate a visual positioning image of the noise source based on the measurement image, position information, and noise signal.

[0044] The measurement image is the image situation near the position where the noise source is located. The position information of the detection device 200 is obtained based on the moving mechanism 100. The position of the moving mechanism 100 is relatively fixed with respect to the position of the scene corresponding to the image captured by the camera. During the movement and detection process of the detection device 200, the noise signal obtained by the detection device 200 at any position forms a corresponding relationship with the position information. Therefore, a distribution image of the noise signal can be formed, and then the distribution image can be combined with the measurement image to form a visual positioning image of the noise source.

[0045] Since the moving mechanism 100 is used to drive the detection device 200 to move along the scanning path, the scanning speed of the detection device is stable, the scanning range is uniform, and the measurement accuracy is relatively high.

[0046] In some embodiments, as shown in FIG. 3, Step S100: Set the measurement area according to the image, including the following steps.

[0047] Step S110: Select the measurement surface according to the image, and the noise source is located in the measurement surface.

[0048] Obtain the image of the position where the noise source is located through the camera, ensure that the noise source is located in the image, and then select the measurement surface in the system to ensure that the noise source is located in the measurement surface.

[0049] Step S120: Obtain the boundary data according to the position of the measurement surface in the image, and determine the measurement area according to the boundary data.

[0050] Based on the range of the selected measurement surface in the image, the boundary data of the measurement surface is calculated, that is, the boundary of the measurement surface in the image can be determined, and then the boundary data of the measurement area can be determined. The moving mechanism 100 can plan the scanning path of the detection device 200 according to the boundary data.

[0051] In some embodiments, in step S300, the controller controls the moving mechanism 100 to drive the detection device 200 to move and detect along the scanning path, and further includes the following steps.

[0052] Step S301, control the moving mechanism 100 to drive the detection device 200 to move at a preset speed, and control the detection device 200 to sample at a preset frequency.

[0053] The moving mechanism 100 sets a preset speed to drive the detection device 200 to move at a constant speed to ensure the smooth movement of the detection device 200. The detection device 200 samples at a preset frequency. According to the preset frequency and the preset speed, the distance between two sampling positions of the detection device 200 can be calculated, and then the noise signal obtained by the detection device 200 can be corresponded to the position information of the detection device 200.

[0054] In some embodiments, referring to Figure 4 as shown, in step S200, the controller designs a scanning path according to the measurement area, and further includes the following steps.

[0055] Step S210, obtain the area of the measurement area, and obtain the preset scanning spacing of the detection device 200.

[0056] The area of the measurement area is calculated according to the boundary data, and the preset scanning spacing of the detection device 200 is approximately the accurate detection range of the detection device 200.

[0057] Step S220, calculate the row spacing according to the area and the preset scanning spacing.

[0058] To ensure that the detection device 200 can cover the entire measurement area, it is necessary to calculate the distance between two rows of paths according to the preset scanning spacing, and this distance is the row spacing.

[0059] Step S230, set the scanning path according to the measurement area and the row spacing.

[0060] Referring to Figure 9 as shown, based on the area of the measurement area and the calculated row spacing, the scanning path of the detection device 200 can be planned. In this embodiment, since the measurement area is generally rectangular, the scanning path is set into multiple rows along the length and width directions of the rectangle and connected end to end in sequence to ensure that the detection range of the scanning device can cover the entire measurement area.

[0061] In some embodiments, referring to Figure 5 as shown, step S300 of obtaining the position information of the detection device and controlling the detection device to obtain the noise signal of the noise source further includes the following steps.

[0062] Step S310, obtaining the position information of the detection device according to the position signal of the moving mechanism.

[0063] The moving mechanism 100 is provided with a position monitoring device, which can emit a position signal, and based on the position signal, the real-time position information of the detection device 200 can be monitored.

[0064] Step S320, controlling the detection device to obtain the sound pressure data and particle velocity data of the noise source, and the sound pressure data and particle velocity data form a noise signal.

[0065] The PU sound intensity probe can directly collect the sound pressure data and particle velocity data. During the movement of the detection device 200, the PU sound intensity probe continuously collects the sound pressure data and particle velocity data.

[0066] Step S330, corresponding the noise signal with the position information one by one.

[0067] After recording the position information of the detection device 200, each position information can correspond to the sound pressure data and particle velocity data.

[0068] In some embodiments, referring to Figure 6 as shown, step S300 of obtaining the position information of the detection device and controlling the detection device to obtain the noise signal of the noise source further includes the following steps.

[0069] Step S340, calculating the sound intensity data according to the sound pressure data and particle velocity data.

[0070] The sound intensity data can be calculated from the sound pressure data and particle velocity data with reference to the following scheme.

[0071] Sound intensity represents the average energy flux density of a sound wave in one period, that is, the sound power passing through a unit cross-section. Sound intensity is a vector with magnitude and direction, which can be used to describe the intensity and direction of sound energy flow. According to the definition of sound intensity, we have: ; where p(t) is the sound pressure and u(t) is the particle velocity.

[0072] The average sound intensity is obtained by averaging over time, and its unit is W / m 2 , and the expression is: ; where p e is the sound pressure, is the medium density, is the propagation speed of sound in the medium.

[0073] Similarly, sound intensity can also be expressed in decibels. The sound intensity corresponding to the hearing threshold is 10 -12 W / m 2 , while the sound intensity corresponding to the pain threshold is 1 W / m 2 , and the difference between the two is 12 orders of magnitude. For simplicity of representation, the sound intensity level also adopts a logarithmic form, with the unit of decibel (dB), and the expression is: ; In the formula, L I is the sound intensity level, I is the sound intensity to be measured, I0 is the reference sound intensity, and I0 is generally 10 -12 W / m 2 in the air.

[0074] Step S350: Establish a coordinate system for the position information and the measurement area, and combine the sound intensity data into the coordinate system to form a sound intensity distribution map.

[0075] Referring to Figure 10 as shown, establish a coordinate system based on the measurement area, fill in the position information one by one into the coordinate system, then combine the sound intensity data corresponding to the position information into the coordinate system, mark different colors according to the magnitude of the sound intensity data, and thus form a sound intensity distribution map.

[0076] In some embodiments, referring to Figure 7 as shown, step S300: Obtain the position information of the detection device and control the detection device to obtain the noise signal of the noise source, and further includes the following steps.

[0077] Step S360: Perform sound pressure analysis based on the sound pressure data and the particle velocity to obtain the sound pressure data.

[0078] The sound pressure level is obtained by taking the common logarithm of the ratio of the sound pressure p to be measured to the reference sound pressure p(ref), and then multiplying by 20, and its unit is decibel.

[0079] The particle velocity level is obtained by first calculating the logarithm to the base 10 of the ratio of the particle velocity to the reference velocity, and then multiplying by 20, and its unit is decibel.

[0080] Step S370: Establish a coordinate system for the position information and the measurement area, and combine the sound pressure data into the coordinate system to form a sound pressure distribution map.

[0081] Calculate the sound pressure data based on the sound pressure level, establish a coordinate system based on the measurement area, fill in the position information one by one into the coordinate system, then combine the sound pressure data corresponding to the position information into the coordinate system, mark different colors according to the magnitude of the sound pressure data, and thus form a sound pressure distribution map. Combine the sound pressure distribution map into the measurement image to form a visual positioning image of the sound pressure of the noise source.

[0082] In some embodiments, as shown in Figure 8 and Figure 11 , step S300, obtaining the position information of the detection device and controlling the detection device to obtain the noise signal of the noise source, further includes the following steps.

[0083] Step S380, performing spectral analysis on the sound pressure data and particle velocity to obtain spectral data.

[0084] The sound pressure level is obtained by taking the common logarithm of the ratio of the measured sound pressure p to the reference sound pressure p(ref), and then multiplying by 20, and its unit is decibel.

[0085] The particle velocity level is obtained by first calculating the logarithm to the base 10 of the ratio of the particle velocity to the reference velocity, and then multiplying by 20, and its unit is decibel.

[0086] Calculate the spectral data based on the sound pressure level and the particle velocity level.

[0087] Step S390, establishing a coordinate system for the position information and the measurement area, and combining the spectral data into the coordinate system to form a spectral analysis diagram.

[0088] Based on the measurement area, establish a coordinate system, fill in the position information one by one into the coordinate system, then combine the spectral data corresponding to the position information into the coordinate system, mark different colors according to the magnitude of the spectral data, and further form a spectral distribution diagram. Combine the spectral distribution diagram into the measurement image to form a visual positioning image of the spectrum of the noise source.

[0089] The signal collected by the PU sound intensity probe is an instantaneous signal in the time domain. However, in engineering practice, people are more concerned about the frequency distribution characteristics of the sound intensity. Especially in noise control, the frequency domain distribution of the sound intensity contains more valuable information. Therefore, frequency domain analysis is particularly important.

[0090] The cross-correlation function between the sound pressure p(t) and the particle velocity u(t) at the measurement point can be expressed as: ; Then the average sound intensity is: ; Perform Fourier transform on the cross-correlation function to obtain the cross-power spectral density function as: ; Then take the inverse Fourier transform to get: ; Then there is: ; Abbreviation: cross-spectrum, which is a complex number representing the frequency distribution of the average sound intensity. Its real part is an even function representing the active sound intensity, and its imaginary part is an odd function representing the reactive sound intensity. It is a bilateral spectrum. For ease of use, the bilateral spectrum needs to be converted into a unilateral spectrum. The conversion relationship can be expressed as:

[0091] Then the sound intensity expression can be written as: .

[0092] The controller in the embodiment of the present application includes: at least one processor; and a memory that stores instructions. When the instructions are executed by at least one processor, the automatic noise source scanning and positioning method described in the above embodiment is performed.

[0093] Taking the example that the processor and memory of the controller can be connected by a bus. The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory and can also include non-transitory memory, such as at least one disk memory, flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory optionally includes a memory remotely set relative to the control processor, and these remote memories can be connected to the controller through a network.

[0094] The non-transitory software programs and instructions required to implement the automatic noise source scanning and positioning method in the above embodiment are stored in the memory. When executed by the processor, the control method in the above embodiment is performed. For example, the method steps S100 to step S400 described above, Figure 2 the method steps S110 to step S120 in Figure 3 the method steps S210 to step S230 in Figure 4 the method steps S310 to step S330 in Figure 5 the method steps S340 to step S350 in Figure 6 the method steps S360 to step S370 in Figure 7 the method steps S380 to step S390 in Figure 8 etc.

[0095] In this embodiment, specifically, the automatic noise source scanning and positioning system mainly consists of two major parts: a scanning mechanism and a data acquisition mechanism. The data acquisition mechanism is provided with a detection device 200. The working principle of the automatic noise source scanning and positioning system can be divided into the following three key steps.

[0096] In the first step, the LabVIEW host computer obtains an image of the location of the noise source through the camera in the data acquisition mechanism. The LabVIEW host computer frames the measurement surface in the image, and the automatic scanning and positioning system for the noise source automatically identifies the boundary data of the measurement surface and transmits the boundary data to the scanning mechanism, thereby determining the scope of the measurement area. This process ensures the accurate positioning of the scanning task, simplifies the operation process of the staff, and provides a reliable boundary basis for subsequent scanning operations.

[0097] In the second step, the scanning mechanism performs precise scanning according to the boundary data and the preset scanning path. At the same time, the data acquisition mechanism uses the USB-4431 module to execute the signal acquisition program, and the LabVIEW host computer monitors and records the position information of the detection device 200 and the collected noise signals in real time. This stage ensures the real-time and accuracy of data acquisition through the synchronous monitoring of the position information and the noise signals.

[0098] In the third step, the LabVIEW host computer post-processes the collected noise signals and position information. Through a series of calculation steps, the system calculates the sound pressure level and the particle vibration velocity level, and at the same time performs sound intensity analysis, sound pressure analysis, and spectrum analysis. On this basis, the system combines the sound intensity data with the position information to generate a visual sound intensity distribution map, thereby providing detailed data support for further acoustic analysis and optimization. Finally, the sound intensity distribution map is combined with the background photo of the measurement area to realize the visualization of the noise source. Through such a process, it is ensured that the whole process of the system from image acquisition, scanning control to data acquisition and processing is automated and highly coordinated, and at the same time, the accuracy and real-time of data acquisition are ensured.

[0099] To verify the positioning accuracy and stability of the system for a single noise source. Refer to Figure 10 As shown, the loudspeaker will play four kinds of acoustic signals of 66.7 Hz, 1000 Hz, white noise, and 2500 Hz in sequence, and each signal sounds alone. The deviation between the center point position of the noise source identified by the system and the actual sound source position is used to evaluate the positioning accuracy of the system in different frequency ranges. Among them, the low-frequency signal of 66.7 Hz can not only be used to simulate the first-order characteristic frequency of the engine but also represent a typical low-frequency noise source. The middle-frequency signal of 1000 Hz can simulate the typical working noise of mechanical equipment. White noise is used to simulate the broadband environmental noise, and the high-frequency signal of 2500 Hz can simulate some high-frequency mechanical noises or airflow noises. Through these four representative acoustic signals, we can comprehensively evaluate the positioning performance of the system in different frequency ranges.

[0100] As Figure 9As shown in the figure, the scanning path is set to square scanning, the scanning line spacing is 50 mm, the scanning speed is 30 mm / s, the center position of the speaker, i.e., the noise source, is (240, 370), and the scanning range is set to (40 - 440, 220 - 520). The sampling mode is selected as continuous sampling, and the sampling frequency is set to 12,800 Hz.

[0101] The results of noise source identification are as Figure 10 shown. Figure 10 In the figure, the dark areas indicate larger sound intensity level values and are possible noise source positions. An obvious dark circular area is shown in all four figures, which is consistent with the actual number of noise sources. The specific data are shown in Table 1. When the speaker plays a single-frequency sound of 66.7 Hz, the coordinates of the center point of the circumscribed circle of the noise source are (235, 371), and the deviation rates of the X and Y axis coordinates from the true values are 2.0% and 0.3% respectively. The maximum sound intensity level is 85 dB, and the difference from the non-noise source area is more than 20 dB. When the speaker plays a single-frequency sound of 1000 Hz, the coordinates of the center point of the circumscribed circle of the noise source are (237, 372), and the deviation rates of the X and Y axes are 1.3% and 0.5% respectively. The maximum sound intensity level is 93.2 dB, and the difference from the non-noise source area is more than 24 dB. When the speaker plays a single-frequency sound of 2500 Hz, the coordinates of the center point of the circumscribed circle of the noise source are (251, 368), and the deviation rates of the X and Y axes are 4.4% and 0.5% respectively. The maximum sound intensity level is 82 dB, and the difference from the non-noise source area is more than 20 dB. When the speaker plays white noise, the coordinates of the center point of the circumscribed circle of the noise source are (250, 373), and the deviation rates of the X and Y axes are 4.2% and 0.8% respectively. The maximum sound intensity level is 75 dB, and the difference from the non-noise source area is more than 20 dB.

[0102] Table 1:

[0103] The experimental results show that under three different frequencies and white noise conditions, the system can accurately identify the position and number of noise sources, and the deviation rate of the center point position of the noise source is less than 5%. Combining the spectrogram and the 1 / 3 octave band diagram, the frequency components of the noise source can be further determined, thus realizing the accurate positioning of the noise source. The identification accuracy and stability of the system perform well under different frequency conditions, verifying its reliability in practical applications.

[0104] The visualization positioning image of the noise source is as Figure 11As shown, Figures a - b respectively show the visualization cloud maps of noise sources under different frequency bands. The positions with higher brightness are the noise sources corresponding to the respective frequency bands. This figure can not only visually present the spatial distribution and relative intensity of the noise sources, but also further analyze the contributions of different frequency components to the noise sources by adjusting the frequency band range. With this visualization method, users can analyze the noise components in a complex sound field environment, accurately identify the main noise sources in specific frequency bands, and thus conduct noise control and acoustic optimization more pertinently.

[0105] The embodiments described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation to the technical solutions provided by the embodiments of the present application. Those skilled in the art know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0106] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation to the embodiments of the present application, and may include more or fewer steps than shown in the figures, or combine certain steps, or different steps.

[0107] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0108] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, and their appropriate combinations.

[0109] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above - mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non - exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these process, method, product, or device.

[0110] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist simultaneously. Here, A and B can be singular or plural. The character " / " generally indicates an "or" relationship between the associated objects before and after. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one (item) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0111] In several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the above division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0112] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0113] In addition, in each embodiment of this application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0114] When an integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of this application. The foregoing storage medium includes: various media that can store programs, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0115] The preferred embodiments of the embodiments of this application have been described above with reference to the accompanying drawings, and thus do not limit the scope of the rights of the embodiments of this application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of this application shall be within the scope of the rights of the embodiments of this application.

Claims

1. An automatic scanning and positioning system for noise sources, characterized in that, Comprising: A camera; A moving mechanism, the position of the moving mechanism being relatively fixed with respect to the position of the camera; A detection device, connected to the moving mechanism, and the moving mechanism drives the detection device to move; A controller, configured to set a measurement area and plan a scanning path, and the controller controls the moving mechanism to drive the detection device to move along the scanning path.

2. The automatic scanning and positioning system for noise sources according to claim 1, wherein The moving mechanism is a three-axis moving platform.

3. An automatic scanning and positioning method for a noise source, characterized in that, Applied to the noise source automatic scanning and positioning system as described in claim 1 or 2, the noise source automatic scanning method includes: Controlling the camera to acquire an image, and setting a measurement area according to the image; Acquiring a measurement image of the measurement area, and the controller designs a scanning path according to the measurement area; The controller controls the moving mechanism to drive the detection device to move and detect along the scanning path, acquires the position information of the detection device, and controls the detection device to acquire the noise signal of the noise source; Generating a visual positioning image of the noise source according to the measurement image, the position information, and the noise signal.

4. The automatic scanning and positioning method for noise sources according to claim 3, characterized in that, The setting the measurement area according to the image includes: Framing a measurement surface according to the image, and the noise source is located in the measurement surface; Obtaining boundary data according to the position of the measurement surface in the image, and determining the measurement area according to the boundary data.

5. The automatic scanning and positioning method for noise sources according to claim 3, characterized in that, The controller controls the moving mechanism to drive the detection device to move and detect along the scanning path, including: Controlling the moving mechanism to drive the detection device to move at a preset speed, and controlling the detection device to sample at a preset frequency.

6. The automatic scanning and positioning method for noise sources according to claim 3, characterized in that The controller designs a scanning path according to the measurement area, including: Obtaining the area of the measurement area, and obtaining the preset scanning spacing of the detection device; Calculating the row spacing according to the area and the preset scanning spacing; Setting the scanning path according to the measurement area and the row spacing.

7. The automatic scanning and positioning method for noise sources according to claim 3, characterized in that The acquiring the position information of the detection device and controlling the detection device to acquire the noise signal of the noise source includes: Obtaining the position information of the detection device according to the position signal of the moving mechanism; Controlling the detection device to acquire the sound pressure data and the particle velocity data of the noise source, and the sound pressure data and the particle velocity data form the noise signal; Corresponding the noise signal with the position information one by one.

8. The automatic scanning and positioning method for a noise source according to claim 7, wherein The acquiring the position information of the detection device and controlling the detection device to acquire the noise signal of the noise source further includes: Calculating sound intensity data according to the sound pressure data and the particle velocity data; Establishing a coordinate system for the position information and the measurement area, and combining the sound intensity data into the coordinate system to form a sound intensity distribution map.

9. The automatic scanning and positioning method for a noise source according to claim 7, characterized in that, The acquiring the position information of the detection device and controlling the detection device to acquire the noise signal of the noise source further includes: Performing sound pressure analysis according to the sound pressure data and the particle velocity to obtain sound pressure data; Establishing a coordinate system for the position information and the measurement area, and combining the sound pressure data into the coordinate system to form a sound pressure distribution map.

10. The automatic scanning and positioning method for noise sources according to claim 7, characterized in that, The acquiring the position information of the detection device and controlling the detection device to acquire the noise signal of the noise source further includes: Perform spectral analysis on the sound pressure data and the particle velocity to obtain spectral data; Establish a coordinate system with the position information and the measurement area, and combine the spectral data into the coordinate system to form a spectral analysis diagram.

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