A method for identifying a generation and propagation pattern of pipeline noise

Abstract

The present application relates to the field of pipeline noise control, and particularly relates to a method for identifying generation and propagation mode of pipeline noise, which combines pipeline noise experimental test and CFD simulation to construct a gas pipeline noise source identification architecture, analyzes the generation approach of gas pipeline noise from two aspects of external sound vibration characteristics and internal flow characteristics of the pipeline, reveals the evolution and generation mechanism of noise from the inside to the outside of the gas pipeline, and further provides effective theoretical and experimental support for the vibration and noise reduction research of the gas pipeline. The method of the present application combines experiment and simulation, has the advantages of quickly obtaining the characteristics of the main noise source space and frequency domain, and verifying the test results of the pipeline surface acceleration with each other to accurately locate the position and frequency of the noise source. In general, the method of the present application has low cost and good identification ability of pipeline noise excitation source, thereby helping to further control and manage the noise of the pipeline.

Description

Technical Field

[0001] This invention relates to the field of pipeline noise control, and specifically to a method for identifying the generation and propagation patterns of pipeline noise. Background Technology

[0002] Pipeline transportation, as one of the five major modes of transportation, is a crucial method for energy transport. With the continuous expansion and rapid development of urban construction, energy consumption is increasing. Pipeline transportation, with its advantages of avoiding urban planning conflicts and saving significant costs, is widely used in the transportation of natural gas and oil. However, this also brings the vibration and noise generated during fluid transportation. The causes of this noise are multifaceted: firstly, the high-speed airflow during operation causes pipeline vibration; secondly, the friction, collision, and disturbance generated during the flow of the internal medium lead to turbulent gas flow, thus generating pipeline noise. Severe vibration and high-intensity pipeline noise not only harm the physical and mental health of workers, but also cause structural vibration in pipeline equipment due to noise excitation. This reduces equipment accuracy and lifespan, and may also lead to loosening of pipeline structures, fittings, and connecting components, posing serious threats to the environment and production safety.

[0003] Most studies on the formation and propagation modes of pipeline noise sources are based on single numerical methods, mainly analyzing the flow characteristics of fluids in pipelines to clarify the formation mechanism and propagation characteristics of noise excitation sources. The drawback of this method is that the results lack reliability, and existing numerical analysis methods often require huge computational costs to ensure high computational accuracy when studying the noise formation mechanism, which is not suitable for small enterprises or individuals and cannot meet practical needs. Summary of the Invention

[0004] Given the enormous computational cost of predicting noise sources and propagation modes using the finite element method, this invention combines pipeline noise experimental testing with CFD simulation to construct a noise source identification architecture for gas pipelines. Starting from both the external acoustic and vibration characteristics and the internal flow characteristics of the pipeline, it analyzes the noise generation pathways of gas pipelines, reveals the evolution and generation mechanism of noise from the inside out of the gas pipeline, and thus provides effective theoretical and experimental support for the research on vibration reduction and noise reduction of gas pipelines.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for identifying the generation and propagation patterns of pipeline noise includes the following steps:

[0007] Step S1. Noise Characteristics Identification: A microphone spiral array test system is set up within a 5 to 10-meter range of the pipeline. Based on the microphone imaging principle, the pipeline is scanned for sound field and array test is performed. The obtained images are processed to obtain the location and frequency domain characteristics of the main noise sources.

[0008] Step S2. Vibration Characteristics Identification: An accelerometer is installed at the sound source location located by the microphone array to test the vibration acceleration of the pipe surface. The results are verified with the noise source location and frequency located by the microphone imaging in Step S1. The main formation mode of pipe noise is determined by comparative analysis.

[0009] Step S3. Flow characteristics analysis inside the pipe: A model is established according to the shape of the outer surface of the pipe using CFD simulation technology, specific parameters are set, no-slip boundary conditions are set for the inner wall of the pipe and the valve core wall, unstructured mesh is used for calculation, and excitation analysis is carried out through actual simulation to study the flow characteristics of natural gas inside the pipe.

[0010] Step S4. Determine the noise formation mechanism: Combine the location results of external noise sources and the excitation characteristics of the internal flow field of the pipeline to analyze the noise generation mechanism, and provide a design basis for subsequent noise control.

[0011] Furthermore, in step S1, the microphone imaging is based on a delay-sum beamforming algorithm to construct acoustic imaging technology to identify noise sources. By performing spectrum conversion on the sound signals collected by all microphones, the spectral characteristic matrix is ​​obtained, and then cross-spectral calculation is performed. At the same time, the space is divided into several grid points, and each grid point of the scanning plane is used as a hypothetical sound source. The sound signal received by the microphone point is calculated, and then the measured results and hypothetical results are analyzed for matching degree to calculate their autospectrum. The one with the highest matching degree is the sound source location.

[0012] Furthermore, in step S1, the number of microphones used for imaging is at least eight.

[0013] Furthermore, in step S2, an accelerometer is used to measure the vibration response of the gas pipeline, and Fourier transform is used to perform frequency domain analysis on the measured signal. The basic calculation formula is as follows:

[0014]

[0015] In the formula, f(t) is the measured signal, e is the natural logarithm, and i is the imaginary unit, the value of which is equal to ω is the angular frequency, measured in radians per second, and t is time, measured in seconds.

[0016] Furthermore, in step S3, when dividing the boundary layer mesh using CFD methods, for low Reynolds number flows, the actual height of the first layer mesh on the wall must ensure that the dimensionless wall distance y+ satisfies y+<5.

[0017] For high Reynolds number flow, the actual height of the first layer of grid on the wall shall ensure that the dimensionless wall distance y+ satisfies y+<5 or 30<y+<200; in order to capture the boundary layer flow, the growth rate of the boundary layer grid is set to 1.1-1.3.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] The present invention combines pipeline noise experimental testing and CFD simulation to construct a noise source identification framework for gas transmission pipelines, and analyzes the generation paths and propagation modes of noise in gas transmission pipelines from two aspects of the acoustic-vibration characteristics outside the pipeline and the internal flow characteristics. The method of the present invention combines experiment and simulation, and has the advantages of quickly acquiring the spatial and frequency-domain characteristics of main noise sources, verifying with the pipeline surface acceleration test results, and accurately positioning the position and frequency of noise sources. In general, the method of the present invention has low cost and good capability of identifying pipeline noise excitation sources, thereby facilitating further noise control and treatment of pipelines. Description of Drawings

[0020] Figure 1 is an implementation flow chart of the method of the present invention.

[0021] Figure 2 is a spectrum analysis diagram of noise.

[0022] Figure 3 shows the acceleration measurement value of the No. 1 sensor.

[0023] Figure 4 shows the acceleration measurement value of the No. 2 sensor. Detailed Description of Embodiments

[0024] The method of the present invention is further described in detail below:

[0025] A method for identifying noise generation and propagation modes in a pipeline comprises the following steps:

[0026] Step S1. Noise characteristic identification: setting up a microphone spiral array testing system within the range of 5 to 10 meters of the pipeline, performing sound field scanning and array testing on the pipeline based on the microphone imaging principle, performing sound source processing according to the obtained images, and acquiring the position and frequency-domain characteristics of main noise sources;

[0027] Microphone imaging is based on the delay-and-sum beamforming algorithm, and constructs acoustic imaging technology to realize noise source identification. Through spectral conversion of sound signals collected by all microphones, the spectral characteristic matrix is obtained, and then cross-spectral operation is performed; meanwhile, the space is divided into a plurality of grid points, each grid point on the scanning plane is taken as a hypothetical sound source, the sound signal received at the microphone point is calculated, and then the matching degree analysis is performed on the actually measured result and the hypothetical result to obtain the self-spectrum, and the one with the highest matching degree is the position of the sound source. The number of microphones used for microphone imaging is at least 8.

[0028] Step S2. Vibration characteristic identification: arranging and installing acceleration sensors at the sound source position located by the microphone array, testing the vibration acceleration of the pipe surface, verifying with the position and frequency of the noise source located by microphone imaging in step S1, and determining the main generation mode of pipeline noise through comparative analysis;

[0029] The acceleration sensor is used to measure the vibration response of the gas transmission pipeline, and Fourier transform is adopted to perform frequency domain analysis on the measurement signal. The basic calculation formula is:

[0030]

[0031] In the formula, f(t) is the measurement signal, e is the natural logarithm, i is the imaginary unit, and its value is equal to ω is circular frequency with unit of radian per second, and t is time with unit of second.

[0032] Step S3. Analysis of flow characteristics in the pipeline: establishing a model according to the outer surface shape of the pipeline by using CFD simulation technology, setting specific parameters, setting no-slip boundary conditions on the inner wall of the pipeline and the wall surface of the valve core, adopting unstructured grids for calculation, performing excitation analysis through live condition simulation, and studying the flow characteristics of natural gas in the pipeline;

[0033] When boundary layer meshes are divided by the CFD method, for low Reynolds number flow, the actual height of the first layer of wall meshes shall ensure that the dimensionless wall distance y+ satisfies y+<5;

[0034] For high Reynolds number flow, the actual height of the first layer of wall meshes shall ensure that the dimensionless wall distance y+ satisfies y+<5 or 30<y+<200; to capture the boundary layer flow, the growth rate of the boundary layer meshes is 1.1 to 1.3.

[0035] Step S4. Determination of noise generation mechanism: combining the external noise source positioning result of the pipeline and the internal flow field excitation characteristics of the pipeline to analyze the noise generation mechanism, which provides a design basis for subsequent noise control.

[0036] Example:

[0037] To identify the noise characteristics of a certain type of natural gas pipeline, an array of 60 high-precision Danish GRAS 40PH microphones was used for acoustic imaging. The array was tested at a distance of 10m from the pipeline. The average noise spectrum was obtained by processing and analyzing the measurement data from the 60 microphones. Figure 2 As shown. By Figure 2 It can be seen that the two main noise frequencies are 1523Hz and 2119Hz. In order to clarify the location of the noise source at the two frequencies, a matching analysis is performed and the source of the pipeline noise is displayed.

[0038] After clearly understanding the acoustic radiation characteristics of the external space of the pipeline, the vibration characteristics of the pipeline were tested to study the relationship between the pipeline vibration performance and its radiated noise. Therefore, PCB accelerometers were installed at the sound source location positioned by the microphone array. Two accelerometers were used to test the pipeline vibration, numbered 1 and 2 from left to right. The test results are as follows: Figure 3 and Figure 4 As shown, the vibration acceleration peaks at 1525Hz and 2278Hz, corresponding to the two noise peaks (e.g., Figure 2 (As shown). In Figure 3 and Figure 4 By comparing the frequency characteristics of pipeline noise and vibration, it can be seen that the vibration response at measuring point 1 is lower than that at measuring point 2 in the 1400–1500 Hz range, while the vibration response at measuring point 1 is higher than that at measuring point 2 in the 2000–3000 Hz range. The main vibration source is located at measuring point 2 in the 1400–1500 Hz range and at measuring point 1 in the 2000–3000 Hz range, which are the same locations as the main noise sources at the corresponding frequencies. This indicates that vibration radiation noise is the primary mode of pipeline noise formation.

[0039] To analyze the flow excitation characteristics within the pipe, a real pipe and valves were used as the research object, and a simplified three-dimensional flow field analysis model was established. The inlet pipe diameter is 0.27 m, the outlet pipe diameter is 0.3 m, and the total pipe length is 6 m, including 0.5 m before the valve, 4.6 m after the valve, and 0.9 m for the pressure regulating valve. The inlet is given a natural gas total pressure of 2.04 MPa and a temperature of 284.15 K measured at the site. The standard flow rate of natural gas in the pipe, measured at the site, is 1.41 × 10⁻⁶. 5 Nm 3 The calculated outlet velocity of the model was 25.427 m / s. Simultaneously, no-slip boundary conditions were applied to the inner wall of the pipe and the valve core wall. The calculation used an unstructured mesh with 11,932,016 elements and a first boundary layer height of 1 × 10⁻⁶. -5 m, growth rate 1.2, number of layers 33.

[0040] The airflow separates after passing the front face of the valve core and rejoins at the rear face, then travels along the pipe. Due to the change in the cross-section of the flow channel of the throttle valve, the airflow velocity increases before the throttle valve and decreases after passing the valve core. A Karman vortex street is formed after the flow passes the rear face of the throttle valve. Furthermore, the change in the cross-section of the inner wall of the pipe further increases the airflow velocity and forms localized separation vortices. The velocity decreases again after entering a straight pipe. The vortices detached from the rear face of the throttle valve and the vortices induced by the change in the cross-section of the inner wall dissipate and separate after propagating a certain distance along the pipe, forming velocity disturbances. The velocity changes are more drastic at positions 1 and 2 in the pipe, resulting in larger disturbances than at other positions, making them more likely to become excitation sources.

[0041] Analysis of the pipeline noise and vibration characteristics test results reveals that the location of maximum internal fluid disturbance coincides with the location of maximum pipeline vibration and noise. Therefore, it can be inferred that the mechanism of noise generation in gas pipelines is as follows: the airflow velocity changes at the rear end face of the throttle valve and the point where the pipeline's inner wall cross-section changes, generating eddies. These eddies propagate along the pipeline and excite pipeline vibration, radiating noise into the air and causing noise pollution.

[0042] The above description is merely an embodiment of the method of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for identifying the generation and propagation modes of pipeline noise, characterized in that: The method comprises the following steps: Step S1. Noise characteristic identification: constructing a microphone spiral array test system within a range of 5 to 10 meters of the pipeline, performing sound field scanning and array testing on the pipeline based on the microphone imaging principle, performing sound source processing according to the obtained images, and acquiring the position and frequency domain characteristics of the main noise source; Step S2. Vibration characteristic identification: arranging and installing acceleration sensors at the sound source position positioned by the microphone array, testing the vibration acceleration of the pipeline surface, verifying with the noise source position and frequency positioned by microphone imaging in step S1, and determining the main formation mode of pipeline noise through comparative analysis; Step S3. Analysis of flow characteristics in the pipeline: establishing a model according to the shape of the outer surface of the pipeline by using CFD simulation technology, setting specific parameters, setting no-slip boundary conditions on the inner wall of the pipeline and the wall surface of the valve core, adopting unstructured grids for calculation, performing excitation analysis through live simulation, and studying the flow characteristics of natural gas in the pipeline; Step S4. Determining the noise formation mechanism: analyzing the noise generation mechanism by combining the positioning result of external noise sources of the pipeline and the flow field excitation characteristics inside the pipeline, so as to provide a design basis for subsequent noise control.

2. The method for identifying the generation and propagation modes of pipeline noise according to claim 1, characterized in that: In said step S1, microphone imaging is based on a delay-and-sum beamforming algorithm, and an acoustic imaging technology is constructed to realize noise source identification. Spectral conversion is performed on sound signals collected by all microphones to obtain the spectral characteristic matrix, and then cross-spectral operation is performed; meanwhile, the space is divided into a plurality of grid points, each grid point on the scanning plane is taken as a hypothetical sound source, the sound signal received at the microphone point is calculated, then the matching degree analysis is performed on the actual measurement result and the hypothetical result, the auto-spectrum is obtained, and the matching degree with the highest value is the sound source position.

3. The method for identifying the generation and propagation modes of pipeline noise according to claim 1 or 2, characterized in that: In said step S1, the number of microphones using microphone imaging is at least 8.

4. The method for identifying the generation and propagation modes of pipeline noise according to claim 3, characterized in that: In said step S2, an acceleration sensor is used to measure the vibration response of the gas transmission pipeline, and Fourier transform is adopted to perform frequency domain analysis on the measured signal, and the basic calculation formula is: In the formula, f(t) is the measured signal, e is the natural logarithm, and i is the imaginary unit, the value of which is equal to ω is the angular frequency, measured in radians per second, and t is time, measured in seconds.

5. The method for identifying the generation and propagation modes of pipeline noise according to claim 4, characterized in that: In said step S3, when the boundary layer mesh is divided by the CFD method, for low Reynolds number flow, the actual height of the first layer of wall mesh shall ensure that the dimensionless wall distance y+ satisfies y+<5; For high Reynolds number flow, the actual height of the first layer of wall mesh shall ensure that the dimensionless wall distance y+ satisfies y+<5 or 30<y+<200; in order to capture the boundary layer flow, the growth rate of the boundary layer mesh is 1.1 to 1.3.

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