A system and method for predicting track radiation noise

Abstract

The invention discloses a track radiation noise prediction system and method for a rail transit system. The system comprises a data acquisition module, a data processing module and a data analysis module. The data acquisition module comprises an acceleration sensor and a microphone. The acceleration sensor comprises a first acceleration sensor and a second acceleration sensor. The first acceleration sensor is arranged on a rail at intervals and arranged along a driving direction to collect a first vibration signal. The second acceleration sensor is arranged on the sleeper at intervals and arranged along a driving direction to collect a second vibration signal. The microphone comprises a first microphone, which is arranged at a first position outside the rail to collect a first sound pressure signal. The data processing module processes data from the data acquisition module. The data analysis module is used for receiving data sent by the data processing module and performing analysis and calculation to obtain a radiation noise value, and publishing a method corresponding to the system, thereby separating the radiation noise of the track and the vehicle.

Description

Technical Field

[0001] The present invention relates to the field of rail transit technology, and in particular to a system and method for predicting rail radiation noise. Background Art

[0002] As people have higher and higher requirements for the noise inside rail transit vehicles and the noise in the track environment, wheel-rail noise, as the main noise source, has become the focus of people's attention. Due to the coupling effect of vehicle and wheel-rail noise, it is difficult to separate the radiated noise of the track with existing methods.

[0003] A locomotive cab noise control system in the prior art (Announcement No.: CN 206475875U) can perform real-time noise data analysis and processing based on changes in the cab noise environment, adaptively generate a cancellation signal with a phase opposite to the noise, and realize adaptive cab noise control to solve the low-frequency noise problem caused by structural vibration in the locomotive cab. However, the system does not analyze the source of noise and does not separate the noise from the vehicle and the track. Summary of the invention

[0004] The object of the present invention is to provide a track radiation noise prediction system and method to separate the noise of the track and the vehicle, thereby providing assistance for subsequent rapid and effective optimization.

[0005] Based on the above purpose, the technical solution provided by the present invention is as follows:

[0006] A track radiation noise prediction system is used in a rail transit system, wherein the rail transit system comprises a track and a vehicle, wherein the track comprises a sleeper and two rails arranged in parallel and supported on the sleeper.

[0007] The track radiation noise prediction system includes a data acquisition module, a data processing module, and a data analysis module;

[0008] The data acquisition module includes an acceleration sensor and a microphone, wherein the acceleration sensor includes a plurality of first acceleration sensors and a plurality of second acceleration sensors, wherein the plurality of first acceleration sensors are arranged at intervals on the rail and arranged along the driving direction to collect a first vibration signal, and the plurality of second acceleration sensors are arranged at intervals on the sleeper and arranged along the driving direction to collect a second vibration signal, and the microphone includes a first microphone, and the first microphone is arranged at a first position outside the rail to collect a first sound pressure signal;

[0009] The first acceleration sensor, the second acceleration sensor, and the first microphone are all connected to the data processing module. The data processing module is used to receive and process the first vibration signal, the second vibration signal, and the first sound pressure signal and send them together to the data analysis module. The data analysis module is used to receive the data sent by the data processing module and perform analysis and calculation to obtain the radiation noise value.

[0010] When the vehicle is stationary on the track, a hammer is used to hit the accessories of each acceleration sensor (including the first acceleration sensor and the second acceleration sensor), the data of the acceleration sensors are collected, and the vibration-acoustic transfer function between the position of each acceleration sensor and the first microphone is obtained. Then, the data of each acceleration sensor when the vehicle passes through the track at different speeds is measured, and the track radiation noise value when the vehicle passes is predicted in combination with the vibration-acoustic transfer function obtained when the vehicle is stationary. The track radiation noise is separated from the total noise. The total noise is the combination of the track radiation noise and the vehicle radiation noise. Separating the track radiation noise is equivalent to separating the radiation noise of the track and the vehicle.

[0011] As a further embodiment, the microphone also includes a second microphone, which is arranged at a second position on the outside of the rail to collect a second sound pressure signal. The second microphone is electrically connected to the data processing module, and the data processing module is used to receive and process the second sound pressure signal and send it to the data analysis module.

[0012] The noise value is collected by the second microphone, and then the predicted value of the track radiation noise is subtracted by an acoustic calculation method to obtain the vehicle radiation noise value. The acoustic calculation method adopts the sound pressure calculation method in the prior art. The specific calculation formula is as follows:

[0013]

[0014] Where P 车辆 is the sound pressure level of vehicle radiated noise when the vehicle is running, P 总 is the overall radiated noise sound pressure level when the vehicle is running, P 轨道 It is the sound pressure level of track radiated noise when the vehicle is running.

[0015] As a further embodiment, the data processing module processes the data according to the acoustic transfer function between the acceleration excitation load produced at the location of each acceleration sensor and the received sound pressure value of the microphone, wherein the acceleration excitation load is a vibration signal collected by the acceleration sensor when the vehicle is stationary or moving, the received sound pressure value is a noise signal collected by the microphone when the vehicle is stationary or moving, and the acoustic transfer function is obtained by using an advanced transfer path analysis method;

[0016] Direct transfer function of vibration to microphone position at each acceleration position

[0017] Where i = 1, 2, ..., n, j represents the microphone number, j = 1 is the far-field microphone, j = 2 is the short-range microphone;

[0018] When a knock occurs at each acceleration position, the ratio of each acceleration test value to the acceleration value of the knock position; It is the ratio of the microphone sound pressure level to the acceleration test value when the knock occurs at each acceleration position; n=N1+N2+M, N1 is the number of acceleration sensors on the first rail, N2 is the number of acceleration sensors on the second rail, M is the number of acceleration sensors on the sleeper, and N1, N2, and M are all natural numbers greater than or equal to 1.

[0019] As a further embodiment, the first position is 3 meters away from the outer side of the rail and 1.2 meters high, and the second position is 7.5 meters away from the outer side of the rail and 1.2 meters high. The first position is 3 meters away and 1.2 meters high, and the second position is 7.5 meters away and 1.2 meters high, which is a preferred embodiment.

[0020] As a further embodiment, the data processing module performs processing based on an acoustic transfer function between an acceleration excitation load produced at the location of each acceleration sensor and a received sound pressure value of the microphone, wherein the acceleration excitation load is a vibration signal collected by the acceleration sensor when the vehicle is stationary or moving, the received sound pressure value is a noise signal collected by the microphone when the vehicle is stationary or moving, and the acoustic transfer function is obtained using an advanced transfer path analysis method.

[0021] The noise transfer function (NTF) refers to the corresponding functional relationship between the excitation load input by the acceleration sensor and the noise output by the microphone. According to the noise transfer theory, the target point sound pressure response of the noise prediction value is obtained based on the transfer function and the excitation force, specifically:

[0022] P(w)=H p (w)*F(w)

[0023] Where: P(w) is the sound pressure response at the target point, H p (w) is the transfer function from the excitation point to the target point, and F(w) is the frequency spectrum of the excitation force.

[0024] TPA (Transfer Path Analysis) and ATPA (Advanced Transfer Path Analysis) are both existing technologies. ATPA is an advanced transfer path method proposed by Mgrans, JSV and others to solve the defects of cumbersome traditional TPA test process and low accuracy of OTPA. This method theoretically realizes the decoupling of various transfer paths and improves the test accuracy. At the same time, it eliminates the need to disassemble the excitation source, thus avoiding the authenticity problem of the measured frequency response function caused by disassembling the excitation source. It is a transfer path analysis method with both accuracy and efficiency.

[0025] Corresponding to the above-mentioned track radiation noise prediction system is a track radiation noise prediction method, which further includes the following specific steps:

[0026] S1: Arrange N1 and N2 acceleration sensors on the rails on both sides along the driving direction, and arrange M acceleration sensors on the sleepers along the driving direction. The acceleration sensors are all connected to the data processing module, where N1, N2, and M are all natural numbers greater than or equal to 1;

[0027] S2: The vehicle is stationary on the track, and a knocking object is used to knock the rail or the sleeper at the position where the acceleration sensor is arranged, and the sound transfer function between the position of each acceleration sensor and the microphone is obtained through advanced transfer path analysis; the microphone is arranged on the outer side of the rail to collect the sound pressure signal;

[0028]

[0029] Where i = 1, 2, ..., n, j represents the microphone number, j = 1 is the far-field microphone, j = 2 is the short-range microphone;

[0030] is the direct transfer function of the vibration to the microphone position when struck for each acceleration position; When a knock occurs at each acceleration position, the ratio of each acceleration test value to the acceleration value of the knock position; It is the ratio of the microphone sound pressure level to the acceleration test value when the knock occurs at each acceleration position; n = N1 + N2 + M;

[0031] S3: When the vehicle passes through the test position track at different speeds, the acceleration sensor data is measured;

[0032] S4: In the data analysis module, the predicted value of the track radiated noise when the vehicle passes is calculated using the data of the acceleration sensor test when the vehicle passes and the sound transfer function of the vehicle at static pressure.

[0033] As a further embodiment, the microphone includes a first microphone and a second microphone, the first microphone is arranged at a first position outside the rail to collect a first sound pressure signal, and the second microphone is arranged at a second position outside the rail to collect a second sound pressure signal, and further includes the steps of:

[0034] S5: obtaining the noise value of the second microphone when the vehicle passes by through advanced transfer path analysis, calculating the noise value of the first microphone according to the transfer function between the second microphone and the first microphone, and subtracting the predicted value of track radiation noise from the noise value of the first microphone in an acoustic calculation manner to obtain the radiation noise value of the vehicle;

[0035] The transfer function from the second microphone to the first microphone is:

[0036] T kl =L pl / L pk

[0037] Among them, when k=1, l=2; when k=2, l=3; and so on;

[0038] L pl is the sound pressure level measured by the microphone at position l, L pk is the sound pressure level measured by the microphone at position k.

[0039] As a preferred embodiment, the number of acceleration sensors arranged on each side of the rail along the driving direction and on the sleeper along the driving direction is 6 to 10.

[0040] Beneficial effects achieved by the present invention:

[0041] The present invention provides a track radiation noise prediction system and method, which separates the noise of the track and the vehicle, thereby providing assistance for subsequent rapid and effective optimization (such as noise peak optimization, structural optimization, etc.). BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of a track radiation noise prediction system according to an embodiment of the present invention;

[0043] Figure 2 This is a path analysis diagram of the track radiation noise prediction system according to an embodiment of the present invention.

[0044] Wherein: 1. rail, 2. sleeper, 3. fastener, 4. wheel, 10. data acquisition module, 11. first acceleration sensor, 12. second acceleration sensor, 13. first microphone, 14. second microphone, 20. data processing module, 30. data analysis module. DETAILED DESCRIPTION

[0045] like Figure 1 As shown, a track radiation noise prediction system is used in a rail transit system, the rail transit system includes a track and a vehicle, the track includes a sleeper 2, and two rails 1 arranged in parallel and supported on the sleeper, the rail 1 is connected to the sleeper 2 by a fastener 3, six first acceleration sensors 11 are arranged on each side of the rail 1 along the driving direction (the wheels 4 of the stationary vehicle on the track avoid directly pressing on the acceleration arrangement position of the rail) (the rail is located in the middle position of two adjacent sleepers), six second acceleration sensors 12 are arranged on the sleeper 2 along the driving direction, and two microphones (13, 14) are arranged at 3m (1.5m to 4.5m, 3m is a preferred method) and 7.5m away and 1.2m high on one side of the track respectively.

[0046] like Figure 2 As shown, the track radiation noise prediction system includes a data acquisition module 10, a data processing module 20, and a data analysis module 30. The data acquisition module 10 includes a first acceleration sensor 11, a second acceleration sensor 12, a first microphone 13, and a second microphone 14. A plurality of first acceleration sensors 11 are arranged on the rail 1 at intervals and arranged along the driving direction to collect a first vibration signal. A plurality of second acceleration sensors 12 are arranged on the sleeper 2 at intervals and arranged along the driving direction to collect a second vibration signal. The microphones include a first microphone 13 and a second microphone 14. The first microphone 13 is arranged at a first position outside the rail 1 to collect a first sound pressure signal (far field, The first accelerometer 11, the second accelerometer 12, the first microphone 13 and the second microphone 14 are all connected to the data processing module 20, and the data processing module 20 is used to receive and process the first vibration signal, the second vibration signal and the first sound pressure signal and the second sound pressure signal and send them together to the data analysis module 30, and the data analysis module 30 is used to receive the data sent by the data processing module 20 and analyze and calculate to obtain the radiated noise value.

[0047] When the vehicle is stationary on the track, a hammer is used to strike the vicinity of each acceleration sensor (including the first acceleration sensor 11 and the second acceleration sensor 12), and the data of the acceleration sensors are collected to obtain the vibration-acoustic transfer function between the location of each acceleration sensor and the first microphone, and the transfer function between the first microphone 13 and the second microphone 14. (Note that the reason for setting up a near-field microphone is that when the background noise is large, when establishing the track ATPA transfer function, the sound of striking the sleeper or track is small, and when it is transmitted to a long distance (such as 7.5 meters), the noise is even smaller and is easily affected by the background. Noise interference, and the use of near-field microphones can effectively solve this problem; when the rail is tapped at a position where the background is low and closest to the remote microphone, a transfer function between the near-field microphone and the remote microphone can be established), and then the data of each acceleration sensor when the vehicle passes through the track at different speeds is measured, and the vibration sound transfer function obtained when it is stationary is combined to predict the track radiation noise value when the vehicle passes, and the track radiation noise is separated from the total noise. The total noise is the combination of the track radiation noise and the vehicle radiation noise. Separating the track radiation noise is equivalent to separating the radiation noise of the track and the vehicle. Specifically, the construction method of the track radiation noise prediction system is as follows:

[0048] First, the vehicle is stationary on the track, and a hammer is used to hit the vicinity of each acceleration sensor to collect data from the acceleration sensors (including the first acceleration sensor 11 and the second acceleration sensor 12), and obtain the acoustic transfer function between the location of each acceleration sensor and the first microphone 13 (the first microphone 13 and the second microphone 14 can both be microphones). The first microphone is located 3 meters away and 1.2 meters high on one side of the track.

[0049] The "vibration-acoustic" acoustic transfer function between the location of each accelerometer and the microphone is obtained by using an advanced transfer path analysis (ATPA) method.

[0050] Transfer Path Analysis (TPA) is a research method for solving noise vibration and harshness (NVH) problems. After more than 20 years of development, this method has been widely used in the location of noise and vibration sources at home and abroad, and has been widely recognized in the field of NVH. In practical applications, the transfer path analysis method has derived many methods, among which the traditional TPA method is currently the most widely used method. TPA and ATPA are both existing technologies. ATPA is an advanced transfer path method proposed by Mgrans, JSV and others to solve the defects of the cumbersome traditional TPA test process and the low accuracy of OTPA. This method theoretically realizes the decoupling of each transfer path and improves the test accuracy; at the same time, it eliminates the need to disassemble the excitation source, avoiding the authenticity problem of the measured frequency response function caused by the disassembly of the excitation source. It is a transfer path analysis method with both accuracy and efficiency.

[0051] Second, when the vehicle passes through the test location track at different speeds, the data of the above sensors are measured, and the "vibration-sound" transfer function obtained when the vehicle passes by and the static pressure of the vehicle are used to predict the track radiation noise when the vehicle passes by.

[0052] Third, a second microphone 14 is added. The second microphone is located at a height of 1.2 meters, 7 meters away, on one side of the track. The microphone noise collected when the vehicle passes by is subtracted from the predicted value of the track radiation noise by acoustic calculation to obtain the vehicle radiation noise.

[0053] The above method can separate the radiated noise of the track and the vehicle, and effectively predict the predicted value of the track radiated noise, with a prediction accuracy within 1dB.

[0054] Finally, it should be noted that the contents described in the above embodiments should be understood as these embodiments are only used to more clearly illustrate the present invention, and are not used to limit the scope of the present invention. After reading the present invention, various equivalent forms of modifications to the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

Claims

1. A rail radiated noise prediction system, used in a rail transit system, wherein the rail transit system comprises a track and a vehicle, wherein the track comprises a sleeper and two rails arranged in parallel and supported on the sleeper, wherein: The track radiation noise prediction system includes a data acquisition module, a data processing module, and a data analysis module; The data acquisition module includes an acceleration sensor and a microphone, wherein the acceleration sensor includes a plurality of first acceleration sensors and a plurality of second acceleration sensors, wherein the plurality of first acceleration sensors are arranged at intervals on the rail and arranged along the driving direction to collect a first vibration signal, and the plurality of second acceleration sensors are arranged at intervals on the sleeper and arranged along the driving direction to collect a second vibration signal, and the microphone includes a first microphone, and the first microphone is arranged at a first position outside the rail to collect a first sound pressure signal; The first acceleration sensor, the second acceleration sensor, and the first microphone are all electrically connected to the data processing module, and the data processing module is used to receive and process the first vibration signal, the second vibration signal, and the first sound pressure signal and send them together to the data analysis module, and the data analysis module is used to receive the data sent by the data processing module and perform analysis and calculation to obtain the radiation noise value; S1: Arrange N1 and N2 acceleration sensors on the rails on both sides along the driving direction, and arrange M acceleration sensors on the sleepers along the driving direction. The acceleration sensors are all connected to the data processing module, where N1, N2, and M are all natural numbers greater than or equal to 1; S2: The vehicle is stationary on the track, and a knocking object is used to knock the rail or the sleeper at a position where an acceleration sensor is arranged, and the acoustic transfer function between the position of each acceleration sensor and the microphone is obtained through advanced transfer path analysis; the microphone is arranged on the outer side of the rail to collect the sound pressure signal; the microphone includes a first microphone and a second microphone, the first microphone is arranged at a first position on the outer side of the rail to collect the first sound pressure signal, and the second microphone is arranged at a second position on the outer side of the rail to collect the second sound pressure signal; Where i = 1, 2, ..., n, j represents the microphone number, j = 1 is the far-field microphone, j = 2 is the short-range microphone; is the direct transfer function of the vibration to the microphone position when struck for each acceleration position; When a knock occurs at each acceleration position, the ratio of each acceleration test value to the acceleration value of the knock position; It is the ratio of the microphone sound pressure level to the acceleration test value when the knock occurs at each acceleration position; n = N1 + N2 + M; S3: When the vehicle passes through the test position track at different speeds, the acceleration sensor data is measured; S4: In the data analysis module, the predicted value of the track radiated noise when the vehicle passes is calculated using the data of the acceleration sensor test when the vehicle passes and the sound transfer function of the vehicle at static pressure; S5: obtaining the noise value of the second microphone when the vehicle passes by through advanced transfer path analysis, calculating the noise value of the first microphone according to the transfer function between the second microphone and the first microphone, and subtracting the predicted value of track radiation noise from the noise value of the first microphone in an acoustic calculation manner to obtain the radiation noise value of the vehicle; The transfer function from the second microphone to the first microphone is: T kl =L pl / L pk Among them, when k=1, l=2; when k=2, l=3; and so on; L pl is the sound pressure level measured by the microphone at position l, L pk is the sound pressure level measured by the microphone at position k.

2. The track radiation noise prediction system according to claim 1, characterized in that: The microphone also includes a second microphone, which is arranged at a second position outside the rail to collect a second sound pressure signal. The second microphone is electrically connected to the data processing module, and the data processing module is used to receive and process the second sound pressure signal and send it to the data analysis module.

3. The track radiation noise prediction system according to claim 1 or 2, characterized in that: The data processing module performs processing according to the acoustic transfer function between the acceleration excitation load produced at the location of each acceleration sensor and the received sound pressure value of the microphone, wherein the acceleration excitation load is a vibration signal collected by the acceleration sensor when the vehicle is stationary or moving, the received sound pressure value is a noise signal collected by the microphone when the vehicle is stationary or moving, and the acoustic transfer function is obtained by using an advanced transfer path analysis method; Direct transfer function of vibration to microphone position at each acceleration position Where i = 1, 2, ..., n, j represents the microphone number, j = 1 is the far-field microphone, j = 2 is the short-range microphone; When a knock occurs at each acceleration position, the ratio of each acceleration test value to the acceleration value of the knock position; It is the ratio of the microphone sound pressure level to the acceleration test value when the knock occurs at each acceleration position; n=N1+N2+M, N1 is the number of acceleration sensors on the first rail, N2 is the number of acceleration sensors on the second rail, M is the number of acceleration sensors on the sleeper, and N1, N2, and M are all natural numbers greater than or equal to 1.

4. A method for constructing a track radiation noise prediction system, characterized in that: The method further comprises the following specific steps: S1: Arrange N1 and N2 acceleration sensors on the rails on both sides along the driving direction, and arrange M acceleration sensors on the sleepers along the driving direction. The acceleration sensors are all connected to the data processing module, where N1, N2, and M are all natural numbers greater than or equal to 1; S2: The vehicle is stationary on the track, and a knocking object is used to knock the rail or the sleeper at a position where an acceleration sensor is arranged, and the acoustic transfer function between the position of each acceleration sensor and the microphone is obtained through advanced transfer path analysis; the microphone is arranged on the outer side of the rail to collect the sound pressure signal; the microphone includes a first microphone and a second microphone, the first microphone is arranged at a first position on the outer side of the rail to collect the first sound pressure signal, and the second microphone is arranged at a second position on the outer side of the rail to collect the second sound pressure signal; Where i = 1, 2, ..., n, j represents the microphone number, j = 1 is the far-field microphone, j = 2 is the short-range microphone; is the direct transfer function of the vibration to the microphone position when struck for each acceleration position; When a knock occurs at each acceleration position, the ratio of each acceleration test value to the acceleration value of the knock position; It is the ratio of the microphone sound pressure level to the acceleration test value when the knock occurs at each acceleration position; n = N1 + N2 + M; S3: When the vehicle passes through the test position track at different speeds, the acceleration sensor data is measured; S4: In the data analysis module, the predicted value of the track radiated noise when the vehicle passes is calculated using the data of the acceleration sensor test when the vehicle passes and the sound transfer function of the vehicle at static pressure; S5: obtaining the noise value of the second microphone when the vehicle passes by through advanced transfer path analysis, calculating the noise value of the first microphone according to the transfer function between the second microphone and the first microphone, and subtracting the predicted value of track radiation noise from the noise value of the first microphone in an acoustic calculation manner to obtain the radiation noise value of the vehicle; The transfer function from the second microphone to the first microphone is: T kl =L pl / L pk Among them, when k=1, l=2; when k=2, l=3; and so on; L pl is the sound pressure level measured by the microphone at position l, L pk is the sound pressure level measured by the microphone at position k.

5. The method for constructing a track radiation noise prediction system according to claim 4, characterized in that: The number of acceleration sensors arranged on each side of the rail along the driving direction and on the sleeper along the driving direction is 6 to 10.

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