CN112550191B - Noise reduction reference signal generation method for automobile active noise reduction system - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 66
- 230000007274 generation of a signal involved in cell-cell signaling Effects 0.000 title claims description 16
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- 238000004378 air conditioning Methods 0.000 claims abstract description 5
- 238000010801 machine learning Methods 0.000 claims abstract description 5
- 239000010426 asphalt Substances 0.000 claims description 6
- 239000004568 cement Substances 0.000 claims description 6
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- 230000000694 effects Effects 0.000 claims description 5
- 230000003321 amplification Effects 0.000 claims description 4
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- 238000003199 nucleic acid amplification method Methods 0.000 claims description 4
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- 210000005069 ears Anatomy 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 abstract description 2
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
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- B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
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- B60R16/037—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for occupant comfort, e.g. for automatic adjustment of appliances according to personal settings, e.g. seats, mirrors, steering wheel
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- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
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Abstract
The invention relates to a vehicle noise reduction technology, which can obtain a steady-state noise signal transmitted to human ears in a typical scene by using a calibrated noise response function NRF and only using a vehicle Speed, an air-conditioning mode, an engine Speed rpm and the like as main signals as input signals. When the vehicle leaves a factory, a human ear steady-state noise response function NRF under each typical scene is given through real vehicle calibration; in the using process of the vehicle, different vehicle using scenes can be identified by using noise signals collected by a microphone in the vehicle through a model trained by machine learning, a proper noise response function NRF is further matched, a noise input signal required by an active noise reduction system is generated, and a required decision and feedforward noise reference signal are provided for the active noise reduction system to generate a reverse-phase noise reduction sound wave.
Description
Technical Field
The invention belongs to the field of automobiles, and relates to a noise reduction reference signal generation method of an active noise reduction system.
Background
The existing active noise reduction technology commonly used for automobiles adopts a microphone, an engine rotating speed sensor and other sensors to collect input of noise source signals, a noise reduction sound wave signal which is opposite to noise is generated through an audio operation processing circuit, then a power amplifier drives an automobile sound box to output the noise reduction sound wave to a passenger cabin, and finally the purpose of noise reduction is realized through the superposition of the noise and the space. The active noise reduction system adopting the principle has three defects: 1. the method is suitable for single noise source, and engine noise or road noise can only be subjected to noise reduction treatment generally; 2. more sensors are needed to obtain noise source signals, the noise source signals are input to a noise reduction system to be processed to generate anti-phase noise reduction signals, and the cost is high; 3. the acoustic transmission characteristic difference caused by the aging of the vehicle cannot be adapted, so that the noise reduction effect is attenuated.
Disclosure of Invention
The purpose of this patent is in order to overcome the not enough in the prior art, provides one kind and obtains the required noise reduction reference signal generation method of car initiative noise reduction system work.
In order to achieve the purpose, the invention adopts the following technical scheme:
a noise reduction reference signal generation method for an automobile active noise reduction system is characterized by comprising the following steps: the method comprises the following steps of,
the first step is as follows: the noise response function is calibrated when the vehicle leaves a factory, so as to obtain an accurate noise response function NRF under each vehicle using scene, wherein the main scenes comprise but are not limited to the following types:
(1) and idling working condition;
(2) paving a dry asphalt pavement to drive;
(3) paving the running working condition of the asphalt ponding road surface;
(4) the driving working condition of the paved cement dry pavement is set;
(5) the running working condition of the paved cement ponding road surface is set;
(6) the non-paved sandstone dry pavement driving working condition;
(7) the running working condition of the non-paved sandstone accumulated water pavement is adopted;
(8) the driving working condition of the non-paved soil dry pavement is adopted;
(9) the running working condition of the non-paved soil ponding road surface;
the air conditioning state (mode is 0,1,2,3, …), the engine speed rpm and the vehicle speed under each working condition scene are used as the input of a noise response function NRF (speed, rpm, mode), and the calibrated noise response functions NRF of each scene are loaded into the vehicle active noise reduction system;
the second step is that: in the using process of the vehicle, generating a human ear noise reference signal required by the active noise reduction system to work, and implementing a noise reduction scene identification and noise reduction signal generation step 101.
The invention uses the calibrated noise response function NRF and only uses the original sensor signals of a plurality of automobiles such as the Speed, the air-conditioning mode, the engine Speed rpm and the like as input signals, thus obtaining the steady-state noise signals transmitted to human ears in a typical scene. When the vehicle leaves a factory, the steady-state noise response function NRF of the human ear under each typical scene is given through real vehicle calibration. In the using process of the vehicle, the method can identify different vehicle using scenes by using noise signals collected by a microphone in the vehicle through a model trained by machine learning, further match a proper noise response function NRF, generate noise input signals required by an active noise reduction system, and provide required decision and feedforward noise reference signals for the active noise reduction system to generate reverse-phase noise reduction sound waves. Reducing the number of sensors required for an active noise reduction system.
Drawings
FIG. 1 is a flow chart of noise-reduced scene recognition and noise-reduced signal generation in the present invention;
fig. 2 is a flow chart of cloud calibration correction and OTA upgrade of the noise response function in the present invention.
Detailed Description
The present invention is further described below with reference to the flow chart. The method uses a calibrated noise response function NRF, and only uses original sensor signals of a plurality of automobiles such as a Speed, an air conditioner gear mode, an engine Speed rpm and the like as input signals, so that a steady-state noise signal transmitted to human ears in a typical scene can be obtained.
Firstly, the automobile using the active noise reduction system of the method needs to calibrate the noise response function when leaving the factory, and obtains the accurate noise response function NRF under each automobile scene.
The main scenarios include, but are not limited to, the following types:
1. idling condition
2. Running condition of paved asphalt dry pavement
3. Pavement asphalt ponding road surface running working condition
4. Running condition of paved cement dry pavement
5. Running condition of paved cement ponded road surface
6. Running condition of non-paved sandstone dry pavement
7. Running condition of non-paved sandstone accumulated water pavement
8. Running condition of non-paved soil dry pavement
9. Running condition of non-paved soil ponding road surface
In each operating condition scene, an air conditioner state (mode ═ 0,1,2,3, …) needs to be distinguished as a subdivision scene, and an engine speed rpm and a vehicle speed are used as the input of a noise response function NRF (speed, rpm, mode). And loading the calibrated scene noise response functions NRF into the vehicle active noise reduction system.
And secondly, generating a human ear noise reference signal required by the active noise reduction system during the use of the vehicle according to a noise reduction scene identification and noise reduction signal generation process 101 shown in the flowchart 1.
The process 101 includes the following processes:
the process 1011 uses the noise signal collected by the in-vehicle microphone through the model trained by machine learning; the process proceeds to a flow 1012 where,
the flow 1012: identifying different vehicle using scenes, and further matching a proper noise response function NRF; the process proceeds to the flow 1013,
a flow 1013, in which the matched noise response function NRF is used to input the vehicle state information air-conditioning state (mode), the engine speed rpm and the vehicle speed obtained in 1014 into NRFi; the following process is carried out in the following flow 1015,
scheme 1015: and generating a noise input signal required by the active noise reduction system, and providing a required decision and a feedforward noise reference signal for the active noise reduction system to generate the reverse-phase noise reduction sound wave. The method can achieve the aim of reducing the number of sensors required by the active noise reduction system; the following flow 1016 is resumed again in the following flow 1016,
the process 1016, the vehicle active noise reduction system, using the feedforward noise reference signal provided in the process 1015, generates the inverse noise cancellation signal, and drives the speaker through the operational amplification circuit to realize the active noise cancellation function.
After the vehicle is used for a period of time, the attribute of the vehicle noise can be changed, for example, the tire is worn and aged, so that the noise transmitted to the ears is changed in the same vehicle scene, the difference between the noise signal received by the active noise reduction system and the actual ear feeling is increased, and the noise reduction effect of the active noise reduction system is further influenced. At this time, the correction and the OTA upgrade process 201 can be executed according to the cloud calibration correction and OTA upgrade process 201 of the noise response function shown in the flowchart 2, so as to perform the correction and upgrade on the noise response function NRF in the vehicle-mounted active noise reduction system. The process 201 includes the following sub-processes,
the process 2011: when the difference between the noise reduction effect and the factory state exceeds a preset standard, the NRF correction process of the active noise reduction system can be started by using the online cloud correction and OTA online upgrade method; the following procedure is continued to be followed,
the process 2012: acquiring vehicle information and a noise signal of an in-vehicle microphone in a typical scene, and uploading the vehicle information and the noise signal to a cloud noise reduction response function correction system server; in carrying out the following procedure, the following procedure was carried out,
the process 2013: running a noise response function NRF updating program deployed at the cloud end on a noise reduction response function correction system server through a cloud calibration method to finish the correction of the noise response function NRF and obtain a corrected new version of the noise response function NRF (V2); finally, the following procedures are carried out,
flow 2014: and then, pushing the corrected and updated new version noise response function NRF (V2) to the vehicle through an OTA online upgrade program, updating the steady-state noise response function NRF deployed in the vehicle active noise reduction system, and recovering the noise reduction effect of the active noise reduction system.
The number of noise sensors used by an active noise reduction system is reduced by using a vehicle scene noise response function calibration method, a microphone in a passenger cabin is used for collecting noise signals, a matched noise response function is selected by judging a vehicle environment through a machine learning model, an input noise signal of the active noise reduction system is generated, a noise reduction signal is generated through system processing to drive a loudspeaker to generate noise reduction sound waves, and a noise reduction target is achieved. The problem of performance reduction of an active noise reduction system caused by NVH performance attenuation of a vehicle is solved through a cloud calibration and OTA online upgrading method.
Claims (7)
1. A noise reduction reference signal generation method for an automobile active noise reduction system is characterized by comprising the following steps: the method comprises the following steps of,
the first step is as follows: the noise response function is calibrated when the vehicle leaves a factory, so as to obtain an accurate noise response function NRF under each vehicle using scene, wherein the main scenes comprise but are not limited to the following types:
(1) and idling working condition;
(2) paving the asphalt dry pavement to run;
(3) paving the asphalt ponding road surface to run;
(4) the driving working condition of the paved cement dry pavement is adopted;
(5) the running working condition of the paved cement ponding road surface is adopted;
(6) the non-paved sandstone dry pavement driving working condition;
(7) the running working condition of the non-paved sandstone accumulated water pavement is adopted;
(8) the running working condition of the non-paved soil dry pavement is described;
(9) the running working condition of the non-paved soil ponding road surface is adopted;
the air conditioning state (mode is 0,1,2,3, …), the engine speed rpm and the vehicle speed under each working condition scene are used as the input of a noise response function NRF (speed, rpm, mode), and the calibrated noise response functions NRF of each scene are loaded into the vehicle active noise reduction system;
the second step is that: in the using process of a vehicle, the generation of human ear noise reference signals required by the work of the active noise reduction system identifies different vehicle scenes, then a proper noise response function NRF is matched, then noise input signals required by the active noise reduction system are generated, the vehicle-mounted active noise reduction system generates anti-phase noise elimination signals by using the noise input signals, and the operational amplification circuit drives the loudspeaker to realize the active noise elimination function.
2. The noise reduction reference signal generation method according to claim 1, characterized in that: the noise reduction scene recognition and noise reduction signal generation steps are performed according to the following process 101:
the process 1011: the model trained by machine learning uses the noise signal collected by the in-vehicle microphone, and the following step 1012 is continued;
the flow 1012: identifying different vehicle using scenes, further matching a proper noise response function NRF, and continuing to the step 1013;
flow 1013: using the matched noise response function NRF and continuing with step 1015 described below;
scheme 1015: generating a noise input signal required by the active noise reduction system, and continuing with flow 1016; the flow 1016: the vehicle-mounted active noise reduction system generates an inverted noise reduction signal by using the noise input signal provided by the process 1015, and drives the loudspeaker through the operational amplification circuit to realize the active noise reduction function.
3. The noise reduction reference signal generation method according to claim 2, characterized in that: the process 1015 generates the noise input signal required by the active noise reduction system, and provides the required decision and feedforward noise reference signal for the active noise reduction system to generate the inverse noise reduction sound wave.
4. The noise reduction reference signal generation method according to claim 2 or 3, characterized in that: in the process 1016, the vehicle-mounted active noise reduction system generates an inverse noise reduction signal by using the feedforward noise reference signal provided in the process 1015, and drives the horn through the operational amplification circuit to realize the active noise reduction function.
5. The noise reduction reference signal generation method according to claim 2 or 3, characterized in that: the matched noise response function NRF in the process 1013 inputs the signals obtained in the process 1014, and the vehicle state information acquired by the process 1014 comprises an air conditioner state (mode), an engine speed rpm and a vehicle speed; then, the process goes to the flow 1015.
6. The noise reduction reference signal generation method according to claim 1, characterized in that: after the vehicle has been in use for a period of time, flow 201 is performed,
the process 201: and (3) carrying out cloud calibration correction and OTA (over the air) upgrade on the noise response function, and carrying out correction upgrade on a NRF (noise response function) in the vehicle-mounted active noise reduction system.
7. The noise reduction reference signal generation method according to claim 6, characterized in that: the process 201 is modified and upgraded according to the following procedures,
the process 2011: when the difference between the noise reduction effect and the factory state exceeds a preset standard, starting an NRF correction process of the active noise reduction system by using online cloud correction and OTA online upgrade;
the process 2012: vehicle information and in-vehicle microphone noise signals under a typical scene are collected and uploaded to a cloud noise reduction response function correction system server;
the process 2013: running a noise response function NRF updating program deployed at the cloud end on a noise reduction response function correction system server through a cloud calibration method to finish the correction of the noise response function NRF and obtain a corrected new version of the noise response function NRF (V2);
flow 2014: and pushing the corrected and updated new version NRF (V2) to the vehicle through an OTA online upgrade program, and updating and deploying a steady-state noise response function NRF in the vehicle active noise reduction system.
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