High-frequency noise filtering method and system based on sound wave interference

Abstract

The invention relates to the technical field of acoustic processing, in particular to a high-frequency noise filtering method and system based on sound wave interference, and the system comprises a sound wave monitoring module, a frequency monitoring module and a noise filtering module. Sound wave intensity and frequency distribution data of a target environment are obtained, a noise filtering adjustment coefficient is generated by combining partition monitoring and a sound wave interference principle, and filtering parameters are dynamically adjusted to realize high-frequency noise separation. According to the invention, the accuracy and adaptability of high-frequency noise filtering can be effectively improved, and the distortion of the target signal is reduced, so that the overall acoustic experience is optimized.

Description

Technical Field

[0001] The present invention belongs to the technical field of acoustic signal processing and noise control, and specifically relates to a high-frequency noise filtering method and system based on sound wave interference. Background Art

[0002] Existing high-frequency noise filtering methods have the following specific limitations when processing sound waves:

[0003] Existing high-frequency noise filtering methods mainly rely on traditional filter structures, which have limited effectiveness in suppressing high-frequency noise in complex environments, easily leading to distortion of the target signal and affecting the overall acoustic experience.

[0004] Existing high-frequency noise filtering methods rarely utilize the principle of acoustic wave interference for optimization processing, making it difficult to achieve accurate separation of noise in specific frequency bands. As a result, there is room for improvement in the accuracy and adaptability of the filtering results. Summary of the Invention

[0005] The present invention belongs to the field of acoustic processing technology, and relates to high-frequency noise filtering technology, in particular to a high-frequency noise filtering method and system based on sound wave interference.

[0006] Existing high-frequency noise filtering methods have the following specific limitations when processing sound waves: existing high-frequency noise filtering methods mainly rely on traditional filter structures, which have limited effects on suppressing high-frequency noise in complex environments, easily leading to distortion of target signals and affecting the overall acoustic experience; existing high-frequency noise filtering methods rarely utilize the principle of sound wave interference for optimization processing, making it difficult to achieve accurate separation of noise in specific frequency bands, which leaves room for improvement in the accuracy and adaptability of the filtering results.

[0007] To this end, we propose a high-frequency noise filtering method and system based on acoustic wave interference.

[0008] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a high-frequency noise filtering method and system based on acoustic wave interference. The present invention aims to improve the accuracy and adaptability of high-frequency noise filtering while reducing the distortion of the target signal.

[0009] In order to achieve the above object, the present invention adopts the following technical solution: a high-frequency noise filtering method based on acoustic wave interference, comprising the following specific steps:

[0010] Step S1: Obtain a sound wave collection period, select several characteristic time points within the sound wave collection period, monitor the target environment in the sound wave collection period for sound wave data, obtain an environmental period monitoring sound wave value, obtain a sound wave monitoring index value corresponding to each characteristic time point, and perform a comprehensive analysis on the obtained multiple sound wave monitoring index values to obtain a sound wave real-time monitoring coefficient, and define the sound wave collection period, the environmental period monitoring sound wave value, and the sound wave real-time monitoring coefficient as periodic sound wave monitoring data;

[0011] Step S2: Selecting a number of frequency characteristic time points within the acoustic wave acquisition period, obtaining the frequency monitoring index value corresponding to each frequency characteristic time point, and performing a comprehensive analysis on the obtained multiple frequency monitoring index values to obtain a frequency real-time monitoring coefficient;

[0012] Step S3: filtering and controlling the high-frequency noise according to the periodic sound wave monitoring data and the frequency real-time monitoring coefficient.

[0013] Furthermore, step S1 further includes the following specific steps:

[0014] Step S11: obtaining a sound wave intensity value in real time through a sound wave sensor installed in the target environment, obtaining a real-time sound wave intensity value, and obtaining a real-time sound wave intensity threshold value; if the real-time sound wave intensity value is greater than or equal to the real-time sound wave intensity threshold value, marking the time value corresponding to the current moment as a first characteristic time point; if the real-time sound wave intensity value is less than the real-time sound wave intensity threshold value, the sound wave sensor continues to perform sound wave monitoring on the target environment;

[0015] Step S12: Taking the first characteristic time point as the cycle start time point, marking a number of acoustic wave monitoring time points in the period after the first characteristic time point, marking the time interval between two consecutive acoustic wave monitoring time points as an acoustic wave collection cycle, obtaining multiple acoustic wave collection cycles, and naming the acoustic wave collection cycle where the cycle start time point is located as the acoustic wave real-time monitoring cycle among the multiple acoustic wave collection cycles obtained;

[0016] Step S13: within the acoustic wave real-time monitoring period, mark a number of acoustic wave monitoring time points, with the interval between each two consecutive acoustic wave monitoring time points being equal in length, and the marked acoustic wave monitoring time points are named in chronological order as the first acoustic wave monitoring time point to the wth acoustic wave monitoring time point;

[0017] Step S14: obtaining a plurality of sound wave intensity values of the target environment from the first sound wave monitoring time point to the wth sound wave monitoring time point, and averaging the obtained plurality of sound wave intensity values to obtain a sound wave value for environmental periodic monitoring;

[0018] Step S15: performing acoustic wave data monitoring on the target environment at the first acoustic wave monitoring time point, and obtaining a first acoustic wave monitoring index value according to the monitoring result;

[0019] Step S16: acquiring the acoustic wave monitoring index values corresponding to the second acoustic wave monitoring time point to the wth acoustic wave monitoring time point respectively, to obtain the second acoustic wave monitoring index value to the wth acoustic wave monitoring index value;

[0020] Step S17: Calculate the average of the first to wth acoustic wave monitoring index values to obtain the acoustic wave real-time monitoring coefficient;

[0021] Step S18: defining the acoustic wave real-time monitoring period, the environmental periodic monitoring acoustic wave value, and the acoustic wave real-time monitoring coefficient as periodic acoustic wave monitoring data.

[0022] Furthermore, step S15 further includes the following specific steps:

[0023] Step S151: Divide the target environment into a plurality of acoustic wave monitoring areas at different locations, and name the marked acoustic wave monitoring areas as the first acoustic wave monitoring area to the ath acoustic wave monitoring area respectively;

[0024] Step S152: respectively obtaining area values corresponding to the first acoustic wave monitoring area to the ath acoustic wave monitoring area, and obtaining area values of the first acoustic wave area to the ath acoustic wave area;

[0025] Step S153: using the acoustic wave sensor to obtain the contact area values of the first acoustic wave monitoring area to the ath acoustic wave monitoring area and the target sound source, respectively, to obtain the first acoustic wave contact area value to the ath acoustic wave contact area value;

[0026] Step S154: Calculate the ratio of the first acoustic wave contact area value to the first acoustic wave region area value to obtain the first acoustic wave area contact ratio; calculate the ratio of the second acoustic wave contact area value to the second acoustic wave region area value to obtain the second acoustic wave area contact ratio; and so on, calculate the ratio of the a-th acoustic wave contact area value to the a-th acoustic wave region area value to obtain the a-th acoustic wave area contact ratio;

[0027] Step S155: respectively obtaining the real-time sound wave intensity values corresponding to the first sound wave monitoring area to the ath sound wave monitoring area at the first sound wave monitoring time point, and obtaining the real-time sound wave intensity values of the first area to the ath area;

[0028] Step S156: calculating the first acoustic wave monitoring index value by dividing the real-time acoustic wave intensity value of the first region by the real-time acoustic wave intensity value of the a-th region and the first acoustic wave area contact ratio by the a-th acoustic wave area contact ratio;

[0029] The first sound wave monitoring index value is calculated, and the specific formula is as follows:

[0030]

[0031] Among them, Yzb1 is the first sound wave monitoring index value, Yqi is the real-time sound wave intensity value of the i-th area, Ymi is the i-th sound wave area contact ratio, and a is the number value of the sound wave monitoring area.

[0032] Furthermore, step S2 further includes the following specific steps:

[0033] Step S21: Acquire periodic frequency monitoring data, and acquire the acoustic wave real-time monitoring period according to the periodic frequency monitoring data;

[0034] Step S22: Marking a number of frequency monitoring time points within the acoustic wave real-time monitoring period, with the interval between each two consecutive frequency monitoring time points being equal in length, and naming the marked frequency monitoring time points in chronological order as the first frequency monitoring time point to the sth frequency monitoring time point;

[0035] Step S23: performing frequency data monitoring on the target environment at the first frequency monitoring time point, and obtaining a first frequency monitoring index value according to the monitoring result;

[0036] Step S24: acquiring the frequency monitoring index values corresponding to the second frequency monitoring time point to the sth frequency monitoring time point respectively, to obtain the second frequency monitoring index value to the sth frequency monitoring index value;

[0037] Step S25: Calculate the average of the first frequency monitoring index value to the sth frequency monitoring index value to obtain the frequency real-time monitoring coefficient.

[0038] Furthermore, step S23 further includes the following specific steps:

[0039] Step S231: Divide the target environment into a number of frequency monitoring areas at different locations, and name the marked frequency monitoring areas as the first frequency monitoring area to the bth frequency monitoring area respectively;

[0040] Step S232: respectively obtaining area values corresponding to the first frequency monitoring area to the bth frequency monitoring area, and obtaining area values of the first frequency area to the bth frequency area;

[0041] Step S233: using an acoustic wave sensor to obtain contact area values between the first frequency monitoring area and the bth frequency monitoring area and the target sound source, thereby obtaining contact area values between the first frequency and the bth frequency;

[0042] Step S234: Calculate the ratio of the first frequency contact area value to the first frequency region area value to obtain the first frequency area contact ratio, calculate the ratio of the second frequency contact area value to the second frequency region area value to obtain the second frequency area contact ratio, and so on, calculate the ratio of the b-th frequency contact area value to the b-th frequency region area value to obtain the b-th frequency area contact ratio;

[0043] Step S235: respectively obtaining the real-time frequency values corresponding to the first frequency monitoring area to the bth frequency monitoring area at the first frequency monitoring time point, and obtaining the real-time frequency values of the first area to the bth area;

[0044] Step S236: Calculating the first frequency monitoring index value by converting the first region real-time frequency value to the b-th region real-time frequency value and the first frequency area contact ratio to the b-th frequency area contact ratio;

[0045] The first frequency monitoring index value is calculated, and the specific formula is as follows:

[0046]

[0047] Among them, P zb1 is the first frequency monitoring index value, P qi is the real-time frequency value of the i-th region, P mi is the contact ratio of the ith frequency area, and b is the number of frequency monitoring areas.

[0048] Furthermore, step S3 further includes the following specific steps:

[0049] Step S31: Acquire periodic acoustic wave monitoring data, and obtain environmental periodic monitoring acoustic wave values and acoustic wave real-time monitoring coefficients according to the periodic acoustic wave monitoring data;

[0050] Step S32: Obtaining frequency real-time monitoring coefficient;

[0051] Step S33: Calculating the sound wave real-time monitoring coefficient and the frequency real-time monitoring coefficient to obtain a noise filtering adjustment coefficient;

[0052] Calculate the noise filtering adjustment coefficient. The specific formula is as follows:

[0053] G lt =Y xs ×P xs

[0054] Among them, G lt is the noise filtering adjustment coefficient, Y xs is the acoustic wave real-time monitoring coefficient, P xs is the frequency real-time monitoring coefficient;

[0055] Step S34: obtaining a noise filtering adjustment coefficient threshold, performing a numerical comparison between the noise filtering adjustment coefficient and the noise filtering adjustment coefficient threshold, and performing noise filtering control on the target environment according to the numerical comparison result;

[0056] Step S35: adjusting filtering parameters of the target environment in the noise filtering state.

[0057] Furthermore, step S34 further includes the following specific steps:

[0058] Step S341: respectively obtaining a sound wave real-time monitoring coefficient threshold and a frequency real-time monitoring coefficient threshold;

[0059] Step S342: Calculating the sound wave real-time monitoring coefficient threshold and the frequency real-time monitoring coefficient threshold to obtain a noise filtering adjustment coefficient threshold;

[0060] Calculate the noise filter adjustment coefficient threshold. The specific formula is as follows:

[0061] G lty =Y xsy ×P xsy

[0062] Among them, G lty is the noise filtering adjustment coefficient threshold, Y xsy is the acoustic wave real-time monitoring coefficient threshold, P xsy is the frequency real-time monitoring coefficient threshold;

[0063] Step S343: If the noise filtering adjustment coefficient is greater than or equal to the noise filtering adjustment coefficient threshold, the noise filtering function of the target environment is activated, and the target environment is in a noise filtering state;

[0064] Step S344: If the noise filtering adjustment coefficient is less than the noise filtering adjustment coefficient threshold, the noise filtering function of the target environment is turned off, and the target environment is in a non-noise filtering state.

[0065] Furthermore, step S35 further includes the following specific steps:

[0066] Step S351: Acquire the real-time filtering parameters corresponding to the target environment to obtain the real-time filtering parameters of the environment;

[0067] Step S352: Obtaining the noise filtering adjustment coefficient and the environmental period monitoring sound wave value;

[0068] Step S353: Calculating the real-time environmental filtering parameter, the noise filtering adjustment coefficient, and the environmental periodic monitoring sound wave value to obtain the filtering parameter adjustment coefficient;

[0069] Calculate the filter parameter adjustment coefficient. The specific formula is as follows:

[0070]

[0071] Among them, Tsx is the filter parameter adjustment coefficient, Glt is the noise filter adjustment coefficient, Ywz is the environmental period monitoring sound wave value, and Cgl is the environmental real-time filtering parameter;

[0072] Step S354: Obtain a filter parameter adjustment coefficient threshold, perform a numerical comparison between the filter parameter adjustment coefficient and the filter parameter adjustment coefficient threshold, and adjust the filter parameters of the target environment according to the numerical comparison result.

[0073] Furthermore, step S354 further includes the following specific steps:

[0074] Step S3541: Obtaining the environmental real-time filtering parameter threshold, the noise filtering adjustment coefficient threshold, and the environmental periodic monitoring sound wave threshold to obtain the filtering parameter adjustment coefficient threshold through calculation;

[0075] Step S3542: Calculating the environmental real-time filtering parameter threshold, the noise filtering adjustment coefficient threshold, and the environmental periodic monitoring sound wave threshold to obtain a filtering parameter adjustment coefficient threshold;

[0076] Calculate the filter parameter adjustment coefficient threshold. The specific formula is as follows:

[0077]

[0078] Among them, Tsxy is the filter parameter adjustment coefficient threshold, Glty is the noise filter adjustment coefficient threshold, Ywzy is the environmental periodic monitoring sound wave threshold, and Cgly is the environmental real-time filter parameter threshold;

[0079] Step S3543: When the filter parameter adjustment coefficient is greater than or equal to the filter parameter adjustment coefficient threshold, the real-time environmental filter parameter is increased until the filter parameter adjustment coefficient is equal to the filter parameter adjustment coefficient threshold;

[0080] Step S3544: When the filter parameter adjustment coefficient is less than the filter parameter adjustment coefficient threshold, the environmental real-time filter parameter is reduced until the filter parameter adjustment coefficient is equal to the filter parameter adjustment coefficient threshold.

[0081] A high-frequency noise filtering system based on acoustic wave interference, comprising:

[0082] Acoustic wave monitoring module: used to obtain the acoustic wave collection period, select several characteristic time points within the acoustic wave collection period, monitor the target environment in the acoustic wave collection period, obtain the environmental period monitoring acoustic wave value, obtain the acoustic wave monitoring index value corresponding to each characteristic time point, and perform a comprehensive analysis of the obtained multiple acoustic wave monitoring index values to obtain the acoustic wave real-time monitoring coefficient. The acoustic wave collection period, the environmental period monitoring acoustic wave value, and the acoustic wave real-time monitoring coefficient are defined as periodic acoustic wave monitoring data;

[0083] Frequency monitoring module: used to select several frequency characteristic time points within the sound wave acquisition cycle, obtain the frequency monitoring index value corresponding to each frequency characteristic time point, and perform comprehensive analysis on the obtained multiple frequency monitoring index values to obtain the frequency real-time monitoring coefficient;

[0084] Noise filtering module: used to filter and control high-frequency noise based on periodic sound wave monitoring data and frequency real-time monitoring coefficient.

[0085] In summary, due to the adoption of the above technical solution, the technical effects of the present invention are:

[0086] The present invention monitors the sound wave intensity and frequency distribution of the target environment in different zones and generates a noise filtering adjustment coefficient based on the principle of acoustic interference. This can effectively separate high-frequency noise from the target signal, thereby improving the accuracy of noise filtering.

[0087] The present invention dynamically analyzes the real-time sound wave data and frequency data of the target environment and adjusts the noise filtering parameters according to the analysis results, thereby enhancing the adaptability of the noise filtering system and reducing the distortion of the target signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Figure 1 This is a schematic diagram of the overall process of the high-frequency noise filtering method based on acoustic wave interference of the present invention, showing the main steps from acoustic wave monitoring to noise filtering.

[0089] Figure 2 This is a schematic diagram of the working principle of the sound wave monitoring module in the present invention, focusing on the acquisition of the real-time intensity value of the sound wave and the marking process of the characteristic time point.

[0090] Figure 3 This is a schematic diagram of the working principle of the frequency monitoring module in the present invention, which describes in detail the calculation process of the frequency monitoring index value and the generation process of the frequency real-time monitoring coefficient.

[0091] Figure 4 This is a control logic diagram of the noise filtering module in the present invention, showing the calculation of the noise filtering adjustment coefficient and the control strategy after comparing it with the threshold.

[0092] Figure 5 It is a flow chart of the filtering parameter adjustment mechanism in the present invention, which illustrates the dynamic adjustment process of the real-time filtering parameters of the environment.

[0093] Figure 6 This is the overall structural block diagram of the system of the present invention, showing the data interaction relationship between the sound wave monitoring module, frequency monitoring module and noise filtering module.

[0094] The accompanying drawings are numbered as follows:

[0095] 1. Sound wave monitoring module; 2. Frequency monitoring module; 3. Noise filtering module; 4. Target environment; 5. Sound wave sensor; 6. Noise filtering adjustment coefficient; 7. Filter parameter adjustment coefficient. DETAILED DESCRIPTION

[0096] The present invention provides a high-frequency noise filtering method and system based on acoustic wave interference. The specific embodiments of the invention are described in detail below with reference to the accompanying drawings. In practical applications, the system collects data through an acoustic wave sensor 5 installed in a target environment 4 and transmits the collected data to an acoustic wave monitoring module 1, a frequency monitoring module 2, and a noise filtering module 3, thereby achieving precise filtering of high-frequency noise.

[0097] like Figure 6 As shown, the entire system consists of an acoustic wave monitoring module 1, a frequency monitoring module 2, and a noise filtering module 3. These three modules interact through data to filter and control high-frequency noise in the target environment 4. Acoustic wave monitoring module 1 is responsible for acquiring acoustic wave intensity distribution data in the target environment 4 and calculating periodic acoustic wave monitoring data. Frequency monitoring module 2 is used to acquire frequency distribution data in the target environment 4 and generate a real-time frequency monitoring coefficient. Noise filtering module 3, based on the outputs of the first two modules, generates a noise filtering adjustment coefficient 6 and controls the noise filtering function in the target environment 4. Furthermore, noise filtering module 3 can dynamically adjust the real-time filtering parameters of the environment to optimize the filtering effect.

[0098] In the specific implementation process, the acoustic wave monitoring module 1 is first started, and its working principle is as follows: Figure 2As shown. The acoustic wave sensor 5 is arranged at different positions of the target environment 4 for collecting acoustic wave intensity values in real time. When the acoustic wave sensor 5 detects that the real-time acoustic wave intensity value in the target environment 4 is greater than or equal to the preset real-time acoustic wave intensity threshold, the time value at the current moment is marked as the first characteristic time point. Subsequently, the period after the first characteristic time point is divided into several acoustic wave collection cycles, each cycle containing several equally spaced acoustic wave monitoring time points. For example, assuming that the period after the first characteristic time point is divided into three acoustic wave collection cycles, each cycle containing five acoustic wave monitoring time points, then these time points are named in chronological order as the first acoustic wave monitoring time point to the fifth acoustic wave monitoring time point. At each acoustic wave monitoring time point, the acoustic wave sensor 5 collects the acoustic wave intensity value of the target environment 4 respectively, and averages the multiple acoustic wave intensity values collected to obtain the environmental period monitoring acoustic wave value. At the same time, at the first acoustic wave monitoring time point, the target environment 4 is divided into several acoustic wave monitoring areas at different locations, such as the first acoustic wave monitoring area to the ath acoustic wave monitoring area. The area value of each area and the area value of contact with the target sound source are obtained by the sound wave sensor 5, and the sound wave area contact ratio of each area is calculated. Combining the real-time sound wave intensity value and the sound wave area contact ratio of each area, the formula The first acoustic wave monitoring index value is calculated, where Yqi is the real-time acoustic wave intensity value of the i-th area, Ymi is the i-th acoustic wave area contact ratio, and a is the number of acoustic wave monitoring areas. Similarly, the acoustic wave monitoring index values corresponding to the second acoustic wave monitoring time point to the fifth acoustic wave monitoring time point are also calculated one by one. Finally, the first to fifth acoustic wave monitoring index values are averaged to obtain the acoustic wave real-time monitoring coefficient, and the acoustic wave acquisition period, the environmental period monitoring acoustic wave value, and the acoustic wave real-time monitoring coefficient are defined as periodic acoustic wave monitoring data.

[0099] After completing the acoustic wave monitoring, the frequency monitoring module 2 starts to operate. Its working principle is as follows: Figure 3 As shown. The frequency monitoring module 2 also selects several frequency characteristic time points within the sound wave acquisition cycle, and collects the frequency distribution data of the target environment 4 at each frequency characteristic time point. First, the target environment 4 is divided into several frequency monitoring areas at different positions, such as the first frequency monitoring area to the bth frequency monitoring area. The area value of each area and the area value in contact with the target sound source are obtained by the sound wave sensor 5, and the frequency-area contact ratio of each area is calculated. Combining the real-time frequency value and the frequency-area contact ratio of each area, the formula is used Calculate the first frequency monitoring index value, where P qi is the real-time frequency value of the i-th region, P miis the area contact ratio for the i-th frequency, and b is the number of frequency monitoring areas. Similarly, the frequency monitoring index values corresponding to the second frequency monitoring time point through the s-th frequency monitoring time point are calculated one by one. Finally, the average of the first to s-th frequency monitoring index values is calculated to obtain the frequency real-time monitoring coefficient.

[0100] Next, the noise filtering module 3 generates a noise filtering adjustment coefficient 6 according to the output results of the sound wave monitoring module 1 and the frequency monitoring module 2, and controls the noise filtering function of the target environment 4. The control logic is as follows: Figure 4 First, the noise filtering module 3 obtains the real-time monitoring coefficient Y of the sound wave xs and frequency real-time monitoring coefficient P xs , and using formula G lt =Y xs ×P xs The noise filtering adjustment coefficient 6 is calculated. At the same time, the noise filtering module 3 also obtains the sound wave real-time monitoring coefficient threshold Y xsy and frequency real-time monitoring coefficient threshold P xsy , and using formula G lty =Y xsy ×P xsy The noise filtering adjustment coefficient threshold is calculated. Subsequently, the noise filtering module 3 compares the noise filtering adjustment coefficient 6 with the noise filtering adjustment coefficient threshold. If the noise filtering adjustment coefficient 6 is greater than or equal to the noise filtering adjustment coefficient threshold, the noise filtering function of the target environment 4 is activated, and the target environment 4 enters a noise filtering state. If the noise filtering adjustment coefficient 6 is less than the noise filtering adjustment coefficient threshold, the noise filtering function of the target environment 4 is disabled, and the target environment 4 enters a non-noise filtering state.

[0101] When the target environment 4 is in the noise filtering state, the noise filtering module 3 can also dynamically adjust the filtering parameters according to the real-time filtering parameter Cgl, the noise filtering adjustment coefficient 6 and the environmental period monitoring sound wave value Ywz. The adjustment mechanism is as follows: Figure 5 As shown. First, the noise filtering module 3 uses the formula The filter parameter adjustment coefficient 7 is calculated. At the same time, the noise filtering module 3 also obtains the environmental real-time filtering parameter threshold Cgly, the noise filtering adjustment coefficient threshold Glty and the environmental period monitoring sound wave threshold Ywzy, and uses the formula The filter parameter adjustment coefficient threshold is calculated. Subsequently, the noise filtering module 3 compares the filter parameter adjustment coefficient 7 with the filter parameter adjustment coefficient threshold. If the filter parameter adjustment coefficient 7 is greater than or equal to the filter parameter adjustment coefficient threshold, the real-time environmental filter parameter Cgl is increased until the filter parameter adjustment coefficient 7 equals the filter parameter adjustment coefficient threshold. If the filter parameter adjustment coefficient 7 is less than the filter parameter adjustment coefficient threshold, the real-time environmental filter parameter Cgl is decreased until the filter parameter adjustment coefficient 7 equals the filter parameter adjustment coefficient threshold.

[0102] In practical application scenarios, such as complex acoustic environments like factory workshops or large conference rooms, the system of the present invention can effectively separate high-frequency noise from target signals. By using the acoustic wave monitoring module 1 and the frequency monitoring module 2 to monitor the acoustic wave intensity and frequency distribution of the target environment 4 in a zoned manner, and combining the acoustic wave interference principle to generate the noise filtering adjustment coefficient 6, the system can accurately identify and filter high-frequency noise. At the same time, the noise filtering module 3 further enhances the system's adaptability by dynamically adjusting the real-time environmental filtering parameter Cgl, ensuring efficient noise filtering under different acoustic conditions.

[0103] In order to better enable relevant personnel in this technical field to fully understand and implement the present invention, the specific implementation principle of the present invention is supplemented below with reference to a specific application scenario.

[0104] In the complex acoustic environment of a factory floor, target environment 4 contains a variety of high-frequency noise sources, such as high-frequency vibration noise generated by the operation of mechanical equipment and whistling noise caused by aerodynamic equipment. These noises are mixed with the target signal in target environment 4 (such as human voices or the sound of normal equipment operation), making it difficult for traditional filters to effectively separate them. Therefore, the present invention achieves more precise noise filtering through a high-frequency noise filtering method and system based on the principle of acoustic wave interference.

[0105] First, multiple acoustic wave sensors 5 are arranged in the target environment 4. These sensors are distributed in different positions according to a predetermined layout to ensure coverage of the entire target environment 4. When the acoustic wave sensor 5 detects that the real-time acoustic wave intensity value within the target environment 4 is greater than or equal to a preset real-time acoustic wave intensity threshold, the time value at the current moment is marked as the first characteristic time point. Subsequently, the period after the first characteristic time point is divided into several acoustic wave collection cycles, each cycle containing several equally spaced acoustic wave monitoring time points. For example, assuming that the period after the first characteristic time point is divided into three acoustic wave collection cycles, each cycle containing five acoustic wave monitoring time points, these time points are named, in sequence, the first acoustic wave monitoring time point to the fifth acoustic wave monitoring time point. At each acoustic wave monitoring time point, the acoustic wave sensor 5 respectively collects the acoustic wave intensity value of the target environment 4, and averages the multiple acoustic wave intensity values collected to obtain the environmental cycle monitoring acoustic wave value. At the same time, at the first acoustic wave monitoring time point, the target environment 4 is divided into several acoustic wave monitoring areas, such as the first acoustic wave monitoring area to the ath acoustic wave monitoring area. The area value of each area and the area value of contact with the target sound source are obtained by the sound wave sensor 5, and the sound wave area contact ratio of each area is calculated. Combining the real-time sound wave intensity value and the sound wave area contact ratio of each area, the formula The first acoustic wave monitoring index value is calculated, where Yqi is the real-time acoustic wave intensity value of the i-th area, Ymi is the i-th acoustic wave area contact ratio, and a is the number of acoustic wave monitoring areas. Similarly, the acoustic wave monitoring index values corresponding to the second acoustic wave monitoring time point to the fifth acoustic wave monitoring time point are also calculated one by one. Finally, the first to fifth acoustic wave monitoring index values are averaged to obtain the acoustic wave real-time monitoring coefficient, and the acoustic wave acquisition period, the environmental period monitoring acoustic wave value, and the acoustic wave real-time monitoring coefficient are defined as periodic acoustic wave monitoring data.

[0106] After completing the acoustic wave monitoring, the frequency monitoring module 2 starts to operate. Its working principle is as follows: Figure 3 As shown. The frequency monitoring module 2 also selects several frequency characteristic time points within the sound wave collection cycle, and collects the frequency distribution data of the target environment 4 at each frequency characteristic time point. First, the target environment 4 is divided into several frequency monitoring areas, such as the first frequency monitoring area to the bth frequency monitoring area. The area value of each area and the area value in contact with the target sound source are obtained by the sound wave sensor 5, and the frequency-area contact ratio of each area is calculated. Combining the real-time frequency value and the frequency-area contact ratio of each area, the formula is used. Calculate the first frequency monitoring index value, where P qi is the real-time frequency value of the i-th region, P miis the area contact ratio for the i-th frequency, and b is the number of frequency monitoring areas. Similarly, the frequency monitoring index values corresponding to the second frequency monitoring time point through the s-th frequency monitoring time point are calculated one by one. Finally, the average of the first to s-th frequency monitoring index values is calculated to obtain the frequency real-time monitoring coefficient.

[0107] Next, the noise filtering module 3 generates a noise filtering adjustment coefficient 6 based on the output results of the sound wave monitoring module 1 and the frequency monitoring module 2, and controls the noise filtering function of the target environment 4. The noise filtering module 3 obtains the real-time sound wave monitoring coefficient Y xs and frequency real-time monitoring coefficient P xs , and using formula G lt =Y xs ×P xs The noise filtering adjustment coefficient 6 is calculated. At the same time, the noise filtering module 3 also obtains the sound wave real-time monitoring coefficient threshold Y xsy and frequency real-time monitoring coefficient threshold P xsy , and using formula G lty =Y xsy ×P xsy The noise filtering adjustment coefficient threshold is calculated. Subsequently, the noise filtering module 3 compares the noise filtering adjustment coefficient 6 with the noise filtering adjustment coefficient threshold. If the noise filtering adjustment coefficient 6 is greater than or equal to the noise filtering adjustment coefficient threshold, the noise filtering function of the target environment 4 is activated, and the target environment 4 enters a noise filtering state. If the noise filtering adjustment coefficient 6 is less than the noise filtering adjustment coefficient threshold, the noise filtering function of the target environment 4 is disabled, and the target environment 4 enters a non-noise filtering state.

[0108] When the target environment 4 is in the noise filtering state, the noise filtering module 3 can also dynamically adjust the filtering parameters according to the real-time filtering parameter Cgl, the noise filtering adjustment coefficient 6 and the environmental period monitoring sound wave value Ywz. The noise filtering module 3 uses the formula The filter parameter adjustment coefficient 7 is calculated. At the same time, the noise filtering module 3 also obtains the environmental real-time filtering parameter threshold Ggly, the noise filtering adjustment coefficient threshold Glty and the environmental period monitoring sound wave threshold Ywzy, and uses the formula The filter parameter adjustment coefficient threshold is calculated. Subsequently, the noise filtering module 3 compares the filter parameter adjustment coefficient 7 with the filter parameter adjustment coefficient threshold. If the filter parameter adjustment coefficient 7 is greater than or equal to the filter parameter adjustment coefficient threshold, the real-time environmental filter parameter Ggl is increased until the filter parameter adjustment coefficient 7 equals the filter parameter adjustment coefficient threshold. If the filter parameter adjustment coefficient 7 is less than the filter parameter adjustment coefficient threshold, the real-time environmental filter parameter Ggl is decreased until the filter parameter adjustment coefficient 7 equals the filter parameter adjustment coefficient threshold.

[0109] Through the above steps, the system of the present invention can effectively separate high-frequency noise from the target signal. In practical applications, for example, high-frequency noise generated by the operation of mechanical equipment in a factory workshop is difficult to accurately suppress with traditional filters due to its high frequency and concentrated energy. However, the present invention monitors the intensity and frequency distribution of sound waves by partitions, and generates a noise filtering adjustment coefficient 6 based on the principle of sound wave interference, which can accurately identify and filter high-frequency noise. At the same time, the noise filtering module 3 further enhances the adaptability of the system by dynamically adjusting the real-time filtering parameter Ggl of the environment, ensuring that efficient noise filtering effects can be achieved under different acoustic conditions.

[0110] In addition, the system of the present invention also performs well in application scenarios in large conference rooms. There may be high-frequency noise from the air-conditioning system or the external environment in the conference room, which will interfere with the clarity of the voice signal. Through the system of the present invention, the sound wave monitoring module 1 and the frequency monitoring module 2 can monitor the sound wave intensity and frequency distribution in the conference room in a partitioned manner, and generate the noise filtering adjustment coefficient 6 based on the principle of sound wave interference, thereby achieving accurate filtering of high-frequency noise. The noise filtering module 3 further optimizes the filtering effect by dynamically adjusting the real-time filtering parameter Ggl of the environment, ensuring that the clarity of the voice signal can be maintained under different acoustic conditions.

[0111] In summary, this invention, by combining the principles of acoustic interference and a dynamic parameter adjustment mechanism, achieves precise separation and filtering of high-frequency noise, significantly improving the accuracy and adaptability of noise filtering while reducing distortion of the target signal. This technical solution has broad application prospects in complex acoustic environments such as factory workshops and large conference rooms.

Claims

1. A high-frequency noise filtering method based on acoustic wave interference, characterized in that: The following steps are involved: Step S1: Obtain a sound wave collection period, select several characteristic time points within the sound wave collection period, monitor the target environment in the sound wave collection period for sound wave data, obtain an environmental period monitoring sound wave value, obtain a sound wave monitoring index value corresponding to each characteristic time point, and perform a comprehensive analysis on the obtained multiple sound wave monitoring index values to obtain a sound wave real-time monitoring coefficient, and define the sound wave collection period, the environmental period monitoring sound wave value, and the sound wave real-time monitoring coefficient as periodic sound wave monitoring data; Step S2: Selecting a number of frequency characteristic time points within the acoustic wave acquisition period, obtaining the frequency monitoring index value corresponding to each frequency characteristic time point, and performing a comprehensive analysis on the obtained multiple frequency monitoring index values to obtain a frequency real-time monitoring coefficient; Step S3: filtering and controlling the high-frequency noise according to the periodic sound wave monitoring data and the frequency real-time monitoring coefficient.

2. The high-frequency noise filtering method based on acoustic wave interference according to claim 1, characterized in that: The step S1 further includes the following steps: Step S11: obtaining a sound wave intensity value in real time through a sound wave sensor installed in the target environment, obtaining a real-time sound wave intensity value, and obtaining a real-time sound wave intensity threshold value; if the real-time sound wave intensity value is greater than or equal to the real-time sound wave intensity threshold value, marking the time value corresponding to the current moment as a first characteristic time point; if the real-time sound wave intensity value is less than the real-time sound wave intensity threshold value, the sound wave sensor continues to perform sound wave monitoring on the target environment; Step S12: Taking the first characteristic time point as the cycle start time point, marking a number of acoustic wave monitoring time points in the period after the first characteristic time point, marking the time interval between two consecutive acoustic wave monitoring time points as an acoustic wave collection cycle, obtaining multiple acoustic wave collection cycles, and naming the acoustic wave collection cycle where the cycle start time point is located as the acoustic wave real-time monitoring cycle among the multiple acoustic wave collection cycles obtained; Step S13: within the acoustic wave real-time monitoring period, mark a number of acoustic wave monitoring time points, with the interval between each two consecutive acoustic wave monitoring time points being equal in length, and the marked acoustic wave monitoring time points are named in chronological order as the first acoustic wave monitoring time point to the wth acoustic wave monitoring time point; Step S14: obtaining a plurality of sound wave intensity values of the target environment from the first sound wave monitoring time point to the wth sound wave monitoring time point, and averaging the obtained plurality of sound wave intensity values to obtain a sound wave value for environmental periodic monitoring; Step S15: performing acoustic wave data monitoring on the target environment at the first acoustic wave monitoring time point, and obtaining a first acoustic wave monitoring index value according to the monitoring result; Step S16: acquiring the acoustic wave monitoring index values corresponding to the second acoustic wave monitoring time point to the wth acoustic wave monitoring time point respectively, to obtain the second acoustic wave monitoring index value to the wth acoustic wave monitoring index value; Step S17: Calculate the average of the first sound wave monitoring index value to the wth sound wave monitoring index value to obtain the sound wave real-time monitoring coefficient.

3. The high-frequency noise filtering method based on acoustic wave interference according to claim 2, characterized in that: The step S15 further includes the following steps: Step S151: Divide the target environment into a plurality of acoustic wave monitoring areas at different locations, and name the marked acoustic wave monitoring areas as the first acoustic wave monitoring area to the ath acoustic wave monitoring area respectively; Step S152: respectively obtaining area values corresponding to the first acoustic wave monitoring area to the ath acoustic wave monitoring area, and obtaining area values of the first acoustic wave area to the ath acoustic wave area; Step S153: using the acoustic wave sensor to obtain the contact area values of the first acoustic wave monitoring area to the ath acoustic wave monitoring area and the target sound source, respectively, to obtain the first acoustic wave contact area value to the ath acoustic wave contact area value; Step S154: Calculate the ratio of the first acoustic wave contact area value to the first acoustic wave region area value to obtain the first acoustic wave area contact ratio; calculate the ratio of the second acoustic wave contact area value to the second acoustic wave region area value to obtain the second acoustic wave area contact ratio; and so on, calculate the ratio of the a-th acoustic wave contact area value to the a-th acoustic wave region area value to obtain the a-th acoustic wave area contact ratio; Step S155: respectively obtaining the real-time sound wave intensity values corresponding to the first sound wave monitoring area to the ath sound wave monitoring area at the first sound wave monitoring time point, and obtaining the real-time sound wave intensity values of the first area to the ath area; Step S156: The first acoustic wave monitoring index value is obtained by calculating the real-time acoustic wave intensity value of the first region to the real-time acoustic wave intensity value of the a-th region and the first acoustic wave area contact ratio to the a-th acoustic wave area contact ratio. The specific formula is as follows: Among them, Yzb1 is the first sound wave monitoring index value, Yqi is the real-time sound wave intensity value of the i-th area, Ymi is the i-th sound wave area contact ratio, and a is the number value of the sound wave monitoring area.

4. The high-frequency noise filtering method based on acoustic wave interference according to claim 1, characterized in that: The step S2 further includes the following steps: Step S21: Acquire periodic frequency monitoring data, and acquire the real-time monitoring period of the acoustic wave according to the periodic frequency monitoring data; Step S22: Marking a number of frequency monitoring time points within the acoustic wave real-time monitoring period, with the interval between each two consecutive frequency monitoring time points being equal in length, and naming the marked frequency monitoring time points in chronological order as the first frequency monitoring time point to the sth frequency monitoring time point; Step S23: performing frequency data monitoring on the target environment at the first frequency monitoring time point, and obtaining a first frequency monitoring index value according to the monitoring result; Step S24: acquiring the frequency monitoring index values corresponding to the second frequency monitoring time point to the sth frequency monitoring time point respectively, to obtain the second frequency monitoring index value to the sth frequency monitoring index value; Step S25: Calculate the average of the first frequency monitoring index value to the sth frequency monitoring index value to obtain the frequency real-time monitoring coefficient.

5. The high-frequency noise filtering method based on acoustic wave interference according to claim 4, characterized in that: The step S23 further includes the following steps: Step S231: Divide the target environment into a number of frequency monitoring areas at different locations, and name the marked frequency monitoring areas as the first frequency monitoring area to the bth frequency monitoring area respectively; Step S232: respectively obtaining area values corresponding to the first frequency monitoring area to the bth frequency monitoring area, and obtaining area values of the first frequency area to the bth frequency area; Step S233: using an acoustic wave sensor to obtain contact area values between the first frequency monitoring area and the bth frequency monitoring area and the target sound source, thereby obtaining contact area values between the first frequency and the bth frequency; Step S234: Calculate the ratio of the first frequency contact area value to the first frequency region area value to obtain the first frequency area contact ratio, calculate the ratio of the second frequency contact area value to the second frequency region area value to obtain the second frequency area contact ratio, and so on, calculate the ratio of the b-th frequency contact area value to the b-th frequency region area value to obtain the b-th frequency area contact ratio; Step S235: respectively obtaining the real-time frequency values corresponding to the first frequency monitoring area to the bth frequency monitoring area at the first frequency monitoring time point, and obtaining the real-time frequency values of the first area to the bth area; Step S236: Calculate the first frequency monitoring index value by dividing the first region's real-time frequency value by the b-th region's real-time frequency value and the first frequency area contact ratio by the b-th frequency area contact ratio. The specific formula is as follows: Among them, P zb1 is the first frequency monitoring index value, P qi is the real-time frequency value of the i-th region, P mi is the contact ratio of the ith frequency area, and b is the number of frequency monitoring areas.

6. The high-frequency noise filtering method based on acoustic wave interference according to claim 1, characterized in that: The step S3 further includes the following steps: Step S31: Acquire periodic acoustic wave monitoring data, and obtain environmental periodic monitoring acoustic wave values and acoustic wave real-time monitoring coefficients according to the periodic acoustic wave monitoring data; Step S32: Obtaining frequency real-time monitoring coefficient; Step S33: The noise filtering adjustment coefficient is obtained by calculating the sound wave real-time monitoring coefficient and the frequency real-time monitoring coefficient. The specific formula is as follows: G lt =Y xs ×P xs Among them, G lt is the noise filtering adjustment coefficient, Y xs is the acoustic wave real-time monitoring coefficient, P xs is the frequency real-time monitoring coefficient; Step S34: obtaining a noise filtering adjustment coefficient threshold, performing a numerical comparison between the noise filtering adjustment coefficient and the noise filtering adjustment coefficient threshold, and performing noise filtering control on the target environment according to the numerical comparison result.

7. The high-frequency noise filtering method based on acoustic wave interference according to claim 6, characterized in that: The step S34 further includes the following steps: Step S341: respectively obtaining a sound wave real-time monitoring coefficient threshold and a frequency real-time monitoring coefficient threshold; Step S342: The noise filtering adjustment coefficient threshold is obtained by calculating the sound wave real-time monitoring coefficient threshold and the frequency real-time monitoring coefficient threshold. The specific formula is as follows: G lty =Y xsy ×P xsy Among them, G lty is the noise filtering adjustment coefficient threshold, Y xsy is the acoustic wave real-time monitoring coefficient threshold, P xsy is the frequency real-time monitoring coefficient threshold; Step S343: If the noise filtering adjustment coefficient is greater than or equal to the noise filtering adjustment coefficient threshold, the noise filtering function of the target environment is activated; Step S344: If the noise filtering adjustment coefficient is less than the noise filtering adjustment coefficient threshold, the noise filtering function of the target environment is turned off.

8. The high-frequency noise filtering method based on acoustic wave interference according to claim 6, characterized in that: The step S3 further comprises the following steps: Step S351: Acquire the real-time filtering parameters corresponding to the target environment to obtain the real-time filtering parameters of the environment; Step S352: Obtaining the noise filtering adjustment coefficient and the environmental period monitoring sound wave value; Step S353: The real-time environmental filtering parameter, the noise filtering adjustment coefficient, and the environmental periodic monitoring sound wave value are calculated to obtain the filtering parameter adjustment coefficient. The specific formula is as follows: Among them, Tsx is the filter parameter adjustment coefficient, Glt is the noise filter adjustment coefficient, Ywz is the environmental period monitoring sound wave value, and Cgl is the environmental real-time filtering parameter; Step S354: Obtain a filter parameter adjustment coefficient threshold, perform a numerical comparison between the filter parameter adjustment coefficient and the filter parameter adjustment coefficient threshold, and adjust the filter parameters of the target environment according to the numerical comparison result.

9. A high-frequency noise filtering system based on acoustic wave interference, characterized in that: include: The acoustic wave monitoring module (1) is used to obtain an acoustic wave collection period, select a number of characteristic time points within the acoustic wave collection period, monitor the target environment in the acoustic wave collection period, obtain an environmental period monitoring acoustic wave value, obtain an acoustic wave monitoring index value corresponding to each characteristic time point, and perform a comprehensive analysis on the obtained multiple acoustic wave monitoring index values to obtain an acoustic wave real-time monitoring coefficient, and define the acoustic wave collection period, the environmental period monitoring acoustic wave value, and the acoustic wave real-time monitoring coefficient as periodic acoustic wave monitoring data; Frequency monitoring module (2): used to select a number of frequency characteristic time points within the sound wave acquisition period, obtain the frequency monitoring index value corresponding to each frequency characteristic time point, and perform comprehensive analysis on the obtained multiple frequency monitoring index values to obtain the frequency real-time monitoring coefficient; Noise filtering module (3): used for filtering and controlling high-frequency noise according to periodic sound wave monitoring data and frequency real-time monitoring coefficient.

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