CN113267249A - Multi-channel noise analysis system and analysis method based on big data - Google Patents
Multi-channel noise analysis system and analysis method based on big data Download PDFInfo
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Abstract
The invention discloses a big data-based multichannel noise analysis system and method, which comprises a sound collection system, a sound source analysis system, a sound filtering system, a sound source positioning system, a data feedback system, a multichannel setting system and a real-time monitoring system, and relates to the technical field of noise analysis. This multichannel noise analysis system and analytic method based on big data, through setting up sound collection system, sound source analysis system and sound filtration system, utilize the limit of decibel setting unit setting noise among the sound collection system, the cooperation sound filtration system filters the sound data that does not belong to the noise, avoid multiple data to influence noise analysis's result, the sound source analysis system of cooperation setting, can distinguish the kind of noise and calculate the intensity of sound source, avoid influencing data analysis's precision because the loss process of sound in the air, after handling based on big data, very big promotion noise analysis's accuracy.
Description
Technical Field
The invention relates to the technical field of noise analysis, in particular to a multichannel noise analysis system and method based on big data.
Background
A channel refers to a signal channel based on a transmission medium, and is defined according to the definition of the channel, and if the channel refers to the transmission medium of the signal only, the channel is called a narrow channel; a channel is referred to as a generalized channel if it is not only a transmission medium but also includes some conversion means in a communication system. A channel is an indispensable component of a communication system, and any communication system can be regarded as being composed of three major parts, namely a transmitting device, a channel and a receiving device. The channel is usually a signal channel based on a transmission medium, and the signal transmission in the channel encounters inevitable noise, i.e. the channel allows the signal to pass through and simultaneously limits and damages the signal, so the research on the channel and the noise is the basis for researching the communication problem
Referring to the chinese patent, a multi-channel noise analysis system and an analysis method thereof (publication No. CN111277348A, published as 2020-06-12) includes a transmitting end, a receiving end, a noise monitoring end and a remote data processing terminal, by comparing encoded data fed back by the noise monitoring end with source data transmitted by the transmitting end, the strength of interference of noise to signal transmission can be determined, and both aspects of detection can be performed, so that the influence of channel noise on signal transmission can be more comprehensively analyzed.
For the above referenced patents, the existing multichannel noise analysis system and analysis method based on big data still have the following defects:
1. in the process of collecting the sound data, the numerical value of the noise decibel is fixed and cannot be set according to requirements, the sound data which does not belong to the noise cannot be filtered, so that various data influence the result of noise analysis,
and the loss process of sound in the air affects the accuracy of data analysis;
2. in the process of analyzing the noise, the accurate positioning of a noise source cannot be realized, the noise cannot be processed in time according to requirements, manual operation is relied on during noise analysis, real-time online control cannot be realized, and the intelligent degree is low;
3. when a single channel analyzes noise, the influence of the noise on data transmission cannot be analyzed more comprehensively, the jamming problem is caused by the simultaneous transmission of data, and adjacent channels are connected with each other
There is a problem of mutual interference.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a multichannel noise analysis system and method based on big data, and solves the problems.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme: the multichannel noise analysis system based on big data comprises a sound collection system, a sound source analysis system, a sound filtering system, a sound source positioning system, a data feedback system, a multichannel setting system and a real-time monitoring system, wherein the output end of the sound collection system is connected with the input ends of the sound source analysis system and the sound filtering system, the output end of the sound source analysis system is connected with the input ends of the sound source positioning system, the data feedback system and the multichannel setting system, the output end of the data feedback system is connected with the input end of the sound source analysis system, and the output end of the multichannel setting system is connected with the input end of the real-time monitoring system; sound collection system includes volume acquisition unit, decibel and sets for unit, contrastive analysis unit and volume output unit, the output of volume acquisition unit is connected with the input that the unit was set for to the decibel, the output that the unit was set for to the decibel is connected with contrastive analysis unit's input, contrastive analysis unit's output is connected with volume output unit's input, volume output unit includes noise volume module and normal volume module, the output of noise volume module is connected with sound source analysis system's input, and the output of normal volume module is connected with sound filtration system's input.
Preferably, the sound source analysis system includes noise classification unit and sound source computational element, noise classification unit includes tone color collection module, processing module, tone color library module and tone color identification module, the output of tone color collection module is connected with processing module's input, processing module's output tone color library module's input is connected, the output of tone color library module is connected with tone color identification module's input.
Preferably, the sound source calculation unit comprises a wave frequency module, an air loss module, a calculation module, a display module and a user interaction parameter setting module, and the output end of the wave frequency module is connected with the input end of the air loss module.
Preferably, the output end of the air loss module is connected with the input end of the calculation module, the output end of the calculation module is connected with the input end of the display module, and the output end of the user interaction parameter setting module is connected with the input ends of the calculation module and the display module.
Preferably, the sound source positioning system comprises a distance calculation unit and a GPS positioning unit, the distance calculation unit comprises a sound transmission time difference module, a speed setting module and a distance display module, the output end of the sound transmission time difference module is connected with the input end of the speed setting module, and the output end of the speed setting module is connected with the input end of the distance display module.
Preferably, the GPS positioning unit includes a map module, a distance value module, and a data combination module, and the output ends of the map module and the distance value module are connected to the input end of the data combination module.
Preferably, the multichannel setting system comprises a channel setting unit and a transcoding output unit, the channel setting unit comprises a channel classification module, a delay passing module, a node capacity expansion module and a signal separation module, the output end of the channel classification module is connected with the input end of the delay passing module, the output end of the delay passing module is connected with the input end of the node capacity expansion module, and the output end of the node capacity expansion module is connected with the input end of the signal separation module.
Preferably, the real-time monitoring system includes information storage unit and on-line control unit, on-line control unit includes remote control terminal, central processing unit, lasts power module and dynamic display module, remote control terminal's output is connected with central processing unit's input, central processing unit's output is connected with central processing unit's input, the output that lasts power module is connected with dynamic display module's input.
The invention also discloses an analysis method of the big data-based multi-channel noise analysis system, which specifically comprises the following steps:
s1, sound data acquisition and filtering: firstly, sound data are collected through a volume collection unit, the decibel of noise is set through a decibel setting unit, a comparison analysis unit is used for analyzing and comparing, a volume output unit determines the output volume to be normal volume or noise volume, if the volume output unit determines the output volume to be normal volume, a sound filtering system directly filters the sound, and if the volume output unit determines the output volume to be noise volume, the sound data enter a sound source analysis system;
s2, sound source analysis: the sound data are collected through a sound color collecting module, the sound data are analyzed and processed through a processing module, data with the same sound color as the sound data are selected from a sound color library module and are identified through a sound color identification module, a wave frequency module displays the wave frequency of the sound data, the loss of sound transmission in the air is calculated through an air loss module, the calculation module displays the calculation result through a display module, and a user interaction parameter setting module can set the parameters of the calculation module and the display module;
s3, sound source positioning: a sound transmission time difference module in the distance calculation unit calculates the time difference of sound transmission of a starting point and a terminal point, the speed setting module sets the transmission speed of sound in the air, and the distance display module displays the distance;
s4, setting a channel and controlling in real time: different types of data transmission channels are arranged through the channel classification module, the transmission time of data can be delayed through the delay module, the storage capacity of the channel is temporarily enlarged through the node capacity expansion module, the signal of the adjacent channel is isolated through the signal separation module, and finally, the central processing unit is remotely controlled by the remote control terminal, the continuous power supply process is carried out through the continuous power supply module, and the dynamic display is carried out through the dynamic display module.
Preferably, in the sound source analysis process in S2, the sound library module may summarize and store the mass data.
(III) advantageous effects
The invention provides a big data-based multi-channel noise analysis system and an analysis method. Compared with the prior art, the method has the following beneficial effects:
(1) this multichannel noise analysis system and analytic method based on big data, through setting up sound collection system, sound source analysis system and sound filtration system, utilize the limit of decibel setting unit setting noise among the sound collection system, the cooperation sound filtration system filters the sound data that does not belong to the noise, avoid multiple data to influence noise analysis's result, the sound source analysis system of cooperation setting, can distinguish the kind of noise and calculate the intensity of sound source, avoid influencing data analysis's precision because the loss process of sound in the air, after handling based on big data, very big promotion noise analysis's accuracy.
(2) The multichannel noise analysis system and the multichannel noise analysis method based on the big data utilize the distance calculation unit to calculate the distance between a sound source and a detected noise position by setting the sound source positioning system and the real-time monitoring system, cooperate with the GPS positioning unit to synchronously display the map position and the distance value of the sound source, realize the accurate positioning of a noise source, are convenient to timely process according to requirements, cooperate with the real-time monitoring system to be set, can realize the online real-time control, and have high intelligent degree.
(3) This multichannel noise analysis system and analytic method based on big data sets for the system through setting up the multichannel, utilizes passageway classification module to set up different kinds of passageways, passes through module and node dilatation module through delaying, avoids the data simultaneous transmission through the card pause that causes, and the module is separated to the signal that the cooperation set up, can effectually avoid the mutual interference between the signal.
Drawings
FIG. 1 is a schematic block diagram of the system of the present invention;
FIG. 2 is a schematic block diagram of a sound collection system of the present invention;
FIG. 3 is a functional block diagram of a noise class unit of the present invention;
FIG. 4 is a schematic block diagram of a sound source calculation unit of the present invention;
FIG. 5 is a schematic block diagram of a distance calculation unit of the present invention;
FIG. 6 is a functional block diagram of a GPS positioning unit of the present invention;
FIG. 7 is a functional block diagram of the channel setup unit of the present invention;
FIG. 8 is a functional block diagram of an online control unit of the present invention;
FIG. 9 is a logic decision diagram of the sound collection system of the present invention;
FIG. 10 is a diagram of the steps of the analysis method of the present invention.
In the figure, 1-sound collection system, 11-volume collection unit, 12-decibel setting unit, 13-contrast analysis unit, 14-volume output unit, 2-sound source analysis system, 21-noise category unit, 211-timbre collection module, 212-processing module, 213-timbre library module, 214-timbre identification module, 22-sound source calculation unit, 221-wave frequency module, 222-air loss module, 223-calculation module, 224-display module, 225-user interaction parameter setting module, 3-sound filtering system, 4-sound source positioning system, 41-distance calculation unit, 411-sound transmission time difference module, 412-speed setting module, 413-distance display module, 42-GPS positioning unit, 12-sound transmission time difference module, 421-a map module, 422-a distance value module, 423-a data combination module, 5-a data feedback system, 6-a multichannel setting system, 61-a channel setting unit, 611-a channel classification module, 612-a delay passing module, 613-a node capacity expansion module, 614-a signal separation module, 62-a transcoding output unit, 7-a real-time monitoring system, 71-an information storage unit, 72-an online control unit, 721-a remote control terminal, 722-a central processing unit, 723-a continuous power supply module and 724-a dynamic display module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1 to 10, an embodiment of the present invention provides a technical solution: the multichannel noise analysis system based on big data comprises a sound collection system 1, a sound source analysis system 2, a sound filtering system 3, a sound source positioning system 4, a data feedback system 5, a multichannel setting system 6 and a real-time monitoring system 7, wherein the output end of the sound collection system 1 is connected with the input ends of the sound source analysis system 2 and the sound filtering system 3, the output end of the sound source analysis system 2 is connected with the input ends of the sound source positioning system 4, the data feedback system 5 and the multichannel setting system 6, the output end of the data feedback system 5 is connected with the input end of the sound source analysis system 2, and the output end of the multichannel setting system 6 is connected with the input end of the real-time monitoring system 7; sound collection system 1 includes volume collection unit 11, decibel sets for unit 12, contrastive analysis unit 13 and volume output unit 14, volume collection unit 11's output and decibel set for unit 12's input and are connected, decibel sets for unit 12's output and contrastive analysis unit 13's input and is connected, contrastive analysis unit 13's output and volume output unit 14's input are connected, volume output unit 14 includes noise volume module and normal volume module, the output of noise volume module is connected with sound source analysis system 2's input, and the output of normal volume module is connected with sound filtration system 3's input.
In the embodiment of the present invention, the sound source analysis system 2 includes a noise category unit 21 and a sound source calculation unit 22, the noise category unit 21 includes a sound color collection module 211, a processing module 212, a sound color library module 213, and a sound color identification module 214, an output end of the sound color collection module 211 is connected to an input end of the processing module 212, an output end of the processing module 212 is connected to an input end of the sound color library module 213, an output end of the sound color library module 213 is connected to an input end of the sound color identification module 214, the sound source calculation unit 22 includes a wave frequency module 221, an air loss module 222, a calculation module 223, a display module 224, and a user interaction parameter setting module 225, an output end of the wave frequency module 221 is connected to an input end of the air loss module 222, an output end of the air loss module 222 is connected to an input end of the calculation module 223, an output end of the calculation module 223 is connected to an input end of the display module 224, the output end of the user interaction parameter setting module 225 is connected with the input ends of the calculation module 223 and the display module 224.
In the embodiment of the present invention, the sound source positioning system 4 includes a distance calculating unit 41 and a GPS positioning unit 42, the distance calculating unit 41 includes a sound transmission time difference module 411, a speed setting module 412 and a distance display module 413, an output end of the sound transmission time difference module 411 is connected to an input end of the speed setting module 412, an output end of the speed setting module 412 is connected to an input end of the distance display module 413, the GPS positioning unit 42 includes a map module 421, a distance value module 422 and a data combining module 423, and output ends of the map module 421 and the distance value module 422 are connected to input ends of the data combining module 423.
In this embodiment of the present invention, the multi-channel setting system 6 includes a channel setting unit 61 and a transcoding output unit 62, where the channel setting unit 61 includes a channel classification module 611, a delay pass module 612, a node capacity expansion module 613, and a signal separation module 614, an output end of the channel classification module 611 is connected to an input end of the delay pass module 612, an output end of the delay pass module 612 is connected to an input end of the node capacity expansion module 613, and an output end of the node capacity expansion module 613 is connected to an input end of the signal separation module 614.
In the embodiment of the present invention, the real-time monitoring system 7 includes an information storage unit 71 and an online control unit 72, the online control unit 72 includes a remote control terminal 721, a central processing unit 722, a continuous power supply module 723, and a dynamic display module 724, an output end of the remote control terminal 721 is connected to an input end of the central processing unit 722, an output end of the central processing unit 722 is connected to an input end of the central processing unit 722, and an output end of the continuous power supply module 723 is connected to an input end of the dynamic display module 724.
The invention also discloses an analysis method of the big data-based multi-channel noise analysis system, which specifically comprises the following steps:
s1, sound data acquisition and filtering: firstly, sound data are collected through a volume collection unit 11, decibels of noise are set through a decibel setting unit 12, a comparison analysis unit 13 is used for analyzing and comparing, a volume output unit 14 determines that the output volume is normal volume or noise volume, if the volume output unit 14 determines that the output volume is normal volume, a sound filtering system 3 can directly filter the output volume, and if the volume output unit 14 determines that the output volume is noise volume, the sound data only need to enter a sound source analysis system 2;
s2, sound source analysis: the sound color of the sound data is collected through a sound color collecting module 211, the sound color of the sound data is collected through a processing module 212, the data which is the same as the sound color of the sound data is selected from a sound color library module 213 and is identified by matching with a sound color identifying module 214, the wave frequency module 221 displays the wave frequency of the sound data, the loss of the sound transmitted in the air is calculated through an air loss module 222, the calculation module 223 displays the calculated result through a display module 224, and a user interaction parameter setting module 225 can set the parameters of the calculation module 223 and the display module 224;
s3, sound source positioning: a sound transmission time difference module 411 in the distance calculation unit 41 calculates the time difference of sound transmission of a starting point and an end point, the speed setting module 412 sets the transmission speed of sound in the air, and the distance display module 413 displays the distance, a map module 421 and a distance value module 422 in the GPS positioning unit 42 synchronously display the map position and the distance value, and the map position and the distance value are comprehensively displayed by matching with a set data combination module 423;
s4, setting a channel and controlling in real time: different types of data transmission channels are set through the channel classification module 611, the transmission time of data can be delayed through the delay pass module 612, the storage capacity of the channels is temporarily expanded through the node capacity expansion module 613, signals of adjacent channels are isolated by the signal separation module 614, finally, the central processing unit 722 is remotely controlled by the remote control terminal 721, the continuous power supply process is performed through the continuous power supply module 723, and the dynamic display is performed through the dynamic display module 724.
In the embodiment of the present invention, in the sound source analysis process in S2, the tone library module 213 may collect and store mass data.
And those not described in detail in this specification are well within the skill of those in the art.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. Multichannel noise analysis system based on big data, its characterized in that: the system comprises a sound collection system (1), a sound source analysis system (2), a sound filtering system (3), a sound source positioning system (4), a data feedback system (5), a multi-channel setting system (6) and a real-time monitoring system (7), wherein the output end of the sound collection system (1) is connected with the input ends of the sound source analysis system (2) and the sound filtering system (3), the output end of the sound source analysis system (2) is connected with the input ends of the sound source positioning system (4), the data feedback system (5) and the multi-channel setting system (6), the output end of the data feedback system (5) is connected with the input end of the sound source analysis system (2), and the output end of the multi-channel setting system (6) is connected with the input end of the real-time monitoring system (7);
sound collection system (1) sets for unit (12), contrastive analysis unit (13) and volume output unit (14) including volume acquisition unit (11), decibel, the output of volume acquisition unit (11) is connected with the input that decibel set for unit (12), the output that decibel set for unit (12) is connected with contrastive analysis unit's (13) input, contrastive analysis unit's (13) output is connected with the input of volume output unit (14), volume output unit (14) are including noise volume module and normal volume module, the output of noise volume module is connected with the input of sound source analysis system (2), and the output of normal volume module is connected with the input of sound filtration system (3).
2. The big-data based multi-channel noise analysis system according to claim 1, wherein: sound source analysis system (2) include noise classification unit (21) and sound source computational element (22), noise classification unit (21) include tone color collection module (211), processing module (212), tone color library module (213) and tone color identification module (214), the output of tone color collection module (211) is connected with the input of processing module (212), the input of output tone color library module (213) of processing module (212) is connected, the output of tone color library module (213) is connected with the input of tone color identification module (214).
3. The big-data based multi-channel noise analysis system according to claim 2, wherein: the sound source computing unit (22) comprises a wave frequency module (221), an air loss module (222), a computing module (223), a display module (224) and a user interaction parameter setting module (225), wherein the output end of the wave frequency module (221) is connected with the input end of the air loss module (222).
4. The big-data based multi-channel noise analysis system according to claim 3, wherein: the output end of the air loss module (222) is connected with the input end of a calculation module (223), the output end of the calculation module (223) is connected with the input end of a display module (224), and the output ends of the user interaction parameter setting modules (225) are connected with the input ends of the calculation module (223) and the display module (224).
5. The big-data based multi-channel noise analysis system according to claim 1, wherein: the sound source positioning system (4) comprises a distance calculation unit (41) and a GPS positioning unit (42), wherein the distance calculation unit (41) comprises a sound transmission time difference module (411), a speed setting module (412) and a distance display module (413), the output end of the sound transmission time difference module (411) is connected with the input end of the speed setting module (412), and the output end of the speed setting module (412) is connected with the input end of the distance display module (413).
6. The big-data based multi-channel noise analysis system according to claim 5, wherein: the GPS positioning unit (42) comprises a map module (421), a distance value module (422) and a data combination module (423), wherein the output ends of the map module (421) and the distance value module (422) are connected with the input end of the data combination module (423).
7. The big-data based multi-channel noise analysis system according to claim 1, wherein: the multichannel setting system (6) comprises a channel setting unit (61) and a transcoding output unit (62), wherein the channel setting unit (61) comprises a channel classification module (611), a delay pass-through module (612), a node capacity expansion module (613) and a signal separation module (614), the output end of the channel classification module (611) is connected with the input end of the delay pass-through module (612), the output end of the delay pass-through module (612) is connected with the input end of the node capacity expansion module (613), and the output end of the node capacity expansion module (613) is connected with the input end of the signal separation module (614).
8. The big-data based multi-channel noise analysis system according to claim 1, wherein: the real-time monitoring system (7) comprises an information storage unit (71) and an online control unit (72), wherein the online control unit (72) comprises a remote control terminal (721), a central processing unit (722), a continuous power supply module (723) and a dynamic display module (724), the output end of the remote control terminal (721) is connected with the input end of the central processing unit (722), the output end of the central processing unit (722) is connected with the input end of the central processing unit (722), and the output end of the continuous power supply module (723) is connected with the input end of the dynamic display module (724).
9. The analysis method of the multichannel noise analysis system based on big data is characterized in that: the method specifically comprises the following steps:
s1, sound data acquisition and filtering: firstly, sound data are collected through a volume collection unit (11), decibels of noise are set through a decibel setting unit (12), a comparison analysis unit (13) is used for analyzing and comparing, a volume output unit (14) determines the output volume to be normal volume or noise volume, if the volume output unit (14) determines the output volume to be normal volume, a sound filtering system (3) can directly filter the output volume, and if the volume output unit (14) determines the output volume to be noise volume, the sound data can enter a sound source analysis system (2);
s2, sound source analysis: the method comprises the steps that tone collection of sound data is carried out through a tone collection module (211), a processing module (212) carries out analysis processing, data which are the same as tone of the sound data are selected from a tone library module (213) and are matched with a tone recognition module (214) for recognition, a wave frequency module (221) displays wave frequency of the sound data, loss of sound transmission in air is calculated through an air loss module (222), a calculation module (223) displays a calculation result through a display module (224), and a user interaction parameter setting module (225) can set parameters of the calculation module (223) and the display module (224);
s3, sound source positioning: a sound transmission time difference module (411) in a distance calculation unit (41) calculates the time difference of sound transmission of a starting point and an end point, a speed setting module (412) sets the transmission speed of sound in the air, and a distance display module (413) displays the distance, a map module (421) and a distance value module (422) in a GPS positioning unit (42) synchronously display the map position and the distance value, and a data combination module (423) which is matched with the map position and the distance value is comprehensively displayed;
s4, setting a channel and controlling in real time: different types of data transmission channels are set through a channel classification module (611), the transmission time of data can be delayed through a module (612) after delay, the storage capacity of the channel is temporarily expanded through a node capacity expansion module (613), signals of adjacent channels are isolated by matching with a signal isolation module (614), and finally a remote control terminal (721) remotely controls a central processing unit (722), continuously supplies power through a continuous power supply module (723), and dynamically displays the power through a dynamic display module (724).
10. The analysis method of the big-data based multi-channel noise analysis system according to claim 9, wherein: in the sound source analysis process in S2, the sound color library module (213) may summarize and store the mass data.
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