CN113739906B - Noise exposure index statistical method, device, equipment and storage medium - Google Patents
Noise exposure index statistical method, device, equipment and storage medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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- H04R3/00—Circuits for transducers, loudspeakers or microphones
- H04R3/005—Circuits for transducers, loudspeakers or microphones for combining the signals of two or more microphones
Abstract
The application discloses a noise exposure index statistical method, a device, equipment and a storage medium, wherein the noise exposure index statistical method comprises the following steps: acquiring the number of devices of the online device; acquiring noise signals acquired by microphones of different online devices, and acquiring exposure time of the noise signals; performing data processing on the noise signal and the exposure time to obtain a corresponding noise exposure value of the online equipment; and averaging the noise exposure value by the number of the devices, and outputting the noise exposure index. According to the application, the noise exposure condition is embodied through the noise exposure index, and a user can know the noise exposure condition of the current environment only by carrying the equipment provided with the microphone, so that corresponding protective measures can be made according to the noise exposure index, and the user experience is improved.
Description
Technical Field
The present application relates to the field of telecommunications technologies, and in particular, to a noise exposure index statistics method, apparatus, device, and storage medium.
Background
Noise is sound which people inevitably contact in daily life, and the noise is extremely harmful to the hearing of individuals when being excessively exposed to the noise environment, and particularly the noise is extremely greatly influenced in places such as construction sites, large factories, military exercise bases and the like. Therefore, the detection of the noise figure can enable people to know the specific noise value of the current place, so that corresponding protective measures can be made according to the noise value, hearing of people can be protected, and later irreversible hearing damage is avoided.
In the related art, a professional noise detector is required for noise calculation, and thus, people want to know the noise situation of the current location need to purchase the professional noise detector, so that the cost of knowing the noise situation increases.
Disclosure of Invention
The present application aims to solve at least one of the technical problems existing in the prior art. Therefore, the application provides the noise exposure index statistical method, which can know the noise exposure index only by the equipment carrying the microphone, saves the cost of noise detection, and is convenient for a user to more accurately master the noise exposure condition of the user so as to adopt a more effective and reasonable mode for protection.
The application also provides a noise exposure index statistics device.
The application further provides electronic equipment.
The application also proposes a computer readable storage medium.
In a first aspect, an embodiment of the present application provides a noise exposure index statistical method, including:
acquiring the number of devices of the online device;
acquiring noise signals acquired by microphones of different online devices, and acquiring exposure time of the noise signals;
performing data processing on the noise signal and the exposure time to obtain a corresponding noise exposure value of the online equipment;
and averaging the noise exposure value by the number of the devices, and outputting the noise exposure index.
The noise exposure index statistical method provided by the embodiment of the application has at least the following beneficial effects: the noise signals and the exposure time length acquired by the microphones of different online devices are acquired, then the noise signals and the exposure time length are subjected to data processing to obtain the noise exposure value of the online devices, and then the noise exposure index is obtained through calculation according to the noise exposure value and the number of the devices, so that the noise exposure condition is embodied through the noise exposure index, a user can know the noise exposure condition of the current environment by only carrying the device provided with the microphones, and corresponding protective measures can be made according to the noise exposure index, so that the user experience is improved.
According to other embodiments of the present application, the noise exposure index statistical method further includes:
acquiring initial time information and standard time information of the online equipment which is connected for the first time;
carrying out synchronous processing on the initial time information according to the standard time information to obtain synchronous time information;
and sending the synchronous time information to the online equipment which is connected for the first time.
According to other embodiments of the present application, the noise exposure index statistical method further includes:
and collecting the noise signals and the exposure time period collected by the microphone of the online equipment according to a preset first time interval period.
According to other embodiments of the present application, the data processing is performed on the noise signal and the exposure time to obtain a noise exposure value corresponding to the online device, including:
carrying out Fourier transform processing on the noise signals to obtain noise transformed signals;
performing compensation processing on the noise conversion signal to obtain a compensation signal;
and carrying out average processing on the compensation signal and the exposure time to obtain the noise exposure value.
According to another embodiment of the present application, the noise exposure index statistics method averages the compensation signal and the exposure duration to obtain the noise exposure value, including:
and carrying out average processing on the compensation signal and the exposure time length according to a preset calculation formula to obtain the noise exposure value.
According to other embodiments of the present application, the noise exposure index statistical method further includes:
acquiring the equipment quantity of the online equipment according to a preset second time interval period, wherein the second time interval is the same as the first time interval;
and updating the noise exposure index according to the second time interval period.
According to other embodiments of the present application, the noise exposure index statistical method further includes:
and sending the noise exposure index to an address link corresponding to preset address information.
In a second aspect, an embodiment of the present application provides a noise exposure index statistical apparatus, including:
the first acquisition module is used for acquiring the equipment number of the online equipment;
the second acquisition module is used for acquiring noise signals acquired by microphones of different online equipment and acquiring the exposure time of the noise signals;
the data processing module is used for carrying out data processing on the noise signal and the exposure time length and outputting a corresponding noise exposure value of the online equipment;
and the average processing module is used for carrying out average processing on the noise exposure value according to the equipment number to obtain the noise exposure index.
The noise exposure index statistical device provided by the embodiment of the application has at least the following beneficial effects: the noise signals and the exposure time length acquired by the microphones of different online devices are acquired, then the noise signals and the exposure time length are subjected to data processing to obtain the noise exposure value of the online devices, and then the noise exposure index is obtained through calculation according to the noise exposure value and the number of the devices, so that the noise exposure condition is embodied through the noise exposure index, a user can know the noise exposure condition of the current environment by only carrying the device provided with the microphones, and corresponding protective measures can be made according to the noise exposure index, so that the user experience is improved.
In a third aspect, an embodiment of the present application provides an electronic device, including:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the noise exposure index statistical method according to the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the noise exposure index statistical method according to the first aspect.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
FIG. 1 is a flowchart of a noise exposure index statistics method according to an embodiment of the application;
FIG. 2 is a flowchart of another embodiment of a noise exposure index statistics method according to an embodiment of the present application;
FIG. 3 is a flowchart of another embodiment of a noise exposure index statistics method according to an embodiment of the present application;
FIG. 4 is a flowchart illustrating the step S300 in FIG. 1;
FIG. 5 is a waveform diagram of an acquired noise signal of a noise exposure index statistical method according to an embodiment of the present application;
FIG. 6 is a waveform diagram of an acquired noise signal of a noise exposure index statistical method according to an embodiment of the present application;
FIG. 7 is a flowchart of another embodiment of a noise exposure index statistics method according to an embodiment of the present application;
FIG. 8 is a block diagram of an embodiment of a noise exposure index statistics apparatus according to an embodiment of the present application;
FIG. 9 is a block diagram of an embodiment of an electronic device in accordance with an embodiment of the present application.
Reference numerals: 100. a first acquisition module; 200. a second acquisition module; 300. a data processing module; 400. the average value processing module; 110. a processor; 120. a memory.
Detailed Description
The conception and the technical effects produced by the present application will be clearly and completely described in conjunction with the embodiments below to fully understand the objects, features and effects of the present application. It is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments, and that other embodiments obtained by those skilled in the art without inventive effort are within the scope of the present application based on the embodiments of the present application.
In the description of the present application, if an orientation description such as "upper", "lower", "front", "rear", "left", "right", etc. is referred to, it is merely for convenience of description and simplification of the description, and does not indicate or imply that the apparatus or element referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the application. If a feature is referred to as being "disposed," "secured," "connected," or "mounted" on another feature, it can be directly disposed, secured, or connected to the other feature or be indirectly disposed, secured, connected, or mounted on the other feature.
In the description of the embodiments of the present application, if "several" is referred to, it means more than one, if "multiple" is referred to, it is understood that the number is not included if "greater than", "less than", "exceeding", and it is understood that the number is included if "above", "below", "within" is referred to. If reference is made to "first", "second" it is to be understood as being used for distinguishing technical features and not as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
Noise is sound which people inevitably contact in daily life, and the hearing of people is damaged due to excessive exposure to the noise environment, and particularly the influence of the noise is huge in occasions such as construction sites, large factories, military exercise bases and the like. People can alleviate noise damage to a certain extent by wearing earmuffs, tamponade and the like, but the inconvenience and discomfort caused by the noise damage can lead staff to reduce the importance degree of the noise damage, so that the protection measures are ignored. However, the noise detection equipment is not installed in the occasions such as construction sites, large factories, military exercise bases and the like, so that people cannot know the current noise value, and cannot make corresponding protective measures according to the noise value, and hidden danger is brought to the health of people.
Based on the method, the application discloses a noise exposure index statistical method, which is characterized in that noise signals acquired by microphones of different online equipment are acquired, so that the noise exposure index is calculated according to the noise signals and the noise time length, and the noise exposure index statistics can be carried out through the noise signals acquired by the microphones, so that a user can clearly know the noise condition of the current environment according to the noise exposure index, and the hearing of the user is more effectively protected by making corresponding protective measures according to the noise exposure index.
In a first aspect, referring to fig. 1, the present application discloses a noise exposure index statistical method, including:
s100, acquiring the number of devices of the online device;
the online equipment is online equipment in the registered equipment, equipment corresponding to the registration information is registered according to the registration information input by a user, the running state of the registered equipment is acquired after the equipment registration is completed, and the registered equipment with the running state of the online equipment is defined as the online equipment. The registered devices are devices currently carried by a user, the device types of the registered devices are different, and each registered device is provided with a microphone so as to collect noise signals of a field environment through the microphone on the online device, thereby improving the accuracy of noise exposure index statistics.
The registered device may be a watch, a bracelet, a sports earphone, a TWS earphone, a mobile phone and the like, so that the registered device in an on-line state is determined to obtain the on-line device, then a noise signal is collected according to a microphone on the on-line device, and then a noise exposure index is determined according to the noise signal and the exposure time length, so that statistics of the noise exposure index is realized, and a user can conveniently know the noise environment of the current environment to make corresponding protective measures.
S200, acquiring noise signals acquired by microphones of different online devices, and acquiring exposure time of the noise signals;
the registered device defining the online state is online device, then the noise signals collected by the microphones on different online devices are obtained, and the exposure time of the noise signals collected by the microphones, namely the time of existence of the noise signals, is calculated. Considering the endurance capacity and the use duration of one device, the same device cannot be guaranteed to be used in one day, and then the noise signals of microphones of different online devices need to be acquired to guarantee the stable acquisition of the noise signals.
S300, carrying out data processing on the noise signals and the exposure time to obtain a corresponding noise exposure value of the online equipment;
after the noise signals and the exposure time are collected, the noise signals and the exposure time collected by each online device are subjected to data processing to obtain noise exposure values, namely noise exposure values measured by the online device.
S400, carrying out average processing on the noise exposure value according to the number of the devices, and outputting a noise exposure index.
After the noise exposure value measured by each online device is determined, the device number of the online devices and the noise exposure values measured by all the online devices are subjected to average processing to obtain a noise exposure index, so that the obtained noise exposure index is more in line with the environment of the current user, and the accuracy of the noise exposure index is improved.
Referring to fig. 2, in some embodiments, the noise exposure index statistical method further comprises:
s500, acquiring initial time information and standard time information of the online equipment which is connected for the first time;
when the online equipment is connected for the first time, because the time of the initial connection is inaccurate, the initial time information of the online equipment which is connected for the first time is acquired, the standard time information is acquired, and the standard time information is from the world standard time sent by the current satellite.
If the online equipment does not have the initial time information, an RTC chip is configured for the online equipment, so that the initial time of the online equipment is calculated through the RTC chip, the initial time information of the online equipment is obtained, and the exposure duration of the noise signal can be clear.
S600, synchronizing the initial time information according to the standard time information to obtain synchronized time information;
and when the acquired initial time information and the standard time information are not synchronous, carrying out synchronous processing on the initial time information according to the standard time information to obtain synchronous time information so as to realize time synchronization. After the time synchronization is completed, the exposure time fed back by the online equipment is acquired more accurately.
And S700, transmitting the synchronous time information to the online equipment which is connected for the first time.
And when the time synchronization is completed, obtaining time synchronization information, and sending the time synchronization information to the online equipment which is connected for the first time, determining the current time by the online equipment according to the time synchronization information so as to complete the time synchronization operation of the online equipment, wherein the exposure time fed back by the online equipment is more accurate.
Referring to fig. 3, in some embodiments, the noise exposure index statistics method is further characterized by:
s800, collecting noise signals and exposure time period collected by a microphone of the online equipment according to a preset first time interval period.
And collecting noise signals and noise duration collected by a microphone of the online equipment according to a preset first time interval period so as to update the noise signals and the exposure duration according to the environment where a user is located, and updating the noise exposure index according to the noise signals and the exposure duration collected again according to the preset first time interval so as to update the noise exposure index according to the preset first time interval periodically so as to improve the accuracy of the noise exposure index.
Referring to fig. 4, in some embodiments, step S300 includes, but is not limited to including steps S310 to S330, step S300 including:
s310, carrying out Fourier transform processing on the noise signal to obtain a noise transformed signal;
s320, compensating the noise conversion signal to obtain a compensation signal;
and S330, carrying out average processing on the compensation signal and the exposure time length to obtain a noise exposure value.
Since the input noise quotation marks are speech frame signals, fourier transform processing is required for the noise signals to obtain noise variation signals in order to perform compensation processing. Because the frequency response of different microphones is different, the missing part is compensated by measuring the frequency response of the microphones so as to simulate the receiving condition of the human ear on the sound through the microphones, and thus the actual noise exposure condition of the human ear is calculated. Therefore, the noise conversion signal is compensated to obtain a compensation signal, an effective compensation signal is obtained through compensation, and then an average process is performed according to the compensation signal and the exposure time to obtain a noise exposure value, so that the noise exposure value of each online device is obtained.
Specifically, because the microphones are different, the sensitivity of each frequency point in the recording process is inconsistent, and the frequency response curve corresponding to the noise signal collected by the microphone is expected to be a straight line, but the noise signal collected by the microphone is shown in fig. 5 and 6, and the noise signal collected by the microphone is actually a curve, so that the noise conversion signal obtained by the noise signal processing needs to be compensated. The compensation processing of the noise conversion signal needs to determine frequency points corresponding to the noise conversion signal, determine a compensation value corresponding to each frequency point, and then construct a compensation value sequence to perform the compensation processing of the noise conversion signal according to the compensation value sequence. If the compensation value sequence of the noise transformed signal at each frequency point is assumed to be H, the compensation value sequence H may be expressed as:
H 1 ＝[x 1 ,x 2 ,x 3 ,…,x N ] (1)
wherein, N frequency points are set with sampling rate of F, x n The corresponding frequency point is f n The corresponding relation between the frequency point and the sampling rate is as follows:
if be equipped with protective equipment on the microphone, wherein, protective equipment includes: and the microphone cover and the microphone plug have influence on the noise signals collected by the microphone by the protective equipment. The protective device thus has blocking capability for the acquired noise signals at various frequency points. Under the condition that the noise energy corresponding to the noise signal is A, measuring to obtain the energy of each frequency point of the on-band protection equipment as P, defining H 2 The correction parameters of the protection device when the noise is counted for the microphone are as follows:
H 2 ＝A-P＝[y 1 ,y 2 ,y 3 ,…,y N ] (3)
therefore, when the microphone carrying the protective equipment is used, the noise transformation signal is modified according to the modification parameters to obtain the modification signal, so that the noise exposure index calculated according to the modification signal is more accurate.
Assuming that the noise signal is s, performing fourier transform processing on the noise signal mainly includes performing fourier transform processing on the noise signal by using a fourier transform formula, and performing fourier transform processing on the noise signal as follows:
S＝FFT(s) (4)
after the noise signal is fourier transformed to obtain a noise transformed signal, the noise transformed signal is compensated to obtain a compensation signal, and the noise transformed signal is compensated as follows:
S＝S+H 1 -H 2 +A (5)
after obtaining the noise conversion signal, the noise conversion signal is subjected to inverse conversion to obtain an effective compensation signal as follows:
s＝IFFT(S) (6)
therefore, the noise signal is fourier transformed by the formulas (4) to (6) and then compensated to obtain a more accurate noise signal.
In some embodiments, step S330 includes, but is not limited to including step S331, step S330 including:
s331, carrying out average processing on the compensation signal and the exposure time length according to a preset calculation formula to obtain a noise exposure value.
By carrying out average processing on the compensation signal and the exposure time length by a preset calculation formula, the noise exposure value can be accurately obtained, namely, the average noise amplitude in the whole exposure time length is known, and the noise influence degree of the environment where the user is can be more accurately displayed.
Specifically, the noise exposure value is obtained by carrying out average processing on the compensation signal and the exposure time according to a preset calculation formula, as follows:
wherein p is ref Representing the minimum audible sound pressure amplitude of 20 muPa for the human ear at 1000 Hz.
Therefore, the noise exposure value is obtained by carrying out average processing on the compensation signal and the exposure time through the formulas (7) and (8), so as to more accurately represent the noise influence degree of the environment in which the user is located.
Referring to fig. 7, in some embodiments, the noise exposure index statistical method further comprises:
s900, acquiring the number of devices of the online device according to a preset second time interval period, wherein the second time interval is the same as the first time interval;
s1000, updating the noise exposure index according to the second time interval period.
The number of the online devices is acquired according to the preset second time interval period, so that the running state of the registered devices is acquired according to the preset second time interval period, the registered devices with the running state of the online state are acquired, the registered devices are defined as the online devices, the number of the online devices is acquired, the noise exposure value can be calculated according to the noise signals acquired by the microphones of each online device, and the noise exposure index is updated according to the re-acquired noise exposure value and the online devices in the second time interval period so as to update the noise exposure condition of the position of the user in real time, and the user can make protection in a more effective and reasonable mode according to the noise exposure index.
TABLE 1
| Time | Apparatus 1 | Device 2 | Device 3 | Noise exposure index |
| t1 | c1 | c1 | ||
| t2 | c2 | c2 | ||
| t3 | c3 | c3 | ||
| t4 | c4 | c4 | ||
| t5 | c5 | c5 | ||
| t6 | a1 | c6 | (a1+c6)/2 | |
| t7 | a2 | c7 | (a2+c7)/2 | |
| t8 | a3 | b1 | c8 | (a3+b1+c8)/3 |
Wherein, table 1 is a noise exposure index updated according to a preset second time interval period. Referring to table 1, wherein the preset first time interval and second time interval are t, the number of devices of the online device is updated at interval t, and the noise exposure index is updated at regular time. As shown in table 1, if the registered device includes device 1, device 2 and device 3, and it is detected that only device 3 is the online device at time t1, the noise exposure value of device 3 is calculated to be c1, and the noise exposure index is c1; if at time t6 it is detected that the online device comprises device 1 and device 3, and that the noise exposure value of device 1 is a1 and the noise exposure value of device 3 is c6, then the noise exposure index is (a1+c6)/2; if at time t8, the online device includes device 1, device 2 and device 3, and the noise exposure value of device 1 is a3, the noise exposure value of device 2 is b1, and the noise exposure value of device 3 is c8, then the current noise exposure index is (a1+a2+a3)/3. Therefore, the noise exposure index is calculated according to the noise exposure value of the on-line equipment and the number of the equipment, the obtained noise exposure index is more concrete, and a user can more accurately master the noise exposure condition of the user.
In some embodiments, the noise exposure index statistical method further includes, but is not limited to, the steps of:
and sending the noise exposure index to an address link corresponding to the preset address information.
And according to the address information preset by the user, calculating to obtain a noise exposure index and then sending the noise exposure index to an address link corresponding to the address information in real time. If the address information is a micro signal, the noise exposure index is sent to a micro message corresponding to the micro signal; if the address information is the IP address, the noise exposure indication is sent to the terminal corresponding to the IP address, so that the user can clearly know the current noise exposure condition, and corresponding protective measures can be conveniently made according to the noise exposure index.
A noise exposure index statistical method according to an embodiment of the present application is described in detail below with reference to fig. 1 to 7 in a specific embodiment. It is to be understood that the following description is exemplary only and is not intended to limit the application in any way.
And acquiring the running state of the registered equipment according to a preset second time interval period, defining the registered equipment with the running state of being in an on-line state as on-line equipment, and acquiring the equipment number of the on-line equipment. And then acquiring a noise signal and exposure time length acquired by a microphone of the online equipment, firstly carrying out Fourier transform processing on the noise signal to obtain a noise transformation signal, then carrying out compensation processing on the noise transformation signal to obtain a more accurate compensation signal, carrying out average processing on the compensation signal and the exposure time length to obtain a noise exposure value, adding the noise exposure value of each online equipment and dividing the noise exposure value by the number of the equipment to obtain a noise exposure index, and sending the noise exposure index to an address link corresponding to preset address information, so that a user can grasp the noise exposure condition of the current environment in real time to make corresponding protective measures according to the noise exposure index, thereby improving the experience of the user.
In a second aspect, referring to fig. 8, an embodiment of the present application further discloses a noise exposure index statistics apparatus, including: the device comprises a first acquisition module 100, a second acquisition module 200, a data processing module 300 and a mean value processing module 400; the first obtaining module 100 is configured to obtain a device number of an online device; the second obtaining module 200 is configured to obtain noise signals collected by microphones of different online devices, and obtain an exposure duration of the noise signals; the data processing module 300 is used for performing data processing on the noise signal and the exposure time, and outputting a corresponding noise exposure value of the online equipment; the mean processing module 400 is configured to average the noise exposure value by the number of devices to obtain a noise exposure index.
The number of devices of the on-line devices is obtained through the first obtaining module 100, the second obtaining module 200 obtains noise signals and exposure time periods collected by microphones of different on-line devices, the data processing module 300 processes the noise signals and the exposure time periods to obtain noise exposure values, the average processing module 400 processes the noise exposure values and the number of devices to obtain noise exposure indexes, the noise exposure indexes can be calculated according to the noise signals collected by the microphones, a user can know the noise signals of the current environment only by carrying the device with the microphone, so that the user can protect in a more effective and reasonable mode according to the noise exposure indexes, and the experience of the user is improved.
The on-line equipment can be an earphone with a real-time clock, an operation bracelet, a mobile phone and the like, so that a microphone is configured according to equipment carried by a user to acquire a noise signal and exposure time, a noise exposure index can be calculated, and user experience is improved.
Referring to fig. 9, in a third aspect, the embodiment of the present application further discloses an electronic device, including:
at least one processor 110, and,
a memory 120 communicatively coupled to the at least one processor 110; wherein,
the memory 120 stores instructions executable by the at least one processor 110 to enable the at least one processor 110 to perform the noise exposure index statistical method as described in the first aspect.
In a fourth aspect, embodiments of the present application also disclose a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the noise exposure index statistical method according to the first aspect.
The above described apparatus embodiments are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
The embodiments of the present application have been described in detail with reference to the accompanying drawings, but the present application is not limited to the above embodiments, and various changes can be made within the knowledge of one of ordinary skill in the art without departing from the spirit of the present application. Furthermore, embodiments of the application and features of the embodiments may be combined with each other without conflict.
Claims (8)
1. A method of noise exposure index statistics, comprising:
acquiring the number of devices of the online device;
acquiring noise signals acquired by microphones of different online devices, and acquiring exposure time of the noise signals;
and carrying out data processing on the noise signal and the exposure time to obtain a corresponding noise exposure value of the on-line equipment, wherein the method specifically comprises the following steps:
carrying out Fourier transform processing on the noise signals to obtain noise transformed signals;
and compensating the noise conversion signal to obtain a compensation signal, wherein the compensation signal specifically comprises:
determining frequency points corresponding to the noise transformation information, and determining a compensation value corresponding to each frequency point;
constructing a compensation sequence according to the compensation value corresponding to each frequency point;
performing compensation processing on the noise conversion signal according to the compensation sequence to obtain the compensation signal;
and carrying out average processing on the compensation signal and the exposure time to obtain the noise exposure value, specifically, carrying out average processing on the compensation signal and the exposure time according to a preset calculation formula to obtain the noise exposure value, wherein the noise exposure value is as follows:
wherein p is ref Represents the minimum audible sound pressure amplitude of 20 muPa for the human ear at 1000Hz, N is the frequencyPoints, x n P is the energy of the compensation signal of each frequency point;
and averaging the noise exposure value by the number of the devices, and outputting the noise exposure index.
2. The noise exposure index statistical method according to claim 1, further comprising:
acquiring initial time information and standard time information of the online equipment which is connected for the first time;
carrying out synchronous processing on the initial time information according to the standard time information to obtain synchronous time information;
and sending the synchronous time information to the online equipment which is connected for the first time.
3. The noise exposure index statistical method according to claim 1, further comprising:
and collecting the noise signals and the exposure time period collected by the microphone of the online equipment according to a preset first time interval period.
4. A noise exposure index statistical method according to claim 3, further comprising:
acquiring the equipment quantity of the online equipment according to a preset second time interval period, wherein the second time interval is the same as the first time interval;
and updating the noise exposure index according to the second time interval period.
5. The noise exposure index statistical method according to claim 4, further comprising:
and sending the noise exposure index to an address link corresponding to preset address information.
6. A noise exposure index statistics apparatus, comprising:
the first acquisition module is used for acquiring the equipment number of the online equipment;
the second acquisition module is used for acquiring noise signals acquired by microphones of different online equipment and acquiring the exposure time of the noise signals;
the data processing module is used for performing data processing on the noise signal and the exposure time length and outputting a corresponding noise exposure value of the on-line equipment, and specifically comprises the following steps:
carrying out Fourier transform processing on the noise signals to obtain noise transformed signals;
and compensating the noise conversion signal to obtain a compensation signal, wherein the compensation signal specifically comprises:
determining frequency points corresponding to the noise transformation information, and determining a compensation value corresponding to each frequency point;
constructing a compensation sequence according to the compensation value corresponding to each frequency point;
performing compensation processing on the noise conversion signal according to the compensation sequence to obtain the compensation signal;
and carrying out average processing on the compensation signal and the exposure time to obtain the noise exposure value, specifically, carrying out average processing on the compensation signal and the exposure time according to a preset calculation formula to obtain the noise exposure value, wherein the noise exposure value is as follows:
wherein p is ref Represents the minimum audible sound pressure amplitude of the human ear at 1000Hz of 20 mu Pa, N is the number of frequency points, x n P is the energy of the compensation signal of each frequency point;
and the average processing module is used for carrying out average processing on the noise exposure value according to the equipment number to obtain the noise exposure index.
7. An electronic device, comprising:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the noise exposure index statistical method of any one of claims 1 to 5.
8. A computer-readable storage medium storing computer-executable instructions for causing a computer to perform the noise exposure index statistical method according to any one of claims 1 to 5.
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| CN202111009746.5A CN113739906B (en) | 2021-08-31 | 2021-08-31 | Noise exposure index statistical method, device, equipment and storage medium |
| PCT/CN2022/092792 WO2023029581A1 (en) | 2021-08-31 | 2022-05-13 | Noise exposure index statistical method and apparatus, and device and storage medium |
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| CN114216557B (en) * | 2021-12-21 | 2023-12-29 | 中国疾病预防控制中心职业卫生与中毒控制所 | Method and device for measuring normalized noise exposure level |
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