Noise reduction method, device, electronic apparatus and readable medium

Abstract

To provide a method, a device, an electronic apparatus and a readable medium for reducing noise audible to passengers riding in an elevator in real time without increasing the cost or load of the elevator.SOLUTION: A noise reduction method includes: collecting noise data during elevator operation and elevator operation data; selecting a corresponding noise reduction processing method based on a noise type of the noise data; performing noise reduction processing on the noise data based on the noise reduction processing method to obtain a noise reduction signal; calculating an output delay time of the noise reduction signal based on a noise reduction position within the elevator and a position of a noise reduction device; and outputting the noise reduction signal based on the delay time.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present application relates to the field of noise processing technology, and in particular to noise reduction methods, devices, electronic devices and readable media. [Background technology]

[0002] With the proliferation of high-rise residential and office buildings, people's reliance on elevators has grown significantly. Elevators are high-power equipment, and each major component, from the machine room to the elevator car, generates significant noise. Elevator noise signals are primarily concentrated in the low- and mid-range frequencies. High-intensity low- and mid-range noise can impair human hearing and cause varying degrees of damage to other parts of the human body. Current elevator noise reduction strategies generally employ passive noise control (PNC), which involves installing additional soundproofing panels. However, PNC technology only effectively blocks high-range noise. However, because airborne and structural noise generated during elevator operation are low- and mid-range noise, using PNC technology to reduce elevator noise does not significantly reduce noise. Furthermore, it requires the installation of a large number of soundproofing panels, which further increases the cost and load of elevators. Summary of the Invention [Problem to be solved by the invention]

[0003] In embodiments, the present application provides a noise reduction method, an apparatus, an electronic device, and a readable medium. [Means for solving the problem]

[0004] In a first aspect, an embodiment of the present application provides a noise reduction method applied to a noise reduction device, the method including: collecting noise data and elevator operation data during elevator operation; selecting a corresponding noise reduction processing method based on the noise type of the noise data; performing noise reduction processing on the noise data based on the noise reduction processing method to obtain a noise-reduced signal; calculating an output delay time of the noise-reduced signal based on the noise reduction position in the elevator and the position of the noise reduction device; and outputting the noise-reduced signal based on the delay time.

[0005] As can be understood, this noise reduction method involves installing multiple noise reduction devices on the interior walls of the elevator car or on the shared wall between the resident's living space and the elevator shaft wall. These noise reduction devices then use a software algorithm to reduce the noise generated by the elevator, thereby reducing the noise audible to the ears of elevator passengers. Furthermore, these noise reduction devices may have a thin, plate-like outer shape, with a small volume and light weight, thereby reducing the load on the elevator operation. The present application detects the elevator operation status based on the noise reduction method, then detects changes in noise data in real time and generates a noise reduction signal, thereby achieving noise reduction in real time.

[0006] In one possible implementation of the above first aspect, the noise types include airborne noise data and structural noise data, and the noise reduction device includes a first noise collecting unit and a second noise collecting unit, where the first noise collecting unit is used to collect airborne noise data during elevator operation, and the second noise collecting unit is used to collect structural noise data during elevator operation.

[0007] In one possible implementation form of the first aspect, the elevator operation data includes at least one of a preset elevator operation speed, a preset acceleration, and preset vibration data of each structure of the elevator that occurs during operation.

[0008] In one possible implementation form of the above first aspect, selecting a corresponding noise reduction processing method based on the noise type of the noise data includes: when the noise type of the noise data is air noise data, the selected noise reduction processing method is a first noise reduction processing method used to noise reduce the air noise data; and when the noise type of the noise data is structural noise data, the selected noise reduction processing method is a second noise reduction processing method used to perform noise reduction on the structural noise data when the structural noise data satisfies the noise reduction condition, and not to perform noise reduction on the structural noise data when the structural noise data does not satisfy the noise reduction condition.

[0009] In one possible implementation of the first aspect, an effective value is calculated for the structural noise data, and if the effective value is equal to or greater than a predetermined threshold, the structural noise data satisfies the noise reduction conditions, and noise reduction processing is performed on the structural noise data; if the effective value is less than the predetermined threshold, the structural noise data does not satisfy the noise reduction conditions, and no processing is performed on the structural noise data.

[0010] In one possible implementation form of the above first aspect, the noise-reduced signal includes a first-class noise-reduced signal corresponding to air noise data, and further, performing noise reduction processing on the noise data based on a noise reduction processing method to obtain the noise-reduced signal includes: filtering air noise data in the noise data based on a first noise reduction processing method to obtain first target noise data; performing a fast Fourier transform on the first target noise data to calculate a center frequency of the first target noise data; determining a first frequency band of the first target noise data based on the center frequency; calculating a median of the first frequency band based on the first frequency band to obtain a first centroid frequency; and combining the first centroid frequencies using a noise reduction algorithm to obtain the first-class noise-reduced signal.

[0011] In one possible implementation form of the above first aspect, performing noise reduction processing on noise data based on a noise reduction processing method to obtain a noise-reduced signal includes: calculating an average value or performing fuzzy processing on structural noise data in the elevator operation data and noise data based on a second noise reduction processing method to obtain effective structural noise data; filtering the effective structural noise data to obtain second target noise data; calculating an effective value of the second target noise data; and processing the second target noise based on the effective value of the second target noise data.

[0012] In one possible implementation of the above first aspect, the noise reduction signal includes a second type noise reduction signal corresponding to structural noise data, and further, processing the second target noise based on the effective value of the second target noise data includes determining that the second target noise data satisfies a noise reduction condition based on the effective value of the second target noise data; performing a fast Fourier transform on the second target noise data to calculate a center frequency of the second target noise data, and determining a second frequency band of the second target noise data based on the center frequency; calculating a second median of the second frequency band based on the second frequency band to obtain a second centroid frequency; and combining the second centroid frequencies using a noise reduction algorithm to obtain the second type noise reduction signal.

[0013] In one possible implementation of the above first aspect, calculating the delay time based on the noise reduction position and the position of the noise reduction device includes, when the noise reduction device is one of a plurality of noise reduction devices, determining the distance between the noise reduction position and the noise reduction device and calculating the delay time at which the noise reduction device outputs a noise reduction signal, wherein the delay time of a noise reduction device among the plurality of noise reduction devices that is farther from the noise reduction position is shorter than the delay time of a noise reduction device that is closer to the noise reduction position.

[0014] In one possible implementation form of the above first aspect, the noise reduction device includes a first noise reduction signal output unit and a second noise reduction signal output unit, wherein the first noise reduction signal output unit in the noise reduction device is used to output a first-class noise reduction signal corresponding to air noise data, and the second noise reduction signal output unit in the noise reduction device is used to output a second-class noise reduction signal corresponding to structure noise data.

[0015] In one possible implementation of the first aspect, the first noise collecting unit comprises at least one reference microphone and the second noise collecting unit comprises at least one vibration sensor.

[0016] In one possible implementation of the first aspect, the first noise-reducing signal output unit comprises at least one diaphragm speaker, and the second noise-reducing signal output unit comprises at least one vibration speaker.

[0017] In one possible implementation of the first aspect, the filtering process includes at least one of high-pass filtering, band-pass filtering, and low-pass filtering.

[0018] In one possible implementation of the first aspect, the noise reduction algorithm is the FxLMS algorithm.

[0019] In a second aspect, an embodiment of the present application provides a noise reduction device, the device including: a data collection module, a data processing module, and a signal output module, wherein the data collection module is used to collect noise data and elevator operation data during elevator operation; the data processing module is used to select a corresponding noise reduction processing method based on the noise type of the noise data, and to perform noise reduction processing on the noise data based on the noise reduction processing method to obtain a noise-reduced signal; the data processing module is also used to calculate an output delay time of the noise reduction signal based on the noise reduction position and the position of the noise reduction device in the elevator; and the signal output module is used to output the noise-reduced signal based on the delay time.

[0020] In one possible implementation of the above second aspect, the noise reduction device is one of a plurality of noise reduction devices attached to the elevator, the noise reduction device is any one of the plurality of noise reduction devices, or the noise reduction device is the noise reduction device of the plurality of noise reduction devices that has the highest degree of idle computing power.

[0021] In one possible implementation form of the above second aspect, the device further includes an intelligent selection module, which is used to obtain the degree of idleness of computing power of each noise reduction device in the plurality of noise reduction devices and determine that the noise reduction device is the noise reduction device with the highest degree of idleness of computing power among the plurality of noise reduction devices.

[0022] In one possible implementation form of the above second aspect, calculating the output delay time of the noise reduction signal based on the noise reduction position in the elevator and the position of the noise reduction device includes: the noise reduction device collecting each centroid frequency obtained by processing the noise data of each of the multiple noise reduction devices; combining each centroid frequency using a noise reduction algorithm to calculate a corresponding noise reduction signal for each of the multiple noise reduction devices; and calculating the delay time of the noise reduction signal output by each noise reduction device in the multiple noise reduction devices based on the noise reduction position and the position of each noise reduction device in the multiple noise reduction devices.

[0023] In one possible implementation form of the second aspect, the noise reduction device has a thin plate-like outer shape.

[0024] In one possible implementation of the second aspect, the location of the noise reduction device includes at least one of an inner wall surface of the elevator car and an outer wall surface of the elevator shaft.

[0025] In a third aspect, an embodiment of the present application provides an electronic device comprising one or more processors and one or more memories, wherein one or more programs are stored in the one or more memories, and when the one or more programs are executed by the one or more processors, the electronic device performs the noise reduction method provided in the first aspect above and each possible implementation form of the first aspect above.

[0026] In a fourth aspect, an embodiment of the present application provides a computer-readable medium having instructions stored thereon that, when executed on a computer, cause the computer to perform the noise reduction method provided in the first aspect above and each possible implementation of the first aspect above. [Brief explanation of the drawings]

[0027] [Figure 1] FIG. 1 is a schematic diagram showing a situation where noise interference occurs when riding an elevator. [Figure 2]FIG. 2 is a schematic diagram showing a situation in which noise generated during elevator operation affects residents. [Figure 3] FIG. 3 is a structural schematic diagram of a noise reduction device provided according to an embodiment of the present application. [Figure 4] FIG. 4 is a specific implementation flow diagram of the noise reduction method provided according to an embodiment of the present application. [Figure 5] FIG. 5 is a schematic diagram illustrating a module of a noise reduction device provided according to an embodiment of the present application. [Figure 6] FIG. 6 is a structural schematic diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION OF THE INVENTION

[0028] Specific embodiments of the present application will now be described in detail with reference to the drawings, but it is clear that the described embodiments are only some of the embodiments of the present application, and are not all of the embodiments. Any other embodiments that can be obtained by a person skilled in the art based on the embodiments of the present application without performing any creative work are also included in the scope of protection of the present application.

[0029] FIG. 1 shows a scene where noise interference occurs when riding an elevator.

[0030] The scene shown in Figure 1 includes a guide rail 101, a suspension cable 102, a car 103, a guide shoe 104, and a shaft wall 105. As shown in Figure 1, passengers encounter two types of noise when riding an elevator: airborne noise and structural noise. Here, airborne noise is wind noise generated by the rapid flow of air in the gap between the car 103 and the shaft wall 105 when the car 103 is moving, and the faster the car 103 moves, the greater the wind noise becomes. Structural noise is noise caused by vibrations of elevator components, such as vibration noise caused by the guide shoe 104 sliding on the guide rail 101, vibration noise of the suspension cable 102, and vibration noise of the car 103.

[0031] Furthermore, FIG. 2 is a schematic diagram showing a situation in which noise generated during elevator operation affects residents.

[0032] The scene shown in Fig. 2 includes a shaft 201, an elevator 202, a shaft wall 203, and a residence 204. As shown in Fig. 2, when a passenger gets on the elevator, airborne noise and structural noise generated between the structures shown in Fig. 1 are transmitted to the residence 204 through the shaft wall 203, causing significant noise interference to the resident. Here, in some scenes, the shaft wall 203 may be the wall of the resident's residence 204.

[0033] As mentioned above, elevator noise is usually physically reduced by adding soundproofing panels to the elevator, for example, by temporarily installing soundproofing panels such as flow control covers or sound-absorbing materials in the elevator. However, the effectiveness of physical reduction methods using soundproofing panels in reducing elevator noise is not guaranteed.

[0034] To solve the above problems, an embodiment of the present application provides a noise reduction method, which involves installing multiple noise reduction devices on the inner wall of an elevator car or on a wall shared between the occupant's living space and the elevator shaft wall, and using a software algorithm to reduce the noise generated in the elevator using these noise reduction devices, thereby reducing the noise audible to the ears of elevator passengers. Furthermore, the noise reduction devices may have an outer shape, such as a thin plate, with a small volume and light mass, thereby reducing the load on the elevator operation.

[0035] Specifically, the method collects noise data and elevator operation data during elevator operation, and selects a corresponding noise reduction processing method based on the noise type of the collected noise data. For example, the noise type determined by the method can be airborne noise or structural noise, with different noise reduction processing methods corresponding to different noise types. Next, the collected noise data is subjected to processing such as filtering to obtain target noise data, and then noise reduction processing is performed on the target noise data based on the selected noise reduction processing method to obtain a noise-reduced signal. Furthermore, the method calculates a delay time for each noise reduction device to output its noise reduction signal based on the noise reduction location, such as the location of the passenger's ears or the location of each noise reduction device. Finally, each noise reduction device can output its noise reduction signal after the corresponding delay time has elapsed. For example, a noise reduction device farther from the noise reduction location can output its noise reduction signal first, while a noise reduction device closer to the noise reduction location can output its noise reduction signal after a certain delay time has elapsed. This ensures that the noise reduction signals arrive at the same noise reduction location at the same time, achieving a good noise reduction effect.

[0036] Some embodiments illustrate specific implementations of the noise reduction method of the present application. For example, for target noise data that actually requires noise reduction processing among collected noise data, the center frequency of the target noise data can be calculated, and the corresponding frequency band can be determined based on the center frequency. Next, the corresponding median value can be calculated based on the corresponding frequency band to obtain the centroid frequency of each noise reduction device. Furthermore, the method can calculate the corresponding noise reduction signal of each noise reduction device using the FxLMS (filters-x least mean square) algorithm based on the centroid frequency of each noise reduction device. Here, the noise reduction signal and the noise signal corresponding to the noise data have the same amplitude but opposite phase, so that the noise reduction signal output by each noise reduction device can cancel out the corresponding target noise data, thereby achieving the noise reduction effect.

[0037] In some embodiments, the noise reduction position is a location area where the ears of passengers riding in the elevator are located, for example, a location area 1.0 m to 1.8 m above the elevator car bottom plate. Based on the noise reduction position, the distance between each noise reduction device and the noise reduction position is determined, and a delay time for outputting a noise reduction signal between each noise reduction device is calculated. Specifically, in the present application, the propagation time required for the noise reduction signal output by each noise reduction device to propagate to the noise reduction position can be calculated based on the speed of sound and the noise reduction position. Furthermore, based on the difference between the propagation times, a delay time for outputting the noise reduction signal between each noise reduction device is determined, thereby ensuring that the noise reduction signals output by each noise reduction device can propagate to the noise reduction position simultaneously.

[0038] As can be understood, since the elevator noise data changes continuously over time, the corresponding target noise frequency can be determined by analyzing the elevator noise data in real time, and based on this, the frequency value of the center frequency, the number of center frequencies, and the frequency of the filter can all be set according to the real-time situation, so as to realize directional filtering of the continuously changing noise signal in the elevator noise data.

[0039] As can be seen from the above, based on the above noise reduction method, the present application detects the elevator operation status, then detects the change status of the noise data in real time, and generates a noise reduction signal, thereby realizing noise reduction in real time.

[0040] Next, the noise reduction device provided in the embodiment of the present application will be described. Specifically, Figure 3 is a structural schematic diagram of the noise reduction device provided according to the embodiment of the present application.

[0041] As shown in Figure 3(A) or (B), Figure 3(A) is a schematic front view of the noise reduction device provided herein, and Figure 3(B) is a schematic side view of the noise reduction device. As shown in Figure 3, the device includes a reference microphone array 301, an error microphone array 302, a vibration sensor 303, a diaphragm speaker 304, a calculation unit 305, and a vibration speaker 306. It should be understood that the position and number of each component in the noise reduction device of the present application can be set according to actual needs and are not limited herein. For example, the noise reduction device shown in Figure 3 may have a thin plate-like outer shape.

[0042] Here, the reference microphone array 301 faces the outside of the elevator car and can be used to collect airborne noise during elevator operation.

[0043] The error microphone array 302 faces the inner wall of the elevator car and measures whether the output noise reduction signal corresponding to the air noise matches the predicted output noise signal. Based on the measurement result, it can be used to perform error detection and correction on the noise reduction signal before output, to ensure the output of an accurate noise reduction signal.

[0044] The vibration sensor 303 is used to collect structural noise during elevator operation.

[0045] The diaphragm speaker 304 is used to output a noise reduction signal corresponding to airborne noise.

[0046] The calculation unit 305 is used to calculate a noise reduction signal corresponding to each noise type based on the noise data.

[0047] The vibration speaker 306 is used to output a noise-reducing signal corresponding to the structure noise.

[0048] In some alternative embodiments, the present application may install one or more noise reduction devices for one elevator, and different noise reduction devices may be installed at different locations, such as, but not limited to, the multiple noise reduction devices may be installed on the same car wall of the elevator car, or on different car walls, or on the shaft wall 203 shown in FIG. 2 above.

[0049] In some embodiments, the present application may select one noise reduction device from a plurality of installed noise reduction devices to perform the noise reduction method, and the noise reduction device may be referred to as a main device. As can be understood, the main device may be used to collect noise data, such as the centroid frequency, processed by other noise reduction devices, and calculate the noise-reduced signal output by each noise reduction device and the delay time for outputting the noise-reduced signal according to the noise reduction algorithm and the centroid frequency.

[0050] As can be understood, among the one or more noise reduction devices, one with computing capabilities can be set as the main device or main equipment, or the one or more noise reduction devices can all have computing capabilities and all be the main device or main equipment, and there is no limitation here.

[0051] To further explain the noise reduction method provided in the embodiments of the present application, the specific process of the noise reduction method provided in the embodiments of the present application will now be described in detail based on the related flow diagram.

[0052] Referring to the related description of each structure of the noise reduction device shown in FIG. 3, FIG. 4 is a specific implementation flow diagram of the noise reduction method provided according to the embodiment of the present application.

[0053] As can be understood, in some embodiments of the present application, the execution body of each step of the flow shown in FIG. 4 may be the plurality of noise reduction devices or noise reduction facilities.

[0054] Specifically, the flow shown in FIG. 4 may include the following steps:

[0055] 401: Collect noise data and elevator operation data during elevator operation.

[0056] Here, the noise reduction device may be provided in plural, and may be installed on the elevator car wall or a noise generating position, such as the car wall where the guide shoe is located.

[0057] As can be understood, during the operation of the elevator, each noise reduction device can collect noise data during elevator operation, where the noise data includes the noise data of air noise and the noise data of structural noise. Specifically, a reference microphone can be installed in each noise reduction device to collect the air noise data during elevator operation, and a vibration sensor can be installed to collect the structural noise data during elevator operation. At the same time, the noise reduction device can obtain the predicted elevator operation speed, acceleration, and vibration data generated by each structure of the elevator during operation from the elevator control end.

[0058] 402: Select a corresponding noise reduction processing method based on the noise type of the noise data.

[0059] As described above, airborne noise and structural noise exist during elevator operation, and are collected separately due to different structures in the noise reduction device or equipment. Therefore, the noise types of the collected noise data can be classified based on different noise collection structures. Different noise types correspond to different noise reduction processing methods. For example, when the noise type is airborne noise, it corresponds to a first noise reduction processing method, and when the noise type is structural noise, it corresponds to a second noise reduction processing method. Here, the specific processing processes of the first noise reduction processing method and the second noise reduction processing method will be described in detail below, and will not be described here again.

[0060] 403: Process the noise data based on the selected noise reduction processing method to obtain a noise-reduced signal.

[0061] As can be understood, when the selected noise reduction processing method is the first noise reduction processing method, the corresponding noise type is airborne noise. Typically, once airborne noise is collected, noise reduction processing is performed on the collected airborne noise. That is, the first noise reduction processing method performs noise reduction processing on the collected airborne noise from start to finish. In this case, it is necessary to first perform filtering on the airborne noise data to determine target noise data. Specifically, the filtering process can be, for example, high-pass filtering, band-pass filtering, or low-pass filtering on the noise data. As can be understood, filtering of elevator noise data can be performed to retain a target frequency in the elevator noise data and filter out other frequencies. Alternatively, frequencies around the target frequency can be retained and other frequencies can be filtered out, or other filtering methods can be used. This method can effectively filter out noise data within the decibel range that passengers perceive in the noise signal during elevator operation. Furthermore, a fast Fourier transform is performed on the noise data collected by the reference microphone in each noise reduction device to calculate the maximum value of the corresponding noise value frequencies of the noise data collected by the reference microphone in each noise reduction device, and this frequency is used as the center frequency to determine the corresponding noise band.Furthermore, a median is calculated for each noise band, that is, all noise values ​​are ranked high and low, and the middle one is found to be the median.If the number of noise values ​​in the noise band is odd, the median is the average value of the middle two noise values ​​after all noise values ​​are ranked high and low.The median is also used as the center frequency corresponding to the area where the noise reduction device is located.

[0062] In some embodiments, the present application can use a main device or main equipment to receive the centroid frequencies of other noise reduction devices, and calculate the corresponding noise reduction signals output by each noise reduction device using an FxLMS algorithm, where the noise reduction signals and the air noise signal have the same amplitude but opposite phases, and the FxLMS algorithm is a filtering algorithm used to obtain the corresponding noise reduction signals based on noise data.

[0063] Furthermore, in some embodiments, the present application may select the noise reduction device that is most idle at the time as the main device or main equipment based on the current idle computing power of the multiple noise reduction devices. For example, the present application may select a random noise reduction device or default noise reduction device from the multiple noise reduction devices to determine the noise reduction device that is most idle at the time as the main device.

[0064] In some other embodiments, the present application also provides that an operator may manually set any noise reduction device or equipment as the main device or main equipment, or randomly select one noise reduction device or equipment as the main device or main equipment, and there is no limitation here. Here, data transmission between the main device and other noise reduction devices can be achieved by a communication method such as wireless fidelity (Wi-Fi) or short-range wireless communication (Bluetooth).

[0065] As can be understood, when the selected noise reduction method is the second noise reduction method, the corresponding noise type is structural noise. Typically, for structural noise, the second noise reduction method first needs to determine whether the current structural noise requires noise reduction, i.e., whether the structural noise will have a significant impact on passengers inside the elevator, and then performs noise reduction on the structural noise that actually requires noise reduction. For example, the method can determine whether collected structural noise requires noise reduction in the following manner: First, compare the operation data provided by the elevator manufacturer with the real-time elevator operation data collected by a sensor installed in the noise reduction device, and then average or perform fuzzy processing on the two operation data to obtain an effective low- to mid-band vibration signal. After filtering the effective low- to mid-band vibration signal, an effective value (rms value, RMS) is calculated. Here, the effective value is the square root of the vibration signal and is used to represent the magnitude of the energy in the vibration signal. Specifically, it can be calculated using Equation (1), where k+1 represents the total number of samples in the calculation section.

[0066]

number

[0067] The following formula represents the sum of squares of the amplitude values ​​in the calculation section.

[0068]

number

[0069] In this way, the effective value is calculated using the above formula (1), and a preset threshold is referenced to determine whether the structural noise requires noise reduction processing. If the effective value is lower than the preset threshold, it indicates that the noise value generated by the low-to-mid band vibration is low, and noise reduction processing is not required. If the effective value is higher than the preset threshold, it indicates that the noise value generated by the low-to-mid band vibration is high, and noise reduction processing is required. Here, the effective value is the real-time effective value of the noise data corresponding to the structural noise during elevator operation.

[0070] As can be understood, when the effective value of noise data corresponding to structural noise during elevator operation is higher than a preset threshold and noise reduction processing is required, first, a fast Fourier transform is performed on the low-to-mid band vibration data of each sensor in each noise reduction device to determine the maximum vibration frequency, and this frequency is used as the center frequency to determine the corresponding noise band. Furthermore, a median is calculated for each noise band, i.e., all noise values ​​are ranked high to low, and the middle one is found to be the median. If the number of noise values ​​in the noise band is odd, the median is the average of the middle two noise values ​​after ranking all noise values ​​high to low. The median is also used as the center frequency corresponding to the area where the noise reduction device is located.

[0071] Furthermore, the noise reduction device can select the noise reduction device with the highest degree of idleness as the main device or main equipment based on the current idle calculation power of the multiple noise reduction devices, and the main device or main equipment receives the centroid frequencies of the other noise reduction devices and calculates the noise reduction signals of each noise reduction device using the FxLMS algorithm, where the noise reduction signals and the air noise signal have the same amplitude but opposite phases.

[0072] 404: Calculate a delay time for each noise reduction device to output a noise reduction signal based on the noise reduction position and the position of each noise reduction device.

[0073] As can be understood, when outputting a noise reduction signal, there is a delay time between each noise reduction device, and for example, a noise reduction device far from the noise reduction position outputs a noise reduction signal at a first timing, and a noise reduction device close to the noise reduction position outputs a noise reduction signal at a second timing, thereby ensuring that the noise reduction signals arrive at the same noise reduction position at the same time.

[0074] Specifically, the delay time for outputting the noise reduction signal between each noise reduction device is calculated based on the noise reduction position, such as a position area 1.0 m to 1.8 m above the elevator car bottom plate (i.e., the position area where passengers' ears are located), and the position of each noise reduction device. Specifically, the propagation time required for the noise reduction signal output by each noise reduction device to propagate to the noise reduction position is calculated, and the delay time for outputting the noise reduction signal between each noise reduction device is determined based on the difference between the propagation times, thereby ensuring that the noise reduction signals output by each noise reduction device can be propagated to the noise reduction position simultaneously.

[0075] 405: Each noise reduction device outputs a noise reduction signal according to the corresponding delay time of each noise reduction device.

[0076] As can be understood, the corresponding noise reduction device outputs a noise reduction signal in accordance with the delay time, for example, at a first timing, a diaphragm speaker in a noise reduction device far from the noise reduction position outputs a noise reduction signal corresponding to air noise, and a vibration speaker outputs a noise reduction signal corresponding to vibration noise. After the delay time has elapsed, i.e., at a second timing, a diaphragm speaker in a noise reduction device close to the noise reduction position outputs a noise reduction signal corresponding to air noise, and a vibration speaker outputs a noise reduction signal corresponding to vibration noise.

[0077] As can be understood, when the corresponding noise type of the noise reduction signal is air noise, each noise reduction device installs an error microphone to measure whether the output noise reduction signal corresponding to the air noise is consistent with the predicted output noise signal, and performs error detection and correction on the noise reduction signal based on the measurement result, to ensure the output of an accurate noise reduction signal.

[0078] As can be understood, referring to the related description of the noise reduction method in FIG. 4 above, FIG. 5 is a module schematic diagram of a noise reduction device provided according to an embodiment of the present application.

[0079] As shown in FIG. 5, the noise reduction device includes a data collection module 501, a data processing module 502, an intelligent selection module 503, and a signal output module 504.

[0080] Here, the data collection module 501 is used to collect noise data and elevator operation data during elevator operation. For the specific collection process, please refer to the relevant description in step 401 above, and the description thereof will be omitted here.

[0081] The data processing module 502 is used to select a corresponding noise reduction processing method based on the noise type of the noise data, and perform noise reduction processing on the noise data based on the noise reduction processing method to obtain a noise-reduced signal.

[0082] The data processing module 502 is further used to calculate the output delay time of the noise reduction signal based on the noise reduction position in the elevator and the position of the noise reduction device.

[0083] The intelligent selection module 503 is used to determine the noise reduction device with the highest idle computing power among the plurality of noise reduction devices as the main device, where the main device collects a plurality of centroid frequencies obtained by processing the noise data of each noise reduction device, combines the plurality of centroid frequencies using a noise reduction algorithm to calculate a corresponding noise reduction signal, and calculates the output delay time of the noise reduction signal according to the noise reduction position in the elevator and the position of the noise reduction device.

[0084] The signal output module 504 is used to output the noise-reduced signal based on the delay time.

[0085] The electronic device 100 further provided in the embodiment of the present application is used to implement the noise reduction method shown in the above Fig. 4. Specifically, Fig. 6 is a structural schematic diagram of the electronic device provided according to the embodiment of the present application.

[0086] As shown in FIG. 6, the electronic device 100 includes one or more processors 101, system internal memory 102, non-volatile memory (NVM) 103, input / output (I / O) facilities 104, communication interface 105, and system control logic 106 for connecting the processor 101, the system internal memory 102, the non-volatile memory 103, the communication interface 105, and the input / output (I / O) facilities 104.

[0087] Here, the processor 101 may include one or more processing units, such as a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a micro-programmed control unit (MCU), an artificial intelligence (AI) processor or field programmable gate array (FPGA), a neural-network processing unit (NPU), or other data processing unit, or the processing circuit may include one or more single-core or multi-core processors.

[0088] The system internal memory 102 may be a volatile memory such as random-access memory (RAM), double data rate synchronous dynamic random access memory (DDR SDRAM), etc. The system internal memory may be used to temporarily store data and / or commands. For example, in some embodiments, the system internal memory 102 may be used to store parsed control commands.

[0089] Non-volatile memory 103 may comprise one or more tangible, non-transitory, computer-readable media for storing data and / or commands. In some embodiments, non-volatile memory 103 may include any suitable non-volatile memory, such as flash memory, and / or any suitable non-volatile storage facility, such as a hard disk drive (HDD), a compact disc (CD), a digital versatile disc (DVD), a solid-state drive (SSD), etc. In some embodiments, non-volatile memory 103 may also be a removable storage medium, such as a secure digital (SD) memory card.

[0090] In particular, the system internal memory 102 and the non-volatile memory 103 may contain temporary and permanent copies, respectively, of commands 107. The commands 107, when executed by at least one of the processors 101, may include causing the electronic device 100 to implement the noise reduction methods provided in the embodiments of the present application.

[0091] Communication interface 105 may include a transceiver to provide electronic device 100 with a wired or wireless communication interface for communicating with any other suitable equipment over one or more networks. In some embodiments, communication interface 105 may be integrated into other elements of electronic device 100, for example, communication interface 105 may be integrated into processor 101. In some embodiments, electronic device 100 may communicate with other equipment via communication interface 105.

[0092] The input / output (I / O) facility 104 may include input facilities such as a keyboard, a mouse, etc., and output facilities such as a display, and a user may interact with the electronic device 100 through the input / output (I / O) facility 104.

[0093] System control logic 106 may include any suitable interface controllers to provide any suitable interfaces to other modules of electronic device 100. For example, in some embodiments, system control logic 106 may include one or more memory controllers to provide interfaces connected to system internal memory 102 and non-volatile memory 103.

[0094] In some embodiments, at least one of the processors 101 may be packaged together with logic used for one or more controllers in the system control logic 106 to form a system in package (SiP). In other embodiments, at least one of the processors 101 may be further integrated on the same chip as logic used for one or more controllers in the system control logic 106 to form a system-on-chip (SoC).

[0095] 6 is merely an example, and in other embodiments, the electronic device 100 may include more or fewer components than those shown, or a combination of some components, or a division of some components, or various arrangements of components. The components shown may be implemented in hardware, software, or a combination of software and hardware, and are not limited thereto.

[0096] Further embodiments of the present application provide chips that include, for example, noise reduction devices.

[0097] The embodiments of the present application further provide a computer program product for implementing the noise reduction method provided in each of the above embodiments.

[0098] Each embodiment of the mechanism disclosed herein may be implemented in hardware, software, firmware, or a combination of these implementation methods. The embodiments of the present application may be implemented by a computer module or module code executed on a programmable system, the programmable system including at least one processor, a storage system (including volatile and non-volatile memory and / or storage elements), at least one input facility, and at least one output facility.

[0099] The modular code may be applied to input commands to perform the functions described herein and generate output information that may be applied to one or more output facilities in known fashion. For purposes of this application, a processing system includes any system having a processor, such as, for example, a digital signal processor (DSP), a microcontroller, an application specific integrated circuit (ASIC), or a microprocessor.

[0100] The modular code may be implemented using a high-level modular or object-oriented programming language to communicate with a processing system. If desired, the modular code may also be implemented using assembly or machine language. Indeed, the mechanisms described herein are not limited in scope to any particular programming language. In any case, the language may be a compiled or interpreted language.

[0101] In some cases, the disclosed embodiments may be implemented in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented by being embodied by or stored in instructions on one or more transient or non-transitory machine-readable (e.g., computer-readable) storage media, which may be read and executed by one or more processors. For example, the instructions may be distributed over a network or other computer-readable media. Thus, a machine-readable medium can include any mechanism for storing or transmitting information in a machine- (e.g., computer-) readable form, including, but not limited to, floppy disks, compact disks, optical disks, CD-ROMs, magneto-optical disks, read-only memory (ROM), random access memory (RAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic or optical cards, flash memory, or tangible machine-readable memory for transmitting information using the Internet in electrical, optical, acoustic, or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.). Thus, a machine-readable medium includes any type of machine-readable medium suitable for storing or transmitting electronic commands or information in a machine- (e.g., computer-) readable form.

[0102] The figures may show certain structural or method features in a particular arrangement and / or order. However, it should be understood that such a particular arrangement and / or order may not be required. Rather, in some embodiments, these features may be arranged differently than the manner and / or order depicted in the illustrative figures. Furthermore, the inclusion of structural or method features in a particular figure does not imply that such features are required in all embodiments, and that some embodiments may not include such features or may be combined with other features. References in the specification to "one embodiment" or "an example" mean that the particular feature, structure, or characteristic described in connection with the example is included in at least one exemplary embodiment or technique disclosed based on the example in this application. Appearances of the phrase "in one example" in various places in the specification do not necessarily all refer to the same example.

[0103] The disclosure of the embodiments of the present application further relates to an operating apparatus for carrying out the operations described herein. The apparatus may be specially constructed for the required purposes, or may comprise a general-purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored on a computer-readable medium, such as, but not limited to, a floppy disk, a compact disk, a CD-ROM, a magneto-optical disk, a read-only memory (ROM), a random-access memory (RAM), an EPROM, an EEPROM, a magnetic or optical card, an application-specific integrated circuit (ASIC), or any type of disk suitable for storing electronic commands, each of which may be coupled to the computer's system bus. Additionally, the computers presented herein may have a single processor or may use a multi-processor architecture for increased computing power.

[0104] It should be further explained that in the examples of the present application, the numbering of steps in the methods and flows is for convenience of reference and does not limit the order of the steps. If there is an order between steps, the letter explanation shall govern.

[0105] Furthermore, the language used herein has been selected primarily for ease of reading and instructional purposes, and may not be selected to delineate or limit the disclosed subject matter. Accordingly, the disclosure of the embodiments herein is intended to be illustrative, and not limiting, of the scope of the concepts discussed herein.

Claims

1. A noise reduction method applied to a noise reduction device, comprising: Collecting noise data and elevator operation data during elevator operation; selecting a corresponding noise reduction processing method based on a noise type of the noise data; performing noise reduction processing on the noise data based on the noise reduction processing method to obtain a noise-reduced signal; Calculating an output delay time of the noise reduction signal based on a noise reduction position in the elevator and a position of the noise reduction device; outputting the noise-reduced signal based on the delay time; The method, comprising:

2. The noise types include air noise data and structure noise data, and the noise reduction device includes a first noise collecting unit and a second noise collecting unit; the first noise collecting unit is used to collect air noise data during elevator operation; The method of claim 1 , wherein the second noise collecting unit is used to collect structural noise data during elevator operation.

3. 2. The method according to claim 1, wherein the elevator operation data includes at least one of a preset elevator operation speed, a preset acceleration, and preset vibration data generated during operation of each structure of the elevator.

4. Selecting a corresponding noise reduction processing method based on the noise type of the noise data includes: When the noise type of the noise data is the air noise data, the selected noise reduction processing method is a first noise reduction processing method used to perform noise reduction processing on the air noise data; When the noise type of the noise data is the structural noise data, the selected noise reduction processing method is a second noise reduction processing method used to perform noise reduction processing on the structural noise data when the structural noise data satisfies a noise reduction condition, and not to perform noise reduction processing on the structural noise data when the structural noise data does not satisfy the noise reduction condition; 3. The method of claim 2, comprising:

5. 5. The method according to claim 4, wherein the noise reduction condition includes that the effective value of the structural noise data is equal to or greater than a preset threshold value.

6. The noise-reduced signal includes a first-class noise-reduced signal corresponding to air noise data; and To obtain a noise-reduced signal by performing noise reduction processing on the noise data based on the noise reduction processing method, filtering air noise data in the noise data based on the first noise reduction processing method to obtain first target noise data; performing a fast Fourier transform on the first target noise data to calculate a center frequency of the first target noise data, and determining a first frequency band of the first target noise data based on the center frequency; calculating a median value of the first frequency band based on the first frequency band to obtain a first centroid frequency; 5. The method of claim 4, further comprising: combining the first centroid frequencies using a noise reduction algorithm to obtain the first class noise reduced signal.

7. To obtain a noise-reduced signal by performing noise reduction processing on the noise data based on the noise reduction processing method, Based on the second noise reduction processing method, average calculation or fuzzy processing is performed on the elevator operation data and the structural noise data in the noise data to obtain effective structural noise data; filtering the valid structural noise data to obtain second target noise data; Calculating an effective value of the second target noise data; and processing the second target noise based on the significance of the second target noise data.

8. The noise-reduced signal includes a second-class noise-reduced signal corresponding to structural noise data; and Processing the second target noise based on the validity value of the second target noise data includes: determining, based on an effective value of the second target noise data, that the second target noise data satisfies the noise reduction condition; performing a fast Fourier transform on the second target noise data to calculate a center frequency of the second target noise data, and determining a second frequency band of the second target noise data based on the center frequency; calculating a second median value for the second frequency band based on the second frequency band to obtain a second centroid frequency; 8. The method of claim 7, further comprising: combining the second centroid frequencies using a noise reduction algorithm to obtain the second class noise reduced signal.

9. Calculating a delay time based on the noise reduction position and the position of the noise reduction device includes: When the noise reduction device is one of a plurality of noise reduction devices, determining a distance between the noise reduction position and the noise reduction device, and calculating a delay time at which the noise reduction device outputs the noise reduction signal; 2. The method according to claim 1, wherein the delay time of a noise reduction device farther from the noise reduction position among the plurality of noise reduction devices is shorter than the delay time of a noise reduction device closer to the noise reduction position.

10. the noise reduction device comprises a first noise reduction signal output unit and a second noise reduction signal output unit; The first noise reduction signal output unit in the noise reduction device is used to output a first type noise reduction signal corresponding to the air noise data; The method according to claim 1 , wherein the second noise-reduced signal output unit of the noise reduction device is used to output a second-class noise-reduced signal corresponding to structure noise data.

11. The method of claim 2 , wherein the first noise collecting unit comprises at least one reference microphone and the second noise collecting unit comprises at least one vibration sensor.

12. The method of claim 10 , wherein the first noise-reducing signal output unit comprises at least one diaphragm speaker, and the second noise-reducing signal output unit comprises at least one vibration speaker.

13. 8. The method according to claim 6 or 7, wherein the filtering process comprises at least one of high-pass filtering, band-pass filtering, and low-pass filtering.

14. 7. The method of claim 6, wherein the noise reduction algorithm is an FxLMS algorithm.

15. A noise reduction device comprising: a data collection module, a data processing module, and a signal output module; The data collection module is used to collect noise data and elevator operation data during elevator operation; The data processing module is used for selecting a corresponding noise reduction processing method according to a noise type of the noise data, and performing noise reduction processing on the noise data according to the noise reduction processing method to obtain a noise-reduced signal; The data processing module is further used for calculating an output delay time of the noise reduction signal according to a noise reduction position in the elevator and a position of the noise reduction device; The device, wherein the signal output module is used to output the noise-reduced signal according to the delay time.

16. the noise reduction device is one of a plurality of noise reduction devices mounted to the elevator; 16. The apparatus of claim 15, wherein the noise reduction device is any one of the plurality of noise reduction devices, or the noise reduction device is the one of the plurality of noise reduction devices that has the greatest degree of idle computing power.

17. The apparatus further comprises an intelligent selection module; 16. The apparatus of claim 15, wherein the intelligent selection module is used to obtain a degree of idle computing power of each noise reduction device in a plurality of noise reduction devices, and determine that the noise reduction device has the highest degree of idle computing power among the plurality of noise reduction devices.

18. Calculating an output delay time of the noise reduction signal based on the noise reduction position in the elevator and the position of the noise reduction device includes: The noise reduction device collects each centroid frequency obtained by processing noise data of each of the plurality of noise reduction devices; combining the centroid frequencies using a noise reduction algorithm to calculate a noise reduction signal corresponding to each of the plurality of noise reduction devices; and 18. The apparatus according to claim 17, further comprising: calculating a delay time of the noise-reduced signal output by each noise reduction device in the plurality of noise reduction devices based on the noise reduction position and the position of each noise reduction device in the plurality of noise reduction devices.

19. The noise reduction device according to claim 15, wherein the noise reduction device has a thin plate-like outer shape.

20. 16. The apparatus of claim 15, wherein the location of the noise reduction device includes at least one of an interior wall surface of the elevator car and an exterior wall of the elevator shaft.

21. 10. An electronic device comprising one or more processors, one or more memories, and one or more programs stored in the one or more memories, wherein the one or more programs, when executed by the one or more processors, cause the electronic device to perform the noise reduction method described in claim 1.

22. 10. A computer readable medium having stored thereon commands that, when executed on a computer, cause the computer to perform the noise reduction method of claim 1.

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