WO2020218905A1 - Dispositif de réduction de bruit d'un animal de compagnie, et équipement de collier pour la réduction du bruit d'un animal de compagnie l'utilisant - Google Patents

Dispositif de réduction de bruit d'un animal de compagnie, et équipement de collier pour la réduction du bruit d'un animal de compagnie l'utilisant Download PDF

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Publication number
WO2020218905A1
WO2020218905A1 PCT/KR2020/005515 KR2020005515W WO2020218905A1 WO 2020218905 A1 WO2020218905 A1 WO 2020218905A1 KR 2020005515 W KR2020005515 W KR 2020005515W WO 2020218905 A1 WO2020218905 A1 WO 2020218905A1
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WIPO (PCT)
Prior art keywords
noise
source
animal
noise reduction
unit
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PCT/KR2020/005515
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English (en)
Korean (ko)
Inventor
유용길
김연섭
Original Assignee
(주)번영
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from KR1020190048406A external-priority patent/KR102194796B1/ko
Priority claimed from KR1020190048387A external-priority patent/KR102162588B1/ko
Application filed by (주)번영 filed Critical (주)번영
Publication of WO2020218905A1 publication Critical patent/WO2020218905A1/fr

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    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K15/00—Devices for taming animals, e.g. nose-rings or hobbles; Devices for overturning animals in general; Training or exercising equipment; Covering boxes
    • A01K15/02—Training or exercising equipment, e.g. mazes or labyrinths for animals ; Electric shock devices ; Toys specially adapted for animals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R3/00—Circuits for transducers, loudspeakers or microphones

Definitions

  • the present invention relates to an animal noise reduction apparatus, and more particularly, to an animal noise reduction apparatus for actively canceling the noise of an animal, and a collar mechanism for reducing pet noise using the same.
  • An object of the present invention for solving the above problems is to effectively reduce noise generated by pets without an inhumane method or harmful problem.
  • the configuration of the present invention to achieve the above object is a sensing unit that detects an input source including a noise source, an analysis unit that analyzes the frequency characteristics of the input source, and extracts a noise source from the input source based on the frequency characteristics. It characterized in that it comprises a noise extraction unit, a generator for generating an anti-noise source canceling the noise source, and an output unit for outputting the anti-noise source.
  • the noise extracting unit is characterized in that it extracts an input source included in a preset frequency characteristic range as a noise source.
  • the frequency characteristic is characterized by including at least an amplitude and a frequency.
  • it further includes an auditory correction circuit for calculating a noise level dBA obtained by adding a weight to the input source, and the noise extraction unit extracts an input source included in a preset noise level dBA range as a noise source.
  • the preset noise level (dBA) is characterized in that 60 dBA or more and 90 dBA or less.
  • it characterized in that it further comprises a setting unit for setting the frequency characteristic range or the noise level (dBA).
  • the sensing unit is characterized in that it includes at least one of a microphone and a vibration sensor.
  • the generator is characterized in that it generates an anti-noise source using a Filtered-x LMS (Least Mean Square) algorithm.
  • the analysis unit is characterized in that the frequency characteristics are analyzed using a Fast Fourier Transform (FFT) algorithm.
  • FFT Fast Fourier Transform
  • the noise source is characterized in that it is generated by barking or howling of an animal.
  • the pet noise reduction collar device is a harness attached to a pet, a sensor disposed on the harness, and connected to a sensor detecting an input source including a noise source, and connected to the sensor, corresponding to a noise source.
  • a microprocessor including a generator for generating an attenuated wave, and a speaker connected to the microprocessor for canceling the noise source by outputting an anti-noise source based on the attenuated wave.
  • An adaptive filter that generates attenuated wave, a low-pass filter and a power amplifier that processes the attenuation wave and provides it to the speaker, a low-pass filter, a power amplifier, and a first error component due to the speaker, and an anti-noise source output from the speaker
  • the first filter that removes the second error component that is input to the signal, an error microphone that detects the residual noise signal generated by the interference between the noise source and the anti-noise source, and the residual noise signal are filtered to improve the dimensions of the residual noise signal and the attenuation wave. It characterized in that it comprises a second filter to match, and a third filter for compensating for a time delay caused by the second filter by filtering the noise source.
  • the error microphone is disposed in a space separated from the sensor, the microprocessor, and the speaker, and further comprises a wireless communication device for wirelessly providing the residual noise signal sensed by the error microphone to the second filter.
  • the effect of the present invention according to the configuration as described above can effectively reduce animal noise by effectively extracting and actively canceling noise sources generated by barking and howling of animals.
  • the noise level Dba may be calculated by adding a weight to the frequency characteristic of the input source I, and the noise source N may be extracted based on this. Accordingly, it is possible to selectively extract and offset noises that cause stress and pain by reflecting a person's hearing sensation that varies depending on the frequency.
  • the setting unit sets the frequency characteristic range (value) and the noise level (dBA) range (value) of the noise source (N) to be canceled in advance, and adjusts the noise source (N) to be canceled according to the animal type and living situation. I can.
  • the generation unit 400 may increase a cancellation effect of a noise source by removing error signals according to a physical system and an electric system.
  • FIG. 1 is a block diagram schematically showing the configuration of an animal noise reduction apparatus according to an embodiment of the present invention.
  • FIG. 2 is a view showing a waveform for explaining the operation of the animal noise reduction device shown in FIG.
  • FIG. 3 is a block diagram schematically showing the configuration of another embodiment of the animal noise reduction apparatus shown in FIG.
  • FIG. 4 is a graph illustrating a hearing correction circuit unit according to an exemplary embodiment of the present invention.
  • FIG. 5 is a flow chart for explaining the operation of the animal noise reduction apparatus shown in FIG.
  • FIG. 6 is a flow chart for explaining the first embodiment of the noise extracting unit shown in FIG. 1.
  • FIG. 7 is a flow chart illustrating a second embodiment of the noise extracting unit shown in FIG. 6.
  • FIG. 8 is a flow chart for explaining a third embodiment of the noise extracting unit shown in FIG. 6.
  • FIG. 9 is a view schematically showing a pet noise reduction collar mechanism according to an embodiment of the present invention.
  • FIG. 10 is a circuit diagram schematically showing the configuration of the generation unit shown in FIG. 9.
  • the configuration of the present invention to achieve the above object is a sensing unit that detects an input source including a noise source, an analysis unit that analyzes the frequency characteristics of the input source, and extracts a noise source from the input source based on the frequency characteristics. It characterized in that it comprises a noise extraction unit, a generator for generating an anti-noise source canceling the noise source, and an output unit for outputting the anti-noise source.
  • FIG. 1 is a block diagram schematically showing the configuration of an animal noise reduction apparatus 10 according to an embodiment of the present invention
  • FIG. 2 is for explaining the operation of the animal noise reduction apparatus 10 shown in FIG. It is a diagram showing the waveform.
  • the animal noise reduction apparatus 10 includes a sensing unit 100, an analysis unit 200, and a noise extraction unit 300 in order to actively reduce animal noise. ), a generation unit 400 and an output unit 500.
  • the sensing unit 100 detects the input source I
  • the analysis unit 200 analyzes the frequency characteristics of the input source I.
  • the noise extraction unit 300 extracts the noise source N from the input source I based on the frequency characteristic.
  • the generation unit 400 generates an anti-noise source AN having a phase difference of 180 degrees based on the noise source N.
  • the output unit 500 outputs an anti-noise source (AN). Accordingly, the noise source N may be canceled by the anti-noise source AN to reduce animal noise.
  • the sensing unit 100 detects an input source I generated by barking, howling, gasping, and growling of an animal.
  • the input source (I) may be a sound source generated by the animal itself or generated around the animal. That is, the input source I may include sound sources I1, I2, I3, ..., IN of various frequency components.
  • the noise source N refers to a sound source of a frequency component that is an object of cancellation (reduction) recognized as noise by humans by the barking of an animal among the input sources I.
  • the noise source (N) may be caused by barking or howling of animals. That is, the noise source N may have a frequency characteristic corresponding to the barking of an animal. Also, the noise source N may have a frequency characteristic corresponding to howling. Accordingly, the noise source N may be set in advance to have frequency characteristics corresponding to barking and howling of animals. For example, when an animal barks, the noise source N may be set to have at least a specific range of frequencies and a specific range of amplitudes. Of course, the noise source N may be set to have a frequency of a specific value and an amplitude of a specific value.
  • the noise source (N) may be set in advance to have a number of frequency characteristics (range) according to the type of animal, size (small, medium, large), gender, and sound occurrence situation (bark, howling, etc.) .
  • the animal noise reduction apparatus 10 of the present invention may further include a storage unit (not shown) for storing a plurality of preset frequency characteristic data.
  • the frequency characteristic includes at least amplitude and frequency.
  • the frequency characteristic may include a phase, a starting point and an ending point of the noise, and the like.
  • the sensing unit 100 may include at least one of the microphone 110 and the vibration sensor 130.
  • the microphone 110 converts sound waves of sound into electrical signals.
  • the microphone 110 largely includes a dynamic microphone and a condenser microphone.
  • the vibration sensor 130 may detect vibration due to movement of the vocal cords. Accordingly, the vibration sensor 130 may detect the input source I at least prior to detection of the microphone 110 due to barking of an animal.
  • the sensing unit 100 may be disposed around the neck of the animal.
  • the vibration sensor 130 may detect the input source I at least prior to detection of the microphone 110 due to barking of an animal. In addition, the vibration sensor 130 can confirm that the pet 21 directly generates sound (barking, etc.). Therefore, when the vibration sensor 130 and the microphone 110 are disposed together, the noise source N, which is a target of offset due to the barking of the pet 21, can be more accurately extracted. That is, accuracy may be improved by utilizing the input sources I of the vibration sensor 130 and the microphone 110, respectively.
  • the analysis unit 200 analyzes the frequency characteristics of the input source I.
  • the input source I includes various frequency components due to noise generated in the surroundings, as well as barking and howling of animals. Among them, in order to extract the noise source N, which is a frequency component recognized as noise by humans, the analysis unit 200 analyzes the frequency characteristics of the input source I.
  • the analysis unit 200 may use a Fast Fourier transform (FFT) algorithm.
  • FFT Fast Fourier transform
  • the Fast Fourier transform (FFT) algorithm is an algorithm that calculates an approximation of a function. When calculating the discrete Fourier transform using an approximation formula based on the Fourier transform, the number of operations can be reduced, enabling fast signal processing.
  • the noise extracting unit 300 extracts the noise source N from the input source I based on the frequency characteristic.
  • the noise extracting unit 300 may extract an input source I included in a preset frequency characteristic range as a noise source N.
  • the input source (I) may have a plurality of frequency components, and a frequency component included in a preset frequency characteristic range (a specific range frequency, a specific range amplitude, etc.) among the plurality of frequency components is used as the noise source (N). Is extracted.
  • a specific value of the frequency characteristic may be used instead of the frequency characteristic range.
  • the generation unit 400 generates an anti-noise source (AN) that cancels the noise source (N).
  • the generation unit 400 may use a Filtered-x LMS (Least Mean Square) algorithm.
  • the Filtered-x Least Mean Square (LMS) algorithm may remove error components generated by the low pass filter, the power amplifier, and the output unit 500 included in the generation unit 400.
  • the output unit 500 outputs the anti-noise source AN generated by the generation unit 400. Thereby, the noise source N may be canceled by the anti-noise source AN.
  • the input source I includes various frequency components I1, I2, I3, ..., IN. Therefore, a frequency component generated by an animal and recognized as a noise by a human, that is, a noise source (N) must be extracted.
  • the noise extracting unit 300 extracts a noise source N, which is a frequency component under a specific condition, from among various frequency components I1, I2, I3, ..., IN.
  • the generation unit 400 generates an anti-noise source (AN) corresponding to the noise source (N) in consideration of the error component. That is, the anti-noise source (AN) has an inverted waveform of the noise source (N).
  • FIG. 3 is a block diagram schematically showing the configuration of another embodiment of the animal noise reduction apparatus 10 shown in FIG. 1, and FIG. 4 is a diagram for explaining a hearing correction circuit unit 600 according to an embodiment of the present invention. It is a graph.
  • the animal noise reduction apparatus 10 may further include a hearing correction circuit unit 600.
  • the auditory correction circuit part 600 calculates a noise level dBA by adding a weight to the input source I analyzed by the analysis part 200.
  • the noise level can be classified into A correction (dBA, blue), B correction (dBB, yellow) and C correction (dBC, red) according to the weight. That is, the noise level dBA here is according to the A correction.
  • the sensing unit 100 mechanically measures the sound pressure. That is, the sensing unit 100 may measure sound having a specific frequency and amplitude. The loudness of the sound increases as the frequency increases. However, humans are more sensitive at a frequency of 1000 Hz, and become dull as the frequency decreases. In other words, the sensitivity that a person can hear varies depending on the frequency. Reflecting this, a noise level dBA obtained by adding a weight to the value measured by the sensing unit 100 for each frequency is calculated. Therefore, by using the noise level dBA, it is possible to extract the noise source N, which is substantially felt to a person as noise.
  • the noise extracting unit 300 may extract the noise source N using the noise level dBA as another embodiment. That is, the noise extracting unit 300 may extract the input source I included in the preset noise level dBA range as the noise source N.
  • the setting of the noise level (dBA) refer to the description of the above frequency characteristic setting.
  • the noise level (dBA) is measured to be 60 dBA or more and 90 dBA or less. Therefore, in order to extract the noise source (N), the noise level (dBA) may be previously set to 60 dBA or more and 90 dBA or less.
  • the gastric noise level (dBA) is the level of discomfort and pain in a person.
  • the apparatus 10 for reducing animal noise may further include a setting unit 700.
  • the setting unit 700 may set at least one of a frequency characteristic range (value) and a noise level dBA.
  • the setting unit 700 may set one or more frequency characteristic ranges (values) in advance.
  • the setting unit 700 may set one or more noise levels dBA in advance.
  • the noise extraction unit 300 may extract the noise source N according to the setting of the setting unit 700.
  • FIG. 5 is a flow chart for explaining the operation of the animal noise reduction apparatus 10 shown in FIG. 1
  • FIG. 6 is a flow chart for explaining the first embodiment of the noise extracting unit 300 shown in FIG. 1 to be.
  • the sensing unit 100 detects an input source I due to barking or howling of an animal (S110).
  • the analysis unit 200 analyzes the frequency characteristics of the input source I (S120).
  • the noise extraction unit 300 extracts a frequency component included in a preset frequency characteristic range (value) from among a plurality of frequency components included in the input source I as the noise source N (S130). For example, the noise extracting unit 300 extracts frequency components included in the preset frequency characteristic range (value) as the noise source N (S220 and S230). Frequency components that are not included are determined as everyday noise and are not extracted.
  • the generator 400 generates an anti-noise source N having an inverted waveform corresponding to the noise source N waveform (S140).
  • the output unit 500 outputs the anti-noise source N to cancel the noise source N (S150).
  • FIG. 7 is a flowchart illustrating a second embodiment of the noise extraction unit 300 shown in FIG. 6.
  • the auditory correction circuit unit 600 calculates the noise level dBA (S320).
  • the noise extracting unit 300 determines whether the calculated noise level Dba is included in the preset noise level dBA range (value) (S330).
  • the noise extracting unit 300 extracts frequency components of the input source I included in the preset noise level dBA range (value) as the noise source N (S340).
  • the auditory correction circuit unit 600 may receive frequency characteristics from the analysis unit 200. However, the hearing correction circuit unit 600 may receive frequency characteristics from the analysis unit 200 or the generation unit 400.
  • the hearing correction circuit part 600 calculates a noise level dBA by adding a weight to the frequency characteristic.
  • the noise extraction unit 300 compares the supplied (input) received noise level dBA with a preset noise level dBA range (value) to determine. In this case, the input sources I included in the preset noise level dBA range (value) are extracted as the noise source N. Input sources (I) not included in the preset frequency characteristic range (value) are not extracted as noise sources (N).
  • FIG. 8 is a flow chart illustrating a third embodiment of the noise extracting unit 300 shown in FIG. 6.
  • the auditory correction circuit unit 600 adds a weight to the frequency characteristic to determine the noise level dBA. It is calculated (S430).
  • the noise extracting unit 300 determines whether the input frequency characteristic is included in a preset frequency characteristic range (value) (S420). In addition, the noise extraction unit 300 determines whether the calculated noise level dBA is included in the preset noise level dBA range (value) (S440).
  • the noise extracting unit 300 extracts a frequency component included in a preset frequency characteristic range (value) and a preset noise level (dBA) range (value) among the frequency components of the input source I as the noise source N. (S450).
  • the noise source N which is generated by the barking of an animal, among the input sources I, and is recognized as noise (stress) by humans, can be effectively and accurately extracted.
  • FIG. 9 is a view schematically showing a pet noise reduction collar device 20 according to an embodiment of the present invention.
  • the pet noise reduction collar 20 is a harness 1000 attached to the pet 21 in order to actively reduce the noise of the pet 21 , A sensor 2000, a microprocessor 3000, and a speaker 4000.
  • the harness 1000 may be disposed to surround the neck of the pet 21.
  • the sensor 2000 is disposed on the harness 1000.
  • the sensor 2000 detects an input source I including a noise source N.
  • the microprocessor 3000 is connected to the sensor 2000 and includes a generator 400 that generates an attenuated wave corresponding to the noise source N.
  • the speaker 4000 is connected to the microprocessor 3000 and cancels the noise source N by outputting the anti-noise source AN based on the attenuated wave.
  • the harness 1000 may have a belt shape extending to a predetermined length, for example.
  • the harness 1000 may be disposed to surround the neck of the pet 21. That is, the harness 1000 may have a necklace shape.
  • the harness 1000 may be disposed to surround the upper body including the chest of the pet 21.
  • the sensor 2000 may include at least one of the microphone 110 and the vibration sensor 130.
  • the microphone 110 converts sound waves of sound into electrical signals.
  • the microphone 110 largely includes a dynamic microphone and a condenser microphone.
  • the vibration sensor 130 may detect vibration due to movement of the vocal cords.
  • FIG. 10 is a circuit diagram schematically showing the configuration of the generator 400 shown in FIG. 9.
  • the generator 400 generates an adaptive filter 411, a low pass filter 412, a power amplifier 413, and a first filter 414 to generate an attenuated wave Y.
  • An error microphone 415, a second filter 416, and a third filter 417 may be included.
  • the adaptive filter 411 generates an attenuated wave Y based on the noise source N. To this end, the adaptive filter 411 has a specific transfer function (W).
  • the low pass filter 412 and the power amplifier 413 process the attenuated wave Y and provide it to the speaker 4000.
  • the low pass filter 412 removes a high frequency component included in the attenuated wave Y, which is an output signal of the adaptive filter 411.
  • the power amplifier 413 amplifies the attenuated wave Y.
  • the error microphone 415 detects the residual noise signal En generated by interference between the noise source N and the anti-noise source AN. The error microphone 415 will be described in more detail later.
  • the low pass filter 412 and the power amplifier 413 generate first error components A and L in the attenuated wave Y.
  • the anti-noise source AN output from the speaker 4000 may flow into the sensor 2000 and generate a second error component F.
  • the first error components (A, L) and the second error component (F) are transfer functions calculated through modeling. Specifically, through modeling, the low pass filter 412 may have a specific transfer function “L”, and the power amplifier 413 may have a specific transfer function “A”.
  • the acoustic feedback input from the speaker 4000 to the sensor 2000 may be modeled with a specific transfer function “F”. Meanwhile, “P” in FIG.
  • P 2 is a transfer function modeling a physical state in which the noise source N generated from the sound source reaches the speaker 4000.
  • P since the speaker 4000 is disposed on the neck of the pet, “P” may be ignored.
  • the present invention is not limited thereto, and “P” may have a specific transfer function through modeling.
  • the first filter 414 removes the first error components (A, L) and the second error component (F). Specifically, the first filter 414 includes the first error components (A, L) and the second error components (F) in order to remove the first error components (A, L) and the second error component (F).
  • the value calculated by convolutional integration can be used as a modeled transfer function. That is, the first filter 414 may have a modeled transfer function (B) of L*A*S*F (“*” is a convolutional integral symbol).
  • the second filter 416 filters the residual noise signal En in order to match the dimensions of the residual noise signal En and the attenuated wave Y.
  • the second filter 416 includes a first error component (A, L) and a second error component (F), and a third error component (E) according to acoustic feedback from the speaker 4000 to the error microphone 415
  • the third filter 417 filters the noise source N to compensate for a time delay caused by the second filter 416.
  • the third filter 316 includes a first error component (A, L) and a second error component (F), and a third error component (E) according to acoustic feedback from the speaker 4000 to the error microphone 415 A model (L*A*S*E) considering these can be used.
  • the speaker 4000 receives an attenuated wave Y, which is an output signal of the adaptive filter 411, and outputs an anti-noise source AN.
  • the noise source N is canceled and reduced by the anti-noise source AN.
  • the pet noise reduction collar device 20 of the present invention may further include a wireless communication device (not shown).
  • the error microphone 415 may be disposed in a separate space spaced apart from the sensor 2000 and the microprocessor 3000.
  • the harness 1000 in which the sensor 2000 or the like is disposed may be filled around the neck of the pet. Separately, the error microphone 415 may be spaced apart from the pet and disposed in a separate space.
  • the wireless communication device mediates communication between the error microphone 415 and the microprocessor 3000.
  • the third error component (E) can be minimized.

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  • Life Sciences & Earth Sciences (AREA)
  • Environmental Sciences (AREA)
  • Physical Education & Sports Medicine (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Animal Behavior & Ethology (AREA)
  • Zoology (AREA)
  • Animal Husbandry (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Engineering & Computer Science (AREA)
  • Soundproofing, Sound Blocking, And Sound Damping (AREA)

Abstract

La présente invention, selon un mode de réalisation, concerne un dispositif de réduction du bruit d'un animal de compagnie. Le dispositif de réduction de bruit d'un animal de compagnie selon un mode de réalisation de la présente invention comprend : une unité de détection destinée à détecter une source d'entrée comprenant une source de bruit ; une unité d'analyse destinée à analyser des caractéristiques de fréquence de la source d'entrée ; une unité d'extraction de bruit destinée à extraire la source de bruit de la source d'entrée sur la base des caractéristiques de fréquence ; une unité de génération destinée à générer une source anti-bruit annulant la source de bruit ; et une unité de sortie destinée à émettre la source anti-bruit. Par conséquent, le bruit généré en raison de l'aboiement, du hurlement, etc. des animaux de compagnie peut être activement réduit. < Dessin représentatif - FIG. 1 >
PCT/KR2020/005515 2019-04-25 2020-04-27 Dispositif de réduction de bruit d'un animal de compagnie, et équipement de collier pour la réduction du bruit d'un animal de compagnie l'utilisant WO2020218905A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
KR10-2019-0048387 2019-04-25
KR10-2019-0048406 2019-04-25
KR1020190048406A KR102194796B1 (ko) 2019-04-25 2019-04-25 동물 소음 저감 장치
KR1020190048387A KR102162588B1 (ko) 2019-04-25 2019-04-25 애완 동물 소음 저감용 목걸이 기구

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WO2020218905A1 true WO2020218905A1 (fr) 2020-10-29

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20080043237A (ko) * 2006-11-13 2008-05-16 소니 가부시끼 가이샤 노이즈 캔슬용의 필터 회로, 노이즈 저감 신호 생성 방법,및 노이즈 캔슬링 시스템
US20120090554A1 (en) * 2010-10-14 2012-04-19 The Kong Company, Llc Pet toy with core assembly incorporating noise making feature
US20150230429A1 (en) * 2014-02-14 2015-08-20 Dominic Mak Pet toy with integral noise making module
KR20160014438A (ko) * 2014-07-29 2016-02-11 엄윤주 동물소음 감소장치
KR20180059684A (ko) * 2016-11-26 2018-06-05 홍동현 노이즈 캔슬링을 이용한 반려견 짖음 소음을 제거하는 목걸이

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20080043237A (ko) * 2006-11-13 2008-05-16 소니 가부시끼 가이샤 노이즈 캔슬용의 필터 회로, 노이즈 저감 신호 생성 방법,및 노이즈 캔슬링 시스템
US20120090554A1 (en) * 2010-10-14 2012-04-19 The Kong Company, Llc Pet toy with core assembly incorporating noise making feature
US20150230429A1 (en) * 2014-02-14 2015-08-20 Dominic Mak Pet toy with integral noise making module
KR20160014438A (ko) * 2014-07-29 2016-02-11 엄윤주 동물소음 감소장치
KR20180059684A (ko) * 2016-11-26 2018-06-05 홍동현 노이즈 캔슬링을 이용한 반려견 짖음 소음을 제거하는 목걸이

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