818results about How to "Improve noise reduction" patented technology

The invention discloses an intelligent glasses audio processing method and system. The method comprises the following steps: data preparation: collecting source domain data and target domain data; pre-training the model; converting the audio signal into sequence data; an RNN model is constructed and trained; model migration: migrating the pre-trained RNN model to target domain data, and processing noise in the target domain data by using parameters and features of the pre-trained model; intelligent analysis and processing, wherein noise in target domain data is analyzed and processed by using the migrated RNN model; real-time processing and feedback are carried out, audio signals captured by a microphone of the intelligent glasses are analyzed in real time, and a noise reduction strategy is dynamically adjusted to eliminate background noise; and optimizing noise reduction parameters and strategies according to the feedback. By collecting the source domain data and performing model pre-training, the RNN model can identify and process various known noise types and features and quickly adapt to different noise environments, so that the noise reduction effect is improved, and a user can obtain the optimal hearing experience in different noise environments.

The invention relates to the technical field of temperature measurement, in particular to an electric energy meter wiring terminal temperature detection method and system, and the method comprises the steps: obtaining the temperature data and current data of each wiring terminal of each electric energy meter in different time periods within a preset time period, the environment temperature of each electric energy meter, and the structure data of each electric energy meter; determining a heat dissipation condition coefficient of the wiring terminal in the time period; selecting a first time period which simultaneously satisfies a subtraction interval in the current fitting curve of all the wiring terminals of the electric energy meter, and selecting a second time period in which the mean value of the current data of each wiring terminal is the lowest from the first time period; determining an external influence index of the wiring terminal in the time period; calculating the electromagnetic interference intensity of the wiring terminal in the time period; and after parameters of Wiener filtering are set to be electromagnetic interference intensity, temperature data of the wiring terminal in the time period are subjected to noise reduction processing. According to the invention, the noise reduction effect of the temperature detection data is improved, and the authenticity and accuracy of the temperature detection data after noise reduction are further improved.

The invention relates to the technical field of power distribution network fault monitoring, in particular to a fault monitoring method and system applied to a digital power distribution network. The method comprises the following steps: firstly, dividing each fault time period from a to-be-filtered time period; according to the difference condition of the fault responsivity of all the monitoring points in each fault time period, obtaining the noise measurement of the digital power distribution network in the to-be-filtered time period; adjusting the smoothing coefficient according to the noise metric, and obtaining the adjusted smoothing coefficient of the digital power distribution network in the to-be-filtered time period; performing filtering processing on the data set in the to-be-filtered time period by using the adjusted smoothing coefficient to obtain a filtered data set; and performing fault detection based on the filtered data set. According to the method, the adjusted smoothing coefficient of the digital power distribution network in the to-be-filtered time period is reasonably set, so that the noise reduction effect is improved, and accurate fault monitoring on the digital power distribution network is guaranteed.

The invention discloses a nonlinear ultrasonic detection signal noise reduction and feature enhancement method and system, and relates to the technical field of nonlinear ultrasonic detection.The method comprises the steps that CEEMDAN decomposition is conducted on detected nonlinear ultrasonic signals of concrete damage, and a plurality of intrinsic mode components IMFs are obtained; classifying and integrating the IMFs obtained by decomposition by using a sample entropy value to obtain a component IN-IMFs after classification and integration; performing variational mode decomposition on the IN-IMFs after classification and integration to obtain a group of intrinsic mode functions IMFs; and dividing the intrinsic mode function IMFs into a training data set and a test data set according to a time step length, inputting the training data set into a gating cycle unit model for training, and outputting a noise reduction and feature enhancement effect result of each IN-IMF. According to the invention, noise interference can be reduced for ultrasonic and nonlinear ultrasonic detection of damage of materials such as rocks and concrete, and nonlinear characteristics of detection signals in nonlinear ultrasonic can be enhanced.

The invention relates to the technical field of audio processing, and discloses a multi-mode audio processing method and system based on an SOC. The method comprises the following steps: inputting multiple paths of audio input signals into an ARM processor of an SOC chip for processing, and generating a preprocessed audio data stream; inputting the preprocessed audio data stream into a basic audio processing stream executed by a digital signal processor (DSP) and a multi-modal feature extraction stream executed by an artificial intelligence (AI) accelerator in parallel; performing adaptive noise reduction processing and multi-channel audio signal sound mixing processing in the basic audio processing stream to generate a basic processing feature stream; performing multi-dimensional feature extraction and scene type identification in the multi-modal feature extraction stream to generate a high-level feature stream; according to the method, the processing capability of the SOC chip on different types of audio signals is improved, the continuity and smoothness of the reconstructed audio signals are ensured, and signal distortion is effectively avoided.

The utility model relates to a soundproof cover, a soundproof cover assembly and an energy storage cabinet, the soundproof cover comprises a cover body and at least one separator, the cover body is internally provided with a cavity, a first opening and a second opening, the first opening and the second opening are communicated with the cavity, the at least one separator is arranged in the cavity and divides the cavity into a plurality of sub-runners, one end of each sub-runner is communicated with the first opening, and the other end of each sub-runner is communicated with the second opening. The cover body is provided with a first arrangement area, the first arrangement area is located on the cavity wall of the cavity, and / or the first arrangement area is arranged in the cover body and communicated with the cavity, the partition piece is provided with a second arrangement area, the second arrangement area is located on the outer surface of the partition piece, and / or the second arrangement area is located on the outer surface of the partition piece. The second arrangement area is arranged in the partition piece and communicates with the cavity, and the first arrangement area and the second arrangement area are both used for arranging the noise reduction piece. Thus, the noise reduction part can make contact with airflow in the flow channel and absorb sound waves (medium-high-low-frequency sound waves) of the airflow, the noise reduction effect is achieved accordingly, the contact area of the airflow and the noise reduction part is large, and the noise reduction effect of the sound insulation cover is improved.

The invention relates to the technical field of wind power generation control, in particular to a generator device and a control method thereof. The method comprises the following steps of performing real-time monitoring on noise frequency, amplitude and phase when a generator device operates, and generating a noise characteristic data set; extracting the main frequency and phase characteristics of a noise source from the noise characteristic data set, and performing reverse analysis on the data to generate reverse sound wave signal data opposite to the phase of the noise source; and the reverse sound wave generating device transmits the reverse sound wave signal data to the generator device, outputs reverse sound waves through a broadband loudspeaker, superposes the reverse sound waves and original noise in the space, and monitors the noise after noise reduction in real time to obtain noise reduction effect feedback data. According to the invention, noise characteristics are monitored in real time, matched reverse sound wave signals are extracted and reversely generated, reverse sound wave characteristics are dynamically adjusted, closed-loop adaptive control is formed, and efficient and stable noise reduction of a generator device is realized.

The invention discloses an automobile road noise active control method and device based on an Elman neural network. The method comprises the following steps: acquiring vibration acceleration data and in-vehicle noise data when a vehicle runs; the vibration acceleration data and the in-vehicle noise data are used for training an Elman neural network; taking a predicted noise signal output by the Elman neural network as a reference signal, and inputting the reference signal into a filter to obtain a filtered signal; playing the filtering signal in the target noise reduction area, and synchronously collecting residual noise as an error signal; adjusting the weight parameter of the filter through the error signal, and processing the reference signal through the filter with the updated weight parameter to obtain an updated filtering signal; the steps of generating the error signal and updating the weight parameter are repeatedly executed until the average noise reduction amount in the vehicle is lower than a preset condition, and a final filtering signal is obtained; and playing the final filtering signal to counteract the noise in the vehicle. According to the invention, the acoustic feedback problem and the noise transmission time delay problem caused by directly using the noise signal as the reference signal can be avoided.

The utility model discloses a noise reduction device for an air source heat pump unit, which belongs to the technical field of air source heat pump units and is characterized in that effective dispersion is carried out through a breathable mesh plate, primary noise reduction treatment is carried out on airflow through a noise reduction plate, and low-frequency noise reduction treatment is carried out on noise in the airflow again through low-frequency sound-absorbing cotton. The noise reduction device for the air source heat pump unit comprises a unit body, a condenser is arranged on the unit body, air guide barrels with cooling fans are symmetrically arranged at the top of the unit body, a cooling air barrel is installed at the top of the unit body, an air guide cavity is formed in the cooling air barrel, and a ventilation mesh plate is installed at the middle section of the air guide cavity. A noise reduction plate is installed on the inner side edge of the heat dissipation air cylinder and corresponds to the position between the two breathable mesh plates, an air outlet is formed in one end of the air guide cavity, and a plurality of pieces of low-frequency sound absorption cotton are installed at the position, corresponding to the air outlet, of the heat dissipation air cylinder.

The invention provides a photovoltaic direct current fault arc signal noise reduction method and device, and relates to the technical field of photovoltaic direct current fault arc diagnosis. The method comprises the following steps: decomposing a photovoltaic DC fault arc signal based on an IMGO-ICEEMDAN decomposition method to obtain a photovoltaic DC fault arc intrinsic mode component; calculating a multivariate intrinsic mode index, and dividing the photovoltaic DC fault arc intrinsic mode component into a high-frequency noise component, a low-frequency signal component and a noisy signal component according to the multivariate intrinsic mode index; performing noise reduction on the noisy signal component through the improved wavelet threshold to obtain an improved wavelet threshold noise reduction signal; and reconstructing the low-frequency signal component and the improved wavelet threshold noise reduction signal to obtain a noise reduction signal. According to the noise reduction method, the noise reduction effect of the fault arc signal is effectively improved while the key characteristics of the photovoltaic direct current fault arc signal are reserved, and the fault arc recognition accuracy can be remarkably improved.

The present invention provides an electronic device for reducing wind noise and its application. The raw materials of the porous block material include zeolite, adhesive and dispersant. The present invention also provides an electronic device comprising the above-mentioned porous block material. The present invention further provides an electronic device for reducing wind noise, including a body, an arc cover and a PCB board, the two ends of the body are respectively connected to the PCB board and the arc cover, the body is provided with an inner sound channel along the central axis, the arc cover is provided with an outer sound channel, the outer sound channel is in a windmill-shaped structure as a whole, including a central cavity and a plurality of branch channels, the branch channels are radially arranged around the central cavity, and each branch channel is a streamlined arc structure. The present invention further provides the application of the above-mentioned electronic device in an electronic device with a microphone. The electronic device provided by the present invention can effectively reduce wind noise and significantly improve the call quality of communication equipment.

The invention provides a method and device for optimizing noise of an indoor fan, an air conditioner and a storage medium, operation parameters and scene information of the air conditioner are obtained, a to-be-used rotating speed relation is determined from pre-stored corresponding relations of parameters and rotating speed relations on the basis of the operation parameters, and the to-be-used rotating speed relation comprises the corresponding relation of information and rotating speed; and determining a target rotating speed based on the scene information and the corresponding relation between the information and the rotating speed, and adjusting the rotating speed of the indoor fan based on the target rotating speed to optimize the noise. Through the mode, the corresponding target rotating speed can be determined according to different operating parameters and scene information, so that the noise is optimized, the noise can be reduced under the condition that the structure of the air conditioner does not need to be changed, and the noise reduction effect can be improved.

The invention discloses an escalator fault diagnosis method based on multi-sensor data input. The escalator fault diagnosis method comprises the four steps of escalator original data collection, data preprocessing, fault data set setting, escalator fault recognition and cloud model updating. According to the data preprocessing, escalator signal data are filtered through an improved wavelet threshold noise reduction method; the quality of escalator signal data is improved; the fault data set is set by fusing fault data of all parts and all types of the escalator, full utilization of the fault data of the escalator is achieved, and the richness of fault category signals is improved. According to fault identification, multi-sensor data is input into a CNN-GRU network, and the CNN-GRU network extracts features in the input data and obtains a final identification result. According to cloud model updating, the CNN-GRU model is optimized by using CFOA, a network model with the optimal CNN-GRU is constructed, the recognition precision is high, the generalization performance is good, and the method can be widely applied to the field of escalator fault diagnosis.

The invention discloses a rotor assembly and a motor using the rotor assembly, and the rotor assembly comprises a rotor injection molding body which is internally provided with a hollow cavity penetrating through the two axial ends of the rotor injection molding body; an output shaft is integrally formed at one axial side end of the rotor injection molding body through injection molding; a shaft hole used for being connected with a rotor supporting shaft in a matched mode is formed between the output shaft and the hollow cavity in a penetrating mode. A magnet ring injection-molded on the outer peripheral side of the rotor injection-molded body; the fixing plug is suitable for being inserted into the hollow cavity from the end, away from the output shaft, of the rotor injection molding body. A through hole which is coaxially communicated and matched with the shaft hole is formed in the fixing plug; wherein the hollow cavity and / or the fixed plug are at least provided with a section of suspension interval which is not completely contacted with the outer wall surface of the rotor support shaft.

The silencing body comprises a first wall and a second wall which are arranged in a spaced mode, at least one partition plate is connected between the first wall and the second wall so that at least one sound cavity can be formed between the first wall and the second wall, and an opening penetrating through the wall thickness is formed in the part, corresponding to the sound cavity, of one of the first wall and the second wall; when the number of the sound cavities is at least two, the structures and the sizes of all the sound cavities are the same, and all the sound cavities correspond to the preset target frequency, so that the noise elimination body can perform noise elimination and noise reduction on the noise of the target frequency; wherein when the size parameter of the sound cavity is determined, the target frequency of the noise absorbed by the sound cavity is acquired; determining a frequency correction coefficient; obtaining a correction frequency according to the frequency correction coefficient and the target frequency; and designing size parameters of the acoustic cavity according to the correction frequency. The silencing body corresponds to the target frequency to be eliminated, the silencing and noise reduction effect is good, and the silencing body can be modularized easily.

The invention relates to an OWS earphone active noise reduction method, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring a noise signal through a microphone; analyzing the noise signal, and when the volume of the noise signal is greater than a preset volume threshold value, generating a noise reduction sound wave opposite to the phase of the noise signal through an electroacoustic transducer to eliminate noise; analyzing the noise signal to determine an environmental scene; when the OWS earphone is in a commuting scene, determining the phase and frequency of a noise reduction sound wave according to a noise signal collected by the microphone; calculating a noise reduction evaluation index in the commuting scene, and adjusting the phase and frequency of a noise reduction sound wave according to the noise reduction evaluation index to maintain an optimal noise reduction effect; different noise reduction modes are set according to common application scenes of the earphone, feedback can be made according to noise reduction requirements of different application scenes, the use experience of a user is not affected while the noise reduction effect is generated, and meanwhile the optimal noise reduction effect is kept through the noise reduction evaluation index.

The invention discloses an optical coherence imaging noise reduction method and device, equipment and a medium, and the method comprises the following steps: obtaining a B-scan image, and constructing a training set; training an image noise reduction model based on the deep neural network by adopting the training set; obtaining a to-be-denoised B-scan image, inputting the to-be-denoised B-scan image into the trained image denoising model for denoising, and outputting a reconstructed B-scan image; wherein the image noise reduction model comprises an encoder and a decoder, and the encoder takes a B-scan image with noise as input to obtain a potential representation of the B-scan image with noise; and the decoder takes the potential representation of the B-scan with noise as input, and outputs a reconstructed B-scan noise reduction image. According to the method, the image noise reduction model is constructed through the deep neural network, the B-scan image is subjected to noise reduction, the clear B-scan image is effectively obtained, and the method has the advantages of being excellent in noise reduction effect and high in speed. The method can be widely applied to the technical field of image imaging noise reduction.

The invention belongs to the technical field of voice noise reduction. The invention provides an edge end real-time voice noise reduction method. According to the embodiment of the invention, pre-emphasis, framing and windowing processing is carried out on the input voice signal, so that the high-frequency component of the signal is improved and the distortion of the signal is reduced. And performing fast Fourier transform on the preprocessed input voice signal to convert a time domain signal into an original frequency domain signal. And calculating the Mel frequency cepstrum coefficient of the original frequency domain signal to extract the MFCC characteristic parameter of the speech. Noise estimation is performed on the MFCC characteristic parameters by using the lightweight separable convolutional neural network, so that the parameter quantity and the calculation quantity are reduced, and efficient noise estimation is realized. And performing adaptive iterative Wiener filtering by using the generated noise estimation, and gradually eliminating noise in the voice signal to obtain a filtered frequency domain signal. And inverse fast Fourier transform is carried out on the filtered frequency domain signal, and a time domain signal is recovered. And outputting a time domain signal which is a voice signal after noise reduction.

The integrated adsorption tower of the oxygen generator comprises an adsorption tower main body, a gas inlet integrated cover part and a gas outlet integrated cover part which are arranged at the two ends of the adsorption tower main body, and a reversing valve arranged on the gas inlet integrated cover part, two molecular sieve cylinders and two air storage tanks are arranged in the adsorption tower main body, the nitrogen removal and noise reduction cylinder is positioned in the middles of the two molecular sieve cylinders and the two air storage tanks, the molecular sieve cylinders are communicated with the air storage tanks, the molecular sieve cylinders can be communicated with the nitrogen removal and noise reduction cylinder under the control of a reversing valve, the reversing valve controls air to alternately enter and remove nitrogen, the molecular sieve cylinders are filled with adsorbents, and the adsorbents are communicated with the nitrogen removal and noise reduction cylinder. The two molecular sieve barrels are integrated on one adsorption tower, so that the assembly difficulty is reduced, the production efficiency is improved, the space utilization rate is improved, and the nitrogen discharge noise is reduced by arranging the silencing barrel.

The invention discloses a noise reduction processing method and device, a vehicle and a storage medium, and relates to the technical field of intelligent cabins, and the method comprises the steps: carrying out the recognition based on an error signal and an accelerometer signal of the vehicle, and obtaining a noise scene where the vehicle is located; decomposing the accelerometer signal into a plurality of sub-band signals which are not overlapped with one another; for each sub-band signal, determining a noise reduction processing parameter corresponding to each sub-band signal based on the energy analysis and noise scene of the sub-band signal; based on the noise reduction processing parameter corresponding to each sub-band signal, performing adaptive filtering on each sub-band signal in combination with the error signal to obtain a noise reduction signal corresponding to each sub-band signal; and carrying out fusion reconstruction on the noise reduction signals corresponding to the plurality of sub-band signals to obtain a full-band noise reduction signal. According to the invention, adaptive filtering and noise reduction are carried out on each sub-band signal based on the noise scene where the sub-band signal is located, efficient division and treatment and response can be carried out on complex and multi-spectral structure noise, the noise reduction effect is improved, and the vehicle use experience feeling of a user is further improved.

The present invention discloses an earphone audio system and control method based on an array sensor module, and relates to the field of earphone audio processing technology, including a noise reduction demand entry module, an environmental audio monitoring unit, an environmental sound analysis unit, and an array audio sensor unit. The noise reduction demand entry module of the present invention provides a more specific noise reduction demand entry method, and the environmental noise data monitored interactively by the microprocessor and the environmental sound analysis unit are displayed on a touch screen in combination with the current direction data, providing users with more accurate noise reduction demand options; after the user selects the noise reduction demand of the corresponding direction by operating the touch screen or recording the voice through the microphone of the earphone, the array audio sensor module transmits the reference reflection signal after adaptive filtering and delay adjustment, and the reference reflection signal should have the same frequency and amplitude as the noise, but the opposite phase, so that the specified direction can be targeted and directional and accurate noise reduction can be performed, and the noise reduction effect is outstanding.

The invention belongs to the technical field of plastic pipelines, and particularly discloses a high-impact-resistance PVC composite mute pipe which comprises an inner layer, a foaming sound insulation layer, a hollow silencing layer and an outer layer which are sequentially arranged from inside to outside. The inner layer comprises an inner layer body and a plurality of flow guide screw flights, and the flow guide screw flights are distributed in the circumferential direction of the inner circumference of the inner layer body at intervals. A plurality of silencing holes are formed in the front side face of the hollow silencing layer in the circumferential direction. According to the high-impact-resistance PVC composite mute pipe and the preparation method thereof, the high-impact-resistance PVC composite mute pipe has high strength and high and low temperature impact resistance, and a good noise reduction effect can be achieved.

The present disclosure provides a method, device, equipment and storage medium for reducing the noise of call speech, which relates to the field of computer technology, and in particular to the field of speech technology. The specific implementation scheme is: obtaining a call speech signal and a reference signal, the call speech signal includes an external dual-microphone front-end signal and a built-in microphone signal; performing a first pre-processing on the external dual-microphone front-end signal to obtain a first pre-processed signal; performing a second pre-processing on the built-in microphone signal to obtain a second pre-processed signal; using a deep neural network DNN noise reduction model, performing noise reduction on the first pre-processed signal to obtain a first noise reduction signal; performing noise reduction on the second pre-processed signal according to voice activity detection information to obtain a second noise reduction signal, and the voice activity detection information comes from the output of the DNN noise reduction model; performing spectrum fusion on the first noise reduction signal and the second noise reduction signal to obtain a noise reduction output speech signal.

The utility model discloses a high-elasticity synthetic rubber and plastic plate with excellent noise reduction, and relates to the technical field of synthetic rubber and plastic plates. A first noise reduction layer is arranged on the left side face of the base layer, a second noise reduction layer is arranged on the right side face of the base layer, the base layer is formed by mixing rubber, silicon dioxide and zinc oxide, the first noise reduction layer and the second noise reduction layer are both made of polyurethane, and a first heat preservation layer is fixed to the left side face of the first noise reduction layer. A second heat preservation layer is fixed to the right side face of the second noise reduction layer, and the second heat preservation layer and the first heat preservation layer are both made of butadiene rubber. According to the high-elasticity synthetic rubber and plastic plate with the excellent noise reduction effect, the noise can be effectively isolated by adopting double-layer noise reduction, so that the noise reduction effect of the synthetic rubber and plastic plate is improved, the arranged heat preservation layer can achieve the low-temperature-resistant effect, and the high-elasticity synthetic rubber and plastic plate has the good noise reduction effect. The high elasticity is ensured by ensuring that the synthetic rubber and plastic plate does not easily become hard at low temperature.

The present invention discloses a method for extracting features of motor bearing faults, comprising the following steps: introducing an inverse tangent non-convex penalty function to define a regularization term in second-order total variation denoising; optimizing the regularization parameter λ and the convexity parameter a in NCTVD by using the BAS algorithm through the fitness function CK_I, limiting the two parameters within a certain region and solving the optimal parameter combination to ensure the strictly convex nature of the convex optimization problem; then, using a minimum optimization algorithm to solve the generated new convex optimization problem to achieve noise reduction and feature enhancement of vibration signals; applying a TEO demodulation method to perform Teager energy spectrum analysis on the denoised signal to achieve feature extraction of motor bearing faults. The method proposed by the present invention mainly solves the problem that the fault features of motor fault bearings are submerged by strong background noise and the fault information representation is not obvious, and can effectively extract fault features in motor bearing vibration signals, having certain engineering application value.

The utility model discloses a sound-absorbing, heat-insulating and corrosion-resistant composite board which comprises a supporting layer, and a bonding layer, a fiber reinforcing layer and a gel coat layer which are sequentially arranged on one side or two sides of the supporting layer, the supporting layer is configured to be of a columnar structure or a plate-shaped structure or a hollowed-out plate-shaped structure or a honeycomb-shaped structure. The thickness of the bonding layer is 0.01 to 2.0 mm; the thickness of the fiber reinforced layer is 0.4 to 3.0 mm; and the thickness of the gel coat layer is 0.05 to 2.5 mm. According to the technical scheme, the structural strength and the heat insulation performance of the composite board can be effectively improved by adopting the fiber reinforcement layer, and the corrosion resistance of the composite board can be improved by adopting the gel coat layer. The supporting layer structure arranged in a column shape or a hollow plate shape reduces the weight of the composite board while playing a supporting role, light weight is achieved, and meanwhile the internal space gap can also play a good noise reduction role.

The invention discloses a muscle force estimation method based on surface electromyogram signals and adjustable input characteristics. The method comprises the steps that the surface electromyogram signals and force signals in a muscle contraction state are synchronously collected; the EMD-DWT method is adopted to preprocess the surface electromyogram signals; segmenting the surface electromyogram signals and the force signals by adopting a sliding window, extracting features of the surface electromyogram signals, extracting an average value of the force signals, and making sample labels; a Pearson's correlation coefficient method is adopted to calculate correlation coefficients of the extracted features and the force signals; sequentially adding features with high correlation coefficients to form an input vector of the model, constructing a muscle force estimation regression model for training and testing, and adjusting the number of input features according to errors of a training set and a testing set. According to the method, effective features can be accurately and rapidly extracted, the number of the features can be determined, and it is guaranteed that high muscle force estimation precision is achieved under the condition that the input dimension is low.

The invention discloses a negative pressure suction system of an endoscope, which comprises a machine base, a double-head negative pressure pump is arranged in the machine base, the double-head negative pressure pump comprises a double-head negative pressure pump A and a double-head negative pressure pump B, the double-head negative pressure pump A is provided with a pump A air inlet and a pump A air outlet, and the double-head negative pressure pump B is provided with a pump B air inlet and a pump B air outlet; the double-head negative pressure pump A and the double-head negative pressure pump B are connected in series, and a pump A air inlet of the double-head negative pressure pump A is connected with a pump B air inlet of the double-head negative pressure pump B through a guide pipe; the machine base is further provided with a negative pressure monitoring protection bottle, the top of the negative pressure monitoring protection bottle is provided with an equipment end negative pressure input connector, a negative pressure output connector and a negative pressure measuring connector, and the equipment end negative pressure input connector, the negative pressure output connector and the negative pressure measuring connector are connected with a cavity of the negative pressure monitoring protection bottle in a communicated mode. According to the invention, the environmental interference in the operation can be reduced, the silencing and shockproof effects are improved, meanwhile, the safety protection is carried out on the negative pressure drainage, and the safe negative pressure is monitored in real time.

The utility model discloses a small brushless motor capable of reducing noise in the field of brushless motors, which comprises a shell and a sealing cover, a stator and a rotor are arranged in the shell, the shell is in sealing connection with the sealing cover, an elastic rubber layer is adhered to the outer surface of the stator, a sound-absorbing cotton layer is adhered to the inner surface of the rotor, and the sound-absorbing cotton layer is adhered to the outer surface of the shell. A main control circuit board is arranged in the shell, and a sound absorption foam layer is adhered to the surface of the main control circuit board; according to the small-sized brushless motor capable of reducing noise, by arranging the sound-absorbing cotton layer, the elastic rubber layer and the sound-absorbing foam layer, the brushless motor can better absorb noise generated during operation, and meanwhile, the closed shell structure can obstruct sound transmission, so that the noise reduction effect is greatly improved.

The utility model belongs to the technical field of breathing machines, and provides a breathing machine resonance type noise reduction structure and a portable breathing machine, the breathing machine resonance type noise reduction structure comprises a shell, an air duct and a cavity are arranged in the shell, the air inlet end of the air duct is communicated with the outside, and the air outlet end of the air duct is communicated with the cavity; the fan is mounted in the shell, and an air inlet of the fan is communicated with the cavity; the at least one resonance plate is arranged in the air channel and arranged from the air inlet end to the air outlet end, a plurality of through holes penetrating through the resonance plate are formed in the resonance plate, the resonance plate and the inner wall of the shell are spaced to form a resonance cavity, and the resonance cavity is filled with sound absorption materials. According to the resonance type noise reduction structure of the breathing machine, the resonance plate is arranged in the air duct, the resonance cavity is formed by the interval between the resonance plate and the inner wall of the shell, the sound absorption material is filled in the resonance cavity, and the resonance noise elimination of the resonance cavity and the sound absorption of the sound absorption material are combined for noise reduction, so that the good noise reduction effect of the breathing machine is achieved; and the user experience is improved.