5164 results about "Low noise" patented technology

An incubator can include a body, a bed supported by the body, and a canopy defining an interior chamber that includes the bed. The incubator can include any combination of various features configured to reduce sound energy inside the incubator. The incubator can include a passive radiator, a Helmholtz resonator, a meta material absorber, an active noise cancelation system, a vented door latch assembly, an acoustically permeable seal, a pressure relief valve, a lift mechanism that uses a belt drive, double paned canopy walls, a bin with insulating compliant elements, a manual pressure release valve, a pressure differential notification system, non-parallel or curved canopy walls, a mattress with reticulated foam, and / or an acoustic filter.

To provide a game machine in which the influence of noise on a signal is reduced.SOLUTION: A power supply pattern for transmitting power of a specified voltage supplied from a power supply board is provided on an outer periphery of a second layer, and specific wiring that is electrically connected to the power supply pattern in the second layer and supplies power to specified components is provided in the first layer so as to extend from the outside to the inside. It is possible to suppress the influence of noise on signals transmitted by signal lines provided on the center side in the first layer. In other words, it is possible to reduce the influence of noise on signals.SELECTED DRAWING: Figure 11

The invention discloses an electromechanical equipment noise reduction method based on machine learning, and relates to the field of electromechanical equipment noise reduction, and the method comprises the steps: collecting sound pressure and vibration signals during the operation of electromechanical equipment, and collecting the operation state data of the electromechanical equipment; sparse reconstruction is carried out on the noise features; carrying out sound source localization on the reconstructed noise features by using a beam forming algorithm to obtain a noise distribution diagram; constructing a noise reduction model based on deep learning to obtain noise signals after noise reduction; extracting the frequency of the noise signal in a preset frequency range through a peak search algorithm; analyzing the acquired running state data by using a time-varying linear predictive coding algorithm TVLPC to obtain a noise frequency offset caused by the abnormal running state of the electromechanical equipment; generating an optimal solution by using a particle swarm algorithm; and according to the optimal solution of noise control, noise dominant frequency components are extracted for separation, and a plurality of phase-reversal noise reduction control signals are obtained. Aiming at low noise reduction precision of electromechanical equipment in the prior art, the noise reduction control precision is improved.

The invention relates to the technical field of voice processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a voice feature processing method, device, equipment and medium. Performing time resolution analysis based on the fused Mel band energy to generate a multi-scale Mel spectrum amplitude value, and performing nonlinear transformation on the multi-scale Mel spectrum amplitude value according to the noise intensity parameter to generate a noise suppression Mel component; and generating a perception weighting coefficient according to an auditory perception model, and executing frequency domain energy adjustment on the noise suppression Mel component to generate Mel spectrum representation. On the basis of frequency resolution self-adaption, time resolution dynamic adjustment and auditory perception modeling, nonlinear transformation and perception weighting processing are applied to the multi-scale Mel spectrum amplitude value, the influence of noise interference on voice features can be effectively reduced, and the key information retention capacity of voice signals is enhanced.

The invention relates to the technical field of cable fault detection, in particular to a cable fault analysis system based on big data, which comprises a disturbance feature extraction module, a time sequence hierarchy judgment module, a reflection characteristic analysis module, a topological section identification module and a fault path mapping module. According to the method, gradient inflection points are extracted by calculating voltage and current increment included angles at adjacent moments, spatial-temporal characteristics of disturbance signals are correlated, interference of noise to a starting point mark is reduced, time difference is fitted in combination with cable length, deviation over-threshold abnormal points are dynamically filtered, influences of synchronization errors on sorting are eliminated, and fault path mapping stability is improved; the method comprises the following steps: generating characteristic parameters by fusing amplitude values and wave crest intervals of main waves and reflection waves, quantifying amplitude attenuation and phase offset coupling, enhancing the multi-path superposed signal separation capability, judging the reflection characteristic similarity of a physical section based on a Manhattan distance and a support vector machine, and dynamically dividing a fault section in combination with line topology. The problem of fuzzy positioning in a branch parallel scene in a traditional method is solved.

The invention discloses a high-precision current detection circuit calibration system, and belongs to the technical field of current detection circuit calibration. Comprising a shunt resistor, a Hall sensor array, a chopping amplifier, a low-noise operational amplifier, a temperature sensor, an ADC acquisition unit, an RC low-pass filter, a signal conditioning unit, a main control unit, an environmental parameter adaptive compensation module and a gain adaptive adjustment module. After an original signal is obtained from a multi-channel sensor, a dynamic error model is constructed in combination with temperature data, a long-term imbalance trend is extracted by using a moving average or median filtering algorithm, and real-time compensation is performed through a pre-calibrated temperature-drift function, so that the system maintenance period is remarkably prolonged.

The invention discloses an automatic anchor point searching and processing method for grid-connected test data of a photovoltaic inverter, and belongs to the technical field of automatic test of a power system. According to the method, a three-phase voltage and current signal output by a power grid simulator and an inverter power instruction signal are aligned through a high-precision time synchronization device; wavelet transform multi-scale noise reduction and moving average filtering combined preprocessing is adopted to improve the signal-to-noise ratio; identifying a voltage zero crossing point candidate set, a drop starting point candidate set and a recovery termination point candidate set based on a self-adaptive dynamic threshold value; transient energy characteristic verification is introduced for a voltage drop starting point; effective anchor points are confirmed through time window association of power instruction step changes. According to the method, the problems of low efficiency of manual key event point identification, misjudgment caused by noise interference, grid event and inverter response time sequence correlation missing and the like are solved, and the automation degree of test data analysis, anchor point positioning precision and control response time sequence analysis reliability are remarkably improved.

The invention relates to the technical field of information transmission, in particular to a multi-band processing system for electronic communication, which comprises a signal separation module, a frequency deviation compensation module, an amplitude correction module, a phase correction module and a dynamic feedback adjustment module. According to the invention, a plurality of frequency bands are extracted to execute band-pass filtering to separate signal components, short-time power spectral density is calculated to describe energy distribution, normalization coefficient operation is carried out to enhance frequency domain balance, high-energy component screening is carried out to reduce noise interference, signal effectiveness is improved, and frequency offset compensation calculates a change rate based on adjacent phase data and eliminates abnormal fluctuation. A time domain coefficient is adjusted to correct a frequency offset error, amplitude correction depends on short-time Fourier transform to screen the maximum amplitude to optimize signal consistency, phase adjustment fits a group delay error curve to optimize compensation parameters, dynamic feedback optimizes a strategy according to a signal-to-noise ratio to enhance compensation precision, and signal transmission quality and stability are improved.

The invention belongs to the technical field of signal acquisition and processing, and discloses a low-noise biopotential signal acquisition system and a low-noise biopotential signal processing method. An original bioelectricity signal of a human body is collected through an electrode array, and analog-to-digital conversion is carried out after the signal is processed by a multi-stage self-adaptive filtering and amplifying circuit. A digital signal is sequentially subjected to adaptive wavelet transform denoising and empirical mode decomposition to obtain a multi-level intrinsic mode function set, an intrinsic mode function of a characteristic frequency band is extracted from the multi-level intrinsic mode function set, and the signal is reconstructed. Introducing a dual noise reduction mechanism combining adaptive wavelet transform and empirical mode decomposition; a signal quality real-time evaluation system is established, and system parameters including the gain of a variable gain amplifier and the bandwidth of a dynamic band-pass filter are dynamically adjusted through closed-loop feedback. The self-adaptive optimization of the whole biopotential signal acquisition process is realized, various interferences are effectively inhibited, the signal characteristics are reserved, and the signal-to-noise ratio is remarkably improved.

The invention relates to the technical field of wireless communication, and provides a radio frequency low-noise amplifier which comprises an input matching module, a power amplification module, an output matching module, an RC attenuation module and an RC feedback module, the first end of the first inductor serves as the input end of the output matching module, the first end of the first inductor is connected with the output end of the power amplification module, the control end of the switch and the first end of the first adjustable resistor, and the second end of the first inductor is connected with the first end of the second inductor and the first end of the third capacitor. The output end of the switch is connected with the first end of the first capacitor and the first end of the second capacitor. The second end of the second capacitor is connected with the second end of the first adjustable resistor and the second end of the second inductor and used for being connected with a power supply. The second end of the first capacitor is connected with the second end of the third capacitor and serves as the output end of the output matching circuit. The radio frequency low-noise amplifier is adjustable in gain, low in noise and good in linearity performance.

The invention discloses a high-precision electric power measurement method based on an intelligent electric meter, and relates to the technical field of electric power measurement. According to the invention, a plurality of high-precision voltage and current sensors with temperature compensation are uniformly arranged in a circuit, a low-noise front-end conditioning and multi-channel high-resolution ADC synchronous sampling technology is adopted, and a digital phase-locked loop is introduced to realize accurate correction of a sampling clock. And performing multi-stage weighted fusion, time domain instantaneous power calculation and FFT frequency domain decomposition compensation on the acquired data, and finally accurately calculating the real power in a power grid period. According to the method, measurement errors caused by temperature excursion, phase deviation and harmonic interference in the prior art are effectively solved, the measurement precision and stability of the system are remarkably improved, and the method is suitable for high-precision power monitoring in a complex power grid environment.

The invention relates to a low-noise water purifier. The water purifier includes a shell, an integrated waterway plate and booster pumps. The integrated waterway plate is fixed to the shell and is connected to water outlets of the booster pumps through pressure stabilizing tanks. The pressure stabilizing tanks are disposed between the booster pumps and the integrated waterway plate. The integrated waterway plate is connected to a plurality of evenly arranged connection tubes and is connected to filter core base assemblies through the connection tubes in a one-one correspondence manner. Beneficial effects of the water purifier are that 1) water knocking abnormal sound of the water purifier is reduced, thus improving user experience, 2) the structure is simple, water leakage is prevented and the production efficiency is high, and 3) replacement of a consumable of the product is simpler and more convenient.

The invention discloses a defect identification system of an ultrasonic flaw detector, and relates to the technical field of nondestructive testing, the system comprises a signal acquisition and preprocessing module, a defect feature identification module, a physical modeling analysis module, a life prediction and evaluation module and an intelligent decision visualization module; the signal acquisition and preprocessing module adopts a multi-frequency-point phased array transducer array, obtains an original signal through low-noise amplification, band-pass filtering and analog-to-digital conversion, and outputs a time domain signal matrix through adaptive noise reduction and gain compensation processing; the multi-frequency-point phased array transducer array and the advanced signal processing technology are integrated, the defect recognition precision and efficiency are remarkably improved, the system obtains high-quality original signals through low-noise amplification, band-pass filtering and analog-to-digital conversion technologies at first, then the high-quality original signals are subjected to self-adaptive noise reduction and gain compensation processing, and the defect recognition accuracy is improved. The background noise interference is effectively eliminated, and the purity of the signal is ensured.

The invention discloses a high-voltage power switch fault diagnosis method based on wavelet threshold correction and noise reduction. Acquiring a voltage signal of the high-voltage power switch by using a sensor, and performing synchronous sampling; a wavelet threshold value correction noise reduction method is adopted to carry out noise reduction processing on the collected signals, wavelet detail coefficients are calculated through multi-scale decomposition, a threshold value is adaptively corrected based on the peak sum ratio, and the noise removal effect is optimized; thirdly, performing normalization processing on the denoised signal, mapping the signal to a polar coordinate system, constructing a two-dimensional Gramer angle field containing an included angle cosine value and amplitude information, and realizing time sequence-space conversion of the signal; and finally, generating two-dimensional image data of the voltage signal of the high-voltage power switch, and providing feature input for subsequent state evaluation and fault detection. According to the method, wavelet transform and two-dimensional feature mapping are combined, noise interference can be effectively reduced, the signal distinguishability and the information retention capacity are improved, and the method is suitable for state monitoring and intelligent diagnosis of a power system.

The invention provides a low-noise amplification circuit and a radio frequency power amplifier module, and the low-noise amplification circuit comprises an input matching circuit, a cascode amplification structure, an output matching circuit and a path switching assembly. The input matching circuit comprises a first inductor, a second inductor, a first capacitor and a third inductor; the output matching circuit comprises a fourth inductor, a second capacitor, a fifth inductor, a third capacitor and a fourth capacitor; and the access switching assembly is used for selecting channels of the low-noise amplification circuit, so that a radio frequency signal accessed by the first inductor is directly output or output after being amplified by the cascode amplification structure. According to the low-noise amplification circuit, on the premise that the noise coefficient is reduced and the gain is matched, the order of an input and output matching network does not need to be increased, and correspondingly, the cost and the area of the low-noise amplification circuit are not increased.

The invention relates to the technical field of earphone noise reduction processing, and discloses a motorcycle riding earphone noise reduction method combining different noise reduction algorithms, comprising the following steps: acquiring an original audio signal, and distributing the original audio signal to each processing module; a preprocessing signal is generated, voice activity information is determined, and environmental noise energy information is calculated; according to the environmental noise energy or the auxiliary information, adaptively adjusting a high-low noise energy threshold value; the original signals are input into the traditional and AI noise reduction module in parallel to generate two paths of noise reduction signals; based on the environment noise, the voice information and the threshold value, performing weighted fusion to generate an output signal; and carrying out equalization and compression processing on the output signal, and driving the loudspeaker to output. According to the invention, comprehensive judgment on environmental noise energy information, voice activity information and riding speed is introduced, an output signal of a traditional noise reduction module is set to be zero in a high-speed voice-free environment, and AI noise reduction is combined, so that tone quality distortion of a traditional noise reduction algorithm in a noise environment is effectively avoided.

The invention discloses a driving module of a reciprocating type shaver. The driving module comprises a base, a driving assembly and a driving assembly, the two ends of the deflection frame are fixed to the base through elastic pieces to form a frame structure. The output shaft is mounted above the deflection frame; the horizontal motor is arranged on the base; the cam is arranged on a motor power shaft, and grooves with parallel normal sections and equal width are formed in the surface of the cam; the lower end of the rocker arm is hinged to the base, a middle rocker arm shaft is assembled in the groove, and the upper end is in linkage with the deflection frame. Rotary motion is converted into high-frequency linear swing through precise cooperation of the cam and the rocker arm, the transmission efficiency is high, and noise is low; the integrated modular structure of the base and the motor enables the cam and the rocker arm to be matched more accurately and reliably; the double-output shaft symmetrically and reversely swings to realize dynamic balance vibration reduction; the compact horizontal layout saves space; the product has the economical efficiency of a common motor and the performance advantages of a linear motor, the comfort and reliability of a shaver product are improved, and meanwhile the cost is reduced.

The invention relates to a gradient diameter microchannel plate and a preparation method and application thereof. The preparation method comprises the following steps: preparing a transparent material into a sheet-shaped substrate; the method comprises the following steps: processing conical array micropores in a substrate by using femtosecond laser to obtain a gradient-diameter substrate; when the conical array micropores are processed, the inlet end is firstly etched to form an opening, then the diameter is gradually and uniformly reduced to the outlet end, and the diameter of the inlet end is greater than that of the outlet end; the ratio of the hole depth of the conical array micropores to the diameter of the outlet end is 30-200, and the taper angle is 1-5 degrees; preparing AlO-SiO-BOsol containing Cs, uniformly coating the AlO-SiO-BOsol on the inner walls of the conical array micropores, and then carrying out hydrogen reduction to obtain a microchannel blank plate; and plating electrodes at the two ends of the micro-channel blank plate to obtain the gradient-diameter micro-channel plate. The gradient diameter microchannel plate provided by the invention has the advantages of high gain and low noise, and is more practical.

In a segmented ball valve for low noise and anti-cavitation applications, a replaceable cartridge is fixed inside and retained by stem and end post. The segment has a machined cylindrical bore with a slide-fit noise cartridge, enabling field replaceability with minor effort & without need of welding or fasteners. The replaceable cartridge also enables use of a fully cylindrical cartridge with greater pressure reduction stages compared to welded-on noise plates on the segment. The segment has a flattened front face resulting in lower Fd enabled by dual flow path in lower openings values thereby attaining higher noise attenuation where the cartridge is not required. The curved plates of the low noise and anti-cavitation cartridge enable: expanding flow resulting in non-impinging jet streams thereby achieving higher noise attenuation in one direction; and converging flow in the opposite direction resulting in reduction of flow energy, and the potential for cavitation for liquids.

The invention discloses a full waveform decomposition method based on a multi-branch convolutional neural network, which belongs to the technical field of airborne depth sounding laser radars, is used for airborne depth sounding laser radar echo signal decomposition, and comprises the following steps: obtaining and preprocessing an original echo sequence, constructing a multi-branch one-dimensional convolutional neural network model, and performing neural network training; and based on the trained multi-branch one-dimensional convolutional neural network, outputting a three-channel probability heat map, performing multi-peak sub-pixel decoding on the three-channel probability heat map, and outputting a peak accurate position, a peak accurate position normalized value and a peak confidence after de-weighting. According to the method, the multi-branch one-dimensional convolutional neural network model is constructed and multi-peak sub-pixel decoding is carried out, so that stable decomposition of full-waveform echoes and high-precision positioning of multi-echo peak values are realized under the conditions of multi-peak superposition, high noise and weak signals, and false detection and false peaks caused by noise are remarkably reduced.

The invention provides a broadband low-noise amplifier based on a three-coil coupling transformer. The broadband low-noise amplifier comprises an input matching network, a common-source differential output driving stage amplifier, an inter-stage matching network, a common-source differential output power stage amplifier and an output matching network which are connected in sequence, broadband matching is realized by using the input matching network and the inter-stage matching network, and the effective transconductance of the transistor is improved; through the cross-coupled capacitors, the LNA gain and stability on a broadband are improved, better isolation is realized, and input and output are decoupled; due to the design of the grounding capacitor, the linearity of the LNA is improved; through the combination of the three-coil coupling transformer and the differential topology, output signals are superposed in the same direction at the output end, and noise is cancelled in the reverse direction at the output end, so that the thermal noise is greatly inhibited, the isolation is improved through the output matching network, the insertion loss is reduced, and the output matching performance is optimized.

The invention discloses a low-illumination image enhancement method suitable for a complex night operation scene. The method comprises the following steps: preprocessing a collected low-illumination RGB image to obtain a preprocessed image; multi-scale features are extracted from the shallow convolution projection and the multilayer axial converter unit, and cross-layer attention is used for weighted aggregation to form enhanced features; forward noise addition is executed according to noise scheduling to obtain potential representation representing low-illumination noise distribution, and deep semantic representation is extracted in combination with a U-Net encoder embedded in CBAM; in the decoding stage, details are reconstructed through jump connection and a multi-layer converter, meanwhile, reverse denoising of a diffusion model is introduced to gradually remove noise, and an enhanced image with high brightness and low noise is output; in the training process, bidirectional mapping from low illumination to normal illumination is constructed, a weighted target of self-encoding loss and enhanced loss is introduced to carry out joint optimization on a converter and diffusion parameters, and a low-illumination scene is monitored on a general GPU / edge device.

The invention provides an oscillator frequency modulation circuit and a communication chip. The oscillator frequency modulation circuit comprises a first resonance area which comprises a first resonance circuit, a first coupling tube (Mn) and a second coupling tube (Mp), wherein the first coupling tube (Mn) and the second coupling tube (Mp) are cross-coupled with the first resonance circuit; the second resonance area comprises a second resonance circuit, and the second resonance circuit comprises a first branch circuit electrically connected with the first coupling tube (Mn) and a second branch circuit electrically connected with the second coupling tube (Mn); the second branch is electrically connected with the second coupling tube (Mp); the first tail inductor (Ln) is connected to the first branch in series; the second tail inductor (Lp) is connected in series with the second branch; and the differential capacitor array (Ct) is connected between the first branch circuit and the second branch circuit in parallel. According to the oscillator frequency modulation circuit and the communication chip, low noise can be realized in a broadband range, the anti-interference capability is realized, meanwhile, the occupied area is relatively small, and high-quality signals can be continuously output for a multi-protocol system.

The invention relates to an unmanned aerial vehicle RemoteID signal detection, demodulation and analysis system and method, an upper computer sends a task instruction to a central control module through a network module to carry out radio frequency data acquisition, the central control module controls a radio frequency receiving module to acquire an electromagnetic wave signal of a specified frequency band in an airspace environment, and the electromagnetic wave signal is transmitted to the central control module; carrying out low-noise amplification and filtering processing on the electromagnetic wave signal of the specified frequency band; iQ data acquisition is carried out, wherein an intermediate frequency acquisition module acquires signals and carries out frequency mixing, filtering and AD sampling processing; inputting the acquired IQ data into a baseband data processing module, and performing analysis processing through the baseband data processing module based on an unmanned aerial vehicle RemoteID signal detection algorithm, an unmanned aerial vehicle RemoteID signal demodulation algorithm and an unmanned aerial vehicle RemoteID signal analysis algorithm; and an operation result of the baseband signal processing module is transmitted to an upper computer for display through the network transmission module. Remote and non-standard frequency band Remote ID signal supervision and analysis can be realized, the system stability is high, and the algorithm detection, demodulation and analysis accuracy is high.

A multi-source spatio-temporal data fusion signal processing system based on a high-elasticity transmission conductor comprises a high-elasticity intelligent transmission conductor body and a low-noise light amplification system, and a multi-source data real-time fusion and intelligent processing method is used in the multi-source spatio-temporal data fusion signal processing system. The high-elasticity intelligent power transmission conductor body is a heat-resistant aluminum alloy stranded wire; the high-elasticity intelligent power transmission conductor body is combined with an optical fiber sensing technology and a meteorological technology to form a point, line and surface combined low-cost wide-area multi-element sensing technology, and a signal processing technology for mining wind dance characteristic parameters by virtue of a deep network and realizing multi-source spatio-temporal data fusion by virtue of big data association analysis is adopted, so that the understanding degree of field monitoring data is improved; the value of the multi-element sensing big data is excavated, and objective scientific basis and theoretical basis are provided for safe operation, efficient management and intelligent decision making of the ultra / extra-high voltage transmission line. The device is good in stability, large in bearing current, high in safety, low in cost and capable of reducing carbon emission, and has remarkable economic benefits and social benefits.

The invention relates to the technical field of motor control, and discloses a low-noise flux linkage adaptive feedback control system of a high-speed motor. The system comprises an acquisition module used for acquiring current, voltage and vibration data of a high-speed motor at various operation rotating speeds to obtain operation parameters and noise characteristic data of the high-speed motor; the transformation processing module is used for performing frequency domain orthogonal transformation processing on the operation parameters and the noise characteristic data of the high-speed motor to obtain flux linkage real-time observation data; the self-adaptive analysis module is used for executing multi-mode working condition self-adaptive analysis according to the flux linkage real-time observation data and generating flux linkage control reference values of different rotating speed intervals; and the output module is used for inputting the flux linkage control reference values of different rotating speed intervals into a magnetic-machine coupling control algorithm, and calculating and outputting a motor low-noise driving control signal. According to the method, the problem of magnetic flux path distortion under high-speed operation is effectively solved, and downtime and efficiency loss caused by a traditional off-line calibration method can be avoided.

The invention relates to the technical field of microscopic biological observation, in particular to a microscopic biological observation method based on a digital microscope. Firstly, original point cloud of a sample area on an objective table is obtained through structured light scanning, noise points are removed, point cloud density is optimized by adjusting scanning intensity for multiple times, high-precision and low-noise preprocessed point cloud is generated, then a reference plane is fitted in combination with the structured light point cloud, and obstacle and non-obstacle features are extracted. Detecting a second center coordinate of the bounding box by using a YOLO model, obtaining a third center coordinate through Hough circle detection, generating a standard coordinate by fusing multi-source coordinates, generating a global path based on a grid map and an RRT algorithm, predicting a track in real time, calculating a minimum Euclidean distance with an obstacle, dynamically inserting a B spline transit point to avoid a dangerous area, and ensuring a safe distance. Finally, collecting sample images in real time along the path and extracting microorganism characteristics; the technical problem that the efficiency is low when a traditional microscope is used for acquiring a microorganism image in a sample is solved.

The invention relates to the technical field of remote monitoring, in particular to a wireless electrocardiograph monitor based on the Internet of Things and a data sharing method. A lead signal sequence is collected, window variance and adjacent difference slope are evaluated to exceed a threshold value to generate a trigger instruction, a low-noise channel packaging data packet is called to monitor time delay and interrupt to generate a parameter set, and the parameter set is sent to a server; and extracting interrupt over-limit interface detection impedance to trigger port switching to generate a connection state, and counting a link stability period comparison threshold value to restart a channel. By calculating the time window variance and the differential slope mean value of the electrocardiosignal in real time, comparing with a preset threshold value, accurately identifying abnormity, reducing abrupt change detection delay, dynamically screening low-interference channels based on channel noise, optimizing a transmission path in combination with data priority classification and transmission interruption statistics, reducing the influence of environmental fluctuation on the waveform, and improving the detection accuracy of the electrocardiosignal. Physical lead switching is triggered through wire harness impedance detection, a double-link redundancy architecture is constructed, and the risk of single-link failure is avoided.

The present invention relates to the technical field of noise reduction of charging piles, and specifically provides a noise reduction method and device for a charging pile, the method comprising: obtaining the local time and the temperature of the charging pile power module, the module fan speed and the number of operations when the charging pile is running; calculating the final target value of the fan speed of the charging pile system, and adjusting the speed of the system fan according to it; turning on the ANC active noise reduction mode when the local time, the temperature of the power module or the number of operations meet the noise reduction conditions; turning off the ANC active noise reduction mode when the fault code of any power module is obtained, and adjusting the speed of the system fan according to the fault code; obtaining noise parameters and environmental parameters when performing ANC active noise reduction, and inputting them into a trained neural network to output the noise reduction data of the ANC active noise reduction mode, and adjusting the ANC active noise reduction mode accordingly. Thus, the noise during the operation of the charging pile can be effectively reduced, the noise reduction effect can be improved, and the noise reduction cost can be kept low.

The invention discloses a noise elimination circuit structure, a low noise amplifier, a chip and electronic equipment. The noise elimination circuit structure comprises an input matching network; a common source stage amplification path connected with the first differential output end of the input matching network, comprising a first common source stage differential amplifier, and outputting an amplified first signal inverted from the radio frequency input signal to the ground; the common-gate amplification path is connected with the second differential output end of the input matching network, comprises a first common-gate differential amplifier and outputs an amplified second signal which is opposite to the radio frequency input signal to the ground; and the output end of the common-source amplification path and the output end of the common-gate amplification path are connected in parallel to form the output end of the noise elimination circuit structure. The common-source amplification path and the common-gate amplification path required by the noise elimination structure are realized by using one amplifier path, the utilization rate of the layout area is improved, the compactness of the layout is realized, and the amplifier can be widely applied to the field of communication or radar.