1151 results about "Noise elimination" patented technology

The invention provides a power grid fault waveform identification and intelligent relay protection rapid control method and system, and relates to the technical field of electric power, and the method comprises the steps: collecting the voltage and current waveform data of a power grid, carrying out the digital filtering and noise elimination processing, carrying out the Fourier transform and wavelet transform, extracting the time domain and frequency domain features, and constructing a combined feature vector. And a deep learning model including a convolutional neural network and a long-short-term memory network is used to identify and evaluate the type, position and amplitude of the power grid fault based on the feature vector database. And then, a multi-target particle swarm optimization algorithm for constructing a target weight matrix based on historical fault data is adopted to optimize fault isolation time, a power supply recovery rate and system stability to obtain a control strategy, and a relay protection device setting value is adjusted according to the control strategy to execute fault isolation and power grid topology reconstruction.

The invention relates to a three-dimensional reconstruction method based on a visual odometer and deep learning. The method comprises the following steps: obtaining related parameters of a monocular camera through camera calibration; shooting continuous image frames of the target area under the plurality of camera poses through the monocular camera to obtain image frames of the target area after distortion correction under the plurality of camera poses; estimating relative poses of the camera among different image frames by using a visual odometer according to related parameters of the monocular camera; constructing a cost body of the image frame by using a cost body generation model according to the relative pose of the camera; optimizing the cost body generation model by using the geometric consistency loss and the depth consistency loss, and generating a depth map of the image frame through the optimized cost body generation model; performing noise elimination and hole filling on the depth map of the image frame to obtain an optimized three-dimensional map; according to the method, a stable reconstruction effect can be kept in a complex environment, a low-texture region and a scene with a large visual angle span, and compared with an existing single deep learning reconstruction method, the method has higher robustness and reconstruction precision.

The invention relates to the technical field of acoustics, in particular to a manufacturing method of an acoustic liner structure and the acoustic liner structure. The acoustic lining structure comprises a first panel, an embedded tube plate, a surrounding wall structure and a second panel which are sequentially arranged in the thickness direction of the acoustic lining structure, the embedded tube plate and the first panel are matched to form a plurality of embedded tubes, the second panel is a through hole panel, and therefore the first panel, the embedded tube plate, the surrounding wall structure and the second panel are matched to form a plurality of acoustic elements. Each acoustic element is provided with a plurality of Helmholtz cavities arranged side by side, the spaced Helmholtz cavities are communicated through embedded pipes to form an element, other Helmholtz cavities which are communicated through or not through the embedded pipes form another element, and the silencing capacity of the acoustic liner structure can be enhanced through the strong coupling effect and the weak coherent coupling effect in different acoustic elements. According to the acoustic liner structure and the manufacturing method thereof, under the condition that the thickness of the acoustic liner structure is limited, the low-frequency, broadband and efficient noise elimination characteristics can be achieved, the manufacturing process is clear, and operability is high.

The invention relates to the technical field of pipeline noise elimination, in particular to a precision filter sealing performance detection method and device.The method comprises the steps that in the pressurization and pressure maintaining process of different temperature grades, air pressure is collected, and the real air pressure sequence, the standard air pressure sequence, the pressurization time period and the pressure maintaining time period of the same temperature grade are determined; determining the temperature influence degree of the precision filter; leakage sub-time periods are divided from the pressurization time period and the pressure maintaining time period, and the intermittent leakage degree corresponding to the same temperature grade is determined according to the duration of all the leakage sub-time periods divided according to the same temperature grade and the duration of the pressurization time period and the duration of the pressure maintaining time period; and combining the difference between all the temperature grades and the actual temperature for detecting the sealing performance of the precision filter and the temperature influence degree of the precision filter to finish the sealing performance detection of the precision filter. The precision filter sealing performance detection accuracy can be improved.

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.

The invention discloses a pipeline high-frequency silencer based on acoustic mode modulation and a perforated pipe. The pipeline high-frequency silencer comprises a shell, and the interior of the shell is connected with a cylindrical inner pipe through a plurality of partition plates; the partition plates are parallel to the axial direction of the inner pipe and evenly arranged in the circumferential direction of the inner pipe. The partition plates divide an annular cavity formed between the shell and the inner pipe into a plurality of sub-cavities of the same size. Flanges are connected to two ends of the shell. The invention further discloses a design method of the pipeline high-frequency silencer based on acoustic mode modulation and the perforated pipe. The design method comprises a perforated design method of the inner layer of the shell and / or the inner layer of the inner pipe and a design method of the partition plate. According to the pipeline high-frequency silencer based on acoustic mode modulation and the perforated pipe, the problem that in the prior art, a sound absorption material which is prone to losing efficacy and harms human health is used for achieving high-frequency noise suppression is solved. High-frequency noise elimination is achieved through the partition plate and the perforated pipe, the structure is simple, and disassembly and replacement are convenient.

The invention relates to the technical field of water quality monitoring and analysis, in particular to an intelligent Agent collaborative decision-making system oriented to environment monitoring. Comprising the steps that original data including water quality parameters and environment data are collected in real time; performing noise elimination, missing value filling and standardization processing on the collected original data, and outputting preprocessed data; the method comprises the following steps: integrating multi-source data including historical monitoring data, pollution source information and treatment cases, performing vectorization coding on the multi-source data by adopting a BERT model, and constructing a retrieval architecture based on hierarchical indexes and inverted indexes of a hierarchical navigable small world to obtain a dynamic water quality knowledge base; and on the basis of a retrieval enhancement generation technology, associating the preprocessed data with the dynamic water quality knowledge base, predicting a water quality change trend through a time sequence prediction model, and generating an abnormality diagnosis report and a closed-loop treatment scheme. According to the invention, analysis and early warning of water quality are realized through collaborative decision-making of the intelligent Agent.

The invention discloses a building live-action three-dimensional reconstruction system based on point cloud data, and relates to the technical field of building live-action three-dimensional reconstruction, the building live-action three-dimensional reconstruction system comprises a preprocessing module, a multistage adaptive noise filtering module, a semantic and geometric joint reasoning module and a three-dimensional model generation module which are connected in sequence; the preprocessing module is used for receiving original building point cloud data, performing registration and initial space division, and outputting a registered point cloud data set. According to the building live-action three-dimensional reconstruction system based on the point cloud data, by introducing a multi-stage adaptive noise filtering and semantic geometry joint reasoning cooperation mechanism, the contradiction that noise elimination is inaccurate and feature details are easy to lose in a complex building scene in an existing method is effectively solved. The system can intelligently distinguish the real discrete noise from the inherent complex geometric features of the building, and maintains the integrity of the details such as decorative members and curved roofs to the greatest extent while ensuring the denoising effect, thereby achieving the high-fidelity point cloud data preprocessing.

The invention relates to the technical field of fracturing wellhead pressure prediction, and discloses a fracturing wellhead pressure real-time prediction method and system, and the method comprises the following steps: collection processing: collecting multi-field data in a fracturing wellhead fracturing process, and carrying out noise elimination and time-space alignment to obtain a standardized time series data set; parameter identification: based on the standardized time series data set, calculating fracture fractal dimensions, fractional order parameters, temperature-sensitive viscosity and random disturbance intensity in the fracturing process by analyzing fracture fractal features and a multi-field coupling relationship to obtain multi-field parameters; and model construction: constructing a physical model fusing fractional order characteristics and random disturbance based on the multi-field parameters. The method comprises the following steps: acquiring and processing multi-field data to obtain a standardized time series data set, extracting multi-field parameters, constructing a physical model fusing fractional order characteristics and random disturbance based on the multi-field parameters, solving by combining fracture expansion constraint conditions, and carrying out weighted fusion on pressure and residual errors of the physical model.

The invention discloses a sliding rail moving type bus duct structure, and relates to the technical field of bus ducts. Comprising a protection shell, a sliding cover, a wire row and a fixed protection assembly, heat generated by the wire row is transmitted to a self-adaptive baffle through a conduction vibration buffering piece, the self-adaptive baffle generates corresponding bending deformation according to the magnitude of the absorbed heat, and therefore a gap of the corresponding size is generated in a heat dissipation opening, and the purpose of self-adaptive heat dissipation according to the temperature is achieved. The fixing frame is used for fixing a wire row, vibration is transmitted to the conduction shock absorber, part of vibration is absorbed through deformation of the arc-shaped spring piece, the vibration is reduced, the transmission plate is used for driving the damping sliding block to slide in the sliding groove of the protection shell in a reciprocating mode, and friction force generated between the damping sliding block and the damping piece resists movement of the damping sliding block. The vibration amplitude of the damping sliding block is weakened, so that the damping sliding block tends to be static more quickly, vibration of the wire row is converted quickly, and the purposes of vibration reduction and noise elimination are achieved.

The invention relates to the technical field of insulation monitoring, and discloses a pipeline insulation monitoring system and method based on a wireless passive sensor, and the system comprises a sensor assembly which comprises a wireless passive electromagnetic sensor; the processing unit collects a reflected signal set for noise elimination; the judgment unit compares the reflected signal set after noise elimination with a standard signal range to judge the signal type; when the suspected abnormal signal is determined, grouping the reflected signal set to determine whether the reflected signal set is an abnormal signal; when the signal is judged to be the abnormal signal, identifying unit abnormal data, and determining whether the characteristic vector judges whether the abnormal data is the same defect or not; and the early warning unit determines a defect weight according to an identification result and determines a pipeline insulation monitoring result. According to the invention, the efficiency of pipeline insulation monitoring is improved, the risks of manual intervention and misjudgment are reduced, and the safe operation of the pipeline is ensured.

The invention provides a noise elimination structure, a compressor and an air conditioner, the noise elimination structure comprises a first noise elimination component which is detachably arranged on a mounting base, and at least part of the first noise elimination component is used for defining a first cavity; at least part of the second silencing component is arranged on the first silencing component in a sleeving mode, and a second cavity is formed by the second silencing component and at least part of the outer wall face of the first silencing component; wherein at least part of the first silencing part is provided with a plurality of silencing holes, so that the first cavity and the second cavity are communicated through the silencing holes, the silencing frequency band of the first cavity is different from that of the second cavity, the first cavity is communicated with the air outlet of the mounting base, and the second cavity is communicated with the air outlet of the mounting base. At least part of gas flowing out of the mounting foundation flows to the first cavity, the silencing holes and the second cavity for vibration reduction; the problems that in the prior art, compressor micro-perforation can only reduce noise in the same frequency band, and full-frequency-band noise control from low frequency to high frequency cannot be effectively achieved are solved.

The invention relates to a 60KW energy storage equipment energy-saving ventilation and noise reduction structure capable of being efficiently and rapidly assembled. The 60KW energy storage equipment energy-saving ventilation and noise reduction structure comprises a ventilation static pressure structure, an air inlet noise elimination structure, an air exhaust noise elimination structure, arc-shaped noise elimination blades, an insertion type noise elimination module, an anti-bird net and a rapidly-assembled hanging type hinge structure. The ventilation static pressure structure homogenizes airflow through the static pressure cavity, reduces resistance and improves ventilation efficiency; according to the air inlet and exhaust noise elimination structure, noise is effectively absorbed through trapezoidal noise elimination pieces and arc-shaped noise elimination blades, and comprehensive noise reduction of low-frequency and medium-high-frequency noise is achieved by combining inclined design of the noise elimination pieces with optimization of the punching rate. The plug-in noise elimination module adopts a modular design, so that quick disassembly, assembly and maintenance are facilitated; the anti-bird net enhances the outdoor adaptability of the equipment and prevents small animals from invading. By optimizing the structural design, the device has remarkable advantages in the aspects of reducing equipment noise, improving ventilation efficiency and facilitating maintenance, and is suitable for various scenes such as industrial, commercial energy storage and civil energy storage equipment.

The invention relates to the technical field of aluminum alloy part casting processes, in particular to a multi-parameter collaborative optimization system and method for a new energy aluminum alloy part casting process. According to the technical scheme, the multi-parameter collaborative optimization system for the new energy aluminum alloy part casting process comprises a multivariate heterogeneous data acquisition module, a multi-physics field coupling optimization module, an intelligent execution control module, a virtual-real fusion verification module and a man-machine collaborative decision module; by deploying the melt state monitoring unit, the mold dynamic thermal field sensing unit and the equipment health monitoring unit, all-around and high-precision monitoring of melt, mold and equipment states is realized, and meanwhile, space-time alignment and noise elimination are performed on multi-source data through a Kalman filtering algorithm; and generating a characteristic matrix containing a melt fluidity index, a mold temperature gradient field and an equipment health state, and providing a high-quality data basis for subsequent optimization.

The invention provides a radon gas detection method and device, electronic equipment and a storage medium. The method comprises the following steps: collecting a plurality of first electric signals from electric signals flowing through a comparator according to a preset time interval in a target time range; in response to the received interrupt signal from the comparator, determining a second electric signal corresponding to the occurrence moment of the interrupt signal from the plurality of first electric signals; determining a first noise value according to the plurality of third electric signals; the first range value is compensated according to the first noise value, a second range value is determined, the first range value is used for representing a signal peak range of particles corresponding to radon in a noise elimination state, and the plurality of third electric signals are signals different from the second electric signals in the plurality of first electric signals; determining a fourth electric signal whose signal peak value satisfies a second range value from the second electric signals; and determining the concentration value of the radon gas according to the number of the fourth electric signals. The accuracy of radon gas concentration detection can be improved.

The invention relates to an electrical equipment room environment humidity control method and system based on difference comparison. The method comprises the following steps: acquiring original humidity signal data through a humidity sensing array, and performing noise elimination processing to obtain humidity data; calculating a humidity change rate based on the humidity data, comparing the humidity change rate with a preset threshold value, and evaluating the environmental humidity complexity; establishing an equipment humidity demand evaluation model and generating an equipment humidity demand matrix in combination with the physical position, the humidity demand and the environmental humidity complexity of the electrical equipment; based on the matrix, fusing environment state parameters and equipment operation state parameters, and calculating a target comprehensive humidity value by adopting a dynamic weight distribution method; the deviation between the target comprehensive humidity value and the actual humidity data is calculated through a feedback control algorithm, and a humidity control instruction is generated to drive humidity adjusting equipment to execute operation. According to the method, through multi-dimensional parameter fusion and dynamic weight distribution, the accuracy and adaptability of humidity control in a complex environment are improved.

The invention provides a mitral valve regurgitation severity assessment method based on PCG signals, which comprises the following steps: firstly, synchronously acquiring signals from a heart sound area and an environmental background by adopting a dual-channel audio acquisition technology, eliminating environmental noise and operation interference (such as clothes friction and non-uniform pressing force of a stethoscope) through a self-adaptive noise elimination algorithm, and calculating the severity of the mitral valve regurgitation severity; and carrying out segmentation processing on continuous heart sound signals of the de-noised heart sound by adopting a dynamic time window segmentation strategy to generate short-time heart sound fragments, evaluating the quality of the short-time heart sound fragments in real time by using a model based on a lightweight convolutional neural network, and filtering low-quality fragments. Then, nonlinear features are directly extracted from the short-time heart sound fragments through a deep neural network model based on a clique block, after each effective fragment is subjected to four classifications, classification results of all the fragments are integrated through a majority voting mechanism, and final mitral valve regurgitation severity judgment is generated. The classification robustness is effectively improved through multi-fragment information fusion, and the random error of single-fragment analysis is reduced.

The invention discloses an induction heating path optimization method suitable for a heterogeneous noise elimination structure, and particularly relates to the field of induction heating path optimization of the heterogeneous noise elimination structure, and the method comprises the steps: building a grid coordinate in a target region, collecting the heat conductivity coefficient, the specific heat capacity, the thermal resistance value and the induction coil gap value of each grid node in the grid coordinate, generating a thermal response model; and performing heat conduction calculation on the thermal response model and a preset heating power curve, calculating a temperature rise value of each grid node in a fixed preset heating time, marking the grid nodes of which the temperature rise values reach or exceed a safe temperature threshold and the adjacent grid nodes as heat concentration areas, and generating risk area data after gathering the heat concentration areas. A risk assessment and dynamic reordering mechanism based on local thermal characteristic difference is introduced in a heating path planning process, so that advanced identification and real-time avoidance of a heat concentration area are realized.

The invention belongs to the technical field of turbofan engine silencing acoustic liner design, and particularly relates to a turbofan engine silencing acoustic liner acoustic impedance determination method comprising the following steps: 1, calculating silencing acoustic liner acoustic resistance rn influenced by high sound intensity; 2, calculating the acoustic resistance rg of the silencing acoustic liner influenced by the tangential flow; 3, considering the influence of high sound intensity and tangential flow, and according to the relative magnitude of the sound particle speed amplitude Vo and the main flow speed Vg in the small hole, calculating the sound resistance r of the sound reduction acoustic liner in a segmented manner; 4, calculating a noise reduction acoustic liner tail end correction coefficient delta under the comprehensive influence of tangential flow and high sound intensity; step 5, considering the comprehensive influence of tangential flow and high sound intensity, and calculating the acoustic reactance x of the silencing acoustic liner; and step 6, integrating the acoustic resistance r and the acoustic resistance x of the silencing acoustic liner, and calculating the acoustic resistance z of the silencing acoustic liner.

A method for reducing voice noise, including: acquiring an algorithm activity detection result corresponding to a current audio frame to be processed by detecting the current audio frame using a predetermined voice activity detection algorithm; acquiring a target activity detection result corresponding to the current audio frame by merging a model activity detection result corresponding to a previous audio frame and the algorithm activity detection result corresponding to the current audio frame, wherein the model activity detection result is outputted by a predetermined voice noise reduction network model; acquiring an initial noise reduction audio frame by performing, based on the target activity detection result, noise estimation and noise elimination on the current audio frame; and outputting a target noise reduction audio frame and a model activity detection result corresponding to the current audio frame by inputting the initial noise reduction audio frame into the predetermined voice noise reduction network model.

The invention discloses a system for eliminating fading noise in a distributed optical fiber sound wave sensing system. The system comprises a light source, an optical frequency shift modulator, an optical amplifier, an optical circulator, a photoelectric detector, a data acquisition card and a data demodulator, laser emitted by the light source is modulated into double-pulse light with frequency difference through the light frequency shift modulator, the double-pulse light is injected into the optical fiber through the optical circulator after being amplified by the optical amplifier, Rayleigh backscattered light generated in the optical fiber is emitted back to the optical circulator, light emitted by the optical circulator is detected and converted into an electric signal through the photoelectric detector, and the electric signal is transmitted to the optical fiber through the optical circulator. The electric signals are collected and converted into digital signals through the data collection card, and the data demodulator demodulates the digital signals through a fading noise elimination method to obtain signals with fading noise eliminated. Therefore, fading noise in the distributed optical fiber acoustic wave sensing system can be effectively eliminated, the signal quality is improved, and error signal interference is eliminated.

The present application relates to pipeline system damping and noise reduction technical field, provide a kind of active noise cancellation pressure relief valve, comprising: valve body, with the liquid inlet cavity and pressure relief cavity being communicated are formed;Bypass pipe, with liquid inlet cavity is communicated;Piezoelectric actuator and pressure relief component, pressure relief component includes adjusting piece, pressure relief elastic piece and pressure relief valve core, pressure relief valve core and pressure relief elastic piece are set in pressure relief cavity, adjusting piece is movably arranged on valve body, piezoelectric actuator is arranged on adjusting piece, pressure relief elastic piece is pressed between piezoelectric actuator and pressure relief valve core;Piezoelectric actuator is configured to drive pressure relief elastic piece, to eliminate the transient noise caused by pulsating pressure when pressure relief valve core moves.The active noise cancellation pressure relief valve provided by the present application introduces active noise cancellation technology into the active noise cancellation pressure relief valve pulsating noise control by arranging piezoelectric actuator, can be adjusted by pressure relief elastic piece The force exerted on the pressure relief valve core can eliminate the transient noise caused by pulsating pressure when the pressure relief valve core moves.

The invention provides a control method and a control system for building an independent acoustic space of an automobile cabin, which are applied to the technical field of sound field control of the automobile cabin, and are used for inputting a multi-channel vibration signal acquired in real time into a deep learning noise prediction model to obtain an in-automobile background noise prediction value at a future moment; the prediction noise is filtered by the secondary path estimation model and then is used as a feedforward reference signal for active noise reduction, and the prediction noise and a residual signal collected by a bright area error microphone are jointly used for weight updating of an adaptive filter; the updated filter generates a reverse-phase noise elimination signal and the reverse-phase noise elimination signal is played by a secondary loudspeaker in real time so as to counteract background noise of the bright area; and closed-loop adjustment of the noise reduction effect is formed based on the sound pressure level contrast ratio of the bright and dark areas, so that the independent acoustic space is kept stable in the time-varying environment of vehicle driving. According to the method, the low noise of the bright area and the isolated sound field of the dark area in the vehicle are realized by fusing deep learning noise prediction and active noise control, and the personalized auditory experience in the vehicle can be remarkably improved.

The present invention belongs to the technical field of VAV air systems, and specifically relates to an active silencing VAV air system that ensures the NC index of an indoor environment, including a main body component, the inner cavity of which is connected to a circulation component; a circulation component, the circulation component includes a fan component, the inner cavity of which is provided with a regulating component; a diversion component, the diversion component includes a driving component arranged in the inner cavity of the main body component, the bottom of the driving component is connected to a pipeline component; a noise reduction component, the noise reduction component is arranged in the inner cavity of the main body component. The invention can adjust the angle of the fan component blades when the air flow rate changes, thereby reducing the noise generated by the contact and friction between the blades and the air, and can also divert the air into three parts, thereby weakening the air flow rate, and blowing the air out evenly, improving comfort and stability, and can monitor the frequency of the noise when the device is running, and generate reverse sound waves to offset the noise, actively reducing the noise emitted by the device operation.

The invention relates to the technical field of exhaust and noise elimination, and discloses a wind power cabin exhaust silencer which comprises an exhaust pipe and a noise elimination pipe which are communicated with each other, an exhaust fan for driving gas to move towards the noise elimination pipe is arranged in the exhaust pipe, and multiple sets of sound absorption assemblies rotating synchronously are arranged in the noise elimination pipe. A gap for air to flow is formed between every two adjacent sound absorption assemblies, and an acute included angle is formed between the plane of each sound absorption assembly and the airflow direction; the sound absorption assembly comprises a first rotating frame and a second rotating frame which are sequentially arranged in the airflow direction and hinged to each other, and sound absorption plates are arranged on the side faces, making contact with airflow, of the first rotating frame and the second rotating frame. According to the silencer, by arranging the included angle adjusting assembly, the included angle between the first rotating frame and the second rotating frame in the silencing pipe is dynamically adjusted, linkage control is conducted on the included angle and the rotating speed of the exhaust fan, and the silencing performance of the silencer can be adaptively optimized according to the actual thermal load of a wind power cabin.

The invention relates to the technical field of pipeline noise elimination, in particular to a pipeline elbow noise reduction device which comprises a connecting elbow, an inner silencer is embedded in a bend of an inner cavity of the connecting elbow, a cavity exists between the inner silencer and the inner wall of the connecting elbow, and a neck bush is arranged between the inner silencer and the inner cavity of the connecting elbow. The inner silencer comprises an inflow part, an inward shrinkage part, a flow guide part and a discharge part which are integrally formed through flexible rubber, the inner diameters of the inflow part, the inward shrinkage part, the flow guide part and the discharge part are smoothly and gradually changed in the flow direction, and the outer wall of the inner silencer and the inner wall of the neck bush are seamlessly attached together. The silencer has the beneficial effects that the gradual change section design of the inner silencer maintains a laminar flow boundary layer through continuous curvature change, and flow separation is effectively reduced; the spiral flow guide fins are used for disassembling macroscopic vortex into micro-scale turbulent flow, so that energy dissipation is accelerated, and medium-high frequency noise is improved in a targeted manner; the sound absorption part is filled with an efficient sound absorption material, and a complementary silencing mechanism is formed with flow field optimization.

The utility model discloses a torsion detection device for an electromagnetic brake. The torsion detection device comprises a workbench, a mounting seat, a transmission push cylinder, a clamp holder, a mounting frame, a detector and a sound insulation device, the sound insulation device is arranged, and the transmission shaft is driven to rotate by starting the driver, so that the transmission shaft can drive the sound insulation cover to rotate towards the top of the mounting seat, and the top of the mounting seat is shielded and covered; the sound insulation device is arranged in the sound insulation cover, the sound insulation cover is matched with the sound insulation pad arranged in the sound insulation cover to block and eliminate noise generated during testing, so that the noise can be quickly dissipated, the harm of the noise is reduced, and abnormal sound and noise generated in the testing process are isolated by arranging the sound insulation device; therefore, the problems that in original equipment, due to the fact that an electromagnetic brake makes contact with a direct fixing assembly, when the electromagnetic brake outputs power, the electromagnetic brake easily shakes, the electromagnetic brake slightly collides with the fixing assembly, and abnormal sound is caused are solved.

The invention provides a high-precision low-delay successive approximation analog-to-digital converter based on sampling noise elimination, and the analog-to-digital converter comprises a main capacitor group which generates an original combined signal according to an original sampling signal and primary sampling noise in a secondary sampling stage; the pre-quantization capacitor bank is used for driving a bottom plate switch of the pre-quantization capacitor bank according to the detection control signal, switching a capacitor weight through a weight control signal to execute pre-quantization operation on the original combined signal and outputting a swing suppression signal; the novel sampling noise elimination module is used for receiving the swing suppression signal, performing gain amplification, generating a purification amplification signal, detecting the differential swing of the original combined signal in real time, and generating a detection control signal and a pre-quantization code according to the differential swing; the successive approximation quantization module is used for generating a main quantization code and a weight control signal according to the purification and amplification signal in a quantization stage; and the digital processing module is used for fusing the pre-quantized code and the main quantized code to obtain a final digital code. And the energy efficiency and the conversion precision of analog signal conversion are obviously improved.

The invention discloses a landslide disaster early warning method based on an LSTM-SARIMA mixed data driving model. Global and local noise elimination is performed on radar displacement monitoring data by adopting a two-stage noise reduction method combining moving average and wavelet transform, so that the signal-to-noise ratio is effectively improved; the method comprises the following steps: decomposing slope displacement data into a trend term dominated by gravity and a periodic term influenced by the environment by utilizing a Hodry-Precott (HP) filtering method, and realizing differentiated analysis of a multi-factor action mechanism; a mixed prediction model combining a long short-term memory network (LSTM) and a seasonal autoregressive integrated moving average model (SARIMA) is provided, modeling and prediction are carried out on decomposed displacement components respectively, and results are fused to obtain a high-precision total displacement prediction value; an improved T-t curve is constructed based on a predicted displacement-time curve, a tangent angle index for landslide early warning is proposed according to a Saito three-stage theory, and quantitative and interpretable early warning criterion setting is realized.

The invention discloses a design method of an array type silencer adaptive to a main ventilation air path between a stator iron core of a hydraulic generator and an air cooler and the array type silencer, and relates to the technical field of suppression or reduction of noise of the hydraulic generator. The method comprises the steps of S1, obtaining aerodynamic noise data and airflow parameters of a main ventilation air path, S2, determining a silencing thought and a micro-perforated plate array core structure according to broadband vortex, discrete rotation, vortex falling and surge noise, S3, determining the boundary dimension and preliminarily calculating the airflow parameters, S4, designing plate parameters in combination with a micro-perforated resonance formula, and S5, calculating the noise of the micro-perforated plate array. S5, performing simulation optimization and S6, accurately accounting airflow parameters, and locking a scheme meeting requirements; the silencer comprises a shell and a plurality of micro-perforated plates, and the multiple layers of micro-perforated plates are arranged in series. The invention has the advantages of no sound absorption material, low wind resistance (the air volume attenuation is less than or equal to 5%, and the pressure loss is less than or equal to 200Pa), the noise of the main wind path is reduced by 5-7dB (A), the service life is long, the operation and maintenance cost is low, and the requirements of the main wind path are met.