555 results about "Electromagnetic noise" patented technology

The invention relates to the field of excavation equipment obstacle avoidance based on image analysis, in particular to a coal mine excavation equipment obstacle avoidance method and system based on machine vision, and the method comprises the steps: obtaining the frequency domain characteristic parameters of the current electromagnetic noise during the operation of underground electromechanical equipment, and synchronously collecting the current original image frame output by a visual sensor; after a current de-noised image frame is obtained after dynamic de-noising processing, an obstacle contour feature point set is extracted through multi-scale edge detection, and an obstacle position confidence map is obtained according to space-time consistency analysis; obtaining point cloud coordinates of an image data loss area caused by electromagnetic interference, and mapping the point cloud coordinates to an image coordinate system to obtain a three-dimensional geometric complemented image; and constructing a dynamic occupation grid map of the underground environment according to the three-dimensional geometric complementation image and the obstacle position confidence map, and planning an obstacle avoidance path of the mining equipment according to the dynamic occupation grid map. And the obstacle avoidance capability of the mining equipment is improved, and safe and efficient coal mining operation is guaranteed.

The invention discloses a motor control method and device based on an encoder, a medium and a program product, and relates to the field of motor control, and the method comprises the steps: receiving a position signal and a speed signal outputted by the encoder, and carrying out the filtering processing to obtain an operation state parameter; collecting mechanical vibration and electromagnetic noise generated in the operation process of the motor to obtain acoustic parameters of the motor, and extracting frequency characteristic parameters representing the rotating speed and motion characteristics of the motor; performing data fusion on the operation state parameters and the frequency characteristic parameters according to a preset weight to generate an operation state model; the operation state model is compared with a standard motion trail, and the position deviation value and the speed deviation value of the actual motion trail of the motor are calculated; and calculating a compensation control quantity according to the position deviation value and the speed deviation value, converting the compensation control quantity into a driving signal and outputting the driving signal to a motor driver so as to drive a motor to perform operation adjustment. According to the invention, the control precision of the motor in actual operation can be improved.

The invention provides an electromagnetic compatibility test method and system for PCB design, a PCB comprises a schematic circuit diagram and a structural model, and the method comprises the following steps: extracting high-frequency signal characteristics in the schematic circuit diagram to obtain an electromagnetic simulation parameter set; performing multi-physical field coupling modeling according to the electromagnetic simulation parameter set and the structure model to obtain an electromagnetic field-circuit model; performing frequency-time domain hybrid excitation loading on the electromagnetic field-circuit model to obtain an electromagnetic noise distribution diagram; performing gradient descent optimization on layout parameters of the structure model according to the electromagnetic noise distribution diagram to obtain an anti-interference layout scheme; and performing multi-working-condition Monte Carlo simulation and residual error calibration on the anti-interference layout scheme to generate a correction guidance library.

The invention provides a magnetic suspension motor control method and device and a magnetic suspension motor, and relates to the technical field of magnetic suspension motor control, and the technical scheme is characterized in that the method comprises the steps: detecting the voltage change rate of a power grid, and judging a voltage fluctuation mode based on a preset threshold value; environment RFID tag information is read through a scene code analysis unit, and a current scene code is obtained; retrieving a maximum compensation current value, a current change rate threshold value and a PID integral time constant from a preset parameter matrix based on the voltage fluctuation mode and the scene code; and limiting the current change rate of the motor winding according to the current change rate threshold, and executing motor control through the maximum compensation current value and the PID integral time constant. The magnetic suspension motor control method and device and the magnetic suspension motor provided by the invention have the advantages of improving the operation stability of the motor in voltage fluctuation and multi-noise scenes, suppressing electromagnetic noise and adapting to different scenes.

The invention relates to a time-varying power high-precision calculation technology of an electric drive system under strong electromagnetic noise interference, and mainly solves the problem of inaccurate power calculation of the electric drive system under strong electromagnetic environment noise and frequency time-varying fluctuation scenes. According to the core technology, a dominant frequency fluctuation curve of a signal is obtained through dynamic tracking of a dominant frequency, and a dynamic band-pass filter changing along with the dominant frequency of the electric drive system is constructed; suppressing pulse noise by combining amplitude self-adaptive filtering of a nonlinear weighting function; a phase demodulation technology fusing zero crossing point correction and Hilbert transform is adopted to eliminate the phase interference problem caused by complex waveforms and weak noise signals; and finally, establishing a time-varying power physical model based on the sliding window. According to the technology, the power calculation accuracy of the electric driving system under the conditions of strong field environmental noise and continuous main frequency conversion is remarkably improved.

The invention relates to the field of biomedical engineering, and discloses an embedded electroencephalogram signal collecting device and system.The device comprises a power management module, a plurality of electrode assemblies, a control module and a storage and communication module; through a control module designed by a system on chip SoC and a multi-electrode assembly in contact with intracranial nerves, the embedded electroencephalogram signal acquisition device which is in multi-level cooperation, supports user-defined sampling parameters and self-adaptive strategies and meets individual requirements of different focus monitoring scenes is constructed. High-precision distributed acquisition and self-adaptive processing of intracranial electroencephalogram signals are realized; a multi-electrode assembly is adopted, each assembly is provided with a plurality of contacts, the limitation of traditional single-point collection is broken through, different nerve areas are covered through the spatially distributed contact layout, and the focus positioning capacity is improved; the acquisition module effectively eliminates power supply ground wire interference and electromagnetic noise by using a differential amplification and common-mode rejection technology, and eliminates power frequency interference by combining band-pass and notch filtering to ensure the quality of an original signal.

The invention discloses a multi-parameter ultrahigh frequency sensor performance comprehensive evaluation method, which belongs to the technical field of sensor performance evaluation, and effectively breaks through the limitation of the traditional static test on a transient interference response blind area through a dynamic interference field simulation test and an original fidelity-false triggering joint evaluation model. The adaptive adjustment mechanism of the multi-source interference field can vividly simulate the space-time non-uniform characteristic of electromagnetic noise in an industrial field, and in combination with a time-frequency domain composite evaluation algorithm, not only is the signal distortion degree of the sensor in typical interference modes such as frequency sweeping and pulse train quantified, but also the error action acceleration rule caused by high-frequency-band noise coupling is disclosed. The dynamic immunity evaluation capability enables a designer to accurately position the electromagnetic shielding weakness of the sensor, optimizes a front-end filter circuit or a signal processing algorithm in a targeted manner, and remarkably improves the reliability of a product in strong interference scenes such as radar detection and wireless communication.

The invention provides an elevator steel wire rope detection method and device, equipment and a storage medium, and belongs to the technical field of automatic monitoring. The method comprises the steps that electromagnetic signal data in a steel wire rope and vibration signal data of the end of the steel wire rope are obtained; performing feature extraction on the electromagnetic signal data and the vibration signal data to obtain electromagnetic noise features and vibration noise features; performing cross fusion on the electromagnetic noise feature and the vibration noise feature to obtain a first joint noise feature; performing denoising processing on the electromagnetic signal data and the vibration signal data based on the first joint noise feature to obtain denoised electromagnetic signal data and denoised vibration signal data; and performing fault prediction based on the denoised electromagnetic signal data and the denoised vibration signal data to obtain fault information of the steel wire rope. According to the elevator steel wire rope detection method and device, the equipment and the storage medium, the elevator steel wire rope fault detection precision can be improved.

The invention relates to the technical field of ultrasonic detection, in particular to an ultrasonic detection method, system and device for integrated circuit plastic package. The method comprises the following steps: analyzing a distribution suspected index from a distribution position according to a proportion of a suspected defect area in an ultrasonic detection image of each sample and distance distribution of the suspected defect area and a module area, and analyzing an air hole characteristic index from internal distribution similarity in combination with a similar condition of ultrasonic signal fluctuation between pixel points in the area; obtaining a pore defect possible index; and correcting the air hole defect possible indexes by combining the overlapping expression of the suspected defect areas among the plurality of ultrasonic detection images, and obtaining the corrected possible indexes for air hole detection. According to the method, through the similarity characterization degree and the overlapping distribution degree of the defect features in the defect areas among the ultrasonic detection images of the multiple samples, the distinguishing accuracy of the electromagnetic noise and the pore defects is improved, the defect detection is more accurate, and then the optimization reliability of subsequent process parameters is improved.

The invention provides a highway bridge joint vibration and deformation condition monitoring method, and particularly relates to the technical field of bridge structure health monitoring, and the method comprises the steps: laying a fiber bragg grating sensor array at a bridge joint, and the array comprises a plurality of fiber bragg grating sensors which are distributed at intervals along the length direction of the joint; and each sensor is connected with the joint filling body contact surface through a pre-embedded fixing structure. The sensor array collects strain signals and vibration signals in the joint in real time, analog-to-digital conversion and caching are completed through the data collection unit, digital sensing signals are generated and stored, and a historical monitoring data set is constructed. A noise suppression algorithm is adopted to filter the signal, and ambient temperature and humidity and electromagnetic noise interference are eliminated. Features are extracted based on a data fusion algorithm, and crack feature parameters reflecting the seam fine crack expansion trend are generated. A historical monitoring data set and the parameters are combined, a supervised learning model is used for calculating a dynamic adjustment threshold value, a real-time monitoring early warning signal is generated through comparison, and early-stage high-sensitivity monitoring of the seam is achieved.

The invention discloses a ground resistance remote online monitoring method and system based on a mobile terminal, and relates to the technical field of ground resistance monitoring, and the method comprises the steps: obtaining a natural electromagnetic noise signal collected by the mobile terminal through a built-in sensor, and calculating a preliminary estimation value of ground resistance according to a preset model; according to the preliminary estimation value and the environmental parameters, using a machine learning algorithm to predict the optimal sampling frequency and time window under the current monitoring condition, and forming a dynamic adjustment mechanism; based on a dynamic adjustment mechanism, multiple mobile terminals are used for cooperative measurement, position information is synchronized and shared through a wireless network, and a virtual quadrupole measurement topological structure is constructed; based on the virtual quadrupole measurement topological structure, one part of the mobile terminals transmit test signals, the other part of the mobile terminals receive response signals, and the optimal sampling frequency and time window are combined to invert and generate a space resistance distribution diagram of the grounding grid; historical monitoring data, a space resistance distribution diagram and real-time environment parameters are combined.

The invention provides a digital twin unmanned aerial vehicle circuit state monitoring method and system, and the method comprises the steps: firstly collecting a partial discharge pulse sequence of an unmanned aerial vehicle switching power supply circuit, separating environment electromagnetic noise through polarization filtering operation, and extracting real discharge pulses to generate partial discharge fingerprint data; inputting the fingerprint data into a pre-established fault search tree model, judging the type of a capacitor or inductor component through a first-stage branch node, and matching a degradation mode such as capacitance attenuation or magnetic saturation through a second-stage branch node to determine the fault type; then, corresponding component parameters of the equivalent circuit model are dynamically updated in the digital twin body, and the circuit operation state change trend is simulated; and finally, according to the state change trend, predicting the residual effective working time of the fault component and outputting a monitoring result. According to the invention, the accuracy of service life evaluation of key components in a complex electromagnetic environment is improved.

The invention relates to a magnetotelluric noise suppression method based on ResAtt-CAE, and the method comprises the steps: generating a noise-free signal, adding a noise type into the noise-free signal to construct a noisy signal, and enabling the noisy signal to be matched with the corresponding noise-free signal to form a training set and a test set; designing a ResAtt-CAE model architecture, and realizing cross-level feature fusion by adopting a symmetric structure and jump connection; the ResAtt-CAE model architecture is trained and optimized through the training set and the test set, and the magnetotelluric noise is suppressed through the optimized ResAtt-CAE model architecture. The method is high in noise suppression capability: ResAtt-CAE captures cross-time scale signal features through multi-scale residual learning, enhances effective signal weights in combination with a time domain attention mechanism, and has a remarkable suppression effect on common magnetotelluric noise (square waves, harmonic waves, pulses, triangular waves and the like).

The invention discloses a sleep aiding method and system based on brain wave data, and the method comprises the steps: synchronously collecting brain waves, electrocardiosignals, environmental noise and user voice data through a flexible electrode array, constructing a multi-mode causal graph, and dynamically recognizing the type of a noise source (electromagnetic interference or psychological noise); the method comprises the following steps of: generating a target antagonistic intervention signal (such as reverse sound wave counteracting electromagnetic noise and binaural rhythm relieving psychological pressure) according to the target antagonistic intervention signal, generating dynamically adaptive light pulse and tactile vibration parameters in combination with a psychological-physiological collaborative model, and synchronously outputting sound, light and tactile intervention signals through a multi-modal actuator. Through causal reasoning and multi-sensory cooperative regulation and control technologies, accurate inhibition of noise interference and personalized induction of the sleep state are realized, the sleep time is remarkably shortened, the deep sleep duration is prolonged, and the method is particularly suitable for complex noise environments and anxiety-related insomnia scenes.

The invention discloses an urban electromagnetic noise suppression method based on multi-source noise. The method comprises the following steps: 1, suppressing power frequency noise in noise by using a Wavelet-NGSE algorithm; 2, random noise in the noise is suppressed through minimum noise separation; (3) residual random noise in the noise in the step (2.3) is suppressed by using a CNN-GRU model; according to the invention, the noise in the collected transient electromagnetic signals is classified in a refined manner, and each type of noise features are removed. In order to solve the problem of power frequency harmonic noise interference, an accurate fundamental frequency value is extracted through a Wavelet-NGSE algorithm, and the suppression of power frequency noise with high correlation is realized by combining the periodicity of power frequency and adjusting the transmitting frequency and waveform; further suppressing random noise by using superposition average; and finally, the minimum noise separation + CNN-GRU network calculates data components and reconstructs signals after minimum noise separation, so that high-precision residual noise separation is realized, electromagnetic data with a high signal-to-noise ratio is obtained, and a foundation is laid for realizing accurate interpretation of deep signals.

The invention provides an unmanned aerial vehicle control instruction trapping method and system based on a pseudo base station technology. According to the method, firstly, signal parameters and environmental electromagnetic noise characteristics of a real base station are collected, and a dynamic base station analog signal is generated and transmitted, so that the unmanned aerial vehicle initiatively initiates a detection signal; analyzing instruction coding characteristics in the detection signal to reconstruct a trapping control signal with protocol deception, and finally enabling the unmanned aerial vehicle to keep communication connection with the pseudo base station device and continuously transmit control instruction data by adaptively adjusting a protocol field parameter and a transmitting power parameter of the trapping control signal; according to the technical scheme provided by the invention, unmanned aerial vehicle counter-reconnaissance alarm caused by abnormal signal characteristics is thoroughly eliminated, and the concealment and reliability of an instruction trapping process are improved.

The invention belongs to the technical field of short-wave radio station control, and particularly relates to a foreign trade short-wave radio station remote control method based on a WiFi link. According to the method, through multi-round data feedback and strategy optimization, the problems of frequency deviation, insufficient power or overload are automatically corrected, the signal distortion and interruption rate are effectively reduced, the high reliability of a communication link is ensured, and based on real-time calculation of an environment interference coefficient and communication compensation information, the transmitting power can be dynamically improved or a more suitable modulation mode can be switched; therefore, the influence of electromagnetic noise on the signal is reduced, the data transmission quality is ensured, flexible adjustment can be performed according to different communication distances, bandwidth requirements or frequency band limitation through a dynamic control strategy, and the rapid deployment and switching requirements of the foreign trade short-wave radio station in multiple scenes are met.

The invention discloses an electromagnetic noise suppression control method for a multi-phase self-excitation synchronous motor. A driving system of the synchronous motor comprises a double-closed-loop control system and an inverter. The specific method comprises the steps that the double-closed-loop control system outputs voltage reference signals of all coordinate axes, and all the coordinate axes are arranged in an electromechanical energy conversion plane and a non-electromechanical energy conversion plane respectively; injecting the square wave signal into a selected coordinate axis, and cooperatively adjusting excitation and noise values by using the positive correlation between excitation current and the amplitude of the square wave and the negative correlation between the excitation current and the frequency of the square wave; and then outputting the adjusted voltage reference signal, processing the adjusted voltage reference signal and other voltage reference signals, and outputting the processed voltage reference signal and other voltage reference signals to an inverter to generate a driving voltage. Therefore, the square wave amplitude is synchronously increased and the excitation current is kept stable when the noise reduction of the square wave frequency is improved by utilizing the quantitative relation that the excitation current is positively correlated with the square wave amplitude and negatively correlated with the square wave frequency, so that the load capacity of the synchronous motor is prevented from being reduced.

The invention relates to the technical field of sensing, and discloses a capacitive touch screen input event classification and processing system which comprises an input capture module, an event classification module, an intention prediction module, a dynamic response module, an energy efficiency optimization module and a multi-channel cooperation module. When an input event of the capacitive touch screen is identified, a dynamic noise suppression model is established, and adaptive filtering strategies are configured for different use scenes, so that the reliability of signal analysis in various electromagnetic interference environments is ensured, and meanwhile, the spatial and temporal distribution characteristics of capacitance variation are analyzed in real time; real touch operation and environmental electromagnetic noise can be effectively distinguished, the identification fidelity of basic operations such as clicking and sliding is ensured, the false triggering rate is reduced, the operation accuracy in a weak signal scene is improved, and when multi-finger operation is detected, the consistency of contact coordinates in a curved surface state and a plane state is maintained, so that the accuracy of the touch operation is improved. And the track continuity of writing and drawing type fine operation is ensured.

The invention relates to the field of safety detection, and discloses a portable secret-related environment anti-eavesdropping and anti-photo stealing equipment detection device, which comprises a lower shell, an upper shell is mounted on one side of the lower shell, a thermal imaging scanning module is mounted in the middle of the upper shell, wireless detection modules are symmetrically mounted on one side of the upper shell, and the wireless detection modules are mounted on the other side of the upper shell. An endoscopic detection module, a nonlinear node detection module and a vibration spectrum analysis module are sequentially installed on the other side of the upper shell, a lens detection module is installed on the outer wall of the upper shell, handles are installed on the two sides of the lower shell, and a power module is installed at the bottom of the lower shell. The detection data of each sensor is collected in real time through the display control module, the weight of each mode is dynamically adjusted based on the environment change, and when it is detected that the false alarm rate of the wireless detection module is increased due to strong electromagnetic noise, the weight ratio is automatically reduced; and the weight of the nonlinear node detection module or the thermal imaging scanning module with higher anti-interference capability is synchronously improved.

The invention relates to the technical field of electrical sensor measurement, and provides a fault test method, system and equipment suitable for a fan converter, and the method comprises the steps: collecting current data in an IGBT module of the fan converter, and taking the current data as an original current signal; screening a plurality of dominant frequencies of the original current signal; decomposing the original current signal to obtain a plurality of component signals, and corresponding to each dominant frequency to obtain a plurality of dominant frequency signals; screening to obtain a reference signal; according to the variation trend difference between each component signal and the reference signal, the variation abnormity of each component signal is obtained; analyzing the energy difference between each component signal and the reference signal in the time-frequency energy matrix to obtain the energy difference index of each component signal; obtaining an anomaly index of each component signal; and performing fault detection on the fan converter based on the anomaly index of each component signal. The invention aims to solve the problem that high-frequency electromagnetic noise affects signal performance of a current sampling loop and covers real fault features.

The invention discloses a vibration phase bit coding test method and device based on a graphene parameter resonator, and relates to the technical field of resonators. The method comprises the following steps: applying an initial bias voltage and a parameter excitation signal, and setting the driving frequency of the parameter excitation signal to be twice of the resonant frequency corresponding to the initial bias voltage; continuously increasing the parameter excitation signal until the resonator enters a parameter vibration state; applying a direct driving signal, and setting the driving frequency of the direct driving signal as the resonant frequency corresponding to the initial bias voltage; selecting bias voltage values on two sides of the initial bias voltage, and scanning from low to high and from high to low to obtain vibration phase change; and obtaining the vibration phase bit code of the to-be-measured graphene parameter resonator according to the vibration phase change. Information is stored through mechanical vibration of the graphene parameter resonator instead of utilizing charge or electron spinning, electromagnetic interference and phase noise are effectively avoided, and the graphene parameter resonator is more stable at high temperature and suitable for a high electromagnetic noise environment.

The invention relates to the technical field of motors, in particular to a motor stator core. The motor stator core comprises a plurality of punching sheets, a plurality of pear-shaped grooves extending along the radial direction are uniformly distributed on the inner circumference of each punching sheet, and two adjacent surfaces of each pear-shaped groove are in fillet transition, so that magnetic field concentration of sharp edges is eliminated, and the problem of overhigh local magnetic flux density is reduced; the arc-shaped structure of the pear-shaped groove can provide a smoother magnetic path, magnetic resistance is reduced, magnetic lines are distributed more reasonably, magnetic hysteresis loss is reduced, and a magnetic circuit is improved. All the punching sheets are stacked in the axial direction, the pear-shaped grooves in all the punching sheets are in one-to-one correspondence to form a plurality of inclined notches, and compared with original vertical notches of the stator iron core, the inclined notches of the stator iron core have the advantages that the space for accommodating windings is increased, and the magnetic field density is improved. And the inclined notches enable the stator teeth and the rotor teeth to be not completely aligned, so that the tooth harmonic phases are different and mutually offset, thereby weakening the overall harmonic, reducing the electromagnetic noise and vibration, and further improving the motor performance.

The invention relates to a strain monitoring system and method for a transformer winding. The strain monitoring system comprises the transformer winding and a strain monitoring device. The strain monitoring device comprises a fiber bragg grating array which is arranged on a transformer winding and is used for capturing strain signals of the transformer winding; the signal processor is connected with the fiber grating array and is used for receiving and processing the strain signal to generate an electric signal; the data analysis unit is connected with the signal processor, and the data analysis unit is used for receiving and analyzing the electric signal to obtain strain information of the transformer winding; and the wireless transmission unit is connected with the data analysis unit and is used for wirelessly transmitting the strain information to a monitoring center. According to the invention, the fiber grating array is arranged on the transformer winding, and the fiber grating array transmits the strain information through the optical signal, so that the electromagnetic noise is suppressed and the monitoring accuracy is improved by using the characteristic that the fiber is not interfered by the strong electromagnetic environment of the transformer.

The invention discloses an electromagnetic field simulation method under the coupling action of tidal waves and sea waves. The method comprises the steps that input parameters of the tidal waves and the sea waves are set; configuring environmental parameters and geomagnetic conditions; superposing the tidal wave velocity field and the sea wave disturbance velocity field to form a total velocity field; the tidal wave part and the sea wave part are linearly coupled in time and space to obtain a tidal wave-sea wave coupling field evolved along with a tidal phase; in the tidal wave-sea wave coupling field, electromagnetic response calculation is executed on each frequency-direction sampling point; general field synthesis and modulation effect analysis: introducing a tidal wave modulation factor to clearly reflect amplitude periodic change and spectrum reconstruction characteristics of an electromagnetic field signal along with a tidal phase; and outputting a time sequence, an amplitude spectrum and a spatial distribution result of the comprehensive electromagnetic field. According to the method, the authenticity and applicability of sea wave induction electromagnetic field simulation can be improved, and a new technical means is provided for electromagnetic noise recognition, sea wave parameter inversion and complex ocean dynamics process research.

The invention discloses an intelligent marketing terminal power data communication security protection method and system, and belongs to the field of power data security, and the method comprises the steps: collecting electromagnetic noise spectrum data through a built-in environment electromagnetic sensing module of a terminal, extracting electromagnetic characteristic factors, and constructing a correlation model of the electromagnetic characteristic factors and the complexity of an elliptic curve cryptosystem; building a terminal twinborn mirror image, predicting a communication instruction sequence and calculating a deviation coefficient in combination with a long-short-term memory neural network; classifying and screening the power data collected by the terminal, desensitizing privacy data, and then fusing the privacy data into the hash fragment of the unique identifier of the terminal equipment to generate a desensitized power data packet containing the terminal identity identifier; a data abstract is generated according to encryption parameters determined by the association model, the access authority is verified, a data acquisition timestamp is converted into a binary coding sequence, the data abstract is embedded, and an encrypted data packet with a time sequence traceability watermark is generated and uploaded to the block chain for evidence storage; according to the invention, full-process security management and control of power data are realized, and the communication security and the data credibility are improved.

An object of the invention is to provide an electromagnetic noise analysis device capable of analyzing a propagation path in a short time even for electromagnetic noise in a high frequency band and securing a certain level of reliability of an analysis result. For this purpose, an electromagnetic noise analysis device according to the invention includes: a propagation characteristic estimation unit configured to statistically estimate an electromagnetic field characteristic in a housing based on information about a housing structure and an electric wire path to output propagation characteristic probability distribution data; a propagation amount calculation unit configured to statistically estimate a noise propagation amount propagated from a noise source to an affected device based on a frequency characteristic of noise generated by the noise source and the propagation characteristic probability distribution data to output data of noise probability distribution on the affected device; and a malfunction risk determination unit configured to determine a malfunction risk of the affected device based on the data of the noise probability distribution on the affected device.

The invention relates to the technical field of signal processing, and discloses an anti-interference electrically tunable wave trap operation control method and system, and the method comprises the steps: collecting an input signal of an adjustable wave trap group, and employing adaptive Kalman filtering to dynamically suppress strong electromagnetic noise to construct a reinforcement learning state vector, and generating an optimal action instruction of the tuning module by using the deep Q network reinforcement learning model so as to control the tuning module to perform parameter adjustment on the adjustable wave trap group, and finally updating and adjusting the deep Q network reinforcement learning model and the adaptive Kalman filtering based on an actual effect index. Therefore, the electrically tunable wave trap high-precision operation control method based on adaptive Kalman filtering and depth Q network depth collaboration is constructed, the electrically tunable wave trap can be helped to stably maintain high-precision wave trapping performance in a scene of complex dynamic interference and strong noise superposition, and the performance of the electrically tunable wave trap is improved. And many limitations of the traditional scheme in the aspects of interference adaptation, precision control, multi-frequency coordination and stability are thoroughly solved.

The invention provides a multi-physics field transformer noise reduction method and a related device, relates to the technical field of transformers, and aims to solve the problems of complex multi-physics field modeling, low simulation efficiency and low response surface model precision in the prior art. The method comprises the following steps: constructing a transformer multi-physical field coupling simulation model covering a circuit field, a magnetic field, a solid mechanical field and an acoustic field; obtaining noise response data under different structure parameters through simulation; verifying the reliability of a simulation result based on an experimental test; key structure parameters are selected, and a response surface model between the iron core structure parameters and modal response is constructed; and with noise reduction as a target, an optimal structure combination is obtained through optimization by using an optimization algorithm, so that the electromagnetic noise in the operation process of the transformer is suppressed. The method has the advantages of being high in modeling precision, high in analysis efficiency and capable of effectively optimizing the structure, and theoretical basis and support can be provided for design of the low-noise transformer.

The invention relates to the technical field of tool machining data acquisition, and provides a broaching tool machining data acquisition method and system, and the method comprises the steps: obtaining original information flows from various mechanical sensors, carrying out the time alignment of the original information flows, and obtaining the aligned original information flows; identifying a transient event based on the aligned original information flow, and extracting multi-dimensional features of the transient event; constructing a multi-channel space-time correlation fingerprint database; constructing a real-time multi-channel event sequence on each channel based on the transient event and the multi-dimensional features, and matching the real-time multi-channel event sequence with a multi-channel space-time association fingerprint database to obtain a fingerprint matching result; and based on the real machining event fingerprints and the electromagnetic noise fingerprints, a real machining event and electromagnetic noise are distinguished in combination with a fingerprint matching result, so that the broaching tool state and machining abnormality are recognized. The method has the effect of improving the accuracy of broaching tool state recognition and machining abnormality diagnosis.