435 results about "Electromagnetic noise" patented technology

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 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 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 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 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.

The invention provides an unmanned aerial vehicle dynamic path planning method and system for a strong electromagnetic interference environment, and relates to the field of unmanned aerial vehicle navigation and interference resistance. The method mainly solves the problem of robust positioning of an optical sensing system in a strong electromagnetic environment. The core of the method lies in a spectrum anti-noise technology of a visual SLAM module, and spectrum separation of visible light and near-infrared band electromagnetic noise is realized through electromagnetic shielding packaging and an adaptive imaging algorithm of a multispectral camera. According to the method, a time-frequency double-domain filtering algorithm is adopted, the phenomena of light intensity abrupt change and frequency spectrum aliasing generated by electromagnetic pulses are eliminated in the feature extraction stage, and the electromagnetic interference mismatching rate of ORB feature points is reduced to 2% or below. The optimized feature point cloud keeps electromagnetic immune characteristics in the dynamic updating process, centimeter-level positioning precision can be achieved in the field intensity environment of 30 dBm or above, and meanwhile real-time detection of dynamic obstacles is achieved through an optical flow acceleration constraint mechanism.

The invention discloses an electric actuator fault diagnosis method and system, and belongs to the technical field of fault diagnosis, and the method specifically comprises the steps: collecting the current, voltage, displacement, temperature rise and electromagnetic noise signals of an electric actuator in the operation process, and forming a multi-dimensional operation data set, performing time-frequency domain fusion processing on the multi-dimensional operation data to obtain a feature vector, constructing a health state track of the electric actuator, introducing an electromagnetic noise coupling factor into the health state track, performing evolutionary analysis on the health state track, extracting trend information related to a fault, and when the trend information exceeds a set threshold value, determining that the electric actuator is in a fault state. Comparing with a pre-stored actuator fault evolution sample, and judging the fault type and severity; according to the method, advanced identification and classification discrimination of potential faults can be realized through trend extraction and adaptive comparison, so that the comprehensiveness and accuracy of diagnosis are improved.

The invention discloses a control method of refrigeration equipment and the refrigeration equipment, and belongs to the technical field of refrigeration equipment. The control method of the refrigeration equipment comprises the steps that under the condition that a compressor is in a running state, a controller calculates a target carrier frequency based on load information corresponding to the compressor and the actual environment temperature of the environment where the compressor is located; the controller performs modulation processing on the target carrier frequency to obtain a target frequency signal; and the controller controls the rotating speed of the compressor based on the target frequency signal. According to the control method of the refrigeration equipment, the switching loss can be minimized on the basis of ensuring the output precision, energy of a single frequency can be dispersed to a wider frequency band, the frequency spectrum is diffused, the interference peak value of a specific frequency point is reduced, electromagnetic interference and electromagnetic noise are reduced, and the use experience of a user is improved.

The application discloses a heat dissipation assembly for reducing electromagnetic noise of a chip, a chip packaging assembly and electronic equipment. The heat dissipation assembly comprises a heat sink, a sealing ring and a suppression ring; the suppression ring is connected between the sealing ring and the heat sink and is used for surrounding the chip; the heat dissipation assembly is used for jointly surrounding a substrate carrying the chip to form a closed space, so that the chip is located in the closed space; and the suppression ring is used for shielding electromagnetic waves radiated by the chip.

The invention relates to the technical field of high-voltage circuit breaker monitoring, and discloses a high-voltage circuit breaker contact wear intelligent online detection and fault prediction system. The system comprises a contact wear online detection module, a data acquisition and processing module, a wear degree intelligent analysis module, a fault risk prediction module, an alarm and output module, a data storage and management module and a user interaction module. When online detection is carried out on the wear state of the contact of the high-voltage circuit breaker, electrical, mechanical and thermal parameters of the contact are synchronously acquired through a multi-sensor fusion technology, and adaptive filtering and optimization are carried out on an original detection signal by adopting a wavelet transform and Kalman filtering multi-stage signal processing algorithm; influences of electric arcs and electromagnetic noise instantaneous strong interference on detection signals can be suppressed, the accuracy of calculation of contact resistance and stroke key parameters of the contact is guaranteed, the accuracy of contact abrasion state evaluation is improved, and evaluation errors caused by signal interference are reduced.

The invention provides an inner diameter measuring device which can obtain an accurate measurement result even in an environment where large electromagnetic noise is generated in a state that the inner diameter measuring device is installed on a mechanical arm. An inner diameter measuring device for measuring the inner diameter of a hole formed in a workpiece, the inner diameter measuring device being removably attached to the tip of a robot arm (14), the inner diameter measuring device comprising: at least two measuring elements (270) that abut against the inner wall surface of the hole formed in the workpiece, the at least two measuring elements (270) being configured so that the at least two measuring elements (270) are in contact with the inner wall surface of the hole formed in the workpiece, and the at least two measuring elements (270) being in contact with the inner wall surface of the hole formed in the workpiece; the data converting and transmitting part converts analog data related to the displacement of the at least two measuring pieces into digital data representing the inner diameter of the hole and then transmits the digital data to external equipment.

The invention discloses a motor, a compressor and refrigeration equipment, and relates to the technical field of refrigeration equipment, stator slots comprise a first stator slot and a second stator slot, the cross section area of the first stator slot is larger than that of the second stator slot, the maximum radius of the outer periphery of a stator punching sheet is R1, and the maximum radius of the outer periphery of the stator punching sheet is R2; the maximum distance between the groove wall of the first stator groove and the circle center of the stator punching sheet is R0, the length of the stator iron core in the axial direction is h, the elastic modulus of the stator iron core is E, the density of the stator iron core is rho, the Poisson ratio of the stator iron core is v, and the condition that the * is larger than or equal to 3000Hz and smaller than or equal to 5000Hz is met. According to the technical scheme provided by the invention, the rigidity of the stator is improved, and the electromagnetic noise of the motor is reduced.

The invention discloses a high-precision identification method and system for a noise source of an asynchronous motor, and relates to the technical field of asynchronous motor detection, and the method comprises the following steps: constructing a finite element model of a to-be-analyzed asynchronous motor, dividing the surface into a plurality of detection sub-regions, and carrying out the operation simulation of the finite element motor, analyzing vibration speed and sound pressure signal data of each sub-region, synchronously acquiring actual signals, calculating relative differences with simulation data, evaluating detection priorities by combining historical fault times, forming a detection sequence according to the priorities, and sequentially performing sound-vibration coherence analysis and coherence function calculation to obtain a sound-vibration coherence detection result; according to the method, noise frequency bands are classified into structural noise and air noise, order tracking analysis is performed on the structural noise obtained through classification, an amplitude stability index and an amplitude change gradient are calculated, automatic classification and identification of electromagnetic noise and mechanical noise are realized based on a preset threshold value, and the efficiency and accuracy of fault processing are remarkably improved.

The invention relates to a low-harmonic permanent magnet synchronous motor rotor punching sheet and a motor rotor, and relates to the technical field of permanent magnet synchronous motors. According to the scheme, the rotor punching sheet is provided with the first magnetic steel groove and the second magnetic steel groove which form a V shape and are symmetrical about the D axis of the motor rotor, and the opening of the V shape faces the outer circumferential wall of the rotor punching sheet body. According to the structure, the distribution of a motor rotor magnetic field is improved, the magnetic field is more uniform, the salient pole rate is higher, the weak magnetic speed expansion capability is stronger, the structural strength is better, the harmonic content is lower, and the sine property of the magnetic field can be improved. On the outer circumferential wall of the rotor punching sheet body, a first auxiliary groove is formed between the first magnetic isolation bridge and the second magnetic isolation bridge and close to the first magnetic isolation bridge, and a second auxiliary groove is formed between the second magnetic isolation bridge and the D shaft and close to the second magnetic isolation bridge. On the premise of ensuring the mechanical strength of the magnetic isolation bridge, the magnetic line direction is changed, the magnetic leakage is reduced, the air gap flux density waveform is improved, the harmonic content is reduced, and the torque ripple and electromagnetic noise are reduced.