141 results about "Frequency spectrum analysis" patented technology

The invention discloses an unmanned aerial vehicle detection method based on multi-band radio spectrum analysis, and the method can recognize the flight control behaviors of a target, such as hovering, cruising or hovering, through the extraction of a signal track and the introduction of a behavior modeling mechanism, and effectively overcomes the defect that the prior art lacks the dynamic behavior analysis capability. A multi-node synchronization mechanism and a TDOA positioning method are combined, so that high-precision traceability of a target space position is realized; meanwhile, risk level assessment is carried out based on signal features, a track mode and a space region, so that the system has intelligent early warning capability. According to the whole scheme, a full-link unmanned aerial vehicle detection method from multi-frequency receiving, frequency spectrum identification, behavior judgment, target positioning to risk output is constructed, and the problems of single frequency band, rough identification means, lack of tracking and evaluation capability and the like in the prior art are effectively solved; and the practicability and the accuracy of the unmanned aerial vehicle detection system in a complex airspace environment are remarkably improved.

The invention discloses an intelligent temperature control mattress system based on multi-mode sensing and adaptive learning, and the system comprises a data collection module which is used for collecting a mattress surface vibration signal, a mattress surface temperature and a mattress surrounding environment parameter; the data analysis module is used for performing deep analysis on the time-frequency domain features according to a biological recognition model to obtain human body or non-human body classification, performing self-learning to obtain body movement changes, accurately recognizing various typical sleeping postures and filtering out error data; and the model prediction module is used for monitoring the physiological parameters of the user according to the spectral analysis, inputting the physiological parameters, the collected temperature and the parameters of the surrounding environment of the mattress into a temperature control model composed of three neural networks of LSTM, GNN and Transform for comprehensive analysis and decision making, and outputting an optimal temperature control strategy. According to heart rate changes or body heat fluctuations, the sleep stage and the sleep and waking time are intelligently recognized, and therefore sleep environment adjustment better conforming to the human body rhythm is achieved.

The invention discloses an intelligent control method and system for a motor driver, and the method comprises the steps: building an acoustoelectric incidence matrix through collecting harmonic current and sound pressure fluctuation data in the operation process of a motor, and forming a fault feature library; identifying an available fault mode to determine an energy collection point, and performing phase deviation processing on the collection point to generate an auxiliary driving signal; performing spectrum analysis on the sound pressure fluctuation data to obtain an acoustic characteristic spectrum, extracting an efficiency indication tone through characteristic decomposition, mapping the efficiency indication tone into a torque optimization parameter, and establishing a noise reduction control table; performing spectrum analysis on the enhanced control domain to identify a high-energy frequency band, executing a frequency shift operation to generate a safety frequency band signal, and forming a multi-frequency band management strategy in combination with a noise reduction control table; a management strategy is decomposed into parallel control flows for sequential staggered arrangement, and an energy-saving control matrix is generated; and generating a PWM control signal based on the matrix, carrying out edge reconstruction, and obtaining a softened edge waveform through an anti-resonance injection technology to complete intelligent control of the motor driver.

The invention belongs to the technical field of hydropower station monitoring and early warning, and particularly relates to a hydropower station intelligent inspection and fault early warning linkage method, which comprises the following steps: arranging a redundant sensor network at key equipment parts, synchronously acquiring pressure, flow, vibration and water turbidity data, establishing a flow-pressure loss reference relationship, and calculating real-time pressure-flow ratio deviation; performing spectral analysis on the vibration signals, extracting characteristic frequency band energy, performing collaborative study and judgment in combination with a turbidity change trend, and ensuring data credibility through data cross validation of main and auxiliary sensors; performing time sequence difference operation on the pressure-flow ratio deviation to obtain a change rate, fusing vibration-turbidity abnormal performance, and comprehensively diagnosing water diversion blockage or foreign matter invasion; early warning levels are divided according to the deviation and the change rate, corresponding response measures are triggered, response actions are executed according to a preset risk priority sequence, and linkage control of the whole process from state sensing, anomaly recognition, fault diagnosis to intelligent response is achieved.

The invention provides a motor multi-band vibration suppression method and a motor multi-band vibration suppression device based on electromagnetic-mechanical cooperative regulation and control. According to the method, vibration signals are collected in real time, and spectral analysis is carried out to identify vibration frequency distribution; dividing the vibration signal into a low-frequency band, a middle-frequency band and a high-frequency band according to a spectral analysis result, and respectively corresponding to a mechanical vibration source, an electromagnetic excitation source and a structural noise source; a control strategy is dynamically selected based on a vibration frequency band, a low-frequency band triggers a mechanical regulation and control module to output a reverse force to perform vibration suppression, a middle-frequency band triggers an electromagnetic control module to optimize a current waveform and a PWM modulation mode, and a high-frequency band starts a cooperative control strategy of the electromagnetic and mechanical control module; through real-time communication between the controller and each module, vibration feedback signals are continuously monitored, and control parameters are dynamically adjusted according to working condition changes so as to maintain the vibration suppression effect. According to the invention, through cooperative adjustment of electromagnetic control and a mechanical structure, active suppression of vibration of the motor in multiple frequency bands is realized.

The invention relates to the field of charging pile use, and discloses a charging pile use frequency analysis method based on charging frequency data, which comprises the following steps: acquiring charging frequency original data of a plurality of charging piles at different time periods and different dates, performing structured processing in combination with a time label, and constructing a charging behavior data set containing a time dimension label; introducing a sliding window algorithm and a periodic spectrum analysis method, and performing frequency feature extraction on the charging behavior data set; using a density peak clustering algorithm to classify the use frequency matrixes of different charging piles under the same time scale, and identifying use preferences and active features of the charging piles under various typical time scenes; based on a lightweight time sequence neural network structure, a frequency fluctuation sensing mechanism is introduced; and predicting the use condition of the charging pile in a future time period based on the trained frequency model in combination with regression prediction and an anomaly detection algorithm. The method has the advantage of improving operation scheduling.

The invention relates to the technical field of concrete detection, in particular to a concrete protective layer void detection method and system based on a detachable piezoelectric ceramic sensor and an electromechanical impedance resonance technology. The detection method comprises the following steps: temporarily fixing a detachable piezoelectric ceramic sensor on a detection point on the surface of a concrete structure; applying an alternating-current sweep-frequency voltage to excite the piezoelectric ceramic sensor, and obtaining an electromechanical impedance signal frequency spectrum; the electromechanical impedance signal frequency spectrum is analyzed, the frequency of a local defect formant is obtained, and according to the frequency of the local defect formant, geometric parameters of a void area are estimated through a defect size and frequency relation model; and moving the sensor and repeatedly detecting other detection points. The detection method has high efficiency and flexibility, and detection can be realized in any environment; the single-point detection speed is high, the efficiency is high, baseline data is not needed for detection, the anti-interference performance is high, and rapid positioning and quantitative evaluation of void damage can be achieved.

The invention provides a method and system for diagnosing high-frequency magnetic disturbance in a quasi-ring symmetrical star simulator, and relates to the technical field of star simulators, and the method comprises the steps: designing the three-dimensional size of a magnetic probe body in combination with a physical research target and a vacuum chamber space limiting condition, and preparing a magnetic probe entity adaptive to an experimental environment; designing a magnetic probe array space layout according to the triangular magnetic configuration characteristics of the CFQS star simulator to obtain a positioned magnetic probe array; a positioned magnetic probe array is utilized to construct a signal transmission link, and a calibration qualification system is formed; generating a multi-channel time domain voltage signal set according to a calibration qualified system; and performing frequency response correction on the multi-channel time domain voltage signal set in combination with a transfer function database, analyzing a disturbance mode structure and a propagation direction through time-frequency spectrum analysis and array phase difference, and finally outputting three-dimensional magnetic disturbance evolution characteristics. The three-dimensional high-frequency magnetic disturbance measuring device has the beneficial effects that the three-dimensional high-frequency magnetic disturbance measuring capability is realized, multi-channel high-fidelity signal acquisition can be realized, and the experimental data quality and the physical analysis capability are improved.

The invention relates to an active sonar echo signal phase jump compensation method and device based on a synchronous serial number, and belongs to the technical field of underwater acoustic signal processing. The method comprises the following steps: adding a synchronous serial number into a wet end signal to form an expansion matrix; transmitting the extended signal to a signal processor and windowing the extended signal; traversing a synchronous serial number in the windowing signal, and detecting the continuity of the synchronous serial number to judge whether packet loss exists or not; if packet loss exists, positioning a packet loss position and performing zero padding operation; and finally, carrying out fast Fourier transform on the zero-filled signal to obtain a spectral analysis result. According to the method, accurate identification and phase compensation of the packet loss position are achieved through the synchronous serial number, the method is suitable for underwater acoustic single-frequency signals, and when the packet loss rate does not exceed 2.5%, spectrum sidelobes can be effectively restrained, and the peak value of the spectrum sidelobes is reduced to be within 10% of the packet loss state. The method has the advantages of being clear in principle, easy and convenient to operate and high in calculation efficiency, is suitable for real-time signal processing, and remarkably improves the reliability and efficiency of target detection.

The invention discloses a coal mine tunneling roadway advanced geological exploration and ground stress inversion method, particularly relates to the technical field of seismic signal processing in geophysical exploration, and is used for solving the problems of geological exploration signal distortion and insufficient stress inversion precision caused by strong noise interference of tunneling equipment in the prior art. Rock mass vibration signals are collected through an optical fiber sensor arranged on a roadway wall, equipment noise characteristics are identified through spectral analysis, a quantitative mapping relation between working condition parameters and noise characteristics is established, a noise reference time period is determined according to the quantitative mapping relation, a spatial coherence characteristic template is constructed, high-coherence noise components are inhibited through template comparison, and the noise reference time period is determined according to the spatial coherence characteristic template. Finally, the geological structure and stress field distribution in front of the working face are inverted based on the purified seismic wave signals, a stress concentration area and a disaster risk area are identified, the signal-to-noise ratio of the seismic signals in the strong noise environment and the reliability of the geological inversion result are effectively improved, and accurate technical support is provided for safe mining of a coal mine.

The invention discloses a gas-solid-sound coupled gas compressor acoustic resonance monitoring method and system, a medium and equipment, and the method comprises the steps: determining the installation number and angle of strain gauges based on a blade modal analysis result, or determining the installation number and position of blade end timing sensors according to the number of rotor and stator blades, and determining the installation position of a pressure probe; carrying out a compressor surge test, and synchronously collecting a sound field signal, a vibration signal and a pulsating pressure signal; frequency domain information of the sound field signal, the vibration signal and the pulsating pressure signal is obtained through spectral analysis; carrying out correlation analysis on the sound and vibration signals, and judging whether abnormal asynchronous peak values appear in the sound pressure and vibration signals or not; carrying out acoustic mode decomposition at the abnormal asynchronous peak frequency of the sound field signal, and judging whether the circumferential mode order is coupled with the vibration pitch diameter and the pressure mode or not; the method comprises the following steps: performing continuous broadband acoustic mode decomposition on an acoustic pressure signal to obtain a spectrogram, monitoring whether the spectrogram is matched with an acoustic resonance characteristic or not, and judging whether the compressor has an acoustic resonance fault or not.

The invention provides a multi-modal fusion unmanned aerial vehicle identification method and system, and the method comprises the steps: obtaining a radio signal, an image signal and a sound signal of an unmanned aerial vehicle; performing feature extraction on the radio signal based on a blind source separation algorithm and adaptive filtering to obtain radio features; performing feature extraction on the image signal based on image super-resolution reconstruction and a double-flow feature extraction network to obtain image features; performing feature extraction on the sound signal based on spectral analysis and harmonic feature extraction to obtain an audio feature; fusing the radio feature, the image feature and the audio feature to form a multi-modal fusion feature; and performing identification based on the multi-modal fusion features to obtain an unmanned aerial vehicle category identification result. By adopting the scheme, the accuracy, reliability and environmental adaptability of unmanned aerial vehicle identification can be remarkably improved.

The invention provides a die cutting equipment error optimization method and system based on group collaboration, and relates to the technical field of die cutting machines, and the method comprises the steps: carrying out the spectrum analysis of a frequency characteristic curve of each piece of die cutting equipment, so as to divide an initial interference group; establishing a virtual spring damping network in the initial interference group, regarding each die cutting device in the initial interference group as a mass point, and determining a spring stiffness coefficient and a damping coefficient according to an actual distance between adjacent mass points; determining vibration mode characteristics of each die cutting device according to the spring stiffness coefficient and the damping coefficient, and converting a control signal generated according to the vibration mode characteristics into a parameter adjusting variable by using a preset control algorithm; and determining a vibration coupling relationship according to the collected vibration energy data of the initial interference group after the initial processing parameters are adjusted according to the parameter adjusting quantity, and determining an optimal production takt and a parameter compensation value according to the vibration coupling relationship. The technical problem that in the prior art, due to vibration coupling of a die cutting equipment group, the machining error cooperative control difficulty is large is solved.

The invention relates to the field of electrical variable measurement, in particular to an insulating layer compactness detection method for a mineral cable, which comprises the following steps: firstly, acquiring a time domain reflection signal of the cable, and carrying out denoising pretreatment by utilizing synchronous average and wavelet transform; and then, carrying out spectrum analysis on the discrete signal segments, calculating a spectrum centroid offset rate to determine high-frequency energy attenuation, and constructing a dynamic compensation gain coefficient according to the high-frequency energy attenuation. And then, improving a traditional layer stripping algorithm by using the gain coefficient, eliminating calculation deviation caused by transmission loss, and accurately reconstructing characteristic impedance distribution along the cable. And finally, by comparing the deviation between the reconstructed impedance and the nominal impedance, positioning and judging the abnormities of the compactness of the insulating layer of the cable and the eccentricity defect of the cable core are realized.

The invention discloses a compressor multi-working-condition feature extraction method based on valve movement acoustic emission, and belongs to the technical field of compressors, and the method comprises the following steps: S1, synchronously collecting compressor valve acoustic emission signals and piston displacement data by using an acoustic emission sensor and a rotating speed encoder, and constructing a time alignment joint signal sequence; s2, calculating a real-time phase according to a piston displacement crankshaft angle, enveloping an energy change rate by combining an acoustic emission signal, and dividing four stages of a compression cycle; s3, extracting the multi-dimensional time-frequency characteristics of the acoustic emission signals in each stage; and S4, inputting the multi-dimensional features into a pre-training auto-encoder, and generating low-dimensional fusion feature vectors to represent operation features. According to the compressor multi-working-condition feature extraction method based on valve movement acoustic emission, acoustic emission and displacement combined modeling is adopted to improve the working condition sensing precision, multi-dimensional features are extracted by means of wavelet packet transformation and spectral analysis fusion to strengthen micro working condition recognition, and the method adapts to multiple typical working conditions and is good in robustness and adaptability.

The invention provides a rapid positioning method and system for excitation system power cabinet draught fan faults, and the method comprises the steps: collecting the operation parameters of an excitation system power cabinet draught fan in real time in a preset time period, and the operation parameters comprise the draught fan rotating speed, the bearing temperature, the vibration frequency, the current value and the voltage value; analyzing the operation parameters by using a threshold value judgment method and a trend analysis method, and judging whether the excitation system power cabinet fan has a fault or not; when the excitation system power cabinet draught fan breaks down, sound signals of the draught fan are collected, spectral analysis is conducted on the sound signals of the draught fan, and a spectral analysis result of the draught fan is obtained; and determining the fault type and the fault position of the fan based on the spectral analysis result of the fan. According to the technical scheme provided by the invention, the fan fault monitoring precision and efficiency are improved.

The invention relates to an intelligent sound field calibration method and system, and the method comprises the steps: transmitting sweep frequency signals in a preset frequency range to a plurality of microphone collection positions in a sound field, collecting echo signals through each microphone, and constructing an acoustic feature database based on the echo signals; extracting a relative position relationship between microphones and corresponding echo signal features from the acoustic feature database, constructing a sound field spatial topological graph and dividing acoustic partitions based on the relative position relationship and the echo signal features, and determining response weights of the partitions; based on the acoustic characteristic database, a frequency spectrum analysis algorithm is adopted to identify and mark howling frequency points, and a preliminary frequency response curve is generated in combination with the howling frequency points and the response weights of the acoustic partitions; adjusting the initial frequency response curve according to historical preference data of the user to generate a target frequency response curve; and applying the target frequency response curve to the audio output path to output the audio signal. The method has the effect of improving the accuracy of sound field calibration.

The invention discloses a fault detection method and system for a permanent magnet synchronous motor, and relates to the technical field of permanent magnet synchronous motor fault detection.The method comprises the steps that stator three-phase current during operation of the permanent magnet synchronous motor is collected in real time, and zero-sequence current is calculated; carrying out multi-band frequency spectrum analysis based on the zero sequence current, respectively detecting a third harmonic amplitude and a sixth harmonic amplitude by adopting a parallel dual-channel FFT (Fast Fourier Transform) processor, and calculating a harmonic amplitude ratio; correcting the third harmonic amplitude and the sixth harmonic amplitude through a preset compensation coefficient matrix, and recalculating the corrected harmonic amplitude ratio; and performing fault classification on the corrected harmonic amplitude ratio based on a preset threshold value in combination with a time accumulation counter, and outputting a final fault code after continuous three times of consistent detection, thereby completing fault detection of the permanent magnet synchronous motor. The fault type can be rapidly positioned, the fault diagnosis precision is improved, it is ensured that an alarm is given after real faults are accumulated to the confirmable level, and the diagnosis reliability and stability are improved.

The invention discloses an automatic half-wave voltage detection device and method for a crystal modulation experiment, and particularly relates to the technical field of photoelectric measurement. Comprising a tunable laser source (the wavelength of 560-750 nm is adjustable), a crystal modulation module (a high-voltage direct-current power supply and a signal source), an integrated detection module (a horizontal rotating support integrated power meter and a photoelectric converter) and a control module (double data acquisition cards and a Python program). The function implementation mode is as follows: the synchronous measurement of an extreme value method (extracting extreme points by moving average fitting of a U-P curve) and a frequency multiplication method (capturing frequency multiplication distortion points by spectral analysis) is automatically executed through a rotary bracket switching detection unit (the alignment precision is less than or equal to 0.1 mm); and a lambda-Upi relation curve is generated in combination with multi-wavelength scanning, and is compared with a theoretical formula Upi = lambda d / (2n03gamma22L) for analysis. According to the invention, manual intervention and optical path dismounting errors are eliminated, full-process closed-loop control is realized, and high-precision data support is provided for parameter optimization of the electro-optical modulator.

The invention discloses an electric reactor vibration detection method, device and equipment and a medium, and relates to the technical field of electric power detection, and the method comprises the steps: obtaining an electric drive signal converted from the mechanical vibration of an electric reactor; based on the electric driving signal, controlling the working state of the passive vibration measurement circuit so as to perform frequency multiplication processing and amplitude modulation on the input radio frequency excitation signal to obtain a modulated harmonic signal; performing spectral analysis on the modulated harmonic signal to obtain carrier component and sideband component information, and determining a vibration frequency estimation value of the reactor based on the carrier component and sideband component information; performing inversion calculation based on the sideband component information, and determining a duty ratio estimation value corresponding to the electric driving signal; wherein the duty ratio estimated value represents the conduction time proportion of the passive vibration measurement circuit controlled by the electric driving signal; and querying a preset calibration relation based on the vibration frequency estimation value and the duty ratio estimation value to obtain the vibration acceleration of the reactor. The method can obtain an accurate detection result.

The application belongs to the technical field of zinc powder purification, and provides a condensation and sedimentation system for zinc powder purification, which comprises the following steps: collecting a time sequence of original radiation intensity of a condensation chamber, performing frequency spectrum analysis through fast Fourier transform, calculating energy values of high and low frequency band frequency domain signals, solving a signal coherence factor and calculating a transmittance attenuation coefficient, constructing a metal thin film radiation compensation model based on a long short-term memory network, inputting the attenuation coefficient and the time sequence of original radiation intensity to output a corrected real temperature of the condensation chamber, expanding an inference layer of a full connection neural network structure, outputting a calibrated attenuation coefficient through the inference layer, selecting an effective attenuation coefficient input model by comparing a deviation threshold value, dynamically responding to temperature measurement nonlinear attenuation caused by zinc film deposition, guaranteeing production continuity and product quality of zinc powder purification, adapting to industrial multi-working condition operation requirements, being convenient to operate and controllable in cost.

The present application relates to the technical field of compression spring resonance frequency detection, and specifically relates to a compression spring resonance frequency detection method and system, the method comprising the following steps: collecting a mixed vibration signal of a compression spring to be measured; collecting a background noise signal of a test device as a reference noise signal; collecting a synchronous signal of a specific noise source of the test device; performing adaptive noise cancellation processing on the mixed vibration signal, the adaptive noise cancellation processing performing initial parameter training using the reference noise signal and using the noise source synchronous signal as a real-time reference input to separate a pure vibration response signal of the compression spring to be measured; performing frequency spectrum analysis on the pure vibration response signal; identifying a wideband vibration response region of the compression spring to be measured, the wideband vibration response region having a continuous amplitude higher than a preset energy threshold and having a specific width; calculating a characteristic parameter of the wideband vibration response region; and judging a degradation state of the compression spring to be measured according to the characteristic parameter. The above improves the accuracy of degradation judgment.

The invention discloses a jitter suppression method and system for an AGV. The method comprises the steps that a rotor speed signal and a torque instruction signal of a permanent magnet synchronous motor of the AGV are collected; performing discretization sampling on the rotor speed signal to obtain a discrete speed signal; performing spectral analysis on the discrete speed signal to extract a corresponding vibration spectrum, and obtaining a main frequency point where resonance occurs; inputting the discrete speed signal into a high-pass filter to extract a component required by active damping suppression of a vibration frequency point, carrying out discretization differential on the discrete speed signal to obtain an acceleration signal, and carrying out band-pass filtering on the acceleration signal by adopting a band-pass filter to obtain a component required by acceleration feedback suppression; the cut-off frequency of the high-pass filter and the center frequency and bandwidth of the band-pass filter are determined by main frequency points; and a compensation torque signal is obtained according to the jitter component and the component required for acceleration feedback suppression, so that jitter caused by resonance of the AGV is suppressed according to the compensation torque signal.

The application relates to the technical field of fault positioning, and discloses a power distribution network grounding fault positioning method and system. The method comprises the following steps: collecting a fault starting transient section signal, an arc burning duration section signal and an arc extinguishing recovery section signal of a power distribution network, and performing frequency spectrum analysis to obtain a fault characteristic matrix; performing zero sequence transient spectrum reconstruction on the fault characteristic matrix to obtain reconstructed spectrum characteristics and time-varying spectrum characteristics; calculating a transient characteristic index and a fault type based on the reconstructed spectrum characteristics and the time-varying spectrum characteristics; performing fault positioning calculation on the power distribution network according to the transient characteristic index and the fault type to obtain an initial fault point position; and performing transient fingerprint matching and probability density accumulation compensation on the initial fault point position to obtain a target fault point position. The application realizes high-precision characterization of rapidly changing signals in a short time window, eliminates the interference of compensation states on fault positioning, and improves the grounding fault positioning accuracy of the power distribution network.

The invention belongs to the technical field of bearing wear resistance detection, and particularly relates to a method for detecting the wear resistance of a bearing. Comprising the steps of data acquisition, primary detection, secondary detection and comprehensive evaluation. Real-time temperature and sound data including environment temperature and background noise interference are acquired; in the primary detection, the temperature data is subjected to difference calculation, Kalman filtering and compensation correction, the sound data is subjected to time-spectrum analysis, frequency-band noise reduction and fusion to calculate a primary wear index, if the primary wear index is smaller than a first threshold value, the primary wear index is judged to be qualified, otherwise, the secondary detection is performed; rolling body, inner ring and outer ring slide way abrasion images are collected through secondary detection, and after preprocessing, secondary abrasion indexes are calculated through the double-branch convolutional network and non-abrasion images; and if the comprehensive wear degree is greater than a second threshold value, judging that the comprehensive wear degree is unqualified and giving an alarm, otherwise, judging that the comprehensive wear degree is qualified. The method dynamically eliminates environmental interference, combines multiple parameters and image features, and improves the detection accuracy and reliability.

The invention discloses a dual-pressure evaporation organic Rankine cycle control method and system. The method comprises the steps that the difference of high-pressure side and low-pressure side operation parameters is collected to detect and recognize the pressure distribution unbalance degree, and a dual-pressure compensation regulation factor is generated; analyzing the high-voltage side operation parameter spectrum to identify a dominant fluctuation frequency band, and generating a frequency deviation degree to determine a pressure regulation key point; a priority adaptation strategy combination is screened based on a pressure regulation and control key point retrieval strategy library, and after a reference control sequence is formed, a composite regulation and control signal is generated through dual-pressure compensation regulation factor time sequence adjustment and gain adjustment; monitoring the pressure distribution unbalance degree and the response coupling strength of the dual-pressure compensation regulation factor to identify pressure instability precursor characteristics and execute a composite regulation signal, and performing gradient jump analysis to generate a control efficiency index; the pressure distribution unbalance degree is dynamically tracked, the pressure fluctuation attenuation rate is analyzed and recognized through oscillation attenuation, the stability margin is generated in combination with the control efficiency index and the pressure fluctuation attenuation rate, and a graded execution instruction is output to achieve dynamic balance of pressure distribution.

The application provides a whole vehicle sound source noise target setting method, system, device and medium, relates to the NVH technical field, and the method comprises the following steps: firstly, obtaining the sound pressure level noise data of a test vehicle under a target working condition through a first bench test; then, respectively determining the sound transmission functions of the test vehicle and a target vehicle through a second bench test; then, performing frequency spectrum analysis on the sound pressure level noise of the test vehicle to obtain target sound pressure level noise in a specific frequency range. Combined with the sound pressure level noise of the test vehicle and the sound transmission function thereof, the sound source noise of the test vehicle is calculated; further, the target sound pressure level noise and the sound transmission function of the target vehicle are utilized to determine the sound source noise of the target vehicle; finally, according to the sound source noises of the test vehicle and the target vehicle, the sound source noise target value of the target vehicle is set. The application can effectively solve the problem that the bench test is inconsistent with the actual performance of the whole vehicle, and improve the accuracy and rationality of the sound source noise target setting.

The invention discloses an improved M3C circulating current suppression method based on a three-phase static coordinate system, and belongs to the technical field of power electronic converter control. The method comprises the following steps: identifying four dominant frequency components (omega1-2omega2, 2omega1-omega2, omega1 + 2omega2 and 2omega1 + omega2) in the M3C circulating current through spectral analysis (omega1 is a power frequency side angular frequency, and omega2 is a low frequency side angular frequency); under a three-phase static coordinate system, proportional resonance controllers are independently arranged on the nine bridge arms to generate circulating current suppression voltage signals, and the four frequency components are suppressed; and meanwhile, a zero-sequence suppression voltage signal is generated through a proportional controller, so that the amplitude of zero-sequence current with the frequency of 3 omega 1 and 3 omega 2 does not exceed 5% of the rated current of the bridge arm. According to the method, coordinate transformation and a phase-locked loop are not needed, the internal loop current of the bridge arm is effectively suppressed, bridge arm current distortion is reduced, and the method is suitable for a power frequency-low frequency alternating current interconnection scene.

The present application relates to the technical field of ripple suppression, and discloses a ripple suppression method and system for a high-voltage electrical network of a vehicle, the method comprising: obtaining a bus voltage ripple waveform under a target operating condition, determining a peak frequency through frequency spectrum analysis; establishing an equivalent impedance model of a high-voltage loop to identify a resonance frequency range; when the peak frequency falls within the resonance frequency range, solving an equivalent inductance increment required by the high-voltage loop under the constraint of a switching frequency characteristic point set and a minimum allowable frequency interval; implementing inductance tuning through equivalent length adjustment of a wire harness or a series inductor device on a high-voltage connection wire harness at a front drive and a rear drive port; re-measuring a ripple index after tuning and comparing it with a threshold value, and if the ripple index does not meet the threshold value, updating the inductance increment and repeating the tuning process. Through frequency domain feature extraction, impedance modeling and frequency avoidance constraint, the present application improves the adaptability and consistency of ripple suppression under different conditions and parameter conditions.

The application provides a flexible direct current transmission line single-end fault distance measurement method based on frequency domain analysis, which comprises the following steps: collecting a reclosing end real-time voltage value and a reclosing end real-time current value, determining equivalent resistance values of each point along a line based on the reclosing end real-time voltage value and the reclosing end real-time current value; performing frequency spectrum analysis on the equivalent resistance values of each point along the line to generate frequency spectrums of each point along the line; respectively calculating a center of gravity frequency of each point along the line based on the frequency spectrums of each point along the line; and sorting the center of gravity frequencies of each point along the line, and determining a fault distance by selecting a line position corresponding to the smallest center of gravity frequency. The method realizes flexible direct current transmission line single-end fault distance measurement, and improves positioning accuracy and stability of flexible direct current transmission line single-end fault distance measurement.