46 results about "Pulse characteristics" patented technology

The invention discloses a partial discharge online monitoring method based on an ultrahigh frequency original signal, and relates to the field of partial discharge monitoring, and the method comprises the steps: autonomously switching an ultrahigh frequency signal capturing frequency band according to the real-time electromagnetic spectrum distribution of a monitoring environment, and obtaining an original signal sequence covering a potential partial discharge feature; the method comprises the following steps: preprocessing an original signal sequence through multi-scale pulse contour extraction, and suppressing environmental noise interference to retain pulse characteristics of partial discharge signals; through real-time electromagnetic spectrum analysis, ultrahigh frequency capture frequency bands are automatically switched, environmental noise changes are dynamically adapted, original signal capture accuracy is improved, through multi-scale pulse contour extraction preprocessing, noise interference is effectively suppressed, key pulse features are reserved, and the accuracy of signal capture is improved. A multi-dimensional feature data set constructed based on the pulse peak gradient, the duration spectrum and the waveform similarity provides a comprehensive basis for partial discharge recognition.

The invention relates to the technical field of signal processing and state monitoring, in particular to an intelligent lubricating state monitoring method based on oil-impact pulse, which comprises the following steps of: constructing a'fluid-solid-heat-electricity 'multi-field coupled particle double-electric-layer electrostatic model, and forming a particle electrostatic characteristic analysis and monitoring method; oil physical and chemical property parameters and mechanical equipment transmission system gear impact pulse characteristics in different lubrication states are collected in real time, an oil-impact pulse-lubrication state correlation model is constructed, and a gear transmission system lubrication state monitoring method is formed in combination with a signal processing method and a deep learning algorithm. According to the invention, the real-time performance and comprehensiveness of lubrication state evaluation are enhanced, and the work and maintenance efficiency of equipment is also improved.

The invention discloses a bionic joint humanoid robot navigation positioning method, device and equipment, and the method comprises the steps: monitoring a landing shock wave signal and reflection echo data of a robot, carrying out the time domain expansion of the shock wave signal to form a pulse characteristic spectrum, extracting multipath propagation components, and carrying out the time difference correlation to generate an environment response value. Screening a direct wave component by using an environmental response value, positioning a sound wave propagation trajectory, and detecting impedance mutation to construct an acoustic matrix. A strong reflection zone is identified through node analysis, a sound pressure gradient field is extracted to determine an obstacle boundary, and a landmark feature bit is determined in combination with an environmental response value. And adjusting a dynamic stride frequency interval based on a landmark feature bit, forming an adaptive detection sequence, and performing sparse processing to construct path configuration. The mechanical vibration component of the shock wave signal is used for piezoelectric conversion to generate recycled electric quantity, the recycled electric quantity is matched with path configuration power to determine a sensing period, intermittent sensing is executed to obtain detection data to construct a detection convergence field, and finally an accurate positioning window is determined and converted into position coordinates.

The invention is suitable for the technical field of distribution network detection, and provides a distribution network overhead line partial discharge integrated live detection system based on a ubiquitous Internet of Things architecture, which comprises a pulse signal detection end, an edge gateway and a cloud monitoring platform, the pulse signal detection end is used for detecting a partial discharge pulse signal of the overhead line and transmitting the partial discharge pulse signal to the edge gateway; the edge gateway comprises a synchronization pulse trigger module, a time calibration module and an edge analysis module. The generation module is used for generating a positioning distribution diagram of partial discharge points; the cloud monitoring platform comprises a multi-terminal data fusion module, a risk assessment module and a result feedback module; the server is used for fusing the positioning distribution map and the pulse characteristics, outputting a global discharge point correction distribution map, identifying a discharge type based on a discharge characteristic spectrogram, generating an insulation state evaluation result and feeding back the evaluation result to a terminal user; and a high-reliability, high-efficiency and low-cost solution is provided for the management and control of the insulation state of the distribution network.

Methods and systems for identifying or classifying charge states of detected ions. An example method for classifying a charge state of detected ions may include generating a pulse for each ion in a plurality of ions detected by a detector, wherein each pulse has a pulse characteristic; generating a pulse-characteristic distribution of the generated pulses; and based on the pulse-characteristic distribution, generating an identification of the charge state of one or more ions in the plurality of ions.

The invention relates to the technical field of centrifugal machines, in particular to an automatic discharging control method and system for a top-suspended scraper discharging centrifugal machine, and the method comprises the steps that vibration data and rotating speed data of a rotary drum of the centrifugal machine are obtained; dividing the whole data acquisition time into a plurality of time windows; according to the peak pulse characteristic, the periodic characteristic, the frequency change characteristic and the high-frequency characteristic of the vibration data of each time window, acquiring a comprehensive abnormal coefficient of each time window, and acquiring an abnormal influence coefficient of each time window in combination with the dispersion degree of the rotating speed data of each time window; and according to the change characteristics of the abnormal influence coefficient of the adjacent window of each time window, the unloading abnormal coefficient of each time window is obtained, and then the optimized prediction range parameter of each time window is obtained, so that the scraper movement control of the next time window is optimized. And the unloading efficiency of the centrifugal machine is improved by adaptively adjusting the prediction range parameter of each time window.

The invention relates to the technical field of bionic control, and discloses a robot control method based on a pulse neural network, and the method comprises the steps: carrying out the spatial-temporal feature coding of the environment perception information and body state information of a robot, and obtaining a pulse feature sequence; performing pulse dependence fusion on the pulse characteristic sequence and the feedback pulse signal to obtain a bionic information processing process, and performing membrane potential integration on the bionic information processing process to obtain an integrated output quantity; performing pulse distribution processing on the integrated output quantity to obtain a driving pulse signal; performing path fitting on the driving pulse signal to obtain a continuous motion track; based on the continuous motion track and the bionic information processing process, performing joint space mapping on the continuous motion track to obtain an execution control instruction; the application executes the control instruction, synchronously collects a pulse response signal and feeds back the pulse response signal in real time so as to obtain an optimization control instruction of the robot; the pulse neural network-based robot control efficiency can be improved.

The invention relates to the field of discharge part detection, and particularly discloses a high-voltage transmission line discharge part intelligent detection method, which comprises the following steps of: arranging UHF (Ultra High Frequency) sensors on a plurality of side-by-side high-voltage transmission lines at equal intervals in a staggered manner, and monitoring signals in real time; screening effective signals based on the signal amplitude, and judging whether the signals are partial discharge signals or not through pulse feature matching; after a discharge range is preliminarily determined based on partial discharge signal intensity, a plurality of triangular sensor arrays are constructed, a time difference positioning method is adopted to calculate and determine suspected discharge points corresponding to the sensor arrays, and discharge parts and intensity thereof are determined through spatial clustering analysis; and finally, collecting a visible light image of a discharge part, extracting physical defect information, analyzing the defect degree, evaluating the discharge severity by combining the discharge intensity and the defect degree, and generating a detection report. The method can effectively eliminate interference, improves the positioning precision and reliability, and achieves the efficient detection and evaluation of the discharge part of the high-voltage transmission line.

This application discloses a diabetes detection system based on multi-sensor pulse characteristics, relating to the field of medical signal processing. The system includes: a pulse wave data acquisition module that uses a pressure sensor and a photoelectric sensor to acquire the user's wrist pressure pulse wave and fingertip photoplethysmography (PPG) pulse wave; a preprocessing module to obtain usable single-cycle pulse wave data; a signal fusion module that converts the pressure pulse wave signal and PPG pulse wave signal into two-dimensional image signals through continuous wavelet transform to retain time-frequency domain information, and processes the two two-dimensional images using non-subsampled shear wave transform and a pulse-coupled neural network; and a feature extraction and calculation module that extracts pulse wave image features through a ResNet network and finally classifies them using a random forest. This detection system improves the fusion effect without increasing computational load, achieving non-invasive diabetes detection using multiple sensors and improving detection accuracy.

The application relates to the technical field of insulation performance detection, in particular to a method and system for detecting the insulation performance of an insulation layer of a power device, which comprises the following steps: acquiring a partial discharge signal, current data and temperature data of the insulation layer of the power device; acquiring a significant value of pulse characteristics of the partial discharge signal and a significant value of periodic similar characteristics of the partial discharge signal, then obtaining abnormal values of the window discharge signals affected by insulation deterioration, and acquiring abnormal values of the current data affected by insulation deterioration through the change randomness of harmonic components of the current data of the power device and the difference degree between the fundamental wave component of the current and the current data; calculating a consistency coefficient of the abnormal characteristic change of insulation deterioration, then obtaining an insulation deterioration degree coefficient to detect the insulation performance of the insulation layer of the power device. The application can improve the insulation performance detection precision of the insulation layer of the power device.

The application relates to the technical field of centrifuges, in particular to an automatic unloading control method and system of an upper-suspension type scraper unloading centrifuge. The method comprises the following steps: acquiring vibration data and rotating speed data of a centrifuge drum; dividing the whole data acquisition time into multiple time windows; acquiring a comprehensive abnormality coefficient of each time window according to the spike pulse characteristics, periodic characteristics, frequency change characteristics and high frequency characteristics of the vibration data of each time window, and acquiring an abnormality influence coefficient of each time window in combination with the discrete degree of the rotating speed data of each time window; acquiring an unloading abnormality coefficient of each time window according to the change characteristics of the abnormality influence coefficients of the adjacent windows of each time window, and then acquiring the optimized prediction range parameters of each time window, so as to optimize the scraper movement control of the next time window. The prediction range parameters of each time window are adaptively adjusted, and the unloading efficiency of the centrifuge is improved.

The application provides a high-purity germanium detector and a detection method thereof. The method comprises the following steps: collecting an electric pulse signal; extracting electric pulse characteristic data from the electric pulse signal based on a preset carrier signal sample; determining a plurality of detection intervals of the high-purity germanium detector by the energy resolution of the high-purity germanium detector and the electric pulse characteristic data; determining a main pulse peak in a first energy gathering area and a secondary pulse peak in a second energy gathering area of the electric pulse signal according to all the detection intervals and the pulse count rate of the electric pulse signal in each detection interval; determining a response bias of the high-purity germanium detector by the main pulse peak and the secondary pulse peak; performing energy spectrum reading on a confidence electric pulse signal determined by the response bias to obtain nuclear radiation energy measured by the high-purity germanium detector. The application obtains the nuclear radiation energy based on the confidence electric pulse signal, can extract the signal characteristics of the electric pulse signal under multiple noise interferences, and thus improves the detection authenticity of the high-purity germanium detector.

The invention discloses a door lock control method and device and an intelligent door lock, the method is applied to the intelligent door lock, and the method comprises the following steps: obtaining a to-be-recognized image, and analyzing the to-be-recognized image to obtain facial feature data of a global face; and processing the facial feature data to obtain a blood perfusion index. Acquiring to-be-processed pulse data of the target user, and processing the to-be-processed pulse data to obtain pulse characteristic parameters. And inputting the blood perfusion index and the pulse characteristic parameter into a preset characteristic fusion model to obtain a control instruction of the intelligent door lock. According to the control instruction, the intelligent door lock is controlled to give out an early warning prompt. According to the door lock control method, signal acquisition and analysis from multiple dimensions are achieved, so that the intelligent door lock is controlled more comprehensively and accurately, finally, early warning prompt is triggered based on the control instruction, accurate and normalized monitoring of the home state of a user is achieved, and effective guarantee is provided for home safety of the user.

The invention discloses a blade breakage detection method and device, related equipment and a computer program product, and relates to the technical field of semiconductor manufacturing processes. The method comprises the following steps: acquiring a target detection signal of a to-be-detected sawtooth blade, the target detection signal comprising an electric signal acquired by converting luminous flux shielded by the to-be-detected sawtooth blade in the process of rotating the to-be-detected sawtooth blade for at least one circle; determining a pulse characteristic parameter of a detection signal segment corresponding to each circle of rotation of the to-be-detected sawtooth blade in the target detection signal; in the target detection signal, under the condition that the pulse characteristic parameters of the detection signal segments not smaller than the preset number meet the first preset damage condition, it is determined that the to-be-detected sawtooth blade is in a damaged state, and the preset number is in direct proportion to the number of rotation cycles of the to-be-detected sawtooth blade. The sawtooth blade damage detection method and device are suitable for sawtooth blade damage detection, and the sawtooth blade damage condition can be accurately recognized.

The invention provides an ambulatory blood pressure measuring device air pump control method and system based on pulse waveform dynamic adjustment, and relates to the technical field of ambulatory blood pressure measuring device air pump control. An optimal detection point is determined through pulse collection information of multiple detection points of an ambulatory blood pressure measuring device, and air pump and physiological data collection, adjustment and analysis are conducted; adjusting and analyzing the body position change according to the compensation fitting adjusting data, obtaining the dynamic control strategy information of the air pump to carry out control constraint analysis and adjustment, and obtaining the optimal control strategy information of the air pump; according to the air pump optimization strategy information, pulse feature anomaly analysis and adjustment are carried out, and air pump physiological adjustment data are obtained; performing pressure calibration adjustment according to the body position air pump adjustment data in combination with the pulse characteristic abnormal data so as to obtain inflation physiological fitting data; according to the method, multi-dimensional data are fused, and the physiological change and the accurate blood pressure measurement capability are dynamically adapted.

The invention discloses a DAS-based building attachment state monitoring and falling object early warning method and system, and relates to the technical field of building safety monitoring, and the method comprises the steps: collecting a global acoustic vibration signal of a building attachment through employing a laid distributed acoustic sensing optical fiber; the global acoustic vibration signals are separated into different modal components, after the modal components corresponding to the environmental noise are removed, the modal components corresponding to the traffic noise and the personnel activity noise are superposed to serve as reference signals, and after the reference signals are filtered through adaptive weights, defect characteristic signals of the building attachments are determined; and judging whether the defect characteristic signal is a suspected defect event based on a modal frequency change rate and a short-time pulse characteristic, if so, extracting a multi-dimensional characteristic parameter, determining a defect level according to the trained evaluation model, and positioning a defect position according to an optical fiber laying scheme. Therefore, attachment global non-blind area monitoring is realized, and the comprehensiveness, accuracy and timeliness of building safety monitoring are improved.

The application discloses a kind of wind turbine speed signal analysis method and system based on flange bolt, the method includes the following steps: based on flange bolt collection pulse basic information;Judge whether the first pulse pulse width exists abnormal condition;Accumulate original pulse information, identify abnormal condition in original pulse information, and correct pulse width variation anomaly;The proportion of abnormal pulse is counted and calculated;Identify the pulse characteristics in accumulated original pulse information, obtain N normal pulse signals according to pulse characteristics, use the N normal pulse signals instead of single pulse period to calculate initial impeller speed;Extract the pulse that meets preset period, add in impeller speed calculation;The probability of occurrence of various abnormal characteristics in speed is counted;The application corrects various abnormal signals, filters out normal bolt pulse signal, to improve the accuracy of speed calculation, reduce the abnormal fluctuation of speed caused by interference factor, provide more accurate data analysis for wind turbine.

The invention particularly relates to a high-power microwave short pulse in-pulse phase change measuring method and device, and the method comprises the steps: carrying out the coupling processing of a microwave excitation pulse signal, and obtaining a first branch signal and a second branch signal; performing delay processing on the first branch signal to obtain a reference signal for intra-pulse phase comparison; performing phase drift on the second branch signal to obtain a measurement signal for intra-pulse phase comparison; and comparing the phase of the reference signal with the phase of the measurement signal, and visualizing the comparison result. Through distribution, amplification, delay and comparison processing of excitation signals, real-time phase measurement of high-power short-pulse signals can be realized under the condition that the structure of a signal main path is not changed. The device has the advantages of being simple in structure and high in measurement precision, can effectively avoid errors caused by instrument bandwidth limitation and insufficient sampling rate in a traditional method, and is suitable for phase stability evaluation and intra-pulse characteristic analysis in a high-power microwave system.

This invention provides a laser parameter synchronous measurement system based on an attenuation fixture, including a beam collimator, a first reflecting mirror, a second reflecting mirror, a first beam splitter prism, a second beam splitter prism, a power meter, and an M... 2 The system includes a test instrument, a spectrum analyzer, a pulse width measurement module, and a spectrum analyzer; after the system is powered on and the laser under test outputs laser light, the power meter and M are simultaneously triggered. 2 The tester, spectrometer, pulse width measurement module, and spectrum analyzer are used to detect the laser parameters output by the laser under test. This invention can simultaneously measure parameters such as laser power, beam quality, and pulse characteristics (repetition frequency, pulse width), avoiding errors introduced by step-by-step measurements. Through synchronous triggering and data acquisition, it ensures that all parameters are measured under the same time reference, making it particularly suitable for dynamic laser systems or pulsed laser analysis. The integrated software can automatically integrate key parameters (such as peak power, average power, pulse width spectrum, etc.) and generate a laser parameter test report.

The application relates to a mechanical fault diagnosis method and device, electronic equipment and a computer readable medium. The method comprises: performing generalized linear W transformation on a mechanical signal to generate a generalized linear W time-frequency spectrum of the mechanical signal; generating group time delays of the mechanical signal at each time-frequency position based on the generalized linear W time-frequency spectrum; generating a transient extraction generalized linear W time-frequency spectrum based on a transient extraction algorithm and the group time delays; and performing mechanical fault diagnosis based on the transient extraction generalized linear W time-frequency spectrum. The mechanical fault diagnosis method, device, electronic equipment and computer readable medium can more finely depict the non-stationary characteristics of a signal, extract the pulse characteristics of a mechanical fault signal, and thus efficiently identify bearing faults.

A system and method for operating an implanted medical device (IMD) based on a waveform player. In one arrangement, the IMD may comprise a first module operative to effectuate a communication interface with an external device for receiving a plurality of program records for storage in a persistent memory, the program records each comprising a plurality of pulse definitions and a plurality of time interval definitions, wherein a pulse definition comprises a set of pulse characteristics to be applied in a particular time interval. A second module may be communicatively coupled to the first module, the second module including a buffer for containing a runtime image of a selected program record loaded from the persistent memory. A waveform player provided as part of the second module is operative to interpret the runtime image to generate control signals to drive an output driver circuit for applying pulse characteristics to a select set of electrodes according to the pulse definitions of the selected program record.

The application is suitable for the technical field of distribution network detection, and provides a local partial discharge integrated live detection system for overhead lines of a distribution network based on an ubiquitous Internet of Things architecture, which comprises a pulse signal detection end, an edge gateway and a cloud monitoring platform; the pulse signal detection end is used for detecting partial discharge pulse signals of overhead lines and transmitting the partial discharge pulse signals to the edge gateway; the edge gateway comprises a synchronous pulse trigger module, a time calibration module and an edge analysis module; the edge analysis module is used for generating a positioning distribution map of partial discharge points; the cloud monitoring platform comprises a multi-end data fusion module, a risk assessment module and a result feedback module; the cloud monitoring platform is used for fusing the positioning distribution map and pulse characteristics, outputting a global discharge point correction distribution map, identifying a discharge type based on a discharge characteristic spectrum, generating an insulation state assessment result and feeding back the assessment result to a terminal user; and the application provides a high-reliability, high-efficiency and low-cost solution for insulation state control of a distribution network.

A system and method for pulsed electromagnetic fields (PEMF) tissue engineering enhances musculoskeletal tissue stimulation. A tissue engineering device may include both low and high pulse frequency signal generation components that may alternatively drive one or more coils to generate PEMFs. These PEMFs may be applied to bone tissue, tendons, ligaments, and / or cartilage. A prescribed treatment regimen using the tissue engineering device may include a first period of time where a first pulse frequency is used in treatment that supports tissue proliferation followed by a second period of time where a second pulse frequency (less than the first pulse frequency) is used in treatment that supports tissue differentiation. A treatment regimen may also include, with the frequency characteristic, applying a slew rate to the pulse characteristics that is on the order of around 30 to 100 Tesla per second to drive tissue differentiation in a targeted manner.

The application provides a detection data acquisition method based on diabetes pulse characteristics, which extracts multiple pulse signal characteristics, realizes multiple pulse characteristic fusion representation according to a fusion strategy, and the fusion representation is the finally obtained pulse diagnosis data. The application extracts pulse characteristics from three different perspectives, obtains a fusion matrix through complementary learning, and realizes the fusion representation of the pulse signal by relying on the fusion matrix. Thus, the application solves the limitation of single pulse characteristic in pulse representation, sets independent projection matrices for various characteristics, projects each characteristic to a public subspace, fully utilizes the complementary information between multiple characteristics, and retains the difference. The representation information in the pulse signal is effectively retained. Meanwhile, the application also provides a detection data acquisition system based on diabetes pulse characteristics.

This invention discloses a method for multi-target detection and localization of QD laser alarms based on spatial spectrum estimation. Specifically, it involves: establishing a precise mapping model between the output signal of a four-quadrant detector (QD) and the laser incident angle, including the signal superposition effect when multiple light sources illuminate simultaneously; based on the mapping model, employing a spatial spectrum estimation algorithm tailored to the limited spatial sampling characteristics of the QD detector to separate and estimate multiple simultaneously existing or temporally overlapping laser incident directions; and combining the pulse characteristics of the laser signal, fusing the temporal information with the spatial spectrum estimation results to achieve multi-target detection and localization. This invention overcomes the application limitations of traditional single-target localization models in multi-light source scenarios, providing an accurate input foundation for spatial spectrum estimation; and solves the technical bottleneck of traditional spatial spectrum estimation relying on multiple array elements, achieving direction separation and localization of simultaneously or temporally overlapping laser sources.

The application discloses a fan coil abnormal state diagnosis method and system, obtains a fan current waveform and a coil vibration signal, establishes a heat exchange efficiency benchmark based on motor load change characteristics and heat exchange pipe vibration modes, identifies an efficiency sudden drop area and positions a heat exchange dead zone expansion range, generates a heat transfer coefficient jump data to determine a heat exchange abnormal position table, obtains a supply and return water temperature difference and a water valve opening degree change, forms a water route imbalance feature through coupling analysis of water flow pulse characteristics and flow state conversion points, identifies an air flow field offset amount based on the heat exchange abnormal position table and the water route imbalance feature, determines a diagnosis focus area and generates a layered detection sequence, classifies active and passive damage, extracts damage development rates, generates damage superposition coefficients, identifies a fault coupling amplification area, generates damage synergistic effect data through chain propagation analysis, completes comprehensive diagnosis of the fan coil abnormal state, and realizes accurate identification of multiple abnormalities and accurate positioning of fault causes.

This invention relates to a feedback-type high-power electromagnetic pulse (HMP) power supply protection circuit and method, belonging to the field of electromagnetic compatibility (EMC) technology. The circuit includes a feedback sampling unit, a delay unit, and a graded protection unit. The feedback sampling unit samples and compares the pulse voltage amplitude and pulse duration; the delay isolation unit isolates fast pulse signals, maintaining the integrity of the pulse in the sampling circuit and protecting the protection circuit and downstream equipment when the pulse is too long; the graded protection unit provides separate protection for fast-edge narrow pulses and long-duration pulses. The feedback sampling unit includes a voltage amplitude sampling circuit and a pulse duration sampling circuit. The graded protection unit includes a first-stage fast-response branch and a second-stage discharge branch. This invention is applied to high-power electromagnetic pulse protection for DC and AC power ports. From the perspective of graded protection, different protection schemes are selected according to the pulse characteristics to maximize the safety of the power supply system and downstream equipment.

The present application relates to a heart disease analysis device and a nail oximeter apparatus, the heart disease analysis device comprising a unit for executing a heart disease analysis method based on a photoplethysmography signal, the heart disease analysis method being applied to the nail oximeter apparatus, the method comprises the following steps: acquiring a photoelectric volume pulse wave signal detected by the nail oximeter equipment; original pulse characteristic parameters are extracted from the photoelectric volume pulse wave signals, and a pulse sequence containing the original pulse characteristic parameters is obtained; performing statistical analysis processing on the original pulse characteristic parameters in the pulse sequence to obtain target pulse characteristic information; and obtaining a heart disease analysis result based on the target pulse feature information and a preset conventional value. According to the application, the accuracy of analyzing heart diseases such as atrial fibrillation and premature beat can be improved.

The invention discloses a partial discharge on-line monitoring method based on a high-frequency original signal, which relates to the field of partial discharge monitoring, and comprises the following steps: setting an adaptive variable sampling rate acquisition mechanism based on the energy density sparsity of the high-frequency original signal, and dynamically adjusting the sampling frequency by monitoring the energy entropy value of the signal in real time; obtaining an original signal sequence containing complete partial discharge transient pulse characteristics; a distinguishing operator is constructed by using the chaotic characteristic difference of partial discharge signals and noise to pre-process an acquired original signal sequence, and background noise and non-partial discharge interference signal components are filtered out through adaptive weight distribution; according to the method, the partial discharge source space coordinate solving model is established by fusing the pulse waveform distortion degree and the multi-monitoring-point signal arrival time difference, the partial discharge source positioning precision is improved in combination with the weighted least square method, and comprehensive and accurate technical support is provided for equipment partial discharge monitoring.

The invention discloses an inverter narrow pulse compensation method, system and device and a storage medium, and relates to the technical field of power electronics and inverter control, and the method comprises the steps: collecting narrow pulse multi-source data through a collection part, inputting the narrow pulse multi-source data into a fitting part, and outputting a blocking pulse feature set; inputting the blockade pulse feature set into a calculation part, outputting the number of times and the distribution mode of the compensation pulse, and storing the number and the distribution mode into a compensation part; the blockade pulse feature set is obtained through adaptive polynomial fitting of blockade narrow pulse envelope; the frequency of the compensation pulse is obtained through the pulse width and a preset threshold value; the output distribution mode is obtained through enveloping and least square; the number of times of the compensation pulses stored in the compensation unit and the distribution mode are superimposed and executed at the same position in the next cycle. The method provided by the invention has better effects in the aspects of completeness of blocking pulse characterization, computability of compensation times and distribution modes and cycle consistency of compensation execution.