427 results about "Signal variation" patented technology

The invention relates to the technical field of communication engineering, and discloses a power line carrier and wireless dual-mode fusion optimized communication method, which comprises the following steps of: 1, acquiring signal quality, noise and delay data of a power line and a wireless link in real time, and constructing a prediction model by utilizing historical data; step 2, dynamically adjusting a judgment threshold value of link switching in real time based on the prediction model, and ensuring that switching is triggered only when the signal change exceeds a preset range; step 3, based on the dynamic threshold, combining multiple indexes of signal-to-noise ratio, delay, packet loss rate and network load; according to the method, the necessity of link switching can be more intelligently judged by dynamically adjusting the judgment threshold of link switching and adopting a fuzzy logic decision mechanism, frequent switching during tiny fluctuation of signals is avoided by dynamic threshold adjustment, and a fuzzy logic system integrates multiple factors, so that the decision is finer, and the reliability of link switching is improved. And unnecessary delay and resource waste are reduced, so that the stability of a communication system is improved.

The invention discloses a brain deep nerve stimulation method and system based on adaptive adjustment, and relates to the technical field of brain deep nerve regulation, and the method comprises the steps: collecting a local field potential signal of a brain deep target region of a target patient, and extracting a beta frequency band power spectrum density and a gamma frequency band phase synchronization index as neural activity characteristic parameters; determining an individual baseline value and a preset threshold value based on historical data, and outputting a stimulation adjustment trigger signal when the beta frequency band power spectral density exceeds the individual baseline value and the gamma frequency band phase synchronization index is lower than the preset threshold value; in response to the trigger signal, calculating an optimal stimulation parameter combination through a gradient descent optimization algorithm and executing nerve regulation; and monitoring the signal change after regulation and control, calculating a relative change rate and updating a threshold value. Through a two-parameter joint judgment mechanism and a threshold updating strategy, individualized adaptive adjustment of stimulation parameters is realized, and the stimulation accuracy and the treatment effect are improved.

The invention provides a non-intrusive diagnosis method for typical rotor faults of a synchronous phase modifier, and the method comprises the steps: carrying out finite element modeling and fault working condition setting, carrying out simulation to obtain magnetic field distribution data under each working condition, carrying out the extraction and feature analysis of stray magnetic field signals, extracting time domain and frequency domain signals of a stray magnetic field under healthy and various fault working conditions, and carrying out the diagnosis of the typical rotor faults of the synchronous phase modifier. Fundamental wave, odd-even harmonic components and signal change trends are compared and analyzed, stray magnetic field characteristics corresponding to faults are extracted and recognized, diagnosis criterion establishment and fault recognition are carried out, diagnosis criteria and threshold values of rotor turn-to-turn short circuit, dynamic eccentricity and shaft-diameter composite eccentricity faults are established according to the stray magnetic field characteristics, and the fault diagnosis accuracy is improved. And when the specific harmonic amplitude or change characteristic of the stray magnetic field signal exceeds the criterion threshold, determining the rotor fault of the corresponding type and degree. Equipment dismounting or structure reconstruction is not needed, the detection system is simple in structure, internal fault characteristics of the phase modifier can be reflected in real time, and high sensitivity and practicability are achieved.

The invention provides an LED lamp adaptive speed regulation heat dissipation method and system based on real-time junction temperature monitoring. The method comprises the following steps: S100, acquiring a PWM signal or an analog signal of an LED driving command signal in real time; s200, on the basis of the change of the driving instruction signal, feedforward prediction is carried out by using a dynamic thermal inertia mapping model, and a feedforward fan control quantity is generated; s300, LED junction temperature is monitored in real time through a forward voltage method, and feedback fan control quantity is generated through a feedback controller according to the deviation between the real-time junction temperature and the target junction temperature; and S400, synthesizing the feedforward control quantity and the feedback control quantity to generate a fan PWM control signal, outputting the fan PWM control signal to a fan driving circuit, and adjusting the rotating speed of the cooling fan. According to the method, driving signals and junction temperature information are processed in parallel, and feedforward and feedback control is combined, so that self-adaptive accurate regulation and control are realized, thermal load change is quickly responded, system lag is effectively inhibited, and LED heat dissipation performance is optimized.

The invention discloses a distribution box operation state monitoring method and system, and relates to the field of distribution boxes, and the system comprises an acquisition module which is used for collecting current and voltage signals of each loop in a distribution box, surface temperature distribution of a box body and opening and closing state signals of a cabinet door, and converting the collected analog signals into a digital signal sequence; the extraction module is used for receiving the digital signal sequence and extracting a signal fluctuation feature, a temperature field distribution feature and a state signal change feature to generate a three-dimensional feature set; the system can obtain loop electrical parameters, box body temperature and cabinet door state in real time, accurately analyze operation characteristics to deduce state trend, quickly position defective loop components and influence range in case of abnormity, scientifically evaluate health level, timely give an early warning, synchronously disconnect power supply of associated equipment in case of severity, effectively reduce fault shutdown, and improve work efficiency. The power utilization safety and the maintenance efficiency are improved, and stable operation of the distribution box is guaranteed.

The invention provides an electric blanket heating wire state judgment method and system, a medium and a product, and relates to the technical field of safety monitoring. In the method, a control processing unit firstly samples at a first preset frequency and calculates a signal change rate; and when the signal change rate value exceeds the standard rate threshold value, the control processing unit judges that the electric blanket is in a suspected heat accumulation state, and at the moment, the output power of the heating wire is controlled to be reduced to a preset duty ratio. Then, the control processing unit adopts a second preset frequency to collect signals and filter the signals, extracts signal values at the first moment and the second moment, and calculates the characteristic value of the thermal attenuation trend; and finally, the control processing unit realizes the distinguishing between the local wire twisting state and the folding state based on the deviation degree of the characteristic value and the standard thermal attenuation characteristic value. According to the method, the technical problem that the high-temperature cause cannot be distinguished only through the instantaneous temperature is relieved, and accurate recognition of the twisted wire fault and the folding working condition is achieved.

The present disclosure relates to a delay module for a CAN device. The delay module is configured to delay only a single signal change of an RXD signal, wherein the single signal change forms the end of an idle state. Use of the delay module allows a second RXD signal to be generated. The present disclosure further relates to a CAN device comprising two CAN controllers. Each of the two CAN controllers may be provided with one of the two RXD signals. The CAN device may further be configured to detect possible errors based on the decoded bits of the RXD signals. As a result, the CAN device can communicate error-free with both distantly located further CAN devices and closely located further CAN devices, while ensuring a high data rate. The present disclosure also relates to a method for the delay module.

The invention provides an ultrasonic guided wave probability imaging method for structural damage in a temperature change environment, an improved U-Net neural network is constructed, input data of the improved U-Net neural network comprises an original guided wave signal and normalized temperature offset, and a model comprises a three-stage down-sampling module, a double-convolution layer and a three-stage up-sampling module. The attention mechanism module is connected behind the downsampling blocks of all levels and used for dynamically adjusting the feature weight, the representation capability of temperature features is enhanced, and the network can learn nonlinear mapping of temperature changes and signal changes. After model training data are obtained, filtering processing is carried out on original ultrasonic guided wave signals, normalized temperature deviation processing is carried out on temperature data, and the ultrasonic guided wave signals at the standard temperature are output through model prediction, so that the amplitude and phase interference of the temperature on ultrasonic guided waves is reduced, and the accuracy of ultrasonic guided wave detection is improved. And high-precision positioning of structural damage is realized in combination with a probability imaging technology. The method is small in data demand and few in execution steps, and the damage positioning efficiency is better than that of a traditional method.

The invention relates to a grabbing manipulator positioning device and method for quickly assembling and disassembling a drill, and belongs to the technical field of coal mine machinery design. The device comprises a drill rod transfer device, a drill rod box, a grabbing manipulator, a mounting frame, a driving motor, a PLC (Programmable Logic Controller), an induction block, a proximity switch sensor and the like. The sensing block is aligned with the corresponding device or the drill rod groove in position, and the proximity switch sensor is arranged below the driving motor. During working, the PLC controls the driving amount of the driving motor according to the signal change of the proximity switch sensor. The grabbing manipulator is driven to move, sensor signals are monitored, the driving amount of the driving motor is controlled according to the number of times, speed reduction and precise stopping are conducted when a target is approached, and drilling rod grabbing or releasing is completed. By means of the mode, rapid and accurate positioning can be achieved, the positioning speed and precision are improved, the drilling and unloading efficiency is improved, the operation stability is improved by adopting an intelligent control strategy, and the system flexibly adapts to different drill rod groove numbers and is high in universality and expandability.

The invention discloses a laser intelligent management system of a laser particle analyzer, particularly relates to the technical field of laser control, and is used for solving the problem that pollution monitoring is not accurate due to intermittent work of a laser when an existing laser particle analyzer is in an energy-saving mode. By synchronously acquiring a laser working state signal and a background scattered light signal of an optical window, whether the laser is in an initial stage awakened from a low-power-consumption state is judged, and a nonlinear response stage dominated by pollutant state change in the background scattered light signal is identified; analyzing the symmetry of the signal change track at the stage to generate a symmetry breaking index, and synchronously executing Granger causal relationship test on the driving current and background scattered light signal time sequence data to obtain a causal relationship index; and distinguishing signal abnormal sources based on a symmetry breaking index and a causal relationship index so as to evaluate the current pollution level of the optical window, adaptively adjusting pollution monitoring parameters and controlling the working mode of a laser.

The invention relates to the technical field of laser radar signal processing, and discloses a laser radar echo signal processing method. The method comprises the following steps: acquiring an original echo signal sequence of a plurality of scanning periods, wherein the sequence comprises signal intensity data of all detection channels at each timestamp; comparing the signal intensity change mode of each detection channel in each scanning period with the signal intensity change mode of all detection channels in all scanning periods, and extracting the signal fluctuation index of each detection channel in each scanning period; analyzing a signal intensity distribution interval and a signal fluctuation index of each detection channel in each scanning period, and generating a signal dynamic variation; then comparing signal space distribution characteristics of each detection channel and all the rest detection channels in each scanning period and signal intensity gradient differences of adjacent channels, and extracting a space correlation difference; and fusing the signal dynamic variation of all the detection channels and the spatial correlation difference to generate a signal quality evaluation value of each scanning period.

The invention discloses a reaction capability evaluation method, head-mounted display equipment and a computer readable storage medium, and relates to the technical field of head-mounted display equipment, the method is applied to the head-mounted display equipment, and the method comprises the following steps: through a prompt output module, outputting prompt information corresponding to at least one reaction test action, and determining prompt output time; through a bio-electricity signal detection module, bio-electricity signal change caused by the fact that the wearer executes the reaction test action is detected in the target body surface area, and signal change time is determined; action completion time is determined through a reaction test action detection module; based on the prompt output time and the signal change time, the cognitive response ability of the wearer is evaluated, and a cognitive response ability evaluation result of the wearer is obtained; and based on the signal change time and the action completion time, evaluating the execution response capability of the wearer to obtain an execution response capability evaluation result of the wearer. According to the invention, refined layered evaluation of the reaction capability can be realized.

The invention discloses an automatic fault prediction method and system for operation and maintenance of a base station, and relates to the technical field of operation and maintenance of the base station, and the method comprises the steps: collecting a plurality of signal features at a plurality of monitoring positions of a communication base station, carrying out the change analysis of the signal features of a base station antenna, and obtaining a plurality of signal change parameters; performing base station antenna offset analysis according to the plurality of signal change parameters to obtain a plurality of antenna offset parameters, and performing offset credibility analysis to obtain a plurality of offset credibility; acquiring environment parameters in an environment where the communication base station is located, and performing base station antenna influence offset analysis in combination with the plurality of antenna offset parameters to obtain a plurality of antenna influence offset parameters; and according to the plurality of offset credibility and in combination with the plurality of antenna influence offset parameters, calculating to obtain an antenna fault scale, and taking the antenna fault scale as a base station operation and maintenance fault prediction result. According to the invention, the technical problem of poor fault prediction accuracy in operation and maintenance of the base station in the prior art is solved.

A power transmitter (101) provides power to a power receiver (105) via an inductive power transfer signal which is also used by the power receiver (105) for communication by load modulation. The power receiver (105) comprises a transmitter (509) arranged to transmit symbols in accordance with a first or second communication mode where the first mode modulates data symbols by a chip sequence from a set of sequences and the second communication mode does not. The power receiver (105) may transmit data symbols requesting a power transfer signal variation using a chip sequence from the set. A detector (515) may detect if the variation occurs, and if so a selector (513) selects the first communication mode and otherwise it selects the second communication mode. The approach may allow selection of an appropriate communication mode without requiring data to be transmitted from the power transmitter. The approach may provide improved backwards compatibility.

The invention relates to the technical field of electrostatic dust collection and discloses an accurate frequency adjustment method for an intelligent frequency modulation high-voltage power supply of an electrostatic dust collector. The method comprises the steps of collecting voltage signals with frequency fluctuation in operation of a high-voltage power supply to form a voltage sequence; dividing period segments by using wave crest distribution in the voltage sequence, and clustering to obtain adjustment subsequences; obtaining a trend fluctuation index based on local signal change trend fluctuation and signal differences of the adjustment subsequences, and obtaining an amplitude drop difference and an amplitude interval difference according to an amplitude change trend difference and an amplitude bit sequence change trend difference; obtaining a period stability coefficient by combining the difference, the average condition of the trend fluctuation index and the average condition of the sub-sequence similarity; constructing a Hankel matrix and performing singular value decomposition, and obtaining a main component proportion and a difference index based on a singular value condition; and according to the Hankel matrix line data correlation, the period stability coefficient, the main component proportion and the difference index, obtaining a signal stability index, and according to the signal stability index, accurately adjusting the high-voltage power supply frequency.

The invention discloses a multi-scene signal data-oriented multi-block mixed expert radio frequency fingerprint identification method, and belongs to the field of software radio. According to the implementation method, a plurality of expert modules are adopted, and each expert module is designed to be used for extracting feature representations under different conditions so as to cope with signal changes under various complex scenes. A lightweight and efficient route selection module is adopted to dynamically distribute and input signals to the most matched expert module according to the dimensionalities such as statistical characteristics, frequency domain structures or time sequence characteristics of the input signals, or output results are weighted and fused among a plurality of experts, so that the pertinence and flexibility of feature extraction and recognition are improved. A cooperative mechanism between expert modules is optimized by adopting a joint training strategy, so that an individual recognition model can maintain the independent expression ability of experts, and the convergence speed and stability of the whole model are improved by sharing bottom-layer expression and high-layer decision-making. The method is suitable for the field of software radio, and high-precision radiation source individual identification is realized.

The invention relates to the technical field of sensor multi-node calibration, in particular to a new energy automobile gear shifting position sensor multi-node calibration method based on the Internet of Things, and the method comprises the steps: obtaining a gear signal of each sensor in a monitoring time period; acquiring a gear signal sequence; acquiring a signal change rate of a single gear signal sequence; classifying each gear signal sequence according to the gear of each gear signal sequence and the gear of the previous gear signal sequence on the time sequence; acquiring a signal consistency factor of the single sensor in the single category according to the difference between the gear signal sequences of the single sensor in the single category; acquiring the signal stability of each sensor; the dynamic weight coefficient of each sensor is obtained by combining the difference degree between the gear signal sequence of each sensor and the gear signal sequence of other sensors; and the gear signal of each sensor is calibrated. According to the method, the calculation precision of the dynamic weight coefficient is improved, so that the multi-node calibration precision of the sensor is improved.

The chain vector results are analyzed to identify a faulty scan chain in the circuit and a fault associated with the faulty scan chain. The scan vector results are analyzed to identify one or more faulty scan element candidates on the faulty scan chain. An analog simulation is then performed to identify a faulty component candidate of the one or more faulty scan element candidates. During the process, a component of each of the one or more faulty scan element candidates that is sensitive to a change in signal at an input of each of the one or more faulty scan element candidates may be determined. Physical failure analysis may be performed on the circuit to locate one or more defective components in the faulty component candidates.

According to the infrared combustible gas sensor and the method thereof, firstly, original voltage signals of a measurement channel and a reference channel and original signals of a temperature sensor are subjected to digital filtering, basic concentration is calculated based on the voltage of the measurement channel and the voltage of the reference channel after filtering, and dynamic impact detection is carried out; obtaining a reference channel signal change rate; furthermore, a self-adaptive dynamic compensation gain is introduced, the gain is dynamically adjusted according to the reference channel signal change rate and the filtered reference channel voltage, and the basic concentration is comprehensively compensated by combining the filtered temperature, so that unbalance caused by thermal shock in the photoelectric system is reflected more directly and more quickly. Therefore, the measurement precision and the data reliability of the infrared combustible gas sensor in a complex and changeable environment can be remarkably improved, and more accurate and more robust effects of compensation can be realized under different working conditions.

The invention discloses a dynamic switching method based on a double-link converged communication system and related equipment, and relates to the technical field of wireless communication. The method is applied to the terminal equipment comprising a first communication module and a second communication module. The method comprises the following steps: calculating a first link quality evaluation value in real time, and obtaining a quality trend characteristic value representing a signal change direction in combination with historical data; based on the first link quality evaluation value, the quality trend characteristic value and the second link availability evaluation value, intelligently switching working modes: executing a first working mode (single link low power consumption) when the link is stable; executing a second working mode (double-link parallel transmission) when the link is deteriorated or a big data demand exists; and executing a third working mode (second module independent transmission) when the link fails. According to the method and the device, the problems of frequent fluctuation and low transmission efficiency caused by single threshold switching in related technologies are solved, and dynamic balance of communication reliability, rate and power consumption in a complex environment is realized.

Microprocessor for a scale system for a mobile storage carrier operates in three states: motion, stable, and fault where stability is determined based on load cell signal variations or external sources and a fault state follows a stable state in response to signal drift in one or more load cells.

The invention discloses a device vibration signal change-based temperature vibration data processing and monitoring system and method, and belongs to the technical field of data processing, a data acquisition module acquires and preprocesses a multi-modal signal to obtain a preprocessed multi-modal signal, a feature extraction module performs feature extraction on the preprocessed multi-modal signal to obtain a feature extraction result, and the feature extraction result is a feature extraction result. The method comprises the following steps: training a health assessment model to obtain a time domain feature, a frequency domain feature and a time-frequency domain feature, performing data fusion on the time domain feature, the frequency domain feature and the time-frequency domain feature by a data fusion module to obtain a fusion feature, inputting the fusion feature into the trained health assessment model by a health assessment module to obtain a health state assessment result, judging whether to trigger an early warning mechanism, and if so, generating early warning information. According to the method, the vibration signals and the temperature signals of the equipment can be continuously monitored, potential fault signs can be recognized earlier, more comprehensive signal representation is obtained by fusing the time domain features, the frequency domain features and the time-frequency domain features, the fault detection accuracy is improved, and early warning is achieved.

The invention relates to the technical field of medical data processing, in particular to an intelligent drainage method and system based on cerebrospinal fluid pressure, and the method comprises the steps: obtaining a pressure signal curve and a pulse period of a cerebrospinal fluid intelligent drainage system at each detection position; obtaining a synchronous conduction error value according to the signal change trend in the pulse period of the to-be-analyzed signal curves of each detection position and other detection positions in combination with the signal change trend between the historical signal curves; according to the signal delay condition between pulse periods in the signal curve to be analyzed of each detection position and other detection positions, combining the signal delay condition of the historical signal curve to obtain a signal delay characteristic value; according to the synchronous conduction error value, the signal delay characteristic value and the signal change trend, analyzing the signal artifacts of each pulse period in the signal curve to be analyzed to obtain an artifact-removed signal; the de-artifact signal is used for a drainage operation. According to the invention, the occurrence of misrecognition is reduced, and the reliability of intelligent drainage decision is ensured.

The invention discloses an analog quantity data adaptive sampling method and system based on a sliding window. The system comprises a data acquisition module, a window setting module, a sliding window module, a sampling decision module and a data storage module. According to the method, the size of a sliding window is dynamically adjusted according to analog quantity signal change frequency and system real-time requirements; the sampling rate is intelligently decided by calculating the change rate of data in the sliding window. When the change rate is lower than a threshold value, the sampling rate is automatically reduced to avoid redundant data; when the change rate is high or a sudden change signal occurs, the sampling rate is maintained or increased to retain key information. According to the method, the change rate is estimated through the standard deviation, the change rate is adaptive to continuously changing analog quantity signals, the mean value is dynamically updated in an exponential weighted moving average (EWMA) mode, and the stability is improved.

The invention discloses a battery mechanical damage monitoring method and system in the transportation process of an electric vehicle based on acoustic emission spectrum analysis, and the method comprises the steps: carrying out the multi-scale decomposition of an original signal sequence through wavelet transform, separating out a high-frequency transient component and low-frequency background noise, and obtaining a denoised elastic wave signal; calculating time domain features including peak amplitude and duration according to the denoised elastic wave signal, and combining frequency domain features such as a main frequency component to obtain a comprehensive feature vector; if the peak amplitude of the comprehensive feature vector exceeds a preset threshold value, judging that the event is a potential damage event, and extracting a damage related subset from the feature vector to obtain a damage candidate feature; training the damage candidate features through a support vector machine classifier to obtain damage type labels; and aiming at the damage type label fusion transportation environment data, a sliding window is adopted to analyze and track the signal change trend, and the damage evolution degree is determined. According to the invention, accurate identification, classification and dynamic monitoring of transportation damage of the battery pack are realized.

The invention relates to the technical field of ultrasonic flowmeter calibration, and discloses an ultrasonic flowmeter calibration system and method based on a time difference method. According to the method, original signal data output by the ultrasonic flowmeter at a starting time point and an ending time point are collected, and meanwhile the time interval between the two time points is calculated. Then, the original signal data at the starting time point and the ending time point are preprocessed, and a more accurate starting preprocessing signal and a more accurate ending preprocessing signal are obtained; signal features are extracted from the preprocessed signals, a starting signal feature set and a terminating signal feature set are formed, and feature difference measures between the starting signal feature set and the terminating signal feature set are calculated; the characteristic difference measure is divided by the time interval to obtain the signal change rate. The signal change rate is compared with a preset threshold value, and calibration parameters of the ultrasonic flowmeter are adjusted according to the comparison result. According to the method, the working state of the ultrasonic flowmeter can be deeply analyzed from the signal feature level, and compared with a traditional calibration method, the calibration precision is effectively improved.

The invention relates to an RFID-based indoor distribution link intelligent diagnosis method and system, and the method comprises the steps: transmitting a preset frequency signal through an excitation signal generation module, recording the feedback intensity of a passive tag, and generating a link state distribution diagram; extracting a signal ratio and a fluctuation trend to generate an adjustment instruction set; adjusting power to obtain an alignment state table; identifying stable section signal change to form an adjustment mark graph; and finally reconstructing a link response distribution output state evaluation value list. According to the invention, link abnormity can be accurately positioned, signal distribution can be dynamically regulated and controlled, complex scene adaptability can be enhanced, and indoor distribution link diagnosis efficiency and precision can be significantly improved.

The invention belongs to the technical field of state observation of piezoelectric ceramic drivers, and relates to a state observation compensation method and device for a piezoelectric ceramic driver. Constructing an asymmetric item of the input signal based on the asymmetry of the hysteresis of the input signal of the piezoelectric ceramic driver in the positive and negative voltage intervals, and constructing a target hysteresis equation; constructing an input signal change rate item based on the frequency-dependent characteristic of an input signal of the piezoelectric ceramic driver in a positive and negative voltage interval, and constructing a target output displacement equation; based on the target hysteresis equation and the target output displacement equation, obtaining an input and output identification model of the piezoelectric ceramic driver, and optimizing the model to obtain a target input and output identification model; acquiring an observed value of the hysteresis amount of the piezoelectric ceramic driver by using a hysteresis state observer; and constructing a feedforward inverse model compensation controller by using a direct model method, and outputting a control signal based on the observation value of the hysteresis so as to control the piezoelectric ceramic driver, thereby realizing high-precision compensation of the hysteresis of the piezoelectric ceramic driver.

The invention provides a segmented adaptive SG filtering method and device based on cosine weight transition. The method comprises the following steps: obtaining a noisy fault signal of a power distribution network; extracting local feature indexes of the signals, wherein the local feature indexes comprise an average gradient representing the change frequency of the signals and a composite feature index representing the noise level; dynamically determining a window length and a polynomial order of SG filtering based on the local feature indexes; the transient stage is the first 1 / 2 period of the post-fault signal, the steady-state stage is the subsequent part of the post-fault signal, an overlapping region is arranged at the junction of the transient stage and the steady-state stage, the overlapping region is a 1 / 2 period following the transient stage, and a cosine weight function is adopted to perform weighted fusion on filtering results of the two stages in the overlapping region; and splicing the filtering results of the non-overlapping region and the overlapping region of the transient stage and the non-overlapping region of the steady stage, and outputting a filtered fault feature signal.

The embodiment of the invention provides a method and equipment for determining an edge position error and a storage medium. The method includes determining a degree of signal variation of a lithographic simulation signal for a control point in a mask pattern at a current position of the lithographic simulation pattern; updating the position of the control point in the photoetching simulation pattern according to the signal change degree of the photoetching simulation signal of the control point at the current position so as to determine the target position of the control point; and determining an edge position error of the control point based on the difference between the initial position and the target position of the control point. In this way, the efficiency of determining the edge position error can be improved, and then the efficiency of optical proximity effect correction is improved.