240 results about "Waveform distortion" patented technology

The invention relates to the technical field of electric power monitoring analysis, and discloses an intelligent analysis system for electric power monitoring data based on a mutual inductor. The system comprises a mutual inductor data acquisition and structuring module which acquires a current waveform, a voltage waveform and a harmonic component in real time, and generates a standardized monitoring data unit through preprocessing, field mapping and association identification establishment; the theoretical monitoring value calculation module constructs a dynamic calculation model according to historical power data, and an input standard data unit outputs a theoretical value; the rule conformity verification module is used for matching the equipment type with the operation rule and generating single compliance judgment; a multi-dimensional difference analysis module compares a theoretical value with a measured value from time domain deviation, frequency domain deviation and waveform distortion, and generates an equipment-level difference coefficient matrix; the association network construction module is used for constructing a multi-monitoring-point association map according to the equipment identifier and the position information; and the anomaly positioning and strategy generation module combines the map, compliance judgment and a difference matrix, calculates a risk score, generates an anomaly probability distribution map, positions anomaly and matches a monitoring strategy.

The invention belongs to the technical field of semiconductor testing, and discloses a novel automatic detection system and method for the electrostatic protection performance of a power device. A distributed parasitic parameter network model is constructed by acquiring packaging structure parameters of a to-be-tested power device and physical layout data of a test fixture, key parasitic parameter distribution is identified in combination with a time domain reflection measurement technology, a waveform distortion coefficient is calculated, and a spatio-temporal evolution model of electrostatic pulse propagation is constructed. Based on the model, a compensatory predistortion waveform is generated to counteract the parasitic effect of a transmission path, a device port response signal is collected in real time, an energy dissipation characteristic spectrum is extracted through wavelet packet decomposition, and quantitative evaluation of the electrostatic protection performance is achieved. According to the invention, the test precision and repeatability are improved, and the method is suitable for electrostatic protection tests of various novel power devices, especially high-frequency wide-band gap devices.

The invention provides an abnormal blood sampling inspection data evaluation processing method and system of a blood sampling system. Wherein the diffusion track dynamic state of an anticoagulant-blood contact surface in a blood sampling tube is tracked in real time, dielectric response waveform distortion characteristics on the two sides are synchronously collected through a capacitance sensor array, and diffusion form parameters are generated; curvature sudden change is analyzed to trigger an acoustic fluid device to modulate audio frequency and flow velocity, and a composite disturbance field is formed; performing capacitance axial scanning on the disturbed mixed fluid, extracting phase angle offset and gradient abrupt change point coordinates, and constructing a dielectric anomaly three-dimensional map; matching a standard dielectric model, positioning a coordinate set of a concentration gradient imbalance area and a coordinate set of an eddy current attenuation area, and generating an anticoagulant abnormal index and a mixed defect matrix in combination with phase angle offset difference; and establishing a data anomaly degree evaluation function based on the anomaly index and the defect matrix, dynamically associating a clinical error threshold, and outputting a test evaluation result. According to the invention, anticoagulant diffusion can be monitored in real time, and the mixing quality error can be accurately evaluated.

The invention relates to a wireless power transmission system parameter identification method based on a time domain differential model, and belongs to the technical field of wireless power transmission system control. The method comprises the following steps: establishing a parameterized time domain dynamic physical model; collecting system dynamic response data; constructing an optimization target based on a time domain residual error; and performing optimal parameter estimation based on iterative optimization. According to the method, a time domain dynamic physical model of a wireless power transmission system is constructed, and unknown parameters are solved through an iterative optimization algorithm with a minimum waveform matching error as a target. According to the algorithm, in an iteration process, a physical model is called to carry out forward differential equation solution, a time domain residual error between a model solution current and a real measurement current is used to drive a parameter estimation value to converge, and finally high-precision and high-robustness wireless power transmission system parameter identification under any working frequency is realized. The problem that in the prior art, due to static stiffness and sensitivity to waveform distortion of a theoretical model, the identification precision is insufficient is effectively solved.

The invention relates to the field of crystal detection, and discloses a multifunctional comprehensive scintillation crystal and semiconductor material energy spectrum test system, which comprises a crystal adaptation module for judging the type and size of a placed crystal through an optical identification and parameter matching mechanism, and a signal acquisition module for amplifying, filtering and digitally processing an acquired signal, the signal correction module is used for correcting waveform distortion and baseline drift through a dynamic gain adjustment algorithm of a low-noise pre-amplifier and a multi-channel pulse analyzer; the data analysis module is used for generating an energy spectrum curve according to input signals and calculating energy resolution, counting rate, light attenuation time or carrier mobility, and the environment calibration module is used for dynamically evaluating shading degree, environment light, temperature and electromagnetic interference through an optical sensor and a temperature and humidity detector in the camera obscura and outputting updated calibration parameters. The method has the advantages of improving the detection efficiency, precision and consistency.

The invention discloses an intelligent diagnosis system for power utilization abnormal information acquisition, particularly relates to the technical field of power system monitoring, and is used for solving the problems of waveform distortion and broadening caused by transmission line distribution parameters in the long-distance wired transmission process of an existing system. The system collects abnormal characteristic waveform data through a distributed intelligent terminal, selects a characteristic harmonic component in the power frequency voltage of a power line to construct an inherent test signal, extracts the envelope form similarity of a response signal and the test signal through envelope analysis as a first distortion evaluation index, and obtains a second distortion evaluation index after statistical significance judgment. Performing instantaneous frequency stability analysis on the signal with significant distortion to obtain a second distortion evaluation index, and finally generating a corresponding waveform compensation parameter based on double indexes to realize real-time compensation correction; the integrity of the abnormal characteristic waveform in the transmission process is effectively maintained, and the accuracy and reliability of power consumption abnormity diagnosis are remarkably improved.

The invention relates to the technical field of electronic exploder control, in particular to an anti-electromagnetic interference dynamic threshold control system and method for an electronic exploder, and aims to solve the problem that the electronic exploder is easily interfered in a complex electromagnetic environment to cause false triggering or missing detection. According to the system and the method, surrounding electromagnetic signals are acquired, time domain, frequency domain, waveform distortion and interference source features are extracted and fused to generate clustering feature vectors, and the signals are divided into pure interference, pure detonation control and superposed signals by using an improved K-means algorithm; and based on the clustering result and the interference intensity, adjusting an identification threshold in real time through a staged dynamic threshold adjustment formula, introducing a multi-dimensional reference factor of historical interference data after the interference is weakened, and stably recovering the threshold to a normal level by adopting a staged adaptive recovery mechanism. According to the system and the method, the anti-interference capability of the electronic detonator in a complex electromagnetic environment can be remarkably improved, and the safety and the accuracy of detonation operation are ensured.

The invention relates to the technical field of electronic component parameter optimization, in particular to an electronic component parameter optimization method and system, and the method comprises the following steps: collecting high-frequency measurement data of an electronic component; performing preliminary interference separation on the high-frequency measurement data to identify and suppress continuous waveform distortion caused by impedance mismatching of the transmission line and accidental transient electromagnetic pulses caused by reduction of shielding capability of the transmission line, and obtaining data after preliminary interference separation; performing purity evaluation on the data after the preliminary interference separation to quantify the degree of residual interference in the data after the preliminary interference separation to obtain a purity evaluation result; and dynamically adjusting an optimization strategy and a data weight of an electronic component parameter optimization program according to a purity evaluation result so as to carry out electronic component parameter optimization. The accuracy and efficiency of parameter optimization of the electronic component can be improved.

The invention relates to the technical field of intelligent control of power electronic converters and induction heating, in particular to an intelligent control system of a medium-frequency power supply, which comprises a data acquisition module configured to acquire end-side voltage data and end-side current data of power conversion hardware in real time; the feature extraction module is configured to receive the end-side voltage data and the end-side current data and extract broadband waveform distortion features; the state evaluation module is configured to receive the broadband waveform distortion characteristics and calculate a model trust entropy value based on the broadband waveform distortion characteristics; the self-adaptive control module is configured to receive the model trust entropy value, trigger a second control mode to generate a second switch instruction and send the second switch instruction to the power conversion hardware; the model trust entropy represents a prediction deviation degree of a preset robust control model to the current real physical state of the power conversion hardware; according to the invention, the problem of insufficient perception of fine-grained service parameters in the background technology is solved.

The invention discloses a laser radar multi-target ranging method and system based on adaptive waveform matching, and relates to the technical field of laser ranging, and the technical scheme is characterized in that the adaptive waveform matching mechanism proposed by the invention dynamically adjusts convolution kernel sampling points through a deformable convolutional network (DCN), and the adaptive waveform matching is realized; various nonlinear waveform distortions caused by electric field interference and complex target reflection characteristics can be actively adapted, and a customized matching template is generated for each input waveform. Equivalently, the system is endowed with the capability of eliminating counterfeit and keeping true in a strong electromagnetic interference environment, so that the robustness to special working conditions of ultra-high voltage hot-line work is fundamentally improved.

The invention discloses a distribution line fault detection method and device, equipment and a storage medium, and relates to the technical field of electric power inspection, hidden danger features are extracted through LSTM time sequence analysis, time sequence modeling is performed on current and voltage waveforms, harmonic distortion rate, waveform distortion and other features are extracted, and early abnormality of the equipment can be accurately identified through quantitative analysis of the features, so that the fault detection accuracy is improved. Early warning before a fault is achieved, and the passive situation that an existing system can only conduct positioning after the fault occurs is changed. The fault type is subjected to weighted fusion judgment by using the random forest + SVM algorithm, and the advantages of the two algorithms are integrated, so that the possible misjudgment condition of a single algorithm is greatly reduced, and the accuracy of fault judgment is improved. Secondly, waveform correction is introduced into a traditional double-end positioning formula, local spectrum analysis of edge nodes is combined, traveling wave propagation speed errors are corrected, dependence on clock synchronization of equipment at the two ends is reduced, and the fault positioning precision is improved.

The invention discloses a fault symptom rapid identification method, a fault symptom rapid identification device, a fault symptom rapid identification device and a computer readable storage medium for a converter transformer valve side external construction frequency resonance test, and the method comprises the steps: firstly, carrying out the real-time synchronous collection of multi-dimensional parameters, such as voltage, current, local discharge amount and waveform distortion; on the basis, a multi-parameter comprehensive criterion system is established, and fault type priorities are configured, so that accurate classification and identification of different types of fault symptoms are realized; a preset linkage disposal operation sequence is automatically triggered according to an identification result, and an automatic closed loop from monitoring and early warning to active protection is formed; and finally, through whole-process data recording and report generation, the traceable management of the fault information is perfected. According to the whole scheme, multi-source information fusion and intelligent decision control are combined, and systematic technical support is provided for early warning and quick response of faults in the test process.

The invention provides a solar inverter grid-connected protection method, device and equipment and a storage medium. The method comprises the following steps: collecting power grid state data in real time through a virtual synchronous machine of a grid-connected inverter; according to a power grid supporting capability index of the power grid state data and historical waveform data, determining a voltage extreme value and a waveform distortion feature vector in a future preset duration, and generating a dynamic protection threshold set; when any threshold in the dynamic protection threshold set is triggered, generating a hash value according to the current fault waveform data, performing row distributed verification in the block chain node network, and outputting a verification result identifier; and performing multi-mode protection on the grid-connected inverter according to the fault level of the verification result identifier. Through the implementation of the scheme of the invention, the protection strategy can be adaptively adjusted according to the real-time state and waveform trend of the power grid, and the accuracy and response speed of fault recognition are remarkably improved.

The invention relates to the technical field of integrated photoelectron and electro-optical modulation, in particular to a thin-film lithium niobate electro-optical modulator structure and a preparation method of the thin-film lithium niobate electro-optical modulator structure. The buried layer is located on the upper surface of the substrate; the partially-etched thin film lithium niobate layer comprises a partially-etched thin film lithium niobate flat plate layer and a thin film lithium niobate ridge waveguide, the partially-etched thin film lithium niobate flat plate layer is located on the upper surface of the buried layer and exposes a part of the buried layer, and the thin film lithium niobate ridge waveguide is located on the partially-etched thin film lithium niobate flat plate layer; the partially-etched buffer layer is located on the partially-etched thin film lithium niobate layer, and the side wall of the partially-etched thin film lithium niobate flat plate layer is exposed; and the metal electrode is in electric contact with the side wall of the partially etched thin film lithium niobate flat plate layer. Therefore, the problems of low-frequency modulation waveform distortion, direct-current bias point drift and the like caused by electro-optical relaxation and electric field shielding of a related thin-film lithium niobate electro-optical modulator are solved.

The invention discloses a track irregularity dynamic detection method based on inertial navigation and non-filtering, which belongs to the field of railway track detection, and comprises the following steps: based on an inertial measurement unit, performing global integrated navigation solution by combining zero-speed information, a speed sensor and a GNSS positioning result to obtain a global reference navigation state sequence; point cloud registration and key point extraction are carried out on the two-dimensional point cloud obtained by scanning the surface of the track to be detected, and key point coordinates are obtained; performing mechanical arrangement of the sliding window inertial navigation system by taking the target chord length as the window length to obtain a bogie motion trail; and performing three-dimensional dynamic lever arm position compensation based on the global reference navigation state sequence, the key point coordinates and the bogie motion trail to obtain a track shape trail: calculating track irregularity parameters, and completing track irregularity dynamic detection. According to the method, track irregularity dynamic detection is realized, band-pass filtering processing is not needed, information loss is less, and waveform distortion can be avoided.

The invention relates to a material damage online monitoring method and system based on ultrasonic multi-feature fusion, and the method comprises the steps: obtaining a reference ultrasonic echo signal and a current ultrasonic echo signal in a current state, and carrying out the parallel calculation of a first damage index and a second damage index, wherein the first damage index is used for quantitatively representing ultrasonic signal energy attenuation characteristics caused by material plastic deformation; the second damage index is used for quantitatively representing ultrasonic signal waveform distortion characteristics caused by material microscopic damage; determining the weight of each damage index based on the data inherent statistical characteristics of the first damage index and the second damage index in the whole monitoring time sequence; and carrying out weighted fusion on each damage index by adopting the corresponding weight, and constructing a comprehensive damage index to quantitatively characterize the damage state of the material. Compared with the prior art, the method has the advantages of realizing accurate, dynamic and quantitative characterization of the damage degree of the material in the whole life cycle and the like.

The invention relates to a material sound velocity measurement method based on an envelope cross-correlation algorithm, relates to the technical field of automatic detection, and solves the technical problem of serious waveform distortion interference in sound velocity measurement of an internal non-uniform material in the prior art. The method comprises the following steps: initialization setting and reference acquisition; performing point-by-point scanning on the current scanning surface of the tested sample to obtain sample echoes; drawing a sound velocity distribution diagram of the current scanning surface of the tested sample; rotating the sample to be measured and continuously measuring until the detection of the three orthogonal surfaces is completed; the average sound velocity of the tested sample is obtained. By applying the material sound velocity measurement method, scattering attenuation and frequency dispersion effect interference caused by material anisotropy can be eliminated, a period jump error caused by carrier phase ambiguity is reduced, the signal-to-noise ratio of a detection signal is effectively improved, automation and high repeatability of sound velocity measurement are achieved, and the measurement accuracy is improved. And the recognition accuracy of the small sound velocity difference is improved.

The application discloses an electromagnetic detection optimized bipolar SHMPWM transmitting method, which comprises the following steps: S1, by analyzing the influence of the resistive and inductive load on the transmitting current waveform distortion and the transmitting spectrum energy loss, extending the current waveform based on the equal-area principle, compensating for the lost transmitting current spectrum energy, and calculating the current waveform extension time; S2, considering the inductive load and the dead zone effect, establishing a bipolar SHMPWM nonlinear equation set; S3, using the particle swarm algorithm to iteratively operate the bipolar SHMPWM nonlinear equation set, and obtaining the solving result of the switching angle of the half-cycle symmetric SHMPWM. The application adopts the optimized particle swarm algorithm to solve the equation set to obtain the switching angle, and realizes that the frequency domain information of the half-cycle symmetric SHMPWM frequency focusing waveform conforms to the specific harmonic amplitude set by the expectation.

The invention discloses a three-phase voltage type PWM rectifier switch tube open-circuit fault diagnosis method, which comprises the steps of 1, implementing three-layer wavelet decomposition on an input side three-phase current historical database after a three-phase voltage type PWM rectifier power switch tube open-circuit fault by adopting a wavelet decomposition method, extracting a characteristic value corresponding to the switch tube fault and finishing normalization; and 2, performing parameter optimization on the support vector machine through an improved mouse group search algorithm, and determining an optimal penalty factor and a kernel parameter so as to carry out data training and fault diagnosis. The invention aims to analyze the waveform distortion condition of the three-phase current at the input side after the open-circuit fault of the three-phase rectifier switch tube, so as to optimize the fault characteristic quantity and realize the accurate diagnosis of the open-circuit fault of the power switch tube. According to the invention, the fault identification capability of the rectifier system under the abnormal working condition can be effectively improved, so that safe and stable operation of power electronic equipment is ensured.

The application provides a chip-scale package interconnection structure failure analysis method and device, comprising: determining the failure external pin corresponding to the failure CSP package interconnection structure according to the current-voltage characteristic curve corresponding to each external pin; collecting and analyzing the time-domain reflection waveform of the failure external pin by using the electro-optical terahertz pulse reflection technology, positioning the target interconnection failure area in the interconnection path where the failure external pin is located according to the amplitude, time delay and waveform distortion characteristics of the reflection pulse; scanning the target interconnection failure area by using the three-dimensional X-ray microscopic imaging technology, and determining the target position of the failure point on the interconnection path where the failure external pin is located and the corresponding structural defects based on the scanning result. The application realizes the non-destructive failure analysis of the CSP package interconnection structure by combining the electro-optical terahertz pulse reflection technology and the three-dimensional X-ray microscopic imaging technology, and improves the failure point fault positioning accuracy and efficiency.

The invention relates to the technical field of motor control, and discloses an anti-locked-rotor starting control system. The system comprises a main control module, a dynamic rule base generation module, a phase compensation module, a pre-triggering module and a feedback correction module. The main control module monitors a three-phase current waveform and a rotor position signal of the motor and generates an instantaneous locked-rotor feature vector; the dynamic rule base generation module extracts a current waveform distortion mode of a historical locked-rotor event, and combines a rotor inertia parameter to construct a fuzzy rule set so as to initialize a dynamic rule base; the phase compensation module dynamically compensates the phase current waveform and constructs a stability evaluation function; the pre-triggering module triggers pre-access of the standby power supply according to the phase offset and verifies compatibility; and the feedback correction module generates a feedback parameter according to the locked-rotor risk index and the power supply verification result, and corrects the mapping relationship between the feature vector and the rule base. The system can accurately identify locked-rotor characteristics, dynamically adapt to operation parameters, actively prevent and control locked-rotor risks, and improve the starting stability of the motor.

The present application belongs to the technical field of data processing, and particularly relates to a kind of spring forming equipment operating state monitoring and fault early warning method, its method includes: through the operating state data of key servo shaft, the torque stiffness is calculated, and the forming cycle is automatically divided into elastic contact, plastic forming and unloading demoulding phase;In the plastic forming phase, the influence of raw material hardness fluctuation is stripped by calculating the dynamic rheological resistance index of material and the upper limit of dynamic current;At the same time, the energy topology consistency coefficient containing position weighting function is calculated to capture the slight waveform distortion;Finally, a comprehensive fault early warning index is constructed based on the above index, and the equipment is warned or stopped in stages.The present application can effectively decouple material attribute fluctuation and mechanical failure, and improve the detection sensitivity of early failure.

The invention relates to the technical field of direct current circuit breaker fault diagnosis, and discloses a fault detection system based on a direct current circuit breaker. The system comprises a signal acquisition module, a signal preprocessing module, a waveform distortion feature extraction module, a feature interval division module, a border crossing evaluation module, a map construction module and a fault identification module. The method comprises the following steps: synchronously collecting multi-channel time domain signals, and carrying out time mark alignment and noise filtering; matching the current signal with a standard template by using a dynamic time warping algorithm to generate a waveform distortion feature vector; dividing feature intervals according to jump edges of the state signals, extracting distortion feature sub-vectors of the state intervals, and performing multi-dimensional space distance operation on the distortion feature sub-vectors to generate interval border-crossing descriptors; integrating and constructing a fault characteristic spectrum representing a complete action process; and matching the fault mode library through an atlas comparison engine to output a recognition result and confidence. According to the invention, accurate quantification of tiny distortion of the action waveform of the DC circuit breaker and accurate positioning of staged faults are realized.

The application discloses a kind of gate drive circuit and display panel.Therein, gate drive circuit includes output control module, first transistor, second transistor and voltage regulation module;Output control module is used to control first transistor and second transistor alternate conduction, to first output signal and second output signal are alternately transmitted to the output end of gate drive circuit;At least one of first transistor and second transistor is double-gate transistor, the first gate of double-gate transistor is connected with output control module;Voltage regulation module is connected with the second gate of double-gate transistor, for adjusting the second gate voltage of double-gate transistor.The technical scheme of the application is helpful to improve the waveform distortion problem of gate drive signal, so as to improve the display effect of display panel.

The invention discloses a gas industry user side pressure remote alarm monitoring system, particularly relates to the technical field of gas pressure remote alarm monitoring, and is used for solving the problem that a fault position cannot be accurately positioned when an existing gas pressure alarm system is triggered based on a fixed threshold value. A pressure time sequence is formed by collecting pressure data of a plurality of monitoring nodes in a gas pipe network in real time, when the pressure data of any monitoring node exceeds a preset threshold value, the corresponding node is identified as an abnormal node, and an abnormal triggering moment is obtained; analyzing pressure imbalance directivity characteristics between the abnormal node and each associated node in a preset time window based on the abnormal triggering moment, and cooperatively analyzing pressure time sequences of the abnormal node and each associated node to identify a fluctuation event with time sequence relevance, and analyzing a waveform distortion rule generated during propagation of the fluctuation event to construct a propagation path of the fluctuation event in a pipe network, and determining a fault position in combination with the pressure unbalance directivity characteristic and the propagation path of the fluctuation event to realize accurate positioning.

The utility model discloses a three-phase voltage, frequency and phase sequence detection circuit, and belongs to the technical field of electric power detection. The three-phase voltage, frequency and phase sequence detection circuit comprises an MCU control unit, an A-phase detection circuit, a B-phase detection circuit and a C-phase detection circuit, wherein the A-phase detection circuit, the B-phase detection circuit and the C-phase detection circuit have the same structure. Each detection circuit comprises a voltage sampling circuit and a frequency detection circuit. According to the utility model, the operational amplifier is used for scaling down the input voltage, and the input voltage is skillfully raised to a range which can be accurately sampled by the MCU, compared with a traditional transformer detection method, the size and the weight are greatly reduced, the waveform distortion is extremely small, the characteristics of an original voltage signal are accurately reflected, and the detection precision is greatly improved. The effects of small size, light weight, low cost and high detection precision can be simultaneously achieved.

The invention relates to the technical field of rail breakage detection, and discloses a rail breakage detection system and method based on a turnout switch rail, and the system comprises an indoor digital twin platform, a trackside control cabinet, a 5G millimeter wave bearing, a built-in detection host, a power module and a wireless communication module. The transmitting end transducer is fixed at the rail web of the heel end of the switch rail through a detachable fixture and is used for injecting a high-frequency stress wave signal into the steel rail; the receiving end sensor is fixed at the rail waist of the point of the switch rail through a pressure self-adaptive clamp and is used for receiving a stress wave signal; the diagnostic analysis module runs in the detection host and identifies the broken rail by analyzing the waveform distortion rate and the energy attenuation coefficient of the stress wave signal; the anti-falling monitoring unit is used for detecting the mounting state of the fixture in real time and triggering a loosening alarm; the problems that an existing broken rail detection system is low in reliability and complex in maintenance are solved.

The invention relates to the field of circuit breakers, in particular to a quantitative analysis method for the influence of transient current on the residual electrical life of a high-voltage circuit breaker, which comprises the following steps: calculating the influence index of the transient current on the residual electrical life of the high-voltage circuit breaker; constructing a related parameter time sequence; calculating an influence factor of the relevant parameters at the current moment on the relevant parameters at the next moment; predicting numerical values of relevant parameters at the next moment; calculating the influence index of the transient current at the next moment on the residual electrical life of the high-voltage circuit breaker; evaluating the decay speed of the residual electrical life, and dynamically adjusting the maintenance cycle. The method has the advantages that the frequency characteristic of the fault current and the waveform distortion characteristic caused by the harmonic wave are brought into the evaluation system of the residual electrical life, the limitation that only the current amplitude is considered in the traditional method is broken through, the actual physical process of the contact ablation by the transient current can be reflected more truly and more comprehensively by constructing the comprehensive quantitative model, and the evaluation accuracy of the residual electrical life is improved. And the scientificity of an evaluation model and the accuracy of a prediction result are fundamentally improved.

The invention provides a state evaluation method and system for an invasive brain-computer interface system and a medium. The method comprises the following steps: randomly generating a test sequence, wherein the test sequence comprises a plurality of stimulation current intensity values; each stimulation current intensity value is sequentially sent to the extracorporeal machine, a body surface artifact signal is synchronously obtained, and when the extracorporeal machine receives the stimulation current intensity value every time, a corresponding stimulation instruction is generated and sent to the implant so as to control the implant to apply electrical stimulation according to the stimulation current intensity value; based on the body surface artifact signal corresponding to each stimulation current intensity value, a state evaluation result of the invasive brain-computer interface system is generated, and the state evaluation result comprises at least one of signal validity, a signal amplitude abnormal condition and a waveform distortion condition. The method objectively and accurately evaluates the working state of the invasive brain-computer interface system.

Provided are an optical measurement device, an optical measurement method, a data processing device, and a program, capable of generating data that is a stimulus value that takes into account the time response of an eye and suppresses waveform distortion, capable of performing good flicker measurement, and also capable of coping with a measurement target object having a non-periodic light emission waveform. A stimulus value acquisition unit (20) receives light from a measurement target object to continuously acquire intensities corresponding to stimulus values at constant time intervals; a response characteristic acquisition unit (32) acquires a pulse response characteristic from a storage unit (31) that stores a pulse response characteristic corresponding to a visual stimulus response; and a digital filter processing unit (32) performs digital filter processing on continuous data of the acquired stimulus value intensities using the acquired pulse response characteristic to generate data on which a visual stimulus response is superimposed.