249 results about "Pulse waveform" patented technology

The invention discloses a live detection method for insulation defects of high-voltage power equipment. The method comprises the following steps: firstly, synchronously arranging ultrahigh frequency sensors and acoustic emission sensors on a plurality of monitoring points on the surface of a gas insulated switchgear shell to form an array, and synchronously acquiring signals for filtering pretreatment; then, pulse events are extracted from the two types of signals respectively, and associated pulses in a time window are matched into matched pulse pairs representing the same discharge source; then, carrying out time-frequency transformation on the ultrahigh frequency and acoustic emission pulse waveform in each matched pulse pair, carrying out joint noise reduction by calculating a coherence coefficient between time-frequency distribution matrixes, and extracting a joint feature vector containing an energy ratio, a time parameter ratio and a frequency difference from the denoised time-frequency matrix; according to the invention, multi-source signals are fused, and high-sensitivity detection, high-precision positioning and high-accuracy identification of insulation defects are realized.

The invention relates to the technical field of pulse acquisition, in particular to a high-speed ADC (Analog to Digital Converter) and FPGA (Field Programmable Gate Array) coordinated extremely-narrow pulse signal acquisition system, which comprises a phase identification monitoring module, a phase lock reference updating module, a sampling permission control module, a prohibition feedback identification module and a synchronous trigger adjustment module. According to the method, a beat tolerance judgment mechanism is introduced, hyper-bound phase deviation trend statistics and frequency vector extraction are combined, beat correction is carried out by utilizing a directional hopping cumulant and a period adjustment amount, a sampling permission judgment and keeping window alignment mechanism is introduced in a multi-frame period, and a two-way judgment means of a sampling starting trigger value is adopted, so that the beat tolerance of the multi-frame period is judged. And meanwhile, centralized extraction and frequency directivity statistics are carried out on the hopping direction in the sampling prohibition time sequence, the synchronous mismatch trend is distinguished, and the initial beat position is adjusted, so that the time domain characteristics of the narrow pulse waveform are kept continuous, the edge response is prevented from deviation, the trigger structure is stable and reliable, and the overall sampling judgment is more accurate and efficient.

The utility model belongs to the technical field of pulse power supplies, and particularly discloses a pulse power supply circuit, which comprises a power supply input module, a PWM (Pulse Width Modulation) signal input module, a feedback control module, a control chip and an output module, the power input module provides working power for the control chip and the whole circuit. The PWM signal input module is used for transmitting an external PWM signal to a signal input pin of the control chip; the feedback control module collects an electric signal in the circuit and transmits a processed feedback signal to the control chip; the control chip drives the output module to output a pulse power supply to provide electric energy for a load based on an input PWM signal and a feedback signal. According to the utility model, the feedback signal acquired by the feedback control module is compared with the reference voltage, the difference value is amplified, the control chip adjusts the duty ratio of the PWM signal according to the amplified error signal, the pulse waveform is effectively optimized, and the output stability and reliability of the pulse power supply are improved.

The invention discloses an accurate X-ray radiation dose measurement system based on artificial intelligence, which comprises the following steps: acquiring CT image data of a patient and pulse irradiation parameters of radiotherapy equipment through terminal equipment, and calculating a patient specific anatomical structure dynamic influence factor set, a pulse waveform time domain characteristic factor and a tissue interface scattering correction factor; all the parameters are substituted into a dose measurement formula to obtain an accurate X-ray radiation dose value; through a deep fusion image recognition technology (such as a high-resolution anatomical structure, tissue density gradient and heterogeneous region distribution provided by CT / MRI), a secondary particle scattering effect of a junction region of a tumor and a normal tissue can be accurately represented; and dynamic anatomical information (such as respiratory movement and organ displacement) in the image is combined to correct the time characteristic (such as dynamic change under an instantaneous high dose rate) of the pulse radiation field in real time, so that the dose calculation accuracy of a fast algorithm in a complex scene is remarkably improved.

The invention relates to the technical field of photoelectric tube detection, in particular to a photoelectric tube high-voltage excitation type solar blind ultraviolet discharge detection method and system, and the method comprises the steps: obtaining original voltage sequence data collected by a high-speed transimpedance sampling circuit in real time; positioning feature points of each suspected pulse according to the original voltage sequence data, and extracting pulse waveform features; obtaining a physical confidence factor of each suspected pulse according to the falling edge attenuation characteristics; calculating effective discharge energy flow in unit time based on the physical confidence factor; calculating a discharge stability coefficient according to a coupling relationship between the time correlation entropy and the effective discharge energy flow; according to the method, a scheme from microscopic physical judgment, waveform form deconstruction and time law analysis to multi-dimensional trend prediction is constructed, so that the contradiction between the detection sensitivity and the quantification precision is solved; and adaptive tracking monitoring of the partial discharge process is realized.

The invention discloses a switch cabinet monitoring method and device based on the Internet of Things technology and a medium, and relates to the technical field of Internet of Things fusion, and the method comprises the steps: inputting a multi-modal time series data set into a multi-physics field coupling digital twin model, and generating a predictive instruction set; dynamically adjusting a discrimination probability threshold and aggressive degree parameters in the lightweight convolutional neural network based on the risk level quantized value in the predictive instruction set to obtain an adjusted lightweight convolutional neural network; performing pattern recognition on the partial discharge pulse waveform data by using the adjusted lightweight convolutional neural network to generate a fault early warning event identifier; by constructing a multi-modal time sequence data set, efficient fusion and time synchronization of multi-physical field information such as partial discharge, temperature and vibration of the switch cabinet are realized, data integrity and accuracy of state sensing are improved, and safety and stability of long-term operation of the switch cabinet are effectively guaranteed.

A high-frequency power supply device includes a first power supply that outputs a high-frequency AC voltage having a first frequency, a second power supply that outputs a DC pulse voltage including one or more continuous pulse waveforms, a matching box that receives the high-frequency AC voltage, performs impedance matching such that impedance viewed from the first power supply becomes constant, and outputs the high-frequency AC voltage, a filter that receives the DC pulse voltage, filters the DC pulse voltage, and outputs the DC pulse voltage to a pulse-power input terminal of a load, and an IMD suppression circuit that includes a first inductor having predetermined inductance provided between the matching box and an AC-power input terminal of the load, receives the high-frequency AC voltage, allows the input high-frequency AC voltage to pass through the first inductor, and outputs the high-frequency AC voltage to the AC-power input terminal of the load.

The invention relates to the technical field of medical instruments, in particular to a magnetic control pulse type pelvic floor nerve muscle stimulator and a parameter optimization system thereof. Comprising a host, a dynamic layered pulse waveform generation technology module, a multi-target reinforcement learning parameter optimization module, a multi-modal biofeedback fusion and VR enhancement module, and a flexible wearable stimulation array and ultrasonic targeting module. The system has the advantages that real-time data and deep learning are achieved, and personalized precise treatment is achieved, in the actual use process, the dynamic layered pulse waveform generation technology module predicts the requirements of muscles in the next stage through a deep learning model on the basis of pelvic floor electromyographic signals, pressure data and infrared thermal imaging which are collected in real time, and the treatment accuracy is improved. Dynamically generating a composite pulse waveform; the multi-objective reinforcement learning parameter optimization module constructs a'state-action-reward 'reinforcement learning framework, and takes patient treatment feedback, muscle force improvement, pain score and treatment compliance as reward signals.

Systems, devices, and methods described herein relate to generation and delivery of pulsed waveforms, e.g., for therapy delivery in soft tissue ablation procedures. In some embodiments, a pulse generator is configured to generate a voltage pulse train including a plurality of biphasic pulses, each biphasic pulse of the plurality of biphasic pulses including a positive pulse, a negative pulse, and an inter-phase delay separating the positive pulse and the negative pulse. In some embodiments, successive biphasic pulses of the plurality of biphasic pulses can be separated by a pulse-to-pulse delay such that the plurality of biphasic pulses is separated by a plurality of pulse-to-pulse delays, and the plurality of pulse-to-pulse delays can include increasing or decreasing sequences of pulse-to-pulse delays.

The invention belongs to the technical field of touch screen static suppression and signal recovery, and relates to an active touch screen static suppression and signal synchronous recovery system, which comprises a static detection module, an instruction generation module, a charge neutralization module, an environment confirmation module, a parameter generation module, an inverse waveform generation module and a signal output module, the electrostatic detection module is used for generating an initial electrostatic disturbance signal; the instruction generation module is used for generating a fixed-point neutralization instruction; the charge neutralization module is used for forming an instantaneous local neutralization electric field; the environment confirmation module is used for generating an environment confirmation signal; the parameter generation module is used for generating feed-forward compensation parameters; the anti-phase waveform generation module is used for generating an anti-phase pulse waveform; the signal output module is used for generating an original touch signal; according to the invention, the problem that it is difficult to realize reliable identification, source elimination and signal synchronous recovery of electrostatic interference is solved.

The invention discloses a broadband feature coupling and sparse low-rank joint imaging method, product and equipment, and belongs to the technical field of electrical equipment monitoring. The method comprises the following steps: S1, establishing a pure acoustic propagation model of a partial discharge sound source, and fusing partial discharge pulse waveforms and sound wave propagation characteristics; s2, constructing a physically constrained over-complete sparse dictionary based on the time domain damped oscillation of the partial discharge signal and the physical fingerprints with concentrated frequency domain and high energy; s3, constructing a joint optimization objective function by combining the characteristics of sparse time domain and low space rank of the partial discharge signal, and iteratively solving a space-time signal matrix; s4, designing a lightweight deep network fused with physical prior, and considering both precision and real-time performance; and S5, realizing data acquisition and imaging real-time processing based on a GPU stream processing architecture in combination with dual-threshold detection and pre-calculation optimization. The broadband transient characteristic and the space-time sparsity of the partial discharge pulse can be embedded into the imaging model, and a traditional general acoustic imaging frame is replaced.

A layered pulse generator for a vertical-cavity surface-emitting laser (“VCSEL”) driver is disclosed consisting of three elements: a low-speed pulse generator, a high-speed pulse generator, and a pulse generator selector, all of which are on-chip with the VCSEL driver. By providing these elements on-chip, overall system power and complexity are reduced while allowing for significantly higher pulse train frequencies compared with known systems. The high-speed pulse generator is capable of generating pulses faster and with higher resolution than that of the low-speed pulse generator. The high-speed pulse generator uses multiple clock outputs, phase shifted, and synthesized into a single pulse waveform capable of wide-ranging frequencies, duty cycles and pulse counts.

A laser device according to one embodiment includes a laser light source configured to output pulsed laser light L1 and a pulse width control unit configured to amplify the pulsed laser light output from the laser light source, change a pulse width of the pulsed laser light, and output the pulsed laser light. The pulse width control unit includes a first laser amplifier configured to amplify the pulsed laser light and a pulse waveform manipulation unit disposed between the first laser amplifier and the laser light source and configured to manipulate a pulse waveform of the pulsed laser light.

In a ranging device, a characteristic setting unit is configured to extract, from one or more pieces of received-light information representing changes with time in amount of received light acquired by the light receiving unit, at least one of a received-light amount range and a light reception time range of pulsed light other than emitted light from the light emitting unit, as a specified range. A received-light integration unit is configured to generate integrated received-light information by integrating the received-light information on a time axis with emission timings matched over a plurality of light receptions. A distance calculation unit is configured to exclude or identify distance noise formed of pulsed waveforms arising from pulsed light other than the emitted light, using the specified range extracted by the characteristic setting unit, and calculate a distance to the object reflecting the emitted light.

The application discloses a kind of generator stator winding partial discharge quantity's inversion method and system, belong to large-scale rotating electrical machine insulation state diagnostic technical field, method includes: obtaining or estimating the key distributed capacitance parameter in insulation structure multi-capacitance equivalent circuit model, mapping relationship database is established;Partial discharge detection is carried out to the generator stator winding of applied test voltage, and the characteristic information of discharge pulse is collected;Based on the key distributed capacitance parameter in mapping relationship database, pre-generated pulse waveform-defect capacitance calibration curve, the characteristic information of discharge pulse collected is executed nonlinear iterative inversion calculation;Quantitative evaluation, type identification and health diagnosis are carried out to the insulation defect of generator stator winding.The application introduces pulse waveform feature into partial discharge physical quantity inversion, improves the accuracy, quantitative level and defect identification ability of generator stator insulation state evaluation, provides technical support for generator life extension and condition maintenance.

The application provides a driving modulation method and device applied to a liquid crystal on silicon (LCoS), the driving modulation method comprising: receiving first information, the first information comprising indication information of a first logic sequence, the first logic sequence comprising a first digital logic and / or a second digital logic, the first digital logic corresponding to a first pulse waveform signal, the second digital logic sequence corresponding to a second pulse waveform signal, at least one of the first pulse waveform signal and the second pulse waveform signal comprising a high level and a low level, the first pulse waveform signal being different from the second pulse waveform signal; and outputting a liquid crystal driving voltage of the LCoS according to the first information. The method realizes dithering suppression through a lower frequency refreshed logic sequence, and reduces the data transmission bandwidth required by a backplane chip.

The invention discloses a random analog pulse signal generation circuit, which is characterized in that the output of an excitation pulse generation module obeying discrete random time distribution is connected to an excitation pulse generation module obeying continuous random time distribution, and the excitation pulse generation module is used for generating square wave pulses of which the time interval of the front edges of two adjacent excitation square waves obeying discrete distribution; the output of the excitation pulse generation module obeying continuous random time distribution is connected to the analog narrow pulse generation module, and the analog narrow pulse generation module is used for converting the generated square-wave pulse into a square-wave excitation pulse of which the leading edge obeys specific distribution; and the analog narrow pulse generation module is used for converting the leading edge of the square wave excitation pulse into a narrow pulse signal so as to generate a signal waveform suitable for a fast detector electronics system test. According to the circuit, the inherent discreteness of digital logic is eliminated while better programmability of the digital logic is kept, so that the finally output pulse waveform signal is closer to the time characteristic of the signal processed by the detector under the real working condition.

The problem to be solved by the present invention is to provide a spot welding spatter detection method that can detect spatter generation without resetting the voltage detection line. To solve the above problem, in the spot welding method, a pulsed waveform welding current is provided to the workpiece by alternately performing the following steps in multiple cycles: a step of maintaining the welding current within a set peak current range; a step of decreasing the welding current from the peak current range towards the bottom current, and then increasing the welding current towards the peak current range when the effective value of the welding current reaches a set target range. In the spatter detection method, the pulse widths IW(1), IW(2), ... of the pulsed waveform in each cycle are measured. If the pulse width difference D(M) = IW(M) - IW(M-1) between the pulse width IW(M) in the target cycle (the Mth cycle) and the pulse width IW(M-1) in the previous cycle exceeds a width threshold Dth, then the generation of spatter is detected.

The invention relates to an EDXRF spectrum intelligent analysis method, system and device and a medium. The method comprises the following steps: acquiring a digital pulse waveform, performing multi-dimensional feature extraction on the digital pulse waveform, and generating a standardized multi-dimensional feature vector; inputting the vector into a pre-trained gradient boosting decision tree model to obtain an event classification result of the current pulse event, taking the event classification result as an event classification judgment result of a preset decision object, and associating the digital pulse waveform to obtain a structured decision object; according to an event classification judgment result in the structured decision object, performing differentiation processing to obtain an effective X-ray photon energy value; and mapping the energy value to a corresponding energy spectrum channel according to an energy-channel mapping relation, and carrying out counting accumulation to generate a high-fidelity energy spectrum. According to the method, through multi-dimensional feature extraction and pre-training model reasoning, the accuracy of pulse signal processing and the fidelity of the energy spectrum are improved, and the precision and stability of EDXRF spectrum analysis in a complex detection scene are enhanced.

The invention relates to a traction inverter IGBT junction temperature calculation method and device, equipment, a medium and a program. The method comprises the steps that the bus voltage, the output current effective value, the output current frequency, the modulation ratio and the power factor of a traction inverter are collected; based on the bus voltage, the output current effective value, the modulation ratio and the power factor, calculating the total average loss of all IGBT devices in the traction inverter in an output fundamental wave period; discretization equivalence is carried out on the average loss, pulse waveforms corresponding to multiple discrete periods are obtained, the loss value corresponding to each pulse waveform is calculated, and the size of the discrete periods is determined according to the set number of the discrete periods and the output current frequency; based on an electric heating model of the traction inverter IGBT device and the loss value corresponding to each pulse waveform, the IGBT junction temperature corresponding to each discrete period is calculated, and rapid and accurate calculation of the junction temperature of the traction inverter under the long-time mission profile is achieved.

A method of operating an electrochemical cell including introducing an aqueous solution into the electrochemical cell, applying a current across an anode and a cathode to produce a product, monitoring the voltage, dissolved hydrogen, or a condition of the aqueous solution, and applying the current in a pulsed waveform responsive to one of the measured parameters is disclosed. An electrochemical system including an electrochemical cell including an anode and a cathode, a source of an aqueous solution having an outlet fluidly connectable to the electrochemical cell, a sensor for measuring a parameter, and a controller configured to cause the anode and the cathode to apply the current in a pulsed waveform responsive to the parameter measurement is disclosed. Methods of suppressing accumulation of hydrogen gas within the electrochemical cell are also disclosed. Methods of facilitating operation of an electrochemical cell are also disclosed.

The invention relates to the technical field of pulse trigger circuits, in particular to a transient high-frequency pulse waveform capturing method of a pulse trigger circuit, which comprises the following steps: acquiring a first sampling signal sequence and a second sampling signal sequence; determining a plurality of prediction sampling signals in a future preset time period based on the first sampling signal sequence so as to determine a prediction trigger characterization value; determining a plurality of key sampling signals in a target time period based on the second sampling signal sequence so as to determine a key trigger characterization value; judging whether a pre-trigger signal is generated or not based on the predicted trigger characterization value and the key trigger characterization value; in response to generation of the pre-trigger signal, obtaining a plurality of continuous sampling signals based on the second sampling signal sequence to determine a signal stability degree value; and determining a waveform generation mode based on a comparison result of the signal stability degree value and a preset stability degree value. The transient high-frequency pulse waveform capture false triggering rate can be reduced, and the waveform capture rate and the waveform integrity are ensured.

This invention relates to a temperature control method and device for a laser detection system based on pulse waveform feature feedback. The laser detection system includes a laser, an integrating sphere, and a laser detector arranged sequentially. The laser detector is equipped with a cooling system for cooling the laser detector. The laser, integrating sphere, laser detector, and cooling system are each connected to a control terminal. The method is applied to the control terminal and includes: acquiring the pulse waveform characteristics and a first real-time temperature of the laser detector; determining whether the cooling system meets the temperature adjustment conditions based on the pulse waveform characteristics; querying the target adjustment temperature corresponding to the current signal deviation from a database based on the current signal deviation; determining a comprehensive error based on the target adjustment temperature, the first real-time temperature, and the target temperature of the laser detector; inputting the comprehensive error into a PID algorithm to obtain control commands for the cooling system. Timely and accurate temperature control of the laser detection system is achieved based on pulse waveform feature feedback.

The application discloses a kind of scintillator decay time test methods based on waveform sampling, the steps of test method include: scintillator is coupled to the optical window of photomultiplier tube placed in shielding box, using radioactive source excitation sample, open oscilloscope automatic acquisition not less than 100 pulse signals and transmission to control computer;Pulse waveform data acquired by oscilloscope is handled calculation, obtains the decay time constant corresponding to single pulse data;The above steps are repeated for processing all collected pulse data, obtain decay time constant set;With decay time constant set histogram, data should present normal distribution;Using Gaussian function to the normal distribution is fitted, the decay time value corresponding to the peak obtained is the decay time of the sample.The application can accurately test the decay time of different scintillating materials, especially suitable for high-throughput decay time measurement.

The invention discloses a pulse wave matching method, device and equipment for non-invasive blood pressure measurement. The method comprises the steps that pulse wave data on each pressure step are collected to obtain a typical pulse wave waveform in a rising-first and falling-second form; performing characteristic value extraction on the pulse waveform by adopting double sliding windows, and judging whether the characteristic values of the current pulse wave and the previous pulse wave are matched or not; the characteristic values comprise a pulse wave amplitude value, a processing signal peak value, a processing signal valley value and a processing signal peak-valley interval; if not, continuing to collect the pulse wave data and continuing to perform characteristic value matching, and if yes, collecting the pulse wave data on the next pressure step. According to the method, the pulse wave features are enhanced through double-window processing, and the influence of interference factors is effectively reduced while the matching judgment precision is improved in combination with the original waveform features.

The embodiment of the invention relates to the technical field of pulse diagnosis, and discloses a pulse analysis method based on a pulse diagnosis instrument, which comprises the following steps: processing a pressure change signal within a set time to obtain an original pulse waveform signal associated with a user; performing high-frequency denoising processing on the first pulse frequency signal according to a set noise threshold value; acquiring all wavelet coefficients associated with the high-frequency detail signal, traversing all the wavelet coefficients, determining that the absolute value of the wavelet coefficient at a certain point is greater than the absolute value of the wavelet coefficient adjacent to the wavelet coefficient, and taking the wavelet coefficient as a signal abrupt change point; generating a corresponding pulse image of the user based on the pulse condition data of the user within a set time range; and inputting the obtained pulse condition graph of the user into a pre-constructed standard pulse condition model to determine a pulse condition type result of the user, and outputting the pulse condition type result of the user. According to the scheme provided by the embodiment of the invention, the user can conveniently, quickly and accurately know the pulse condition and the physique state of the user, and the use convenience is improved.

The application discloses a kind of based on multi-path pulse current implementation's ultra-high frequency pulse welding power supply system, comprising: N Independent constant current source, output same or different constant current value;Current switching circuit is used to switch selected constant current source and access welding assembly;Control unit is used to drive the on-off of current switching circuit according to preset pulse waveform, to output pulse current with different amplitude of multiple sections;Absorption circuit is used to actively switch the freewheeling loop of parasitic inductance in the switching moment of pulse current from large current jump to small current;Welding assembly includes welding gun and the welding platform of bearing to be welded workpiece;Control unit is also used to actively turn on absorption circuit when the amplitude of current is switched from high to low step, and the energy stored in the output loop of parasitic inductance is quickly released through absorption resistance.This application has the advantages of realizing accurate current step control, significantly improving dynamic performance, improving system reliability and modular maintenance.

The invention discloses an inverse time limit overload protection method and device for a doubly-fed motor rotor winding. The method comprises the following steps: acquiring three-phase current of the doubly-fed motor rotor winding; rectifying the three-phase current signal of the rotor winding, and converting the three-phase current signal into a rectified current signal with six pulsating waveforms; converting an overload reference current; calculating a heat accumulation value in real time by adopting an inverse time limit heat accumulation equation based on the overload reference current and the rectified current; whether the heat accumulation value is larger than or equal to a heat accumulation threshold value or not is judged, and if yes, the protection system sends out a tripping signal. According to the technical scheme of the invention, the three-phase AC signal is rectified, and the overload heat accumulation value of the rectified output signal is calculated and discriminated by converting the overload reference current, so that the problem that the conventional inverse time limit protection method cannot meet the requirements of accuracy and timeliness when processing the extremely-low-frequency rotor current is solved. And accurate and timely inverse time limit overload protection is provided for the doubly-fed motor.

The invention discloses a non-contact real-time heart rate detection method and system based on rPPG and wavelet enhancement, and belongs to the technical field of medical health. Face video signals are collected through the camera, a sensor or an electrode does not need to be worn, real non-contact physiological signal detection is achieved, and the comfort level and use convenience of a user are improved; discrete wavelet transform denoising and enhancement processing is introduced on the basis of pulse signals extracted by a POS algorithm, and high-frequency noise caused by illumination variation, camera quantization errors and facial movement is removed through multi-scale decomposition and threshold filtering, so that the signal-to-noise ratio of the pulse signals is remarkably increased; the fast Fourier transform is combined with a sliding window mechanism, so that real-time updating and continuous calculation of the heart rate can be realized; the signal after wavelet enhancement is clearer in periodicity, so that the heart rate calculation error is remarkably reduced, a dynamic visual interface of a heart rate change curve and a pulse waveform is provided, a user can observe physiological state changes in real time, and good interactive experience is achieved.

The invention provides a traditional Chinese medicine pulse diagnosis instrument based on artificial intelligence and a data analysis method thereof. The pressure detection mechanism comprises an air bag wrapping the to-be-detected part, an inflation part used for inflating the air bag to enable the air bag to pressurize the to-be-detected part of the user, a gas pressure sensor linked with the air bag and a flexible pressure sensor, and the pressure detection mechanism is used for applying different pressures to the to-be-detected part and collecting pulse information under the different pressures; the data acquisition module is used for converting the analog signal into a digital signal and preprocessing the digital signal; the signal processing module is used for carrying out segmentation, calibration, normalization and SG smoothing on the pulse waveform and extracting features; and the pulse condition analysis module is used for carrying out pulse condition recognition and classification on the quantization parameters by utilizing a machine learning algorithm. According to the method, pulse information under different pressures is collected and processed, and stable, accurate and lossless collection and quantitative analysis of pulse condition information are achieved through one-to-one mapping of characteristic values and traditional Chinese medicine conclusions.