109results about How to "Solve misjudgment" patented technology

The invention relates to the technical field of coal mill powder pipes, in particular to a powder leakage defect automatic identification method based on digital twinning and AI video analysis, and the method comprises the steps: obtaining operation parameters and environmental parameters of a coal mill powder pipe, calculating a powder leakage risk characterization coefficient, and judging whether there is a potential risk of powder leakage; image data of the surface and the surrounding area of the powder pipe in the initial starting period are collected through an AI video analysis module, powder leakage characteristic parameters are extracted, a characteristic change curve segment is drawn, similarity comparison is conducted on the characteristic change curve segment and the reference characteristic curve segment, and whether a suspected powder leakage area exists or not is judged; actual operation parameters and model prediction parameters of the powder pipe in a stable operation period are obtained based on a digital twin model, the fluctuation degree of parameter deviation is calculated, and whether the powder leakage defect exists or not is comprehensively judged by combining a suspected powder leakage area judgment result; the early-stage accurate identification of the powder leakage defect is realized, the detection efficiency and precision are improved, and the operation and maintenance cost and the safety risk are reduced.

The invention relates to the technical field of medical instrument detection, in particular to a method and a system for detecting coating uniformity of a medical catheter, and solves the technical problem of low detection accuracy in the prior art. The method comprises the following steps: acquiring liquid-solid three-phase line contour information of each measurement point in a preset grid on the surface of a medical catheter sample and a corresponding initial contact angle; the preset grid is composed of a plurality of longitudinal measurement point sets; according to the liquid-solid three-phase line contour information of each measurement point in the preset grid and the corresponding initial contact angle, carrying out hydrophilic change trend analysis, and determining a local morphology disturbance degree corresponding to each measurement point and a comparability coefficient between different longitudinal measurement point sets; performing spatial interpolation correction on the initial contact angle based on the local morphology disturbance degree and the comparability coefficient to obtain a corrected contact angle of each measurement point; and performing coating uniformity detection on the medical catheter according to the corrected contact angle of each measuring point.

The invention discloses an unmanned express delivery vehicle control system and method based on operation state perception, and relates to the field of unmanned express delivery vehicle control systems. The method comprises the following steps: acquiring vehicle-mounted data in a driving period through a vehicle-mounted sensor array, performing time alignment and validity marking on the vehicle-mounted data to obtain a data quality label, constructing an evidence item set based on the data quality label, generating a sub-portrait label set according to the evidence item set, and displaying the sub-portrait label set in the driving period. And generating a portrait parameter set based on the sub-portrait label set through a preset priority rule and a persistence judgment strategy. Although the scheme has excellent performance in the aspects of improving system adaptability, safety, dynamic decision-making capability, reviewable performance and resource utilization efficiency, the problems of sensor faults, data loss, real-time data processing bottleneck, label interpretation errors and the like may influence the real-time response and decision-making precision of the system in a complex or extreme environment. Therefore, the overall performance and stability are reduced, especially under the condition of high load or low signal.

The invention provides a communication connection adjustment method and device, electronic equipment and a storage medium, and the method comprises the steps that first communication equipment determines a received signal strength indication of a communication signal received from second communication equipment, and determines a data packet error rate of the communication signal received from the second communication equipment; determining a target communication parameter according to the received signal strength indication and the data packet error rate; and adjusting the communication connection between the first communication device and the second communication device according to the target communication parameter. According to the embodiment of the invention, the PER is used as a core link quality evaluation index, a cooperative discrimination mechanism is formed with the RSSI, two typical link states of high signal strength but obvious interference and low signal strength but stable transmission are effectively distinguished, the problem of misjudgment caused by only depending on RSSI evaluation in the prior art is solved, and the accuracy of rate switching decision and the environmental adaptability are improved.

The invention discloses a semantic structure feature-based ancient book content integrity detection method and system, and relates to the technical field of information processing, the system comprises a data acquisition unit, a chapter integrity analysis unit, a paragraph integrity analysis unit, an integrity comprehensive analysis unit, a result feedback unit and a display terminal; structural features of chapters and paragraphs are accurately extracted by utilizing a semantic structure recognition technology, and the content integrity of the ancient books is comprehensively detected from the aspects of chapters and paragraphs in combination with an integrity analysis model, so that the defect that a traditional means depends on manual proofreading or simple page number comparison and keyword extraction, and the efficiency is high is effectively overcome. According to the method, the problems of typesetting confusion, chapter page missing, quotation omission and fuzzy paraphrasing which are common in the ancient books are difficult to deal with, automatic and multi-level analysis of the structural content and semantic level content integrity of the ancient books is realized, and the detection and recognition efficiency of the content integrity of the ancient books is improved.

This invention provides a label defect detection method, apparatus, electronic device, and storage medium, belonging to the field of machine vision technology. The method includes: acquiring a registered and aligned binarized image of a template edge and a binarized image of the edge to be tested; performing dilation processing on the template edge binarized image and finding its intersection with the binarized image of the edge to be tested; subtracting this intersection from the binarized image of the edge to be tested to obtain a first defect region with redundant features; performing dilation processing on the binarized image of the edge to be tested and finding its intersection with the template edge binarized image; subtracting this intersection from the template edge binarized image to obtain a second defect region with missing features; and determining the defect detection result based on the aforementioned defect regions. This invention, through a bidirectional dilation tolerance differential mechanism, effectively accommodates local deformation caused by label wrinkles and positional offset of edge pixels, solving the problem of numerous false positives caused by local deformation, and significantly reducing the false alarm rate while ensuring a high defect detection rate.

The application provides an intelligent cruise garbage pickup and classification vehicle, method, equipment and medium to solve the problem that the existing laser radar can only obtain two-dimensional point cloud data and cannot identify garbage material, volume and other characteristics. The garbage pickup and classification vehicle comprises the following components: an upper computer, a lower computer, a laser radar, a depth camera, an odometer, an IMU, a mechanical arm and a wireless communication port. Through the heterogeneous data cooperation of the laser radar and the depth camera, the limitations of a single sensor are effectively eliminated. The laser radar provides high-precision two-dimensional spatial information, and the depth camera supplements three-dimensional geometric and visual semantic features, significantly enhancing the comprehensive perception ability of the garbage material, shape and volume. This fusion not only solves the problem of garbage material misjudgment in the traditional scheme, but also supports the adaptive grabbing strategy of the mechanical arm, reducing the risk of grabbing failure caused by environmental complexity. A double-bus communication redundancy design is adopted to ensure the stable transmission of key signals.

The present application relates to the technical field of automatic control and machine vision, and particularly relates to a path planning and blind area elimination method for a crawler-type cleaning robot, which comprises the following steps: collecting a photovoltaic module surface image through a vision sensor arranged on a robot body, extracting photovoltaic cell grid line features and establishing a local coordinate system; generating a path reference line based on the grid line direction, and calculating a lateral deviation and an angle deviation between a current position of the robot and the path reference line in real time; dynamically adjusting a robot walking path through a fuzzy control method; dynamically adjusting a cleaning interval by calculating a current cleaning width and an expected overlap rate; and executing an obstacle crossing or board crossing decision based on an inclination angle data when sensor data conflicts. A multi-sensor data fusion technology improves the anti-interference capability of the robot, so that the robot can stably operate in a strong light, a reflective light and the like.

This invention provides a test method for determining injection fusion in multiple injections of a high-pressure common rail system, comprising the following steps: S1. Constructing a high-pressure common rail system injection pattern test system to test the injection pattern of two injections: pre-injection + main injection; S2. Constructing a high-speed photography direct-view test system for the injection process of the high-pressure common rail system to test the spray development characteristics under injection intervals; S3. Processing the images of the spray development process of multiple injections of the high-pressure common rail system, and repeating the spray development characteristic test until the fuel sprays of the two injections merge. The test method for determining injection fusion in multiple injections of a high-pressure common rail system described in this invention employs a spray visualization test method, obtaining the actual development process of real fuel spray in the cylinder, which can accurately determine whether actual fuel spray fusion has occurred in the cylinder, solving the problem of misjudgment of injection fusion based on control signals and injection pattern curves.

This invention provides a method and system for constructing a negative obstacle risk map, relating to the field of robot environmental perception technology. The method includes: acquiring multimodal sensing data of a legged robot in the current operating environment to obtain the types of negative obstacles, multiple candidate regions, and the corresponding confidence and uncertainty of each candidate region; using a risk diffusion algorithm, performing ink blurring processing based on the type, confidence, and uncertainty to generate a continuous risk field corresponding to each candidate region; dividing the continuous risk field to generate a continuous risk gradient distribution corresponding to each candidate region; performing terrain modeling based on laser point clouds, updating the continuous risk gradient distribution using Bayesian fusion to obtain a multi-level grid map, and then performing tactile closed-loop correction on the multi-level grid map to generate a risk cost map. This invention improves the accuracy of constructing a negative obstacle risk map.

The invention discloses a blood oxygen signal denoising method and system based on adaptive filtering, and the method comprises the steps: synchronously collecting an original blood oxygen signal and a three-axis acceleration signal through a sensor module, and obtaining an original blood oxygen signal sequence and a three-axis acceleration signal sequence which are aligned in time; the three-axis acceleration signals are fused into one-dimensional motion artifact reference noise signals used for representing the limb motion state of the user; the method comprises the following steps: dynamically calculating an adaptive step length factor sequence through a nonlinear mapping function based on multilevel energy analysis of a motion artifact reference noise signal; constructing a time-varying step size adaptive filter, and calculating noise components in the original blood oxygen signal by using the motion artifact reference noise signal and an adaptive step size factor; and subtracting the calculation noise signal from the original blood oxygen signal, and reconstructing to obtain a pure blood oxygen signal without motion artifacts. According to the method, accurate calculation and efficient suppression of motion artifacts can be achieved, and the purification quality and processing efficiency of blood oxygen signals are remarkably improved.

The present application relates to a kind of detection method and system for air bag bag production, it is related to the field of automobile passive safety technology, it includes obtaining current process number;Determine current tool number;Call in report record;Call in tool use information;Analysis report record and tool use information, to output abnormal reason;Real-time acquisition global overhead view and air bag fabric side view;Determine air bag fabric fluctuation point;Frame select air bag fabric fluctuation point corresponding fluctuation area;Determine fluctuation area height feature;Determine fluctuation area texture feature;Determine coating thickness anomaly, and output defect air bag bag signal;When there is no coating thickness anomaly, determine wrinkle area;When there is wrinkle area, execute flattening operation, and re-execute step 9 to step 12;When there is still wrinkle area after flattening operation, determine permanent wrinkle and output defect air bag bag signal.The present application has the effect of timely maintenance to tool and accurate traceability abnormal point in production process.

The invention provides a flower quality grading quality inspection method and system based on AI and image processing, and belongs to the technical field of computer vision and pattern recognizing.The method comprises the steps that an original image of the surface of a flower is collected through high-resolution imaging equipment, and high-frequency sub-band data representing tiny physical characteristics are extracted through multistage discrete wavelet transform; meanwhile, a sliding window is adopted to traverse the image, the color information entropy of a local area is calculated, and a color entropy graph is constructed. And after vectoring and splicing the two types of features, inputting the two types of features into a deep belief network model based on a multilayer restricted Boltzmann machine, and extracting deep abnormal feature codes. And finally, performing linear discriminant analysis on the code by utilizing a classification projection vector based on inter-class and intra-class distance optimization to generate an insect attack infection index, and realizing automatic grading quality inspection of the flower quality according to the insect attack infection index. According to the method, precise recognition and quantitative grading of tiny insect pests and recessive lesions on the surfaces of the fresh flowers are realized.

An optical time-of-flight sensor includes a sensor array and a channel sampling circuit. The channel sampling circuit is configured to receive a photon pulse signal generated from a sensor cell of the sensor array, receive a first channel select signal to generate a first freeze signal, generate a first channel event signal in response to the first freeze signal and the photon pulse signal to a first counting circuit, receive the first channel event signal, and generate and count a number of pulses of the photon pulse signal received by the first channel. The first freeze signal maintains a previous state when a rising edge of the photon pulse signal occurs until a falling edge of the photon pulse signal occurs. The provided time-of-flight sensor can significantly improve accuracy of a distance estimation operation by avoiding channel misjudgments without repeatedly calculating a number of arrived photons.

The invention relates to a walnut pairing method and device based on category feature self-adaption, equipment and a medium, and relates to the technical field of amusement walnut pairing, and the method comprises the steps: carrying out the rigid alignment processing of first contour data corresponding to a first walnut and second contour data corresponding to a second walnut; based on the first contour data and the second contour data after alignment processing, obtaining total contour loss between the first walnut and the second walnut, and based on the total contour loss, obtaining a target contour score; based on the type information of the first walnut or the second walnut, obtaining a target bottom line score and a target front line score between the first walnut and the second walnut; and based on the target contour score, the target bottom line score and the front line score, obtaining a comprehensive pairing score between the first walnut and the second walnut. According to the method, automatic pairing frameworks of different analysis strategies can be adaptively selected according to walnut category features, and the accuracy and efficiency of pairing are improved.

This invention relates to the technical field of deep integration of radio frequency identification (RFID) technology, indoor positioning technology, and intelligent algorithms. It discloses an RFID point-to-point positioning method and system that integrates inspection behavior characteristics. The method includes: within a single scanning cycle, using a mobile reading terminal to read multiple RFID tags and collect the identification information and multi-dimensional signal characteristics of each tag, including signal strength, TOA timestamp, and reading frequency; based on signal strength and reading frequency, eliminating invalid tags to obtain a candidate tag set; when the candidate tag set contains multiple tags, automatically determining a unique target tag from the multiple tags using a progressive judgment logic, where the inspection route information includes the order of each inspection node and its corresponding path weight; and outputting the physical location corresponding to the target tag as the current location. This invention fundamentally solves the technical problem of not being able to automatically distinguish valid locations when multiple tag signals conflict in traditional RFID tag-based positioning.

This invention relates to the field of packer testing technology, specifically to a device for testing the airtightness of packers. The device includes a mounting base with a transparent water tank on its upper surface. A vertical lifting assembly is mounted on the mounting base, with its upper end extending outside the mounting base and fixedly mounted with a connecting block. One end of the connecting block is fixedly connected to a mounting plate, on which an air compressor is fixedly mounted. The other end of the connecting block is fixedly connected to a support block. A rotating hole is formed inside the support block, and a storage tube is rotatably connected to the rotating hole via a bearing. The storage tube is filled with an environmentally friendly water-based marking solution. The packer is quickly fixed via a threaded joint. A push plate and positioning rod control the entry of the marking solution. The sealing performance is visually assessed using the conspicuous, water-insoluble marking solution, air compressor pressurization, and the transparent water tank. A filter membrane separates the marking solution from the water; both are recyclable, residue-free, and environmentally friendly.

The invention relates to the technical field of nondestructive testing, in particular to a copper bar coating lower substrate defect nondestructive testing device based on terahertz waves, which comprises a terahertz scanning acquisition module used for controlling a transmitting and receiving unit to perform two-dimensional scanning so as to acquire an original waveform; the flight time dynamic correction module is used for resolving the local coating thickness and carrying out dynamic time axis alignment; the substrate roughness deconvolution module is used for calling the reference model to carry out deconvolution filtering so as to strip background scattering noise; the interface dielectric feature analysis module is used for extracting a dielectric feature vector reflecting an interface dielectric constant mutation state; the defect risk assessment imaging module is used for constructing a three-dimensional chromatography map and outputting a detection result; according to the method, the physical characteristic decoupling of the signal source is realized, the coating thickness fluctuation and the real defect are effectively distinguished, the misjudgment rate is obviously reduced, and the evaluation accuracy is ensured.

The application discloses a data intelligent analysis system and method based on network IP tracing, relates to the technical field of network tracing, and comprises the following steps: collecting network traffic data every unit period, identifying abnormal events in each unit period; identifying abnormal behavior patterns in different unit periods; extracting key information under the same behavior pattern; obtaining IP jump conditions of any abnormal event and generating an IP tracing path; judging the abnormality of each tracing path; analyzing the confidence of each key information and obtaining the comprehensive confidence of the extracted tracing path, setting a tracing confidence threshold of the tracing path; extracting key information from the real-time captured abnormal event and generating an expected tracing path; identifying the effectiveness of the expected tracing result; solving the misjudgment problem caused by static evaluation and greatly improving the reliability of the tracing result.

This invention relates to the field of intelligent manufacturing and industrial data analysis technology, specifically to a method, system, and storage medium for identifying production bottlenecks based on multi-dimensional data fusion. The method includes: acquiring production data and constructing a multi-dimensional data vector; updating the weights of a linear prediction model based on the multi-dimensional data vector; performing multi-dimensional data fusion using the updated weights to obtain a comprehensive index value; obtaining a production bottleneck severity score based on the comprehensive index value; determining the production bottleneck status based on the production bottleneck severity score and the comprehensive index value; and identifying factors influencing the production bottleneck based on weight changes. This invention dynamically adjusts the weights using a gradient descent method to score the bottleneck, and dynamically updates the judgment threshold using an exponentially weighted moving average. Finally, it performs multi-dimensional cause analysis by comprehensively considering the weight contribution, change trend, and data anomaly, achieving adaptive and accurate location and cause identification of production bottlenecks.

The invention relates to a bean lack detection method and device for beverage equipment, the beverage equipment and a storage medium. In response to a beverage making instruction, a correlation signal is detected, the state of a bean grinder is detected at the same time, in any bean grinding period, if the correlation signal is not detected and it is determined that the bean grinder does not have an empty grinding state, a powder pressing link after grinding is executed, and the thickness of pressed powder is obtained; under the condition that the thickness of the pressed powder is smaller than the thickness threshold value, a first bean lack prompt signal is sent out. Whether beans exist in a bean storage bin or not is judged by detecting correlation signals at the beginning of bean grinding or in the bean grinding process, so that the situation that no beans exist in the bean storage bin can be found in time, the number of rotation turns of the bean grinder is dynamically monitored in the bean grinding stage, and bean lack detection is achieved in combination with a dual verification mechanism for monitoring the thickness of pressed powder in the powder pressing stage; the problem of misjudgment caused by detection only through correlation signals can be avoided, and the accuracy and robustness of bean lack detection are remarkably improved.

This disclosure provides a security detection method, apparatus, storage medium, and electronic device based on a large model, relating to the field of network security technology. The method includes: acquiring training sample emails to train a Bayesian classifier, determining the trained Bayesian classifier; using the trained Bayesian classifier to detect emails to be detected, determining a first detection result; if the first detection result is in a first detection interval, determining structured prompt words based on the first detection result; inputting the structured prompt words into a locally deployed large language model, determining the output result of the large language model; and performing either allow or block actions on the emails to be detected based on the first detection result and the output result of the large language model. This achieves accurate email identification.

The application relates to the technical field of wireless communication and data transmission, and discloses a main-backup link digital transmission control method and system of an intelligent fusion terminal, wherein the method comprises the following steps: acquiring multi-dimensional observation parameters of a main link and a backup link and constructing a normalized vector; forming a main-backup link fusion score; constructing short window and long window exponential average values; calculating a score residual, a degradation energy quantization value and a cumulative degradation amount; generating a pre-switching control parameter; performing shunt transmission of a service packet; and completing session context migration and old link release. Compared with the link switching mode depending on received signal strength in the prior art, especially under high-speed movement and base station boundary switching conditions, the technical problems of mis-switching or switching lag are prone to occur. Due to the dynamic weighted fusion score of the multi-dimensional normalized parameters and the score prediction based on trend extrapolation, the application realizes forward-looking identification and predictive switching of the link state.

This invention discloses a fault-risk coupling comprehensive assessment method, system, and medium for grid-type offshore wind turbines, belonging to the field of offshore wind turbine fault diagnosis technology. The method includes the following steps: S1: Operating condition classification and adaptive preprocessing; S2: Multi-dimensional joint fault feature mining; S3: Multi-operating condition adapted intelligent fault identification; S4: Fault-risk coupling transmission modeling; S5: Comprehensive risk coupling quantitative assessment; S6: Closed-loop operation and maintenance decision-making. This invention combines the characteristics of grid-type turbine coupled operation with the grid, integrating multi-operating condition adaptive data processing, multi-dimensional fault identification, fault cascading transmission analysis, and comprehensive risk quantitative assessment into a novel method. It overcomes the shortcomings of existing technologies in operating condition adaptation, fault prediction, and coupled risk assessment, providing technical support for the offshore operation and intelligent operation and maintenance of grid-type offshore wind turbines.

The present application relates to the field of agricultural big data and fertilizer supply chain management, and particularly to a selenium-rich bio-organic fertilizer supply chain collaborative management system based on big data, comprising: a source evaluation step: a management center calls material attributes, a raw material evaluation unit analyzes source quality fluctuations to distinguish batches; an efficiency drift analysis step: in response to abnormal control signals, a conversion analysis unit performs efficiency drift evaluation feedback analysis; a supply-demand collaborative matching step: in response to regular control signals, a collaborative demand unit obtains a collaborative demand coefficient, and a matching division unit performs quantitative matching analysis of control decision; a control execution step: compare control evaluation indexes to generate control signals; the present application constructs a source fluctuation perception and supply-demand collaborative matching closed loop, solves the spatiotemporal mismatch contradiction of raw material fluctuations and soil adsorption specificity, and improves the overall efficiency of the supply chain.

The utility model discloses a rare earth chloride feeding device with a liquid level sensor, and relates to the field of chemical engineering. Comprising a feeding device body, a telescopic supporting column and a liquid level sensor. A telescopic supporting column is installed at the bottom of the feeding device body, a bottom plate is arranged at the bottom of the telescopic supporting column, a limiting locking bolt is installed on the bottom plate, the height of equipment can be adjusted through the structure, different ground conditions can be adapted, and the stability of the equipment is improved. The filter plate is arranged in the feeding device body, and the liquid level sensor is mounted on the filter plate, so that the liquid level is monitored in real time, manual visual inspection errors are avoided, and the feeding precision and stability are improved. The siphon tank is arranged on the left side of the device and connected with the feeding device body through the feeding conveying channel, the control valve is arranged, the feeding flow can be adjusted, and stable feeding is guaranteed.

The application discloses a kind of middle voltage distribution equipment grounding fault precision detection method, it is related to distribution network fault detection and protection technical field.The method includes: in each feeder head synchronous acquisition zero sequence current and transient traveling wave signal;Zero sequence current and transient traveling wave are normalized and fused to construct joint transient signal, and net energy ratio is calculated by wavelet packet decomposition;Equivalent dynamic grounding impedance and impedance homology change rate are calculated;Intermittent grounding coupling index is constructed by jointly identifying arc reignition;Multi-feeder correlation discriminant matrix is constructed, and fault feeder is positioned according to fault correlation discriminant value sorting.The application realizes the collaborative use of zero sequence quantity and high-frequency transient information, improves the detection accuracy and positioning reliability of complex grounding fault.

The utility model relates to a head and tail plate bolt unscrewing turn number counting misjudgment prevention mechanism which comprises a pneumatic hammer (7) used for driving a special sleeve (1) arranged at the front end of the pneumatic hammer (7) to rotate, and a counting sensing structure is further arranged at the front end of the pneumatic hammer (7). The special sleeve (1) is provided with a characteristic through hole (8), and the counting sensing structure is used for conducting signal sensing processing on the characteristic through hole (8) and recording the number of turns based on the obtained signal. According to the head and tail plate bolt unscrewing turn number counting misjudgment prevention mechanism, through the arranged counting sensing structure, the number of rotation turns of a pneumatic hammer can be accurately recorded, the problem that under the condition that a nut is still not moved, the nut is misjudged to be rotating by the turn number counting sensor is solved, the misjudgment problem can be effectively solved, and certain application value is achieved.

The application discloses an AI large model-based personalized auxiliary teaching content dynamic generation and pushing method, and belongs to the technical field of data processing, and comprises the following steps: acquiring the conditional probability distribution of an AI large model output layer and constructing a benchmark probability distribution vector, acquiring a generation probability distribution feature vector in a subsequent generation round and performing distribution similarity analysis to determine a generation probability distribution drift state; performing controlled adjustment on the generation parameter set in the drift state, constructing a stable window in a continuous non-drift state, and dynamically updating the benchmark probability distribution vector. Teaching content is generated based on the adjusted generation parameter set and is pushed in batches, generation stability monitoring is performed in the pushing process, pushing constraint adjustment is performed according to the shock state and the convergence state, and finally, the converged generation parameter set is saved as an initial generation strategy corresponding to a teaching task, thereby solving the problem of implicit degradation of the teaching content generation quality in the prior art.

The application provides a wave energy power generation method and system based on a two-dimensional offline lookup table maximum power tracking, comprising the following steps: S1, performing mathematical analysis on a generator and a circuit collection system and building a simulation model; S2, obtaining a boost circuit duty cycle corresponding to a maximum output power of the generator on a load side under different rotating speeds and loads through the simulation model; S3, establishing a two-dimensional offline table and constructing an offline lookup table MPPT algorithm; and S4, measuring the rotating speed and the load of the generator in real time by using a hardware device and tracking the maximum power point of the device by using the lookup table MPPT. The improved MPPT method can correctly track the maximum power point of the wave energy power generation device and always work in a maximum power output state.