4920results about How to "Improve applicability" patented technology

The invention discloses a pallet protection corner automatic putting machine. The pallet protection corner automatic putting machine comprises a top protection corner putting combination machine and aside face protection corner putting combination machine; the top protection corner putting combination machine comprises a bottom circulation base and a pair of top protection corner single machines,the side face protection corner putting combination machine comprises a bottom fixed base and four side face protection corner single machines, the top face protection corner single machines are provided with electrical control parts, top protection corner containing grooves, limiting mechanisms, and top protection corner mounting claws, the top protection corner mounting claws grab protection corners in the top protection corner containing grooves, and put the protection corners on four edges of the top of a packaging box, each side face protection corner single machine comprises a second electrical control part, a side protection corner containing groove, and a side protection corner mounting claw, and the side protection corner mounting claws grab the protection corners in the side protection corner mounting grooves and put the protection corners on the four sides of the side face of the packaging box. The pallet protection corner automatic putting machine is reasonable in layout,smooth in operation, high in adaptation, automatic in full process, free of artificial duty and capable of greatly improving protection corner putting and threading packaging capacity.

The invention is suitable for the technical field of road construction, and provides a wind power plant road intelligent line selection method based on multi-dimensional constraint dynamic modeling, and the method comprises the steps: obtaining a multi-dimensional constraint condition of wind power plant road line selection, and constructing a constraint model; generating a slope grid map based on a digital elevation model, and fusing the slope grid map with a constraint map layer reflecting geological stability and a land cover type to generate a dynamic cost surface; adopting an improved heuristic search algorithm to perform parallel path search from the road starting point to each target fan position, generating a plurality of initial feasible paths, and calculating a comprehensive cost value; screening a candidate line set according to a comparison result of the comprehensive cost values; receiving real-time updating data in a construction process and environment monitoring, inputting the real-time updating data into the constraint model to trigger model updating, performing iterative optimization on the candidate line set based on the updated constraint model, and outputting a final line selection scheme; and the line selection efficiency, economy and reliability are effectively improved.

This invention discloses a method for indicating the degree of pyrite development in carbonate reservoirs, belonging to the field of geological exploration technology. Its key features include the following steps: a) selecting sensitive parameters to distinguish pyrite development based on the well logging response characteristics of pyrite-developed strata; b) establishing trend lines for the variation of sensitive parameters in formations with no or low pyrite content using these sensitive parameters; c) constructing trend lines for the variation of sensitive parameters with pyrite content based on strata data from key wells with different pyrite contents; d) identifying pyrite-enriched strata in the wells to be identified based on the intersection indications of the sensitive parameters; e) evaluating the degree of pyrite development in the pyrite-enriched strata by assessing the degree of difference in the intersection of sensitive parameters. This invention achieves the identification of pyrite-enriched strata through resistivity and sonic transit time intersection, enabling rapid and accurate identification of the degree of pyrite development in carbonate reservoirs.

The invention relates to the technical field of city data representation. The invention discloses an urban space general representation learning method and device based on multi-modal spatio-temporal data fusion, a terminal and a storage medium, which can improve the applicability of urban general representation and enable the urban general representation to be applicable to diversified urban analysis tasks. The method comprises the following steps: acquiring multiple modal spatio-temporal data of each space unit in a target city, and setting a corresponding view for each modal spatio-temporal data; on the basis of each modal spatio-temporal data of each space unit, generating a representation of each space unit in a single view under a view corresponding to each modal spatio-temporal data; generating a multi-view fusion representation corresponding to each space unit based on the representation of each space unit in a single view under the views corresponding to all modal spatio-temporal data, and forming a multi-view fusion representation matrix by the multi-view fusion representations corresponding to all the space units; and performing global aggregation processing on the multi-view fusion representation matrix to obtain urban general representation.

The invention relates to the technical field of multi-beam sounding calibration, and discloses a multi-beam sounding online real-time calibration method. The method comprises the following steps: acquiring original water depth data and corresponding sensor attitude data in real time; generating a data quality evaluation result containing a data credibility index and a data abnormal distribution feature based on the original water depth data; triggering a dynamic calibration mechanism containing a calibration period adaptive adjustment strategy and a calibration parameter optimization rule according to the data credibility index; optimizing the target calibration rule parameters in combination with the sensor attitude data to generate an optimized calibration parameter set, and correcting the original water depth data in real time by using the parameter set to generate primary calibration data; and performing topographic feature consistency check on the primary calibration data, if the primary calibration data does not pass the topographic feature consistency check, starting a re-calibration process containing a rule base updating mechanism and a parameter iteration mechanism, and analyzing a deviation trend based on historical calibration records to generate a system error prediction model.

The invention provides an excitation amplitude automatic closed-loop control system and method for a DLCP test. The system comprises a multi-frequency alternating current excitation and direct current bias voltage applying module which is used for automatically applying alternating current excitation signals and direct current bias voltage signals according to a preset excitation amplitude sequence under a plurality of test frequencies; the PID closed-loop control module is used for performing closed-loop correction on the applied voltage according to the response of the test port of the tested semiconductor device, so that the condition of the applied voltage at the test port meets a preset requirement; the capacitance measurement module is used for acquiring an equivalent capacitance response signal of the tested semiconductor device; the capacitance test data caching module is used for performing associated marking and classified caching on the capacitance test data according to the test frequency, the excitation level and the bias voltage set point; and the main control module is used for coordinating automatic test processes under the conditions of a plurality of test frequencies and different excitation amplitudes and outputting corresponding capacitance test data so as to improve the consistency, stability and automation degree of the DLCP test.

The invention discloses a rapid fault isolation method integrating protection, measurement and control of a box-type substation, particularly relates to the technical field of fault isolation of a power distribution network, and aims to solve the problem that an existing box-type substation is not complete in protection action information, disturbance exists in measurement and a primary wiring relation is complex. The problems of difficulty in timely and accurate judgment of a fault section, large isolation range, insufficient supply guarantee of important users and lack of traceable evidence chain in a fault processing process are solved. The method comprises the following steps: dividing sections according to primary switches and cable joints in a box-type substation, establishing a section-level topology model for unified time service and fault evidence fingerprints bound with protection configuration, scoring operation slices based on section fault hypothesis and a theoretical event mode, and solving a minimum isolation switch set under isolation constraint, so as to obtain a minimum isolation switch set; therefore, when the protection action is incomplete, the measurement is disturbed and the wiring is complicated, the fault section can still be locked, and an isolation scheme considering the user supply guarantee and the electrical safety boundary is generated, so that the fault isolation correctness and rapidity are improved.

The invention relates to the technical field of slope disaster monitoring, in particular to a high and steep slope geological disaster monitoring method and system based on multi-source data fusion. The method comprises the following steps: tracking surface deformation through PS-InSAR time sequence analysis and atmospheric phase correction to obtain surface deformation characteristics; identifying the apparent diseases of the slope, and extracting spatial and temporal distribution characteristics of the apparent diseases of the slope; analyzing spatio-temporal evolution characteristics under geologic structure constraints by utilizing slope rock mass structure characteristics and the earth surface deformation characteristics; according to underground water level dynamic and potential sliding surface weakening features and the slope apparent disease spatial and temporal distribution features, extracting disaster-causing key factor features after cooperative correction; and combining the disaster-causing key factor characteristics, the true three-dimensional geological environment background characteristics and the spatio-temporal evolution characteristics to analyze the comprehensive early warning grade and the potential instability mode of the landslide. Scientific support is provided for high and steep slope geological disaster prevention and control, and engineering construction and operation safety can be guaranteed.

The invention provides a non-stationary industrial process monitoring method and system. The method comprises an offline training stage: calculating a time Laplacian matrix and a space Laplacian matrix based on a historical data matrix; constructing an objective function of the stationary subspace analysis method, and adding a time constraint term of a time Laplacian matrix and a space constraint term of a space Laplacian matrix into the objective function; solving the objective function to obtain a stable projection matrix; calculating a stationary component and a monitoring index of each sample in the data matrix X in sequence; determining a control limit by using a kernel density estimation method; an online monitoring stage: based on the real-time operation data x, calculating a stationary component of the real-time operation data x and a corresponding real-time monitoring index according to the stationary projection matrix, and if the real-time monitoring index is greater than a control limit, judging that the operation of the non-stationary process has a fault; the monitoring accuracy can be improved.

The invention discloses a multi-source data fusion transformer substation digital twinning model construction method and system, and belongs to the technical field of intelligent power grid digital twinning, and the method comprises the steps: carrying out the multi-source data collection to obtain the related data of a transformer substation, and constructing a three-dimensional entity model; deploying a multi-physical field monitoring device, constructing a real-time data acquisition network, and dynamically fusing multi-source data and a three-dimensional entity model; performing feature extraction and weighted fusion on the dynamically fused multi-source data; a multi-physics field coupling analysis model is constructed based on a deep learning network, and dynamic simulation and visualization of multiple physics fields are realized by using fusion feature data; system function modularization is achieved through a micro-service architecture, real-time updating, cross-platform deployment and multi-user interaction of a multi-physics coupling analysis model are supported, and a transformer substation digital twinborn model is obtained. According to the method, data of multiple physical quantities can be fused, multi-physical field coupling analysis is carried out, the overall layout and actual errors are optimized, and the precision and accuracy of the model are improved.

This invention discloses a medical ablation catheter, an ablation system, and a method of use. The medical ablation catheter includes a first catheter located at its distal end; a second catheter including an inner catheter and an outer catheter, the outer catheter being sleeved outside the inner catheter and slidably relative to it; a conductive part connecting the first catheter and the inner catheter, its distal end fixed inside the first catheter and its proximal end fixed to the inner catheter; and an adjustment part, its distal end fixed inside the first catheter and its proximal end movably inserted inside the inner catheter. The conductive part can switch between a linear state and an expanded state, and ablation is performed when the conductive part is in the expanded state. This medical ablation catheter enables various ablation methods, allowing for different working modes to be changed as needed to improve applicability, and the use of expandable electrodes to conform to the area to be ablated improves conformability.

The invention provides a multi-reflection superposition enhanced microwave displacement measurement method and system, and the method comprises the steps: S1, constructing a microwave multi-reflection propagation path, enabling a microwave radar to transmit electromagnetic waves to the microwave multi-reflection propagation path as a transmission signal, and receiving a corresponding echo signal; s2, extracting length change information of a microwave multi-reflection propagation path according to the echo signal; s3, establishing a linear superposition relation model between the total length of the microwave propagation path and respective displacements of W reflection surfaces in the microwave multi-reflection propagation path; w2; and S4, based on the linear superposition relation model, displacement information of the corresponding reflection surface is obtained and output. According to the invention, a larger phase variation can be obtained under the condition of small displacement or weak vibration, so that the measurement sensitivity is improved and the signal-to-noise ratio is improved.

The invention relates to the technical field of automobile part machining, and discloses an automobile part multi-station synchronous clamping and positioning device which comprises a support, a vertical plate is fixedly arranged in the middle of the support, the vertical plate is slidably connected with a plurality of sliding plates, a sliding seat is fixedly arranged on one side of each sliding plate, a baffle is arranged on one side of each sliding seat, and the baffle is fixedly connected with the support. Two sliding rods in sliding connection with the sliding seat are fixedly arranged on one side of the baffle, the surfaces of the sliding rods are sleeved with springs, and a first clamping plate is fixedly arranged at one end of each sliding rod; the single air cylinder drives the cross beam to synchronously push all the sliding plates, synchronous clamping of workpieces at multiple stations is achieved, the auxiliary clamping time is greatly shortened, the production efficiency is improved, the consistency of clamping actions of all the stations is guaranteed, and the problem of workpiece deformation or displacement caused by uneven clamping force is solved.

The utility model relates to a prefabricated middle partition wall structure of a tunnel ventilation inclined shaft. The prefabricated middle partition wall structure at least comprises a bottom supporting structure, a steel supporting assembly and a prefabricated modular wallboard. A positioning groove is formed in the top face of the bottom supporting structure, and the bottom of the steel supporting assembly is embedded into the positioning groove and fixed. The prefabricated modular wallboard is formed by splicing a plurality of prefabricated slabs, the adjacent prefabricated slabs are connected through tongue-and-groove structures which are matched in a concave-convex mode, and the tongue-and-groove joints are filled with sealing materials. The steel supporting assemblies are longitudinally arranged at intervals, and the tops of the steel supporting assemblies are fixed to a tunnel lining to form a steel-concrete combined structure for supporting the prefabricated modular wallboard. The steel supporting assembly and the prefabricated modular wall plate form a steel-concrete prefabricated structure, and the stability of the whole structure is enhanced. By adopting the autoclaved aerated concrete precast block material and the concave-convex groove embedded modular structure, the problems that the construction quality is difficult to control, the construction period is long, the on-way resistance of air flow is large and the like in the existing reinforced concrete mid-partition wall are solved.

The invention discloses a wafer defect atlas intelligent identification and classification method and system, and relates to the technical field of semiconductor integrated circuit manufacturing and detection, and the method comprises the steps: obtaining a detection point set, an original image and standard reference attribute data; constructing a space weight matrix based on reference data; calculating a generalized connection cost based on a path weighted cumulative value, constructing an initial graph model, and performing probability sparsification; determining verification points based on the weight matrix and extracting local gradient features of the original image; correcting the connection probability by using a Bayesian inference model, and updating a graph topological structure; and finally, outputting a classification result according to the connected sub-graph features. According to the method, layout physical attributes and image microscopic features are combined, and accurate reconstruction and classification of defect forms under a complex background are realized.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a memory analysis question and answer data construction method and device, equipment and a medium. The method comprises the steps of extracting a fact information set containing entities, relationships and values based on structured message representation, generating candidate question and answer pairs by utilizing a language model, executing multi-source verification to form a target question and answer set, performing semantic extension and question method transformation to generate a diversified question and answer set, and completing credibility screening based on a verification result to obtain a memory analysis question and answer set. And generating a memory analysis data set in combination with the user message sequence. According to the method, through multi-stage extraction, generation, verification and screening, reliability and diversity unification of question and answer content are achieved, the constructed memory analysis data set has the advantages of being consistent in context, accurate in fact, rich in expression and the like, and therefore the credibility of memory ability evaluation of the large language model is improved.

This invention discloses a high-speed slitting device for cold-rolled steel sheets, relating to the field of cold-rolled steel sheet shearing technology. It includes a shearing assembly for cutting cold-rolled steel sheet coils, with a pre-treatment box mounted on the front surface of the shearing assembly. In operation, the invention starts an electromagnetic rod and a rolling motor. The rolling motor drives a drive gear to rotate, which in turn drives two driven gears to rotate in opposite directions. These gears, through a gear ring, drive two toothed rods to rotate, further rotating the upper and lower rolling rollers to electromagnetically roll the two sides of the cold-rolled steel sheet. Combined with an eddy current sensor and a PLC controller, the magnetic field force is intelligently and dynamically adjusted according to the edge conditions of different hardness levels, achieving "flexible de-hardening." Then, a U-shaped focusing induction coil is activated to achieve rapid localized heating of the hardened layer, restoring the hardness to near that of the substrate, thus eliminating work hardening. The combination of magnetic rolling and localized heating softening achieves "full-thickness softening."

The invention relates to a BERT and multi-module fusion-based track circuit fault label classification method and device and a medium, and the method comprises the steps: obtaining a to-be-classified track circuit fault text, and carrying out the cleaning and standardization processing of the to-be-classified track circuit fault text; performing word segmentation and vectorization processing on the track circuit fault text to generate a lexical symbol sequence conforming to BERT encoder input specifications; extracting a context semantic vector representation of the input lexical symbol sequence through a BERT encoder; performing feature extraction through a TextCNN module and a self-attention module which are parallel to obtain local features and weighted global features, and splicing the local features and the weighted global features to obtain a comprehensive feature vector; and synchronously generating a multi-label classification result of a fault phenomenon, a fault reason and a solution measure corresponding to the current fault text through a multi-label classification head based on the comprehensive feature vector. Compared with the prior art, the method has the advantages of high discrimination, high accuracy, high practicability and the like.

The invention discloses a lithium battery health condition multi-dimensional diagnosis method and system, and relates to the field of lithium battery health diagnos.The lithium battery health condition multi-dimensional diagnosis method comprises the steps that discrete charging data fragments are obtained from a vehicle management system, and intelligent reconstruction of a virtual incremental capacity analysis curve is conducted based on the fragments; a confidence map is synchronously generated to quantify the reliability of the reconstructed data. And then, key health features are extracted from the reconstruction curve, and adaptive weighting is performed on the features by using a confidence map, so that a comprehensive index vector capable of accurately reflecting the real aging state in the battery is generated. And finally, deep diagnosis is carried out based on the index vector, and multi-dimensional accurate diagnosis of the health condition of the battery is realized, so that a multi-dimensional evaluation report of the health condition of the battery is output. Therefore, the interference of poor data quality on the diagnosis precision under the real driving working condition can be effectively overcome, and the practical applicability and reliability of diagnosis are remarkably improved.

The invention discloses a tunnel-pile interaction experiment method and device based on a 3D printing technology, and belongs to the technical field of civil engineering underground structure tests. The method comprises the steps that the geometric and mechanical similarity ratio is determined according to an engineering prototype, a tunnel lining model and a pile group model are prepared through the 3D printing technology, and controllable adjustment of the rigidity of the tunnel model is achieved by adjusting the type, the filling rate and the internal structure of a printing material; controllable adjustment of the rigidity of the pile foundation model is realized by adjusting the size of the magnetic field; the model is placed in a soil body groove, the shield tunnel excavation process is simulated, and deformation data of a tunnel and a pile foundation are collected through a PIV technology and a sensor. Accurate control over the rigidity of the tunnel and pile foundation model is achieved through 3D printing, the influence of shield tunnel construction on the pile group foundation can be simulated under the condition that the similarity criterion is met, and the device has the advantages of being adjustable in structure, high in experiment efficiency and the like and can be used for researching a dense urban area tunnel-pile deformation coupling mechanism and optimizing related engineering parameters.

The invention discloses a drilling pump pressure prediction method based on an artificial neural network, and the method comprises the following steps: S1, data collection; s2, data preprocessing; s3, constructing a neural network model; s4, model training and optimization; and S5, model verification and deployment. According to the method, multi-channel data fusion and time synchronization optimization are innovatively adopted, so that the data quality and consistency are improved; in combination with a deep neural network and a self-adaptive optimization strategy, the precision and generalization ability of pump pressure prediction of the drilling pump are improved; and an online updating mechanism is introduced, so that the model can be dynamically optimized according to real-time data, the defects of low prediction precision, poor adaptability and difficulty in real-time updating of a traditional method are overcome, and an efficient and reliable prediction means is provided for intelligent drilling control.

The invention relates to the technical field of fluidized beds, in particular to a fluidization coating device with pulse, stirring and double-particle triple synergy, which comprises a spray fluidized bed reactor, a fluidized bed reactor, a stirring device and a double-particle fluidized bed reactor, the gas distributor is positioned above the carrier gas inlet and is used for uniformly distributing carrier gas entering from the carrier gas inlet on the whole bed layer to form fluidized gas; the gas-liquid two-phase flow nozzle is connected with the gas supply unit and the coating liquid conveying tank and is used for atomizing the coating liquid into micron-sized small liquid drops and then spraying the micron-sized small liquid drops into the spray fluidized bed reactor; the mechanical shearing unit continuously generates local mechanical crushing on the aggregate; the pulse air inlet device is connected with the air supply unit and is used for applying periodic pulse airflow to the fluidized bed layer and breaking particle aggregation and channeling formed during initial fluidization; and the flow aiding particles and the fine powder particles to be coated jointly form a double-particle fluidization system. The problems of difficult fluidization starting, non-uniform fluidization and the like of ultrafine powder particles are solved through triple synergy of pulse, stirring and double particles.

The invention discloses a data-mechanism-knowledge combined driving dam safety state self-diagnosis method and system, and the method comprises the steps: obtaining dam operation state data, extracting a state quantity based on a pre-constructed computable evidence graph, and generating a monitoring evidence; performing inversion correction on mechanism model parameters under the priori constraint of the atlas, and generating mechanism evidence; the monitoring evidence and the mechanism evidence are accessed to a probability graph model for joint inference, and arbitration correction is carried out when a conflict triggering condition is met; and carrying out credibility calibration on the diagnosis result by adopting a conformal prediction method based on the historical calibration sample set, and outputting a security state diagnosis conclusion containing a confidence interval. According to the method, the problems of multi-source evidence conflict, mechanism parameter distortion and low diagnosis result credibility are effectively solved, and credible and automatic diagnosis of dam safety is realized.

The invention relates to the technical field of rock mechanics and intelligent detection, in particular to a rock strength and failure mode prediction method and system. The method comprises the following steps: acquiring data of a rock sample to be detected to obtain a multi-source feature set; constructing a feature coefficient prediction model, and inputting the multi-source feature set into the feature coefficient prediction model to obtain a feature coefficient; screening the multi-source feature set based on the feature coefficient to obtain an optimal feature subset; constructing a rock strength and failure mode prediction model, and optimizing hyper-parameters of the rock strength and failure mode prediction model by adopting an automatic hyper-parameter optimization framework; and inputting the optimal feature subset into the optimized rock strength and failure mode prediction model to obtain a rock strength prediction value and a failure mode. The problem that rock strength and failure mode prediction precision is not accurate enough and cannot be predicted at the same time in the prior art is solved, and the prediction precision is greatly improved through multi-source data collaborative prediction.

The utility model discloses an adjustable crop uniform seeding machine which comprises a rack, a plurality of groups of discharge ports are formed in the bottom of a seed box, discharge mechanisms are arranged on the inner sides of the discharge ports, two groups of mounting frames are arranged on the inner side of the rack, the top of one group of mounting frames is connected with a driving mechanism, and the inner sides of the two groups of mounting frames are connected with a plurality of groups of mounting arms through adjusting mechanisms. A plurality of groups of installation arms on the inner side of one installation frame are all provided with seed discharging pipes and are all connected with the corresponding discharging ports through connecting hoses, and a plurality of groups of installation arms on the inner side of the other installation frame are all provided with furrow openers, uniform seed discharging can be completed through the discharging mechanism, the driving mechanism can drive the installation frames to ascend and descend so as to adjust the furrow opening depth, and the furrow opening depth can be adjusted. The spacing between the seed-metering pipe and the furrow opener can be adjusted through the adjusting mechanism so as to adapt to the planting line spacing of different crops, so that through the structure, the flexible adjustment of the seeding line spacing and depth is realized, the planting requirements of various crops can be met, and the seeding applicability and uniformity are improved.

The invention provides a low-loss bionic elastic tooth type picking table of a linear pepper harvester. The low-loss bionic elastic tooth type picking table of the linear pepper harvester comprises a header frame, a picking roller, a pull-back rolling shaft and a conveying device. The header frame, the picking roller, the back-pulling rolling shaft and the conveying device are sequentially arranged from front to back in the feeding direction; the picking roller comprises a middle rotating shaft, a cam track disc, a spring tooth and a spring tooth shaft; the middle rotating shaft is installed on the header frame, the cam track discs are installed at the two ends of the middle rotating shaft respectively, a plurality of cam grooves are distributed in the circumferences of the cam track discs, the spring teeth are installed on the spring tooth shafts, the spring tooth shafts are arranged along the circumference of the middle rotating shaft, the ends of the spring tooth shafts are embedded into the cam grooves respectively, and the ends of the spring tooth shafts are matched with the cam grooves of the cam track discs. The spring teeth do radial telescopic motion under the constraint of the cam groove when the picking roller rotates; and the rotation direction of the back-shifting rolling shaft is opposite to that of the picking roller. The line pepper picking machine can efficiently complete line pepper picking so as to improve the picking efficiency, and the phenomena of less harvesting and missing harvesting are reduced by adopting secondary callback.

The invention discloses an auxiliary open fire heating device for improving the surface quality of extruded plastics. The auxiliary open fire heating device comprises a bracket base device and a fire jetting combustion furnace tray device and is characterized in that the bracket base device comprises a base and a support frame, and the support frame is mounted on the base; the fire jetting combustion furnace tray device comprises a gas inlet valve, a gas guide pipe and nozzle devices; the gas inlet valve is mounted at an inlet of the gas guide pipe; the nozzle devices are mounted on the gas guide pipe; and the fire jetting combustion furnace tray device is mounted on the bracket base device through the support frame. The auxiliary open fire heating device has the advantages of simplicity, convenience and feasibility and also has the advantages of being convenient to use, high in efficiency, high in practicability, light in structure and convenient to mount, disassemble and operate. Generally, when large-molecular-weight plastics of a molecular chain net structure, such as organosilane crosslinked polyethylene, are processed and produced, the auxiliary open fire heating device is directly mounted on a nose of the existing extruder by using magnetic absorption and utilizes open fire to carry out auxiliary open fire heating on a forming die orifice and an extruded wire so as to improve the poor surface quality of the extruded product.

This invention proposes a method for predicting the health status of lithium batteries based on multidimensional features and neural network constant differential equations. The method includes the following steps: S1, preprocessing the capacity data and charging stage operation data collected during lithium battery operation, and constructing features from historical health status data; S2, constructing multidimensional feature inputs for health status prediction based on the charging stage operation data; S3, inputting the multidimensional features into a gated recurrent unit network to fuse and encode the historical health status sequence and constant current charging stage features to obtain a potential feature representation characterizing the battery degradation state; S4, comparing the predicted health status value output by the neural network constant differential equation model with the corresponding actual health status value, calculating the prediction error, and evaluating the prediction accuracy. This application achieves high-precision prediction of lithium battery health status by integrating a multidimensional feature screening mechanism and a continuous-time state evolution modeling method.

The invention discloses a method for predicting the residual fatigue life of a titanium alloy component based on frequency mixing nonlinear ultrasound. The method comprises the following steps: firstly, building a detection system; the detection system is controlled to generate low-frequency f1 and high-frequency f2 sinusoidal signals to carry out frequency mixing excitation on the titanium alloy component, and ultrasonic response signals are collected; performing frequency domain analysis on the ultrasonic response signal, extracting a characteristic amplitude and calculating a nonlinear modulation parameter beta m; then, a Nazarov-Sutin equation and an Elber equation are combined, and a theoretical prediction model of the nonlinear modulation parameter beta m changing along with the fatigue life percentage f is constructed; finally, actual measurement parameters are substituted into the model to reversely derive the consumed fatigue cycle number N, and the residual fatigue life Nr is predicted by combining the critical failure total cycle number Nt of the component. According to the method, the quantitative mapping relation between the nonlinear acoustic parameters and fatigue damage accumulation is revealed by establishing the physical model, and accurate quantitative prediction of the residual fatigue life of the titanium alloy component is achieved.

This invention discloses a method, system, equipment, and storage medium for configuring the capacity of a static synchronous compensator (STATCOM) in a SLCC valve hall, belonging to the field of high-voltage direct current (HVDC) transmission technology. The method includes: analyzing the LCC commutation process based on an electromagnetic transient model of the commutation circuit using LCC capacitor reactive power compensation to determine a first analytical relationship between the amplitude of the power frequency component of the first commutation current and the capacitor reactive power compensation capacity; determining an electromagnetic transient model of the SLCC commutation circuit operating with STATCOM fundamental reactive power compensation and harmonic elimination functions based on the SLCC topology; analyzing the SLCC commutation process based on the electromagnetic transient model of the SLCC commutation circuit to determine a second analytical relationship between the amplitude of the power frequency component of the second commutation current and the fundamental reactive power compensation capacity and harmonic reactive power compensation capacity; and determining the STATCOM configuration capacity based on the first and second analytical relationships and according to capacity equivalence constraints. The technical solution provided by this invention can ensure the safety of SLCC commutation and harmonic compensation capabilities while reducing the redundancy of STATCOM capacity configuration.