36 results about "Fuzzy linguistic" patented technology

The invention provides a JKW control method based on adaptive fuzzy control, which belongs to the technical field of reactive power compensation of a power system, and comprises the following steps of: interacting reactive power compensation states of JKW devices in adjacent regions based on an edge physical agent, constructing a regional reactive power topological graph in combination with local power grid topological data, generating a regional coordination instruction according to a supply-demand relationship, and establishing a regional coordination graph according to the regional coordination instruction; the method comprises the following steps: acquiring proportion deviation, power factor deviation and reactive power change gradient of a mutual inductor, constructing a standard fuzzy input vector in combination with a regional cooperation instruction, mapping the standard fuzzy input vector into a fuzzy linguistic variable through a dynamically updated fuzzy rule base, and reasoning and outputting an initial switching strategy; and comparing and analyzing the proportion deviation and the power factor deviation through a hardware comparator, determining a trigger condition and existence of a fault, and dynamically optimizing an initial switching strategy by combining a regional reactive topological graph to realize the control of the JKW. And the operation stability of the power grid is obviously improved.

The invention discloses a spiral anchor foundation grouting pressure-flow-deformation intelligent coupling control method, and relates to the technical field of foundation grouting technologies, and the spiral anchor foundation grouting pressure-flow-deformation intelligent coupling control method comprises the steps that according to specification parameters of a spiral anchor and the type of a soil body where the spiral anchor is located, a preset engineering parameter set is matched; collecting grouting data of each grouting channel, and calculating grouting deviation data in combination with the engineering parameter set; performing fuzzification processing on the grouting deviation data, and converting the grouting deviation data into fuzzy linguistic variables; inputting the fuzzy language variable into a preset fuzzy rule base for reasoning, and outputting a PID parameter correction amount; parameters of a PID controller are dynamically adjusted according to the correction amount, and a pump speed adjusting instruction is generated; executing the pump speed adjusting instruction, and collecting grouting data after execution; a soil body permeability coefficient is obtained through inversion by constructing a digital twinborn model, and the fuzzy rule base is optimized and updated by combining the executed grouting data. The method is used for solving the problem that a traditional spiral anchor foundation grouting technology is poor in adaptability to complex geology.

The invention discloses a park micro-grid energy prediction and correction method based on a fuzzy language function. According to the method, a park micro-grid photovoltaic power generation capacity is taken as a prediction target, illuminance, temperature and air visibility are taken as core indexes to construct a park micro-grid photovoltaic power generation system prediction model, and the characteristics of high calculation speed and high responsiveness of a fuzzy language function are creatively utilized to track system prediction errors and error change rates. Core parameter indexes of the model are corrected in real time after fuzzy reasoning calculation, so that the model always tracks real-time environment characteristics to realize evolution, the park microgrid energy state is effectively predicted, a basis is provided for power dispatching and the like of the whole system, the charging and discharging time sequence of an energy storage system is guided, and the energy efficiency is improved. Therefore, a scientific solution is provided for the problem.

The invention discloses a precise sensing control method for the combustion state of an internal combustion engine. The method comprises the steps that S1, parameters are collected; s2, establishing a neural network model, training the neural network model, and identifying the running state of the internal combustion engine; s3, a fuzzy language is established, and respective fuzzy adjustment amounts of a fuel injection system, a valve transmission system and an ignition system are obtained; s4, self-adaptive control models of the fuel injection system, the valve transmission system and the ignition system are established respectively, and the self-adaptive adjustment amount of the fuel injection system, the self-adaptive adjustment amount of the valve transmission system and the self-adaptive adjustment amount of the ignition system are obtained; and S5, carrying out weighted fusion on the fuzzy adjustment amount and the adaptive adjustment amount to obtain a final adjustment amount. By collecting multi-dimensional operation parameters in real time, extracting time domain and frequency domain features and combining a deep neural network model, precise recognition and early warning of the operation state of the internal combustion engine are achieved, detection and response can be made in time when the working condition of the internal combustion engine changes slightly, and the problem that a traditional control system is lagged in response is solved.

The invention relates to the technical field of ownership intelligence, in particular to a ownership intelligence fuzzy language instruction recognition method based on scene risk guidance. In order to solve the problem that a fuzzy language instruction recognition method in the prior art easily causes understanding deviation and potential safety hazards, the invention provides an intelligent fuzzy language instruction recognition method based on scene risk guidance, which comprises the following steps of: 1) constructing a scene risk map according to a basic risk and a distance risk; 2) identifying an instruction type; 3) instruction analysis and risk assessment; and 4) instruction rewriting and object identification replacement. According to the method, a risk perception mechanism is introduced, the high-risk behavior execution probability caused by semantic deviation of the intelligent robot is effectively reduced, the understanding accuracy and interaction safety of the intelligent robot in a real scene are improved, and the method is suitable for a complex application environment with high requirements for task reliability and behavior controllability of the intelligent robot.

The invention discloses a vacuum exhaust throttle valve setting method and system. The method comprises the steps that the current pressure value in a vacuum pipeline is obtained; calculating a pressure deviation and a pressure deviation change rate according to a preset target pressure value and the collected current pressure value; fuzzifying the calculated pressure deviation and the pressure deviation change rate to obtain a corresponding fuzzy linguistic variable; performing fuzzy reasoning based on a preset fuzzy rule base to obtain a valve opening adjustment amount in a fuzzy form; performing defuzzification processing on the valve opening adjustment amount in the fuzzy form to obtain an accurate valve opening adjustment amount value; and the opening degree of the exhaust throttle valve is adjusted according to the accurate valve opening degree adjustment amount value. The opening degree of the exhaust throttle valve is dynamically adjusted, and rapid and accurate control is achieved.

The embodiment of the invention provides an intelligent bone drilling self-adaptive control method for a mechanical arm, which comprises the following steps: acquiring displacement deviation of the tail end of a drill bit of an orthopedic surgical robot, obtaining an error change rate through differential calculation, and combining a bone layer type as an input variable of a fuzzy controller and a feeding speed as an output variable; input variables are fuzzified through a membership function, and a fuzzy language variable set is obtained; according to the set and a preset rule base, constructing a multi-rule group structure comprising three types of scenes of free space, cancellous bone and cortical bone, and setting corresponding fuzzy rule subsets for different bone layers; designing a ''minimum-maximum'' rule activation and combination strategy for reasoning by adopting a Mamdani type fuzzy reasoning method according to fuzzification input and a multi-rule group structure, and generating a fuzzification output variable set; and defuzzification is performed through a gravity center method to obtain a continuous speed instruction, and dynamic regulation and control of the drill bit feeding speed are achieved. When approaching a penetration point, the device automatically decelerates and safely stops, so that the safety and accuracy of an operation are effectively guaranteed, and over-drilling injury is prevented.

The invention discloses a hazardous chemical substance transportation early warning system based on a fuzzy neural network, and relates to the technical field of traffic transportation and road safety monitoring. According to the hazardous chemical substance transportation early warning system based on the fuzzy neural network, road geometric influence in original data of a sensor is accurately stripped from dynamic response of a vehicle; according to the method, false risk signals caused by road design can be eliminated, the method focuses on instability risks really caused by dynamic factors such as vehicle control and load transfer, and the rollover risk can be judged more essentially and more accurately; converting the preprocessed characteristic quantity into a fuzzy linguistic variable, reasoning by simulating a fuzzy rule of human expert experience, and finally outputting continuous risk indexes and levels; the processing mode not only better conforms to the imprecise characteristic of risk assessment, but also enhances the adaptability and robustness of the system to different vehicle types, loads and road conditions.

The invention discloses a medicine cold-chain logistics enterprise recommendation method based on a Fermat fuzzy set. The method comprises the steps of obtaining a transportation quality data set of a plurality of alternative logistics enterprises under evaluation indexes; constructing an expert evaluation matrix through the Fermat fuzzy linguistic variables, and evaluating the importance of experts through the Fermat fuzzy linguistic variables so as to determine the weight of each expert; giving a language evaluation matrix through a Fermat fuzzy language variable and converting the language evaluation matrix into a Fermat fuzzy number; obtaining a Fermat fuzzy group evaluation matrix based on the expert weight and a Fermat fuzzy Einstein interactive integration operator, and performing standardization; based on a Fermat fuzzy set score function and an Einstein interactive integration operator, objective and subjective weights of evaluation indexes are obtained through a Fermat fuzzy variable coefficient method and a Fermat fuzzy step-by-step weight evaluation ratio analysis method respectively, and then a comprehensive index weight is obtained; and according to a Fermat fuzzy set-based scoring function and an Einstein integration operator, obtaining a sequence through an improved comprehensive compromise solution method so as to determine an optimal enterprise.

Methods for determining the reliability of a technical system using fault tree analysis, comprising the following steps: S1 - Defining basic events of fault tree analysis; S2 - for each basic event, defining a fuzzy linguistic variable and a set of membership functions; S3 - at least partially based on real-time embedded software, defines a minimal cutting set for linguistic fault tree analysis; S4 - at least partially based on the minimum intersection theorem, determining the reliability of the technical system. Furthermore, the invention relates to a control unit, vehicle system, a computer program product and a computer-readable medium for executing the method.

This invention discloses a risk analysis method for lithium battery assembly, comprising the following steps: Step S1, using a two-layer hesitant fuzzy language terminology set to evaluate the severity, frequency of occurrence, and detectability of failure modes in lithium battery assembly; wherein, the two-layer hesitant fuzzy language terminology set includes a two-layer language terminology set and a hesitant fuzzy language terminology set, both composed of evaluation information from evaluators; Step S2, calculating evaluator weights based on similarity measures, and calculating the influencing factor weights of severity, frequency of occurrence, and detectability based on the principle of water injection; Step S3, aggregating the evaluation information of evaluators using a combined compromise ranking method to calculate the failure mode risk value; Step S4, determining the optimal evaluation information through multi-objective aggregation technology; This invention accurately describes the degree of risk by expressing basic semantics at the main layer and modifying the degree of modification at the sub-layer, thus avoiding misjudgment of extreme values. Simultaneously, semantic constraint rules are used to eliminate logical conflicts and improve expression efficiency.

The invention discloses a weight-adaptive multi-scene energy storage power station participation frequency modulation contribution degree evaluation method, which comprises the steps of establishing a multi-dimensional index model of an energy storage power station in a frequency modulation scene, determining an initial weight of the established index model by adopting a hesitant fuzzy language-cloud model, and calculating the frequency modulation contribution degree of the energy storage power station according to the frequency deviation of an actual system. And determining an adaptive weight coefficient to adjust a weight system, and evaluating the contribution degree of participation in frequency modulation of the energy storage power station based on a PROMETHEE-II evaluation method improved by TODIM. The evaluation method can scientifically quantify the actual contribution of the energy storage power station participating in the power grid frequency modulation in different scenes, and provides an important basis for the energy storage power station participating in the power grid frequency modulation scheduling strategy and establishment of an incentive mechanism of an auxiliary service market.

The application provides a medical data-oriented deep convolution fuzzy neural network and a training method thereof, and comprises a medical data explainability prediction model (IP-DCFNN) based on a deep convolution fuzzy neural network. The IP-DCFNN is composed of three parts: a fuzzy logic antecedent part, a deep convolution calculation part and a fuzzy result representation part. The fuzzy logic antecedent part extracts input data, and the input data is converted from a numerical value into a set of membership degree values for fuzzy language scalars through the operation of a membership function in the fuzzy logic antecedent part. The deep convolution calculation part extracts hidden features in input rule weights, and converts hidden layer weights into high latitude information representation. The fuzzy result representation part is used to process the defuzzification process in fuzzy reasoning. The application relates to the technical field of computer technology, and the IP-DCFNN adds the concept of a deep convolution neural network on the basis of a fuzzy reasoning system to achieve the explainability prediction capability for medical data.

The application discloses a kind of nuclear power equipment value chain manufacturing risk assessment methods.The present application determines risk group and risk factor in nuclear power equipment manufacturing from risk database;Adopt hesitating fuzzy language term set method, define a set of risk grade evaluation language set, define semantic function as conversion standard;According to risk group, risk factor and risk grade evaluation language set, obtain the evaluation information of each nuclear power equipment value chain manufacturing risk factor from risk database;The evaluation information is converted into triangular fuzzy number and aggregated, the risk importance and risk grade of each risk factor and risk group are determined, and the overall risk importance and risk grade are determined.The present application effectively and accurately processes fuzzy information in risk assessment, comprehensively analyzes the risk importance of each risk factor and risk group, and provides a systematic method for developing nuclear power equipment value chain manufacturing risk assessment.

The invention provides a multi-dimensional data fusion-based aging-suitable service coordination method and system for a double-aged community, and the method comprises the steps: collecting multi-source heterogeneous data through an Internet of Things terminal and a community database API interface, constructing a four-dimensional data model of technology, space, service and system, and carrying out the classification and structuring of the data; subjective data are processed by adopting a fuzzy language evaluation method, and objective weighting is carried out on model indexes in combination with an entropy weight method; calculating a comprehensive coordination degree value of the service system by utilizing the coupling coordination degree model; and when the coordination degree is lower than a preset threshold value, generating and outputting a targeted optimization path based on a multi-objective optimization algorithm, including technology upgrading, space transformation, service scheduling and system optimization. The system comprises a data acquisition module, a coordination degree evaluation module, a dynamic optimization module and a user interaction module. According to the method, the problem of resource mismatching caused by data splitting and assessment missing of an existing intelligent old-age care system is solved, and accurate, efficient and fair configuration of old-age care services is realized.

The invention provides an electric vehicle fire tracing method, system and device and a medium. The method comprises the steps that multiple fire features and fire reasons of an electric vehicle are obtained, the fire features are classified, multiple state categories are obtained, the fire features form a state space, and the fire reasons form an action space; determining the membership degree of each fire feature on a fuzzy linguistic variable value threshold by adopting a trapezoidal membership degree function; setting a state transition constraint according to the state category, and then iteratively learning a Q value of any action in any state execution action space in the state space by using a Q learning algorithm based on the state transition constraint and the membership to obtain a plurality of related Q values; and selecting the fire reason corresponding to the maximum correlation Q value as the fire reason of the current electric vehicle. The problems that in the prior art, fire source tracing related data are missing, judgment depends on expert experience, objectivity is difficult to guarantee, and rapid positioning cannot be achieved are solved.

The invention provides a phosphine production equipment control method and device, equipment and a medium, and belongs to the technical field of automatic control, and the method comprises the steps: mapping a real-time operation parameter into a corresponding fuzzy linguistic variable based on a preset membership function; based on the fuzzy linguistic variable of the refining unit, determining a target adjusting unit according to a preset top fuzzy rule; determining a first adjustment instruction corresponding to the target adjustment unit according to a preset middle-layer fuzzy rule based on the target adjustment unit and the fuzzy linguistic variable of each production equipment unit; based on the target adjustment unit, the first adjustment instruction and the fuzzy linguistic variable of the reaction unit, determining a second adjustment instruction of the reaction unit according to a preset bottom fuzzy rule; and issuing the first adjustment instruction and the second adjustment instruction to the corresponding production equipment units so as to realize control of each production equipment unit. According to the phosphine production equipment control method and device, the equipment and the medium provided by the invention, the equipment adjustment accuracy can be improved.

The application relates to a semantic asymmetric similarity recommendation system considering user preference consistency, and belongs to the technical field of recommendation. The application comprises the following steps: acquiring and cleaning data information; converting scores into fuzzy language terms; acquiring a user set U that has scored on a target item i i ; calculating semantic similarity between items by means of a probability language term set theory; acquiring preference information of users on items i and j; calculating user preference consistency between items by means of a Bhattacharyya coefficient method; adjusting semantic similarity by using the user consistency result; acquiring the number of common evaluation items of items i and j and the number of user evaluations of the target item i, and calculating the asymmetric relationship between items by means of a Sigmoid function; breaking the symmetry of weighted semantic similarity by means of the asymmetric relationship between items; calculating a predicted value of a target user u on an un-scored item by means of a score prediction method; sorting a prediction set, and pushing the first n items with the highest predicted values to the target user u.

The present invention discloses a method for intelligently coupling pressure-flow-deformation control of spiral anchor foundation grouting, which relates to the technical field of foundation grouting technology, including: matching a preset engineering parameter set according to the specification parameters of the spiral anchor and the type of soil in which it is located; collecting grouting data of each grouting channel, and calculating grouting deviation data in combination with the engineering parameter set; fuzzifying the grouting deviation data and converting it into fuzzy language variables; inputting the fuzzy language variables into a preset fuzzy rule library for reasoning, and outputting PID parameter corrections; dynamically adjusting the parameters of the PID controller according to the corrections to generate a pump speed adjustment instruction; executing the pump speed adjustment instruction and collecting the grouting data after execution; obtaining the soil permeability coefficient by inversion through the construction of a digital twin model, and optimizing and updating the fuzzy rule library in combination with the grouting data after execution. This application is used to solve the problem that the traditional spiral anchor foundation grouting process has poor adaptability to complex geology.

The invention discloses an artificial intelligence-based policy text key content extraction and analysis method. The method comprises the following steps of: establishing a structured keyword knowledge base, identifying and explaining a retrieval intention by adopting a large model, acquiring literature contents, and classifying and labeling the literature contents to obtain a labeling result; evaluating the labeling result by using the large model to obtain an evaluation result; aggregation processing is carried out on policy content in a time period in the labeling result, a vocabulary structure map and an evolution trend are generated, and an analysis result is obtained; and according to the analysis result and the evaluation result, in combination with the policy orientation demand input by the user, generating a policy suggestion text conforming to the document specification. The mandatory and suggestion of terms are accurately judged, and the problem that an existing model is insufficient in fuzzy language processing is avoided. In industry discrimination, an action verb and industry behavior matrix mapping mechanism is introduced, and the directivity and exclusiveness of industry tags are improved in combination with subject co-occurrence features.

This invention discloses a fuzzy multi-attribute decision-making evaluation method and system. The method includes defining a hesitant fuzzy language terminology set; determining the evaluation object and its influencing factors based on the hesitant fuzzy language terminology set to form a factor set, and assigning weights to each influencing factor to determine the membership function of each factor; performing fuzzy synthesis operations on the membership function of each factor and its corresponding weights to obtain a comprehensive membership value; and performing fuzzy evaluation on the evaluation object based on the comprehensive membership value to obtain a fuzzy comprehensive evaluation result of the evaluation object. This invention's multi-attribute decision-making method, capable of handling incomplete and imprecise fuzzy information, plays a crucial role in ensuring the rationality and accuracy of investment risk assessment.

The invention discloses a slope safety level classification method based on a fuzzy language neighborhood grain concept, and relates to the technical field of slope safety, and the method comprises the steps: collecting slope sample data, detecting slope condition features, and constructing a language concept set of the slope condition features by using language terms, constructing a binary relationship between the slope condition features and the language concept set, determining a neighborhood of a slope sample through cosine similarity, and generating an initial fuzzy language neighborhood grain concept space; on the basis of the initial fuzzy language neighborhood grain concept space, the fusible concept clusters in the subspaces are marked, and a fusion concept space is generated through weighted fusion; and based on the fusion concept space, carrying out slope safety classification on the new slope sample through the minimum identification degree. Therefore, the slope safety level classification method based on the fuzzy language neighborhood grain concept is suitable for slope safety level classification of complex slopes, and reference is provided for flexible classification and multi-factor coupling influence quantification of special slopes.

The invention discloses an intelligent supplier selection method and system, and belongs to the technical field of enterprise resource management and decision support. The system comprises a supplier resource library module used for storing and managing data of suppliers; the supplier admission preliminary screening module is used for aggregating qualitative evaluation of a plurality of decision-making experts based on a possibility distribution hesitation fuzzy language set model, and processing data of suppliers according to a preset comprehensive evaluation value threshold value to obtain potential suppliers; the evaluation index system management module dynamically configures a differentiated performance evaluation index system comprising three dimensions of economy, society and environment for different types of suppliers in the supplier resource library module; the comprehensive evaluation engine module is constructed based on an intuitionistic fuzzy set theory; and the supplier portrait module is used for visually displaying the comprehensive information and the evaluation result of the supplier. According to the method, the defects of high subjectivity, single index and insufficient fuzzy information processing capability in the existing supplier evaluation method are overcome.

The invention belongs to the technical field of Internet of Vehicles intersection routing, and particularly relates to an Internet of Vehicles intersection routing method and system based on fuzzy multi-factor decision. Performing fuzzy language quantization on three evaluation factors of the lane number, the direction angle and the traffic flow of the candidate road section by using a triangular fuzzy number; a clear value is obtained through defuzzification, a standard value is obtained through standardization, evaluation factor information entropy is calculated based on the standard value, and a dynamic weight value on each evaluation factor is obtained after normalization; and calculating a comprehensive fuzzy number score of each candidate road section, performing defuzzification to obtain a clear optimal non-fuzzy performance value BNP, and selecting the road section with the highest BNP value as a target road section. The technical scheme provided by the invention has the effects of high decision accuracy, strong adaptability, good robustness and strong pertinence.

This application discloses a wind power and energy storage coordinated frequency regulation method, device, storage medium, and electronic equipment, relating to the field of information technology. The method includes: fuzzifying frequency deviation, frequency deviation change rate, and wind speed deviation to obtain the membership degrees of each frequency deviation, frequency deviation change rate, and wind speed deviation belonging to different fuzzy linguistic values; calculating the activation intensity corresponding to each frequency regulation rule in a preset fuzzy rule base based on the membership degrees; determining the overall membership degrees of wind turbine gain and energy storage gain belonging to different fuzzy linguistic values ​​based on the activation intensity; defuzzifying the wind turbine gain and energy storage gain based on the overall membership degrees to obtain the defuzzified output values ​​of the wind turbine gain and energy storage gain; and performing dynamic frequency regulation of the power grid based on the defuzzified output values ​​of the wind turbine gain and energy storage gain. This application can improve the frequency regulation performance of the system and achieve optimal allocation of wind power resources and energy storage resources under different disturbances.

The present invention provides a control method based on differential speed and torque distribution, which relates to the field of intelligent control technology. The method includes: calculating the difference between an initial input and a preset speed command to generate a speed deviation signal and a deviation change rate; establishing a dynamic membership function library using a fuzzy controller, mapping the speed deviation and its change rate into fuzzy linguistic variables, performing inference operations based on a preset fuzzy control rule library, and outputting a frequency adjustment value and a torque compensation coefficient for the frequency converter; reading the generated torque compensation coefficient and the shaft torque values ​​measured by two torque meters, calculating the dynamic difference between the current total load torque and the target torque, establishing a torque distribution weight model based on the differential transmission characteristics, and generating differentiated torque correction commands for the two motors based on the real-time speed value. The present invention improves the control performance of the differential drive.

The invention discloses a cabin internal illumination calculation and optimization method, which comprises the following steps of S1, presetting a lamp and an illumination sensor, modeling a model according to the overall arrangement in a cabin, and adopting an actual-scale cabin and a parameterized cabin three-dimensional model for numerical simulation; s2, calculating direct illumination; s3, calculating indirect illumination; s4, taking the calculated direct illumination and indirect illumination parameters as input of a fuzzy neural network, performing fuzzification processing on the input direct illumination and indirect illumination parameters, and converting the parameters into fuzzy linguistic variables; s5, establishing a fuzzy rule base according to expert knowledge or experience data; and S6, performing fuzzy reasoning according to the input fuzzy language variable and the fuzzy rule base, and converting fuzzy output into a specific brightness adjustment value. The method has the advantages that dynamic optimization control over cabin illumination is achieved, the optimization result is closer to reality, the calculation speed is greatly increased, and the overall ship design efficiency is improved.

This application discloses a method for early warning of rubbing during the transportation of wind turbine blades, comprising: S1, initiating an early warning program based on the real-time location information of the transport vehicle, collecting relative position and relative velocity data between the wind turbine blades and obstacles on both sides of the road, as well as the vibration acceleration and angular velocity of the transport vehicle, and preprocessing the collected data to remove invalid data; S2, denoising the preprocessed relative position and relative velocity data; S3, evaluating the bump intensity based on the preprocessed vibration acceleration and angular velocity data of the transport vehicle; S4, mapping the denoised relative position data, relative velocity data, and bump intensity evaluation into fuzzy linguistic variables; S5, evaluating the early warning level based on the fuzzy linguistic variables, and dynamically updating the early warning level evaluation rules during operation; S6, clarifying the early warning level evaluation, and finally outputting a clear risk level.

The invention discloses an intelligent image-text design method and system, and relates to the technical field of image-text design, the number of plates required by image-text design of a user and a design label corresponding to each plate are identified by receiving fuzzy language description input by the user, and a corresponding number of port data groups are called according to the number of the plates and the design labels; carrying out multi-dimensional retrieval on the multi-level content branches of each port data group, and respectively positioning the optimal branch combination in each port data group through dynamic weight to carry out fusion display, so as to form a preliminary design scheme; and receiving feedback information of the user on the preliminary design scheme, updating the weight distribution and association relationship of the port data group, re-executing branch combination retrieval based on the updated port data group, executing multi-modal fusion processing by utilizing the re-retrieved branch combination, and generating a final image-text design scheme conforming to the fuzzy language description of the user. The problem that a user quickly generates personalized image-text design through fuzzy language description is solved.

The invention relates to the field of quality and reliability engineering, and discloses an industrial robot manufacturing process potential failure mode risk analysis method, which comprises the following steps: S1, describing the risk of a potential failure mode in an industrial robot manufacturing process by using a graduatory fuzzy language; s2, solving evaluation personnel and influence factor weights based on a best worst method and a water injection theory; s3, performing compromise calculation on risk values of the failure modes by adopting a multi-criterion iterative decision-making method, and determining a risk sequence of the failure modes; considering that the structure of the industrial robot is complex and the evaluation personnel have a blind area in understanding the failure mode, the hesitant psychology of the evaluation personnel is captured by adopting the graduatory fuzzy language with higher degree of freedom, and meanwhile, the weight of the evaluation personnel is calculated to quantify the ability of the evaluation personnel, so that the evaluation result is more objective; according to the method, a multi-criterion iterative decision method is adopted by considering that the consequence is serious when the industrial robot fails, and the weight of an influence factor must be considered in failure mode risk calculation.