9 results about "Fuzzy group" patented technology

The invention discloses a device-level fault diagnosis method for a water jet propulsion device, and relates to the field of fault diagnosis, and the method comprises the steps: judging whether a target fault fuzzy group corresponding to a kth measurement point exists in all fault fuzzy groups of the kth measurement point or not if the working state of a control system of the water jet propulsion device is abnormal, judging whether the target fault fuzzy groups corresponding to the nth measuring point and the (n-1) th measuring point are intersected or not, if yes, adding 1 to k, then returning to the step until all the measuring points in the optimal measuring point set are traversed, and judging whether the number of typical fault modes in the intersection of the nth measuring point and the (n-1) th measuring point is 1 or not, and if not, judging whether the number of typical fault modes in the intersection of the target fault fuzzy groups corresponding to the nth measuring point and the (n-1) th measuring point is 1 or not; and if the result is 1, obtaining the fault mode and the fault component of the control system of the water jet propulsion device according to the typical fault mode in the intersection and the component corresponding to each typical fault mode. According to the application, component-level fault diagnosis can be realized.

The application provides an intelligent control system, method and device of an underwater screed and the underwater screed, and relates to the field of ocean engineering equipment and automatic control. The intelligent control system comprises: a perception subsystem configured to obtain working state data of the underwater screed; a decision subsystem comprising a stage decision unit and a fuzzy group intelligence optimization unit; the decision subsystem is configured to discretize the working process of the underwater screed into multiple stages, and determine the framework parameters of the current stage based on the working state data in each stage; the fuzzy group intelligence optimization unit is configured to determine the liquid level change amount of each target cabin based on the framework parameters to generate the control instruction of the current stage; and an execution subsystem configured to receive the multi-stage control instruction sent from the decision subsystem, and control the underwater screed to work underwater based on the multi-stage control instruction. The system can improve the stability of the posture control of the underwater screed in a complex working environment.

The present application proposes a fuzzy comprehensive evaluation method for the characteristics of the ship air flow field based on the use requirements of the ship air flow field of the carrier aircraft and typical carrier equipment. The analytic hierarchy process and the technique for order preference by similarity to ideal solution are extended to the interval type-2 fuzzy group decision-making situation to effectively deal with the uncertainty and difference of expert opinions. To solve the problem that the consistency verification is difficult to pass due to the increase in the number of evaluation indexes, an improved algorithm for geometric consistency of individual judgment matrix is proposed. An improved IT2FAHP-based weighting method for the evaluation indexes of the characteristics of the ship air flow field is established to improve the rationality and operability of the index weight distribution. To solve the problem that it is difficult to scientifically evaluate the satisfaction of the use requirements of the ship air flow field characteristics under the actual atmospheric environment combination working condition, a fuzzy envelope-based performance evaluation method for the ship air flow field indexes is proposed. An improved IT2FTOPSIS-based comprehensive evaluation method for the characteristics of the ship air flow field is established to provide new ideas and methods for solving the evaluation problem of the ship air flow field.

The invention discloses a radio frequency system testability modeling method based on an improved auto-encoder, and belongs to the field of radio frequency system testability modeling. Establishing a simulation circuit model, obtaining measurement data, and expanding the measurement data; performing fuzzy group labeling on the expanded measurement data by using a voltage drop threshold to obtain a multi-valued D matrix; establishing an auto-encoder model, and initializing parameters of the auto-encoder model; and training the simulation circuit model, and finally outputting a reconstruction matrix. The fuzzy group constraint loss function is added in the auto-encoder, the improved auto-encoder is obtained, the improved auto-encoder can learn the internal structure of data, a data mode can be found by learning training data, a fault fuzzy group and potential representation can be associated when analog circuit test signal data is processed, and the fault fuzzy group constraint loss function is obtained. And the fuzzy group division reasonability is verified.

The application discloses a sequential diagnosis measuring point fault positioning method for electromechanical systems based on an electrical topology model. The method comprises the following steps: establishing an electrical topology structure model of a to-be-tested electromechanical system, inputting a preset number of external executing devices of a fault and a fault mode, and outputting an initial fault fuzzy group; using a measuring point recommendation method to obtain a recommended measuring point, using a measuring point test method to obtain an actual measurement result, inputting the actual measurement result into the model, and outputting a fault fuzzy group until the fault fuzzy group cannot be divided, taking the fault fuzzy group of this time as a diagnosis result, positioning a fault device, ending the diagnosis, and realizing sequential diagnosis measuring point fault positioning. The method has the characteristics of fast operation speed, reasonable recommended measuring point, few fault diagnosis steps, high fault recognition efficiency and the like, and can greatly improve the efficiency of sequential diagnosis testing for fault diagnosis of electromechanical systems.

This invention discloses a testability modeling method for radio frequency (RF) systems based on an improved autoencoder, belonging to the field of RF system testability modeling. The method involves establishing a simulation circuit model, acquiring and expanding measurement data, using a voltage drop threshold to perform fuzzy group annotation on the expanded measurement data to obtain a multi-valued D matrix, establishing an autoencoder model, and initializing its parameters, training the simulation circuit model, and finally outputting a reconstructed matrix. This invention incorporates a fuzzy group constraint loss function into the autoencoder, resulting in an improved autoencoder. This improved autoencoder can learn the intrinsic structure of the data, discover data patterns through training data, and correlate fault fuzzy groups with latent representations when processing analog circuit test signal data, thereby verifying the rationality of the fuzzy group partitioning.

The application is divisional application, and the application number of the original application is 2025118241829. The invention provides an intelligent control system, method and equipment of an underwater leveling machine and the underwater leveling machine, and relates to the field of ocean engineering equipment and automatic control. The intelligent control system comprises a sensing subsystem configured to obtain working state data of the underwater leveling machine; the decision-making subsystem comprises a stage decision-making unit and a fuzzy crowd-sourcing optimization unit; the discretization module is configured to discretize the working process of the underwater leveling machine into a plurality of stages and determine frame parameters of the current stage based on working state data in each stage; the fuzzy crowd-sourcing optimization unit is configured to determine the liquid level variation of each target shipping space based on the frame parameters so as to generate a control instruction of the current stage; and the execution subsystem is configured to control the underwater leveling machine to work underwater based on the multi-stage control instruction. The system can improve the attitude control stability of the underwater leveling machine in a complex operation environment.

The invention relates to the technical field of valve testing, and discloses an online testing method for friction force of a low-temperature pneumatic stop valve. According to the method, a plurality of test parameter data points of the low-temperature pneumatic stop valve are obtained firstly, and then friction force testing is achieved through grouping processing of the data points. And in any grouping processing stage, determining a current activation group, selecting a preset number of previous reference grouping processing stages, and dividing data points into corresponding data sets according to the distance between the test parameter data points and the group in each grouping stage. A fuzzy group is obtained by analyzing the intersection of the current data set of the activation group and the reference data sets of other groups, and after an adjustment factor is calculated, the fuzzy group and the activation group are updated according to the adjustment factor. According to the method, multi-stage data can be integrated, fuzzy data can be precisely processed, testing can be dynamically adjusted, the testing accuracy and reliability are improved, real-time testing can be conducted when the valve normally operates, production interference is reduced, and the method is suitable for performance testing of the low-temperature pneumatic stop valve.

The present application relates to a kind of settlement based on grouping recommendation system and method of list, belong to DRG grouping technical field.The present application discloses grouping recommendation system includes in situ fuzzy grouping module, ectopic fuzzy grouping module, QY (ambiguity) grouping module, missing code recommendation module, grouping fit degree module, and grouping recommendation method steps are as follows: in situ fuzzy grouping is carried out, and grouping range is expanded;Ectopic fuzzy grouping is carried out, and grouping range is further expanded;QY (ambiguity) grouping supplement is carried out, and grouping is carried out with the main diagnosis code of surgical coding collocation, obtains the possible existence of real grouping;Missing code grouping supplement is carried out, and in situ fuzzy grouping is carried out, obtains the possible existence of real grouping;The fit degree of S1-S4 all groupings is calculated respectively, and grouping fit degree value is arranged in descending order form and is arranged in list.The present application can recommend the most suitable grouping to doctor by analyzing the position of ICD coding, classification relationship.