49results about How to "Avoid computational burden" patented technology

The invention discloses a composite fault diagnosis method for a rotary machine based on an improved deep sparse auto-encoder network. The method comprises the following steps: 1) acquiring vibrationsignals of the rotary machine under c conditions in a normal state and different fault states respectively to obtain d groups of time domain vibration signal samples respectively; 2) carrying out Fourier transform on each sample to obtain preprocessed signal samples; 3) constructing a diagnosis sample set to serve as a training sample set; 4) building a rotary machine composite fault diagnosis model to obtain the connection weight and bias parameter of the deep sparse auto-encoder network; 5) acquiring a softmax classifier model; 6) carrying out fast Fourier transform, and selecting a test sample; 7) carrying out deep learning on the test sample by using the test sample as the input of a trained improved deep sparse auto-encoder network, and carrying out feature extraction to obtain a testsample feature signal; and 8) using test feature information as the matching feature of the test sample to obtain the composite fault diagnosis result of the rotary machine to be tested. Through theadoption of the method, the diagnosis accuracy and efficiency are improved.

The invention relates to an observability constraint-based random planet landing track optimizing method, and belongs to the technical field of the deep space probe navigation and guidance. According to the method, a deep space landing guidance control task based on the monocular vision navigation is used as the background, the dual problem between the effective control and the reliable estimation is considered, the system uncertainty is used as partial cost and is introduced into a quadratic performance index through an expansion-state space, so that a random optimization feedback control law can be provided by adopting a linear quadratic type control technique, an expansion-state space description model of a established probe system is substituted, the real-time optimization of a planet landing track is realized. The dynamic planning and the burden in calculation based on a searching method are avoided, the problem of observability shortage in the landing process is effectively overcome, and the navigation estimation performance of the system is improved, so that the overall performance during the planet probe navigation and guidance control is ensured, and the final target that a planet is reliably landed is achieved.

The invention belongs to the field of artificial intelligence and visual dialogues, particularly relates to an autonomous evolution intelligent dialogue method, system and device based on a physical environment game, and aims to solve the problems of high calculation consumption, low convergence speed and low information processing accuracy of an intelligent system. The method comprises the stepsof obtaining a to-be-processed image and a corresponding problem text; Encoding the picture into a picture vector by adopting an optimized dialogue model, and encoding the question text into a question vector; Generating a state vector based on the picture vector and the question vector; And decoding the state vector to obtain a response text and outputting the response text. Wherein a discriminator needs to be introduced in the optimization process of the dialogue model, the dialogue model and the discriminator are alternately optimized until the mixed loss function of the dialogue model andthe loss function value of the discriminator are not reduced or lower than a preset value, and model optimization is completed. Compared with a traditional method, the method is low in calculation consumption and high in convergence speed, and the information processing accuracy is further improved.

The disclosure relates to a short message field classification method as well as a short message field identification method and apparatus. The short message field classification method comprises: determining a short message template set corresponding to each short message field in all collected short message fields; determining a training data set of a classifier according to the short message template set corresponding to each short message field in all the short message fields; determining a classifier training frequency corresponding to each short message template according to a frequency corresponding to each short message template in the short message template set corresponding to each short message field, subjected to statistics within a set time period; and training the classifier through the training data set and the classifier training frequency corresponding to each short message template in the short message template set. According to the technical scheme, the problem of computing burden caused by matching received short messages by taking all semantic templates as candidate templates in related technologies can be avoided, and a relatively good bedding is made for deep understanding of short message content.

A hybrid electromagnetic transient simulation method for microgrid real-time simulation, wherein a traditional node analysis method (NAM) and a highly parallel latency insertion method (LIM) are combined, so that the microgrid is firstly divided from a filter of a distributed power generation system to form one latency insertion method (LIM) network containing a power distribution line and a plurality of node analysis method (NAM) networks containing the distributed power generation system respectively, the NAM network being simulated by traditional node analysis method, the LIM network being simulated by the latency insertion method, in an initialization stage, one correlation matrix and four diagonal matrixes containing line parameters used for LIM network simulation being formed according to line topology and parameters of the microgrid, in a main cycle of the simulation, the LIM network solved simultaneously with multiple NAM networks, a parallelism of a microgrid simulation being improved.

The invention provides a semi-supervised image deblurring method based on a fusion attention mechanism, and the method comprises the steps: step 1, obtaining an image training data set, and dividing the image training data set into two training subsets; step 2, constructing an image blurring reduction model based on full supervision and non-supervision, wherein the image blurring reduction model comprises a full supervision network and a non-supervision network; step 3, inputting one subset into a fully supervised network to be trained for learning, and inputting the other subset into an unsupervised network to be trained; step 4, screening image features through the attention mechanism in the network, distributing corresponding weights to feature information extracted by the network, obtaining important image information, carrying out feature fusion on the important image information, and obtaining a final clear image.According to the invention, the attention mechanism and the neural network are combined; a network model for motion blurred image restoration is established, and effective and accurate restoration of the blurred image is realized.

A method for the generation of a set of conflicts for model-based system diagnostics is described, with which system a plurality of sensors is associated for the observation of variables indicative of operation conditions.

The method starts from generating a complete set of Analytical Redundancy Relations (ARRs) in implicit form and, for each diagnosis instance: it performs a system simulation, computing the expected values for a first subset of Analytical Redundancy Relations (D-ARRs) including the relations involving only one system observation variable; it compares the expected and observed values of the system observation variables to identify the inconsistent variables, i.e. the unsatisfied redundancy relations, indicating a fault in at least one system component; and, when discrepancies are detected, it checks the consistency of each relation belonging to a second subset of Analytical Redundancy Relations (I-ARR), comprising relations involving a plurality of system observation variables, at least one of which exhibits discrepancies between expected and observed values; therefore identifying the support set of the unsatisfied Redundancy Relations as set of system conflicts.

The invention discloses a method for adaptively performing data encryption and authentication without an authentication center, which comprises the following steps that: (1) system parameters are determined; (2) information is sent and received and both parties are registered; (3) a sender carries out data encryption and authentication protection operation on a plaintext message to be sent to a receiver; and (4) the receiver carries out reading and verification operation on the received data message. The step (3) is realized by computing a key parameter, computing a signature parameter, outputting an electronic signature which is equal to zero when only carrying out data encryption on the plaintext message, outputting an encrypted ciphertext which is equal to the plaintext message when only carrying out electronic signing, computing the electronic signature when carrying out both data encryption and electronic signing, carrying out encryption operation on the combination of the plaintext message and the electronic signature, combining the ciphertext, the signature parameter and the electronic signature to form a data message and sending the data message. The plaintext message can be adaptively subjected to data encryption and content integrity authentication; and the problems caused by adoption of the authentication center and a plurality of functional parts in the conventional method are solved.

A turbogenerator main throttle valve opening predication control method based on a delaying observer is provided. The method comprises the following four steps: step 1: analyzing and modeling a turbogenerator main throttle valve opening control system; step 2: designing turbogenerator main throttle valve opening predication control; step 3: designing the delaying observer; and step 4: finishing the design. Aiming at a main throttle valve opening control system model, a control principle with a closed analytical solution is designed, and the output delaying observer is designed to correct a measured signal, so that the overall stability of a closed loop control system is guaranteed under the time varying delaying condition; meanwhile, the rapid and accurate tracking of a pre-set track by a power angle of a turbogenerator is realized.

The invention provides a maneuvering target tracking algorithm based on a road network. According to the algorithm, a tracking algorithm model adaptive strategy realized through road information is given by aid of a prior road information base, and a variable-structure multi-model method is adopted to realize ground multi-maneuvering-target tracking. In this way, state estimation precision of maneuvering target tracking can be improved, and the target missing rate is lowered; meanwhile, computing burden brought by multiple models adopted in a fixed multi-model algorithm is avoided, and operating time is greatly shortened; and the scheme has practical value in terms of ground target tracking.

The invention provides a steam turbine generator main steam valve opening degree prediction control method based on a non-linear interference observer. The method comprises the four major steps that 1, a steam turbine generator main steam valve opening degree control system carries out analysis and modeling; 2, the steam turbine generator main steam valve opening degree prediction control design is carried out; 3, the non-linear interference observer is designed; 4, the design is completed. The method aims at a main steam valve opening degree control system model, a control rule with the closed type analytical solution is designed, and then, the non-linear interference observer is designed for controlling the interference for compensation, so that the global stability of the closed loop control system is ensured under the condition with higher input interference, and meanwhile, the fast and precise tracking of a steam turbine generator power angle on the preset tracks is realized.

The embodiment of the invention relates to the technical field of communication, and discloses an image recognition method, electronic equipment and a computer readable storage medium. The method comprises the following steps: obtaining the similarity between an image block to be detected in a video frame and each candidate image block in a candidate object set; if the candidate image blocks of which the similarity with the to-be-tested image blocks is greater than a first preset threshold exist in the candidate object set, taking the candidate image blocks of which the similarity is greater than the first preset threshold as target candidate image blocks; if to-be-detected image blocks always exist in a first preset frame number continuous to the video frames, wherein the similarity between the to-be-detected image block and the target candidate image block is greater than a first preset threshold value all the time, and if the distance between the position information of the to-be-detected image block in the video frame and the position information of the to-be-detected image block in the video frame is smaller than the preset threshold, judging the to-be-detected image block tobe a real image block, so that the image can be identified more accurately through simple operation, and the success rate of image identification is increased.

The invention provides a vehicle lithium ion battery capacity estimation method based on surface temperature, which makes full use of battery temperature data, acquires and constructs a temperature rise curve, determines a capacity sensitive interval from the temperature rise curve, and samples a health factor sequence for capacity estimation. According to the method, the calculation burden causedby extracting specific features from the temperature signal is avoided; the temperature acquisition signals can be fully utilized to realize capacity estimation, supplement can be provided for an existing capacity estimation method based on voltage and current, the reliability and accuracy of capacity estimation in a battery management system are improved, and new hardware does not need to be added, so that the method has many beneficial effects which do not exist in the prior art.

The invention provides a distributed sensor network consistency filtering method with unknown colored noise, which comprises the following steps of: learning state noise and measurement noise parameters of each node in a distributed sensor network according to a group of given training data; meanwhile, performing state extension, extending learned colored noise parameters to a state vector, and finally, state estimation is completed by using a consistency Kalman filtering algorithm, so that estimated values of all sensor nodes are converged to be globally consistent. To improve computational efficiency, only local measurement noise and state noise are integrated into an extended state for each node. Simulation results show that the unknown colored noise in the distributed sensor network can be effectively estimated, and the accuracy of distributed estimation is improved. The method can be applied to the fields of distributed sensor network radars, infrared target tracking, mobile robot positioning and the like.

The invention relates to the technical field of image recognition, and provides a picture filtering method and device, electronic equipment and a storage medium. The method comprises the steps: carrying out the clustering and filing of obtained interference picture data, carrying out the duplicate removal of a first feature value corresponding to the interference picture data, obtaining an initialblacklist file, and enabling the initial blacklist file to comprise the duplicate-removed first feature value; obtaining to-be-archived picture data, and calculating feature value similarity betweena second feature value of the to-be-archived picture data and the first feature value; and filtering the to-be-archived picture data of which the feature value similarity reaches a preset similarity threshold to obtain a blacklist archived picture library. According to the embodiment of the invention, the data volume of data calculation can be reduced, and the filing efficiency of picture data isimproved.