935results about How to "Strong fault tolerance" patented technology

Image display device having an image source generating an image, a beam splitter positioned at forty five degrees to the main optical path, to project and focus the image generated by the image source into the entrance pupil of the human eye, two achromatic standard doublet lenses positioned perpendicularly to the main optical path and placed between the image source and the beam splitter, and configured to amplify, collimate, and correct optical aberrations of said image, wherein the image source, beam splitter and the doublet lenses are in an on-axis configuration and the image display device comprises two mounting brackets parallel to the main optical axis, each having an extremity part holding an edge of the beam splitter and the other extremity pivotally attached to a housing, allowing the brackets and beam splitter to rotate in an axis perpendicular to the main optical path.

The invention provides a method for detecting lane lines based on grayscale estimation and cascade Hough transform, belonging to the technical field of image processing, and relating to image segmentation, image line geometrical characteristics detection and intelligent vehicle navigation simultaneously, which is mainly applicable to an auxiliary safety drive system. The method comprises the following steps: carrying out grayscale estimation on sensitive areas of an original image I of the collected vehicle road conditions ahead; dividing the sensitive areas into a vehicle shadow region, a roadway non-mark region and a roadway mark region (including the area of the car body of the vehicles ahead); adopting a mathematical morphology method to obtain a boundary image from the roadway mark region in the areas divided by the grayscale estimation; then carrying out Hough transform on the obtained boundary image of the roadway mark region to extract line image characteristics therein; and finally realizing the detection of the lane lines by searching end points of roadway mark boundary. Compared with the congeneric method, the method in the invention has stronger stability and wider application occasions and the like.

A robot airplane for tour inspection of power line in counterwise driving structure of coxial double propeller uses two engines to control flight stability, GPS and GIS to confirm flight path, computer processor to adjust flight attitute and battery to provide power for motor, transducer and data link system. Its control system consists of navigation system, autonomous planning system, data link system and on line detection system.

The invention relates to a nuclear power plant working robot and a control system thereof, which belong to the fields of robots and automation equipment. The nuclear power plant working robot is a crawler-type mobile manipulator and is composed of a mobile platform driven by double crawlers and a four freedom degree manipulator carried on the mobile platform. The nuclear power plant working robot can move inside a nuclear power plant, has two control modes of manual remote control and autonomous control, and is remotely controlled by a wireless or wired mode. The control system of the nuclear power plant working robot includes a host monitoring and planning control system and a robot control system which are matched to control the operation of the robot. The robot operates autonomously, is safe and reliable, can complete certain dangerous tasks in high radioactivity environment; the robot has small size, stable performance, great maneuverability and low operation cost; a crawler-type chassis has strong gripping force as well as certain climbing and obstacle clearing ability, and is suitable to walking over complex terrains; and the robot has high intelligence degree and can realize autonomous control and manual remote control.

The invention discloses a traffic-road condition information processing method based on a vehicle wireless sensor network. The method is characterized in that: firstly, a wireless communication network is established and the network includes an information center, a vehicle wireless sensor network sub-system formed by limited vehicle mobile knots and an information publishing sub-system based on a broadcasting network; the information center is fixed in a traffic hub in a city as the center of the wireless communication network; secondly, each vehicle mobile knot collects the timely road condition information and integrates data through the vehicle wireless sensor network sub-system according to the instruction of the information center; then the timely road condition information from the information collection and data integration of each road section is reported to the information center through the vehicle wireless sensor network sub-system; finally, the processed traffic road condition information and network control instructions are published by the information center through the information issuing sub-system to each vehicle mobile knot for the road choosing by drivers.

The invention discloses a plurality of united observer based fault diagnosis and fault-tolerant control device and a method and belongs to the field of aerospace. The plurality of united observer based fault diagnosis and fault-tolerant control device comprises following modules of a fault injection module, a fault diagnosis module, a real time monitoring module and a hardware control module. According to the method, the problem that traditional observer based fault diagnosis methods are limited by conditions is mainly solved, the operation is simple, the implementability is high, and the method can be used for diagnosing faults of actuating mechanisms of a four rotor wing helicopter and verifying feasibility of state monitoring.

The invention relates to a system and a method for intelligently monitoring and managing the logistics of dangerous articles on the basis of radio frequency identification in the technical field of logistics monitor. The invention comprising the steps of installing a system for monitoring the state of dangerous article packing box within the dangerous article packing box, collecting in real time the physical state of the dangerous articles and writing onto a RFID label outside a container; using a dangerous article vehicle monitoring system, each monitoring station and checking stations on the way to read and write in real time the information of the RFID label in the entire process of logistics, and dynamically exchanging for dangerous article logistics information, state information, safety information and vehicle driving state information with a dangerous article logistics integrated monitor and management platform; adopting the dangerous article logistics integrated monitor and management platform to realize the integrated monitor and management in the process of logistics and to provide the real-time inquiry for the remote users, which forms the intelligent monitor of the dangerous article logistics with the functions of article multilevel real time monitor, synchronous in-time alarm, malfunction automatic treatment and unified logic distribution, thus integrally accomplishing the distribution multilevel monitor, process real-time follow, automatic error processing and remote real-time inquiry in the process of dangerous article logistics.

The invention discloses a neural network method for diagnosing analog circuit failures which is based on a particle swarm algorithm, and comprises the following steps: imposing an actuating signal to an analog circuit to be tested, measuring an actuating response signal in the testing nodes of the circuit, extracting the candidate signal of failure characteristics by implementing noise elimination and then wavelet packet transformation on the measured actuating response signal, extracting the failure characteristics information by further implementing orthogonal principal component analysis and normalization processing on the candidate signal of failure characteristics, and sending the failure characteristics information as samples to the neural network for implementing classification. The method adopts the particle swarm algorithm instead of a gradient descent method in traditional BP algorithms, thus leading the improved algorithm to be characterized in that the algorithm avoids the local minimum problem and has better generalization performance. The BP neural network method for diagnosing the analog circuit failures which is optimized on the basis of particle swarm can obviously reduce iteration times in the algorithm, improve the precision of network convergence, and improve diagnosis speed and precision.

The invention discloses an assistant decision system for condition-based maintenance and risk evaluation of power transmission and transformation equipment, which is composed of six navigation buttons and functions thereof wherein the six navigation buttons comprise a condition-based maintenance button, a task processing button, an inquiry statistics button, a data maintenance button, a system management button and system help button, and the system is additionally equipped with five shortcut menus such as a condition parameter early-warning menu, an equipment state early-warning menu, an equipment indexes menu, a user information menu and a system logging out menu. The invention provides a whole set of the assistant decision system for the condition-based maintenance and the risk evaluation of the power transmission and transformation equipment which has simple operation, detailed content, complete functions, convenient and fast execution, high efficiency and friendly man-machine interaction interface.

The invention discloses a various-information coupling emotion recognition method for the human-computer interaction. The method is characterized by including the steps of 1, acquiring the video and audio data of facial expression; 2, extracting features of text content, and acquiring the text information features; 3, extracting and coupling the prosodic features and overall audio features of the audio data; 4, coupling the text information features, audio information features and expression information features, and acquiring the comprehensive information features; 5, performing data optimization on the comprehensive information features by the deep learning method, utilizing a classifier to train the optimized comprehensive information features, and acquiring an emotion recognition model for various information coupling emotion recognition. According to the method, data information of text, audio and video can be combined completely, and the accuracy of emotion state judgment in human-computer interaction can be improved accordingly.

The invention relates to an embedded distributing emulation platform basen od HLA faced to space instrumentation and command and a method for carrying out same. The platform supports a distributed interactive simulation and is developped to high application based on HLA / DIS bottom protocol, and carrys out parallel running of multi-emulation platforms, and can record and playback the display and emulation process of two-dimension situation and three-dimension virtual environment for measurement and control environment and measurement and control object during the emulation process. The specific fuction of system includes: carrying out the emulation for measurement and control environment and measurement and control object by the emulation environment platform; adding, replacing or modifying the dynamic model, behavior, sensor and countermeasure of emulation body in the emulation engine by the assemble structure; having expandability; the platform development package having the application interface independently to the protocol; having the functon of route prediction and smoothness in order to display image of situation emulation more fluent and smooth; capable of record in-situ emulation data such that the whole process of virtual emulation training is playbacked, analyzed and evaluated.

The invention discloses an aircraft-mounted multi-navigation-source comprehensive navigation simulation system. In the system, each navigation simulation sub system really simulates functions, performances and interfaces which are same as those of a model according to a self-navigation principle. A scheduling system responds a display control command, a load command and load data information sent by a mission system, and drives the navigation simulation sub systems to perform simulation calculation with combination of environment simulation data. A combined navigation system, with an INS simulation sub system as a main navigation source, performs integrated navigation based on and fault detection federated Kalman filter with GNSS, TACAN and IFDL as auxiliary navigation sources. Information fusion is achieved through a generalized federated Kalman filter in a two-stage structure constructed through a federated filter algorithm, wherein a main filter performs total information fusion and performs information distribution and information reset to each sub filter. Optimal estimation is carried out to a result of each sub filter through a dynamic information distribution coefficient. Meanwhile, the INS simulation sub system is subjected to closed-loop negative feedback correction through an estimated error by the system.

The invention relates to a tracking control method and especially relates to a distributed limited time tracking control method for formation-flying satellites. The invention aims at solving problems that the communication among formation-flying satellites is limited in a conventional formation-flying satellite control method, the control input upper limit information of a pilotage satellite is difficult to obtain, the inevitable perturbation of all satellites in a system cannot be considered, and the formation is longer in time. The method comprises the following steps: 1, building a double-satellite relative movement dynamic model; 2, building a relative dynamic model of the formation-flying satellites relative to a reference point; 3, designing a distributed limited time tracking control rule. The method solves a problem that the communication among formation-flying satellites is limited in the conventional satellite formation control method, considers the inevitable perturbation of all satellites in the system, and can complete the formation in a shorter time. The method can be used in the field of tracking control.

The invention discloses an intelligent fault diagnosis system for an ICNI system, which can improve the maintenance efficiency, carry out intelligent and automatic diagnosis and is applicable to the ICNI system. According to the technical scheme of the invention, a knowledge base and a management module thereof carry out standardization research and mathematical modeling based on a fault tree, an SQL Server database software framework is adopted, a relational database is used for building a logic relation among a fault phenomenon, a fault mode, a detection method, a historical case and a fault tree internal event to form the knowledge base; and a diagnosis information acquisition module interacts with an automatic testing system via Ethernet to acquire diagnosis data from the ICNI system and a testing instrument, a reasoning machine module adopts CBR and RBR hybrid diagnostic reasoning, after comprehensive judgment is carried out on the fault phenomenon inputted by the user, the field knowledge stored by the knowledge base and the diagnosis data from the automatic testing system, a reasoning method is automatically selected to carry out reasoning diagnosis on the fault, a reasoning process and a reasoning result are outputted to an explanation machine module, and a diagnosis report is generated.

The invention discloses a SVM (Support Vector Machine)-based multi-sensor target tracking data fusion algorithm. According to target information acquired by sensors, a compact combination mode is adopted, the SVM serves as a middle layer, an environmental variable and a measurement variance normalized vector serve as input of the SVM, output of the SVM serves as trust of the sensor, a known training sample is used for offline training, real-time filter information is used for online estimation, and a fusion knowledge base performs track fusion through real-time weighting according to the obtained trust of the sensor. According to the SVM-based multi-sensor target tracking data fusion algorithm and the system thereof, the SVM principle is adopted, the algorithm complexity is low, the environmental variable and the measurement variance normalized vector are introduced, the biological robustness and the fault tolerance are strong, extension is easy, and the algorithm and the system thereof are applicable to the field of multi-sensor tracking.

The invention discloses an active fault tolerance control method of a four-rotor aircraft based on a sliding-mode observer. The active fault tolerance control method is provided by considering that a performer may have faults when the four-rotor aircraft is in a state delay condition and combining the sliding-mode observer with sliding-mode control. The sliding-mode observer is designed, linear transformation is carried out on the system, faults of the performer are reconstructed on the basis of the ideal of equivalent error injection, compensation control is added into sliding-mode control by utilizing the reconstructed estimation value of the performer faults, and a complete active fault tolerance controller is formed. According to the invention, the sliding-mode observer is designed, the faults are reconstructed and estimated, online adjustment of the controller gain is realized, the provided control law is optimal, the control precision and response speed of flight of the four-rotor aircraft are effectively improved, and a design basis of the fault tolerance controller is provided for the complex four-rotor aircraft with performer faults. The method can be applied to active fault tolerance control for the four-rotor aircraft with time variation and time lag.

The invention discloses a intra-pulse modulation and recognition method of a low signal-to-noise radar radiation source signal, which comprises the following steps of: receiving a radar radiation source pulse signal by an electronic reconnaissance receiver, after dimension reduction and A / D sampling process from radio frequency to intermediate frequency, obtaining a radar radiation source signal S(t) having different intra-pulse modulation modes, and processing the signal S(t) in a signal processing module, identifying and outputting intra-pulse modulation mode of the radar radiation source signal. With the method, the intra-pulse modulation mode of multiple radar radiation source signals can be correctly identified when the signal-to-noise is as low as -6dB; and compared with the conventional method for identifying multiple radar radiation source signals, the computational complex O (n2) or (n3) is lower.

The invention discloses a hybrid excitation block type stator and rotor switch reluctance machine which belongs to the field of switch reluctance machines. The hybrid excitation block type stator and rotor switch reluctance machine comprises a block type stator, stator windings, a magnetism isolating plate, a permanent magnet, a block type rotor and a rotor metal sleeve, wherein a rotating shaft penetrates through the metal sleeve, the block type rotor is formed from fan-shaped block-shaped rotor tooth blocks, the fan-shaped block-shaped rotor tooth blocks are embedded into the rotor metal sleeve without magnetic conductivity, the block type stator is formed from C-shaped stator tooth blocks, and each stator winding is embedded into a groove of the two opposite stator tooth blocks. The block type stator and rotor are convenient for module production; alternate magnetic fields are not coupled, and the fault tolerance performance of the reluctance machine is strong; and the permanent magnet is magnetized in parallel, torque is generated only when an electric exciting winding is electrified, and the reluctance machine has large output power, high power density and convenient control through hybrid excitation and has the same power circuit and control strategy with an ordinary switch reluctance machine.

The invention relates to the technical field of the internet of things, and especially relates to a method for internet of things platform access equipment. Access equipment must be the equipment capable of running a MQTT client and having a complete TCP / IP protocol stack; platform equipment is a server supporting a MQTT protocol and responsible for receiving and sending the whole MQTT protocol; aplatform has a WEB page side and a mobile APP client; the platform system provides equipment access service, data gateway service, automatic server, data statement service and application service, and the communication among the services is realized through remote process calling. Micro-service architecture is adopted from the whole, each service is responsible for a core function, and the service is operated through a Docker in a virtual container way, and the features of high availability, load balancing and redundancy backup are realized through the configuration, so that the platform access equipment cost is obviously reduced, and the quick local deployment is realized; and high stability, strong fault tolerance and disaster tolerance are provided.

The invention relates to the fields of an airplane model and an aircraft, in particular to a multi-rotor aircraft with a rolling function. The multi-rotor aircraft comprises three circular rings, a connecting arm, six power units, an energy source, a flight control system, a load, a machine body and a machine body upper cover, wherein rotating centers of three power units are in the same flat surface, the rotating centers of the other three power units are in the other flat surface, the two flat surfaces are parallel but not are coincided, and lift vectors and moment vectors generated by the six power units are mutually orthogonal. Force vector and torque in any direction can be generated by regulating the rotating speed and the direction of rotors of the six power units, the decoupling of motion and gesture of the aircraft can be realized, different motion and gesture variations can be finished by the aircraft, the aircraft can move forwards along the ground or cross obstacles by matching with the circular rings, and the aircraft has extremely high flexibility and controllability.

The invention provides a database transaction processing method and device based on a message queue, and the method allows an assigned server to asynchronously consume and process the message; the method comprises the following steps: receiving a database access request; generating an ordered message queue according to the database access request; using a monitor mechanism to execute the message queue processing by sequence until all messages in the message queue are successfully processed or a retry frequency of abnormity messages in the message queue excess a preset threshold; backspacing the executed messages in the message queue when the retry frequency of abnormity messages in the message queue excess the preset threshold.

The invention relates to a voice song-selecting method, which belongs to song-selection application technology. The invention is characterized in that a data initialization module containing files of Chinese character database and a similarity metric value chart of initials and finals of Chinese syllables, a song database character pre-processing module containing character strings of target syllable chains corresponding to the name of the song or the name of the singer, a voice recognition module for converting the voice recording data of the name of the song or the name of the singer input from the sound card into the corresponding character strings of Chinese characters, a recognition result post-processing module for converting the character strings of Chinese characters into the character strings of source syllable chains, and a searching and matching module for calculating the difference value based on the metric of the similarity between initials and finals according to the character strings of target syllable chains corresponding to the name of the song or the name of the singer and the character strings of source syllable chains obtained from the recognition result post-processing module, Besides calculating the integral difference by using the dynamic programming method and outputting the result of the minimum difference value. The average button pressing time and the average operating time of song-selection are reduced, and the efficiency of song-selection operation is greatly enhanced.

The invention discloses a robust controller of a permanent magnet synchronous motor based on a fuzzy-neural network generalized inverse and a construction method thereof. The construction method of the invention comprises the following steps of: combining an internal model controller and a fuzzy-neural network generalized inverse to form a compound controlled object; serially connecting two linear transfer functions and one integrator with the fuzzy-neural network with determined parameters and weight coefficients to form the fuzzy-neural network generalized inverse, serially connecting the fuzzy-neural network generalized inverse and the compound controlled object to form a generalized pseudo-linear system, linearizing a PMSM (permanent magnet synchronous motor), and decoupling and equalizing the linearized PMSM into a second-order speed pseudo-linear subsystem and a first-order current pseudo-linear subsystem; and respectively introducing an internal-model control method in the two pseudo-linear subsystems to construct the internal model controller. The robust controller of the invention has the advantages of overcoming the dependence and local convergence of the optimal gradient method on initial values and solving the problems of randomness and probability caused by using the simple genetic algorithm, obtaining the high performance control, anti-disturbance performance and adaptability of the motor and simplifying the control difficulty, along with simple structure and high system robustness.

The invention provides a brain-like coprocessor based on a neuromorphic circuit. The brain-like coprocessor comprises a storage module storing training characteristic information, a processing module of the neuromorphic circuit based on a hierarchical structure, an encoder and a decoder which are respectively connected with the input end and the output end of the processing module, and a comparison module which is respectively connected with the output end of the storage module and the output end of the decoder. The storage module of the brain-like coprocessor comprises a training characteristic database and / or a configurable training characteristic database. The processing module comprises a solidification function network module and / or a configurable function network module and has a quite good expansion capability. According to the invention, the brain-like coprocessor employs a distributed storage and parallel cooperative processing mode, is especially suitable for processing non-formal problems and unstructured information and can also process formal problems and structured information, such that the speed of a computer in processing such problems as brain-like calculation, artificial intelligence and the like is substantially accelerated, the energy consumption is reduced, the fault tolerance capability is greatly improved, the programming complexity is reduced, and the computer performance is enhanced.

The invention discloses a constructing method of a nerval net generalized inversing bearingless permanent magnet synchronous motor decoupling controlling device, which takes two Clark inverse transformations, two electric current tracing type inverters, a bearingless permanent magnet and a load model as a whole to form a composite controlled object, a nerval net generalized inverse of the composite controlled object is formed through adopting static nerval net added with a plurality of linear links, then the nerval net generalized inverse is reversely arranged before the composite controlled object to form a generalized pseudolinear system, the generalized pseudolinear system is decoupled to three single input and output subsystems through linearization, finally a nerval net generalized inverse, the two Clark inverse transformations and the two electric current tracing type inverters are all formed to a nerval net generalized inversing bearingless permanent magnet synchronous motor controlling device, the controlling device can not only realize dynamic decoupling between a radial position system of a motor and torque moment system and between radial forces, but also be taken as a nonlinear open-cycle controlling device to use directly, and stable suspension and operation of a rotor of a motor can be ensured.

The invention relates to a spacecraft fault tolerant control method based on an angular speed observer. The method comprises a step of considering an actuator fault and external disturbance borne by a spacecraft, and establishing a spacecraft attitude control system dynamics and kinematics model, a step of designing a finite time observer to estimate the attitude angular velocity information of a spacecraft, and a step of constructing a robust controller based on the obtained angular velocity information, and at the same time considering control amount input saturation and designing an auxiliary system such that the spacecraft has robustness for the actuator fault without angular velocity information. According to the method, the stability of an attitude control system is ensured when an on-orbit working spacecraft has the actuator fault and even the attitude angular velocity information is unknown, and the method has high control precision, high fault tolerance ability and robustness to external disturbance.

The invention discloses a multiple moving target tracking method based on a BP neural network and relates to the field of computer vision technologies. The method comprises the following steps of S1, performing fusion detection to obtain multiple moving targets based on the background difference method and the frame difference method; S2, subjecting a binarization image to further denoising, and inputting the processed image in the BP neural network for multiple target segmentation; and S3, performing multiple moving target tracking based on the BP neural network. The multiple moving target detection mainly comprises three steps of 1) establishing an initialization background model, 2) updating a background using the frame difference method and performing binarization, and 3) performing background difference using the background difference method, and then subjecting the image to binarization. The invention meets requirements for robustness and accuracy of the video image moving target detecting and tracking technology, reduces the computational complexity of neural network global search, and meets requirements for processing speed of the video image moving target detecting and tracking technology.

The invention discloses an NFTL data storage system applied to an NAND flash. The NFTL data storage system comprises a data access interface for obtaining a data storing / reading / deleting / updating command; a logic / physical block mapping management device for operating a logic / physical block mapping table; and a data access device for storing / reading / deleting / updating data. The data access device comprises a data storing module, a data reading module and a physical block erasing module for carrying out physical block erasing operation. The NFTL data storage system further comprises a physical block recovery device which can increase blank physical blocks, and the physical block recovery device comprises an invalid physical webpage notification module. The NFTL data storage system further comprises a physical block abrasion balance module for balancing the number of erasing times of the physical blocks. The NFTL data storage system further comprises a bad block management device used for carrying out state detection for the physical blocks and managing a bad block management table. Therefore, the NFTL data storage system which ensures the maximum number of use times and the maximum use efficiency of the NAND flash is provided.

The invention discloses a fuzzy rough set and decision tree-based track circuit red light strip fault positioning method. The method mainly comprises the following steps of: 1) establishing an initial decision table; 2) carrying out fuzzy discretization on continuous fault feature attributes to establish a fuzzy decision table; 3) inputting fault sample training data to obtain a reduced decision table; 4) establishing a diagnosis decision tree model; 5) inputting measured data into the diagnosis decision tree model, carrying out calculation to obtain a fault diagnosis result, inputting the measured data into a diagnosis positioning decision tree model, carrying out preliminary judgement to obtain a fault positioning result, judging faults of specific equipment by combining expert experiences, and giving corresponding fault maintenance suggestions. The method can rapidly and correctly position fault points of uninsulated frequency shift track circuit red light strip faults, greatly reduce the blindness and complexity of fault diagnosis, have relatively good rule explanation and relatively good robustness, improve the fault positioning speed and correctness and provide a new fault positioning technological means for intelligent fault diagnosis of track circuits.