323results about How to "Fault-tolerant" patented technology

The invention provides a cascade megawatt photovoltaic grid-connected inverter, wherein a topology structure of the cascade megawatt photovoltaic grid-connected inverter is composed of two levels, namely a DC/DC (direct current/direct current) isolation level and a DC/AC (direct current/alternating current) output level; the structures of three phases of circuits are the same; the output ends of a power inverter group of each single-phase of DC/DC output level are connected in a star shape; the input sides of power units of each single-phase level are provided with independent PV (photovoltaic) modules of the same structure; the DC/DC isolation level comprises high-frequency DC/AC, a high-frequency transformer and high-frequency AC/DC nodes of each single-phase for realizing isolation and boosting, and reducing the consumption of a switch tube via action of a resonant soft switch; the output level power transformer set adopts a bridge type inverter circuit; and the single-phase output level power units are connected with each other in a cascade mode. Based output cascade, the device can realize megawatt grid connection; as a high-frequency chain technology is used, the traditional low frequency transformer is omitted, and the power density is high; and compared with the existing photovoltaic grid-connected inverter structure, the device provided by the invention has the advantages of high energy conversion efficiency, excellent output energy quality, certain fault-tolerant capability and the like.

The invention belongs to the field of optical parameter measurement in tissue optics research, and relates to a multi-wavelength tissue optical parameter trans-construction method based on a neural network. The method comprises: using double integrating sphere technology and a high-sensitivity photoelectric detector to collect reflected light and transmitted light on the surface of a tested sample, and using a method of relative measurement to obtain the reflectivity, diffuse transmittance and collimation transmittance of the sample; using a Monte Carlo method to establish a mapping model of a tissue optical parameter (mua, mus and g) to a measurement amount (Rd, Td and Tc); establishing a BP neural network containing two buried layers, and adopting a gradient descent weight learning function to train a BP network; and predicting the optical parameter of the measured sample through the (Rd, Td and Tc) obtained by measurement in real time, wherein an input signal of the neural network is (Rd, Td and Tc), and an output signal is (mua, mus and g). The invention provides a device adopted by the method at the same time. The method provided by the invention can quickly and accurately measure the tissue optical parameters under multi-wavelength.

A chemical and biological transducer is prepared by setting two long period fibre gratings, fibre covering and fibre core on one piece of fibre to form a MZ interferometer and then plating a metal film on fibre covering surface to form SPR transducer of fibre MZ interferometer structure. The sensing system comprises wide band light source, fibre, chemical and biological transducer formed as above, fibre spectrograph and computer as said transducer is set in gas or solution of chemical composition or biological molecule to be tested.

The invention discloses a stream preprocessing system and method based on mass information of a mobile internet, and belongs to the field of big data. The system comprises the mobile internet (000), an interface machine (100), a Kafka cluster (200), a Spark cluster (300) and a Hadoop cluster (400) which are communicated in sequence. The method mainly comprises the steps that a control module is connected with the Kafka cluster through a Zookeeper and reads data cached in the Kafka cluster; and a preprocessing module processes the data according to a specified processing process and finally writes the data into an HBase. According to the preprocessing system and method, the deficiency that MapReduce does not support stream data processing is made up for; the processing speed is high and the fault tolerance is achieved; by integrating three technologies of a distributed message system, a distributed stream processing framework and a hadoop distributed file system in the field of big data, a reference is provided for modular integration of other big data technologies; and all the mass information of the mobile internet can be processed in real time and technical support can be provided for real-time services of operators.

The invention provides a wireless sensor network connection recovery method based on minimum movement of nodes. The method comprises the steps of conducting system initialization a wireless sensor network, searching out a cut point in the network through a cut point search algorithm based on depth-first, selecting a minimum connected dominating set as a backup node of the cut point, judging whether the backup node fails according to the working state, monitored by a heartbeat packet, of the cut point, and selecting a minimum connected dominating set in a subregion where the backup node is located to conduct cascading motion to substitute the failure node after the backup node detects any fault, wherein the substitute node does not directly move to the exact position of the failure node, but only moves to a certain optimum position to manage multiple sensors, and child nodes of the failure node also correspondingly move and keep connection with a pioneer node until recovery of the whole network is completed. The method is applicable to any wireless sensor network, not only can ensure that coverage is reduced at a minimum, but also can reduce network overhead.

The invention relates to an open winding type permanent magnet motor driven reconstructed vehicle-mounted charging system for an electric vehicle. The system comprises a single-phase AC power supply,a rectifier bridge, an input filtering capacitor, three-phase voltage inverters, a three-phase permanent magnet motor winding, an output filtering capacitor, a storage battery and mode switches. The charging system sufficiently utilizes original double three-phase inverters, the permanent magnet motor winding, control and sensor units and the like of electric vehicles, and total integration of functions such as motor driving, high-power factor charging, harmonic control and the like is realized by optimizing topology to complete rectification, inversion and power factor correction. During charging, two three-phase voltage inverters are reconstructed into a three-phase cascading Buck-Boost circuit; the permanent magnet motor winding serves as an energy storage inductor of the three-phase cascading Buck-Boost circuit. By means of the charging system, the cost of a device can be effectively reduced and high-power factor charging can be realized.

The invention provides a sensor fault tolerance observing method for a satellite attitude control system. Firstly, the control system carries out the sensor fault detecting isolation; if a first sensor is judged to have faults according to an isolation result, a second KX observer is selected to observe; and if a second sensor is judged to have faults, a first KX observer is selected to observe. The first or second KX observer has the ensuring method that if the second or first sensor has faults, the control system is analyzed into a normal subsystem and a fault subsystem by using system feedback stable control as a target, and a low-dimension KX function observer is designed by respectively aiming at the two subsystems to combine and obtain a system KX observer with fault tolerance performance. The two parallel KX observers are designed and are fused into a controlling and switching flow; and when the partial sensor output is unreliable, the satellite attitude control system still can ensure the fault tolerance observation of system rest part observed quantity to ensure the closed loop control integrality of a failure system.

The invention discloses a transformer fault diagnosis method based on an added momentum item BP (back propagation) neural network. On the basis of the added momentum item BP neural network, the invention structures a full sense of intelligent method, namely a transformer fault diagnosis method based on gas data dissolved in oil, so as to improve the speed and accuracy rate of fault diagnosis. The method comprises the following steps of 1) determining neural elements of an input layer and an output layer; 2) determining activation function, the number of hidden layers of the neural network and the neural element number of the hidden layers, thereby establishing a neural network; 3) utilizing a BP algorithm of the added momentum item to adjust the network parameter, and training the established neural network; and 4) utilizing an MATLAB (matrix laboratory) software to simulate the tested neural network, thereby performing test diagnosis for the transformer fault.

The invention relates to a multipath routing reliable transmission method based on network coding. The method comprises the steps as follows: a converged node periodically broadcasts routing update information, and each node acquires hop counts from self to the converged node and a neighbor table which contains all neighbor nodes and residual energy thereof; a source node calculates the needed path number; the source node encodes data packets needing to be transmitted, selects the next hop of node and sends the data; after the next hop of node receives the encoded packets, the data packets with the same group of marks are encoded, and the needed path number is recalculated; and the process above is repeated until the last node arrives at the converged node, and then the original data packet is decoded by the converged node. By adopting the method provided by the invention, reliable transmission of the network and the balance of the energy of the network can be guaranteed.

The invention discloses a network management data reporting method and a system; the reporting method includes the steps that a network element management system reads the preset configuration file; when the file output timing arrives, the network element management system acquires the network management data according the requirement of the configuration file to generate a text file and store in a specified directory; the network management system uses the network element management system to assign an FTP ID and a password for the network management system which is enabled to access to the network element management system; the text file is acquired through the FTP protocol; the system includes the network element management system and the network management system; wherein, the network element management system includes a network management data acquisition module and a file storage module; the network management system includes a file acquiring module. The network management data reporting method and the system adopts the FTP protocol to realize the butt-joint of the network element management system of the equipment provider and the network management system of the operation business.

The invention discloses a wind field power predication method based on a deep neural network in the technical field of power system prediction and control. The method includes the steps that firstly, data of the wind speed, the wind direction, the temperature, the humidity and the atmospheric pressure which are actually measured are obtained; secondly, the projection pursuit is adopted for extracting main constituents, the neutral-position absolute deviation serves as a projection index in the projection pursuit, the interference of outliers irrelevant or little relevant to data structures and features can be effectively removed, and the main constituents can be extracted stably. A deep neural network model is adopted, and a predication model between five influence factors and the output power of a wind field is established, wherein the five influence factors include the wind speed, the wind direction, the humidity, the temperature and the atmospheric pressure. The power of the wind field is predicated, and the predicated power is obtained. According to the wind field power predication method, the precision of predicated power in future 72 hours of the wind electric field is improved, a basis is provided for reasonable dispatching of power grids, and the grid connection pressure is relieved.

The invention discloses a data collection method in a smart power grid based on user privacy protection. The method comprises the following steps that: firstly, a system is initialized; secondly, a smart electric meter sends a plurality of kinds of electricity consumption information of users to a local aggregator; thirdly, the smart electric meter signs the user information and sends the user information to the local aggregator; fourthly, the local aggregator determines the user information and signatures; fifthly, the local aggregator verifies the signatures in batch; sixthly, the local aggregator aggregates total electricity consumption information of all users; seventhly, the local aggregator searches for invalid signatures; eighthly, electric meter fault conditions are processed; and ninthly, user joining and exiting conditions are processed. According to the invention, the collection of plurality of kinds of electricity consumption information is realized, external attackers are resisted, internal attackers can also be resisted, and unforgeability of information is realized, so that the electricity consumption privacy of the users is protected.

The invention relates to a positioning method for a distribution circuit fault section based on BPSO and a GA. The mixture of a binary system particle swarm and the genetic algorithm is achieved by a bi-population evolution and information interchange strategy utilized by the method, and a binary system mixed algorithm is formed; two subpopulations are each provided with an individual scale, an evolutionary process of each generation is not affected, after evolution of each generation is completed, information interchange transmission is conducted, an optimal individual is selected, optimizing searches are carried out on the next generation of the two populations respectively until an optimal solution is found out. The probability of immature convergence occurred in a fault positioning process can be reduced by the algorithm, a certain fault tolerance is obtained, and compared with fault section positioning conducted by single binary system particle swarm or the single genetic algorithm, the convergence speed is obviously improved.

The invention provides a double-arm robot system in plug-in mounting production. The double-arm robot system comprises two industrial cameras, two laser ranging displacement sensors, two arms, binocular vision cameras and two LED plug-in mounting plates. A system control layer is composed of an industrial computer and a high-speed Ethercat bus. The invention further provides an intelligent control method of the double-arm robot system in plug-in mounting production. The method includes the steps of initiating the system and returning to zero, conducting rough positioning through the binocular vision cameras, sending data to a movement controller to be processed to obtain the laser sensor rotating angle and the laser ranging sensor distance so that precise positioning can be achieved, obtaining coordinates of a target workpiece under a laser ranging system through a positioning algorithm, moving a double-arm robot to the target position according to the coordinates, grapping the workpiece through claws at the tail ends, and placing the workpiece into the device to be assembled to be installed. The double-arm robot system is simple in structure, high in work efficiency and capable of being widely applied to plug-in mounting production of precise assembling of LED automobile lamps and automobile motor claw poles.

The invention provides a wiring error detection method and device and a heating and ventilation device. The wiring error detection method includes the steps that state parameter curves corresponding to all operation modes for a household appliance are stored in advance; the real-time operation mode and real-time state parameter curve of the household appliance are obtained within a preset time period of operation after the household appliance is started; the real-time state parameter curve is compared with the state parameter curves, and whether wiring of multiple electronic expansion valves in the household appliance is correct or not is judged according to a comparison result. According to the technical scheme, whether wiring of the electronic expansion valves of the household appliances with the electronic expansion valves or not can be rapidly detected, when wiring errors happen on the electronic expansion valves, through adjusting the control logic of the electronic expansion valves, the household appliance has a fault-tolerant function and can till work normally, and stability and safety of a system are improved.

The invention discloses an intelligent auxiliary steering system and a control method thereof. The intelligent auxiliary steering system comprises a steering wheel, a rotating angle sensor, an automobile speed sensor, a lateral acceleration sensor, an upper steering column, a lower steering column, a double-planetary-gear mechanism, a worm wheel and worm mechanism, a speed reduction mechanism, a gear and rack steering device, a front shaft, two braking wheels, a first clutch, a second clutch, a first motor, a second motor, an ECU, an upper steering column electromagnetic lock and a planet carrier electromagnetic lock. During working, according to different working modes and automobile states, the first motor and the second motor exert different functions. According to the intelligent auxiliary steering system and the control method thereof, automatic steering and manual steering can be achieved, the function of the steering system is expanded, the road feeling of a driver is improved,and the operation stability of an automobile of improved.

The invention relates to the field of data processing technology, in particular to a novel concurrent memory data organization and access method. The method is characterized in that the memory data organizational form provides two types of data access methods: Key-Value accurate index method and Key-ValueList clustered index method; any attribute of each entity can be accessed according to requirements; a multidimensional index is simultaneously supported and a single entity can be retrieved through different indexes; the entire memory data can be managed in a manner of block organization; management information of different levels and different types is stored respectively in each memory block; and data access is controlled in series based on the logic of each memory block. Compared with the prior art, the method has the advantages that the memory data structure is flexibly designed and organized on the premises of data integrity and high concurrent access efficiency, an efficient data retrieval model is provided, the WORM (write-once-read-many) concurrent data access is supported, the integrity of data read and write transaction is effectively ensured, the resource consumption is effectively reduced, and the concurrent access ability is improved.