81results about How to "Fast fault detection" patented technology

An apparatus in a LAN has first and second hardware interfaces to connect to the LAN. First and second monitoring request messages are transmitted to one or more devices in a first VLAN and one or more devices in a second VLAN respectively, via both the first and second hardware interfaces. The monitoring request messages use the Address Resolution Protocol (ARP) or the Neighbor Discovery Protocol (NDP). First and second monitoring response messages are received via the first and/or second hardware interfaces in response to the first and second monitoring request messages respectively. A selection is made between the first and second hardware interfaces for performing data communication, based on the first and second monitoring response messages. The selection is performed independently for data communication via the first and second VLANs based on at least one characteristic of the first and second monitoring response messages respectively.

The present invention provides scalable and rapid Ethernet fault detection which eliminates the requirement to contiguously send heartbeat frames at regular intervals to detect connectivity faults for each Ethernet Path. The present invention generates Continuity Check Message (CCM) frames only when a fault occurs, continues generating CCM frames while the fault remains, and discontinues when the fault clears. The present invention can be utilized with Ethernet Protection Switching to rapidly detect faults. Additionally, the present invention can be used in any Ethernet topology including point-to-point, rings, and the like.

The invention relates to the field of wireless sensor networks and fault diagnosis, and discloses a method for carrying out fault diagnosis on wireless sensor networks. The method comprises the following steps: S1, carrying out online real-time acquisition on data measured by sensor nodes in a wireless sensor network; S2, detecting the fault of a single sensor node by using the space and time characteristics of the data; S3, detecting the fault of the whole wireless sensor network by using the correlation between two adjacent nodes; S4, carrying out attribute reduction on parameters obtained in the steps S2 and S3; and S5, obtaining a fault diagnosis result of the wireless sensor network according to the attribute reduction result obtained in the step S4. In the invention, the fault of a single sensor node is detected by using the space and time characteristics of data measured by sensor nodes in a wireless sensor network, and the rapid and correct fault detection on all nodes in the network by using the correlation between the nodes is realized.

We describe a method of controlling turn off time delay of a switching device of a switch mode power converter (SMPC). The SMPC has an inductive component comprising an input winding coupled to receive power from an input; and a switching device to, when on, conduct input winding current. In embodiments the method comprises applying turn on and turn-off signals to the switching device; applying at least one turn off signal, to initiate turning off of the switching device, and detecting a sensing signal from a further winding of the inductive component, inductively coupled to the input winding, to thereby indicate an end of a turn off time delay or duration. The method controls the turn on signal for a subsequent switching cycle of the SMPC device to regulate the turn off delay time.

The invention discloses a chemical fault detection method based on particle swarm optimization and a noise reduction sparse coding machine. The method comprises the following steps of carrying out unsupervised feature learning on standardized and whitened training data by using a plurality of stacked noise reduction sparse autocoders; carrying out Softmax classifier model training in a supervisedmanner; and finally, finely adjusting the weight parameters of the whole network through supervision, and introducing a particle swarm optimization algorithm into the key adjustable hyper-parameters for automatic optimization to obtain a trained chemical process fault detection intelligent model for fault detection of process real-time data. According to the invention, the greedy layer-by-layer training method of the deep neural network is adopted to adaptively and intelligently learn knowledge implied by original data in the chemical process; Compared with a traditional method, the method hasthe advantages that the method is more intelligent, the fault detection performance can be improved, and due to the fact that an automatic optimization algorithm is added, much time is saved comparedwith manual parameter tuning.

The invention relates to a transient travelling wave amplitude integral type superspeed bus protection system which has the advantages of simple structure, rapid detection speed, high sensitivity and the like and is convenient in use and a method thereof. The method is implemented as follows: installing N numbered protection units at the outlet of each outgoing line if a bus is connected with N numbered outgoing lines; realizing mutual communication between every two protection units via a signal bus; collecting the current and voltage signals of the line by each protection unit at a high speed, and independently judging the failure direction; if a certain protection unit judges that the line has a forward direction failure, sending out a lockout action message, transmitting the judgment result to other protection units by signal buses, receiving judgment results about respective line failure direction from other protection units, and comprehensively analyzing the judgment results of all protection units by each protection unit so as to determine the bus state; if all the protection units judge that the failure comes from the reverse direction, determining that the bus has a failure so as to promptly give out an instruction to trip off respective side switch to isolate the failed bus; and otherwise, determining that the bus has no failure and requires no isolation.

The invention discloses a power tube open-circuit fault detection and locating method. The state of health or the fault topological structure of the system is located and determined by using a similarity measurement method, then a fault bridge arm is determined by the percentage of the number of sampling points near the current zero point in the number of the sampling points of one period, and finally a power tube is located by current periodic integral polarity. The power tube open-circuit fault detection and locating method is suitable for any rectification, inversion and rectification and inversion integrated systems. The method is real-time online, rapid, highly robust and accurate.

The invention uses the combination of the software and the hardware to improve the speed and accuracy of the fault detection; in the approach for main equipment protection or recovery, it uses a self-adaptive main equipment protection and recovery approach. Wherein, when equipment runs at a non-route signaling mode, it uses a partly synchronous method, and when it runs at a route signaling mode, it firstly decides if all neighboring nodes have the protocol expanding functionality; if yes, using the protocol expanding approach to make main equipment protection; otherwise, using the state fully synchronizing approach.

The invention discloses a fault detection starting method and an apparatus thereof. The method comprises the following steps of acquiring a historical time interval of uploaded data of terminal equipment in a set time period by a server; optimizing the historical time interval and determining a first mean value and a first variance of the optimized historical time interval; according to the first mean value and the first variance of the optimized historical time interval, determining a time interval threshold of fault detection; and if a time interval of current uploaded data of the terminal equipment is determined to be greater than the time interval threshold of fault detection, carrying out the fault detection of the terminal equipment. Through the historical time interval of the uploaded data of the terminal equipment, the time interval threshold of the fault detection is automatically calculated and generated; and after the time interval of the current uploaded data of the terminal equipment is determined to exceed the time interval threshold, a fault detection flow is automatically started; and rapid fault detection starting can be realized and fault detection efficiency is increased.

The invention discloses a vibration-proof hammer fault online detection and identification method based on a binocular vision image. The method comprises the following steps of using two cameras to form a binocular stereo vision system; establishing one vibration-proof hammer state attribute set S; under an original state, acquiring initial image information possessing a vibration-proof hammer and a fixed reference object, through the initial image information, acquiring a three-dimensional coordinate of the vibration-proof hammer, a three-dimensional coordinate of the fixed reference object and then acquiring an initial value S0 of the vibration-proof hammer state attribute set S; under a current state, when the vibration-proof hammer is discovered to have an abnormal fault, acquiring current image information possessing the vibration-proof hammer and the fixed reference object, through the current image information, acquiring the three-dimensional coordinate of the vibration-proof hammer, the three-dimensional coordinate of the fixed reference object and then acquiring a current value St of the vibration-proof hammer state attribute set S; identifying a vibration-proof hammer fault type; and according to the current value St and the initial value S0, calculating a changing value delta S of a vibration-proof hammer state attribute, and according to the delta S, determining and acquiring a vibration-proof hammer fault condition.

A two-point VI curve scanning comparison fault diagnosis method for various circuit boards comprises the following steps of preparing a faultless standard board which is the same with the circuit board whose fault needs to be detected; taking each exposed conductive portion on the board surface of the standard board as the detection point of a VI curve; detecting two-point VI curve information between the detection point of each VI curve on the standard board surface and the detection points of the other VI curves on the standard board surface, and storing the measured two-point VI curve information of the standard board and the position coordinates of the detection points of the two associated VI curves; and according to the position coordinates of the stored detection points of each VI curve on the standard board, arranging the detection points of the VI curve on the board surface of the circuit board to be detected which needs to be detected. The invention aims at providing the two-point VI curve scanning comparison fault diagnosis method for various circuit boards, and the method can be used to carry out fault detection on a circuit board card without a graph and without data under the condition that circuit board welding spot distribution, a circuit work principle and functions do not known.

The invention relates to an electric vehicle driving permanent magnet synchronous motor control technology and particularly relates to an electric vehicle software and hardware decoding redundant circuit, which comprises a motor controller main control chip DSP, a sinusoidal signal conversion circuit, a rotary transformer decoding chip, a logic control circuit, a software and hardware decoding switching relay control circuit, an excitation signal processing circuit, a rotary transformer and a feedback signal switching and processing circuit. The motor controller main control chip DSP is respectively connected with the sinusoidal signal conversion circuit, the rotary transformer decoding chip, the logic control circuit and the feedback signal switching and processing circuit; the rotary transformer decoding chip is respectively connected with the logic control circuit, the software and hardware decoding switching relay control circuit and the feedback signal switching and processing circuit; the software and hardware decoding switching relay control circuit is connected with the excitation signal processing circuit; the excitation signal processing circuit is connected with the rotary transformer; and the rotary transformer is connected with the feedback signal switching and processing circuit. The circuit is rapid in fault detection switching, simple in circuit and low in cost.

The present invention discloses an electric control device of textile machine. Said control device includes the following several portions: power supply, main circuit, brake circuit, textile machine, control circuit, protection circuit, starting button and stopping button. Said invention also provides the connection mode of all the above-mentioned portions, and provides the working principle of said control device and its concrete operation method.

The invention provides a modular multi-level DC power transmission system fault identification method based on a support vector machine. The method is suitable for fault identification of a modular multi-level DC power transmission system. According to the method of the invention, characteristic values of a training sample are acquired, and the characteristic values are classified to a three-phasebalance fault and an imbalance fault; a corresponding fault identification model is established; then the characteristic valve of the to-be-identified power system is acquired; after fault type dividing, normalization processing is performed in a corresponding fault identification model; and finally the fault type of the system is identified through a method of the support vector machine, and thefault type is output. Actual verification results show a fact that the fault type which is identified according to the fault identification model is same with the actual fault type and low identification time is realized; quick, accurate and high-efficiency technology support can be supplied for fault testing of the modular multi-level DC power transmission system.

The embodiment of the invention provides a novel power distribution network fault detection method based on a quick switch. The method comprises the steps of fault current signal acquisition, data extraction, neural network training, fault classification and quick switch action control. A multi-layer sensor is adopted to acquire current information, and a particle swarm optimization algorithm is adopted to diagnose hierarchical information. A line E-type traveling wave distance measurement method is adopted to estimate the position of the fault, and is combined with an Attention mechanism to judge the position of the fault. An eddy current repulsion is adopted as a quick switch of a driving mechanism, and breaking can be achieved within 3 ms after a fault action signal is received. The method improves the fault detection level, improves the utilization rate of power supply equipment, reduces the electric energy loss, and improves the overall operation level of a power distribution network. The fault self-healing capability of the power distribution network is improved, and the power supply reliability is effectively improved. The embodiment of the invention further provides a novelpower distribution network fault self-healing system based on the method.

The invention discloses a large water delivering and transferring unit preventive control method. The large water delivering and transferring unit preventive control method is characterized by comprising the following steps that firstly, temperature, vibration degree and lubricating oil amount data of a water pump motor and liquid level data of a water inlet pond are collected, the collected dataare sent to a unit control cabinet, and the unit control cabinet sends control signals to the water pump motor, a pump control valve, an overhauling valve and a monitoring instrument; secondly, the unit control cabinet controls running of the water pump motor, the pump control valve, the overhauling valve and the monitoring instrument; thirdly, the unit control cabinet detects unit exterior suddenchange signals and unit interior signal faults; and fourthly, corresponding measures are taken according to the detection result for preventive control. The large water delivering and transferring unit preventive control method solves the problem that in the unit producing and running process, due to exterior technology sudden changes or self faults, sudden shutdown is caused, and damage is caused; and advanced preventive measures are taken for a unit in the production process, automatic detection is timely, and protection measures are taken.

The embodiment of the invention relates to liveness detection and route convergence in a software-defined networking distributed system, and the invention describes techniques for improving speed of network convergence after node failure. In one example, a method includes the steps: storing, by SDN controller, an underlay routing table having routes for an underlay network of a data center and an overlay routing table having a set of routes for a virtual network of an overlay network for the data center, wherein the underlay network includes physical network switches, gateway routers, and a set of virtual routers executing on respective compute nodes of the data center; installing, within the underlay routing table, a route to a destination address assigned to a particular one of the virtual routers as an indicator of a reachability status to the particular virtual router in the underlay network. The SDN controller controls, based on presence or absence of the route within the underlay routing table, advertisement of the routes for the virtual network of the overlay network.

The utility model provides a fault detection device of a shipborne antenna and a method thereof. The shipborne antenna is provided with a plurality of sensors used for obtaining the operation state of the shipborne antenna. A data collecting module is used for collecting the current data of the plurality of sensors of the shipborne antenna and storing the current data as first data. A network transmission module is used for converting the first data into second data and sending the second data through a network. A data analysis module is used for receiving the second data and analyzing the second data to obtain a detection result. A result display module is used for displaying the detection result. According to the fault detection device of the shipborne antenna and the method thereof, the automatic detection of relevant data of the antenna is realized, through the reliable transmission mode, the rapid fault detection of shipborne equipment is realized, and compared with manual detection and maintenance, the time, efficiency and reliability are greatly improved.