33results about How to "Fast fault diagnosis" patented technology

The invention discloses a rail transit vehicle equipment universal detection and fault diagnosis method and a system thereof. The method comprises the following steps: signals acquired through a data acquisition module are input to a fault diagnosis module to obtain a fault diagnosis conclusion; an expert system rule base is arranged in the fault diagnosis module; and a plurality of rules relevant to faults are stored in the expert system rule base; the expert system rule base adopts fault trees to represent the interrelationship of the various rules; a fault diagnosis process is served as a data matching process based on importance degree; the acquired data and the rules in the expert system rule base are matched from the highest importance degree to the lowest importance degree; if the matching is successful, a matching result is output and a fault conclusion is given out; and no fault occurs if the matching is not successful after the whole rule base is browsed. The rail transit vehicle equipment universal detection and fault diagnosis method and the system have good universality and are quick in fault diagnosis.

The invention discloses a diagnosis method for an active power filter switching device open-circuit fault based on model reference analysis. The diagnosis method includes the steps that on the basis of building an actual operation model of active power filter main circuits, a reference model is constructed; measurable active power filters in all sampling periods are used for outputting three-phase compensating currents, and voltage residual errors are generated according to reference analysis of the model; by setting a threshold value and two judgment flag bits, the residual errors are evaluated to detect whether the open-circuit fault happens on an APF switching device or not in real time; if the fault happens, the specific position where the open-circuit fault of the switching device happens is diagnosed according to the two judgment flag bits. The diagnosis method is effectively used for monitoring the active power filters on line and diagnosing faults, and electric, electronic and electric energy quality control devices such as the active power filters and reactive compensators operate reliably and safely.

The invention, which relates to the technical field of the analog circuit fault diagnosis, provides an improved particle swarm optimization diagnosis method and system of an analog non-linear direct current circuit. With the method and system, a problem that the existing pattern-classification-based fault diagnosis method does not has the enough diagnosis capability for the unknown fault state and a multi-fault state of the analog circuit can be solved. The method comprises: establishing a fault diagnosis equation; calculating fitness values of all particles; calculating a unified inertia weight of all particles; calculating changes of the fitness values; determining a final value of the inertia weight of all particles at current iteration; updating speeds and positions of all particles in the particle swarm; and repeating all above-mentioned steps until method convergence is realized. Compared with the standard PSO algorithm, the method and system based on the technical scheme have the high fault diagnosis coverage rate and the fast fault diagnosis speed.

The invention discloses a phase failure diagnosis method of a permanent magnet synchronous motor (PMSM) drive system of an electric vehicle. According to the method, a drive failure of the PMSM drive system of the electric vehicle is detected based on detectable stator current, and a phase failure of the PMSM drive system can be diagnosed in real time in an on-line manner. The method can be applicable to running conditions of the electric vehicle, has technical advantages of high failure diagnosis speed, high diagnosis precision and the like, and is easily integrated with the control of the electric drive system to realize the safe and reliable running of the electric drive system.

The invention discloses an electro-magnetic doubly salient motor power converter open-circuit fault diagnosis method, and relates to the technical field of fault diagnosis. According to the method, the position of a current sensor in a power converter topology is changed, a first current sensor is placed on a direct-current bus and used for detecting bus current, and a second current sensor is placed on an upper bridge arm power tube bus and used for detecting upper bridge arm power tube breakover current; in combination with the working state of the motor, the phase current is indirectly obtained through the relationship between the breakover current and the phase current of the upper bridge arm power tube to realize the normal operation of the motor; according to different current flowing paths corresponding to faults of different power tubes, fault diagnosis is realized by combining driving signals and position signals of the power tubes. Compared with a traditional fault diagnosis method without changing the positions of the current sensors, the method has the advantages that the number of the current sensors is reduced, open-circuit fault positioning of the power tube can be quickly realized, and the implementation method is simple and accurate.

The invention relates to the technical field of power. The invention provides a voiceprint-based intelligent health monitoring method for power equipment. The voiceprint-based intelligent health monitoring method comprises the following steps: S1, arranging a voiceprint signal collector on the site of the power equipment, and uniformly deploying a plurality of wireless sensors on each piece of power equipment to acquire voiceprint signals of each piece of equipment working on the site of the power equipment; S2, enabling the voiceprint signal collector to be composed of a Bluetooth wireless communication module, a data packet forwarding module, a 4G communication module and a power supply module; S3, enabling the cloud voiceprint data memory to be composed of an IP communication module, adata storage module and a data processing module; and S4, periodically performing feature extraction, fault diagnosis and threshold correction on the voiceprint data stored in the disk by adopting anequipment health intelligent manager. According to the invention, the problems of difficult deployment of acquisition nodes, unstable work of a data server, slow fault diagnosis speed, low precision,non-adjustable fault diagnosis threshold and the like in the existing power equipment health monitoring technology are solved.

The invention discloses a high-voltage direct-current power source testing device of an X-ray irradiator, and relates to the technical field of X-ray irradiator manufacturing, in particular to a testing technology of a high-voltage direct-current power source of an X-ray irradiator. The device is characterized in that the device is of a box structure and comprises an operation panel, a case and aninternal circuit board; a display meter head, a fault indicating column, a state indicating column, a lamp filament control column and a high-voltage control column are arranged on the operation panel, and the components and parts are connected with corresponding pins of a DR50 interface terminal arranged on the side face of the case. The internal circuit board is a power conversion board, +15V voltage provided by a communication interface of a high-voltage direct-current power source master control panel of the X-ray irradiator is received, and a power supply is provided for the components and parts on the panel of the case. The high-voltage direct-current power source testing device has the advantages that a complete machine debugging scheme of a touch screen and a PLC can be replaced,a high-voltage direct-current power component of the X-ray irradiator is independently tested, industrial field use is convenient, fault judgment is fast, the cost is low, and maintenance is easy.

The invention discloses a doubly salient electro-magnetic motor converter power tube and winding open-circuit fault diagnosis method, and relates to the field of doubly salient electro-magnetic motors. And the neutral point voltage of the armature winding of the electro-magnetic doubly salient motor is compared with half of the bus voltage, open-circuit fault diagnosis is carried out on the power tube and the armature winding in the current operation state, the implementation method is simple and accurate, the fault diagnosis speed is high, the diagnosis cost is low, and the fault diagnosis accuracy is high. And the stability of the whole driving system is improved.

The invention relates to a current-limiting blockout device and method of a DC power distribution network. The device is composed of a current-limiting blockout loop (1) and a pre-charging circuit (2). The fault current-limiting blockout loop (1) is composed of a first capacitor (C), a first lightning arrester (Z), a first power electronic switch device (S1), a second power electronic switch device (S2), a third power electronic switch device (S3), a fourth power electronic switch device (S4) and a first current-limiting inductor (L). Thus, a fault current in the DC power distribution networkcan be limited and blocked rapidly, and impact of the fault current on a power supply and loads is greatly reduced in the DC power distribution network.

The invention provides an Ethernet concentrator with a fault diagnosis and isolation function and belongs to the technical field of airborne network communication. According to the concentrator, a network communication system can be changed from a bus topology to a star topology. The concentrator has the advantages of convenient connection and high expandability. Influences of bus circuit break onthe whole communication system are reduced. However, a whole communication network still can be paralyzed due to faults such as link short circuit or node disordered distribution. For the problem, the invention provides a fault diagnosis and isolation scheme. Whether communication nodes and links are normal or not is monitored in a mode that Ethernet data transceiving modules communicate with each node independently, and the influences of fault nodes on the communication links are shielded through utilization of control switches. The fault diagnosis and isolation scheme has the advantages that the fault diagnosis accuracy is high, the detection speed is fast, the fault nodes and links can be effectively isolated, and the reliability and the fault-tolerant capability of the communication system can be improved.

The invention discloses a rail transit vehicle equipment universal detection and fault diagnosis method and a system thereof. The method comprises the following steps: signals acquired through a data acquisition module are input to a fault diagnosis module to obtain a fault diagnosis conclusion; an expert system rule base is arranged in the fault diagnosis module; and a plurality of rules relevant to faults are stored in the expert system rule base; the expert system rule base adopts fault trees to represent the interrelationship of the various rules; a fault diagnosis process is served as a data matching process based on importance degree; the acquired data and the rules in the expert system rule base are matched from the highest importance degree to the lowest importance degree; if the matching is successful, a matching result is output and a fault conclusion is given out; and no fault occurs if the matching is not successful after the whole rule base is browsed. The rail transit vehicle equipment universal detection and fault diagnosis method and the system have good universality and are quick in fault diagnosis.

Embodiments of the invention provide a switch cabinet arc light protection method and device. The method comprises the steps that arc light of a switch cabinet is collected through an avalanche photodiode, the arc light is amplified and converted into a voltage signal, and the voltage signal is sent to a signal processing device; the signal processing device is used for judging whether the voltagesignal is larger than an early warning threshold value and a protection threshold value or not separately; if the voltage signal is larger than the early warning threshold value, an early warning signal is sent to a control center; if the voltage signal is larger than the early warning threshold value and the protection threshold value, a tripping signal is sent to a switch of the switch cabinet;and the signal processing device sends an alarm signal to the control center according to the condition that the voltage signal is larger than the early warning threshold value and the protection threshold value. According to the embodiments of the invention, the early warning threshold value and the protection threshold value participate in action logic judgment to serve as the locking conditionfor judging the switch cabinet fault, so that the fault judgment speed is high, the accuracy is high, and the operation safety of the switch cabinet is improved.

The invention discloses an unmanned aerial vehicle actuating mechanism fault diagnosis method based on extended Kalman filtering. The extended Kalman filtering technology is adopted to introduce the state of an actuating mechanism into a state vector of a filter, and only one filter can be used for monitoring all health states of one actuating mechanism, so that the method has the advantages of small calculated amount and high fault diagnosis speed. According to the unmanned aerial vehicle actuating mechanism fault diagnosis method based on extended Kalman filtering, three fault types of jamming, swinging and proportionality coefficient of the actuating mechanism can be comprehensively monitored, and the unmanned aerial vehicle actuating mechanism fault diagnosis method can be suitable fora flight control system which is limited in operational capability and requires rapid diagnosis and determination of the fault type of the unmanned aerial vehicle actuating mechanism.

The invention discloses an object-oriented address modeling method. The method includes: multi-dimensional tree structures are used to perform precise modeling management on user address nodes and personnel information and building identifications related to addresses by the aid of object-oriented address business modeling models and a multi-dimensional data object storage system. When low-pressure models are available, user fault positions can be precisely positioned and topological analysis can be completed by fuzzy matching of addresses; when low-pressure models are unavailable, user addresses and fault range can be geographically and precisely positioned by the models, and a dispatcher can be guided to complete fault judgment fast.

The invention discloses fault handling method and device for a pumping well, a storage medium and an electronic device. The method comprises the following steps of, obtaining fault state information of the pumping well in a fault state, wherein the fault state information comprises at least one state keyword; looking up at least one target triplet that matches the state keyword in a plurality of triplets in a pre-created knowledge graph database; generating the triplet in the knowledge graph database based on historical fault data of the pumping well, wherein the historical fault data at leastcomprises historical fault types of the pumping well, fault state data corresponding to the historical fault types, and handling measure data; and obtaining target fault type data and / or target handling measure data of the pumping well based on the target triplet; and outputting the target fault type data and / or target handling measure data of the pumping well.

The invention provides a power electronic current converter and a control method capable of eliminating two-way fault current. The current converter comprises current conversion bridge arms connected through electric reactors. The current conversion bridge arms comprise T-shaped power submodules connected in series. The two horizontal ends of one T-shaped power submodule are connected through a capacitor and then connected with the vertical end of another T-shaped power submodule. The current conversion bridge arms are sequentially connected through the vertical ends, the electric reactors and the horizontal ends. Submodule controllers and optical fiber current mutual inductors of the current conversion bridge arms are connected with current conversion bridge arm controllers through optical fibers. The current conversion bridge arm controllers are connected with a current converter master controller. According to the control method, dual fault current protection is carried out on the power electronic current converter through a current detection method for a driving circuit and the current conversion bridge arms of a fully-controlled device. Compared with the prior art, the power electronic current converter and the control method capable of eliminating the two-way fault current can rapidly and effectively eliminate the two-way fault current.

The present invention relates to the technical field of fault diagnosis of analog circuits, and provides an improved particle swarm optimization diagnosis method and system for simulating non-linear direct current circuits, so as to solve the problem of unknown fault states and multiple fault states of analog circuits by current fault diagnosis methods based on pattern classification Insufficient diagnostic ability of the problem, the method includes: establish a fault diagnosis equation; calculate the fitness value of each particle; calculate the uniform inertia weight of all particles; calculate the change of fitness value; determine the final inertia weight of each particle in the current iteration value; update the velocity and position of each particle of the particle swarm; repeat the above steps until the method converges. Compared with the standard PSO algorithm, the technical solution proposed by the invention has higher fault diagnosis coverage and faster fault diagnosis speed.

The invention provides a wiring-free centralized control type distribution automation terminal and a system thereof. The terminal comprises a terminal central processing unit and a plurality of powerdistribution terminal subunits, wherein the terminal central processing unit is composed of a first power supply module, a first anti-surge protection module, a first EMC filtering module, a first central processing unit, a first Ethernet module and a WIFI module, the plurality of power distribution terminal subunits are used for collecting electrical signals of power distribution equipment, and the terminal central processing unit communicates with the plurality of power distribution terminal subunits through the WIFI module. The system provided by the invention comprises the power distribution automation terminal. The terminal is simple in structure, reasonable in design, free of wiring, and capable of rapidly positioning faults and being replaced in an electrified mode, and can guarantee the power supply continuity and reliability of a power distribution network so as to meet the requirements of an intelligent power grid.

The invention discloses an LLC resonant converter open-circuit fault diagnosis method based on resonant capacitor voltage, and the method comprises the steps: setting a reasonable threshold value according to the amplitude of the resonant capacitor voltage of an LLC resonant converter under a normal working condition, sampling the resonant capacitor voltage after a fault, and comparing the sampledresonant capacitor voltage with the set threshold value, thereby achieving the fault diagnosis; then, through phase shift control between bridge arms, realizing the fault positioning. The LLC resonant converter open-circuit fault diagnosis method provided by the invention is high in diagnosis speed, low in error diagnosis rate and high in robustness, and has important significance for ensuring the uninterrupted operation of the LLC resonant converter under the condition of an open-circuit fault.

The invention provides a real-time fault diagnosis method and system based on a sequential random forest. The method comprises: obtaining a to-be-detected residual signal of a to-be-diagnosed nonlinear system; extracting a time-frequency feature vector of the residual signal to be measured based on wavelet packet decomposition; substituting the time-frequency feature vector into a trained random forest fault separator, and performing sequential probability ratio test on the to-be-diagnosed nonlinear system to obtain target fault information, wherein the target fault information comprises a target fault type and target fault occurrence time; and substituting the time-frequency feature vector and the target fault type into a trained regression random forest fault identifier to obtain fault size information corresponding to the target fault type. The technical problems that in the prior art, real-time fault diagnosis cannot be achieved, and the missed diagnosis rate and the misdiagnosis rate are high are solved.

The invention discloses a power grid fault diagnosis method based on equipment failure probability, which includes collecting historical operation data of relay protection and circuit breakers through real-time perception of power equipment, and counting the failure probability of relay protection and circuit breakers; collecting data from the power grid fault information system The number of relay protection and circuit breakers and the configuration parameters between them; the actual action status of relay protection and circuit breakers, and the status of grid components are collected from the grid dispatching automatic control system; the actual action status and status of relay protection and circuit breakers The goal is to minimize the difference between the expected action state and the estimated risk, and build a multi-objective optimization model for power grid fault diagnosis based on the failure probability of relay protection and circuit breakers and the collected data; linearize the optimization model to obtain a linear optimization model; use Fuzzy optimization methods solve linear optimization models. The invention obtains more accurate and rapid fault diagnosis results by solving the multi-objective optimization model.

The invention relates to the field of lightning electromagnetic pulse protection, and specifically discloses a power carrier-based lightning electromagnetic pulse protection performance detection system and method. The detection system includes a host networking interface device, a state monitoring center and a multi-channel lightning electromagnetic protection real-time fault monitoring suppressor , the multi-channel lightning electromagnetic protection real-time fault monitoring suppressor is installed in the protection line; the detection method includes the following steps: S1, the multi-channel lightning electromagnetic protection real-time fault monitoring suppressor is used to set its unique address inside, and pass the status monitoring center. Address setting function. The invention can monitor the working state of the lightning suppressor online without disassembling the equipment, switch the bypass after the fault is judged, and eject the faulty component from the circuit breaker, and use the bypass to maintain the protection performance, so as to protect the aircraft against lightning and high intensity. Radiated field effects provide maximum protection, greatly reducing test cost and test difficulty.

The present invention provides a real-time fault diagnosis method and system based on sequential random forest, comprising: obtaining the residual signal to be tested of the nonlinear system to be diagnosed; extracting the time-frequency feature vector of the residual signal to be tested based on wavelet packet decomposition; The time-frequency feature vector is substituted into the random forest fault separator after training, and the sequential probability ratio test is performed on the nonlinear system to be diagnosed to obtain the target fault information; the target fault information includes the target fault type and the target fault occurrence time; the time The frequency feature vector and the target fault type are substituted into the trained regression random forest fault identifier to obtain the fault size information corresponding to the target fault type. The invention alleviates the technical problems in the prior art that real-time fault diagnosis cannot be realized and the rate of missed diagnosis and misdiagnosis are relatively high.

The invention provides a server fault diagnosis rule screening method based on GRA, and the method comprises the following steps: traversing each fault and each rule, calculating a rule fault matching rate, and obtaining a fault matching rate sequence; removing the number of faults of low fault levels through an inter-partition neglect minimum algorithm, and calculating the severity of rule matching faults according to the preset weight of each fault level and the corresponding number of faults to obtain a fault severity sequence; calculating the correlation degree of any two rules through a GRA algorithm, calculating the correlation degree of each rule and the rule database set, obtaining a correlation degree sequence, and then carrying out steering to obtain a steering correlation degree sequence; calculating weight values of the fault matching rate sequence, the fault severity sequence and the steering similarity sequence through a reciprocal variance algorithm, obtaining a good and bad value sequence through weighted summation, and setting priorities for all rules according to good and bad values. According to the method, the rule with high quality value is preferentially used for diagnosis, so that the redundancy of repeated diagnosis is reduced, and the diagnosis speed is increased.

The invention discloses a power grid fault diagnosis method based on an equipment fault probability. The method comprises the steps: collecting historical operation data of relay protection and circuit breakers through real-time sensing of power equipment, and carrying out statistics of the relay protection and circuit breaker fault probabilities; collecting the number of relay protection and thecircuit breakers and configuration parameters between the relay protection and the circuit breakers from a power grid fault information system; collecting actual action states of the relay protectionand the circuit breakers and a power grid element state from a power grid dispatching automatic control system; constructing a power grid fault diagnosis multi-objective optimization model based on the fault probabilities of the relay protection and the circuit breakers and the acquired data by taking a minimum difference degree and a minimum evaluation risk of an actual action state and an expected action state of the relay protection and the circuit breakers as objectives; linearizing the optimization model to obtain a linear optimization model; and solving the linear optimization model by using a fuzzy optimization method. In the invention, a more accurate and rapid fault diagnosis result is obtained through solving the multi-objective optimization model.

The invention discloses a track-control fault-tolerant control method for a reentry type aircraft during the off-track braking process. The method comprises the following steps of S1, during the off-track braking process, calculating the instruction speed in real time; S2, according to the instruction speed and the navigation speed, calculating the required speed of the aircraft; S3, according to the required change of the speed, judging whether a main engine has a fault or not; S4, if the main engine is judged to have a fault, conducting the emergency treatment. According to the invention, a track-control fault can be judged through continuously increasing the required speed. The method is feasible in algorithm and high in reliability and has obvious advantages.

The invention belongs to the technical field of electric power system transmission safety, and discloses an LSTM-based method and system for diagnosing a fault area of ​​an AC / DC hybrid power grid. Including: building a power system time-domain simulation model to simulate various working conditions to obtain the voltage amplitude of the entire network node and the corresponding label to obtain the basic sample set; using the sliding window method to intercept the basic sample to obtain the sample set for training the fault time judgment model and the fault area judgment model Carry out training and properly adjust the relevant parameters of the model; input the samples at the current sliding window time, the fault time judgment model judges whether a fault occurs, and if a fault is confirmed, input the samples into the fault area judgment model to obtain the fault location; finally output the current fault diagnosis information. The invention uses a deep neural network to quickly and effectively determine the time of fault occurrence in the power grid and determine the fault area, has better performance under different operating conditions and certain noise conditions, and can meet the needs of fault diagnosis in complex power systems.