1338 results about "Fault occurrence" patented technology

The communication availability information between a plurality of transmitters and a plurality of destinations before the communication state between a transmitter and a destinations in a communication network changes from available to unavailable is compared, layer by layer from an upper layer toward a lower layer, with the communication availability information after change, and destinations in paths where the communication state has changed from available to unavailable are grouped. Thus, the communication network is divided into a plurality of affected ranges and an interface of a device located at the border between the affected ranges is deduced as a fault occurrence point.

A system and method that provides improved fault detection in turbine engines is disclosed. The fault detection system provides the ability to detect symptoms of engine faults based on a relatively limited number of engine parameters that are sampled relatively infrequently. The fault detection system includes a sensor data processor that receives engine sensor data during operation and augments the sensor data. The augmented data set is passed to a fuzzy logic inference system that determines the likelihood that a fault has occurred. The inference system output can then be passed to a diagnostic system where evaluation of the output may yield a detailed diagnostic result and a prediction horizon.

The invention discloses a distributed hadoop cluster fault automatic diagnosis and restoration system which comprises a cluster file system monitoring module for collecting and obtaining cluster node information and a database file; a work and task monitoring module for collecting information of work and tasks; a physical node monitoring module for monitoring resource consumption information of each physical node; a data storage and analysis and processing module for storing monitoring data to a database, setting monitoring alarm rules and configuring alarm ID, level and reasons in advance; and an automatic restoration module for defining and configuring various common alarm faults in advance and making a preprocessing script for each alarm fault, matching the fault happened at present with the alarm faults defined and configured in advance when monitoring a fault, and calling the corresponding preprocessing script to finish automatic restoration of the fault. The method can diagnose and restore system fault automatically to allow maintenance to become easier, and performance data and node state to be clearer and more obvious.

A network fault managing system for a network including network elements as nodes includes a fault node indication data storage section, a fault indication data storage section, a flag, a fault node indication data processing section, a fault indication data processing section and an output unit. The fault node indication data storage section stores a fault node indication data set in which fault nodes are managed in a tree form. The fault node indication data processing section receives a fault association notice having a fault occurrence position identifier and a fault indication data, the fault occurrence position identifier indicating a fault node in which a fault has occurred, and the fault indication data indicating data associated with the fault, and determines whether a fault node indication data corresponding to the fault node specified by the fault occurrence position identifier of the fault association notice is present in the fault node indication data set. Also, the fault node indication data processing section generates the fault node indication data based on the fault occurrence position identifier to store in the fault node indication data set of the fault node indication data storage section, when the fault node indication data is not present in the fault node indication data set, and sets the flag.

A method of fault identification on a semiconductor manufacturing tool includes monitoring tool sensor output, establishing a fingerprint of tool states based on the plurality of sensors outputs, capturing sensor data indicative of fault conditions, building a library of such fault fingerprints, comparing present tool fingerprint with fault fingerprints to identify a fault condition and estimating the effect of such a fault condition on process output. The fault library is constructed by inducing faults in a systematic way or by adding fingerprints of known faults after they occur.

A method for installing software to software-defined radio equipment. The method includes the step of transferring software to one or more software-defined radio devices from a remotely located software server. The software server can be a computer operatively connected to the software-defined radio device via a communications network. The transferring step can occur while the software-defined radio device continues to perform software-defined radio functions. The software can be stored to a portion of a data store associated with the software-defined radio device which is not being used as a storage for currently running software. The software can be loaded on a restart of the software defined device. An error indication can be provided if a fault occurs in the transferring step or the loading step. The method also can include the step of reverting from the selected software to a previous software version upon a fault occurrence.

The present invention provides a control strategy for a parallel hybrid electric vehicle (HEV) configuration where power from the engine and the motor can each independently provide torque to the vehicle powertrain. The invention has a logical structure defining main system operating modes (states) and the transition between the different states. In addition to the predefined states, the present invention provides a set of rules defining logical relationships between each of the plurality of predefined states and a set of commands unique to each state. These commands are supplied to subsystem controllers to achieve desired vehicle functionality. The predefined states can be prioritized according to operator demands, energy management requirements, and system fault occurrences. The present invention can also be configured to have at least one of a plurality of transition flags. Each transition flag represents a logical relationship associated with efficient management of energy, operator demand, or system faults.

The invention discloses a fault positioning method for a power distribution network by combining simulation calculation and real-time monitoring, and belongs to the technical field of fault detection of the power distribution network. The method comprises the following steps of: extracting information of a target power distribution network from the conventional power distribution network geographic information system and a power distribution network energy management system through an organizational data analysis interface to automatically generate a real-time simulation calculation model of the target network; putting forward a virtual node-based fault positioning algorithm according to the simulation calculation model so as to solve functional relation between voltage amplitude of any node and a fault position parameter when a symmetric and asymmetric fault occurs at any point in the target network; and finally calculating an accurate position of the actual fault of the power distribution network by using a small amount of real-time data of voltage drop amplitude in a fault process. By using the fault positioning method for the power distribution network by combining the simulation calculation and the real-time monitoring, the state and the parameter of the network are accurately and effectively reflected when the fault occurs, the accuracy of the fault positioning is improved, and the method is suitable for various network structures and fault types.

The invention discloses a locomotive wheelset bearing fault diagnosis method based on the angular domain-time domain-frequency domain, and belongs to the technical field of bearing testing. The method includes the steps that firstly, collected vibration acceleration signals of locomotive wheelset bearings are analyzed in the time domain and the frequency domain, whether the bearings are in a fault state or not is judged, the specific portions of the faults are judged, angular domain analysis is conducted on vibration acceleration creatively, and quantitative analysis data of the faults are acquired, so that the severity degrees of the faults are grasped, and basic data are provided for further fault monitoring. The analysis method in which the time domain, the frequency domain and the angular domain are combined is adopted, information such as fault occurrence, fault types and fault severity degrees of the bearings can be accurately provided, especially, the angular domain fault diagnosis method is creatively provided, an accurate monitoring mode is provided for the fault development degree, and more abundant reference data are provided for subsequent fault processing.

A method for installing software to software-defined radio equipment. The method includes the step of transferring software to one or more software-defined radio devices from a remotely located software server. The software server can be a computer operatively connected to the software-defined radio device via a communications network. The transferring step can occur while the software-defined radio device continues to perform software-defined radio functions. The software can be stored to a portion of a data store associated with the software-defined radio device which is not being used as a storage for currently running software. The software can be loaded on a restart of the software defined device. An error indication can be provided if a fault occurs in the transferring step or the loading step. The method also can include the step of reverting from the selected software to a previous software version upon a fault occurrence.

The invention relates to a fiber link fault recognition method, a device and a system. The method comprises the following steps: detecting power of one or a plurality of optical network units in real time; when detecting a fault in the fiber link corresponding to a certain optical network unit, extracting at least two upstream optical power values in the fiber link fault occurrence process; and according to the upstream optical power values in the fiber link fault occurrence process, recognizing the fault type of the fiber link corresponding to the optical network unit. The fiber link fault recognition method of the embodiment of the invention detects whether a fault exists in the fiber link corresponding to the optical network unit in real time by detecting the power of the optical network units in real time. When detecting a fault in the fiber link corresponding to the optical network unit, the upstream optical power values in the fiber link fault occurrence process are extracted, and the fault type of the fiber link is recognized in real time according to extracted power values.

A fault management apparatus that enables calculation of evaluation values relating to a fault occurring to a management target as objective values without involvement of human judgment is provided. Fault information containing fault content information showing content of a fault occurring to a process in a production line, and detection status information and action content information associated with the fault is stored in a fault occurrence history storage part as a fault occurrence history. A fault extraction part reads the fault occurrence history from the fault occurrence history storage part to extract fault information containing specific fault content information. An influence degree calculation part calculates a degree of influence showing the degree of influence caused by a specific fault by performing statistical processing based on detection status information and action content information contained in the fault information extracted by the fault extraction part.

Apparatus and method of detecting a fault in a network service includes an Ethernet access network domain in which a heartbeat message is broadcast at a periodic interval by each of a plurality of edge devices associated with an instance of the network service. Each of the edge devices also receives the heartbeat messages broadcast at the periodic interval from other edge devices. A fault occurrence is identified when the edge device fails to receive an expected heartbeat message at the periodic interval from one of the other edge devices.

A low-voltage arc fault detection method comprises collecting current signals in a loop through a current sensor, obtaining fundamental frequency analog signals and high frequency analog signals, achieving accumulating calculation of the fundamental frequency analog signals and high frequency analog signals of power frequency cycle through an integrating circuit, an interrupt trigger and a timer, and further obtaining higher harmonic occupancy. According to the method, whether arc faults occur is judged by real-time monitoring of change characteristics of the line current higher harmonic occupancy and calculation of over-limit times of the higher harmonic occupancy, normal arc and fault arc which are generated by some special electric appliance loads and normal on-off action are distinguished by judging whether higher harmonic occupancy changes caused by the arc faults are periodic and judging occurring frequency, occurrence of the arc faults can be detected in real time, the method is not limited by an installing position, malfunction caused by disturbance of operating arc generated by normal circuit opening and closing and loads such as a switch power and a dust collector can be avoided well, and the reliability is high.

An apparatus for remotely determining a fault of subscriber terminals and a method thereof, and more specifically, an apparatus by which in a passive optical network (PON) system, a central office determines a remote fault of subscriber terminals, and a method thereof are provided. The apparatus for determining a remote fault of subscriber terminals includes: a frequency analysis unit recognizing a fault occurrence of a subscriber terminal from an upstream signal and analyzing the frequency spectrum of the upstream signal; and a fault determination unit selecting a specific frequency corresponding to the shape of the spectrum, determining a diagnosis signal corresponding to the specific frequency, transmitting a message requesting to upward transmit the diagnosis signal to each ONT, finding a peak frequency from the frequency spectrum of the diagnosis signal transmitted by the ONT, determining a fault of the subscriber terminal by comparing the peak frequency with the selected specific frequency.

The invention discloses a rolling bearing probabilistic intelligent fault diagnosis method based on adaptive MRVM. The method comprises the steps that the original fault data of a rolling bearing are measured through an acceleration sensor; a vibration signal is segmented, and wavelet packet energy characteristics are extracted; principal component analysis and dimension reduction are used for normalization simultaneously; a training sample set and a test sample set are processed and divided; an algorithm is used to adaptively select nuclear parameters; the training sample set is used to train and test a multi-class correlation vector machine; and the test result is compared with the actual fault type to acquire the validity of a diagnosis model. According to the invention, the method overcomes the defect that a traditional intelligent fault diagnosis method cannot output the fault probability value; the fault diagnosis accuracy of the rolling bearing is improved; more fault type determining information of the rolling bearing can be provided; through the fault type probability value provided by the invention, the state of the rolling bearing can be further assessed; and method has the advantages of good engineering value and application prospect.

The invention discloses a photovoltaic system fault arc detection method combining multiple detection signals. The method comprises the following steps: carrying out an equal time interval analysis of the multiple detection signals when the signal statuses are not changed; acquiring multiple characteristic values of a current time period based on a characteristic quantity obtained through the photovoltaic system fault arc detection method and the input multiple analysis time period detection signals; acquiring a typical value based on the selected detection signals; constructing correction factors for characteristic values of the next time period based on the typical values and the characteristic values of the detection signals for the current time period and the next time period; and carrying out linear weighting of each constructed correction factor and the corresponding characteristic value of the next time period to obtain a combined characteristic quantity, so as to complete the combined detection of photovoltaic system fault arcs. The method provided by the invention has the advantages that the photovoltaic system fault arc detection working conditions are expanded, the resistance of the photovoltaic system fault arc detection characteristic quantity against external interference is improved, the judgment of the combined characteristic quantity on the time of fault occurrence is more accurate, and a photovoltaic system can run more stably and safely.

A ground fault detector for use in resistance grounded electrical systems. In one embodiment, the system includes a digital processor to monitor an electrical parameter of the resistance to determine and indicate whether a ground fault has occurred. Data regarding the ground fault occurrence can then be digitally stored transmitted, or processed, such as by an external computer. In another embodiment, the ground fault detector includes a filter to remove the harmonic components of the monitored electrical parameter, to avoid false alarms. In addition, in another embodiment, the ground fault detector can also determine whether a high harmonic condition is present in the monitored electrical system. The phase of the electrical system can be grounded by pressing a test switch, thereby causing a ground fault and allowing the harmonic components of the signal in the electrical system to be monitored.

The invention relates to an exploration method of faulted basin slope oil reservoir distribution and belongs to the field of oil exploration technology. In allusion to the later period of faulted basin exploration, through statistics of related information of source rock, fluid potential, sedimentary rock phase and fault in a target area and according to the principle of source potential conduction, the above information is comprehensively analyzed so as to determine a favorable oil reservoir distribution area in the target area. Forward oil control exploration limitations are broken and are shifted to negative structure and positive structure. Comprehensive analysis is carried out according to an oil source, fluid potential, sedimentary facies distribution and fault occurrence in the area, the slope is evaluated, and a favorable exploration target area is selected.

In order to solve the problems of too simple fault management and unavailability of complete vehicle system fault processing strategies of the existing hybrid electric car, the embodiment of the invention provides a fault processing method and a fault processing system of a hybrid electric car. The fault processing method of the hybrid electric car comprises the following steps of detecting current fault types of various parts of the hybrid electric car, and determining fault levels of the parts according to the fault types; performing mapping to obtain fault response levels of the parts according to the fault levels of the parts; determining the highest fault response level of the fault response levels of the parts as the final fault response level; and carrying out corresponding fault processing according to the final fault response level. The fault processing method provided by the embodiment of the invention is more complete, vulnerability in vehicle control when faults occur can be effectively avoided, the potential safety hazard is eliminated, and vehicle dynamic control can be adjusted properly according to specific faults.

The invention discloses a power distribution network line fault on-line monitoring and alarming system. The system includes a fault positioning software system and a power distribution line fault indicator. The fault positioning software system and the power distribution line fault indicator cooperate. The fault positioning software system includes an intrastation grounding line selection apparatus, a communication front-end processor, an injection signal source and an aerial conductor line fault positioning main station monitoring system. The grounding line selection apparatus and the injection signal source serve to perform single phase grounding fault positioning. The power distribution line fault indicator and a data acquisition concentrator are outrastation apparatuses. The data acquisition concentrator and the power distribution fault indicator form a subnetwork. Among the subnetworks, a monitoring system for a line via the intrastation communication front-end processor is constituted. The fault positioning software system and the power distribution line fault indicator communicate by using cascade via radio frequency. According to the invention, with the cooperation between the fault position software system on a fault line selection host computer and the power distribution fault indicator which has communication function on the line, information which indicates the position and time of the fault can be displayed within minutes of the occurrence of the fault on a geographic information system map of a monitoring center, which facilitates maintenance personnel to head to the site of the fault, eliminate the fault and increase reliability of power supply.

In order to rapidly restoration at a time of fault occurrence without lowering usage efficiency of circuit resources, in a configuration in which a plurality of physical circuits are grouped and communication is carried out with transmission data being distributed, a circuit having the minimum traffic from among the grouped circuits is set as a standby circuit, and, a traffic in a fault circuit is transferred to the standby circuit in a lump when a fault occurs in another working circuit.

The invention discloses a method for recognizing an early fault of a bearing based on a long and short-term memory recurrent neural network, which comprises the steps of collecting full life vibrationsignals of the bearing, and then extracting common time domain characteristics; constructing waveform entropy characteristics, and verifying the validity of the waveform entropy according to a squaredemodulation method; building a characteristic data set by using the time domain characteristics and the entropy characteristics, and selecting a normal data set and a deep fault data set; taking thenormal data set and the deep fault data set to serve as training samples to train the LSTM (Long and Short-Term Memory) recurrent neural network; and performing time domain characteristic and entropycharacteristic extraction on an online bearing vibration signal, and then inputting the online bearing vibration signal into the trained LSTM recurrent neural network so as to recognize the fault occurrence time. The traditional characteristics and the entropy characteristics of the vibration signals are combined, so that the current state of the bearing is accurately reflected under the condition of ensuring the physical meaning of the vibration characteristics. The adopted recurrent neural network can effectively apply the degraded historical data so as to perform effective recognition on the fault occurrence time of the bearing.

The invention discloses a method of monitoring faults in sections for an intermittent control system and relates to a fault monitoring method. Firstly, a plurality of batches of collected intermittent process data are standardized in a way of expanding variables, and a data matrix on each sampling time is subjected to principal component analysis; secondly, a fuzzy C-means clustering is a fuzzy clustering analysis method which is suitable for soft partition and is generated through combining a fuzzy set theory and a k-means clustering; and thirdly, after segmentation is finished, an improved MPCA (Multiway Principal Component Analysis) model with a time varying principal element covariance on the basis of expanding variables is established on each subphase, then when on-line monitoring is carried out, which phase a new batch of data belongs to is judged, whether the data exceeds the fault monitoring control limit or not is calculated and judged, if so, a fault occurs, and the fault monitoring in sections ends. According to the invention, process multi-phase partition is more accurate, misinformation and missing report rates in monitoring are reduced, and the practical application and operability are strong.

The invention mainly provides a flight monitoring device for carrying out monitoring on a flight state of an unmanned aerial vehicle. The unmanned aerial vehicle is provided with a detection device for detecting a flight state parameter of the unmanned aerial vehicle. The flight monitoring device comprises a data acquisition module for collecting a detection signal of the detection device, a monitoring module for generating operation state information of the unmanned aerial vehicle based on a pre-stored reference condition and the collected detection signal, and a network communication module for transmitting the operation state information to a third-party server. In addition, the invention also provides an unmanned aerial vehicle including the flight monitoring device, a ground control station and a corresponding flight monitoring method. According to the scheme, a manned aerial vehicle operator can carry out maintenance and real-time fault monitoring on the unmanned aerial vehicle regularly and timely, thereby effectively improving the flight safety factor of the unmanned aerial vehicle and reducing the probability of fault occurrence during the flight process of the unmanned aerial vehicle.

The invention provides a method for high-voltage direct-current transmission commutation failure prevention. The method comprises the following steps that: whether commutation failure caused by alternating current-side faults occurs or not is judged; a commutation failure prevention system outputs rectangular wave commands to a control protection system; and rectangular waves are subtracted from trigger angle commands in the control protection system, and a thyristor is triggered in advance. With the method adopted, commutation failure can be prevented when grounding faults or interphase short-circuit faults occur on an alternating current system, and the reduction amplitude of direct-current voltage and power transmission can be lowered after the faults occur.

The invention discloses a root fault cause analysis method and analysis device relating to the data mining and network management field, solving the problems that in the current root fault cause analysis process, a great deal of manpower and time are used to analyze weblogs, the root fault cause analysis efficiency is relatively low, and the network fault cannot be eliminated timely. The method comprises: determining the fault time point of a network device; obtaining the first log information set generated by the network device in the first time period; wherein the first log information set comprises M kinds of log information; analyzing every kind of log information in the M kinds of log information according to a preset analysis strategy, obtaining N kinds of root cause logs in the M kinds of log information; wherein the root cause logs are log information generated when the network device generates the fault, N is more than or equal to 1 and is less than or equal to M, the preset analyzing strategy is: preset fault generation rule when the network device fault is generated; and determining the cause of generating the network device fault according to the N kinds of root cause logs.

The invention relates to a fault phase selection method based on a current break variable, which belongs to the technical field of fault judgment of a power system and constructs a fault phase selection coefficient by use of the current break variable to realize selection of the fault type and fault phase. The method comprises the following steps of: constructing a fault phase selection coefficient by use of the proportional relationship between the fault current of one phase and the difference between the fault current of other two phases measured by a protection device of a high-voltage line; and then analyzing the different characteristics of the coefficient in various fault conditions to realize fault phase selection of the power system. The method can accurately identify the fault phase within a cyclic wave after the fault occurs, has relatively high sensitivity to various types of faults, is not influenced by the fault position, transition resistance and load current, and has relatively high reliability and good selectivity; and meanwhile, the method has enough sensitivity to the fault phase selection on the weak power side.

The invention discloses a system resource monitoring device based on business variable quantity. The system resource monitoring device comprises a concentrated configuration module, a unified acquisition module, a distributed type analysis module and a historical data archiving module, wherein the concentrated configuration module is used for configuring a monitored host list, an acquired monitoring item, acquisition time, an acquisition format and a corresponding relation of a business module and an SQL (Structured Query Language) sentence; the unified acquisition module is used for acquiring related metadata according to configuration information of the concentrated configuration module and sending the metadata to the distributed type analysis module to carry out real-time analysis; the distributed type analysis module is used for calculating a system resource consumption distribution condition according to an acquired metadata counting business quantity index and a system resource utilization condition, calculating a system resource consumption distribution condition, and combining a business growth trend estimation resource dilatation plan; the historical data archiving module is used for compressing and archiving the metadata, and carrying out offline on the metadata of the earlier part according to configured offline time, and archiving result data to be used for report display and historical trend analysis. According to the system resource monitoring device, the resource consumption is clear, the dilatation and optimization requirements are predictable; the fault occurrence rate and the management cost are greatly reduced and the system stability is improved.