624 results about "Fault probability" patented technology

The invention provides a method for early warning of sensitive client electric energy experience quality under the voltage dip disturbance. The method comprises the steps that based on the S conversion rapid algorithm and an increment SVM classifier, voltage dip disturbances of sensitive clients are automatically identified; based on identification results of the voltage dip disturbances, voltage tolerance curves of devices corresponding to multiple types of sensitive clients at different load levels are determined; historical monitoring data of the voltage dip disturbances serve as samples, the samples are converted into sample values of a voltage dip amplitude ponderance index MSI and a lasting time ponderance index DSI, a probability density function of the MSI and the DSI is determined on the basis of the maximum entropy principle, the sensitive device fault probability is evaluated, and the probabilities of the sensitive devices corresponding to the sensitive clients at the voltage dip level are obtained. By the adoption of the method for early warning of sensitive client electric energy experience quality under the voltage dip disturbance, the electric energy quality disturbance condition can be accurately monitored, whether a client load is influenced by the disturbance or not is determined according to the load sensitivity degree of each client, and potential risks of load operation are found.

Systems and methods for fault prediction are described to reduce equipment failure by effectively monitoring equipment, removing anomalous data, and reducing false alarms. Such systems and methods can be used to receive monitoring data, extract information from the data, and combine extracted information for establishing prediction models. Additionally, fault probabilities may be quantified and faults may be predicted based on the probabilities.

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 controller and a control method of a pure electric vehicle. The controller is realized by using an embedded processor internally provided with an A / D (Analog / Digital) conversion function and a CAN (Controller Area Network) bus conversion function, therefore, an A / D conversion interface circuit in the controller is saved, the CAN bus conversion circuit is simplified, elements in the controller are further reduced, the circuit structure is simplified, the fault probability of the controller can be reduced, and the reliability of the controller is improved. Meanwhile, the invention realizes the control on all CAN bus nodes of the pure electric vehicle based on a CAN bus by using the interrupt service program of a CPU (Central Processing Unit).

The invention discloses a method and a device for analyzing an abnormal state of a spacecraft in the operating process. The method comprises the following steps of: comparing telemeasuring data in a time period to be detected with historical data in a normal state so as to determine an abnormal condition of the telemeasuring data; under the condition that the telemeasuring data is abnormal, according to a correlation coefficient of sequences corresponding to the two groups of data, determining abnormality degree information of corresponding parameters of the telemeasuring data; according to spacecraft design data, establishing an incidence matrix of the corresponding parameters of the telemeasuring data and stand-alone equipment; according to associated data corresponding to the incidence matrix and the abnormality degree information, determining a fault probability of each piece of stand-alone equipment so as to analyze the possibility that the abnormal condition occurs to each piece of stand-alone equipment. The method and the device utilize the telemeasuring data so as to analyze the abnormal condition of the telemeasuring data, and solve the problem that due to shortage of a method for analyzing the abnormal state of the spacecraft in the operating process, a fault part cannot be determined when the spacecraft is abnormal in the operating process.

The invention relates to a power system weak link identification method based on risk evaluation and belongs to the field of power system analysis. The method includes acquiring fault probability of elements of a power system, a future load curve of the power system, states of the elements and load of nodes of the power system; utilizing a minimum load shedding loss optimization model to judge the failure state of the power system and determining the optimum load shedding quantity of each node under each element sampling state; finishing calculation of risk indicators of the power system through repeated sampling and power system failure state judgment; conducting statistics on the weak link characteristic quantity corresponding to faults of generators and an electric transmission and transformation device, calculating five element weakness recognition indicators of the elements according to the risk indicators and the weak link characteristic quantity and finally sorting the recognition indicator values to recognize the weak link of a generator set and the electric transmission and transformation device. By means of the method, the weak link of the power system is improved, large-area power failure of the power system is prevented, and operation safety of the power system is improved.

The invention discloses a power system fault diagnosis method comprehensively using electricity amount and timing sequence information. Firstly, power-off areas before and after a fault are compared and analyzed to determine the fault area, and a suspicious element set is formed; secondly, a weighting fuzzy timing sequence Petri net model is built, and SCADA information, electricity amount information of a WAMS and the timing sequence characteristics included in the information are integrated to form the alarm information criterion, place delay restraints and the electricity amount criterion; a Gaussian function is adopted, the confidence coefficient of alarm information is obtained in combination with timing sequence reasoning, the initial confidence coefficient of the Petri net model is calculated through array calculation, and the model is solved; finally, backward reasoning is carried out according to the fault probability of an element, and protection and judgment of maloperation and motion refusal of a disconnector are carried out. The power system fault diagnosis method is high in fault-tolerant capability, can handle the phenomena of protection and maloperation / motion refusal of the disconnector and the phenomenon that an alarm is lost or wrong, and improves the accuracy and reliability of the fault diagnosis result.

The invention provides a power secondary equipment risk assessment method and a system thereof. By building a calculation model for secondary equipment maintenance state values in advance, the maintenance state values of secondary equipment can be calculated according to the maintenance state parameters of the power secondary equipment. By building a secondary equipment fault probability curve, the maintenance state values are converted into the fault probabilities of the secondary equipment. Then, by building a calculation model for secondary equipment fault loss values, corresponding probable losses caused by all kinds of faults to the secondary equipment are calculated. The products of the fault loss values and the fault probabilities are taken as the risk values of the secondary equipment. Secondary equipment state assessment is closely correlated with risk assessment through the average fault probability of the equipment. The current operation risk of the equipment can be obtained through a state assessment result. Therefore, operators can aim at and well do the operation and maintenance of the equipment according to the calculation results of the risk values, secondary professional operation management can be optimized and objective bases can be provided for equipment type selection and whether the equipment is required to be replaced or not.

The invention discloses a method for evaluating probability of forest fire induced transmission line fault, which belongs to the technical field of power systems and automation thereof. By adopting the method disclosed by the invention, quantitative evaluation on probability of forest fire induced transmission line fault is realized, an accurate line fault probability model is created according to the principle of the forest fire induced transmission line fault, internal and external factors related to the transmission line fault are correctly reflected, the evaluation on the probability of the forest fire induced transmission line fault is not depended on the accumulation of historical data, and key factors can be considered, so that the adaptability is strong. The method disclosed by the invention is used for greatly promoting the risk management of transmission lines and improving the external disaster defense ability of the power systems.

The invention discloses a numerical control generating gear grinding machine, a numerical control device of the generating gear grinding machine and a driving method of the generating gear grinding machine. In the invention, the numerical control device respectively controls a motor to drive a sliding block of a work bench to make rectilinear motion and drive the work bench to make reciprocating circumferential swing, that the motor drives the work bench to make reciprocating circumferential swing by virtue of a multistage mechanical drive mechanism is not needed, thus no mechanical drive error caused by the processing precision and installation precision of the drive part exists in the generating motion of a gear to be processed driven by the sliding block of the work bench and the work bench, and the processing precision of the generating gear grinding machine is further improved; by replacing a great number of mechanical drive mechanisms with the motor, the fault probability of the generating gear grinding machine is greatly reduced.

The invention discloses an oil-immersed transformer fault diagnosis method based on a fault probability distribution model, aiming to provide the probability of various faults of the oil-immersed transformer according to analysis of dissolved gas in oil. The oil-immersed transformer fault diagnosis method includes the steps of collecting massive analysis data of the dissolved gas in the oil of the transformer and normalizing the data, utilizing a Sigmoid function to realize probability output on the basis of a support vector machine, computing according to the collected massive analysis data of the dissolved gas in the oil to acquire optimal parameters of the support vector machine and the Sigmoid function, fusing the probability output of multiple support vector machines into probability output of multi-class problems, and obtaining a diagnosis result by referring to the maximum probability classification and standard deviation. The oil-immersed transformer fault diagnosis method based on the fault probability distribution model has high accuracy without error diagnosis, can be used for processing multiple fault conditions effectively and has high practicability.

The invention discloses a quantitative risk evaluation method for power equipment based on state evaluation. The method comprises that according to statistic data of power equipment, risks of potential faults of different parts in the power equipment are identified by utilizing an influence analysis method; the fault probability of equipment when the risk occurs is predicted, and the health degree of the equipment is obtained via reference state analysis; a relation model between the fault probability and the healthy degree of the equipment is established, and a risk consequence of potential faults of the parts of the power equipment is analyzed; the influential degree of each part on the equipment function is determined; according to the equipment fault probability and risk consequence, a risk value of the potential fault of each part of the power equipment is calculated; and a risk grading model is established, and according to the risk values, risk grades of the potential faults of the parts of the power equipment are determined. According to technical schemes of the invention, accurate technical basis is provide for operation and maintenance of the power equipment.

The invention provides a fault diagnosis method, a fault diagnosis device and a server. The fault diagnosis method comprises the following steps: establishing topology of a network system; obtaining alarm information in a network system; associating the alarm information with nodes in the topology, and determining a fault link; and determining a fault root node in the fault link according to a preset fault probability calculation rule. According to the method, the fault link is determined by associating the alarm information with the topology of the network system, so that the service influence range and degree caused by the alarm can be quickly obtained, the fault root node is determined in the fault link according to the preset rule, the automatic positioning and accurate positioning ofthe fault are realized, and the fault processing efficiency is improved.

The invention provides a self-inspection control method of a robot, the robot and a dispatch server. The self-inspection control method comprises the steps that when a starting instruction or a wakeupinstruction is obtained, all components of the robot are controlled to start self-inspection treatment; when it is confirmed that a self-inspection result of any one component is abnormal, the identification of the component and the abnormal result are sent to the dispatch server; and an abnormal handling instruction issued by the dispatch server is received and executed. According to the self-inspection control method of the robot, after the robot is started or waken up, all the components of the robot are controlled to conduct self-inspection treatment, when the self-inspection result is abnormal, the abnormal handling instruction is received, and abnormal handling is conducted according to the abnormal handling instruction, it is achieved that abnormal detection is conducted before therobot executes a task, the fault probability of the robot in the task execution process is lowered, and therefore the reliability of the robot is improved.

The invention provides a probability forecasting method and \system of switch equipment faults. The method comprises the following steps of: A) carrying out data processing on SF6 gas decomposition product detection data that the switch equipment has faults, and selecting a probability distribution which meets the requirements on relevance as a fault distribution; B) establishing an SF6 gas decomposition product probability model according to the selected fault distribution, and thereby predicting the probability that the switch equipment has faults. The system comprises a data processing module and a data modeling module, wherein the data processing module comprises a data counting module, a parameter estimating module and an error analyzing module; and the data modeling module comprises a fault distribution fitting module and a fault probability estimating module. By adoption of the method and the system, the SF6 gas decomposition product detection data in the equipment are processed, the fault probability of the equipment is predicted by using the established SF6 gas decomposition product probability model, and an effective basis is provided for the state judgment and evaluation, the fault diagnosis and the like for SF6 switch equipment.

The invention discloses a quantitative analyzing method based on a Monte-Carlo simulation solution dynamic fault tree model. The method comprises the steps of establishing the dynamic fault tree model for a system at first, then using assembly fault probability data to carry out fault probability parameter dynamic estimation to serve as input values of dynamic fault tree operation, using a Monte-Carlo method to simulate the dynamic fault tree model and obtaining the fault probability distribution analyzing data and the assembly importance analyzing data of the system according to the simulation solution dynamic fault tree model. The risk analyzing method can effectively estimate risks of complex systems with large state quantity, can obtain the importance analyzing data of system assemblies and can effectively analyze risks of situations with unknown fault rates and situations with changeable fault rates.

The invention discloses an approximate calculation method for a weibull type spare part demanded quantity by means of characteristic numbers. The approximate calculation method mainly comprises the following steps that 1, gamma distribution parameters alpha g and lambda by means of weibull distribution parameters, and normal distribution parameters mu and sigma are calculated; 2, the skewness and kurtosis are calculated, and the skewness and kurtosis of three distribution characteristic numbers are calculated according to the following formula on the basis of the gamma distribution parameters alpha g and lambda and the normal distribution parameters mu and sigma; 3, the skewness and kurtosis of three distribution characteristic numbers are compared, and if the skewness absolute difference between gamma distribution and weibull distribution is small, the spare part fault probability is calculated according to the method; otherwise, the spare part fault probability Ps is calculated according to other methods. According to the approximate calculation method for the spare part demanded quantity, the calculation process can be simplified, and the approximate calculation precision can be improved.

The invention discloses a method for locating faults in a power communication network. The method comprises the steps that a bipartite graph model is built according to the many-to-many uncertainty of faults and symptoms; fault effect weight factors are led in on the basis of the bipartite graph model; the fault effect degree is calculated and corrected through credible parameters to obtain suspected fault sets. According to the method, the many-to-many uncertainty of faults and symptoms is modeled through a weighting bipartite graph, so that the causal relationship between the faults and the symptoms is expressed, the modeling capacity is good, noise immunity is high, and the method can adapt to real environment with fault burstiness and network complexity. The fault effect weight is led in, the total probability and the Bayes thought are utilized under the bipartite graph model, prior fault probability is transformed into condition probability, and the fault effect degree is calculated; finally, credible parameters are added to control effect of suspected faults, the cover degree and the contribution degree are combined, and the suspected fault sets of which the effect degree is within the controllable parameter range are picked out.

The invention discloses a quantification estimation method of oil-paper insulation states of a transformer and relates to the technical field of fault diagnosis of transformers. According to the invention, based on a transformer X model, the complex capacitivity, the complex relative dielectric constant and the change rule of relative frequency of medium loss values of a to-be-tested device are tested; frequency domain dielectric fingerprints which reflect insulation aging states of the transformer are extracted; and according to the frequency domain dielectric fingerprints, the insulation aging states of the transformer are effectively estimated. Thus, effective estimation of the insulation aging states of old transformers is achieved; financial loss caused by change of the transformer isavoided; and fault probability caused by the insulation aging is avoided.

The invention discloses a power grid fault diagnosis method based on temporal Bayesian knowledge base (TBKB). The power grid fault diagnosis method comprises steps of establishing a corresponding temporal Bayesian knowledge base (TBKB) diagnosis model; clearly describing work principles and processes of relevant protectors and circuit breakers after elements are broken down; establishing a temporal causal relationship (TCR) among different action events; quantificationally expressing a successive restraint relationship among different action status nodes in the aspect of timing sequence; and identifying conditions of action events, time mark errors and the like of the abnormal protectors and the abnormal circuit breaks. Uncertain states of nodes and information loss nodes which do not pass TCR examination in alarm information are supposed and combined, so that a supposed state combination gather is formed, the fault probability of every supposed state combination is obtained, the fault probability of suspected fault elements is obtained, and fault elements are diagnosed. The protectors and the circuit breakers which operate mistakenly and fail to operate and the time mark error condition of the protectors and the circuit breakers are detected by forward reasoning of the TBKB modal to the fault elements. The total power grid diagnosis method is fast and accurate and is high in fault tolerance.

The invention relates to a method for calculating the chain fault probability of a parallel power supply system, which comprises the steps of S1, acquiring line operation data from a power grid energy management system (EMS), wherein the line operation data comprises the number of line overload times, the time and occurrence conditions, determining a Poisson distribution function of the overload probability of an ith line by adopting a Monte-Carlo simulation method, and determining a parameter Lambda; S2, acquiring transformer operation data from the power grid EMS, wherein the transformer operation data comprises the number of transformer overload times, the time and occurrence conditions, determining a Poisson distribution function of the overload probability of an ith transformer by adopting the Monte-Carlo simulation method, and determining a parameter Lambda<Ti>; S3, calculating the n times of line chain fault probability of the parallel power supply system with the calculation formula being defined in the description, wherein the n is greater than or equal to 1 and less than or equal to NL; S4, calculating the n times of transformer chain fault probability of the parallel power supply system with the calculation formula being defined in the description, wherein the n is greater than or equal to 1 and less than or equal to NT; and S5, calculating the chain fault probability of the parallel power supply system with the calculation formula being defined in the description. The method provided by the invention can provide necessary technical support for power grid dispatching operations.

A fault location method includes steps: 1, establishing correlation matrix between fault pattern and tested item, 2, optimizing correlation matrix through fault location rate FDR and failure isolation rate FIR, 3, optimizing correlation matrix through maintenance data, 4, when single board gone wrong, according to optimized correlation matrix positioning fault device. Said invention utilizes Bayes' theorem to calculate single board fault probability and determining replacing which device according to probability to realize fault positioning. Said invented method has continuously modification positioning function.

The invention relates to the technical field of keyword query search, in particular to a fuzzy keyword query method and a system based on weighing edit distance. The traditional information retrieval system asks users to provide a precise query word to search a result. The existing fuzzy retrieval system overcomes the shortage and can carry out fault-tolerant search. But the systems do not consider the situation that bigger input fault probability happens between adjacent key characters and shape similar characters when returning results are sorted, thereby greatly lowering user degree of satisfaction. Thus, the invention provides the weighing edit distance to measure the adjacent key characters and the shape similar characters and improves proper weight for the similar matching keyword which conforms to the two situations so as to enable the keyword to rank in the more front position. Based on the weighing edit distance, the search algorithm provided by the invention adopts Trie tree structure and has the characteristics of real time and interaction. The invention can more effectively return data queried truly by users and improves user degree of satisfaction.

The invention discloses a transmission line fault probability assessment method based on historical fault information. According to the method, through system analysis, the line historical fault information is deeply mined, a quantitative method of the influence degree of each factor of line faults is found out, and the fault probability is integrally computed according to the quantitative method and the operation conditions of a to-be-assessed line. The transmission line fault probability is assessed by using the method, not only can a variety of variable influence factors in the line operation be comprehensively considered to ensure the accuracy of an assessment result, but also the requirements of the method for basic data can be reduced to ensure the operability of the method in practical application. According to the transmission line fault probability assessment method based on the historical fault information, the problem that conflict between the accuracy of the assessment result and the operability of an existing assessment method exists in the existing transmission line fault probability assessment method is solved, and the transmission line fault probability assessment method based on the historical fault information is worth of being popularized.

The invention discloses a comprehensive power distribution network fault risk assessment method. According to the method, firstly basic information of a power distribution network is obtained for calculating the value of a basic index; then the index is graded based on a grading standard; a comprehensive fault probability value, a comprehensive fault result value and a fault risk value are calculated according to the weight of the index, the grade of the index and the value of each factor; and finally, the power distribution network is subjected to fault risk grading according to the calculation results and then analysis of weak links of the power distribution network is carried out. Compared with the prior art, the method can comprehensive assess the power distribution network fault power-off risk under influence of many factors, is suitable for evaluation and comparison of power distribution networks in different regions in China, and has a good guidance function for plan and construction of power distribution networks.

The invention discloses a fault diagnosing and repairing method for a washing machine. The fault diagnosing and repairing method includes the steps of monitoring a washing progress, a loading state and a motor operation state of the washing machine in real time; if fault information is detected, judging a fault type according to the motor operation state; repairing the washing machine according to the fault type and the washing progress and the loading state of the washing machine when the washing machine breaks down; judging whether the fault is a hardware fault according to a repair result; if yes, performing fault alarming; if not, continuously operating the washing progress when the washing machine breaks down after repairing. The fault diagnosing and repairing method for the washing machine has the advantages that judgment fault probability can be lowered, and a repair rate of the washing machine can be lowered.

The invention provides a fault prediction method. The method comprises the steps of obtaining target historical fault data of a target object in a first preset time period, wherein the target historical fault data comprises at least one historical fault index and a historical fault probability; wherein each historical fault index in the at least one historical fault index has a corresponding historical index value; and determining a relationship model between the at least one historical fault index and the historical fault probability based on the target historical fault data, obtaining at least one current fault index of the target object, and predicting the fault probability of the target object in a second preset time period based on the at least one current fault index by using the relationship model. The invention further provides a fault prediction device, a computing device and a computer readable storage medium.

The invention provides a method for seeking a weak link of an electric network causing voltage sag, which comprises the following steps: recording voltage sag events and electric network faults; calculating a user voltage sag amplitude expected value and the fault probability of each place; establishing a random analog computation model; performing random analog computation to calculating the user voltage sag amplitude expected value; comparing a computing result and a statistic result; changing fault probabilities of different places, and calculating the voltage sag amplitude expected value; and calculating indexes of the weak link of the electric network, comparing the indexes, and obtaining a result. The method starts from identifying a fault place of the electric network which easily causes the voltage sag events, provides calculation of the indexes of the weak link of the electric network, combines two factors of the fault probability of the electric network and a user voltage sag amplitude caused by the fault, and accurately identifies the fault place of the electric network which easily causes large voltage sag amplitude of the electric network so as to provide priority selection basis for planning and establishment, daily maintenance and technical reformation of the electric network.

The invention relates to a numerical control machine tool system component reliability evaluation method based on cascading fault analysis. The method comprises the following steps that the entire numerical control machine tool system components are divided into multiple subsystems, and a fault transfer directed graph model is established according to the fault transfer relation between all the subsystems; the fault transfer directed graph model is described by using an adjacency matrix; a fault-correlation-based influence degree CK value of each subsystem is calculated; an inherent fault probability function of each subsystem is obtained according to the fault-correlation-based influence degree CK value of each subsystem and a comprehensive fault probability function through calculation; and reliability evaluation is performed on the numerical control machine tool system components by utilizing the inherent fault probability function. The cumulative fault process of the elements of the subsystems is considered by a reliability model, and fault correlation influence degree factors of other subsystem are also integrated so that the reliability model meets the reality further in comparison with the reliability model based on mutually independent assumption between systems.