12 results about "Fault detection and isolation" patented technology

The invention discloses a multi-source autonomous navigation system and method with embedded carrier dynamic characteristics, and the method comprises the steps: building a carrier dynamic model in a dynamic modeling stage; in a filter prediction stage, a Kalman filter driven by dynamics is established, a carrier execution mechanism control signal is periodically read as filter input, and a state vector and a covariance matrix are predicted in each sampling period; a filter updating stage: calculating information of each sensor and a carrier maneuvering strength index, constructing a dynamics consistency judgment quantity, adaptively adjusting an observation variance matrix, updating a filtering state according to observation information of the sensor, and realizing multi-source information fusion; and a fault detection and isolation stage: constructing a multi-source consistency index, and judging the health state of the navigation system. According to the invention, the problem that the performance of a traditional navigation system is reduced when a carrier platform violently moves or is disturbed by external force of the environment is solved, and robust high-precision navigation under GNSS denial, sensor failure or complex dynamic conditions is realized.

The present invention belongs to the technical field of traction battery fault diagnosis. Disclosed are an active isolation method for a fault of a traction battery formation device. In the method, a traction battery formation device state model including an unknown-but-bounded noise and fault is acquired, a space update strategy is designed on the basis of a fully symmetric polytopic set-membership filtering concept, a state observer is constructed, and in this case, it is not necessary to assume that the prior distribution of the noise of the model is known, such that the robustness and practicability of an algorithm are enhanced; a test point is introduced to execute fault detection, the tangency between a state admissible set and a fault set is denoted as a critical condition for the occurrence of the fault, and the critical condition is described as two optimization problems to directly solve the values of auxiliary signals, such that effective isolation for the fault is realized, thereby avoiding the problem complexity caused by auxiliary signals being designed on the basis of performance indicators of an observer in a conventional method; and compared with the conventional method, the method has a higher sensitivity to a tiny fault and can thus avoid delayed detection or missed detection for the fault, thereby improving the efficiency of fault detection and isolation.

A system for real-time fault detection and isolation in a high-voltage transmission network, the system comprising: a plurality of input terminals configured to be connected to instrument transformers associated with at least one transmission line to receive analog voltage signals and analog current signals corresponding to multiple phases of the transmission line; a signal conditioning unit electrically connected to the plurality of input terminals, the signal conditioning unit comprising an isolation arrangement, a programmable gain arrangement, and an anti-aliasing filter arrangement configured to produce conditioned analog signals;a multi-channel analog-to-digital converter unit that is operationally coupled with the signal conditioning unit and configured to simultaneously sample the processed analog signals at a predetermined sampling rate to generate digitized electrical parameter data; a time synchronization unit configured to assign precise timestamps to the digitized electrical parameter data based on a reference time source;a processing unit operationally coupled with the analog-to-digital converter unit and the time synchronization unit, wherein the processing unit is configured to execute instructions for detecting abnormal electrical states by performing signal preprocessing, extracting characteristic features from the digitized electrical parameter data, comparing the extracted features with predefined operating criteria, classifying a detected fault state based on the extracted features, and determining a fault location along the transmission line; and an isolation control unit operationally coupled with the processing unit, configured to generate control signals for actuating at least one switching device to isolate a faulty section of the transmission network in response to the detected fault state.

The application discloses a kind of based on navigation attitude angle's ten table redundant inertial measurement unit gyro fault detection and isolation method, it is related to aerospace technology field, including: at least six groups of independent navigation attitude solution loop are established under the established inertial measurement unit measurement coordinate system, the absolute value of comparison result is obtained by navigation attitude solution loop, it is judged whether the size of each comparison result absolute value is less than the preset threshold value, if all do not exceed the preset threshold value, the solution result of a group of navigation attitude solution loop is used as the attitude angle used by control system;If there is one or more comparison results absolute value exceeds or equal to the preset threshold value, the gyro of fault is isolated, selects a group from the navigation attitude solution loop corresponding to the gyro not isolated as new reference, and the solution result of the navigation attitude solution loop corresponding to new reference is used as the attitude angle used by control system.The application can improve the accuracy of gyro fault monitoring and isolation.

The invention provides an aero-engine fault-tolerant airborne adaptive model modeling method. A component-level model, an adaptive linear variable parameter model and an MIRLS-MAEKF are included. According to the method, the advantage of high precision of a component-level model and the advantage of high real-time performance of a self-adaptive LPV model are combined to establish a mixed structure model as an airborne model, and on the basis of a traditional extended Kalman filter, a covariance matrix is multiplied by a forgetting factor to compensate the adverse effect of an incomplete dynamic equation; mIRLS is improved based on IRLS, and the residual weight is determined by depending on the generalized residual; the MIRLS and the MAEKF are combined, a novel MIRLS-MAEKF is designed, and the novel MIRLS-MAEKF is applied to establishment of an aero-engine fault-tolerant airborne adaptive model. Therefore, the estimation precision and the real-time performance of the airborne model are improved, rapid fault detection and isolation can be realized when a plurality of sensors fail at the same time, the fault tolerance and the estimation precision of the airborne self-adaptive model are improved, and meanwhile, the accurate value of the parameter measured by the faulted sensor is estimated.

The application provides a fault detection and isolation federated filtering fault-tolerant integrated navigation method, according to the number N of fusion sensors required by integrated navigation, N-1 sub-filters and a main filter are constructed to construct a federated filter structure. The observation innovation in each sub-filter system and the corresponding covariance are calculated, a fault detection system of kernel multivariate exponentially weighted moving average control chart is constructed, whether the sub-filter needs to be isolated is judged according to the alarm threshold, i.e. the control limit of the control chart, if the constructed multivariate exponentially weighted moving average statistic is greater than the alarm threshold, a warning is given, and if four of the five consecutive monitored statistics exceed the alarm threshold, the sub-filter is isolated. The method can more accurately and quickly detect the occurrence of faults and isolate the fault sensors in time to improve the fault tolerance of the whole system.

The invention relates to the technical field of navigation systems, and particularly discloses a high-precision navigation system construction method based on five-sensor conical configuration, and the method specifically comprises the following steps: S1, defining a carrier coordinate system and a sensor position matrix; s2, determining the optimal sensor space configuration of the five sensors; and S3, fault detection and isolation of the five sensors. The method has the beneficial effects that by adopting the non-orthogonal conical configuration of the five sensors, the data of the five sensors are mutually fused, so that the error of the whole navigation system is effectively reduced; the sensor fault is detected by using the multi-threshold moving average residual method, so that the misjudgment probability can be reduced while the sensor fault is effectively detected; by constructing the position matrix for the sensor and performing variance analysis, the optimal mounting angle of the sensor is found, and the mounting efficiency and the precision of the navigation system are improved.

The application provides a low-orbit enhanced BDS and INS tight combination navigation fault detection and isolation method, introduces an FDE method based on adaptive maximum correlation entropy robust filtering, constructs a unified BDS / LEO / INS tight combination mathematical model, and studies a rough error detection and elimination method under multi-source heterogeneous observation conditions. Experimental results show that the FDE method can effectively identify and eliminate rough error satellites, significantly improve the system positioning accuracy, and compared with the BDS / INS tight combination system without using FDE, the east, north and sky direction positioning accuracy is improved by 86.56%, 77.12% and 51.80% respectively after introducing FDE; under the enhancement of LEO, the BDS / LEO / INS-FDE system is further improved to 86.95%, 82.60% and 53.94%. In addition, under the environment of low observation satellites, the introduction of LEO satellites significantly improves the satellite geometric configuration and enhances the navigation ability of the system in the case of partial BDS satellite failure, providing an effective theoretical method for continuous and reliable high-precision navigation in complex environments.

The present invention belongs to the technical field of traction battery fault diagnosis. Disclosed are an active isolation method for a fault of a traction battery formation device. In the method, a traction battery formation device state model including an unknown-but-bounded noise and fault is acquired, a space update strategy is designed on the basis of a fully symmetric polytopic set-membership filtering concept, a state observer is constructed, and in this case, it is not necessary to assume that the prior distribution of the noise of the model is known, such that the robustness and practicability of an algorithm are enhanced; a test point is introduced to execute fault detection, the tangency between a state admissible set and a fault set is denoted as a critical condition for the occurrence of the fault, and the critical condition is described as two optimization problems to directly solve the values of auxiliary signals, such that effective isolation for the fault is realized, thereby avoiding the problem complexity caused by auxiliary signals being designed on the basis of performance indicators of an observer in a conventional method; and compared with the conventional method, the method has a higher sensitivity to a tiny fault and can thus avoid delayed detection or missed detection for the fault, thereby improving the efficiency of fault detection and isolation.

This invention relates to the field of navigation system technology, specifically disclosing a method for constructing a high-precision navigation system based on a five-sensor conical configuration. The method includes the following steps: S1, defining the carrier coordinate system and sensor position matrix; S2, determining the optimal spatial configuration of the five sensors; and S3, fault detection and isolation of the five sensors. The beneficial effects of this invention are: by employing a non-orthogonal conical configuration of the five sensors, the data from the five sensors are fused together, effectively reducing the overall navigation system error; by using a multi-threshold moving average residual method to detect sensor faults, the probability of false positives is reduced while effectively detecting sensor faults; and by constructing a position matrix for the sensors and performing variance analysis, the optimal installation angle of the sensors is found, improving installation efficiency and the accuracy of the navigation system.

The invention belongs to the technical field of intelligent detection, and particularly relates to an intelligent power distribution system fault detection and isolation method based on edge calculation. The method is cooperatively executed by an edge node and an edge sink node, and comprises the following three steps: step 1, executing edge node side data construction and graphical preprocessing, setting the edge node at each segment position of the intelligent power distribution system, and forming a switch state table and a controllable switch list corresponding to a graph signal frame; step 2, continuously executing graph wavelet local abnormal focusing processing, BOCPD online confirmation processing and set member estimation processing on one side of the edge aggregation node to form a minimum suspicious segment set; and step 3, executing isolation and power restoration control based on the minimum suspicious segment set. The method has the advantages of being high in detection precision, high in response speed and high in fault tolerance, millisecond autonomous fault isolation and power restoration control can be achieved under the conditions that communication is limited and topology is complex, and the safety, reliability and recovery efficiency of a power distribution system are effectively improved.

The present application belongs to the technical field of intelligent detection, and particularly relates to a method for fault detection and isolation of an intelligent power distribution system based on edge computing. The method is cooperatively executed by edge nodes and edge aggregation nodes, and comprises the following three steps: Step 1, data construction and graphization preprocessing on the edge node side are executed, wherein edge nodes are arranged at each segmented position of the intelligent power distribution system, and a switch state table and a controllable switch list corresponding to a graph signal frame are formed; Step 2, graph wavelet local anomaly focusing processing, BOCPD online confirmation processing and set member estimation processing are continuously executed on the edge aggregation node side to form a minimum suspicious segment set; and Step 3, isolation and power restoration control based on the minimum suspicious segment set is executed. The present application has the characteristics of high detection accuracy, fast response speed and strong fault tolerance, and can realize millisecond-level autonomous fault isolation and power restoration control under the conditions of limited communication and complex topology, thereby effectively improving the safety, reliability and recovery efficiency of the power distribution system.