1511 results about "Failure data" patented technology

By using monitoring data, feedback data, and pooling of failure data from a plurality of electronic devices, real-time failure prediction and diagnoses of electronic systems operating in a network environment can be achieved. First, the diagnostic system requests data on the state of a machine and / or its components and collections thereof as part of the machine's normal operation. Secondly, real-time processing of the data either at the machine site or elsewhere in the distributed network allows for predicting or diagnosing system failures. Having determined and / or predicted a system failure, a communication to one or more remote observers in the network allows the remote observers to view the diagnostic information and / or required action to repair the failure. Furthermore, interrogation of either the particular electronic system, or a database containing data on similar electronic systems by the diagnostic server allows the diagnostic server to refine original diagnoses based on this population data to achieve a comprehensive failure predication / diagnosing system.

A method and method that builds accurate operational profiles for COTS software. The systems and methods disclosed allow software vendors to detect misused and unused features; identify common machine configurations for a given piece of software or software component; monitor changing user habits as new software version are released; derive more accurate testing methods for in-house testing purposes; and create user manuals which focus on those features most frequently used, or misused, by users. The disclosed system and method provides the tools enabling a software certification laboratory (SCL) to gather detailed usage data and failure data for a software application as it is used in the field. With this data the SCL can confidently issue certificates of reliability for software products.

A system, method, and computer program product assist a technician in troubleshooting an aircraft auxiliary power unit (APU). A portable computer is couplable of download the fault data captured in a memory of the ECU. The fault data corresponds to one or more instances of APU failure. The computer is further programmed to compare the fault data to predetermined fault patterns stored in a database. Each record of the database has one of the fault patterns, a corresponding fault indication, and a corresponding service recommendation indication. The computer is further programmed so that when a record in which the fault pattern matches the fault data is found, the corresponding fault indication and service recommendation are retrieved from the database and provided to the technician via the computer's display or other suitable output mechanism.

An apparatus, system, and method are disclosed for detecting and replacing failed data storage. A read module reads data from an array of memory devices. The array includes two or more memory devices and one or more extra memory devices storing parity information from the memory devices. An ECC module determines, using an error correcting code (“ECC”), if one or more errors exist in tested data and if the errors are correctable using the ECC. The tested data includes data read by the read module. An isolation module selects a memory device in response to the ECC module determining that errors exists in the data read by the read module and that the errors are uncorrectable using the ECC. The isolation module also replaces data read from the selected memory device with replacement data and available data wherein the tested data includes the available data combined with the replacement data.

The present invention discloses devices Including a transparent client-connection manager for exchanging client data between an application server and the device: a request analyzer for analyzing query requests from at least one application server; a data-retrieval / command-execution module for executing query requests; a database connection manager for exchanging database data between at least one database server and the device: a cache-memory pool for storing data items from at least one database server: a cache-policy module for determining cache criteria for storing the data Items In the cache-memory pool; and a data-consistency invalidation module for determining invalidated data Items based on invalidation criteria for removing from the cache-memory pool. The cache-memory pool Is configured to utilize memory modules residing in data proxy devices and distributed cache management utility, enabling the memory capacity to be used as a cluster to balance workloads.

System and method for collecting and using vehicle data. Crash data is received from a plurality of vehicle monitoring devices and added to a crash data database. The database is updated with additional information gathered from specific crashes. The crash data is correlated based upon a vehicle type parameter. Crash data parameters associated with one or more injury severity thresholds are identified. Alternatively, crash data parameters associated with one or more vehicle damage severity thresholds are identified. Injury and property damage estimates for subsequent crashes are made based upon the information collected in the crash database.

A data storage device (DSD) tester is disclosed for testing a DSD. The DSD tester comprises control circuitry operable to receive production line data through an interface, wherein the production line data is related to the DSD. The control circuitry executes a DSD test on the DSD, and transmits failure data generated by the DSD test and the production line data to a failure information database.

A system and method is provided for monitoring the operating condition of a pump by evaluating fault data encoded in the instantaneous current of the motor driving the pump. The data is converted to a frequency spectrum which is analyzed to create a fault signature having fault attributes relating to various fault conditions associated with the pump. The fault signature is then input to a neural network that operates in conjunction with a preprocessing and post processing module to perform decisions and output those decisions to a user interface. A stand alone module is also provided that includes an adaptive preprocessing module, a one-shot unsupervised neural network and a fuzzy based expert system to provide a decision making module that operates with limited human supervision.

A structure and method for an integrated circuit which includes read / write memory having a plurality of memory devices, each of the memory devices having a unique address; a built-in self-test (BIST) engine, the BIST engine having a controller responsive to a test enable signal and operative to generate and store test data in the read / write memory; a comparator operative to compare retrieved data read from the read / write memory and the test data during a first pass test, the comparator identifying failed cycles where the retrieved data does not correspond correctly to the test data; and a diagnostic unit operative to store the failed cycles and being responsive to the controller generating and storing the test data in the read / write memory and operative to store failed data and failing addresses during a first pass test, wherein the BIST engine stops only at each of the failed cycles during the first pass test.

Managing a content management system. The content management system is one that is configured and controlled to establish a connection between a client and a library server, generate a transaction identifier and insert, a record for the transaction in a tracking table associated with the library server, pass transaction data from the client to a resource manager, process the transaction at the resource manager and record transaction data in a tracking table associated with the resource manager. The resource manager returns transaction success / failure data to the client, compares activity recorded in the tracking tables, and takes corrective action based upon the activity comparison.

The invention discloses an intelligent fault classification and location method for an ultra-high voltage direct current transmission line, and belongs to the technical field of relay protection of power systems. The method comprises the following steps of: classifying fault data by using a neural network by adopting a layered and distributed neural network model; distinguishing fault types; sending the classified data into different neural networks respectively for performing fault location; when the direct current transmission line has a fault and a sampling frequency is 10 kHz, selecting a discrete line mode voltage signal which has the sampling sequence length of 100 after the fault and performing S-transform, wherein a transform result is a complex time-frequency matrix of 51*100; solving the modulus of each element in the complex matrix to obtain transient energy distribution of the line mode voltage at all frequencies; selecting first five energy spectrums as sample properties; selecting a transfer function and a learning rule; setting proper neural network parameters for constructing a BP network model; and performing fault classification and fault location. A large number of simulation results show that the method has a good effect.

A system for automated fault analysis and execution of post-flight or pre-flight tests for an aircraft is provided. The system includes a maintenance test client system onboard the aircraft, and a ground-based maintenance test server system that is remote from the aircraft. The maintenance test client system is configured to collect fault data for the aircraft, and to wirelessly transmit the fault data to the ground-based maintenance test server system after the aircraft has landed. The ground-based maintenance test server system is configured to receive the fault data, to generate a test checklist that is influenced by the fault data, and to transmit the test checklist to the maintenance test client system. The maintenance test client system wirelessly receives the test checklist, and initiates execution of at least one test specified in the test checklist.

Provided is an intelligent ammeter fault real time prediction method based on a decision-making tree, comprising the steps of: 1, pre-processing intelligent ammeter data of an electricity information acquisition system; 2, according to an intelligent ammeter fault determination model, screening the fault data of intelligent ammeters in the electricity information acquisition system and sending the fault data into an intelligent ammeter fault database; 3, dividing the historic data in the intelligent ammeter fault database into a training set and a test set, employing a decision-making tree algorithm to perform data excavation on the training set, and forming an intelligent ammeter fault decision-making tree and a preliminary classification rule; 4, through the data of the test set, performing accuracy assessment on the preliminary classification rule, determining the preliminary classification rule if the accuracy meets requirements, or else returning to the training set for training again; 5, generating an intelligent ammeter fault real time prediction model according to a finally determined classification rule; and 6, linking an intelligent ammeter real time fault database to the intelligent ammeter fault real time prediction model for real time prediction to obtain intelligent ammeter fault real time prediction results.

The invention discloses an embedded real-time emulation and fault simulation system based on multiple data buses, comprising upper computer simulation management software and an embedded real-time emulation and fault simulation device. The upper computer simulation management software guides the user to perform emulation configuration and fault setting aiming at a fault-tolerant control system to be tested through a human-computer interface, and generates fault emulation data of multiple redundancy equipment. The embedded real-time emulation and fault simulation device outputs the fault emulation data in real-time and synchronously through the multiple data buses, simulates the fault of the multiple redundancy equipment and outputs the fault data stream. The upper computer and a lower computer communicate mutually through an Ethernet to achieve the downloading of the information configuration, the fault emulation data and the emulation control command of the upper computer, and the uploading of the working condition of the lower computer. The invention overcomes the defects of poor universality and lower synchronous precision of the traditional multiple equipment fault simulation device based on the emulation, and is suitable for the test and the verification of the different redundancy fault-tolerant designs of the complex spacecraft system with numerous equipment and frequent data exchange.

A system (100) for analyzing a fault includes a fault object factory (110) constructed and arranged to receive fault data and create a fault object (112), and a fault diagnosis engine (101) constructed and arranged to perform root cause analysis of the fault object. The system may further include a fault detector (130) constructed and arranged to detect the fault data in a monitored entity, a fault repository (140) constructed and arranged to store and access the fault object; and a fault handler (150) constructed and arranged to be triggered by the fault diagnosis engine to analyze the fault object.

The invention provides a fault diagnosis server, a method, a device and a system for detecting and diagnosing vehicle faults. The device for detecting and diagnosing vehicle faults comprises a fault information acquisition unit, a fault information generation unit, a fault information transmitting unit, a diagnosis information receiving unit and an information output unit, wherein the fault information acquisition unit is used for acquiring original vehicle fault data from a vehicle-mounted on-line diagnosis system; the fault information generation unit is used for generating fault information after analyzing the original fault data; the fault information transmitting unit is used for transmitting the fault information to the background fault diagnosis server; the diagnosis information receiving unit is used for receiving fault diagnosis information which is fed back by the background fault diagnosis server; and the information output unit is used for outputting the fault information and / or the fault diagnosis information. Through the invention, a user can conveniently receive diagnosis information provided by a 4S shop according to fault information in time, thereby solving vehicle faults.

User input defines transmission filter rules to be met when sending an error report to a support provider. User input also defines collection filter rules to be met when including failure data within an error report. Error reports corresponding to crash failures at clients are filtered with the transmission filter rules to determine which of the error reports to send to the support provider, and each error report to be sent to the support provider is further filtered to remove any failure data that fails to satisfy the collection filter rules. Each error report that satisfies the transmission filter rules, along with the failure data satisfying the collection filter rules, is sent to the support provider for analysis. Standard and or custom failure responses corresponding to the failures at the clients may be retrieved and sent to the clients in accordance with the collection filter rules.

An analysis scheduler for scheduling the automatic processing of performance data through a plurality of analysis tools is disclosed. Performance data provided to some of the tools by the analysis scheduler may be specified to be within a predetermined (but variable) look-back period. The analysis tools identify faults and anomalous conditions and also create repair recommendations, and automatically create problem cases when conditions warrant, or update existing problem cases with additional data, all under control of the analysis scheduler. The problem cases are reviewed by a human user and then forwarded to the railroad for implementation.

The invention provides a transformer substation remote monitoring system and method. All indexes of a transformer substation can be monitored online in real time, wherein the indexes include all monitoring data in a transformer, a breaker and an arrester; when a certain index of the transformer substation becomes abnormal, an alarm sound can be sent out in time, failure data and failure devices are displayed on a display screen of a monitoring module, workers are reminded, the data monitoring accuracy and timeliness are improved, and the data transmitting safety and reliability are improved. Meanwhile, the monitoring data of the transformer substation are analyzed and processed in real time at a remote monitoring center, failure reasons and failure sources are found, a maintenance reference scheme is generated, and maintainers of the transformer substation are guided to remove failures in time. In addition, the maintenance records of routing inspection personnel can be recorded, monitored and fed back in time, and the routing inspection personnel are reminded to complete conventional maintenance in time.

A network management system (10) includes a fault diagnosis system (12) connectable to a communications network (20). The fault diagnosis system includes a fault object factory, a path determination module, and a fault diagnosis engine. The fault object factory is constructed and arranged to receive fault data and create fault objects. The path determination module is constructed to determine, in a communications network, a path related to the fault data. The fault diagnosis engine is constructed to perform, using the determined path, a fault analysis on the fault data to diagnose a fault related to the communications network. The network management may also include a help desk system (18), a topology mapper (14) or an impact analyzer (16).

A method for automatically optimizing a neighbor list for processing handover in an asynchronous WCDMA (Wide-band Code Division Multiple Access) network includes the steps of: collecting neighbor list data, call fault data, handover statistical data, base station location data and PSC information data of each base station sub-cell (or, sector) in a nationwide network; extracting all target sub-cells (or, sectors) available for handover by analyzing the collected data; endowing a weighting factor to the extracted target sub-cells (or, sectors) according to importance and then sorting calculated results so as to determine priorities; and subsequently inputting the target sub-cell (or, sector) information to the neighbor list according to the priorities.

The invention discloses a comprehensive test method of a small satellite power subsystem. In the method, a solar cell array is replaced by a solar matrix simulator; a ground wired test and control platform of a satellite comprehensive test system is used to transmit wired instructions and collect important parameters; and ground test and control equipment, a remote measurement and control front end and a test computer are used to transmit remote control instructions and collect remote test data. After the satellite is electrified, the on operation time, off operation time and remote control command transmission time of the solar matrix simulator are reasonably controlled, the working state of a power subsystem is set, various parameters and states are monitored and interpreted, and thus, various test items are accomplished. In addition, a method of injecting normal or fault data blocks and program blocks is adopted to test the up injection function, reliability and fault tolerance are tested. The method has high test coverage, clear and definite flow, simple and reliable operation and convenient construction.

The invention provides an intelligent high-voltage management system of an electric car. According to the intelligent high-voltage management system of the electric car, a signal collecting system collects the car operation state, failure detection object state and car posture state in real time; an intelligent high-voltage control unit receives an instruction of a vehicle control unit (VCU) and / or a battery management system (BMS), enables a high-voltage electricity distribution system to normally distribute electricity to vehicle high-voltage equipment and feeds back the execution result to the VCU and / or the BMS; meanwhile, fault diagnosis and detection are carried out on the high-voltage electricity distribution system according to collected data and received vehicle real-time interaction data; the fault type is determined according to a preset fault database, the high-voltage electricity distribution system is made to execute the high-voltage electricity on-off control logic under the preset fault types, and the diagnosis result is stored and sent; the high-voltage electricity distribution system caries out high-voltage electricity distribution, high-voltage electricity on / off control, circuit overcurrent protection and high-voltage pre-charging on all high-voltage devices of the car according to the instruction of the intelligent high-voltage control unit. The intelligent high-voltage management system of the electric car realizes intelligent management of high-voltage electricity of the whole car, and better improves the high-voltage safety of the electric car.

Test result data can be classified across multiple tests, test scenarios, and lab runs. Test result files can be parsed by extracting information from them. Extracted information can be compared to failure information in a database. If a match is found, the extracted information can be linked to the failure, creating a history for each failure. New failures can be identified when no match is found. Failure data can be cross-referenced to further aid in results analysis. For each failure, lists of useful information can be accessed. Analysis information can be associated with failures, for example whether the failure is new, occurred previously, is for a different reason than expected, or has been added to a baseline of expected failures. A Graphic User Interface (“GUI”) is also provided to expose the analyzed results to the result analyzers.

A power system fault diagnostic method belongs to the power system dispatch and fault analysis domain, comprising: step 1 of downloading the fault data base of the power system to process to form a rule base; step 2 of collecting the voltage of the power system, current, the on off state signal of the breaker and the action signal of the relaying protection using the collecting device; step 3 of performing on-line fault diagnosis; step 4 of uploading the fault information to the host computer of the device and on-line adding the fault. The prior data collecting device, the mature technique and the outlying theoretical knowledge are combined together. The modified general rough intensivism contracted calculation can solve the problem that it is incapable for diagnosing or accurately diagnosing due to information deletion when the large scale chain fault generates. Especially the method can solves the fault diagnosis under 'avalanche data' which can not be solved by conventional method and ensure the system safely and stably run under each condition.

Disclosed herein is data replication and recovery method in an asymmetric clustered distributed file system, which divides the storage space of a data server into main partitions and sub-partitions, and separately manages main chunks and sub-chunks in the main partitions and the sub-partitions, thus efficiently processing chunk replication and recovery. In the disclosed method, when a failure occurs in a data server in an asymmetric clustered distributed file system, a failed partition is reported to all data servers including other partitions of a volume to which the partitions of the failed data server belong. Accordingly, other data servers can simultaneously perform the recovery of chunks using the information of their own main chunks and sub-chunks. As a result, when a failure occurs in a data server, all related data servers can simultaneously participate in data recovery, thus more promptly and efficiently coping with the failure.

The invention relates to an intelligent gearbox fault diagnosis method based on mixed inference and neural network, mainly comprising the following steps: enriching a knowledge base of an intelligent diagnosis system; storing expert knowledge into a computer; combining the neural network to recognize patterns; analyzing a main abnormal phenomenon of a gearbox; systematically researching generation mechanisms of vibration and noise of a gear; analyzing a mathematical model of gear vibration; analyzing the vibration mechanisms of various fault types by fully using on-site fault data; enriching time domain and frequency domain characteristics of various faults; and ensuring a characteristic extraction method of gear fault signals. A data analysis method mainly comprises the steps: band-pass filter frequency analysis, double-meaning analysis, envelope demodulation analysis and demodulation analysis based on EMD. The intelligent gearbox fault diagnosis method based on mixed inference and neural network solves the problems of the traditional serial information processing in the fields of pattern recognition, artificial intelligence, and the like so that a pattern recognition network is completely realized by the computer; and the intelligent gearbox fault diagnosis method based on mixed inference and neural network is convenient to realize the automation and the intelligence of the fault diagnosis and can provide a basis for a diagnosis decision in time.

The present invention provides a disk fault processing method in a disk array system and a data reconstruction method, including: the disk of the disk array generates read-write faults; the fault data block is located, the residual correction data of the fault disk is retained, the fault information table is checked, the strip of the faulty data block whether existing other fault data blocks or not is judged, if yes, the disk array system is provided to a ''read-only mode'', forbidding user execute write operation, if not, the position information of the fault data block is recorded in the fault information table, then whether a redundancy data disk existing in the disk array system or not is judged, if not, entering in the ''degradation'' operation mode, otherwise, the fault data block is processed with data reconstruction, recovering the fault data.

An equipment fault diagnosis method successively comprises fault diagnosis training steps and fault diagnosis operation steps. The method focuses on a data form characteristic essence and combines a multi-dimensional segmentation fitting algorithm and an optimized dynamic time warping algorithm based on equipment fault data to carry out pattern expression of modeling and distance threshold extraction, and extract form characteristics from the found equipment abnormity data to carry out mode matching, so that an equipment data fault type can be identified and a reason diagnosis function is realized. In this way, the difficulties in current fault diagnosis technologies that similarity degrees among the fault data can hardly be described efficiently and accurately can be solved.