30results about How to "Improve failure analysis efficiency" patented technology

The invention discloses a fault diagnosis method and fault diagnosis equipment. The method comprises the following steps of: acquiring network data; acquiring the network element data of network element equipment according to a pre-stored case script program when the network data determines that the network element equipment has a fault; and determining fault information according to the network element data and the pre-stored case script program. In an embodiment of the invention, a key performance indicator (KPI) intelligent diagnosis tool determines the fault information according to the pre-stored case script program and the network element data acquired from the network element equipment, can realize the real-time monitoring of the KPI of a radio access network (RAN) system, and can improve the efficiency of the equipment fault analysis of the RAN system.

The embodiment of the invention discloses a power grid image recognition system based on a neural network. The system comprises a data set generation module for artificial neural network training, anartificial neural network training module, an artificial neural network reasoning prediction module and a man-machine interaction module, the data set generation module for artificial neural network training preprocesses example image data used for training an artificial neural network and creates an image data set. The artificial neural network training module takes an image data set as input; outputting an artificial neural network classifier; the artificial neural network reasoning prediction module takes an original data image as an input; and the artificial neural network classifier carries out batch automatic reasoning prediction on the category represented by each image, a category identifier corresponding to each image is output, a to-be-analyzed original data image is input intothe human-computer interaction interface, and a power grid fault is processed according to an analysis output result. The method solves the problems that an existing power system is low in fault analysis efficiency and long in processing period.

The invention discloses a fault analysis method and device, computing equipment and a computer storage medium. The fault analysis method comprises the steps of obtaining fault information of an information system; processing the fault information by using a word frequency dictionary and an N-Gram algorithm to obtain a fault feature word set; based on the fault feature words in the fault feature word set, establishing a fuzzy fault Petri network model of an information system operation process containing the fault feature words; and performing fault analysis processing on the information systemby using the fuzzy fault Petri network model to obtain a fault analysis result. Based on the scheme, feature words are extracted from fault information, the extracted feature words are used for faultanalysis, the fault analysis efficiency is improved, the manual screening time of information system faults is greatly shortened, the established fuzzy fault Petri network model is used for fault analysis, and the effectiveness and accuracy of fault recognition are improved. In addition, fault redundancy alarm is reduced, and the fault recognition rate is increased.

The invention provides a sample preparation method and sample preparation equipment for chip failure analysis. The method comprises the following steps of: removing the back surface of a chip to be processed until a processed chip exposing the back surface of a bare chip in the chip to be processed and the cross section of a chip lead is obtained, and fixing the front surface of the processed chip on a fixing plate; and electrically connecting the cross section of the chip lead with the analysis circuit board through the target wire by adopting a preset wire welding machine based on the configured wire welding debugging parameters. According to the method, the defect that failure analysis of multi-welding-spot power-up cannot be carried out on the failure chip in the prior art is overcome, and meanwhile, the failure analysis efficiency is improved.

The invention discloses a data analysis method and apparatus of urban rail signal equipment. The method includes: receiving a to-be-inquired system identifier and a fault keyword corresponding to the system identifier input by a user; obtaining log data of all the urban rail signal equipment in the system in a preset period according to the system identifier; matching the data format of each piece of log data with the data format of a data format dynamic database, and determining the data types of the log data; selecting a network protocol corresponding to the data type according to each data type, and sending the log data of the data type to an analysis module of a simulation MSS server; and analyzing all the log data by the analysis module, and screening fault information corresponding to the fault keyword from the analyzed log data for display. According to the method, the search of problems is facilitated, the fault analysis efficiency is improved, and the cost is reduced.

The invention discloses an algebraic persistence fault analysis method and device for block ciphers, comprising: injecting faults into block ciphers to obtain target ciphers containing faults; inputting random plaintext into the target ciphers to obtain fault ciphertexts; Described fault ciphertext, obtain fault value According to described fault value, construct the encryption algebraic equation of reciprocal r rounds for each described fault ciphertext, and add corresponding key constraint algebraic equation for described encryption algebraic equation; Solve the above encryption algebraic equation to obtain the encryption master key. The method combines persistent fault analysis and algebraic analysis, takes advantage of both, and minimizes the number of fault ciphertexts required to recover keys.

The invention is applicable to the technical field of clouds, and provides a construction and evaluation method of a fault model based on an SVM (Support Vector Machine). The method comprises the following steps: selecting a radial basis function RBF to construct a cloud fault prediction model of the support vector machine SVM; training the support vector machine SVM based on a given cloud sampletraining set, wherein the training process is specifically as follows: based on the support vector machine SVM, converting cloud fault prediction into quadratic programming with a constraint condition; building a decision function based on the solution of the quadratic programming, wherein the decision function is a hyperplane; and performing fault evaluation on a test sample point based on the hyperplane. Compared with a BP model and an LVQ (Learning Vector Quantization) model, an SVM model can find a global optimal solution, avoid the curse of dimensionality, and improve the convergence speed rapidly at the same time; and in addition, the embodiment of the invention selects the radial basis function RBF to construct the cloud fault prediction model of the support vector machine SVM, therefore, the complexity of model construction can be reduced and the fault analysis efficiency can be improved while the accuracy is satisfied.

The invention relates to an HBase fault prediction method, system and device based on a decision function model and a medium, and belongs to the technical field of distributed storage, and the method comprises the steps: collecting monitoring item data of HBase in various fault scenes, classifying the monitoring item data according to each fault scene, and determining a plurality of monitoring items corresponding to each fault scene; based on the plurality of monitoring items corresponding to each fault scene, a decision function model corresponding to each fault scene is established, and a prediction conclusion of each decision function model is associated with a threshold range of the plurality of monitoring items corresponding to each fault scene; and obtaining the value of each monitoring item in the HBase environment, correspondingly inputting the values of the plurality of monitoring items corresponding to each fault scene into the decision function model corresponding to each fault scene, and obtaining a prediction conclusion corresponding to each fault scene. According to the method, automatic analysis of fault conclusions is realized, fault analysis efficiency is improved, faults can be classified and processed, and accuracy of prediction results is improved at the same time.

The invention discloses a motor state acquisition device, and the device comprises a probe and a controller; the probe is arranged corresponding to a gear of a motor; the probe is connected with the controller, and the controller is used for determining position change parameters of an identification part of the gear according to at least two detection parameters and determining running state information of the motor according to the position change parameters; at least two detection parameters are obtained by detecting the state of the gear at different moments by the probe. The invention also discloses a motor state acquisition method, projection equipment and a computer readable storage medium. According to the invention, the operation state of the packaging motor is effectively obtained, and the fault analysis efficiency of equipment is improved.

The invention relates to a portable telemetry data monitoring platform and a monitoring method. The monitoring platform includes two parts: a sending end and a ground receiving end. The sending end includes sensors, converters, encoders, transmitters and other equipment to complete data collection, encoding and transmission; The receiving end includes a receiver, a data processing module, a recording module and a display module, and completes the receiving, recording, parsing, smoothing processing and interface display of telemetry data. The monitoring method of the present invention is implemented by the software of the data monitoring platform, which simplifies the hardware structure and improves the portability and flexibility of the system; the improved Garrote threshold wavelet method is used for data smoothing, which greatly reduces the impact of errors and makes The data measurement value is closer to the real value, and is displayed through a combination of text interface and curve interface, so that ground monitoring personnel can grasp the operating status of the aircraft more intuitively and accurately, and improve the efficiency of system maintenance and failure analysis.

The invention discloses a fault judgment system with an auxiliary analysis function, and the system comprises: a collection subsystem which collects the operation data of equipment; a fault diagnosis subsystem which is used for judging whether the equipment has a fault or not based on the operation data acquired by the acquisition subsystem, and generating a corresponding fault name based on a generated fault type; and a fault analysis subsystem which outputs a fault maintenance scheme corresponding to the fault name based on the fault name generated by the fault diagnosis subsystem. The fault judgment system provided by the invention not only can diagnose the fault reason of the equipment on line, but also can provide a corresponding maintenance processing scheme and related data according to the fault reason, so that the fault analysis efficiency of equipment operation and maintenance personnel is effectively improved.

The present invention provides a test structure and a manufacturing method thereof. The method includes the following steps: 1) providing a sample to be tested, wherein at least one first metal pad is discretely arranged on the surface of the sample to be tested; the first metal pad A circuit structure is formed below; 2) At least one metal pad component connected to the first metal pad is formed discretely on the free area of ​​the surface of the sample to be tested to obtain a test structure. The present invention forms an additional metal pad assembly on the basis of the original metal pad in the test sample, wherein the metal pad assembly is formed in the free area of ​​the test sample and will not affect the test sample; the metal pad assembly can be used for wire bonding in the failure analysis stage Access to electrical signals avoids device damage caused by repeated bonding or cracks of the device under the first metal pad, which is conducive to improving the efficiency of failure analysis; and both gold wire bonding and aluminum wire bonding can be used to reduce costs .

The present invention provides a fault analysis method and device for a communication link. The method includes: obtaining a network topology, and using the network topology to determine a chain object and a ring object; when an interruption alarm is obtained, obtaining the interruption location where the type alarm occurs; if the interruption type alarm occurs on the network element device, when the communication link between the source network element device and the destination network element device passes through the link object, it is judged whether the link object contains the network element device. element device; if yes, determine that the communication link between the source network element device and the destination network element device has been interrupted. Through the technical solution of the present invention, the workload of manual analysis is reduced, the time for failure analysis is reduced, the service of the user is restored as soon as possible, and the user experience is improved. It can quickly analyze a batch of communication link faults, improve the efficiency of fault analysis, and reduce the pressure on the system caused by fault analysis. It is possible to analyze only the communication link that may have a fault, thereby improving the accuracy of the analysis.

The present invention discloses a bearing installation monitoring system for a pump valve. The system comprises an adjusting base, a sleeve base and clamping bases, the sleeve base is arranged on oneside of the adjusting base, a first sleeve groove is formed in the inner side of the adjusting base and the inner side of the sleeve base, and the two clamping bases are arranged in one end of the first sleeve groove in a sleeved mode; according to the invention, the positions of the pump valve bearings in three directions are sensed by the phase sensors which are arranged at an angle of 120 degrees, when measurement data is the same or is within an allowable error range, the installation positions of the pump valve bearings are accurate, when the measurement data exceeds the allowable error range, the pump valve bearings are required to be reinstalled to rapidly and conveniently monitor the installation positions of the pump valve bearings, timely obtain monitoring information and avoid the problems occurring in the installation of the pump valve bearings, the bearing installation monitoring device can monitor installation, temperature and vibration of the pump valve bearings, guarantees mutual noninterference through the structural design of the device when monitoring the installation, temperature and vibration of the pump valve bearings, and can quickly, normally and conveniently complete monitoring of the pump valve bearing.

The invention provides a test method on failure analysis of a storage cell, which comprises the steps of defining an internal storage region, in which the number and the position of internal storage cells correspond to storage cells on a chip; pressurizing the storage cells in the adjustable value range and measuring the storage cells to obtain threshold voltages of the storage cells, storing step value information related to the threshold voltage into an internal storage position which corresponds to the internal storage region until threshold voltages of all storage cells can be tested; reading out the step value information related to the threshold voltages in the internal storage region to generate a data file; and analyzing the data file to obtain information of the threshold voltages corresponding to the storage cell position, and calculating the information of threshold voltage distribution of a whole storage chip at the same time. The method can be used for accurately positioning the failure point of the threshold voltage, so as to improve the test efficiency.

The invention relates to a message middleware fault positioning method, device and equipment and a computer medium, and the method comprises the steps: creating a detector packaging class according to a preset detection method of each node in an asynchronous link; analyzing the preset configuration file to obtain a path of a physical configuration file of the message producer; according to the path of the physical configuration file, the physical configuration file is read, the physical configuration file is analyzed to obtain the service name of a message producer and the IP information of the message production equipment, and the message producer is deployed in the message production equipment; obtaining a log and a message file of the message producer according to the service name of the message producer and the IP information of the message production equipment, and instantiating a detector packaging class according to the log and the message file of the message producer; and executing the instantiation object of the detector packaging class, detecting each node in the asynchronous link in sequence according to the preset detection method, and determining a fault node and a fault reason corresponding to the fault node. The fault positioning efficiency of the message-oriented middleware is improved.

The invention belongs to the technical field of electric actuator torque testing, and discloses an electric actuator torque testing system which comprises a workbench, a fixing device is arranged on the workbench, an electric actuator is fixed to the fixing device, and an output shaft of the electric actuator is connected with one end of a dynamic torque sensor. One end of the dynamic torque sensor is connected with the fixing device, the other end of the dynamic torque sensor is connected with a load loader for providing a torque load, the dynamic torque sensor is connected with a control center of a test system, and the fixing device is characterized in that the fixing device is also provided with a plurality of piezoelectric surface acoustic wave sensors wirelessly connected with the control center; and the piezoelectric surface acoustic wave sensor is fixed on a transmission part in the electric actuator. The method has the advantages that the torque value of the installed transmission part is measured through the piezoelectric surface acoustic wave sensor, the reason for insufficient output torque of the electric actuator is analyzed and judged, the fault point is found, and guarantee is provided for stable work of the electric actuator.

The invention provides a chip failure analysis method and device, electronic equipment and a medium. The method comprises the steps that after hot melt wax in a first state is obtained, the first state is a softened state, a sample to be ground is embedded into one side of the hot melt wax in the first state in a preset embedding mode, the other side of the hot melt wax in the first state is molded, and a grinding body in the first state is obtained; the to-be-ground sample in the grinding body is kept horizontal; based on the grinding body in the first state, a grinding body in a second state is obtained, and the second state is a solidification state; after the hot melt wax molded on the grinding body in the second state is fixed, grinding the to-be-ground sample in the grinding body to obtain a to-be-analyzed chip; and performing failure analysis on the to-be-analyzed chip to obtain an analysis result. According to the method, the grinding stability and safety are improved, and the failure analysis efficiency is also improved.