30results about How to "Improve troubleshooting speed" patented technology

The invention relates to the technical field of electric power measurement and control instruments, in particular to an operation method and system based on an electric power measurement and control instrument, and the method comprises the following steps: based on the electric power measurement and control instrument, remotely collecting real-time operation data of a power grid, screening and removing abnormal data, integrating historical operation data, analyzing data collected from a sensor, and obtaining an equipment fault probability index. According to the invention, real-time data remotely collected by the electric power measurement and control instrument is combined with historical data for analysis, so that fault prediction is more accurate, the probability of power grid interruption is reduced, the accuracy of real-time determination of key monitoring points and fault prediction is improved, resource allocation is optimized, the fault processing speed is accelerated, and intelligent comparison with maintenance period data is realized. The method optimizes the maintenance schedule, guarantees the efficient operation of the power equipment, effectively predicts the future load change through analyzing the difference between the current load and the predicted load, guarantees that the power grid can adapt to different operation conditions, and improves the reliability and efficiency of the whole power grid.

The invention discloses an intelligent equipment fault diagnosis method based on multi-modal fusion, and the method achieves the quick and accurate diagnosis of an intelligent equipment fault through integrating various sensor data such as sound, images, vibration and temperature, and carrying out the automatic analysis through a deep learning model. The invention aims to improve the accuracy and efficiency of fault diagnosis, reduce manual intervention, reduce the maintenance cost and improve the reliability of equipment operation. The technology is suitable for the fields of industrial automation, intelligent manufacturing and the like, and an efficient solution is provided for equipment maintenance and management.

The invention discloses a gas turbine oscillation combustion fault detection method and system, and relates to the technical field of gas turbine fault detection, and the method comprises the steps: collecting the data of a gas turbine for preprocessing; performing multi-scale analysis on the gas turbine data by using continuous wavelet transform, and analyzing and extracting a wavelet coefficient; classifying and distinguishing fault features and stable features; and taking the classified wavelet coefficient as the input of the convolutional neural network, and training the model until the diagnosis effect is optimal. According to the method, time-frequency analysis is carried out on flame pressure pulsation data by adopting continuous wavelet transform, wavelet coefficients are extracted, and data dimension reduction and feature extraction are realized. A convolutional neural network deep learning algorithm is used for flame feature classification, and compared with a traditional fault diagnosis method, the fault diagnosis time is shortened, the fault diagnosis speed is increased, and the calculation cost is reduced. The oscillation combustion fault detection algorithm provided by the invention has higher detection speed and higher accuracy.

The invention discloses a circulating filtration system fault positioning method based on a step-by-step optimization gradient decision tree, and the method comprises the following steps: S1, collecting real-time signal data of a circulating filtration system of metal additive manufacturing equipment through a multi-source sensor, and carrying out the normalization index processing and fusion of the collected data; s2, eliminating and extracting features of different signals in the circulating filtration system from the fused data; s3, labels of different signal features are determined; adopting grid search to obtain optimal parameters of a gradient decision tree algorithm so as to construct a fault positioning model; training a fault positioning model; and S4, the implementation activity of the circulating filtration system of the metal additive manufacturing equipment is monitored, and the real-time state of the equipment is determined. According to the method, input data of the multi-source sensor is provided for the fault positioning model, and data redundancy is effectively reduced through data preprocessing and optimization of genetic algorithm hyper-parameters, so that the accuracy and efficiency of the fault diagnosis model are greatly improved.

The invention discloses a power grid fault identification system based on big data. The system comprises a data acquisition module used for acquiring real-time operation data in power grid operation; the data storage module stores real-time operation data; the data processing module preprocesses the real-time operation data; the fault identification module is used for inputting the real-time operation data into a fault identification model and identifying a fault type; the fault analysis module compares the voltage phasor difference and the current phasor difference of different PMU nodes, calculates the fault position and evaluates the fault involved range when the fault occurs; the fault processing scheme generation module is used for generating a fault processing scheme; the alarm and processing module is used for sending fault information to operation and maintenance personnel; and the visualization module is used for displaying the fault type, the fault factor and the fault related range when the fault occurs, and providing an interactive operation interface for operation and maintenance personnel. The fault processing speed is increased by analyzing the fault information, the possibility of human errors is reduced, and the processing efficiency is improved.

The invention discloses an elevator fault rapid diagnosis method, device, equipment and system based on artificial intelligence, the elevator fault rapid diagnosis device comprises a mobile phone A1, a remote monitoring client C1, an intelligent remote monitoring system Y1 arranged at a cloud end, an elevator E1, a DTU terminal T1, a maintainer P1 and an expert P2, and the intelligent remote monitoring system comprises a remote monitoring server S1, a communication server Z1, a database B1 and an elevator large model X1. The remote monitoring client C1 is installed on the mobile phone A1; according to the scheme, the elevator large model system is constructed, the causal relationship between behaviors and faults is set, the behaviors and the associated faults in the elevator before the faults occur are automatically and dynamically analyzed, the accurate reasons of the faults are quickly diagnosed, the elevator faults are automatically researched, judged and accurately positioned, the optimal fault solution is recommended, and the working efficiency is improved. Maintenance personnel are guided to carry out elevator fault processing in an intelligent and processized mode, the fault processing efficiency is greatly improved, the fault processing time is shortened, use of the elevator is rapidly recovered, and the method is far better than a traditional fault processing method and has innovativeness.

This invention discloses a method, apparatus, vehicle, and storage medium for processing DDS messages. The method includes: obtaining participant identifiers and establishing a classification strategy table based on the participant identifiers; obtaining subscriber identifiers, publisher identifiers, and topic names, and establishing a correspondence between participants, subscribers, publishers, and topic names according to the classification strategy table; obtaining RTPS sub-message data, and classifying and storing the RTPS sub-message data according to the correspondence. This application allows developers or users to intuitively see the interaction between different DDS applications, thereby quickly locating the problem and improving the troubleshooting speed during DDS network transmission.

The utility model provides a common rail pipe assembly which comprises an outer layer pipe and an oil leakage point observation component, the outer layer pipe comprises a plurality of outer pipe sections which are arranged at intervals to form a plurality of intervals, and the oil leakage point observation component comprises a sleeve which is arranged outside the outer layer pipe in a sleeved mode. Part of each sleeve is located at the interval between every two adjacent sleeves in the multiple outer pipe sections, and the sleeves are in clearance fit with the two corresponding outer pipe sections. The two sealing element combinations are respectively arranged between the sleeve and the two corresponding outer pipe sections; and the two fixing piece combinations are arranged at the two ends of the sleeve correspondingly and detachably installed on the two corresponding outer pipe sections correspondingly, so that the problems that in the prior art, the mode for judging the fuel leakage point of the common rail pipe is complex, and the judgment result is interfered are solved.

The invention provides a fault processing method and device, equipment, a medium and a program product, which can be applied to the field of information technology or financial science and technology. The method comprises the following steps: acquiring fault data of a target subsystem, a target user corresponding to the target subsystem and a terminal of the target user; obtaining candidate fault processing schemes for the fault data from a plurality of subsystems by using a preset clustering model; under the condition that the login token of the target user is not expired, sending a candidate fault processing scheme to the terminal; and in response to receiving a target fault processing scheme sent by the terminal, executing the target fault processing scheme, the target fault processing scheme being selected from the candidate fault processing scheme by the target user.

The invention discloses a fault diagnosis system for a drum granulator, relates to the technical field of fault diagnosis, and solves the technical problems that it is difficult to quickly locate the faulty parts of the drum granulator, it is also difficult to detect the internal data of the equipment, and it is not convenient to quickly locate the fault nodes inside the drum granulator; the parts in the component area are divided into a plurality of similar fault data part groups through a first fault diagnosis module, the fault data of the similar fault data part groups are statistically analyzed, and similar fault analysis models of each component area are established; the parts are grouped according to similar faults, so as to more accurately determine the location of the fault, which is helpful for quickly locating and repairing the fault; at the same time, by analyzing the similar fault data, the potential faults of the parts can be discovered in time; by collecting the operation data of the component area and performing group analysis, it is helpful to deeply understand the operation status of the equipment and determine the scope of the fault.

The invention discloses a digital twin gate system construction method, and relates to the technical field of hydropower stations, and the digital twin gate system construction method comprises the following steps: obtaining the actual operation data of a physical gate system, and in each operation device of an internal operation structure of the physical gate system, obtaining the actual operation data of the physical gate system; correspondingly arranging at least one sensing device to collect actual operation data so as to form a sensing monitoring network; constructing a three-dimensional model according to the physical gate system; establishing and forming a digital twin gate system according to the three-dimensional model and a sensing monitoring network; independently comparing the actual operation data of each operation device with an operation data threshold value; when the actual operation data of any operation device exceeds the operation data threshold value, the corresponding operation device is determined to be in a fault state, and maintenance reminding information is sent out. According to the technical scheme provided by the invention, the exact position of the fault and related components can be quickly positioned, the fault maintenance speed is accelerated, and the method has the advantages of reducing the troubleshooting workload and improving the troubleshooting speed.

The application belongs to the technical field of computers and provides a fault diagnosis method and system based on equipment maintenance knowledge base. The method comprises the following steps: constructing an equipment maintenance knowledge base, wherein the equipment maintenance knowledge base comprises phenomenon events, fault causes and the relationship between the phenomenon events and the fault causes, the relationship is a fault scene, and the fault scene comprises a single cause scene and a combined cause scene; acquiring a last node in a fault diagnosis path as a phenomenon event, retrieving a fault scene of the phenomenon event, and if the retrieval result is empty, the phenomenon event is a fault diagnosis result. The single cause scene can realize the reasoning ability of the traditional decision tree rule, the combined cause scene is combined with the single cause scene, the fault combination condition traversal with exponential complexity can be automatically expanded based on a small amount of structured expression, the knowledge representation is simplified, and the complexity and workload of the construction and maintenance of the knowledge base are reduced.

The application relates to the technical field of electrical engineering fault diagnosis, and provides a fault diagnosis method and system of a cascade H-bridge converter. g dc The system is determined whether an open-circuit fault of a power device occurs and a suspicious fault tube pair is determined by comparing with a preset threshold value; the DC bus voltage equalization control is cut off from the system, the DC bus voltage equalization control of the remaining modules except the fault module is restored after the fault module is located; the fault module is short-circuited by changing the driving signal of the power device of the fault module, and the specific fault switch tube is located; the system is restored to stable work by using the redundancy of the modulation coefficients of other modules. After the open-circuit fault occurs, the fault device is quickly, efficiently and reliably located and the system is restored to normal work by temporarily cutting off the voltage equalization control.

The present application relates to the field of optical cable routing survey, and discloses an optical cable routing determination method based on an exciter, an optical sensing system, equipment and a storage medium. The method comprises: the exciter converts device information and position information of the exciter into voice information based on a start instruction issued by a server, and plays the voice information to generate sound waves, which act on an optical cable arranged around the exciter to cause deformation, an optical cable sensing device acquires reflected light signals returned based on the deformation, and obtains the position of the optical cable well based on vibration information, and the server obtains the optical cable routing based on the positions of the optical cable wells. The scheme places an exciter capable of emitting specific voice content on the optical cable well, analyzes vibration characteristics in the optical cable to obtain the position of the exciter, thereby determining the optical cable routing, ensuring the positioning accuracy of the optical cable well, improving the accuracy of the optical cable routing determination result, and improving the optical cable routing troubleshooting speed.

The invention relates to the technical field of motor train detection, and discloses an automatic testing device and method for an end simulator of a motor train unit, and the method comprises the steps: installing a camera on the end simulator, monitoring the eye movement of an operator through an image recognition technology, giving an alarm when the operator watches a 46-pin adapter continuously for a long time, and setting a timed reminding function. And an operator is reminded to have a rest or distract attention at regular intervals, so that visual fatigue is relieved. Through the automatic test script and the intelligent prompt function, the operation steps and the input frequency are reduced, the time of an operator is saved, the test efficiency is improved, the real-time monitoring system continuously monitors the operation state of the end simulator and key indexes in the test process, feedback and alarm are provided in time, problems can be found and processed in time, and the test efficiency is improved. And the test accuracy is improved.

According to the distribution line wave velocity measurement and calibration method based on the distribution automation master station, the master station sends and uploads an instruction of last wave recording to all traveling wave distance measurement devices of a line where a switch is located after operation of the remote control switch; after receiving the instruction, the traveling wave distance measuring device uploads the last cached recorded wave, namely the recorded wave data started by the switch operation wave, and the main station calculates and updates the wave speed after receiving the recorded wave uploaded by the device. The invention provides the active and easy-to-operate distribution line wave velocity measurement and calibration method, the line wave velocity can be actually measured and calibrated without relying on faults and without a large amount of data statistics, the problem of large distribution line fault positioning error caused by inaccurate wave velocity can be solved, the fault positioning precision is improved, and the fault positioning accuracy is improved. Therefore, the fault processing speed of the distribution line is greatly accelerated, and property loss, personal safety risk and power supply reliability loss caused by the fault are greatly reduced.

The invention discloses an energy storage power station fault diagnosis method and system, and the method comprises the steps: obtaining an environment factor of an environment where an energy storage power station is located and the equipment information of an energy storage power station site; determining an actual input value, an actual output value, an expected input value and an expected output value of each index of each device of the field devices of the energy storage power station based on the environmental factors of the environment where the energy storage power station is located; a diagnostic value for each indicator of each device is determined based on the real-time input value, the actual output value, the desired input value, and the desired output value for each indicator of each device. The technical problems that an existing fault diagnosis method for the energy storage power station is low in speed and cannot effectively position a fault part, so that the energy storage power station causes economic loss and is low in operation and maintenance efficiency are solved.

The embodiment of the invention belongs to the technical field of computers, and relates to an air traffic control equipment three-dimensional rendering display method, which comprises the following steps: acquiring modeling preparation data of air traffic control equipment, including basic information, layout information and connection information of the equipment; classifying all the air traffic control equipment according to the basic information; establishing a device layer corresponding to each type of air traffic control device; in the equipment layer of each type of air traffic control equipment, rendering the modeling preparation data of each type of air traffic control equipment through a three-dimensional rendering engine to obtain a three-dimensional model layer of each type of air traffic control equipment; performing layer superposition on the three-dimensional model layers to obtain an initial three-dimensional monitoring model; and acquiring operation state data of each air traffic control device, binding the acquired operation state data to the corresponding air traffic control device in the initial three-dimensional monitoring model to obtain a three-dimensional monitoring model of each air traffic control device, and displaying the operation state of each air traffic control device by the three-dimensional monitoring model based on a layer. According to the invention, the management efficiency and accuracy of the air traffic control equipment are improved.

The invention discloses a fixed value dynamic switching method, device and system based on real-time state perception, and the method comprises the steps: calculating a current voltage deviation rate, a current voltage change rate, a current frequency deviation rate and a current frequency change rate based on the obtained real-time electrical quantity of a transformer substation; inputting the voltage and the frequency at the current moment into a time sequence prediction model to obtain a prediction result, wherein the prediction result comprises a voltage prediction value, a frequency prediction value and the confidence coefficient of each prediction value; combining the current voltage deviation rate, the current voltage change rate, the current frequency deviation rate and the current frequency change rate to perform effectiveness evaluation on the prediction result; aiming at the effective prediction result, generating a fault constant value by adopting a hierarchical control strategy, and writing the fault constant value into a standby constant value area; and when the switching requirement is met, replacing the current constant value with the generated fault constant value. According to the method, the problems of poor adaptability, dependence on manual switching and low switching efficiency of a traditional fixed value strategy in a high-proportion new energy power grid can be solved, and the risk of misoperation of a stability control device is reduced.

The present invention discloses a line single-phase grounding detection tool, comprising a grounding current signal wireless transmitter and an on-site detection device, wherein the grounding current signal wireless transmitter comprises a current transformer [1], a frequency modulation signal modulator [2], and a frequency modulation signal transmitter [3]; the on-site detection device comprises a metal grounding signal collection device, a signal receiver, and a signal strength display. The detection of the present invention does not require manual pole climbing, which brings a qualitative change to the single-phase grounding detection operation, helps to improve the fault handling speed of the distribution network system, and the effect of the present invention is more prominent at night or in bad weather.

The invention discloses a voice alarm system for a gypsum board production line. The voice alarm system comprises a control module, a fault detection module and a voice broadcast module which establish a communication relationship, the control module polls the fault detection module to obtain a fault code matched with a fault problem and then sends an alarm code matched with the fault code to the voice broadcast module, and the voice broadcast module sequentially broadcasts alarm audios matched with the alarm code. A classified fault broadcasting mode is adopted, communication connection among the fault detection module, the control module and the voice broadcasting module is established through the communication module, the wiring difficulty and the maintenance difficulty are effectively reduced, and after a fault occurs, the fault detection module generates a fault code matched with the fault problem, so that the fault detection efficiency is improved. And after the control module polls the fault detection module to obtain the fault code, the control module sends an alarm code matched with the fault code to the voice broadcast module, so that the voice broadcast module broadcasts an alarm audio matched with the alarm code, thereby realizing rapid positioning of the fault problem and improving the fault processing speed.

The present invention discloses a line single-phase grounding detection system, comprising a grounding current signal wireless transmitter and an on-site detection device, wherein the grounding current signal wireless transmitter comprises a current transformer [1], a frequency modulation signal modulator [2], and a frequency modulation signal transmitter [3]; the on-site detection device comprises a metal grounding signal collection device, a signal receiver, and a signal strength display. The detection of the present invention does not require manual pole climbing, which brings a qualitative change to the single-phase grounding detection operation, helps to improve the fault handling speed of the distribution network system, and the effect of the present invention is more prominent at night or in bad weather.

The invention particularly relates to a medium and low voltage distribution network power management system and method based on transformer area flexible interconnection. The system comprises two flexible interaction devices, two side-side communication units, two transformer area intelligent fusion terminals, a cloud master station and a scheduling control system. The two flexible interaction devices are connected through a direct-current bus, each flexible interaction device is connected with one transformer area intelligent fusion terminal, the two side-side communication units are connected with each other to carry out information interaction, and the two transformer area intelligent fusion terminals carry out information interaction through the side-side communication units connected with the two transformer area intelligent fusion terminals respectively. The cloud master station is connected with the two transformer area intelligent fusion terminals through communication links, and the dispatching control system is connected with the cloud master station. According to the method, the overall solution of the target of'device fault processing-transformer area power mutual aid-medium voltage optimization adjustment 'is realized, and the whole set of requirements from transient fault processing of the flexible interaction device to layered and graded steady-state optimization adjustment of the medium and low voltage distribution network are met.

The application relates to a power distribution network fault positioning method, device, equipment, storage medium and product. The method comprises the following steps: in response to a fault occurring in a power distribution network, acquiring electrical signals of different fault recording devices in the power distribution network before and after the fault occurring in the power distribution network; processing each electrical signal respectively to obtain time-frequency characteristics of the corresponding fault recording device; selecting at least one candidate fault line from different power distribution lines of the power distribution network according to the time-frequency characteristics; and determining a target fault position of the power distribution network according to the time-frequency characteristics and historical fault information of each candidate fault line. The method can improve the fault positioning efficiency and meet the real-time requirement.

The invention discloses a distributed training system and method for an artificial intelligence model, and a controller, and belongs to the technical field of artificial intelligence infrastructures. The system comprises a controller, a monitor, n working nodes and m hot standby nodes, wherein n and m are positive integers; the controller is used for deploying training programs corresponding to the training tasks to the n working nodes and the m hot standby nodes; the n working nodes are used for cooperatively executing training tasks; the monitor is used for monitoring health states of the n working nodes; and the controller is used for switching the training sub-task corresponding to a first working node to a first hot standby node in the m hot standby nodes for execution under the condition that the first working node in the n working nodes has a fault.

The utility model provides a broadcast transmitter antenna switch modularization automatic control system. The system comprises a switch matrix composed of a plurality of switches; the switch matrix is connected with a plurality of transmitters and a plurality of antennas; each switch is correspondingly connected with a switch control module to form a control module matrix corresponding to the position of the switch matrix; the switch control module is connected with a PLC. And the PLC is connected with a client module. According to the application, the automatic control of the transmitter antenna switch is realized, the state of the switch resource shared by multiple transmitters is monitored in real time, the signal interference and equipment conflict are avoided, the accurate execution of the switch action is ensured through the PLC feedback, and the system reliability is improved; the module matrix corresponds to an actual antenna switch matrix, so that the position of a fault module can be quickly found through matrix comparison when a fault occurs; when maintenance is carried out, the module corresponds to the antenna switch, so that debugging at two ends and maintenance of workers are facilitated.

The invention provides an interface performance test index data noise reduction method and a related device, and relates to the technical field of performance testing, and the method comprises the steps: obtaining a first sample matrix of Web interface performance test index data through data enhancement; performing singular value decomposition on the first sample matrix to obtain a singular value matrix, and performing noise reduction on the singular value matrix; and reconstructing and recovering a second sample matrix of the Web interface performance test index data by using the singular value matrix after noise reduction. According to the method, the influence of noise in the performance test index data on the performance analysis process can be effectively reduced, by suppressing the noise, on one hand, performance defects in the performance test index data can be more obviously exposed, the accuracy of performance analysis is improved, on the other hand, the analysis direction can be accurately found, the performance defect checking speed is increased, and the performance analysis efficiency is improved. And the performance analysis efficiency is improved.

The present invention relates to the technical field of electric power measurement and control instruments, and specifically to an operation method and system based on electric power measurement and control instruments, comprising the following steps: based on the electric power measurement and control instrument, remotely collect real-time operation data of the power grid, screen and eliminate abnormal data, integrate historical operation data, analyze data collected from sensors, and obtain equipment failure probability indicators. In the present invention, the real-time data collected remotely by the electric power measurement and control instrument is combined with historical data for analysis, so that fault prediction is more accurate, the probability of power grid interruption is reduced, the real-time determination of key monitoring points and the accuracy of fault prediction are improved, resource allocation is optimized and fault handling speed is accelerated, intelligent comparison with maintenance cycle data is performed, the maintenance schedule is optimized, and the efficient operation of electric power equipment is guaranteed. By analyzing the difference between the current load and the predicted load, future load changes are effectively predicted, ensuring that the power grid can adapt to different operating conditions, and improving the reliability and efficiency of the overall power grid.

The invention relates to the technical field of DTU protection, in particular to a power distribution network DTU protection method based on access of a distributed power supply. According to the technical scheme, the system comprises an analysis module, a protection strategy making module, an optimization scheduling module and a simulation verification module, the analysis module collects data such as output characteristics and operation parameters of a distributed power supply to carry out fault characteristic analysis so as to provide a basis for making a subsequent protection strategy; the protection strategy formulating module formulates a reasonable protection strategy in combination with characteristics of the distributed power supply and protection requirements of the power distribution network, the optimal scheduling module realizes real-time monitoring and operation control of the power distribution network through optimal scheduling, and the simulation verification module ensures feasibility of the proposed method in practical application through simulation verification. Normal operation and effective protection of the DTU are ensured, the function of the DTU in the power distribution network is fully played, and safe, stable and efficient operation of the power grid is ensured.

The invention discloses a sewage treatment equipment fault determination method and device and a computer readable storage medium. The method for determining the fault of the sewage treatment equipment comprises the following steps: collecting sewage data of the sewage treatment equipment at a plurality of continuous moments in a preset period; feature extraction is carried out on the sewage data at the first moment through a feature extraction model according to the incidence relation between the sewage data at the first moment and sewage data at the second moment in the preset period, first feature information is generated, and the second moment is the moment before the first moment in the preset period; and performing classification processing on the first feature information through a classification model, and determining whether the sewage treatment equipment has a fault or not.