102 results about "Fault avoidance" patented technology

Disclosed in the present invention are a fault identification method and system based on the operating condition of a continuous system in an open-pit mine. The method comprises: establishing a simulation model for a continuous system in an open-pit mine, and monitoring device data in real time; pre-processing the data, and performing potential fault identification; on the basis of a system pressure change rate and an adaptive adjustment mechanism of the continuous system in the open-pit mine, optimizing fault identification output; and designing a fault response and real-time adjustment mechanism to prevent fault occurrence. The fault identification method and system based on the operating condition of a continuous system in an open-pit mine provided in the present invention improve the speed and accuracy of fault diagnosis, particularly the rapid processing capability for complex data relationships. A breakthrough is achieved in fault prevention, thus enabling early warning and adaptive adjustment to be implemented before faults occur. Thus, the stability and safety of continuous systems in open-pit mines are significantly improved, and a more efficient technical solution is provided for operation management of modern open-pit mines.

The invention discloses a gas compressor blade state monitoring method and system based on a health management platform, and relates to the technical field of gas turbines. Comprising the following steps: acquiring real-time operating parameters of the gas turbine, and transmitting the real-time operating parameters to a health management platform at a fixed sampling frequency; performing data preprocessing and feature extraction on the real-time operation parameter data; calculating the performance parameter degradation quantity of the gas turbine according to the real-time operation parameter data; performing blade fault identification according to the parameter degradation quantity and a preset fault diagnosis criterion; calculating a fault early warning index through the real-time operation parameter data, and judging whether the gas turbine is in a normal operation condition or not; and judging a fault early warning level according to the parameter degradation quantity and sending out a corresponding early warning signal. According to the method, the blade fault type can be accurately predicted, false alarms and false alarms can be reduced, meanwhile, early warning level signals are sent out, measures can be taken, fault expansion is avoided, and downtime and maintenance cost are reduced.

The invention relates to the technical field of intelligent power distribution network automatic protection, and discloses a power distribution network fault strategy generation method, system and device based on a self-healing loop graph, and a medium, and the method comprises the steps: constructing a power distribution network topological graph, and recognizing a self-healing loop; generating a cooperative protection constant value based on the incidence relation of the dynamic correction path impedance and the protection device; a delay parameter is adjusted through conflict detection of the dynamic impedance track and the high-frequency phase sequence; simulating a fault action to generate an SOE event chain; identifying an abnormal time delay combination in combination with historical time delay distribution and marking conflicting nodes; adjusting parameters for the second time to generate a self-healing strategy matched with the topology; through multi-dimensional time sequence conflict detection and closed-loop feedback optimization, precise control of cooperative action of the protection device is realized, fault isolation delay and maloperation of a non-fault area are effectively avoided, and self-healing reliability and power supply recovery efficiency in a complex power distribution network scene are improved.

The invention relates to the technical field of safety valve fault monitoring, in particular to a safety valve full-life-cycle fault detection method and system, and aims to solve the problems that sudden safety accidents occur frequently due to the fact that a traditional method depends on leakage flow monitoring and cannot capture hidden faults such as valve element jamming and spring fatigue, a power supply system mostly adopts a single power generation mode, and the power consumption is low. In a low discharge scene, the electric quantity of the energy storage module is used up, and monitoring interruption is caused. According to the invention, the problems of safety valve hidden fault monitoring deficiency and unstable power supply are effectively solved. By means of multi-dimensional data collection, spring elasticity attenuation and valve element movement abnormity can be found in advance, and faults are prevented from being evolved into serious leakage. The composite power supply system maintains basic monitoring in the non-discharge stage, energy is quickly supplemented in the discharge stage, and continuous operation of the whole life cycle is guaranteed. A model analysis result can guide maintenance personnel to accurately position a fault part, and unnecessary shutdown maintenance is reduced.

Disclosed in the present application are a fault detection method, a fault detection apparatus, a computer device, and a storage medium. The method comprises: on the basis of the opening degree of a flow control apparatus and a preset mapping function, calculating a first flow coefficient; on the basis of a first operating parameter of the flow control apparatus and a second operating parameter of a compressor, calculating a second flow coefficient; and on the basis of a deviation between the first flow coefficient and the second flow coefficient, performing fault detection on the flow control apparatus, so as to determine a fault detection result. By comparing a flow coefficient, which is obtained by means of real-time detection, with a theoretical flow coefficient to obtain a deviation therebetween, fault detection can be performed on a flow control apparatus in a timely manner, which is conducive to avoiding the impact of a faulty component in a timely manner, thereby improving the stability and reliability of an air conditioning system.

The invention discloses a power distribution control method and system based on an urban network, and relates to the technical field of power distribution control, and the method comprises the steps: monitoring the operation parameters of a power grid in a governed power distribution region in real time at an edge calculation terminal disposed at the edge side of a power distribution network; and when it is monitored that the power grid operation parameters are abnormal, determining fault occurrence and a specific position of a fault section based on a preset fault diagnosis model. According to the method, the edge computing terminal is deployed on the edge side of the power distribution network, real-time monitoring of the operation parameters of the power grid in the jurisdiction area is achieved, when the parameters are abnormal, the fault section can be rapidly positioned by means of the preset fault diagnosis model, the fault response speed is greatly improved, and the problem that decision-making time is long in a traditional centralized master station mode is solved. The edge computing terminal can directly generate an instruction isolation fault, and the fault range is prevented from being expanded.

The invention discloses a 5G-TSN (Time Sensitive Network) clock synchronization error prediction method based on LSTM (Long Short Term Memory), and belongs to a clock synchronization technology of a time sensitive network (TSN) and 5G (5th Generation) mobile communication. According to the method, the synchronization error trend can be captured in the 5G-TSN clock synchronization process, and an effective prediction mechanism is provided for clock synchronization regulation and control and fault prevention. Compared with the existing research on 5G-TSN clock synchronization, the invention proposes that an error prediction mechanism is introduced into a 5G-TSN clock synchronization process for the first time, and a monitoring mechanism is established for advanced calibration regulation and fault avoidance of clock synchronization.

The invention provides a soft start cooperative control method and system for a large industrial air conditioning unit, and the method comprises the steps: a central cooperative controller collects the operation parameters and start dependence conditions of all parts through a high-speed real-time communication network, builds a fault feature database, and carries out the real-time recognition of an abnormal signal; a fault tree analysis module is adopted, faults are divided into three levels according to the types and severity of the faults, if communication interruption occurs, a hardware watchdog circuit of a safety protection unit executes emergency shutdown within 500 ms, out-of-control is prevented, and the method relates to the technical field of large-scale industrial air conditioning unit control. The fault grade and the influence range are dynamically evaluated, rapid positioning and collaborative response of faults are achieved, fault spreading is avoided, the safety and reliability of the large industrial air conditioning unit starting process are improved, the problems of power grid impact and system reliability during multi-device starting are solved, and the method is suitable for large air conditioning units of data centers, factories and the like.

The invention belongs to the technical field of fault judgment, and discloses a wind turbine generator system fault judgment method based on a Relief algorithm and a related device. The wind turbine generator system fault judgment method based on the Relief algorithm comprises the steps of selecting characteristic quantities and preprocessing the characteristic quantities, iteratively calculating the weight of the preprocessed characteristic quantities according to the Relief algorithm to obtain a characteristic variable set, establishing a regression model between the average wind speed and the characteristic variable set and calculating the regression model, obtaining a normal reference characteristic quantity state of the wind turbine generator system under the real-time state data, and judging whether the wind turbine generator system has a fault or not through a state judgment algorithm according to the real-time state data and the normal reference characteristic quantity state of the wind turbine generator system under the real-time state data; the abnormal condition of the wind turbine generator system can be found in time, an early warning mechanism is triggered, the early warning accuracy is remarkably improved, and occurrence or expansion of faults is avoided.

The invention provides a method for reducing the failure rate of a unit air cooling island speed reducer. The method comprises the following steps that S1, a multi-module cooperative prevention and control system is built; s2, configuring a parameter monitoring module assembly; s3, standardizing the installation standard of the sensor; s4, building a data transmission and analysis platform; s5, starting an intelligent diagnosis and data tracing function; s6, executing a monitor calibration and maintenance process; s7, carrying out preventive maintenance operation; s8, starting a working condition linkage adjusting mechanism; s9, activating an operation and maintenance training auxiliary module; and S10, a supplement lubricating oil leakage monitoring link. According to the method for reducing the failure rate of the unit air cooling island speed reducer, full-dimension real-time monitoring and intelligent diagnosis of operation parameters of the speed reducer are achieved by building a multi-module cooperative prevention and control system, and by combining graded early warning and preventive maintenance, fault hidden dangers are accurately positioned and handled; the working condition linkage adjusting mechanism can actively adjust the operation state when parameters are abnormal, and fault expansion is avoided.

The invention belongs to the technical field of electrical equipment. The intelligent reclosing type circuit breaker control system comprises a scene monitoring unit, a data analysis and decision-making unit, a circuit monitoring unit and a self-adaptive control unit. According to the control system, real-time and planned operation data are combined, dynamic fault critical characteristics are generated and integrated and analyzed, and precise regulation and control of the circuit breaker are achieved. Therefore, timely opening can be realized to avoid faults, timely closing can be realized to restore power supply, misoperation and power supply interruption are reduced, circuit safety and power supply continuity are improved, and the circuit is adaptive to complex load scenes.

This application provides a method, apparatus, and storage medium for collecting memory fault information, relating to the field of data storage, and capable of preventing missed fault information reports. The method is applied to a server, which includes memory, an out-of-band controller, and an in-band controller. The method includes: during server operation, the in-band controller performs fault detection on the memory and sends the detected fault information to the out-of-band controller; during server restart, if the server's startup mode is a cold restart, the in-band controller determines whether new fault information exists in the memory, wherein the new fault information is fault information not stored in the out-of-band controller; if new fault information exists in the memory, the in-band controller sends the new fault information to the out-of-band controller.

The invention relates to the technical field of industrial automation control, and discloses an auxiliary control workshop control system based on a DCS, and the system comprises a process topological graph construction module which is used for mapping a physical workshop into a dynamic graph containing an equipment digital object in real time; the task analysis module is used for converting the advanced task instruction into a quantitative target state set on a graph; the dynamic path planning module is used for automatically searching and generating an optimal atomic operation instruction sequence for reaching a target state based on the real-time state of the map; and the instruction execution and transaction management module and the exception handling and secure rollback module are used for ensuring atomic execution of the instruction sequence and secure rollback during failure. According to the method, a process control problem is converted into a graph theory path planning problem, so that the control system has the capabilities of dynamically avoiding faults and autonomously deciding, and the automation level, the reliability and the safety of the operation of the auxiliary control system are remarkably improved.

The invention discloses a wind facing deviation identification method and device for a wind turbine generator, electronic equipment and a storage medium, and belongs to the technical field of wind turbine generator fault diagnosis, and the method comprises the steps: obtaining historical fault signals of a wind direction sensor of the wind turbine generator, generating a fault signal data set, and counting fault features of the wind direction sensor of the wind turbine generator; carrying out dimensionality reduction processing on the fault signal data set according to the fault features to obtain a fault signal feature set, carrying out training calculation on the fault signal feature set, generating a wind turbine deviation fault classifier, collecting to-be-identified signal data of a wind direction sensor of a wind turbine generator in real time, carrying out feature extraction on the to-be-identified signal data, and carrying out similarity calculation to obtain a wind turbine deviation fault classifier; according to the calculation result, the fault class of the to-be-identified signal data is judged, signal fault identification of the wind direction sensor of the wind turbine generator is completed, the situation that the faulted wind direction sensor cannot be found due to long-time fault operation can be avoided, power generation loss is reduced, and the service life of a fan is prolonged.

The present invention discloses a method for locating faults in an automobile engine based on data analysis, belonging to the technical field of automobile fault detection, including Step 1: formulating the normal operation data range of each monitoring item of the engine under different environmental condition values; Step 2: judging whether the operation data of each monitoring item under this environmental condition value is normal according to the obtained operation data information; Step 3: when the operation data of the monitoring item is abnormal, generating a corresponding fault alarm and determining the danger level of the fault; Step 4: when the operation data of the monitoring item is normal, predicting whether there is a potential fault risk for each monitoring item. When the engine has not failed, the present invention predicts whether there is a potential fault risk for each monitoring item according to the historical accumulation of the operation data at the positions of each monitoring item, so as to timely remind the user to perform corresponding inspections and repairs on the corresponding positions, thereby avoiding the occurrence of faults.

The application discloses a fault distance measurement method and system for an electrified railway AT power supply mode, relates to the technical field of fault distance measurement, determines whether load current is contained in fault current according to impedance angle, and calculates fault current without containing load current; that is, the mixed load current is removed in the fault current calculation process, so that the accuracy of the fault current is ensured; the fault type is judged based on the self-coupling variable absorption current direction characteristics, so that the fault type judgment error caused when the fault occurs at the end section of the traction network is avoided, the fault type identification accuracy is greatly improved, and the fault distance measurement precision is improved.

The application discloses a vehicle fault processing method, a battery cooperative controller and a vehicle. The vehicle fault processing method is applied to the battery cooperative controller which is connected with a high-voltage battery and a low-voltage battery. The vehicle fault processing method comprises the following steps: obtaining fault diagnosis data of a plurality of function management units in the battery cooperative controller, wherein the plurality of function management units comprise a low-voltage battery management unit, a high-voltage battery management unit, a voltage conversion unit and a charging communication unit; performing fault cooperative decision on the fault diagnosis data to obtain a global fault processing scheme; and controlling the plurality of function management units to perform corresponding fault processing operations according to the global fault processing scheme. The application realizes fault information sharing and cooperative processing across subsystems, can avoid problems such as fault island and decision conflict, and improves the consistency and real-time performance of fault response.

The invention discloses a motor anomaly detection early warning method based on big data, and relates to the technical field of motor detection, multi-index historical data of a target motor is obtained, indexes comprise a preceding index and a lagging index, and the occurrence time of each index anomaly value is recorded; the method comprises the following steps: segmenting historical data, dividing data intervals according to fault events, and calculating a time difference between a preceding index anomaly and a lagging index anomaly in the same interval to form a time delay sample set; and a time delay probability distribution model is constructed based on the sample set, and normal time delay ranges corresponding to different index combinations are determined. Through the real-time monitoring and abnormity determination module, fault expansion can be avoided, motor operation safety and reliability can be improved, and loss caused by faults can be reduced.

This application provides a method, device, apparatus, and storage medium for selecting computing power nodes. The method includes: acquiring multiple undetermined service requests received through the same entry computing power routing node; and determining, based on whether the senders of the multiple undetermined service requests are the same user, selecting target computing power nodes that meet the requirements of each undetermined service request according to a first rule or a second rule. This application addresses specific application scenarios by prioritizing the processing of multiple service requests from the same user using the same or similar computing power nodes, thereby achieving parallel data forwarding, reusing transmission resources, and improving resource utilization. Furthermore, by using different computing power nodes belonging to different computing power routing nodes to process service requests of the same type from multiple users as much as possible, it avoids service paralysis across the entire region due to faults, thus accurately and specifically selecting the optimal computing power node for multiple concurrent computing power services in specific application scenarios.

The utility model relates to IGBT module technical field, specifically, it is the fault detection alarm circuit of IGBT module, including IGBT module, detection module, detection chip and alarm module, and detection module includes voltage acquisition unit, current acquisition unit and temperature acquisition unit, voltage acquisition unit is used for detecting the collector voltage value of IGBT module, and current acquisition unit is used for detecting the on current value of IGBT module, and temperature acquisition unit is used for detecting the working temperature of IGBT module, in the utility model, the collector voltage value, on current value and working temperature of IGBT module can be detected in real time, realize the comprehensive monitoring of module working condition, compared with the detection mode of only monitoring single parameter, can more timely, accurately discover the abnormal situation of module, provides the basis for taking measures in advance to avoid the expansion of fault.

The present application relates to a redundant switching arbitration method, device and electronic medium. After all channels on a redundant card exchange diagnostic information, each channel generates its own switching arbitration result to determine whether the card needs to be switched to the working / standby state. The arbitration results are exchanged again, and each channel compares the arbitration results of all channels obtained by the interaction. Only when all channels determine that redundant switching is required will the card be switched to the working / standby state, thereby ensuring the reliability of redundant switching, effectively avoiding mis-cutting and ensuring system stability. At the same time, by setting a delayed switching, the card will not be switched to the working / standby state until the arbitration results of multiple consecutive comparisons between channels are consistent and all need to be switched. By using the delayed switching setting of multiple cycles, when the card encounters a fault in a short period of time, the original working / standby state can be maintained, thereby avoiding the jitter problem caused by the fault recovery in a short period of time and increasing stability.

This application discloses a server management system, method, electronic device, and storage medium, relating to the field of server management technology. The system includes: transmitting weights and server hardware information to a management information generation module; generating server management information based on the weights and server hardware information; generating hardware control information based on the server management information and adjusting the server hardware using the hardware control information; and a network control module, further used to generate alarm information based on the server management information and hardware control information. This system can solve the problems of difficulty in identifying hardware faults caused by complex factors and the inability to adjust server hardware in a timely manner for hardware faults. By introducing a dedicated neural network to create the management information generation module, the system enhances the BMC (Browser Control Center) function, enabling the identification of subtle fault characteristics and avoiding missed fault reports; it eliminates the need for manual analysis of data or faults, improving the efficiency of fault handling and saving manpower.

The invention belongs to the field of mechano-electronics and industrial automation control, and particularly relates to an industrial-grade electromagnetic boosting arm device with a fault self-diagnosis and passive safety mode, which comprises a loading seat integrated with a circuit board. The device comprises an electromagnetic driving execution module, a multi-mode sensing acquisition module, a self-adaptive signal conditioning module, a real-time fault diagnosis module, a passive safety decision module and a dynamic trajectory planning module. Through the dynamic filtering and phase locking technology of the adaptive signal conditioning module, the interference of the noise of the power switch on the signal of the rotary transformer is effectively suppressed, and the accuracy of fault diagnosis and the positioning precision of the device are remarkably improved. A multi-dimensional parallel diagnosis mechanism of the real-time fault diagnosis module can identify potential faults of a motor, a transmission chain and a sensor in an early stage, and device performance deterioration caused by fault accumulation is avoided.

This invention provides an intelligent CNC hydraulic system and control method, including a sensing and monitoring unit comprising a multi-source heterogeneous sensor network deployed at key nodes throughout the system. The invention is rationally designed, using a multi-source heterogeneous sensor network deployed throughout the system to simultaneously collect multi-dimensional operating parameters such as pressure, flow rate, temperature, and vibration. Edge computing is used to complete data preprocessing and fault-sensitive feature extraction. Relying on an SVM-LSTM dual-model fusion fault intelligent diagnosis module and integrating a fault tree FTA analysis submodule, it achieves accurate classification of fault types, rapid location of fault points, and root cause tracing. It also provides early warning of early system faults, significantly improving fault diagnosis accuracy compared to traditional threshold alarm methods. Furthermore, it can identify fault types that traditional methods cannot detect, such as directional valve sticking, predicting fault development trends in advance and effectively preventing equipment damage caused by fault escalation.

The invention discloses a vertical tube short circuit fault detection and identification method in NPP circuit topology, and the method comprises the steps: triggering a grid driver to generate a fault signal with a fixed time length t3 if the collector-emitter voltage of a vertical tube is lower than a target voltage during the time when the vertical tube is turned off and a horizontal tube is turned on; and when the controller detects the fault signal with the duration of t3, the controller judges that the vertical pipe has a short-circuit fault, and identifies the bit number of the faulted vertical pipe according to the hardware interface address for feeding back the fault signal. Compared with the prior art, the method has the advantages that the short-circuit fault of the standpipe can be detected and the bit number of the faulted standpipe can be identified before the bus straight-through fault, so that the bus straight-through fault can be pre-judged, and fault expansion is avoided. Besides, the gate driver utilizes the monostable trigger to realize that the fault signal is continuous in the monostable time, and the controller can judge that the corresponding vertical pipe has a short-circuit fault when receiving the fault signal and the duration of the fault signal is equal to the monostable time, so that misjudgment can be prevented.

The invention provides a retrieval optimization strategy and device based on a large model knowledge base and a storage medium, and belongs to the technical field of retrieval based on a large model. Constructing a system layered architecture; the method comprises the following steps of: integrating RagFlow into a Dify workflow by utilizing a Dify plug-in system and a user-defined tool; through collaborative construction of Dify and RAGFlow, creation, connection and recall testing of a knowledge base are realized; creating a workflow in Dify, and selecting an application type, a function block and a tool component; implementing an innovative RAG strategy, including dynamic knowledge graph construction, adaptive weight fusion, dynamic partitioning strategy, multi-mode reflection verification, incremental knowledge distillation and generative adversarial network optimization; an architecture design principle is followed, and modular splitting, RESTful API interaction, fault avoidance and data verification are adopted; according to the method, large model illusion is reduced, the fault handling efficiency is improved, and rapid access to a new service scene is supported.

The present invention provides a method and device for diagnosing and avoiding faults in a circulating water pump of an electric vehicle. The method comprises: obtaining a first control instruction for the circulating water pump; wherein the first control instruction is to control the circulating water pump to reach a first target speed; controlling the circulating water pump to execute the first control instruction; collecting feedback from the circulating water pump after executing the first control instruction; and determining whether an abnormality has occurred in the circulating water pump based on the first control instruction and the feedback. This allows for immediate identification of circulating water pump abnormalities, saving time and cost. Relevant processing / responses can also be promptly implemented to avoid impacting relevant functions of the circulating water pump in operational scenarios, thus meeting the user's requirement for quickly locating circulating water pump abnormalities during overall use.

The application provides a chip fault control method, a display driving circuit, a display panel and a medium, which are applied to the display driving circuit, the display driving circuit further comprises a plurality of other chips connected with a timing control chip, and the control method comprises the following steps: the timing control chip sends a fault detection signal to the plurality of other chips every interval of a preset frame number; if the fault detection pin level of at least one chip in the plurality of other chips is a preset level, the plurality of other chips are controlled to stop working. Since the timing control chip and each other chip are in real-time interaction through the fault detection signal and the fault recognition signal, the faulty chip can be located immediately. After the faulty chip is located, the timing control chip controls the plurality of other chips to stop working, so that the faulty chip, the other chips and peripheral devices can be prevented from being burned out, the detection efficiency of the faulty chip is improved, the repair rate of the driving board is improved, and the production cost of the driving board is reduced.

The invention discloses a method, a device and equipment for monitoring a self-triggering instruction fault of an aircraft side lever. The method comprises the following steps: acquiring original flight data of a to-be-monitored aircraft at a preset acquisition frequency; identifying a self-triggering flight control instruction of a side rod of the to-be-monitored aircraft according to the original flight data; monitoring and counting appearance characteristics of the self-triggering flight control instruction; and analyzing appearance characteristics of the self-triggering flight control instruction to obtain a self-triggering instruction fault state of the side rod. According to the technical scheme, when the fault phenomenon that the actual position of the flight control surface is inconsistent with the position corresponding to the flight control instruction occurs, the fault range can be accurately limited to the aircraft side lever, the fault state of the aircraft side lever self-triggering instruction can be monitored in advance, the fault state can be predicted in time, and the service life of the aircraft side lever can be prolonged. And the occurrence of warning or unsafe phenomena caused by fault deterioration is avoided.

Embodiments of the present invention provide a shielding method and device for an error-correcting code (ECC) fault of a random access memory (RAM), comprising: detecting an RAM, and recording an ECC fault address that can be skipped; converting the ECC fault address into a readable / writable ECC fault address; on the basis of entry information and readable / writable ECC fault address of the RAM, calculating an entry where the readable / writable ECC fault address is present; on the basis of the entry where the readable / writable ECC fault address is present, calculating an index position of the readable / writable ECC fault address; if the readable / writable ECC fault address is in a preset entry, determining the readable / writable ECC fault address as a target ECC fault address; and shielding an index position of the target ECC fault address. The present invention solves the problems that additional resource overhead is required for ECC fault repair and repeated generation of ECC faults cannot be avoided.