670 results about "Maintenance strategy" patented technology

The invention provides an electrical equipment state maintenance system. The electrical equipment state maintenance system comprises an operation and maintenance base layer platform, a state monitoring module, a state evaluation module, a risk assessment module, a fault diagnosis module and a maintenance strategy module, wherein production area I data of a power grid system and production area III data of the power grid system are integrated on the operation and maintenance base layer platform, the state monitoring module is used for collecting on-line monitoring data of electrical equipment and operating environment information of the electrical equipment through the operation and maintenance base layer platform, the state evaluation module is used for evaluating the on-line monitoring data according to state evaluation standards of the electrical equipment to acquire an electrical equipment health state represented by the on-line monitoring data, the risk assessment module is used for calculating the risk index of the electrical equipment according to risk assessment standards of the electrical equipment, the fault diagnosis module is used for diagnosing faults of the electrical equipment and generating a fault diagnosis report according to the health state and the risk index of the electrical equipment, and the maintenance strategy module is used for generating maintenance strategy information of the electrical equipment according to the health state, the risk index and the fault diagnosis report of the electrical equipment. By means of the electrical equipment state maintenance system, evaluation, assessment and predication are automatically carried out on the power grid system, and therefore the automation level and the intelligentization level of the power grid system are improved.

A systematic approach is presented for the development and implementation of cost-effective transmission asset maintenance strategies. The overall concept and methodology are based on transmission reliability and risk management and address the value of preventive maintenance activities. This may help electric network utilities conduct maintenance policy assessment, region-wide criticality analysis, and optimal maintenance resource allocation and task scheduling.

The invention discloses an ultra-high-frequency partial discharge signal identification method for gas insulated switchgear (GIS). The method comprises a model training process and a defect identification process, and specifically comprises the following steps of: reprocessing partial discharge signals of the GIS; extracting discharge characteristic parameters such as average discharge amplitude, discharge amplitude standard deviation, discharge phase distribution, discharge polarity, discharge time interval mean, discharge time interval standard deviation; optimizing a weight and a threshold value of a back propagation (BP) neural network by utilizing a genetic simulated annealing tool; training samples by utilizing a BP neural network tool; establishing a corresponding gas statistic algorithm (GSA)-BP model; preprocessing the partial discharge signals to be identified of the GIS; and identifying the samples to be measured in a classified way according to the GSA-BP model after extracting the corresponding characteristic parameters. By the method, the efficiency and the accuracy of partial discharge fault diagnosis of the GIS are improved effectively; and the method is critical to evaluate the insulation state of the GIS and formulate a reasonable maintenance strategy.

The invention discloses a multi-state system dynamic reliability assessment method. According to state information monitored by multi-state systems and constitution logic of units in the multi-state systems, current state probabilities of the units in the multi-state systems are calculated by building a Bayes recursive model, and therefore the state probabilities and reliability of the multi-state systems in the surplus service period are deduced. The method makes full use of the state information monitored by each system to update a reliability assessment model. Compared with an existing reliability assessment method, the multi-state system dynamic reliability assessment method can achieve the fact that more accurate and dynamically updated reliability assessment values of each system can be obtained, and therefore each system can be effectively prevented from losing efficacy, and more accurate maintaining strategies are generated in a guided mode.

The invention relates to an access prediction-based data cache strategy for a P2P Video-on-Demand (VoD) system server. The strategy comprises a data access classification and prediction strategy, a data prefetching strategy and a cache queue maintenance strategy, wherein the data access classification and prediction strategy is in charge of classifying data requests of the server, performing access prediction on different types of requests by different methods according to the application characteristics of the VoD, and predicting data access targets of nodes, which perform the data requests, in the future; a cache queue maintenance sub-strategy is in charge of maintaining a fixed-length cache queue and performing inserting, deleting and replacing operation of the cache queue by a future access frequency-based cache replacement algorithm; and the calculation of the future access frequency synthesizes the probability of the cache item accessed sequentially and randomly in the future and takes consideration on the influence factors of data access stability such as on-off line of the nodes in the P2P VoD system, server replacement and the like.

The invention discloses a method for optimizing reliability and maintenance strategy of a piece of chemical refining equipment. The method comprises the following steps of collecting the historical testing and maintaining data of equipment inside a chemical refining device; carrying out the regression analysis by a failure distribution function for the historical data to obtain the characteristic parameters of the reliability and maintenance of single equipment; establishing a mathematical simulation model of system reliability of the chemical refining device, and collecting the relevant economic parameters of the device; carrying out the system simulation analysis for the chemical refining device by using the mathematical simulation model of system reliability, then obtaining the characteristics parameters of system reliability, usability and maintenance of the device, and then further obtaining the testing and maintaining scheme of the optimized system equipment, such as inspecting and maintaining order, frequency and cost; and obtaining the spare part stock scheme of the optimized system equipment, such as purchasing quantity, purchasing cycle and spare part stock, thus adjusting the equipment managing strategy of the device. The method for optimizing the reliability and maintenance strategy of the chemical refining equipment reduces the unplanned fault rate of the chemical refining equipment, and provides guarantee for long-period safety operation of the chemical refining equipment.

The invention provides a power equipment operation and maintenance service system and method based on a cloud service platform. The system comprises a cloud platform comprehensive management module, a cloud client application module and a cloud database, wherein the cloud platform comprehensive management module and the cloud client application module perform information interaction through a TCP/IP communication protocol to provide services for operation and maintenance of power equipment. Through the power equipment operation and maintenance service system and method, all kinds of information collected in the operating and maintaining process of the power equipment can be managed and analyzed, the problems that a current power equipment state diagnosis system has a single function, information is isolated, formats are disordered, input is repeated, operation is inconvenient, and data overall management is lacked are solved through virtualized and distributed computing resources and networked computing power, and an intensive, intelligent and comprehensive equipment operation and maintenance strategy is provided for operation and maintenance of the power equipment and work of maintainers.

The present invention provides a method and a system for inspecting and maintaining equipment. According to the method, an equipment functional part is adopted as an object. After that, an inspection and maintenance strategy, spare part materials, an inspection and maintenance standard, and an inspection and maintenance service process, which are adaptive to the technical characteristics of the equipment functional part, are established. The method specifically comprises the steps of S1, identifying the critical functional part of the equipment; S2, establishing a standing book for the critical functional part; S3, conducting the factor and precautions analysis on the critical functional part of the equipment; S4, according to the factor analysis result, establishing an inspection and maintenance structure; S5, according to the inspection and maintenance structure, establishing the inspection and maintenance operation standard for the equipment; S6, setting the inspection and maintenance service flow; S7, according to the inspection and maintenance service flow, conducting the routine inspection and maintenance on the equipment. According to the technical scheme of the invention, the service management process and the service operation behavior of the equipment are in the controlled state. Therefore, the efficient and stable operation of equipment is guaranteed. The quality requirements of products are met and the safety production is ensured.

The invention relates to a clustering time synchronization method combining topological maintenance. The method comprises the steps that in the election stage, the system selects a node of the maximum connectivity to act as a network root node; in the clustering stage, network clustering is completed with the network root node acting as the start under the scene of network event asynchronization and equipping a directional antenna, and network initial synchronization is also completed; in the synchronization stage, the synchronization effect is stabilized through intra-cluster and inter-cluster synchronization; and in the maintenance stage, maintenance strategy analysis is performed on mobile network accessing and network withdrawing of the node. Compared with the methods in the prior art, the clustering time synchronization method has excellent synchronization performance and can greatly solve the problem of clustering synchronization based on a beam forming antenna, the synchronization efficiency can be effectively enhanced by adopting an inter-cluster synchronization priority policy, and the influence caused by dynamic network topology can be greatly adopted by combining topological maintenance.

The invention discloses a power communication transmission network operation trend analysis method. The method is characterized by comprising the following steps: (1) real-time performance monitoring: monitoring the performance of network equipment in real time during transmission network daily operation monitoring; (2) performance trend and early warning analysis: entering a processing link when finding performance fault early warning, calculating the early warning index of monitored performance data according to an early warning algorithm, and grading the early warning according to predetermined levels of faults in aspects of importance, range and urgency; (3) maintenance strategy management: proposing an equipment maintenance strategy including the maintenance object, time, estimated root, influence scope, required resources and the like for different levels of early warning faults according to predetermined rules and further formulating a maintenance task suggestion; and (4) maintenance execution: assisting in forming a maintenance plan according to the maintenance strategy and completing on-site maintenance work according to the maintenance process.

The invention relates to a method for measuring a converter transformer paper oil insulation partial discharge characteristic, and belongs to the technical field of insulation detection of high-voltage electrical equipment. The converter transformer paper oil insulation partial discharge phenomenon belongs to a random process, in the method, based on the relation between the discharge capacity and the time interval in the discharge phenomenon, a series of relational graphs are built, and statistic characteristic parameters of partial discharge are extracted from the rational graphs, wherein the parameters include a degree of skewness Sk (representing the deviation degree of a spectrogram distribution curve relative to normal distribution), a kurtosis Ku (representing the sharpness of the spectrogram distribution curve relative to normal distribution), a Weibull distribution parameter scale parameter alpha and a shape parameter beta. Twenty characteristic parameters obtained by the method are used as the criterion for judging the types and order of severity of the converter transformer paper oil insulation partial discharge, according to the criterion, operators make a rational state maintenance strategy for the converter transformer, and a reliable technical support is provided for manufacturing and operating of the converter transformers.

The invention provides an optimization method for the periodic preventive maintenance strategy of a repairable degraded system. The reliability model of the repairable degraded system under the cumulative Poisson shock is classified, a suitable reliability model is selected according to the situation and simplified, and the It is applied to the preventive maintenance strategy optimization model as a constraint condition, and a more practical preventive maintenance strategy optimization model is obtained. The invention comprehensively considers the system maintenance cost and the probability that the system is in a normal state at any time, and determines the optimal preventive maintenance period and the system update period under the premise of satisfying the reliability index. It avoids the loss of human and material resources caused by excessive maintenance, and also avoids inconvenience and economic losses caused by untimely maintenance, and obtains maximum benefits for the company in system maintenance. It can also guide enterprises to formulate reasonable equipment maintenance strategies and reduce production costs.

The invention relates to a maintenance decision-making method based on equipment comprehensive health condition analysis and management. The maintenance decision-making method comprises the followingsteps: collecting data; carrying out equipment hierarchical division; acquiring key equipment; evaluating the risk level of key equipment; evaluating the state monitoring grade of the key equipment; evaluating the reliability level of key equipment; key equipment health conditions; maintenance decision making; device fault management. According to the method, the health condition of the equipmentis comprehensively evaluated from three aspects, namely the reliability level, the risk level and the state monitoring level of the equipment, and the situation that the health condition of one part of equipment is obtained from one side to be overhauled or lost is avoided. A corresponding maintenance strategy is given in combination with the health condition of the equipment, the service life ofthe equipment is prolonged to the maximum extent, and maintenance cost is saved. The fault tree is combined with the state monitoring relation variable of the equipment, and the fault type of the equipment is automatically judged by utilizing the change condition of the relation variable so as to give a reasonable maintenance strategy. The equipment fault, the maintenance record and the operationof the equipment form a closed-loop influence, and the newly added equipment fault record is used as basic data of reliability calculation to re-optimize the reliability model so as to reflect the reliability state of the equipment more accurately and discover the fault of the equipment in time.

The invention discloses a garden maintenance management service system and method. The system comprises a sensor, a monitoring station, a network server and a mobile terminal, wherein the sensor is connected with the monitoring station; the monitoring station is connected with the network server; the network server is wirelessly connected with the mobile terminal; and a maintenance worker has the mobile terminal. The method comprises the following steps: the sensor is used for collecting garden information, the monitoring station is used for obtaining the garden information collected by the sensor, the monitoring station uploads the garden information to the network server, and the maintenance worker obtains the processed maintenance information through the mobile terminal and guides maintenance work. Garden maintenance and remote management control are combined, the garden information is detected, a maintenance strategy is made according to plant attributes, the garden information and the maintenance strategy are processed as big data so as to improve a green plant landscape effect and guide a garden maintenance process, and the scientific management and the integrated management of the garden green plate are realized. The system and the method also have the advantages that resource configuration is optimized, management cost is lowered and the like.

The invention discloses a general fault detecting and maintenance method for equipment. The general fault detecting and maintenance method for the equipment comprises the following steps of carrying out modeling on maintenance knowledge of the equipment faults, automatically detecting and diagnosing the faults and carrying out auxiliary maintenance based on a model, simulating maintenance training based on the model, optimizing an experience knowledge model in real time in the maintenance training process, and synchronizing maintenance information and experience knowledge model information in the maintenance training process. Compared with an existing equipment maintenance method, the general fault detecting and maintenance method for the equipment enables the accumulation and the sharing of equipment maintenance experience knowledge and the automatic diagnosis of equipment faults to be achieved, and assistance can be provided for related maintenance strategies through the analysis and the exploitation of the maintenance record information. In addition, effective transmission of the experience of experts to primary maintainers is achieved through the step of simulation training. The general fault detecting and maintenance method for the equipment is especially suitable for chemical defense troops and other occasions where a large amount of complex equipment needs to be maintained frequently and where the turnover rate of maintenance personnel is high. Practice proves that the general fault detecting and maintenance method for the equipment can obvious improve equipment maintenance efficiency, promote maintenance levels and improve maintenance quality.

The invention discloses a method for analyzing a running trend of an electric power communication transmission network. The method is characterized by comprising the following steps: (1) acquiring basic data, and providing dynamic parameters and static parameters for a trend analysis model; (2) performing mutation analysis on performance; judging whether the acquired dynamic parameters are out of limit or not based on a performance parameter early warning threshold value; directly generating a performance alarm if the acquired dynamic parameters are out of limit; (3) performing trend analysis when the performance is steadily changed; constructing an error rate and optical power analysis model according to dynamically acquired performance parameters by adopting secondary dynamic exponential smoothing; obtaining a trend analysis weight through a steepest descent iteration method by combining the dynamic parameters and historical data, and further, constructing a linear prediction equation; (4) performing early warning computation, and outputting a performance prediction result. The method disclosed by the invention is applied to a communication management system, and therefore, a powerful data support is provided for the whole-process intelligent computational analysis from data acquisition, trend prediction, early warning analysis and a maintenance strategy.

The invention provides a method, device and system for regulating an operating state of a server, and the method comprises the steps: determining at least one monitoring index of the server and the threshold range and maintenance strategy corresponding to each monitoring index; and transmitting the maintenance strategy corresponding to the monitoring index to the server when the current measurement value of any monitoring index is obtained if the current measurement value is within the threshold range corresponding to the monitoring index. The method can monitor whether the server works normally or not according to the measurement values of all monitoring indexes of the server, and can carry out regulation and timely removing of abnormality in a targeted manner through a corresponding maintenance strategy, thereby avoiding the hidden troubles. Therefore, the method can carry out the timely maintenance of the sever with an abnormality.

The invention relates to a method for diagnosing the severity degree of a transformer fault. The method comprises analyzing the gas content in transformer oil by using chromatography; accumulating the dissolved gas content in the transformer oil tested over a certain period; calculating the nitrogen or total hydrocarbon absolute aerogenesis rate and the change rate of the aerogenesis rate; and drawing a diagram, in which the absolute aerogenesis rate is the vertical coordinate and the time is the horizontal coordinate; and judging whether a fault occurs to the interior of a transformer according to the absolute aerogenesis rate and the change rate of the aerogenesis rate. According to the method, the development and the severity degree of the fault in the interior of the transformer are judged by calculating the absolute aerogenesis rate and the change rate of the aerogenesis rate in a mode of diagram; a corresponding transformer monitoring and maintenance strategy is made; the accurate master of the operation and the interior fault situation of the transformer is achieved; the security operation of the transformer in a power grid is guaranteed; and the accident that the transformer is damaged is prevented.

The invention provides a single event upset fault processing method based on an AT697 processor. The method comprises a step 101) of defining the format of variables of the AT697 processor, a step 102) initializing the data of an Error Detection And Correction (EDAC) functional module and a Random Access Memory (RAM)space of the AT697 processor, a step 103) detecting and modifying errors, caused by single vent upset, of an RAM or Electrically Erasable Programmable Read-Only Memory (EEPROM) connected with the EDAC module, and a step 104) of establishing a maintenance strategy and carrying out initiatively periodic traversal access to the storage spaces of all RAMs and EEPROMs, thereby reducing and eliminating single bit errors. The single event upset fault processing method is used for providing a set of complete software processing design scheme for spatial single event faults according to the characteristic that the AT697 processor provides an EDAC detection interface. The single event upset fault processing method does not need to add an extra chip, so that the weight, volume and power consumption of equipment are not increased; the processing method is simple and efficient; the single event upset fault processing method is flexible in interfaces and high in portability, and has great significance for improving the reliability and safety of satellite development of China.

The invention discloses an optical fiber state evaluating method based on the combination of an improved membership function and a neural network, and relates to the technical field of optical fiber circuit state evaluating and analyzing. The problems that potential failures in a circuit state can not be analyzed and evaluated in the prior art and failures going to happen can not be avoided are solved. By means of the evaluating and analyzing method, the membership weight of an attached optical fiber state membership comprehensive evaluating method is optimized and combined through an improvedEuclidean distance formula, the circuit state healthy degree is accurately evaluated and analyzed, whether potential failures exist in a circuit or not is analyzed, a maintenance strategy is formulated in advance, and the requirement for optical fiber communication ceaseless transmission is met. By means of an RBF neural network evaluating and analyzing model, evaluating performance has good fitting precision and convergence speed, and the evaluating of the optical fiber state is better achieved.

The invention discloses a predication method for electric power optical fiber communication optical power, relates to the technical field of optical fiber communication predication, and solves the problems that analysis and predication of a circuit state tendency cannot be achieved in the prior art and accordingly impending faults and the like cannot be avoided. According to the method, an improved particle swarm optimization algorithm is provided to optimize parameters in a predication model, so as to achieve a mixed predication based electric power optical fiber communication optical power predication method, accurately predicate a future state tendency of a circuit, predicate future possible faults of the circuit, make a maintenance strategy in advance, avoid fault generation and satisfy an optical fiber communication requirement for intermittent transmission. According to the predication method for the electric power optical fiber communication optical power, the parameters of the SVM model are optimized through the improved particle swarm optimization algorithm, the model not only has a quick operation convergence rate, but also has good predication accuracy and stability, a mixed predication model is adopted, respective advantages of every single predication model are effectively composited, mutual disadvantages are remedied, and improvement of the performance of the integral predication model is facilitated.

The invention relates to an electric transmission line maintenance plan optimization method and system based on manifold learning. The method comprises the following steps: extracting state variable information of an electric transmission line, and performing a state evaluation and a risk assessment on the electric transmission line; combining a transmission line state evaluation result and a risk assessment model with a local operation and maintenance strategy library to make an operation and maintenance strategy; determining an optimization object, and building an operation and maintenance multi-objective optimization model of the electric transmission line; performing a dimensionality reduction solution on a decision variable in a mathematics model by adopting a multi-object manifold learning method, thus acquiring an optimized operation and maintenance strategy of the electric transmission line; and performing research and development on an operation and maintenance system of the electric transmission line to realize intelligence and high-efficiency generated by the operation and maintenance strategy. By adopting the electric transmission line maintenance plan optimization method and system based on manifold learning, the operation and maintenance strategy of the electric transmission line can be made optimally, and the economy, reliability and safety are improved.