184 results about "Optimal maintenance" patented technology

In an embodiment of this invention, a diagnosis engine refers to a risk assessment DB and anti-risk measure DB, calculates along the time sequence a risk estimate amount in case of failure for each device and a maintenance cost in executing a measure method in advance, and adds the risk estimate amount and maintenance cost along the time sequence to calculate an optimum maintenance period of the device. When a failure has occurred in the device, the diagnosis engine refers to a failure diagnosis DB on the basis of the identification information of the device and the failure mode and analyzes, on the basis of an operation record, a failure which is different from a secular change.

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 belongs to the field of maintenance decision-making of hydraulic equipment, and relates to a method for the optimal maintenance decision-making of hydraulic equipment with risk control. The method mainly comprises three steps: 1) judging whether a system is in a status of defect by using a variable-weight association rule algorithm, if so, calculating the probability values of occurrences of latent faults of the system; 2) calculating the comprehensive evaluation value for the consequence of each latent fault by using a BP neural network; and 3) multiplying the probability values obtained in step 1 by the comprehensive evaluation values obtained in step 2 so as to obtain the VaRs (values-at-risk) of the latent faults, judging whether the VaRs are more than a specified threshold, if so, ranking the VaRs in descending order so as to determine the maintenance sequence; otherwise, returning to the step of monitoring. The method can judge whether a device is in a status of defect, judge the type of the latent fault and calculate the probability values of occurrences of latent faults only through a calculation; and compared with traditional risk maintenance methods, the method of the invention improves the accuracy of fault diagnosis, speeds up the diagnosis speed, and provides a better reference for online decision-making.

Disclosed in the present application are a method and apparatus for timing maintenance under a coverage enhancement mechanism. The method comprises: determining a time domain position for the last repeated transmission of a timing-related physical layer channel; and determining the start time of the timing according to the determined time domain position. According to the embodiment provided in the present application, the start time of the timing is determined according to the time domain position for the last repeated transmission of the timing-related physical layer channel. The invention avoids performing maintenance of said timing in a way as prescribed by the existing standards, and thereby solves the problem of how to perform physical layer channel-related timing maintenance under a coverage enhancement mechanism.

The invention discloses a security early warning system and a method based on RAID, which belong to the field of computer system structure storage. The system comprises a fault decision unit, a fault detection unit and a fault simulation unit, wherein the fault decision unit is responsible for collecting the health information of a storage system in real time, and can send early warning information according to the preset health threshold value or other early warning strategies, the fault detection unit detects the operation state of a disc, detects the operation state of the disc array, and detects the sate of the operation environment, and the fault simulation unit is used for disc fault simulation, disc array fault simulation and external environment simulation, and can trigger the fault decision unit for implementing the early warning. The invention also provides a security early warning method based on RAID, and the security early warning is carried out on the storage system by using the system. The system and the method can be used for giving early warning on the fault of the RAID in advance, and users can adopt optimal maintenance management to ensure the data security and the system health.

The invention discloses a multi-component system group maintenance decision method and a multi-component system group maintenance decision device based on prediction. The method comprises the following steps: predicting the residue life of single components at a monitoring time point, and calculating the single-component optimal maintenance time; setting a time window with each monitoring time point as the starting time point and the maintenance preparation duration as the time length, and calculating the single-component optimal maintenance time falling into the time range of the time window; building a penalty function, and acquiring a maintenance group structure with minimum penalty function value and the maintenance group optimal maintenance time according to the calculated single-component optimal maintenance time falling into the time window for each monitoring time point; grouping-maintaining the single components in the maintenance group structure; and after maintenance, continuing acquiring the single-component optimal maintenance time, and so on. According to the invention, the most saving group maintenance mode for maintenance of a multi-component system can be decided according to the predicted single-component residue life, so that the maintenance cost is saved, the downtime is reduced, and the loss is reduced.

The invention realtes to an online service-life management system for the important parts of the host machine of plant-level multi-electric motor machine sets. The invention is characterized in that the system comprises a service-life calculation/ application server and software, a database server, an external system interface, a plant-level supervisory information system SIS, a parameter measuring point, a web page server and a user-end browser. The online service-life management method is that the calculation analysis software for the host machine of the plant-level multi-electric motor machine sets, which is compiled by the C Language, is applied to the calculation/ application server, carries through the online calculation of the transient life loss and the accumulative life loss of the importants parts of the host machine, directs the operational manipulation and the optimal operation of the electric motor machine sets, and recommends the optimal maintenance measures of the plant-level multi-electric motor machine sets. The management system has the advantages of realizing the online management for the important parts of the host machine of the plant-level multi-electric motor machine sets and achieving the technical effect that the service life of the important parts of the host machine of the multi-electric motor machine sets in a power plant are managed by a set of the service-life management system.

Methods and apparatus are provided for determining a lowest total cost maintenance plan. The method comprises receiving a sequence of maintenance actions in an order of a waiting time for each maintenance action, wherein one of the maintenance actions is likely to repair the failure mode. Each maintenance action has an associated cost equal to a waiting time cost, an execution time cost and a material cost, wherein the waiting time of each maintenance action is the time required to requisition and receive material required to perform the maintenance action. The method also constructs a maintenance plan comprising a primary requisition and a secondary requisition by assigning each of the sequence of maintenance actions to one of the primary and secondary requisition.

The invention discloses a network-level road maintenance management decision-making system, which comprises a data management subsystem, a road section sorting platform and a network-level road surface decision-making system, wherein the data management subsystem is used for acquiring and storing spatial data and attribute data of a road; and performing statistical analysis based on each highway,and generating an analysis report and a statistical report based on an analysis result. According to the method, the weight of each influence factor is calculated by adopting an analytic hierarchy process. Wherein each influence factor of the network-level decision comprises road surface performance, road surface structural strength, road surface structural materials, traffic axle loads, road ages, road levels and the like; On the basis of real road information, a road management decision-making system supported by multiple kinds of data is constructed, and a road database is analyzed in a data organization mode, so that maintenance decision making of a road is facilitated; and furthermore, an optimal maintenance strategy can be sought under the constraint of specified budget funds and other resources, so that the benefit target is maximized.

The invention relates to a method for realizing reliability maintenance planning of a high temperature pipeline system, which comprises the following steps of: collecting and acquiring detection data of a high temperature pipeline system; calculating a finite element of the high temperature pipeline system; determining creep damage parameters according to the influence degree of all factors on the life of the high temperature pipeline; creating a creep damage probability model through determining the probability distribution of the creep damage parameters; calculating a structural failure probability according to the creep damage probability model; creating a maintenance planning model based on reliability analysis according to the detection data, test results of materials and structures of the high temperature pipeline system and the structural failure probability; and carrying out calculation processing according to the maintenance planning model to obtain the optimal maintenance time of the high temperature pipeline system. By adopting the method for realizing the reliability maintenance planning of the high temperature pipeline system, the structural reliability is determined efficiently and accurately, a maintenance scheme can be accurately determined, the similar problem of the maintenance planning of the high temperature pipelines in other fields can be solved, and the method has wider application range.

The invention discloses a fault work order distribution method and a fault work order management system. The method comprises the steps of collecting fault work orders of a plurality of electrical devices; extracting a characteristic quantity of a fault type in each fault work order, judging the level of each fault type, and dividing the fault type of the electrical equipment into a plurality of levels in advance according to the influence degree of the fault type; and matching the optimal maintenance personnel for the fault work orders corresponding to different fault types according to the descending order of the levels, and automatically distributing the optimal maintenance personnel. According to the invention, high efficiency and high quality of mass fault work order distribution workare ensured.

The invention discloses a reliability-based preventive maintenance optimization method for multi-components of metro vehicles, A method for determine that optimal maintenance interval of a single component of a metro vehicle is proposed, that is to say, imperfect maintenance mode is applied to each single component, based on component maintenance economy and train availability, By comparing the effects of component faults on equipment safety, the optimal maintenance interval is determined. Secondly, the opportunistic maintenance threshold delta t is introduced, and the opportunistic maintenance strategy of metro train multi-component system considering the time correlation between components is adopted. According to the operation and maintenance characteristics of metro train, the opportunistic maintenance model of metro train multi-component system is established. Finally, the steps to solve the model are given. On the premise that the invention can meet the reliability requirement, the maintenance cost and the train availability are optimized simultaneously, and the optimal maintenance plan can be obtained by solving the problem, thereby providing theoretical support for the maintenance optimization of the metro train.

The invention relates to a power equipment maintenance decision-making method, and particularly relates to a power equipment maintenance decision-making method utilizing an equal degradation theory and equipment risks. According to the invention, the equal degradation theory is introduced into the power industry, analysis and comparison are performed on changes in equipment risk before and after maintenance by sufficiently considering changes in equipment failure probability before and after maintenance, and the equipment maintenance cost is considered so as to acquire an optimal maintenance scheme. The power equipment maintenance decision-making method starts from the view of asset management, the cost required by equipment in the whole life cycle is enabled to reduce to minimum, and a balance point is found between self values of the equipment and economic benefits brought by the equipment to a system, between LCCM (Life Cycle Costing Management) and equipment maintenance and between technologies and management of the power system.

The invention discloses an equipment maintenance management method and system and a computer readable storage medium, and the method comprises the steps: determining key equipment and non-key equipment, and obtaining the maintainability and reliability parameters of each key equipment; quantitative simulation analysis is carried out on the maintenance activity of each key device, and an optimal active maintenance strategy and key maintenance parameters are determined; according to the result of the quantitative simulation analysis, determining an optimal maintenance plan which enables the sumof the maintenance costs of all the devices maintained by adopting the active maintenance strategy not to exceed the active maintenance budget and the sum of the maintenance costs of all the devices maintained by adopting the passive maintenance strategy to be minimum, and obtaining a maintenance strategy which should be adopted by each device; and generating an equipment maintenance task according to the optimal maintenance plan and the equipment repair request record. Expert experience analysis is replaced by computer-aided scientific analysis and calculation, the result objectivity is ensured, and the workload of maintenance plans is reduced.

The purpose of the invention is to provide a maintenance decision-making method for a diesel engine fuel oil system through cost analysis in combination with a Bayesian network model. The method comprises the steps of: firstly, establishing the Bayesian network model of the diesel engine fuel oil system, and carrying out fault diagnosis on the fuel oil system based on the model to obtain an occurrence probability of each fault; secondly, carrying out non-dimensional processing on factors which influence a maintenance operation cost of the fuel oil system by use of a standardization formula; thirdly, fusing a plurality of influence factors in maintenance operations by use of an RBF (Radial Basis Function) neural network, and evaluating a corresponding maintenance cost; and finally, comprehensively evaluating a fault occurrence probability and a maintenance cost through a multiplication formula, and ordering the maintenance operations according to a product decreasing rule to obtain an optimal maintenance strategy of the fuel oil system. According to the method, through the cost analysis in combination with the Bayesian network model, the fault probability and the maintenance cost are comprehensively evaluated, and a decision making is carried out on a maintenance strategy of the fuel oil system so that a decision-making result has reference value.

The invention relates to an offshore wind turbine generator maintenance path stochastic planning method considering a wake effect. The method comprises the following steps: 1) describing correlation and uncertainty of wind, waves and surges in ocean weather; 2) considering the cost composition of personnel, ships, punishment and shutdown loss, taking the minimum maintenance cost as an objective function, and constructing corresponding constraint conditions based on the influence of wind, waves and surges on the navigation time of the ships and the accessible windows of the ships; 3) because the maintenance state changes the wake flow distribution among the units, describing the change of the input wind speed of each unit in combination with the wake flow model and the maintenance state, and refining the unit shutdown loss in the objective function; and 4) solving the target function to obtain an optimal maintenance path. Compared with the prior art, the method has the advantages of high adaptability, high economy, high solving speed and the like.

The invention discloses a fleet maintenance decision method based on CBM (condition-based maintenance), so as to solve the problem that the existing method aims at a civil aero engine and an unstructured part, the single plane retention rate can not reach training requirements, and the fleet maintenance cost is not considered. The method comprises steps: 1, the residual life predication on the plane fatigue structure is carried out, and the remaining life of the fatigue structure is obtained; 2, according to the obtained remaining life of the fatigue structure, a single plane maintenance costdecision optimization model is built; 3, according to the single plane maintenance cost decision optimization model built in the second step, a fleet maintenance cost decision optimization model is built; 4, a fleet retention rate optimization model is built; and 5, a multi-objective optimization decision model for the fleet is built according to the third step and the fourth step, and according to the multi-objective optimization decision model, a nondominated sorting multi-objective optimization algorithm method is adopted to determine the optimal maintenance scheme for the fatigue structureof each plane in the fleet. The method is used in the fleet maintenance field.