26 results about "Planned maintenance" patented technology

The invention discloses a health monitoring system of a speed reducer, and belongs to the field of mechanical equipment state monitoring. Comprising a sensor module, a data acquisition module, a data processing module, an early warning module and a display module, the sensor module comprises a displacement sensor, a pressure sensor, a rotating speed sensor, a vibration sensor and a temperature sensor, and the displacement sensor and the pressure sensor are arranged at the position of a brake piston of the speed reducer and used for monitoring piston displacement and brake pressure in real time; the rotating speed sensor is arranged at the output end of the reducer and used for monitoring the output rotating speed of the reducer. Real-time monitoring of key parameters of the speed reducer is achieved through multi-sensor fusion, potential faults can be found in time, and fundamental transformation from passive maintenance to active early warning and from planned maintenance to predicted maintenance is achieved. The brake performance and the abrasion degree of a friction plate are accurately evaluated through combined monitoring of displacement and pressure of a brake piston; and early fault diagnosis is realized through spectrum analysis of the vibration signals.

The utility model discloses a rotary drum stirring suspension shaft assembly which comprises a suspension shaft, a bearing box, a bearing gland and a self-aligning roller bearing, the self-aligning roller bearing is connected to one end part of the suspension shaft in a sleeving manner; the bearing box covers the outer parts of the self-aligning roller bearing and the suspension shaft; and a bearing gland is arranged at an opening, close to the self-aligning roller bearing, of the bearing box. The shaft sleeve is transformed into a rolling bearing supporting structure, so that the abrasion of the suspension shaft is obviously limited. Therefore, the risk of abrasion and leakage of the box body is reduced. The equipment operation period is prolonged, the maintenance frequency is reduced, the bearing is convenient to disassemble and replace during planned maintenance, the drum core does not need to be hung, and the maintenance risk and the maintenance time are reduced.

The utility model discloses a hydro-generator thrust bearing elastic oil tank which comprises an oil tank seat and supporting iron, the supporting iron is installed in the oil tank seat, the upper end of the supporting iron is fixedly connected with the oil tank seat, a cavity is formed between the interior of the oil tank seat and the supporting iron, the side wall of the oil tank seat is of a corrugated pipe structure, and the bottom supporting face in the oil tank seat is a downwards-concave arc face. The lower end part of the supporting iron is a downwards convex cambered surface; and the curvature radius of the bottom supporting surface is greater than that of the lower end part. According to the utility model, the lower end part of the supporting iron is improved to be the downwards convex cambered surface, the bottom supporting surface in the oil tank seat is improved to be the downwards concave cambered surface, and the curvature radius of the bottom supporting surface is greater than that of the lower end part, so that the supporting iron can be adaptively swung and finely adjusted after the elastic oil tank loses efficacy, and the thrust bearing bush is stressed more uniformly; the elastic fuel tank can still insist to run for a period of time after failure, and preparation time is provided for planned maintenance.

The invention provides a rail vehicle direct maintenance cost target allocation method, which comprises the following steps of: 1, determining influence factors, and identifying seven types of core influence factors, namely complexity, technical maturity, environmental factors, utilization rate, severity, accessibility and repair material cost, based on a plan maintenance cost model and a non-plan maintenance cost model of a DMC; 2, determining an assignment range and a standard of each influence factor; step 3, according to the range and the standard of the step 2, assigning each influence factor of each system; 4, calculating a DMC comprehensive score of each system; 5, calculating a DMC proportion and a DMC distribution value of each system, judging whether the distribution value needs to be adjusted, if so, returning to the step 3, and if not, executing the step 6; and step 6, outputting a final DMC distribution result. According to the method, seven types of core influence factors are identified through the planned maintenance cost model and the non-planned maintenance cost model based on the DMC, and the accuracy and rationality of DMC distribution are remarkably improved.

This invention discloses a time-axis-based method and device for visualizing the risks of optical transmission systems, relating to the field of risk visualization technology. This invention constructs a mapping between the time axis and the maintenance link by acquiring planned maintenance information, combines link disconnection simulation to locate target services affected at different times, and then assesses the risk level of the service links and maps them into a topology visualization graphic. This achieves a closed-loop process for handling affected services in scenarios with simultaneous maintenance of multiple transmission paths or nodes, moving from inefficient manual analysis to automated system identification, quantitative assessment, and intuitive presentation. This significantly improves the efficiency and accuracy of service impact analysis and overcomes the decision-making lag problem caused by cumbersome manual derivation in complex maintenance scenarios using traditional methods.

The invention provides an intelligent load transfer auxiliary decision-making method and system, and belongs to the technical field of power grid dispatching automation. In order to solve the problems that an existing intelligent decision-making system cannot be used when data is missing, wrong or delayed due to excessive pursuit of data completeness and algorithm accuracy, and even misleads decision making, a light-weight decision-making design concept oriented to data authenticity is provided. The system actively abandons dependence on non-essential data, strictly limits a data input source as a limited data set which is highly trusted and inevitably used in daily work of a dispatcher, and the limited data set comprises switch displacement, recent steady-state load stored before a fault, an equipment rated parameter table and planned maintenance information.

The invention relates to an automatic control method and system for a concrete mixing plant, and belongs to the technical field of concrete production control, and the method comprises the steps: collecting the operation state data of key equipment in a mixing plant production line in real time; inputting the operation state data into a preset equipment health prediction model to generate predictive maintenance information for the key equipment; when the early warning key equipment meets the condition that the corresponding predictive maintenance information meets a preset early warning condition, a production scheduling plan is dynamically adjusted based on the predicted fault time point corresponding to the early warning key equipment, and a planned maintenance window before the corresponding predicted fault time point is planned for the early warning key equipment; the maintenance personnel are reminded to maintain the early warning key equipment during the planned maintenance window; wherein in the planned maintenance window, other parts except the early warning key equipment normally operate on the production line of the mixing plant. The device has the effect of improving the production efficiency under the abnormal condition of the stirring station equipment.

The present application relates to the technical field of structural health monitoring and artificial intelligence, and discloses a steel structure corrosion prevention evaluation system based on environmental data and AI, which comprises a data sensing module, an environmental index generating module, an impact function generating module, a stress-corrosion coupling effect model constructing module, a steel structure life prediction module, a grading early warning module and a system self-learning module; the present application can quantify the corrosion impact of environmental emergencies and realize advanced early warning; for the first time, real-time stress monitoring data is directly incorporated into a corrosion life evaluation model, and the coupling effect of stress corrosion is accurately depicted; modeling and prediction are carried out for the unique environment and stress state of each specific structure, and the results are more instructive; the present application realizes the transformation from planned maintenance to condition-based maintenance, avoids waste caused by excessive maintenance, prevents risks caused by insufficient maintenance, and significantly reduces the life cycle cost.

The invention relates to a road condition index prediction method and system based on index attenuation. The method comprises the following steps: firstly, obtaining historical and planned maintenance information, road condition data and road surface types of a target road, calculating annual index attenuation values of various road surface types, extracting sample paragraphs of specified road surface types, calculating historical annual interval attenuation values of the sample paragraphs, and further obtaining a latest annual attenuation value through a weighted average algorithm; dividing a target road into basic road units, determining the latest road surface type of each unit by using a time sequence covering method, and matching a corresponding attenuation value; and finally, subtracting the attenuation value from the latest annual road condition index value to obtain the predicted annual road condition index of each unit. According to the method, data-driven attenuation law analysis is adopted, weighted average and time sequence coverage technologies are combined, the accuracy of road surface technical condition index prediction is improved, and maintenance road section selection, scheme making and resource allocation decision making can be effectively guided.

The invention provides a method for predicting fatigue cracks of a welding structure. The method comprises the following steps: S1, accurately acquiring the crack length and the maximum crack depth of a sample under different cycle times; and S2, obtaining a fatigue crack propagation model formula, namely, the unit is as follows. S3, if the crack depth is L1 when the fatigue test is circulated for N1 times, and the cycle index corresponding to the crack depth L2 is N2, N2 is calculated according to the following formula. According to the method, the maintenance interval can be scientifically prolonged or maintenance can be arranged in advance by establishing the crack propagation model and predicting the residual life of the structure, and if the residual life predicted by the model is far longer than the next planned maintenance period, the maintenance period is properly prolonged to save docking cost, labor loss and the like; if the residual life predicted by the model is lower than a safety threshold value, overhauling is arranged in advance, and hidden dangers are eliminated to avoid sudden disasters and accidents.

The invention provides a nuclear power equipment maintenance isolation ring planning method and system, and the method comprises the steps: collecting equipment information and region division information of a nuclear power station, rating each to-be-maintained equipment according to the equipment information, and obtaining a rating report of each equipment, the equipment information represents the current condition of the equipment, and the region division information represents the current condition of the equipment; the device level in the rating report is used for determining an isolation index; acquiring historical maintenance data of each device, and preprocessing the historical maintenance data; performing comparison processing analysis on the rating report and historical maintenance data, and determining an overhaul risk grade of each device; and dividing a corresponding maintenance isolation ring for each device in combination with the region division information and the maintenance risk level and maintenance efficiency of each device. According to the method, the difference between the set area size of the maintenance isolation ring and the actual demand can be reduced, and the reasonability and accuracy of the divided maintenance isolation ring are improved.

The invention relates to the technical field of intelligent maintenance of the Internet of Things, and discloses a UV printing remote monitoring and maintenance system based on the Internet of Things, and the system comprises a data collection and preprocessing module which collects the operation parameters and environment data of UV printing equipment, and carries out the data preprocessing and state evaluation; the maintenance scheduling and resource coordination module is used for dividing the UV printing equipment network into a plurality of regional maintenance centers, constructing a deep Q network maintenance scheduling model, learning an optimal maintenance strategy and realizing resource coordination among regions; the intelligent contract and path optimization module automatically distributes and executes maintenance tasks and plans maintenance paths of technicians; the maintenance quality evaluation module is used for evaluating the maintenance task completion degree and updating the reputation value of a technician; the knowledge sharing and model optimization module is used for realizing maintenance knowledge sharing and model optimization among equipment; according to the invention, a decentralized architecture is adopted to eliminate the single-point fault risk, and the stability and reliability of the whole system are ensured.

The application discloses a kind of rotary drum granulator gear ring support plate replacement frock and method, including support seat, push-pull piece and extrusion piece, the support seat includes seat plate, the two ends of seat plate upper side are respectively provided with clamping groove, clamping groove is used to clamp support plate, the two sides of seat plate middle part are respectively installed with push-pull piece, and one extrusion piece is jointly installed on the push-pull piece of two sides, and extrusion piece is located the upper side of seat plate.Can be bent adjustment to support plate in the narrow space between rotary drum and gear ring, make support plate adapt to the angle change of base mounting surface caused by rotary drum deformation, realize the replacement of support plate.And can replace support plate in half-day time of monthly planned maintenance.

We provide the system. [Solution] A means for receiving information on production machinery and its operating status acquired from a data acquisition module, and for analyzing said information to optimize the manufacturing process, A means for analyzing visual information of a product received from an image acquisition module and detecting product defects based on said visual information, A means to monitor the status of equipment, identify signs of equipment failure using predictive technology, and support planned maintenance, A means of providing work instructions and warnings to workers in real time and supporting their work, A means for visualizing the status data of factory machinery and displaying analysis results that support the improvement of production efficiency, A system that includes this.

The application provides a power distribution network plan maintenance optimization method based on network reconstruction interval optimization, comprising: constructing an upper maintenance time optimization model with the lowest total maintenance cost as an objective function; constructing a lower power distribution network reconstruction interval optimization model with the minimum energy loss of the maintenance period as an objective function; performing cyclic solution iteration calculation on the upper maintenance time optimization model and the lower power distribution network reconstruction interval optimization model to determine the optimal maintenance period of the power distribution network equipment and the power distribution network reconstruction strategy in the corresponding period. The method solves the problems that the traditional maintenance optimization does not fully consider the uncertainty of the operation of the power distribution network and the maintenance scheme pays attention to the economy and to some extent ignores the power supply reliability, and obtains a more economic and reliable power distribution network maintenance plan optimization scheme.

The invention provides a filler friction force diagnosis method and device for a regulating valve. The method comprises the following steps: acquiring air inlet pressure and exhaust pressure of the regulating valve under different valve position percentages; according to the air inlet pressure and the exhaust pressure under the different valve position percentages and the area of an air cylinder diaphragm of an executing mechanism of the adjusting valve, the filler friction force under the different valve position percentages is obtained; obtaining characteristic data of the filler friction force according to the filler friction force under different valve position percentages; and obtaining a diagnosis result of the regulating valve according to the characteristic data of the filler friction force. The filler friction force under different valve position percentages is obtained by obtaining the air inlet pressure and the exhaust pressure under different valve position percentages, then feature data are extracted from the filler friction force, the regulating valve is diagnosed according to the feature data, maintenance or repair suggestions are given, the maintenance or repair date can be pre-judged, and the maintenance or repair efficiency is improved. Therefore, a user can carry out planned maintenance or repair on the regulating valve.

The invention discloses a planned maintenance credit user interface, and provides an aircraft maintenance user interface. The interface includes an alarm indicator that displays an alarm associated with the aircraft system that must be addressed for maintenance compliance of the aircraft. A compliance window indicator displays a normalized slip ratio of a percentage of elapse of a preamble time between an alarm and a maintenance compliance deadline. The remaining unit indicator displays the number of units that have been used among the total number of units that measure the allocation of the remaining preamble time.

This application provides a method and system for managing the entire lifecycle information of power plant equipment, relating to the field of equipment condition monitoring technology. The method includes: acquiring oil index data and vibration data associated with QR code tags; mapping the elemental content in the oil to the source of wear components based on the material composition of equipment parts to construct a wear distribution map; identifying the dominant wear components based on the wear distribution map and extracting state feature vectors; combining the state feature vectors with vibration data and using a particle filter algorithm for state tracking, recursively predicting the remaining lifespan distribution; comparing the remaining lifespan distribution with the planned maintenance window, and pushing maintenance suggestions and writing them into the database when the remaining lifespan is lower than the planned maintenance interval. This application improves the synergy between wear condition assessment and maintenance decision-making for rotating equipment.

Implementations for operational simulations of planned maintenance effects for a plurality of vehicles are provided. One aspect provides a computing system comprising processing circuitry configured to provide a plurality of operational models that comprises a route model, a preparation model, and a planned maintenance model. The processing circuitry is further configured to, using the plurality of operational models, execute an operational simulation that generates interactions between a route simulation and a planned maintenance simulation for a plurality of routes in a route schedule, wherein executing the operational simulation comprises simulating performance of a scheduled maintenance task for a vehicle of the plurality of vehicles and determining an effect of the simulated performance of the scheduled maintenance task on the route simulation. The processing circuitry is further configured to output the effect of the simulated performance.

The application discloses a risk prediction and optimization algorithm in an intelligent civil aviation safety management system, relates to the technical field of risk control, and is used for improving the problem of low module adaptability caused by non-planned maintenance operation and leading to safety hazards, and comprises the following steps: self-inspection and judgment on whether intermittent module operation replacement occurs in the aircraft before and after flight operation, selection of whether to enter a scoring mechanism or a maintenance monitoring mechanism according to a judgment result, monitoring of behaviors of each module in the aircraft when the maintenance monitoring mechanism is entered, identification of a module locking state, explanation of a state change amplitude through a verification mechanism, calling of aircraft log to obtain aircraft maintenance data, combination of the state change amplitude to judge whether the aircraft is subjected to non-planned maintenance operation, acquisition of aircraft flight operation data and module change data, risk classification of the current non-planned maintenance operation, judgment on whether to enter a maintenance interception management system according to a risk classification result, screening of sensitive modules, and judgment on whether to perform alarm processing.

The application relates to the field of civil aviation technology, and relates to a planned maintenance work cost evaluation method and system for a supplier SB / SIL. The evaluation method comprises the following steps: S1, establishing a basic cost motive identification database; S2, establishing an SB / SIL storage analysis database module; S3, calculating and measuring total cost; and S4, outputting a quantitative analysis suggestion report corresponding to whether an SB / SIL maintenance item is implemented. The evaluation system comprises a basic cost motive identification database module, an SB / SIL storage analysis database module, an algorithm matching accounting module and an evaluation report generation module. The planned maintenance work cost evaluation method and system for the supplier SB / SIL can improve the judgment accuracy of whether maintenance work is implemented by a planning maintenance engineering department of an airline, thereby being favorable to saving maintenance costs of the airline, avoiding safety hazards and improving the reliability and safety of airline operation.

The invention belongs to the technical field of factory management, and discloses a factory management method and system based on industrial big data. Comprising the following modules: a data acquisition module used for acquiring state data of production equipment in a plant; by setting the maintenance time prediction model and comparing the predicted maintenance time with the planned maintenance time, the system can automatically calculate the number of maintenance personnel needing to be supplemented and intelligently dispatch support personnel of other workshops based on the principle of proximity, it is ensured that the maintenance task is efficiently completed within the planned time, and the maintenance efficiency is improved. The method greatly improves the utilization efficiency of human resources and the on-schedule completion rate of maintenance tasks, dynamically evaluates the potential productivity of other non-maintenance workshops in the planned maintenance period by setting a maximum production speed prediction model at the production task scheduling level, and calculates the number of products that can be accepted by each workshop. And a production task redistribution scheme is intelligently generated based on constraints such as transportation distance and the like in combination with the number of auxiliary products of the factory building to be maintained.

The invention belongs to the technical field of storage tank detection, and particularly relates to an intelligent storage tank detection method and system based on the Internet of Things technology, firstly, a high-fidelity three-dimensional digital twin model is constructed, and real-time sensing data, static attribute data and historical archive data are uniformly associated and integrated, so that an information island is broken through; secondly, the dynamic risk index and the reference risk index of the storage tank are evaluated and calculated based on the multi-source fusion data, and then the comprehensive risk value of the storage tank is calculated based on the evaluation result of the dynamic risk index and the evaluation result of the reference risk index; then, the risk level of the storage tank is judged according to the calculation result of the comprehensive risk value, finally, early warning is carried out based on the risk level judgment result, and a maintenance strategy is synchronously output, so that precise transformation from planned maintenance to predictive maintenance can be realized, slowly accumulated potential risks of the storage tank can be recognized in the early stage, and the maintenance efficiency is improved. And enough early warning perspectiveness can be provided for the high-risk old storage tank.

This invention discloses a power equipment health assessment and fault prediction system, relating to the field of power equipment monitoring and maintenance technology. The system includes: a data acquisition module, a data processing and storage module, a short-term fault prediction model, a medium-term fault prediction model, a long-term fault prediction model, a model fusion and decision-making module, and a user interface. By integrating short-term, medium-term, and long-term fault prediction models, this invention achieves a comprehensive assessment of the health status of power equipment and fault prediction. The short-term model can quickly capture abnormal changes in the current operating status of the equipment and provide immediate fault warnings. The medium-term model, through a combination of time series analysis and mechanistic models, predicts the performance change trend of the equipment over a future period, providing decision support for planned maintenance work. The long-term model focuses on predicting the remaining lifespan of the equipment, providing an important reference for long-term operation and maintenance planning.

The invention relates to a programmed scheduling execution method based on planned maintenance of a power distribution network, which belongs to the field of power grid scheduling, and comprises the following steps: programmed starting, presetting an initial state of a state machine as to-be-started, automatically associating an application form with a work ticket, verifying information consistency, and switching to start and passing verification after the information consistency passes; programmed power failure is carried out, the system issues a pre-command and a dynamic command to the mobile terminal, command receiving, command returning and operation progress are monitored in real time, and the state is converted into power failure completion; programming permissions, automatically checking security measures, issuing networked permissions, triggering prompts, and converting the state into permissions to complete the permissions; programmed termination: automatically terminating the work ticket and the associated application form after acceptance report, and converting the state into termination completion; programmed power transmission is carried out, power transmission instruction operation is executed, and the state is converted into power transmission completion; programmed stamping is carried out, and application form stamping is automatically completed; the method effectively solves the problems of tedious manual operation and low execution efficiency in the conventional planned maintenance process of the power distribution network.

The invention discloses a charging user portrait precision verification system and method, and relates to the technical field of precision verification, and the method comprises the following steps: first analysis and second analysis: obtaining a first maintenance plan and a first analysis result, executing a first operation, screening a first charging pile, carrying out the first verification of a preset user portrait, and obtaining a second maintenance plan and a second analysis result; and correcting the first verification result, and outputting the corrected first verification result. Through data cross validation of four layers of maintenance, power supply, charging and nature, abstract indexes such as traditional AUC and F1 are converted into absolute error rates of prediction maintenance requirements and actual maintenance requirements, engineering measurability of user portrait precision is achieved, an execution result of each planned maintenance is used as a new sample for backflow, and the accuracy of the user portrait is improved. The portrait model is iterated online along with equipment aging and user habit changes, and manual retraining is not needed.