CN-121146346-B - Full life cycle management method for mountain highway electromechanical equipment

CN121146346BCN 121146346 BCN121146346 BCN 121146346BCN-121146346-B

Abstract

The invention discloses a full life cycle management method of mountain highway electromechanical equipment, which relates to the technical field of intelligent traffic infrastructure management and comprises the steps of inputting a standardized equipment operation data set into a Bayesian network evaluation framework, analyzing posterior probability of each node under the dynamic constraint of environmental parameters through a multi-level fault propagation path, generating an equipment health evaluation report, fusing equipment control execution state records with historical electromechanical equipment operation data, constructing an equipment full life cycle degradation curve through space-time correlation analysis, extracting trend characteristics, separating signals, and generating an equipment full life cycle analysis report. The invention improves pertinence and timeliness of maintenance decision making, and realizes fine monitoring and prediction of the full-period operation performance of the equipment, thereby providing reliable basis for scientifically making maintenance plan, reducing full-life period cost and prolonging the service life of the equipment.

Inventors

WU GANG
LI YOUHE
ZUO RONG
WEN JINGZHOU
YANG XUXIANG
Shengcheng Yaji

Assignees

云南省公路科学技术研究院

Dates

Publication Date: 20260508
Application Date: 20250822

Claims (8)

1. A full life cycle management method of mountain highway electromechanical equipment is characterized by comprising the following steps of, Collecting electromechanical equipment operation data in a mountain highway tunnel, cleaning and standardizing the electromechanical equipment operation data, and outputting a standardized equipment operation data set; Inputting the standardized equipment operation data set into a Bayesian network evaluation architecture, analyzing posterior probability of each node under the dynamic constraint of environmental parameters through a multi-level fault propagation path, generating an equipment health evaluation report, specifically comprising the following steps of, Inputting the standardized equipment operation data set into a Bayesian network evaluation framework according to equipment types and time sequences, mapping the standardized equipment operation data set to physical layer nodes, functional layer nodes and operation risk nodes, and obtaining a three-level node mapping result; According to the three-level node mapping result, combining historical fault data and space-time weight relation among nodes, quantifying causal dependence of each node and constructing a dynamic condition probability table; Based on a dynamic condition probability table, carrying out multi-level fault propagation path analysis, and iteratively calculating posterior probability of each node through forward propagation and backward correction; Mapping the fault risks of the physical layer nodes and the functional layer nodes into equipment health grades according to posterior probabilities of the nodes, forming equipment health state indexes, generating maintenance priorities by combining probability ordering of operation risk nodes, and outputting equipment health evaluation reports; According to the equipment health evaluation report, performing intelligent scheduling and resource optimization on the electromechanical equipment maintenance tasks of the maintenance task queue and the limited resource set to generate an executable scheduling scheme; The method comprises the steps of utilizing an executable scheduling scheme to cooperatively control electromechanical equipment of different types in a mountain highway tunnel, and recording to obtain equipment control execution state records; Fusing the device control execution state record with the historical electromechanical device operation data, constructing a device full life cycle degradation curve through space-time correlation analysis, extracting trend characteristics and separating signals, generating a device full life cycle analysis report, specifically comprising the following steps, The device control execution state record and the historical electromechanical device operation data are aligned according to the device ID, the time stamp and the space position, and a multi-dimensional index structure is utilized to construct a unified data view; on the basis of the unified data view, forming an equipment state evolution association matrix through the state similarity of the electromechanical equipment at adjacent time points and space positions and integrating according to weights; weighting and integrating the state changes of adjacent time points and space positions in the equipment state evolution correlation matrix to construct an equipment full life cycle degradation curve; Carrying out signal processing on a full life cycle degradation curve of the equipment by utilizing a first-order differential processing algorithm, extracting short-term trend change of the electromechanical equipment, and separating long-term degradation trend and periodic fluctuation signals by utilizing a wavelet transformation decomposition algorithm; And integrating the short-term trend change, the long-term degradation trend and the periodic fluctuation signal of the electromechanical equipment to generate a full life cycle analysis report of the equipment.
2. The method for managing the complete life cycle of mountain highway electromechanical equipment according to claim 1, wherein said electromechanical equipment operation data comprises operation state parameters, energy consumption data, environment monitoring data and fault alarm information.
3. The method for managing the complete life cycle of the electromechanical equipment in the mountain highway according to claim 2, wherein said washing and normalizing the operation data of the electromechanical equipment and outputting a normalized operation data set comprises the steps of, Detecting the continuity of the time stamp, the field integrity and the abnormal value of the operation data of the electromechanical equipment, and eliminating the missing and abnormal records to obtain the operation data after cleaning; The method comprises the steps of carrying out unified unit, format and coding on the cleaned operation data, and carrying out normalization processing to obtain standardized operation data; And grouping and storing the standardized operation data according to the equipment type and the time sequence to form a standardized equipment operation data set.
4. The method for managing the full life cycle of the mountain highway electromechanical equipment according to claim 1, wherein the Bayesian network evaluation framework is constructed by determining a three-level node system based on the fault mode and the influence analysis of the electromechanical equipment, quantifying complex causal relationships among nodes through a dynamic condition probability table, and fusing space-time constraints to perform parameter optimization.
5. The method for managing the full life cycle of the mountain highway electromechanical device according to claim 1, wherein the steps of performing intelligent scheduling and resource optimization of electromechanical device maintenance tasks on the maintenance task queue and the limited resource set according to the device health evaluation report to generate an executable scheduling scheme are as follows, According to the maintenance priority in the equipment health evaluation report, generating a maintenance task queue for the electromechanical equipment task to be maintained according to the risk level and the emergency degree; performing attribute modeling on a limited resource set, and calculating the matching degree of each resource and a maintenance task to form a resource availability matrix, wherein the limited resource set is obtained by counting the number of available maintenance personnel, skill level and the type and number of available tool equipment; Inputting the maintenance task queue and the resource availability matrix into an intelligent scheduling algorithm, and performing scheduling optimization according to the task priority, the resource matching degree and the task dependency relationship to generate a preliminary scheduling scheme; And performing conflict detection on the preliminary scheduling scheme, and performing optimization by iteratively adjusting the task sequence and the resource allocation to output an executable scheduling scheme.
6. The method for managing the complete life cycle of the mountain highway electromechanical device according to claim 5, wherein the executable scheduling scheme comprises a maintenance task instruction sequence and a dynamic resource allocation parameter set, wherein the maintenance task instruction sequence comprises an execution time window, a responsible person ID and a required spare part code, and the dynamic resource allocation parameter set comprises a person path planning, a spare part allocation route and a device downtime window.
7. The method for managing the complete life cycle of the mountain highway electromechanical device according to claim 5, wherein the method for managing the complete life cycle of the mountain highway electromechanical device comprises the steps of cooperatively controlling and recording electromechanical devices of different types in a mountain highway tunnel by using an executable scheduling scheme, acquiring a device control execution state record, Analyzing the executable scheduling scheme one by one according to the equipment type and the maintenance sequence, and generating an operation instruction list according to the starting time, the ending time and the allocation resources of each task; issuing an operation instruction list to a corresponding electromechanical device control node, performing cooperative control according to the task sequence and the execution time, and recording the device control execution process in real time to form preliminary device execution state information; And integrating and time sequence ordering the preliminary equipment execution state information to generate an equipment control execution state record.
8. The method for managing the full life cycle of the mountain highway electromechanical device according to claim 1, wherein said multi-dimensional index structure is created by mapping each device control execution state record to a corresponding multi-dimensional coordinate position using device ID, time stamp and spatial position in the device control execution state record and the historical electromechanical device operation data as index dimensions, and using a tree structure.

Description

Full life cycle management method for mountain highway electromechanical equipment Technical Field The invention relates to the technical field of intelligent traffic infrastructure management, in particular to a full life cycle management method of mountain highway electromechanical equipment. Background The technical field of tunnel electromechanical equipment management has made remarkable progress in recent years with the development of intelligent transportation systems. The current mainstream tunnel electromechanical equipment management system generally adopts a distributed sensor network architecture, and realizes real-time acquisition and transmission of key operation parameters by deploying various environment monitoring sensors and equipment state acquisition terminals. The system generally adopts a three-layer architecture design, comprises a field sensing layer, a data transmission layer and a central processing layer, and can complete basic equipment state monitoring and abnormality alarming functions. In terms of data processing, the prior art mostly adopts a simple judgment rule based on a threshold value or a traditional statistical analysis model to perform preliminary processing and analysis on collected equipment operation data. Particularly in the aspect of environmental parameter monitoring, the system can monitor key parameters such as temperature, humidity, smoke concentration and the like more reliably through a multisource sensor data fusion technology, and provides a basic guarantee for tunnel safety operation. The prior art has significant limitations in terms of electromechanical device full lifecycle management. The problem of influence quantification of dynamic changes of environmental parameters on equipment fault propagation paths is not solved in the prior art, so that accuracy of health assessment is greatly interfered by the environment. The mountain tunnel environment is complex and changeable, the fluctuation of parameters such as temperature, humidity and air pressure is remarkable, and the correlation between the dynamic environment factors and the equipment failure modes cannot be fully considered by the existing evaluation model, so that the deviation exists between the health state evaluation result and the actual working condition. Meanwhile, in the aspect of maintenance resource optimization, the existing system adopts a static priority scheduling strategy, and cannot be dynamically adjusted according to the actual degradation state of equipment, so that optimal allocation is difficult to realize under the condition of limited maintenance resources, and the overall maintenance efficiency is affected. Disclosure of Invention The present invention has been made in view of the above-described problems occurring in the prior art. Therefore, the invention provides a full life cycle management method of mountain highway electromechanical equipment, which solves the problems that in the prior art, health assessment is greatly interfered by environment and maintenance resource allocation is not optimal. In order to solve the technical problems, the invention provides the following technical scheme: The invention provides a full life cycle management method of electromechanical equipment in mountain highway, which comprises the steps of collecting electromechanical equipment operation data in mountain highway tunnels, cleaning and standardizing the electromechanical equipment operation data, and outputting a standardized equipment operation data set; inputting the standardized equipment operation data set into a Bayesian network evaluation architecture, and analyzing posterior probability of each node under the dynamic constraint of the environmental parameters through a multi-level fault propagation path to generate an equipment health evaluation report; According to the equipment health evaluation report, performing intelligent scheduling and resource optimization on the electromechanical equipment maintenance tasks of the maintenance task queue and the limited resource set to generate an executable scheduling scheme; The method comprises the steps of utilizing an executable scheduling scheme to cooperatively control electromechanical equipment of different types in a mountain highway tunnel, and recording to obtain equipment control execution state records; and fusing the equipment control execution state record with the historical electromechanical equipment operation data, constructing an equipment full life cycle degradation curve through space-time correlation analysis, extracting trend characteristics and separating signals, and generating an equipment full life cycle analysis report. As a preferable scheme of the full life cycle management method of the mountain highway electromechanical equipment, the electromechanical equipment operation data comprise operation state parameters, energy consumption data, environment monitoring data and fault alarm information. A