CN116957531A - Intelligent rail transit operation and maintenance system and method based on state perception - Google Patents
Intelligent rail transit operation and maintenance system and method based on state perception Download PDFInfo
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Abstract
The application provides a state-awareness-based intelligent rail transit operation and maintenance system and method, comprising the following steps: the equipment on-line monitoring module collects monitoring data of each professional maintenance equipment and preprocesses the collected monitoring data of each professional maintenance equipment; the intelligent maintenance module builds a fault and maintenance service scene analysis model based on the preprocessed monitoring data of each professional maintenance device, and performs fault diagnosis, early warning, hierarchical warning and fault automatic reporting; the remote inspection module monitors the point data threshold value through preset equipment to realize remote inspection of whether the equipment is complete, whether the equipment has faults or not and whether the equipment is at the corresponding position or not; the automatic overhaul monitoring module monitors the overhaul process of the fault equipment automatically according to the monitoring data collected in the overhaul process of the equipment; the intelligent maintenance guidance module intelligently analyzes personnel, materials, tools and working hours required by the same type of equipment maintenance according to the fault expert database and provides maintenance guidance suggestions for maintenance and treatment methods.
Description
Technical Field
The application relates to the technical field of equipment operation and maintenance management, in particular to a state-awareness-based intelligent rail transit operation and maintenance system and method.
Background
With the rapid development of urban rail transit, the scale of the wire network is increasingly expanded, the operation time is continuously prolonged, the maintenance tasks, maintenance cost and operation safety pressure on subway vehicles and operation equipment are also increasingly and rapidly increased, and the reliability of the maintenance equipment and the safety of operation management cannot be ensured in the traditional maintenance mode.
At present, an urban rail transit equipment maintenance system mainly comprises 'empirical planning repair and expert fault repair', and the service promotion gradually encounters bottlenecks along with the continuous expansion of the scale of a wire network. Firstly, the scheduled repair process is more rigid, and excessive repair is often generated in the early stage of the service life of the equipment (namely, excessive repair), but the equipment cannot be timely repaired in the middle and later stages of the service life of the equipment when the equipment is in a poor state (namely, fatigue repair); secondly, the service specialists with rich experience are highly relied on from discovery and reporting to maintenance and disposal of fault repair, but the service specialists are rare, so that the problems of unclear equipment fault phenomenon reporting, inaccurate reason investigation, improper disposal scheme and the like often occur, fault maintenance information is reduced, and fault maintenance cost is increased; thirdly, a large amount of repeated and simple daily maintenance service relies on manpower in a large amount, so that heavy workload is brought to operators, and meanwhile, the operation quality is difficult to guarantee.
Patent document CN112596988A (application number 202110008397.9) discloses a rail transit multi-professional intelligent operation and maintenance system and method. The data acquisition module acquires multi-specialty data related to rail transit driving, performs unified processing on the data format of the multi-specialty data, and uploads the multi-specialty data in the unified data format to the big data platform; the large data platform stores multi-specialty data in a unified data format into a shared resource pool, monitors states and predicts faults of target specialty based on the stored target specialty data, and analyzes fault reasons of the target specialty based on multi-specialty fault correlation when the target specialty is predicted to have faults; and the data display module displays the analysis result of the big data platform. The intelligent operation and maintenance system is divided into two parts, namely, intelligent operation and maintenance is carried out on each specialty independently, and cross-specialty comprehensive analysis is carried out on the basis of the intelligent operation and maintenance of each specialty. But no mention is made of an overall solution for full-tier user oriented, full-professional equipment covered, support equipment operation and maintenance full-service management.
Patent document CN111930835a (application number 202010685705.7) discloses an intelligent operation and maintenance big data management system and method for urban rail transit, comprising an infrastructure module for building a private cloud cluster; the data analysis and access module is used for converting the original data analysis into message data; the heterogeneous data storage module is used for establishing a data table for storing message data; the data processing analysis module is used for carrying out data processing; and the cluster monitoring module is used for acquiring the hardware facilities and the running state data, comparing the running state data with the corresponding threshold value, and giving an alarm signal when the running state data exceeds the corresponding threshold value. The vehicle-mounted monitoring system has stronger data display effectiveness, effectively stores and processes massive structured/unstructured data, provides convenience for analysis of large data of the metro vehicle, and meets the requirements of intelligent operation and maintenance management of the metro vehicle. But does not cover the architecture of the intelligent operation and maintenance system of the rail transit, which consists of an online monitoring platform, a big data platform, a business management platform and a mobile APP.
Disclosure of Invention
Aiming at the defects in the prior art, the application aims to provide a rail transit intelligent operation and maintenance system and method based on state awareness.
The application provides a rail transit intelligent operation and maintenance system based on state perception, which comprises the following steps:
the equipment on-line monitoring module: acquiring monitoring data of each professional maintenance device through an online intelligent sensing device, and preprocessing the acquired monitoring data of each professional maintenance device to obtain preprocessed monitoring data of each professional maintenance device;
and an intelligent maintenance module: based on the preprocessed monitoring data of each professional maintenance device, constructing a fault and overhaul service scene analysis model, and performing fault diagnosis, early warning, hierarchical warning and fault automatic reporting;
remote inspection module: the device operation state is collected by presetting a device monitoring point position data threshold and combining a device online monitoring module, so that whether the device is complete or not is remotely checked, whether the device has faults or not is detected, and whether the device is at a corresponding position or not is realized;
and an automatic maintenance monitoring module: based on the monitoring data collected in the equipment overhaul process, automatically monitoring the fault equipment overhaul process, and physically sensing the change of the overhaul process data to realize overhaul monitoring of an overhaul item;
and the intelligent maintenance guidance module: and intelligently analyzing personnel, materials, tools, working hours and maintenance treatment methods required by the same class of equipment maintenance according to the fault expert database, and providing maintenance guidance suggestions.
Preferably, in the device on-line monitoring module,
module M1.1: collecting monitoring data of each professional maintenance device through an online intelligent sensing device, comprising: equipment operation data, meter parameters, and meter status;
module M1.2: and performing data cleaning and treatment on the acquired equipment monitoring data to obtain the preprocessed equipment monitoring data.
Preferably, in the intelligent maintenance module:
module M2.1: creating a fault positioning operation model, separating a class template and a tag point variable according to the number of the fault positioning operation model, and carrying out value polling on the point position of the monitored object;
module M2.2: collecting point location data in real time, and matching and screening fault monitoring objects according to operation rules of a fault positioning operation model;
module M2.3: acquiring fault information including fault equipment, fault phenomenon, fault reason, action mode, fault occurrence time and state according to algorithm numbers in the fault positioning operation model numbers, accurately positioning equipment faults, and automatically triggering fault repair and report;
module M2.4: automatic dispatching is realized based on a preset hanging relation between equipment and workers;
module M2.5: the equipment online monitoring module automatically monitors maintenance results and real-time running current status information of equipment, automatically verifies the maintenance results and the real-time running current status information, acquires work order closed-loop information, and determines whether the equipment is recovered to be normal or not;
the fault positioning operation model is characterized in that on-line monitoring points are defined, single-point or multi-point standard operation values are created according to a fault mechanism of equipment, time is divided into a plurality of stages, point values of each time stage are used, abnormal point readings are screened by combining influence factors comprising a change frequency range and a difference value, an abnormal algorithm and a fault system are returned, fault equipment, fault phenomenon and abnormal operation state are judged, and faults are rapidly, accurately and automatically reported;
the fault system comprises a fault phenomenon, a fault reason and an action mode.
Preferably, in the remote inspection module, the equipment facility point location monitored in real time by the equipment online monitoring module is configured with a normal data threshold value as a remote inspection point location standard matching value; based on the inspection work order triggering remote inspection, the monitoring object, the tag point location and the algorithm number are acquired according to the inspection items, the tag point location on-line monitoring data are acquired in real time, and the work order inspection item numerical value is recorded.
Preferably, in the automatic inspection module for overhauling, in the process of overhauling the equipment, for the inspection items which are not finished when the work order is started and overhauled exist, an inspection algorithm is triggered at intervals of n minutes, historical n minutes of data of points are obtained through online monitoring, the change of the data of the overhauling process is physically perceived, the inspection of the inspection items is realized, and the real redemption of the overhauling operation is ensured.
Preferably, in the intelligent maintenance guidance module, a maintenance person is allocated according to the equipment work hanging relation and the regional maintenance configuration, and a matched fault maintenance work is obtained; combining a fault knowledge base and a fault base of similar equipment, acquiring maintenance tools and materials to be carried, and monitoring and alarming the use of the maintenance materials; establishing a maintenance knowledge base, and analyzing fault reasons by combining a similar equipment fault base to acquire an acceptable maintenance scheme; and analyzing the time required by the similar fault restoration, and carrying out monitoring alarm.
Preferably, it comprises: the intelligent emergency linkage module is used for making an emergency management plan for each professional device, linking the field end with the dispatching command center, allocating maintenance teams, accessing the field individual soldiers, carrying out video connection and voice communication, and providing remote command for emergency fault treatment in real time.
Preferably, in the intelligent emergency linkage module, barriers reach a certain level, operation safety is affected, situations of irregular plan execution, non-linkage of treatment progress and untimely arrival of personnel exist, intelligent emergency linkage is started at the moment, and resource guarantee is coordinated comprehensively; an emergency plan is formulated aiming at similar faults, after the fault event is received and reported, the fault knowledge base is combined to conduct initial judgment on the event, emergency plans meeting the conditions are screened, emergency teams are deployed, emergency materials are required to be equipped, the emergency teams are contacted with a library expert for guidance, and meanwhile, the emergency teams are connected with an on-site individual soldier and are linked with an emergency command large screen to track on-site fault handling conditions and conduct remote maintenance command.
The application provides a state-awareness-based intelligent rail transit operation and maintenance method, which comprises the following steps:
step S1: the equipment online monitoring module acquires monitoring data of each professional maintenance equipment through online intelligent sensing equipment, and preprocesses the acquired monitoring data of each professional maintenance equipment to obtain preprocessed monitoring data of each professional maintenance equipment;
step S2: the intelligent maintenance module builds a fault and maintenance service scene analysis model based on the preprocessed monitoring data of each professional maintenance device, and performs fault diagnosis, early warning, hierarchical warning and fault automatic reporting;
step S3: the remote inspection module is used for presetting a device monitoring point position data threshold value and combining the device on-line monitoring module to acquire the running state of the device, so that whether the device is complete or not is remotely inspected, whether the device has faults or not is detected, and whether the device is at a corresponding position or not is realized;
step S4: the automatic overhaul monitoring module monitors the overhaul process of the fault equipment automatically based on the monitoring data collected in the overhaul process of the equipment, and physical perception of the change of the overhaul process data is realized to realize the overhaul monitoring of an overhaul item;
step S5: the intelligent maintenance guidance module intelligently analyzes personnel, materials, tools and working hours and maintenance treatment methods required by the same type of equipment maintenance according to the fault expert database, and provides maintenance guidance suggestions.
Preferably, in the device on-line monitoring module,
module M1.1: collecting monitoring data of each professional maintenance device through an online intelligent sensing device, comprising: equipment operation data, meter parameters, and meter status;
module M1.2: performing data cleaning and treatment on the acquired equipment monitoring data to obtain preprocessed equipment monitoring data;
in the intelligent maintenance module:
module M2.1: creating a fault positioning operation model, separating a class template and a tag point variable according to the number of the fault positioning operation model, and carrying out value polling on the point position of the monitored object;
module M2.2: collecting point location data in real time, and matching and screening fault monitoring objects according to operation rules of a fault positioning operation model;
module M2.3: acquiring fault information including fault equipment, fault phenomenon, fault reason, action mode, fault occurrence time and state according to algorithm numbers in the fault positioning operation model numbers, accurately positioning equipment faults, and automatically triggering fault repair and report;
module M2.4: automatic dispatching is realized based on a preset hanging relation between equipment and workers;
module M2.5: the equipment online monitoring module automatically monitors maintenance results and real-time running current status information of equipment, automatically verifies the maintenance results and the real-time running current status information, acquires work order closed-loop information, and determines whether the equipment is recovered to be normal or not;
the fault positioning operation model is characterized in that on-line monitoring points are defined, single-point or multi-point standard operation values are created according to a fault mechanism of equipment, time is divided into a plurality of stages, point values of each time stage are used, abnormal point readings are screened by combining influence factors comprising a change frequency range and a difference value, an abnormal algorithm and a fault system are returned, fault equipment, fault phenomenon and abnormal operation state are judged, and faults are rapidly, accurately and automatically reported;
the fault system comprises a fault phenomenon, a fault reason and an action mode;
in the remote inspection module, the equipment facility point position monitored in real time by the equipment online monitoring module is configured with a normal data threshold value to be used as a remote inspection point position standard matching value; based on the inspection work order triggering remote inspection, acquiring a monitoring object, a tag point location and an algorithm number according to an inspection item, acquiring tag point location on-line monitoring data in real time, and recording the work order inspection item value;
in the automatic overhaul monitoring module, in the overhaul process of equipment, an overhaul item which is not finished in the work order state and can be overhauled and monitored is triggered at intervals of n minutes, the history of point positions is obtained through online monitoring, the change of the overhaul process data is physically perceived, so that the overhaul monitoring of the overhaul item is realized, and the real redemption of overhaul operation is ensured;
in the intelligent maintenance guidance module, maintenance personnel are allocated according to the equipment work hanging relation and the regional maintenance configuration, and a matched fault maintenance work is obtained; combining a fault knowledge base and a fault base of similar equipment, acquiring maintenance tools and materials to be carried, and monitoring and alarming the use of the maintenance materials; establishing a maintenance knowledge base, and analyzing fault reasons by combining a similar equipment fault base to acquire an acceptable maintenance scheme; analyzing the time required by the similar fault restoration, and carrying out monitoring alarm;
comprising the following steps: the intelligent emergency linkage module is used for making an emergency management plan for each professional device, linking the field end with the dispatching command center, allocating maintenance teams, accessing the field individual soldiers, carrying out video connection and voice communication, and providing remote command for emergency fault treatment in real time;
in the intelligent emergency linkage module, barriers reach a certain level, operation safety is affected, situations of irregular plan execution, non-linkage of treatment progress and untimely arrival of personnel exist, intelligent emergency linkage is started at the moment, and resource guarantee is coordinated in an overall mode; an emergency plan is formulated aiming at similar faults, after the fault event is received and reported, the fault knowledge base is combined to conduct initial judgment on the event, emergency plans meeting the conditions are screened, emergency teams are deployed, emergency materials are required to be equipped, the emergency teams are contacted with a library expert for guidance, and meanwhile, the emergency teams are connected with an on-site individual soldier and are linked with an emergency command large screen to track on-site fault handling conditions and conduct remote maintenance command.
Compared with the prior art, the application has the following beneficial effects:
1. the application provides a state-awareness-based intelligent rail transit operation and maintenance system, which provides a set of intelligent operation and maintenance overall solution and system architecture of equipment based on analysis of equipment mechanism, analysis of operation and maintenance scene, analysis of multidimensional data, analysis of artificial intelligence and the like.
2. The application improves the equipment fault positioning precision, improves the scientificity of equipment maintenance decision, accelerates the fault handling efficiency, strengthens the overall command of emergency faults, reduces excessive repair and fatigue repair of equipment and strengthens the management and control of equipment maintenance cost; meanwhile, the labor and material consumption of equipment maintenance are reduced, the supervision of equipment maintenance operation is enhanced, the cost reduction and synergy are promoted.
3. The application can be widely applied to the rail transit industry. By automatically collecting the state of the equipment, intelligently sensing the state of the equipment and intelligently analyzing the data of the equipment, intelligent decision assistance is provided for equipment maintenance, the manpower dependence is reduced, and a rail transit equipment maintenance system is pushed to change into intelligent prediction repair and sensing state repair.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a diagram of a fault localization and fault prediction algorithm.
Fig. 2 is a diagram of a remote inspection algorithm.
Fig. 3 is a diagram of an automatic inspection algorithm.
Detailed Description
The present application will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present application, but are not intended to limit the application in any way. It should be noted that variations and modifications could be made by those skilled in the art without departing from the inventive concept. These are all within the scope of the present application.
Aiming at the prior defects, the application aims at solving the following difficulties: an integrated platform mainly based on a predictive maintenance mode is established, and the integrated platform takes operation and maintenance production visualization as a window to monitor the operation health state of key equipment in real time, execute fault prediction and equipment degradation trend analysis, and realize remote inspection, maintenance monitoring, state maintenance, online real-time fault positioning diagnosis and linkage, maintenance operation guidance, emergency linkage and the like of the key equipment.
In order to realize intelligent transformation, cost reduction and synergy of the equipment maintenance system, the application provides two innovations: (1) Providing an intelligent operation and maintenance integral solution which accords with the rail traffic industry and is full-level, full-specialized and full-service; (2) An industrial Internet architecture of an on-line monitoring platform, a big data platform, a business management platform and a mobile APP is constructed, and an intelligent operation and maintenance system for rail transit is built with automation, intellectualization and informatization as a core.
The technical scheme of the application is designed for full-level operation and maintenance users of the rail transit equipment, including high-level management personnel, middle-level management personnel, scheduling personnel, technical specialization personnel, working staff, station personnel and the like, and the business occurring in the data center is presented to each level of operation and maintenance management personnel in a multi-channel, multi-angle and multi-granularity mode to assist in intelligent decision making. Facing to a high-level manager, comprehensively displaying the equipment operation and maintenance core indexes and intuitively reflecting the operation type indexes of the equipment maintenance and maintenance quality, and providing a management grip for a leader through the same-loop ratio of the core indexes, threshold overrun and the like; the method includes the steps of facing production scheduling, displaying the number of work orders to be processed, providing quick processing links, highlighting faults needing to be managed with emphasis and handling overtime faults, providing a quick linkage entrance of emergency command scheduling in a fault emergency repair scene, and linking with an intelligent individual system; and providing an alarm overview of main equipment of the station for the station staff, checking the monitoring information details in a grading manner, and displaying the station maintenance work completion condition overview on the current day.
The system design supports the operation and maintenance all-service management of the rail transit equipment, and covers the services of equipment on-line monitoring, equipment facility remote inspection, equipment maintenance intelligent scheduling, equipment maintenance automatic monitoring, intelligent fault prediction, fault accurate positioning and linkage, intelligent maintenance guidance, repair process maintenance optimization and state maintenance, intelligent emergency linkage, equipment overhaul intelligent decision assistance, production cost management and control, grading decision and the like.
Example 1
According to the present application, as shown in fig. 1 to 3, a rail transit intelligent operation and maintenance system based on state sensing includes:
the equipment on-line monitoring module: and collecting monitoring data of each professional maintenance device, including device operation data, instrument parameters and instrument states, through the online intelligent sensing device. And establishing an on-line monitoring interface standard and a network transmission protocol standard, realizing standardization and samplings of collected data, and rapidly, accurately and timely transmitting the collected data to an intelligent operation and maintenance data platform through a special communication network, thereby providing a standardized calculation basis for comprehensive scene modeling. And (3) constructing an equipment health center based on-line monitoring, accessing the processed and analyzed data of each professional monitoring subsystem into an on-line monitoring module, and realizing service linkage such as fault early warning and the like by combining a scene model through a wire network-level on-line monitoring module.
And an intelligent maintenance module: in order to improve the fault handling efficiency, the closed loop control of the fault is realized, and the intelligent operation and maintenance data platform scene model operation is combined to perform fault diagnosis, early warning, hierarchical warning and automatic fault reporting. Creating a fault positioning operation model, separating a class template and TAG point variables according to model numbers, carrying out point position value polling of a monitored object, and screening the monitored object with faults by matching the real-time acquisition point position data at the lower end with a model operation rule; meanwhile, fault information is obtained according to algorithm numbers in the model numbers, including fault equipment, fault phenomena, fault reasons, action modes, fault occurrence time, states and the like, equipment faults are accurately positioned, fault repair and report is automatically triggered, automatic dispatching is achieved based on the hanging relation between equipment and workers, an intelligent operation and maintenance data platform on-line monitoring module automatically monitors maintenance results and real-time operation current information of the equipment, automatic verification is conducted, work order closed-loop information is obtained, and whether the equipment is recovered to be normal is confirmed. And aiming at major faults, carrying out systematic fault analysis, and providing basis for the execution of subsequent preventive measures.
When the line operation equipment is abnormal in state, operation production can still be carried out under the condition that no fault exists, the equipment health situation is calculated according to the intelligent operation data platform scene model, and preventive state repair and report is carried out in a grading manner by combining a fault three-code library (namely, fault phenomenon code, fault reason code and fault disposal action code) and a state result influence library.
Remote inspection module: the application provides patrol management based on remote perception in order to improve the operability and convenience of maintenance work and ensure the accuracy of a patrol result. And configuring normal data threshold values for equipment and facility point positions which can be monitored in real time by on-line monitoring in a patrol procedure, acquiring monitoring objects, TAG point positions and algorithm numbers according to overhaul items based on patrol worksheets in a remote way, acquiring TAG point position on-line monitoring data in real time, and recording worksheets overhaul item values. The remote inspection replaces manual inspection, so that the manual inspection error is reduced, the real-time performance of equipment monitoring is improved, and the equipment maintenance cost is saved.
And an automatic maintenance monitoring module: in the manual overhaul operation process, an effective supervision means is lacking, whether equipment is overhauled and maintained cannot be known, supervision holes exist, the equipment is difficult to track, and once the equipment operates, the equipment fails and is difficult to determine responsibility. The application provides an automatic monitoring device for an overhaul process based on monitoring data collected in the overhaul process of equipment. The method is characterized in that the standard resource pool is configured with maintenance items and monitoring point position data, in the equipment maintenance process, maintenance monitoring of the maintenance items is realized by triggering a maintenance monitoring algorithm at intervals of n minutes when the work order state is that the work is started and the maintenance items which are not maintained exist, acquiring point position history n minutes of data through online monitoring, and physically sensing maintenance process data change.
And the intelligent maintenance guidance module: on the one hand, the intelligent operation and maintenance are relied on, the efficiency of maintenance production business is improved through technical means, the cost is reduced, and on the other hand, the maintenance business management is driven to be upgraded through visual monitoring and intelligent analysis of 'man-machine-object-method-ring' related to the maintenance business.
The maintenance personnel distributes fault maintenance work matched according to the equipment work hanging relation and the regional maintenance configuration; the fault knowledge base and the fault base of similar equipment are combined, maintenance tools and materials which are required to be carried are intelligently suggested, and monitoring and alarming are carried out on the use of the maintenance materials; establishing a maintenance knowledge base, intelligently analyzing possible fault reasons by combining a fault base of the similar equipment, and suggesting a maintenance scheme which can be adopted; and (5) intelligently analyzing the time required by the similar fault restoration and carrying out monitoring and alarming.
Intelligent emergency linkage module: when equipment faults reach a certain level, operation safety is affected, the situations of irregular plan execution, unlink treatment progress and untimely personnel arrival exist, intelligent emergency linkage is started at the moment, and resource guarantee is coordinated comprehensively. An emergency plan is formulated aiming at similar faults, after the fault event is received and reported, the fault knowledge base is combined to conduct initial judgment on the event, emergency plans meeting the conditions are screened, emergency teams are deployed, emergency materials are required to be equipped, the emergency teams are contacted with a library expert for guidance, and meanwhile, the emergency teams are connected with an on-site individual soldier and are linked with an emergency command large screen to track on-site fault handling conditions and conduct remote maintenance command.
Intelligent operation system architecture
The intelligent operation and maintenance system is based on-line monitoring, and constructs an intelligent operation and maintenance data platform and a business management platform, and covers mobile terminal application. The intelligent operation and maintenance data platform online monitoring module acquires equipment monitoring data from each online monitoring system, performs pretreatment such as data cleaning and treatment, provides mass storage and long-term storage of multi-element heterogeneous data and derivative data, performs deep data analysis on the basis, and provides a data basis for comprehensive scene modeling.
The intelligent operation and maintenance comprehensive scene model library, the rule library and the algorithm library are constructed, the standardized monitoring data of the intelligent operation and maintenance data platform are utilized to carry out subject data extraction and model operation, and the accurate fault positioning and prediction information and the instantaneous and change frequency monitoring information are formed through data time, function and service correlation analysis to provide a service data foundation for operation and maintenance scheduling management.
The comprehensive scene modeling in the intelligent operation and data platform relates to a general model, a basic model and a differential model, and the model structure mainly comprises model input, data modeling and model output.
The fault location operation model is one of general models. Carrying out intelligent fault repair and state repair by using the output result of the general model; remote inspection; automatic inspection; intelligent maintenance guidance and intelligent emergency linkage business;
the basic model provides basic information such as executive personnel, materials and the like required by the service development;
the differencing model is based on a generic model superposition influencing factor, such as: environmental factors, climate factors, temperature, humidity, etc.
Universal model
Acquiring key equipment point location information and combined point location related data according to equipment characteristics and equipment repair procedure repair contents, and meeting the input conditions of a general model; and according to basic application analysis of different professional equipment and related point positions, a complete general model is established, and a model output result is uploaded to a monitoring center, so that remote inspection, rapid fault positioning and early warning functions are realized.
Basic model
Meeting the input conditions of the basic model, establishing personnel configuration, fault reasons, treatment modes and emergency plan configuration, having the data modeling conditions of the basic model, and constructing a standard resource library meeting different scenes and different prediction models; the output results comprise suggestions of fault positioning and treatment methods, repair optimization suggestions, emergency plan guidance suggestions and the like.
Differential model
The geographic characteristic difference, the time period difference and the equipment reliability difference are fully considered, the input conditions of a differential model are met, differential characteristic factors are constructed, and output results comprise adjustment of inspection times matched with different humiture, increase and decrease of inspection processes according to flood season and drought season, and repair process repair optimization combined with equipment reliability and operation condition analysis.
The intelligent rail transit operation and maintenance system based on state sensing provided by the application can be realized through the step flow in the intelligent rail transit operation and maintenance method based on state sensing. The intelligent operation and maintenance method of the rail transit based on the state sensing can be understood as a preferable example of the intelligent operation and maintenance system of the rail transit based on the state sensing by a person skilled in the art.
Example 2
Example 2 is a preferred example of example 1
And the intelligent application functions of interface layering display, equipment health evaluation, fault early warning work order linkage, state repair, repair and process repair optimization, auxiliary decision, periodic inspection, equipment overhaul, scene management and the like are realized by combining the data analysis results of the ventilation air conditioner, water supply and drainage, low-voltage power distribution, BAS and TIAS on-line monitoring subsystems with the equipment model of the intelligent operation and maintenance data platform. Meanwhile, the intelligent operation and maintenance data platform collects equipment monitoring data based on an on-line monitoring subsystem, supports storage, analysis, output and management of structured and unstructured data, establishes a complete comprehensive scene service model through intelligent and informationized technical means, and achieves intelligent application of maintenance service.
Those skilled in the art will appreciate that the systems, apparatus, and their respective modules provided herein may be implemented entirely by logic programming of method steps such that the systems, apparatus, and their respective modules are implemented as logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc., in addition to the systems, apparatus, and their respective modules being implemented as pure computer readable program code. Therefore, the system, the apparatus, and the respective modules thereof provided by the present application may be regarded as one hardware component, and the modules included therein for implementing various programs may also be regarded as structures within the hardware component; modules for implementing various functions may also be regarded as being either software programs for implementing the methods or structures within hardware components.
The foregoing describes specific embodiments of the present application. It is to be understood that the application is not limited to the particular embodiments described above, and that various changes or modifications may be made by those skilled in the art within the scope of the appended claims without affecting the spirit of the application. The embodiments of the application and the features of the embodiments may be combined with each other arbitrarily without conflict.
Claims (10)
1. The utility model provides a track traffic wisdom fortune dimension system based on state perception which characterized in that includes:
the equipment on-line monitoring module: acquiring monitoring data of each professional maintenance device through an online intelligent sensing device, and preprocessing the acquired monitoring data of each professional maintenance device to obtain preprocessed monitoring data of each professional maintenance device;
and an intelligent maintenance module: based on the preprocessed monitoring data of each professional maintenance device, constructing a fault and overhaul service scene analysis model, and performing fault diagnosis, early warning, hierarchical warning and fault automatic reporting;
remote inspection module: the device operation state is collected by presetting a device monitoring point position data threshold and combining a device online monitoring module, so that whether the device is complete or not is remotely checked, whether the device has faults or not is detected, and whether the device is at a corresponding position or not is realized;
and an automatic maintenance monitoring module: based on the monitoring data collected in the equipment overhaul process, automatically monitoring the fault equipment overhaul process, and physically sensing the change of the overhaul process data to realize overhaul monitoring of an overhaul item;
and the intelligent maintenance guidance module: and intelligently analyzing personnel, materials, tools, working hours and maintenance treatment methods required by the same class of equipment maintenance according to the fault expert database, and providing maintenance guidance suggestions.
2. The intelligent operation and maintenance system for rail transit based on state sensing according to claim 1, wherein, in the on-line monitoring module of the device,
module M1.1: collecting monitoring data of each professional maintenance device through an online intelligent sensing device, comprising: equipment operation data, meter parameters, and meter status;
module M1.2: and performing data cleaning and treatment on the acquired equipment monitoring data to obtain the preprocessed equipment monitoring data.
3. The state-aware rail transit intelligent operation and maintenance system of claim 1, wherein in the intelligent maintenance module:
module M2.1: creating a fault positioning operation model, separating a class template and a tag point variable according to the number of the fault positioning operation model, and carrying out value polling on the point position of the monitored object;
module M2.2: collecting point location data in real time, and matching and screening fault monitoring objects according to operation rules of a fault positioning operation model;
module M2.3: acquiring fault information including fault equipment, fault phenomenon, fault reason, action mode, fault occurrence time and state according to algorithm numbers in the fault positioning operation model numbers, accurately positioning equipment faults, and automatically triggering fault repair and report;
module M2.4: automatic dispatching is realized based on a preset hanging relation between equipment and workers;
module M2.5: the equipment online monitoring module automatically monitors maintenance results and real-time running current status information of equipment, automatically verifies the maintenance results and the real-time running current status information, acquires work order closed-loop information, and determines whether the equipment is recovered to be normal or not;
the fault positioning operation model is characterized in that on-line monitoring points are defined, single-point or multi-point standard operation values are created according to a fault mechanism of equipment, time is divided into a plurality of stages, point values of each time stage are used, abnormal point readings are screened by combining influence factors comprising a change frequency range and a difference value, an abnormal algorithm and a fault system are returned, fault equipment, fault phenomenon and abnormal operation state are judged, and faults are rapidly, accurately and automatically reported;
the fault system comprises a fault phenomenon, a fault reason and an action mode.
4. The intelligent operation and maintenance system for rail transit based on state sensing according to claim 1, wherein in the remote inspection module, the equipment facility point location monitored in real time by the equipment on-line monitoring module is configured with a normal data threshold value as a remote inspection point location standard matching value; based on the inspection work order triggering remote inspection, the monitoring object, the tag point location and the algorithm number are acquired according to the inspection items, the tag point location on-line monitoring data are acquired in real time, and the work order inspection item numerical value is recorded.
5. The intelligent rail transit operation and maintenance system based on state sensing according to claim 1, wherein in the automatic overhaul monitoring module, overhaul items which are not overhauled and can be overhauled exist for work order states which are unfinished in the overhaul process of equipment, an overhaul monitoring algorithm is triggered at intervals of n minutes, point location history n minutes data are obtained through online monitoring, overhaul process data change is physically sensed, overhaul monitoring of the overhaul items is achieved, and real redemption of overhaul operation is ensured.
6. The intelligent operation and maintenance system for rail transit based on state sensing according to claim 1, wherein in the intelligent maintenance guidance module, maintenance personnel are allocated according to equipment work hanging relation and regional maintenance configuration, and a matched fault maintenance work is obtained; combining a fault knowledge base and a fault base of similar equipment, acquiring maintenance tools and materials to be carried, and monitoring and alarming the use of the maintenance materials; establishing a maintenance knowledge base, and analyzing fault reasons by combining a similar equipment fault base to acquire an acceptable maintenance scheme; and analyzing the time required by the similar fault restoration, and carrying out monitoring alarm.
7. The state-aware-based rail transit intelligent operation and maintenance system according to claim 1, comprising: the intelligent emergency linkage module is used for making an emergency management plan for each professional device, linking the field end with the dispatching command center, allocating maintenance teams, accessing the field individual soldiers, carrying out video connection and voice communication, and providing remote command for emergency fault treatment in real time.
8. The intelligent operation and maintenance system for rail transit based on state sensing according to claim 7, wherein in the intelligent emergency linkage module, barriers reach a certain level, operation safety is affected, situations of irregular execution of a plan, non-linkage of treatment progress and untimely arrival of personnel exist, intelligent emergency linkage is started at the moment, and resource guarantee is coordinated comprehensively; an emergency plan is formulated aiming at similar faults, after the fault event is received and reported, the fault knowledge base is combined to conduct initial judgment on the event, emergency plans meeting the conditions are screened, emergency teams are deployed, emergency materials are required to be equipped, the emergency teams are contacted with a library expert for guidance, and meanwhile, the emergency teams are connected with an on-site individual soldier and are linked with an emergency command large screen to track on-site fault handling conditions and conduct remote maintenance command.
9. The intelligent rail transit operation and maintenance method based on state perception is characterized by comprising the following steps of:
step S1: the equipment online monitoring module acquires monitoring data of each professional maintenance equipment through online intelligent sensing equipment, and preprocesses the acquired monitoring data of each professional maintenance equipment to obtain preprocessed monitoring data of each professional maintenance equipment;
step S2: the intelligent maintenance module builds a fault and maintenance service scene analysis model based on the preprocessed monitoring data of each professional maintenance device, and performs fault diagnosis, early warning, hierarchical warning and fault automatic reporting;
step S3: the remote inspection module is used for presetting a device monitoring point position data threshold value and combining the device on-line monitoring module to acquire the running state of the device, so that whether the device is complete or not is remotely inspected, whether the device has faults or not is detected, and whether the device is at a corresponding position or not is realized;
step S4: the automatic overhaul monitoring module monitors the overhaul process of the fault equipment automatically based on the monitoring data collected in the overhaul process of the equipment, and physical perception of the change of the overhaul process data is realized to realize the overhaul monitoring of an overhaul item;
step S5: the intelligent maintenance guidance module intelligently analyzes personnel, materials, tools and working hours and maintenance treatment methods required by the same type of equipment maintenance according to the fault expert database, and provides maintenance guidance suggestions.
10. The intelligent operation and maintenance method for rail transit based on state sensing according to claim 9, wherein, in the on-line monitoring module of the device,
module M1.1: collecting monitoring data of each professional maintenance device through an online intelligent sensing device, comprising: equipment operation data, meter parameters, and meter status;
module M1.2: performing data cleaning and treatment on the acquired equipment monitoring data to obtain preprocessed equipment monitoring data;
in the intelligent maintenance module:
module M2.1: creating a fault positioning operation model, separating a class template and a tag point variable according to the number of the fault positioning operation model, and carrying out value polling on the point position of the monitored object;
module M2.2: collecting point location data in real time, and matching and screening fault monitoring objects according to operation rules of a fault positioning operation model;
module M2.3: acquiring fault information including fault equipment, fault phenomenon, fault reason, action mode, fault occurrence time and state according to algorithm numbers in the fault positioning operation model numbers, accurately positioning equipment faults, and automatically triggering fault repair and report;
module M2.4: automatic dispatching is realized based on a preset hanging relation between equipment and workers;
module M2.5: the equipment online monitoring module automatically monitors maintenance results and real-time running current status information of equipment, automatically verifies the maintenance results and the real-time running current status information, acquires work order closed-loop information, and determines whether the equipment is recovered to be normal or not;
the fault positioning operation model is characterized in that on-line monitoring points are defined, single-point or multi-point standard operation values are created according to a fault mechanism of equipment, time is divided into a plurality of stages, point values of each time stage are used, abnormal point readings are screened by combining influence factors comprising a change frequency range and a difference value, an abnormal algorithm and a fault system are returned, fault equipment, fault phenomenon and abnormal operation state are judged, and faults are rapidly, accurately and automatically reported;
the fault system comprises a fault phenomenon, a fault reason and an action mode;
in the remote inspection module, the equipment facility point position monitored in real time by the equipment online monitoring module is configured with a normal data threshold value to be used as a remote inspection point position standard matching value; based on the inspection work order triggering remote inspection, acquiring a monitoring object, a tag point location and an algorithm number according to an inspection item, acquiring tag point location on-line monitoring data in real time, and recording the work order inspection item value;
in the automatic overhaul monitoring module, in the overhaul process of equipment, an overhaul item which is not finished in the work order state and can be overhauled and monitored is triggered at intervals of n minutes, the history of point positions is obtained through online monitoring, the change of the overhaul process data is physically perceived, so that the overhaul monitoring of the overhaul item is realized, and the real redemption of overhaul operation is ensured;
in the intelligent maintenance guidance module, maintenance personnel are allocated according to the equipment work hanging relation and the regional maintenance configuration, and a matched fault maintenance work is obtained; combining a fault knowledge base and a fault base of similar equipment, acquiring maintenance tools and materials to be carried, and monitoring and alarming the use of the maintenance materials; establishing a maintenance knowledge base, and analyzing fault reasons by combining a similar equipment fault base to acquire an acceptable maintenance scheme; analyzing the time required by the similar fault restoration, and carrying out monitoring alarm;
comprising the following steps: the intelligent emergency linkage module is used for making an emergency management plan for each professional device, linking the field end with the dispatching command center, allocating maintenance teams, accessing the field individual soldiers, carrying out video connection and voice communication, and providing remote command for emergency fault treatment in real time;
in the intelligent emergency linkage module, barriers reach a certain level, operation safety is affected, situations of irregular plan execution, non-linkage of treatment progress and untimely arrival of personnel exist, intelligent emergency linkage is started at the moment, and resource guarantee is coordinated in an overall mode; an emergency plan is formulated aiming at similar faults, after the fault event is received and reported, the fault knowledge base is combined to conduct initial judgment on the event, emergency plans meeting the conditions are screened, emergency teams are deployed, emergency materials are required to be equipped, the emergency teams are contacted with a library expert for guidance, and meanwhile, the emergency teams are connected with an on-site individual soldier and are linked with an emergency command large screen to track on-site fault handling conditions and conduct remote maintenance command.
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| CN117369398A (en) * | 2023-12-05 | 2024-01-09 | 国网江西省电力有限公司供电服务管理中心 | Pipeline verification centralized control method based on unified simplified control instruction set |
| CN117369398B (en) * | 2023-12-05 | 2024-03-08 | 国网江西省电力有限公司供电服务管理中心 | Pipeline verification centralized control method based on unified simplified control instruction set |
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