Mechanical and electrical equipment whole life cycle maintenance management method and system

Abstract

The application provides a kind of electromechanical equipment whole life cycle maintenance management method and system, it is related to equipment management technical field, the method comprises: determining configuration knowledge graph;The node of configuration knowledge graph is the configuration of the minimum maintenance unit of electromechanical equipment, edge is the association between each minimum maintenance unit;Based on configuration knowledge graph and evaluation parameter, determine the maintenance value of each minimum maintenance unit;Wherein, evaluation parameter includes at least one of expected maintenance execution cost, effective decision-making time window and risk coefficient;According to the maintenance value of each minimum maintenance unit, combination optimization is carried out, and maintenance decision is obtained, to generate configuration dispatch order.In this way, based on configuration knowledge graph, whole life cycle operation and maintenance decision can be refined to the minimum maintenance unit, and compared with subjective experience judgment, a plurality of configuration units can be combined and optimized in coordination by combining quantifiable maintenance value, so as to realize accurate maintenance of electromechanical equipment through quantitative operation and maintenance decision.

Description

Technical Field

[0001] This invention relates to the field of equipment management technology, and provides a method and system for the whole life cycle maintenance management of electromechanical equipment. Background Technology

[0002] Most existing equipment maintenance management systems only provide static data. Maintenance decisions often rely on expert experience or fixed-cycle downtime for inspections. Maintenance personnel need to troubleshoot the complex hierarchical relationships of the entire machine one by one, resulting in low maintenance efficiency and long downtime.

[0003] Furthermore, most existing equipment maintenance management systems focus on the entire machine. When equipment shows signs of performance degradation or failure, they can only roughly assess the general condition of the entire machine. When a functional unit fails or ages during maintenance, the on-site maintenance strategy often leans towards replacing the entire machine or the assembly, resulting in the premature scrapping of a large number of still usable equipment units and increasing the cost of electromechanical equipment. Summary of the Invention

[0004] This invention provides a method and system for the whole life cycle maintenance management of electromechanical equipment, which solves the defects of maintenance decision-making relying on manual labor and extensive management in related technologies, and achieves precise maintenance of electromechanical equipment through quantitative operation and maintenance decision-making.

[0005] This invention provides a method for the whole life cycle maintenance management of electromechanical equipment, including: A configuration knowledge graph is determined; the nodes of the configuration knowledge graph are the configurations of the smallest maintenance units of electromechanical equipment, and the edges are the relationships between the smallest maintenance units. The maintenance value of each of the minimum maintenance units is determined based on the configuration knowledge graph and evaluation parameters; wherein, the evaluation parameters include at least one of the expected maintenance execution cost, effective decision time window, and risk coefficient; Based on the maintenance value of each of the minimum maintenance units, a combination optimization is performed to obtain a maintenance decision, thereby generating a configuration work order.

[0006] According to one embodiment of the present invention, determining the configuration knowledge graph includes: Generate an association matrix between the configuration and maintenance attributes of each smallest maintenance unit of the electromechanical equipment; the maintenance attributes include at least one of faults and repair procedures; The configuration knowledge graph is determined based on each of the aforementioned association matrices; wherein, the nodes of the configuration knowledge graph are associated with the maintenance attributes, and the association relationships between each of the smallest maintenance units include physical combination relationships, fault propagation relationships, and maintenance process impact relationships.

[0007] According to one embodiment of the present invention, determining the configuration knowledge graph includes: The operating parameters of each of the minimum maintenance units are collected to identify the corresponding performance degradation trajectory; Based on the performance degradation trajectory, the configuration state and repair process decision of the minimum maintenance unit are determined to update the configuration knowledge graph.

[0008] According to one embodiment of the present invention, the collection of operating parameters of each of the minimum maintenance units includes: The operating parameters of each minimum maintenance unit are read based on the three-dimensional geometric model corresponding to the minimum maintenance unit. The operating parameters of each of the minimum maintenance units are associated with and stored in relation to the configuration code of each of the minimum maintenance units, so as to collect the operating parameters of each of the minimum maintenance units.

[0009] According to one embodiment of the present invention, reading the operating parameters of each minimum maintenance unit based on the three-dimensional geometric model corresponding to the minimum maintenance unit includes: The reading frequency of the three-dimensional geometric model of the corresponding minimum maintenance unit is dynamically adjusted based on the performance degradation trajectory to obtain the operating parameters of each minimum maintenance unit; wherein the reading frequency is negatively correlated with the trend of the performance degradation trajectory.

[0010] According to one embodiment of the present invention, after generating a configuration work order, the method further includes: Collect maintenance results; Update the configuration knowledge graph and the three-dimensional geometric model based on the maintenance results; and / or update the full life cycle maintenance management information model of the electromechanical equipment based on the maintenance results; The maintenance results include at least one of actual execution data, fault measurement data, and configuration change data; the display framework of the full life cycle maintenance management information model is a configuration tree, which displays the corresponding status information based on the configuration code of the smallest maintenance unit; the status information includes at least one of health status, remaining life, cost accumulation, and maintenance history.

[0011] According to one embodiment of the present invention, determining the maintenance value of each of the minimum repair units based on the configuration knowledge graph and evaluation parameters includes: Based on the configuration knowledge graph, the expected present value of avoidable losses within the remaining lifespan is obtained, and the maintenance value of each of the minimum repair units is calculated in conjunction with the evaluation parameters.

[0012] According to an embodiment of the present invention, before obtaining the expected present value of avoidable losses within the remaining lifetime based on the configuration knowledge graph, the method further includes: Based on the configuration knowledge graph, hierarchical analysis is performed to determine the weights of the aging parameters that lead to the failure of the minimum repair unit; The aging parameters corresponding to the minimum maintenance unit are collected, and the corresponding configuration aging anomaly coefficient is calculated in combination with the weight to obtain the remaining life of the minimum maintenance unit; wherein, the aging parameters include the stress deviation, geometric deformation, surface damage accumulation data and service strength factor of the minimum maintenance unit.

[0013] According to one embodiment of the present invention, the method further includes: Determine the system language environment to obtain language code based on the system language environment; The corresponding terminology data is loaded according to the language code and the preset mapping table; wherein, the preset mapping table is a triple mapping table of configuration code, language code and terminology data; the terminology data includes at least one of configuration name, fault mode description, maintenance operation instructions and technical parameter units.

[0014] This invention also provides a life-cycle maintenance and management system for electromechanical equipment, comprising: A knowledge graph determination module is used to determine a configuration knowledge graph; the nodes of the configuration knowledge graph are the configurations of the smallest maintenance units of electromechanical equipment, and the edges are the associations between the smallest maintenance units. The maintenance value determination module is used to determine the maintenance value of each of the minimum maintenance units based on the configuration knowledge graph and evaluation parameters; wherein, the evaluation parameters include at least one of expected maintenance execution cost, effective decision time window and risk coefficient; The maintenance management module is used to combine and optimize the maintenance value of each of the minimum maintenance units to obtain maintenance decisions and generate configuration work orders.

[0015] This invention provides a method and system for full life-cycle maintenance management of electromechanical equipment. By determining a configuration knowledge graph, the maintenance value of each minimum repair unit is determined based on the configuration knowledge graph and evaluation parameters. The maintenance values ​​of each minimum repair unit are combined and optimized to obtain maintenance decisions and generate configuration work orders. In this way, based on the configuration knowledge graph, the full life-cycle operation and maintenance decisions can be refined to the minimum repair unit. Moreover, compared with subjective experience judgment, multiple configuration units can be collaboratively combined and optimized by combining quantifiable maintenance values, thereby achieving precise maintenance of electromechanical equipment through quantified operation and maintenance decisions. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is a schematic flowchart of the electromechanical equipment full life cycle maintenance management method provided by the present invention.

[0018] Figure 2 This is one of the schematic structural diagrams of the electromechanical equipment full life cycle maintenance management system provided by the present invention.

[0019] Figure 3 This is the second schematic structural diagram of the electromechanical equipment life cycle maintenance management system provided by the present invention.

[0020] Figure 4 This is a schematic diagram of the physical structure of the electronic device provided by the present invention. Detailed Implementation

[0021] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0022] like Figures 1 to 3 As shown, the present invention provides a method and system for the whole life cycle maintenance management of electromechanical equipment, which is used for the management of electromechanical equipment assets.

[0023] Figure 1 This is a schematic flowchart of the electromechanical equipment full life cycle maintenance management method provided by the present invention, such as... Figure 1 As shown, the method includes the following steps.

[0024] Step 101: Determine the configuration knowledge graph; the nodes of the configuration knowledge graph are the configurations of the smallest maintenance units of electromechanical equipment, and the edges are the relationships between the smallest maintenance units.

[0025] The configuration knowledge graph can also be called a configuration knowledge network or a configuration-level fault causal knowledge graph. The minimum maintenance unit (MINU) is a physical object of a functional unit that can be independently replaced, repaired, or inspected during maintenance operations. The configuration of the MINU is a data object of the functional unit that can be independently replaced, repaired, or inspected during maintenance operations. In some embodiments, the configuration of the MINU has a uniquely identified configuration code to facilitate the associated storage of data related to the MINU.

[0026] It should be noted that there are many ways to determine the configuration knowledge graph. One can obtain a pre-constructed configuration knowledge graph, or collect the configuration of each minimum maintenance unit of electromechanical equipment and the relationship between each minimum maintenance unit to construct the configuration knowledge graph, etc. This embodiment does not limit this.

[0027] Step 102: Determine the maintenance value of each of the minimum maintenance units based on the configuration knowledge graph and evaluation parameters; wherein the evaluation parameters include at least one of the expected maintenance execution cost, effective decision-making time window, and risk coefficient.

[0028] The maintenance value of the smallest repair unit refers to a quantitative indicator that measures the revenue obtained from maintaining the smallest repair unit.

[0029] It should be noted that the expected maintenance execution cost of the minimum maintenance unit can be obtained based on the configuration cost ledger and historical maintenance events. The corresponding effective decision-making time window and risk coefficient can be obtained based on the remaining life of the minimum maintenance unit and the severity of its failure. This embodiment does not limit these aspects.

[0030] In some embodiments, decision-making costs, design costs, construction costs, operation and maintenance costs, and scrapping costs can be allocated to the corresponding minimum maintenance unit, and a mapping table between costs and configuration codes of the minimum maintenance unit can be constructed to form a configuration cost ledger.

[0031] Step 103: Combine and optimize the maintenance value of each of the minimum maintenance units to obtain a maintenance decision and generate a configuration work order.

[0032] Maintenance decisions, also known as optimal maintenance decision sets, are planning-level maintenance execution plans for electromechanical equipment generated based on the smallest maintenance unit. These plans guide the generation of configuration work orders. For example, maintenance decisions may include the maintenance priority of each smallest maintenance unit, suggested maintenance timing, required resources, and risk control measures. Required resources may include budget and professional skills; risk control measures may include safety measures between smallest maintenance units or process isolation measures.

[0033] Configuration-based work orders are work orders generated based on maintenance decisions, used to guide specific maintenance operations on the smallest repair unit in the field.

[0034] It should be noted that the maintenance decision combination of multiple minimum maintenance units can be taken as the investment object, the objective function is to maximize the total maintenance value of electromechanical equipment, and the constraints are the total budget, spare parts inventory, professional skills and human resources, and safety association constraints between configurations. The maintenance decision is obtained by using an integer programming algorithm.

[0035] The electromechanical equipment lifecycle maintenance management method provided in this invention determines the maintenance value of each minimum maintenance unit based on the configuration knowledge graph and evaluation parameters, and optimizes the combination of the maintenance values ​​of each minimum maintenance unit to obtain maintenance decisions and generate configuration work orders. In this way, the configuration knowledge graph can refine the lifecycle operation and maintenance decisions to the minimum maintenance unit. Moreover, compared with subjective experience judgment, it can combine quantifiable maintenance values ​​to perform collaborative combination optimization of multiple configuration units, thereby achieving precise maintenance of electromechanical equipment through quantified operation and maintenance decisions.

[0036] Based on the above embodiments, determining the configuration knowledge graph includes: Generate an association matrix between the configuration and maintenance attributes of each smallest maintenance unit of the electromechanical equipment; the maintenance attributes include at least one of faults and repair procedures; The configuration knowledge graph is determined based on each of the aforementioned association matrices; wherein, the nodes of the configuration knowledge graph are associated with the maintenance attributes, and the association relationships between each of the smallest maintenance units include physical combination relationships, fault propagation relationships, and maintenance process impact relationships.

[0037] Here, a fault can be a set of fault modes, and a repair process can be a set of repair tasks. In some embodiments, maintenance attributes may also include solutions, which can be a set of maintenance activities.

[0038] Physical assembly relationships can include the assembly hierarchy, spatial location, or mechanical connection relationships between the minimum repair units. Fault propagation relationships characterize how faults propagate between the minimum repair units; for example, when a fault occurs in one minimum repair unit, the path the fault spreads to other minimum repair units along physical assembly relationships or functional coupling relationships. Repair process impact relationships characterize the effect of repair activities on the state of the minimum repair units.

[0039] It should be noted that a hierarchical configuration tree structure for electromechanical equipment can be constructed to generate a configuration coding system for each minimum maintenance unit, thereby establishing an association matrix among the configuration, faults, and repair processes of each minimum maintenance unit. Then, a configuration knowledge graph is determined using the configuration entities of each minimum maintenance unit in the configuration tree as nodes and the association relationships between configuration, faults, and repair processes as edges.

[0040] Understandably, by constructing a configuration knowledge graph that includes physical combination relationships, fault propagation relationships, and repair process impact relationships through the association matrix between the configuration of each minimum maintenance unit and maintenance attributes such as faults and repair processes, the maintenance object can be refined from the traditional whole equipment to the minimum maintenance unit. Furthermore, the knowledge graph based on the causal relationships between the minimum maintenance units can improve the accuracy of fault tracing and the pertinence of maintenance decisions. Thus, by using the minimum maintenance unit as the management object, the accuracy of fault location can be improved, maintenance strategies can be refined, and precision maintenance can be achieved.

[0041] Based on any of the above embodiments, determining the configuration knowledge graph includes: The operating parameters of each of the minimum maintenance units are collected to identify the corresponding performance degradation trajectory; Based on the performance degradation trajectory, the configuration state and repair process decision of the minimum maintenance unit are determined to update the configuration knowledge graph.

[0042] Among them, the performance degradation trajectory can also be called the health state evolution trajectory or health state evolution law, which is used to characterize the performance state as it gradually deteriorates.

[0043] It should be noted that the system can collect operating parameters such as vibration, temperature, stress, wear status parameters, historical fault frequency, and outlier trends of the minimum maintenance unit to identify the health status evolution pattern of the minimum maintenance unit. When the health status evolution pattern indicates that there is room for optimization in the existing maintenance strategy, the configuration status and repair process decision of the minimum maintenance unit are redefined to generate new causal rules that include configuration status conditions and repair process decision conclusions. These rules are then injected into the configuration knowledge graph by adding causal edges or updating weights, thereby achieving dynamic updating of the configuration knowledge graph.

[0044] Based on any of the above embodiments, the collection of operating parameters for each of the minimum maintenance units includes: The operating parameters of each minimum maintenance unit are read based on the three-dimensional geometric model corresponding to the minimum maintenance unit. The operating parameters of each of the minimum maintenance units are associated with and stored in relation to the configuration code of each of the minimum maintenance units, so as to collect the operating parameters of each of the minimum maintenance units.

[0045] It should be noted that, specifically, a three-dimensional geometric model can be established first based on the configuration code of the minimum maintenance unit. The configuration code is uniquely associated with the geometric entity through the three-dimensional geometric model to establish a digital twin model of the electromechanical equipment. Then, the stress, vibration, temperature rise and wear status data of each minimum maintenance unit collected by the sensors are obtained through the Internet of Things using the digital twin model. The status data is associated with the corresponding configuration code and stored to collect the operating parameters of each minimum maintenance unit.

[0046] It is understandable that by reading the operating parameters based on the three-dimensional geometric model corresponding to the minimum maintenance unit and storing the operating parameters in association with the configuration code, the physical operating status of the minimum maintenance unit can be obtained in real time through the configuration code of the minimum maintenance unit, and the operating status of the electromechanical equipment can be accurately grasped from the minimum maintenance unit level.

[0047] In some embodiments, historical maintenance events can be acquired periodically. While keeping the state of the minimum maintenance unit unchanged in the historical maintenance events, guided by the causal rules of the configuration knowledge graph, the stress redistribution and life evolution of the minimum maintenance unit under different maintenance decisions are simulated through the three-dimensional geometric model corresponding to the minimum maintenance unit. The utility gain of the maintenance decision relative to the actual decision is calculated. When the utility gain is greater than a preset threshold, a new causal rule is generated based on the maintenance decision and injected into the configuration knowledge graph by adding causal edges or updating weights, so as to realize the dynamic updating of the configuration knowledge graph.

[0048] The specific methods for determining different repair process decisions and preset thresholds can be set according to the actual working conditions, and are not limited in this embodiment.

[0049] Based on any of the above embodiments, reading the operating parameters of each minimum maintenance unit based on the three-dimensional geometric model corresponding to the minimum maintenance unit includes: The reading frequency of the three-dimensional geometric model of the corresponding minimum maintenance unit is dynamically adjusted based on the performance degradation trajectory to obtain the operating parameters of each minimum maintenance unit; wherein the reading frequency is negatively correlated with the trend of the performance degradation trajectory.

[0050] It should be noted that the read frequency is negatively correlated with the trend of performance degradation trajectory. Since the performance degradation trajectory can characterize the security risk level, it can also be understood that the read frequency and the security risk level are negatively correlated.

[0051] Understandably, by dynamically adjusting the reading frequency of the operating parameters of the three-dimensional geometric model corresponding to each minimum maintenance unit based on the performance degradation trajectory, and making the reading frequency negatively correlated with the performance degradation trend, the monitoring frequency can be adaptively reduced when the health status of the configuration unit deteriorates rapidly. This achieves adaptive acquisition from fixed-cycle acquisition to state-driven acquisition, thereby optimizing the configuration of monitoring resources and avoiding data redundancy and system overhead caused by invalid detection while ensuring the integrity of critical status data.

[0052] Based on any of the above embodiments, after generating the configuration work order, the method further includes: Collect maintenance results; Update the configuration knowledge graph and the three-dimensional geometric model based on the maintenance results; and / or update the full life cycle maintenance management information model of the electromechanical equipment based on the maintenance results; The maintenance results include at least one of actual execution data, fault measurement data, and configuration change data; the display framework of the full life cycle maintenance management information model is a configuration tree, which displays the corresponding status information based on the configuration code of the smallest maintenance unit; the status information includes at least one of health status, remaining life, cost accumulation, and maintenance history.

[0053] It should be noted that after generating the configuration work order, it can be assigned to the corresponding work station to perform maintenance tasks based on the location of the smallest maintenance unit and the maintenance process, and the maintenance results can be collected after the maintenance tasks are completed.

[0054] The configuration work order, also known as a task work order, may include a configuration code, maintenance content, technical standards, required materials, and time quotas. In some embodiments, the work instructions can be displayed to on-site maintenance personnel in response to them scanning the configuration code via a mobile terminal.

[0055] In some embodiments, when the minimum maintenance unit of electromechanical equipment is determined to have undergone physical changes, fault repairs, or component replacements based on maintenance results, the corresponding three-dimensional geometric model, physical state, and relationships in the digital twin model can be updated synchronously based on the configuration coding index.

[0056] In some embodiments, when updating the digital twin model, the update of the digital twin model can be triggered based on the configuration encoding label, and at the same time, the weight update of the relevant edges in the configuration knowledge graph can be triggered.

[0057] In some embodiments, in response to test data from the digital twin model or human instructions, a state transition can be triggered for the smallest repair unit throughout its entire lifecycle, from entry for inspection, disassembly and repair, component replacement, assembly and debugging, acceptance testing, to field application.

[0058] In some embodiments, the maintenance results also include the actual cost of performing the maintenance tasks, as shown in the Dongdai update configuration cost ledger.

[0059] Based on any of the above embodiments, determining the maintenance value of each of the minimum repair units based on the configuration knowledge graph and evaluation parameters includes: Based on the configuration knowledge graph, the expected present value of avoidable losses within the remaining lifespan is obtained, and the maintenance value of each of the minimum repair units is calculated in conjunction with the evaluation parameters.

[0060] The expected present value of avoidable loss is the loss that would be expected to occur if maintenance is not performed. For example, this loss may include the replacement cost of the minimum maintenance unit, the maintenance cost of related minimum maintenance units caused by the failure of the minimum maintenance unit through the fault propagation relationship, and production losses caused by unplanned downtime of electromechanical equipment.

[0061] Understandably, by obtaining the expected present value of avoidable losses within the remaining lifespan and combining it with evaluation parameters to calculate the maintenance value of each minimum maintenance unit, the fault propagation relationships and associated losses between configurations in the knowledge graph can be transformed into quantifiable decision-making criteria. This transforms the maintenance value from the cost of a single minimum maintenance unit to the actual loss that considers the impact of its failure on associated minimum maintenance units and the overall electromechanical equipment, thereby improving the accuracy of subsequent maintenance decisions.

[0062] Based on any of the above embodiments, before obtaining the expected present value of avoidable losses within the remaining lifetime based on the configuration knowledge graph, the method further includes: Based on the configuration knowledge graph, hierarchical analysis is performed to determine the weights of the aging parameters that lead to the failure of the minimum repair unit; The aging parameters corresponding to the minimum maintenance unit are collected, and the corresponding configuration aging anomaly coefficient is calculated in combination with the weight to obtain the remaining life of the minimum maintenance unit; wherein, the aging parameters include the stress deviation, geometric deformation, surface damage accumulation data and service strength factor of the minimum maintenance unit.

[0063] It should be noted that the configuration aging anomaly coefficient can be input into a pre-trained deep learning neural network. The remaining lifespan of the minimum maintenance unit configuration can be predicted through the deep learning neural network, and the full life cycle maintenance management information model of electromechanical equipment can be updated based on the remaining lifespan.

[0064] The pre-training method for the deep learning neural network can be selected according to the actual working conditions, and this embodiment does not impose any restrictions on it.

[0065] Based on any of the above embodiments, the method further includes: Determine the system language environment to obtain language code based on the system language environment; The corresponding terminology data is loaded according to the language code and the preset mapping table; wherein, the preset mapping table is a triple mapping table of configuration code, language code and terminology data; the terminology data includes at least one of configuration name, fault mode description, maintenance operation instructions and technical parameter units.

[0066] In some embodiments, the region code to which the electromechanical equipment belongs can also be determined based on the language code. The corresponding regional standard is then loaded based on the region code and a second mapping table. The regional standards include a maintenance cycle standard library, a safety specification library, and an approval process template library, etc. It is understood that after determining the corresponding regional standard, the full life-cycle maintenance management information model of the electromechanical equipment can be adaptively updated according to the regional standard.

[0067] It should be noted that it supports one-click switching between major global languages ​​such as Chinese, English, French, Portuguese, Spanish, Arabic, and Indonesian, as well as localized mapping of terminology databases and units of measurement.

[0068] Understandably, by determining the system's language environment to obtain the language code, and loading the corresponding terminology data based on the language code and a preset mapping table, multilingual adaptation can be refined from traditional interface text translation to the business data layer, such as configuration names, fault mode descriptions, maintenance operation instructions, and technical parameter units. This allows the same configuration code to be automatically associated with the corresponding regional business terms in different language environments, avoiding data redundancy and maintenance burden caused by repeatedly entering basic data in different regions.

[0069] The following describes the electromechanical equipment life cycle maintenance management system provided by the present invention. The electromechanical equipment life cycle maintenance management system described below can be referred to in correspondence with the electromechanical equipment life cycle maintenance management method described above.

[0070] Figure 2 This is one of the schematic structural diagrams of the electromechanical equipment life cycle maintenance management system provided by the present invention, such as... Figure 2 As shown, the system includes: The knowledge graph determination module 210 is used to determine the configuration knowledge graph; the nodes of the configuration knowledge graph are the configurations of the smallest maintenance units of electromechanical equipment, and the edges are the association relationships between the smallest maintenance units. The maintenance value determination module 220 is used to determine the maintenance value of each of the minimum maintenance units based on the configuration knowledge graph and evaluation parameters; wherein, the evaluation parameters include at least one of expected maintenance execution cost, effective decision time window and risk coefficient; The maintenance management module 230 is used to combine and optimize the maintenance value of each of the minimum maintenance units to obtain maintenance decisions and generate configuration work orders.

[0071] Figure 3 This is the second schematic structural diagram of the electromechanical equipment life-cycle maintenance and management system provided by the present invention, as shown below. Figure 3 As shown, in order to illustrate the functions of the electromechanical equipment life cycle maintenance management system provided in this embodiment, a specific example is provided below.

[0072] The electromechanical equipment lifecycle maintenance management system includes a configuration management module, a configuration knowledge graph determination module, a digital twin model, a lifecycle cost quantification module, a lifecycle maintenance management information model, and a multilingual flexible configuration module. The configuration management module is used to build a hierarchical configuration tree structure for electromechanical equipment and generate a configuration coding system for each minimum maintenance unit of the electromechanical equipment, so as to establish an association matrix between the configuration, faults and repair processes of each minimum maintenance unit. A configuration knowledge graph determination module is used to generate an association matrix between the configuration and maintenance attributes of each minimum maintenance unit of electromechanical equipment; the maintenance attributes include at least one of faults and repair procedures; the configuration knowledge graph is determined based on each association matrix; wherein, the nodes of the configuration knowledge graph are associated with the maintenance attributes, and the association relationships between each minimum maintenance unit include physical combination relationships, fault propagation relationships, and repair procedure impact relationships; A digital twin model is used to establish a three-dimensional geometric model based on the configuration code of the minimum maintenance unit. The configuration code is uniquely associated with the geometric entity through the three-dimensional geometric model. The stress, vibration, temperature rise and wear status data of each minimum maintenance unit are acquired by sensors through the Internet of Things, and the status data are associated with the corresponding configuration code and stored. The operating parameters of each minimum maintenance unit are collected. The full life cycle cost quantification module is used to determine the weights of aging parameters that lead to the failure of the minimum maintenance unit based on the configuration knowledge graph through hierarchical analysis; collect the aging parameters corresponding to the minimum maintenance unit, and calculate the corresponding configuration aging anomaly coefficient in combination with the weights to obtain the remaining life of the minimum maintenance unit; obtain the expected present value of avoidable losses within the remaining life cycle based on the configuration knowledge graph, and calculate the maintenance value of each minimum maintenance unit in combination with the evaluation parameters. The full life cycle maintenance management information model is used to display the corresponding status information based on the configuration code of the smallest maintenance unit, using a configuration tree as the display framework. The status information includes at least one of health status, remaining life, cost accumulation, and maintenance history. The model also collects maintenance results and updates the full life cycle maintenance management information model of the electromechanical equipment based on the maintenance results. A multilingual flexible configuration module is used to determine the system language environment, obtain language codes based on the system language environment, and load corresponding terminology data according to the language codes and a preset mapping table. The preset mapping table is a triple mapping table of configuration encoding, language codes, and terminology data. The terminology data includes at least one of configuration name, fault mode description, maintenance operation instructions, and technical parameter units.

[0073] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communications interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute the following methods: A configuration knowledge graph is determined; the nodes of the configuration knowledge graph are the configurations of the smallest maintenance units of electromechanical equipment, and the edges are the relationships between the smallest maintenance units; the maintenance value of each smallest maintenance unit is determined based on the configuration knowledge graph and evaluation parameters; wherein, the evaluation parameters include at least one of expected maintenance execution cost, effective decision time window, and risk coefficient; the maintenance value of each smallest maintenance unit is combined and optimized to obtain a maintenance decision, thereby generating a configuration work order.

[0074] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to related technologies, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0075] This invention discloses a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer can perform the methods provided in the above-described method embodiments, such as including: A configuration knowledge graph is determined; the nodes of the configuration knowledge graph are the configurations of the smallest maintenance units of electromechanical equipment, and the edges are the relationships between the smallest maintenance units; the maintenance value of each smallest maintenance unit is determined based on the configuration knowledge graph and evaluation parameters; wherein, the evaluation parameters include at least one of expected maintenance execution cost, effective decision time window, and risk coefficient; the maintenance value of each smallest maintenance unit is combined and optimized to obtain a maintenance decision, thereby generating a configuration work order.

[0076] On the other hand, embodiments of the present invention also provide a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the transmission methods provided in the above embodiments, including, for example: A configuration knowledge graph is determined; the nodes of the configuration knowledge graph are the configurations of the smallest maintenance units of electromechanical equipment, and the edges are the relationships between the smallest maintenance units; the maintenance value of each smallest maintenance unit is determined based on the configuration knowledge graph and evaluation parameters; wherein, the evaluation parameters include at least one of expected maintenance execution cost, effective decision time window, and risk coefficient; the maintenance value of each smallest maintenance unit is combined and optimized to obtain a maintenance decision, thereby generating a configuration work order.

[0077] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0078] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of software products. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for the whole life cycle maintenance management of electromechanical equipment, characterized in that, include: A configuration knowledge graph is determined; the nodes of the configuration knowledge graph are the configurations of the smallest maintenance units of electromechanical equipment, and the edges are the relationships between the smallest maintenance units. The maintenance value of each of the minimum maintenance units is determined based on the configuration knowledge graph and evaluation parameters; wherein, the evaluation parameters include at least one of the expected maintenance execution cost, effective decision time window, and risk coefficient; Based on the maintenance value of each of the minimum maintenance units, a combination optimization is performed to obtain a maintenance decision, thereby generating a configuration work order.

2. The method for full life-cycle maintenance management of electromechanical equipment according to claim 1, characterized in that, The defined configuration knowledge graph includes: Generate an association matrix between the configuration and maintenance attributes of each smallest maintenance unit of the electromechanical equipment; the maintenance attributes include at least one of faults and repair procedures; The configuration knowledge graph is determined based on each of the aforementioned association matrices; wherein, the nodes of the configuration knowledge graph are associated with the maintenance attributes, and the association relationships between each of the smallest maintenance units include physical combination relationships, fault propagation relationships, and maintenance process impact relationships.

3. The method for full life-cycle maintenance management of electromechanical equipment according to claim 1 or 2, characterized in that, The defined configuration knowledge graph includes: The operating parameters of each of the minimum maintenance units are collected to identify the corresponding performance degradation trajectory; Based on the performance degradation trajectory, the configuration state and repair process decision of the minimum maintenance unit are determined to update the configuration knowledge graph.

4. The method for full life-cycle maintenance management of electromechanical equipment according to claim 3, characterized in that, The collection of operating parameters for each of the minimum maintenance units includes: The operating parameters of each minimum maintenance unit are read based on the three-dimensional geometric model corresponding to the minimum maintenance unit. The operating parameters of each of the minimum maintenance units are associated with and stored in relation to the configuration code of each of the minimum maintenance units, so as to collect the operating parameters of each of the minimum maintenance units.

5. The method for full life-cycle maintenance management of electromechanical equipment according to claim 4, characterized in that, The step of reading the operating parameters of each minimum maintenance unit based on the three-dimensional geometric model corresponding to the minimum maintenance unit includes: The reading frequency of the three-dimensional geometric model of the corresponding minimum maintenance unit is dynamically adjusted based on the performance degradation trajectory to obtain the operating parameters of each minimum maintenance unit; wherein the reading frequency is negatively correlated with the trend of the performance degradation trajectory.

6. The method for full life-cycle maintenance management of electromechanical equipment according to claim 4, characterized in that, After generating the configuration work order, the method further includes: Collect maintenance results; Update the configuration knowledge graph and the three-dimensional geometric model based on the maintenance results; and / or update the full life cycle maintenance management information model of the electromechanical equipment based on the maintenance results; The maintenance results include at least one of actual execution data, fault measurement data, and configuration change data; the display framework of the full life cycle maintenance management information model is a configuration tree, which displays the corresponding status information based on the configuration code of the smallest maintenance unit; the status information includes at least one of health status, remaining life, cost accumulation, and maintenance history.

7. The method for full life-cycle maintenance management of electromechanical equipment according to claim 1, characterized in that, The determination of the maintenance value of each of the minimum repair units based on the configuration knowledge graph and evaluation parameters includes: Based on the configuration knowledge graph, the expected present value of avoidable losses within the remaining lifespan is obtained, and the maintenance value of each of the minimum repair units is calculated in conjunction with the evaluation parameters.

8. The method for full life-cycle maintenance management of electromechanical equipment according to claim 7, characterized in that, Before obtaining the expected present value of avoidable losses within the remaining lifetime based on the configuration knowledge graph, the method further includes: Based on the configuration knowledge graph, hierarchical analysis is performed to determine the weights of the aging parameters that lead to the failure of the minimum maintenance unit; The aging parameters corresponding to the minimum maintenance unit are collected, and the corresponding configuration aging anomaly coefficient is calculated in combination with the weight to obtain the remaining life of the minimum maintenance unit; wherein, the aging parameters include the stress deviation, geometric deformation, surface damage accumulation data and service strength factor of the minimum maintenance unit.

9. The method for full life-cycle maintenance management of electromechanical equipment according to claim 1, characterized in that, The method further includes: Determine the system language environment, and obtain the language code based on the system language environment; The corresponding terminology data is loaded according to the language code and the preset mapping table; wherein, the preset mapping table is a triple mapping table of configuration code, language code and terminology data; the terminology data includes at least one of configuration name, fault mode description, maintenance operation instructions and technical parameter units.

10. A life-cycle maintenance and management system for electromechanical equipment, characterized in that, include: A knowledge graph determination module is used to determine a configuration knowledge graph; the nodes of the configuration knowledge graph are the configurations of the smallest maintenance units of electromechanical equipment, and the edges are the associations between the smallest maintenance units. The maintenance value determination module is used to determine the maintenance value of each of the minimum maintenance units based on the configuration knowledge graph and evaluation parameters; wherein, the evaluation parameters include at least one of expected maintenance execution cost, effective decision time window and risk coefficient; The maintenance management module is used to combine and optimize the maintenance value of each of the minimum maintenance units to obtain maintenance decisions and generate configuration work orders.

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