BIM-based predictive maintenance management method and system for pipelines in gas turbine power plants

Abstract

The present invention is applicable to the technical field of gas turbine power plant management, and provides a predictive maintenance management method and system for gas turbine power plant pipelines based on BIM. The present invention determines multiple power plant pipeline points, performs monitoring and control, and records point monitoring data; compares the point monitoring data according to preset standard maintenance data, selects multiple risk pipeline points, and extracts multiple risk monitoring data; processes the multiple risk monitoring data, calculates the time period risk values ​​of the multiple risk pipeline points; compares the multiple time period risk values ​​according to preset risk management data, records the risk comparison results, and performs corresponding predictive maintenance management. It is possible to comprehensively and effectively monitor multiple power plant pipeline points, select multiple risk pipeline points, calculate multiple time period risk values, perform risk comparison and corresponding predictive maintenance management, which can not only ensure the effective operation of the gas turbine power plant, but also reduce the cost of maintenance management.

Description

Technical Field

[0001] The present invention belongs to the technical field of gas turbine power plant management, and in particular relates to a BIM-based predictive maintenance management method and system for gas turbine power plant pipelines. Background Art

[0002] Gas turbine power plant pipelines are pipelines and related ancillary facilities that connect various equipment and systems within a gas turbine power plant and are used to transport gases, liquids and other media to ensure the normal operation of the power plant. By organically connecting various production links such as fuel supply, gas turbine power generation, waste heat utilization, steam circulation, and cooling water circulation, a complete energy conversion and transmission system is formed.

[0003] In the existing technology, due to the complex layout of pipelines in gas turbine power plants, comprehensive and effective monitoring is impossible. Usually, only two extreme maintenance management methods can be carried out: (1) when the pipelines are abnormal, they are replaced and repaired, which has a great impact on the operation of the gas turbine power plant; (2) when the pipelines are at risk, they are directly replaced and repaired. Although this can ensure the effective operation of the gas turbine power plant, the maintenance and management costs are high. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a BIM-based predictive maintenance management method and system for gas turbine power plant pipelines, aiming to solve the technical problems existing in the existing technology mentioned in the background technology.

[0005] The embodiment of the present invention is implemented as follows:

[0006] A predictive maintenance management method for pipelines in a gas turbine power plant based on BIM, the method specifically comprising the following steps:

[0007] Based on BIM data, multiple power plant pipeline points are determined, and multiple power plant pipeline points are monitored and controlled, and point monitoring data is recorded;

[0008] Comparing the point monitoring data according to preset standard maintenance data, selecting a plurality of risk pipeline points from the plurality of power plant pipeline points, and extracting a plurality of risk monitoring data;

[0009] Processing the plurality of risk monitoring data to generate a plurality of risk offset data, and calculating the time period risk values ​​of the plurality of risk pipeline points;

[0010] According to the preset risk management data, the risk values ​​of the multiple time periods are compared, the risk comparison results are recorded, and corresponding predictive maintenance management is performed according to the risk comparison results.

[0011] As a further limitation of the technical solution of the embodiment of the present invention, the determining of multiple power plant pipeline points based on BIM data, monitoring and controlling the multiple power plant pipeline points, and recording the point monitoring data specifically include the following steps:

[0012] Determine the locations of multiple power plant pipelines based on the BIM data of the gas turbine power plant;

[0013] Generate monitoring instructions periodically according to the preset point monitoring cycle;

[0014] Wirelessly sending the monitoring instruction to a plurality of pipeline points of the power plant;

[0015] Receive multiple wirelessly transmitted wireless monitoring data, monitor and control multiple power plant pipeline points according to the multiple wireless monitoring data, and record the point monitoring data.

[0016] As a further limitation of the technical solution of the embodiment of the present invention, the receiving of a plurality of wirelessly transmitted wireless monitoring data, monitoring and controlling a plurality of power plant pipeline points according to the plurality of wireless monitoring data, and recording the point monitoring data specifically include the following steps:

[0017] receiving wireless monitoring data transmitted by multiple wireless devices;

[0018] Based on the plurality of power plant pipeline points, performing source analysis on the plurality of wireless monitoring data to determine a plurality of online pipeline points and a plurality of offline pipeline points;

[0019] Based on the BIM data of the gas turbine power plant, wired communication planning is performed for the plurality of online pipeline points and the plurality of offline pipeline points, and a plurality of wired communication connections are determined;

[0020] According to the plurality of wired communication connections, wired auxiliary monitoring and control are performed on the plurality of offline pipeline points to obtain a plurality of auxiliary monitoring data;

[0021] The plurality of wireless monitoring data and the plurality of auxiliary monitoring data are sorted and recorded to obtain point monitoring data.

[0022] As a further limitation of the technical solution of the embodiment of the present invention, the step of comparing the point monitoring data according to the preset standard maintenance data, selecting a plurality of risk pipeline points from the plurality of power plant pipeline points, and extracting a plurality of risk monitoring data specifically includes the following steps:

[0023] Compare the monitoring data of the points according to the preset standard maintenance data and record the monitoring comparison results;

[0024] According to the monitoring and comparison results, multiple risk pipeline points are selected from multiple power plant pipeline points;

[0025] From the point monitoring data, risk monitoring data corresponding to a plurality of risky pipeline points are extracted.

[0026] As a further limitation of the technical solution of the embodiment of the present invention, the processing of the plurality of risk monitoring data, generating a plurality of risk offset data, and calculating the period risk values ​​of the plurality of risk pipeline points specifically includes the following steps:

[0027] Based on the standard maintenance data, performing offset calculation and recording on the plurality of risk monitoring data to generate a plurality of risk offset data;

[0028] Identifying a plurality of risk offset data, and determining a plurality of risk offset time periods and corresponding offset numerical data;

[0029] According to the plurality of risk deviation time periods and the plurality of deviation numerical data, the time period risk values ​​of the plurality of risky pipeline points are calculated.

[0030] As a further limitation of the technical solution of the embodiment of the present invention, the calculation formula of the period risk value of the multiple risk pipeline points is:

[0031] ;

[0032] in, For the The period risk value of each risk pipeline point, For the The risk start time of each risk pipeline point, is the current time, is the preset temperature standard coefficient, For the The temperature deviation value of each risk pipeline point, is the preset pressure standard coefficient, For the The pressure deviation value of each risk pipeline point.

[0033] As a further limitation of the technical solution of the embodiment of the present invention, comparing the risk values ​​of the multiple time periods according to the preset risk management data, recording the risk comparison results, and performing corresponding predictive maintenance management according to the risk comparison results specifically includes the following steps:

[0034] Compare the risk values ​​of multiple time periods according to the preset risk management data and record the risk comparison results;

[0035] Determining predicted maintenance levels of the plurality of risky pipeline points based on the risk comparison results;

[0036] According to the plurality of predicted maintenance levels, matching a plurality of corresponding predicted maintenance strategies;

[0037] According to the plurality of predictive maintenance strategies, corresponding predictive maintenance management is performed on a plurality of corresponding risk pipeline points.

[0038] A predictive maintenance management system for pipelines in gas turbine power plants based on BIM, comprising a monitoring, control, and recording module, a risk point selection module, a time period risk value calculation module, and a predictive maintenance management module, wherein:

[0039] A monitoring, control and recording module is used to determine multiple power plant pipeline points based on BIM data, monitor and control the multiple power plant pipeline points, and record the point monitoring data;

[0040] a risk point selection module, configured to compare the point monitoring data according to preset standard maintenance data, select a plurality of risky pipeline points from the plurality of power plant pipeline points, and extract a plurality of risk monitoring data;

[0041] a period risk value calculation module, configured to process the plurality of risk monitoring data, generate a plurality of risk offset data, and calculate the period risk values ​​of the plurality of risk pipeline points;

[0042] The predictive maintenance management module is used to compare the risk values ​​of multiple time periods according to preset risk management data, record the risk comparison results, and perform corresponding predictive maintenance management according to the risk comparison results.

[0043] As a further limitation of the technical solution of the embodiment of the present invention, the monitoring control recording module specifically includes:

[0044] The pipeline location determination unit is used to determine the locations of multiple power plant pipelines based on the BIM data of the gas turbine power plant;

[0045] An instruction generation unit, configured to periodically generate monitoring instructions according to a preset point monitoring cycle;

[0046] An instruction wireless sending unit, used for wirelessly sending the monitoring instruction to a plurality of pipeline points in the power plant;

[0047] The monitoring control unit is used to receive a plurality of wireless monitoring data transmitted wirelessly, monitor and control a plurality of power plant pipeline points according to the plurality of wireless monitoring data, and record the point monitoring data.

[0048] As a further limitation of the technical solution of the embodiment of the present invention, the monitoring control unit specifically includes:

[0049] A data receiving subunit, configured to receive a plurality of wireless monitoring data transmitted wirelessly;

[0050] A source analysis subunit, configured to perform source analysis on the plurality of wireless monitoring data based on the plurality of power plant pipeline points, and determine a plurality of online pipeline points and a plurality of offline pipeline points;

[0051] A wired communication planning subunit is used to plan wired communications between the plurality of online pipeline points and the plurality of offline pipeline points based on the BIM data of the gas turbine power plant, and determine a plurality of wired communication connections;

[0052] a wired auxiliary monitoring and control subunit, configured to perform wired auxiliary monitoring and control on the plurality of offline pipeline points according to the plurality of wired communication connections, and obtain a plurality of auxiliary monitoring data;

[0053] The arranging and recording subunit is used to arrange and record the plurality of wireless monitoring data and the plurality of auxiliary monitoring data to obtain point monitoring data.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The embodiment of the present invention determines multiple power plant pipeline points, monitors and controls them, and records the monitoring data of the points; compares the monitoring data of the points according to preset standard maintenance data, selects multiple risk pipeline points, and extracts multiple risk monitoring data; processes the multiple risk monitoring data, calculates the time period risk values ​​of the multiple risk pipeline points; compares the risk values ​​of the multiple time periods according to preset risk management data, records the risk comparison results, and performs corresponding predictive maintenance management. It is possible to comprehensively and effectively monitor multiple power plant pipeline points, select multiple risk pipeline points, calculate the risk values ​​of multiple time periods, perform risk comparisons, and perform corresponding predictive maintenance management, thereby ensuring the effective operation of the gas turbine power plant and reducing the cost of maintenance management. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A flowchart of a BIM-based predictive maintenance management method for pipelines in a gas turbine power plant provided by an embodiment of the present invention is shown;

[0057] Figure 2 A flow chart showing the monitoring and control of pipeline points in the method provided by an embodiment of the present invention is shown;

[0058] Figure 3 A flowchart of recording point monitoring data in a method provided by an embodiment of the present invention is shown;

[0059] Figure 4 A flowchart of extracting multiple risk monitoring data in the method provided by an embodiment of the present invention is shown;

[0060] Figure 5A flowchart of calculating risk values ​​for multiple time periods in a method provided by an embodiment of the present invention is shown;

[0061] Figure 6 A flowchart of predictive maintenance management in a method provided by an embodiment of the present invention is shown;

[0062] Figure 7 The application architecture diagram of the BIM-based predictive maintenance management system for gas turbine power plant pipelines provided by an embodiment of the present invention is shown;

[0063] Figure 8 It shows a structural block diagram of the monitoring control recording module in the system provided by an embodiment of the present invention;

[0064] Figure 9 The structure block diagram of the monitoring control unit in the system provided by the embodiment of the present invention is shown. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0066] It is understandable that in the existing technology, due to the complex layout of pipelines in gas turbine power plants, comprehensive and effective monitoring is impossible, and usually only two extreme maintenance management methods can be carried out: (1) when the pipelines are abnormal, they are replaced and repaired, which has a great impact on the operation of the gas turbine power plant; (2) when the pipelines are at risk, they are directly replaced and repaired. Although this can ensure the effective operation of the gas turbine power plant, the cost of maintenance management is high.

[0067] To solve the above problems, the embodiments of the present invention disclose a predictive maintenance management method and system for gas turbine power plant pipelines based on BIM. Based on BIM data, multiple power plant pipeline points are determined, and multiple power plant pipeline points are monitored and controlled, and point monitoring data is recorded; according to preset standard maintenance data, the point monitoring data is compared, and multiple risk pipeline points are selected from multiple power plant pipeline points, and multiple risk monitoring data are extracted; the multiple risk monitoring data are processed to generate multiple risk offset data, and the time period risk values ​​of the multiple risk pipeline points are calculated; according to preset risk management data, the multiple time period risk values ​​are compared, the risk comparison results are recorded, and corresponding predictive maintenance management is performed according to the risk comparison results. It is possible to comprehensively and effectively monitor multiple power plant pipeline points, select multiple risk pipeline points, calculate multiple time period risk values, perform risk comparison and corresponding predictive maintenance management, which can not only ensure the effective operation of the gas turbine power plant, but also reduce the cost of maintenance management.

[0068] Specifically, Figure 1 A flowchart of a BIM-based predictive maintenance management method for pipelines in a gas turbine power plant provided by an embodiment of the present invention is shown.

[0069] In a preferred embodiment of the present invention, a BIM-based predictive maintenance management method for pipelines in a gas turbine power plant comprises the following steps:

[0070] Step S101: Based on BIM data, multiple power plant pipeline points are determined, and the multiple power plant pipeline points are monitored and controlled, and the point monitoring data is recorded.

[0071] In an embodiment of the present invention, BIM data of a gas turbine power plant is obtained, and a plurality of power plant pipeline points in the gas turbine power plant are determined by performing monitoring point analysis on the BIM data. Monitoring instructions are periodically generated according to a preset point monitoring period, and the monitoring instructions are wirelessly sent to the plurality of power plant pipeline points through wireless communication technology, and a plurality of wirelessly transmitted wireless monitoring data are received. By performing data source analysis on the plurality of wireless monitoring data, the power plant pipeline points that perform wireless transmission of wireless monitoring data are marked as online pipeline points from the plurality of power plant pipeline points, and the power plant pipeline points that do not perform wireless transmission of wireless monitoring data are marked as offline pipeline points, thereby enabling the plurality of power plant pipeline points to be divided into a plurality of online pipeline points. Pipeline points and multiple offline pipeline points, based on the BIM data of the gas turbine power plant, the wired communication between multiple online pipeline points and multiple offline pipeline points is connected and identified, and wired communication planning is performed to determine multiple wired communication connections, and then according to the multiple wired communication connections, wired auxiliary monitoring and control are performed on the multiple offline pipeline points. Through the wired communication connections between the multiple online pipeline points and the multiple offline pipeline points, the auxiliary monitoring data corresponding to the multiple offline pipeline points are transitionally transmitted by wire, and then the multiple auxiliary monitoring data are wirelessly transmitted through the multiple online pipeline points to obtain multiple auxiliary monitoring data, and then the multiple wireless monitoring data and the multiple auxiliary monitoring data are sorted and recorded to obtain point monitoring data.

[0072] It can be understood that multiple power plant pipeline points are deployment nodes with pressure sensors, temperature sensors, etc. deployed at key locations (such as elbows and valves) in the pipelines of gas turbine power plants.

[0073] It is understandable that due to the complex pipeline layout and harsh environment (high temperature, vibration, noise, steam, pyrolysis products, etc.) of gas turbine power plants, wireless transmission may be abnormally offline. Extensive deployment of wired communication will increase application costs. In addition, in the harsh environment of gas turbine power plants, wired communication cables are also likely to be damaged, making extensive wired communication unfeasible.

[0074] Specifically, Figure 2The flowchart of the monitoring and control of pipeline points in the method provided by the embodiment of the present invention is shown.

[0075] In another preferred embodiment of the present invention, determining multiple power plant pipeline points based on BIM data, monitoring and controlling the multiple power plant pipeline points, and recording the point monitoring data specifically include the following steps:

[0076] Step S1011: Determine multiple power plant pipeline locations based on the BIM data of the gas turbine power plant.

[0077] Step S1012: Generate monitoring instructions periodically according to the preset point monitoring period.

[0078] Step S1013: wirelessly sending the monitoring instruction to multiple pipeline points in the power plant.

[0079] Step S1014: receiving a plurality of wireless monitoring data transmitted wirelessly, monitoring and controlling a plurality of pipeline points of the power plant according to the plurality of wireless monitoring data, and recording the point monitoring data.

[0080] Specifically, Figure 3 A flow chart of recording point monitoring data in the method provided by an embodiment of the present invention is shown.

[0081] In another preferred embodiment of the present invention, receiving a plurality of wirelessly transmitted wireless monitoring data, monitoring and controlling a plurality of power plant pipeline points according to the plurality of wireless monitoring data, and recording the point monitoring data specifically comprises the following steps:

[0082] Step S10141: Receive multiple wireless monitoring data transmitted wirelessly.

[0083] Step S10142: Based on the plurality of pipeline points of the power plant, perform source analysis on the plurality of wireless monitoring data to determine a plurality of online pipeline points and a plurality of offline pipeline points.

[0084] Step S10143: Based on the BIM data of the gas turbine power plant, wired communication planning is performed for the plurality of online pipeline points and the plurality of offline pipeline points, and a plurality of wired communication connections are determined.

[0085] Step S10144: perform wired auxiliary monitoring and control on the multiple offline pipeline points according to the multiple wired communication connections to obtain multiple auxiliary monitoring data.

[0086] Step S10145: Arrange and record the plurality of wireless monitoring data and the plurality of auxiliary monitoring data to obtain point monitoring data.

[0087] Furthermore, the BIM-based predictive maintenance management method for gas turbine power plant pipelines further includes the following steps:

[0088] Step S102: comparing the point monitoring data according to preset standard maintenance data, selecting a plurality of risky pipeline points from the plurality of power plant pipeline points, and extracting a plurality of risk monitoring data.

[0089] In an embodiment of the present invention, according to preset standard maintenance data, the point monitoring data is numerically compared, and the monitoring comparison results are recorded. Then, according to the monitoring comparison results, multiple risk pipeline points are selected from multiple power plant pipeline points, and then the risk monitoring data corresponding to the multiple risk pipeline points are extracted from the point monitoring data.

[0090] It can be understood that standard maintenance data refers to the numerical range between the risk state (risk is a state with abnormal trends but no abnormality occurs) and the abnormal state of the pressure and temperature monitoring values ​​at different power plant pipeline points; the risk pipeline points refer to the corresponding pressure and temperature monitoring values ​​that are within the numerical range corresponding to the standard maintenance data.

[0091] Specifically, Figure 4 A flowchart of extracting multiple risk monitoring data in the method provided by an embodiment of the present invention is shown.

[0092] Among them, in another preferred embodiment provided by the present invention, the comparing of the point monitoring data according to the preset standard maintenance data, selecting multiple risk pipeline points from the multiple power plant pipeline points, and extracting multiple risk monitoring data specifically include the following steps:

[0093] Step S1021: Compare the point monitoring data according to the preset standard maintenance data, and record the monitoring comparison results.

[0094] Step S1022: Select multiple risky pipeline points from multiple power plant pipeline points according to the monitoring and comparison results.

[0095] Step S1023: extract risk monitoring data corresponding to a plurality of risky pipeline points from the point monitoring data.

[0096] Furthermore, the BIM-based predictive maintenance management method for gas turbine power plant pipelines further includes the following steps:

[0097] Step S103: Process the plurality of risk monitoring data to generate a plurality of risk offset data, and calculate the time period risk values ​​of the plurality of risk pipeline points.

[0098] In an embodiment of the present invention, standard risk values ​​corresponding to multiple risk pipeline points are extracted from standard maintenance data, an offset calculation is performed by subtracting the values ​​in the multiple risk monitoring data from the multiple corresponding standard risk values, multiple risk offset data are recorded, and then the multiple risk offset data are identified. From the multiple risk offset data, risk offset time periods and offset value data of the multiple risk pipeline points are extracted, and then the period risk values ​​of the multiple risk pipeline points are calculated according to the multiple risk offset time periods and the multiple offset value data. Specifically, the calculation formula for the period risk values ​​of the multiple risk pipeline points is:

[0099] ;

[0100] in, For the The period risk value of each risk pipeline point, For the The risk start time of each risk pipeline point, is the current time, is the preset temperature standard coefficient, For the The temperature deviation value of each risk pipeline point, is the preset pressure standard coefficient, For the The pressure deviation value of each risk pipeline point.

[0101] It can be understood that the standard risk value is a boundary value in a risk state extracted from the value range corresponding to the standard maintenance data.

[0102] Specifically, Figure 5 A flow chart of calculating risk values ​​for multiple time periods in the method provided by an embodiment of the present invention is shown.

[0103] In another preferred embodiment of the present invention, the processing of the plurality of risk monitoring data to generate a plurality of risk offset data and calculating the period risk values ​​of the plurality of risk pipeline points specifically includes the following steps:

[0104] Step S1031: Based on the standard maintenance data, perform offset calculation and recording on the plurality of risk monitoring data to generate a plurality of risk offset data.

[0105] Step S1032: Identify the plurality of risk offset data, and determine a plurality of risk offset time periods and corresponding offset numerical data.

[0106] Step S1033: Calculate the period risk values ​​of the plurality of risky pipeline points according to the plurality of risky offset period and the plurality of offset numerical data.

[0107] Furthermore, the BIM-based predictive maintenance management method for gas turbine power plant pipelines further includes the following steps:

[0108] Step S104: Compare the risk values ​​of the multiple time periods according to the preset risk management data, record the risk comparison results, and perform corresponding predictive maintenance management according to the risk comparison results.

[0109] In an embodiment of the present invention, risk values ​​for multiple time periods are compared according to preset risk management data, and the risk comparison results are recorded. Based on the risk comparison results, the predicted maintenance levels of multiple risk pipeline points are determined, and then, based on the multiple predicted maintenance levels, multiple corresponding predictive maintenance strategies are matched. Based on the multiple predictive maintenance strategies, corresponding predictive maintenance management is performed on the multiple corresponding risk pipeline points.

[0110] It can be understood that, in the embodiment of the present invention, the period risk is a cumulative process, which is related to both the size of the offset value and the duration.

[0111] It is understandable that different predictive maintenance levels correspond to different predictive maintenance strategies and different predictive maintenance management. Specifically, different predictive maintenance management may include no processing, cleaning, replacement of lubricating oil, replacement of gaskets, replacement of valves / elbows, etc.

[0112] Specifically, Figure 6 A flowchart of predictive maintenance management in the method provided by an embodiment of the present invention is shown.

[0113] In another preferred embodiment of the present invention, comparing the risk values ​​of the multiple time periods according to the preset risk management data, recording the risk comparison results, and performing corresponding predictive maintenance management according to the risk comparison results specifically include the following steps:

[0114] Step S1041: Compare the risk values ​​of the multiple time periods according to the preset risk management data, and record the risk comparison results.

[0115] Step S1042: Determine the predicted maintenance levels of the plurality of risky pipeline points based on the risk comparison results.

[0116] Step S1043: Match multiple corresponding predictive maintenance strategies according to the multiple predictive maintenance levels.

[0117] Step S1044: performing corresponding predictive maintenance management on a plurality of corresponding risky pipeline points according to the plurality of predictive maintenance strategies.

[0118] Further, Figure 7The application architecture diagram of the BIM-based predictive maintenance management system for gas turbine power plant pipelines provided by an embodiment of the present invention is shown.

[0119] Specifically, in another preferred embodiment provided by the present invention, a BIM-based predictive maintenance management system for pipelines in a gas turbine power plant includes:

[0120] The monitoring control recording module 101 is used to determine multiple power plant pipeline points based on BIM data, monitor and control the multiple power plant pipeline points, and record point monitoring data.

[0121] In an embodiment of the present invention, the monitoring control recording module 101 obtains the BIM data of the gas turbine power plant, determines multiple power plant pipeline points in the gas turbine power plant by performing monitoring point analysis on the BIM data, periodically generates monitoring instructions according to a preset point monitoring cycle, and then wirelessly sends the monitoring instructions to multiple power plant pipeline points through wireless communication technology, and receives multiple wirelessly transmitted wireless monitoring data. By performing data source analysis on the multiple wireless monitoring data, the power plant pipeline points that perform wireless transmission of wireless monitoring data are marked as online pipeline points from the multiple power plant pipeline points, and the power plant pipeline points that do not perform wireless transmission of wireless monitoring data are marked as offline pipeline points, so that the multiple power plant pipeline points can be divided into online and offline pipeline points. It is divided into multiple online pipeline points and multiple offline pipeline points. Based on the BIM data of the gas turbine power plant, the wired communication between the multiple online pipeline points and the multiple offline pipeline points is identified, and wired communication planning is performed to determine multiple wired communication connections. Then, according to the multiple wired communication connections, wired auxiliary monitoring and control are performed on the multiple offline pipeline points. Through the wired communication connection between the multiple online pipeline points and the multiple offline pipeline points, the auxiliary monitoring data corresponding to the multiple offline pipeline points are transmitted by transitional wire. Then, the multiple auxiliary monitoring data are wirelessly transmitted through the multiple online pipeline points to obtain multiple auxiliary monitoring data. Then, the multiple wireless monitoring data and the multiple auxiliary monitoring data are sorted and recorded to obtain point monitoring data.

[0122] Specifically, Figure 8 It shows a structural block diagram of the monitoring control recording module 101 in the system provided by an embodiment of the present invention.

[0123] In another preferred embodiment of the present invention, the monitoring control recording module 101 specifically includes:

[0124] The pipeline point determination unit 1011 is used to determine the pipeline points of multiple power plants based on the BIM data of the gas turbine power plant.

[0125] The instruction generation unit 1012 is used to periodically generate monitoring instructions according to a preset point monitoring period.

[0126] The instruction wireless sending unit 1013 is used to wirelessly send the monitoring instruction to multiple pipeline points in the power plant.

[0127] The monitoring control unit 1014 is used to receive a plurality of wireless monitoring data transmitted wirelessly, monitor and control a plurality of pipeline points of the power plant according to the plurality of wireless monitoring data, and record the point monitoring data.

[0128] Specifically, Figure 9 It shows a structural block diagram of the monitoring control unit 1014 in the system provided by an embodiment of the present invention.

[0129] In another preferred embodiment of the present invention, the monitoring control unit 1014 specifically includes:

[0130] The data receiving subunit 10141 is configured to receive a plurality of wireless monitoring data transmitted wirelessly.

[0131] The source analysis subunit 10142 is configured to perform source analysis on the plurality of wireless monitoring data based on the plurality of power plant pipeline points, and determine a plurality of online pipeline points and a plurality of offline pipeline points.

[0132] The wired communication planning subunit 10143 is used to plan wired communications between the plurality of online pipeline points and the plurality of offline pipeline points based on the BIM data of the gas turbine power plant, and determine a plurality of wired communication connections.

[0133] The wired assisted monitoring control subunit 10144 is used to perform wired assisted monitoring and control on the multiple offline pipeline points according to the multiple wired communication connections, and obtain multiple assisted monitoring data.

[0134] The arranging and recording subunit 10145 is used to arrange and record the plurality of wireless monitoring data and the plurality of auxiliary monitoring data to obtain point monitoring data.

[0135] Furthermore, the BIM-based predictive maintenance management system for gas turbine power plant pipelines further includes:

[0136] The risk point selection module 102 is used to compare the point monitoring data according to the preset standard maintenance data, select multiple risk pipeline points from multiple power plant pipeline points, and extract multiple risk monitoring data.

[0137] In an embodiment of the present invention, the risk point selection module 102 performs numerical comparison on the point monitoring data according to preset standard maintenance data, records the monitoring comparison results, and then selects multiple risk pipeline points from multiple power plant pipeline points according to the monitoring comparison results, and then extracts risk monitoring data corresponding to the multiple risk pipeline points from the point monitoring data.

[0138] The period risk value calculation module 103 is used to process the plurality of risk monitoring data, generate a plurality of risk offset data, and calculate the period risk values ​​of the plurality of risky pipeline points.

[0139] In an embodiment of the present invention, the period risk value calculation module 103 extracts standard risk values ​​corresponding to multiple risk pipeline points from the standard maintenance data, performs offset calculation by subtracting the values ​​in the multiple risk monitoring data from the multiple corresponding standard risk values, records multiple risk offset data, and then identifies the multiple risk offset data. From the multiple risk offset data, the risk offset period and offset value data of the multiple risk pipeline points are extracted, and then the period risk values ​​of the multiple risk pipeline points are calculated according to the multiple risk offset period and the multiple offset value data. Specifically, the calculation formula of the period risk value of the multiple risk pipeline points is:

[0140] ;

[0141] in, For the The period risk value of each risk pipeline point, For the The risk start time of each risk pipeline point, is the current time, is the preset temperature standard coefficient, For the The temperature deviation value of each risk pipeline point, is the preset pressure standard coefficient, For the The pressure deviation value of each risk pipeline point.

[0142] The predictive maintenance management module 104 is configured to compare the risk values ​​of the multiple time periods according to preset risk management data, record the risk comparison results, and perform corresponding predictive maintenance management according to the risk comparison results.

[0143] In an embodiment of the present invention, the predictive maintenance management module 104 compares the risk values ​​of multiple time periods according to preset risk management data, records the risk comparison results, and then determines the predictive maintenance levels of multiple risk pipeline points based on the risk comparison results. Then, according to the multiple predictive maintenance levels, multiple corresponding predictive maintenance strategies are matched, and corresponding predictive maintenance management is performed on the multiple corresponding risk pipeline points according to the multiple predictive maintenance strategies.

[0144] It should be understood that, although the various steps in the flow chart of each embodiment of the present invention are shown in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0145] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When executed, the program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media used in the various embodiments provided herein may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM).

[0146] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A predictive maintenance management method for pipelines in gas turbine power plants based on BIM, characterized by: The method specifically comprises the following steps: Based on BIM data, multiple power plant pipeline points are determined, and multiple power plant pipeline points are monitored and controlled, and point monitoring data is recorded; According to the preset point monitoring cycle, monitoring instructions are generated periodically, and then the monitoring instructions are wirelessly sent to multiple power plant pipeline points through wireless communication technology, and multiple wireless monitoring data transmitted wirelessly are received. By analyzing the source of the multiple wireless monitoring data, the power plant pipeline points that have wirelessly transmitted the wireless monitoring data are marked as online pipeline points from the multiple power plant pipeline points, and the power plant pipeline points that have not wirelessly transmitted the wireless monitoring data are marked as offline pipeline points. Based on the BIM data of the gas turbine power plant, multiple online pipeline points and multiple offline pipeline points are compared. The wired communication between the multiple online pipeline points is used to identify the connection, and the wired communication planning is performed to determine multiple wired communication connections. Then, according to the multiple wired communication connections, wired auxiliary monitoring and control are performed on the multiple offline pipeline points. Through the wired communication connection between the multiple online pipeline points and the multiple offline pipeline points, the auxiliary monitoring data corresponding to the multiple offline pipeline points are transmitted by transitional wires. Then, the multiple auxiliary monitoring data are wirelessly transmitted through the multiple online pipeline points to obtain multiple auxiliary monitoring data. Then, the multiple wireless monitoring data and the multiple auxiliary monitoring data are sorted and recorded to obtain point monitoring data. Comparing the point monitoring data according to preset standard maintenance data, selecting a plurality of risk pipeline points from the plurality of power plant pipeline points, and extracting a plurality of risk monitoring data; Processing the plurality of risk monitoring data to generate a plurality of risk offset data, and calculating the time period risk values ​​of the plurality of risk pipeline points; Extract standard risk values ​​corresponding to multiple risk pipeline points from standard maintenance data, perform offset calculation by subtracting values ​​in multiple risk monitoring data from multiple corresponding standard risk values, record multiple risk offset data, and then identify the multiple risk offset data. Extract risk offset time periods and offset value data of multiple risk pipeline points from the multiple risk offset data, and then calculate the period risk values ​​of the multiple risk pipeline points according to the multiple risk offset time periods and multiple offset value data. Specifically, the calculation formula for the period risk values ​​of the multiple risk pipeline points is: ； in, For the The period risk value of each risk pipeline point, For the The risk start time of each risk pipeline point, is the current time, is the preset temperature standard coefficient, For the The temperature deviation value of each risk pipeline point, is the preset pressure standard coefficient, For the The pressure deviation value of each risk pipeline point; According to the preset risk management data, the risk values ​​of the multiple time periods are compared, the risk comparison results are recorded, and corresponding predictive maintenance management is performed according to the risk comparison results.

2. The predictive maintenance management method for pipelines in a gas turbine power plant based on BIM according to claim 1 is characterized in that: The step of comparing the point monitoring data according to the preset standard maintenance data, selecting a plurality of risk pipeline points from the plurality of power plant pipeline points, and extracting a plurality of risk monitoring data specifically includes the following steps: Compare the monitoring data of the points according to the preset standard maintenance data and record the monitoring comparison results; According to the monitoring and comparison results, multiple risk pipeline points are selected from multiple power plant pipeline points; From the point monitoring data, risk monitoring data corresponding to a plurality of risky pipeline points are extracted.

3. The predictive maintenance management method for pipelines in a gas turbine power plant based on BIM according to claim 1 is characterized in that: The method of comparing the risk values ​​of the multiple time periods according to the preset risk management data, recording the risk comparison results, and performing corresponding predictive maintenance management according to the risk comparison results specifically includes the following steps: Compare the risk values ​​of multiple time periods according to the preset risk management data and record the risk comparison results; Determining predicted maintenance levels of the plurality of risky pipeline points based on the risk comparison results; According to the plurality of predicted maintenance levels, matching a plurality of corresponding predicted maintenance strategies; According to the plurality of predictive maintenance strategies, corresponding predictive maintenance management is performed on a plurality of corresponding risk pipeline points.

4. The BIM-based predictive maintenance management system for gas turbine power plant pipelines is characterized by: The system includes a monitoring control recording module, a risk point selection module, a period risk value calculation module and a predictive maintenance management module, wherein: A monitoring, control and recording module is used to determine multiple power plant pipeline points based on BIM data, monitor and control the multiple power plant pipeline points, and record the point monitoring data; The monitoring control recording module generates monitoring instructions periodically according to the preset point monitoring cycle, and then sends the monitoring instructions wirelessly to multiple power plant pipeline points through wireless communication technology, and receives multiple wireless monitoring data transmitted wirelessly. By analyzing the source of the multiple wireless monitoring data, the power plant pipeline points that transmit wireless monitoring data are marked as online pipeline points from multiple power plant pipeline points, and the power plant pipeline points that do not transmit wireless monitoring data are marked as offline pipeline points. Based on the BIM data of the gas turbine power plant, multiple online pipeline points are compared with multiple offline pipeline points. The wired communication between pipeline points is used to identify connections and perform wired communication planning to determine multiple wired communication connections. Then, according to the multiple wired communication connections, wired auxiliary monitoring and control are performed on multiple offline pipeline points. Through the wired communication connections between multiple online pipeline points and multiple offline pipeline points, auxiliary monitoring data corresponding to the multiple offline pipeline points are transmitted by transitional wires. Then, the multiple auxiliary monitoring data are wirelessly transmitted through multiple online pipeline points to obtain multiple auxiliary monitoring data. Then, the multiple wireless monitoring data and the multiple auxiliary monitoring data are collated and recorded to obtain point monitoring data. a risk point selection module, configured to compare the point monitoring data according to preset standard maintenance data, select a plurality of risky pipeline points from the plurality of power plant pipeline points, and extract a plurality of risk monitoring data; a period risk value calculation module, configured to process the plurality of risk monitoring data, generate a plurality of risk offset data, and calculate the period risk values ​​of the plurality of risk pipeline points; The period risk value calculation module extracts the standard risk values ​​corresponding to multiple risk pipeline points from the standard maintenance data, performs offset calculation by subtracting the values ​​in the multiple risk monitoring data from the multiple corresponding standard risk values, records multiple risk offset data, and then identifies the multiple risk offset data. From the multiple risk offset data, the module extracts the risk offset period and offset value data of the multiple risk pipeline points, and then calculates the period risk values ​​of the multiple risk pipeline points according to the multiple risk offset period and multiple offset value data. Specifically, the calculation formula for the period risk value of the multiple risk pipeline points is: ； in, For the The period risk value of each risk pipeline point, For the The risk start time of each risk pipeline point, is the current time, is the preset temperature standard coefficient, For the The temperature deviation value of each risk pipeline point, is the preset pressure standard coefficient, For the The pressure deviation value of each risk pipeline point; The predictive maintenance management module is used to compare the risk values ​​of multiple time periods according to preset risk management data, record the risk comparison results, and perform corresponding predictive maintenance management according to the risk comparison results.

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