A monitoring system for power plant support hangers and a monitoring method thereof

Abstract

The present application relates to the technical field of power plant support hanger monitoring, in particular to a power plant support hanger monitoring system and a monitoring method thereof, comprising a state acquisition unit arranged at a monitoring position of a power plant pipeline system for acquiring pipeline state data of the power plant pipeline system; and a calculation unit in communication connection with the state acquisition unit for receiving the pipeline state data. The present application can acquire pipeline state data of the power plant pipeline system by arranging the state acquisition unit at the monitoring position of the power plant pipeline system. The monitoring position is made to correspond to a measuring point mark in a three-dimensional refined model, and the pipeline state data is associated with the measuring point mark by the calculation unit, so that the operation data collected in the field can be accurately mapped to the corresponding measuring point position in the three-dimensional refined model, thereby reducing the error caused by manual matching of measuring points and data arrangement.

Description

Technical Field

[0001] This invention relates to the field of power plant support and hanger monitoring technology, and in particular to a monitoring system and method for power plant supports and hangers. Background Technology

[0002] Power plant piping systems typically include main steam pipelines, reheat steam pipelines, and supports for these pipelines. During unit operation, the pipelines are affected by factors such as temperature, pressure, weight, and the constraints imposed by the supports. This is especially true under conditions of frequent load changes, where thermal expansion and contraction of the pipelines and the stress state of the supports can easily alter. If the load-bearing state of the supports deviates from the design state, or if the pipeline displacement is abnormally constrained, the actual stress state of the piping system can easily become inconsistent with the design calculations, leading to increased stress in local pipe sections and affecting the safe operation of the power plant piping system.

[0003] In existing technologies, the operating status of pipelines and supports can typically be monitored using load sensors, displacement sensors, or temperature acquisition devices. However, these monitoring methods often focus on the acquisition and display of data from single measuring points. There is a lack of effective correlation between the acquired pipeline status data and the specific measuring point locations in the 3D model, making it difficult to directly convert real-time acquired data into the current state parameters required for pipeline stress calculation. Therefore, when performing pipeline stress analysis, it is often still necessary to manually locate measuring points, manually organize the status data, and substitute it into the calculation model. This results in problems such as low data correlation efficiency, easy mismatch between measuring point and model locations, and calculation results that fail to reflect the current operating status in a timely manner. Consequently, this affects the timeliness of identifying abnormal conditions in the power plant pipeline system and adjusting and maintaining supports. Summary of the Invention

[0004] In this section, as well as in the abstract and title of this application, some simplifications or omissions may be made to avoid obscuring the purpose of this section, the abstract, and the title of this application, and such simplifications or omissions shall not be used to limit the scope of the invention.

[0005] To address the shortcomings of existing technologies, one objective of this invention is to provide an intelligent monitoring system for power plant supports and hangers.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: an intelligent monitoring system for power plant pipe supports, comprising a status acquisition unit, which is set at the monitoring position of the power plant piping system for acquiring the piping system status data; and a calculation unit, which is communicatively connected to the status acquisition unit for receiving the piping system status data; wherein the monitoring position corresponds to the measuring point marker in the corresponding three-dimensional refined model of the power plant piping system; the calculation unit associates the piping system status data with the measuring point marker, and determines the current status parameters of the power plant piping system based on the piping system status data associated with the measuring point marker, so as to update the piping system equilibrium equation and solve the pipe stress state according to the current status parameters.

[0007] As a preferred embodiment of the intelligent monitoring system for power plant supports and hangers described in this invention, the power plant piping system includes pipes and supports and hangers, the piping system status data includes support and hanger load data, piping system displacement data and pipe temperature data, and the current status parameters include load parameters obtained from the support and hanger load data, displacement parameters obtained from the piping system displacement data, and temperature parameters obtained from the pipe temperature data.

[0008] As a preferred embodiment of the intelligent monitoring system for power plant supports and hangers described in this invention, the status acquisition unit includes a load acquisition component, a displacement acquisition component, and a temperature data interface; the load acquisition component is installed at the tie rod of the support and hanger and is used to acquire the load data of the support and hanger; the displacement acquisition component is installed corresponding to the pipeline and is used to acquire the displacement data of the pipeline system; the temperature data interface is communicatively connected to the power plant operation monitoring system and is used to acquire the pipeline temperature data.

[0009] As a preferred embodiment of the intelligent monitoring system for power plant supports and hangers described in this invention, the displacement acquisition device includes a non-contact laser displacement acquisition device, which is used to acquire displacement data of the pipeline in the X-axis, Y-axis and Z-axis directions.

[0010] As a preferred embodiment of the intelligent monitoring system for power plant supports and hangers described in this invention, the load acquisition component is prefabricated and welded onto the tie rod of the support and hanger, and is calibrated before the support and hanger is installed, so that the load data of the support and hanger acquired by the load acquisition component corresponds to the stress state of the tie rod.

[0011] As a preferred embodiment of the intelligent monitoring system for power plant supports and hangers according to the present invention, the three-dimensional refined model includes multiple model partitions, and at least some of the model partitions are respectively set with a measuring point identifier; the calculation unit determines the current state parameters of the power plant piping system based on the piping system state data corresponding to the measuring point identifier.

[0012] As a preferred embodiment of the intelligent monitoring system for power plant supports and hangers according to the present invention, the status acquisition unit further includes a data acquisition device, which is communicatively connected to the load acquisition device and the displacement acquisition device respectively; the data acquisition device is used to upload the support and hanger load data and the pipeline displacement data to the calculation unit, and the temperature data interface is used to upload the pipeline temperature data obtained from the power plant operation monitoring system to the calculation unit.

[0013] As a preferred embodiment of the intelligent monitoring system for power plant supports and hangers described in this invention, the calculation unit establishes the relationship between the unit node force P and the node displacement D based on the current state parameters: , Wherein, K is the stiffness matrix, T is the temperature difference force matrix, G is the uniformly distributed load matrix, α is the linear expansion coefficient, Δt is the temperature change, and W is the weight per unit length of the element; the calculation unit transforms the relationship between the element nodal force P and the nodal displacement D of multiple model partitions into a unified coordinate system to form the pipeline equilibrium equation, and solves it to obtain the pipeline stress state.

[0014] As a preferred embodiment of the intelligent monitoring system for power plant supports and hangers according to the present invention, the pipeline stress state includes the zone stress state corresponding to each of the model zones, and each zone stress state includes a primary stress state and a secondary stress state; the calculation unit compares the primary stress state and the secondary stress state corresponding to each of the model zones with the corresponding preset stress thresholds, and determines the model zone whose primary stress state and / or secondary stress state meet the abnormal conditions as an abnormal model zone, and the calculation unit outputs alarm information corresponding to the abnormal model zone.

[0015] To address the shortcomings of existing technologies, another objective of this invention is to provide an intelligent monitoring method for power plant supports and hangers.

[0016] The present invention adopts the following technical solution: an intelligent monitoring method for power plant supports and hangers, comprising the following steps: acquiring pipe system status data of the power plant pipe system through a status acquisition unit set at the monitoring location of the power plant pipe system; receiving the pipe system status data through a calculation unit communicatively connected to the status acquisition unit; determining the correspondence between the monitoring location and the measuring point identifiers in the corresponding three-dimensional refined model of the power plant pipe system; associating the pipe system status data with the measuring point identifiers through the calculation unit; determining the current status parameters of the power plant pipe system based on the pipe system status data associated with the measuring point identifiers; updating the pipe system equilibrium equation according to the current status parameters, and solving for the partition stress state corresponding to each model partition, wherein the partition stress state includes primary stress state and secondary stress state; comparing the primary stress state and secondary stress state corresponding to each model partition with the corresponding preset stress threshold, and determining the model partition whose primary stress state and / or secondary stress state meet the abnormal conditions as an abnormal model partition, and outputting alarm information corresponding to the abnormal model partition through the calculation unit.

[0017] The beneficial effects of the intelligent monitoring system for power plant pipe supports of the present invention are as follows: By setting the status acquisition unit at the monitoring position of the power plant piping system, the present invention can collect the piping system status data. By corresponding the monitoring position with the measuring point marker in the three-dimensional refined model, and by having the calculation unit associate the piping system status data with the measuring point marker, the operating data collected on site can be accurately mapped to the corresponding measuring point position in the three-dimensional refined model, thereby reducing the errors caused by manual matching of measuring points and data processing. Furthermore, the calculation unit determines the current status parameters of the power plant piping system based on the piping system status data associated with the measuring point marker, and updates the piping system equilibrium equation according to the current status parameters to solve the pipeline stress state. This allows the pipeline stress analysis to be based on the current actual operating data, improving the accuracy and timeliness of piping system status monitoring, stress analysis, and anomaly judgment, and providing a basis for the adjustment and maintenance of supports and the safe operation of the power plant piping system. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the overall structure of the intelligent monitoring system for power plant supports and hangers of the present invention.

[0020] Figure 2 This is a schematic diagram illustrating the data association between the piping system status data and the calculation unit of the present invention.

[0021] Figure 3 This is a schematic diagram of the arrangement of the status acquisition unit of the present invention on the power plant piping system.

[0022] Figure 4 This is a schematic diagram of the pipes and supports in the power plant piping system of the present invention.

[0023] Figure 5 This is a schematic diagram of the status acquisition unit of the present invention acquiring support load data, pipe system displacement data, and pipe temperature data.

[0024] Figure 6 This is a schematic diagram showing the correspondence between model partitions and measurement point markers in the three-dimensional refined model of this invention.

[0025] Figure 7 This is a schematic diagram of data transmission between the status acquisition unit and the calculation unit of the present invention.

[0026] Figure 8 This is a schematic diagram illustrating the alarm information output based on the stress state of each zone according to the present invention.

[0027] Figure 9 This is a schematic diagram of coordinate transformation and element node relationships in the piping system balance equation of this invention. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0029] The terminology used in this invention is that which is currently widely used in the art in consideration of the function of the invention; however, these terms may vary according to the intent of those skilled in the art, precedent, or new technology in the art. Furthermore, specific terms may be chosen by the applicant, and in such cases, their detailed meanings will be described in the detailed description of the invention. Therefore, the terms used in this specification should not be construed as simple names, but rather based on their meanings and the overall description of the invention.

[0030] Example 1

[0031] Reference Figure 1 and Figure 2This embodiment provides an intelligent monitoring system for power plant supports and hangers, including a status acquisition unit 100, a calculation unit 300, and a three-dimensional refined model 400 corresponding to the power plant piping system 200. The status acquisition unit 100 is located at monitoring position A of the power plant piping system 200 and is used to collect piping system status data B during the operation of the power plant piping system 200. The calculation unit 300 is communicatively connected to the status acquisition unit 100 and is used to receive the piping system status data B and establish an association between the received data and the measuring point identifier A' in the three-dimensional refined model 400.

[0032] In this embodiment, monitoring location A is not an abstract data acquisition point, but a real physical location on the power plant piping system 200. For example, monitoring location A can be the installation location of the tie rod 202a of the support 202, the displacement monitoring location of the pipeline 201, the pipe section location on both sides of the elbow, the location near the weld, the location near the turbine side interface, or the boiler side expansion monitoring location. The three-dimensional refined model 400 can be established according to the actual layout of the power plant piping system 200, and the measuring point identifier A' corresponding to monitoring location A is pre-set in the model. The measuring point identifier A' can include the measuring point code, pipeline number, support number, floor area number, boiler side or turbine side orientation information, and corresponding model coordinate information. In this way, the data collected on site, after entering the calculation unit 300, no longer exists as isolated sensor data, but can be accurately located to the specific measuring point location in the three-dimensional refined model 400.

[0033] Specifically, after the status acquisition unit 100 acquires the piping system status data B, it can send the piping system status data B and the acquisition number corresponding to the monitoring location A to the calculation unit 300. The calculation unit 300 queries the pre-established measurement point mapping table according to the acquisition number and maps the acquisition number to the measurement point identifier A' in the three-dimensional refined model 400. The measurement point mapping table can be stored in the form of "field acquisition number - monitoring location coordinates - model measurement point identifier - model component number". For example, if a certain hanger load acquisition component 101 is installed at the constant force hanger on the side of the main steam pipeline BA21, its field acquisition number can correspond to the support and hanger component code and measurement point identifier A' in the model; after receiving the load data, the calculation unit 300 can determine that the load data belongs to the support and hanger component and its adjacent pipe section, rather than simply storing it as an ordinary load value.

[0034] Based on the above, the calculation unit 300 determines the current state parameter C of the power plant piping system 200 based on the piping system state data B associated with the measuring point identifier A'. The current state parameter C is not simply the raw collected data, but rather a state parameter formed after calibration, conversion, coordinate matching, unit unification, and outlier filtering of the field-collected data, which can be used for piping system stress analysis. For example, the electrical signal collected by the load acquisition device 101 can be converted into support and hanger load parameters, the distance change collected by the displacement acquisition device 102 can be converted into the displacement parameter of the pipe 201 in the corresponding direction, and the operating temperature obtained by the temperature data interface 103 can be converted into the temperature parameter used in thermal expansion calculations. Because the current state parameter C maintains a correspondence with the measuring point identifier A', the calculation unit 300 can know the specific location in the piping system from which each state parameter originates and can substitute it into the piping system equilibrium equation at the corresponding location.

[0035] Conventional online monitoring systems typically only complete the process of "sensor acquisition - data display - limit violation alert," lacking a stable correspondence between the acquired data and the structural calculation model. Subsequent stress analysis still relies on manually locating measuring points, manually organizing data, and manually importing it into the calculation model. Compared to conventional online monitoring methods, the improvements in this embodiment are as follows: by setting the correspondence between monitoring location A and measuring point identifier A', the field-acquired data has model positioning attributes from the acquisition stage; by associating the piping system status data B with the measuring point identifier A' through the calculation unit 300, the data can be transformed from "display data" to "calculation data"; by determining the current state parameter C based on the associated data, the piping system balance equation can be updated according to the current actual operating state, instead of continuing to use static design parameters or offline inspection data.

[0036] The calculation unit 300 updates the piping system equilibrium equations based on the current state parameter C and solves for the pipe stress state F. Here, "updating" can be understood as inputting real-time or near-real-time acquired load parameters, displacement parameters, temperature parameters, etc., as boundary conditions, load conditions, or displacement constraints into the piping system equilibrium equations, so that the equilibrium equations reflect the actual stress state under the current operating conditions. For example, when the measured load of a certain hanger 202 is higher than the design value, this load change will be entered into the calculation model of the relevant pipe section through the corresponding measuring point identifier A'; when a pipe section experiences a thermal displacement deviation, this displacement change will participate in the calculation as a nodal displacement or constraint change; when the pipe temperature in a certain area rises, the corresponding temperature change will participate in the calculation of the thermal force caused by thermal expansion and contraction.

[0037] The technical advantage of this embodiment lies in the formation of a continuous technical chain among the state acquisition unit 100, the calculation unit 300, and the three-dimensional refined model 400. This chain extends from field measurement points to model measurement points, from raw data to current state parameters, from current state parameters to piping system equilibrium equations, and from piping system equilibrium equations to the pipe stress state F. This technical chain does not simply address the problem of displaying monitoring data, but rather the difficulty of accurately inputting real-time field data into the three-dimensional model and mechanical calculation equations. Consequently, it reduces errors from manual matching of measurement point locations, improves the real-time performance and accuracy of piping system state analysis, and provides a reliable basis for adjusting supports and hangers 202, risk warnings for pipelines 201, and the operation and maintenance of the power plant piping system 200.

[0038] Example 2

[0039] Reference Figures 2-4 Based on Example 1, this example further describes the power plant piping system 200 and the piping system status data B. The power plant piping system 200 includes pipes 201 and supports 202. Pipes 201 can be main steam pipes, primary reheat pipes, secondary reheat pipes, or boiler expansion-related pipe sections. Supports 202 can include constant force spring hangers, variable force spring hangers, rigid hangers, limiting supports, or other support structures used to bear the self-weight of the pipes, external loads, and limit pipe displacement.

[0040] Piping system status data B includes support and hanger load data B1, piping system displacement data B2, and pipe temperature data B3. Support and hanger load data B1 reflects the actual load borne by support and hanger 202. Piping system displacement data B2 reflects the displacement change of pipe 201 relative to the reference position during cold, hot, or variable load operation. Piping temperature data B3 reflects the actual temperature state of pipe 201 in the corresponding monitoring section. These three types of data correspond to the main influencing factors in piping system stress analysis: load data reflects the force distribution between pipe 201 and support and hanger 202; displacement data reflects the spatial position of pipe 201 and the constraint on its expansion; and temperature data reflects the thermal stress conditions caused by thermal expansion and contraction.

[0041] In this embodiment, the current state parameter C includes load parameters obtained from the support and hanger load data B1, displacement parameters obtained from the pipe system displacement data B2, and temperature parameters obtained from the pipe temperature data B3. To ensure that the current state parameter C can be directly used for subsequent calculations, the calculation unit 300 can preprocess the three types of data. For the support and hanger load data B1, the calculation unit 300 can convert the collected voltage, current, or digital quantity into actual load values ​​according to the calibration curve of the load acquisition device 101, and normalize it with the design load value, cold state check value, or hot state check value. For the pipe system displacement data B2, the calculation unit 300 can convert the distance collected by the displacement acquisition device 102 into displacement parameters in the X-axis, Y-axis, and Z-axis directions, and keep them consistent with the coordinate directions in the three-dimensional refined model 400. For the pipe temperature data B3, the calculation unit 300 can convert it into a temperature change Δt, which serves as the input condition for calculating the temperature difference force.

[0042] Furthermore, the calculation unit 300 can add a data timestamp and a measurement point identifier A' to each group of current state parameters C. The data timestamp is used to determine the acquisition time corresponding to the group of state parameters, and the measurement point identifier A' is used to determine the model location corresponding to the group of state parameters. With this setting, the calculation unit 300 can perform fusion processing on load parameters, displacement parameters, and temperature parameters within the same time or the same calculation cycle, avoiding the mixing of data from different acquisition cycles into the same stress solution process. For example, within a calculation cycle, the calculation unit 300 can select support load data B1, pipe displacement data B2, and pipe temperature data B3 within the same time window, and map these data to the same pipe segment, adjacent node, or the same model partition 401 according to the measurement point identifier A'.

[0043] In this embodiment, the piping system status data B is no longer a single type of monitoring data, but rather forms multi-source status data covering stress, displacement, and temperature. This multi-source status data collectively reflects the current operating status of the power plant piping system 200, providing a more complete data foundation for subsequent updates to the piping system balance equations. Compared to schemes that only collect support loads or only collect pipe displacements, this embodiment can simultaneously consider the impact of load redistribution, thermal expansion displacement, and temperature changes on the pipe stress state F, thereby improving the reliability of determining the primary stress state F1 and the secondary stress state F2.

[0044] Example 3

[0045] Reference Figure 5Based on Embodiment 2, this embodiment describes the specific composition and connection relationship of the status acquisition unit 100. The status acquisition unit 100 includes a load acquisition component 101, a displacement acquisition component 102, and a temperature data interface 103. The load acquisition component 101 is installed at the tie rod 202a of the support 202 and is used to acquire support load data B1. The displacement acquisition component 102 is installed corresponding to the pipeline 201 and is used to acquire pipeline displacement data B2. The temperature data interface 103 is communicatively connected to the power plant operation monitoring system and is used to acquire pipeline temperature data B3 of the pipeline 201.

[0046] The load acquisition device 101 can be a strain gauge load sensor, a pin-type load sensor, a tie rod clamp-type load sensor, or a welded load sensor. For the tie rod 202a of the support 202, the load acquisition device 101 can be arranged on the force transmission path of the tie rod 202a so that the axial tensile force borne by the tie rod 202a can be acquired. Since the stress state of the tie rod 202a can directly reflect the support state of the support 202 on the pipe 201, setting the load acquisition device 101 at the tie rod 202a can avoid the errors caused by manual judgment based solely on the appearance of the support or the spring scale.

[0047] The displacement acquisition unit 102 can be positioned near the outer wall, pipe clamp, suspension point, or preset measurement reference point of the pipeline 201. The displacement acquisition unit 102 and the pipeline 201 can be connected via a non-contact distance measurement method or a wire-type displacement acquisition method. When using the non-contact distance measurement method, the displacement acquisition unit 102 maintains a preset measurement distance from the pipeline 201 and transmits a measurement signal towards the target measurement surface of the pipeline 201. When the pipeline 201 experiences thermal expansion or abnormal constraint, the target measurement surface changes position relative to the displacement acquisition unit 102, and the displacement acquisition unit 102 can then obtain the pipeline displacement data B2.

[0048] The temperature data interface 103 can be a data interface with the power plant's operation monitoring system, such as an industrial Ethernet interface, serial communication interface, fieldbus interface, or software data interface. The temperature data interface 103 does not necessarily require reconfiguring the temperature sensor; instead, it can read the pipeline temperature data B3 from the power plant's existing operation monitoring system. This is because the power plant's operation system typically already contains temperature monitoring data, and repeatedly deploying temperature acquisition hardware would increase construction complexity and maintenance costs. By directly acquiring the pipeline temperature data B3, the temperature data interface 103 can integrate existing operational data with the stress calculation logic of this invention.

[0049] The load acquisition unit 101, displacement acquisition unit 102, and temperature data interface 103 correspond to the three key factors affecting the pipeline stress state F: load, displacement, and temperature, respectively. The parallel acquisition of these three data points, coupled with unified correlation within the calculation unit 300, avoids the problem of single-point data being unable to explain pipeline stress changes. For example, when the load on a certain support 202 is high, if the corresponding pipeline 201 also exhibits abnormal displacement and operates at a high temperature, the calculation unit 300 can determine that there may be thermal expansion obstruction or support stress redistribution issues in that area. If the load is high but the displacement and temperature are normal, it may be more likely that the local support installation or calibration status is abnormal. Therefore, this embodiment provides a foundation for subsequent anomaly cause analysis through the combination of multiple types of state data.

[0050] Example 4

[0051] Reference Figure 5 Based on Example 3, this example provides a specific method for acquiring pipeline displacement data B2. The displacement acquisition device 102 includes a non-contact laser displacement acquisition device, which is used to acquire displacement data of pipeline 201 in the X-axis, Y-axis and Z-axis directions.

[0052] In practice, a mounting bracket can be installed near monitoring position A of pipeline 201, and the non-contact laser displacement acquisition device can be fixed to the mounting bracket. The mounting bracket can be fixed to the power plant building structure, steel structure platform, or a support foundation that is relatively stable relative to the position of pipeline 201. To obtain three-dimensional displacement data, three non-contact laser displacement acquisition devices with different laser ranging directions can be arranged at the same monitoring position A, corresponding to the X-axis, Y-axis, and Z-axis directions respectively; alternatively, a multi-axis displacement acquisition device can be arranged to obtain the displacement in the three directions through multiple measurement channels.

[0053] The X, Y, and Z axes can be consistent with the unified coordinate system used in the 3D refined model 400. For example, the X-axis can be defined as a horizontal extension direction of the pipe 201, the Y-axis as the vertical direction, and the Z-axis as a horizontal transverse direction perpendicular to both the X and Y axes. Alternatively, they can be defined according to the actual modeling coordinate system of the power plant piping system 200. The key is that the displacement direction acquired by the non-contact laser displacement acquisition device should be able to be converted or mapped to the coordinate direction of the 3D refined model 400, so that the displacement parameters can directly participate in the piping system equilibrium equations.

[0054] The non-contact laser displacement acquisition device does not directly contact the pipeline 201, reducing interference with the pipeline's thermal expansion and vibration. For high-temperature pipelines or pipeline areas with limited operating space, non-contact measurement can also reduce measurement errors caused by sensor heating, cable pulling, or mechanical wear. When the pipeline 201 undergoes thermal expansion displacement during operation, the laser displacement acquisition device can continuously or periodically acquire the distance change of the target measurement surface, which is then converted into pipeline displacement data B2 by the calculation unit 300.

[0055] In one specific implementation, the calculation unit 300 records the initial displacement reference value for each monitoring position A after the cold installation of the pipeline 201. During unit operation, the non-contact laser displacement acquisition device collects the current distance value in real time. The calculation unit 300 calculates the difference between the current distance value and the initial displacement reference value to obtain the displacement changes in the X, Y, and Z axis directions. If the unit is under different load conditions, the calculation unit 300 can also compare the displacement changes with the design thermal displacement value under the corresponding conditions to determine whether the pipeline 201 has problems such as abnormal expansion, insufficient expansion, or obstructed expansion.

[0056] The purpose of this embodiment is to endow the piping system displacement data B2 with spatial directional attributes through three-dimensional displacement acquisition. Ordinary unidirectional displacement acquisition can only reflect displacement changes in one direction, which is difficult to support stress analysis of spatial piping systems. Power plant piping systems 200 typically have complex spatial orientations, and elbows, diameter changes, support points, and interface locations may all exhibit multi-directional displacements. By using displacement data in the X, Y, and Z axis directions, the calculation unit 300 can more accurately establish the nodal displacements D and use them as important inputs for updating the piping system equilibrium equations, thereby improving the solution accuracy of the pipeline stress state F.

[0057] Example 5

[0058] Reference Figure 4 and Figure 5 Based on Example 4, this example further describes the installation method of the load acquisition component 101. The load acquisition component 101 is prefabricated and welded to the tie rod 202a of the support 202, and is calibrated before the support 202 is installed, so that the support load data B1 collected by the load acquisition component 101 corresponds to the stress state of the tie rod 202a.

[0059] Specifically, the support 202 may include a lifting point assembly connected to the pipe 201, a tie rod 202a, and a spring assembly or rigid support assembly for generating supporting force. The tie rod 202a is the component in the support 202 with a relatively clear load transfer function; the weight of the pipe 201, the additional force caused by thermal displacement, and local load changes are all reflected through the tie rod 202a. Prefabricating and welding the load acquisition component 101 to the tie rod 202a can ensure a stable connection between the load acquisition component 101 and the tie rod 202a, avoiding positional offset and measurement drift caused by subsequent on-site clamping, binding, or temporary installation.

[0060] Prefabrication welding can be completed before the support 202 is installed on site. After prefabrication welding, the detection assembly consisting of tie rod 202a and load acquisition device 101 can be calibrated in the factory or on a testing platform. During calibration, multiple known load values ​​can be applied to tie rod 202a, and the electrical signal values ​​output by load acquisition device 101 can be recorded to form a load-output signal correspondence. The calculation unit 300 or data acquisition device 104 can store this correspondence and convert the output signal of load acquisition device 101 into support load data B1 based on this correspondence during on-site operation.

[0061] During the on-site installation of the support bracket 202, since the load acquisition component 101 has already formed an integrated prefabricated structure with the tie rod 202a, the installers can complete the assembly of the support bracket 202 in the same way as ordinary support brackets, without having to readjust the position of the load acquisition component 101 in narrow, high-temperature, or high-altitude areas. This setup reduces the complexity of on-site construction and ensures that the measurement position of each load acquisition component 101 is consistent with the force path of the tie rod 202a.

[0062] This embodiment emphasizes the combination of "prefabrication welding" and "pre-installation calibration". Simply installing the sensor on the tie rod 202a does not guarantee a stable correspondence between the collected values ​​and the actual stress state of the tie rod 202a; calibration alone is insufficient, as the sensor's position may change during on-site installation, affecting the reliability of the calibration results. By prefabricating and welding first, followed by pre-installation calibration, the structural position, force transmission path, and calibration relationships of the load acquisition component 101 can be fixed before it enters the site, thereby improving the accuracy and traceability of the support load data B1.

[0063] Example 6

[0064] Reference Figure 6Based on Embodiment 3 or Embodiment 4, this embodiment describes the three-dimensional refined model 400 and model partitions 401. The three-dimensional refined model 400 includes multiple model partitions 401, and at least some model partitions 401 are respectively assigned a measuring point identifier A'. The calculation unit 300 determines the current state parameter C of the power plant piping system 200 based on the piping system state data B corresponding to the measuring point identifier A'.

[0065] The three-dimensional refined model 400 can be established based on the actual structure of the power plant piping system 200, including pipes 201, supports 202, elbows, welds, reducers, valves, lifting points, limiting points, and nodes related to stress analysis. To facilitate data management and zonal calculations, the three-dimensional refined model 400 can be divided into multiple model zones 401 according to pipeline type, spatial region, functional region, or stress analysis unit. For example, the boiler-side region of the main steam pipeline can be set as one model zone 401, and the turbine-side region of the main steam pipeline can be set as another model zone 401; the primary reheat pipeline and the secondary reheat pipeline can also be divided into different model zones 401; zoning can also be based on densely populated support and hanger areas, concentrated elbow areas, or high-stress-risk areas.

[0066] Each model partition 401 may include one or more measurement point identifiers A'. When a measurement point identifier A' is set in a model partition 401, it can serve as a key monitoring point for that partition. When multiple measurement point identifiers A' are set in a model partition 401, the calculation unit 300 can jointly determine the current state parameter C of the model partition 401 based on the pipe system state data B from multiple measurement points. This configuration allows the model partition 401 to not only serve as a graphical display area but also as a basic management unit for data fusion and mechanical calculations.

[0067] The measuring point identifier A' can correspond one-to-one with the monitoring location A, or it can form a many-to-one or one-to-many relationship with the monitoring location A. For example, when multiple displacement measuring points and multiple load measuring points are set in a certain model partition 401, each monitoring location A has an independent measuring point identifier A'; when determining the current state parameter C of the model partition 401, the calculation unit 300 can integrate the pipe system state data B corresponding to these measuring point identifiers A'. For some model partitions 401 that do not have sensors directly arranged, the calculation unit 300 can also determine their boundary state parameters based on the measuring point data of adjacent model partitions 401, the pipe system connection relationship, and the interpolation rules.

[0068] The technical advantage of this embodiment lies in transforming the refined 3D model 400 from a simple visualization model into a model that participates in data association and computational management. Ordinary 3D display systems typically only show the geometry of pipes and supports, with collected data existing independently in tabular or curve form. This embodiment, through the corresponding setting of model partitions 401 and measuring point identifiers A', enables the data collected by the status acquisition unit 100 to be located to a specific model partition 401 and further transformed into the current status parameter C of that partition. This provides a foundation for subsequent partition stress calculation, partition alarm, and anomaly location.

[0069] Example 7

[0070] Reference Figure 7 and Figure 9 Based on Embodiment 6, this embodiment describes the data upload structure of the status acquisition unit 100. The status acquisition unit 100 also includes a data acquisition unit 104, which is communicatively connected to the load acquisition unit 101 and the displacement acquisition unit 102. The data acquisition unit 104 is used to upload the support load data B1 and the pipe system displacement data B2 to the calculation unit 300, and the temperature data interface 103 is used to upload the pipe temperature data B3 obtained from the power plant operation monitoring system to the calculation unit 300.

[0071] The data acquisition unit 104 can be installed near the monitoring area of ​​the field acquisition box, local control cabinet, or support bracket. The load acquisition unit 101 and displacement acquisition unit 102 can be connected to the data acquisition unit 104 via wired or wireless means. Wired connections can utilize shielded cables, industrial buses, analog input lines, or digital communication lines; wireless connections can employ low-power wireless communication methods suitable for power plant sites. Considering the high temperatures, strong electromagnetic interference, and complex steel structure obstructions present at power plant sites, this embodiment preferably uses a wired communication method with strong anti-interference capabilities. The data acquisition unit 104 centrally acquires, preliminarily processes, and uploads data from multiple field acquisition units.

[0072] The data acquisition unit 104 can sample, filter, remove outliers, convert units, and package data for the support load data B1 and the pipe system displacement data B2. The data packet can contain the acquisition part number, acquisition time, acquired value, data type, monitoring location A code, and verification information. After receiving the data packet, the calculation unit 300 can query the measuring point mapping table based on the acquisition part number and monitoring location A code, and associate the acquired value in the data packet with the corresponding measuring point identifier A'.

[0073] Temperature data interface 103 can connect to the power plant operation monitoring system and acquire pipeline temperature data B3. Temperature data interface 103 and data acquisition unit 104 can upload data separately, or the pipeline temperature data B3 can be transmitted to data acquisition unit 104 and then uploaded uniformly. If the separate upload method is used, calculation unit 300 can align data from different sources based on timestamps and measurement point identifiers A'; if the unified upload method is used, data acquisition unit 104 can first perform preliminary combination of load, displacement, and temperature data before uploading it to calculation unit 300.

[0074] In this embodiment, the power plant operation monitoring system can be a power plant-level monitoring information system (SIS), which is used to collect operating parameters collected by the DCS system, field instruments, or other monitoring systems during power plant operation. The temperature data interface 103 communicates with the SIS and obtains the pipe temperature data B3 at the corresponding location of pipe 201 through the SIS. Therefore, it is unnecessary to add a separate temperature sensor at each pipe monitoring location A; the temperature data from the existing power plant operation monitoring system can be used for pipe system status analysis, reducing the complexity of field sensor placement and improving the consistency between the pipe temperature data B3 and the actual operating status of the power plant.

[0075] This embodiment addresses the data access challenges arising from the dispersed deployment of multiple sensors on-site using a data acquisition unit 104. The power plant piping system 200 has a large number of monitoring locations A. Directly connecting each acquisition unit to the computing unit 300 would result in complex wiring, difficult address management, and inconsistent data timing. The data acquisition unit 104, acting as a field data aggregation node, can uniformly manage multiple load acquisition units 101 and displacement acquisition units 102, and upload data to the computing unit 300 at fixed intervals, facilitating the formation of a synchronized dataset suitable for computation.

[0076] Example 8

[0077] Reference Figure 8 and Figure 9 Based on Example 7, this example describes the establishment of the piping system equilibrium equation, coordinate transformation, and the solution process for the pipe stress state F. The calculation unit 300 establishes the relationship between the element nodal force P and the nodal displacement D based on the current state parameter C: P = KD + TαΔt - GW. Where K is the stiffness matrix, T is the thermal force matrix, G is the uniformly distributed load matrix, α is the linear expansion coefficient, Δt is the temperature change, and W is the weight per unit length of the element.

[0078] In practical implementation, calculation unit 300 can first divide the power plant piping system 200 into units. The units to be divided can include straight pipe units, bend units, reducing pipe units, spring support units, and other units related to the stress on the piping system. Welds, support points, both sides of bends, both ends of reducing pipes, and interfaces of important equipment can be used as calculation nodes. Each unit has corresponding head and tail nodes. Node displacement D can include the translation and rotation of the node in the spatial coordinate direction, and unit node force P can include node force and node moment.

[0079] For each element, computational element 300 establishes the relationship between nodal forces P and nodal displacements D based on element type, geometric dimensions, material parameters, temperature changes, and weight parameters. The stiffness matrix K reflects the stiffness characteristics of the element under force-induced displacement. The thermal force matrix T, together with the linear expansion coefficient α and temperature change Δt, reflects the thermal expansion and contraction effects caused by temperature changes. The uniformly distributed load matrix G, together with the element's weight per unit length W, reflects the influence of the pipe 201's self-weight and related uniformly distributed loads on the nodal forces.

[0080] Because the power plant piping system 200 typically has a complex orientation in three-dimensional space, different elements may have different local coordinate orientations. The computational unit 300 transforms the relationships between nodal forces P and nodal displacements D of multiple model partitions 401 into a unified coordinate system to form the piping system equilibrium equations. The unified coordinate system can be the global coordinate system of the three-dimensional refined model 400. For each element, the computational unit 300 can establish a coordinate transformation matrix based on the directional relationship between the element's local coordinate system and the unified coordinate system, transforming the stiffness matrix, temperature force matrix, uniformly distributed load matrix, nodal force vector, and nodal displacement vector from the local coordinate system to the unified coordinate system.

[0081] The purpose of coordinate transformation is to prevent elements in different spatial directions from failing to be assembled into a unified equilibrium equation. Without a unified coordinate transformation, the displacement direction of a horizontal pipe segment, the displacement direction of a vertical pipe segment, and the local coordinate direction of a bend element may be inconsistent, leading to confusion in the physical meaning of nodal forces and displacements when directly assembled. By unifying the coordinate system, the computational element 300 can assemble the element relationships in all model partitions 401 into the same pipe system equilibrium equation, thereby solving for the nodal displacements, nodal internal forces, and pipe stress state F of the entire power plant pipe system 200.

[0082] During the solution process, the calculation unit 300 can input the current state parameter C as a boundary condition or load condition into the piping system equilibrium equation. For example, the load parameters obtained from the support and hanger load data B1 can correct the nodal forces or support conditions at the support and hanger points; the displacement parameters obtained from the piping system displacement data B2 can correct the corresponding nodal displacement D or be used as displacement constraints; and the temperature parameters obtained from the pipe temperature data B3 can determine the temperature change Δt. After solving the piping system equilibrium equation, the calculation unit 300 can obtain the nodal displacements, the internal forces of each element, and the further calculated pipe stress state F.

[0083] The calculation unit 300 establishes a unified coordinate system X for the power plant piping system 200. The unified coordinate system X may include a first coordinate axis X1, a second coordinate axis X2, and a third coordinate axis X3, wherein the second coordinate axis X2 can be set to the vertically upward direction. For each model partition 401, the calculation unit 300 establishes a unit local coordinate system λ according to the spatial orientation of the model partition 401, and transforms the nodal forces, nodal displacements, stiffness matrices, thermal force matrices, and uniformly distributed load matrices under the local coordinate system λ to the unified coordinate system X through a coordinate transformation matrix.

[0084] After coordinate transformation, the calculation unit 300 assembles the relationships between multiple model partitions 401 into an overall piping system equilibrium equation according to the connection relationships of the calculation nodes. The overall piping system equilibrium equation reflects the mechanical relationship between pipes 201, supports 202, equipment interfaces, and boundary constraints. The calculation unit 300 can solve this equilibrium equation using Gaussian elimination, sparse matrix solving, iterative solving, or finite element methods to obtain the displacement of each calculation node, the internal forces of each model partition 401, and the corresponding pipe stress state F.

[0085] The key function of this embodiment is to transform real-time monitoring data into real-time input conditions for the piping system balance equation. Ordinary online monitoring systems often only trigger alarms when sensor readings exceed thresholds, without assessing the impact of these reading changes on pipe stress. This embodiment addresses this by... The formula incorporates load, displacement, and temperature data into mechanical calculations, enabling the calculation unit 300 to further derive the pipeline stress state F from the measurement point data.

[0086] By transforming multiple model partitions 401 to a unified coordinate system X to form the pipeline system equilibrium equation, this embodiment avoids the problem of complex spatial pipelines being unable to be solved uniformly due to inconsistencies in local coordinates. Especially for pipeline systems with multiple bends, supports, and equipment interfaces, such as the three major pipelines, it is difficult to accurately assess risks using only a single measuring point threshold. This embodiment, however, can determine the impact of local anomalies on the overall stress distribution based on the overall pipeline system equilibrium relationship, thereby improving the engineering value of the monitoring results.

[0087] A model is established based on the principle of residual energy: P= , In the formula: , K is the stiffness matrix, T is the thermal force matrix, G is the uniformly distributed load matrix, α is the linear expansion coefficient, Δt is the temperature change, and W is the weight per unit length of the element. Establish the equilibrium equations for nodal forces P and nodal displacements D between each element in the λ coordinate system. P(λ)=K(λ)D(λ)+T(λ) -G(λ)W(λ), Apply the rotation matrix from the X coordinate system to the λ coordinate system:

[0088] Expressing P(λ), W(λ), and D(λ) as vectors in the X-coordinate system, we can write:

[0089] In the formula: ; Right now, P(x) = K(x)D(x) + T(x) -G(x)W(x), In the formula: K(x) = T(x) = G(x) = W(x) = {0, -w, 0} represents the stiffness matrix, thermal force matrix, and uniformly distributed load matrix of the element in the X coordinate system, respectively. The Gaussian elimination method is used to solve large sparse matrices to obtain the displacement and internal force of each element, and then the primary and secondary stresses are calculated.

[0090] In this embodiment, let the e-th unit in a piping system be Le, and its endpoints be numbered i and j. Then the basic equation can be written as:

[0091] In the formula: , P e D e W and W represent the nodal forces, nodal displacements, and weight per unit length of element Le, respectively. , Ke Let Te and Ge be the stiffness matrix, thermal force matrix, and uniformly distributed load matrix of element Le in the X-coordinate system, respectively. Substituting further, we get: , The above formula can be used to derive the force balance equations for each element of the entire piping system. Based on the equations, the Gaussian elimination method is used to solve the large sparse matrix, obtaining the head and tail displacements and internal forces of each element. The stresses of each element, namely the primary stress and secondary stress, are then obtained based on the internal forces.

[0092] Example 9

[0093] Reference Figure 8 Based on Example 8, this example describes the zone stress state and alarm information output. The pipeline stress state F includes the zone stress state corresponding to each model zone 401. Each zone stress state includes a primary stress state F1 and a secondary stress state F2. The calculation unit 300 compares the primary stress state F1 and the secondary stress state F2 corresponding to each model zone 401 with the corresponding preset stress thresholds, and determines the model zone 401 whose primary stress state F1 and / or secondary stress state F2 meet the abnormal conditions as an abnormal model zone. The calculation unit 300 outputs the alarm information corresponding to the abnormal model zone.

[0094] The primary stress state F1 reflects the stress state of pipeline 201 under primary loads such as internal pressure, self-weight, and load distribution from supports and hangers. The secondary stress state F2 reflects the stress state of pipeline 201 caused by constraints due to thermal expansion and contraction, misaligned displacement, or abnormal constraints from supports and hangers. Since the causes of primary and secondary stresses differ, and their abnormal consequences and handling methods also differ, this embodiment sets preset stress thresholds for both primary stress state F1 and secondary stress state F2.

[0095] The preset stress threshold can be set according to the pipe grade, material properties, design allowable stress, operating conditions, the importance of model partition 401, or historical operating data. For model partition 401 near the turbine side interface, a stricter threshold can be set to promptly detect the risk of interface thrust caused by insufficient support or expansion obstruction. For ordinary straight pipe section model partition 401, the threshold can be set based on the design allowable stress and operating experience. For high-temperature and high-pressure pipe sections, primary stress thresholds and secondary stress thresholds can be set separately, and different alarm levels are allowed for them.

[0096] When the calculation unit 300 makes comparisons, it can calculate each model partition 401 one by one. For example, model partition 401-1 corresponds to the boiler side of the main steam pipeline, model partition 401-2 corresponds to the turbine side of the main steam pipeline, and model partition 401-3 corresponds to the primary reheat pipeline area. When the primary stress state F1 of model partition 401-1 exceeds its preset stress threshold, while model partitions 401-2 and 401-3 do not exceed their corresponding thresholds, the calculation unit 300 only identifies model partition 401-1 as an abnormal model partition and outputs the alarm information corresponding to model partition 401-1. This setting can avoid a general alarm for the entire 3D refined model 400 and reduce misjudgments by maintenance personnel.

[0097] Alarm information may include the partition number of anomaly model partition 401, the corresponding measuring point identifier A', the anomaly type, the anomaly stress value, the preset stress threshold, the over-limit ratio, the anomaly occurrence time, and the suggested review objects. Anomaly types may include primary stress anomalies, secondary stress anomalies, or simultaneous primary and secondary stress anomalies. If the primary stress state F1 is abnormal, the alarm information may prompt a focus on reviewing the load distribution of supports and hangers, the self-weight support status of the pipeline, or local bearing deviations. If the secondary stress state F2 is abnormal, the alarm information may prompt a focus on reviewing the pipeline's thermal expansion displacement, limit status, sliding support status, or support and hanger constraint status.

[0098] The core of this embodiment lies in directional alarm. Alarm information is output by the computing unit 300 and corresponds to the anomaly model partition 401. The 3D refined model 400 can serve as a display carrier for the anomaly location, showing the anomaly model partition 401, the corresponding measuring point identifier A', and the alarm information. In a further implementation, the computing unit 300 can also send the alarm information to the front-end 3D visualization interface, allowing the anomaly model partition 401 to be presented using color, flashing, list, pop-up, or icon methods.

[0099] Example 10

[0100] Reference Figures 1 to 9 This embodiment provides an intelligent monitoring method for power plant supports and hangers. This method can be executed by the intelligent monitoring system for power plant supports and hangers in any of the foregoing embodiments, and includes the following steps.

[0101] First, the status acquisition unit 100, located at monitoring position A of the power plant piping system 200, acquires the piping system status data B of the power plant piping system 200. The piping system status data B may include support and hanger load data B1, piping system displacement data B2, and pipe temperature data B3. During acquisition, the load acquisition unit 101 can acquire the force data of the tie rod 202a of the support and hanger 202, the displacement acquisition unit 102 can acquire the displacement data of the pipe 201 in the X, Y, and Z axis directions, and the temperature data interface 103 can obtain the pipe temperature data B3 from the power plant operation monitoring system.

[0102] Secondly, the computing unit 300, which is communicatively connected to the status acquisition unit 100, receives the piping system status data B. When receiving data, the computing unit 300 can simultaneously receive the acquisition component number, monitoring location A code, and acquisition time. For data uploaded by the data acquisition unit 104, the computing unit 300 can first perform data integrity verification to confirm whether the required load, displacement, and temperature data within the same calculation cycle meet the calculation requirements.

[0103] Then, the correspondence between monitoring location A and the measuring point identifier A' in the corresponding 3D refined model 400 of the power plant piping system 200 is determined. This correspondence can be pre-established during the system deployment phase. For example, technicians can set a measuring point identifier A' for each actual monitoring location A in the 3D refined model 400 and establish a mapping table containing the field acquisition number, model component number, measuring point identifier A', and model partition 401. During the operation phase, the calculation unit 300 can determine the model location corresponding to each set of piping system status data B based on the mapping table.

[0104] Next, the piping system status data B is associated with the measuring point identifier A' through the calculation unit 300. The association process may include data type identification, unit conversion, calibration conversion, coordinate direction matching, and timestamp alignment. After association, each set of status data has clear model positioning attributes and calculation attributes. That is, the calculation unit 300 not only knows what the acquired value is, but also knows which model partition 401 the acquired value comes from, which support 202 or pipe 201 node it corresponds to, and which part of the piping system balance equation it should participate in.

[0105] Subsequently, based on the piping system status data B associated with the measuring point identifier A', the current status parameters C of the power plant piping system 200 are determined. The current status parameters C may include load parameters, displacement parameters, and temperature parameters. Load parameters can be calculated from the support and hanger load data B1, displacement parameters can be calculated from the piping system displacement data B2, and temperature parameters can be calculated from the pipe temperature data B3. The calculation unit 300 can combine the current status parameters C within the same model partition 401 or related adjacent model partitions 401 into a set of calculation parameters.

[0106] Subsequently, the piping system equilibrium equations are updated based on the current state parameter C, and the stress states corresponding to each model partition 401 are obtained by solving the equations. The partition stress states include primary stress state F1 and secondary stress state F2. Specifically, the calculation unit 300 can establish or update the relationship between element nodal forces P and nodal displacements D based on the current state parameter C, transform the element relationships in each model partition 401 to a unified coordinate system, and assemble them into the piping system equilibrium equations. The calculation unit 300 obtains the nodal displacements, nodal internal forces, and partition stress states by solving the piping system equilibrium equations.

[0107] Finally, the primary stress state F1 and secondary stress state F2 corresponding to each model partition 401 are compared with the corresponding preset stress thresholds. Model partitions 401 that meet the abnormal conditions for primary stress state F1 and / or secondary stress state F2 are identified as abnormal model partitions. The calculation unit 300 outputs alarm information corresponding to the abnormal model partitions. The alarm information can be used to prompt maintenance personnel to review the supports 202, pipes 201, limiting structures, or related measuring points within the abnormal model partitions 401.

[0108] Using this method, the operating status of the power plant piping system 200 no longer depends on offline analysis after manual inspection, but can be continuously, regionally, and computationally monitored based on on-site collected data and a three-dimensional refined model 400.

[0109] Example 11

[0110] To further illustrate the engineering application of the present invention, in a specific application scenario, the power plant piping system 200 includes main steam pipelines, primary reheat pipelines, and secondary reheat pipelines. Each type of pipeline can be divided into model partitions 401 according to the boiler side and the turbine side. Several measuring point identifiers A' are set within each model partition 401, and the measuring point identifiers A' correspond to the acquisition positions of the load acquisition device 101, the displacement acquisition device 102, and the pipeline temperature data B3, respectively.

[0111] When the unit increases from low load to high load, the temperature of pipe 201 rises and thermal expansion occurs, causing a change in the stress state of the support 202. After the status acquisition unit 100 acquires the support load data B1 and the pipe system displacement data B2, the calculation unit 300 imports these data into the corresponding model partition 401 according to the measuring point identifier A'. If the displacement of pipe 201 in a certain turbine-side model partition 401 is less than the design thermal displacement, and the corresponding support load data B1 shows a significant increase, the calculation unit 300 can solve for the increase in the secondary stress state F2 of that partition after updating the pipe system equilibrium equation. At this time, the calculation unit 300 can identify that partition as an abnormal model partition and output an alarm message for abnormal secondary stress.

[0112] In this application scenario, a single sensor alarm may only indicate an increase in load or abnormal displacement, but it cannot determine whether the abnormality will lead to stress risks in pipe 201. This invention uses the piping system balance equation to transform load, displacement, and temperature data into zoned stress states, enabling a more accurate assessment of the impact of abnormalities on piping system safety. This approach allows maintenance personnel to prioritize checking supports 202, limiting structures, sliding supports, and adjacent pipe sections in the abnormality model zone 401, without needing to perform indiscriminate inspections of the entire power plant piping system 200.

[0113] Example 12

[0114] In another specific implementation, the measuring point identifier A' in the 3D refined model 400 can also be associated with model component codes, data acquisition device codes, and maintenance record codes. The model component codes are used to identify model components such as pipes 201, supports 202, elbows, welds, or valves. The data acquisition device codes are used to identify load acquisition devices 101, displacement acquisition devices 102, or data acquisition devices 104. The maintenance record codes are used to associate with the corresponding component's inspection records, calibration records, or support adjustment records.

[0115] After the calculation unit 300 outputs the alarm information corresponding to the abnormal model partition 401, it can further query the model component code and maintenance record code based on the measuring point identifier A' within the abnormal model partition 401. For example, if the alarm information shows that the secondary stress state F2 is abnormal in a certain model partition 401, the calculation unit 300 can list the pipe 201 elbow, support 202 suspension point, and displacement measuring point involved in that partition, and indicate the most recent support 202 adjustment time, load acquisition device 101 calibration time, and historical alarm count. This setting enables the alarm information to not only serve as an anomaly indication but also as a maintenance guidance function.

[0116] Finally, it should be noted that the methods and devices described in detail above are merely embodiments, and those skilled in the art can modify these embodiments in different ways as long as they do not depart from the scope of the present invention.

Claims

1. A smart monitoring system for power plant supports and hangers, characterized in that: include, A status acquisition unit (100) is set at the monitoring position (A) of the power plant piping system (200) to collect the piping system status data (B) of the power plant piping system (200). A computing unit (300) is communicatively connected to the status acquisition unit (100) and is used to receive the pipeline status data (B). The monitoring location (A) corresponds to the measuring point marker (A') in the three-dimensional refined model (400) corresponding to the power plant piping system (200); The calculation unit (300) associates the piping system status data (B) with the measuring point identifier (A'), and determines the current status parameter (C) of the power plant piping system (200) based on the piping system status data (B) associated with the measuring point identifier (A'), so as to update the piping system equilibrium equation and solve the pipe stress state (F) according to the current status parameter (C).

2. The intelligent monitoring system for power plant supports and hangers as described in claim 1, characterized in that: The power plant piping system (200) includes pipes (201) and supports (202). The piping system status data (B) includes support load data (B1), piping system displacement data (B2), and pipe temperature data (B3). The current status parameters (C) include load parameters obtained from the support load data (B1), displacement parameters obtained from the piping system displacement data (B2), and temperature parameters obtained from the pipe temperature data (B3).

3. The intelligent monitoring system for power plant supports and hangers as described in claim 2, characterized in that: The status acquisition unit (100) includes a load acquisition component (101), a displacement acquisition component (102), and a temperature data interface (103). The load acquisition device (101) is installed at the tie rod (202a) of the support (202) and is used to acquire the load data (B1) of the support. The displacement acquisition device (102) is set in relation to the pipeline (201) and is used to acquire the displacement data (B2) of the pipeline system. The temperature data interface (103) is connected to the power plant operation monitoring system and is used to obtain the pipeline temperature data (B3) of the pipeline (201).

4. The intelligent monitoring system for power plant supports and hangers as described in claim 3, characterized in that: The displacement acquisition device (102) includes a non-contact laser displacement acquisition device, which is used to acquire displacement data of the pipe (201) in the X-axis, Y-axis and Z-axis directions.

5. The intelligent monitoring system for power plant supports and hangers as described in claim 4, characterized in that: The load acquisition component (101) is prefabricated and welded to the tie rod (202a) of the support (202), and is calibrated before the support (202) is installed so that the support load data (B1) acquired by the load acquisition component (101) corresponds to the stress state of the tie rod (202a).

6. The intelligent monitoring system for power plant supports and hangers as described in claim 3 or 4, characterized in that: The three-dimensional refined model (400) includes multiple model partitions (401), and at least some of the model partitions (401) are respectively provided with a measurement point identifier (A'); The calculation unit (300) determines the current status parameters (C) of the power plant piping system (200) based on the piping system status data (B) corresponding to the measuring point identifier (A').

7. The intelligent monitoring system for power plant supports and hangers as described in claim 6, characterized in that: The status acquisition unit (100) further includes a data acquisition unit (104), which is communicatively connected to the load acquisition unit (101) and the displacement acquisition unit (102). The data acquisition unit (104) is used to upload the support load data (B1) and the pipe displacement data (B2) to the calculation unit (300), and the temperature data interface (103) is used to upload the pipe temperature data (B3) obtained from the power plant operation monitoring system to the calculation unit (300).

8. The intelligent monitoring system for power plant supports and hangers as described in claim 7, characterized in that: The calculation unit (300) establishes the relationship between the unit nodal force P and the nodal displacement D based on the current state parameter (C): ， Where K is the stiffness matrix, T is the thermal force matrix, G is the uniformly distributed load matrix, α is the linear expansion coefficient, Δt is the temperature change, and W is the weight per unit length of the element. The calculation unit (300) transforms the relationship between the unit node force P and the node displacement D of multiple model partitions (401) into a unified coordinate system to form the pipeline equilibrium equation, and solves the pipeline stress state (F).

9. The intelligent monitoring system for power plant supports and hangers as described in claim 7 or 8, characterized in that: The pipeline stress state (F) includes the partition stress state corresponding to each of the model partitions (401), and each partition stress state includes a primary stress state (F1) and a secondary stress state (F2). The calculation unit (300) compares the primary stress state (F1) and secondary stress state (F2) corresponding to each model partition (401) with the corresponding preset stress threshold, and determines the model partition (401) whose primary stress state (F1) and / or secondary stress state (F2) meet the abnormal conditions as an abnormal model partition. The calculation unit (300) outputs alarm information corresponding to the abnormal model partition.

10. A method for intelligent monitoring of power plant supports and hangers, characterized in that, Includes the following steps: The status data (B) of the power plant piping system (200) is collected by the status acquisition unit (100) at the monitoring location (A) of the power plant piping system (200). The system status data (B) is received by the computing unit (300) which is communicatively connected to the status acquisition unit (100). Determine the correspondence between the monitoring location (A) and the measuring point marker (A') in the three-dimensional refined model (400) corresponding to the power plant piping system (200); The calculation unit (300) associates the piping system status data (B) with the measuring point identifier (A'). Based on the piping system status data (B) associated with the measuring point identifier (A'), the current status parameters (C) of the power plant piping system (200) are determined. The piping system equilibrium equation is updated based on the current state parameter (C), and the stress state of each model partition (401) is obtained by solving the partition stress state, which includes the primary stress state (F1) and the secondary stress state (F2). The primary stress state (F1) and secondary stress state (F2) corresponding to each model partition (401) are compared with the corresponding preset stress thresholds, and the model partition (401) whose primary stress state (F1) and / or secondary stress state (F2) meet the abnormal conditions are determined as abnormal model partitions. The alarm information corresponding to the abnormal model partitions is output by the calculation unit (300).

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