Method and system for monitoring stress of reheat steam pipeline

Abstract

The invention discloses a reheat steam pipeline stress monitoring method and system, and the method comprises the steps: obtaining stress data messages of a plurality of positions through a stress sensor disposed on a reheat steam pipeline; setting a pipeline stress propagation model, and simulating the propagation condition of stress in the pipeline according to the stress data messages of the plurality of positions; setting a stress propagation model at the stress concentration position of the pipeline, and calculating a stress propagation index at the stress concentration position of the pipeline according to the stress data message at the stress concentration position of the pipeline; acquiring the temperature in the pipeline, setting a stress heat transfer model, and simulating the influence condition of heat conduction on the stress distribution of the pipeline in a high-temperature environment by combining the stress data messages of the plurality of positions; and uploading the propagation condition of the stress in the pipeline, the stress propagation index at the stress concentration position of the pipeline and the stress distribution influence condition of heat conduction on the pipeline in the high-temperature environment to a cloud platform so as to complete stress monitoring.

Description

Technical Field

[0001] The present invention belongs to the technical field of stress propagation monitoring, and more specifically, relates to a reheat steam pipeline stress monitoring method and system. Background Art

[0002] The reheat steam pipeline of a power plant boiler is one of the main pressure-bearing components in the boiler system. It operates under high temperature and high pressure for a long time, and the safety risk is extremely high. At present, the monitoring of hot steam pipelines in China mainly focuses on the parameters of the medium in the pipeline and the operation status, and performs real-time monitoring of steam temperature, pressure, flow, etc. There is no monitoring method for the monitoring of the pipeline equipment itself and the intrinsic safety of the pipeline equipment. It mainly relies on professionals to detect the pipeline when the furnace is shut down to find out whether there is a problem, which results in untimely and incomplete feedback on the material status. It is impossible to achieve safe monitoring of the pipeline under operation. Under long-term high temperature and high pressure operation environment, stress concentration parts such as welds of the reheat pipeline are prone to crack defects, the wall thickness of the elbow is thinned under high pressure steam scouring, the pipeline as a whole will produce creep damage, and the microstructure will cause material degradation as the operation time increases. Almost all damage directly affects the state of pipeline strain / stress. Distributed optical fiber sensing technology has the advantages of being passive, resistant to high temperature environment, and resistant to electromagnetic interference, and has great advantages in stress monitoring of reheat steam pipelines. Therefore, it is very meaningful to develop a stress monitoring system for reheat steam pipelines based on distributed power plant boilers. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes a reheat steam pipeline stress monitoring method, comprising:

[0004] Obtain stress data messages at multiple locations through stress sensors installed on the reheat steam pipe;

[0005] Setting a pipeline stress propagation model, and simulating the propagation of stress in the pipeline according to the stress data messages at the multiple locations;

[0006] A stress propagation model is set at the stress concentration point of the pipeline, and a stress propagation index at the stress concentration point of the pipeline is calculated according to the stress data message at the stress concentration point of the pipeline;

[0007] Obtain the temperature in the pipeline, set a stress heat transfer model, and combine the stress data messages of the multiple positions to simulate the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment;

[0008] The propagation of stress in the pipeline, the stress propagation index at the pipeline concentration point, and the impact of heat conduction on the stress distribution of the pipeline under high temperature environment are uploaded to the cloud platform to complete stress monitoring.

[0009] Furthermore, the stress data messages at multiple locations are parsed and encapsulated through the ring queue.

[0010] Furthermore, the pipeline stress propagation model includes:

[0011]

[0012] Among them, u(x, t) is the stress displacement field at the position x of the pipeline at time t, which represents the change of stress displacement at the position x of the pipeline with time, v(x, t) is the stress propagation velocity at the position x of the pipeline at time t, and f is the stress concentration effect index, which is used to describe the stress concentration at the cracks, welds or other defects of the pipeline. is the gradient of the stress displacement field at position x of the pipeline at time t.

[0013] Furthermore, the stress concentration effect index f includes:

[0014]

[0015] Among them, λ1 is the first adjustment factor of the stress concentration effect index, λ2 is the second adjustment factor of the stress concentration effect index, γ is the fourth adjustment factor of the stress concentration effect index, λ3 is the third adjustment factor of the stress concentration effect index, and α′ is the fifth adjustment factor of the stress concentration effect index.

[0016] Furthermore, to capture the stress propagation at cracks, welds or other defects in the pipeline, the stress propagation model at the pipeline concentration includes:

[0017]

[0018] Where T is the stress propagation index at the pipeline concentration, σ(x, t) is the stress at the position x of the pipeline at time t, γ′ is the first adjustment factor of the stress propagation index, and δ is the second adjustment factor of the stress propagation index. is the stress gradient at position x in the pipeline at time t.

[0019] Furthermore, the stress heat transfer model is used to describe the influence of heat conduction on the stress distribution of the pipeline under high temperature environment, including:

[0020]

[0021] Wherein, T′(x, t) is the temperature field at position x of the pipeline at time t, α1 is the first adjustment factor of stress distribution, α2 is the second adjustment factor of stress distribution, β1 is the third adjustment factor of stress distribution, λ′ is the fourth adjustment factor of stress distribution, and σ(x, t) is the stress at position x of the pipeline at time t.

[0022] The present invention also provides a reheat steam pipeline stress monitoring system, comprising:

[0023] A data message acquisition module is used to acquire stress data messages at multiple locations through a stress sensor installed on a reheat steam pipe;

[0024] A pipeline stress propagation model is simulated, which is used to set the pipeline stress propagation model and simulate the propagation of stress in the pipeline according to the stress data messages at the multiple positions;

[0025] Simulate the stress propagation model at the pipeline stress concentration point, which is used to set the stress propagation model at the pipeline stress concentration point, and calculate the stress propagation index at the pipeline stress concentration point according to the stress data message at the pipeline stress concentration point;

[0026] A stress distribution influence model is simulated to obtain the temperature in the pipeline, and a stress heat transfer model is set to simulate the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment by combining the stress data messages of the multiple positions;

[0027] The monitoring module is used to upload the propagation of stress in the pipeline, the stress propagation index at the pipeline concentration point, and the influence of heat conduction on the stress distribution of the pipeline in a high-temperature environment to the cloud platform to complete stress monitoring.

[0028] Furthermore, the stress data messages at multiple locations are parsed and encapsulated through the ring queue.

[0029] Furthermore, the pipeline stress propagation model includes:

[0030]

[0031] Among them, u(x, t) is the stress displacement field at the position x of the pipeline at time t, which represents the change of stress displacement at the position x of the pipeline with time, v(x, t) is the stress propagation velocity at the position x of the pipeline at time t, and f is the stress concentration effect index, which is used to describe the stress concentration at the cracks, welds or other defects of the pipeline. is the gradient of the stress displacement field at position x of the pipeline at time t.

[0032] Furthermore, the stress concentration effect index f includes:

[0033]

[0034] Among them, λ1 is the first adjustment factor of the stress concentration effect index, λ2 is the second adjustment factor of the stress concentration effect index, γ is the fourth adjustment factor of the stress concentration effect index, λ3 is the third adjustment factor of the stress concentration effect index, and α′ is the fifth adjustment factor of the stress concentration effect index.

[0035] In general, the above technical solution conceived by the present invention has the following beneficial effects compared with the prior art:

[0036] The present invention realizes strain / stress monitoring of the reheat steam pipeline, making up for the defects of existing monitoring. Through this method, managers can be reminded of the safety status of the reheat steam pipeline, reduce unnecessary shutdown inspections, and reduce shutdown costs. Predicting the safety status trend of the main reheat steam pipeline provides a scientific basis for managers to make scientific decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flow chart of the method of embodiment 1 of the present invention;

[0038] Figure 2 is a structural diagram of a system in Embodiment 2 of the present invention;

[0039] Figure 3 This is the on-site layout diagram of the distributed stress optical fiber according to Example 1 of the present invention. DETAILED DESCRIPTION

[0040] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0041] The method provided by the present invention can be implemented in the following terminal environment, and the terminal may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method described in the following embodiment.

[0042] The processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts in the entire terminal, and executes various functions of the terminal and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and calling data stored in the storage medium.

[0043] The storage medium may include a random access memory (RAM) or a read-only memory (ROM). The storage medium may be used to store instructions, programs, codes, code sets or instructions.

[0044] The display screen is used to display the user interface of each application.

[0045] In addition, those skilled in the art can understand that the structure of the above terminal does not constitute a limitation on the terminal, and the terminal may include more or fewer components, or combine certain components, or arrange the components differently. For example, the terminal also includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, and a power supply, which will not be described in detail here.

[0046] Example 1

[0047] like Figure 1 As shown, an embodiment of the present invention provides a reheat steam pipeline stress monitoring method, comprising:

[0048] Step 101, obtaining stress data messages at multiple locations through a stress sensor installed on a reheat steam pipeline;

[0049] The reheat steam pipe stress monitoring system consists of three layers:

[0050] The bottom layer is the perception layer: the perception object of the perception layer is the boiler reheat steam pipe, and the internal medium is high-temperature and high-pressure steam. Strain / stress optical fibers are arranged at the elbows, elbow welds and straight pipe sections of the reheat pipe to form measurement points to convert the strain physical state parameters of the pipe into optical signals. Through signal demodulation, the perceived optical signals are converted into formatted magnitudes corresponding to the strain physical quantities to become signal frames that can be used for data transmission.

[0051] The second layer is the demodulation layer: it collects and processes the perception signals from the bottom layer. The main function of this layer is to coordinate data collection and data transmission, and use the ring queue to coordinate the communication processor of this layer to complete the analysis of the upper layer data message and the encapsulation of the data message of this layer.

[0052] The third layer of the system is the top layer: this layer uses a cloud platform. The benefits of establishing a system based on a cloud platform are mainly to reduce the physical cable connection between the equipment and the release system on site, making on-site construction and maintenance very convenient. The equipment's trouble-free time is improved. Cloud-based remote application system management, configuration, diagnosis, backup, update, and data sharing are more convenient.

[0053] like Figure 3 As shown, the optical fiber is wrapped around the elbow and the elbow weld, and the straight pipe section is wrapped

[0054] Specifically, the stress data messages at multiple locations are parsed and encapsulated through the ring queue.

[0055] Step 102, setting a pipeline stress propagation model, and simulating the propagation of stress in the pipeline according to the stress data messages at the multiple positions;

[0056] Specifically, the pipeline stress propagation model includes:

[0057]

[0058] Among them, u(x, t) is the stress displacement field at the position x of the pipeline at time t, which represents the change of stress displacement at the position x of the pipeline with time, v(x, t) is the stress propagation velocity at the position x of the pipeline at time t, and f is the stress concentration effect index, which is used to describe the stress concentration at the cracks, welds or other defects of the pipeline. is the gradient of the stress displacement field at position x of the pipeline at time t.

[0059] Specifically, the stress concentration effect index f includes:

[0060]

[0061] Among them, λ1 is the first adjustment factor of the stress concentration effect index, λ2 is the second adjustment factor of the stress concentration effect index, γ is the fourth adjustment factor of the stress concentration effect index, λ3 is the third adjustment factor of the stress concentration effect index, and α′ is the fifth adjustment factor of the stress concentration effect index.

[0062] Step 103, setting a stress propagation model at the pipeline stress concentration point, and calculating a stress propagation index at the pipeline stress concentration point according to the stress data message at the pipeline stress concentration point;

[0063] Specifically, it is used to capture the stress propagation at cracks, welds or other defects in the pipeline. The stress propagation model at the pipeline concentration includes:

[0064]

[0065] Where T is the stress propagation index at the pipeline concentration, σ(x, t) is the stress at the position x of the pipeline at time t, γ′ is the first adjustment factor of the stress propagation index, and δ is the second adjustment factor of the stress propagation index. is the stress gradient at position x in the pipeline at time t.

[0066] Step 104, obtaining the temperature in the pipeline, setting a stress heat transfer model, combining the stress data messages of the multiple positions, and simulating the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment;

[0067] Specifically, the stress heat transfer model is used to describe the influence of heat conduction on the stress distribution of the pipeline under high temperature environment, including:

[0068]

[0069] Wherein, T′(x, t) is the temperature field at position x of the pipeline at time t, α1 is the first adjustment factor of stress distribution, α2 is the second adjustment factor of stress distribution, β1 is the third adjustment factor of stress distribution, λ′ is the fourth adjustment factor of stress distribution, and σ(x, t) is the stress at position x of the pipeline at time t.

[0070] Step 105 , uploading the propagation of stress in the pipeline, the stress propagation index at the concentrated point of the pipeline, and the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment to the cloud platform to complete stress monitoring.

[0071] Example 2

[0072] like Figure 2 As shown, an embodiment of the present invention further provides a reheat steam pipeline stress monitoring system, comprising:

[0073] A data message acquisition module is used to acquire stress data messages at multiple locations through a stress sensor installed on a reheat steam pipe;

[0074] Specifically, the stress data messages at multiple locations are parsed and encapsulated through the ring queue.

[0075] A pipeline stress propagation model is simulated, which is used to set the pipeline stress propagation model and simulate the propagation of stress in the pipeline according to the stress data messages at the multiple positions;

[0076] Specifically, the pipeline stress propagation model includes:

[0077]

[0078] Among them, u(x, t) is the stress displacement field at the position x of the pipeline at time t, which represents the change of stress displacement at the position x of the pipeline with time, v(x, t) is the stress propagation velocity at the position x of the pipeline at time t, and f is the stress concentration effect index, which is used to describe the stress concentration at the cracks, welds or other defects of the pipeline. is the gradient of the stress displacement field at position x of the pipeline at time t.

[0079] Specifically, the stress concentration effect index f includes:

[0080]

[0081] Among them, λ1 is the first adjustment factor of the stress concentration effect index, λ2 is the second adjustment factor of the stress concentration effect index, γ is the fourth adjustment factor of the stress concentration effect index, λ3 is the third adjustment factor of the stress concentration effect index, and α′ is the fifth adjustment factor of the stress concentration effect index.

[0082] Simulate the stress propagation model at the pipeline stress concentration point, which is used to set the stress propagation model at the pipeline stress concentration point, and calculate the stress propagation index at the pipeline stress concentration point according to the stress data message at the pipeline stress concentration point;

[0083] Specifically, it is used to capture the stress propagation at cracks, welds or other defects in the pipeline. The stress propagation model at the pipeline concentration includes:

[0084]

[0085] Where T is the stress propagation index at the pipeline concentration, σ(x, t) is the stress at the position x of the pipeline at time t, γ′ is the first adjustment factor of the stress propagation index, and δ is the second adjustment factor of the stress propagation index. is the stress gradient at position x in the pipeline at time t.

[0086] A stress distribution influence model is simulated to obtain the temperature in the pipeline, and a stress heat transfer model is set to simulate the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment by combining the stress data messages of the multiple positions;

[0087] Specifically, the stress heat transfer model is used to describe the influence of heat conduction on the stress distribution of the pipeline under high temperature environment, including:

[0088]

[0089] Wherein, T′(x, t) is the temperature field at position x of the pipeline at time t, α1 is the first adjustment factor of stress distribution, α2 is the second adjustment factor of stress distribution, β1 is the third adjustment factor of stress distribution, λ′ is the fourth adjustment factor of stress distribution, and σ(x, t) is the stress at position x of the pipeline at time t.

[0090] The monitoring module is used to upload the propagation of stress in the pipeline, the stress propagation index at the pipeline concentration point, and the influence of heat conduction on the stress distribution of the pipeline in a high-temperature environment to the cloud platform to complete stress monitoring.

[0091] Example 3

[0092] The embodiment of the present invention further provides a storage medium storing a plurality of instructions, wherein the instructions are used to implement the reheat steam pipeline stress monitoring method.

[0093] Optionally, in this embodiment, the above storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0094] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps: Step 101, obtaining stress data messages at multiple locations through a stress sensor installed on a reheat steam pipe;

[0095] Specifically, the stress data messages at multiple locations are parsed and encapsulated through the ring queue.

[0096] Step 102, setting a pipeline stress propagation model, and simulating the propagation of stress in the pipeline according to the stress data messages at the multiple positions;

[0097] Specifically, the pipeline stress propagation model includes:

[0098]

[0099] Among them, u(x, t) is the stress displacement field at the position x of the pipeline at time t, which represents the change of stress displacement at the position x of the pipeline with time, v(x, t) is the stress propagation velocity at the position x of the pipeline at time t, and f is the stress concentration effect index, which is used to describe the stress concentration at the cracks, welds or other defects of the pipeline. is the gradient of the stress displacement field at position x of the pipeline at time t.

[0100] Specifically, the stress concentration effect index f includes:

[0101]

[0102] Among them, λ1 is the first adjustment factor of the stress concentration effect index, λ2 is the second adjustment factor of the stress concentration effect index, γ is the fourth adjustment factor of the stress concentration effect index, λ3 is the third adjustment factor of the stress concentration effect index, and α′ is the fifth adjustment factor of the stress concentration effect index.

[0103] Step 103, setting a stress propagation model at the pipeline concentration point, and calculating a stress propagation index at the pipeline concentration point according to the stress data message at the pipeline concentration point;

[0104] Specifically, it is used to capture the stress propagation at cracks, welds or other defects in the pipeline. The stress propagation model at the pipeline concentration includes:

[0105]

[0106] Where T is the stress propagation index at the pipeline concentration, σ(x, t) is the stress at the position x of the pipeline at time t, γ′ is the first adjustment factor of the stress propagation index, and δ is the second adjustment factor of the stress propagation index. is the stress gradient at position x in the pipeline at time t.

[0107] Step 104, obtaining the temperature in the pipeline, setting a stress heat transfer model, combining the stress data messages of the multiple positions, and simulating the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment;

[0108] Specifically, the stress heat transfer model is used to describe the influence of heat conduction on the stress distribution of the pipeline under high temperature environment, including:

[0109]

[0110] Wherein, T′(x, t) is the temperature field at position x of the pipeline at time t, α1 is the first adjustment factor of stress distribution, α2 is the second adjustment factor of stress distribution, β1 is the third adjustment factor of stress distribution, λ′ is the fourth adjustment factor of stress distribution, and σ(x, t) is the stress at position x of the pipeline at time t.

[0111] Step 105 , uploading the propagation of stress in the pipeline, the stress propagation index at the concentrated point of the pipeline, and the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment to the cloud platform to complete stress monitoring.

[0112] Example 4

[0113] An embodiment of the present invention also proposes an electronic device, including a processor and a storage medium connected to the processor, wherein the storage medium stores multiple instructions, and the instructions can be loaded and executed by the processor so that the processor can execute the reheat steam pipeline stress monitoring method.

[0114] Specifically, the electronic device of this embodiment may be a computer terminal, and the computer terminal may include: one or more processors, and a storage medium.

[0115] Among them, the storage medium can be used to store software programs and modules, such as a reheat steam pipeline stress monitoring method in an embodiment of the present invention, and the corresponding program instructions / modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the storage medium, that is, realizing the above-mentioned reheat steam pipeline stress monitoring method. The storage medium may include high-speed random storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely arranged relative to the processor, and these remote storage media may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0116] The processor may call the information and application program stored in the storage medium through the transmission system to perform the following steps: Step 101, obtaining stress data messages at multiple locations through a stress sensor installed on a reheat steam pipeline;

[0117] Specifically, the stress data messages at multiple locations are parsed and encapsulated through the ring queue.

[0118] Step 102, setting a pipeline stress propagation model, and simulating the propagation of stress in the pipeline according to the stress data messages at the multiple positions;

[0119] Specifically, the pipeline stress propagation model includes:

[0120]

[0121] Among them, u(x, t) is the stress displacement field at the position x of the pipeline at time t, which represents the change of stress displacement at the position x of the pipeline with time, v(x, t) is the stress propagation velocity at the position x of the pipeline at time t, and f is the stress concentration effect index, which is used to describe the stress concentration at the cracks, welds or other defects of the pipeline. is the gradient of the stress displacement field at position x of the pipeline at time t.

[0122] Specifically, the stress concentration effect index f includes:

[0123]

[0124] Among them, λ1 is the first adjustment factor of the stress concentration effect index, λ2 is the second adjustment factor of the stress concentration effect index, γ is the fourth adjustment factor of the stress concentration effect index, λ3 is the third adjustment factor of the stress concentration effect index, and α′ is the fifth adjustment factor of the stress concentration effect index.

[0125] Step 103, setting a stress propagation model at the pipeline concentration point, and calculating a stress propagation index at the pipeline concentration point according to the stress data message at the pipeline concentration point;

[0126] Specifically, it is used to capture the stress propagation at cracks, welds or other defects in the pipeline. The stress propagation model at the pipeline concentration includes:

[0127]

[0128] Where T is the stress propagation index at the pipeline concentration, σ(x, t) is the stress at the position x of the pipeline at time t, γ′ is the first adjustment factor of the stress propagation index, and δ is the second adjustment factor of the stress propagation index. is the stress gradient at position x in the pipeline at time t.

[0129] Step 104, obtaining the temperature in the pipeline, setting a stress heat transfer model, combining the stress data messages of the multiple positions, and simulating the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment;

[0130] Specifically, the stress heat transfer model is used to describe the influence of heat conduction on the stress distribution of the pipeline under high temperature environment, including:

[0131]

[0132] Wherein, T′(x, t) is the temperature field at position x of the pipeline at time t, α1 is the first adjustment factor of stress distribution, α2 is the second adjustment factor of stress distribution, β1 is the third adjustment factor of stress distribution, λ′ is the fourth adjustment factor of stress distribution, and σ(x, t) is the stress at position x of the pipeline at time t.

[0133] Step 105 , uploading the propagation of stress in the pipeline, the stress propagation index at the concentrated point of the pipeline, and the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment to the cloud platform to complete stress monitoring.

[0134] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0135] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0136] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0137] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0138] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0139] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only storage medium (ROM, Read-Only Memory), random access storage medium (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0140] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A reheat steam pipeline stress monitoring method, characterized in that: include: Obtain stress data messages at multiple locations through stress sensors installed on the reheat steam pipe; Setting a pipeline stress propagation model, and simulating the propagation of stress in the pipeline according to the stress data messages at the multiple locations; A stress propagation model is set at the stress concentration point of the pipeline, and a stress propagation index at the stress concentration point of the pipeline is calculated according to the stress data message at the stress concentration point of the pipeline; Obtain the temperature in the pipeline, set a stress heat transfer model, and combine the stress data messages of the multiple positions to simulate the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment; The propagation of stress in the pipeline, the stress propagation index at the pipeline concentration point, and the impact of heat conduction on the stress distribution of the pipeline under high temperature environment are uploaded to the cloud platform to complete stress monitoring.

2. A reheat steam pipeline stress monitoring method according to claim 1, characterized in that: The stress data messages at multiple locations are parsed and encapsulated through a circular queue.

3. A reheat steam pipeline stress monitoring method according to claim 2, characterized in that: The pipeline stress propagation model includes: Among them, u(x, t) is the stress displacement field at the position x of the pipeline at time t, which represents the change of stress displacement at the position x of the pipeline with time, v(x, t) is the stress propagation velocity at the position x of the pipeline at time t, and f is the stress concentration effect index, which is used to describe the stress concentration at the cracks, welds or other defects of the pipeline. is the gradient of the stress displacement field at position x of the pipeline at time t.

4. A reheat steam pipeline stress monitoring method according to claim 3, characterized in that: The stress concentration effect index f includes: Among them, λ1 is the first adjustment factor of the stress concentration effect index, λ2 is the second adjustment factor of the stress concentration effect index, γ is the fourth adjustment factor of the stress concentration effect index, λ3 is the third adjustment factor of the stress concentration effect index, and α′ is the fifth adjustment factor of the stress concentration effect index.

5. A reheat steam pipeline stress monitoring method according to claim 2, characterized in that: Used to capture the stress propagation at cracks, welds or other defects in the pipeline. The stress propagation model at the stress concentration of the pipeline includes: Where T is the stress propagation index at the stress concentration point of the pipeline, σ(x, t) is the stress at position x of the pipeline at time t, γ′ is the first adjustment factor of the stress propagation index, and δ is the second adjustment factor of the stress propagation index. is the stress gradient at position x in the pipeline at time t.

6. A reheat steam pipeline stress monitoring method according to claim 2, characterized in that: The stress heat transfer model is used to describe the influence of heat conduction on the stress distribution of the pipeline under high temperature environment, including: Wherein, T′(x, t) is the temperature field at position x of the pipeline at time t, α1 is the first adjustment factor of stress distribution, α2 is the second adjustment factor of stress distribution, β1 is the third adjustment factor of stress distribution, λ′ is the fourth adjustment factor of stress distribution, and σ(x, t) is the stress at position x of the pipeline at time t.

7. A reheat steam pipeline stress monitoring system, characterized in that: include: A data message acquisition module is used to acquire stress data messages at multiple locations through a stress sensor installed on a reheat steam pipe; A pipeline stress propagation model is simulated, which is used to set the pipeline stress propagation model and simulate the propagation of stress in the pipeline according to the stress data messages at the multiple positions; Simulate the stress propagation model at the pipeline stress concentration point, which is used to set the stress propagation model at the pipeline stress concentration point, and calculate the stress propagation index at the pipeline stress concentration point according to the stress data message at the pipeline stress concentration point; A stress distribution influence model is simulated to obtain the temperature in the pipeline, and a stress heat transfer model is set to simulate the influence of heat conduction on the stress distribution of the pipeline in a high temperature environment by combining the stress data messages of the multiple positions; The monitoring module is used to upload the propagation of stress in the pipeline, the stress propagation index at the pipeline concentration point, and the influence of heat conduction on the stress distribution of the pipeline in a high-temperature environment to the cloud platform to complete stress monitoring.

8. A reheat steam pipeline stress monitoring system according to claim 7, characterized in that: The stress data messages at multiple locations are parsed and encapsulated through a circular queue.

9. A reheat steam pipeline stress monitoring system according to claim 8, characterized in that: The pipeline stress propagation model includes: Among them, u(x, t) is the stress displacement field at the position x of the pipeline at time t, which represents the change of stress displacement at the position x of the pipeline with time, v(x, t) is the stress propagation velocity at the position x of the pipeline at time t, and f is the stress concentration effect index, which is used to describe the stress concentration at the cracks, welds or other defects of the pipeline. is the gradient of the stress displacement field at position x of the pipeline at time t.

10. A reheat steam pipeline stress monitoring system according to claim 9, characterized in that: The stress concentration effect index f includes: Among them, λ1 is the first adjustment factor of the stress concentration effect index, λ2 is the second adjustment factor of the stress concentration effect index, γ is the fourth adjustment factor of the stress concentration effect index, λ3 is the third adjustment factor of the stress concentration effect index, and α′ is the fifth adjustment factor of the stress concentration effect index.

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