A method and system for eliminating invalid data for stress monitoring

Abstract

The present invention provides a method and system for eliminating invalid data for stress monitoring, which includes obtaining a first sensor layout scheme, obtaining collected data of N sensors, performing a first operation on the collected data, obtaining a first error set based on a Euclidean approximate solution and a true solution, and matching the first sensor; eliminating the first collected data corresponding to the first sensor from the collected data to obtain first eliminated data; until the number of the first eliminated data meets a first preset requirement and / or the maximum error meets a second preset requirement, then the steps are repeated to obtain a first valid data set; obtaining a maximum stress value; and eliminating data from the first valid data set based on the maximum stress value to obtain a second valid data set. This solves the technical problem that there is a lack of a method in the prior art that can effectively eliminate invalid data in stress monitoring data obtained by multiple sensors of a single pipeline section, resulting in inaccurate and unreliable monitoring data.

Description

Technical Field

[0001] The present invention relates to the technical field related to stress safety monitoring of long-distance oil and gas pipelines, and in particular to a method and system for eliminating invalid data for stress monitoring. Background Art

[0002] Long-distance oil and gas pipelines often pass through geological disaster areas such as landslides, mining, and frozen soil areas. The soil will produce a large stress superposition on the pipeline and the degree of change is unpredictable. It is often necessary to install strain sensors to monitor the pipeline stress for a long time. Based on high stability and reliability, vibrating string sensors are often used to monitor stress in engineering. However, even so, there are several possibilities for generating invalid data: (1) The sensor is affected by environmental vibration, causing a large deviation in the acquisition frequency; (2) Instability caused by factors such as wear and corrosion. After the sensor on the steel pipeline is installed by welding, long-term use is prone to base corrosion and cause data anomalies. (3) The installation regulations require that the sensors are located in the same section, but it is difficult to measure the center axis during the actual installation process, resulting in the sensors not being on the same section. As a result, there is a correlation between the values ​​of each sensor, but it is not completely correlated. In the above cases, it is necessary to eliminate the abnormal data.

[0003] However, the inventors of this application found that the above technology has at least the following technical problems in the process of implementing the technical solution of the invention in the embodiment of this application:

[0004] The existing technology lacks a method that can effectively eliminate invalid data in the stress monitoring data obtained by multiple sensors in a single pipeline section, resulting in a technical problem that the monitoring data is not accurate and reliable enough. Summary of the invention

[0005] The embodiments of the present application provide a method and system for eliminating invalid data in stress monitoring, thereby solving the technical problem that the prior art lacks a method for effectively eliminating invalid data in stress monitoring data acquired by multiple sensors in a single pipe section, resulting in inaccurate and unreliable monitoring data. By analyzing and processing the monitoring data from each sensor on the same section, the stress data monitored by aging or abnormal sensors can be accurately identified and eliminated, thereby achieving the technical effect of making the monitoring data more accurate and reliable.

[0006] In view of the above problems, an embodiment of the present application provides a method and system for eliminating invalid data for stress monitoring.

[0007] In a first aspect, an embodiment of the present application provides a method for eliminating invalid data for stress monitoring, the method comprising: S100, obtaining a first sensor layout scheme, and performing N sensor layouts according to the first sensor layout scheme to obtain collected data of the N sensors, wherein N is a positive integer greater than 4; S200, performing a first operation on the collected data to obtain a Euclidean approximate solution; S300, obtaining a first error set according to the Euclidean approximate solution and a true solution, and matching a first sensor according to the first error set; S400, eliminating the first collected data corresponding to the first sensor from the collected data to obtain first eliminated data; S500, repeating steps S200-S400 according to the first eliminated data until the number of the first eliminated data meets a first preset requirement and / or the maximum error meets a second preset requirement, then ending the step repetition to obtain a first valid data set; S600, performing a second operation on the first valid data set to obtain a maximum stress value; S700, eliminating data from the first valid data set according to the maximum stress value to obtain a second valid data set.

[0008] On the other hand, an embodiment of the present application provides a system for eliminating invalid data for stress monitoring, the system comprising: a first obtaining unit, the first obtaining unit being used to obtain a first sensor layout scheme, and N sensors are deployed according to the first sensor layout scheme to obtain collected data of the N sensors, wherein N is a positive integer greater than 4; a second obtaining unit, the second obtaining unit being used to perform a first operation on the collected data to obtain a Euclidean approximate solution; a third obtaining unit, the third obtaining unit being used to obtain a first error set according to the Euclidean approximate solution and a true solution, and matching a first sensor according to the first error set; a fourth obtaining unit, the fourth obtaining unit being used to match the first sensor The first collected data corresponding to the sensor is eliminated from the collected data to obtain first eliminated data; a first repeating unit, the first repeating unit is used to repeat the second obtaining unit to the fourth obtaining unit according to the first eliminated data, until the number of the first eliminated data meets the first preset requirement and / or the maximum error meets the second preset requirement, then the step repetition is ended to obtain a first valid data set; a fifth obtaining unit, the fifth obtaining unit is used to perform a second operation processing according to the first valid data set to obtain a maximum stress value; a sixth obtaining unit, the sixth obtaining unit is used to perform data elimination on the first valid data set according to the maximum stress value to obtain a second valid data set.

[0009] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods described in the first aspect when executing the program.

[0010] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0011] Due to the adoption of the first sensor layout scheme, N sensors are laid out according to the first sensor layout scheme to obtain the collected data of the N sensors, wherein N is a positive integer greater than 4; the collected data is subjected to a first operation process to obtain a Euclidean approximate solution; a first error set is obtained according to the Euclidean approximate solution and the true solution, and the first sensor is matched according to the first error set; the first collected data corresponding to the first sensor is removed from the collected data to obtain the first removed data; according to the first removed data, until the number of the first removed data meets the first preset requirement and / or the maximum error meets the second preset requirement, the steps are repeated to obtain the first valid data set; the second operation process is performed according to the first valid data set to obtain the maximum stress value; the first valid data set is subjected to data removal according to the maximum stress value to obtain the second valid data set. By analyzing and processing the monitoring data of each sensor on the same cross section, the aging or abnormal sensor values ​​are removed to make the monitoring data more accurate and reliable.

[0012] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic flow chart of a method for eliminating invalid data for stress monitoring is provided for an embodiment of the present application;

[0014] Figure 2 A schematic diagram of the cross-sectional layout of N sensors for a method of eliminating invalid data for stress monitoring;

[0015] Figure 3 A schematic diagram of a process for obtaining the Euclidean approximate solution of a method for eliminating invalid data for stress monitoring;

[0016] Figure 4 A schematic diagram of a flow chart of obtaining a first sensor layout scheme for a method for eliminating invalid data for stress monitoring;

[0017] Figure 5 A schematic diagram of a process for obtaining a refinement of a Euclidean approximate solution for a method for eliminating invalid data for stress monitoring;

[0018] Figure 6 A schematic diagram of a process of obtaining a first sensor in a method for eliminating invalid data for stress monitoring;

[0019] Figure 7 A schematic diagram of a flow chart of obtaining a second conversion equation for a method of eliminating invalid data for stress monitoring;

[0020] Figure 8 A schematic diagram of a process for obtaining the maximum stress value in a method for eliminating invalid data for stress monitoring;

[0021] Fig. 9 A schematic diagram of the structure of a system for eliminating invalid data for stress monitoring;

[0022] Fig.10 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application.

[0023] Explanation of the figure marks: first obtaining unit 11, second obtaining unit 12, third obtaining unit 13, fourth obtaining unit 14, first repeating unit 15, fifth obtaining unit 16, sixth obtaining unit 17, electronic device 300, memory 301, processor 302, communication interface 303, bus architecture 304. DETAILED DESCRIPTION

[0024] The embodiment of the present application provides a method for eliminating invalid data for stress monitoring, thereby solving the technical problem that the prior art lacks a method for effectively eliminating invalid data in stress monitoring data acquired by multiple sensors in a single pipe cross section, resulting in inaccurate and unreliable monitoring data. By analyzing and processing the monitoring data from each sensor on the same cross section, the stress data monitored by aging or abnormal sensors can be accurately identified and eliminated, thereby achieving the technical effect of making the monitoring data more accurate and reliable.

[0025] Application Overview

[0026] For long-distance oil and gas pipelines, they often pass through some geological disaster areas such as landslides, mining, and frozen soil areas. The soil will produce a large stress superposition on the pipeline and the degree of change is unpredictable. It is often necessary to install strain sensors to monitor the pipeline stress for a long time. Through scientific research, it is found that there are many mechanical and mathematical assumptions in the derivation process of the traditional three-point calculation formula, but these conditions are difficult to meet in the actual application process. Therefore, it is difficult to meet the needs of actual pipe section monitoring using the traditional three-sensor monitoring method. Studies have shown that four or more sensors are required to more accurately reflect the actual maximum stress of the pipe section. The increase in sensors will inevitably increase the difficulty of installation and increase the possibility of data anomalies. Therefore, it is necessary to eliminate invalid data in the monitoring data.

[0027] In response to the above technical problems, the overall idea of ​​the technical solution provided by this application is as follows:

[0028] The embodiment of the present application provides a method for eliminating invalid data for stress monitoring, the method comprising: S100, obtaining a first sensor layout scheme, and performing N sensor layouts according to the first sensor layout scheme to obtain collected data of the N sensors, wherein N is a positive integer greater than 4; S200, performing a first operation process on the collected data to obtain a Euclidean approximate solution; S300, obtaining a first error set according to the Euclidean approximate solution and a true solution, and matching a first sensor according to the first error set; S400, eliminating the first collected data corresponding to the first sensor from the collected data to obtain first eliminated data; S500, repeating steps S200-S400 according to the first eliminated data until the number of the first eliminated data meets a first preset requirement and / or the maximum error meets a second preset requirement, then ending the step repetition to obtain a first valid data set; S600, performing a second operation process on the first valid data set to obtain a maximum stress value; S700, eliminating data from the first valid data set according to the maximum stress value to obtain a second valid data set.

[0029] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically described below in conjunction with the drawings in the specification.

[0030] Embodiment 1

[0031] like Figure 1 As shown, an embodiment of the present application provides a method for eliminating invalid data for stress monitoring, the method comprising:

[0032] Step S100: obtaining a first sensor deployment scheme, deploying N sensors according to the first sensor deployment scheme, and obtaining data collected by the N sensors, wherein N is a positive integer greater than 4;

[0033] Specifically, the oil and gas pipelines in operation are often subjected to external loads, which causes the axial stress to increase. After the location is checked by other detection technologies, the method of installing sensors is generally used to perform long-term stress safety monitoring. The first sensor layout scheme is a cross-sectional location layout scheme at the same check location. In order to make the judgment of invalid data in stress monitoring more accurate, N in N sensors is a positive integer greater than 4, and the N sensors are arranged on the risk section of the pipeline, and the installation direction is as parallel to the axial direction as possible, such as Figure 2 The figure shows the layout result of N sensors. The N sensors are labeled and the collected data of the N sensors are obtained. The layout and identification of the N sensors provide support for the subsequent accurate stress monitoring result analysis and invalid data elimination.

[0034] Step S200: performing a first operation on the collected data to obtain a Euclidean approximate solution;

[0035] Further, such as Figure 3 As shown, step S200 of the embodiment of the present application also includes:

[0036] Step S210: constructing a Cartesian coordinate system, and obtaining position coordinates (x, y) of the N sensors according to the Cartesian coordinate system;

[0037] Step S220: Obtain the first equilibrium equation: lx+my+nz=1;

[0038] Step S230: obtaining a first calculation result according to the collected data of the N sensors and the first balance equation, wherein l, m, n are unknown coefficients of the balance equation, z is the axial strain magnitude of each point on the circumference of the pipeline, x is the horizontal coordinate position of each point on the circumference of the pipeline, and y is the vertical coordinate position of each point on the circumference of the pipeline;

[0039] Step S240: obtaining the Euclidean approximate solution according to the first calculation result.

[0040] Specifically, the N sensors are labeled according to predetermined numbers. For example, the N sensors are labeled 1-N in a clockwise direction. The inner diameter r of the oil and gas pipeline at the measurement position of the N sensors is obtained, and a Cartesian coordinate system is constructed at the position where the N sensors are installed on the oil and gas pipeline. The Cartesian coordinate system is a general term for a rectangular coordinate system and an oblique coordinate system. It forms a plane affine coordinate system through two axes intersecting at the origin. According to the constructed Cartesian coordinate system, the position coordinate information of each sensor in the N sensors is obtained, represented by (x, y), where the angle between each sensor and the x-axis of the Cartesian coordinate system is θ i The first equilibrium equation is the equilibrium equation of the current measurement section, lx+my+nz=1; wherein l, m, n are the unknown coefficients of the equilibrium equation, z is the axial strain magnitude of each point on the circumference of the pipeline, x is the horizontal coordinate position of each point on the circumference of the pipeline, and y is the vertical coordinate position of each point on the circumference of the pipeline.

[0041] Furthermore, the value corresponding to the strain data collected by N sensors is expressed as ε i (i=1,2,....,N) means that the position data and collected strain data of N sensors are substituted into the first equilibrium equation to obtain That is, the first calculation result. The Euclidean distance error of each sensor is obtained by searching the first calculation result for the solution with the shortest Euclidean distance as the solution with the highest similarity.

[0042] Step S300: obtaining a first error set according to the Euclidean approximate solution and the true solution, and matching a first sensor according to the first error set;

[0043] Step S400: removing the first collected data corresponding to the first sensor from the collected data to obtain first removed data;

[0044] Specifically, the first calculation result is rewritten into an equation system as AX=b, where X = [lmn] T , According to the rewritten equation AX=b, the error calculation of the approximate solution and the true solution is performed to obtain a set of error calculations of the N sensors, namely the first error set. The first error set is sorted in order according to the size of the error, and the first sensor with the largest error between the approximate solution and the true solution is obtained. The stress data measured by the first sensor is removed from the collected data, and the first removed data is obtained according to the removal result. By calculating the first error set, the corresponding sensors are matched by comparing the error sizes in the first error set, and preliminary invalid data of the stress monitoring data is eliminated according to the matching results, which lays a solid foundation for further invalid data analysis and elimination.

[0045] Step S500: Repeating steps S200-S400 according to the first eliminated data until the number of the first eliminated data meets the first preset requirement and / or the maximum error meets the second preset requirement, then ending the step repetition to obtain a first valid data set;

[0046] Specifically, after the stress data collected by the first sensor is eliminated, the first eliminated data is obtained by eliminating the stress data collected by the first sensor from the collected data, and the eliminated data is subjected to a first operation to obtain a Euclidean approximate solution. A second error set is obtained according to the Euclidean approximate solution and the true solution, and the second error set is sorted in error order to obtain a second sensor with the largest error in the second error set, and the collected data of the second sensor is eliminated from the first eliminated data to obtain second eliminated data, and the cycle is repeated continuously until the number of the first eliminated data meets the first preset requirement and / or the maximum error meets the second preset requirement, then the step is repeated, wherein the first preset requirement refers to the first eliminated data being 3 groups, and the second preset requirement refers to r k-1 ≥r k , where r k-1 is the maximum error in the remaining sensor after removing invalid data once, r k is the maximum error in the sensor before invalid data is eliminated. When the number of the first eliminated data meets the first preset requirement and / or the maximum error meets the second preset requirement, the step is repeated to obtain a first valid data set based on the collected data of the eliminated error data.

[0047] Step S600: performing a second operation process according to the first valid data set to obtain a maximum stress value;

[0048] Step S700: Eliminate data from the first valid data set according to the maximum stress value to obtain a second valid data set.

[0049] Specifically, the first effective data set is substituted into the first balance equation to obtain a balance matrix consisting of k sensors, as follows:

[0050] After rewriting the equilibrium matrix, it is transformed into solving the following equation: According to the equation, the first equilibrium equation and the circular section equation, the maximum stress value is obtained. Based on the maximum stress value, the data of the first valid data set is eliminated, and the stress data exceeding the maximum stress value in the first valid data set is eliminated, and the second valid data set is formed according to the eliminated data. By analyzing and processing the monitoring data of each sensor on the same cross section, the stress data of the aging or abnormal sensor monitoring is accurately identified and eliminated, so that the monitoring data is more accurate and reliable.

[0051] Further, such as Figure 4 As shown, step S100 in the embodiment of the present application also includes:

[0052] Step S110: obtaining a first position distribution requirement, and obtaining a first position layout plan according to the first position distribution requirement;

[0053] Step S120: obtaining a first installation direction layout requirement, and obtaining a first direction layout solution according to the first installation direction layout requirement;

[0054] Step S130: Obtain the first sensor layout plan according to the first position layout plan and the first direction layout plan.

[0055] Specifically, the first position distribution requirement is a predetermined requirement for the position layout of N sensors in the oil and gas pipeline, and the first position distribution requirement includes a position requirement that the center positions of the N sensors are located on the same cross section as much as possible, and also includes the distribution of the circumferential positions of the N sensors in the same cross section of the oil and gas pipeline. Generally speaking, there should be at least one sensor in each of the up, down, left, and right directions of the cross section of the oil and gas pipeline. According to the number of sensors, based on the first position layout requirement, a first position layout plan is obtained.

[0056] Specifically, the first installation direction layout requirement refers to the installation direction of the N sensors, and the first installation layout requirement is that the installation direction of the N sensors should be as parallel as possible to the axial direction of the oil and gas pipeline. Based on the first installation direction layout requirement, the first direction layout scheme of the N sensors is obtained. Based on the first position layout scheme and the first direction layout scheme, the first sensor layout scheme is obtained. By limiting the layout scheme of the N sensors, the measurement results of the N sensors have a more accurate correlation, thereby providing support for subsequent accurate data analysis and elimination of invalid stress data.

[0057] Further, such as Figure 5 As shown, step S240 in the embodiment of the present application also includes:

[0058] Step S241: obtaining a first equation change result according to the first calculation result;

[0059] Step S242: obtaining a first conversion equation according to the first equation change result;

[0060] Step S243: Obtain the Euclidean approximate solution according to the first transformation equation.

[0061] Further, such as Figure 6 As shown, step S300 of the embodiment of the present application also includes:

[0062] Step S310: obtaining a Euclidean distance error through a second operation process;

[0063] Step S320: obtaining the first error set according to the Euclidean distance error;

[0064] Step S330: obtaining a sensor with a maximum error value in the first error set, and using the sensor as the first sensor.

[0065] Specifically, the first equation change result AX=b is obtained, wherein X = [lmn] T , This equation has 3 variables and N equations, and inconsistent solutions may appear. The main reason for this phenomenon is that the sensors actually installed are difficult to meet the ideal installation conditions. On the contrary, if the ideal conditions can be met, matrix A will become a singular matrix and some sensors will become redundant. In this case, the requirement can be met by finding the solution with the shortest Euclidean distance as the solution with the highest similarity. The first transformation equation is obtained according to the result of the first equation change. Then the Euclidean distance error of each sensor is in, In order to obtain the error between the approximate solution and the true solution, the errors between the approximate solution and the true solution of the N sensors are statistically analyzed to obtain the first error set. The sensor with the farthest Euclidean distance from the true solution in the first error set is r m =max{r i}, i = 1, 2, ..., N. The sensor is used as the first sensor, the contribution value of the first sensor with the maximum error value is eliminated, and a balance matrix of N-1 sensors is reconstructed.

[0066] Further, such as Figure 7 As shown, step S600 of the embodiment of the present application also includes:

[0067] Step S610: obtaining a balance matrix according to the first valid data set and the first balance equation;

[0068] Step S620: obtaining a second equation change result according to the balance matrix;

[0069] Step S630: obtaining a second transformation equation according to the second equation change result;

[0070] Step S640: obtaining the maximum stress value according to the second transformation equation.

[0071] Further, such as Figure 8 As shown, step S640 of the embodiment of the present application also includes:

[0072] Step S641: Obtaining a Euclidean nearest similarity solution according to the second transformation equation;

[0073] Step S642: Obtain a second calculation result by applying the Euclidean nearest similarity solution to the first equilibrium equation;

[0074] Step S643: Obtain a circular cross-section equation, and obtain the maximum stress value based on the circular cross-section equation and the second calculation result.

[0075] Specifically, the first valid data set is substituted into the first balance equation to obtain the balance matrix of K sensors. Rewrite the equilibrium matrix as the result of the second equation change, that is, AX = b, where X = [lmn] T , According to the second equation change result, a second conversion equation is obtained, According to the second transformation equation, the Euclidean nearest similarity solution is obtained Substituting the Euclidean nearest similarity solution into the first equilibrium equation, we obtain That is, the second calculation result, the circular section equation is x 2 +y 2 =r 2 , combine the second calculation result and the circular section equation to obtain the function of z(x), By solving Get the corresponding extreme point (x0, y0) is the point where the stress on the pipe section is the largest. The maximum stress is The stress values ​​of the first valid data set are compared with the calculated maximum stress, and the monitoring data that does not meet the maximum stress is eliminated to obtain the second valid data set. By analyzing and processing the monitoring data of each sensor on the same cross section, the aging or abnormal sensor monitoring stress data can be accurately identified and eliminated, making the monitoring data more accurate and reliable.

[0076] In summary, the method for eliminating invalid data for stress monitoring provided by the embodiment of the present application has the following technical effects:

[0077] Due to the adoption of the first sensor layout scheme, N sensors are laid out according to the first sensor layout scheme to obtain the collected data of the N sensors, wherein N is a positive integer greater than 4; the collected data is subjected to a first operation process to obtain a Euclidean approximate solution; a first error set is obtained according to the Euclidean approximate solution and the true solution, and the first sensor is matched according to the first error set; the first collected data corresponding to the first sensor is removed from the collected data to obtain the first removed data; according to the first removed data, until the number of the first removed data meets the first preset requirement and / or the maximum error meets the second preset requirement, the steps are repeated to obtain the first valid data set; the second operation process is performed according to the first valid data set to obtain the maximum stress value; the first valid data set is subjected to data removal according to the maximum stress value to obtain the second valid data set. By analyzing and processing the monitoring data of each sensor on the same cross section, the aging or abnormal sensor values ​​are removed to make the monitoring data more accurate and reliable.

[0078] Embodiment 2

[0079] Based on the same inventive concept as the method for eliminating invalid data for stress monitoring in the aforementioned embodiment, Fig. 9 As shown, an embodiment of the present application provides a system for eliminating invalid data for stress monitoring, the system comprising:

[0080] A first obtaining unit 11, the first obtaining unit 11 is used to obtain a first sensor deployment scheme, deploy N sensors according to the first sensor deployment scheme, and obtain collected data of the N sensors, wherein N is a positive integer greater than 4;

[0081] A second obtaining unit 12, the second obtaining unit 12 is used to perform a first operation on the collected data to obtain a Euclidean approximate solution;

[0082] A third obtaining unit 13, the third obtaining unit 13 is used to obtain a first error set according to the Euclidean approximate solution and the true solution, and match a first sensor according to the first error set;

[0083] A fourth obtaining unit 14, the fourth obtaining unit 14 is used to remove the first collected data corresponding to the first sensor from the collected data to obtain first removed data;

[0084] A first repeating unit 15, wherein the first repeating unit 15 is used to repeat the second obtaining unit to the fourth obtaining unit according to the first eliminated data, until the number of the first eliminated data meets the first preset requirement and / or the maximum error meets the second preset requirement, then the step repetition is terminated to obtain a first valid data set;

[0085] a fifth obtaining unit 16, the fifth obtaining unit 16 being configured to perform a second operation process according to the first valid data set to obtain a maximum stress value;

[0086] The sixth obtaining unit 17 is used to perform data elimination on the first valid data set according to the maximum stress value to obtain a second valid data set.

[0087] Furthermore, the system also includes:

[0088] a seventh obtaining unit, the seventh obtaining unit being configured to obtain a first position distribution requirement, and obtain a first position layout scheme according to the first position distribution requirement;

[0089] An eighth obtaining unit, the eighth obtaining unit is used to obtain a first installation direction layout requirement, and obtain a first direction layout solution according to the first installation direction layout requirement;

[0090] A ninth obtaining unit, wherein the ninth obtaining unit is configured to obtain the first sensor layout scheme according to the first position layout scheme and the first direction layout scheme.

[0091] Furthermore, the system also includes:

[0092] A first construction unit, wherein the first construction unit is used to construct a Cartesian coordinate system, and obtain position coordinates (x, y) of the N sensors according to the Cartesian coordinate system;

[0093] A tenth obtaining unit, the tenth obtaining unit is used to obtain a first equilibrium equation: lx+my+nz=1;

[0094] an eleventh obtaining unit, the eleventh obtaining unit being used to obtain a first calculation result according to the collected data of the N sensors and the first balance equation, wherein l, m, and n are undetermined coefficients of the balance equation, z is the axial strain magnitude of each point on the circumference of the pipeline, x is the horizontal coordinate position of each point on the circumference of the pipeline, and y is the vertical coordinate position of each point on the circumference of the pipeline;

[0095] A twelfth obtaining unit, the twelfth obtaining unit is used to obtain the Euclidean approximate solution according to the first calculation result.

[0096] Furthermore, the system also includes:

[0097] a thirteenth obtaining unit, the thirteenth obtaining unit being used to obtain a first equation changing result according to the first calculation result;

[0098] a fourteenth obtaining unit, the fourteenth obtaining unit being used to obtain a first transformation equation according to a result of changing the first equation;

[0099] A fifteenth obtaining unit is used to obtain the Euclidean approximate solution according to the first transformation equation.

[0100] Furthermore, the system also includes:

[0101] a sixteenth obtaining unit, the sixteenth obtaining unit being used to obtain a Euclidean distance error through a second operation process;

[0102] a seventeenth obtaining unit, the seventeenth obtaining unit being configured to obtain the first error set according to the Euclidean distance error;

[0103] An eighteenth obtaining unit, wherein the eighteenth obtaining unit is used to obtain a sensor with a maximum error value in the first error set, and use the sensor as the first sensor.

[0104] Furthermore, the system also includes:

[0105] a nineteenth obtaining unit, the nineteenth obtaining unit being configured to obtain a balance matrix according to the first valid data set and the first balance equation;

[0106] a twentieth obtaining unit, the twentieth obtaining unit being used to obtain a second equation change result according to the balance matrix;

[0107] A twenty-first obtaining unit, the twenty-first obtaining unit is used to obtain a second conversion equation according to the second equation change result;

[0108] A twenty-second obtaining unit, the twenty-second obtaining unit is used to obtain the maximum stress value according to the second conversion equation.

[0109] Furthermore, the system also includes:

[0110] A twenty-third obtaining unit, the twenty-third obtaining unit is used to obtain a Euclidean nearest similarity solution according to the second conversion equation;

[0111] A twenty-fourth obtaining unit, the twenty-fourth obtaining unit is used to obtain a second calculation result by combining the Euclidean nearest similar solution and the first equilibrium equation;

[0112] The twenty-fifth obtaining unit is used to obtain a circular section equation, and obtain the maximum stress value based on the circular section equation and the second calculation result.

[0113] Exemplary Electronic Devices

[0114] Reference below Fig.10 To describe the electronic device of the embodiment of the present application.

[0115] Fig.10 The figure shows a schematic structural diagram of an electronic device according to an embodiment of the present application.

[0116] Based on the inventive concept of a method for eliminating invalid data for stress monitoring in the aforementioned embodiment, the present invention further provides an electronic device, as follows, Fig.10 The electronic device according to the embodiment of the present application is described. The electronic device may be a mobile device itself, or a stand-alone device independent of the mobile device, on which a computer program is stored, and when the program is executed by a processor, the steps of any of the above methods are implemented.

[0117] like Fig.10 As shown, the electronic device 50 includes one or more processors 51 and a memory 52 .

[0118] The processor 51 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 50 to perform desired functions.

[0119] The memory 52 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 51 may execute the program instructions to implement the methods of the various embodiments of the present application described above and / or other desired functions.

[0120] In one example, the electronic device 50 may further include: an input device 53 and an output device 54, and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0121] An embodiment of the present invention provides a method for eliminating invalid data for stress monitoring, the method comprising: S100, obtaining a first sensor layout scheme, and performing N sensor layouts according to the first sensor layout scheme to obtain collected data of the N sensors, wherein N is a positive integer greater than 4; S200, performing a first operation on the collected data to obtain a Euclidean approximate solution; S300, obtaining a first error set according to the Euclidean approximate solution and a true solution, and matching a first sensor according to the first error set; S400, eliminating the first collected data corresponding to the first sensor from the collected data to obtain first eliminated data; S500, repeating steps S200-S400 according to the first eliminated data until the number of the first eliminated data meets a first preset requirement and / or the maximum error meets a second preset requirement, then ending the step repetition to obtain a first valid data set; S600, performing a second operation on the first valid data set to obtain a maximum stress value; S700, eliminating data from the first valid data set according to the maximum stress value to obtain a second valid data set. The present invention solves the technical problem that the existing technology lacks a method for effectively eliminating invalid data in the stress monitoring data obtained by multiple sensors in a single pipeline section, resulting in the monitoring data being inaccurate and unreliable. By analyzing and processing the monitoring data from each sensor on the same section, the stress data monitored by aging or abnormal sensors can be accurately identified and eliminated, thereby achieving the technical effect of making the monitoring data more accurate and reliable.

[0122] Through the description of the above implementation methods, the technicians in the relevant field can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course, it can also be implemented by special hardware including special integrated circuits, special CPUs, special memories, special components, etc. In general, all functions completed by computer programs can be easily implemented with corresponding hardware, and the specific hardware structures used to implement the same function can also be various, such as analog circuits, digital circuits or special circuits. However, for the present application, software program implementation is a better implementation method in more cases. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, U disk, mobile hard disk, ROM, RAM, disk or optical disk, etc., including a number of instructions to enable a computer device to execute the methods described in each embodiment of the present application.

[0123] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0124] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from a computer-readable storage medium to another computer-readable storage medium, and the available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

[0125] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0126] In addition, the terms "system" and "network" are often used interchangeably in this article. The term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0127] It should be understood that in the embodiment of the present application, "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0128] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0129] In short, the above is only a preferred embodiment of the technical solution of this application, and is not intended to limit the protection scope of this application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included in the protection scope of this application.

Claims

1. A method for eliminating invalid data for stress monitoring, characterized in that: The method comprises: S100, obtaining a first sensor deployment scheme, deploying N sensors according to the first sensor deployment scheme, and obtaining collected data of the N sensors, wherein N is a positive integer greater than 4; S200, performing a first operation on the collected data to obtain a Euclidean approximate solution; S300, obtaining a first error set according to the Euclidean approximate solution and the true solution, and matching a first sensor according to the first error set; S400, removing first collected data corresponding to the first sensor from the collected data to obtain first removed data; S500, repeating steps S200-S400 according to the first eliminated data until the number of the first eliminated data meets a first preset requirement and / or the maximum error meets a second preset requirement, then ending the step repetition to obtain a first valid data set; S600, performing a second operation process according to the first valid data set to obtain a maximum stress value; S700: Eliminate data from the first valid data set according to the maximum stress value to obtain a second valid data set.

2. The method according to claim 1, characterized in that The S100 further includes: Obtaining a first position distribution requirement, and obtaining a first position layout plan according to the first position distribution requirement; Obtaining a first installation direction layout requirement, and obtaining a first direction layout plan according to the first installation direction layout requirement; The first sensor layout scheme is obtained according to the first position layout scheme and the first direction layout scheme.

3. The method according to claim 1, characterized in that The S200 further includes: Constructing a Cartesian coordinate system, and obtaining position coordinates (x, y) of the N sensors according to the Cartesian coordinate system; Obtain the first equilibrium equation: lx+my+nz=1; Obtain a first calculation result according to the collected data of the N sensors and the first balance equation, wherein l, m, and n are unknown coefficients of the balance equation, z is the axial strain magnitude of each point on the circumference of the pipeline, x is the horizontal coordinate position of each point on the circumference of the pipeline, and y is the vertical coordinate position of each point on the circumference of the pipeline; The Euclidean approximate solution is obtained according to the first calculation result.

4. The method according to claim 3, characterized in that The method further comprises: Obtaining a first equation change result according to the first calculation result; Obtaining a first conversion equation according to the result of changing the first equation; The Euclidean approximate solution is obtained according to the first transformation equation.

5. The method according to claim 4, characterized in that The S300 further includes: Obtaining the Euclidean distance error through the second operation processing; Obtaining the first error set according to the Euclidean distance error; A sensor with a maximum error value in the first error set is obtained, and the sensor is used as the first sensor.

6. The method according to claim 3, characterized in that The S600 further includes: Obtaining a balance matrix according to the first valid data set and the first balance equation; Obtaining a second equation change result according to the balance matrix; Obtaining a second conversion equation according to the second equation change result; The maximum stress value is obtained according to the second conversion equation.

7. The method according to claim 6, characterized in that The method further comprises: Obtaining a Euclidean nearest similarity solution according to the second transformation equation; Obtain a second calculation result by combining the Euclidean nearest similarity solution and the first equilibrium equation; A circular cross-section equation is obtained, and the maximum stress value is obtained based on the circular cross-section equation and the second calculation result.

8. A system for eliminating invalid data for stress monitoring, characterized in that: The system comprises: A first obtaining unit, wherein the first obtaining unit is used to obtain a first sensor deployment scheme, deploy N sensors according to the first sensor deployment scheme, and obtain collected data of the N sensors, wherein N is a positive integer greater than 4; a second obtaining unit, the second obtaining unit being used to perform a first operation on the collected data to obtain a Euclidean approximate solution; a third obtaining unit, the third obtaining unit being configured to obtain a first error set according to the Euclidean approximate solution and the true solution, and to match a first sensor according to the first error set; a fourth obtaining unit, the fourth obtaining unit being used to remove the first collected data corresponding to the first sensor from the collected data to obtain first removed data; a first repeating unit, wherein the first repeating unit is used to repeat the second obtaining unit to the fourth obtaining unit according to the first eliminated data until the number of the first eliminated data meets the first preset requirement and / or the maximum error meets the second preset requirement, then the step repetition is terminated to obtain a first valid data set; a fifth obtaining unit, the fifth obtaining unit being configured to perform a second operation process according to the first valid data set to obtain a maximum stress value; A sixth obtaining unit is used to eliminate data from the first valid data set according to the maximum stress value to obtain a second valid data set.

9. An electronic device, comprising: A processor, the processor is coupled to a memory, the memory is used to store a program, and is characterized in that when the program is executed by the processor, the system is enabled to execute the method according to any one of claims 1 to 7.

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