System and method for processing stress monitoring values ​​during pipe truss installation

Abstract

A system and method for processing stress monitoring values ​​during pipe truss installation, belonging to the technical field of monitoring value processing technology, divides numerous and continuous initial stress monitoring values ​​into several smaller-scale stress monitoring value clusters, allowing the stress monitoring values ​​to be transmitted more reliably under different wireless communication conditions. By introducing a floating condition mode, favorable conditions are created for determining the accuracy and confidence of the stress monitoring values. After the stress monitoring values ​​are transmitted to a data management and application platform, the completeness and accuracy of the stress monitoring values ​​are globally evaluated by comparing the floating parameters of the stress monitoring values ​​before and after transmission. Therefore, the present invention not only improves the efficiency of stress monitoring value processing, but also enhances the robustness and reliability of the stress monitoring values, ensuring the accuracy, precision and efficiency of the stress monitoring values, and can display accurate stress monitoring values ​​during pipe truss installation on the display module of the data management and application platform.

Description

Technical Field

[0001] The present invention belongs to the technical field of monitoring value processing, and in particular relates to a system and method for processing stress monitoring values ​​during installation of a pipe truss. Background Art

[0002] A tubular truss is a lattice structure made of round rods connected at their ends. These trusses make the truss structure economical in material usage, lightweight, and easy to create in a variety of shapes to suit different applications, such as simply supported trusses, arches, frames, and towers.

[0003] In practical applications, the current processing system for stress monitoring values ​​during the installation of a tube truss often uses the prior art solution mentioned in patent publication number "CN118548816A", in which a vibrating wire strain sensor provided at the connection between the horizontal and vertical bars of the tube truss is connected to an intelligent wireless data acquisition terminal, and the intelligent wireless data acquisition terminal is wirelessly connected to a data management and application platform. During the installation of the tube truss, the vibrating wire strain sensor is used to transmit stress data at the connection between the horizontal and vertical bars of the tube truss to the intelligent wireless data acquisition terminal. The stress data at the connection between the horizontal and vertical bars of the tube truss is the stress monitoring value during the installation of the tube truss. The intelligent wireless data acquisition terminal is used to transmit the transmitted stress monitoring value during the installation of the tube truss to the screen display module of the data management and application platform for display, thereby achieving the purpose of stress monitoring during the installation of the tube truss.

[0004] However, in actual application, because the intelligent wireless data acquisition terminal is wirelessly connected to the data management and application platform, and the intelligent wireless data acquisition terminal needs to wirelessly transmit a large number of stress monitoring values ​​to the data management and application platform, the stress monitoring values ​​are often subject to unexpected disturbances during transmission, such as clutter disturbances, noise disturbances, etc., which is not conducive to the accuracy and confidence of the stress monitoring values. At present, the identification of stress monitoring values ​​often tends to be a completeness test of stress monitoring values, but the performance of determining the accuracy and confidence of stress monitoring values ​​is poor, especially when facing the complex and changeable pipe truss installation site. The current stress monitoring value identification method is difficult to accurately determine whether the stress monitoring value is noisy under clutter disturbances, noise disturbances, and cannot accurately and efficiently lock the noise value, and cannot efficiently detect and deal with the noise value. Therefore, it is impossible to display the accurate stress monitoring value during the pipe truss installation on the screen display module of the data management and application platform. Summary of the Invention

[0005] In order to solve the defects in the existing technology, the present invention proposes a system and method for processing stress monitoring values ​​during the installation of a pipe truss. The present invention effectively avoids the defects in the existing technology that the stress monitoring value identification method faced with the complex and changeable pipe truss installation site is difficult to accurately determine whether the stress monitoring value has a noise value under clutter disturbance or noise disturbance, cannot accurately and efficiently lock the noise value, cannot efficiently detect and deal with the noise value, and cannot display the accurate stress monitoring value during the installation of the pipe truss on the screen display module of the data management and application platform.

[0006] The present invention utilizes the following technical solutions.

[0007] A method for processing stress monitoring values ​​during installation of a pipe truss, comprising:

[0008] During the installation of the tube truss, the vibrating wire strain sensor transmits the sampled stress data of the connection between the horizontal and vertical bars of the tube truss to the intelligent wireless data acquisition terminal. The stress data of the connection between the horizontal and vertical bars of the tube truss is the stress monitoring value during the installation of the tube truss. The intelligent wireless data acquisition terminal transmits the transmitted stress monitoring value during the installation of the tube truss to the data management and application platform for processing, and then transmits the processed stress monitoring value during the installation of the tube truss to the screen display module of the data management and application platform for display;

[0009] The method for processing stress monitoring values ​​during installation of a pipe truss by a data management and application platform includes:

[0010] Step 1: The intelligent wireless data acquisition terminal arranges the sampling times transmitted by the vibrating wire strain sensor in order to form a sampling time queue, obtains the initial stress monitoring value queue transmitted by the vibrating wire strain sensor based on the sampling time queue, and divides the initial stress monitoring value queue into a plurality of stress monitoring value clusters 1, where each stress monitoring value cluster 1 includes a plurality of stress monitoring values;

[0011] Step 2: Obtain a stress monitoring value floating parameter 1 related to the stress monitoring value cluster 1 according to the floating status pattern and the stress monitoring value cluster 1, and obtain a global floating parameter 1 according to a plurality of stress monitoring value floating parameters 1.

[0012] Furthermore, after step 2, the method further includes:

[0013] Step 3: The intelligent wireless data acquisition terminal transmits the stress monitoring value clusters 1 to the data management and application platform, and transmits the global floating parameter 1 and the stress monitoring value floating parameters 1 to the data management and application platform. The data management and application platform treats the collected stress monitoring value cluster 1 as stress monitoring value cluster 2.

[0014] Step 4: Obtain stress monitoring value floating parameter 2 related to stress monitoring value cluster 2 according to the floating status pattern and stress monitoring value cluster 2, and obtain global floating parameter 2 according to a plurality of stress monitoring value floating parameters 2;

[0015] Step 5: Obtain stress monitoring value identification information according to stress monitoring value floating parameter 1, stress monitoring value floating parameter 2, global floating parameter 1, and global floating parameter 2.

[0016] Furthermore, in step 1, during the installation of the pipe truss, the vibrating wire strain sensor samples the stress monitoring value during the installation of the pipe truss and transmits the stress monitoring value and the sampling time to the intelligent wireless data acquisition terminal. The intelligent wireless data acquisition terminal arranges the sampling times transmitted by the vibrating wire strain sensor in order to form a sampling time queue; then the intelligent wireless data acquisition terminal arranges the stress monitoring values ​​corresponding to each sampling time according to the order of the sampling times in the sampling time queue, thereby forming a value queue arranged in order of the sampling times, that is, an initial stress monitoring value queue; then the initial stress monitoring value queue is cut into a plurality of stress monitoring value clusters 1, each stress monitoring value cluster 1 containing a plurality of stress monitoring values ​​that are continuous at the sampling time.

[0017] Furthermore, step 5 specifically includes:

[0018] Step 5-1: Obtain spacing value 1 based on global floating parameter 1 and global floating parameter 2, and determine whether spacing value 1 exceeds threshold value 1;

[0019] Step 5-2: If the value is not higher, the stress monitoring value identification information is "same" or "no change". Based on this, the plurality of stress monitoring value clusters are reconstructed according to the order of sampling time to form a stress monitoring value queue to be processed. The stress monitoring value queue to be processed is sent out. The stress monitoring values ​​in the stress monitoring value queue to be processed are the stress monitoring values ​​during the installation of the pipe truss after processing.

[0020] Step 5-3: If it is higher, the stress monitoring value identification information is "different" or "changed", and the spacing value 2 is obtained based on the stress monitoring value floating parameter 1 and the stress monitoring value floating parameter 2 related to each stress monitoring value cluster 2. The stress monitoring value cluster 2 with the spacing value 2 higher than the critical value 2 is obtained and regarded as the noise value cluster, and the stress monitoring value cluster 2 with the spacing value 2 not higher than the critical value 2 is obtained and regarded as the reasonable stress monitoring value cluster, and the noise value cluster and the reasonable stress monitoring value cluster are sent out.

[0021] Furthermore, in step 5-1, the spacing between the global floating parameter 1 and the global floating parameter 2 is initially calculated based on the global floating parameter 1 and the global floating parameter 2 obtained by the previous calculation. The spacing is the spacing 1.

[0022] Furthermore, in step 5-1, the method for calculating the spacing between the global floating parameter one and the global floating parameter two is: calculating the absolute value of the amount obtained by subtracting the global floating parameter one from the global floating parameter two, and the absolute value is the spacing between the global floating parameter one and the global floating parameter two.

[0023] Furthermore, in step 5-2, the received stress monitoring value clusters 2 are arranged in the order of sampling time, and the arranged adjacent stress monitoring value clusters 2 are docked to reconstruct a complete stress monitoring value queue, that is, the stress monitoring value queue to be processed, and then the stress monitoring value queue to be processed is sent out.

[0024] Furthermore, in step 5-3, the floating parameter spacing between each stress monitoring value cluster 2 and its corresponding stress monitoring value cluster is calculated. This spacing is referred to as spacing 2 of stress monitoring value cluster 2. After calculating spacing 2 of stress monitoring value cluster 2, it is compared with a predefined critical value 2.

[0025] If the spacing value 2 of the stress monitoring value cluster 2 is higher than the critical value 2, the stress monitoring value cluster 2 is registered as a noise value cluster; if the spacing value 2 of the stress monitoring value cluster 2 is not higher than the critical value 2, the stress monitoring value cluster 2 is registered as a reasonable stress monitoring value cluster;

[0026] Then the noise value cluster and the reasonable stress monitoring value cluster are sent out. The method of sending out the noise value cluster and the reasonable stress monitoring value cluster is: first use the Kalman filter to perform denoising on the stress monitoring values ​​in the noise value cluster, and the noise value cluster and the reasonable stress monitoring value cluster after denoising are arranged in the order of sampling time to form a cluster, and then the stress monitoring values ​​in the cluster are transmitted to the screen display module of the data management and application platform in the order of sampling time for display. The stress monitoring values ​​in the cluster are the stress monitoring values ​​during the installation of the pipe truss after processing.

[0027] Furthermore, in step 5-3, the method for calculating the floating parameter spacing between each stress monitoring value cluster 2 and its corresponding stress monitoring value cluster is: calculating the absolute value of the amount obtained by subtracting the stress monitoring value floating parameter 2 of each stress monitoring value cluster 2 from the stress monitoring value floating parameter 2 of its corresponding stress monitoring value cluster 1, and this absolute value is the spacing amount 2 of the stress monitoring value cluster 2.

[0028] Furthermore, in step 2, the method of obtaining the stress monitoring value floating parameter 1 related to the stress monitoring value cluster 1 according to the floating condition pattern and the stress monitoring value cluster 1 includes:

[0029] Step 2-1: Get the Stress monitoring value cluster ;

[0030] Step 2-2: Calculate based on the floating status mode The partial floating value of each stress monitoring value;

[0031] Step 2-3: Calculate based on the floating status mode The floating trend of

[0032] Step 2-4: Obtain according to the floating status model, segmented floating value and floating trend The stress monitoring value of the floating parameter is one.

[0033] Further, in step 2-2, the floating state mode is calculated The floating status pattern of the partial floating values ​​of each stress monitoring value is as follows: Here, yes Neidi The partial floating value of each stress monitoring value, yes Neidi Stress monitoring value, yes Neidi A stress monitoring value.

[0034] Further, in step 2-3, the floating state mode is calculated The floating status pattern in the floating trend is: Here, yes The floating trend, yes Neidi Stress monitoring value, yes The average of all stress monitoring values ​​within yes The number of internal stress monitoring values.

[0035] Furthermore, in steps 2-4, according to the floating status model, the floating value of each part and the floating trend, The floating condition mode of the stress monitoring value floating parameter 1 is: Here, yes The stress monitoring value floating parameter is one, and is the weight factor.

[0036] A system for processing stress monitoring values ​​during installation of a pipe truss, comprising:

[0037] The vibrating wire strain sensor installed at the connection between the horizontal and vertical bars of the tube truss is connected to the intelligent wireless data acquisition terminal, and the intelligent wireless data acquisition terminal is wirelessly connected to the data management and application platform. During the installation of the tube truss, the vibrating wire strain sensor is used to transmit the sampled stress data of the connection between the horizontal and vertical bars of the tube truss to the intelligent wireless data acquisition terminal. The stress data of the connection between the horizontal and vertical bars of the tube truss is the stress monitoring value during the installation of the tube truss. The intelligent wireless data acquisition terminal is used to transmit the transmitted stress monitoring value during the installation of the tube truss to the data management and application platform for processing, and then transmit the processed stress monitoring value during the installation of the tube truss to the screen display module of the data management and application platform for display;

[0038] The system for processing stress monitoring values ​​during the installation of a pipe truss also includes:

[0039] a cutting module, configured to arrange the sampling moments transmitted by the vibrating wire strain sensor in a sequential order to form a sampling moment queue, obtain an initial stress monitoring value queue transmitted by the vibrating wire strain sensor based on the sampling moment queue, and cut the initial stress monitoring value queue into a plurality of stress monitoring value clusters 1, wherein the stress monitoring value cluster 1 includes a plurality of stress monitoring values;

[0040] The parameter module 1 is used to obtain a stress monitoring value floating parameter 1 related to the stress monitoring value cluster 1 according to a floating status pattern and the stress monitoring value cluster 1, and to obtain a global floating parameter 1 according to a plurality of stress monitoring value floating parameters 1.

[0041] Furthermore, the system for processing stress monitoring values ​​during installation of the pipe truss further includes:

[0042] a transmission module, which is used for the intelligent wireless data acquisition terminal to transmit the plurality of stress monitoring value clusters 1 respectively to the data management and application platform, and transmit the global floating parameter 1 and the plurality of stress monitoring value floating parameters 1 to the data management and application platform, and the data management and application platform treats the received stress monitoring value cluster 1 as stress monitoring value cluster 2;

[0043] A parameter module 2 is used to obtain a stress monitoring value floating parameter 2 related to the stress monitoring value cluster 2 according to the floating condition pattern and the stress monitoring value cluster 2, and to obtain a global floating parameter 2 according to a plurality of stress monitoring value floating parameters 2;

[0044] The identification module is used to obtain stress monitoring value identification information according to the stress monitoring value floating parameter 1, the stress monitoring value floating parameter 2, the global floating parameter 1 and the global floating parameter 2.

[0045] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0046] Dividing the numerous and continuous initial stress monitoring values ​​into several smaller clusters of stress monitoring values ​​reduces the complexity of stress monitoring value processing and improves the flexibility of stress monitoring value transmission, allowing for more reliable transmission of stress monitoring values ​​under varying wireless communication conditions. By introducing a floating state mode, this method can capture and digitize the floating nature of stress monitoring values, creating favorable conditions for determining the accuracy and confidence of stress monitoring values. After the stress monitoring values ​​are transmitted to the data management and application platform, by comparing the floating parameters of the stress monitoring values ​​before and after transmission, it is possible to accurately determine whether the stress monitoring values ​​contain noise during transmission. Furthermore, the global floating parameters and the floating parameters of the stress monitoring value clusters are considered, providing a comprehensive assessment of the completeness and accuracy of the stress monitoring values. Therefore, the present invention not only improves the efficiency of stress monitoring value processing but also enhances the robustness and reliability of stress monitoring values, ensuring the accuracy, precision, and efficiency of stress monitoring values. Accurate stress monitoring values ​​during pipe truss installation can be displayed on the display module of the data management and application platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a flow chart of a method for processing stress monitoring values ​​during installation of a pipe truss according to the present invention;

[0048] Figure 2 It is a partial structural diagram of the stress monitoring value processing system during the installation of the pipe truss according to the present invention. DETAILED DESCRIPTION

[0049] To make the objectives, technical solutions, and advantages of the present invention more clear, the following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely express the technical solutions of the present invention. The embodiments expressed in this application are only some embodiments of the present invention, not all embodiments. Based on the spirit of the present invention, other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0050] like Figure 1 As shown, the method for processing stress monitoring values ​​during installation of a pipe truss according to the present invention includes:

[0051] During the installation of the tube truss, the vibrating wire strain sensor transmits the sampled stress data at the connection between the horizontal and vertical bars of the tube truss to the intelligent wireless data acquisition terminal. The stress data at the connection between the horizontal and vertical bars of the tube truss serves as the stress monitoring value during the installation of the tube truss. The intelligent wireless data acquisition terminal transmits the transmitted stress monitoring value during the installation of the tube truss to the data management and application platform for processing. The processed stress monitoring value during the installation of the tube truss is then transmitted to the display module of the data management and application platform for display, thereby achieving the purpose of stress monitoring during the installation of the tube truss. When the vibrating wire strain sensor transmits the sampled stress data at the connection between the horizontal and vertical bars of the tube truss to the intelligent wireless data acquisition terminal, it also synchronously transmits the corresponding sampling time of the stress data to the intelligent wireless data acquisition terminal. When the intelligent wireless data acquisition terminal transmits the stress monitoring value during the installation of the tube truss to the data management and application platform, it also synchronously transmits the corresponding sampling time of the stress monitoring value to the data management and application platform. The method by which the intelligent wireless data acquisition terminal transmits the stress monitoring value during the installation of the pipe truss to the data management and application platform is to use a wireless communication transmission method.

[0052] The method for processing stress monitoring values ​​during installation of a pipe truss by a data management and application platform includes:

[0053] Step 1: The intelligent wireless data acquisition terminal arranges the sampling times transmitted by the vibrating wire strain sensor in order to form a sampling time queue, obtains the initial stress monitoring value queue transmitted by the vibrating wire strain sensor based on the sampling time queue, and divides the initial stress monitoring value queue into a plurality of stress monitoring value clusters 1, where each stress monitoring value cluster 1 includes a plurality of stress monitoring values;

[0054] Step 2: Obtaining a stress monitoring value floating parameter 1 related to the stress monitoring value cluster 1 according to the floating state pattern and the stress monitoring value cluster 1, and obtaining a global floating parameter 1 according to a plurality of stress monitoring value floating parameters 1;

[0055] Step 3: The intelligent wireless data acquisition terminal transmits the stress monitoring value clusters 1 to the data management and application platform, and transmits the global floating parameter 1 and the stress monitoring value floating parameters 1 to the data management and application platform. The data management and application platform treats the collected stress monitoring value cluster 1 as stress monitoring value cluster 2.

[0056] Step 4: Obtain stress monitoring value floating parameter 2 related to stress monitoring value cluster 2 according to the floating status pattern and stress monitoring value cluster 2, and obtain global floating parameter 2 according to a plurality of stress monitoring value floating parameters 2;

[0057] Step 5: Obtain stress monitoring value identification information according to stress monitoring value floating parameter 1, stress monitoring value floating parameter 2, global floating parameter 1, and global floating parameter 2.

[0058] In a preferred but non-limiting embodiment of the present invention, in step 1, during the installation of the pipe truss, the vibrating wire strain sensor continuously samples the stress monitoring value during the installation of the pipe truss and transmits the stress monitoring value and its sampling time to the intelligent wireless data acquisition terminal. The intelligent wireless data acquisition terminal arranges the sampling times transmitted by the vibrating wire strain sensor in order to form a sampling time queue; then the intelligent wireless data acquisition terminal arranges the stress monitoring values ​​corresponding to each sampling time according to the order of the sampling times in the sampling time queue, thereby forming a value queue arranged in order of the sampling times, that is, an initial stress monitoring value queue; then the initial stress monitoring value queue is cut into a plurality of stress monitoring value clusters 1, each stress monitoring value cluster 1 containing a plurality of stress monitoring values ​​that are continuous at the sampling time. Just as the string-type strain sensor samples the stress monitoring value during the installation of the pipe truss once every 1ms, the intelligent wireless data acquisition terminal forms a continuous sampling time queue with the corresponding sampling times of the stress monitoring values ​​sampled by the string-type strain sensor during the installation of the pipe truss every 2s. 2000 stress monitoring values ​​will be sampled in these 2s, and the 2000 stress monitoring values ​​will be divided into several stress monitoring value clusters. Each stress monitoring value cluster can contain all the stress monitoring values ​​sampled in 20ms, which is convenient for the subsequent stress monitoring value analysis and processing.

[0059] In summary, by cutting the numerous initial stress monitoring values ​​into several smaller stress monitoring value clusters, the clustered stress monitoring values ​​are more suitable for synchronous processing, which can reduce the complexity of stress monitoring value processing. In addition, this type of cluster processing method is also suitable for improving the flexibility of stress monitoring value transmission, allowing stress monitoring values ​​to be transmitted more reliably under different wireless communication conditions, reducing the noise values ​​generated by interference disturbances and noise disturbances during wireless communication. The formation of several stress monitoring value clusters also creates conditions for parameter comparison during the subsequent stress monitoring value identification period.

[0060] In step 2, the floating state model is a model used to characterize the stress monitoring value with time-varying properties. During the installation of the pipe truss, the fluctuation of the stress monitoring value can be obtained and digitized. Such fluctuation is often caused by several factors (such as different installation process factors such as assembly, welding and hoisting during the installation of the pipe truss); for each stress monitoring value cluster 1, the floating state model is used to calculate its corresponding stress monitoring value floating parameter. This parameter is unique to each stress monitoring value cluster 1 and can characterize the floating properties of the stress monitoring value in the stress monitoring value cluster 1. For example, the dispersion and fluctuation of the stress monitoring value can be measured using the range, coefficient of variation or other parameters; after obtaining the floating parameters of several stress monitoring value clusters 1, Then, the overall floating status of the parameter is calculated, which is the global floating parameter one. This parameter is also unique and can characterize the floating properties of all the initial stress monitoring value queues. It can be a comprehensive evaluation of the mean, maximum value, minimum value and other parameters of the floating parameters of each stress monitoring value cluster one. It can be obtained through non-equal weighted averaging methods or differential mean methods. Of course, the mean of the floating parameters of each stress monitoring value cluster one can also be regarded as the global floating parameter one. Due to the uniqueness of the stress monitoring value floating parameter one and the global floating parameter one, it can create good conditions for the subsequent identification process of steps 3, 4 and 5. By comparing the floating parameters before and after transmission, it can be accurately determined whether the stress monitoring value cluster one has noise values ​​during transmission.

[0061] In step 3, the previously segmented stress monitoring value clusters 1 are initially transmitted separately (here, separately can be understood as multiple times, i.e., one stress monitoring value cluster 1 is transmitted at a time) to the data management and application platform via the intelligent wireless data acquisition terminal. Global floating parameter 1 and several stress monitoring value floating parameters 1, previously calculated in step 2, are also transmitted to the data management and application platform. At the data management and application platform, the received stress monitoring value cluster 1 is redefined as stress monitoring value cluster 2. The data management and application platform now has the related stress monitoring value clusters 1 and 2, as well as the corresponding stress monitoring value floating parameter 1, creating favorable conditions for subsequent stress monitoring value accuracy and confidence assessment and noise value detection.

[0062] In summary, the use of a scheme of transmitting several stress monitoring value clusters separately improves the flexibility of stress monitoring value transmission. Because external conditions are complex and changeable, wireless communication conditions often change, such as bit rate fluctuations, channel disturbances, etc. By transmitting stress monitoring values ​​in clusters, it can be well adapted to such wireless communication conditions, ensuring that stress monitoring values ​​can be transmitted more reliably under different wireless communication conditions; taking into account that stress monitoring value cluster 1 is often subject to interference disturbances and noise disturbances during transmission and changes, that is, generating noise values, etc., the received stress monitoring value cluster 1 is redefined as stress monitoring value cluster 2 at the data management and application platform, which is to perform obvious differentiation from the initial stress monitoring value cluster 1, so as to perform subsequent identification and processing.

[0063] In step 4, the data management and application platform will use the same floating state model as in step 2 to analyze the received stress monitoring value cluster 2 (that is, the stress monitoring value cluster 1 after transmission). The analysis process is the same as step 2, but the object this time is the stress monitoring value after transmission. Through the floating state model, the data management and application platform can calculate the stress monitoring value floating parameter 2 corresponding to each stress monitoring value cluster 2. This parameter digitizes the floating properties of each stress monitoring value cluster 1 after transmission. After completing the calculation of the stress monitoring value floating parameter 2, the data management and application platform will then obtain the global floating parameter 2 based on this parameter. This parameter is obtained after a comprehensive evaluation of the entire stress monitoring value floating parameter 2, which reflects the floating properties of the entire value queue after transmission.

[0064] In step 5, the data management and application platform will centrally use the stress monitoring value floating parameter 1, stress monitoring value floating parameter 2, global floating parameter 1 and global floating parameter 2 obtained by the previous calculation to perform stress monitoring value identification. These parameters together form the main basis for evaluating the completeness and accuracy of stress monitoring value transmission; by comparing the stress monitoring value floating parameter 1 and the stress monitoring value floating parameter 2, it can be determined whether each actual stress monitoring value cluster 1 has undergone significant changes during the transmission period; and by comparing the global floating parameter 1 and the global floating parameter 2, it can be evaluated whether the global floating properties of all value queues after transmission are maintained with the initial stress monitoring value. The same, that is, if the difference between the stress monitoring value floating parameter 2 and the corresponding stress monitoring value floating parameter 1 is small, and the global floating parameter 2 and the global floating parameter 1 are also similar, then it can be determined that the stress monitoring value maintains a high degree of stability and accuracy during transmission, and the stress monitoring value identification information is "the same" or "no change". Otherwise, if there is a significant difference between the floating parameters, or the global floating parameters have changed significantly, it often indicates that the stress monitoring value transmission period is subject to noise disturbance or noise disturbance and contains noise values, and the stress monitoring value identification information is "different" or "changed". At this time, denoising processing should be performed to ensure the accuracy of the stress monitoring value.

[0065] Therefore, the data management and application platform will initially perform a comparative analysis of the global floating parameter one and the global floating parameter two; the global floating parameter one and the global floating parameter two respectively represent the global floating properties of the initial value queue and the value queue after transmission. If the global floating parameter one is not much different from the global floating parameter two, that is, it is within the allowable deviation range, it also indicates that the stress monitoring value maintains a high degree of stability and coordination during the transmission period, and it can be preliminarily determined that the stress monitoring value is correct. In this case, it is not necessary to analyze the stress monitoring value floating parameter one and the stress monitoring value floating parameter two of each stress monitoring value cluster, because the coordination reflected by the global floating parameters has already provided a guarantee for the correctness of the stress monitoring value.

[0066] More importantly, after forming the stress monitoring value identification information, the stress monitoring value floating parameter 1, the stress monitoring value floating parameter 2, the global floating parameter 1 and the global floating parameter 2 can also be beneficial to the subsequent processing of the stress monitoring value, thereby greatly saving the amount of calculation and improving the efficiency and function of the stress monitoring value processing, just as the floating parameters can be used to define early warning rules, evaluate the performance of stress monitoring values, estimate the future trend of stress monitoring values ​​in advance, and efficiently detect defects or hidden dangers in the installation of pipe trusses.

[0067] In summary, in the method of processing the stress monitoring values ​​during the installation of the pipe truss by the data management and application platform, the numerous and continuous initial stress monitoring values ​​are first cut into several smaller stress monitoring value clusters, which reduces the complexity of stress monitoring value processing and improves the flexibility of stress monitoring value transmission, so that stress monitoring values ​​can be transmitted more reliably under different wireless communication conditions; then, by introducing the floating state mode, this method can obtain and digitize the floatability of stress monitoring values, creating good conditions for the accuracy and confidence of stress monitoring values; then, after the stress monitoring values ​​are transmitted to the data management and application platform, by comparing them with the values ​​before and after transmission, the stress monitoring values ​​are transmitted to the data management and application platform. The floating parameters of the stress monitoring values ​​after transmission can accurately determine whether the stress monitoring values ​​carry noise values ​​during transmission. In addition, the floating parameters of the global floating parameters and the floating parameters of the actual stress monitoring value cluster are taken into account, giving a comprehensive evaluation of the completeness and accuracy of the stress monitoring values. Therefore, the method of processing the stress monitoring values ​​during the installation of the pipe truss by the data management and application platform not only improves the efficiency of the stress monitoring value processing, but also enhances the robustness and reliability of the stress monitoring values, ensuring the correctness, accuracy and efficiency of the stress monitoring values, and can display accurate stress monitoring values ​​during the installation of the pipe truss on the display module of the data management and application platform.

[0068] In a preferred but non-limiting embodiment of the present invention, step 5 specifically comprises:

[0069] Step 5-1: Obtain spacing value 1 based on global floating parameter 1 and global floating parameter 2, and determine whether spacing value 1 exceeds threshold value 1;

[0070] Step 5-2: If not, the stress monitoring value identification information is "same" or "no change", and accordingly, a plurality of stress monitoring value clusters are reconstructed according to the order of sampling time to form a stress monitoring value queue to be processed, and the stress monitoring value queue to be processed is sent out. The stress monitoring values ​​in the stress monitoring value queue to be processed are the stress monitoring values ​​during the installation of the pipe truss after processing; sending out the stress monitoring value queue to be processed includes: transmitting the stress monitoring values ​​in the stress monitoring value queue to be processed according to the order of their sampling time to a screen display module of the data management and application platform for display.

[0071] Step 5-3: If it is higher, the stress monitoring value identification information is "different" or "changed", and the spacing value 2 is obtained based on the stress monitoring value floating parameter 1 and the stress monitoring value floating parameter 2 related to each stress monitoring value cluster 2. The stress monitoring value cluster 2 with the spacing value 2 higher than the critical value 2 is obtained and regarded as the noise value cluster, and the stress monitoring value cluster 2 with the spacing value 2 not higher than the critical value 2 is obtained and regarded as the reasonable stress monitoring value cluster, and the noise value cluster and the reasonable stress monitoring value cluster are sent out.

[0072] In a preferred but non-restrictive embodiment of the present invention, in step 5-1, the distance between the global floating parameter 1 and the global floating parameter 2 is calculated based on the global floating parameter 1 and the global floating parameter 2 obtained by the previous calculation. The distance is the distance 1; the distance 1 reflects the difference in global float between the initial value queue (composed of the stress monitoring value cluster 1) and the transferred value queue (composed of the stress monitoring value cluster 2). After the distance 1 is calculated, it is then compared with the previously defined critical value 1. The critical value 1 is determined based on the actual application conditions and the application. It depends on the stress monitoring value attribute, which represents an allowable fluctuation difference range; if the interval value is not higher than the critical value, it means that the global fluctuation of the stress monitoring value after transmission is consistent with the initial stress monitoring value, and the transmission process of the stress monitoring value is very smooth, and it can be determined that the stress monitoring value does not contain noise; if the interval value is higher than the critical value, it means that the global fluctuation of the stress monitoring value after transmission is significantly different from the initial stress monitoring value, which often indicates that the stress monitoring value contains noise under the interference and noise disturbance during transmission, and analysis and processing are required.

[0073] In a preferred but non-limiting embodiment of the present invention, in step 5-1, the method for calculating the spacing between global floating parameter one and global floating parameter two is: calculating the absolute value of the amount obtained by subtracting global floating parameter one from global floating parameter two, and this absolute value is the spacing between global floating parameter one and global floating parameter two.

[0074] In a preferred but non-limiting embodiment of the present invention, in step 5-2, after determining that the stress monitoring value transmission is stable, the first step is to arrange the received several stress monitoring value clusters 2 according to the order of sampling time. This is because the stress monitoring values ​​are generated according to the order of sampling time in the sampling time queue during the installation of the pipe truss; the arranged two adjacent stress monitoring value clusters 2 are docked to reconstruct a complete stress monitoring value queue, that is, a stress monitoring value queue to be processed. This queue must maintain corresponding uniformity with the initial stress monitoring value queue in terms of global volatility and stress monitoring values. Then, the stress monitoring value queue to be processed is sent out, and the stress monitoring value queue to be processed can be used as an information source for display, processing, or storage on the screen display module of the data management and application platform.

[0075] In a preferred but non-limiting embodiment of the present invention, in step 5-3, when the spacing value 1 exceeds the threshold value 1, it indicates that the stress monitoring value transmission is often unstable or contains noise. To address this condition, a floating parameter spacing value is calculated between each stress monitoring value cluster 2 and its corresponding stress monitoring value cluster. This spacing value is the spacing value 2 of stress monitoring value cluster 2. This spacing value 2 is calculated by comparing the stress monitoring value floating parameter 2 of each stress monitoring value cluster 2 with the stress monitoring value floating parameter 1 of its corresponding stress monitoring value cluster 2. After the calculated spacing value 2 of stress monitoring value cluster 2 is calculated, it is compared with a predefined threshold value 2. This threshold value 2 is determined based on actual application conditions and stress monitoring value attributes and is used to determine whether the floating parameter spacing value is permitted.

[0076] If the spacing value 2 of the stress monitoring value cluster 2 is higher than the critical value 2, it indicates that there is a significant difference between the stress monitoring value cluster 2 and the corresponding stress monitoring value cluster, which often indicates that the stress monitoring value transmission is disturbed by clutter and noise and contains noise values, so the stress monitoring value cluster 2 is registered as a noise value cluster; if the spacing value 2 of the stress monitoring value cluster 2 is not higher than the critical value 2, it indicates that the stress monitoring value cluster 2 and the corresponding stress monitoring value cluster maintain consistency and the stress monitoring value transmission process is very smooth, so the stress monitoring value cluster 2 is registered as a reasonable stress monitoring value cluster;

[0077] The noise value cluster and the valid stress monitoring value cluster are then sent out. The method for sending out the noise value cluster and the valid stress monitoring value cluster is as follows: first, a Kalman filter is used to denoise the stress monitoring values ​​within the noise value cluster. The denoised noise value cluster and the valid stress monitoring value cluster are arranged in the order of sampling time to form a cluster. The stress monitoring values ​​within the cluster are then transmitted to the display module of the data management and application platform in the order of sampling time for display. The stress monitoring values ​​within the cluster are the processed stress monitoring values ​​during the installation of the pipe truss. Based on the judgment information of the second spacing quantity, the data management and application platform sends out the noise value cluster and the valid stress monitoring value cluster.

[0078] In a preferred but non-limiting embodiment of the present invention, in step 5-3, the method for calculating the floating parameter spacing between each stress monitoring value cluster two and its corresponding stress monitoring value cluster is: calculating the absolute value of the amount obtained by subtracting the stress monitoring value floating parameter two of each stress monitoring value cluster two from the stress monitoring value floating parameter two of its corresponding stress monitoring value cluster one, and this absolute value is the spacing amount two of the stress monitoring value cluster two.

[0079] In a preferred but non-limiting embodiment of the present invention, in step 2, the method of obtaining stress monitoring value floating parameter 1 associated with stress monitoring value cluster 1 based on the floating condition pattern and stress monitoring value cluster 1 includes:

[0080] Step 2-1: Get the Stress monitoring value cluster ;

[0081] Step 2-2: Calculate based on the floating status mode The partial floating value of each stress monitoring value;

[0082] Step 2-3: Calculate based on the floating status mode The floating trend of

[0083] Step 2-4: Obtain according to the floating status model, segmented floating value and floating trend The stress monitoring value of the floating parameter is one.

[0084] In step 2-1, ; Similarly The second stress monitoring value cluster is , and Respectively characterize and The number of internal stress monitoring values, under normal conditions, , here, yes Neidi Stress monitoring value, is the serial number of the stress monitoring value, which can also represent the sampling time; similarly yes Neidi Stress monitoring value, It is the serial number of the stress monitoring value and can also represent the sampling time. Once the serial number or sampling time is identified, the actual stress monitoring value can be locked.

[0085] In step 2-2, the partial floating value is a measure of the floatingness of each stress monitoring value in the stress monitoring value cluster 1 compared with its previous stress monitoring value, that is, the difference between each digitized stress monitoring value and the entire stress monitoring value in the previous continuous sampling moment, to reflect the local floating status of the stress monitoring value cluster 1. It reflects the real-time floating amplitude of the stress monitoring value and is a key parameter for the floating status model operation.

[0086] In step 2-3, the floating trend is the overall change trend of the digital stress monitoring value cluster. The floating trend can indicate whether the stress monitoring value increases, decreases, or remains stable, which is of great significance for determining the trend change during the installation of the pipe truss.

[0087] In step 2-4, the partial floating value obtained by calculation in step 2-2 and the floating trend obtained by calculation in step 2-3 are integrated. The partial floating value reflects the floating amplitude of each stress monitoring value in the stress monitoring value cluster, and the floating trend represents the change direction and rate of the stress monitoring value as a whole. In short, the stress monitoring value floating parameter takes into account the partial floating value and the floating trend, and gives a digital value. Therefore, it can globally and efficiently reflect the floating attribute of the stress monitoring value, which is suitable for improving the recognition efficiency and function of the stress monitoring value. It can also use the calculated stress monitoring value floating parameter to improve the efficiency and function of the subsequent stress monitoring value processing.

[0088] In step 4, the stress monitoring value floating parameter 2 related to the stress monitoring value cluster 2 is obtained based on the floating state pattern and the stress monitoring value cluster 2. The steps here are also used to achieve processing to ensure the coordination of parameter formation.

[0089] In a preferred but non-limiting embodiment of the present invention, in step 2-2, the floating state mode is calculated The floating status pattern of the partial floating values ​​of each stress monitoring value is as follows: Here, yes Neidi The partial floating value of each stress monitoring value, yes Neidi Stress monitoring value, yes Neidi A stress monitoring value.

[0090] Here The equation is calculated by The amount obtained by subtracting a stress monitoring value from its previous stress monitoring value cluster is used to digitize the partial fluctuation of the stress monitoring value cluster. This method can ensure that the floating value of each stress monitoring value is based on the global evaluation of its previous stress monitoring value cluster, rather than relying solely on adjacent stress monitoring values, thereby more globally reflecting the partial fluctuation status of the stress monitoring value cluster.

[0091] In a preferred but non-limiting embodiment of the present invention, in step 2-3, the floating state mode is calculated The floating status pattern in the floating trend is: Here, yes The floating trend, yes Neidi Stress monitoring value, yes The average of all stress monitoring values ​​within yes The number of internal stress monitoring values.

[0092] In the floating state model here, by taking into account the difference between the stress monitoring value and its mean and the sequence number of the stress monitoring value in the stress monitoring value cluster, the The equation can effectively identify the floating trend of stress monitoring value cluster 1; by dividing the square sum of the distance from the same stress monitoring value to the center of stress monitoring value cluster 1, The equation dedimensionalizes the floating trend, making the floating trends between different stress monitoring value clusters comparable.

[0093] Sent accordingly It represents the average speed of stress monitoring value changing with time. If it is higher than zero, it indicates that the stress monitoring value increases with the delay of time; Below zero, indicating that the stress monitoring value decreases with the delay of time. The absolute value of represents the speed of change of stress monitoring value. The higher the absolute value of is, the higher the speed of change of the stress monitoring value is. The lower the absolute value of is, the lower the speed of change of the stress monitoring value is. The value above or below zero plus its absolute value together represent the direction and rhythm of the change of stress monitoring value.

[0094] In a preferred but non-limiting embodiment of the present invention, in steps 2-4, the floating status mode, the floating value of each part and the floating trend are obtained. The floating condition mode of the stress monitoring value floating parameter 1 is: Here, yes The stress monitoring value floating parameter is one, and is the weight factor. The value of can be seventy percent, The value can be thirty percent.

[0095] In this floating state model, a number of partial floating values ​​are integrated through the non-equal weighted average method to ensure that the model can obtain small changes in stress monitoring values ​​at different times or conditions, and the introduction of floating trend items takes into account the long-term trend of stress monitoring value fluctuations, making the model more global. and , can flexibly configure the ratio of partial floating and overall trend within the floating parameters according to actual conditions to meet different pipe truss installation requirements.

[0096] Then, the average of the floating parameters of each stress monitoring value cluster one is taken as the global floating parameter one.

[0097] In a preferred but non-limiting embodiment of the present invention, in step 1, the method of cutting the initial stress monitoring value queue into a plurality of stress monitoring value clusters includes:

[0098] The initial stress monitoring value queue is sequentially cut into a number of stress monitoring value clusters according to a predefined time period, or the initial stress monitoring value queue is sequentially cut into a number of stress monitoring value clusters corresponding to each period according to the periods of each process flow of the pipe truss installation.

[0099] In step 1, the method of dividing the initial stress monitoring value queue into a plurality of stress monitoring value clusters can be the above two types:

[0100] One type is to sequentially cut the initial stress monitoring value queue into several stress monitoring value clusters based on a pre-defined time length. The pre-defined time length is a constant time period size, such as 10ms, 20ms, etc., which is used to cut the initial stress monitoring value queue into stress monitoring value clusters of equal time period size. The goal of this type of cutting method is to align the stress monitoring values ​​at the same time, which is suitable for detecting the change rules of stress monitoring values ​​with time.

[0101] The other type is to cut the initial stress monitoring value queue into several stress monitoring value clusters in sequence according to the time of each process of pipe truss installation. The process is the main task during the installation of pipe truss, just like the process of assembly, welding, and hoisting during the installation of pipe truss. Such process often causes obvious changes in stress monitoring values, so taking the time occupied by it as the basis for cutting can more accurately reflect the actual situation of pipe truss installation.

[0102] like Figure 2 As shown, the stress monitoring value processing system during the installation of a pipe truss according to the present invention includes:

[0103] The vibrating wire strain sensor installed at the connection between the horizontal and vertical bars of the tube truss is connected to the intelligent wireless data acquisition terminal, and the intelligent wireless data acquisition terminal is wirelessly connected to the data management and application platform. During the installation of the tube truss, the vibrating wire strain sensor is used to transmit the sampled stress data of the connection between the horizontal and vertical bars of the tube truss to the intelligent wireless data acquisition terminal. The stress data of the connection between the horizontal and vertical bars of the tube truss is the stress monitoring value during the installation of the tube truss. The intelligent wireless data acquisition terminal is used to transmit the transmitted stress monitoring value during the installation of the tube truss to the data management and application platform for processing, and then transmit the processed stress monitoring value during the installation of the tube truss to the screen display module of the data management and application platform for display, thereby achieving the purpose of stress monitoring during the installation of the tube truss;

[0104] The system for processing stress monitoring values ​​during pipe truss installation also includes:

[0105] a cutting module, configured to arrange the sampling moments transmitted by the vibrating wire strain sensor in a sequential order to form a sampling moment queue, obtain an initial stress monitoring value queue transmitted by the vibrating wire strain sensor based on the sampling moment queue, and cut the initial stress monitoring value queue into a plurality of stress monitoring value clusters 1, wherein the stress monitoring value cluster 1 includes a plurality of stress monitoring values;

[0106] a parameter module 1 for obtaining a stress monitoring value floating parameter 1 related to the stress monitoring value cluster 1 according to a floating condition pattern and the stress monitoring value cluster 1, and obtaining a global floating parameter 1 according to a plurality of stress monitoring value floating parameters 1;

[0107] a transmission module, which is used for the intelligent wireless data acquisition terminal to transmit the plurality of stress monitoring value clusters 1 respectively to the data management and application platform, and transmit the global floating parameter 1 and the plurality of stress monitoring value floating parameters 1 to the data management and application platform, and the data management and application platform treats the received stress monitoring value cluster 1 as stress monitoring value cluster 2;

[0108] A parameter module 2 is used to obtain a stress monitoring value floating parameter 2 related to the stress monitoring value cluster 2 according to the floating condition pattern and the stress monitoring value cluster 2, and to obtain a global floating parameter 2 according to a plurality of stress monitoring value floating parameters 2;

[0109] The identification module is used to obtain stress monitoring value identification information according to the stress monitoring value floating parameter 1, the stress monitoring value floating parameter 2, the global floating parameter 1 and the global floating parameter 2.

[0110] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0111] Dividing the numerous and continuous initial stress monitoring values ​​into several smaller clusters of stress monitoring values ​​reduces the complexity of stress monitoring value processing and improves the flexibility of stress monitoring value transmission, allowing for more reliable transmission of stress monitoring values ​​under varying wireless communication conditions. By introducing a floating state mode, this method can capture and digitize the floating nature of stress monitoring values, creating favorable conditions for determining the accuracy and confidence of stress monitoring values. After the stress monitoring values ​​are transmitted to the data management and application platform, by comparing the floating parameters of the stress monitoring values ​​before and after transmission, it is possible to accurately determine whether the stress monitoring values ​​contain noise during transmission. Furthermore, the global floating parameters and the floating parameters of the stress monitoring value clusters are considered, providing a comprehensive assessment of the completeness and accuracy of the stress monitoring values. Therefore, the present invention not only improves the efficiency of stress monitoring value processing but also enhances the robustness and reliability of stress monitoring values, ensuring the accuracy, precision, and efficiency of stress monitoring values. Accurate stress monitoring values ​​during pipe truss installation can be displayed on the display module of the data management and application platform.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the specific implementation methods of the present invention can still be modified or replaced with equivalents, and any modifications or equivalent replacements that do not deviate from the spirit and scope of the present invention should be covered within the protection space of the claims of the present invention.

Claims

1. A method for processing stress monitoring values ​​during installation of a pipe truss, characterized in that: include: During the installation of the tube truss, the vibrating wire strain sensor transmits the sampled stress data of the connection between the horizontal and vertical bars of the tube truss to the intelligent wireless data acquisition terminal. The stress data of the connection between the horizontal and vertical bars of the tube truss is the stress monitoring value during the installation of the tube truss. The intelligent wireless data acquisition terminal transmits the transmitted stress monitoring value during the installation of the tube truss to the data management and application platform for processing, and then transmits the processed stress monitoring value during the installation of the tube truss to the screen display module of the data management and application platform for display; The method for processing stress monitoring values ​​during installation of a pipe truss by a data management and application platform includes: Step 1: The intelligent wireless data acquisition terminal arranges the sampling times transmitted by the vibrating wire strain sensor in order to form a sampling time queue, obtains the initial stress monitoring value queue transmitted by the vibrating wire strain sensor based on the sampling time queue, and divides the initial stress monitoring value queue into a plurality of stress monitoring value clusters 1, where each stress monitoring value cluster 1 includes a plurality of stress monitoring values; Step 2: Obtaining a stress monitoring value floating parameter 1 related to the stress monitoring value cluster 1 according to the floating state pattern and the stress monitoring value cluster 1, and obtaining a global floating parameter 1 according to a plurality of stress monitoring value floating parameters 1; After step 2, also include: Step 3: The intelligent wireless data acquisition terminal transmits the stress monitoring value clusters 1 to the data management and application platform, and transmits the global floating parameter 1 and the stress monitoring value floating parameters 1 to the data management and application platform. The data management and application platform treats the collected stress monitoring value cluster 1 as stress monitoring value cluster 2. Step 4: Obtain stress monitoring value floating parameter 2 related to stress monitoring value cluster 2 according to the floating status pattern and stress monitoring value cluster 2, and obtain global floating parameter 2 according to a plurality of stress monitoring value floating parameters 2; Step 5: Obtain stress monitoring value identification information according to stress monitoring value floating parameter 1, stress monitoring value floating parameter 2, global floating parameter 1, and global floating parameter 2.

2. The method for processing stress monitoring values ​​during installation of a pipe truss according to claim 1, characterized in that: In step 1, during the installation of the pipe truss, the vibrating wire strain sensor samples the stress monitoring value during the installation of the pipe truss and transmits the stress monitoring value and the sampling time to the intelligent wireless data acquisition terminal. The intelligent wireless data acquisition terminal arranges the sampling times transmitted by the vibrating wire strain sensor in order to form a sampling time queue. The intelligent wireless data acquisition terminal then arranges the stress monitoring values ​​corresponding to each sampling time according to the order of the sampling times in the sampling time queue, thereby forming a value queue arranged in order of the sampling times, that is, an initial stress monitoring value queue. The initial stress monitoring value queue is then divided into a plurality of stress monitoring value clusters 1, each of which contains a plurality of stress monitoring values ​​that are continuous at the sampling time.

3. The method for processing stress monitoring values ​​during installation of a pipe truss according to claim 2, characterized in that: Step 5 specifically includes: Step 5-1: Obtain spacing value 1 based on global floating parameter 1 and global floating parameter 2, and determine whether spacing value 1 exceeds threshold value 1; Step 5-2: If the value is not higher, the stress monitoring value identification information is "same" or "no change". Based on this, the plurality of stress monitoring value clusters are reconstructed according to the order of sampling time to form a stress monitoring value queue to be processed. The stress monitoring value queue to be processed is sent out. The stress monitoring values ​​in the stress monitoring value queue to be processed are the stress monitoring values ​​during the installation of the pipe truss after processing. Step 5-3: If it is higher, the stress monitoring value identification information is "different" or "changed", and the spacing value 2 is obtained based on the stress monitoring value floating parameter 1 and the stress monitoring value floating parameter 2 related to each stress monitoring value cluster 2. The stress monitoring value cluster 2 with the spacing value 2 higher than the critical value 2 is obtained and regarded as the noise value cluster, and the stress monitoring value cluster 2 with the spacing value 2 not higher than the critical value 2 is obtained and regarded as the reasonable stress monitoring value cluster, and the noise value cluster and the reasonable stress monitoring value cluster are sent out.

4. The method for processing stress monitoring values ​​during installation of a pipe truss according to claim 3, characterized in that: In step 5-1, the distance between global floating parameter 1 and global floating parameter 2 is calculated based on the previously calculated global floating parameter 1 and global floating parameter 2. This distance is called distance 1. In step 5-1, the method for calculating the distance between the global floating parameter 1 and the global floating parameter 2 is: calculating the absolute value of the difference between the global floating parameter 1 and the global floating parameter 2, and the absolute value is the distance between the global floating parameter 1 and the global floating parameter 2; In step 5-2, the received stress monitoring value clusters 2 are arranged in the order of sampling time, and the adjacent stress monitoring value clusters 2 are docked to reconstruct a complete stress monitoring value queue, i.e., the stress monitoring value queue to be processed. The stress monitoring value queue to be processed is then sent out. In step 5-3, the floating parameter spacing between each stress monitoring value cluster 2 and its corresponding stress monitoring value cluster is calculated. This spacing is referred to as spacing 2 for stress monitoring value cluster 2. After calculating spacing 2 for stress monitoring value cluster 2, it is compared with a predefined critical value 2. If the spacing value 2 of the stress monitoring value cluster 2 is higher than the critical value 2, the stress monitoring value cluster 2 is registered as a noise value cluster; If the spacing value 2 of the stress monitoring value cluster 2 is not higher than the critical value 2, the stress monitoring value cluster 2 is registered as a reasonable stress monitoring value cluster; Then, the noise value cluster and the reasonable stress monitoring value cluster are sent out. The method for sending out the noise value cluster and the reasonable stress monitoring value cluster is as follows: first, a Kalman filter is used to perform denoising processing on the stress monitoring values ​​in the noise value cluster. The noise value cluster and the reasonable stress monitoring value cluster after denoising are arranged in the order of sampling time to form a cluster. Then, the stress monitoring values ​​in the cluster are transmitted to the screen display module of the data management and application platform in the order of sampling time for display. The stress monitoring values ​​in the cluster are the stress monitoring values ​​during the installation of the pipe truss after processing. In step 5-3, the method for calculating the floating parameter spacing between each stress monitoring value cluster 2 and its corresponding stress monitoring value cluster is: calculating the absolute value of the amount obtained by subtracting the stress monitoring value floating parameter 2 of each stress monitoring value cluster 2 from the stress monitoring value floating parameter 2 of its corresponding stress monitoring value cluster 1, and this absolute value is the spacing amount 2 of the stress monitoring value cluster 2.

5. The method for processing stress monitoring values ​​during installation of a pipe truss according to claim 4, characterized in that: In step 2, the method of obtaining a stress monitoring value floating parameter 1 associated with the stress monitoring value cluster 1 according to the floating condition pattern and the stress monitoring value cluster 1 includes: Step 2-1: Get the Stress monitoring value cluster ; Step 2-2: Calculate based on the floating status mode The partial floating value of each stress monitoring value; Step 2-3: Calculate based on the floating status mode The floating trend of Step 2-4: Obtain according to the floating status model, segmented floating value and floating trend The stress monitoring value of the floating parameter is one.

6. The method for processing stress monitoring values ​​during installation of a pipe truss according to claim 5, characterized in that: In step 2-2, calculate according to the floating status mode The floating status pattern of the partial floating values ​​of each stress monitoring value is as follows: Here, yes Neidi The partial floating value of each stress monitoring value, yes Neidi Stress monitoring value, yes Neidi A stress monitoring value.

7. The method for processing stress monitoring values ​​during installation of a pipe truss according to claim 6, characterized in that: In steps 2-3, calculate according to the floating status model The floating status pattern in the floating trend is: Here, yes The floating trend, yes Neidi Stress monitoring value, yes The average of all stress monitoring values ​​within yes Number of internal stress monitoring values; In steps 2-4, according to the floating status model, the floating value of each part and the floating trend, The floating condition mode of the stress monitoring value floating parameter 1 is: Here, yes The stress monitoring value floating parameter is one, and is the weight factor.

8. A system for processing stress monitoring values ​​during installation of a pipe truss, characterized in that: include: The vibrating wire strain sensor installed at the connection between the horizontal and vertical bars of the tube truss is connected to the intelligent wireless data acquisition terminal, and the intelligent wireless data acquisition terminal is wirelessly connected to the data management and application platform. During the installation of the tube truss, the vibrating wire strain sensor is used to transmit the sampled stress data of the connection between the horizontal and vertical bars of the tube truss to the intelligent wireless data acquisition terminal. The stress data of the connection between the horizontal and vertical bars of the tube truss is the stress monitoring value during the installation of the tube truss. The intelligent wireless data acquisition terminal is used to transmit the transmitted stress monitoring value during the installation of the tube truss to the data management and application platform for processing, and then transmit the processed stress monitoring value during the installation of the tube truss to the screen display module of the data management and application platform for display; The system for processing stress monitoring values ​​during pipe truss installation also includes: a cutting module, configured to arrange the sampling moments transmitted by the vibrating wire strain sensor in a sequential order to form a sampling moment queue, obtain an initial stress monitoring value queue transmitted by the vibrating wire strain sensor based on the sampling moment queue, and cut the initial stress monitoring value queue into a plurality of stress monitoring value clusters 1, wherein the stress monitoring value cluster 1 includes a plurality of stress monitoring values; a parameter module 1 for obtaining a stress monitoring value floating parameter 1 related to the stress monitoring value cluster 1 according to a floating condition pattern and the stress monitoring value cluster 1, and obtaining a global floating parameter 1 according to a plurality of stress monitoring value floating parameters 1; The system for processing stress monitoring values ​​during pipe truss installation also includes: a transmission module, which is used for the intelligent wireless data acquisition terminal to transmit the plurality of stress monitoring value clusters 1 respectively to the data management and application platform, and transmit the global floating parameter 1 and the plurality of stress monitoring value floating parameters 1 to the data management and application platform, and the data management and application platform treats the received stress monitoring value cluster 1 as stress monitoring value cluster 2; A parameter module 2 is used to obtain a stress monitoring value floating parameter 2 related to the stress monitoring value cluster 2 according to the floating condition pattern and the stress monitoring value cluster 2, and to obtain a global floating parameter 2 according to a plurality of stress monitoring value floating parameters 2; The identification module is used to obtain stress monitoring value identification information according to the stress monitoring value floating parameter 1, the stress monitoring value floating parameter 2, the global floating parameter 1 and the global floating parameter 2.

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