Intelligent testing method and system for pressure resistance of pipe and pipe fitting

Abstract

The invention relates to the technical field of intelligent testing of pressure resistance, in particular to an intelligent testing method and system for the pressure resistance of a pipe and a pipe fitting, and the method comprises the steps: setting a target pressure value, generating a segmented pressure increment sequence and a corresponding segmented pressurization time sequence based on the target pressure value through employing an optimization algorithm, and obtaining a segmented pressurization rate sequence; performing segmented pressurization according to the segmented pressurization rate sequence, and constructing an adaptive rate adjustment function to adjust pressurization rates at different moments; collecting multi-source state data of the pipe and the pipe fitting in real time in the testing process, and performing comprehensive analysis to obtain a real-time comprehensive state index; establishing a multi-level early warning mechanism according to the real-time comprehensive state index, and performing real-time early warning and processing on the test process; and acquiring a comprehensive state index sequence of the whole test process, and evaluating the service life of the pipe and the pipe fitting based on the comprehensive state index sequence. According to the invention, accurate control of the intelligent test process of the pressure resistance performance can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent testing of pressure resistance performance, and particularly to an intelligent testing method and system for the pressure resistance performance of pipes and pipe fittings. Background Technique

[0002] With the rapid development of urban construction and the continuous improvement of residents' living standards, the pipe network systems for urban water supply and heating are becoming increasingly large and complex, and the requirements for the safety and reliability of the pipeline system are also continuously increasing. As the core components of the pipeline system, pipes and pipe fittings are directly related to the safe operation of the entire system. The pressure resistance performance test of pipes and pipe fittings is an important means to evaluate their safety and reliability. By simulating the pressure conditions under actual working conditions, a systematic pressure resistance performance evaluation of pipes and pipe fittings is carried out to provide technical support for their safe application. However, the current pressure resistance performance test methods still have limitations.

[0003] In the pressure loading link of the pressure resistance performance test process of pipes and pipe fittings, it is difficult for the existing test methods to achieve precise pressure control, and problems such as pressure mutation, overpressure or underpressure are likely to occur; in addition, the existing test methods usually only rely on pressure sensors to monitor the internal pressure changes of the pipeline, lacking real-time monitoring of multi-source data of pipes and pipe fittings, and unable to comprehensively reflect the state changes of pipes and pipe fittings during the test process, thereby affecting the control accuracy of the test process.

[0004] Therefore, an intelligent testing method and system for the pressure resistance performance of pipes and pipe fittings are proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent testing method and system for the pressure resistance performance of pipes and pipe fittings. First, by setting a target pressure value, a segmented pressure increment sequence, a corresponding segmented pressurization time sequence and a segmented pressurization rate sequence are generated based on the target pressure value by using an optimization algorithm; then, segmented pressurization is carried out according to the segmented pressurization rate sequence, and an adaptive rate adjustment function is constructed to adjust the pressurization rate at different times; multi-source state data of pipes and pipe fittings during the test process are collected in real time and comprehensively analyzed to obtain a real-time comprehensive state index; then, a multi-level early warning mechanism is established according to the real-time comprehensive state index to carry out real-time early warning and processing of the test process; finally, a comprehensive state index sequence of the entire test process is obtained, and the service life of pipes and pipe fittings is evaluated based on the comprehensive state index sequence.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An intelligent testing method for the pressure resistance performance of pipes and pipe fittings, comprising:

[0008] Set the target pressure value according to the specification information of the pipe and fitting to be tested and the maximum working pressure of the pipeline, and generate a segmented pressure increment sequence and a corresponding segmented pressurization time sequence based on the target pressure value by using an optimization algorithm;

[0009] Calculate the segmented pressurization rate sequence through the segmented pressure increment sequence and the segmented pressurization time sequence;

[0010] Seal the pipe and fitting to be tested and conduct a pressure resistance test. The test includes a pressurization stage and a pressure holding stage; the operations in the pressurization stage include: performing segmented pressurization according to the segmented pressurization rate sequence, and at the same time constructing an adaptive rate adjustment function to adjust the pressurization rate at different times. When the internal pressure reaches the target pressure value, stop pressurizing and enter the pressure holding stage; the operations in the pressure holding stage include: maintaining the internal pressure unchanged, and ending the test when the pressure holding time reaches the standard pressure holding time;

[0011] Collect multi-source status data of the pipe and fitting in real time during the test, and comprehensively analyze the multi-source status data in each time window to obtain the real-time comprehensive status index of the pipe and fitting; the multi-source status data includes pipe wall pressure data, pipe wall strain data, acoustic emission data, surface temperature data, wall thickness change data and leakage data;

[0012] Establish a first-level warning mechanism, a second-level warning mechanism and a third-level warning mechanism according to the real-time comprehensive status index to conduct real-time warning and processing on the test process;

[0013] When the test ends to obtain the comprehensive status index sequence of the entire test process, evaluate the service life of the pipe and fitting based on the comprehensive status index sequence.

[0014] Further, the pressure holding stage further includes: calculating the pressure loss value through continuous sampling, and performing pressure compensation when the pressure loss value exceeds the loss threshold.

[0015] Further, the steps of generating a segmented pressure increment sequence and a corresponding segmented pressurization time sequence based on the target pressure value by using an optimization algorithm are as follows:

[0016] Set n pressure levels according to the target pressure value, and define the segmented pressure increment sequence and the segmented pressurization time sequence with a length of n;

[0017] Construct an optimization objective function and optimization constraints, and use an optimization algorithm to generate a segmented pressure increment sequence and a segmented pressurization time sequence under the optimization constraints; the optimization constraints include target pressure value constraint, pressure increment constraint, pressurization time constraint and pressurization rate constraint.

[0018] Further, the steps of constructing an adaptive rate adjustment function to adjust the pressurization rate at different times are as follows:

[0019] During the stepwise pressure application at the i-th pressure level, samples are taken at fixed time intervals to obtain the target pressure increment and the actual pressure increment at the sampling moments.

[0020] Calculate the pressure increment deviation at the current sampling moment based on the target pressure increment and the actual pressure increment.

[0021] Construct an adaptive rate adjustment function based on the pressure increment deviation, with the formula:

[0022]

[0023] where v i (t s ) represents the pressure application rate at the s-th sampling moment t s ; Δt adj represents the length of the time interval; v i (t s -Δt adj ) represents the pressure application rate at the previous sampling moment; α and β represent adjustment coefficients; e(t s ) represents the pressure increment deviation at the s-th sampling moment; e(t j ) represents the pressure increment deviation at the j-th sampling moment during the period from the start of the current stepwise pressure application to the s-th sampling moment.

[0024] Adjust the pressure application rate at the current sampling moment in real time according to the adaptive rate adjustment function.

[0025] Furthermore, the steps for comprehensively analyzing the multi-source status data in each time window are as follows:

[0026] Perform noise reduction and smoothing processing on the multi-source status data.

[0027] Extract the statistical features of the multi-source status data within the current time window to obtain the initial status feature matrix; the statistical features include mean, standard deviation, peak value, valley value, and change rate.

[0028] Perform weighted fusion on all the initial status feature vectors in the initial status feature matrix to obtain the comprehensive status feature vector of the current time window.

[0029] Calculate the correlation coefficient between the comprehensive status feature vectors of the current time window and the previous time window.

[0030] Calculate the real-time comprehensive status index based on the comprehensive status feature vector and the correlation coefficient, with the formula:

[0031]

[0032] Among them, CSI(m) represents the real-time comprehensive status index of the m-th time window; w1, w1, and w3 represent weight coefficients; S(m) represents the comprehensive status feature vector of the m-th time window; R(m, m - 1) represents the correlation coefficient between the comprehensive status feature vectors of the m-th and (m - 1)-th time windows; ||S(m)||2 represents the Euclidean norm of S(m); CSI(m - 1) represents the real-time comprehensive status index of the (m - 1)-th time window; CSI(m - 2) represents the real-time comprehensive status index of the (m - 2)-th time window; Δt ana represents the time window length.

[0033] Furthermore, a first-level warning mechanism, a second-level warning mechanism, and a third-level warning mechanism are established based on the real-time comprehensive status index, and the steps for real-time warning and processing of the test process are as follows:

[0034] Set the comprehensive status index benchmark threshold, the first warning threshold λ1, and the second warning threshold λ2, where λ1 < λ2;

[0035] Calculate the deviation degree d between the real-time comprehensive status index and the comprehensive status index benchmark threshold;

[0036] When λ1 ≤ d ≤ λ2 and in the pressurization stage, trigger a first-level warning and adjust the target pressure value and the segmented pressurization rate at the subsequent pressure levels;

[0037] When λ1 ≤ d ≤ λ2 and in the pressure-holding stage, trigger a second-level warning and adjust the standard pressure-holding time;

[0038] When d > λ2, trigger a third-level warning, stop the test, and record the current data.

[0039] Furthermore, the steps for evaluating the service life of pipes and pipe fittings based on the comprehensive status index sequence are as follows: perform regression analysis on the comprehensive status index sequence to obtain a comprehensive status index equation related to time; set a comprehensive status index critical threshold, solve the comprehensive status index equation, and obtain the service life of pipes and pipe fittings.

[0040] An intelligent pressure resistance test system for pipes and pipe fittings includes:

[0041] A test parameter generation unit, which sets a target pressure value according to the specification information of the pipes and pipe fittings to be tested and the maximum working pressure of the pipeline, generates a segmented pressure increment sequence and a corresponding segmented pressurization time sequence based on the target pressure value using an optimization algorithm; calculates a segmented pressurization rate sequence through the segmented pressure increment sequence and the segmented pressurization time sequence;

[0042] The pressure resistance performance test unit seals the pipe and pipe fittings to be tested and conducts a pressure resistance performance test, which includes a pressurization stage and a pressure holding stage; the operations in the pressurization stage include: performing segmented pressurization according to the segmented pressurization rate sequence, and constructing an adaptive rate adjustment function to adjust the pressurization rate at different times. When the internal pressure reaches the target pressure value, stop pressurization and enter the pressure holding stage; the operations in the pressure holding stage include: maintaining the internal pressure unchanged, and ending the test when the pressure holding time reaches the standard pressure holding time;

[0043] The test data analysis unit collects multi-source status data of the pipe and pipe fittings during the test in real time, and comprehensively analyzes the multi-source status data in each time window to obtain the real-time comprehensive status index of the pipe and pipe fittings; the multi-source status data includes wall pressure data, wall strain data, acoustic emission data, surface temperature data, wall thickness change data, and leakage data;

[0044] The pressure resistance test warning unit establishes a first-level warning mechanism, a second-level warning mechanism, and a third-level warning mechanism based on the real-time comprehensive status index, and conducts real-time warning and processing on the test process;

[0045] The service life evaluation unit, when the test ends to obtain the comprehensive status index sequence of the entire test process, evaluates the service life of the pipe and pipe fittings based on the comprehensive status index sequence.

[0046] Further, the steps for the pressure resistance performance test unit to construct an adaptive rate adjustment function to adjust the pressurization rate at different times are as follows:

[0047] During the segmented pressurization process at the i-th pressure level, sample at a fixed time interval to obtain the target pressure increment and the actual pressure increment at the sampling moment;

[0048] Calculate the pressure increment deviation at the current sampling moment according to the target pressure increment and the actual pressure increment;

[0049] Construct an adaptive rate adjustment function based on the pressure increment deviation;

[0050] Adjust the pressurization rate at the current sampling moment in real time according to the adaptive rate adjustment function.

[0051] Further, the steps for the test data analysis unit to comprehensively analyze the multi-source status data in each time window are as follows:

[0052] Perform noise reduction and smoothing processing on the multi-source status data;

[0053] Extract the statistical features of the multi-source status data within the current time window to obtain the initial status feature matrix; the statistical features include mean, standard deviation, peak value, valley value, and change rate;

[0054] Fuse all the initial state feature vectors in the initial state feature matrix with weights to obtain the comprehensive state feature vector of the current time window;

[0055] Calculate the correlation coefficient between the comprehensive state feature vectors of the current time window and the previous time window;

[0056] Calculate the real-time comprehensive state index based on the comprehensive state feature vector and the correlation coefficient.

[0057] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0058] 1. The present invention first sets a target pressure value, and then generates a segmented pressure increment sequence and a pressurization time sequence through an optimization algorithm, which can ensure a stable and controllable pressurization process and avoid pressure mutations; during the pressurization process, an adaptive rate adjustment function is constructed to adjust the pressurization rate in real time, which can compensate for external interference and system errors in real time and improve the pressurization accuracy; timely pressure compensation is performed during the pressure holding stage, reducing the test error during the pressure holding stage and improving the test accuracy during the pressure holding stage; segmented pressurization, real-time adjustment of the pressurization rate, and pressure compensation provide a basic guarantee for realizing accurate control of the pressure resistance performance test.

[0059] 2. The present invention collects multi-source state data of the pipe during the test in real time, providing comprehensive state monitoring and avoiding the one-sidedness caused by single-dimensional data; by preprocessing, feature extraction, weighted fusion, and analysis and calculation of the multi-source state data to obtain a real-time comprehensive state index, noise interference can be effectively eliminated, data reliability can be improved, and at the same time, important features can be highlighted, enhancing the accuracy of the state evaluation of the pipe and fittings during the test, realizing all-round monitoring and evaluation of the pressure resistance performance test process of the pipe and fittings, and providing a data basis for accurately controlling the pressure resistance performance test process of the pipe and fittings.

[0060] 3. The present invention establishes a three-level early warning mechanism based on the real-time comprehensive state index, triggering different levels of responses through the deviation degree between the real-time comprehensive state index and the reference threshold, considering the overall performance of multi-source data and avoiding misjudgment that may be caused by single-parameter early warning; the progressive mechanism of the three-level early warning enables the system to take corresponding treatment measures according to the degree of abnormality, ensuring the continuity and safety of the test; the differential treatment after early warning triggering provides a more flexible abnormal treatment plan, reducing unnecessary test interruptions and improving the control accuracy of the intelligent test process of the pressure resistance performance of the pipe and fittings. Description of the Drawings

[0061] Figure 1 It is a schematic flow chart of an intelligent test method for the pressure resistance performance of pipes and fittings of the present invention;

[0062] Figure 2Schematic diagram of the intelligent testing process for the pressure resistance performance of the present invention;

[0063] Figure 3 Schematic diagram of the process for adjusting the pressure increasing rate of the present invention;

[0064] Figure 4 Schematic diagram of the structure of an intelligent testing system for the pressure resistance performance of a pipe and pipe fitting of the present invention. Detailed implementation manners

[0065] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0066] With the rapid development of urban construction and the continuous improvement of residents' living standards, the safety and reliability of the water heating pipeline system are becoming increasingly important. The pressure resistance performance of pipes and pipe fittings is directly related to the safe operation of the entire water supply and heating system. Traditional pressure testing methods are difficult to ensure the accuracy of control and lack the ability of multi-parameter real-time monitoring and dynamic adjustment. An intelligent testing method and system for the pressure resistance performance of pipes and pipe fittings proposed by the present invention can optimize the pressurization process, adjust the test parameters in real time, and provide accurate test results through comprehensive status monitoring, providing important technical support for the quality control of the water heating pipeline system; the present invention will be described through the following embodiments.

[0067] Embodiment 1

[0068] In the water supply pipe renovation project of a certain residential community, it is necessary to test the pressure resistance performance of the water supply pipes. Now, a section of pipe is selected as the test object, and an intelligent testing method for the pressure resistance performance of a pipe and pipe fitting of the present invention is adopted. The specific process is as follows Figure 1 , including:

[0069] Set the target pressure value according to the specification information of the pipe and pipe fitting to be tested and the maximum working pressure of the pipeline, and generate a segmented pressure increment sequence and the corresponding segmented pressurization time sequence based on the target pressure value by using an optimization algorithm;

[0070] Calculate the segmented pressurization rate sequence through the segmented pressure increment sequence and the segmented pressurization time sequence;

[0071] Seal the pipe and pipe fitting to be tested and conduct the pressure resistance performance test. The test includes a pressurization stage and a pressure holding stage. The specific process is as follows Figure 2; The operations in the pressurization stage include: performing segmented pressurization according to the segmented pressurization rate sequence, and simultaneously constructing an adaptive rate adjustment function to adjust the pressurization rate at different times. When the internal pressure reaches the target pressure value, stop pressurization and enter the pressure holding stage; The operations in the pressure holding stage include: maintaining the internal pressure unchanged, and ending the test when the pressure holding time reaches the standard pressure holding time;

[0072] Collect multi-source status data of the pipe and fittings in real time during the test, and comprehensively analyze the multi-source status data in each time window to obtain the real-time comprehensive status index of the pipe and fittings; The multi-source status data includes wall pressure data, wall strain data, acoustic emission data, surface temperature data, wall thickness change data, and leakage data;

[0073] Establish a first-level warning mechanism, a second-level warning mechanism, and a third-level warning mechanism according to the real-time comprehensive status index, and perform real-time warning and processing on the test process;

[0074] When the test ends, obtain the comprehensive status index sequence of the entire test process, and evaluate the service life of the pipe and fittings based on the comprehensive status index sequence.

[0075] Further, the pressure holding stage further includes: calculating the pressure loss value through continuous sampling, and performing pressure compensation when the pressure loss value exceeds the loss threshold.

[0076] In the pressure holding stage, calculating the pressure loss value through continuous sampling and performing pressure compensation improves the test accuracy and pressure holding stability, effectively prevents test errors caused by pressure loss, and makes the test results more reliable.

[0077] Further, the steps of generating a segmented pressure increment sequence and a corresponding segmented pressurization time sequence based on the target pressure value using an optimization algorithm are:

[0078] Set n pressure levels according to the target pressure value, and define the segmented pressure increment sequence and the segmented pressurization time sequence with a length of n;

[0079] Construct an optimization objective function and optimization constraint conditions, and use an optimization algorithm to generate a segmented pressure increment sequence and a segmented pressurization time sequence under the optimization constraint conditions; The optimization constraint conditions include target pressure value constraint, pressure increment constraint, pressurization time constraint, and pressurization rate constraint.

[0080] Using an optimization algorithm to generate a segmented pressure increment sequence and a segmented pressurization time sequence optimizes the pressure change path in the test process, improves the test efficiency and accuracy, ensures the smoothness of the pressurization process, and reduces the risk of pressure mutation.

[0081] The maximum working pressure of the water supply pipe in this residential area is 0.8MPa, and the target pressure value is set to 1.0MPa. Five pressure levels are used for segmented pressurization, and the generated segmented pressure increment sequence, segmented pressurization time sequence and corresponding segmented pressurization rate sequence are shown in Table 1.

[0082] Table 1 Pressure resistance test parameters

[0083]

[0084] Further, see Figure 3 , the steps to construct an adaptive rate adjustment function to adjust the pressure rate at different times are:

[0085] During the staged pressurization process of the i-th pressure level, sampling is performed at fixed time intervals to obtain the target pressure increment and the actual pressure increment at the sampling moment;

[0086] Calculating the pressure increment deviation at the current sampling moment according to the target pressure increment and the actual pressure increment;

[0087] An adaptive rate adjustment function is constructed based on the pressure increment deviation, and the formula is:

[0088]

[0089] Among them, v i (t s ) represents the sth sampling time t s The pressurization rate; Δt adj Indicates the length of the time interval; v i (t s -Δt adj ) represents the pressure increase rate at the last sampling moment; α and β represent the adjustment coefficients; e(t s ) represents the pressure increment deviation at the sth sampling moment; e(t j ) represents the pressure increment deviation at the jth sampling moment during the period from the start of the current segmented pressurization process to the sth sampling moment;

[0090] The pressurization rate at the current sampling moment is adjusted in real time according to the adaptive rate adjustment function.

[0091] Furthermore, the target pressure increment is calculated as: Δp i =v i ·Δt adj ; where Δp i represents the target pressure increment at each sampling moment during the pressurization process of the i-th pressure level; v i represents the i-th segmented pressurization rate in the segmented pressurization rate sequence; Δt adj Indicates the length of the time interval;

[0092] The calculation formula for the pressure increment deviation is: e(t s ) = Δp i - Δp i ′(t s ); where, Δp i ′(t s ) represents the actual pressure increment at the sampling time t s during the pressurization process of the i-th pressure level.

[0093] Constructing an adaptive rate adjustment function based on the pressure increment deviation to adjust the pressurization rate in real time can achieve precise pressure control, avoid overshoot and instability phenomena that may occur in traditional methods, and improve the accuracy, stability, and safety of the pressurization process.

[0094] Taking the segmented pressurization process of the second pressure level as an example, the time interval is set to 0.5 min. The specific data for adjusting the pressurization rate at different times through the adaptive rate adjustment function are shown in Table 2.

[0095] Table 2 Pressurization Rate Adjustment Data

[0096]

[0097] Furthermore, the steps for comprehensively analyzing the multi-source status data in each time window are as follows:

[0098] Perform noise reduction and smoothing processing on the multi-source status data;

[0099] Extract the statistical features of the multi-source status data within the current time window to obtain the initial status feature matrix; the statistical features include mean, standard deviation, peak value, valley value, and change rate;

[0100] Perform weighted fusion on all the initial status feature vectors in the initial status feature matrix to obtain the comprehensive status feature vector of the current time window;

[0101] Calculate the correlation coefficient between the comprehensive status feature vectors of the current time window and the previous time window;

[0102] Calculate the real-time comprehensive status index according to the comprehensive status feature vector and the correlation coefficient. The formula is:

[0103]

[0104] Among them, CSI(m) represents the real-time comprehensive status index of the m-th time window; w1, w1, and w3 represent weight coefficients; S(m) represents the comprehensive status feature vector of the m-th time window; R(m, m - 1) represents the correlation coefficient between the comprehensive status feature vectors of the m-th and the (m - 1)-th time windows; ||S(m)||2 represents the Euclidean norm of S(m); CSI(m - 1) represents the real-time comprehensive status index of the (m - 1)-th time window; CSI(m - 2) represents the real-time comprehensive status index of the (m - 2)-th time window; Δt ana represents the time window length; S(m - 1) represents the comprehensive status feature vector of the (m - 1)-th time window; Cov(S(m), S(m - 1)) represents the covariance of S(m) and S(m - 1); σ(S(m)) and σ(S(m - 1)) represent the standard deviations of S(m) and S(m - 1) respectively.

[0105] By denoising, feature extraction, and weighted fusion of multi-source status data, and considering the correlation between time windows, a comprehensive and accurate assessment of the pipe state is achieved, improving the reliability and accuracy of the state monitoring of pipes and fittings during the test process; the performance state of pipes and fittings is comprehensively reflected by the real-time comprehensive status index, providing a reliable basis for the subsequent early warning mechanism.

[0106] Furthermore, a first-level early warning mechanism, a second-level early warning mechanism, and a third-level early warning mechanism are established according to the real-time comprehensive status index. The steps for real-time early warning and processing of the test process are as follows:

[0107] Set the comprehensive status index baseline threshold, the first warning threshold λ1, and the second warning threshold λ2, where λ1 < λ2;

[0108] Calculate the deviation d of the real-time comprehensive status index CSI(m) from the comprehensive status index baseline threshold CSI0, d = (CSI(m) - CSI0) / CSI0;

[0109] When λ1 ≤ d ≤ λ2 and in the pressurization stage, trigger a first-level early warning and adjust the target pressure value and the segmented pressurization rate at the subsequent pressure levels;

[0110] When λ1 ≤ d ≤ λ2 and in the pressure holding stage, trigger a second-level early warning and adjust the standard pressure holding time;

[0111] When d > λ2, trigger a third-level early warning, stop the test, and record the current data.

[0112] When λ1 ≤ d ≤ λ2, it indicates that there is a slight abnormal state of the pipe during the test. The specific adjustment operation during the pressurization stage is to reduce the target pressure value and the sectional pressurization rate at subsequent pressure levels to avoid excessive pressure impact on the pipe and fittings, which may lead to a decrease in the accuracy of the test results. The specific adjustment operation during the pressure holding stage is to extend the pressure holding time to further observe the performance of the pipe. When d > λ2, it indicates that there is a serious abnormal state of the pipe during the test. The specific operation is to stop the pressurization or pressure holding operation, unload the pressure, and record the current test data for subsequent analysis.

[0113] By establishing a three - level early warning mechanism based on the comprehensive state index, real - time processing of abnormal situations during the test is carried out, significantly improving the test safety and reliability, ensuring that rapid responses and measures can be taken in case of abnormalities, and avoiding uncontrollable risks during the test.

[0114] Furthermore, the steps for evaluating the service life of pipes and fittings based on the comprehensive state index sequence are as follows: performing regression analysis on the comprehensive state index sequence to obtain a time - related comprehensive state index equation; setting a critical threshold for the comprehensive state index, and solving the comprehensive state index equation to obtain the service life of pipes and fittings.

[0115] Based on the comprehensive state index sequence, a comprehensive state index equation is obtained through regression analysis to evaluate the service life of pipes and fittings. By using a scientific mathematical model to accurately evaluate the service life of pipes and fittings, the empirical errors in traditional methods are reduced.

[0116] The present invention relates to an intelligent test method for the pressure resistance performance of pipes and fittings. By optimizing the algorithm to generate a sectional pressurization sequence and combining with an adaptive pressurization rate adjustment, precise control of the pressure resistance test process is achieved; through real - time acquisition and comprehensive analysis of multi - source state data, all - round state monitoring of the test process is realized; based on the comprehensive state index, a multi - level early warning mechanism is established to ensure the safety and precise control of the test process; by analyzing the state index sequence of the entire test process, scientific evaluation of the service life of pipes is realized.

[0117] Embodiment Two

[0118] In Embodiment One, an intelligent test method for the pressure resistance performance of pipes and fittings is used to realize the intelligent test of the pressure resistance performance of pipes. In this embodiment, an intelligent test system for the pressure resistance performance of pipes and fittings is used to realize an intelligent test method for the pressure resistance performance of pipes and fittings. The system structure is shown in Figure 4 , including:

[0119] A test parameter generation unit sets a target pressure value according to the specification information of the pipe and fittings to be tested and the maximum working pressure of the pipeline, and generates a segmented pressure increment sequence and a corresponding segmented pressurization time sequence based on the target pressure value by using an optimization algorithm; calculates a segmented pressurization rate sequence through the segmented pressure increment sequence and the segmented pressurization time sequence;

[0120] A pressure resistance performance test unit seals the pipe and fittings to be tested and conducts a pressure resistance performance test, and the test includes a pressurization stage and a pressure holding stage; the operations in the pressurization stage include: performing segmented pressurization according to the segmented pressurization rate sequence, and simultaneously constructing an adaptive rate adjustment function to adjust the pressurization rate at different times, and stopping pressurization when the internal pressure reaches the target pressure value and entering the pressure holding stage; the operations in the pressure holding stage include: maintaining the internal pressure unchanged and ending the test when the pressure holding time reaches the standard pressure holding time;

[0121] A test data analysis unit collects multi-source status data of the pipe and fittings during the test in real time, and comprehensively analyzes the multi-source status data in each time window to obtain a real-time comprehensive status index of the pipe and fittings; the multi-source status data includes pipe wall pressure data, pipe wall strain data, acoustic emission data, surface temperature data, wall thickness change data and leakage data;

[0122] A pressure resistance test warning unit establishes a first-level warning mechanism, a second-level warning mechanism and a third-level warning mechanism according to the real-time comprehensive status index, and conducts real-time warning and processing on the test process;

[0123] A service life evaluation unit, when the test ends to obtain a comprehensive status index sequence of the whole test process, evaluates the service life of the pipe and fittings based on the comprehensive status index sequence.

[0124] Further, the steps for the pressure resistance performance test unit to construct an adaptive rate adjustment function to adjust the pressurization rate at different times are as follows:

[0125] During the segmented pressurization process of the i-th pressure level, sampling is performed at fixed time intervals to obtain the target pressure increment and the actual pressure increment at the sampling moment;

[0126] Calculate the pressure increment deviation at the current sampling moment according to the target pressure increment and the actual pressure increment;

[0127] Construct an adaptive rate adjustment function based on the pressure increment deviation;

[0128] Adjust the pressurization rate at the current sampling moment in real time according to the adaptive rate adjustment function.

[0129] Further, the steps for the test data analysis unit to comprehensively analyze the multi-source status data in each time window are as follows:

[0130] Perform noise reduction and smoothing processing on the multi-source status data;

[0131] Extract the statistical features of the multi-source status data within the current time window to obtain an initial status feature matrix; the statistical features include mean, standard deviation, peak value, valley value, and change rate;

[0132] Perform weighted fusion on all the initial status feature vectors in the initial status feature matrix to obtain a comprehensive status feature vector for the current time window;

[0133] Calculate the correlation coefficient between the comprehensive status feature vectors of the current time window and the previous time window;

[0134] Calculate the real-time comprehensive status index based on the comprehensive status feature vector and the correlation coefficient. Some calculation data of the real-time comprehensive status index during the pressure resistance performance test are shown in Table 3. The comprehensive status index shows a slow upward trend over time. By monitoring the comprehensive status index through the pressure resistance test warning unit, the control accuracy of the test process can be effectively improved.

[0135] Table 3 Example of calculation data of the real-time comprehensive status index

[0136] Time window (min) Norm of state feature vector Correlation coefficient Real-time comprehensive state index 4～6 0.412 0.986 0.406 6～8 0.458 0.975 0.447 8～10 0.482 0.968 0.467 12～14 0.495 0.962 0.476 14～16 0.503 0.958 0.482

[0137] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent test method for the pressure resistance of pipes and pipe fittings, characterized in that: include: The target pressure value is set according to the specification information of the pipe and pipe fittings to be tested and the maximum working pressure of the pipeline, and the segmented pressure increment sequence and the corresponding segmented pressurization time sequence are generated by using an optimization algorithm based on the target pressure value; Calculating a segmented pressurization rate sequence through the segmented pressure increment sequence and the segmented pressurization time sequence; After the pipes and fittings to be tested are sealed, a pressure resistance test is performed, and the test includes a pressurization stage and a pressure holding stage; the operation of the pressurization stage includes: performing segmented pressurization according to the segmented pressurization rate sequence, and constructing an adaptive rate adjustment function to adjust the pressurization rate at different times, and stopping pressurization when the internal pressure reaches the target pressure value, and entering the pressure holding stage; the operation of the pressure holding stage includes: maintaining the internal pressure unchanged, and ending the test when the pressure holding time reaches the standard pressure holding time; Real-time collection of multi-source status data of pipes and fittings during the test process, comprehensive analysis of the multi-source status data in each time window, and obtaining real-time comprehensive status indexes of pipes and fittings; the multi-source status data includes pipe wall pressure data, pipe wall strain data, acoustic emission data, surface temperature data, wall thickness change data and leakage data; Establishing a first-level early warning mechanism, a second-level early warning mechanism and a third-level early warning mechanism according to the real-time comprehensive status index to provide real-time early warning and processing for the test process; When the test is finished, a comprehensive state index sequence of the entire test process is obtained, and the service life of the pipes and fittings is evaluated based on the comprehensive state index sequence.

2. According to claim 1, a method for intelligently testing the pressure resistance of pipes and pipe fittings is characterized in that: The pressure maintaining stage also includes: calculating a pressure loss value through continuous sampling, and performing pressure compensation when the pressure loss value exceeds a loss threshold.

3. The intelligent test method for the pressure resistance of pipes and pipe fittings according to claim 1 is characterized in that: The steps of using an optimization algorithm to generate a segmented pressure increment sequence and a corresponding segmented pressurization time sequence based on the target pressure value are as follows: Setting n pressure levels according to the target pressure value, defining the segmented pressure increment sequence and the segmented pressurization time sequence with a length of n; An optimization objective function and optimization constraints are constructed, and an optimization algorithm is used to generate a segmented pressure increment sequence and a segmented pressurization time sequence under the optimization constraints; the optimization constraints include a target pressure value constraint, a pressure increment constraint, a pressurization time constraint, and a pressurization rate constraint.

4. The intelligent test method for the pressure resistance of pipes and pipe fittings according to claim 1 is characterized in that: The steps to construct an adaptive rate adjustment function to adjust the pressure rate at different times are: During the staged pressurization process of the i-th pressure level, sampling is performed at fixed time intervals to obtain the target pressure increment and the actual pressure increment at the sampling moment; Calculating the pressure increment deviation at the current sampling moment according to the target pressure increment and the actual pressure increment; An adaptive rate adjustment function is constructed based on the pressure increment deviation, and the formula is: Among them, v i (t s ) represents the sth sampling time t s The pressurization rate; Δt adj Indicates the length of the time interval; v i (t s -Δt adj ) represents the pressure increase rate at the last sampling moment; α and β represent the adjustment coefficients; e(t s ) represents the pressure increment deviation at the sth sampling moment; e(t j ) represents the pressure increment deviation at the jth sampling moment during the period from the start of the current segmented pressurization process to the sth sampling moment; The pressurization rate at the current sampling moment is adjusted in real time according to the adaptive rate adjustment function.

5. The intelligent test method for the pressure resistance of pipes and pipe fittings according to claim 1 is characterized in that: The steps of comprehensively analyzing the multi-source status data in each time window are as follows: Performing noise reduction and smoothing processing on the multi-source state data; Extracting statistical features of the multi-source state data in the current time window to obtain an initial state feature matrix; the statistical features include mean, standard deviation, peak value, valley value and change rate; Performing weighted fusion on all initial state feature vectors in the initial state feature matrix to obtain a comprehensive state feature vector of the current time window; Calculating the correlation coefficient between the comprehensive state feature vectors of the current time window and the previous time window; The real-time comprehensive state index is calculated according to the comprehensive state feature vector and the correlation coefficient, and the formula is: Wherein, CSI(m) represents the real-time comprehensive state index of the m-th time window; w1, w2 and w3 represent weight coefficients; S(m) represents the comprehensive state feature vector of the m-th time window; R(m,m-1) represents the correlation coefficient between the comprehensive state feature vectors of the m-th and m-1-th time windows; ||S(m)||2 represents the Euclidean norm of S(m); CSI(m-1) represents the real-time comprehensive state index of the m-1-th time window; CSI(m-2) represents the real-time comprehensive state index of the m-2-th time window; Δt ana Indicates the length of the time window.

6. The intelligent test method for the pressure resistance of pipes and pipe fittings according to claim 1 is characterized in that: According to the real-time comprehensive status index, a first-level early warning mechanism, a second-level early warning mechanism and a third-level early warning mechanism are established to provide real-time early warning and processing steps for the test process: Set a comprehensive status index benchmark threshold, a first warning threshold λ1, and a second warning threshold λ2, where λ1<λ2; Calculating the deviation d between the real-time comprehensive status index and the comprehensive status index reference threshold; When λ1≤d≤λ2 and in the pressurization stage, a first-level warning is triggered, and the target pressure value and the staged pressurization rate under the subsequent pressure levels are adjusted; When λ1≤d≤λ2 and in the pressure holding stage, a second-level warning is triggered and the standard pressure holding time is adjusted; When d>λ2, the third level warning is triggered, the test is stopped and the current data is recorded.

7. The intelligent test method for the pressure resistance of pipes and pipe fittings according to claim 1 is characterized in that: The steps of evaluating the service life of pipes and fittings based on the comprehensive state index sequence are: performing regression analysis on the comprehensive state index sequence to obtain a time-dependent comprehensive state index equation; A critical threshold value of the comprehensive state index is set, and the comprehensive state index equation is solved to obtain the service life of the pipes and fittings.

8. An intelligent testing system for the pressure resistance of pipes and pipe fittings, characterized in that: include: The test parameter generation unit sets a target pressure value according to the specification information of the pipe and pipe fittings to be tested and the maximum working pressure of the pipeline, and generates a segmented pressure increment sequence and a corresponding segmented pressurization time sequence based on the target pressure value by using an optimization algorithm; and calculates a segmented pressurization rate sequence through the segmented pressure increment sequence and the segmented pressurization time sequence; The pressure resistance performance test unit is used to perform pressure resistance performance test on the pipes and fittings to be tested after sealing. The test includes a pressurization stage and a pressure holding stage. The operation of the pressurization stage includes: performing segmented pressurization according to the segmented pressurization rate sequence, and constructing an adaptive rate adjustment function to adjust the pressurization rate at different times. When the internal pressure reaches the target pressure value, the pressurization is stopped and the pressure holding stage is entered. The operation of the pressure holding stage includes: maintaining the internal pressure unchanged, and ending the test when the pressure holding time reaches the standard pressure holding time. The test data analysis unit collects multi-source status data of pipes and fittings in real time during the test process, and performs comprehensive analysis on the multi-source status data in each time window to obtain a real-time comprehensive status index of pipes and fittings; the multi-source status data includes pipe wall pressure data, pipe wall strain data, acoustic emission data, surface temperature data, wall thickness change data and leakage data; The withstand voltage test early warning unit establishes a first-level early warning mechanism, a second-level early warning mechanism and a third-level early warning mechanism according to the real-time comprehensive status index, and performs real-time early warning and processing on the test process; The service life evaluation unit obtains a comprehensive state index sequence of the entire test process when the test is completed, and evaluates the service life of the pipes and pipe fittings based on the comprehensive state index sequence.

9. The intelligent pressure resistance testing system for pipes and pipe fittings according to claim 8 is characterized in that: The pressure resistance performance test unit constructs an adaptive rate adjustment function to adjust the pressurization rate at different times in the following steps: During the staged pressurization process of the i-th pressure level, sampling is performed at fixed time intervals to obtain the target pressure increment and the actual pressure increment at the sampling moment; Calculating the pressure increment deviation at the current sampling moment according to the target pressure increment and the actual pressure increment; constructing an adaptive rate adjustment function based on the pressure increment deviation; The pressurization rate at the current sampling moment is adjusted in real time according to the adaptive rate adjustment function.

10. The intelligent pressure resistance testing system for pipes and pipe fittings according to claim 8, characterized in that: The test data analysis unit performs comprehensive analysis on the multi-source status data in each time window in the following steps: Performing noise reduction and smoothing processing on the multi-source state data; Extracting statistical features of the multi-source state data in the current time window to obtain an initial state feature matrix; the statistical features include mean, standard deviation, peak value, valley value and change rate; Performing weighted fusion on all initial state feature vectors in the initial state feature matrix to obtain a comprehensive state feature vector of the current time window; Calculating the correlation coefficient between the comprehensive state feature vectors of the current time window and the previous time window; The real-time comprehensive state index is calculated according to the comprehensive state feature vector and the correlation coefficient.

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