Pipeline safety early warning method and system based on stress detection

Abstract

The invention relates to the technical field of stress detection, in particular to a pipeline safety early warning method and system based on stress detection, and the method comprises the steps: obtaining an intensity distribution sequence of a pipeline in a current sampling time period, and determining an intensity correlation coefficient of the pipeline based on the intensity values of M intensity sequences, if it is determined that the strength correlation coefficient exceeds a preset strength correlation threshold value, pipeline safety early warning is conducted; otherwise, determining the amplitude fluctuation value of the detection point based on N intensity values in the intensity sequence of the detection point, and determining the intensity balance degree of the pipeline based on the amplitude fluctuation values of M detection points; determining a damage index of the pipeline based on the intensity distribution sequence, and obtaining a corrected damage prediction value based on the damage index and the intensity balance degree; obtaining a damage threshold interval which is predicted to be constructed, and if it is determined that the corrected damage prediction value exceeds the maximum value of the damage threshold interval, carrying out pipeline safety early warning; the pipeline safety early warning system can realize pipeline safety early warning.

Description

Technical Field

[0001] The present invention relates to the technical field of stress detection, and in particular to a pipeline safety early warning method and system based on stress detection. Background Art

[0002] At present, chemical enterprises commonly use technical means to detect pipeline leakage, including applying soapy water, installing fixed gas detectors, and handheld ultrasonic leak detectors. Due to the concealment of pipeline leakage, the current troubleshooting methods may have been in place for a period of time when the leakage is discovered. This situation will have an adverse impact on economic costs, personnel safety, and environmental protection. These methods are inefficient and difficult to operate, and at night, in an environment with poor visibility, it is even more difficult to implement leak detection.

[0003] During the operation of large units, the supporting structure and inlet and outlet pipeline systems of the units are always under stress, especially for reciprocating compressors. If the threaded fasteners in these parts are loose and not handled in time, and the displacement of the supporting structure is not discovered in time, serious problems such as machine tripping will occur. Therefore, it is necessary to monitor the excessive deformation state of the threaded fasteners, realize pipeline safety early warning, and improve the ability to predict the safe operation of the unit. Summary of the invention

[0004] The present invention aims to provide a pipeline safety early warning method and system based on stress detection, which performs data analysis on the stress detected by the stress sensor to achieve pipeline safety early warning and improve the predictive ability of safety early warning.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present invention provides a pipeline safety early warning method based on stress detection, the method comprising the following steps:

[0007] S100, obtaining an intensity distribution sequence of the pipeline in the current sampling time period, the intensity distribution sequence comprising an intensity sequence of M detection points; wherein the intensity sequence comprises N intensity values, N being the total number of sampling time points in the sampling time period; the M detection points are cocircular and evenly arranged on the flange plate of the end face of the pipeline; the intensity distribution sequence is obtained by sampling after performing photoelectric conversion on a detection light signal, and the detection light signal is obtained by performing stress detection on the M detection points using a stress sensor;

[0008] S200, determining a strength correlation coefficient of the pipeline based on the strength values ​​of the M strength sequences, and if it is determined that the strength correlation coefficient exceeds a preset strength correlation threshold, issuing a pipeline safety warning;

[0009] S300, if it is determined that the strength correlation coefficient does not exceed the preset strength correlation threshold, determining the amplitude fluctuation value of the detection point based on N strength values ​​in the strength sequence of the detection point, and determining the strength balance of the pipeline based on the amplitude fluctuation values ​​of the M detection points;

[0010] S400, determining a damage index of the pipeline based on the strength distribution sequence, and obtaining a corrected damage prediction value based on the damage index and the strength balance;

[0011] S500, obtaining the estimated damage threshold interval, and if it is determined that the corrected damage prediction value exceeds the maximum value of the damage threshold interval, a pipeline safety warning is issued.

[0012] Optionally, in S200, determining the strength correlation coefficient of the pipeline based on the strength values ​​of the M strength sequences includes:

[0013] S210, grouping the M intensity sequences into two, calculating the Hausdorff distance between the two intensity sequences in each group, and obtaining a plurality of intensity difference values;

[0014] S220, after one-to-one correspondence between the N intensity values ​​of the two intensity sequences in each group according to the sampling time points, calculate the mutual correlation coefficient between the two intensity sequences;

[0015] S230, calculating the intensity difference and the mutual correlation coefficient of the two intensity sequences in each group to obtain a plurality of correlation coefficients, and taking the correlation coefficient with the largest value as the intensity correlation coefficient of the pipeline.

[0016] Optionally, in S300, determining the amplitude fluctuation value of the detection point based on N intensity values ​​in the intensity sequence of the detection point, and determining the intensity balance of the pipeline based on the amplitude fluctuation values ​​of the M detection points, includes:

[0017] S310, obtaining N intensity values ​​in an intensity sequence of M detection points;

[0018] S320: For each detection point, the amplitude fluctuation value of the detection point is calculated by the following formula:

[0019]

[0020] Among them, Af j is the amplitude fluctuation value of the jth detection point, Ap j is the intensity value of the intensity sequence of the jth detection point at the peak, At j is the intensity value of the intensity sequence of the jth detection point at the trough, A ij Aavg is the intensity value of the jth detection point at the i-th sampling time point, jis the intensity mean of the jth detection point, normal represents linear normalization, the amplitude fluctuation value range is [0, 1], i = 1, 2, ..., N, j = 1, 2, ..., M;

[0021] S330, the strength balance of the pipeline is calculated by the following formula:

[0022] Bd=max(Af j ) / min(Af j )

[0023] Among them, Bd is the strength balance of the pipeline, max(Af j ) is the maximum value of the amplitude fluctuation value of M detection points, min(Af j ) is the minimum value of the amplitude fluctuation values ​​of the M detection points.

[0024] Optionally, in S400, determining the damage index of the pipeline based on the strength distribution sequence, and obtaining a corrected damage prediction value based on the damage index and the strength balance degree, includes:

[0025] S410, obtaining an intensity distribution sequence of a current sampling time period, and normalizing the amplitude of each sampling time point in the intensity distribution sequence to obtain a normalized amplitude of each sampling time point;

[0026] S420, obtaining the total number of peaks in the intensity sequence of each detection point and the reference amplitude of the pipeline, and determining the damage index of the pipeline based on the normalized amplitude at each sampling time point, the total number of peaks in the intensity sequence of each detection point and the reference amplitude of the pipeline; wherein the reference amplitude of the pipeline represents the critical amplitude when the pipeline is damaged;

[0027] S430, multiplying the damage index and the strength balance of the pipeline to obtain a corrected damage prediction value.

[0028] Optionally, the damage index of the pipeline is calculated by the following formula:

[0029]

[0030] Where Da is the damage index of the pipeline, Af ij is the normalized amplitude of the jth detection point at the i-th sampling time point, Afavg is the reference amplitude of the pipeline, max(n j ) is the maximum value of the total number of peaks of M detection points, min(n j ) is the minimum value of the total number of peaks of M detection points, avg(n j) is the average value of the total number of peaks of M detection points, λ1 and λ2 are weight coefficients: 0<λ1<1, 0<λ2<1, and λ1+λ2=1.

[0031] Optionally, the damage threshold interval is predetermined by:

[0032] S101, applying a plurality of forces with different test amplitudes to the pipeline to test the corresponding test vibration times when the pipeline changes from being locked to being loosened;

[0033] S102, constructing an amplitude combination based on the test amplitude and the corresponding test vibration number, and determining a test damage index of the pipeline based on a plurality of the amplitude combinations;

[0034] S103, determining a damage threshold interval based on multiple test damage indices.

[0035] Optionally, determining the damage threshold interval based on multiple test damage indices includes:

[0036] determining a mean and a deviation value of the damage index based on a plurality of tested damage indices;

[0037] A damage threshold interval is determined based on the mean and deviation values ​​of the damage index.

[0038] In a second aspect, an embodiment of the present invention provides a pipeline safety early warning system based on stress detection, the system comprising:

[0039] at least one processor;

[0040] at least one memory for storing at least one program;

[0041] When the at least one program is executed by the at least one processor, the at least one processor implements any one of the methods described above.

[0042] The beneficial effects of the present invention are as follows: the present invention discloses a pipeline safety early warning method and system based on stress detection, the present invention obtains the strength distribution sequence of the pipeline in the current sampling time period, determines the strength correlation coefficient of the pipeline based on the strength values ​​of M strength sequences, and performs a pipeline safety early warning if it is determined that the strength correlation coefficient exceeds the preset strength correlation threshold value; thereby, a real-time early warning is performed when the pipeline is already damaged; the amplitude fluctuation value of the detection point is determined based on the N strength values ​​in the strength sequence of the detection point, and the strength balance of the pipeline is determined based on the amplitude fluctuation values ​​of the M detection points; the damage index of the pipeline is determined based on the strength distribution sequence, and a corrected damage prediction value is obtained based on the damage index and the strength balance; the final damage index of the pipeline is comprehensively reflected in combination with the current and previous loss degrees of the pipeline; by obtaining the damage threshold interval that is expected to be constructed, if it is determined that the corrected damage prediction value exceeds the maximum value of the damage threshold interval, a pipeline safety early warning is performed. The present invention performs data analysis through the stress detected by the stress sensor, realizes pipeline safety early warning, and improves the predictive ability of safety early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0044] Figure 1 Schematic diagram of a pipeline safety early warning method based on stress detection in an embodiment of the present invention;

[0045] Figure 2 Schematic diagram of the effect of vibration amplitude on preload in an embodiment of the present invention;

[0046] Figure 3 The structure diagram of a pipeline safety early warning system based on stress detection in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the embodiments and drawings to clearly and completely describe the concept, specific structure and technical effects of the present invention, so as to fully understand the purpose, scheme and effect of the present invention. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0048] Elastic stress luminescent material refers to a material that also has stress luminescence during elastic deformation, and its stress luminescence intensity is linearly related to the applied stress. It is a non-destructive stress luminescence, and the stress condition of the object can be deduced based on the stress luminescence intensity. After being excited by an external light source, the luminescence intensity of the elastic stress luminescent material can be fully restored. Because the elastic stress luminescent material has the characteristics of lossless luminescence, repeatability, and force-light conversion sensing.

[0049] Due to the characteristics of elastic stress luminescent materials responding to light, the stress sensors made of them can perform wireless sensing or long-distance stress distribution observation, and measure the force distribution of irregular or moving objects. Therefore, elastic stress luminescent materials have potential application value in measuring the stress distribution of mechanical parts.

[0050] Based on this, the present invention provides a pipeline safety early warning method and system based on stress detection, which performs data analysis on the stress detected by the stress sensor to achieve pipeline safety early warning and improve the predictive ability of safety early warning.

[0051] See also Figure 1 and Figure 2 The present invention provides a pipeline safety early warning method based on stress detection, the method comprising the following steps:

[0052] S100, obtaining an intensity distribution sequence of the pipeline in the current sampling time period, the intensity distribution sequence comprising an intensity sequence of M detection points; wherein the intensity sequence comprises N intensity values, N being the total number of sampling time points in the sampling time period; the M detection points are cocircular and evenly arranged on the flange plate of the end face of the pipeline; the intensity distribution sequence is obtained by sampling after performing photoelectric conversion on a detection light signal, and the detection light signal is obtained by performing stress detection on the M detection points using a stress sensor;

[0053] It should be noted that when the unit is in normal working conditions, the connecting end face of the pipeline is evenly stressed, and the stress at each detection point is generally consistent, which will fluctuate within the stress range; when the threaded fasteners become loose, the pipeline will shake, and the stress at each detection point will be different, resulting in a significant increase or decrease in the stress luminescence intensity of some detection points; based on this phenomenon, in the embodiment provided by the present invention, the light intensity of each detection point is analyzed and processed, and a pipeline safety warning is performed through data processing.

[0054] Specifically, the connecting end face of the pipeline is provided with a flange, and the flange is provided with a plurality of circular screw holes, the centers of the plurality of screw holes are cocircular and evenly arranged; a plurality of screw holes are evenly arranged at the connection of the pipeline, and each screw hole is provided with an elastic stress luminescent material as a detection point; the light intensity of each detection point is detected by the elastic stress luminescent material provided in each screw hole. A stress sensor based on elastic stress luminescent material is used to convert the stress magnitude of the detection point into a detection light signal of corresponding light intensity and send it to a background processing device (such as a server); after the processing device converts the detection light signal into a corresponding analog electrical signal through a photoelectric sensor, the analog electrical signal is subjected to gain amplification, analog-to-digital conversion and digital sampling to obtain a serialized digital signal, forming an intensity distribution sequence, and the intensity distribution sequence includes the intensity sequence of M detection points, and the pipeline safety warning is realized by analyzing and processing the intensity value of the digital signal. In some embodiments, M and N are both positive integers, and M≥3, N≥30.

[0055] S200, determining a strength correlation coefficient of the pipeline based on the strength values ​​of the M strength sequences, and if it is determined that the strength correlation coefficient exceeds a preset strength correlation threshold, issuing a pipeline safety warning;

[0056] It should be noted that when some bolts become seriously loose or even fall off, the forces acting on each detection point are significantly different. For example, when a bolt is loose, the stress at the corresponding position on the flange surface decreases as the preload force of the corresponding loose bolt decreases. The stress variation range at the corresponding position of the flange varies with the size of the applied preload force. By determining the strength correlation coefficient of M detection points, this step can first determine whether the pipeline is severely damaged, and issue a pipeline safety warning if the pipeline is already damaged. The strength correlation threshold can be pre-set based on the results of the actual scenario calculation to ensure that the strength correlation coefficient does not exceed the preset strength correlation threshold when the pipeline is safe.

[0057] S300, if it is determined that the strength correlation coefficient does not exceed the preset strength correlation threshold, determining the amplitude fluctuation value of the detection point based on N strength values ​​in the strength sequence of the detection point, and determining the strength balance of the pipeline based on the amplitude fluctuation values ​​of the M detection points;

[0058] It should be noted that when a bolt is loose, the pipeline will become unbalanced, and the strength balance can reflect the previous damage of the pipeline.

[0059] S400, determining a damage index of the pipeline based on the strength distribution sequence, and obtaining a corrected damage prediction value based on the damage index and the strength balance;

[0060] It should be noted that the amplitude and frequency reflect the current damage to the pipeline, and combined with the current and previous loss levels of the pipeline, they comprehensively reflect the final damage index of the pipeline.

[0061] S500, obtaining the estimated damage threshold interval, and if it is determined that the corrected damage prediction value exceeds the maximum value of the damage threshold interval, a pipeline safety warning is issued.

[0062] It should be noted that the preload will decay rapidly with the increase of vibration amplitude. In the early stage of bolt loosening, the preload will drop rapidly, and then show regular periodic decay. Therefore, it is necessary to consider the size of the strength correlation coefficient and the change of the amplitude fluctuation value to identify the different stages of bolt loosening and the change of preload between pipelines, so as to obtain accurate safety warnings.

[0063] In some embodiments, in S200, determining the intensity correlation coefficient of the pipeline based on the intensity values ​​of the M intensity sequences includes:

[0064] S210, grouping the M intensity sequences into two, calculating the Hausdorff distance between the two intensity sequences in each group, and obtaining a plurality of intensity difference values;

[0065] S220, after one-to-one correspondence between the N intensity values ​​of the two intensity sequences in each group according to the sampling time points, calculate the mutual correlation coefficient between the two intensity sequences;

[0066] S230, calculating the intensity difference and the mutual correlation coefficient of the two intensity sequences in each group to obtain a plurality of correlation coefficients, and taking the correlation coefficient with the largest value as the intensity correlation coefficient of the pipeline.

[0067] In this embodiment, the consistency of the M detection points can be preliminarily judged by the intensity difference, which can highlight the situation where the intensity difference is too large. If the intensity difference is small, it means that the consistency is strong, or there is a misalignment, which leads to the illusion that the Hausdorff distance is small. In order to eliminate this possibility, the overall intensity distribution is obtained in combination with the mutual correlation coefficient, so as to accurately judge the consistency of the M detection points;

[0068] In some embodiments, for two intensity sequences X={x i} and Y={y i}, x i represents the intensity value of the i-th time sampling point in the intensity sequence X, y i represents the intensity value of the i-th time sampling point in the intensity sequence Y. The correlation coefficient ρxy of the two corresponding detection points is calculated by the following formula:

[0069]

[0070] The correlation coefficient of two detection points is calculated using the formula exp(max(dxy))+exp(max(ρxy)), where dxy represents two intensity sequences X={x i} and Y={y i}, max(dxy) represents the maximum value of all intensity differences, and max(ρxy) represents the maximum value of all correlation coefficients.

[0071] In some embodiments, in S300, determining the amplitude fluctuation value of the detection point based on N intensity values ​​in the intensity sequence of the detection point, and determining the intensity balance of the pipeline based on the amplitude fluctuation values ​​of the M detection points, includes:

[0072] S310, obtaining N intensity values ​​in an intensity sequence of M detection points;

[0073] S320: For each detection point, the amplitude fluctuation value of the detection point is calculated by the following formula:

[0074]

[0075] Among them, Af j is the amplitude fluctuation value of the jth detection point, Ap j is the intensity value of the intensity sequence of the jth detection point at the peak, At j is the intensity value of the intensity sequence of the jth detection point at the trough, A ij Aavg is the intensity value of the jth detection point at the i-th sampling time point, j is the intensity mean of the jth detection point, normal represents linear normalization, the amplitude fluctuation value range is [0, 1], i = 1, 2, ..., N, j = 1, 2, ..., M;

[0076] S330, the strength balance of the pipeline is calculated by the following formula:

[0077] Bd=max(Af j ) / min(Af j )

[0078] Among them, Bd is the strength balance of the pipeline, max(Af j ) is the maximum value of the amplitude fluctuation value of M detection points, min(Af j ) is the minimum value of the amplitude fluctuation values ​​of the M detection points.

[0079] In some embodiments, in S400, determining the damage index of the pipeline based on the intensity distribution sequence, and obtaining a corrected damage prediction value based on the damage index and the intensity balance degree include:

[0080] S410, obtaining an intensity distribution sequence of a current sampling time period, and normalizing the amplitude of each sampling time point in the intensity distribution sequence to obtain a normalized amplitude of each sampling time point;

[0081] S420, obtaining the total number of peaks in the intensity sequence of each detection point and the reference amplitude of the pipeline, and determining the damage index of the pipeline based on the normalized amplitude at each sampling time point, the total number of peaks in the intensity sequence of each detection point and the reference amplitude of the pipeline; wherein the reference amplitude of the pipeline represents the critical amplitude when the pipeline is damaged;

[0082] The damage index of the pipeline is calculated by the following formula:

[0083]

[0084] Among them, Af ij is the normalized amplitude of the jth detection point at the i-th sampling time point, Afavg is the reference amplitude of the pipeline, max(n j ) is the maximum value of the total number of peaks of M detection points, min(n j ) is the minimum value of the total number of peaks of M detection points, avg(n j ) is the average value of the total number of peaks of M detection points, λ1 and λ2 are weight coefficients: 0<λ1<1, 0<λ2<1, and λ1+λ2=1.

[0085] It should be noted that the larger the amplitude, the more destructive it is to the pipeline, which is reflected in the larger damage prediction value. The amplitude at each sampling time point is linearly normalized and mapped to the interval [0,1]. The benchmark amplitude that the pipeline can withstand without being damaged is obtained through pre-testing, which is used as the benchmark amplitude of the pipeline. Based on the difference between the amplitude and the benchmark amplitude of the pipeline, a model of amplitude affecting pipeline loss is constructed, and the total number of peaks is approximated to the number of vibrations. The damage index of the pipeline is calculated by combining the amplitude and the number of vibrations, which can reflect the superimposed damage of the pipeline to the force of different amplitudes.

[0086] S430, multiplying the damage index and the strength balance of the pipeline to obtain a corrected damage prediction value.

[0087] In some embodiments, the damage threshold interval is predetermined by:

[0088] S101, applying a plurality of forces with different test amplitudes to the pipeline to test the corresponding test vibration times when the pipeline changes from being locked to being loosened;

[0089] S102, constructing an amplitude combination based on the test amplitude and the corresponding test vibration number, and determining a test damage index of the pipeline based on a plurality of the amplitude combinations;

[0090] Specifically, multiple test amplitudes and corresponding test vibration times are obtained by performing multiple test tests. For different test tests, forces with different test amplitudes are applied. In the same test, forces with the same test amplitude are applied to the M detection points in the pipeline. The test amplitude and the corresponding test vibration times are used as amplitude combinations to obtain several groups of amplitude combinations and construct an amplitude set. The test amplitude is linearly normalized and mapped to the interval [0,1], and then the test damage index of the pipeline is calculated:

[0091] The test damage index is calculated by the following formula:

[0092]

[0093] Among them, avg is the mean value of the test amplitude, Tf avg is the average value of the test vibration times; λ3 and λ4 are weight coefficients: 0<λ3<1, 0<λ4<1, and λ3+λ4=1, Ta ij is the test amplitude of the jth detection point at the i-th sampling time point, Tf j is the number of test vibrations at the jth detection point, and T is the total number of amplitude combinations;

[0094] S103, determining a damage threshold interval based on multiple test damage indices.

[0095] The damage threshold interval is calculated by the following formula:

[0096]

[0097] Where k = 1, 2, ..., K, K is the total number of test damage indices, TDa avg is the mean value of the damage index; TDa i is the i-th damage index.

[0098] It should be noted that the damage index reflects the degree of damage caused by the continuous application of a force with the same amplitude to the pipeline. Since the external force on the pipeline may not be balanced, it is usually the result of the superposition of multiple forces with different amplitudes. It is necessary to comprehensively consider the damage to the pipeline caused by this imbalance. By updating the damage index, it can more comprehensively and accurately reflect the degree of damage to the pipeline.

[0099] and Figure 1 Corresponding to the method, refer to Figure 3 , an embodiment of the present invention provides a pipeline safety early warning system based on stress detection, comprising:

[0100] at least one processor;

[0101] at least one memory for storing at least one program;

[0102] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0103] It can be seen that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0104] In addition, an embodiment of the present invention further discloses a computer program product or a computer program, which is stored in a computer-readable storage medium. A processor of a computer device can read the computer program from a computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the above method. Similarly, the contents of the above method embodiment are all applicable to the storage medium embodiment, and the functions specifically implemented by the storage medium embodiment are the same as those of the above method embodiment, and the beneficial effects achieved are also the same as those achieved by the above method embodiment.

[0105] It will be appreciated by those skilled in the art that all or some of the methods disclosed above, the system can be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0106] The above is a specific description of the preferred implementation of the present disclosure, but the present disclosure is not limited to the above-mentioned implementation mode. Technical personnel familiar with the field can also make various equivalent deformations or substitutions without violating the spirit of the present disclosure. These equivalent deformations or substitutions are all included in the scope defined by the claims of the present disclosure.

Claims

1. A pipeline safety early warning method based on stress detection, characterized in that: The method comprises the following steps: S100, obtaining an intensity distribution sequence of the pipeline in the current sampling time period, the intensity distribution sequence comprising an intensity sequence of M detection points; wherein the intensity sequence comprises N intensity values, N being the total number of sampling time points in the sampling time period; the M detection points are cocircular and evenly arranged on the flange plate of the end face of the pipeline; the intensity distribution sequence is obtained by sampling after performing photoelectric conversion on a detection light signal, and the detection light signal is obtained by performing stress detection on the M detection points using a stress sensor; S200, determining a strength correlation coefficient of the pipeline based on the strength values ​​of the M strength sequences, and if it is determined that the strength correlation coefficient exceeds a preset strength correlation threshold, issuing a pipeline safety warning; S300, if it is determined that the strength correlation coefficient does not exceed the preset strength correlation threshold, determining the amplitude fluctuation value of the detection point based on N strength values ​​in the strength sequence of the detection point, and determining the strength balance of the pipeline based on the amplitude fluctuation values ​​of the M detection points; S400, determining a damage index of the pipeline based on the strength distribution sequence, and obtaining a corrected damage prediction value based on the damage index and the strength balance; S500, obtaining the estimated damage threshold interval, and if it is determined that the corrected damage prediction value exceeds the maximum value of the damage threshold interval, a pipeline safety warning is issued.

2. The method according to claim 1, characterized in that In S200, determining the strength correlation coefficient of the pipeline based on the strength values ​​of the M strength sequences includes: S210, grouping the M intensity sequences into two, calculating the Hausdorff distance between the two intensity sequences in each group, and obtaining a plurality of intensity difference values; S220, after one-to-one correspondence between the N intensity values ​​of the two intensity sequences in each group according to the sampling time points, calculate the mutual correlation coefficient between the two intensity sequences; S230, calculating the intensity difference and the mutual correlation coefficient of the two intensity sequences in each group to obtain a plurality of correlation coefficients, and taking the correlation coefficient with the largest value as the intensity correlation coefficient of the pipeline.

3. The method according to claim 1, characterized in that In S300, the step of determining the amplitude fluctuation value of the detection point based on N intensity values ​​in the intensity sequence of the detection point, and determining the intensity balance of the pipeline based on the amplitude fluctuation values ​​of the M detection points includes: S310, obtaining N intensity values ​​in an intensity sequence of M detection points; S320: For each detection point, the amplitude fluctuation value of the detection point is calculated by the following formula: ； in, is the amplitude fluctuation value of the jth detection point, is the intensity value of the intensity sequence of the jth detection point at the peak, is the intensity value of the intensity sequence of the jth detection point at the trough, is the intensity value of the jth detection point at the i-th sampling time point, is the intensity mean of the jth detection point, normal means linear normalization, and the amplitude fluctuation value range is , N, ; S330, the strength balance of the pipeline is calculated by the following formula: ； in, is the strength balance of the pipeline, is the maximum value of the amplitude fluctuation values ​​of the M detection points, It is the minimum value of the amplitude fluctuation values ​​of the M detection points.

4. The method according to claim 3, characterized in that In S400, the damage index of the pipeline is determined based on the strength distribution sequence, and a corrected damage prediction value is obtained based on the damage index and the strength balance, including: S410, obtaining an intensity distribution sequence of a current sampling time period, and normalizing the amplitude of each sampling time point in the intensity distribution sequence to obtain a normalized amplitude of each sampling time point; S420, obtaining the total number of peaks in the intensity sequence of each detection point and the reference amplitude of the pipeline, and determining the damage index of the pipeline based on the normalized amplitude at each sampling time point, the total number of peaks in the intensity sequence of each detection point and the reference amplitude of the pipeline; wherein the reference amplitude of the pipeline represents the critical amplitude when the pipeline is damaged; S430, multiplying the damage index and the strength balance of the pipeline to obtain a corrected damage prediction value.

5. The method according to claim 4, characterized in that The damage index of the pipeline is calculated by the following formula: ； in, is the damage index of the pipeline, is the normalized amplitude of the jth detection point at the i-th sampling time point, is the base amplitude of the pipeline, is the maximum value of the total number of peaks at M detection points, is the minimum value of the total number of peaks at M detection points, is the average value of the total number of peaks at M detection points, is the weight coefficient: ,and .

6. The method according to claim 1, characterized in that The damage threshold interval is predetermined by: S101, applying a plurality of forces with different test amplitudes to the pipeline to test the corresponding test vibration times when the pipeline changes from being locked to being loosened; S102, constructing an amplitude combination based on the test amplitude and the corresponding test vibration number, and determining a test damage index of the pipeline based on a plurality of the amplitude combinations; S103, determining a damage threshold interval based on multiple test damage indices.

7. The method according to claim 6, characterized in that Determining the damage threshold interval based on multiple test damage indices includes: determining a mean and a deviation value of the damage index based on a plurality of tested damage indices; A damage threshold interval is determined based on the mean and deviation values ​​of the damage index.

8. A pipeline safety early warning system based on stress detection, characterized in that: The system comprises: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 7.

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