Pipeline corrosion monitoring method and system based on ultrasonic thickness sensor, electronic equipment and storage medium

Abstract

The invention relates to the technical field of intelligent monitoring, and discloses a pipeline corrosion monitoring method and system based on an ultrasonic thickness sensor, electronic equipment and a storage medium, and the method comprises the steps: arranging the ultrasonic thickness sensor at a vulnerable position of a pipeline, collecting the thickness data of the pipeline, building a data-position matrix, and judging whether offset data occurs or not; when the offset data exists, pipeline vibration data are collected and compared with a vibration threshold value, and whether data interference exists or not is judged; when it is judged that data interference exists, the thickness data of the pipeline is collected again after waiting time, and the pipeline corrosion amount is determined according to the second data-position matrix and the standard pipeline thickness; determining the current state parameter and comparing the current state parameter with a historical parameter, and determining a cycle detection interval; and recording the corrosion amount of the pipeline during each cycle of detection, and performing early warning when the corrosion amount of the pipeline is higher than a corrosion threshold value. The anti-interference capability is improved by analyzing the offset data, and the false alarm rate is reduced and the detection precision is improved by multiple times of data acquisition and comparative analysis.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and in particular to a pipeline corrosion monitoring method, system, electronic equipment and storage medium based on an ultrasonic thickness sensor. Background Art

[0002] Pipeline corrosion is a common phenomenon of equipment aging. Over time, the reduction in pipeline wall thickness will reduce the pressure-bearing capacity of the pipeline and may even lead to serious accidents such as leakage and explosion. In a complex industrial environment, the safety and stability of the pipeline system are crucial factors in the production process, especially in the fields of oil, natural gas, and chemicals. Pipeline corrosion monitoring is of great value in avoiding safety accidents and ensuring normal production. Therefore, how to effectively monitor pipeline corrosion and take preventive measures in time at an early stage has become a key issue in pipeline safety management.

[0003] However, in actual industrial environments, pipelines are usually under harsh conditions such as high temperature, high pressure, and strong vibration. The data collected by the sensor is easily disturbed by environmental noise and mechanical vibration, resulting in inaccurate thickness data. In addition, existing systems rely on manual judgment or simple threshold settings to judge pipeline corrosion conditions, lack automatic analysis algorithms, and are difficult to process complex and changeable corrosion data. At the same time, the existing early warning mechanism is also relatively lagging and cannot be dynamically adjusted according to real-time data, resulting in sometimes untimely warnings or false alarms.

[0004] Therefore, it is necessary to design a pipeline corrosion monitoring method and system based on ultrasonic thickness sensor to solve the problems existing in the current technology. Summary of the invention

[0005] In view of this, the present invention proposes a pipeline corrosion monitoring method, system, electronic device and storage medium based on ultrasonic thickness sensor, aiming to solve the problems existing in the current pipeline corrosion monitoring technology, such as low accuracy of monitoring results caused by data interference and delayed warning caused by lack of feedback adjustment mechanism.

[0006] The present invention proposes a pipeline corrosion monitoring method based on an ultrasonic thickness sensor, comprising:

[0007] An ultrasonic thickness sensor is arranged at a vulnerable position of the pipeline, wherein the ultrasonic thickness sensor is provided with a plurality of single crystal probes, and the thickness data of the pipeline is collected to establish a data-position matrix, and the data-position matrix is ​​analyzed to determine whether offset data occurs;

[0008] When there is offset data, pipeline vibration data is collected, and the pipeline vibration data is compared with the vibration threshold to determine whether there is data interference; when it is determined that there is data interference, the thickness data of the pipeline is collected again after a waiting time, a second data-position matrix is ​​established, and the pipeline corrosion amount is determined according to the second data-position matrix and the standard pipeline thickness;

[0009] Determine current state parameters according to the pipeline corrosion amount and pipeline parameters, and compare the current state parameters with historical parameters to determine a cyclic detection interval;

[0010] The amount of pipeline corrosion during each cycle detection is recorded, and an early warning is issued when the amount of pipeline corrosion exceeds the corrosion threshold.

[0011] Furthermore, collecting the real-time thickness data of the pipeline to establish a real-time data-position matrix, analyzing the real-time data-position matrix, and determining whether offset data occurs, including:

[0012] Corresponding the collected real-time thickness data to the position and establishing a plane coordinate system, and using the plane coordinate system as the real-time data-position matrix;

[0013] Randomly select a point in the real-time data-position matrix as a point to be determined;

[0014] Taking the point to be judged as the center and r as the radius, determine the judgment range;

[0015] Determine the average data value of the judgment range according to the value of each data within the judgment range;

[0016] When the difference between the data value at the to-be-determined point and the average data value is greater than the data threshold, the data at the to-be-determined point is determined to be offset data.

[0017] Furthermore, the average data value of the judgment range is calculated by the following formula:

[0018]

[0019] Among them, S avg represents the average data value, r represents the radius of the judgment range, (x0, y0) represents the coordinates of the point to be judged, and S(x, y) represents the data value of the point (x, y) on the real-time data-position matrix.

[0020] Furthermore, when determining whether data interference exists, the following steps are included:

[0021] When the pipeline vibration data is greater than the vibration threshold, it is determined that data interference exists, and the waiting time is determined according to the pipeline vibration data and the vibration threshold;

[0022] When the pipeline vibration data is less than or equal to the vibration threshold, it is determined that there is no data interference.

[0023] Further, when the waiting time is determined according to the pipeline vibration data and the vibration threshold, it includes:

[0024] Determine a vibration difference value according to the pipeline vibration data and the vibration threshold value, wherein the vibration difference value is the difference between the pipeline vibration data and the vibration threshold value, compare the vibration difference value with a first preset vibration difference value and a second preset vibration difference value respectively, and determine the waiting time according to the comparison result; the first preset vibration difference value is smaller than the second preset vibration difference value;

[0025] When the vibration difference is less than or equal to a first preset vibration difference, the waiting time is determined to be the first preset waiting time; when the vibration difference is greater than the first preset vibration difference and less than or equal to the second preset vibration difference, the waiting time is determined to be the second preset waiting time; when the vibration difference is greater than the second preset vibration difference, the waiting time is determined to be the third preset waiting time.

[0026] Further, when determining the amount of pipeline corrosion according to the second data-position matrix and the standard pipeline thickness, it includes:

[0027] Compare each real-time thickness data in the second data-position matrix with the standard pipeline thickness, select the data that is smaller than the standard pipeline thickness and record the data position, and determine the pipeline corrosion amount according to the number of data and the data position;

[0028]

[0029] Wherein, C represents the amount of pipeline corrosion, di represents the corrosion depth of data point i, Δxi represents the distance between adjacent data points among the data points that are less than the standard pipeline thickness, and n represents the number of data points that are less than the standard pipeline thickness.

[0030] Further, when the current state parameter is determined according to the pipeline corrosion amount and the pipeline parameter, the current state parameter is calculated by the following formula:

[0031]

[0032] Among them, T represents the current state parameter, C represents the amount of pipeline corrosion, H represents the standard pipeline thickness, L represents the length of the detection area, A represents the pipeline cross-sectional area, and E represents the elastic modulus of the pipeline material.

[0033] Furthermore, comparing the current state parameter with the historical parameter to determine the cyclic detection interval includes:

[0034] When the historical parameters contain data identical to the current state parameters, the historical cycle detection interval corresponding to the historical parameters is used as the cycle detection interval;

[0035] When there is no data identical to the current state parameter in the historical parameters, an initial cycle detection interval is determined according to the pipeline corrosion amount, and after the initial cycle detection interval, the pipeline corrosion amount at the second moment is obtained again, and the corrosion rate is obtained according to the pipeline corrosion amount and the pipeline corrosion amount at the second moment, and the initial cycle detection interval is adjusted according to the corrosion rate to obtain the cycle detection interval.

[0036] Further, the initial cycle detection interval is adjusted according to the corrosion rate to obtain the cycle detection interval, including:

[0037] The corrosion rate is compared with the corrosion rate under steady-state conditions, and an adjustment coefficient is determined according to the comparison result to adjust the initial cycle detection interval, wherein the adjustment coefficient is in inverse proportional relationship with the difference between the corrosion rate and the corrosion rate under steady-state conditions.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows: by setting an ultrasonic thickness sensor at a vulnerable position of the pipeline, combining several single crystal probes to collect pipeline wall thickness data, forming a data-position matrix, accurate monitoring of pipeline corrosion is achieved. Compared with the traditional method, it is possible to analyze the offset data and combine the pipeline vibration data to make anti-interference judgments to ensure the accuracy and stability of data acquisition. When there is interference, the detection interval is adaptively adjusted and the thickness data is re-collected, thereby improving the reliability of corrosion monitoring. Based on the comparison of the real-time collected pipeline corrosion amount with historical parameters, the interval of cyclic detection is dynamically adjusted, and a timely warning is issued when the corrosion amount exceeds the threshold, thereby improving the intelligent level of pipeline safety monitoring. Through multiple data collection and comparative analysis, the false alarm rate is effectively reduced, and the anti-interference ability and detection accuracy are enhanced.

[0039] On the other hand, the present application also provides a pipeline corrosion monitoring system based on an ultrasonic thickness sensor, which is used to apply the above pipeline corrosion monitoring method based on an ultrasonic thickness sensor, including:

[0040] An ultrasonic thickness sensor is arranged at a vulnerable position of the pipeline, and the ultrasonic thickness sensor is provided with a plurality of single crystal probes;

[0041] A collection unit is configured to collect thickness data of the pipeline to establish a data-position matrix, analyze the data-position matrix, and determine whether offset data occurs;

[0042] The judgment unit is configured to collect pipeline vibration data when there is offset data, compare the pipeline vibration data with the vibration threshold, and judge whether there is data interference; when it is determined that there is data interference, collect the thickness data of the pipeline again after a waiting time, establish a second data-position matrix, and determine the pipeline corrosion amount according to the second data-position matrix and the standard pipeline thickness;

[0043] A processing unit is configured to determine a current state parameter according to the pipeline corrosion amount and the pipeline parameter, and compare the current state parameter with the historical parameter to determine a cyclic detection interval;

[0044] The early warning unit is configured to record the amount of pipeline corrosion during each cycle detection, and issue an early warning when the amount of pipeline corrosion is higher than a corrosion threshold.

[0045] It is understandable that the above-mentioned pipeline corrosion monitoring method and system based on ultrasonic thickness sensor have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0047] Figure 1 A flow chart of a pipeline corrosion monitoring method based on an ultrasonic thickness sensor provided in an embodiment of the present invention;

[0048] Figure 2 A structural block diagram of a pipeline corrosion monitoring system based on an ultrasonic thickness sensor provided in an embodiment of the present invention;

[0049] Figure 3 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0051] Pipeline corrosion is a common and potentially dangerous phenomenon in the aging process of industrial equipment. As the pipeline is used for a longer time, the thickness of the pipe wall gradually decreases, which not only weakens the pressure-bearing capacity of the pipeline, but may also cause serious safety accidents, such as pipeline leakage or even explosion. In fields such as oil, natural gas, and chemicals that require extremely high pipeline safety, pipeline corrosion monitoring is particularly important. In order to avoid production accidents and ensure the normal operation of production, it is necessary to be able to effectively grasp the corrosion of the pipeline in real time and take preventive measures at an early stage.

[0052] However, the actual industrial environment is usually very complex, and pipelines are often under extreme conditions such as high temperature, high pressure, and strong vibration. In such a harsh environment, the data of the monitoring sensor is easily affected by various interference factors. In particular, the noise caused by vibration will directly affect the accuracy of the ultrasonic thickness sensor, resulting in deviations in the collected thickness data, which cannot accurately reflect the actual corrosion situation of the pipeline. In addition, existing corrosion monitoring systems usually rely on manual judgment, or simply set fixed thresholds to assess the health of the pipeline. This method is powerless when faced with complex and changeable corrosion data, lacks sufficient flexibility and accuracy, and cannot cope with data fluctuations under multiple influencing factors.

[0053] The existing early warning mechanism also has a lag problem. Once the corrosion situation worsens, the early warning information is often not issued in time, causing managers to miss the best maintenance opportunity. In addition, simple threshold warnings may also produce false alarms due to oversensitivity, increasing maintenance costs and affecting normal production operations. Therefore, it is necessary to design a pipeline corrosion monitoring method and system based on ultrasonic thickness sensors to solve the problems existing in current technologies.

[0054] In some embodiments of the present application, see Figure 1 As shown, a pipeline corrosion monitoring method based on an ultrasonic thickness sensor comprises:

[0055] S100: An ultrasonic thickness sensor is set at a vulnerable position of the pipeline. The ultrasonic thickness sensor is provided with a plurality of single crystal probes, and the thickness data of the pipeline is collected to establish a data-position matrix. The data-position matrix is ​​analyzed to determine whether offset data occurs.

[0056] S200: When there is offset data, pipeline vibration data is collected, and the pipeline vibration data is compared with the vibration threshold to determine whether there is data interference. When it is determined that there is data interference, the thickness data of the pipeline is collected again after a waiting time, a second data-position matrix is ​​established, and the pipeline corrosion amount is determined according to the second data-position matrix and the standard pipeline thickness.

[0057] S300: Determine current state parameters according to the pipeline corrosion amount and pipeline parameters, and compare the current state parameters with historical parameters to determine a cyclic detection interval.

[0058] S400: Record the amount of pipeline corrosion during each cycle detection, and issue an early warning when the amount of pipeline corrosion exceeds the corrosion threshold.

[0059] Specifically, in S100, an ultrasonic thickness sensor is installed at a vulnerable position of the pipeline. The ultrasonic thickness sensor is equipped with a number of single crystal probes, which can be arranged at equal intervals or in other distribution methods at vulnerable positions of the pipeline. The single crystal probe is used to accurately collect thickness data on the surface of the pipeline. The single crystal probe emits ultrasonic waves and calculates the wall thickness data at different positions of the pipeline by measuring the propagation time of the wave. Subsequently, these thickness data are combined with the corresponding position coordinates to establish a "data-position matrix". This matrix represents the wall thickness distribution of each position of the pipeline in space. By analyzing this matrix, possible wall thickness changes are identified to determine whether "offset data" appears. Offset data refers to abnormal thickness values ​​at certain positions, which are significantly different from other positions or standard thickness values, and may be a sign of corrosion or damage. In S200, when offset data is found, vibration data of the pipeline is collected to prevent misjudgment. Vibration data monitors the mechanical vibration of the pipeline through sensors, and vibration may interfere with ultrasonic thickness measurement. The collected vibration data is compared with the set vibration threshold. If the vibration exceeds the threshold, it means that the collected thickness data may be interfered by vibration. In this case, the system enters a waiting state to wait for the vibration to disappear or weaken. After that, the thickness data is collected again, and a second "data-position matrix" is established. This matrix again reflects the wall thickness of the pipeline. The thickness value in the matrix is ​​compared with the standard pipeline thickness value to finally determine the amount of corrosion of the pipeline. Once the amount of pipeline corrosion is calculated in S300, the current pipeline status parameters are determined based on the amount of corrosion and other parameters of the pipeline (such as material, diameter, etc.). The current status parameters reflect the current health status of the pipeline. After comparing with the historical status parameters of the pipeline, the subsequent detection intervals can be dynamically adjusted. The amount of pipeline corrosion detected in each cycle is recorded in S400, and long-term data storage and analysis are performed. When the detected corrosion amount exceeds the set corrosion threshold, an early warning is issued to remind the user to perform maintenance or replace the damaged pipeline in time.

[0060] It is understandable that high-precision monitoring of pipeline corrosion is achieved through the combination of ultrasonic thickness sensors and anti-interference vibration analysis. Compared with traditional methods, it can intelligently determine whether the thickness data is disturbed by vibration, and effectively avoid false alarms through secondary data collection and matrix comparison analysis. By dynamically adjusting the detection interval, the monitoring system is adaptable and can flexibly adjust the detection frequency according to the actual corrosion situation to ensure the timeliness and accuracy of monitoring. An automatic early warning mechanism has been introduced, which can actively issue a warning when the corrosion exceeds the threshold, improving the intelligence level of pipeline safety management and effectively reducing the risk of accidents.

[0061] In some embodiments of the present application, real-time thickness data of the pipeline is collected to establish a real-time data-position matrix, and the real-time data-position matrix is ​​analyzed to determine whether offset data occurs, including:

[0062] The collected real-time thickness data is matched with the position and a plane coordinate system is established, and the plane coordinate system is used as a real-time data-position matrix.

[0063] A point is randomly selected in the real-time data-position matrix as the point to be judged.

[0064] The judgment range is determined with the point to be judged as the center and r as the radius. The judgment range can be a circle with r as the radius, or a square with 2r as the side length, with the center of the square being the point to be judged, or any other shape, which is not limited in this application.

[0065] The average data value of the judgment range is determined based on the values ​​of each data within the judgment range.

[0066] When the difference between the data value at the point to be determined and the average data value is greater than the data threshold, the data at the point to be determined is determined to be offset data.

[0067] In some embodiments of the present application, the average data value of the judgment range is calculated by the following formula:

[0068]

[0069] Among them, S avg represents the average data value, r represents the radius of the judgment range, (x0, y0) represents the coordinates of the point to be judged, S(x, y) represents the data value of the point (x, y) on the real-time data-position matrix, It represents the cumulative sum of the data values ​​of the points included in the square with a side length of 2r and a center of (x0, y0). For example, the unit of r is the point spacing, that is, the value of r represents how many point spacings this distance is equivalent to. For example, if r is 2, it means a range with a radius of 2 point spacings; when the side length r is 1, It represents the cumulative sum of the data values ​​of the points within the 3×3 matrix.

[0070] Specifically, the collected real-time thickness data is obtained by ultrasonic thickness sensors and corresponds to its corresponding pipeline position to form a "real-time data-position matrix". Each point in this matrix represents the thickness value at a specific position. By constructing a plane coordinate system, the coordinates of each point in the matrix can be clearly identified, so that the thickness data can be spatially analyzed. In order to determine whether the thickness data of a certain point is "offset data", a point is randomly selected in the matrix as a "point to be judged", that is, the data of this point needs to be further evaluated whether it is abnormal. With the "point to be judged" as the center, a range (square area) with a radius of r is set. This range contains multiple thickness data points, which serve as neighboring points for judgment reference. The data of these neighboring points will be used to calculate the average thickness value of the area. Within the square judgment range, the thickness data of all points will be used to calculate the average data value. The thickness data of the "point to be judged" is compared with the average data value within the range. If the difference between the thickness value of the point and the average value exceeds the set threshold, the point is judged as "offset data". It means that the thickness value of the point is significantly lower than the average thickness around it, representing the corrosion phenomenon of the pipeline.

[0071] It can be understood that by randomly selecting the points to be judged in the data-position matrix and setting the judgment range, and taking the average data value within the range as a reference, the offset data can be effectively identified. Compared with directly comparing single-point data values, the influence of measurement errors is reduced by calculating the average value of the adjacent area, making data judgment more stable and accurate. At the same time, by setting the judgment radius r, it can flexibly adapt to corrosion areas of different sizes, thereby improving the accuracy and reliability of corrosion monitoring.

[0072] In some embodiments of the present application, when determining whether there is data interference, it includes: when the pipeline vibration data is greater than the vibration threshold, determining that there is data interference, and determining the waiting time according to the pipeline vibration data and the vibration threshold. When the pipeline vibration data is less than or equal to the vibration threshold, determining that there is no data interference.

[0073] In some embodiments of the present application, when the waiting time is determined according to the pipeline vibration data and the vibration threshold, it includes:

[0074] The vibration difference is determined according to the pipeline vibration data and the vibration threshold, the vibration difference is the difference between the pipeline vibration data and the vibration threshold, the vibration difference is compared with a first preset vibration difference and a second preset vibration difference respectively, and the waiting time is determined according to the comparison result. The first preset vibration difference is smaller than the second preset vibration difference.

[0075] Specifically, when the vibration difference is less than or equal to the first preset vibration difference, the waiting time is determined to be the first preset waiting time. When the vibration difference is greater than the first preset vibration difference and less than or equal to the second preset vibration difference, the waiting time is determined to be the second preset waiting time. When the vibration difference is greater than the second preset vibration difference, the waiting time is determined to be the third preset waiting time.

[0076] It is understandable that during the monitoring process, if the vibration data of the pipeline exceeds the preset vibration threshold, it is determined that there is data interference. This is because in actual industrial environments, large pipeline vibrations will cause inaccurate thickness data collected by the ultrasonic thickness sensor, generating noise and interference. Therefore, judging whether the pipeline vibration data exceeds the vibration threshold can effectively identify possible interference during the collection process. By dynamically adjusting the waiting time, the impact of vibration interference on pipeline thickness data collection is effectively solved. A graded processing method is adopted according to different vibration intensities to ensure the accuracy of the collected data. At the same time, by calculating the vibration difference and comparing it with the preset standard, it is possible to flexibly respond to vibrations of different intensities, avoiding the lag and inefficiency of fixed waiting time. The stability of thickness data collection is improved, the time efficiency of data collection is optimized, and excessive pause time is avoided, further improving the real-time and reliability of the entire system.

[0077] In some embodiments of the present application, when determining the amount of pipeline corrosion based on the second data-position matrix and the standard pipeline thickness, it includes: comparing each real-time thickness data in the second data-position matrix with the standard pipeline thickness, screening the data that is smaller than the standard pipeline thickness and recording the data position, and determining the amount of pipeline corrosion based on the number of data and the data position.

[0078]

[0079] Wherein, C represents the amount of pipeline corrosion, di represents the corrosion depth of data point i, Δxi represents the distance between adjacent data points among the data points less than the standard pipeline thickness, and the distance between adjacent data points can be obtained by searching for the data point i closest to the data point less than the standard pipeline thickness to obtain the distance between the two points, and can also be obtained by making a reference to the previous i points, which is not limited in this application, and n represents the number of data less than the standard pipeline thickness.

[0080] It is understandable that the second data-position matrix is ​​established by the real-time thickness data collected by the ultrasonic thickness sensor. Then, the thickness value of each data point in the matrix is ​​compared with the standard pipeline thickness, and those data points that are less than the standard pipeline thickness are screened out. These data points indicate that the pipeline has been corroded at these positions and the thickness has decreased. For the screened corrosion data, the positions of these data are recorded. Through the data of these corrosion points, the specific position range where the corrosion occurs on the pipeline is analyzed, thereby providing data support for the subsequent corrosion amount calculation. By accurately comparing the thickness of each data point with the standard pipeline thickness, the corrosion area of ​​the pipeline can be accurately identified, and the corrosion amount of the pipeline can be comprehensively calculated by combining the corrosion depth and the distribution of the corrosion area. The actual corrosion amount of each data point is not only related to its corrosion depth (thickness difference), but also to the distance between the point and its adjacent data points. In actual situations, the data points are not necessarily evenly distributed, so the corrosion amount is weighted and calculated according to the physical distance between each data point and its adjacent points. If the distance between the data points is large, the corrosion contribution to the corrosion amount of the section area is small. The total corrosion amount of the pipeline is obtained by accumulating the weighted corrosion depth of each corrosion point. Compared with traditional methods, it can more accurately capture the specific location and scope of corrosion, avoiding the roughness of corrosion judgment based solely on overall thickness changes. Considering the distance between adjacent data points makes the calculation of corrosion more three-dimensional and comprehensive, improving the accuracy of data analysis.

[0081] In some embodiments of the present application, when the current state parameter is determined according to the pipeline corrosion amount and the pipeline parameter, the current state parameter is calculated by the following formula:

[0082]

[0083] Among them, T represents the current state parameter, C represents the amount of pipeline corrosion, H represents the standard pipeline thickness, L represents the length of the detection area, A represents the pipeline cross-sectional area, and E represents the elastic modulus of the pipeline material.

[0084] In some embodiments of the present application, when comparing the current state parameter with the historical parameter to determine the cycle detection interval, it includes: when the historical parameter has the same data as the current state parameter, the historical cycle detection interval corresponding to the historical parameter is used as the cycle detection interval, and the historical parameter may include the state parameters of various pipelines. When the historical parameter does not have the same data as the current state parameter, the initial cycle detection interval is determined according to the pipeline corrosion amount, and after the initial cycle detection interval, the pipeline corrosion amount at the second moment is obtained again, the corrosion rate is obtained according to the pipeline corrosion amount and the pipeline corrosion amount at the second moment, and the initial cycle detection interval is adjusted according to the corrosion rate to obtain the cycle detection interval.

[0085] In some embodiments of the present application, the initial cycle detection interval is adjusted according to the corrosion rate to obtain the cycle detection interval, including:

[0086] The corrosion rate is compared with the corrosion rate under steady-state conditions, and an adjustment coefficient is determined according to the comparison result to adjust the initial cycle detection interval. The adjustment coefficient is inversely proportional to the difference between the corrosion rate and the corrosion rate under steady-state conditions.

[0087] Specifically, if there is data in the historical records that is the same or similar to the current state parameters, the cyclic detection interval corresponding to the historical data is used as the current detection interval. If there is no identical parameter in the historical records, an initial cyclic detection interval is set according to the current pipeline corrosion amount. After this initial interval, the detection is performed again to obtain the pipeline corrosion amount at the second moment. After obtaining the corrosion amount of the second detection, the corrosion rate is calculated based on the difference between the two corrosion amounts. By comparing the current corrosion rate with the corrosion rate under steady-state conditions, the detection interval is adjusted to obtain the cyclic detection interval, and the adjustment coefficient is inversely proportional to the difference between the corrosion rate and the steady-state corrosion rate. That is, when the corrosion rate is faster, the detection interval will be shortened to monitor the corrosion progress in time; when the corrosion rate is close to the steady state, the detection interval can be appropriately extended. After determining the cyclic detection interval time, the final determined cyclic monitoring time and the current state parameters are stored for quick next judgment.

[0088] It is understandable that by comparing historical data and automatically optimizing the detection interval, it is possible to reasonably reduce the number of unnecessary tests and improve detection efficiency while ensuring safety. When historical data is insufficient, the detection interval is dynamically adjusted based on the corrosion rate to ensure that the detection frequency can adapt to the development trend of pipeline corrosion, thus achieving more flexible and efficient pipeline corrosion monitoring management.

[0089] In the above embodiment, an ultrasonic thickness sensor is set at a vulnerable position of the pipeline, and several single crystal probes are combined to collect pipeline wall thickness data to form a data-position matrix, thereby realizing accurate monitoring of pipeline corrosion. Compared with the traditional method, it is possible to analyze the offset data and combine it with the pipeline vibration data to make anti-interference judgments to ensure the accuracy and stability of data acquisition. When there is interference, the detection interval is adaptively adjusted and the thickness data is re-collected, thereby improving the reliability of corrosion monitoring. Based on the comparison of the pipeline corrosion amount collected in real time with the historical parameters, the interval of the cyclic detection is dynamically adjusted, and a warning is issued in time when the corrosion amount exceeds the threshold, thereby improving the intelligent level of pipeline safety monitoring. Through multiple data collection and comparative analysis, the false alarm rate is effectively reduced, and the anti-interference ability and detection accuracy are enhanced.

[0090] In another preferred embodiment based on the above embodiment, refer to Figure 2As shown, this embodiment provides a pipeline corrosion monitoring system based on an ultrasonic thickness sensor, which is used to apply the above pipeline corrosion monitoring method based on an ultrasonic thickness sensor, including:

[0091] The ultrasonic thickness sensor is arranged at the vulnerable position of the pipeline, and is provided with a plurality of single crystal probes;

[0092] A collection unit is configured to collect thickness data of the pipeline to establish a data-position matrix, analyze the data-position matrix, and determine whether offset data occurs;

[0093] The judgment unit is configured to collect pipeline vibration data when there is offset data, compare the pipeline vibration data with the vibration threshold, and judge whether there is data interference; when it is determined that there is data interference, collect the pipeline thickness data again after a waiting time, establish a second data-position matrix, and determine the pipeline corrosion amount according to the second data-position matrix and the standard pipeline thickness;

[0094] The processing unit is configured to determine the current state parameter according to the pipeline corrosion amount and the pipeline parameter, and compare the current state parameter with the historical parameter to determine the cycle detection interval;

[0095] The early warning unit is configured to record the amount of pipeline corrosion during each cycle detection, and issue an early warning when the amount of pipeline corrosion exceeds a corrosion threshold.

[0096] It is understandable that by setting ultrasonic thickness sensors at vulnerable positions of pipelines and combining several single crystal probes to collect pipeline wall thickness data and form a data-position matrix, accurate monitoring of pipeline corrosion is achieved. Compared with traditional methods, it is possible to analyze offset data and combine pipeline vibration data to make anti-interference judgments to ensure the accuracy and stability of data acquisition. When there is interference, the detection interval is adaptively adjusted and the thickness data is re-collected to improve the reliability of corrosion monitoring. Based on the comparison of the real-time collected pipeline corrosion amount with historical parameters, the interval of cyclic detection is dynamically adjusted, and timely warning is issued when the corrosion amount exceeds the threshold, which improves the intelligent level of pipeline safety monitoring. Through multiple data collection and comparative analysis, the false alarm rate is effectively reduced, and the anti-interference ability and detection accuracy are enhanced.

[0097] Figure 3 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention is shown in FIG. Figure 3 As shown, the electronic device includes a processor 410, a memory 420, an input device 430, and an output device 440; the number of processors 410 in the device can be one or more. Figure 3 A processor 410 is taken as an example; the processor 410, the memory 420, the input device 430 and the output device 440 in the device can be connected via a bus or other means. Figure 3 The example of connecting through bus is taken in the following.

[0098] The memory 420 is a computer-readable storage medium that can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to a data storage method in an embodiment of the present invention. The processor 410 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 420.

[0099] The memory 420 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 420 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 420 may further include a memory remotely arranged relative to the processor 410, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0100] The input device 430 may be used to receive input digital or character information and generate signal input related to user settings and function control of the device. The output device 440 may include a display device such as a display screen.

[0101] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0102] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0103] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0104] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A pipeline corrosion monitoring method based on ultrasonic thickness sensor, characterized in that: include: An ultrasonic thickness sensor is arranged at a vulnerable position of the pipeline, wherein the ultrasonic thickness sensor is provided with a plurality of single crystal probes, and the thickness data of the pipeline is collected to establish a data-position matrix, and the data-position matrix is ​​analyzed to determine whether offset data occurs; When there is offset data, pipeline vibration data is collected, and the pipeline vibration data is compared with a vibration threshold to determine whether there is data interference; When it is determined that there is data interference, the thickness data of the pipeline is collected again after a waiting time, a second data-position matrix is ​​established, and the pipeline corrosion amount is determined according to the second data-position matrix and the standard pipeline thickness; Determine current state parameters according to the pipeline corrosion amount and pipeline parameters, and compare the current state parameters with historical parameters to determine a cyclic detection interval; The amount of pipeline corrosion during each cycle detection is recorded, and an early warning is issued when the amount of pipeline corrosion exceeds the corrosion threshold.

2. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 1 is characterized in that: Collecting real-time thickness data of the pipeline to establish a real-time data-position matrix, analyzing the real-time data-position matrix, and determining whether offset data occurs, including: Corresponding the collected real-time thickness data to the position and establishing a plane coordinate system, and using the plane coordinate system as the real-time data-position matrix; Randomly select a point in the real-time data-position matrix as a point to be determined; Taking the point to be judged as the center and r as the radius, determine the judgment range; Determine the average data value of the judgment range according to the value of each data within the judgment range; When the difference between the data value at the to-be-determined point and the average data value is greater than the data threshold, the data at the to-be-determined point is determined to be offset data.

3. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 2 is characterized in that: The average data value of the judgment range is calculated by the following formula: Among them, S avg represents the average data value, r represents the radius of the judgment range, (x0, y0) represents the coordinates of the point to be judged, and S(x, y) represents the data value of the point (x, y) on the real-time data-position matrix.

4. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 1 is characterized in that: When judging whether there is data interference, it includes: When the pipeline vibration data is greater than the vibration threshold, it is determined that data interference exists, and the waiting time is determined according to the pipeline vibration data and the vibration threshold; When the pipeline vibration data is less than or equal to the vibration threshold, it is determined that there is no data interference.

5. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 4 is characterized in that: When the waiting time is determined according to the pipeline vibration data and the vibration threshold, it includes: Determine a vibration difference value according to the pipeline vibration data and the vibration threshold value, wherein the vibration difference value is the difference between the pipeline vibration data and the vibration threshold value, compare the vibration difference value with a first preset vibration difference value and a second preset vibration difference value respectively, and determine the waiting time according to the comparison result; the first preset vibration difference value is smaller than the second preset vibration difference value; When the vibration difference is less than or equal to a first preset vibration difference, the waiting time is determined to be the first preset waiting time; when the vibration difference is greater than the first preset vibration difference and less than or equal to the second preset vibration difference, the waiting time is determined to be the second preset waiting time; when the vibration difference is greater than the second preset vibration difference, the waiting time is determined to be the third preset waiting time.

6. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 5 is characterized in that: When determining the amount of pipeline corrosion according to the second data-position matrix and the standard pipeline thickness, it includes: Compare each real-time thickness data in the second data-position matrix with the standard pipeline thickness, select the data that is smaller than the standard pipeline thickness and record the data position, and determine the pipeline corrosion amount according to the number of data and the data position; Wherein, C represents the amount of pipeline corrosion, di represents the corrosion depth of data point i, Δxi represents the distance between adjacent data points among the data points that are less than the standard pipeline thickness, and n represents the number of data points that are less than the standard pipeline thickness.

7. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 6 is characterized in that: When the current state parameter is determined according to the pipeline corrosion amount and pipeline parameters, the current state parameter is calculated by the following formula: Among them, T represents the current state parameter, C represents the amount of pipeline corrosion, H represents the standard pipeline thickness, L represents the length of the detection area, A represents the pipeline cross-sectional area, and E represents the elastic modulus of the pipeline material.

8. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 7 is characterized in that: When comparing the current state parameter with the historical parameter to determine the cycle detection interval, it includes: When the historical parameters contain data identical to the current state parameters, the historical cycle detection interval corresponding to the historical parameters is used as the cycle detection interval; When there is no data identical to the current state parameter in the historical parameters, an initial cycle detection interval is determined according to the pipeline corrosion amount, and after the initial cycle detection interval, the pipeline corrosion amount at the second moment is obtained again, and the corrosion rate is obtained according to the pipeline corrosion amount and the pipeline corrosion amount at the second moment, and the initial cycle detection interval is adjusted according to the corrosion rate to obtain the cycle detection interval.

9. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 8 is characterized in that: The initial cycle detection interval is adjusted according to the corrosion rate to obtain the cycle detection interval, including: The corrosion rate is compared with the corrosion rate under steady-state conditions, and an adjustment coefficient is determined according to the comparison result to adjust the initial cycle detection interval, wherein the adjustment coefficient is inversely proportional to the difference between the corrosion rate and the corrosion rate under steady-state conditions.

10. A pipeline corrosion monitoring system based on an ultrasonic thickness sensor, used for applying the pipeline corrosion monitoring method based on an ultrasonic thickness sensor as claimed in any one of claims 1 to 9, characterized in that: include: An ultrasonic thickness sensor is arranged at a vulnerable position of the pipeline, and the ultrasonic thickness sensor is provided with a plurality of single crystal probes; A collection unit is configured to collect thickness data of the pipeline to establish a data-position matrix, analyze the data-position matrix, and determine whether offset data occurs; A judgment unit is configured to collect pipeline vibration data when there is offset data, compare the pipeline vibration data with a vibration threshold, and judge whether there is data interference; When it is determined that there is data interference, the thickness data of the pipeline is collected again after a waiting time, a second data-position matrix is ​​established, and the pipeline corrosion amount is determined according to the second data-position matrix and the standard pipeline thickness; A processing unit is configured to determine a current state parameter according to the pipeline corrosion amount and the pipeline parameter, and compare the current state parameter with the historical parameter to determine a cyclic detection interval; The early warning unit is configured to record the amount of pipeline corrosion during each cycle detection, and issue an early warning when the amount of pipeline corrosion is higher than a corrosion threshold.

11. An electronic device, characterized in that: The electronic device comprises: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the pipeline corrosion monitoring method as described in any one of claims 1-9.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the pipeline corrosion monitoring method as described in any one of claims 1 to 9 is implemented.

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