A pipeline corrosion monitoring method, system, electronic device and storage medium based on ultrasonic thickness sensor

Abstract

The application 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, the method comprising the following steps: arranging an ultrasonic thickness sensor at a vulnerable position of a pipeline, collecting thickness data of the pipeline to establish a data-position matrix to determine whether offset data exists; when the offset data exists, collecting pipeline vibration data and comparing the pipeline vibration data with a vibration threshold value to determine whether data interference exists; when it is determined that the data interference exists, collecting the thickness data of the pipeline again after a waiting time, and determining a pipeline corrosion amount according to a second data-position matrix and a standard pipeline thickness; comparing a current state parameter with a historical parameter to determine a cycle detection interval; and recording the pipeline corrosion amount at each cycle detection, and giving a warning when the pipeline corrosion amount is higher than a corrosion threshold value. The application improves the anti-interference capability by analyzing the offset data, reduces the false alarm rate through multiple data collection and comparative analysis, and improves the detection precision.

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 aging phenomenon in equipment. Over time, the reduction in pipe wall thickness reduces the pipe's pressure-bearing capacity and can even lead to serious accidents such as leaks and explosions. In complex industrial environments, the safety and stability of pipeline systems are crucial factors in the production process. This is especially true in the oil, natural gas, and chemical industries. Pipeline corrosion monitoring is extremely valuable for avoiding safety accidents and ensuring normal production. Therefore, how to effectively monitor pipeline corrosion and take timely preventive measures at an early stage has become a key issue in pipeline safety management.

[0003] However, in real industrial environments, pipelines are often exposed to harsh conditions such as high temperature, high pressure, and strong vibration. Data collected by sensors is easily affected by environmental noise and mechanical vibration, resulting in inaccurate thickness data. Existing systems also rely on manual judgment or simple threshold settings to determine pipeline corrosion conditions. They lack automated analysis algorithms and struggle to process complex and variable corrosion data. Furthermore, existing early warning mechanisms are often lagging and unable to dynamically adjust based on real-time data, resulting in untimely warnings or false alarms.

[0004] 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 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 an ultrasonic thickness sensor, aiming to solve the problems existing in current pipeline corrosion monitoring technology, such as data interference resulting in low monitoring result accuracy and lack of feedback adjustment mechanism resulting in early warning lag.

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

[0007] An ultrasonic thickness sensor is installed at a vulnerable position of the pipeline. The ultrasonic thickness sensor is equipped with several single crystal probes to collect thickness data of the pipeline to establish a data-position matrix. The data-position matrix is ​​analyzed to determine whether offset data occurs.

[0008] When offset data exists, pipeline vibration data is collected, and the pipeline vibration data is compared with a vibration threshold to determine whether data interference exists. If data interference is determined to exist, pipeline thickness data is collected again after a waiting time, a second data-position matrix is ​​established, and the amount of pipeline corrosion is determined based on 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 a corrosion threshold.

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

[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] Determine the judgment range with the point to be judged as the center and r as the radius;

[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 a 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, determining whether data interference exists includes:

[0021] When the pipeline vibration data is greater than the vibration threshold, determining that data interference exists, and determining the waiting time 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] Furthermore, when determining the waiting time according to the pipeline vibration data and the vibration threshold, it includes:

[0024] determining a vibration difference value based on the pipeline vibration data and the vibration threshold, the vibration difference value being the difference between the pipeline vibration data and the vibration threshold value, comparing the vibration difference value with a first preset vibration difference value and a second preset vibration difference value, respectively, and determining the waiting time based on the comparison results; the first preset vibration difference value being 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 a 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] Furthermore, when determining the amount of pipeline corrosion based on the second data-position matrix and the standard pipeline thickness, the method includes:

[0027] Comparing each real-time thickness data in the second data-position matrix with the standard pipeline thickness, filtering out data that is smaller than the standard pipeline thickness and recording the data position, and determining the pipeline corrosion amount based on 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] Furthermore, when determining the current state parameter according to the pipeline corrosion amount and the pipeline parameter, the current state parameter is calculated by the following formula:

[0031]

[0032] Where 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 parameters with historical parameters 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 the historical parameters do not contain data identical to the current state parameters, an initial cyclic detection interval is determined based on the pipeline corrosion amount, and after the initial cyclic detection interval has passed, the pipeline corrosion amount at a second moment is obtained again, and a corrosion rate is obtained based on the pipeline corrosion amount and the pipeline corrosion amount at the second moment. The initial cyclic detection interval is adjusted based on the corrosion rate to obtain the cyclic detection interval.

[0036] Furthermore, 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 proportion to the difference between the corrosion rate and the corrosion rate under steady-state conditions.

[0038] Compared with the existing technology, the present invention has the following advantages: by installing ultrasonic thickness sensors at vulnerable locations on the pipeline and combining them with several single-crystal probes to collect pipeline wall thickness data, a data-position matrix is ​​formed, enabling accurate monitoring of pipeline corrosion. Compared with traditional methods, this method can analyze offset data and combine it with pipeline vibration data to perform anti-interference judgment, ensuring the accuracy and stability of data acquisition. When interference occurs, the detection interval is adaptively adjusted and thickness data is re-collected, thereby improving the reliability of corrosion monitoring. Based on the real-time collected pipeline corrosion volume and comparing it with historical parameters, the interval between cyclic detections is dynamically adjusted, and a timely warning is issued when the corrosion volume 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 capability 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, comprising:

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

[0041] an acquisition unit configured to acquire thickness data of the pipeline to establish a data-position matrix, analyze the data-position matrix, and determine whether offset data occurs;

[0042] a judgment unit configured to collect pipeline vibration data when offset data exists, compare the pipeline vibration data with a vibration threshold, and determine whether data interference exists; if data interference exists, collect pipeline thickness data again after a waiting time, establish a second data-position matrix, and determine the amount of pipeline corrosion based on the second data-position matrix and a standard pipeline thickness;

[0043] a processing unit configured to determine a current state parameter according to the pipeline corrosion amount and the pipeline parameter, and compare the current state parameter with a 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 exceeds 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 skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the 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 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 set forth herein. On the contrary, these embodiments are provided 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, unless there is a conflict, the embodiments of the present disclosure and the features 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 conjunction with the embodiments.

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

[0052] However, the actual industrial environment is usually very complex, and the pipeline is often under extreme conditions such as high temperature, high pressure and strong vibration. In such harsh environments, the data of the monitoring sensor is easily affected by various interference factors. Especially the noise caused by vibration, which will directly affect the accuracy of the ultrasonic thickness sensor, causing the collected thickness data to deviate, so as to cannot accurately reflect the actual corrosion situation of the pipeline. In addition, the existing corrosion monitoring system usually relies on manual judgment, or simply evaluates the health condition of the pipeline by setting a fixed threshold. This method is not competent when faced with complex and variable corrosion data, and lacks enough flexibility and accuracy to deal with data fluctuations under various influencing factors.

[0053] The existing early warning mechanism also has the problem of lag. Once the corrosion situation is aggravated, the warning information cannot be sent in time, causing the manager to miss the best maintenance opportunity. In addition, simple threshold early warning may produce false alarms due to excessive sensitivity, increasing the maintenance cost and affecting the normal production operation. 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.

[0054] In some embodiments of the present application, referring to Figure 1 The pipeline corrosion monitoring method based on ultrasonic thickness sensor comprises:

[0055] S100: setting an ultrasonic thickness sensor at a vulnerable position of the pipeline, the ultrasonic thickness sensor is provided with a plurality of single crystal probes, collecting the thickness data of the pipeline to establish a data-position matrix, analyzing the data-position matrix to determine whether there is offset data.

[0056] S200: collecting the pipeline vibration data when there is offset data, comparing the pipeline vibration data 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 the current state parameter according to the pipeline corrosion amount and pipeline parameters, and compare the current state parameter with the historical parameter to determine the cycle detection interval.

[0058] S400: Record the pipeline corrosion amount at each cycle detection, and give a warning when the pipeline corrosion amount is higher than the corrosion threshold.

[0059] Specifically, in S100, an ultrasonic thickness sensor is installed at the vulnerable position of the pipeline. The ultrasonic thickness sensor is equipped with several single crystal probes, which can be arranged in equal intervals or other distribution modes at the vulnerable position of the pipeline. The single crystal probes are used to accurately collect the thickness data of the pipeline surface. The single crystal probes emit ultrasonic waves, and by measuring the propagation time of the waves, the wall thickness data of different positions of the pipeline is calculated. Then, the thickness data and the corresponding position coordinates are combined to establish a "data-position matrix". This matrix represents the wall thickness distribution of the pipeline at different positions in space. By analyzing this matrix, possible wall thickness changes are identified, and it is determined whether there is "offset data". Offset data refers to the thickness values of some positions that are abnormal and have a large difference from other positions or standard thickness values, which 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. The vibration data is collected by sensors to monitor the mechanical vibration of the pipeline. Vibration may interfere with ultrasonic thickness measurement. The collected vibration data is compared with the set vibration threshold value. If the vibration exceeds the threshold value, it means that the collected thickness data may be disturbed by vibration. In this case, the system enters a waiting state to wait for the vibration to disappear or weaken. Then, the thickness data is collected again, and a second "data-position matrix" is established. This matrix reflects the wall thickness of the pipeline again. The thickness values in this matrix are compared with the standard pipeline thickness values to finally determine the corrosion amount of the pipeline. In S300, once the pipeline corrosion amount is calculated, the current pipeline state parameter is determined according to the corrosion amount and other parameters of the pipeline (such as material, diameter, etc.). The current state parameter reflects the current health status of the pipeline, and after comparing with the historical state parameter of the pipeline, the subsequent detection interval can be dynamically adjusted. In S400, the pipeline corrosion amount of each cycle detection is recorded, and long-term data storage and analysis are performed. When the detected corrosion amount exceeds the set corrosion threshold, a warning is given to remind users to maintain or replace the damaged pipeline in a timely manner.

[0060] It can be understood that through the ultrasonic thickness sensor combined with anti-interference vibration analysis, high-precision monitoring of pipeline corrosion is realized. Compared with traditional methods, it can intelligently judge whether the thickness data is disturbed by vibration, and effectively avoid false reports through secondary data collection and matrix comparison analysis. Through dynamic adjustment of detection interval, the monitoring system has adaptability, which can flexibly adjust the detection frequency according to the actual corrosion situation, and ensure the timeliness and accuracy of monitoring. The automatic early warning mechanism is introduced, which can actively warn when the corrosion exceeds the threshold, improving the intelligent 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 there is offset data, including:

[0062] Corresponding the collected real-time thickness data with the position and establishing a plane coordinate system, the plane coordinate system is taken as the real-time data-position matrix.

[0063] Randomly selecting a point in the real-time data-position matrix as a to-be-judged point.

[0064] Determining a judgment range with the to-be-judged point as the center and r as the radius, the judgment range can be a circle with r as the radius, a square with 2r as the side length, the center of the square being the to-be-judged point, or other arbitrary shapes, which are not limited in the present application.

[0065] Determining the average data value of the judgment range according to the values of each data in the judgment range.

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

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

[0068]

[0069] Wherein, S avg represents the average data value, r represents the radius of the judgment range, (x0, y0) represents the coordinates of the to-be-judged point, S(x, y) represents the data value of the point (x, y) on the real-time data-position matrix, represents the cumulative sum of the data values of the points included in the square with (x0, y0) as the center and 2r as the side length. For example, the unit of r is the distance between points, that is, the value of r represents the distance equivalent to how many point distances, for example, r is 2, which represents a range with a radius of 2 point distances; when the value of the side length r is 1, represents the cumulative sum of the data values of the points in the 3x3 matrix range.

[0070] Specifically, real-time thickness data collected by ultrasonic thickness sensors is mapped to corresponding pipeline locations, forming a "real-time data-position matrix." Each point in this matrix represents the thickness value at a specific location. By constructing a planar coordinate system, the coordinates of each point in the matrix can be clearly identified, enabling spatial analysis of the thickness data. To determine whether the thickness data at a particular point is "offset data," a point is randomly selected in the matrix as a "point to be judged," meaning that the data at this point requires further evaluation for abnormalities. A range (a square area) with a radius of r is defined, centered around the "point to be judged." This range contains multiple thickness data points, which serve as neighboring reference points for judgment. The data from these neighboring points is used to calculate the average thickness value for the area. The thickness data from all points within the square judgment range is used to calculate the average data value. The thickness data from the "point to be judged" is compared with the average data value within the range. If the difference between the thickness value at the point to be judged and the average exceeds a set threshold, the point is judged as "offset data." This means that the thickness value at the point is significantly lower than the surrounding average, indicating pipeline corrosion.

[0071] It can be understood that by randomly selecting points to be judged in the data-position matrix, setting a judgment range, and using the average data value within this range as a reference, offset data can be effectively identified. Compared to directly comparing single-point data values, calculating the average value of the adjacent area reduces the impact of measurement errors, 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, improving the accuracy and reliability of corrosion monitoring.

[0072] In some embodiments of the present application, determining whether data interference exists includes: determining that data interference exists when pipeline vibration data is greater than a vibration threshold, and determining a waiting time based on the pipeline vibration data and the vibration threshold. When the pipeline vibration data is less than or equal to the vibration threshold, determining that data interference does not exist.

[0073] In some embodiments of the present application, determining the waiting time based on pipeline vibration data and a vibration threshold includes:

[0074] A vibration difference is determined based on the pipeline vibration data and the vibration threshold, the vibration difference being 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 a waiting time is determined based on the comparison results. 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's understandable that during the monitoring process, if the pipeline vibration data exceeds the preset vibration threshold, data interference is detected. This is because in real industrial environments, large pipeline vibrations can lead to inaccurate thickness data collected by the ultrasonic thickness sensor, generating noise and interference. Therefore, determining whether the pipeline vibration data exceeds the vibration threshold can effectively identify potential interference during the collection process. By dynamically adjusting the waiting time, the impact of vibration interference on pipeline thickness data collection is effectively addressed. A graded processing method is adopted based on different vibration intensities to ensure the accuracy of the collected data. Furthermore, by calculating the vibration difference and comparing it with a preset standard, it can flexibly respond to vibrations of varying intensities, avoiding the lag and inefficiency of a fixed waiting time. This improves the stability of thickness data collection, optimizes the time efficiency of data collection, avoids excessive pauses, and further enhances the real-time performance and reliability of the entire system.

[0077] In some embodiments of the present application, determining the amount of pipeline corrosion based on the second data-position matrix and the standard pipeline thickness includes: comparing each real-time thickness data in the second data-position matrix with the standard pipeline thickness, screening out 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 that are less than the standard pipeline thickness. The distance between adjacent data points can be obtained by searching for the data point that is less than the standard pipeline thickness nearest to data point i, or by using the previous i points as a reference to obtain the distance between the two points. This application does not impose any restrictions on this. n represents the number of data points that are less than the standard pipeline thickness.

[0080] It can be understood that the real-time thickness data collected by the ultrasonic thickness sensor establishes a second data-position matrix. Then, the thickness value of each data point in the matrix is compared with the standard pipeline thickness, and those data points less than the standard pipeline thickness are screened out. These data points indicate that the pipeline has corrosion at these positions, and the thickness is reduced. For the screened corrosion data, the positions of these data points are recorded. Through the data of these corrosion points, the specific position range of the corrosion on the pipeline is analyzed, thereby providing data support for 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 calculated comprehensively in combination with 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 related to the distance between the point and its adjacent data points. In actual situations, data points are not necessarily uniformly distributed, so the corrosion amount is weighted according to the physical distance between each data point and its adjacent points. If the distance between data points is large, the corrosion contribution of the corrosion amount of the region is small. By accumulating the weighted corrosion depth of each corrosion point, the total corrosion amount of the pipeline is obtained. Compared with the traditional method, the specific position and range of the corrosion can be more accurately captured, and the roughness of the corrosion judgment by only the overall thickness change is avoided. The consideration of the distance between adjacent data points makes the corrosion amount calculation more three-dimensional and comprehensive, and improves the accuracy of data analysis.

[0081] In some embodiments of the present application, when the pipeline corrosion amount and the pipeline parameters are used to determine the current state parameter, the current state parameter is obtained by calculation according to the following formula:

[0082]

[0083] Wherein, T represents the current state parameter, C represents the pipeline corrosion amount, 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 the current state parameter is compared with the historical parameter to determine the cycle detection interval, the cycle detection interval is obtained by: when there is the same data as the current state parameter in the historical parameter, the historical cycle detection interval corresponding to the historical parameter is taken as the cycle detection interval, and the historical parameter can include the state parameters of various pipelines. When there is no data same as the current state parameter in the historical parameter, an initial cycle detection interval is determined according to the pipeline corrosion amount, and the pipeline corrosion amount at the second time is obtained again after the initial cycle detection interval, the corrosion speed is obtained according to the pipeline corrosion amount and the pipeline corrosion amount at the second time, and the initial cycle detection interval is adjusted according to the corrosion speed 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 based on 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 historical records contain data with the same or similar parameters as the current state, the cyclic detection interval corresponding to the historical data is used as the current detection interval. If the historical records do not contain the same parameters, an initial cyclic detection interval is set based on the current pipeline corrosion level. After this initial interval, another detection is performed to obtain the pipeline corrosion level at the second moment. After obtaining the second corrosion level, the corrosion rate is calculated based on the difference between the two values. The cyclic detection interval is determined by comparing the current corrosion rate with the corrosion rate under steady-state conditions. The detection interval is adjusted using an adjustment factor that is inversely proportional to the difference between the corrosion rate and the steady-state corrosion rate. Specifically, when the corrosion rate is high, the detection interval is shortened to monitor corrosion progress more quickly; when the corrosion rate approaches steady-state, the detection interval can be appropriately extended. After determining the cyclic detection interval, the final cyclic monitoring time and the current state parameters are stored for rapid evaluation.

[0088] It is understandable that automatically optimizing inspection intervals based on historical data comparisons can reasonably reduce unnecessary inspections while ensuring safety, thereby improving inspection efficiency. When historical data is insufficient, dynamic adjustment of inspection intervals based on corrosion rates ensures that inspection frequency can adapt to the development of pipeline corrosion, achieving more flexible and efficient pipeline corrosion monitoring and management.

[0089] In the above-described embodiment, ultrasonic thickness sensors are installed at vulnerable locations on the pipeline, combined with several single-crystal probes to collect pipeline wall thickness data, forming a data-position matrix, enabling precise monitoring of pipeline corrosion. Compared to traditional methods, this method can analyze offset data and combine it with pipeline vibration data to perform anti-interference judgment, ensuring the accuracy and stability of data acquisition. When interference occurs, the detection interval is adaptively adjusted and thickness data is re-collected, thereby improving the reliability of corrosion monitoring. Based on the real-time collected pipeline corrosion data and comparing it with historical parameters, the interval between cyclic detections is dynamically adjusted, and timely warnings are issued when the corrosion level exceeds the threshold, 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 capability 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 installed at the vulnerable position of the pipeline. The ultrasonic thickness sensor is equipped with several single crystal probes;

[0092] an acquisition unit configured to acquire thickness data of the pipeline to establish a data-position matrix, analyze the data-position matrix, and determine whether offset data occurs;

[0093] a judgment unit configured to collect pipeline vibration data when offset data exists, compare the pipeline vibration data with a vibration threshold, and determine whether data interference exists; if data interference exists, collect pipeline thickness data again after a waiting time, establish a second data-position matrix, and determine the amount of pipeline corrosion based on the second data-position matrix and a standard pipeline thickness;

[0094] a processing unit configured to determine a current state parameter based on the amount of pipeline corrosion and pipeline parameters, and compare the current state parameter with a historical parameter to determine a cyclic 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] As can be understood, by placing ultrasonic thickness sensors at vulnerable locations on the pipeline and combining them with several single-crystal probes to collect pipeline wall thickness data, forming a data-position matrix, precise monitoring of pipeline corrosion is achieved. Compared to traditional methods, this method can analyze offset data and combine it with pipeline vibration data to perform anti-interference judgment, ensuring the accuracy and stability of data acquisition. When interference occurs, the detection interval is adaptively adjusted and thickness data is re-collected, thereby improving the reliability of corrosion monitoring. Based on the real-time pipeline corrosion data collected, it is compared with historical parameters to dynamically adjust the interval between cyclic detections and issue timely warnings when the corrosion data exceeds the threshold, thus 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 capability 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 In the embodiment, a processor 410 is used as an example; the processor 410, memory 420, input device 430 and output device 440 in the device can be connected via a bus or other means. Figure 3 The bus connection is taken as an example.

[0098] Memory 420, as a computer-readable storage medium, 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. Processor 410 executes the software programs, instructions, and modules stored in memory 420 to perform various functional applications and data processing of the device.

[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 and applications required for at least one function; the data storage area may store data created based on 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 located 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 take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0102] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the 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 the 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 produce 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 that can direct a computer or other programmable data processing device to work 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 The 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 operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function 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 and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the 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 by 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 installed at a vulnerable position of the pipeline. The ultrasonic thickness sensor is equipped with several single crystal probes to collect thickness data of the pipeline to establish a data-position matrix. 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 data interference exists, the thickness data of the pipeline is collected again after a waiting time, a second data-position matrix is ​​established, and the amount of pipeline corrosion is determined based on 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; Record the amount of pipeline corrosion during each cycle of detection, and issue an early warning when the amount of pipeline corrosion exceeds the corrosion threshold; When determining whether there is data interference, the following are included: When the pipeline vibration data is greater than the vibration threshold, determining that data interference exists, 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; Determining the waiting time according to the pipeline vibration data and the vibration threshold includes: determining a vibration difference value based on the pipeline vibration data and the vibration threshold, the vibration difference value being the difference between the pipeline vibration data and the vibration threshold value, comparing the vibration difference value with a first preset vibration difference value and a second preset vibration difference value, respectively, and determining the waiting time based on the comparison results; the first preset vibration difference value being 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 a 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.

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 to determine 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; Determine the judgment range with the point to be judged as the center and r as the radius; 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 a 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 vag 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: Determining the amount of pipeline corrosion based on the second data-position matrix and the standard pipeline thickness includes: Comparing each real-time thickness data in the second data-position matrix with the standard pipeline thickness, filtering out data that is smaller than the standard pipeline thickness and recording the data position, and determining the pipeline corrosion amount based on 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.

5. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 4 is characterized in that: When determining the current state parameter according to the pipeline corrosion amount and pipeline parameters, the current state parameter is calculated by the following formula: Where 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.

6. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 5 is characterized in that: Comparing the current state parameters with the historical parameters to determine the cyclic detection interval 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 the historical parameters do not contain data identical to the current state parameters, an initial cyclic detection interval is determined based on the pipeline corrosion amount, and after the initial cyclic detection interval has passed, the pipeline corrosion amount at a second moment is obtained again, and a corrosion rate is obtained based on the pipeline corrosion amount and the pipeline corrosion amount at the second moment. The initial cyclic detection interval is adjusted based on the corrosion rate to obtain the cyclic detection interval.

7. The pipeline corrosion monitoring method based on ultrasonic thickness sensor according to claim 6 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.

8. 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 according to any one of claims 1 to 7, characterized in that: include: An ultrasonic thickness sensor is provided at a vulnerable position of the pipeline, and the ultrasonic thickness sensor is provided with a plurality of single crystal probes; an acquisition unit configured to acquire 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 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 data interference exists, the thickness data of the pipeline is collected again after a waiting time, a second data-position matrix is ​​established, and the amount of pipeline corrosion is determined based on the second data-position matrix and the standard pipeline thickness; a processing unit configured to determine a current state parameter according to the pipeline corrosion amount and the pipeline parameter, and compare the current state parameter with a 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 exceeds a corrosion threshold.

9. 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 according to any one of claims 1 to 7.

10. 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 according to any one of claims 1 to 7 is implemented.

Images