Pipeline coating thickness early warning system and method

Abstract

The invention relates to the technical field of pipeline early warning, and discloses a pipeline coating thickness early warning system and method, and the system comprises a collection module which is configured to collect the pipeline information of a to-be-monitored point, and obtains the thickness data of a pipeline coating according to an ultrasonic sensor; the data processing module is configured to obtain and calculate the detection time according to the detection interval, establish a time-thickness curve according to the detection time and the thickness data corresponding to the detection time, and calculate the slope of the time-thickness curve; the first reference module is configured to obtain first detection time according to the slope; the second reference module is configured to obtain second detection time when the thickness data is equal to a thickness threshold value according to the time-thickness curve of the comparison monitoring point; and the early warning module is configured to determine the early warning time when the pipeline coating thickness has the safety risk according to the first detection time and the second detection time. The early warning efficiency of the pipeline coating thickness is improved.

Description

Technical Field

[0001] The present application relates to the technical field of pipeline early warning, and in particular, to a pipeline coating thickness early warning system and method. Background Art

[0002] With the wide application of pipeline transportation systems, especially in industries such as oil, natural gas, and chemicals, the safety and long-term stability of pipelines have become key issues. Pipeline coatings, as an effective measure for anti-corrosion, anti-wear, and improving pipeline durability, have become an important part of pipeline construction. The thickness of the coating directly affects the service life of the pipeline and its anti-corrosion performance. However, as the service life of the pipeline increases, the coating may become thinner or damaged to varying degrees due to environmental factors, the corrosiveness of the transportation medium, and mechanical wear. The damage to the coating not only affects the safety of the pipeline but may also trigger major safety accidents such as leakage and corrosion. Especially for pipelines transporting flammable and explosive media, the risk of weak coatings is particularly serious.

[0003] In related technologies, the monitoring methods for pipeline coating thickness mostly rely on detecting the pipeline coating thickness through manual regular inspections or local area detection methods (such as eddy current detection, ultrasonic detection), and timely discovering pipeline monitoring points with potential safety risks. Due to the different knowledge reserves of technicians, the accuracy of manual monitoring of pipeline coating thickness is low, and pipeline monitoring points with potential safety risks cannot be discovered in a timely manner. Therefore, how to improve the early warning efficiency of pipeline coating thickness remains a technical problem to be solved. Summary of the Invention

[0004] In view of this, the present invention proposes a pipeline coating thickness early warning system and method, aiming to improve the early warning efficiency of pipeline coating thickness.

[0005] In a first aspect, a pipeline coating thickness system proposed by the present invention includes:

[0006] The acquisition module includes an ultrasonic sensor installed at the point to be monitored; the acquisition module is configured to acquire pipeline information at the point to be monitored and obtain thickness data of the pipeline coating according to the ultrasonic sensor; the data processing module is configured to obtain and calculate the detection time according to the detection interval, establish a time-thickness curve for the detection time and the corresponding thickness data, store the time-thickness curve according to the identifier of the point to be monitored, and calculate the slope of the time-thickness curve; the first reference module is configured to determine whether to adjust the thickness threshold to obtain a corrected threshold according to the slope; determine whether to adjust the detection interval to obtain a corrected detection interval according to the slope; fit the time-thickness curve of the point to be monitored to obtain a time-thickness function, input the corrected threshold into the time-thickness function to obtain the first detection time; the second reference module is configured to, when the slope of the point to be monitored is negative, determine similar monitoring points from the set of monitoring points other than the point to be monitored according to the pipeline information; calculate the similarity result between the slope of the point to be monitored and the slope of each monitoring point in the similar monitoring points, and determine a comparison monitoring point from the similar monitoring points based on the similarity result; the similarity result of the comparison monitoring point is greater than the first threshold; obtain the second detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring point; the warning module is configured to determine the warning time of the safety risk of the pipeline coating thickness according to the first detection time and the second detection time.

[0007] Optionally, compare the slope threshold with the slope;

[0008] When the slope is less than or equal to the slope threshold, it is determined that the thickness threshold needs to be adjusted; when the slope is greater than the slope threshold, it is determined that the thickness threshold is not adjusted;

[0009] The slope threshold satisfies the following formula:

[0010]

[0011] where k 0 represents the slope threshold, t i represents the i-th detection interval, d i represents the coating thickness of the i-th detection, λ is the attenuation factor, which is used to represent the speed of the consumption rate of the coating thickness over time, 0.01 ≤ λ ≤ 0.05, n is the total number of detections, t represents the average value of the n detection intervals, and d represents the average value of the coating thickness of the n detections.

[0012] Optionally, the corrected threshold satisfies the following formula: m' = m(1 + k 0 - k); where m' represents the corrected threshold; k represents the slope; k 0 represents the slope threshold; m represents the thickness threshold.

[0013] Optionally, the first reference module determines whether to adjust the detection interval to obtain a corrected detection interval based on the slope, including: when the slope is less than or equal to the slope threshold, it is determined that the detection interval needs to be corrected; obtaining the minimum detection interval of the acquisition module, and determining the corrected detection interval based on the minimum detection interval; the corrected detection interval satisfies the following formula: where t ′ represents the corrected detection interval.

[0014] Optionally, the time-thickness function satisfies the following formula:

[0015]

[0016] where a represents the slope of the straight line and b represents the intercept.

[0017] Optionally, the second reference module determines similar monitoring points from the set of monitoring points other than the monitoring point according to the pipeline information, including: comparing the pipeline information of the point to be monitored with the pipeline information of the monitoring points in the first monitoring point set, and determining similar monitoring points from the first set; the first monitoring point set is the set of monitoring points other than the point to be monitored, and the similarity between the pipeline information of the similar monitoring points and the pipeline information of the point to be monitored is greater than the second threshold; the pipeline information is the pipeline material, pipeline inner diameter, pipeline service life, transportation medium type and medium flow rate.

[0018] Optionally, the second reference module calculates the similarity result between the slope of the point to be monitored and the slope of each monitoring point in the similar monitoring points, and determines the comparison monitoring point from the similar monitoring points, including:

[0019] obtaining N groups of consecutive first thickness data with a negative slope in the point to be monitored; obtaining N groups of consecutive second thickness data with a negative slope in the similar monitoring points, calculating the first difference between the first thickness data and the second thickness data, and calculating the second difference between the first slope corresponding to the first thickness data and the second slope corresponding to the second thickness data; determining the comparison monitoring point from the similar monitoring points; the comparison monitoring point is the monitoring point with the smallest first difference and second difference in the similar monitoring.

[0020] Optionally, the second reference module obtains the detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring point, including: inputting the thickness threshold into the time-thickness curve of the comparison monitoring point to obtain the second detection time.

[0021] Optionally, the warning time includes the following formula: P = min(p1, p2); where P represents the warning time, p1 represents the first detection time, and p2 represents the second detection time.

[0022] Optionally, the detection time satisfies the following formula: Among them, T represents the detection time, and t i represents the i-th detection interval.

[0023] In a second aspect, a method for warning of pipeline coating thickness is provided, including: collecting pipeline information of a point to be monitored through an ultrasonic sensor, and obtaining thickness data of the pipeline coating according to the ultrasonic sensor; obtaining and calculating the detection time according to the detection interval, establishing a time-thickness curve for the detection time and the thickness data corresponding to the detection time, and storing the time-thickness curve according to the identifier of the point to be monitored, and calculating the slope of the time-thickness curve; judging whether to adjust the thickness threshold according to the slope to obtain a corrected threshold; judging whether to adjust the detection interval according to the slope to obtain a corrected detection interval; fitting the time-thickness curve of the point to be monitored to obtain a time-thickness function, inputting the corrected threshold into the time-thickness function to obtain a first detection time; when the slope of the point to be monitored is negative, determining a similar monitoring point from the set of monitoring points other than the point to be monitored according to the pipeline information; calculating the similarity result between the slope of the point to be monitored and the slope of each monitoring point in the similar monitoring points, and determining a comparison monitoring point from the similar monitoring points based on the similarity result; the similarity result of the comparison monitoring point is greater than a first threshold; obtaining the detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring point, denoted as a second detection time; determining a warning time for the pipeline coating thickness to have a safety risk according to the first detection time and the second detection time.

[0024] In a third aspect, a warning device for pipeline coating thickness is provided, including a memory and a processor; the memory is used for storing computer execution instructions, and the processor is connected to the memory through a bus; when the warning device for pipeline coating thickness runs, the processor executes the computer execution instructions stored in the memory, so that the warning device for pipeline coating thickness executes the method for warning of pipeline coating thickness in the second aspect.

[0025] The warning device for pipeline coating thickness can be a network device or a part of a device in the network device, such as a chip system in the network device. The chip system is used to support the network device to implement the functions involved in the first aspect and any one of its possible implementation manners. For example, obtaining, determining, and sending the data and / or information involved in the method for warning of pipeline coating thickness described above. The chip system includes a chip and may also include other discrete devices or circuit structures.

[0026] In a fourth aspect, a computer-readable storage medium is provided, and the computer-readable storage medium includes computer execution instructions. When the computer execution instructions run on a computer, the computer executes the method for warning of pipeline coating thickness in the second aspect.

[0027] In a fifth aspect, a computer program product is further provided. The computer program product includes computer instructions that, when running on a warning device for pipeline coating thickness, cause the warning device for pipeline coating thickness to execute the warning method for pipeline coating thickness as described in the second aspect above.

[0028] It should be noted that the above computer instructions may be stored in whole or in part on a computer-readable storage medium. Among them, the computer-readable storage medium may be packaged together with the processor of the warning device for pipeline coating thickness, or may be separately packaged from the processor of the warning device for pipeline coating thickness. The embodiments of the present application do not make any limitations in this regard.

[0029] For the descriptions of the second aspect, the third aspect, the fourth aspect, and the fifth aspect in the present application, reference may be made to the detailed description of the first aspect.

[0030] In the embodiments of the present application, the name of the above warning device for pipeline coating thickness does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear under other names. For example, the receiving unit may also be referred to as a receiving module, a receiver, etc. As long as the functions of each device or functional module are similar to those of the present application and fall within the scope of the claims of the present application and their equivalent technologies.

[0031] The present application provides an early warning system and method for the thickness of a pipeline coating. By collecting the thickness data of the pipeline coating in real time and calculating the slope of the time-thickness curve, the attenuation rate of the pipeline coating can be accurately monitored. This is of great significance for timely detecting potential problems such as too thin coating and aggravated corrosion, thereby effectively improving the safety and operation reliability of the pipeline. The pipeline coating thickness early warning system can automatically determine whether to adjust the preset thickness threshold according to the changes in the slope and thickness data. When the coating consumption rate accelerates, the thickness threshold and detection interval are modified to monitor the coating changes more frequently to ensure timely detection of risks. By screening similar monitoring points according to pipeline information, the pipeline coating thickness early warning system can compare with the historical data of similar monitoring points to further optimize the early warning strategy and reduce the risk of false alarms or missed alarms. Using the time-thickness curve fitting method to model the law of coating thickness change as a function can more accurately predict the consumption trend of the pipeline coating. The pipeline coating thickness early warning system can predict the future state of the coating according to the thickness threshold and historical data, further improving the accuracy and intelligent level of pipeline management. By analyzing, screening, and comparing the slopes of the monitoring points, the system can better identify the pipeline monitoring points with a faster coating attenuation rate, timely adjust the detection strategy, and concentrate resources for maintenance. This not only helps to extend the service life of the pipeline but also reduces the maintenance cost and the frequency of human intervention. The present application can improve the early warning efficiency of the pipeline coating thickness, timely detect abnormal changes in the pipeline coating, and avoid accidents such as corrosion and leakage caused by too thin coating thickness, thereby improving the safety of the pipeline. At the same time, the automatic adjustment and prediction functions reduce the need for human intervention and improve the efficiency and maintainability of pipeline management. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present application. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0033] Figure 1 is a structural block diagram of an early warning system for the thickness of a pipeline coating provided by an embodiment of the present application;

[0034] Figure 2 is a flow block diagram of an early warning method for the thickness of a pipeline coating provided by an embodiment of the present application;

[0035] Figure 3 is a structural block diagram of an early warning device for the thickness of a pipeline coating provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the 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 so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0037] In some embodiments of the present application, referring to Figure 1 as shown, an early warning system for the thickness of a pipeline coating includes: a collection module, a data processing module, a first reference module, a second reference module, and an early warning module.

[0038] Among them, the collection module includes an ultrasonic sensor installed at the point to be monitored; the collection module is configured to collect pipeline information at the point to be monitored and obtain the thickness data of the pipeline coating according to the ultrasonic sensor.

[0039] In a possible implementation, the collection module obtains the thickness data of the coating through an ultrasonic sensor by means of a collector, and the collector is also used to configure the detection interval.

[0040] Optionally, the collector is an intermediate device connecting the ultrasonic sensor and the data processing module, and is responsible for collecting, storing, and transmitting the coating thickness data measured by the ultrasonic sensor.

[0041] Optionally, the model of the ultrasonic sensor is TMS-B or TMS-S, the probe accuracy is 0.05 mm, and the resolution accuracy is 0.01 mm. The sensor is a wireless passive sensor.

[0042] It should be explained that the ultrasonic sensor is one of the core components of the collection module, and it is used to measure the thickness of the pipeline coating in a non-contact manner. The ultrasonic sensor calculates the thickness of the coating by emitting an ultrasonic signal and receiving the time difference of the signal return and the speed of sound wave propagation.

[0043] It can be understood that the present application monitors the thickness of the pipeline coating in real time through the ultrasonic sensor of the collection module, and combines the detection interval configured by the collector to achieve accurate tracking and data collection of the thickness of the pipeline coating. By continuously obtaining the coating thickness data at the monitoring point, the trend of coating consumption can be reflected in a timely manner, avoiding the problems of long traditional manual detection cycles and untimely data, and ensuring that the state of the pipeline coating is always under monitoring.

[0044] Furthermore, the collector receives the measurement data of the coating thickness from the ultrasonic sensor and temporarily stores these data in the memory or storage. To ensure the accuracy and reliability of the data, the collector regularly activates the sensor for measurement and obtains a set of stable thickness data.

[0045] It should be noted that the collector is not only responsible for data acquisition but also can configure different detection intervals according to system settings. For example, the collector adjusts the detection interval based on factors such as the pipeline status, ambient temperature, and coating type to ensure the real-time nature of the detection results and the low-power mode of the system. The collector can also automatically adjust the detection interval according to the slope change, so as to extend the detection cycle when the coating consumption is slow.

[0046] Optionally, the collector not only measures the coating thickness but also collects other information related to the pipeline. Other information related to the pipeline includes but is not limited to: pipeline material: for pipelines of different materials such as steel, stainless steel, and polyethylene, the coating consumption may vary; pipeline inner diameter: the diameter of the pipeline affects the thickness distribution and consumption rate of the coating; pipeline service life: as the pipeline service life increases, the coating consumption will change; type and flow rate of the transported medium: the transported medium (such as natural gas, oil, water, etc.) and its flow rate also affect the consumption rate of the pipeline coating, especially factors such as friction and corrosion will cause the coating to wear more severely. This information is read by the sensor and transmitted to the collector, and then analyzed and stored by the collector to provide support for subsequent data processing and judgment.

[0047] The data processing module is configured to obtain and calculate the detection time according to the detection interval, establish a time-thickness curve for the detection time and the thickness data corresponding to the detection time, store the time-thickness curve according to the identifier of the point to be monitored, and calculate the slope of the time-thickness curve.

[0048] Among them, the detection time satisfies the following formula: Among them, T represents the detection time, and t i represents the i-th detection interval.

[0049] The data processing module obtains the coating thickness data and pipeline information collected by the collector through a wireless communication module (Wi-Fi, Zigbee, LoRa) or a wired communication interface (Ethernet, serial port). The data processing module further processes the data according to a preset algorithm, generates a time-thickness curve, conducts slope analysis, and determines whether it is necessary to adjust the thickness threshold and detection interval.

[0050] A first reference module, configured to determine whether to adjust a thickness threshold to obtain a corrected threshold according to a slope; determine whether to adjust a detection interval to obtain a corrected detection interval according to the slope; fit a time-thickness curve of a point to be monitored to obtain a time-thickness function, and input the corrected threshold into the time-thickness function to obtain a first detection time.

[0051] Wherein, the corrected threshold satisfies the following formula:

[0052] m’ = m(1 + k 0 - k);

[0053] Wherein, m’ represents the corrected threshold; k represents the slope; k 0 represents the slope threshold; m represents the thickness threshold.

[0054] It should be noted that when the warning system for the pipeline coating thickness determines that the thickness threshold needs to be adjusted according to the change trend of the coating thickness, the corrected thickness threshold is calculated according to the relationship between the slope and the slope threshold. This adjustment can help the system dynamically correct the thickness threshold according to the actual situation of the coating consumption rate, thereby improving the accuracy and response speed of the warning system.

[0055] Specifically, the calculation process of the corrected threshold takes into account the slope of the time-thickness curve corresponding to the current monitoring point and the preset slope threshold. If it is determined that the thickness threshold needs to be adjusted after comparing the current slope value with the set slope threshold, the corrected threshold will be calculated according to the difference between the two. In this way, the warning system for the pipeline coating thickness can intelligently update the threshold according to the coating consumption rate and the time change trend, so as to accurately reflect the current state and future change trend of the coating. In this way, it is ensured that in practical applications, the coating thickness threshold can adapt to the actual working conditions of the pipeline and the coating consumption situation, so that when the coating thickness approaches the preset threshold, the system can issue a warning in time and take appropriate maintenance measures. At the same time, the corrected threshold is more flexible and can be dynamically adjusted according to the actual situation, further improving the reliability and intelligent level of the pipeline monitoring system.

[0056] The time-thickness function satisfies the following formula:

[0057]

[0058] Wherein, a represents the slope of the straight line, and b represents the intercept.

[0059] It should be noted that the data processing module can intelligently determine whether it is necessary to adjust the preset coating thickness threshold based on the slope analysis of the time-thickness curve. When the coating consumption rate changes significantly, the early warning system for pipeline coating thickness can automatically adjust the threshold or detection interval, avoiding the limitations of manual intervention. Through the intelligent slope calculation and adjustment mechanism, the system can achieve the optimal monitoring frequency, improve the monitoring accuracy and reduce resource waste.

[0060] It can be understood that the data processing module fits the time-thickness curve of the monitoring point to generate a time-thickness function, and calculates the first detection time after substituting the corrected threshold. In this way, the change of the coating thickness at a certain future time point can be accurately predicted, and the moment when the coating may reach the dangerous thickness can be identified in advance, thus providing reliable decision-making support for pipeline maintenance and repair.

[0061] The second reference module is configured to, when the slope of the monitoring point to be monitored is negative, determine similar monitoring points from the set of monitoring points other than the monitoring point to be monitored according to the pipeline information; calculate the similarity results between the slope of the monitoring point to be monitored and the slopes of each monitoring point in the similar monitoring points, and determine the comparison monitoring point from the similar monitoring points based on the similarity results; the similarity result of the comparison monitoring point is greater than the first threshold; obtain the second detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring point.

[0062] It should be noted that when the slope of the monitoring point is negative, the second reference module can screen out similar monitoring points based on the pipeline information, compare the slope of the similar monitoring points with the current monitoring point, and find the closest comparison monitoring point. Through this comparison mechanism, the early warning system for pipeline coating thickness can more accurately evaluate the trend of coating thickness change, identify potential coating consumption problems, and provide targeted early warning information for maintenance personnel.

[0063] The early warning module is configured to determine the early warning time when there is a safety risk in the pipeline coating thickness according to the first detection time and the second detection time.

[0064] Among them, the early warning time includes the following formula: P = min(p1, p2); where P represents the early warning time, p1 represents the first detection time, and p2 represents the second detection time.

[0065] It should be noted that the early warning system for pipeline coating thickness selects the detection time with the smallest value from the first detection time and the second detection time as the early warning time.

[0066] Optionally, the value of the early warning time is inversely proportional to the severity of the early warning level. This ensures the earliest warning of coating problems, reduces the risk of pipeline damage, and improves the safety of the pipeline. The inverse relationship between the early warning time and the early warning level means that when the early warning time is short, it indicates that the coating thickness loss is fast, the early warning level is high, and maintenance work needs to intervene as soon as possible; while when the early warning time is long, it means that the coating loss rate is low and the early warning level is low.

[0067] Optionally, the early warning system for the pipeline coating thickness can automatically adjust the priority of the alarm according to the actual situation of the coating change by calculating the early warning time between the first detection time and the second detection time and setting the early warning level according to the early warning time.

[0068] It should be noted that after obtaining the first detection time and the second detection time, the early warning system for the pipeline coating thickness calculates these two times to obtain the early warning time. The early warning time is based on the coating thickness change trend and the corrected time prediction, and can give an early warning signal that the pipeline coating may reach the threshold in advance.

[0069] Specifically, the early warning system for the pipeline coating thickness compares and calculates the first detection time and the second detection time to obtain the early warning time. The calculation of the early warning time is not only a response to the change of the pipeline coating thickness, but also can provide a more targeted early warning signal. Since the above calculation is based on historical data and time prediction models, the maintenance and management of the pipeline can be more forward-looking and accurate.

[0070] It can be understood that by operating the first detection time and the second detection time, the early warning system for the pipeline coating thickness can obtain an early warning time that comprehensively considers factors such as the coating consumption rate and the attenuation factor. In addition, in some embodiments of the present application, the detection time is obtained by summing all detection intervals. Specifically, each detection interval is automatically calculated by the system according to the time interval set by the acquisition module. After these detection intervals are accumulated, a total detection time is obtained. The total detection time reflects the time span from the start of the first monitoring to the current monitoring point, and can effectively help predict the trend of the coating thickness change over time.

[0071] It should be explained that the early warning time is usually used to judge the future change trend of the pipeline coating and judge the loss state of the coating in combination with the preset threshold.

[0072] In some embodiments of the present application, the first reference module judges whether to adjust the thickness threshold according to the slope, including:

[0073] Comparing the slope threshold with the slope; when the slope is less than or equal to the slope threshold, it is judged that the thickness threshold needs to be adjusted; when the slope is greater than the slope threshold, it is judged that the thickness threshold is not adjusted.

[0074] The slope threshold satisfies the following formula:

[0075]

[0076] where k 0 represents the slope threshold, t i represents the i-th detection interval, d i represents the coating thickness of the i-th detection, λ is the attenuation factor, which is used to represent the speed of the consumption rate of the coating thickness with time, 0.01 ≤ λ ≤ 0.05, n is the total number of detections, represents the average value of n detection intervals, represents the average value of the coating thickness of n detections.

[0077] In some embodiments of the present application, the first reference module determines whether to adjust the detection interval to obtain a corrected detection interval according to the slope, including:

[0078] When the slope is less than or equal to the slope threshold, it is determined that the detection interval needs to be corrected; the minimum detection interval of the acquisition module is obtained, and the corrected detection interval is determined based on the minimum detection interval.

[0079] where the corrected detection interval satisfies the following formula:

[0080] where t ′ represents the corrected detection interval.

[0081] It should be noted that the early warning system for the pipeline coating thickness will determine whether to adjust the detection interval according to the change of the slope, so as to better adapt to the trend of the coating thickness change and provide more accurate monitoring.

[0082] Specifically, when the calculated slope of the coating thickness is less than or equal to the preset slope threshold, the early warning of the pipeline coating thickness determines that the attenuation rate of the coating thickness is slow and the detection interval needs to be adjusted. The purpose of this adjustment is to optimize the monitoring frequency. In the case where the coating changes relatively slowly, unnecessary frequent detections are reduced, thereby reducing energy consumption and extending the service life of the sensor, while maintaining sufficient monitoring accuracy.

[0083] When the system determines that the detection interval needs to be adjusted, the corrected detection interval will be calculated based on the minimum detection interval of the acquisition module. The determination of the corrected detection interval satisfies a certain relationship, so that the system can dynamically adjust the detection frequency according to the actual coating attenuation rate. If the coating consumption is slow, the corrected detection interval can be reduced to reduce redundant data in the acquisition process; conversely, if the slope is large (i.e., the coating consumption is fast), the detection frequency will be increased accordingly to ensure that the change of the coating thickness can be captured in time.

[0084] This flexible detection interval adjustment mechanism can improve the monitoring efficiency, ensure that the system maintains the best performance under different working environments and coating consumption rates, and achieve a more accurate and energy-saving monitoring effect.

[0085] In some embodiments of the present application, the second reference module determines similar monitoring points from the set of monitoring points other than the monitoring point according to the pipeline information, including:

[0086] Compare the pipeline information of the point to be monitored with the pipeline information of the monitoring points in the first set of monitoring points, and determine similar monitoring points from the first set.

[0087] Among them, the first set of monitoring points is the set of monitoring points other than the point to be monitored, and the similarity between the pipeline information of the similar monitoring points and the pipeline information of the point to be monitored is greater than the second threshold. The pipeline information is pipeline material, pipeline inner diameter, pipeline service life, type of transported medium, and medium flow rate.

[0088] It should be noted that in some embodiments of the present application, when judging whether to adjust the thickness threshold according to the change slope of the coating thickness of the monitoring point, the early warning system of the pipeline coating thickness will set a slope threshold. If the change slope of the coating thickness of the monitoring point is less than or equal to the set slope threshold, the early warning system of the pipeline coating thickness judges that the thickness threshold needs to be adjusted. On the contrary, if the slope is greater than the slope threshold, it means that the coating thickness changes rapidly, and the early warning system of the pipeline coating thickness determines that there is no need to adjust the thickness threshold. In this way, the early warning system of the pipeline coating thickness can dynamically adjust the monitoring standard according to the actual situation of coating consumption, ensuring that the monitoring threshold is more in line with the actual consumption situation.

[0089] When the thickness threshold needs to be adjusted, the early warning system of the pipeline coating thickness will also adjust the detection frequency according to the coating consumption rate. If the slope is less than or equal to the set threshold, it means that the coating consumption is slow, and the system will appropriately extend the detection interval, thereby reducing the energy consumption and system burden caused by frequent detection. If the slope is large, it means that the coating consumption is fast, and the system will correspondingly increase the detection frequency to ensure that the change of the coating thickness is detected in time. This correction mechanism can flexibly adjust the monitoring frequency according to the actual situation, achieving the purpose of energy saving and efficient monitoring.

[0090] It should be explained that the time and coating thickness data of the monitoring point will be converted into a time-thickness function through a fitting algorithm. The core of this process is to fit a straight line describing the change of coating thickness with time through multiple detection data. Through this fitting line, the early warning system of the pipeline coating thickness can predict the change of the coating thickness at a future time point, and further adjust the thickness threshold and detection strategy according to this trend, thereby improving the early warning ability and response efficiency of the system.

[0091] It is understandable that when the slope of the coating thickness change at a certain monitoring point is negative, it indicates that the coating at this monitoring point is consumed relatively fast, and the system will screen out other similar monitoring points based on the relevant information of the pipeline. By comparing these pipeline information, the system can screen out those monitoring points with similar consumption rates as "similar monitoring points". By comparing with the time-thickness curves of these similar monitoring points, the system can more accurately judge the coating consumption trend of the current monitoring point and make corresponding adjustments.

[0092] Optionally, the system of the present invention can dynamically adjust the monitoring frequency and threshold according to the change of coating consumption, avoid overly frequent detection, and reduce unnecessary energy consumption. By fitting the time-thickness curve and screening similar monitoring points, the system not only improves the prediction accuracy, but also can timely detect abnormal situations in the change of coating consumption. In summary, the system can optimize the monitoring strategy, improve efficiency, and ensure the safety and service life of the pipeline coating while ensuring long-term stable operation.

[0093] In this embodiment, by calculating the slope threshold and comparing it with the current slope, the coating thickness threshold and detection frequency are intelligently adjusted to adapt to the changes in different coating consumption rates. This method can effectively cope with the situation of gradual consumption of the pipeline coating thickness, improve the flexibility and adaptability of the system while ensuring the monitoring accuracy. In addition, the acquisition mechanism of the slope threshold and the adjustment mechanism of the thickness threshold make the system have strong self-adaptive ability.

[0094] Optionally, the judgment conditions for similar monitoring points are: the pipeline materials are the same, the types of transported media are the same, the current pipeline inner diameter / the pipeline inner diameter of the other monitoring points ≥ 0.8, 0.8 ≤ the current pipeline service life / the service life of the other monitoring points ≤ 1.2, and 0.8 ≤ the current pipeline flow rate / the pipeline flow rate of the other monitoring points ≤ 1.2.

[0095] In some embodiments of the present application, the second reference module calculates the similarity results between the slope of the monitoring point to be monitored and the slope of each monitoring point in the similar monitoring points, and determines the comparison monitoring points from the similar monitoring points, including:

[0096] Obtain N groups of consecutive first thickness data with negative slopes in the monitoring point to be monitored; obtain N groups of consecutive second thickness data with negative slopes in the similar monitoring points, calculate the first difference between the first thickness data and the second thickness data, calculate the second difference between the first slope corresponding to the first thickness data and the second slope corresponding to the second thickness data; determine the comparison monitoring points from the similar monitoring points; the comparison monitoring point is the monitoring point with the smallest first difference and second difference in the similar monitoring.

[0097] It should be noted that when the slope of the coating thickness change at the monitoring point is negative, it indicates that the coating thickness at this monitoring point is decreasing, and the early warning system for pipeline coating thickness will conduct further analysis on this monitoring point.

[0098] Specifically, the early warning system for pipeline coating thickness will select N consecutive groups of data among the current monitoring points, and the slopes of these data are all negative, that is to say, the coating thickness continuously decreases during this period. To improve the prediction accuracy, the system will screen out the thickness data with N consecutive negative slopes among other monitoring points as "similar monitoring points". The early warning system for pipeline coating thickness compares the slopes and thickness data of these selected similar monitoring points with those of the current monitoring point.

[0099] Optionally, the early warning system for pipeline coating thickness calculates the differences in slope and thickness data between the similar monitoring points and the current monitoring point, and selects the similar monitoring points with the smallest differences in both slope and thickness data as "comparison monitoring points".

[0100] Through this comparison process, the system can find the monitoring point that is most similar to the current monitoring point in terms of coating consumption rate and change trend, and predict the coating consumption trend of the current monitoring point based on the historical data of this comparison monitoring point. This not only helps to improve the accuracy of coating thickness monitoring, but also enables the system to better identify abnormal situations and early warn of potential coating damage risks.

[0101] In some embodiments of the present application, the second reference module obtains the detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring point, including: inputting the thickness threshold into the time-thickness curve of the comparison monitoring point to obtain the second detection time.

[0102] It should be noted that when the slope of the monitoring point is negative, the early warning system for pipeline coating thickness will screen the data of other monitoring points to obtain a more accurate coating consumption trend.

[0103] Specifically, when obtaining the comparison monitoring point, the early warning system for pipeline coating thickness starts from the current monitoring point and selects N consecutive groups of thickness data with negative slopes. Screen out N groups of thickness data with continuously negative slopes among other monitoring points to form a set of candidate monitoring points.

[0104] Optionally, these N consecutive groups of thickness data with negative slopes represent the attenuation trend of the coating thickness within a certain period of time.

[0105] Specifically, in order to find the most matching comparison monitoring point, the early warning system for pipeline coating thickness will screen by comparing the similarity between the current monitoring point and the candidate monitoring points. The system will calculate the slope difference and the coating thickness data difference between the current monitoring point and the candidate monitoring points, and select the candidate monitoring point with the smallest slope difference and thickness difference as the comparison monitoring point. In this way, it is ensured that the selected comparison monitoring point is closest to the current monitoring point in terms of attenuation rate and coating thickness change trend, thereby improving the accuracy of comparative analysis.

[0106] After obtaining the comparison monitoring point, the system will use the time-thickness curve of this comparison monitoring point for further calculation. Specifically, the system will substitute the set thickness threshold into the time-thickness curve of the comparison monitoring point, and calculate the time point when the coating thickness reaches the set threshold under this curve. This time point is the second detection time.

[0107] Since the calculation method of the second detection time is based on the historical data of the comparison monitoring point through an accurate fitting algorithm. Therefore, the early warning system for pipeline coating thickness can accurately predict the time when the pipeline coating reaches the set thickness threshold at a certain future moment. This result can be used as a key basis for pipeline health management to early warn of possible losses of the pipeline coating and help maintenance personnel formulate maintenance plans in advance. The second detection time calculated through the time-thickness curve of the comparison monitoring point can effectively improve the accuracy and efficiency of pipeline management, avoid the occurrence of sudden failures, and ensure the safe and stable operation of the pipeline system.

[0108] In some embodiments, as Figure 2 shown, the embodiment of the present application also provides an early warning method for pipeline coating thickness, which is applied to the early warning system for pipeline coating thickness in the above Figure 1 , and includes:

[0109] S201. Collect pipeline information of the to-be-monitored point through an ultrasonic sensor, and obtain the thickness data of the pipeline coating according to the ultrasonic sensor.

[0110] S202. Obtain and calculate the detection time according to the detection interval, establish a time-thickness curve for the detection time and the thickness data corresponding to the detection time, store the time-thickness curve according to the identifier of the to-be-monitored point, and calculate the slope of the time-thickness curve.

[0111] Wherein, the detection time satisfies the following formula: Wherein, T represents the detection time, and t i represents the i-th detection interval.

[0112] S203. Determine whether to adjust the thickness threshold to obtain a corrected threshold according to the slope; determine whether to adjust the detection interval to obtain a corrected detection interval according to the slope; fit the time-thickness curve of the point to be monitored to obtain a time-thickness function, and input the corrected threshold into the time-thickness function to obtain the first detection time.

[0113] Among them, the corrected threshold satisfies the following formula: m' = m(1 + k 0 - k); where, m' represents the corrected threshold; k represents the slope; k 0 represents the slope threshold; m represents the thickness threshold.

[0114] S204. When the slope of the point to be monitored is negative, determine similar monitoring points from the set of monitoring points other than the point to be monitored according to the pipeline information; calculate the similarity results between the slope of the point to be monitored and the slopes of each monitoring point in the similar monitoring points, and determine the comparison monitoring points from the similar monitoring points based on the similarity results; obtain the second detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring points.

[0115] Among them, the similarity result of the comparison monitoring point is greater than the first threshold.

[0116] Optionally, the time-thickness function satisfies the following formula:

[0117]

[0118] Among them, a represents the slope of the straight line, and b represents the intercept.

[0119] S205. Determine the warning time when there is a safety risk in the pipeline coating thickness according to the first detection time and the second detection time.

[0120] The warning time includes the following formula: P = min(p1, p2); where, P represents the warning time, p1 represents the first detection time, and p2 represents the second detection time.

[0121] This application provides an early warning system and method for the thickness of pipeline coatings. By collecting the thickness data of pipeline coatings in real time and calculating the slope of the time-thickness curve, the attenuation rate of pipeline coatings can be accurately monitored. This is of great significance for timely detecting potential problems such as too thin coatings and increased corrosion, thereby effectively improving the safety and operational reliability of pipelines. The pipeline coating thickness early warning system can automatically determine whether to adjust the preset thickness threshold according to the changes in the slope and thickness data. When the coating consumption rate accelerates, the thickness threshold and detection interval are modified to monitor the coating changes more frequently to ensure timely detection of risks. By screening similar monitoring points based on pipeline information, the pipeline coating thickness early warning system can compare with the historical data of similar monitoring points to further optimize the early warning strategy and reduce the risk of false alarms or missed alarms. Using the time-thickness curve fitting method to model the law of coating thickness change as a function can more accurately predict the consumption trend of pipeline coatings. The pipeline coating thickness early warning system can predict the future state of the coating based on the thickness threshold and historical data, further improving the accuracy and intelligent level of pipeline management. By analyzing, screening, and comparing the slopes of monitoring points, the system can better identify the pipeline monitoring points with a faster coating attenuation rate, timely adjust the detection strategy, and concentrate resources for maintenance. This not only helps to extend the service life of pipelines but also reduces maintenance costs and the frequency of human intervention. This application can improve the early warning efficiency of pipeline coating thickness, timely detect abnormal changes in pipeline coatings, and avoid accidents such as corrosion and leakage caused by too thin coating thickness, thereby improving the safety of pipelines. At the same time, the automatic adjustment and prediction functions reduce the need for human intervention and improve the efficiency and maintainability of pipeline management.

[0122] In some embodiments of this application, in the above S204, judging whether to adjust the thickness threshold according to the slope includes:

[0123] Comparing the slope threshold with the slope; when the slope is less than or equal to the slope threshold, it is judged that the thickness threshold needs to be adjusted; when the slope is greater than the slope threshold, it is judged that the thickness threshold is not adjusted; the slope threshold satisfies the following formula:

[0124] where k 0 represents the slope threshold, t i represents the i-th detection interval, d i represents the coating thickness of the i-th detection, λ is the attenuation factor, used to represent the speed of the coating thickness consumption rate over time, 0.01 ≤ λ ≤ 0.05, n is the total number of detections, t represents the average value of the n detection intervals, and d represents the average value of the coating thickness of the n detections.

[0125] In some embodiments of the present application, in the above S204, determining whether to adjust the detection interval to obtain a corrected detection interval according to the slope includes:

[0126] When the slope is less than or equal to the slope threshold, it is determined that the detection interval needs to be corrected; obtain the minimum detection interval of the acquisition module, and determine the corrected detection interval based on the minimum detection interval; the corrected detection interval satisfies the following formula:

[0127] where t ′ represents the corrected detection interval.

[0128] In some embodiments of the present application, in the above S205, determining similar monitoring points from the set of monitoring points other than the monitoring point according to the pipeline information includes:

[0129] Compare the pipeline information of the point to be monitored with the pipeline information of the monitoring points in the first set of monitoring points, and determine similar monitoring points from the first set; the first set of monitoring points is the set of monitoring points other than the point to be monitored, and the similarity between the pipeline information of the similar monitoring points and the pipeline information of the point to be monitored is greater than the second threshold; the pipeline information is the pipeline material, pipeline inner diameter, pipeline service life, type of transported medium, and medium flow rate.

[0130] In some embodiments of the present application, in the above S205, calculating the similarity result between the slope of the point to be monitored and the slope of each monitoring point in the similar monitoring points, and determining the comparison monitoring point from the similar monitoring points according to the similarity result includes:

[0131] Obtain N groups of consecutive first thickness data with a negative slope in the point to be monitored; obtain N groups of consecutive second thickness data with a negative slope in the similar monitoring points, calculate the first difference between the first thickness data and the second thickness data, and calculate the second difference between the first slope corresponding to the first thickness data and the second slope corresponding to the second thickness data; determine the comparison monitoring point from the similar monitoring points.

[0132] where the comparison monitoring point is the monitoring point with the smallest first difference and second difference among the similar monitoring points.

[0133] In some embodiments of the present application, in the above S205, obtaining the detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring point includes: inputting the thickness threshold into the time-thickness curve of the comparison monitoring point to obtain the second detection time.

[0134] As Figure 3 shown, it is a schematic structural diagram of an early warning device for pipeline coating thickness provided by an embodiment of the present application. Figure 3 The early warning device for pipeline coating thickness shown includes: an acquisition unit 301 and a processing unit 302;

[0135] An acquisition unit 301, configured to collect pipeline information of a to-be-monitored point and obtain thickness data of a pipeline coating according to an ultrasonic sensor. A processing unit 302, configured to obtain and calculate a detection time according to a detection interval, establish a time-thickness curve for the detection time and the thickness data corresponding to the detection time, store the time-thickness curve according to the identifier of the to-be-monitored point, and calculate the slope of the time-thickness curve. The processing unit 302 is configured to determine whether to adjust a thickness threshold to obtain a corrected threshold according to the slope; determine whether to adjust the detection interval to obtain a corrected detection interval according to the slope; fit the time-thickness curve of the to-be-monitored point to obtain a time-thickness function, input the corrected threshold into the time-thickness function, and obtain a first detection time. The processing unit 302 is configured to, when the slope of the to-be-monitored point is negative, determine a similar monitoring point from a set of monitoring points other than the to-be-monitored point according to the pipeline information; calculate a similarity result between the slope of the to-be-monitored point and the slope of each monitoring point in the similar monitoring points, and determine a comparison monitoring point from the similar monitoring points based on the similarity result; the similarity result of the comparison monitoring point is greater than a first threshold; obtain a second detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring point. The processing unit 302 is configured to determine a warning time when there is a safety risk in the pipeline coating thickness according to the first detection time and the second detection time.

[0136] In some embodiments of the present application, the processing unit 302 is specifically configured to:

[0137] Compare the slope threshold with the slope; when the slope is less than or equal to the slope threshold, determine that the thickness threshold needs to be adjusted; when the slope is greater than the slope threshold, determine that the thickness threshold is not adjusted; the slope threshold satisfies the following formula:

[0138]

[0139] where k 0 represents the slope threshold, t i represents the i-th detection interval, d i represents the coating thickness of the i-th detection, λ is an attenuation factor, used to represent the speed of the consumption rate of the coating thickness over time, 0.01 ≤ λ ≤ 0.05, n is the total number of detections, t represents the average value of the n detection intervals, and d represents the average value of the coating thicknesses of the n detections.

[0140] In some embodiments of the present application, the corrected threshold satisfies the following formula: m' = m(1 + k 0 - k); where m' represents the corrected threshold; k represents the slope; k 0 represents the slope threshold; m represents the thickness threshold.

[0141] In some embodiments of the present application, the processing unit 302 is specifically configured to: when the slope is less than or equal to the slope threshold, determine that the detection interval needs to be corrected; obtain the minimum detection interval of the acquisition module, and determine the corrected detection interval based on the minimum detection interval; the corrected detection interval satisfies the following formula:

[0142] where t ′ represents the corrected detection interval.

[0143] In some embodiments of the present application, the time-thickness function satisfies the following formula:

[0144]

[0145] where a represents the slope of the straight line and b represents the intercept.

[0146] In some embodiments of the present application, the processing unit 302 is specifically configured to: compare the pipeline information of the point to be monitored with the pipeline information of the monitoring points in the first monitoring point set to determine similar monitoring points from the first set; the first monitoring point set is the set of monitoring points other than the point to be monitored, and the similarity between the pipeline information of the similar monitoring points and the pipeline information of the point to be monitored is greater than the second threshold; the pipeline information is the pipeline material, pipeline inner diameter, pipeline service life, type of transported medium, and medium flow rate.

[0147] In some embodiments of the present application, the processing unit 302 is specifically configured to: obtain N sets of consecutive first thickness data with a negative slope in the point to be monitored; obtain N sets of consecutive second thickness data with a negative slope in the similar monitoring points, calculate the first difference between the first thickness data and the second thickness data, and calculate the second difference between the first slope corresponding to the first thickness data and the second slope corresponding to the second thickness data; determine the comparison monitoring points from the similar monitoring points; the comparison monitoring points are the monitoring points with the smallest first difference and second difference among the similar monitoring points.

[0148] In some embodiments of the present application, the processing unit 302 is specifically configured to: input the thickness threshold into the time-thickness curve of the comparison monitoring point to obtain the second detection time.

[0149] In some embodiments of the present application, the warning time includes the following formula: P = min(p1, p2); where P represents the warning time, p1 represents the first detection time, and p2 represents the second detection time.

[0150] In some embodiments of the present application, the detection time satisfies the following formula: where T represents the detection time, and t i represents the i-th detection interval.

[0151] The embodiments of the present application further provide a computer-readable storage medium. The computer-readable storage medium includes computer-executable instructions. When the computer-executable instructions run on a computer, the computer is caused to execute the warning method for the pipeline coating thickness provided in the above embodiments.

[0152] The embodiments of the present application further provide a computer program product. The computer program product can be directly loaded into a memory and contains software code. After being loaded and executed by a computer, the computer program product can implement the warning method for the pipeline coating thickness provided in the above embodiments. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify or equivalently replace the technical solutions of the present invention, and these modifications or equivalent replacements do not cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

[0153] For the system provided in the above embodiments, only the division of the above functional modules is used for illustration. In practical applications, the above functions can be allocated to different functional modules according to needs, that is, the modules or steps in the embodiments of the present invention can be further decomposed or combined. For example, the modules in the above embodiments can be combined into one module, or further split into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only used to distinguish each module or step and are not regarded as an improper limitation of the present invention.

[0154] Those skilled in the art should be able to realize that the modules and method steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. The programs corresponding to the software modules and method steps can be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, or any other form of storage medium well-known in the technical field. To clearly illustrate the interchangeability of electronic hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in the form of electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

Claims

1. An early warning system for pipeline coating thickness, characterized in that: include: A collection module, comprising an ultrasonic sensor installed at a point to be monitored; the collection module is configured to collect pipeline information at the point to be monitored, and obtain thickness data of the pipeline coating according to the ultrasonic sensor; A data processing module is configured to obtain and calculate the detection time according to the detection interval, establish a time-thickness curve with the detection time and the thickness data corresponding to the detection time, store the time-thickness curve according to the identification of the point to be monitored, and calculate the slope of the time-thickness curve; A first reference module is configured to determine whether to adjust the thickness threshold to obtain a modified threshold according to the slope; determine whether to adjust the detection interval to obtain a modified detection interval according to the slope; fit the time-thickness curve of the point to be monitored to obtain a time-thickness function, and input the modified threshold into the time-thickness function to obtain a first detection time; A second reference module is configured to determine a similar monitoring point from a set of monitoring points other than the point to be monitored according to the pipeline information when the slope of the point to be monitored is negative; Calculating a similarity result between the slope of the point to be monitored and the slope of each of the similar monitoring points, and determining a comparison monitoring point from the similar monitoring points based on the similarity result; the similarity result of the comparison monitoring point is greater than a first threshold; Acquire a second detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring point; The early warning module is configured to determine an early warning time when the pipeline coating thickness presents a safety risk according to the first detection time and the second detection time.

2. The system according to claim 1, characterized in that The first reference module determines whether to adjust the thickness threshold according to the slope, including: Compare the slope threshold to the slope; When the slope is less than or equal to the slope threshold, it is determined that the thickness threshold needs to be adjusted; when the slope is greater than the slope threshold, it is determined that the thickness threshold does not need to be adjusted; The slope threshold satisfies the following formula: Where k0 represents the slope threshold, t i represents the i-th detection interval, d i It represents the coating thickness detected for the i-th time, λ is the attenuation factor, which is used to indicate how fast the coating thickness consumption rate changes with time, 0.01≤λ≤0.05, n is the total number of detections, t represents the average value of the n detection intervals, and d represents the average value of the coating thickness detected for n times.

3. The system according to claim 2, characterized in that The correction threshold satisfies the following formula: m'=m(1+k0-k); Wherein, m' represents the correction threshold; k represents the slope; k0 represents the slope threshold; and m represents the thickness threshold.

4. The system according to claim 3, characterized in that The first reference module determines whether to adjust the detection interval to obtain a corrected detection interval according to the slope, including: When the slope is less than or equal to the slope threshold, determining that the detection interval needs to be corrected; The minimum detection interval of the acquisition module is obtained, and the modified detection interval is determined based on the minimum detection interval; the modified detection interval satisfies the following formula: Among them, t ′ Indicates the correction detection interval.

5. The system according to claim 4, characterized in that The time-thickness function satisfies the following formula: Among them, a is the slope of the line and b is the intercept.

6. The system according to claim 5, characterized in that The second reference module determines similar monitoring points from a set of monitoring points other than the monitoring point according to the pipeline information, including: The pipeline information of the point to be monitored is compared with the pipeline information of the monitoring points in the first monitoring point set for similarity, and the similar monitoring point is determined from the first set; the first monitoring point set is a set of monitoring points excluding the point to be monitored, and the similarity between the pipeline information of the similar monitoring point and the pipeline information of the point to be monitored is greater than a second threshold; the pipeline information includes pipeline material, pipeline inner diameter, pipeline service life, transport medium type and medium flow rate.

7. The system according to claim 6, characterized in that The second reference module calculates a similarity result between the slope of the to-be-monitored point and the slope of each of the similar monitoring points, and determines a comparison monitoring point from the similar monitoring points based on the similarity result, including: Obtain N groups of continuous first thickness data with a negative slope from the points to be monitored; obtain N groups of continuous second thickness data with a negative slope from the similar monitoring points, calculate a first difference between the first thickness data and the second thickness data, and calculate a second difference between a first slope corresponding to the first thickness data and a second slope corresponding to the second thickness data; determine the comparison monitoring point from the similar monitoring points; the comparison monitoring point is the monitoring point at which the first difference and the second difference in the similar monitoring are the smallest.

8. The system according to claim 7, characterized in that The second reference module obtains the detection time when the thickness data is equal to the thickness threshold according to the time-thickness curve of the comparison monitoring point, including: inputting the thickness threshold into the time-thickness curve of the comparison monitoring point to obtain the second detection time.

9. The system according to any one of claims 1 to 8, characterized in that: The warning time includes the following formula: P = min(p1,p2); Among them, P represents the warning time, p1 represents the first detection time, and p2 represents the second detection time.

10. The system according to any one of claims 1 to 8, characterized in that: The detection time satisfies the following formula: Where T represents the detection time, t i represents the i-th detection interval.

11. A pipeline coating thickness early warning method, characterized in that: The method comprises: Collecting pipeline information of the monitoring point through an ultrasonic sensor, and obtaining thickness data of the pipeline coating according to the ultrasonic sensor; Acquire and calculate the detection time according to the detection interval, establish a time-thickness curve with the detection time and the thickness data corresponding to the detection time, store the time-thickness curve according to the identification of the point to be monitored, and calculate the slope of the time-thickness curve; Determine whether to adjust the thickness threshold to obtain a corrected threshold according to the slope; determine whether to adjust the detection interval to obtain a corrected detection interval according to the slope; fit the time-thickness curve of the point to be monitored to obtain a time-thickness function, input the corrected threshold into the time-thickness function to obtain a first detection time; When the slope of the point to be monitored is a negative number, a similar monitoring point is determined from a set of monitoring points other than the point to be monitored according to the pipeline information; a similarity result between the slope of the point to be monitored and the slope of each of the similar monitoring points is calculated, and a comparison monitoring point is determined from the similar monitoring points based on the similarity result; the similarity result of the comparison monitoring point is greater than a first threshold; and a second detection time when the thickness data is equal to the thickness threshold is obtained according to a time-thickness curve of the comparison monitoring point; The warning time when the pipeline coating thickness presents a safety risk is determined according to the first detection time and the second detection time.

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