Marine oil exploitation equipment state monitoring method and system based on machine vision

Abstract

The invention is suitable for the technical field of offshore oil exploitation equipment monitoring and maintenance, and provides an offshore oil exploitation equipment state monitoring method and system based on machine vision, and the method comprises the steps: obtaining historical monitoring records and historical vibration data of a key pipeline section, and determining the current sediment state of the key pipeline section, meanwhile, evaluating a current structure stability score of the key pipeline section; analyzing the historical monitoring records, screening out a plurality of local historical monitoring logs which are consistent with the current sediment state and conform to a preset water flow vortex condition from the historical monitoring records, and matching a plurality of corresponding local historical vibration records based on timestamps. According to the method, the structural stability of the key pipeline section is accurately evaluated by combining the dynamic influence of the water flow vortex and the vibration characteristics of the pipeline.

Description

Technical Field

[0001] This invention belongs to the field of monitoring and maintenance technology for offshore oil extraction equipment, and particularly relates to a method and system for monitoring the condition of offshore oil extraction equipment based on machine vision. Background Technology

[0002] With the continuous development of offshore oil extraction technology, subsea pipelines have become a key component connecting oil and gas fields with processing facilities. In the long-term marine environment, pipelines face severe challenges, including the effects of natural factors such as seawater corrosion, sediment accumulation, seismic activity, and water current eddies. These factors can lead to structural damage to the pipelines, thereby affecting the safety and stability of the oil and gas extraction process. Traditional offshore oil extraction equipment condition monitoring relies heavily on static sensors and periodic inspections to assess the pipeline's health status. While these methods provide some monitoring, they cannot dynamically capture the real-time impact of environmental changes on the pipeline structure, resulting in assessment results that are lagging and inaccurate, failing to reflect the true health status of the pipeline in complex environments.

[0003] Currently, traditional monitoring methods primarily focus on monitoring pipeline conditions through physical quantities such as pressure and temperature. However, the impact of dynamic factors such as water flow eddies and pipeline vibration on pipeline stability has not been fully considered. Dynamic changes in the intensity, frequency, and direction of water flow eddies can intensify pipeline vibration during operation, especially in critical areas (such as joints and bends). Existing sensors typically only record single physical parameters and cannot comprehensively assess the relationship between the dynamic effects of water flow eddies and pipeline vibration characteristics, resulting in a lack of comprehensiveness and accuracy in assessing pipeline health. Summary of the Invention

[0004] The purpose of this invention is to provide a machine vision-based method for monitoring the condition of offshore oil extraction equipment, aiming to solve the problems mentioned in the background art.

[0005] This invention is implemented as follows: a machine vision-based method for monitoring the condition of offshore oil extraction equipment, the method comprising:

[0006] Acquire historical monitoring records and historical vibration data of key pipeline sections, determine the current sediment state of key pipeline sections, and assess the current structural stability score of key pipeline sections.

[0007] Historical monitoring records were analyzed to select several local historical monitoring logs that were consistent with the current sediment state and met the predetermined water flow eddy conditions. Based on the timestamp, several corresponding local historical vibration records were matched.

[0008] Based on several local historical vibration records, the vibration characteristics of key pipeline sections caused by water flow vortex are analyzed, vibration change trends are constructed, and the first correction factor is generated accordingly.

[0009] Find the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions. Generate a second correction factor based on the deviation amplitude between the two.

[0010] The first and second correction factors are applied to the current structural stability score for correction.

[0011] As a further limitation of the technical solution of the present invention, the predetermined water vortex condition refers to the type of water vortex that the key pipeline section encounters most frequently at the current time point. It is usually the water vortex mode that is most common under the current season or marine environmental conditions. The predetermined water vortex condition includes the intensity, frequency, direction and duration of the water vortex.

[0012] As a further limitation of the technical solution of this invention, the steps of analyzing the vibration characteristics of key pipeline sections caused by water flow vortices based on several local historical vibration records, constructing vibration change trends, and generating a first correction factor based on these trends include:

[0013] By sequentially analyzing each local historical vibration record and local historical monitoring log, the average vibration amplitude characteristic parameters of the key pipeline section during the period of contact with the predetermined water flow vortex condition are obtained.

[0014] Several average vibration amplitude characteristic parameters are sorted according to timestamps, and vibration change trends are constructed.

[0015] Calculate the average slope of the vibration change trend and use this average slope as the first correction factor.

[0016] As a further limitation of the technical solution of this invention, the step of identifying the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions, and generating a second correction factor based on the deviation amplitude between the two, includes:

[0017] Identify the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions;

[0018] Calculate the vibration offset of the key pipeline section in the first and second reference vibration records during the period of contact with the predetermined water flow vortex conditions, respectively.

[0019] A second correction factor is generated based on the deviation of the vibration offsets of the two.

[0020] As a further limitation of the technical solution of this embodiment of the invention, the step of applying the first correction factor and the second correction factor to the current structural stability score for correction includes:

[0021] The preset structural stability score correction model is invoked, and the first correction factor and the second correction factor are substituted into it to correct the current structural stability score, so as to obtain the corrected structural stability score.

[0022] The revised structural stability score is applied to the status monitoring and early warning system for critical pipeline sections to adjust the equipment's operating status and maintenance plans in real time.

[0023] As a further limitation of the technical solution of this embodiment of the invention, the structural stability scoring correction model is as follows:

[0024] ;

[0025] in, This refers to the revised structural stability score. This refers to the current structural stability score. This refers to the first correction factor, which is the average slope of the vibration trend. This refers to the adjustment weight corresponding to the first correction factor. This refers to the vibration offset corresponding to the primary reference vibration record. This refers to the vibration offset corresponding to the secondary reference vibration record. This refers to the second correction factor, which is the deviation magnitude of the vibration offset between the first and second reference vibration records. This refers to the adjustment weight corresponding to the second correction factor.

[0026] A machine vision-based condition monitoring system for offshore oil extraction equipment includes: a data acquisition module, a data filtering module, a first correction factor determination module, a second correction factor determination module, and a scoring correction module, wherein:

[0027] The data acquisition module is used to acquire historical monitoring records and historical vibration data of key pipeline sections, determine the current sediment state of key pipeline sections, and evaluate the current structural stability score of key pipeline sections.

[0028] The data filtering module is used to analyze historical monitoring records, filter out several local historical monitoring logs that are consistent with the current sediment state and meet the predetermined water flow vortex conditions, and match the corresponding local historical vibration records based on the timestamp; the predetermined water flow vortex conditions refer to the type of water flow vortex most frequently encountered by the key pipeline section at the current time point, which is usually the most common water flow vortex pattern under the current season or marine environmental conditions. The predetermined water flow vortex conditions include the intensity, frequency, direction and duration of the water flow vortex;

[0029] The first correction factor determination module is used to analyze the vibration characteristics of key pipeline sections caused by water flow vortex based on several local historical vibration records, construct the vibration change trend, and generate the first correction factor accordingly.

[0030] The second correction factor determination module is used to find the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions, and to generate a second correction factor based on the deviation amplitude between the two.

[0031] The scoring correction module is used to apply the first correction factor and the second correction factor to the current structural stability score for correction.

[0032] As a further limitation of the technical solution of this embodiment of the invention, the first correction factor determination module specifically includes:

[0033] The data parsing unit is used to sequentially parse each local historical vibration record and local historical monitoring log to obtain the average vibration amplitude characteristic parameters of the key pipeline section during the period of contact with the predetermined water flow vortex conditions;

[0034] The trend construction unit is used to sort several average vibration amplitude characteristic parameters according to timestamps and construct vibration change trends.

[0035] The average slope calculation unit is used to calculate the average slope of the vibration change trend and uses the average slope as the first correction factor.

[0036] As a further limitation of the technical solution of this embodiment of the invention, the second correction factor determination module specifically includes:

[0037] The data lookup unit is used to find the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, as well as the second reference vibration record that is closest to the current time point under the same conditions.

[0038] The vibration offset calculation unit is used to calculate the vibration offset of the key pipeline section in the first reference vibration record and the second reference vibration record during the period of contact with the predetermined water flow vortex condition.

[0039] The deviation amplitude quantization unit is used to generate a second correction factor based on the deviation amplitude of the vibration offset between the two.

[0040] As a further limitation of the technical solution of this embodiment of the invention, the scoring correction module specifically includes:

[0041] The model application unit is used to call the preset structural stability score correction model, and substitute the first correction factor and the second correction factor into it to correct the current structural stability score, so as to obtain the corrected structural stability score.

[0042] The modified scoring application unit is used to apply the modified structural stability score to the status monitoring and early warning system of critical pipeline sections, so as to adjust the operating status and maintenance plan of the equipment in real time.

[0043] The structural stability scoring correction model is as follows:

[0044] ;

[0045] in, This refers to the revised structural stability score. This refers to the current structural stability score. This refers to the first correction factor, which is the average slope of the vibration trend. This refers to the adjustment weight corresponding to the first correction factor. This refers to the vibration offset corresponding to the primary reference vibration record. This refers to the vibration offset corresponding to the secondary reference vibration record. This refers to the second correction factor, which is the deviation magnitude of the vibration offset between the first and second reference vibration records. This refers to the adjustment weight corresponding to the second correction factor.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] This invention provides a condition monitoring method for offshore oil extraction equipment based on machine vision and vibration monitoring. By combining the dynamic influence of water vortexes with the vibration characteristics of pipelines, the structural stability of key pipeline sections can be accurately assessed. By analyzing current water vortex conditions (including the intensity, frequency, and direction of the water vortexes), historical data consistent with the current sediment conditions is extracted, and two correction factors are calculated: the first correction factor is based on the average slope of the pipeline vibration change trend, reflecting the rate of change of pipeline vibration after contact with water vortexes; the second correction factor further quantifies the actual impact of water vortexes on pipeline vibration by comparing the deviation amplitude between the primary and secondary reference vibration records.

[0048] By combining these two correction factors and applying them to the current structural stability score, the system can adjust the score in real time and predict the pipeline's stability performance under similar future water flow vortex conditions. This method not only improves the accuracy of condition assessment but also enables timely identification of potential risks, optimization of maintenance plans, and significantly enhances the safety and reliability of offshore oil extraction equipment. Attached Figure Description

[0049] Figure 1 A flowchart of the method provided in the embodiments of the present invention;

[0050] Figure 2 This is a flowchart illustrating the generation of the first correction factor in the method provided in this embodiment of the invention;

[0051] Figure 3 This is a flowchart illustrating the generation of the second correction factor in the method provided in this embodiment of the invention;

[0052] Figure 4 This is a flowchart illustrating the correction of the current structural stability score in the method provided by the embodiments of the present invention;

[0053] Figure 5 Application architecture diagram of the system provided in the embodiments of the present invention;

[0054] Figure 6 This is a structural block diagram of the first correction factor determination module in the system provided in the embodiments of the present invention;

[0055] Figure 7 This is a structural block diagram of the second correction factor determination module in the system provided in the embodiments of the present invention;

[0056] Figure 8 This is a structural block diagram of the scoring correction module in the system provided in the embodiment of the present invention. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0058] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0059] Specifically, a method for monitoring the condition of offshore oil extraction equipment based on machine vision includes the following steps:

[0060] Step S100: Obtain historical monitoring records and historical vibration data of the critical pipeline section, determine the current sediment state of the critical pipeline section, and evaluate the current structural stability score of the critical pipeline section.

[0061] In this embodiment of the invention, pipelines play a crucial role in offshore oil extraction equipment, responsible for transporting oil, gas, and other substances. Due to the unique characteristics of the seabed environment, pipelines face challenges such as seawater corrosion, sediment accumulation, seabed currents, and eddies. Therefore, condition monitoring of pipelines is essential. By monitoring pipeline vibration and structural stability, potential risks can be identified promptly, preventing malfunctions and ensuring the safe operation of the equipment.

[0062] Critical pipeline sections refer to the parts of a pipeline that are susceptible to water flow eddies, sediment accumulation, and other external factors. These areas typically include pipe joints, bends, and corners. In these areas, the impact of water flow and sediment buildup are more concentrated. Therefore, focusing on monitoring these critical pipeline sections helps to promptly identify potential failure points, thereby strengthening risk management and early warning systems.

[0063] In this invention, historical monitoring records refer to video monitoring data of critical pipeline sections. Long-term real-time monitoring of the pipeline is conducted using underwater cameras or other video acquisition equipment to obtain image data of the pipeline surface. These historical video records help analyze sediment accumulation, corrosion, and other changes that may affect the pipeline's structural stability. Furthermore, historical monitoring records also include environmental videos of critical pipeline sections; this video data is used to assess the water flow eddies in the pipeline's location. Water flow eddies directly affect the pipeline's vibration patterns and sediment accumulation; therefore, environmental videos are crucial for a comprehensive understanding of the dynamic changes in the pipeline's environment.

[0064] Historical vibration data comes from vibration sensors installed on the subsea pipeline section. These sensors collect vibration data of the pipeline in real time, including vibration amplitude, frequency, and waveform. Changes in vibration data can reflect the pipeline's response to factors such as water flow, pressure, and sediment. Especially in critical areas such as connections and bends, vibration characteristics can often reflect the health status of the pipeline.

[0065] The current state of the sediment is analyzed using machine vision technology. Real-time data is collected using underwater high-definition cameras, laser scanners, and other equipment, combined with image processing algorithms (such as edge detection and image segmentation) to accurately identify the sediment layer on the pipe surface and obtain its thickness, distribution, and variations.

[0066] Current structural stability scoring is used to assess the structural health of pipelines. This score integrates factors such as pipeline vibration characteristics, sediment condition, historical damage, and environmental impacts, and uses a computational model to obtain a quantitative score reflecting the pipeline's current stability. Similar structural stability scoring methods have been applied in existing technologies, especially in pipeline health monitoring systems, typically combining sensor data, historical maintenance records, and other data with mathematical or machine learning models for comprehensive evaluation.

[0067] Historical monitoring records and historical vibration data contain a wealth of pipeline operation information. Historical monitoring records primarily include historical video data of key pipeline sections, providing information on pipeline surface deposits, corrosion, and damage. Simultaneously, historical monitoring records also include environmental videos of key pipeline sections to assess the impact of environmental factors such as water flow eddies on the pipeline. Historical vibration data mainly includes the vibration characteristics experienced by the pipeline during operation, including vibration frequency, amplitude, and waveform, effectively reflecting the pipeline's response to changes in the external environment.

[0068] Furthermore, the machine vision-based method for monitoring the condition of offshore oil extraction equipment also includes the following steps:

[0069] Step S200: Analyze historical monitoring records, select several local historical monitoring logs that are consistent with the current sediment state and meet the predetermined water flow eddy conditions, and match the corresponding local historical vibration records based on the timestamp.

[0070] The predetermined water vortex condition refers to the type of water vortex most frequently encountered by the critical pipeline section at the current time point. It is usually the most common water vortex pattern under the current season or marine environmental conditions. The predetermined water vortex condition includes the intensity, frequency, direction and duration of the water vortex.

[0071] In this embodiment of the invention, the historical monitoring records primarily originate from long-term video monitoring data of key pipeline sections. This data is collected in real time using underwater cameras or other video acquisition devices, recording changes in sediment, corrosion, and damage on the pipeline surface. These historical monitoring records provide intuitive data on changes in the pipeline surface condition and are crucial for analyzing the pipeline's health status. By analyzing this video data using machine vision technology, the thickness, distribution, and other influencing factors of the sediment layer can be extracted, thus providing detailed information for subsequent analysis.

[0072] When filtering historical monitoring records, the system needs to match them with the current sediment condition. After identifying the current sediment condition on the pipeline surface using machine vision technology, the system filters out records from historical monitoring data that match the current sediment condition. This filtering process ensures the relevance and real-time nature of historical data, helping to determine the changing trend of the pipeline under similar sediment conditions.

[0073] Furthermore, historical monitoring records must conform to predetermined water flow vortex conditions. These predetermined water flow vortex conditions refer to the type of water flow vortex most frequently encountered by the critical pipeline section at the current time, typically the most common water flow vortex pattern under the current season or marine environmental conditions. These conditions include the intensity, frequency, direction, and duration of the water flow vortex. Depending on the characteristics of the water flow vortex, the vibration behavior of the pipeline will differ under different water flow vortex conditions. Therefore, when selecting historical monitoring records, it is necessary to ensure that these records conform to the current water flow vortex conditions to guarantee the accuracy of the analysis.

[0074] Each historical monitoring record is timestamped, allowing the system to match it with historical vibration data. This timestamping ensures the accuracy of the vibration data corresponding to each historical monitoring record, providing essential data support for subsequent vibration analysis. The historical vibration data comes from vibration sensors within the pipeline section, recording the pipeline's vibration characteristics over different time periods. This historical data allows for the analysis of the pipeline's vibration patterns and the relationship between vibration and environmental factors (such as water flow eddies and sediment effects).

[0075] Furthermore, the machine vision-based method for monitoring the condition of offshore oil extraction equipment also includes the following steps:

[0076] Step S300: Based on several local historical vibration records, analyze the vibration characteristics of key pipeline sections caused by water flow vortex, construct the vibration change trend, and generate the first correction factor accordingly.

[0077] Specifically, Figure 2 A flowchart for generating the first correction factor is shown.

[0078] The process of analyzing the vibration characteristics of key pipeline sections caused by water flow vortices based on several local historical vibration records, constructing vibration change trends, and generating the first correction factor specifically includes the following steps:

[0079] Step S301: Sequentially analyze each local historical vibration record and local historical monitoring log to obtain the average vibration amplitude characteristic parameters of the key pipeline section during the period of contact with the predetermined water flow vortex condition;

[0080] Step S302: Sort several average vibration amplitude characteristic parameters according to timestamps and construct vibration change trends;

[0081] Step S303: Calculate the average slope of the vibration change trend and use the average slope as the first correction factor.

[0082] In this embodiment of the invention, obtaining the average vibration amplitude characteristic parameters of a key pipeline section during a predetermined period of contact with water flow vortex conditions first relies on the acquisition of historical vibration data, which is continuously monitored and recorded by vibration sensors installed on the pipeline. Using machine vision technology, the historical monitoring records of the key pipeline section are analyzed, and the system can extract monitoring logs consistent with the current sediment state. By matching these logs with the current water flow vortex conditions, historical monitoring records that meet the criteria are selected. Then, based on these selected monitoring records and the corresponding vibration data, the system calculates the vibration amplitude characteristic parameters for each time period, ultimately obtaining the average vibration amplitude characteristic parameters for that time period.

[0083] After analyzing historical monitoring records and selecting those consistent with the current sediment state, several average vibration amplitude characteristic parameters are sorted according to timestamps to construct vibration change trends. Sorting the data by timestamps ensures that the vibration characteristics of the pipeline under the same water flow vortex conditions (predetermined water flow vortex conditions) are organized chronologically. Then, by analyzing this sorted data, the system can obtain the pipeline vibration change trends, reflecting the vibration modes and variation patterns of the pipeline under the same water flow vortex conditions.

[0084] When calculating the average slope of vibration trends, the system considers not only vibration changes within each time period but also long-term temporal evolution. In this process, the system obtains the slope of vibration changes through linear regression or the difference method on historical data. The magnitude of the slope reflects the rate of change of pipeline vibration over time. A faster rate of vibration change indicates that the pipeline may be experiencing more drastic environmental changes, particularly the effects of water flow vortices. Because it considers long-term temporal evolution, the average slope can reflect the cumulative effect of water flow vortex influences on the pipeline over a longer period, providing a more stable and comprehensive evaluation indicator.

[0085] Using the average slope of vibration trends as the first correction factor can accurately reflect the dynamic health status of pipelines under specific water flow vortex conditions. When vibration changes are more drastic, the correction factor increases accordingly, reflecting a potential significant impact on the pipeline's structural stability. This method helps to promptly identify pipeline trends under the same water flow vortex conditions and dynamically adjust structural stability scores, thereby improving the accuracy and operability of risk prediction. By introducing the concept of time evolution, the average slope can also comprehensively consider long-term vibration trends, providing a more scientific basis for pipeline health management.

[0086] Furthermore, the machine vision-based method for monitoring the condition of offshore oil extraction equipment also includes the following steps:

[0087] Step S400: Identify the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions. Generate a second correction factor based on the deviation amplitude between the two.

[0088] Specifically, Figure 3 A flowchart for generating the second correction factor is shown.

[0089] The process of identifying the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions, and generating a second correction factor based on the deviation between the two, specifically includes the following steps:

[0090] Step S401: Find the first reference vibration record in the historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions.

[0091] Step S402: Calculate the vibration offset of the key pipeline section in the first reference vibration record and the second reference vibration record during the contact period of the predetermined water flow vortex condition.

[0092] Step S403: Generate a second correction factor based on the deviation amplitude of the vibration offset between the two.

[0093] In this embodiment of the invention, the system first selects two sets of vibration records from historical vibration data as comparison data, namely the first reference vibration record and the second reference vibration record. The first reference vibration record refers to the vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions for the first time in history. The second reference vibration record is the vibration record most recent to the current time point under the same water flow eddy conditions.

[0094] When extracting vibration offset from these two sets of records, it is first necessary to understand the definition of vibration offset. Vibration offset reflects the difference in vibration of the pipeline before and after contact with water flow vortices. Specifically, the process of calculating vibration offset is as follows:

[0095] First, the system extracts the vibration parameters of the pipeline under conditions without contact with water vortices from the initial reference vibration record. These parameters can include vibration amplitude, frequency, and waveform, reflecting the normal vibration state of the pipeline when not affected by water vortices. Next, the system extracts the vibration parameters from the initial reference vibration record after contact with water vortices. These parameters also include vibration amplitude and frequency, representing the vibration changes that occur in the pipeline under the influence of water vortices.

[0096] By comparing these two vibration data points, the system can calculate the difference between them, obtaining the vibration offset. Specifically, the vibration offset refers to the difference in vibration parameters between the pipeline before and after it comes into contact with the water vortex condition. A larger offset indicates that the water vortex has a greater impact on the pipeline, which may lead to significant changes in the pipeline's vibration characteristics.

[0097] The same method applies to secondary reference vibration records. In these records, the system extracts vibration data of the pipe before and after contact with the water flow vortex, and calculates the vibration offset.

[0098] The reason for using the deviation amplitude of the vibration offset of the key pipeline section in the first reference vibration record and the second reference vibration record during the period of contact with the predetermined water flow vortex as the second correction factor is mainly to quantify the change of pipeline vibration by comparing the two, and then dynamically adjust the structural stability score to ensure that the health status of the pipeline is accurately assessed in different time periods.

[0099] The initial reference vibration record is highly reliable because it records the pipe's vibration for the first time under specific water flow vortex conditions. This allows the initial reference vibration record to reflect the pipe's vibration state upon initial contact with the water flow vortex, serving as a new benchmark. Through this record, the system can understand the pipe's response characteristics under initial water flow vortex conditions and provide reliable basic data for subsequent comparative analysis.

[0100] The secondary reference vibration record is the most recent vibration record of the pipeline under the same water flow vortex conditions. This allows the secondary reference vibration record to more accurately reflect the current actual vibration state of the pipeline. By comparing it with the primary reference vibration record, the system can obtain the vibration characteristics of the pipeline after experiencing changes over time under the same water flow vortex conditions, thereby identifying changes in the pipeline's health status.

[0101] By comparing the vibration offsets of these two vibration records, the system can calculate the difference between them, i.e., the magnitude of the vibration offset deviation. A larger deviation magnitude indicates a greater variation in the pipe's vibration under the same water flow vortex conditions, potentially reflecting a stronger external influence or a potential structural problem. A second correction factor generated based on this deviation magnitude can adjust the current structural stability score, providing a more accurate risk assessment.

[0102] The advantage of using the deviation amplitude of vibration offset as the second correction factor is that it provides a dynamic and quantitative basis for assessing pipeline health. A large deviation amplitude suggests potential pipeline anomalies, and timely score correction helps to provide early warning of potential faults, ensuring that the pipeline's structural stability is more accurately reflected when affected by external factors such as water flow eddies.

[0103] This method enables the system not only to identify pipeline changes over different time periods but also to accurately assess pipeline risks in the face of complex marine environmental factors and take corresponding maintenance measures. Such correction factors make pipeline health management more scientific and real-time, contributing to improved pipeline safety and operational efficiency.

[0104] Furthermore, the machine vision-based method for monitoring the condition of offshore oil extraction equipment also includes the following steps:

[0105] Step S500: Apply the first correction factor and the second correction factor to the current structural stability score to make corrections.

[0106] Specifically, Figure 4 A flowchart illustrating the correction of the current structural stability score is shown.

[0107] The specific steps for applying the first and second correction factors to the current structural stability score for correction include:

[0108] Step S501: Call the preset structural stability score correction model, and substitute the first correction factor and the second correction factor into it to correct the current structural stability score, so as to obtain the corrected structural stability score.

[0109] Step S502: Apply the revised structural stability score to the status monitoring and early warning system for critical pipeline sections to adjust the equipment's operating status and maintenance plan in real time.

[0110] The structural stability scoring correction model is as follows:

[0111] ;

[0112] in, This refers to the revised structural stability score. This refers to the current structural stability score. This refers to the first correction factor, which is the average slope of the vibration trend. This refers to the adjustment weight corresponding to the first correction factor. This refers to the vibration offset corresponding to the primary reference vibration record. This refers to the vibration offset corresponding to the secondary reference vibration record. This refers to the second correction factor, which is the deviation magnitude of the vibration offset between the first and second reference vibration records. This refers to the adjustment weight corresponding to the second correction factor.

[0113] In this embodiment of the invention, the first correction factor considers the vibration trend of the pipeline under the action of water vortexes, which is represented by the average slope of the vibration. The average slope reflects the rate of change of the pipeline vibration. If the rate of change is large, it may indicate that the pipeline's resistance to water vortex vibration is getting worse after long-term underwater operation, or that its structure is showing potential risks. Through the first correction factor, the system can adjust the current structural stability score according to the vibration trend, reflecting the health status of the pipeline after contact with water vortexes.

[0114] Secondly, the second correction factor is based on the vibration offset of the pipeline at different time points. By comparing the primary reference vibration record and the secondary reference vibration record, the system can calculate the vibration offset between them, and then generate the second correction factor. If the vibration variation of the pipeline is large, it indicates that the pipeline structure may have been subjected to significant external disturbances or damage. The system will further adjust the structural stability score based on this deviation amplitude to reflect changes in the pipeline's health.

[0115] By combining the first and second correction factors for scoring correction, the system comprehensively considers the pipeline's changes over different time periods, as well as the impact of external environmental factors such as water flow vortices. Through this combination, the system can not only identify the pipeline's current health status but also reflect its stability changes under long-term vibration and external disturbances. This combined approach provides a more accurate structural stability assessment, ensuring a more comprehensive risk assessment of the pipeline.

[0116] The structural stability scoring correction model proposed in the above technical solution provides only an intuitive and effective calculation method, but it is not the only solution. In other embodiments, different calculation methods can be used, such as those based on more complex machine learning algorithms, fuzzy logic control, or physical models, to comprehensively evaluate the structural stability of the pipeline. These methods can be adjusted according to different application scenarios and requirements to obtain more suitable results.

[0117] Furthermore, Figure 5 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0118] In another preferred embodiment of the present invention, a machine vision-based offshore oil extraction equipment status monitoring system includes:

[0119] The data acquisition module 100 is used to acquire historical monitoring records and historical vibration data of the critical pipeline section, determine the current sediment state of the critical pipeline section, and evaluate the current structural stability score of the critical pipeline section.

[0120] Furthermore, the machine vision-based offshore oil extraction equipment condition monitoring system also includes:

[0121] The data filtering module 200 is used to analyze historical monitoring records, filter out several local historical monitoring logs that are consistent with the current sediment state and meet the predetermined water flow vortex conditions, and match the corresponding several local historical vibration records based on the timestamp; the predetermined water flow vortex conditions refer to the type of water flow vortex most frequently encountered by the key pipeline section at the current time point, which is usually the most common water flow vortex pattern under the current season or marine environmental conditions. The predetermined water flow vortex conditions include the intensity, frequency, direction and duration of the water flow vortex.

[0122] Furthermore, the machine vision-based offshore oil extraction equipment condition monitoring system also includes:

[0123] The first correction factor determination module 300 is used to analyze the vibration characteristics of key pipeline sections caused by water flow vortex based on several local historical vibration records, construct the vibration change trend, and generate the first correction factor accordingly.

[0124] Specifically, Figure 6 The diagram shows a structural block diagram of the first correction factor determination module 300 in the system provided by an embodiment of the present invention.

[0125] In a preferred embodiment provided by the present invention, the first correction factor determination module 300 specifically includes:

[0126] Data parsing unit 301 is used to sequentially parse each local historical vibration record and local historical monitoring log to obtain the average vibration amplitude characteristic parameters of the key pipeline section during the period of contact with the predetermined water flow vortex condition;

[0127] The trend construction unit 302 is used to sort several average vibration amplitude characteristic parameters according to the timestamp and construct the vibration change trend.

[0128] The average slope calculation unit 303 is used to calculate the average slope of the vibration change trend and use the average slope as the first correction factor.

[0129] Furthermore, the machine vision-based offshore oil extraction equipment condition monitoring system also includes:

[0130] The second correction factor determination module 400 is used to find the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow vortex conditions, and the second reference vibration record that is closest to the current time point under the same conditions, and generate a second correction factor based on the deviation amplitude between the two.

[0131] Specifically, Figure 7 The diagram shows a structural block diagram of the second correction factor determination module 400 in the system provided by an embodiment of the present invention.

[0132] In a preferred embodiment of the present invention, the second correction factor determination module 400 specifically includes:

[0133] The data lookup unit 401 is used to find the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow vortex conditions, as well as the second reference vibration record that is closest to the current time point under the same conditions.

[0134] Vibration offset calculation unit 402 is used to calculate the vibration offset of the key pipeline section in the first reference vibration record and the second reference vibration record during the period of contact with the predetermined water flow vortex condition.

[0135] The deviation amplitude quantization unit 403 is used to generate a second correction factor based on the deviation amplitude of the vibration offset between the two.

[0136] Furthermore, the machine vision-based offshore oil extraction equipment condition monitoring system also includes:

[0137] The scoring correction module 500 is used to apply the first correction factor and the second correction factor to the current structural stability score for correction.

[0138] Specifically, Figure 8 A structural block diagram of the scoring correction module 500 in the system provided in an embodiment of the present invention is shown.

[0139] In a preferred embodiment provided by the present invention, the scoring correction module 500 specifically includes:

[0140] The model application unit 501 is used to call the preset structural stability score correction model, and substitute the first correction factor and the second correction factor into it to correct the current structural stability score, so as to obtain the corrected structural stability score.

[0141] The correction score application unit 502 is used to apply the corrected structural stability score to the status monitoring and early warning system of critical pipeline sections in order to adjust the operating status and maintenance plan of the equipment in real time.

[0142] The structural stability scoring correction model is as follows:

[0143] ;

[0144] in, This refers to the revised structural stability score. This refers to the current structural stability score. This refers to the first correction factor, which is the average slope of the vibration trend. This refers to the adjustment weight corresponding to the first correction factor. This refers to the vibration offset corresponding to the primary reference vibration record. This refers to the vibration offset corresponding to the secondary reference vibration record. This refers to the second correction factor, which is the deviation magnitude of the vibration offset between the first and second reference vibration records. This refers to the adjustment weight corresponding to the second correction factor.

[0145] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0146] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0147] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0148] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0149] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for monitoring the condition of offshore oil extraction equipment based on machine vision, characterized in that, The method includes: Acquire historical monitoring records and historical vibration data of key pipeline sections, determine the current sediment state of key pipeline sections, and assess the current structural stability score of key pipeline sections. Historical monitoring records were analyzed to select several local historical monitoring logs that were consistent with the current sediment state and met the predetermined water flow eddy conditions. Based on the timestamp, several corresponding local historical vibration records were matched. Based on several local historical vibration records, the vibration characteristics of key pipeline sections caused by water flow vortex are analyzed, vibration change trends are constructed, and the first correction factor is generated accordingly. Find the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions. Generate a second correction factor based on the deviation amplitude between the two. The first and second correction factors are applied to the current structural stability score for correction.

2. The method for monitoring the condition of offshore oil extraction equipment based on machine vision according to claim 1, characterized in that, The predetermined water vortex condition refers to the type of water vortex most frequently encountered by the critical pipeline section at the current time point. It is usually the most common water vortex pattern under the current season or marine environmental conditions. The predetermined water vortex condition includes the intensity, frequency, direction and duration of the water vortex.

3. The method for monitoring the condition of offshore oil extraction equipment based on machine vision according to claim 1, characterized in that, The steps for analyzing the vibration characteristics of key pipeline sections caused by water flow vortices based on several local historical vibration records, constructing vibration change trends, and generating the first correction factor include: By sequentially analyzing each local historical vibration record and local historical monitoring log, the average vibration amplitude characteristic parameters of the key pipeline section during the period of contact with the predetermined water flow vortex condition are obtained. Several average vibration amplitude characteristic parameters are sorted according to timestamps, and vibration change trends are constructed. Calculate the average slope of the vibration change trend and use this average slope as the first correction factor.

4. The method for monitoring the condition of offshore oil extraction equipment based on machine vision according to claim 3, characterized in that, The steps for identifying the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is most recent to the current time point under the same conditions, and generating a second correction factor based on the deviation amplitude between the two, include: Identify the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions; Calculate the vibration offset of the key pipeline section in the first and second reference vibration records during the period of contact with the predetermined water flow vortex conditions, respectively. A second correction factor is generated based on the deviation of the vibration offsets of the two.

5. The method for monitoring the condition of offshore oil extraction equipment based on machine vision according to claim 4, characterized in that, The steps for applying the first and second correction factors to the current structural stability score include: The preset structural stability score correction model is invoked, and the first correction factor and the second correction factor are substituted into it to correct the current structural stability score, so as to obtain the corrected structural stability score. The revised structural stability score is applied to the status monitoring and early warning system for critical pipeline sections to adjust the equipment's operating status and maintenance plans in real time.

6. The method for monitoring the condition of offshore oil extraction equipment based on machine vision according to claim 5, characterized in that, The structural stability scoring correction model is as follows: ； in, This refers to the revised structural stability score. This refers to the current structural stability score. This refers to the first correction factor, which is the average slope of the vibration trend. This refers to the adjustment weight corresponding to the first correction factor. This refers to the vibration offset corresponding to the primary reference vibration record. This refers to the vibration offset corresponding to the secondary reference vibration record. This refers to the second correction factor, which is the deviation magnitude of the vibration offset between the first and second reference vibration records. This refers to the adjustment weight corresponding to the second correction factor.

7. A machine vision-based condition monitoring system for offshore oil extraction equipment, characterized in that, The system includes: a data acquisition module, a data filtering module, a first correction factor determination module, a second correction factor determination module, and a scoring correction module, wherein: The data acquisition module is used to acquire historical monitoring records and historical vibration data of key pipeline sections, determine the current sediment state of key pipeline sections, and evaluate the current structural stability score of key pipeline sections. The data filtering module is used to analyze historical monitoring records, filter out several local historical monitoring logs that are consistent with the current sediment state and meet the predetermined water flow vortex conditions, and match the corresponding local historical vibration records based on the timestamp; the predetermined water flow vortex conditions refer to the type of water flow vortex most frequently encountered by the key pipeline section at the current time point, which is usually the most common water flow vortex pattern under the current season or marine environmental conditions. The predetermined water flow vortex conditions include the intensity, frequency, direction and duration of the water flow vortex; The first correction factor determination module is used to analyze the vibration characteristics of key pipeline sections caused by water flow vortex based on several local historical vibration records, construct the vibration change trend, and generate the first correction factor accordingly. The second correction factor determination module is used to find the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, and the second reference vibration record that is closest to the current time point under the same conditions, and to generate a second correction factor based on the deviation amplitude between the two. The scoring correction module is used to apply the first correction factor and the second correction factor to the current structural stability score for correction.

8. The machine vision-based offshore oil extraction equipment condition monitoring system according to claim 7, characterized in that, The first correction factor determination module specifically includes: The data parsing unit is used to sequentially parse each local historical vibration record and local historical monitoring log to obtain the average vibration amplitude characteristic parameters of the key pipeline section during the period of contact with the predetermined water flow vortex conditions; The trend construction unit is used to sort several average vibration amplitude characteristic parameters according to timestamps and construct vibration change trends. The average slope calculation unit is used to calculate the average slope of the vibration change trend and uses the average slope as the first correction factor.

9. The machine vision-based condition monitoring system for offshore oil extraction equipment according to claim 8, characterized in that, The second correction factor determination module specifically includes: The data lookup unit is used to find the first reference vibration record in historical vibration data that is consistent with the current sediment state and meets the predetermined water flow eddy conditions, as well as the second reference vibration record that is closest to the current time point under the same conditions. The vibration offset calculation unit is used to calculate the vibration offset of the key pipeline section in the first reference vibration record and the second reference vibration record during the period of contact with the predetermined water flow vortex condition. The deviation amplitude quantization unit is used to generate a second correction factor based on the deviation amplitude of the vibration offset between the two.

10. The machine vision-based condition monitoring system for offshore oil extraction equipment according to claim 9, characterized in that, The scoring correction module specifically includes: The model application unit is used to call the preset structural stability score correction model, and substitute the first correction factor and the second correction factor into it to correct the current structural stability score, so as to obtain the corrected structural stability score. The modified scoring application unit is used to apply the modified structural stability score to the status monitoring and early warning system of critical pipeline sections, so as to adjust the operating status and maintenance plan of the equipment in real time. The structural stability scoring correction model is as follows: ； in, This refers to the revised structural stability score. This refers to the current structural stability score. This refers to the first correction factor, which is the average slope of the vibration trend. This refers to the adjustment weight corresponding to the first correction factor. This refers to the vibration offset corresponding to the primary reference vibration record. This refers to the vibration offset corresponding to the secondary reference vibration record. This refers to the second correction factor, which is the deviation magnitude of the vibration offset between the first and second reference vibration records. This refers to the adjustment weight corresponding to the second correction factor.

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