A digital twin-based well control high-pressure hose failure monitoring and early warning system

Abstract

This application relates to a digital twin-based well control high-pressure hose failure monitoring and early warning system. The system includes a pan-tilt control module that adjusts the position and posture of a hardness tester in real time, controlling the hardness tester to pressurize the well control high-pressure hose under test. A data acquisition module collects the hardness tester's measured hardness value and real-time operating data corresponding to the pressurization. A wireless communication module receives the hardness tester's measured hardness value and real-time operating data and sends them to an aging life calculation module and a digital twin modeling module for the well control high-pressure hose. The digital twin modeling module constructs a digital twin model of the well control high-pressure hose based on historical operating data and real-time operating data combined with a three-dimensional geometric model. The aging life calculation module predicts the life of the hose based on the hardness tester's measured hardness value and the digital twin model of the well control high-pressure hose combined with an aging life model based on hardness characterization. The monitoring and early warning module monitors the life prediction results and issues a three-color alarm and an audible alarm. This system comprehensively detects hose failures.

Description

Technical Field

[0001] The present application relates to the technical field of aging monitoring and life prediction of well control high-pressure hoses, and in particular to a well control high-pressure hose failure monitoring and early warning system based on digital twins. Background Art

[0002] In the oil and gas development sector, well control systems are essential for safe and efficient operations. As a key component, high-pressure hoses are crucial for conveying high-pressure fluids, transmitting pressure and torque, transferring well control media, protecting the wellbore, and preventing wellhead leaks. Their performance and reliability are crucial to oil and gas production operations. In recent years, with the rapid development of China's energy industry, the application of non-metallic hoses, particularly well control hoses, has continued to expand, leading to increasing safety risks. Aging and failure of the inner lining and outer protective layer are particularly prominent. Because polymer materials like rubber are susceptible to various physical and chemical reactions, such as light, heat, hydrolysis, corrosion, and fatigue, they are prone to aging and degradation, leading to hose failure. Failure of in-service high-pressure hoses not only results in direct or indirect economic losses, but can also potentially lead to environmental risks and even safety incidents. However, due to limitations in existing aging evaluation methods, aging monitoring systems for well control hoses are extremely scarce on the market, posing significant challenges to the innovation of related detection and monitoring technologies.

[0003] In the existing rubber hose evaluation system, performance indicators obtained through destructive testing are usually used as the main basis for judging hose aging and failure. For example, the decline in tensile strength and elongation at break is used for judgment. However, this destructive testing method cannot be applied to the evaluation of in-service equipment, and the testing cycle is long and the process is cumbersome, making it difficult to meet the requirements of building a real-time online monitoring system. Most existing hardness testing devices are auxiliary measurement equipment, and the testing process relies on manual operation, which makes it difficult to meet the automation requirements of the online monitoring system; the testing scope is usually limited to spot checks of some questionable pipe sections, and it is impossible to conduct a comprehensive risk investigation of the entire hose, which may lead to missed detection risks; and most of them are only suitable for laboratory sample testing. Some existing fully automatic rubber Shore hardness testing platforms use open-loop control for the pressurization process, which makes it difficult to adjust the pressurization angle and position in real time, and cannot meet the actual needs of on-site monitoring of in-service high-pressure hoses.

[0004] Currently, there is a gap in the market for rubber aging and failure monitoring systems. Some online quality monitoring methods based on rubber hardness are mainly targeted at quality control in specific production processes. They are "static" testing methods and cannot meet the full lifecycle quality assessment needs of the "dynamic" process of aging and failure of well control high-pressure hoses. Although the hardness characterization ideas in these methods have certain reference value, they still have significant limitations when actually applied to well control high-pressure hose monitoring. In addition, the lack of an effective monitoring system makes it impossible to remotely collect aging detection data. Because well control high-pressure hoses are used in high-altitude operations and are long in length, full-section monitoring is difficult, making data storage and subsequent analysis difficult, and making it impossible to conduct an overall evaluation and global analysis of the test results. At the same time, the lack of a high-pressure hose failure warning system means that the test results are delayed, making it difficult to prevent risks in advance.

[0005] Therefore, in the related art, there is an urgent need for a method that can comprehensively and quickly detect and prevent the failure of well control high-pressure hoses. Summary of the Invention

[0006] Based on this, it is necessary to address the above technical problems and provide a digital twin-based well control high-pressure hose failure monitoring and early warning system that can comprehensively and quickly detect and prevent the failure of well control high-pressure hoses.

[0007] In a first aspect, the present application provides a digital twin-based well control high-pressure hose failure monitoring and early warning system. The method includes:

[0008] The pan / tilt control module is used to adjust the position and posture of the hardness tester in real time and control the hardness tester to pressurize the high-pressure hose of the well to be tested;

[0009] The data acquisition module is used to collect the hardness value and real-time operation data of the hardness tester corresponding to the pressure, analyze and send them to the wireless communication module;

[0010] A wireless communication module is used to receive the hardness value measured by the hardness tester and the real-time operation data and send them to the aging life calculation module and the well control high-pressure hose digital twin model modeling module respectively;

[0011] A digital twin modeling module for well control high-pressure hoses, which is used to build a digital twin model of well control high-pressure hoses based on historical and real-time operation data combined with a three-dimensional geometric model;

[0012] An aging life calculation module, for predicting the life of the well control high-pressure hose based on the hardness value measured by the hardness tester and the digital twin model in combination with an aging life model based on hardness characterization;

[0013] The monitoring and early warning module is used to monitor the life prediction results and provide three-color alarm and sound alarm.

[0014] Optionally, in one embodiment of the present application, the gimbal control module includes a hardness tester control unit, a pressurization control unit, and an inertial measurement unit;

[0015] The hardness tester control unit is used to control the position of the hardness tester and the angle of the indenter by outputting a motor driving torque based on the measured data of the inertial measurement unit;

[0016] The pressurization control unit is used to control the pressurization angle based on a linear quadratic optimal control algorithm and a PID control algorithm;

[0017] The inertial measurement unit is used to measure the real-time pan-tilt position and to control the pressure angle of the hardness tester based on the real-time pan-tilt position.

[0018] Optionally, in one embodiment of the present application, the data acquisition module includes a data acquisition unit, a data analysis unit, a pressure acquisition unit, a timing control unit and a data verification unit;

[0019] The data acquisition unit is used to set key nodes, divide the well control high-pressure hose into multiple monitoring pipe sections based on the key nodes, and deploy monitoring sensors in each monitoring pipe section to collect real-time operation data;

[0020] The data analysis unit is used to analyze the data collected by the hardness tester and the sensor;

[0021] The pressure acquisition unit is used to verify whether the hardness tester pressurization process meets the standard operation;

[0022] The timing control unit is used to control the data reading timing;

[0023] The data verification unit is used to verify the validity of the hardness collection data.

[0024] Optionally, in one embodiment of the present application, the well control high-pressure hose digital twin modeling module includes a physical modeling unit, an environmental integration unit, and a spatial visualization unit;

[0025] The physical modeling unit is used to perform hose physical modeling based on historical operation data and real-time operation data;

[0026] The environmental integration unit is used to collect environmental data based on remote sensing and optimize the hose physical model;

[0027] The spatial visualization unit is used to construct a three-dimensional geometric model of the hose and perform attribute annotation based on the hose physical model.

[0028] Optionally, in one embodiment of the present application, the aging life calculation module includes an aging life model fitting unit and an aging life prediction unit, and the aging life model fitting unit is used to:

[0029] Based on the high temperature accelerated aging test data, the interpolation algorithm was used to obtain the fitting equation of elongation at break and aging time;

[0030] Based on the mapping relationship between long-term low-temperature and short-term high-temperature tests, a conversion factor is determined. The activation energy of the Arrhenius equation is determined based on the conversion factor. The pre-exponential factor is determined based on the rubber material properties of the well control high-pressure hose. Finally, an aging model characterized by elongation at break is determined based on the activation energy, pre-exponential factor, and Arrhenius equation.

[0031] Determining an aging life model based on hardness characterization based on the hardness data and the elongation at break data in the hardening stage in combination with the aging model characterized by the elongation at break;

[0032] The aging life prediction unit is used to calculate the aging life based on the hardness value actually measured by the hardness meter in combination with the aging life model based on hardness characterization.

[0033] Optionally, in one embodiment of the present application, the monitoring and early warning module includes a monitoring visualization unit and an early warning unit;

[0034] The monitoring visualization unit is used to generate a life curve and a life cloud diagram based on the life prediction result;

[0035] The early warning unit is used to make a failure judgment based on the hose failure threshold and the failure alarm threshold, and to make a three-color alarm and a sound alarm based on the judgment result.

[0036] Optionally, in one embodiment of the present application, the hose failure threshold is determined based on a mapping relationship between the elongation at break and the hardness at failure, and the failure alarm threshold is determined based on a finite element simulation analysis.

[0037] The above-mentioned digital twin-based well control high-pressure hose failure monitoring and early warning system includes a control pan-tilt module, a data acquisition module, a wireless communication module, a well control high-pressure hose digital twin model building module, an aging life calculation module, and a monitoring and early warning module, wherein the control pan-tilt module is used to adjust the position and posture of the hardness tester in real time and control the hardness tester to pressurize the well control high-pressure hose to be tested; the data acquisition module is used to collect the hardness value and real-time operation data of the hardness tester corresponding to the pressurization, parse and send them to the wireless communication module; the wireless communication module is used to receive the hardness value and real-time operation data of the hardness tester and send them to the aging life calculation module and the well control high-pressure hose digital twin model building module respectively; the well control high-pressure hose digital twin model building module is used to construct a digital twin model of the well control high-pressure hose based on historical operation data and real-time operation data in combination with a three-dimensional geometric model; the aging life calculation module is used to predict the life based on the hardness value of the hardness tester and the digital twin model of the well control high-pressure hose in combination with an aging life model based on hardness characterization; the monitoring and early warning module is used to monitor the life prediction results and issue a three-color alarm and a sound alarm. The unique gimbal stabilizer for the durometer enables real-time adjustment of the durometer's position and posture, eliminating field vibrations and achieving, for the first time, standardized operation using automated equipment, ensuring both high measurement efficiency and accuracy. Furthermore, a method for evaluating hose aging failure based on hardness characterization was employed, and a portable rubber durometer was used to construct the testing equipment. A multi-dimensional mobility scheme was designed for the device, enabling multi-point monitoring of high-pressure hoses using a single device. Furthermore, digital twin technology was employed to combine field sensor data and hose information. A multidisciplinary, multi-physics, multi-scale, and multi-probabilistic simulation process was used to construct a digital twin model of the well control high-pressure hose. This digital twin model enables global system monitoring. By fitting a functional relationship between hardness and aging, full lifecycle monitoring of aging conditions was achieved. A color and sound alarm scheme was designed to provide emergency alerts for critical conditions. Compared to conventional well control high-pressure hose testing technologies, this invention offers a higher degree of automation, improved timeliness, and more comprehensive functionality. Overall, it can meet the general needs of routine hose monitoring at well control sites. This makes well control system operations smoother and more efficient, mitigates operational risks, and significantly reduces human resources and frees up labor. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a structural block diagram of a digital twin well control high-pressure hose failure monitoring and early warning system in one embodiment;

[0039] Figure 2 A schematic diagram of the final assembly of an automatic monitoring device for aging failure of an annular well control high-pressure hose in one embodiment;

[0040] Figure 3 Schematic diagram of a variable diameter clamping mechanism in one embodiment;

[0041] Figure 4 is a schematic diagram of a gimbal stabilizer according to one embodiment;

[0042] Figure 5 is a schematic diagram of a hardness tester in one embodiment;

[0043] Figure 6 A schematic diagram of a well control high-pressure hose monitoring interface in one embodiment;

[0044] Figure 7 A schematic diagram of a life curve interface for monitoring a well control high-pressure hose in one embodiment. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0046] In one embodiment, Figure 1 As shown in the figure, a well control high-pressure hose failure monitoring and early warning system based on digital twin is provided, including:

[0047] S1: Control the pan / tilt module, used to adjust the position and posture of the hardness tester in real time, and control the hardness tester to pressurize the high-pressure hose of the well to be tested.

[0048] In the examples of the present application, a sufficient number of test samples of hose rubber materials are prepared for the types of well control high-pressure hoses actually used on site. The preparation process requires strict control of relevant variables such as vulcanizers, antioxidants, and vulcanization processes. In accordance with the relevant specifications of GB / T3512 "Hot air accelerated aging and heat resistance test for vulcanized rubber or thermoplastic rubber", a high-temperature accelerated aging test is carried out on a sufficient number of rubber hose material test samples. The aging temperature is 60°C to 120°C, the temperature gradient is 30°C, the aging cycle is 5 days, and sampling is carried out every 24 hours. The hardness, tensile strength, tearing, rebound and other physical properties of different rubber material samples are measured; chemical tests such as nuclear magnetic resonance cross-linking analysis, Fourier transform infrared spectroscopy analysis, and gel permeation chromatography are carried out simultaneously. The aging mechanism of rubber materials is analyzed, the aging performance of well control high-pressure hose rubber materials is studied, and test data is obtained.

[0049] Combined with the actual working conditions of the well control site, and imitating the outdoor mobile camera process, a pan-tilt stabilizer solution for the automatic monitoring device of aging failure of the well control high-pressure hose is designed to realize the pressurization of the portable hardness tester. Figure 2The figure shows the schematic diagram of the automatic monitoring device for aging and failure of well control high-pressure hose, in which ① is the inspected pipe section, which represents the monitored section of the well control high-pressure hose; ② is the device body, which is the main structure for connecting the various parts of the monitoring device; ③ is the device cavity, in which a power supply battery pack and a brushless motor group are installed to drive the roller and crawler to perform periodic motion; ④ is the mounting hole, which is used to fix the device body and the cavity. The device can be disassembled from here to achieve replacement of the battery pack and maintenance of the motor; ⑤ is the base, which is used to stably place the device on the ground for long-term storage of equipment and can be disassembled during operation; ⑥ is the crawler mechanism, which is relatively stationary with the pan-tilt head pressurized stabilizer device and is driven by a motor behind the crawler to achieve rotation of the pan-tilt head around the pipe body. Figure 3 Figure 1 is a schematic diagram of the variable diameter clamping mechanism in the device, where ① is the clamping mechanism body, which is used to connect the motor and the device body; ② is the variable diameter rod, which can be adjusted up and down to make the device suitable for monitoring well control high-pressure hoses of different diameters to a certain extent; ③ is the roller, which enables the device to move freely on the hose section, realizes the relative position adjustment of the hardness tester and the tested hose, and realizes multi-point monitoring.

[0050] In specific applications, a Shore A durometer is selected based on the hardness range of the rubber material used for well control high-pressure hoses. To ensure smooth interaction between hardness data and host computer software, a durometer with real-time data transmission is recommended. Based on the diameter range of commonly used high-pressure hoses in well control sites, a variable-diameter hose clamping mechanism is designed to secure the automated monitoring device to the well control high-pressure hose being tested. A displacement mechanism is also designed for the monitoring device. Rollers and a motor assembly allow for free translation of the device on the hose, enabling adjustment of the relative position of the durometer and the tested hose, enabling multi-point dynamic monitoring. Tracks are used to enable circumferential monitoring of the same monitoring section using the durometer, while motor-controlled translation and rotation enable automatic monitoring of the circumferential high-pressure hose. An insertable servo gimbal is designed to insert the portable durometer into the servo gimbal, preventing relative movement. The gimbal stabilizer's movement is identical to that of the portable durometer. By adjusting the durometer's position and posture in real time, the durometer controls the pressure applied to the well control high-pressure hose being tested.

[0051] Specifically, in one embodiment of the present application, the gimbal control module includes a hardness tester control unit, a pressurization control unit, and an inertial measurement unit;

[0052] The hardness tester control unit is used to control the position of the hardness tester and the angle of the indenter by outputting a motor driving torque based on the measured data of the inertial measurement unit;

[0053] The pressurization control unit is used to control the pressurization angle based on a linear quadratic optimal control algorithm and a PID control algorithm;

[0054] The inertial measurement unit is used to measure the real-time pan-tilt position and to control the pressure angle of the hardness tester based on the real-time pan-tilt position.

[0055] In one embodiment of the present application, a gimbal control module includes a hardness tester control unit, a pressure control unit, and an inertial measurement unit. The hardness tester control unit establishes a mathematical model of the gimbal stabilizer control system by defining the input, output, and state variables. The input variable is the motor driving force F, the output variables are the stabilizer position x and the pressure pin angle Φ, and the state variables are x, dx, Φ, and dΦ. Based on the measured data from the inertial measurement unit, a self-designed servo is used as an actuator to adjust the output variables x and Φ in real time. The servo design primarily involves the selection of a small DC motor and the design of a variable speed gear set. The pressure control unit is used to adjust the pressure angle in real time to maintain a standardized pressure using a linear quadratic optimal control (LQR) algorithm and a PID control algorithm. The inertial measurement unit uses accelerometers and gyroscopes to measure the hardness tester's center of mass position and the pressure pin angle. The accelerometer measures acceleration along three axes and estimates the angle using trigonometric functions, but this method suffers from poor dynamic stability. The gyroscope measures angular velocity using the Coriolis force, and the angle is obtained by integrating the angular velocity. However, this method suffers from cumulative errors, resulting in poor static stability. The inertial measurement unit uses complementary filtering to achieve accurate pose measurement by combining the two measurement methods. It then uses a control algorithm to output a pulse-width modulation (PWM) signal to generate torque from the servo, thus achieving position correction. When the angle of the durometer and the relative position of the center of mass approach zero, the main control chip controls the electric elastic telescopic rod to apply pressure.

[0056] In addition, a Kalman filter is used to estimate the angular velocity of the pressure needle and the velocity of the gimbal's center of mass to further optimize control accuracy and speed. The gimbal control module is also designed with a limit mechanism. When the hardness tester's inclination angle approaches ±90°, the PWM output is immediately cut off and reverse braking is triggered. The hardware watchdog circuit monitors the controller's operating status to prevent the program from running away and causing loss of control. In specific applications, the automatic monitoring device for aging and failure of the well control high-pressure hose and the gimbal stabilizer are jointly debugged. Vibration environment tests are carried out. If the test accuracy of the vibration environment is not met, the mechanical structure of the automatic monitoring device for aging and failure of the well control high-pressure hose is improved; the initial angle and starting position of the pressure needle are changed to verify the controller's adaptability to parameter perturbations and complete robustness verification.

[0057] like Figure 4As shown in the figure, it is a schematic diagram of the gimbal stabilizer, in which ① is the connecting mechanism - connecting the gimbal stabilizer and the device body (the schematic diagram is only for display and is actually integrated with the crawler mechanism); ② is the circuit board layout mechanism - used to arrange the lower computer system; ③ is the servo gimbal - including the posture sensor and the servo (including a small DC motor, an adjustable potentiometer, a speed gear set and an output shaft); ④ is the communication box - used to place the data remote transmission module to achieve real-time communication with the upper computer software; ⑤ is the gimbal stabilizer body - used to connect various mechanisms, and the mechanism is hollow, and the interior is used for wiring; ⑥ is the electric elastic telescopic rod - used for automatic pressurization of the hardness tester, and there is a pressure sensor under the telescopic rod for standardized pressure feedback. As shown in the figure Figure 5 The figure shows a schematic diagram of a hardness tester, where ① is a button that contacts the electric elastic telescopic rod to achieve automatic pressurization; ② is a shock-absorbing spring that protects the hardness tester in a vibrating environment and also acts as a force relief after pressurization; ③ is a charging jack that is used to charge the hardness tester; and ④ is a data jack that is used for data exchange between the hardness tester and the lower computer system.

[0058] S2: Data acquisition module, used to collect the hardness value and real-time operation data of the hardness tester corresponding to the pressure, analyze and send them to the wireless communication module.

[0059] In the embodiment of the present application, the data acquisition module collects the hardness value and real-time operation data of the hardness meter corresponding to the pressurization, analyzes them and sends them to the wireless communication module.

[0060] Specifically, in one embodiment of the present application, the data acquisition module includes a data acquisition unit, a data analysis unit, a pressure acquisition unit, a timing control unit, and a data verification unit;

[0061] The data acquisition unit is used to set key nodes, divide the well control high-pressure hose into multiple monitoring pipe sections based on the key nodes, and deploy monitoring sensors in each monitoring pipe section to collect real-time operation data;

[0062] The data analysis unit is used to analyze the data collected by the hardness tester and the sensor;

[0063] The pressure acquisition unit is used to verify whether the hardness tester pressurization process meets the standard operation;

[0064] The timing control unit is used to control the data reading timing;

[0065] The data verification unit is used to verify the validity of the hardness collection data.

[0066] In one embodiment of the present application, the data acquisition unit is used to set up multiple key nodes, divide the lengthy well control high-pressure hose into multiple monitoring sections, and deploy pressure sensors, flow meters, temperature and humidity sensors, and vibration monitoring equipment at the same time to collect real-time operation data. The data parsing unit is used to parse the data collected by the hardness tester and the sensor according to the data frame structure and communication rules of the source protocol. The pressure acquisition unit mounts the pressure sensor FSR402 above the hardness tester, and the MCU sets the upper and lower pressure limits. The pressure sensor collects stress data, and when the stress is within the set range, it is considered a valid hardness measurement. The timing control unit controls the timing, and when the pressure value remains unchanged, it is considered that the pressure foot is in full contact with the sample, and controls the timer to read the hardness value within 1 second. The data verification unit collects three valid hardness data in succession, and calculates the difference between them two by two. If the difference results are all within the set absolute error range, the hardness value is considered valid.

[0067] S3: A wireless communication module, used to receive the hardness value actually measured by the hardness tester and the real-time operation data and send them to the aging life calculation module and the well control high-pressure hose digital twin model modeling module respectively.

[0068] In the embodiment of the present application, the wireless communication module adopts wireless communication to receive the hardness value measured by the hardness meter and the real-time operation data and send them to the aging life calculation module and the well control high-pressure hose digital twin model modeling module respectively to ensure the accuracy of the message format, data frame structure and communication rules. Configure the communication parameters of both parties to ensure parameter matching. Design mechanisms such as timeout retransmission, data verification, and baud rate dynamic switching fault tolerance to avoid communication interruption or data loss. Perform simple tests on data integrity and delay through methods such as CRC cyclic redundancy check, frame structure check, serial number and timestamp mechanism, and physical layer test to prevent data packet loss and other situations. Carry out data transmission tests in interference environments to ensure smooth and fast data transmission under on-site working conditions.

[0069] S4: Well control high-pressure hose digital twin model modeling module, used to build a well control high-pressure hose digital twin model based on historical operation data and real-time operation data combined with a three-dimensional geometric model.

[0070] In an embodiment of the present application, a digital twin model modeling module for a well control high-pressure hose is constructed based on real-time operation data and historical operation data collected historically, combined with a three-dimensional geometric model constructed by a CAD tool, to construct a digital twin model for a well control high-pressure hose.

[0071] Specifically, in one embodiment of the present application, the well control high-pressure hose digital twin modeling module includes a physical modeling unit, an environmental integration unit, and a spatial visualization unit;

[0072] The physical modeling unit is used to perform hose physical modeling based on historical operation data and real-time operation data;

[0073] The environmental integration unit is used to collect environmental data based on remote sensing and optimize the hose physical model;

[0074] The spatial visualization unit is used to construct a three-dimensional geometric model of the hose and perform attribute annotation based on the hose physical model.

[0075] In one embodiment of the present application, the physical modeling unit performs multi-physics, multi-scale, and multi-probability hose physical modeling based on historical and real-time operating data. The environmental integration unit uses remote sensing technology to acquire geological and meteorological data surrounding the pipeline and integrates these environmental variables to further optimize the hose physical model. The spatial visualization unit imports static data such as pipeline design drawings and maintenance records, constructs a 3D hose geometric model using CAD tools, and annotates attributes such as material, diameter, and connection method. This model then integrates with a GIS system to annotate the pipeline's geographic coordinates, enabling spatial visualization.

[0076] S5: An aging life calculation module, which is used to predict the life based on the hardness value measured by the hardness tester and the digital twin model of the well control high-pressure hose combined with the aging life model based on hardness characterization.

[0077] In an embodiment of the present application, the aging life calculation module predicts the life of the well control high-pressure hose by combining the hardness value measured by the hardness tester and the constructed digital twin model of the well control high-pressure hose with the aging life model based on hardness characterization.

[0078] Specifically, in one embodiment of the present application, the aging life calculation module includes an aging life model fitting unit and an aging life prediction unit, and the aging life model fitting unit is used to:

[0079] Based on the high temperature accelerated aging test data, the interpolation algorithm was used to obtain the fitting equation of elongation at break and aging time;

[0080] Based on the mapping relationship between long-term low-temperature and short-term high-temperature tests, a conversion factor is determined. The activation energy of the Arrhenius equation is determined based on the conversion factor. The pre-exponential factor is determined based on the rubber material properties of the well control high-pressure hose. Finally, an aging model characterized by elongation at break is determined based on the activation energy, pre-exponential factor, and Arrhenius equation.

[0081] Determining an aging life model based on hardness characterization based on the hardness data and the elongation at break data in the hardening stage in combination with the aging model characterized by the elongation at break;

[0082] The aging life prediction unit is used to calculate the aging life based on the hardness value actually measured by the hardness meter in combination with the aging life model based on hardness characterization.

[0083] In one embodiment of the present application, TTSP is time-temperature equivalence, which means that in some simple systems, the changes in the system at low temperature for a long time can be equivalent to the changes in the system at high temperature for a short time. According to the TTSP theory, the results of the high-temperature accelerated aging test conducted in the early stage can be equivalent to the aging test results of the material at the reference temperature for a longer time. There is a simple translation relationship between the low-temperature long-term "characteristic quantity-aging time" test curve and the high-temperature short-term test curve. This mapping relationship is usually represented by the conversion factor describe:

[0084]

[0085] in, Indicates temperature The aging time coordinates under Represents the aging time coordinate at temperature T. The corresponding performance indicators of the two are the same, and are represented by Establish a one-to-one correspondence.

[0086] The large amount of discrete test data obtained from the high-temperature accelerated aging test can be translated to the same reference temperature, forming a relatively dense test data point. Using an interpolation algorithm, a smooth "characteristic quantity - aging time" curve can be drawn. Based on the judgment criteria for aging failure in GB / T24145 and the applicable conditions of the subsequent Arrhenius equation, the characteristic quantity here is the elongation at break, represented by the letter M and expressed in %.

[0087] When the experimental temperature is less than 500K, the activity parameter of the rubber is a constant, specifically the activation energy The elongation at break of the material satisfies the Arrhenius equation, namely:

[0088]

[0089] in, is the pre-exponential factor, is the gas constant, which is a fixed value. 、 are performance indicators at different times.

[0090] Let the current time be , and remember is the time when the material fails, so the material life is:

[0091]

[0092] in, The elongation at break at failure is 50% according to the relevant provisions of GB / T24145; is the performance indicator at the current moment.

[0093] It is obvious from this model that the inverse of the thermodynamic temperature is basically linear with the logarithm of the sample life. A simple deduction yields:

[0094]

[0095] It is generally believed that the gas constant R=8.314J*mol-1*K-1, so the conversion factor Achievable activation energy The aging model characterized by the elongation at break can be determined by calculating the pre-exponential factor 1 / A0=0.0047. That is, there is an aging model characterized by elongation at break:

[0096]

[0097] Research on the aging mechanism of rubber materials shows that during aging, rubber hardness typically softens and then hardens. The former is often the result of molecular chain breakage caused by thermal oxidative aging. The material then hardens due to an increase in the crosslink density of the molecular chains during aging. Hose failure typically occurs during the hardening phase. A linear fit was performed on the hardness data during the hardening phase and compared to the elongation at break data under the same test conditions, yielding the following formula:

[0098]

[0099] Where X represents the hardness variable, and the unit is shoreA. Taking the hose material used in the present invention as an example, a=-34.5865, b=2430.8619.

[0100]

[0101] Among them, 48 shore A is the minimum hardness point.

[0102] Substituting the above formula into the aging model characterized by elongation at break, we get:

[0103]

[0104] in, is the hardness value at failure, and the elongation at failure of 50% is substituted into g(X) to obtain the hardness value at failure of approximately 68.8379 shoreA. When constructing the system, the failure threshold should be slightly less than , take the failure alarm threshold as 68shaoeA. It is the current hardness value, which can be monitored in real time by a hardness tester.

[0105] The aging life model based on hardness characterization is:

[0106]

[0107] The aging life prediction unit takes the hardness value measured by the automatic monitoring device for aging failure of the annular well control high-pressure hose as input, calculates the aging life of each monitoring point through an aging life model based on hardness characterization, and outputs the aging life of the pipe section through the weighted average of the life of each monitoring point.

[0108] S6: Monitoring and early warning module, used to monitor life prediction results and issue three-color alarm and sound alarm.

[0109] In the embodiment of the present application, the monitoring and early warning module is mainly used to monitor the life prediction results and visualize them, while also providing three-color alarms and sound alarms.

[0110] In one embodiment of the present application, the monitoring and early warning module includes a monitoring visualization unit and an early warning unit;

[0111] The monitoring visualization unit is used to generate a life curve and a life cloud diagram based on the life prediction result;

[0112] The early warning unit is used to make a failure judgment based on the hose failure threshold and the failure alarm threshold, and to make a three-color alarm and a sound alarm based on the judgment result.

[0113] In one embodiment of the present application, the monitoring visualization unit is used to generate a life curve and a life cloud diagram based on the life prediction result, such as Figure 6 and Figure 7 As shown, click on different pipe sections to view the segmented aging life curve of the hose. Different colors will be displayed on the main page according to the difference in pipe section life. The depth of color intuitively reflects the hose life. The aging degree of some pipe sections of the hose is represented in the form of a cloud map. This is the life cloud map.

[0114] The early warning unit determines hose failure based on the hose failure threshold and failure warning threshold, and issues a three-color alarm and an audible alarm based on the judgment results. Specifically, small lights are placed above different pipe segments in the digital twin model. Under normal hose conditions, the lights are solid green. If the software determines that a segment is nearing failure, the lights flash yellow. If the system determines that the hose has already failed, the lights turn solid red, and a host computer buzzer sounds an alarm. This implements three-color and audible alarms. The alarm module has three triggering mechanisms. The first is based on the hose failure threshold and aging failure warning value. If the aging life (represented by the hardness value) falls below the aging failure warning value, failure is imminent, and the lights flash yellow. If the aging life falls outside the dangerous alarm threshold, the system deems the hose to have failed, the lights turn solid red, and a host computer buzzer sounds an alarm. The second and third criteria are flow rate and vibration, respectively. Abnormal flow and vibration monitoring of a pipe segment—that is, if the flow and vibration data fall outside the set warning and dangerous thresholds, respectively—will trigger a three-color and audible alarm. Aging is the main criterion, while flow and vibration are supplementary. The three complement each other to further reduce the risks of missed detection or untimely monitoring.

[0115] In one embodiment of the present application, the hose failure threshold is determined based on a mapping relationship between the elongation at break and the hardness at failure, and the failure alarm threshold is determined based on finite element simulation analysis.

[0116] In one embodiment of the present application, the hose failure threshold is determined based on the mapping relationship between the elongation at break and the hardness at failure. That is, in the above-mentioned aging model characterized by the elongation at break, substituting 50% of the elongation at break into g(X) yields a hardness value of approximately 68.8379 shoreA at failure. When constructing the system, the failure threshold should be slightly less than , taking the hose failure threshold as 68shoreA. At the same time, based on finite element simulation analysis and simulation tests, the dangerous warning value of hose hardness was determined to be 66.5shoreA, which was set as the failure alarm threshold to supplement the hose failure threshold and achieve a "three-color alarm".

[0117] The finite element simulation process is as follows: The structure of the well control high-pressure hose is relatively complex, making it extremely difficult to incorporate all of its actual structural characteristics in theoretical analysis. Therefore, the structure needs to be simplified based on the following assumptions: ① The layered assumption divides the hose into a series of structural layers based on its structural form and material properties; ② The bonding assumption states that when the hose is subjected to external forces, its layers always maintain bonded contact and do not separate; ③ The planar cross-section assumption states that each layer within the same cross-section has the same elongation and remains flat; ④ The uniformity assumption assumes that the hose material has no initial defects and uniformly and continuously fills the space within it; and ⑤ The hose is a three-layer structure: the inner and outer layers are rubber, and a single spirally wound steel bar is embedded in the middle layer. Material parameters and constitutive equations are then determined. The rubber material parameters use the second-order Reduced Polynomia model. The software automatically fits the constitutive equation based on experimentally measured stress-strain data, setting the elastic modulus, Poisson's ratio, and density based on the material properties. Afterwards, a finite element model was established using ABAQUS finite element analysis software, employing a coupling method between the reinforcement layer and the rubber layer to create a 3D deformable wire-wound hose model. Fatigue life calculations were then performed using ABAQUS simulations to obtain the model's stress and strain fields and generate an .odb file. The .odb file was then imported into FE-SAFE for fatigue life calculations. Finally, threshold verification was performed: Actual operating conditions such as pressure and throttling were simulated, and material parameters in ABAQUS were varied to examine the fatigue and wear of well control high-pressure hoses of varying hardness in FE-SAFE. Simultaneously, the hose stress conditions in ABAQUS were examined, and both were used as a basis to verify the rationality of the failure threshold for the well control high-pressure hose.

[0118] The above-mentioned digital twin-based well control high-pressure hose failure monitoring and early warning system includes a control pan-tilt module, a data acquisition module, a wireless communication module, a well control high-pressure hose digital twin model building module, an aging life calculation module, and a monitoring and early warning module, wherein the control pan-tilt module is used to adjust the position and posture of the hardness tester in real time and control the hardness tester to pressurize the well control high-pressure hose to be tested; the data acquisition module is used to collect the hardness value and real-time operation data of the hardness tester corresponding to the pressurization, parse and send them to the wireless communication module; the wireless communication module is used to receive the hardness value and real-time operation data of the hardness tester and send them to the aging life calculation module and the well control high-pressure hose digital twin model building module respectively; the well control high-pressure hose digital twin model building module is used to construct a digital twin model of the well control high-pressure hose based on historical operation data and real-time operation data in combination with a three-dimensional geometric model; the aging life calculation module is used to predict the life based on the hardness value and the digital twin model of the well control high-pressure hose in combination with an aging life model based on hardness characterization; the monitoring and early warning module is used to monitor the life prediction results and issue a three-color alarm and a sound alarm. The unique gimbal stabilizer for the durometer enables real-time adjustment of the durometer's position and posture, eliminating field vibrations and achieving, for the first time, standardized operation using automated equipment, ensuring both high measurement efficiency and accuracy. Furthermore, a method for evaluating hose aging failure based on hardness characterization was employed, and a portable rubber durometer was used to construct the testing equipment. A multi-dimensional mobility scheme was designed for the device, enabling multi-point monitoring of high-pressure hoses using a single device. Furthermore, digital twin technology was employed to combine field sensor data and hose information. A multidisciplinary, multi-physics, multi-scale, and multi-probabilistic simulation process was used to construct a digital twin model of the well control high-pressure hose. This digital twin model enables global system monitoring. By fitting a functional relationship between hardness and aging, full lifecycle monitoring of aging conditions was achieved. A color and sound alarm scheme was designed to provide emergency alerts for critical conditions. Compared to conventional well control high-pressure hose testing technologies, this invention offers a higher degree of automation, improved timeliness, and more comprehensive functionality. Overall, it can meet the general needs of routine hose monitoring at well control sites. This makes well control system operations smoother and more efficient, mitigates operational risks, and significantly reduces human resources and frees up labor.

[0119] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0120] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0121] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0122] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, 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.

[0123] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A digital twin-based well control high-pressure hose failure monitoring and early warning system, characterized by: The system comprises: The pan / tilt control module is used to adjust the position and posture of the hardness tester in real time and control the hardness tester to pressurize the high-pressure hose of the well to be tested; The data acquisition module is used to collect the hardness value and real-time operation data of the hardness tester corresponding to the pressure, analyze and send them to the wireless communication module; A wireless communication module is used to receive the hardness value measured by the hardness tester and the real-time operation data and send them to the aging life calculation module and the well control high-pressure hose digital twin model modeling module respectively; A digital twin modeling module for well control high-pressure hoses, which is used to build a digital twin model of well control high-pressure hoses based on historical and real-time operation data combined with a three-dimensional geometric model; An aging life calculation module, for predicting the life of the well control high-pressure hose based on the hardness value measured by the hardness tester and the digital twin model in combination with an aging life model based on hardness characterization; Monitoring and early warning module, used to monitor life prediction results and provide three-color alarm and sound alarm; The control platform module includes a hardness tester control unit, a pressure control unit and an inertial measurement unit; The hardness tester control unit is used to control the position of the hardness tester and the angle of the indenter by outputting a motor driving torque based on the measured data of the inertial measurement unit; The pressurization control unit is used to control the pressurization angle based on a linear quadratic optimal control algorithm and a PID control algorithm; The inertial measurement unit is used to measure the real-time pan-tilt position and to control the pressure angle of the hardness tester based on the real-time pan-tilt position.

2. A digital twin-based well control high-pressure hose failure monitoring and early warning system according to claim 1, characterized in that: The data acquisition module includes a data acquisition unit, a data analysis unit, a pressure acquisition unit, a timing control unit and a data verification unit; The data acquisition unit is used to set key nodes, divide the well control high-pressure hose into multiple monitoring pipe sections based on the key nodes, and deploy monitoring sensors in each monitoring pipe section to collect real-time operation data; The data analysis unit is used to analyze the data collected by the hardness tester and the sensor; The pressure acquisition unit is used to verify whether the hardness tester pressurization process meets the standard operation; The timing control unit is used to control the data reading timing; The data verification unit is used to verify the validity of the hardness collection data.

3. The digital twin-based well control high-pressure hose failure monitoring and early warning system according to claim 1 is characterized in that: The well control high-pressure hose digital twin model modeling module includes a physical modeling unit, an environmental integration unit and a spatial visualization unit; The physical modeling unit is used to perform hose physical modeling based on historical operation data and real-time operation data; The environmental integration unit is used to collect environmental data based on remote sensing and optimize the hose physical model; The spatial visualization unit is used to construct a three-dimensional geometric model of the hose and perform attribute annotation based on the hose physical model.

4. The digital twin-based well control high-pressure hose failure monitoring and early warning system according to claim 1 is characterized in that: The aging life calculation module includes an aging life model fitting unit and an aging life prediction unit. The aging life model fitting unit is used to: Based on the high temperature accelerated aging test data, the interpolation algorithm was used to obtain the fitting equation of elongation at break and aging time; Based on the mapping relationship between long-term low-temperature and short-term high-temperature tests, a conversion factor is determined. The activation energy of the Arrhenius equation is determined based on the conversion factor. The pre-exponential factor is determined based on the rubber material properties of the well control high-pressure hose. Finally, an aging model characterized by elongation at break is determined based on the activation energy, pre-exponential factor, and Arrhenius equation. Determining an aging life model based on hardness characterization based on the hardness data and elongation at break data of the hardening stage in combination with the aging model characterized by elongation at break; The aging life prediction unit is used to calculate the aging life based on the hardness value actually measured by the hardness meter in combination with the aging life model based on hardness characterization.

5. The digital twin-based well control high-pressure hose failure monitoring and early warning system according to claim 1 is characterized in that: The monitoring and early warning module includes a monitoring visualization unit and an early warning unit; The monitoring visualization unit is used to generate a life curve and a life cloud diagram based on the life prediction result; The early warning unit is used to make a failure judgment based on the hose failure threshold and the failure alarm threshold, and to make a three-color alarm and a sound alarm based on the judgment result.

6. A digital twin-based well control high-pressure hose failure monitoring and early warning system according to claim 5, characterized in that: The hose failure threshold is determined based on a mapping relationship between the elongation at break and the hardness at failure, and the failure alarm threshold is determined based on finite element simulation analysis.

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