Fault diagnosis and optimization method for deepwater blowout preventer control system

Abstract

The invention relates to a fault diagnosis and optimization method for a deepwater blowout preventer control system. The method comprises the following steps: establishing a local model of each sub-element included in the deepwater blowout preventer control system; according to the working principle of the deepwater blowout preventer control system, the local models of all the sub-elements are associated into an overall model; actual working state parameters of the deepwater blowout preventer control system are collected, simulation output of the integrated local model and the integrated overall model is obtained, the simulation output and a second subset of the actual working state parameters are compared and verified, the reproduction degree of the actual working condition is obtained, the local model and the overall model are adjusted according to the reproduction degree, the step is repeated continuously, and the actual working condition of the deepwater blowout preventer control system is obtained. Obtaining a final local model and an overall model; and according to the obtained final local model and the overall model, fault diagnosis and working state optimization adjustment of the deepwater blowout preventer control system are carried out.

Description

Technical Field

[0001] This invention relates to the field of deepwater blowout preventer (BOP) fault diagnosis technology, and in particular to a method for fault diagnosis and optimization of a deepwater BOP control system. Background Technology

[0002] Deepwater blowout preventer (BOP) units are the core safety barrier for deepwater drilling operations. Their core function is to effectively control wellhead pressure in emergency situations such as blowouts or well kicks, ensuring the safe evacuation of drilling equipment and reliable wellhead closure, thereby protecting personnel and equipment safety and preventing damage to the marine environment and oil and gas resources.

[0003] As the core drive unit for the operation of deep-water blowout preventers (BOPs), the control system directly commands the opening and closing of key valves within the submersible BOP. Among these, the hydraulic control system is particularly critical, responsible for providing the direct hydraulic power required for the opening and closing of various BOPs. The system's valve bodies, pipelines, and other critical components face extreme service conditions in deep-water environments: they must withstand the dual high pressures of external static water and internal driving hydraulic pressure. This harsh environment poses a severe challenge to the hydraulic control system's pressure resistance, corrosion resistance, and long-term sealing reliability.

[0004] However, deepwater blowout preventer (BOP) control systems are highly complex and operate under harsh conditions such as high pressure, low temperature, and corrosive seawater for extended periods, making fault diagnosis extremely difficult. Existing fault diagnosis technologies often focus on single components or localized parts of the system, failing to fully consider the close coupling relationships and dynamic interactions between various operating components. This isolated analysis approach often struggles to accurately pinpoint the root causes of complex faults, leading to inaccurate fault diagnosis or delayed troubleshooting. Furthermore, a failure of the control system can easily trigger catastrophic consequences. Summary of the Invention

[0005] To address the aforementioned problems, the present invention aims to provide a fault diagnosis and optimization method for a deepwater blowout preventer (BOP) control system. This method establishes corresponding multi-domain coupled local models for each of the multiple sub-components of the BOP control system, then associates these local models with a global model. During model simulation, the simulations of the local and global models are integrated to determine the final model parameters. The global model with the final optimized parameters is then used for fault diagnosis and operational state optimization of the deepwater BOP control system. This avoids the problem of isolated analysis in existing technologies and improves the accuracy of diagnosis.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, this application provides a method for fault diagnosis and optimization of a deep-water blowout preventer control system, including: Step (1): Establish local models of each sub-component contained in the deep-water blowout preventer control system; Step (2): Based on the working principle of the deep-water blowout preventer control system, the local models of each sub-component are associated with the overall model; Step (3): Collect the actual working state parameters of the deep-water blowout preventer control system, and use the first subset of them as the input of the local model and the overall model. Perform simulation of the selected number of local models in the first time period and the simulation of the overall model in the second time period to obtain the simulation output of the integrated local model and the overall model. Compare and verify the simulation output with the second subset of the actual working state parameters to obtain the reproducibility of the actual working condition. Adjust the local model and the overall model according to the reproducibility. Repeat this step continuously to obtain the final local model and the overall model. Step (4): Based on the final local and global models obtained, perform fault diagnosis and operational status optimization of the deep-water blowout preventer control system.

[0007] In one implementation, in step (1), the local models of each sub-element respectively include: The local models corresponding to the power input unit, the underwater accumulator group, the logic control components, the pressure reducing valve, the directional valve, and the annular blowout preventer simulation unit model.

[0008] In one implementation, each local model digitally simulates the specific function of each component, including: The local model corresponding to the power input unit simulates the constant flow hydraulic power provided by the power input unit. The local model includes a step signal source and a flow source from left to right. The local model corresponding to the underwater accumulator group simulates the underwater accumulator group undertaking the functions of energy buffering and pressure compensation. The local model is built by constructing the accumulator in the hydraulic tank according to the system hydraulic level. The local model corresponding to the logic control component simulates the logic control component for maintaining the pressure mechanism. The local model includes a pressure relief valve, a piecewise linear signal source, and a two-position three-way solenoid valve to form a pressure maintenance mechanism. The local model corresponding to the pressure reducing valve includes a pressure regulating chamber, a damping piston, a valve core and valve seat assembly, a mass block of the valve moving parts, a balance chamber, a velocity reference, pipeline volume, flow rate and volume terminal, and an output throttling port. The local model corresponding to the reversing valve includes a spring action chamber, a valve core and valve seat assembly, a mass block of the valve moving parts, a hydraulic control chamber, a speed reference, a power hydraulic source, a hydraulic container, and a hydraulic control hydraulic source; The annular blowout preventer simulation unit includes a blowout preventer hydraulic cylinder, a back pressure check valve, a mass block for the blowout preventer moving parts, and a displacement sensor.

[0009] In one implementation, in step (3), a number of local model simulations are selected, including: pressure reducing valve constant pressure output simulation and directional valve directional switching simulation; The simulation of the overall model includes the simulation of the overall execution actions of the deep-water blowout preventer control system.

[0010] In one implementation, the deep-water blowout preventer control system performs an overall action simulation. The set second time period is related to the first time period of the simulation of each selected local model. The second time period covers at least one or more simulations of each local model.

[0011] In one implementation, the constant pressure output simulation of the pressure reducing valve specifically includes: providing a pressure source for plotting static characteristic curves by setting the working pressure of the hydraulic source to vary within the range of 56 MPa to 69 MPa; providing a hydraulic output curve for plotting dynamic characteristic curves by changing the control time; and judging the rationality of the model by using the hydraulic output curve.

[0012] In one implementation, the reversing simulation of the reversing valve specifically includes: controlling high-pressure control oil to enter the valve chamber, controlling the oil to push the piston to slide, during the sliding process, the high-pressure working power fluid port will be connected with the return oil port and the working oil port until the control oil pushes the piston to the maximum displacement, and judging whether the piston completely blocks the return oil port by the displacement and pressure curve, so that the working oil port and the high-pressure working power fluid port are completely connected.

[0013] In one implementation, the overall execution of the deep-water blowout preventer (BOP) control system is simulated, including: the BOP hydraulic control system starting to operate, the SPM valve core starting to move, and the BOP piston only starting to move after the SPM valve is fully open and the pressure in the BOP hydraulic cylinder rises sufficiently to push the piston. Simulation tests are conducted to compare the time taken for the annular BOP and the gate BOP to reach their maximum stroke with the API standard requirements: the closing time for the underwater gate BOP is within 45 seconds, and for the annular BOP, it is within 60 seconds, verifying the overall rationality of the model.

[0014] The present invention has the following advantages due to the adoption of the above technical solutions: The method provided by this invention enables the monitoring and early warning of stuck pipe risk based on a cuttings transport model and a deep learning machine learning model. Its main effects include: by establishing a wellbore cuttings transport model, it can calculate the cuttings bed height in real time, characterize and analyze the wellbore flow obstruction trend and cuttings accumulation, providing data and mechanistic basis for the machine learning model; through the deep learning machine learning model, it can automatically monitor the coupling anomalies between cuttings bed height and logging parameters, and calculate the probability of stuck pipe risk caused by cuttings accumulation in real time. Because it incorporates a cuttings transport model, this method improves the accuracy of identifying stuck pipe risk caused by cuttings accumulation and reduces false alarms and missed alarms. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the overall process in one embodiment of this application; Figure 2 This is a schematic diagram with annotations of a partial model of a pressure reducing valve according to one embodiment of this application; Figure 3 This is a schematic diagram with annotations of a partial model of a directional valve according to an embodiment of this application; Figure 4 This is a schematic diagram with annotations of an overall model of one embodiment of this application; Figures 5 to 14 A comparison of fault simulation results under normal and abnormal operating conditions for integrated simulation of local and global models; Wherein: 0-Comprehensive hydraulic fluid properties, 1-Step signal source, 2-Flow source, 3-Pressure relief valve, 4-Accumulator group, 5-Segmented linear signal source, 6-Two-position two-way solenoid directional valve, 7-Pressure sensor, 8-Pressure source, 9-Segmented linear signal source, 10-Two-position three-way solenoid directional valve, 11-Blowout preventer hydraulic cylinder, 12-Back pressure check valve, 13-Mass block of blowout preventer moving parts, 14-Displacement sensor, 15-Pressure regulating chamber, 16-Resistance 17-Valve piston, 18-Valve core and seat assembly, 19-Valve moving part mass block, 20-Balance chamber, 21-Speed ​​reference, 22-Pipeline volume, 23-Output throttle orifice, 24-Control signal, 25-Adjustable throttle valve, 26-Pressure source, 27-Spring action chamber, 28-30-Valve core and seat assembly, 29-Valve moving part mass block, 31-Hydraulic control chamber, 32-Power hydraulic source, 33-Hydraulic container, 34-Hydraulic control hydraulic source. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention are within the scope of protection of the present invention.

[0017] based on Figure 1 The above forms the overall framework of the present invention. In one embodiment, a method for fault diagnosis and optimization of a deep-water blowout preventer control system is described.

[0018] The method of this application embodiment includes the following steps: Step (1): Establish local models of each sub-component contained in the deep-water blowout preventer control system; Step (2): Based on the working principle of the deep-water blowout preventer control system, the local models of each sub-component are associated with the overall model; Step (3): Collect the actual working state parameters of the deep-water blowout preventer control system, and use the first subset of them as the input of the local model and the overall model. Perform simulation of the selected number of local models in the first time period and the simulation of the overall model in the second time period to obtain the simulation output of the integrated local model and the overall model. Compare and verify the simulation output with the second subset of the actual working state parameters to obtain the reproducibility of the actual working condition. Adjust the local model and the overall model according to the reproducibility. Repeat this step continuously to obtain the final local model and the overall model. Step (4): Based on the final local and global models obtained, perform fault diagnosis and operational status optimization of the deep-water blowout preventer control system.

[0019] The above method is described below in a more detailed embodiment with reference to more accompanying drawings.

[0020] Step (1): Establish local models of each sub-component contained in the deep-water blowout preventer control system; Specifically, the local models of each sub-component include: The local models corresponding to the power input unit, the underwater accumulator group, the logic control components, the pressure reducing valve, the directional valve, and the annular blowout preventer simulation unit model.

[0021] Among them, the local model corresponding to the power input unit simulates the constant flow hydraulic power provided by the power input unit. The local model includes a step signal source and a flow source from left to right. The local model corresponding to the underwater accumulator group simulates the underwater accumulator group undertaking the functions of energy buffering and pressure compensation. The local model is built by constructing the accumulator in the hydraulic tank according to the system hydraulic level. The local model corresponding to the logic control component simulates the logic control component to maintain the pressure mechanism. The local model includes a pressure relief valve, a piecewise linear signal source, and a two-position three-way solenoid valve to form a pressure maintenance mechanism. The local model corresponding to the pressure reducing valve includes the pressure regulating chamber, damping piston, valve core and valve seat assembly, valve moving part mass block, balance chamber, velocity reference, pipeline volume, flow and volume terminal, and output throttling port; The local model corresponding to the directional valve includes the spring action chamber, valve core and valve seat assembly, valve moving part mass block, hydraulic control chamber, speed reference, power hydraulic source, hydraulic container, and hydraulic control hydraulic source; The annular blowout preventer simulation unit includes a blowout preventer hydraulic cylinder, a back pressure check valve, a mass block for the blowout preventer moving parts, and a displacement sensor.

[0022] More specifically, and exemplaryly, using AMEsim software as an example, we construct a local model of multi-domain coupling between a pressure reducing valve and a directional valve.

[0023] Modeling of pressure reducing valves includes: Step 1: Determine the structure of the pressure reducing valve for constant pressure output and determine the module attributes. Specifically, this means: according to the AMESim module, select the necessary structural parameter types and obtain the actual structural parameters of the pressure reducing valve to be simulated for constant pressure output. The structural parameters include at least the piston diameter, piston rod diameter, orifice cross-section type, orifice geometry parameters, valve core mass, piston spring stiffness, piston spring preload, damping piston, regulating chamber, and balance chamber structure. Step 2: Based on the actual structural characteristics of the pressure reducing valve with constant pressure output, establish basic models of different functional parts based on the AMESim database. The basic models should include at least: pressure regulating chamber, damping piston, valve core and valve seat assembly, valve moving part mass block, balance chamber, velocity reference, pipeline volume, flow and volume terminal, and output throttling port.

[0024] exist Figure 2In this system, the main control unit consists of a pressure regulating chamber (assembly 15) and a damping piston (assembly 16), which suppresses pressure fluctuations through dynamic damping characteristics. A conical valve core-seat assembly (assemblies 17 and 18) is used to form the valve core assembly, which adjusts the flow area through axial displacement to create a pressure-flow coupling control mechanism. An integrated valve core mass block (assembly 19) and a return spring are used to construct a second-order vibration system to simulate dynamic response characteristics. A balance chamber (assembly 20) is connected to the main control chamber via a feedback pipeline to form a pressure compensation loop to improve control stability. A pipeline volume module (assembly 22) and terminal nodes are used to simulate the capacitive effect and end-load characteristics of actual hydraulic pipelines. An adjustable throttle valve (assembly 25) and an external hydraulic source (assembly 26) form a pressure supply loop, which achieves closed-loop regulation of the output pressure through a control signal (assembly 24). Step 3: Utilize AMESim's SUBMODEL mode to assign the preferred submodels to the functional modules included in the basic model. For modules not mentioned above, use the Premier submodel function to assign them to AMESim's preferred models. In AMESim's SUBMODEL mode, first assign the recommended submodels to the modules included in the basic model. For modules not mentioned above, the Premier submodel function can be used to assign AMESim's recommended submodels, or the submodels can be determined based on user experience, model simplification, and product structure. This step is part of the AMESim modeling process and further refines the model built in the previous step. It is used to determine the physical models (physical assumptions) and corresponding mathematical expressions for each module in the model. Without this step, the next step cannot be performed. The specific unit model configuration is as follows: Based on the BAP12, BAF01, BAO001, BAP12, BAP016, BHC11, and BHORF0 unit models from the AMESim hydraulic component library, the pressure regulating chamber, damping piston, valve core and seat assembly, balance chamber, piping volume, and output throttling orifice are configured. Based on the MECMAS21 and F000 unit models from the AMESim one-dimensional mechanical library, the mass block and velocity reference of the valve moving parts are configured. Based on the HYDVORF0 and PS00 unit models from the AMESim hydraulic library, the throttle valve and hydraulic source are configured.

[0025] The recommended sub-models are derived from the typical structural forms of pressure reducing valves with constant pressure output. They are applicable to the AMESim modeling process of most pressure reducing valves. To a certain extent, while ensuring the credibility of the model, the workload of selecting sub-models of each module in the AMESim modeling process of pressure reducing valves is reduced, and the efficiency of AMESim modeling of pressure reducing valves is improved. Step 4: Based on the actual parameters of the pressure reducing valve designed for constant pressure output, define global parameters and configure basic model parameters using AMESim's PARAMETER component.

[0026] The pressure reducing valve is designed with a rated pressure of 70 MPa, a rated flow rate of 200 L / min, a pressure adjustment range of 21 MPa-55 MPa, an allowable change in outlet pressure caused by changes in inlet pressure of 0.5 MPa, an allowable change in outlet pressure caused by changes in flow rate of 0.5 MPa, and an allowable external leakage of 0.2 L / min.

[0027] ① The inlet and outlet diameters of the pressure reducing valve

[0028] 4.63

[0029] In the formula For the rated flow rate, take 200 (L / min), Let be the oil flow velocity at the diameter d of the inlet and outlet. =6 (m / s), so d = 30 mm.

[0030] ② The large diameter D and small diameter of the main valve core of the pressure reducing valve

[0031] From the perspective of strength

[0032] The flow rate formula through the annular channel between the main valve core and the valve body of the pressure reducing valve is:

[0033] Use the rated flow rate Q in the above formula. Given that the oil flow velocity V in the annular channel is ≤6m / s, take... = D, then we get: .2

[0034] Substituting the rated flow rate, we get D ≥ 31.1 mm. Setting D = 32 mm, we obtain... =16mm.

[0035] ③ Damping orifice diameter and length

[0036] In theory: =8.0~2.1m, =70~250mm, take =1.0mm, =100mm.

[0037] ④ Maximum opening of the main valve port of the pressure reducing valve

[0038] Because oil undergoes diffusion losses as it flows through the valve orifice, to prevent this, the opening area should be kept within a certain range. Not greater than the annular cross-sectional area between the main valve core and the valve body of the pressure reducing valve. .Right now:

[0039] D and Substitute and get 6mm.

[0040] ⑤ Minimum displacement of the main valve core of the pressure reducing valve and maximum displacement

[0041] Minimum displacement :

[0042] Maximum displacement :

[0043] In the formula: Maximum opening of the main valve port. Rated flow rate Flow coefficient of the main valve orifice, =0.65, D is the main valve core large diameter, The density of hydraulic oil, Rated pressure, The highest set pressure for exports, The lowest set pressure for exports.

[0044] Substituting the values, we get =5.7mm, =5.8mm.

[0045] ⑥ Main valve spring stiffness and pre-compression

[0046]

[0047] In the formula: The pressure drop caused by the oil flowing through the damping orifice, G is the weight of the main valve core, and A is the cross-sectional area at the large diameter D of the main valve core. The flow angle at the main valve port is taken as follows: =69 degrees, The displacement of the main valve core.

[0048] get =195N / mm, =230mm.

[0049] In summary, the basic model parameters are set as follows: the constant pressure of the hydraulic source is 56MPa, the pipeline volume, flow rate, and volume terminal are 2 cubic centimeters and 100 cubic centimeters, respectively; the valve core and valve stem diameters are 32mm and 16mm, respectively; the spring pre-compression is 230mm; the spring stiffness is 195N / mm; and the valve core mass and stroke are 0.03kg and 6mm, respectively. Step 5: Using AMESim's SIMULATION component, configure the simulation run time to 60 seconds and the time interval to 0.01 seconds, perform single or batch simulation calculations, and determine the characteristics of the pressure reducing valve and the influence of each parameter on the output pressure of the pressure reducing valve. Step Six: Based on the determined physical operating parameters and working environment parameters of the pressure reducing valve under normal operating conditions, return to Step Four and change the valve core displacement stroke and hydraulic source pressure respectively. Obtain the outlet pressure change curve and valve core displacement velocity change curve for two fault modes: valve core jamming and insufficient hydraulic source pressure due to leakage. Simulation results show that in the case of valve core jamming, the outlet pressure is 0 because the valve core does not move, and the outlet cannot obtain pressure from the pressure source. In the case of insufficient hydraulic pressure due to leakage, because the spring force remains unchanged, the valve core's speed and displacement change rapidly until reaching their maximum value and cannot return to their original position.

[0050] The model diagram of the pressure reducing valve is shown below. Figure 2 .

[0051] For example, modeling a directional control valve (SPM directional control valve) includes: Step 1: Determine the structure of the directional valve and the attributes of the module. Specifically, this means: according to the AMESim module, select the necessary structural parameter types and obtain the actual structural parameters of the SPM directional valve to be simulated. The structural parameters include at least the piston diameter, piston rod diameter, orifice cross-section type, orifice geometry parameters, valve core mass, piston spring stiffness, piston spring preload, upper and lower valve bodies, oil inlet channel, oil outlet channel, and the structural form of the regulating chamber. Step 2: Based on the actual structural characteristics of the SPM directional valve, establish basic models of different functional parts based on the AMESim database. The basic models should include at least: spring action chamber, valve core and valve seat assembly, valve moving part mass block, hydraulic control chamber, speed reference, power hydraulic source, hydraulic container, and hydraulic control hydraulic source.

[0052] When high-pressure control fluid is injected into the pilot stage actuator (assembly 31), the control pressure acts on the end face of the drive piston to form an axial thrust, causing the piston to produce a linear displacement within the valve chamber. During the piston's movement, its valve port structure creates a dynamic communication area between the high-pressure power fluid channel, the return oil channel, and the working oil port. During this stage, the hydraulic system is in a pressure transition regulation state. When the piston stroke reaches its limit displacement, its sealing end face completely covers the return oil channel port, achieving a one-way full-flow connection between the high-pressure power fluid and the working oil port. Step 3: Utilize AMESim's SUBMODEL mode to select the optimal model for each functional module within the basic model. For modules not included, use the Premier submodel function to assign them to the optimal model selected by AMESim. The specific unit model configuration is as follows: Based on the BAP016, BAO001, BAP12, and BHC11 unit models from the AMESim hydraulic component library, the spring actuation chamber, valve core and valve seat assembly, hydraulic control chamber, and hydraulic container are configured respectively. Based on the MECMAS21 and F000 unit models from the AMESim one-dimensional mechanical library, the mass block and velocity reference of the valve moving parts are configured respectively. Based on the PS00 unit model from the AMESim hydraulic library, the power hydraulic source and hydraulic control hydraulic source are configured.

[0053] Step 4: Based on the actual parameters of the designed SPM directional valve, use AMESim's PARAMETER component to define global parameters and configure basic model parameters.

[0054] Referring to relevant product data from both domestic and international sources, design the rated pressure of the SPM valve. 70MPa, rated flow rate Pressure loss at rated flow rate of 200 L / min Internal leakage at 1 MPa, rated pressure 1 / Lmin, allowable back pressure value at the oil return port 31MPa, the minimum control pressure of the hydraulic valve 45MPa.

[0055] ① Inlet and outlet diameters 4.63

[0056] In the formula For rated flow rate, Oil flow rate at the diameter of the inlet and outlet ports =200L / min, =6m / s, thus d 26.83mm, take d=38mm.

[0057] ② The large diameter D and small diameter of the main valve core

[0058]

[0059]

[0060] Substituting the rated flow rate, we get D. 31.1mm, take D=60mm, =40mm.

[0061] ③ Maximum opening of the main valve port

[0062] Because oil flowing through the valve port may experience diffusion losses, to prevent this, the opening area should be kept within a certain range. Not greater than the annular cross-sectional area between the main valve core and the valve body ,have to: .1875D D and Substitute and get ≤11mm, take =10mm.

[0063] ④ Effective oil sealing length and sealing length

[0064]

[0065] Zb In the formula: D represents the large diameter of the valve core. The clearance of the single-sided fit between the valve core and the valve body bore. Rated pressure, Number of sealing surfaces with internal leakage. Dynamic viscosity of oil Permissible internal leakage, Z-sealing length. Number of internal pressure equalization grooves, b is the average pressure groove width.

[0066] With D=60mm, =0.003mm, =70MPa =2, =0.072 kg / m·s, =1L / min, Z=3, b=0.5mm Substituting these values, we get... =0.95mm, =1.56mm.

[0067] ⑤ Valve core stroke S

[0068] The value of S is 11.56 mm.

[0069] In summary, the basic model parameters are set as follows: the spring pre-compression is 4mm, the spring stiffness is 2500N / mm, the valve core mass and stroke are 10kg and 12mm respectively, the valve core and valve stem diameters are 60mm and 40mm respectively, the power hydraulic source is set to 70MPa, the hydraulic control source is set to a gradient change from 0 to 45MPa, and the flow volume is set to 1000 cubic centimeters. Step 5: Using AMESim's SIMULATION component, configure the simulation run time to 90 seconds and the interval time to 0.01 seconds, perform single or batch simulation calculations, and determine the characteristics of the SPM reversing valve and the influence of each parameter on the reversing valve's reversing speed. Step Six: Based on the determined physical operating parameters and working environment parameters of the SPM directional valve under normal operating conditions, return to Step Four and change the hydraulic control pressure, valve core stroke, and spring stiffness respectively. Obtain the valve core speed and outlet pressure change curves under three fault modes: internal leakage, valve core jamming, and decreased spring stiffness. Simulation results show that internal leakage leads to pressure loss in the hydraulic control chamber, reduced valve core driving force, slower movement speed, a 4-second delay in displacement response, and insufficient displacement. Under the valve core jamming fault condition, the output pressure decreases significantly and rises rapidly from 0 to 7 MPa, consistent with actual conditions. Under the decreased spring stiffness fault condition, the valve core movement speed increases significantly, failing to provide sufficient reaction force to slow the valve core movement, thus failing to effectively control the valve core speed and position changes, consistent with expectations.

[0070] Step (2): Based on the working principle of the deep-water blowout preventer control system, the local models of each sub-component are associated with the overall model; Specifically, the parameters of each subsystem component established above are input according to the actual working conditions to achieve the function of each component. Then, according to the hydraulic control logic and control principle diagram of the deep-water blowout preventer control system, the subsystem components are connected step by step. That is, the power input unit, underwater accumulator group, logic control component unit, constant pressure output pressure reducing valve, SPM reversing valve and annular blowout preventer simulation unit model are linked step by step to realize the establishment of the overall model of the deep-water blowout preventer control system.

[0071] Figure 4 The diagram shows the annotations for the overall model.

[0072] Step (3): Collect the actual working state parameters of the deep-water blowout preventer control system, and use the first subset of them as the input of the local model and the overall model. Perform simulation of the selected number of local models in the first time period and the simulation of the overall model in the second time period to obtain the simulation output of the integrated local model and the overall model. Compare and verify the simulation output with the second subset of the actual working state parameters to obtain the reproducibility of the actual working condition. Adjust the local model and the overall model according to the reproducibility. Repeat this step continuously to obtain the final local model and the overall model. Specifically, a number of local models are selected for simulation, including: pressure reducing valve constant pressure output simulation and directional valve switching simulation; The simulation of the overall model includes the simulation of the overall execution actions of the deep-water blowout preventer control system.

[0073] In this embodiment, the overall execution action simulation of the water blowout preventer control system is set in a second time period, which is related to the first time period of the simulation of each selected local model. The second time period covers at least one or more simulations of each local model.

[0074] In this embodiment, the constant pressure output simulation of the pressure reducing valve specifically includes: providing a pressure source for plotting static characteristic curves by setting the working pressure of the hydraulic source to vary within the range of 56 MPa to 69 MPa; providing a hydraulic output curve for plotting dynamic characteristic curves by changing the control time; and judging the rationality of the model by using the hydraulic output curve.

[0075] In this embodiment, the reversing simulation of the reversing valve specifically includes: controlling the high-pressure control oil to enter the valve chamber, controlling the oil to push the piston to slide, during the sliding process, the high-pressure working power fluid port will be connected with the return oil port and the working oil port until the control oil pushes the piston to the maximum displacement, and judging whether the piston completely blocks the return oil port by the displacement and pressure curve, so that the working oil port and the high-pressure working power fluid port are completely connected.

[0076] In this embodiment, the overall execution of the deep-water blowout preventer (BOP) control system is simulated, including: the start of the BOP hydraulic control system, the initial movement of the SPM valve core, and the piston only starting to move after the SPM valve is fully open and the pressure in the BOP hydraulic cylinder rises sufficiently to push the piston. The simulation tests compare the time taken for the annular BOP and the gate BOP to reach their maximum stroke with the API standard requirements: the closing time for the underwater gate BOP is within 45 seconds, and for the annular BOP, it is within 60 seconds, thus verifying the overall rationality of the model.

[0077] The following is an example of the specific process: Step 1: Determine the structure of the deep-water blowout preventer control system and determine the module attributes. Specifically, this means: according to the AMESim module, select the necessary structural parameter types and obtain the actual structural parameters of the deep-water blowout preventer control system to be simulated. Since the structural parameters of the pressure reducing valve and the SPM reversing valve have been obtained in the previous embodiment, other structural parameters include at least the number of underwater accumulators, pressure and gas volume, and the mass and stroke of the hydraulic cylinder in the annular blowout preventer group. Step 2: Based on the actual structural characteristics of the deepwater blowout preventer control system, establish basic models of different functional parts based on the AMESim database. Excluding the basic models of the pressure reducing valve and the reversing valve in the example above, other basic models should include at least: step signal source, flow source, pressure relief valve, accumulator group, piecewise linear signal source, two-position two-way solenoid reversing valve, pressure sensor, pressure source, piecewise linear signal source, two-position three-way solenoid reversing valve, blowout preventer hydraulic cylinder, back pressure check valve, mass block of the blowout preventer moving parts, and displacement sensor.

[0078] A constant-flow hydraulic power source (component 2) constitutes the system's energy input unit; a safety relief valve (component 3) ensures pipeline operation safety through pressure threshold control; an underwater accumulator group (component 4) performs energy buffering and pressure compensation functions; a two-position two-way solenoid directional valve (component 6) and a two-position three-way solenoid directional valve (component 10) together constitute the logic control component of the fluid passage, forming a pressure maintenance mechanism in conjunction with a back pressure check valve (component 12); a blowout preventer hydraulic actuator (component 11) and an equivalent mass module (component 13) form the end-effector unit, realizing the final conversion of mechanical work; a pressure sensor (component 7) and a displacement sensor (component 14) respectively construct a system status monitoring network, forming the data foundation for closed-loop control. Additional functional modules include a constant-pressure output pressure reducing valve, an SPM-type directional valve, and a ring-shaped blowout preventer simulation unit, collectively improving the system's functional completeness and scenario adaptability. This configuration scheme achieves the orderly integration of power transmission, pressure regulation, status perception, and actuators through modular design. Step 3: Utilize AMESim's SUBMODEL mode to select the optimal model for each functional module within the basic model. For modules not included, use the Premier submodel function to assign them to the optimal model selected by AMESim. The specific unit model configuration is as follows: Based on the HFLOC, RV010, HA0000, RV00022, PT002, PS00, HJ020, and CV010 unit models in the AMESim hydraulic library, flow sources, pressure relief valves, accumulator groups, two-position two-way solenoid directional valves, pressure sensors, pressure sources, blowout preventer hydraulic cylinders, and back pressure check valves are configured respectively. Based on the UD00d and STEP0 unit models in the AMESim signal control library, step signal sources and piecewise linear signal sources are configured respectively. Based on the MECMAS21 and MECDS0A unit models in the AMESim one-dimensional mechanical library, mass blocks and displacement sensors of the blowout preventer moving parts are configured respectively. Other unit models are configured according to Cases 1 and 2; Step 4: Based on the actual parameters of the designed deepwater blowout preventer control system, define global parameters and configure basic model parameters using AMESim's PARAMETER component. The basic model parameters for the pressure reducing valve and SPM reversing valve are given in the above embodiments; other parameter settings are as follows: In the annular blowout preventer assembly: the piston diameter and rod diameter in the hydraulic cylinder are 837mm and 12mm respectively, the piston stroke is 400mm, and the mass is set to 100kg; the opening pressure of the pressure relief valve 3 is set to 70MPa; the pressure of the underwater accumulator 4 is set to 70MPa, the gas pre-charge pressure is 45MPa, the accumulator capacity is 800L, and the pressure source 4 is 45MPa; Step 5: Using AMESim's SIMULATION component, configure the simulation run time to 140 seconds and the interval time to 0.01 seconds, perform single or batch simulation calculations, and determine the characteristics of the control system and the influence of each parameter on the closing speed of the annular blowout preventer. Step Six: Based on the determined physical operating state parameters and working environment state parameters of the control system under normal operating conditions, return to Step Four to change the pressure of the underwater accumulator and obtain the hydraulic cylinder displacement change curve under the accumulator leakage fault mode. Under the fault of underwater accumulator leakage and insufficient hydraulic power source, the hydraulic cylinder displacement response time remains unchanged, but it cannot complete the entire process within the specified time, that is, the gate cannot close within the specified time.

[0079] In this step, the simulation of the local model and the model as a whole is compared with the actual reasonable working conditions and standard values. Outliers are screened and the model parameters are optimized. Furthermore, the simulation effect of the optimized model is compared again until the model feedback effect reaches the reasonable value.

[0080] Step (4): Based on the final local and global models obtained, perform fault diagnosis and operational status optimization of the deep-water blowout preventer control system.

[0081] See attached figures for reference. Figures 5 to 14 .

[0082] The model is used to simulate and diagnose faults in the deep-water blowout preventer control system, specifically including: By modifying key parameters of the model and setting fault modes, the impact of different faults on valves and systems can be explored. Specifically, the fault modes include: simulating internal leakage, valve core jamming and reduced spring stiffness of SPM valves; simulating valve core jamming and leakage of pressure reducing valves leading to insufficient hydraulic source pressure; and simulating the impact of leakage of underwater accumulators on the overall system.

[0083] Furthermore, by setting and diagnosing faults, we explored the impact of various fault modes on the system, thereby investigating the key fault modes and solutions for the deep-water blowout preventer control system.

[0084] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0085] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0086] 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, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for fault diagnosis and optimization of a deepwater blowout preventer control system, characterized in that, include: Step (1): Establish local models of each sub-component contained in the deep-water blowout preventer control system; Step (2): Based on the working principle of the deep-water blowout preventer control system, the local models of each sub-component are associated with the overall model; Step (3): Collect the actual working state parameters of the deep-water blowout preventer control system, and use the first subset of them as the input of the local model and the overall model. Perform simulation of the selected number of local models in the first time period and the simulation of the overall model in the second time period to obtain the simulation output of the integrated local model and the overall model. Compare and verify the simulation output with the second subset of the actual working state parameters to obtain the reproducibility of the actual working condition. Adjust the local model and the overall model according to the reproducibility. Repeat this step continuously to obtain the final local model and the overall model. Step (4): Based on the final local and global models obtained, perform fault diagnosis and operational status optimization of the deep-water blowout preventer control system.

2. The method according to claim 1, characterized in that, In step (1), the local models of each sub-element include: The local models corresponding to the power input unit, the underwater accumulator group, the logic control components, the pressure reducing valve, the directional valve, and the annular blowout preventer simulation unit model.

3. The method according to claim 2, characterized in that, Each local model digitally simulates the specific function of each component, including: The local model corresponding to the power input unit simulates the constant flow hydraulic power provided by the power input unit. The local model includes a step signal source and a flow source from left to right. The local model corresponding to the underwater accumulator group simulates the underwater accumulator group undertaking the functions of energy buffering and pressure compensation. The local model is built by constructing the accumulator in the hydraulic tank according to the system hydraulic level. The local model corresponding to the logic control component simulates the logic control component for maintaining the pressure mechanism. The local model includes a pressure relief valve, a piecewise linear signal source, and a two-position three-way solenoid valve to form a pressure maintenance mechanism. The local model corresponding to the pressure reducing valve includes a pressure regulating chamber, a damping piston, a valve core and valve seat assembly, a mass block of the valve moving parts, a balance chamber, a velocity reference, pipeline volume, flow rate and volume terminal, and an output throttling port. The local model corresponding to the reversing valve includes a spring action chamber, a valve core and valve seat assembly, a mass block of the valve moving parts, a hydraulic control chamber, a speed reference, a power hydraulic source, a hydraulic container, and a hydraulic control hydraulic source; The annular blowout preventer simulation unit includes a blowout preventer hydraulic cylinder, a back pressure check valve, a mass block for the blowout preventer moving parts, and a displacement sensor.

4. The method according to claim 3, characterized in that, In step (3), a number of local models are selected for simulation, including: pressure reducing valve constant pressure output simulation and directional valve reversing simulation; The simulation of the overall model includes the simulation of the overall execution actions of the deep-water blowout preventer control system.

5. The method according to claim 4, characterized in that, The simulation of the overall execution action of the deep-water blowout preventer control system is set in a second time period, which is related to the first time period of the simulation of each selected local model. The second time period covers at least one or more simulations of each local model.

6. The method according to claim 5, characterized in that, The pressure-reducing valve constant pressure output simulation specifically includes: providing a pressure source for plotting static characteristic curves by setting the working pressure of the hydraulic source to vary within the range of 56 MPa to 69 MPa; providing a hydraulic output curve for plotting dynamic characteristic curves by changing the control time; and judging the rationality of the model by using the hydraulic output curve.

7. The method according to claim 5, characterized in that, The reversing simulation of the reversing valve specifically includes: controlling high-pressure control oil to enter the valve chamber, controlling the oil to push the piston to slide, during the sliding process, the high-pressure working power fluid port will be connected with the return oil port and the working oil port until the control oil pushes the piston to the maximum displacement, and judging whether the piston completely blocks the return oil port by the displacement and pressure curve, so that the working oil port and the high-pressure working power fluid port are completely connected.

8. The method according to claim 5, characterized in that, The simulation of the overall execution of the deep-water blowout preventer (BOP) control system includes: the start of the BOP hydraulic control system, the start of movement of the SPM valve core, and the start of movement of the BOP piston only after the SPM valve is fully open and the pressure in the BOP hydraulic cylinder rises sufficiently to push the piston. The simulation tests the time taken for the annular BOP and the gate BOP to reach their maximum stroke, comparing them with the API standard requirements: the closing time of the underwater gate BOP is within 45 seconds and the closing time of the annular BOP is within 60 seconds, thus verifying the overall rationality of the model.

9. A computer storage medium, characterized in that, The device contains a computer program that is executed by a processor to implement the method of any one of claims 1 to 8.

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