An underwater electrically controlled hydraulic accumulator type valve controller and valve thereof

Abstract

The application discloses an underwater electrically-controlled liquid energy accumulator type valve controller and a valve thereof, and belongs to the technical field of valve control devices.The underwater electrically-controlled liquid energy accumulator type valve controller comprises a main valve, an energy converter, an arc-shaped energy accumulator, a power hub and an oil liquid balancer, and further comprises a pressure regulation system, wherein the pressure regulation system is provided with an environment state analysis module, a load state analysis module, a hydraulic medium state analysis module and a dynamic performance analysis module, which are used for respectively acquiring an environment state coefficient, a load state coefficient, a hydraulic medium state coefficient and a response-pressure drop adaptability; and a pressure optimization module is used for dynamically adjusting a target preset pressure of the energy accumulator.The underwater electrically-controlled liquid energy accumulator type valve controller can realize self-energy-supply opening and closing and dynamic pressure setting of the valve, effectively improves system response speed, reduces energy consumption, and enhances underwater environment adaptability and operation reliability.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of valves, and particularly relates to an underwater electrically-controlled liquid accumulator type valve controller and a valve thereof. BACKGROUND

[0002] An underwater valve control system is core equipment in the fields of oil and gas exploitation and underwater pipeline control, and its performance directly affects production safety and operation efficiency. Traditional underwater valves are mostly driven by hydraulic pressure, and a surface platform hydraulic power unit provides continuous power through a long umbilical cable, which has problems such as complex system, slow response, high energy consumption, and huge installation and maintenance costs.

[0003] At present, underwater hydraulic actuators in the prior art generally rely on external continuous power supply, have large power transmission loss, and cannot dynamically adjust system parameters according to actual working conditions. Although some integrated electro-hydraulic actuators reduce some pipelines, they still have problems such as extensive energy management, poor environmental adaptability, and medium state affecting response performance, and are difficult to meet the needs of deep water, long period, and high reliability operation. SUMMARY

[0004] In view of the deficiencies of the prior art, the application provides an underwater electrically-controlled liquid accumulator type valve controller and a valve thereof, which solve the above problems.

[0005] To achieve the above purpose, the application is implemented by the following technical scheme: an underwater electrically-controlled liquid accumulator type valve controller, comprising an energy converter installed on a main valve for driving the main valve to open and close:

[0006] An energy accumulator is provided with a plurality of arc-shaped energy storage devices evenly arranged on the main valve.

[0007] A power hub is installed on the main valve for supplying pressure to the hydraulic medium in the energy accumulator.

[0008] An oil balance device is installed on the main valve for storing hydraulic medium.

[0009] A pressure regulation system is used for dynamically regulating the pressure threshold in the energy accumulator, comprising:

[0010] An environmental state analysis module obtains an environmental state coefficient through an environmental state model based on the external pressure, external temperature and depth of the energy accumulator.

[0011] A load state analysis module obtains a load state coefficient through a load state model based on the valve opening frequency and the number of times of underpressure (the number of times that the pressure of the energy accumulator is lower than the pressure of the pressure compensation).

[0012] The hydraulic medium state analysis module obtains a hydraulic medium state coefficient based on viscosity, dust particle concentration and dust particle size of the hydraulic medium;

[0013] The dynamic performance analysis module obtains a response-pressure drop adaptation degree based on the valve response time length and the energy accumulator pressure drop speed under the environment state coefficient and the hydraulic medium state coefficient through a dynamic performance analysis model.

[0014] The pressure optimization module outputs a target preset pressure based on the load state coefficient, the response-pressure drop adaptation degree and the current preset pressure through a pressure optimization model.

[0015] On the basis of the above technical solutions, the application further provides the following optional technical solutions.

[0016] The working steps of the pressure optimization module are:

[0017] A comprehensive adjustment model is constructed based on the load state coefficient and the response-pressure drop adaptation degree to output a comprehensive adjustment factor, and the comprehensive adjustment model is represented as:

[0018] ;

[0019] Wherein, represents the comprehensive adjustment factor, represents the load state coefficient, represents the response-pressure drop adaptation degree.

[0020] A pressure optimization model is constructed based on the comprehensive adjustment factor and the current preset pressure to output a target preset pressure, and the pressure optimization model is represented as:

[0021] ;

[0022] Wherein, represents the target preset pressure, represents the current preset pressure, represents a pressure adjustment maximum amplitude, represents an adjustment sensitivity coefficient, represents the comprehensive adjustment factor, represents an adjustment factor threshold value.

[0023] The working steps of the dynamic performance analysis module are:

[0024] The response time length is subjected to absolute difference processing with the optimal response time length and then subjected to ratio processing with the allowed deviation from the optimal response time length to obtain a response time length index.

[0025] An absolute difference between the energy accumulator pressure drop speed and the optimal pressure drop speed is processed, and a ratio between the absolute difference and an allowable deviation from the optimal pressure drop speed is processed to obtain a pressure drop speed index;

[0026] A dynamic performance analysis model is constructed based on the response time index and the pressure drop speed index under the environment state coefficient and the hydraulic medium state coefficient to output a response-pressure drop fitness, and the dynamic performance analysis model is represented as:

[0027] ;

[0028] wherein, represents the response-pressure drop fitness, represents the response time index, represents the pressure drop speed index, represents the environment state coefficient, represents the hydraulic medium state coefficient, represents a weight coefficient, and The greater the value is, the better the system fitness is.

[0029] A further technical solution is that the working steps of the load state analysis module are:

[0030] A ratio between the valve opening frequency and the under-pressure frequency (the number of times that the energy accumulator pressure is lower than the pressure compensation pressure) and a corresponding initial threshold value (not zero) is processed to obtain a frequency index and an under-pressure frequency index;

[0031] A load state model is constructed based on the frequency index and the under-pressure frequency index to output a load state coefficient, and the load state model is represented as:

[0032] ;

[0033] wherein, represents the load state coefficient, represents the frequency index, represents the under-pressure frequency index, represents a valve opening frequency sensitivity, represents an under-pressure frequency sensitivity, and The greater the value is, the greater the energy accumulator load is.

[0034] A further technical solution is that the working steps of the environment state analysis module are:

[0035] Maximum-minimum normalization processing is performed on the external pressure, the external temperature, and the depth to obtain a pressure index, a temperature index, and a depth index;

[0036] ​An environmental state model is constructed based on the pressure index, the temperature index and the depth index to output an environmental state coefficient, and the environmental state model is represented as:

[0037]

[0038] wherein, represents the environmental state coefficient, represents the pressure index, represents the depth index, represents the temperature index, represents the weight coefficient, and the greater the value, the better the environmental state.

[0039] A further technical solution is that the working steps of the hydraulic medium state analysis module are:

[0040] The viscosity, the dust particle concentration and the dust particle size (the maximum particle size) are subjected to difference processing and then ratio processing with the corresponding allowable deviation reference values to obtain a viscosity deviation index, a dust particle concentration deviation index and a dust particle size deviation index.

[0041] A hydraulic medium state model is constructed based on the viscosity deviation index, the dust particle concentration deviation index and the dust particle size deviation index to output a hydraulic medium state coefficient, and the hydraulic medium state model is represented as:

[0042]

[0043] wherein, represents the hydraulic medium state coefficient, represents the viscosity deviation index, represents the dust particle concentration deviation index, represents the dust particle size deviation index, represents the weight coefficient, and the greater the value, the better the hydraulic medium state. A further technical solution is that the energy converter comprises a cylinder body, a piston D and cavities A, B and C formed in the cylinder body, the cavity A is connected with an output end of an energy accumulator through an oil path a, the cavity B is connected with an oil inlet of a main valve through an oil path c, the cavity C is connected with an oil port of an oil equalizer through an oil path d, the cavity C is connected with an oil inlet of the energy accumulator through the oil path d, and the cavity A is connected with the oil port of the oil equalizer through an oil path b.

[0044] An underwater electrically-controlled liquid accumulator type valve is controlled by the underwater electrically-controlled liquid accumulator type valve controller.

[0045] ​​​​

[0046] The application provides an underwater electrically-controlled liquid energy accumulator type valve controller and a valve thereof, and has the following beneficial effects compared with the prior art:

[0047] 1. The application realizes self-energy supply of valve driving, saves the traditional on-water hydraulic power unit and long distance umbilical cable by integrating an energy accumulator and a power hub, significantly reduces equipment procurement, installation and operation and maintenance costs, and avoids energy loss of long distance hydraulic transmission;

[0048] 2. The application can automatically optimize the preset pressure threshold of the energy accumulator according to the underwater environment state, valve operation load, hydraulic medium performance and system dynamic response characteristics through a multi-parameter fusion pressure regulation system, effectively reduces system energy consumption while ensuring valve response speed;

[0049] 3. The application enhances the adaptability of the system to complex underwater environments, senses the changes of external pressure, temperature and depth in real time through an environment state analysis module, and adjusts system parameters accordingly, so that the valve controller can maintain stable performance under different water depths and temperature conditions;

[0050] 4. The application monitors the valve opening frequency and underpressure events through a load state analysis module, evaluates the response adaptation degree in combination with a dynamic performance analysis module, can customize the optimal pressure strategy for each valve, avoids mutual interference between multiple valves, and improves overall control accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 It is a three-dimensional structural schematic diagram of the application.

[0052] Figure 2 It is a structural schematic diagram of the whole application.

[0053] Figure 3 It is a structural schematic diagram of the energy converter of the application.

[0054] Figure 4 It is a distribution schematic diagram of the energy accumulator of the application.

[0055] Figure 5 It is a flow schematic diagram of the pressure regulation system in the application.

[0056] Legend: 1, main valve; 2, shell; 3, energy converter; 301, cylinder body; 302, cavity A; 303, cavity B; 304, cavity C; 305, piston D; 306, oil line a; 307, oil line b; 308, oil line c; 309, oil line d; 4, power hub; 5, oil balance; 6, energy accumulator. DETAILED DESCRIPTION

[0057] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.

[0058] The specific implementation of the present application is described in detail below in combination with specific embodiments.

[0059] Please refer to Figures 1 to 4 According to an embodiment of the present application, an underwater electrically-controlled liquid accumulator energy storage valve controller comprises an energy converter 3 (a booster cylinder) installed on a main valve 1 (a flat plate main valve) for driving the main valve 1 to open, and further comprises:

[0060] An energy accumulator 6 (a piston accumulator) is arranged on the main valve 1 and is used for energy storage.

[0061] A power hub 4 is installed on the main valve 1 and is used for supplying pressure to the hydraulic medium in the energy accumulator 6.

[0062] An oil balancer 5 (a bladder accumulator) is installed on the main valve 1 and is used for storing the hydraulic medium.

[0063] Preferably, the power hub 4 is a pressure supply device of an integrated power pump group, comprising an electric control unit (a motor drive control board, an electric control main board, integrated circuits and other components), a power pump group (composed of three sets of micro motor pumps) and a pressure sensor (two pressure sensors), the power pump group and the pressure sensor are electrically connected with the electric control unit, the power hub 4 is connected with the energy accumulator 6 and is used for pressurizing the oil in the energy accumulator 6.

[0064] Preferably, the main valve 1 is sleeved with a shell 2 for protecting the devices installed outside the main valve 1.

[0065] Preferably, the energy converter 3 comprises a cylinder body 301, a piston D 305 and cavities A 302, B 303 and C 304 opened on the cylinder body 301, the cavity A 302 is connected with the output end of the energy accumulator 6 through an oil path a 306, the cavity B 303 is connected with the oil inlet of the main valve 1 through an oil path c 308, the cavity C 304 is connected with the oil inlet of the energy accumulator 6 through an oil path d 309, the cavity C 304 is connected with the oil inlet of the oil balancer 5 through an oil path d 309, and the cavity A 302 is connected with the oil inlet of the oil balancer 5 through an oil path b 307.

[0066] In the embodiment of the present application, when the pressure sensor of the energy accumulator 6 sends a pressure deficiency signal to the electric control mainboard, the electric control mainboard sends a power hub 4 (power pump group) starting command to supply pressure for the energy accumulator 6, and when the pressure of the energy accumulator 6 reaches the pressure threshold, the electric control mainboard sends a power hub 4 (power pump group) stopping command. When the main control board of the system receives an opening main valve 1 command transmitted by the upper computer, the oil in the energy accumulator 6 enters the cavity A 302 through the oil path a 306 (the oil path b 307 is closed), pushes the piston D 305 to move to the cavity B 303, the oil in the cavity B 303 enters the main valve 1 through the oil path c 308 to start the main valve 1, and the oil in the cavity C 304 enters the oil equalizer 5 through the oil path d 309. When the main valve 1 is to be closed, the oil in the main valve 1 enters the cavity B 303 through the oil path c 308 (the oil path a 306 is closed, and the oil path b 307 is opened), the oil in the energy accumulator 6 enters the cavity C 304 through the oil path d 309, and the piston D 305 moves to the cavity A 302 (speeds up the closing speed of the main valve 1). At this time, the oil in the cavity A 302 enters the oil equalizer 5 through the oil path b 307, the oil in the main valve 1 completely enters the cavity B 303, and the closing of the main valve 1 is completed.

[0067] Preferably, the oil path a 306, the oil path b 307, the oil path c 308 and the oil path d 309 are provided with valve pieces, and the valve pieces are electrically connected with the main control board of the system. The purpose of this kind of arrangement is to control the oil entering the execution end through the valve piece.

[0068] Preferably, the cross-sectional area ratio of the cavity A 302 to the cavity B 303 is 3:2. The purpose of this kind of arrangement is to make the output pressure 1.5 times of the input pressure.

[0069] Please refer to Figure 5 As an embodiment of the present application, it further includes a pressure regulation system for dynamically regulating the pressure threshold in the energy accumulator 6, comprising:

[0070] An environmental state analysis module obtains an environmental state coefficient through an environmental state model based on the external pressure, the external temperature and the depth of the energy accumulator 6;

[0071] A load state analysis module obtains a load state coefficient through a load state model based on the valve opening frequency and the under-pressure frequency (the number of times that the pressure of the energy accumulator 6 is lower than the pressure compensation pressure);

[0072] A hydraulic medium state analysis module obtains a hydraulic medium state coefficient based on the viscosity, the dust particle concentration and the dust particle size of the hydraulic medium;

[0073] The dynamic performance analysis module obtains a response-pressure drop adaptation degree through a dynamic performance analysis model based on valve response time length, energy accumulator 6 pressure drop speed under the environment state coefficient and the hydraulic medium state coefficient;

[0074] The pressure optimization module outputs a target preset pressure through a pressure optimization model based on the load state coefficient, the response-pressure drop adaptation degree and the current preset pressure.

[0075] Through the above technical solutions, the energy accumulator 6 pressure threshold of the valve controller can be automatically optimized, effectively adapting to changes in different water depths, temperatures and medium states, and the energy accumulator 6 pressure threshold can be automatically optimized according to the actual load intensity, ensuring response speed while reducing energy loss. By monitoring the hydraulic medium performance attenuation degree in real time, the system maintenance cycle is significantly prolonged and the operation reliability is improved.

[0076] Preferably, the working steps of the environment state analysis module are:

[0077] The maximum-minimum normalization processing is performed on the external pressure, the external temperature and the depth, and a pressure index, a temperature index and a depth index are obtained;

[0078] An environment state model is constructed based on the pressure index, the temperature index and the depth index to output an environment state coefficient, and the environment state model is represented as:

[0079] ;

[0080] wherein, represents the environment state coefficient, represents the pressure index, represents the depth index, represents the temperature index, represents a weight coefficient and , the and the greater the value, the better the environment state.

[0081] The pressure index refers to a normalized external pressure quantitative value, which can be calculated by using real-time data collected by a pressure sensor and a preset pressure extreme value, and is used to represent the influence degree of the current pressure on the system. The depth index refers to a normalized underwater depth quantitative value, which can be calculated by using a depth sensor measurement value and a preset working depth range, and is used to reflect the compression effect of depth change on the hydraulic medium. The temperature index refers to a normalized external temperature quantitative value, which can be calculated by using temperature sensor data and a preset temperature threshold, and is used to evaluate the influence of temperature on the performance of the sealing element. The weight coefficient refers to an adjustment factor assigned to each environmental parameter, which can be determined by expert experience or historical data training, and is used to dynamically adjust the evaluation priority of the pressure, depth and temperature parameters according to the application scenario.

[0082] Compared with the prior art, the traditional environmental evaluation method usually only uses a single pressure parameter or a fixed weight combination for judgment, and cannot accurately reflect the coupling effect of multiple factors. For example, the prior art can directly use a pressure threshold to trigger an alarm, but ignores the medium compression effect caused by depth change. The present scheme establishes the comparability of multiple parameters through normalization processing, and uses a dynamic weight distribution mechanism to adjust the evaluation model according to the actual working conditions, for example, automatically reducing the pressure weight and increasing the temperature weight in the shallow water high temperature area, so as to more accurately quantify the influence of the environmental state on the system.

[0083] Through the above technical scheme, the present application realizes comprehensive quantitative evaluation of underwater environmental parameters, and solves the evaluation deviation problem caused by the dimensional difference of parameters in the traditional method. Through the reverse correction mechanism of the pressure index and the depth index, the negative influence of high pressure and deep water environment on the hydraulic system is accurately reflected; through the positive correction mechanism of the temperature index, the improvement effect of temperature change on the fluidity of the medium is effectively captured. The dynamic configuration function of the weight coefficient enables the system to adapt to the working condition changes in different sea areas and different operation stages, for example, automatically increasing the temperature weight to optimize the sealing performance evaluation in the polar low temperature sea area, thereby improving the calculation accuracy of the environmental state coefficient and providing reliable input parameters for dynamic regulation of the pressure threshold.

[0084] Preferably, the working steps of the load state analysis module are:

[0085] The valve opening frequency and the under-pressure frequency (the number of times that the energy accumulator 6 pressure is lower than the pressure compensation pressure) are subjected to ratio processing with the corresponding initial threshold value (not zero) to obtain a frequency index and an under-pressure frequency index;

[0086] A load state model is constructed based on the frequency index and the under-pressure frequency index to output a load state coefficient, and the load state model is represented as:

[0087] ;

[0088] wherein, represents the load status coefficient, represents the frequency index, represents the under-pressure frequency index, represents the valve opening frequency sensitivity, represents the under-pressure frequency sensitivity, and the and the greater the value, the greater the load of the energy accumulator 6.

[0089] wherein the valve opening frequency refers to the number of times the valve is driven per unit time, which can be realized by counting the number of triggers in a statistical time window, and is used to reflect the periodic opening load of the energy accumulator 6. The under-pressure frequency refers to the cumulative number of events in which the pressure of the energy accumulator 6 is lower than the threshold pressure of the pressure compensation, which can be realized by monitoring the pressure of the energy accumulator 6 with a pressure sensor and recording the number of times the pressure is lower than the threshold value, and is used to represent the risk of insufficient pressure of the energy accumulator 6 due to frequent energy supply. The initial threshold value refers to a pre-set reference value, for example, the initial threshold value of the valve opening frequency can be 10 times per hour, and the initial threshold value of the under-pressure frequency can be 5 times per day. By ratio processing the actual value and the initial threshold value, the dimensional difference is eliminated and the deviation degree of the working condition is quantified. The frequency index and the under-pressure frequency index are calculated by the ratio of the actual value to the initial threshold value, for example, when the valve opening frequency is 20 times per hour, the frequency index is 20 / 10=2, which is used to reflect the multiple relationship of the actual load relative to the reference. The load status model adopts an exponential function form, and the sensitivity coefficients and , for example 0.5, 0.8, non-linearly map the frequency index and the under-pressure frequency index to the interval of 0 to 1, so that the load status coefficient dynamically changes with the actual working condition.

[0090] Specifically, the load status analysis module acquires the valve opening frequency and the under-pressure frequency data in real time, and performs ratio calculation with the pre-set initial threshold value respectively to generate the frequency index and the under-pressure frequency index. For example, when the valve opening frequency reaches 2 times the initial threshold value, the frequency index is 2; when the under-pressure frequency reaches 3 times the initial threshold value, the under-pressure frequency index is 3. Subsequently, the two indexes are input into the load status model to calculate the load status coefficient by the exponential function . Among them, the sensitivity coefficients and are used to adjust the contribution weight of different indexes to the load status, for example, when is greater than ,At this time, the system pays more attention to the influence of high frequency opening on the load. As the load state coefficient tends to 1, it indicates that the energy storage 6 is in a high load state, and the preset pressure threshold needs to be adjusted to reduce the risk of underpressure; on the contrary, when the coefficient tends to 0, it indicates that the load is low, and the current pressure setting can be maintained.

[0091] Compared with the prior art, the traditional method usually only judges the energy storage state according to a fixed threshold, and cannot quantitatively evaluate the dynamic load change. For example, the prior art may trigger pressure compensation only when the underpressure times exceed a fixed value, but does not consider the associated influence of valve opening frequency and underpressure times. The scheme constructs a load state model, normalizes the two types of working condition data into exponential form, and dynamically integrates the influence of multiple factors by using an exponential decay function, so that the load evaluation is more in line with the actual working condition.

[0092] Through the above technical scheme, the application can dynamically evaluate the cumulative load state of the energy storage 6 according to the actual use frequency of the valve and the pressure abnormal event of the energy storage 6, and provide real-time and quantitative adjustment basis for the pressure regulation system. For example, in deep sea operation, when the underpressure times increase rapidly due to frequent opening and closing of the valve, the load state coefficient rises rapidly, triggering the pressure optimization module to increase the preset pressure threshold, thereby avoiding the delay of valve response caused by insufficient energy supply of the energy storage 6. At the same time, through the flexible configuration of the sensitivity coefficient, the differentiated needs of different underwater scenes for valve opening frequency and pressure stability can be adapted, and the system reliability can be improved.

[0093] Preferably, the working steps of the hydraulic medium state analysis module are:

[0094] After the viscosity, dust particle concentration and dust particle size (maximum particle size) are processed by difference with the corresponding reference value, and the viscosity deviation index, dust particle concentration deviation index and dust particle size deviation index are obtained by processing the ratio of the corresponding allowed deviation reference value;

[0095] Based on the viscosity deviation index, dust particle concentration deviation index and dust particle size deviation index, a hydraulic medium state model is constructed to output a hydraulic medium state coefficient, and the hydraulic medium state model is represented as:

[0096] ;

[0097] Wherein, represents the hydraulic medium state coefficient, represents the viscosity deviation index, represents the dust particle concentration deviation index, represents the dust particle size deviation index, represents the weight coefficient and , the and the greater the value, the better the hydraulic medium state.

[0098] The viscosity deviation index refers to the difference between the actual viscosity of the hydraulic medium and the reference viscosity relative to the ratio of the allowed deviation from the reference value. Specifically, real-time viscosity data can be collected by a viscosity sensor, compared with the preset reference value, and the standardized deviation degree can be calculated to realize the viscosity deviation index, which is used to represent the deterioration degree of the medium flowability. The dust particle concentration deviation index refers to the difference between the particle pollutant concentration in the hydraulic oil and the reference concentration relative to the ratio of the allowed deviation from the reference concentration. Specifically, the particle concentration can be monitored online by a particle counter or a visual detection system, and the pollution degree quantitative index can be converted by normalization processing, which is used to reflect the decreasing trend of the medium cleanliness. The dust particle size deviation index refers to the difference between the maximum particle size in the hydraulic medium and the reference particle size relative to the ratio of the allowed deviation from the reference particle size. Specifically, the maximum particle size can be measured by a laser particle size analyzer, and the size exceeding the standard ratio can be calculated to realize the dust particle size deviation index, which is used to evaluate the potential risk of hard particles in the medium to the valve wear. The weight coefficient is used to adjust the influence weight of different deviation indexes on the hydraulic medium state. Specifically, the weight coefficient can be determined by expert experience method or machine learning algorithm according to historical data to realize the multi-parameter collaborative evaluation.

[0099] Specifically, the hydraulic medium state analysis module first standardizes the viscosity, particle concentration and particle size to eliminate the dimensional difference and quantify the deterioration degree of each parameter. For example, when the viscosity of the hydraulic oil increases due to temperature change, the viscosity deviation index will increase. When external pollutants invade the system due to seal failure, the particle concentration and particle size deviation indexes will simultaneously increase. Then, the multi-dimensional pollution state is integrated into a single comprehensive index by weighted summation, and the linear superposition deviation is converted into a nonlinear decay hydraulic medium state coefficient by using an exponential function. The coefficient can sensitively capture the critical mutation of the medium performance. For example, when the particle concentration exceeds the threshold value, the coefficient value will sharply decrease. The coefficient as an input parameter of the pressure optimization model can trigger the dynamic compensation adjustment of the preset pressure threshold, for example, automatically increasing the pressure compensation pressure when the medium viscosity abnormally increases to offset the influence of the increased flow resistance, thereby maintaining the valve response speed.

[0100] Compared with the prior art, the traditional hydraulic system usually only sets a fixed threshold to trigger filter replacement or medium replacement, and cannot quantitatively evaluate the dynamic influence of the medium state on the system performance in real time. The present scheme realizes continuous monitoring and nonlinear mapping of the medium deterioration degree by multi-parameter fusion modeling, so that the pressure regulation system can perceive the performance degradation trend of the medium in advance and take preventive adjustment to avoid valve jamming or response delay caused by medium pollution or viscosity mutation.

[0101] By the technical solution, the viscosity change and the particle pollution degree of the hydraulic medium can be perceived in real time, and the preset pressure threshold of the energy accumulator 6 is dynamically adjusted to compensate for the negative influence of the medium degradation on the valve response speed. For example, when the dust particle concentration exceeds the standard, the system automatically increases the pressure compensation pressure to enhance the driving capacity, so as to offset the additional resistance caused by particle friction; when the viscosity of the hydraulic oil is too high, the medium flowability is improved by optimizing the pressure gradient, and finally the response performance and operation reliability of the valve controller are maintained.

[0102] Preferably, the steps of the dynamic performance analysis module are:

[0103] After the absolute difference value of the valve response time and the optimal response time is processed, the ratio of the allowed deviation of the optimal response time is processed to obtain a response time index;

[0104] After the absolute difference value of the pressure drop speed of the energy accumulator 6 and the optimal pressure drop speed is processed, the ratio of the allowed deviation of the optimal pressure drop speed is processed to obtain a pressure drop speed index;

[0105] Based on the response time index and the pressure drop speed index under the environmental state coefficient and the hydraulic medium state coefficient, a dynamic performance analysis model is constructed to output a response-pressure drop adaptation degree, and the dynamic performance analysis model is represented as:

[0106] ;

[0107] Wherein, represents the response-pressure drop adaptation degree, represents the response time index, represents the pressure drop speed index, represents the environmental state coefficient, represents the hydraulic medium state coefficient, represents the weight coefficient, and , the and the greater the value is, the better the system adaptation degree is.

[0108] Wherein, the response time index is used to quantify the influence of the valve action delay on the system performance, and a timer can be used to measure the valve opening time. The pressure drop speed index is used to evaluate the energy supply efficiency of the energy accumulator 6, and a pressure sensor can be used to monitor the pressure of the energy accumulator 6 in real time and cooperate with a timer to calculate the pressure drop speed. The environmental state coefficient is an environmental influence factor calculated by the external pressure, temperature and depth, and is used to reflect the constraint of the underwater environment on the system performance. The hydraulic medium state coefficient is used to characterize the influence of the hydraulic oil state on the energy transmission efficiency.

[0109] Specifically, the response duration index and the pressure drop speed index in the model are squared and weighted summed, and then squared to form a comprehensive deviation index, and then multiplied by the environmental and medium state coefficient, and finally a response-pressure drop fitness between 0 and 1 is generated. The larger the fitness value is, the higher the matching degree of the current system parameters and the environment and medium conditions is. By adjusting the weight coefficient, the contribution proportion of the response duration and the pressure drop speed in the fitness calculation can be flexibly configured. For example, when the system pays more attention to the response speed, the weight coefficient of the response duration index can be increased.

[0110] Compared with the prior art, the traditional underwater valve control system only monitors a single performance parameter, does not establish a quantitative evaluation model, and cannot dynamically reflect the combined influence of the environment and medium state on the system performance. In the prior art, the pressure drop speed control adopts a fixed threshold, which is easy to cause the valve opening speed and the energy storage device 6 energy supply rate to be mismatched when the hydraulic oil viscosity changes or the external pressure fluctuates. The present scheme converts the non-mechanical factors such as environmental pressure and medium pollution into quantifiable coefficients by constructing a dynamic performance analysis model coupled with multiple parameters, so that the pressure regulation system can real-time perceive and compensate the influence of these factors on the dynamic performance of the system.

[0111] Through the above technical scheme, the present application solves the problem of unstable response of the traditional system caused by changes in the environment and medium state, and realizes dynamic matching of the pressure drop speed and the valve opening demand. When the viscosity of the hydraulic oil increases due to temperature reduction, the hydraulic medium state coefficient is automatically reduced to prompt the system to increase the pressure threshold to compensate for the loss of energy transmission efficiency; when the external water pressure suddenly increases to cause the valve opening resistance to increase, the environmental state coefficient decreases to drive the pressure optimization module to adjust the pressure threshold of the energy storage device 6, so as to ensure that the response duration is maintained within the allowable range. This dynamic adaptation mechanism enables the system to maintain stable opening performance in complex underwater environments, avoiding the risk of valve action delay or energy storage device overpressure caused by medium degradation or environmental mutation.

[0112] Preferably, the working steps of the pressure optimization module are:

[0113] An integrated adjustment model is constructed based on the load state coefficient and the response-pressure drop fitness to output an integrated adjustment factor, and the integrated adjustment model is represented as:

[0114] ;

[0115] Wherein, represents the integrated adjustment factor, represents the load state coefficient, represents the response-pressure drop fitness;

[0116] A pressure optimization model is constructed based on the integrated adjustment factor and the current preset pressure to output a target preset pressure, and the pressure optimization model is represented as:

[0117] ;

[0118] wherein, represents the target preset pressure, represents the current preset pressure, represents the pressure adjustment maximum amplitude, represents the adjustment sensitivity coefficient, represents the comprehensive adjustment factor, represents the adjustment factor threshold.

[0119] wherein, the comprehensive adjustment factor refers to an adjustment parameter calculated by the load state coefficient and the response-pressure drop fitness, which can be realized in a linear weighting manner, for example, the average value of the load state coefficient and the dynamic performance inverse compensation term is taken as the comprehensive adjustment factor, which is used to balance the influence of long-term load and real-time performance. The pressure adjustment maximum amplitude refers to the limit range of pressure adjustment, which can be realized in a preset fixed value or a dynamic setting based on system safety threshold, which is used to limit the amplitude of pressure fluctuation. The adjustment sensitivity coefficient refers to the parameter for controlling the rate of pressure adjustment, which can be determined by experience calibration, experimental calibration or adaptive algorithm. The adjustment factor threshold refers to the critical point for triggering pressure adjustment, which can be determined by experience value or based on system stability analysis, which is used to judge whether to start pressure optimization.

[0120] Specifically, the comprehensive adjustment model associates long-term running load with real-time dynamic performance by weighting calculation of the load state coefficient and the response-pressure drop fitness. For example, when the load state coefficient increases (load increases) or the response-pressure drop fitness decreases (dynamic performance deteriorates), the comprehensive adjustment factor increases, triggering the pressure optimization model to adjust the pressure. The pressure optimization model adopts a hyperbolic tangent function, which restricts the adjustment amplitude through a nonlinear function when the comprehensive adjustment factor deviates from the adjustment factor threshold. For example, when the comprehensive adjustment factor exceeds the adjustment factor threshold, the pressure adjustment amplitude rapidly rises with the increase of the deviation, but is limited by the saturation characteristics of the hyperbolic tangent function to avoid overshoot risk. The adjustment sensitivity coefficient can further control the adjustment rate, for example, a smaller sensitivity coefficient is used in deep-sea high-pressure environment to avoid frequent adjustment, while a larger coefficient is used in shallow water working condition to improve response speed.

[0121] Compared with the prior art, the traditional scheme usually adopts a fixed pressure threshold or a linear adjustment based on a single parameter, which cannot coordinate the load state and dynamic performance. For example, the prior art may only adjust the pressure according to the valve opening frequency, resulting in maintaining a high pressure setting when the hydraulic medium state deteriorates, which aggravates energy loss. The present scheme couples multi-dimensional parameters through the comprehensive adjustment factor, and realizes adaptive constraint of pressure adjustment amplitude by using a nonlinear function, which not only avoids the rigidity problem of fixed threshold, but also overcomes the overshoot defect of linear adjustment.

[0122] Through the technical solution, the application can optimize the pressure threshold in real time according to the load state and dynamic performance, and solve the response lag problem caused by the fixed pressure of the traditional controller. For example, when the dust concentration of the hydraulic medium increases, the response-pressure drop adaptation degree decreases to trigger the pressure threshold to be adjusted upward, compensating for the pressure drop caused by the medium pollution to accelerate the valve response speed; and in the low load working condition, the pressure threshold is reduced to reduce energy loss. At the same time, the introduction of the hyperbolic tangent function avoids the influence of pressure mutation on the stability of the system, such as suppressing the pressure fluctuation amplitude in the deep sea high pressure environment, and preventing the sealing structure from being overloaded.

[0123] An underwater electric control liquid accumulator type valve adopts the underwater electric control liquid accumulator type valve controller.

[0124] It should be noted that, in this document, the terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply these entities or operations have any such actual relationship or order. Also, the terms "comprises", "comprising", or any other variations thereof are intended to cover non-exclusive inclusions, so that a process, method, article, or apparatus including a series of elements includes not only those elements, but also other elements not explicitly listed, or inherent to such a process, method, article, or apparatus.

[0125] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made thereto without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. An underwater electro-hydraulic accumulator type valve controller, comprising a power hub and an oil balancer mounted on the main valve, characterized in that, Also includes: An energy converter, installed on the main valve, is used to drive the main valve to open and close. The energy storage device has several arc-shaped components evenly arranged on the main valve for energy storage. A pressure regulation system is used to dynamically regulate the pressure threshold within the energy storage device, including: The environmental state analysis module obtains environmental state coefficients based on the external pressure, external temperature, and depth of the energy storage device through an environmental state model. The load state analysis module obtains load state coefficients based on valve opening frequency and undervoltage occurrences through a load state model. The hydraulic medium state analysis module obtains the hydraulic medium state coefficient based on the viscosity, dust particle concentration, and dust particle size of the hydraulic medium. The dynamic performance analysis module, based on the valve response time and energy storage pressure drop rate under environmental state coefficients and hydraulic medium state coefficients, obtains the response-pressure drop fit through a dynamic performance analysis model. The pressure optimization module outputs the target preset pressure based on the load state coefficient, response-pressure drop fit, and the current preset pressure through the pressure optimization model.

2. The underwater electro-hydraulic accumulator valve controller according to claim 1, characterized in that, The working steps of the pressure optimization module are as follows: A comprehensive adjustment model is constructed based on the load state coefficient and the response-voltage drop fit, and the comprehensive adjustment factor is output. The comprehensive adjustment model is expressed as follows: ； in, Indicates the overall adjustment factor. Represents the load state factor. Indicates the response-voltage drop fit; Based on a comprehensive adjustment factor and the current preset pressure, a pressure optimization model is constructed to output the target preset pressure. The pressure optimization model is expressed as follows: ； in, This indicates the target has pre-set pressure. Indicates the current preset pressure. This indicates the maximum pressure adjustment range. This indicates the adjustment sensitivity coefficient. Indicates the overall adjustment factor. This indicates the threshold for the adjustment factor.

3. The underwater electro-hydraulic accumulator valve controller according to claim 2, characterized in that, The steps of the dynamic performance analysis module are as follows: The absolute difference between the valve response time and the optimal response time is processed and then compared with the allowable deviation from the optimal response time to obtain the response time index. The voltage drop rate index is obtained by taking the absolute difference between the energy storage device's voltage drop rate and the optimal voltage drop rate, and then comparing it with the allowable deviation from the optimal voltage drop rate. A dynamic performance analysis model is constructed based on the response time exponent and pressure drop rate exponent under environmental state coefficients and hydraulic medium state coefficients, and outputs the response-pressure drop fit. The dynamic performance analysis model is expressed as follows: ； in, Indicates the response-voltage drop fit. This represents the response time index. Indicates the pressure drop rate index. Represents the environmental state coefficient. Represents the state coefficient of the hydraulic medium. Represents the weight coefficient and The The larger the value, the better the system compatibility.

4. The underwater electro-hydraulic accumulator valve controller according to claim 3, characterized in that, The working steps of the load status analysis module are as follows: The frequency index and the number of undervoltage events are obtained by comparing the valve opening frequency and the number of undervoltage events with the corresponding initial thresholds. A load state model is constructed based on the frequency index and the undervoltage occurrence index to output load state coefficients. The load state model is expressed as follows: ； in, Represents the load state factor. Indicates frequency index. This indicates the number of times the voltage is undercharged. Indicates the sensitivity of valve opening frequency. The sensitivity to undervoltage counts, the The larger the value, the greater the load on the energy storage device.

5. The underwater electro-hydraulic accumulator valve controller according to claim 3, characterized in that, The working steps of the environmental status analysis module are as follows: The external pressure, external temperature, and depth are subjected to maximum-min normalization to obtain the pressure index, temperature index, and depth index. An environmental state model is constructed based on the pressure index, temperature index, and depth index, and the environmental state coefficients are output. The environmental state model is expressed as follows: ； in, Represents the environmental state coefficient. Indicates the stress index. Indicates depth index, Indicates the temperature index. Represents the weight coefficient and The The higher the value, the better the environmental condition.

6. The underwater electro-hydraulic accumulator valve controller according to claim 3, characterized in that, The working steps of the hydraulic medium state analysis module are as follows: The viscosity, dust particle concentration, and dust particle size are compared with the corresponding benchmark values ​​by performing difference processing on the values, and then the ratios are processed with the corresponding allowable deviation benchmark values ​​to obtain the viscosity deviation index, dust particle concentration deviation index, and dust particle size deviation index. Based on the viscosity deviation index, dust particle concentration deviation index, and dust particle size deviation index, a hydraulic medium state model is constructed to output hydraulic medium state coefficients. The hydraulic medium state model is expressed as follows: ； in, Represents the state coefficient of the hydraulic medium. This indicates the viscosity deviation index. This indicates that the concentration of dust particles deviates from the index. This indicates the deviation index of dust particle size. Represents the weight coefficient and The The larger the value, the better the condition of the hydraulic medium.

7. The underwater electro-hydraulic accumulator valve controller according to claim 1, characterized in that, The energy converter includes a cylinder, a piston D, and cavities A, B, and C formed on the cylinder. Cavity A is connected to the output end of the energy storage device via oil passage a. Cavity B is connected to the main valve inlet via oil passage c. Cavity C is connected to the oil port of the oil balancer via oil passage d. Cavity C is also connected to the inlet of the energy storage device via oil passage d. Cavity A is connected to the oil port of the oil balancer via oil passage b.

8. An underwater electro-hydraulic accumulator valve, characterized in that, The underwater electro-hydraulic energy storage valve controller according to any one of claims 1-7 is adopted.

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