A compensating hydraulic hose control method and system adapted to sudden pressure changes in deep sea.

Abstract

This application relates to the field of deep-sea hydraulic pipeline technology, specifically a compensating hydraulic hose control method and system adapted to sudden pressure changes in the deep sea. The method includes: acquiring seawater pressure data and hydraulic oil pressure data; generating an internal and external pressure difference sequence based on the seawater pressure data and hydraulic oil pressure data; solving the global stress gradient of the hydraulic hose and extracting stress abrupt change regions, and statistically analyzing the spatial distribution density of the stress abrupt change regions; locating stress abrupt change concentration sections based on the spatial distribution density; retrieving pre-stored microscopic material parameters of the rubber matrix in the stress abrupt change concentration sections; calculating the rubber fatigue cumulative damage index of the stress abrupt change concentration sections; quantifying the effective cross-sectional area of ​​the leakage channels inside the hydraulic hose based on the rubber fatigue cumulative damage index; and determining the compensation pressure parameters used for pressure compensation control based on the effective cross-sectional area of ​​the leakage channels. This application can adapt to extreme alternating deep-sea conditions, improving the adaptability and accuracy of detection and evaluation under complex deep-sea conditions.

Description

Technical Field

[0001] The present application belongs to the technical field of deep-sea hydraulic pipelines, and specifically relates to a compensated hydraulic rubber hose control method and system adapted to sudden deep-sea pressure changes. Background Art

[0002] Deep-sea exploration and underwater operation equipment are generally equipped with high-pressure large-flow hydraulic components and hydraulic delivery pipelines matched with hydraulic systems. As the core pressure-bearing sealing component of the system, hydraulic rubber hoses are in the extreme alternating working condition of deep-sea high pressure and frequent sudden changes of internal and external pressure difference for a long time. Continuous alternating loading easily causes fatigue microcracks in the rubber matrix and gradually expands to form leakage channels. Seawater intrusion into the pipeline can easily cause hydraulic system leakage, pressure instability and even overall failure. Therefore, accurate detection and status assessment of the pressure-bearing status and fatigue damage of deep-sea hydraulic rubber hoses, and then adaptive regulation of the working pressure of the hoses are of great significance for ensuring the safe and stable operation of deep-sea hydraulic systems. Existing deep-sea hydraulic rubber hose detection technologies mainly rely on external pressure monitoring, macro stress analysis and off-line performance tests to complete pipeline status assessment. The working status of the hose is determined by collecting the internal and external pressure fluctuation data of the pipeline and extracting the macro stress distribution characteristics, and the overall durability of the hose is evaluated in combination with conventional mechanical test methods, so as to realize abnormal pipeline status screening and fault identification, and provide a basic reference for pipeline inspection and maintenance. However, such pipeline detection and assessment methods have low detection accuracy and insufficient adaptability to complex working conditions. Under the alternating environment of sudden deep-sea pressure changes, it cannot conform to the real-time damage evolution law of the hose, and it is difficult to carry out refined and dynamic quantitative assessment of hose damage. It can only roughly screen faults and passively issue early warnings. The assessment result has a large gap with the actual sealing and pressure-bearing status of the hose, and cannot meet the engineering application requirements of high-precision status assessment and dynamic adaptive pressure regulation of hydraulic hoses under deep-sea working conditions. Summary of the Invention

[0003] In view of the above problems, the present application provides a compensated hydraulic rubber hose control method and system adapted to sudden deep-sea pressure changes, which is used to solve the problems of low detection accuracy and poor adaptability to alternating working conditions of existing deep-sea hydraulic rubber hoses.

[0004] To achieve the above object, the technical solution adopted by the present application is: According to one aspect of the present application, there is provided a compensated hydraulic rubber hose control method adapted to sudden deep-sea pressure changes, comprising: acquiring seawater pressure data outside the hydraulic rubber hose and hydraulic oil pressure data inside the hydraulic rubber hose, and generating an internal and external pressure difference sequence according to the seawater pressure data and the hydraulic oil pressure data; solving the global stress gradient of the hydraulic rubber hose according to the internal and external pressure difference sequence, extracting stress sudden change regions, and counting the spatial distribution density of the stress sudden change regions; Based on the spatial distribution density, the stress abrupt concentration section is located, and the pre-stored microscopic material parameters of the rubber matrix in the stress abrupt concentration section are retrieved. Based on the microscopic material parameters and the internal and external pressure difference sequence, the rubber fatigue cumulative damage index of the stress abrupt concentration section is calculated, and the effective cross-sectional area of ​​the leakage channel inside the hydraulic hose is quantified by combining the rubber fatigue cumulative damage index. The compensation pressure parameters for pressure compensation control are determined based on the effective cross-sectional area of ​​the leakage channel.

[0005] According to another aspect of this application, a compensated hydraulic hose control system adapted to sudden pressure changes in deep sea is provided, comprising: The data acquisition module is used to acquire seawater pressure data outside the hydraulic hose and hydraulic oil pressure data inside the hydraulic hose, and generate an internal and external pressure difference sequence based on the seawater pressure data and the hydraulic oil pressure data. The structural damage detection module is used to solve the global stress gradient of the hydraulic hose based on the internal and external pressure difference sequence, extract the stress change region, and statistically analyze the spatial distribution density of the stress change region. The leakage damage detection module is used to locate the stress abrupt concentration section based on the spatial distribution density, retrieve the pre-stored microscopic material parameters of the rubber matrix of the stress abrupt concentration section, calculate the rubber fatigue cumulative damage index of the stress abrupt concentration section based on the microscopic material parameters and the internal and external pressure difference sequence, and quantify the effective cross-sectional area of ​​the leakage channel inside the hydraulic hose by combining the rubber fatigue cumulative damage index. The parameter determination module is used to determine the compensation pressure parameters for pressure compensation control based on the effective cross-sectional area of ​​the leakage channel.

[0006] The technical solution of this application, firstly, simultaneously collects pressure data from both inside and outside the hose to construct a continuous internal and external pressure difference sequence. This internal and external pressure difference sequence is used as the core input to solve the global stress gradient and statistically analyze the spatial distribution density of stress abrupt change regions. Specifically, using continuous time-series pressure difference data to complete the stress solution for all operating conditions can fully cover the complete load history of sudden pressure changes, ensuring that the stress analysis results accurately correspond to the real-time evolution of hose damage. This effectively overcomes the limitations of existing technologies that rely on static stress analysis, significantly improving the timeliness and adaptability of hose condition perception. Secondly, using the microscopic material parameters of the stress abrupt change concentration zone with the most concentrated stress and the most significant damage as the calculation benchmark, and the dynamic internal and external pressure difference sequence as the load input, the degree of damage is quantified based on the fatigue cumulative damage mechanism. This allows the damage index to directly correspond to the geometric dimensions of the leakage channels formed by the propagation of micro-cracks, achieving a precise quantitative assessment of the degree of hose sealing performance degradation, breaking through the technical bottleneck of traditional methods that can only provide coarse-grained fault warnings. Finally, based on the quantified effective cross-sectional area of ​​the leakage channel, compensation pressure parameters adapted to the current leakage conditions are output. This transforms the quantitative damage detection results into standard parameters usable for pressure control, overcoming the shortcomings of traditional detection schemes that can only output fault warnings and cannot provide quantitative basis for pipeline pressure adaptation and control. This provides accurate data support for the subsequent dynamic pressure adaptation and control of deep-sea hydraulic hoses. In summary, this application's entire process control chain, from dynamic pressure acquisition, global stress analysis, local microscopic material damage calculation to compensation parameter output, is based on dynamic load data calculations of frequent and sudden pressure differential changes in the deep sea. It can adapt to extreme alternating conditions in the deep sea, improving the adaptability and accuracy of detection and evaluation under complex deep-sea conditions. Attached Figure Description

[0007] Figure 1 A flowchart illustrating a compensating hydraulic hose control method adapted to sudden pressure changes in the deep sea, provided as an embodiment of this application.

[0008] Figure 2 This is a schematic diagram of a compensating hydraulic hose control system adapted to sudden pressure changes in the deep sea, provided as an embodiment of this application. Detailed Implementation

[0009] To enable those skilled in the art to better understand the technical solution, the present application will be described in detail below with reference to the embodiments. The description in this section is only exemplary and explanatory, and should not be used to limit the scope of protection of the present application in any way.

[0010] Figure 1This document presents a flowchart of a compensating hydraulic hose control method adapted to sudden pressure changes in deep sea conditions, as provided in this application. This embodiment is applicable to scenarios involving stress damage detection, fatigue damage quantification, effective cross-sectional area quantification of leakage channels, and adaptive pressure compensation control of hydraulic hoses under high-pressure alternating conditions in deep sea. This method can be executed by a compensating hydraulic hose control system adapted to sudden pressure changes in deep sea conditions. Figure 1 As shown, the method includes: S110: Acquire seawater pressure data outside the hydraulic hose and hydraulic oil pressure data inside the hydraulic hose, and generate an internal and external pressure difference sequence based on the seawater pressure data and hydraulic oil pressure data.

[0011] Specifically, the seawater pressure data is the real-time pressure series value of the deep-sea water applied to the outer wall of the hydraulic hose, reflecting the external pressure of the deep-sea environment, which changes abruptly with diving, surfacing, and ocean current disturbances. The hydraulic oil pressure data is the time-series value of the internal pressure generated by the hydraulic oil transported inside the hydraulic hose, representing the working oil pressure for underwater equipment operations; pressure fluctuations occur during start-up, shutdown, and load switching. Both seawater pressure and hydraulic oil pressure data can be collected using mechanical sensors. The internal and external pressure difference sequence is a continuous difference array formed by aligning two sets of synchronously collected data (seawater pressure and hydraulic oil pressure) with a unified time axis, calculating the internal and external pressure difference at each moment, and arranging them sequentially according to the collection time. The internal and external pressure difference sequence completely records the dynamic change process of the internal and external pressure difference of the hose throughout the entire time period.

[0012] In this embodiment, a waterproof, high-precision hydrostatic sensor is installed on the outer wall of the hydraulic hose. This sensor is in direct contact with seawater, collecting external seawater pressure data in real time. An internal hydraulic pressure sensor module is connected in series inside the hydraulic hose, isolating it from seawater and directly contacting the hydraulic oil to collect internal hydraulic oil data. Both sensors share the same synchronous clock for triggering data acquisition, and the sampling frequency is uniformly set to ensure synchronous output of seawater pressure data and hydraulic oil pressure data at the same time point. The two raw pressure data streams are transmitted in real time to the local processing unit for storage. After receiving the two synchronous raw pressure data streams, the local processing unit performs noise filtering and time-series alignment operations to eliminate noise interference caused by water flow and pump vibration, and to unify the timestamps of the two sets of data. Then, differential calculations are performed on the seawater pressure data and hydraulic oil pressure data at the same sampling time after time-series alignment to obtain the internal and external pressure difference at a single moment. Finally, the internal and external pressure differences at all moments are arranged sequentially according to the acquisition time to form a continuous and complete internal and external pressure difference sequence. This embodiment is applicable to high-pressure, high-flow hydraulic components and hydraulic systems. This high-pressure, high-flow-rate hydraulic component and system is a complete hydraulic drive system mounted on deep-sea exploration and underwater operation equipment. Using high-pressure hydraulic oil as the transmission medium, it possesses a large-flow-rate delivery capability and includes core pressure-bearing transmission components such as hydraulic pumps, hydraulic valves, hydraulic hoses, and underwater actuator cylinders. It is primarily used for driving heavy-duty actions such as lifting, propulsion, and robotic arm operations of underwater equipment. The hydraulic hoses, as pressure-bearing and sealing delivery components of the high-pressure, high-flow-rate hydraulic component and system, undertake the long-distance transmission of high-pressure hydraulic oil, enduring the alternating loads of external hydrostatic pressure and internal high-pressure oil pressure differential over extended periods.

[0013] Optionally, an internal and external pressure difference sequence is generated based on seawater pressure data and hydraulic oil pressure data, including: noise filtering and time-series alignment of seawater pressure data and hydraulic oil pressure data; synchronous differential operation of time-series aligned seawater pressure data and hydraulic oil pressure data, followed by nonlinear mapping processing to generate the internal and external pressure difference sequence.

[0014] Specifically, noise filtering refers to denoising the raw seawater pressure data and hydraulic oil pressure data collected by sensors, filtering out high-frequency spike noise generated by water flow disturbances, pump pulsations, and electromagnetic interference, while retaining the true and effective pressure time-series signal. Time-series alignment involves calibrating and matching the seawater pressure data and hydraulic oil pressure data from two different acquisition channels based on a unified timestamp, ensuring strict synchronization of internal and external pressure data at the same calculation time. Synchronous differential calculation specifically involves simultaneously calculating the pressure difference between hydraulic oil pressure and seawater pressure at each aligned time node to obtain the raw data of the dynamic pressure difference at each time step. Nonlinear mapping processing refers to nonlinearly correcting the raw pressure difference obtained by linear differential calculation based on the mechanical properties and pressure-bearing deformation law of the hydraulic hose rubber material, compensating for the pressure difference calculation error caused by hose expansion under pressure and wall thickness deformation. Furthermore, the pressure difference calculated by direct differential calculation is the theoretical pressure difference of an ideal rigid pipeline. However, hydraulic hoses are flexible rubber components. When high-pressure oil flows through them, they expand radially, thinning the hose wall. Furthermore, the pressure of deep-sea water causes the hose wall to contract. The degree of hose deformation and the pressure difference are not simply proportional; deformation alters the actual stress on the hose wall. A simple subtraction calculation of the pressure difference will result in a discrepancy between the calculated pressure difference and the hose's actual load-bearing capacity. Nonlinear mapping processing, through a set of nonlinear conversion functions, corrects the theoretical pressure difference of rigid pipelines to the effective pressure difference actually borne by the flexible hose. This eliminates the calculation errors of the rigid pressure difference caused by the expansion and thinning of the flexible hose under pressure, making the load input for fatigue calculations more closely match the actual stress state.

[0015] For example, online stress damage detection and pressure compensation control were carried out on a 25 mm nominal inner diameter rubber hydraulic hose used in a deep-sea underwater robot. The operating water depth was set to 1200 m, corresponding to a static seawater pressure of 12 MPa and a rated working internal pressure of 16 MPa for the hydraulic hose. The specific implementation process is as follows: Seawater pressure data and hydraulic oil pressure data were synchronously collected by a seawater pressure sensor placed on the outer wall of the hose and an internal oil pressure sensor. The single collection time was 30 min, and the sampling frequency was set to 50 Hz. To address high-frequency noise interference such as water flow disturbance and hydraulic pump pulsation in the original pressure data, mean filtering was first used to remove peak abnormal data. Then, the seawater pressure data and hydraulic oil pressure data were accurately time-series aligned using a unified timestamp. The two pressure data streams after time-series alignment were synchronously differentially calculated moment by moment, and nonlinear mapping correction was performed by combining the Poisson's ratio of the hydraulic hose rubber, the hose inner diameter, and the stiffness of the steel wire reinforcement layer. Finally, a continuous internal and external pressure difference sequence with a duration of 30 min and a single step time interval of 0.02 s was generated. The calculation steps for nonlinear mapping are as follows: First, the nominal timing voltage difference is obtained through synchronous differential:

[0016] in, The nominal internal and external pressure difference is obtained by time-series differential analysis; for The pressure of the hydraulic oil inside the hydraulic hose at all times; for The external seawater pressure of the hydraulic hose is constantly monitored. Then, the radial strain of the hose wall is calculated based on the stress theory of thin-walled cylinders. The corresponding formula is as follows:

[0017] in, This refers to the nominal inner diameter of the hose. Poisson's ratio for rubber materials; The equivalent elastic modulus of the coupling between the rubber matrix and the steel wire reinforcement layer is given. Finally, a nonlinear pressure difference mapping model is constructed to obtain the effective internal and external pressure difference. The corresponding formula is as follows:

[0018] in, This is a correction factor for the hose structure; This represents the nonlinear exponent of rubber hyperelasticity. The effective internal and external pressure differences are arranged to obtain a continuous sequence of internal and external pressure differences. The hose structure correction factor is a mechanical correction parameter for the heterogeneous structure of multi-layer composite hydraulic hoses. It is used to compensate for the stress calculation deviation caused by the ideal assumptions of the elastic analytical formula for a homogeneous thick-walled cylinder and the difference in stiffness distribution between the actual hose and the actual hose. By linearly correcting the theoretical circumferential stress output by the thick-walled cylinder formula using the hose structure correction factor, the true stress suitable for the actual hose structure can be obtained. The hose structure correction factor is directly related to the number of reinforcing layers, wire braiding, winding density, and the stiffness ratio of the rubber matrix. For example, offline calibration can be performed through sampling tests. Samples of the same batch of rubber hoses are placed on a standard pressure testing bench, and graded gradient pressure differences are applied to the samples. Circumferential strain data for corresponding segments are collected using surface strain gauges attached to each equal testing unit, and the actual circumferential stress for each segment is calculated. The same pressure difference parameter is substituted into the elastic analytical formula for a thick-walled cylinder to calculate the theoretical circumferential stress for the corresponding segment. The ratio of the measured actual circumferential stress to the theoretical circumferential stress is used as the measured correction coefficient for the hose structure of that segment. In this embodiment, the hose structure correction coefficient is 1.13. The rubber hyperelastic nonlinear index is a core constitutive parameter describing the hyperelastic mechanical behavior of rubber, used to characterize the degree of nonlinearity in the stress-strain relationship of rubber under large deformation. Rubber undergoes significant large deformation under large pressure differences in the deep sea, and the calculation error of the linear elastic assumption for small deformations is relatively large. Introducing the rubber hyperelastic nonlinear index can correct the calculation deviations of stress and strain, providing a material mechanics basis for solving the fatigue failure cycle life and microcrack opening scale of rubber. Samples from the same batch of rubber hoses can be prepared according to the rubber tensile testing standard. Uniaxial constant-rate tensile tests can be conducted, and stress-strain data across the entire strain range can be collected. The hyperelastic nonlinear index of the rubber can then be obtained by fitting the test curve. In this embodiment, the hyperelastic nonlinear index of the rubber is taken as 1.6.

[0019] In this embodiment, time-matched pressure data is obtained through synchronous internal and external acquisition, constructing a dynamic and continuous internal and external pressure difference sequence. This fully captures the instantaneous pressure changes caused by deep-sea chutes and equipment start-ups and shutdowns, completely reconstructing the entire process of alternating loads borne by the hose. The internal and external pressure difference sequence serves as the foundational input for subsequent global stress gradient calculations, accurately reflecting the actual pressure load changes on the hose and avoiding significant errors caused by relying on a single internal or external pressure for stress calculations. This improves the overall calculation accuracy of subsequent stress field solutions and damage assessments. The time-seriesd internal and external pressure difference sequence also fully records the cyclical variation of the load, providing a continuous and complete load data source for subsequent counting analysis and calculation of the rubber fatigue cumulative damage index. This ensures that the fatigue damage quantification results closely match the actual damage evolution state of the hose.

[0020] S120: Solve the global stress gradient of the hydraulic hose based on the internal and external pressure difference sequence and extract the stress change region, and statistically analyze the spatial distribution density of the stress change region.

[0021] Specifically, the global stress gradient uses the entire axial length of the hose as the solution domain. The effective internal and external pressure difference sequence, corrected by nonlinear mapping at each moment, is used as the load input. Based on the composite pipe mechanical model, the circumferential and radial stresses of the pipe wall are solved axially at each position. Then, the stress change rate is calculated along the axial direction, ultimately forming a stress change rate physical quantity continuously distributed along the hose axis. A stress abrupt change region refers to a pipe section within the global stress gradient field where the local stress change amplitude exceeds a preset stress fluctuation threshold; this is the preferred location for fatigue crack initiation. For example, for a rubber hydraulic hose with a nominal inner diameter of 25 mm, the critical stress change amplitude for rubber fatigue is 0.68 MPa / m. With a safety margin of 0.12 MPa / m, the preset stress fluctuation threshold is set to 0.8 MPa / m. Only when the local stress gradient change amplitude exceeds 0.8 MPa / m is it identified as a stress abrupt change region. The spatial distribution density of the stress abrupt change region characterizes the coverage ratio of the stress abrupt change region in the unit axial space of the hydraulic hose, and is used to quantify the degree of severe stress fluctuation in the pipe section.

[0022] In this embodiment, deep-sea hydraulic hoses typically employ a multi-layered composite structure, such as an inner lining, a reinforcing braided layer, and an outer protective layer. Under the combined action of external seawater pressure and internal hydraulic oil pressure, these hoses experience complex stress states. When the hose suffers microscopic damage due to manufacturing defects, fatigue, or extreme pressure impacts, such as microcracks or interlayer delamination, the damaged area disrupts the structural continuity, leading to stress redistribution at the damage boundary and stress concentration. This stress concentration manifests as a sharp spatial change in stress values, i.e., a sudden change in stress gradient, with the corresponding region being the stress abrupt change region. By monitoring the internal and external pressure difference sequence in real time, the stress field distribution of the hose wall can be calculated. In the damaged area, the stress gradient is significantly higher than in the healthy area. Therefore, extracting the stress gradient abrupt change region and statistically analyzing its spatial distribution density essentially locates and quantifies these stress anomaly areas. Higher density indicates more damage points or a denser damaged area, resulting in poorer structural integrity, thus enabling non-destructive structural damage detection of the hose from a mechanical perspective.

[0023] Optionally, the global stress gradient of the hydraulic hose is solved based on the internal and external pressure difference sequence, and stress abrupt change regions are extracted. The spatial distribution density of the stress abrupt change regions is statistically analyzed. This includes: solving the global stress gradient of the hydraulic hose based on the internal and external pressure difference sequence; constructing a stress gradient field based on the global stress gradient; selecting stress abrupt change regions from the stress gradient field based on the local stress change amplitude of the hydraulic hose; dividing the hydraulic hose into multiple equal detection units; statistically analyzing the coverage length of the stress abrupt change regions in each equal detection unit; and obtaining the spatial distribution density of the stress abrupt change regions.

[0024] Specifically, the stress gradient field refers to a continuous spatial data field composed of the global stress gradients corresponding to all axial positions of the hydraulic hose. The local stress change amplitude is the stress gradient fluctuation amplitude at any position within the stress gradient field. The uniform detection unit is a number of equally long segmented units obtained by uniformly dividing the entire hydraulic hose along the axial direction.

[0025] For example, based on the pre-calibrated pressure difference-stress mapping correction coefficients of each equal detection unit, the real-time internal and external pressure difference sequence is substituted into the elastic analytical formula of the thick-walled cylinder to directly solve for the stress values ​​of each segment along the entire axial direction of the hose. The global stress gradient is obtained through axial difference calculation, and a two-dimensional stress gradient field is constructed along the axial length of the hose from 0 to 5m. Stress at each coordinate position is extracted along the hose axis, and the global stress gradient is calculated point-by-point by the ratio of the stress difference between adjacent positions to the axial spacing. A two-dimensional stress gradient field is constructed by combining the axial spatial coordinates and the time dimension. A stress change amplitude threshold of 0.8 MPa / m is set, and regions exceeding the threshold are selected from the stress gradient field as stress abrupt change regions. Then, the entire 5m hose is equally divided into 50 equal detection units of 0.1m length. The coverage length of the stress abrupt change region within each unit is statistically analyzed, and the spatial distribution density of the stress abrupt change region in each unit is finally calculated. The density value of the 3.2m–3.8m segment is significantly higher than other segments, and this segment is determined to be a stress abrupt change concentration segment. The pressure difference-stress mapping correction coefficient was obtained through offline pre-calibration before shipment. Using an Abaqus three-dimensional layered transient finite element model, the hydraulic hose was discretized into numerous micro-grid elements based on the inner rubber layer, steel wire reinforcement layer, and outer rubber layer. Hyperelastic mechanical parameters of the hydraulic hose rubber layer and linear elastic mechanical parameters of the steel wire layer were entered. Multiple sets of standard pressure differences were used as boundary conditions for the inner and outer walls of the hose to perform transient mechanical solutions. After outputting the stress data corresponding to all spatial grid nodes of the hose, the pressure difference-stress mapping correction coefficient for each uniform detection unit was fitted. The elastic analytical formula for thick-walled cylinders, also known as the Lame formula, is a classical elastic mechanical analytical solution for axisymmetric thick-walled cylinders subjected to uniform internal and external pressures. It can directly solve for the stress value at any position on the cylinder wall using the internal and external pressure difference.

[0026] S130: Based on the spatial distribution density, locate the stress abrupt concentration section, retrieve the pre-stored microscopic material parameters of the rubber matrix in the stress abrupt concentration section, calculate the rubber fatigue cumulative damage index of the stress abrupt concentration section based on the microscopic material parameters and the internal and external pressure difference sequence, and quantify the effective cross-sectional area of ​​the leakage channel inside the hydraulic hose by combining the rubber fatigue cumulative damage index.

[0027] Specifically, the stress abrupt change concentration zone is the hose section within the equal detection unit where the spatial distribution density of stress abrupt changes is significantly higher than other sections. This is a high-risk area where the rubber repeatedly experiences severe stress fluctuations and is prone to fatigue crack initiation. Rubber matrix micromaterial parameters are indicators of the internal micromechanical properties of rubber, which may include rubber crosslinking density, fracture toughness, fatigue crack propagation rate, elastic modulus, Poisson's ratio, etc., used to characterize the rubber's resistance to fatigue cracking. For example, the collection of rubber matrix micromaterial parameters can be achieved using two methods: pre-embedded acquisition and remotely operated vehicle (ROV) inspection acquisition. The collected micromaterial parameters are pre-stored in the parameter library of the control unit executing this compensating hydraulic hose control method adapted to sudden changes in deep-sea pressure. At each preset service cycle or after the end of a single dive mission, micromaterial parameters of the rubber matrix in the stress abrupt change concentration zone are collected, and the micromaterial parameters in the parameter library are updated. The rubber fatigue cumulative damage index is a dimensionless index that quantitatively characterizes the degree of continuous accumulation of fatigue damage in rubber under cyclic alternating pressure differential loads. A higher cumulative fatigue damage index (CFDI) indicates a higher risk of fatigue cracking. The effective cross-sectional area of ​​the leakage channel is the equivalent flow cross-sectional area formed by the interconnection of fatigue cracks in the rubber, and it can directly reflect the severity of hose leakage failure.

[0028] In this embodiment, microscopic material parameters are collected and damage calculations are performed only in areas of concentrated stress abrupt changes, eliminating the need for full-area testing of the entire hose and reducing unnecessary calculations and sampling workload. Simultaneously, collecting in-situ microscopic material parameters only in high-risk areas accurately reflects the performance degradation caused by local rubber aging and stress softening, eliminating calculation biases caused by single-mean parameters and ensuring fatigue damage calculations closely match the actual local operating conditions of the hose. Furthermore, combining this with on-site time-series differential pressure loads to quantify cumulative fatigue damage transforms the abstract degree of fatigue damage into a directly quantifiable physical indicator—the effective cross-sectional area of ​​the leakage channel. This enables quantitative detection of leakage damage in deep-sea hydraulic hoses, directly reflecting the severity of internal cracks connecting leakage pathways. This facilitates early prediction of hose leakage failure, allowing for timely maintenance and replacement plans and preventing safety malfunctions such as underwater equipment shutdowns and seal failures caused by deep-sea hydraulic media leaks.

[0029] Optionally, the microscopic material parameters include in-situ elastic modulus, local hardness, cross-linking aging degree, and residual elongation. The cumulative fatigue damage index of rubber in stress-concentration zones is calculated based on the microscopic material parameters and the internal and external pressure difference sequence. This includes: determining the rubber fatigue failure cycle life in stress-concentration zones based on the in-situ elastic modulus, local hardness, and cross-linking aging degree; performing rainflow counting analysis on the internal and external pressure difference sequence to obtain the number of load cycles corresponding to various pressure difference fluctuations; and solving for the cumulative fatigue damage index of rubber based on the Mainner cumulative damage criterion, considering the rubber fatigue failure cycle life and the number of load cycles.

[0030] Specifically, rainflow counting analysis is a time-domain statistical method for load analysis. It can decompose and statistically analyze the complete load cycle count corresponding to different amplitude pressure difference fluctuations from continuously changing internal and external pressure difference time-series data. Rainflow counting analysis can accurately decompose random and asymmetric alternating loads caused by sudden changes in deep-sea pressure, avoiding the underestimation of fatigue damage caused by conventional average load calculations. The load cycle count is the actual number of cycles corresponding to each pressure difference fluctuation amplitude after rainflow counting separation. The Miner cumulative damage criterion is a linear fatigue damage superposition theory. The damage caused by various load cycles is linearly accumulated and used to calculate the total fatigue damage degree.

[0031] In this embodiment, the in-situ elastic modulus can be measured using an underwater ultrasonic sensing module. The propagation velocity of ultrasound within the rubber has a fixed mapping relationship with the elastic modulus. The probe, attached to the tube wall, emits and receives sound waves. Combined with a deep-sea hydrostatic pressure compensation algorithm, the in-situ elastic modulus of the section can be directly calculated. Local hardness is detected using a matching underwater micro-indentation sensing probe. The mechanical micro-indenter slightly contacts the outer wall of the tubing, collecting the indentation deformation and converting it into the local hardness of the rubber. Crosslinking aging degree is collected using a probe equipped with an underwater near-infrared spectroscopy system. Infrared light scans the spectral characteristics of the rubber surface, and the degree of crosslinking and aging degradation is determined based on the absorption peaks of molecular functional groups, thus obtaining the crosslinking aging degree. Residual elongation can be collected using distributed fiber optic strain sensors deployed on the tube wall. By recording the irreversible deformation of the rubber under long-term load and comparing it with the original standard dimensions, the residual elongation of the rubber section is calculated.

[0032] Furthermore, the degree of crosslinking aging directly reflects the damage to the crosslinking network of rubber molecules and is a core microscopic indicator determining the rubber's resistance to fatigue cracking. In-situ elastic modulus reflects the stiffness change of rubber after long-term alternating loads. Local hardness directly characterizes the hardening and softening state of the rubber surface. These three parameters, from the perspectives of molecular microstructure, overall mechanical stiffness, and surface macrohardness, jointly depict the current true aging damage state of the rubber. Using them in combination can accurately match the actual working conditions of the local rubber, improving the accuracy of fatigue failure cycle life calculation. For example, rubber samples with formulations and molding processes completely identical to those of the deep-sea hydraulic hose under test are selected and grouped for accelerated aging tests. Multiple groups of samples with different aging degrees are prepared, and the in-situ elastic modulus, local hardness, and degree of crosslinking aging of each group are measured. Fatigue cyclic loads are then applied to each group of samples until penetrating fatigue cracks occur. The total number of cycles corresponding to the failure of each group of samples is recorded as the rubber fatigue failure cycle life matched to the material parameters of that group. The three material parameters of all samples and the corresponding number of fatigue failure cycles are summarized to construct a standardized calibration data table. On-site, non-destructive testing was used to collect in-situ measured values ​​of the elastic modulus, local hardness, and cross-linking aging degree of the rubber in the stress concentration zone. These three parameters were compared with a calibration data table, and two sets of calibration samples with parameters closest to the measured values ​​were selected. Linear interpolation was performed based on the fatigue failure cycle life corresponding to these two sets of samples, and the interpolated result is the fatigue failure cycle life of the rubber in the stress concentration zone. Then, the continuous time-series internal and external pressure difference data were organized into a load-time curve. The curve was then subjected to inflection point extraction and cycle splitting using standard rainflow counting rules. Invalid small fluctuations were filtered out, and complete loading-unloading cycles were separated. The curves were then grouped and categorized according to the pressure difference fluctuation amplitude, and the number of complete load cycles corresponding to each amplitude range was counted, outputting the load cycle number for each amplitude group. Finally, the fatigue cumulative damage index was calculated based on the Mainner linear cumulative damage criterion, which can be calculated using the following formula:

[0033] in, The cumulative fatigue damage index for rubber; The total number of pressure difference amplitude types separated from the rainflow count; For the first The number of load cycles corresponding to differential pressure fluctuations; For the first Under pressure differential amplitude, the fatigue failure cycle life of rubber.

[0034] Optionally, the effective cross-sectional area of ​​the leakage channel inside the hydraulic hose can be quantified by combining the cumulative damage index of rubber fatigue, including: determining the basic opening size of the rubber microcracks in the stress concentration section based on the cumulative damage index of rubber fatigue; correcting the basic opening size of the rubber microcracks using residual elongation to obtain the actual opening width of the rubber microcracks; and integrating the actual opening widths of all rubber microcracks in the stress concentration section to obtain the effective cross-sectional area of ​​the leakage channel inside the hydraulic hose.

[0035] Specifically, the basic opening size of the rubber microcrack is the theoretical crack opening size calculated solely based on the fatigue cumulative damage index. Residual elongation refers to the ratio of the permanent elongation that the rubber cannot recover after multiple cycles of alternating pressure differential unloading to its original size. The actual opening width of the rubber microcrack is the microcrack opening width that conforms to the actual working conditions of the hose after incorporating the residual elongation to correct the basic opening size. The effective cross-sectional area of ​​the leakage channel refers to the equivalent flow cross-sectional area formed by the superposition of all interconnected fatigue microcracks within the stress abrupt change zone, directly reflecting the leakage capacity of the hydraulic medium.

[0036] In this embodiment, within the stress abrupt concentration zone, the fatigue damage of the rubber matrix manifests primarily as the initiation and propagation of microcracks. Rubber fatigue cumulative damage index. This reflects the cumulative damage level of the material in this section under alternating loads. Based on the principles of damage mechanics and fracture mechanics, the basic opening scale of microcracks... With damage index The relationship exhibits a power-law nature and can be estimated using the following formula:

[0037] in, It is the leakage ratio coefficient, used to calibrate the benchmark value of leakage rate under unit pressure difference and unit equivalent leakage area. The leakage area index characterizes the nonlinearity of the leakage rate as a function of the effective cross-sectional area of ​​the leakage channel. Both can be simultaneously calibrated offline using the same set of experiments: multiple groups of rubber samples from the same batch with different fatigue damage levels are selected, and the equivalent leakage cross-sectional area and actual leakage rate under a fixed pressure difference are measured for each group. The two parameters are then simultaneously solved using power function fitting. Alternatively, a double logarithm of the leakage rate and cross-sectional area can be used for linear fitting, and the leakage ratio coefficient can be obtained from the intercept, while the leakage area index is directly obtained from the slope. For conventional deep-sea hydraulic hoses, the leakage ratio coefficient is typically 0.15-0.7; the lower the rubber hardness, the more severe the fatigue damage, and the more unobstructed the leakage channel, the larger the leakage ratio coefficient. The leakage area index ranges from 1.1-1.8; the more severe the fatigue damage and the closer the crack is to a regular slit, the larger the leakage area index.

[0038] Under actual working conditions, rubber materials undergo irreversible permanent deformation (i.e., residual strain) under long-term alternating loads, leading to a further increase in the actual opening width of microcracks. Therefore, the residual elongation of the rubber matrix in the stress concentration zone is introduced. The basic opening dimensions are revised as follows:

[0039] in, This represents the actual opening width of the rubber microcrack. This is the residual deformation gain correction coefficient. The residual deformation gain correction coefficient is used to calibrate the amplification gain of residual elongation on microcrack opening width. For hydraulic hoses made of rubber with different hardness and formulations, the proportion of permanent deformation converted into crack propagation varies. The residual deformation gain correction coefficient can be used to match the actual material properties of the hose. Multiple sets of alternating pressure differential cycles can be applied to rubber samples from the same batch, and the residual elongation and the measured microcrack opening width can be observed simultaneously. The residual deformation gain correction coefficient can be obtained by fitting multiple sets of data. For deep-sea hydraulic hoses commonly made of nitrile rubber, the conventional range for the residual deformation gain correction coefficient is 0.7-0.14. In stress abrupt concentration zones, it is assumed that microcracks are distributed along the hose wall thickness direction and their orientation is perpendicular to the principal stress direction. The number density of microcracks per unit area in this zone can be determined through microscopic observation or based on a statistical damage model. The effective cross-sectional area of ​​the leakage channel. It can be obtained by integrating along the entire space of this segment:

[0040] in, This represents the volume of the stress concentration zone. This represents a volumetric micro-element. In practical calculations, this section can be discretized into a finite number of micro-elements. For each micro-element, its contribution to the leakage area is calculated using the above formula, and then summed to obtain the total effective cross-sectional area. Compared to the method of uniform parameter calculation across the entire pipe, this application identifies high-risk stress-burden concentration sections by using stress-burden density. Then, only microscopic sampling is performed on the local damage area, which avoids the calculation distortion caused by uniformizing the pipe parameters and significantly reduces the computational load, achieving a balance between accuracy and efficiency.

[0041] S140: Determine the compensation pressure parameters for pressure compensation control based on the effective cross-sectional area of ​​the leakage channel.

[0042] Specifically, the compensation pressure parameter refers to the control setpoint used by the hydraulic system pressure compensation controller. The compensation pressure parameter may include control indicators such as compensation pressure amplitude, continuous compensation duration, and graded compensation levels, which are used to actively adjust the hydraulic oil pressure inside the pipeline to offset the pressure loss caused by medium leakage.

[0043] Optionally, the compensation pressure parameters for pressure compensation control are determined based on the effective cross-sectional area of ​​the leakage channel, including: solving the target reference oil pressure based on the effective cross-sectional area of ​​the leakage channel and seawater pressure data, and generating the compensation pressure parameters based on the target reference oil pressure.

[0044] In this embodiment, the target reference oil pressure is composed of two superimposed parts: first, the real-time seawater pressure outside the hose, serving as the basic bearing pressure value; and second, the leakage compensation pressure increment, which is the product of the effective cross-sectional area of ​​the leakage channel and the leakage pressure correction coefficient. The larger the effective cross-sectional area of ​​the leakage channel, the greater the leakage compensation pressure increment. By raising the oil pressure inside the hose, a positive pressure barrier is formed, preventing seawater from seeping inward along the micro-cracks in the hose. This can be expressed by the following formula:

[0045] in, Indicates the target reference oil pressure; This represents the static pressure of seawater outside the hose, obtained from seawater pressure data. This represents the leakage pressure correction factor. The leakage pressure correction factor is a calibration parameter used in rubber microcrack seepage scenarios to correct the deviation between the ideal rubber matrix leakage model and the actual leakage characteristics of the rubber matrix. The ideal rubber matrix leakage model assumes the leakage channel is a smooth, straight circular tube, while the actual leakage channel inside the hose is a tortuous, variable cross-section channel formed by fatigue microcracks. Simultaneously, rubber under pressure will experience a microcrack closure effect, resulting in an inherent deviation between the theoretical calculation value and the actual leakage volume. Introducing the leakage pressure correction factor can calibrate the calculation error of the leakage rate, improve the calculation accuracy of the leakage rate corresponding to the effective cross-sectional area of ​​the leakage channel, and ultimately ensure the accuracy of the compensation pressure parameter. The leakage pressure correction factor can be calibrated through offline testing. Samples of different fatigue damage levels from the same batch of hoses are prepared, and the leakage volume per unit time is collected under standard pressure differential to convert it into the actual leakage rate. The ratio of the actual leakage rate to the theoretical leakage rate is the leakage pressure correction factor. In this embodiment, the leakage pressure correction factor can be taken as 0.78.

[0046] Then, the current real-time internal hydraulic oil pressure in the pipeline is compared with the target reference oil pressure, and the oil pressure difference between the two is calculated as the basic compensation increment. Then, the basic compensation increment is limited and smoothed by combining the upper limit of hydraulic system pressure regulation and pressure regulation response rate. Finally, the compensation pressure parameters, including the target reference oil pressure, compensation pressure increase amplitude, pressure regulation rise rate, and compensation duration, are output and transmitted to the pipeline pressure compensation controller to perform closed-loop pressure regulation.

[0047] Furthermore, this embodiment dynamically matches the compensation pressure increase based on the effective cross-sectional area of ​​the leakage channel. The more severe the leakage, the higher the corresponding compensation pressure increment. This forms a precise positive oil pressure barrier inside the pipeline, preventing external seawater from seeping into the pipeline through rubber micro-cracks and contaminating the hydraulic oil, while also reducing pressure loss caused by leakage of the medium inside the pipe. Moreover, real-time seawater static pressure is simultaneously introduced when calculating the target reference oil pressure, adapting to the external water pressure corresponding to different depths in the deep sea. This ensures that the compensation pressure matches the actual underwater pressure conditions, improving the accuracy of compensation control. When generating compensation parameters, the upper limit of the compensation increment is also limited, and pressure smoothing corrections are applied to avoid sudden pressure increases that could cause shocks and exacerbate hose fatigue damage, thus extending the service life of the hose while suppressing leakage.

[0048] Based on the above embodiments, optionally, after determining the compensation pressure parameters for pressure compensation control based on the effective cross-sectional area of ​​the leakage channel, the method further includes: adjusting the hydraulic oil pressure of the hydraulic hose based on the compensation pressure parameters. In this embodiment, after the compensation pressure parameters are sent to the pipeline pressure compensation controller, the controller will gradually increase the internal oil pressure of the hydraulic hose according to the pressure increase amplitude and adjustment rate within the compensation pressure parameters, thereby completing the leakage compensation pressure adjustment operation.

[0049] Furthermore, in this embodiment, the compensation pressure is set according to the effective cross-sectional area of ​​the leakage channel and the hydraulic oil pressure inside the hose is increased to form a seepage-proof pressure barrier. This can effectively block seawater from seeping in, reduce the leakage of media inside the pipe, prevent the continuous action of high pressure from aggravating the expansion of rubber microcracks and permanent deformation of the pipeline, significantly improve the pipeline operation stability under the condition of sudden pressure change in deep sea, and reduce the probability of underwater leakage failure and shutdown.

[0050] The technical solution of this application embodiment firstly involves simultaneously acquiring pressure data from both inside and outside the hose to construct a continuous internal and external pressure difference sequence. This internal and external pressure difference sequence is then used as the core input to solve for the global stress gradient and statistically analyze the spatial distribution density of stress abrupt change regions. The use of continuous time-series pressure difference data to complete the stress solution under all operating conditions fully covers the complete load history of sudden pressure changes, ensuring that the stress analysis results accurately correspond to the real-time evolution of hose damage. This effectively overcomes the limitations of existing technologies that rely on static stress analysis, significantly improving the timeliness and adaptability of hose condition perception. Secondly, using the microscopic material parameters of the stress abrupt change concentration zone where stress is most concentrated and damage is most significant as the calculation benchmark, and the dynamic internal and external pressure difference sequence as the load input, the degree of damage is quantified based on the fatigue cumulative damage mechanism. This allows the damage index to directly correspond to the geometric dimensions of the leakage channels formed by the propagation of micro-cracks, achieving a precise quantitative assessment of the degree of hose sealing performance degradation. This overcomes the technical bottleneck of traditional methods that can only provide coarse-grained fault warnings. Finally, based on the quantified effective cross-sectional area of ​​the leakage channel, compensation pressure parameters adapted to the current leakage conditions are output. This transforms the quantitative damage detection results into standard parameters usable for pressure control, overcoming the shortcomings of traditional detection schemes that can only output fault warnings and cannot provide quantitative basis for pipeline pressure adaptation and control. This provides accurate data support for the subsequent dynamic pressure adaptation and control of deep-sea hydraulic hoses. In summary, this application's process control chain, from dynamic pressure acquisition, global stress analysis, local microscopic material damage calculation to compensation parameter output, is based on dynamic load data calculations of frequent and sudden pressure differential changes in the deep sea. It can adapt to extreme alternating conditions in the deep sea, improving the adaptability and accuracy of detection and evaluation under complex deep-sea conditions.

[0051] Among them, the process control refers to the entire solution relying on real-time collected dynamic pressure data to complete the closed-loop calculation of pressure sensing, stress solution, damage quantification, and compensation parameter output. Based on the real-time changes in deep-sea pressure difference, it continuously outputs pressure regulation parameters that match the working conditions, realizing integrated dynamic management and control of hose damage detection and pipeline pressure regulation.

[0052] Figure 2 This is a schematic diagram of a compensating hydraulic hose control system adapted to sudden pressure changes in the deep sea, provided as an embodiment of this application. This embodiment is applicable to scenarios involving stress damage detection, quantitative fatigue damage assessment, quantitative evaluation of the effective cross-sectional area of ​​leakage channels, and adaptive pressure compensation control of hydraulic hoses under high-pressure alternating conditions in the deep sea. This compensating hydraulic hose control system adapted to sudden pressure changes in the deep sea can be implemented in hardware and / or software. It can be configured in the pipeline monitoring terminal or hydraulic control system of equipment equipped with hydraulic delivery systems, such as deep-sea exploration equipment and underwater robots. Figure 2 As shown, the compensated hydraulic hose control system adapted to sudden pressure changes in the deep sea includes: The data acquisition module 210 is used to acquire seawater pressure data outside the hydraulic hose and hydraulic oil pressure data inside the hydraulic hose, and generate an internal and external pressure difference sequence based on the seawater pressure data and hydraulic oil pressure data.

[0053] The structural damage detection module 220 is used to solve the global stress gradient of the hydraulic hose based on the internal and external pressure difference sequence, extract the stress change region, and statistically analyze the spatial distribution density of the stress change region.

[0054] The leakage damage detection module 230 is used to locate stress abrupt concentration sections based on spatial distribution density, retrieve the pre-stored microscopic material parameters of the rubber matrix in the stress abrupt concentration sections, calculate the rubber fatigue cumulative damage index of the stress abrupt concentration sections based on the microscopic material parameters and the internal and external pressure difference sequence, and quantify the effective cross-sectional area of ​​the leakage channel inside the hydraulic hose by combining the rubber fatigue cumulative damage index.

[0055] The parameter determination module 240 is used to determine the compensation pressure parameters for pressure compensation control based on the effective cross-sectional area of ​​the leakage channel.

[0056] Optional, continue to refer to Figure 2 The compensating hydraulic hose control system, adapted to sudden pressure changes in the deep sea, also includes: The oil pressure regulation and correction module 250 is used to regulate the internal hydraulic oil pressure of the hydraulic hose based on the compensation pressure parameters.

[0057] The compensating hydraulic hose control system adapted to sudden changes in deep-sea pressure provided in the embodiments of this application can execute the compensating hydraulic hose control method adapted to sudden changes in deep-sea pressure provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the execution method.

[0058] This application also provides a compensating hydraulic hose control device adapted to sudden changes in deep-sea pressure. The compensating hydraulic hose control device adapted to sudden changes in deep-sea pressure includes a control module. The control module is used to execute the compensating hydraulic hose control method adapted to sudden changes in deep-sea pressure provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the method.

[0059] It should be noted that, in this document, the terms "comprising," "including," and any other variations are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Specific examples have been used in this document to illustrate the principles and implementation methods of the technical solutions of this application. The above examples are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are merely preferred embodiments of this application. It should be pointed out that, due to the limitations of written expression and the objective existence of infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this application, and can also combine the above technical features in an appropriate manner; these improvements, modifications, changes, or combinations, or the direct application of the concept and technical solutions of this application to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. A compensating hydraulic hose control method adapted to sudden pressure changes in deep sea, characterized in that, include: Obtain seawater pressure data outside the hydraulic hose and hydraulic oil pressure data inside the hydraulic hose, and generate an internal and external pressure difference sequence based on the seawater pressure data and the hydraulic oil pressure data; The global stress gradient of the hydraulic hose is calculated based on the internal and external pressure difference sequence, and the stress change region is extracted. The spatial distribution density of the stress change region is then statistically analyzed. Based on the spatial distribution density, the stress abrupt concentration section is located, and the pre-stored microscopic material parameters of the rubber matrix in the stress abrupt concentration section are retrieved. Based on the microscopic material parameters and the internal and external pressure difference sequence, the rubber fatigue cumulative damage index of the stress abrupt concentration section is calculated, and the effective cross-sectional area of ​​the leakage channel inside the hydraulic hose is quantified by combining the rubber fatigue cumulative damage index. The compensation pressure parameters for pressure compensation control are determined based on the effective cross-sectional area of ​​the leakage channel.

2. The compensating hydraulic hose control method for adapting to sudden pressure changes in deep sea as described in claim 1, characterized in that, The step of generating the internal and external pressure difference sequence based on the seawater pressure data and the hydraulic oil pressure data includes: Noise filtering and timing alignment are performed on the seawater pressure data and the hydraulic oil pressure data; The time-aligned seawater pressure data and hydraulic oil pressure data are subjected to synchronous differential operation, and then nonlinear mapping processing is performed to generate the internal and external pressure difference sequence.

3. The compensating hydraulic hose control method for adapting to sudden pressure changes in deep sea as described in claim 1, characterized in that, The process of calculating the global stress gradient of the hydraulic hose based on the internal and external pressure difference sequence and extracting stress abrupt change regions, and statistically analyzing the spatial distribution density of the stress abrupt change regions, includes: The global stress gradient of the hydraulic hose is calculated based on the internal and external pressure difference sequence, and a stress gradient field is constructed based on the global stress gradient. The stress abrupt change region is selected from the stress gradient field based on the local stress change amplitude of the hydraulic hose; The hydraulic hose is divided into multiple equal detection units, and the coverage length of the stress change region in each equal detection unit is counted to obtain the spatial distribution density of the stress change region.

4. The compensating hydraulic hose control method for adapting to sudden pressure changes in deep sea as described in claim 1, characterized in that, The microscopic material parameters include in-situ elastic modulus, local hardness, cross-linking aging degree, and residual elongation; the calculation of the rubber fatigue cumulative damage index of the stress abrupt concentration section based on the microscopic material parameters and the internal and external pressure difference sequence includes: The rubber fatigue failure cycle life of the stress abrupt concentration section is determined based on the in-situ elastic modulus, the local hardness, and the degree of crosslinking aging. Rainflow counting analysis is performed on the internal and external pressure difference sequences to obtain the number of load cycles corresponding to various pressure difference fluctuations; Based on the Mainner cumulative damage criterion, the rubber fatigue cumulative damage index is calculated according to the rubber fatigue failure cycle life and the number of load cycles.

5. The compensating hydraulic hose control method for adapting to sudden pressure changes in deep sea as described in claim 4, characterized in that, The quantification of the effective cross-sectional area of ​​the leakage channel inside the hydraulic hose by combining the rubber fatigue cumulative damage index includes: The opening size of the rubber microcrack foundation in the stress abrupt concentration section is determined based on the rubber fatigue cumulative damage index. The residual elongation is used to correct the opening size of the rubber microcrack foundation to obtain the actual opening width of the rubber microcrack; The effective cross-sectional area of ​​the leakage channel inside the hydraulic hose is obtained by integrating the actual opening width of all the rubber microcracks in the stress abrupt concentration section.

6. The compensating hydraulic hose control method for adapting to sudden pressure changes in deep sea as described in claim 1, characterized in that, The determination of the compensation pressure parameters for pressure compensation control based on the effective cross-sectional area of ​​the leakage channel includes: Based on the effective cross-sectional area of ​​the leakage channel and the seawater pressure data, the target reference oil pressure is calculated, and the compensation pressure parameters are generated based on the target reference oil pressure.

7. The compensating hydraulic hose control method for adapting to sudden pressure changes in deep sea as described in claim 1, characterized in that, After determining the compensation pressure parameters for pressure compensation control based on the effective cross-sectional area of ​​the leakage channel, the method further includes: The hydraulic oil pressure of the hydraulic hose is adjusted based on the compensation pressure parameter.

8. A compensating hydraulic hose control system adapted to sudden pressure changes in deep sea, characterized in that, include: The data acquisition module is used to acquire seawater pressure data outside the hydraulic hose and hydraulic oil pressure data inside the hydraulic hose, and generate an internal and external pressure difference sequence based on the seawater pressure data and the hydraulic oil pressure data. The structural damage detection module is used to solve the global stress gradient of the hydraulic hose based on the internal and external pressure difference sequence, extract the stress change region, and statistically analyze the spatial distribution density of the stress change region. The leakage damage detection module is used to locate the stress abrupt concentration section based on the spatial distribution density, retrieve the pre-stored microscopic material parameters of the rubber matrix of the stress abrupt concentration section, calculate the rubber fatigue cumulative damage index of the stress abrupt concentration section based on the microscopic material parameters and the internal and external pressure difference sequence, and quantify the effective cross-sectional area of ​​the leakage channel inside the hydraulic hose by combining the rubber fatigue cumulative damage index. The parameter determination module is used to determine the compensation pressure parameters for pressure compensation control based on the effective cross-sectional area of ​​the leakage channel.

9. The compensating hydraulic hose control system for adapting to sudden pressure changes in deep sea as described in claim 8, characterized in that, Also includes: The oil pressure regulating module is used to regulate the hydraulic oil pressure of the hydraulic hose based on the compensation pressure parameter.

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