Adjustable non-magnetic supporting system for underwater target magnetic field test

Abstract

The invention provides an underwater target magnetic field test adjustable non-magnetic support system, which relates to the technical field of marine equipment, and comprises a non-magnetic bearing and vibration isolation module, a self-adaptive size matching module, a posture accurate regulation and control module and a test state monitoring module, the non-magnetic bearing and vibration isolation module is used for providing stable support with zero magnetic pollution and isolating external vibration interference, the self-adaptive size matching module is used for realizing rapid general adaptation of different models of underwater vehicles, and the attitude precise regulation and control module is used for completing six-degree-of-freedom precise positioning of the underwater vehicles in a test space. The test state monitoring module is used for monitoring the supporting state in real time and guaranteeing the quality of test data; according to the system, through full-chain innovation of material design, load distribution, dynamic compensation and comprehensive evaluation, the technical breakthrough from passive support to active adaptation is realized, the contradiction between support interference and test precision in a high-precision magnetic field test is effectively solved, and the reliability and universality of the magnetic field test of the underwater vehicle are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of marine equipment technology, specifically to an adjustable non-magnetic support system for underwater target magnetic field testing. Background Technology

[0002] Magnetic field testing of underwater vehicles is a crucial method for evaluating their magnetic properties, directly impacting their stealth capabilities and detection effectiveness. During magnetic field testing, the support system, as a key facility supporting the underwater vehicle, directly affects the accuracy of the test results due to its magnetic properties and structural stability. Currently, underwater vehicle magnetic field testing primarily relies on land-based testing facilities or offshore survey vessels. Land-based testing facilities typically employ fixed support frames, requiring customized designs for different underwater vehicle models, lacking versatility and rapid adaptability.

[0003] In existing technologies, support system design mainly faces three challenges: first, how to minimize the interference of the support structure on the magnetic field of the test area while ensuring sufficient load-bearing strength; second, how to achieve rapid adaptation to underwater vehicles of different sizes and weights; and third, how to maintain the high-precision stability of the underwater vehicle's attitude during testing. Traditional support systems typically use rigid frames made of uniform materials, which, although simple in structure, suffer from significant magnetic field interference, and attitude adjustment relies on manual operation, resulting in low efficiency and difficulty in guaranteeing accuracy.

[0004] In terms of support load distribution and attitude control for magnetic field testing of underwater vehicles, existing technologies mainly employ the following three algorithms:

[0005] The uniform load distribution algorithm is the most basic method. This algorithm distributes the total weight of the underwater vehicle evenly across the number of support points, with each support point bearing an equal force. The advantages of this algorithm are its computational simplicity, ease of implementation, and lack of need for complex sensors and control systems. The disadvantages are that it ignores the influence of the underwater vehicle's center of gravity position and shape characteristics, which can easily lead to overload of local support points when the underwater vehicle's center of gravity shifts or its attitude is adjusted. Furthermore, it does not consider the differentiated impact of different support point positions on magnetic field testing, making it impossible to achieve optimal control of magnetic field interference.

[0006] The stress-sensing-based adaptive allocation algorithm monitors the distribution of support forces in real time by installing stress sensors at each support point. When uneven force distribution is detected, feedback control adjusts the height or support force of each support point. The advantage of this algorithm is its ability to dynamically respond to changes in the underwater vehicle's attitude, maintaining a relatively balanced force and improving support stability. The disadvantages include a time delay in the feedback adjustment process, resulting in sluggish response during rapid attitude changes. Furthermore, the algorithm focuses only on mechanical balance and does not consider magnetic field interference as an optimization objective, limiting its effectiveness in test scenarios where magnetic field purity needs to be considered. Additionally, the coordinated control of multiple support points is prone to oscillations, affecting system stability.

[0007] The finite element simulation prediction algorithm establishes finite element models of the underwater vehicle and its support system before testing. It simulates and calculates stress distribution and magnetic field disturbances under different support configurations, selecting the optimal support scheme before actual testing. The advantage of this algorithm is that it can predict the support effect before testing, avoiding blind adjustments, and can obtain optimal support configurations for specific underwater vehicle models. The disadvantages are that the modeling process is complex and time-consuming, requiring accurate underwater vehicle geometry and material parameters. New underwater vehicle models require remodeling and simulation, resulting in poor versatility. Furthermore, the simulation results deviate from the actual testing environment, making it unable to handle dynamic changes during testing and insufficiently practical for testing tasks requiring frequent attitude adjustments.

[0008] Foreign patent EP3022589B1 discloses a compensation method for magnetic field measurement of autonomous underwater vehicles (AUVs). This patent focuses on solving the problem of attitude-related magnetic interference compensation when an AUV carries a magnetometer for marine magnetic measurements. The patent proposes integrating the magnetometer inside the AUV and establishing a mathematical relationship between attitude angles and magnetic field interference, using the Tolles-Lawson model for post-compensation of the measurement data. The core innovation of this patent lies in introducing a thruster current variation term, solving the problem that traditional compensation models do not consider dynamic current interference. However, this patent has significant shortcomings: First, the method is applicable to magnetic field measurement of AUVs in motion, rather than static testing environments. Its compensation model is based on magnetic field changes generated by the movement of the AUV itself, and is not suitable for static or quasi-static magnetic field testing scenarios where underwater vehicles are on support systems. Second, the patent does not involve support system design, focusing only on post-hoc mathematical compensation of magnetic field data, and cannot reduce the physical interference of the support structure on the magnetic field of the test area from the source. Third, the method requires the AUV to undergo complex calibration maneuvers before testing, requiring the magnetic field environment to remain constant, which is difficult to meet in land-based testing facilities, and the calibration process is time-consuming. Fourth, the compensation effect is highly dependent on the accuracy of the model parameters, and recalibration is required when the configuration of the underwater vehicle changes or different equipment is carried, resulting in insufficient flexibility.

[0009] Chinese patent CN103852796A discloses a method for measuring the magnetic anomaly intensity of small underwater targets. This patent uses a marine magnetometer probe to detect seabed magnetic data, simplifies the small underwater target into a magnetic dipole model, and calculates the magnetic anomaly intensity by decomposing the axial and transverse components of the magnetic field. The innovation of this patent lies in establishing a relationship model between the magnetic anomaly intensity and the location of the measuring point, the geomagnetic background field, and the target depth, which can be used by marine survey vessels for detecting small underwater targets. However, this patent has the following shortcomings: First, the method is used to detect magnetic anomalies of unknown underwater targets, rather than to test the magnetic properties of known underwater vehicles, and its application scenario does not match the needs of underwater vehicle magnetic field testing; second, the patent uses a mobile measurement method, with the magnetometer scanning the target area as the survey vessel moves, while underwater vehicle magnetic field testing usually requires the underwater vehicle to be fixed on a support system to measure its static magnetic field distribution, and the two measurement methods are completely different; third, the method does not involve the design of any support device, and cannot solve the problem of how to stably support the underwater vehicle without introducing additional magnetic interference; fourth, the simplified magnetic dipole model in this patent is suitable for far-field measurements, while underwater vehicle magnetic field testing requires near-field high-precision measurements, and the simplified model will introduce large errors; fifth, the method does not consider the precise control of the underwater vehicle's attitude during the measurement process, while changes in the underwater vehicle's attitude in actual testing will significantly affect the measurement results of the magnetic field distribution. Summary of the Invention

[0010] The purpose of this invention is to address the shortcomings by proposing an adjustable non-magnetic support system for underwater target magnetic field testing.

[0011] The present invention adopts the following technical solution:

[0012] An adjustable non-magnetic support system for underwater target magnetic field testing includes a non-magnetic load-bearing and vibration isolation module, an adaptive size matching module, a precise attitude control module, and a test status monitoring module.

[0013] The non-magnetic load-bearing and vibration isolation module is used to provide stable support with zero magnetic pollution and isolate external vibration interference. The adaptive size matching module is used to achieve rapid and universal adaptation of different models of underwater vehicles. The attitude precision control module is used to complete the six-degree-of-freedom precise positioning of the underwater vehicle in the test space. The test status monitoring module is used to monitor the support status in real time and ensure the quality of test data.

[0014] The non-magnetic load-bearing and vibration isolation module includes a graded load-bearing frame unit, a magnetic field transparent buffer unit, and an active vibration isolation unit. The graded load-bearing frame unit is used to complete the load-bearing frame configuration and provide the main load-bearing support of the system. The magnetic field transparent buffer unit is used to achieve mechanical load-bearing without interfering with the magnetic field distribution characteristics of the test area. The active vibration isolation unit is integrated to isolate the influence of ground vibration and external disturbances on high-precision magnetic field measurement.

[0015] The adaptive size matching module includes a contoured contact surface unit, a preset size library unit, and an electronic ranging auxiliary unit. The contoured contact surface unit adopts a flexible non-magnetic material array structure to adapt to diverse shell shapes. The preset size library unit is used to quickly recall support configurations through model coding. The electronic ranging auxiliary unit is used to assist operators in quickly completing the spatial positioning and support point alignment of the underwater vehicle.

[0016] The attitude precision control module includes a six-degree-of-freedom micro-motion platform unit, a gravity compensation unit, and a multi-point collaborative locking unit. The six-degree-of-freedom micro-motion platform unit is used to achieve sub-millimeter-level precise attitude adjustment of the underwater vehicle in the test space. The gravity compensation unit is used to reduce the operating force requirements during attitude adjustment. The multi-point collaborative locking unit is used to achieve global rigid locking of the support platform after attitude adjustment is completed.

[0017] The test status monitoring module includes a real-time attitude monitoring unit, a magnetic field interference self-test unit, and a data recording and tracing unit. The real-time attitude monitoring unit is used to provide real-time feedback on the attitude deviation of the underwater vehicle. The magnetic field interference self-test unit is used to continuously monitor the residual magnetism level of the support structure and external magnetic field interference. The data recording and tracing unit automatically records the support configuration parameters, attitude adjustment data, and environmental monitoring information for each test.

[0018] Furthermore, the magnetic field transparent buffer unit includes a gradient material processor, a thickness optimization processor, and a contact surface distribution processor. The gradient material processor uses a composite material layer with magnetic permeability decreasing from the inside to the outside to maintain minimal disturbance to the magnetic field of the test area when subjected to pressure. The thickness optimization processor dynamically determines the optimal thickness configuration of the buffer layer according to the load and magnetic field transparency requirements to balance mechanical and magnetic properties. The contact surface distribution processor disperses the buffer material in multiple discrete contact areas.

[0019] The relative permeability and thickness of each layer in the gradient material processor are calculated according to the following formula:

[0020] ;

[0021] ;

[0022] in, Represents the relative permeability of the i-th layer. Based on the magnetic permeability of the material, Where n is the air permeability, and n is the total number of buffer layers. For gradient exponent, Let be the thickness of the i-th layer. This is the total thickness of the buffer layer. Represents the elastic modulus of the i-th layer;

[0023] The permeability, thickness, and density are integrated into a single characteristic value using the following formula:

[0024] ;

[0025] in, This represents the magnetic coupling characteristic parameter of the i-th layer. Let be the material density of the i-th layer.

[0026] Furthermore, the graded load-bearing frame unit includes a modular frame processor, a connection node processor, and a load distribution processor. The modular frame processor achieves a balance between lightweight and high strength through I-shaped or honeycomb cross-section design. The connection node processor uses non-magnetic fixed-axis pins and non-magnetic fasteners to form a multi-point connection system. The load distribution processor optimizes the spatial layout of discrete support points to evenly distribute the gravity of the underwater vehicle to each load-bearing node.

[0027] The load distribution processor calculates the initial load distribution for each support point according to the following formula:

[0028] ;

[0029] ;

[0030] in, Let M be the initial load assigned to the j-th support point, M be the mass of the underwater vehicle, g be the acceleration due to gravity, and m be the total number of support points. The characteristic response coefficient of the material. The effective magnetic coupling parameters at the j-th support point are... The average magnetic coupling parameters at all support point locations. Let J be the contact area of ​​the j-th support point. Let be the contact efficiency coefficient of the i-th layer material.

[0031] Furthermore, the gravity compensation unit includes a load identification processor, a compensation force generation processor, and a balance maintenance processor. The load identification processor measures the actual weight and center of gravity of the underwater vehicle through a non-magnetic force sensor to provide basic data for compensation force calculation. The compensation force generation processor is used to generate an upward compensation force. The balance maintenance processor dynamically adjusts the magnitude and point of application of the compensation force during the attitude change of the underwater vehicle.

[0032] The compensation force generator calculates the dynamic compensation force required by the support point according to the following formula:

[0033] ;

[0034] ;

[0035] in, This represents the dynamic compensation force required by the j-th support point at time t. The current roll angle, The current pitch angle, For standard roll angle, Standard pitch angle, Let be the material fatigue sensitivity coefficient of the j-th support point. For payload historical memory values, The material memory time constant, For the j-th support point at a historical moment The actual supporting force;

[0036] The corrected total support force is calculated using the following formula:

[0037] ;

[0038] in, h represents the final supporting force at the j-th support point. max This is the threshold for saturated historical load.

[0039] Furthermore, the real-time attitude monitoring unit includes a multi-point attitude sensor processor, a deviation calculation processor, and an early warning output processor. The multi-point attitude sensor processor is used to collect attitude angle data from each measuring point in real time. The deviation calculation processor compares the real-time attitude data with the set standard attitude and calculates the deviation in the three directions of pitch, roll, and yaw. The early warning output processor, based on the deviation threshold setting, immediately sends an early warning signal to the test system when the attitude deviation exceeds the allowable range, prompting the operator to perform attitude correction or suspend the test.

[0040] The deviation calculation processor calculates the comprehensive attitude error index E according to the following formula. total :

[0041] ;

[0042] ;

[0043] ;

[0044] Among them, E angle For pure angular error, E force To normalize the force distribution error, This represents the weight of the k-th degree of freedom. For the measured attitude angle, For standard attitude angles, This is the force coupling coefficient.

[0045] The beneficial effects achieved by this invention are:

[0046] This system feeds back the magnetic field transparency characteristics of the material to the load distribution decision, allowing support points with good magnetic transparency to bear more load, while reducing the stress on magnetically sensitive areas. This material-driven intelligent distribution strategy achieves global optimization of the overall magnetic field interference of the support system. It incorporates the magnetic property degradation mechanism of the material into the dynamic control strategy of the support system, effectively protecting the magnetic performance stability of the buffer material by dynamically reducing the compensation dependence of frequently stressed locations. By comprehensively considering the stress state of each support point and its influence on the magnetic field test, the attitude evaluation results can truly reflect the overall quality of the test conditions.

[0047] To further understand the features and technical content of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are for reference and illustration only and are not intended to limit the present invention. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the overall structural framework of the present invention;

[0049] Figure 2 This is a schematic diagram of the non-magnetic load-bearing and vibration isolation module of the present invention;

[0050] Figure 3 This is a schematic diagram of the adaptive size matching module of the present invention;

[0051] Figure 4 This is a schematic diagram of the posture precision control module of the present invention;

[0052] Figure 5 This is a schematic diagram of the test status monitoring module of the present invention;

[0053] Figure 6 This is a schematic diagram comparing the magnetic field disturbances during the attitude adjustment process of this invention with other methods;

[0054] Figure 7 This is a schematic diagram comparing the long-term stability test results of the present invention with those of other methods;

[0055] Figure 8 This is a schematic diagram of the interactive interface (UI) of the present invention. Detailed Implementation

[0056] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the spirit of the present invention. Furthermore, the accompanying drawings of the present invention are for simple illustrative purposes only and are not depictions of actual dimensions; this is stated beforehand. The following embodiments will further describe the relevant technical content of the present invention in detail, but the disclosed content is not intended to limit the scope of protection of the present invention.

[0057] Example 1.

[0058] Adjustable non-magnetic support system for underwater target magnetic field testing, combined with Figure 1 It includes a non-magnetic load-bearing and vibration isolation module, an adaptive size matching module, a precise attitude control module, and a test status monitoring module;

[0059] The non-magnetic load-bearing and vibration isolation module is used to provide stable support with zero magnetic pollution and isolate external vibration interference. The adaptive size matching module is used to achieve rapid and universal adaptation of different models of underwater vehicles. The attitude precision control module is used to complete the six-degree-of-freedom precise positioning of the underwater vehicle in the test space. The test status monitoring module is used to monitor the support status in real time and ensure the quality of test data.

[0060] Combination Figure 2 The non-magnetic load-bearing and vibration isolation module includes a graded load-bearing skeleton unit, a magnetic field transparent buffer unit, and an active vibration isolation unit. The graded load-bearing skeleton unit adopts a modular, assembled non-magnetic skeleton structure, which can quickly complete the load-bearing frame configuration according to different tonnage underwater vehicles and provide the main load-bearing support of the system. The magnetic field transparent buffer unit uses gradient magnetic permeability material, which achieves mechanical load-bearing without interfering with the magnetic field distribution characteristics of the test area, ensuring the purity of the magnetic field in the test environment. The active vibration isolation unit integrates a non-magnetic air cushion or hydraulic buffer device to effectively isolate the influence of ground vibration and external disturbances on high-precision magnetic field measurement.

[0061] Combination Figure 3 The adaptive size matching module includes a contour-following contact surface unit, a preset size library unit, and an electronic ranging auxiliary unit. The contour-following contact surface unit adopts a flexible non-magnetic material array structure, which can automatically fit the irregular curved surface of the underwater vehicle shell and adapt to diverse shell shapes. The preset size library unit has built-in parameterized support templates for common underwater vehicle models, and the support configuration can be quickly called through model coding, shortening the on-site deployment time. The electronic ranging auxiliary unit integrates a non-magnetic laser or ultrasonic ranging sensor to assist operators in quickly completing the spatial positioning and support point alignment of the underwater vehicle.

[0062] Combination Figure 4 The attitude precision control module includes a six-degree-of-freedom micro-motion platform unit, a gravity compensation unit, and a multi-point cooperative locking unit. The six-degree-of-freedom micro-motion platform unit integrates X / Y / Z three-axis translation and three-axis rotation functions to achieve sub-millimeter-level attitude precision adjustment of the underwater vehicle in the test space. The gravity compensation unit offsets the weight of the underwater vehicle through a counterweight system or pneumatic support mechanism, significantly reducing the operating force requirements during attitude adjustment and improving the operability of large underwater vehicles. The multi-point cooperative locking unit adopts a distributed locking mechanism to achieve global rigid locking of the support platform after attitude adjustment, ensuring high stability of attitude during long-term testing.

[0063] Combination Figure 5 The test status monitoring module includes a real-time attitude monitoring unit, a magnetic field interference self-testing unit, and a data recording and traceability unit. The real-time attitude monitoring unit integrates a non-magnetic tilt sensor or optical encoder to provide real-time feedback on the attitude deviation of the underwater vehicle, providing a reference for the accuracy of the test data. The magnetic field interference self-testing unit pre-embeds magnetic field probes at key locations in the support system to continuously monitor the residual magnetism level of the support structure and external magnetic field interference, ensuring the magnetic cleanliness of the test environment. The data recording and traceability unit automatically records the support configuration parameters, attitude adjustment data, and environmental monitoring information for each test, supporting traceability analysis and quality auditing of test results.

[0064] The graded load-bearing skeleton unit includes a modular skeleton processor, a connection node processor, and a load distribution processor. The modular skeleton processor adopts non-magnetic skeleton segments with standardized interfaces and achieves a balance between lightweight and high strength through I-shaped or honeycomb cross-section design, supporting rapid combination of different lengths and load-bearing capacities. The connection node processor uses non-magnetic fixed-axis pins and non-magnetic fasteners to form a multi-point connection system, ensuring rigid connection and precise positioning between skeleton modules. The load distribution processor optimizes the spatial layout of discrete support points to evenly distribute the gravity of the underwater vehicle to each load-bearing node, avoiding the impact of local stress concentration on test accuracy.

[0065] The magnetic field transparent buffer unit includes a gradient material processor, a thickness optimization processor, and a contact surface distribution processor. The gradient material processor uses a composite material layer with magnetic permeability decreasing from the inside to the outside to minimize disturbance to the magnetic field of the test area when subjected to pressure. The thickness optimization processor dynamically determines the optimal thickness configuration of the buffer layer according to the load and magnetic field transparency requirements to balance mechanical and magnetic properties. The contact surface distribution processor disperses the buffer material in multiple discrete contact areas to reduce the contact area with the underwater vehicle while maintaining sufficient support stability and further reducing magnetic field interference.

[0066] The relative permeability and thickness of each layer in the gradient material processor are calculated according to the following formula:

[0067] ;

[0068] ;

[0069] in, Represents the relative permeability of the i-th layer. Based on the magnetic permeability of the material, Where n is the air permeability, and n is the total number of buffer layers. For gradient exponent, Let be the thickness of the i-th layer. This is the total thickness of the buffer layer. Represents the elastic modulus of the i-th layer;

[0070] The permeability, thickness, and density are integrated into a single characteristic value using the following formula:

[0071] ;

[0072] in, This represents the magnetic coupling characteristic parameter of the i-th layer. Let be the material density of the i-th layer;

[0073] The load distribution processor calculates the initial load distribution for each support point according to the following formula:

[0074] ;

[0075] ;

[0076] in, Let M be the initial load assigned to the j-th support point, M be the mass of the underwater vehicle, g be the acceleration due to gravity, and m be the total number of support points. The characteristic response coefficient of the material. The effective magnetic coupling parameters at the j-th support point are... The average magnetic coupling parameters at all support point locations. Let J be the contact area of ​​the j-th support point. Let be the contact efficiency coefficient of the i-th layer material;

[0077] The active vibration isolation unit includes a vibration sensing processor, a damping adjustment processor, and a response control processor. The vibration sensing processor monitors the vibration characteristics of the support platform in real time through a non-magnetic accelerometer and identifies the frequency and amplitude of external disturbances. The damping adjustment processor adjusts the damping coefficient of the air cushion or hydraulic buffer according to the vibration sensing signal to achieve adaptive suppression of vibrations in different frequency bands. The response control processor coordinates the damping output of multiple vibration isolation points to ensure that the entire support platform maintains its attitude balance during the vibration isolation process and avoids introducing additional positional offsets.

[0078] The contoured contact surface unit includes a flexible array processor, a curvature adaptation processor, and a pressure equalization processor. The flexible array processor consists of multiple independent, movable, non-magnetic elastic contacts. Each contact can independently extend and retract along the normal direction to conform to complex curved surfaces. The curvature adaptation processor automatically identifies and matches the curvature characteristics of the underwater vehicle's outer shell through the coordinated movement of the contact array, achieving continuous conformation in areas with large curvature changes. The pressure equalization processor monitors the contact pressure of each contact and adjusts it in real time to ensure uniform force on all contact points and avoid damage to the outer shell or magnetic interference caused by excessive local pressure.

[0079] The preset size library unit includes a parameter storage processor, a fast matching processor, and a configuration execution processor. The parameter storage processor has a built-in database of geometric parameters, center of gravity positions, and support point distributions for common underwater vehicle models, which can be quickly retrieved by model code. The fast matching processor automatically retrieves the optimal support configuration scheme from the database based on the input underwater vehicle model or measured size data, and generates instructions for support point positions and outrigger extension / retraction. The configuration execution processor drives each support module to automatically adjust to the target position according to the matching scheme, realizing the rapid conversion of the support system from one configuration to another.

[0080] The electronic ranging auxiliary unit includes a non-magnetic ranging processor, a coordinate calculation processor, and an alignment guidance processor. The non-magnetic ranging processor integrates a laser or ultrasonic ranging sensor to measure the spatial distance between key feature points of the underwater vehicle's hull and the support points in real time. The coordinate calculation processor establishes a three-dimensional coordinate model of the underwater vehicle in the support space based on multi-point ranging data and calculates the deviation between the current position and the ideal test position. The alignment guidance processor provides real-time guidance information on adjustment direction and adjustment amount to the operator through a display interface or indicator lights, assisting in quickly completing the precise positioning of the underwater vehicle.

[0081] The six-degree-of-freedom micro-motion platform unit includes a multi-axis drive processor, a precision control processor, and a motion coordination processor. The multi-axis drive processor integrates six independent non-magnetic linear or rotary drive mechanisms, which respectively control the X / Y / Z axis translation and the pitch / roll / yaw axis rotation. The precision control processor adopts a closed-loop feedback control strategy and achieves sub-millimeter or sub-angle level adjustment accuracy for each degree of freedom through a high-resolution position encoder. The motion coordination processor calculates the motion coupling relationship between the six degrees of freedom to ensure that no interference occurs during multi-axis synchronous motion and achieves smooth adjustment of complex spatial attitude.

[0082] The gravity compensation unit includes a load identification processor, a compensation force generation processor, and a balance maintenance processor. The load identification processor measures the actual weight and center of gravity of the underwater vehicle using a non-magnetic force sensor, providing basic data for compensation force calculation. The compensation force generation processor drives the counterweight system or pneumatic support device to generate an upward compensation force based on the load information, so that the operator only needs to overcome a small residual force when adjusting the attitude. The balance maintenance processor dynamically adjusts the magnitude and point of application of the compensation force during the attitude change of the underwater vehicle to maintain the mechanical balance of the entire adjustment process and avoid instability caused by changes in gravitational torque.

[0083] The compensation force generator calculates the dynamic compensation force required by the support point according to the following formula:

[0084] ;

[0085] ;

[0086] in, This represents the dynamic compensation force required by the j-th support point at time t. The current roll angle, The current pitch angle, For standard roll angle, Standard pitch angle, Let be the material fatigue sensitivity coefficient of the j-th support point. For payload historical memory values, The material memory time constant, For the j-th support point at a historical moment The actual supporting force;

[0087] The corrected total support force is calculated using the following formula:

[0088] ;

[0089] in, h represents the final supporting force at the j-th support point. max The threshold for saturated historical load;

[0090] The multi-point collaborative locking unit includes a distributed locking processor, a synchronous triggering processor, and a locking status monitoring processor. The distributed locking processor sets independent locking mechanisms at multiple key locations on the support platform. Each mechanism can perform locking actions independently or collaboratively. The synchronous triggering processor triggers all locking points simultaneously through a unified control signal, ensuring that the support platform achieves global rigid fixation in a very short time and avoiding attitude drift caused by step-by-step locking. The locking status monitoring processor detects the locking force and position status of each locking point in real time. Once inadequate locking or abnormal loosening is detected, an alarm is immediately triggered to ensure attitude stability during long-term testing.

[0091] The real-time attitude monitoring unit includes a multi-point attitude sensor processor, a deviation calculation processor, and an early warning output processor. The multi-point attitude sensor processor deploys non-magnetic tilt sensors or optical encoders at key locations on the underwater vehicle and support platform to collect attitude angle data from each measuring point in real time. The deviation calculation processor compares the real-time attitude data with the set standard attitude and calculates the deviation in the pitch, roll, and yaw directions. The early warning output processor, based on the deviation threshold, immediately sends an early warning signal to the testing system when the attitude deviation exceeds the allowable range, prompting the operator to perform attitude correction or suspend the test.

[0092] The deviation calculation processor calculates the comprehensive attitude error index E according to the following formula. total :

[0093] ;

[0094] ;

[0095] ;

[0096] Among them, E angle For pure angular error, E force To normalize the force distribution error, This represents the weight of the k-th degree of freedom. For the measured attitude angle, For standard attitude angles, For force-resource coupling coefficient;

[0097] The three angular degrees of freedom are, in order, roll angle, pitch angle, and yaw angle;

[0098] The magnetic field interference self-test unit includes a magnetic field probe processor, an interference identification processor, and a calibration compensation processor. The magnetic field probe processor has a high-sensitivity magnetic field sensor embedded in the key load-bearing position of the support system to continuously monitor the changes in local magnetic field strength and direction. The interference identification processor performs spectrum analysis and anomaly detection on the collected magnetic field data to identify interference sources from residual magnetism of the support structure, external electromagnetic equipment, or material magnetization. The calibration compensation processor generates compensation parameters based on the identified interference characteristics to provide a correction basis for the post-processing of magnetic field test data, or to trigger the system demagnetization procedure when the interference exceeds the standard.

[0099] The data recording and traceability unit includes a parameter acquisition processor, a data storage processor, and a traceability query processor. The parameter acquisition processor automatically records the supporting configuration parameters, attitude adjustment data, environmental monitoring information, and operation timestamps for each test, forming a complete test process dataset. The data storage processor adopts a structured database management system to associate and store test data with information such as underwater vehicle model and test task number, supporting long-term archiving and fast retrieval. The traceability query processor provides multi-dimensional data query and analysis functions, allowing users to trace historical test configurations based on test time, underwater vehicle model, or abnormal events, providing data support for quality auditing and problem investigation of test results.

[0100] The i, j, and k mentioned above are ordinal numbers used to represent sequence numbers and have no actual meaning.

[0101] This experiment employs a comparative testing method to evaluate the performance of the support system of this invention and three existing technical solutions under identical testing conditions. The experimental subject is a torpedo-shaped underwater vehicle, 6.5 meters long, 0.53 meters in diameter, and weighing approximately 3.2 tons. The testing environment is a standard magnetic field anechoic chamber, with the background magnetic field strength controlled below 50 nT and the temperature maintained at 20 ± 2℃. The four testing schemes are as follows: Scheme A uses the gradient permeability material of this invention in conjunction with the intelligent load distribution system; Scheme B uses a traditional uniform load distribution algorithm; and Scheme C uses a stress-sensing adaptive load distribution algorithm.

[0102] Preparation phase: The test chamber is demagnetized, and a high-precision fluxgate magnetometer array is used to establish a magnetic field reference value in the test area. The underwater vehicle is hoisted to the initial position of the support system to ensure that the axis of the underwater vehicle is parallel to the north-south direction of the geomagnetic field and that the pitch and roll angles are both zero.

[0103] Dynamic attitude adjustment test: The underwater vehicle underwent 10 consecutive attitude adjustments, each adjusting the pitch angle by ±5 degrees or the roll angle by ±3 degrees. The load changes at each support point and the peak value of the magnetic field disturbance were recorded during the adjustment process. Scheme A employed the historical memory mechanism of the compensating force generation processor, while other schemes used traditional compensation methods. The data was then processed to obtain... Figure 6.

[0104] Long-term stability testing: Under each scenario, the underwater vehicle was kept stationary for 8 hours. Attitude deviation and magnetic field drift were recorded hourly. Scenario A employed a force-attitude joint evaluation model using a deviation calculation processor for real-time monitoring. The data was then processed to obtain... Figure 7 .

[0105] Example 2.

[0106] An adjustable non-magnetic support system for underwater target magnetic field testing includes a non-magnetic load-bearing and vibration isolation module, an adaptive size matching module, a precise attitude control module, and a test status monitoring module. This embodiment is designed to adapt to a certain type of medium-sized torpedo-shaped underwater vehicle. The underwater vehicle is 5800mm long, has a maximum diameter of 480mm, and weighs approximately 2600kg. The test environment is a double-layer permalloy magnetic shielding chamber with a magnetic shielding coefficient of 80dB and an indoor background magnetic field strength of less than 30nT.

[0107] The graded load-bearing frame unit in the non-magnetic load-bearing and vibration isolation module uses Nitronic 60 non-magnetic stainless steel (magnetic permeability μr≤1.003) as the main load-bearing frame material. This material has a yield strength of 414MPa and excellent corrosion resistance. The frame adopts an I-beam design with a cross-sectional dimension of 120mm×80mm, a web thickness of 8mm, a flange width of 80mm, and a flange thickness of 12mm. Finite element analysis verifies that under a load of 3000kg, the maximum stress is only 185MPa, the maximum deformation is 0.85mm, and the safety factor reaches 2.24. The frame beam length is designed in two standard modular unit specifications of 1500mm and 1000mm, which can be combined to meet the support requirements of underwater vehicles of different lengths from 3500mm to 8000mm through modular combination. The connection nodes use NAS1149 series titanium alloy fixed shaft pins (Ti-6Al-4V). ELI (with a permeability μr ≤ 1.0005) is used in conjunction with M16 titanium alloy fastening bolts. Each connection node is equipped with four fixed-axis pins to ensure positioning accuracy within ±0.05mm. The fastening bolts are controlled with a torque wrench to maintain a pre-tightening torque of 85N·m ± 5N·m, ensuring connection rigidity while avoiding localized magnetization caused by stress concentration. The load distribution processor evenly distributes support positions below eight support points. The support points are spaced 700mm ± 20mm apart along the axial direction of the underwater vehicle. The circumferential positions are distributed at 0 degrees, 45 degrees, 135 degrees, 180 degrees, 225 degrees, and 315 degrees on the front, middle, and rear sections, forming a stable structure. The triangular support configuration is equipped with a U10M type three-dimensional force sensor (range 0-5kN, accuracy class 0.05%FS) at each support point. It monitors the force components in each direction in real time and transmits them to the control system via CAN bus. The control system sampling frequency is set to 100Hz to capture dynamic load changes. It calculates the load distribution variance of each support point based on the real-time force data. When the variance exceeds the set threshold of 150N², it triggers an automatic adjustment program. The load is redistributed by adjusting the height adjustment mechanism under each support point, so that the load distribution variance is controlled within 80N². Compared with the traditional fixed support point scheme, the load distribution uniformity is improved by 42%.

[0108] The magnetic field transparent buffer unit adopts a three-layer gradient composite structure design. The inner layer, in contact with the underwater vehicle hull, is made of Ultrason E series polyethersulfone (PES, magnetic permeability μr=1.042, elastic modulus 2600MPa, density 1.37g / cm³), with a thickness of 6mm±0.2mm. This layer provides the main load-bearing function and has excellent creep resistance. The middle layer is made of TPX polymethylpentene (magnetic permeability μr=1.018, elastic modulus 1200MPa, density 0.83g / cm³), with a thickness of 10mm±0.3mm. This layer acts as a transition buffer and further reduces magnetic field disturbance. The outer layer, in contact with the skeleton, is made of Delrin500CL polyoxymethylene (magnetic permeability μr=1.008, elastic modulus 3100MPa, density 1.42g / cm³), with a thickness of 8mm±0.2mm. This layer provides a rigid support foundation. The three layers are connected by Loctite. 406 non-magnetic fast-drying adhesive (magnetic permeability μr ≤ 1.002 after curing) is used for interlayer bonding, achieving a bond strength of over 12MPa to ensure no delamination during use. A thickness optimization processor dynamically adjusts the thickness ratio of each layer based on actual test loads. When the underwater vehicle weighs less than 1500kg, the inner layer thickness is reduced to 4mm and the middle layer increased to 12mm to prioritize magnetic field transparency. When the underwater vehicle weighs over 4000kg, the inner layer thickness is increased to 8mm and the outer layer increased to 10mm to enhance load-bearing capacity. This is achieved using the magnetic field simulation software Ansys. Maxwell established a three-dimensional magnetic field model of a three-layer structure. Simulation results showed that under a pressure of 3000N, the magnetic field disturbance of the gradient structure at a distance of 500mm from the support point was 2.8nT, which is 47.2% lower than the 5.3nT of a single-material structure. The contact surface distribution processor dispersed the buffer material into 12 discrete contact areas, each with an area of ​​80mm×60mm. The area was processed into a rectangular block with an edge chamfer of R2 using laser cutting technology. The contact areas were pre-shaped according to the curvature of the underwater vehicle to ensure that the initial contact angle error was less than 2 degrees. The discrete contact design kept the proportion of the actual contact area with the underwater vehicle to the total projected area below 35%, minimizing the magnetic field interference path while ensuring sufficient support stability. The measured data showed that this design reduced magnetic field interference by 28% and the peak contact pressure by 41% compared to the continuous contact method.

[0109] The active vibration isolation unit uses BE-SL series pneumatic vibration isolators. Each isolator has an adjustable load capacity of 500-1500 kg, a natural frequency of 1.2 Hz, and an isolation efficiency exceeding 95% in the frequency range above 5 Hz. One isolator is configured below each of the eight main support points to form a distributed vibration isolation system. The vibration sensing processor uses a 4507-B-004 type triaxial accelerometer (frequency range 0.3-8000 Hz, sensitivity 10 mV / g, background noise 0.15 mg). The sensor is fixed to five measuring points on the support platform—four corners and the center—using M5 titanium alloy bolts, forming a complete monitoring network for the spatial vibration field. The data acquisition system uses a cDAQ-9174 chassis with a 9234 type dynamic signal acquisition module, with a sampling rate set to 25.6 kHz to accurately capture high-frequency vibration components. The damping adjustment processor performs spectral analysis based on the real-time vibration signal. When a low-frequency vibration amplitude exceeding 0.02 Hz is detected, the damping adjustment processor... At time g, the air pressure of the pneumatic vibration isolator is increased from 0.4MPa to 0.6MPa by adjusting the electromagnetic proportional valve to improve the damping coefficient. When mid-frequency vibration in the 50-200Hz range is detected, the active control algorithm is activated to generate reverse excitation through the piezoelectric ceramic actuator to achieve vibration cancellation. The response control processor adopts a fuzzy PID control strategy to coordinate the damping output of the eight vibration isolation points. By setting the membership function, the vibration amplitude is divided into three levels: small, medium, and large, and the PID parameters are adjusted accordingly. This achieves that the tilt angle of the support platform is controlled within 0.15mrad during the vibration isolation process. Compared with the traditional passive vibration isolation system, the vibration isolation efficiency is improved by 35% and the attitude stability is improved by 2.8 times. The measured data shows that when the external ground vibration excitation amplitude is 0.08g, the vibration amplitude transmitted to the underwater vehicle support platform after passing through the vibration isolation system is reduced to 0.003g. The corresponding magnetic field measurement noise is reduced from 4.5nT to 0.8nT, which meets the strict requirements of high-precision magnetic field testing for vibration environment.

[0110] The flexible array processor of the contoured contact surface unit consists of 48 independent movable contacts arranged in a 6×8 matrix. Each contact is driven by a DGST-12-30-EA type miniature rodless cylinder with a stroke of 30mm, a thrust of up to 120N, and a positioning accuracy of ±0.05mm. The contact head uses an ultra-high molecular weight polyethylene spherical contact head (diameter 25mm, magnetic permeability μr≤1.002, Shore D60 hardness). The spherical design allows the contact to adapt to angular deviations within a range of ±15 degrees. The curvature adaptation processor performs a three-dimensional scan of the underwater vehicle's outer shell using an LMS511-10100 laser contour scanner (measurement range 0-80m, angular resolution 0.1667 degrees, distance resolution ±15mm). The scanned data point cloud density reaches more than 5000 points per square meter. MATLAB software is used for point cloud processing and surface reconstruction, extracting local curvature radii and calculating the optimal contact position and angle for each contact. The entire scanning and recognition process... Completed within 45 seconds, this method is more than 10 times more efficient than manual measurement. The pressure equalization processor integrates a PHS-2KA miniature pressure sensor (range 0-2kN, diameter 8mm, thickness 1.5mm, accuracy 0.3%FS) at each contact point. The sensor signal is transmitted to the control system after being converted by a 16-bit ADC. The control algorithm adopts an iterative learning control strategy. First, the target contact pressure of each contact point is set to 50N±5N. Then, the pressure closed-loop control is achieved by adjusting the air supply pressure of the cylinder at each contact point. The iterative convergence time is less than 8 seconds, and the standard deviation of the pressure at each contact point after convergence is less than 3.2N. The pressure uniformity is improved by 68% compared to open-loop control. Actual tests show that this contour-following contact system can adapt to different underwater vehicle shapes with curvature radii ranging from 200mm to 5000mm. It can still achieve good fit for complex hyperboloid structures such as the bow transition section of underwater vehicles. The uniformity of contact pressure distribution reduces magnetic field disturbances caused by local stress concentration by 54%.

[0111] The parameter storage processor of the preset size library unit adopts an embedded SQLite database system. The database capacity supports storing geometric parameters, mass characteristics, and support configuration schemes for more than 200 underwater vehicle models. Each model's data includes 36 parameters, including overall length, maximum diameter, bow length, parallel midbody length, stern length, longitudinal position of center of gravity, lateral offset of center of gravity, height of center of gravity, three-axis components of moment of inertia, shell material, and typical test attitude. The data structure adopts JSON format for easy expansion and maintenance. The fast matching processor uses a weighted nearest neighbor algorithm for model matching. When the length L and diameter D of a new underwater vehicle are input, the similarity score S with each model in the database is calculated as S=1 / sqrt[(L-Li)² / σL²+(D-Di)² / σD²], where σL and σD are the normalization coefficients for length and diameter, respectively, set to 500mm and 50mm. The three similar models with the highest scores are selected for parameter interpolation calculation to generate the initial support configuration. The configuration scheme includes 12 configuration parameters such as the number of support points, axial spacing, circumferential distribution angle, and expected load distribution. The entire matching calculation process is completed within 0.3 seconds. The configuration execution processor controls eight 17-series hollow cup stepper motors (step angle 0.9 degrees, holding torque 0.8 N·m) through an EL7041 stepper motor drive module. The stepper motors drive the support arms to extend and retract through ball screw pairs (lead 5 mm, accuracy grade C5). The extension and retraction range is 150 mm to 450 mm, and the positioning accuracy reaches ±0.1 mm. The motor control adopts a trapezoidal acceleration and deceleration curve, with the maximum speed set to 50 mm / s and the acceleration to 300 mm / s². The average time for the eight support arms to adjust from the initial position to the target configuration is 18 seconds, which is more than 8 times more efficient and 5 times more accurate in repeatability than manual adjustment. Practical application shows that this automatic configuration system can complete the complete switch from one type of underwater vehicle to another within 5 minutes, which greatly improves the utilization rate of the test facility.

[0112] The non-magnetic ranging processor of the electronic ranging auxiliary unit uses a Disto D810 handheld laser rangefinder (range 0.05-200m, accuracy ±1mm, laser wavelength 635nm, laser safety level 2). The rangefinder is fixed at three reference positions on the support system via a non-magnetic aluminum alloy bracket. It works in conjunction with a GLL3-330CG green light projector (accuracy ±0.1mm / m, working distance 30m, automatic leveling accuracy ±0.2 degrees) to establish a three-dimensional spatial measurement reference. The coordinate calculation processor uses a spatial multi-point positioning algorithm. By measuring the distances from at least six feature points on the underwater vehicle's hull (typically the bow tip, stern tip, and four circumferential reference points on the parallel midbody section) to the three reference rangefinders, an overdetermined equation system is established, and the least squares method is used to solve for the underwater vehicle's spatial position and attitude. The calculation accuracy reaches a position deviation of ±0.5mm and an angle deviation of ±0.05 degrees. The alignment guidance processor... The G121SN01 12.1-inch industrial display screen (800×600 resolution, 450cd / m² brightness) displays the deviation between the current position and the target position of the underwater vehicle in real time. The display interface adopts the Qt development framework and displays the underwater vehicle model and target position in a three-dimensional graphical manner. Different colors are used to indicate the six degrees of freedom deviation: green indicates a deviation of less than 0.2mm or 0.05 degrees, yellow indicates a deviation of 0.2-0.5mm or 0.05-0.1 degrees, and red indicates a deviation of more than 0.5mm or 0.1 degrees. At the same time, numerical values ​​and arrows indicate the adjustment direction and adjustment amount. The operator can manually fine-tune or start the automatic adjustment program according to the interface guidance. Actual tests show that this ranging assistance system reduces the underwater vehicle alignment time from the traditional 25 minutes to 8 minutes, and increases the first alignment success rate from 62% to 95%.

[0113] The multi-axis drive processor of the six-degree-of-freedom micro-motion platform unit uses ETB series electric cylinders (model ETB34-050-32-MCAC, stroke 127mm, thrust 4450N, speed adjustable from 0.02-300mm / s, repeatability ±0.01mm). The six electric cylinders are arranged according to the Stewart platform configuration, connecting the moving platform and the stationary platform via ball joints. The moving platform measures 1200mm × 800mm and is made of 7075-T6 aluminum alloy, while the stationary platform measures 1600mm × 1200mm and uses a cast iron welded structure. The precision control processor uses MINAS. The A6 series servo drive (model MBDLN25SG, control cycle 125μs, encoder resolution 23-bit absolute) connects to the CX5140 embedded controller via EtherCAT bus. The control cycle is set to 1ms to achieve real-time coordinated control of six degrees of freedom. Position feedback uses a LIF481R linear encoder (resolution 0.001mm, accuracy ±1μm, measurement length 150mm). Angle measurement uses a TM6100A total station (angle measurement accuracy 0.5 seconds, prism-free distance measurement accuracy 2mm+2ppm). The motion coprocessor employs an inverse kinematics algorithm based on the Jacobian matrix to decompose the six-degree-of-freedom pose changes into the lengths of six electric cylinders. The system avoids kinematic singularities through singular value decomposition and uses S-shaped acceleration / deceleration curves in motion planning to ensure smooth, shock-free motion. The maximum translational speed is set to 5 mm / s and the maximum rotational speed is set to 0.5 degrees / s. At these speeds, the positioning time for a single attitude adjustment is 15-25 seconds. The position repeatability after positioning is ±0.015 mm and the angle repeatability is ±0.008 degrees, which is more than 30 times higher than the ±0.5 mm and ±0.2 degree accuracy of traditional manual adjustments. In practical applications, this micro-motion platform can achieve a translational range of ±50 mm in each of the X / Y / Z directions and a rotational range of ±8 degrees in each of the roll / pitch / yaw directions. The workspace covers all typical attitude requirements for magnetic field testing of underwater vehicles.

[0114] The load identification processor of the gravity compensation unit uses a PR6201 weighing platform (range 0-6000kg, accuracy 5kg, platform size 1200mm×1200mm). The weighing platform integrates four H200C3MK shear beam load cells, and outputs a standard 4-20mA signal through a PR5410 weighing transmitter. The center of gravity position is calculated using the torque balance method by measuring the load distribution of the underwater vehicle under different support configurations. The longitudinal position accuracy of the center of gravity reaches ±20mm, and the transverse position accuracy reaches ±20mm. The directional and vertical accuracy reaches ±10mm. The compensating force generator adopts a pneumatic counterweight system, which consists of eight DGPL-63-800-PPV-A-KF-B type rodless cylinders (63mm diameter, 800mm stroke, theoretical thrust 2980N@6bar). The cylinders are vertically mounted above each support point and connected to the underwater vehicle's support attachment points via flexible steel wire ropes. The cylinder air supply pressure is controlled by a VPPM series proportional pressure reducing valve (control range 0-10bar, resolution 0.01bar). The system precisely adjusts the load (with a hysteresis of less than 0.15%) and calculates the required output force of each cylinder in real time based on the load identification result and the current attitude angle. The compensation force is continuously adjustable by adjusting the air supply pressure. Compared with the traditional fixed counterweight method, this design has better dynamic adaptability. The balance maintenance processor adopts an incremental PID control algorithm. It compares the real-time load data fed back by the force sensor with the target compensation force and calculates the PID output to control the opening of the proportional pressure reducing valve. The control parameters are set as proportional coefficient Kp=0.15, integral coefficient Ki=0.008, derivative coefficient Kd=0.025, and control cycle 20ms. This control system can control the residual load fluctuation of each support point within ±50N during attitude changes. The force required for manual attitude adjustment by the operator is reduced from 300-500N to 80-120N. The difficulty of attitude adjustment is significantly reduced and the safety is greatly improved. The measured data shows that after adopting gravity compensation, the attitude adjustment time is shortened by 55%, the adjustment accuracy is improved by 40%, and the operator fatigue is reduced by 70%.

[0115] The distributed locking processor of the multi-point collaborative locking unit is equipped with a VERO-SNSE3 138 type quick locking device (locking force 25kN, repeatability 0.005mm, locking time 0.15 seconds, unlocking time 0.1 seconds) at each of the eight support points. The locking device adopts pneumatic drive with a working pressure of 6bar and uses a wedge-shaped self-locking mechanism to achieve mechanical retention after air cut-off to ensure safety. The synchronous trigger processor adopts a CPV14 series bus-type pneumatic island (model CPV14-GE-MP-8, integrating 8 solenoid valves, response time 5ms, supporting Profinet and EtherCAT communication). Through hardware synchronous trigger signal, the eight locking points are synchronized within a 10ms time window. The synchronization accuracy is more than 8 times higher than that of distributed control, effectively avoiding attitude drift caused by step locking. The locking status monitoring processor integrates a proximity switch and a pressure sensor at each locking point for dual monitoring. The proximity switch adopts BES. The M18MI-PSC80B-S04G inductive proximity switch (8mm detection distance, 0.01mm repeatability, 1500Hz response frequency) detects the locking position. The pressure sensor uses a PN7006 pressure transmitter (0-400bar range, 0.5%FS accuracy, 5ms response time) to monitor the locking air pressure. When the pressure is lower than the set threshold of 5.5bar or the proximity switch fails to detect the locking position signal, an audible and visual alarm is immediately triggered, and the fault location is displayed on the control interface. At the same time, the fault time and support point number are automatically recorded for subsequent analysis. This dual monitoring mechanism ensures that the reliability of the locking state reaches 99.98%. In an actual 8-hour stability test, the attitude maintenance accuracy of each support point was ±0.08mrad for roll angle, ±0.10mrad for pitch angle, and ±0.12mrad for yaw angle, which is 4.5 times more stable than the traditional manual locking method.

[0116] The multi-point attitude sensing processor of the attitude real-time monitoring unit is equipped with five STIM300 fiber optic gyroscope inertial measurement units (gyroscope zero-bias stability 0.3 degrees / hour, accelerometer zero-bias stability 10 μg, angle random walk 0.15 degrees / √h, data update rate 125Hz) on the underwater vehicle. The sensors transmit data to a MIC-7700 fanless embedded industrial computer (Intel Core i7 processor, 8GB memory, 128GB RAM) via an RS422 interface. The industrial control computer runs real-time data processing software based on the Ubuntu system. The deviation calculation processor uses an extended Kalman filter algorithm to fuse multi-sensor data. It establishes a 15-dimensional state space model of the underwater vehicle (including 3D position, 3D velocity, 3D attitude, 3D gyro bias, and 3D accelerometer bias) to perform optimal state estimation. The filtering period is 10ms, and the attitude calculation accuracy reaches ±0.05 degrees for roll and pitch, and ±0.08 degrees for yaw, which is 3 times higher than the accuracy of a single sensor. The warning output processor sets three levels of alarm thresholds. The first level of warning threshold is when the attitude deviation exceeds 0.2 degrees for 10 seconds. The above triggers a yellow warning light and an alarm sound. The second-level warning threshold is triggered when the attitude deviation exceeds 0.5 degrees or the rate of change of deviation exceeds 0.05 degrees / minute, triggering an orange warning light and a buzzer. The third-level warning threshold is triggered when the attitude deviation exceeds 1 degree, triggering a red warning light, a buzzer, and an automatic pause test command. The warning information is also sent to the test manager's mobile phone via SMS. This graded warning mechanism reduces the response time for attitude abnormalities from the traditional 5-10 minutes to less than 10 seconds, avoiding invalid test data caused by attitude deviations. Actual application statistics show that the test data validity rate has increased from 82% to 96.5% after adopting this monitoring system.

[0117] The magnetic field probe processor of the self-test unit for magnetic field interference uses an MFS-07e high-precision fluxgate magnetometer (sensitivity 0.01nT, range ±100μT, frequency range DC-1kHz, temperature coefficient 0.05nT / ℃). One magnetometer is placed near each of the eight main support points to form a distributed monitoring network. The magnetometers are fixed 200mm from the support points by non-magnetic carbon fiber supports. The supports are made of T700 grade carbon fiber prepreg with a laminate thickness of 3mm and a permeability μr ≤ 1.0003. The magnetometer signal... The signal is transmitted via shielded twisted-pair cable to the Mag-03MCL100 magnetometer control unit. The control unit provides a ±15V regulated power supply and a 24-bit ADC sampling rate set to 250Hz. The interference identification processor uses a fast Fourier transform algorithm to perform spectral analysis on the magnetic field data, covering a frequency band of 0.1Hz-100Hz. By setting a background noise baseline and an anomaly detection threshold (set to 5 times the root mean square value of the background noise), interference events are automatically identified. When 50Hz and its harmonic components are detected, it is determined to be external AC electromagnetic field interference. When a low-frequency drift trend is detected, it is determined to be a change in remanence caused by temperature change or material creep. When a transient spike signal is detected, it is determined to be the movement of an external ferromagnetic object or the switching action of electrical equipment. The accuracy of the identification algorithm reaches 92%. The calibration compensation processor calls the corresponding compensation algorithm according to the identified interference type. For periodic electromagnetic interference, an adaptive notch filter is used for frequency domain compensation; for slowly varying drift, a polynomial fitting is used for time domain detrending processing; and for transient interference, median filtering is used to remove outliers. The compensated magnetic field measurement noise is reduced from... The magnetic field strength is reduced from 3.5nT to 1.2nT. Simultaneously, when the magnetic field disturbance at any measuring point exceeds 20nT for more than 5 seconds, the demagnetization program is automatically triggered. The demagnetization program generates a gradually decaying alternating magnetic field by using demagnetizing coils (20 turns, 600mm in diameter, with decaying AC current) arranged around the support frame. The initial amplitude of the demagnetizing current is 5A and the frequency is 50Hz. It decays to zero within 90 seconds at a rate of 10% every 5 seconds. After demagnetization, the residual magnetism level of the support system can be reduced from 15-20nT to 3-5nT, meeting the requirements for high-precision magnetic field testing.

[0118] The parameter acquisition processor of the data recording and traceability unit uniformly collects data from all sensors and controllers via the OPC UA protocol. The data types include approximately 200 channels: three-dimensional force data from 8 support points, data from 8 magnetic field probes, data from 5 attitude sensors, pressure data from 8 pneumatic cylinders, position and pressure data from 48 contact points, position data from 6 electric cylinders, data from 5 vibration sensors, and data from 2 temperature and humidity sensors. The sampling frequency is divided into a 100Hz fast channel (force and magnetic field data), a 10Hz medium-speed channel (position and attitude data), and a 1Hz slow channel (temperature and configuration parameters) based on data characteristics. The data storage processor uses a CX5240 embedded controller (Intel Core i7 processor, 16GB memory, 1TB SSD) running TwinCAT 3 real-time control software, and the database system uses PostgreSQL. Version 14 supports efficient storage and querying of time-series data. The database adopts a time-partitioned table structure, automatically creating new partitions every 24 hours. Historical data is automatically archived to a network storage server (50TB capacity, RAID6 array) after 180 days. The data record format adopts the industry standard HDF5 format, supporting data compression and fast random access. The data file size of a single test is approximately 2-5GB. The traceability query processor provides a web-based query interface, developed using the Python Django framework. It supports combined queries by multiple dimensions such as test date, underwater vehicle model, test personnel, task number, and data type. Query results can be displayed in real time in chart form or exported to various formats such as Excel, CSV, and PDF. The system also provides a data comparison function, which can overlay data from different test batches for easy analysis of performance change trends. The traceability query response time is less than 3 seconds, and the annual test data volume of approximately 25TB can be fully searched within 30 seconds. This data system has passed ISO 9001 quality management system certification and GJB9001C military quality management system audit, and the data integrity and traceability meet the requirements of aerospace testing standards.

[0119] The content disclosed above is only a preferred and feasible embodiment of the present invention, and is not intended to limit the scope of protection of the present invention. Therefore, all equivalent technical changes made based on the content of the present invention specification and drawings are included within the scope of protection of the present invention. Furthermore, the elements therein can be updated as technology develops.

Claims

1. An adjustable non-magnetic support system for underwater target magnetic field testing, characterized in that, The module comprises a non-magnetic bearing and vibration isolation module, an adaptive size matching module, an attitude precise control module and a test state monitoring module. The non-magnetic bearing and vibration isolation module is used for providing stable support with zero magnetic pollution and isolating external vibration interference, the adaptive size matching module is used for realizing quick universal adaptation of different types of underwater vehicles, the attitude precise control module is used for completing six-degree-of-freedom precise positioning of the underwater vehicle in the test space, and the test state monitoring module is used for monitoring the support state in real time and guaranteeing test data quality. The non-magnetic bearing and vibration isolation module comprises a hierarchical bearing framework unit, a magnetic field transparent buffer unit and an active vibration isolation unit, the hierarchical bearing framework unit is used for completing bearing frame configuration and providing system main bearing support, the magnetic field transparent buffer unit is used for realizing mechanical bearing while not interfering with the magnetic field distribution characteristics of the test area, and the active vibration isolation unit is integrated for isolating the influence of ground vibration and external disturbance on high-precision magnetic field measurement. The adaptive size matching module comprises a profiled contact surface unit, a preset size library unit and an electronic distance measurement auxiliary unit, the profiled contact surface unit adopts a flexible non-magnetic material array structure to adapt to diversified shell shapes, the preset size library unit is used for realizing quick calling of support configuration through type coding, and the electronic distance measurement auxiliary unit is used for assisting the operator to quickly complete spatial positioning and support point alignment of the underwater vehicle. The attitude precise control module comprises a six-degree-of-freedom micro-motion platform unit, a gravity compensation unit and a multi-point cooperative locking unit, the six-degree-of-freedom micro-motion platform unit is used for realizing sub-millimeter level attitude precise adjustment of the underwater vehicle in the test space, the gravity compensation unit is used for reducing the operation force demand in the attitude adjustment process, and the multi-point cooperative locking unit is used for realizing global rigid locking of the support platform after the attitude adjustment is completed. The test state monitoring module comprises an attitude real-time monitoring unit, a magnetic field interference self-checking unit and a data recording and tracing unit, the attitude real-time monitoring unit is used for feeding back the attitude deviation amount of the underwater vehicle in real time, the magnetic field interference self-checking unit is used for continuously monitoring the residual magnetism level and external magnetic field interference of the support structure, and the data recording and tracing unit automatically records the support configuration parameters, attitude adjustment data and environmental monitoring information of each test.

2. The adjustable non-magnetic support system for underwater object magnetic field testing of claim 1, wherein, The magnetic field transparent buffer unit comprises a gradient material processor, a thickness optimization processor and a contact surface distribution processor, the gradient material processor adopts a composite material layer with magnetic permeability gradually decreasing from inside to outside, and keeps the minimum disturbance to the magnetic field of the test area when pressure is borne, the thickness optimization processor dynamically determines the optimal thickness configuration of the buffer layer according to the bearing load and magnetic field transparency requirement, and balances the mechanical performance and magnetic performance, and the contact surface distribution processor dispersely arranges the buffer material in multiple discrete contact areas. The relative magnetic permeability and thickness of each layer in the gradient material processor are calculated according to the following formula: ； ； wherein, μri represents the relative permeability of the i-th layer, μb represents the permeability of the base material, μ0 represents the permeability of air, and n represents the total number of the buffer layers, η represents the gradient index, di represents the thickness of the i-th layer, d represents the total thickness of the buffer layers, Ei represents the elastic modulus of the i-th layer; The magnetic permeability, thickness and density are integrated into a single characteristic value through the following formula: ； wherein, represents the magnetic coupling characteristic parameter of the i-th layer, is the material density of the i-th layer.

3. The adjustable non-magnetic support system for underwater object magnetic field testing of claim 2, wherein, The hierarchical load-bearing skeleton unit comprises a modular skeleton processor, a connecting node processor and a load distribution processor, the modular skeleton processor realizes the balance between light weight and high strength through an I-shaped or cellular cross-section design, the connecting node processor uses a non-magnetic fixed shaft pin and a non-magnetic fastener to form a multi-point connecting system, and the load distribution processor optimizes the spatial layout of discrete support points to uniformly disperse the gravity of the underwater vehicle to each load-bearing node; The load distribution processor calculates the initial distribution load of each support point according to the following formula: ； ； wherein, M is the initial assigned load for the jth support point, M is the mass of the underwater vehicle, g is the gravitational acceleration, and m is the total number of support points, is the material characteristic response coefficient, is the effective magnetic force coupling parameter for the jth support point location, is the average magnetic force coupling parameter for all support point locations, is the contact area for the jth support point, is the contact efficiency coefficient for the ith layer of material.

4. The adjustable non-magnetic support system for underwater object magnetic field testing of claim 3, wherein, The gravity compensation unit comprises a load identification processor, a compensation force generation processor and a balance maintenance processor, the load identification processor measures the actual weight and the center of gravity position of the underwater vehicle through a non-magnetic force sensor to provide basic data for compensation force calculation, the compensation force generation processor is used to generate upward compensation force, and the balance maintenance processor dynamically adjusts the size and action point of the compensation force during the attitude change of the underwater vehicle; The compensation force generation processor calculates the dynamic compensation force required by the support point according to the following formula: ； ； wherein, represents the dynamic compensation force required by the jth support point at time t, is the current roll angle, is the current pitch angle, is the standard roll angle, is the standard pitch angle, is the material fatigue sensitivity coefficient of the jth support point, is the load history memory value, is the material memory time constant, is the actual support force of the jth support point at the historical time t, is the actual support force of the jth support point at the historical time t. The corrected total support force is calculated according to the following formula: ； wherein, is the final support force for the jth support point, h max is a saturation history load threshold.

5. The adjustable non-magnetic support system for underwater object magnetic field testing of claim 4, wherein, The attitude real-time monitoring unit comprises a multi-point attitude sensing processor, a deviation calculation processor and a early warning output processor, the multi-point attitude sensing processor is used to collect the attitude angle data of each measuring point in real time, the deviation calculation processor compares the real-time attitude data with the set standard attitude to calculate the deviation amount in three directions of pitch, roll and yaw, and the early warning output processor sends an early warning signal to the test system to prompt the operator to correct the attitude or pause the test when the attitude deviation exceeds the allowed range according to the deviation threshold setting; The deviation calculation processor calculates the integrated attitude error index E according to the following equation total : ； ； ； where E angle is the pure angular error, E force is the normalized force distribution error, denotes the weight of the kth angular degree of freedom, is the measured attitude angle, is the standard attitude angle, is the force coupling coefficient.

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