A method and device for automatically positioning the underwater depth of a test bar

Abstract

The application discloses a kind of test measuring rod underwater depth automatic positioning method and device, specifically relates to underwater detection technical field;By integrating pressure sensor, sonar ranging module and inertial navigation unit on measuring rod, in combination with the temperature-salinity-depth sensor data obtained in real time, dynamic correction pressure depth conversion result is generated high-precision target water depth value by data fusion, simultaneously, system utilizes inertial navigation information and target depth variation trend, using fuzzy logic control method, the real-time self-adapting adjustment of measuring rod posture and depth position is realized, the positioning precision and environmental adaptability of the method effectively improve underwater measuring rod in complex layered water body, with good practicality and innovation.

Description

Technical Field

[0001] This invention relates to the field of underwater exploration technology, specifically to an automatic underwater depth positioning method and device for a test probe. Background Technology

[0002] Automatic underwater depth positioning of a test probe refers to the ability of an automated system to precisely determine the position and depth of a test probe during underwater testing or measurement. This technology typically combines sensors, control systems, and positioning algorithms to monitor changes in the probe's depth in the water in real time and automatically adjust or record its position, avoiding human error and improving the accuracy and efficiency of measurements. It is widely used in underwater exploration, engineering testing, and scientific research.

[0003] In existing technologies, positioning accuracy and robustness are improved by fusing multiple sensing methods. For example, pressure sensors are combined with sonar, or INS is combined with GPS (when on the surface), and then the measuring rod is adjusted in real time and automatically fed back through a control system to achieve automated and continuous measurement and control of underwater depth.

[0004] The existing technology has the following shortcomings:

[0005] In environments with thermocline-salinity stratification, such as oceans or deep lakes, pressure sensors, assuming a constant water density, are prone to depth calculation errors at thermoclines or haloclines. When there are significant density differences between the upper and lower layers, the same pressure value may correspond to different water depths, causing the actual position of the probe to deviate from the calculated result by 0.5 to 2 meters, severely impacting underwater positioning accuracy. Furthermore, this error problem is particularly pronounced in systems without CTD (conductivity, temperature, and depth) sensors, often increasing system complexity and affecting the accuracy of scientific research or engineering operations. Summary of the Invention

[0006] The purpose of this invention is to provide an automatic underwater depth positioning method and device for a test probe, so as to overcome the shortcomings of the prior art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an automatic underwater depth positioning method for a test measuring rod, comprising:

[0008] A pressure sensor, a sonar ranging module, and an inertial navigation unit are integrated on the test probe to acquire the probe's current underwater pressure data, relative depth distance, and motion status information in real time.

[0009] A temperature, salinity, and depth sensor is further integrated into the measuring rod to monitor the changes in temperature, salinity, and density at the current location of the water body in real time and obtain the actual water density data at the current location.

[0010] The actual water density data is input into the pressure sensor depth conversion module, and the pressure depth data corresponding to the original pressure value output by the pressure sensor is dynamically corrected based on the actual water density data.

[0011] The relative depth data obtained by the sonar ranging module is compared and fused with the corrected pressure depth data to generate the target water depth value.

[0012] By combining the changing trends of motion state information provided by the inertial navigation unit and the target water depth value, the attitude and depth position of the test probe are adjusted in real time through the control system.

[0013] Preferably, the pressure sensor is used to collect the hydrostatic pressure value corresponding to the water depth position of the measuring rod in real time, the sonar ranging module calculates the relative distance between the measuring rod and the water surface or bottom through the sound wave propagation time, and the inertial navigation unit includes a three-axis accelerometer, a three-axis gyroscope and a magnetometer, used to obtain the acceleration, angular velocity and attitude angle of the measuring rod in three-dimensional space, and to deduce motion trend information.

[0014] Preferably, the temperature, salinity, and depth sensor includes a temperature acquisition unit, a salinity acquisition unit, and a pressure acquisition unit. It calculates the water density based on temperature and salinity parameters and transmits the density data to the pressure-depth conversion module via a standard communication protocol.

[0015] Preferably, the pressure-depth conversion module further calculates a depth correction coefficient based on the obtained water compressibility and the change value of sound velocity in the water, and performs nonlinear correction on the initial water depth corresponding to the original pressure value, and outputs the corrected water depth data.

[0016] Preferably, the water compressibility is obtained by calculating the bulk modulus of pure water using a fourth-order polynomial based on the collected water temperature data, and using this as the benchmark bulk modulus. Based on the water temperature, correction terms A and B related to salinity are calculated: A is the linear salinity correction term, and B is the squared salinity correction term. After combining A and B with the salinity value, the basic bulk modulus of the saline body is obtained. Water compressibility is the basic bulk modulus. The reciprocal of.

[0017] Preferably, the method for obtaining the change value of sound velocity in water is as follows: The practical salinity (SP), original temperature (t), and water depth pressure (p) are collected on-site using a temperature, salinity, and depth sensor. These are then converted into absolute salinity (SA) and conservative temperature (CT) using the conversion algorithm in the GSW model. This includes using the salinity conversion function in the GSW model, substituting the input SP, p, latitude, and longitude to obtain the corresponding SA; converting the original measured water temperature into conservative temperature (CT) using the GSW model, with the conversion function taking SA, t, and p as input and outputting CT; and inputting the converted parameters SA, CT, and p into the sound velocity calculation function of the GSW model to obtain the isothermal compressibility. The speed of sound is derived internally from the thermodynamic derivative of Gibbs free energy in the GSW model.

[0018] Preferably, a water depth correction coefficient is calculated based on the obtained changes in sound velocity in water and water compressibility. The changes in sound velocity in water and water compressibility are directly proportional to the water depth correction coefficient. The original pressure value P output by the pressure sensor in real time and the obtained actual water density ρ are input together to the conversion module to calculate the corrected water depth value.

[0019] Preferably, the real-time acquired sonar data and corrected pressure data are normalized to be within the range [0,1]. The normalized sonar data and corrected pressure data are then weighted and averaged to generate a normalized target water depth value. Finally, the normalized target water depth value is denormalized to restore the actual target water depth value. .

[0020] Preferably, fuzzy logic reasoning is used to dynamically generate control commands for the test probe. The fuzzy controller takes the changing trend of motion state information and the target water depth as input items, and takes the probe attitude adjustment amount and depth position correction amount as output items.

[0021] The motion state information provided by the inertial navigation unit and the deviation between the fused target water depth value and the current water depth are converted into fuzzy linguistic variables.

[0022] Based on the fuzzification result of the current input variables, match the rules that meet the conditions in the fuzzy rule base and perform fuzzy inference operations;

[0023] The reasoning process uses the Mamdani fuzzy reasoning method, which fuzzily synthesizes the output results of multiple rules that meet the conditions to form a fuzzy set of output variables;

[0024] When multiple rules are activated simultaneously, the output set will be a union of multiple fuzzy outputs;

[0025] The fuzzy output set is converted into control variables through a defuzzification process, which are used to drive the control system to perform specific adjustment actions. Defuzzification methods include the centroid method, and the result is a weighted average of all output membership functions multiplied by their values.

[0026] The final control quantity is sent as a command signal to the attitude adjustment mechanism and depth adjustment mechanism on the test probe to achieve dynamic control of its real-time attitude and position.

[0027] The present invention also provides an automatic underwater depth positioning device for a test probe, including a multi-source sensor acquisition module, an environmental parameter measurement module, a pressure and depth dynamic correction module, a data fusion module, and an intelligent control decision module;

[0028] Multi-source sensor acquisition module: A pressure sensor, sonar ranging module and inertial navigation unit are integrated on the test rod to acquire the current underwater pressure data, relative depth distance and motion status information of the test rod in real time;

[0029] Environmental parameter measurement module: The temperature, salinity and depth sensors are further integrated on the measuring rod to monitor the temperature, salinity and density changes of the water body at the current location in real time and obtain the actual water density data at the current location;

[0030] Pressure Depth Dynamic Correction Module: Inputs the acquired actual water density data into the pressure sensor depth conversion module, and dynamically corrects the pressure depth data corresponding to the original pressure value output by the pressure sensor based on the actual water density data;

[0031] Data fusion module: compares and fuses the relative depth data obtained by the sonar ranging module with the corrected pressure depth data to generate the target water depth value;

[0032] Intelligent control decision module: Combining the changing trends of motion state information provided by the inertial navigation unit and the target water depth value, the control system adjusts the attitude and depth position of the test probe in real time.

[0033] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0034] This invention integrates multiple high-precision sensors and intelligent control modules onto a test probe, constructing an automatic underwater depth positioning method that combines environmental perception, dynamic correction, and intelligent control. This effectively overcomes the depth measurement error problem caused by the assumption of constant density in traditional systems operating in temperature-salinity stratified environments. By introducing temperature-salinity-depth sensors to acquire water density in real time and combining this with changes in water compressibility and sound velocity in water to perform nonlinear correction of pressure depth, the measurement accuracy under complex hydrological conditions is significantly improved. Simultaneously, sonar and pressure data are fused to generate target depth values. Based on this, and combined with the changing trends of inertial navigation data, a fuzzy logic control algorithm is used to adaptively adjust the probe's attitude and depth, enhancing the system's stability and robustness in dynamically disturbed environments. This invention not only improves underwater positioning accuracy and reduces operational risks caused by errors but also enhances the system's intelligence and adaptability, making it suitable for various scenarios such as underwater testing, exploration, and environmental monitoring. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0036] Figure 1 This is a schematic diagram of the method of the present invention.

[0037] Figure 2 This is a schematic diagram of the device module of the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Example 1, please refer to Figure 1 As shown in this embodiment, an automatic underwater depth positioning method for a test probe includes:

[0040] A pressure sensor, a sonar ranging module, and an inertial navigation unit are integrated on the test probe to acquire the probe's current underwater pressure data, relative depth distance, and motion status information in real time.

[0041] A temperature, salinity, and depth sensor is further integrated into the measuring rod to monitor the changes in temperature, salinity, and density at the current location of the water body in real time and obtain the actual water density data at the current location.

[0042] The actual water density data is input into the pressure sensor depth conversion module, and the pressure depth data corresponding to the original pressure value output by the pressure sensor is dynamically corrected based on the actual water density data.

[0043] The relative depth data obtained by the sonar ranging module is compared and fused with the corrected pressure depth data to generate the target water depth value.

[0044] By combining the changing trends of motion state information provided by the inertial navigation unit and the target water depth value, the attitude and depth position of the test probe are adjusted in real time through the control system.

[0045] Pressure sensors are typically housed within the bottom or near-end cavity of the probe, or within a waterproof enclosure, to ensure that the pressure value reflects the actual depth of the probe. The pressure sensor senses the hydrostatic pressure corresponding to the probe's current depth in real time. By measuring the pressure per unit area, and combining this with liquid density and the gravitational constant, a preliminary depth value is calculated. High-precision miniature pressure sensors are generally used, with sampling frequencies of 1–10 Hz and accuracy up to ±0.01 meters. In temperature-salinity stratification environments, corrections must be made based on water density (provided by a CTD sensor); otherwise, the calculated depth will have a systematic bias.

[0046] Sonar ranging modules are typically positioned on the side or bottom of the ranging rod, facing the target surface (such as the bottom, surface, or reference object), and have both sound wave transmission and reception capabilities. By emitting sound wave pulses, the module measures the time required for the sound wave to travel from emission to reception of the reflected wave, and then calculates the distance to the reflecting surface by combining this with the speed of sound. Typical application modes: downward ranging: the reflecting surface is the bottom, calculating the relative depth of the ranging rod from the bottom; upward ranging: the reflecting surface is the surface, calculating the relative depth of the surface. Redundancy or verification mechanisms are established with pressure sensors, providing reliable reference even when the ranging rod accelerates or changes its attitude.

[0047] An inertial navigation unit typically consists of a three-axis accelerometer, a three-axis gyroscope, and a magnetometer, and can be integrated into a miniature inertial measurement unit (IMU). It is usually fixed to the central axis or near the center of gravity of the probe to improve the accuracy of motion state perception. It is used to acquire real-time information such as acceleration, angular velocity, and attitude angle of the probe in three-dimensional space. Short-term position change trends are calculated using integral algorithms, providing a basis for the dynamic control and compensation of the probe. When the probe is subjected to water flow disturbances, inertial drift, or short-term separation from the reference signal, it can provide continuous attitude and depth change trends. In the fusion of pressure and sonar data, it enhances the system's robustness to sudden movements or underwater disturbances.

[0048] In summary, by integrating and deploying the above three types of sensors on the test rod structure and constructing a unified data acquisition and control bus system, the test rod can achieve high-frequency, high-precision, and redundant verification sensing of its own status during underwater operations.

[0049] A temperature, salinity, and depth (CTD) sensor is a widely used water parameter sensor system for marine and lake environmental monitoring. In this invention, it is used to acquire real-time density data of the water body, providing a basis for pressure-depth correction. It is typically positioned in the lower part of the measuring rod near the pressure sensor to avoid local disturbances and to be as close as possible to the depth measurement point, thereby improving the accuracy of density correction.

[0050] Sensors are typically housed in independent, corrosion-resistant, and waterproof enclosures, transmitting information via a system data bus. Instantaneous water temperature (T) is measured using high-sensitivity thermocouples or thermistors; temperature is one of the dominant factors affecting water density changes, especially in the thermocline region. Salinity measurement (S): Salinity is actually inferred by measuring water conductivity; salinity changes, especially in marine environments, significantly affect water density and are a key parameter for cross-layer errors. Density conversion (ρ): International standard formulas (such as the UNESCO 1983 seawater state equation) are used to convert temperature and salinity into water density; density data is output in real-time to the pressure-depth conversion module to replace traditional fixed density values ​​for dynamic correction.

[0051] The data applications and advantages include: dynamic acquisition of temperature, salinity, and density profiles at different depths as the measuring rod descends; effective resolution of depth error issues caused by density changes in stratified water environments, particularly suitable for multi-layered water bodies such as oceans, lakes, and reservoirs; and high system integration: it can be directly connected to the measuring rod control system via a communication bus (such as RS-485 or CAN), and the data can be used in fusion algorithms and error compensation models.

[0052] In summary, by integrating temperature, salinity, and depth sensors onto the test probe, the system can dynamically acquire the true density data of the current water body at different water layers. This density data is input in real time to the depth conversion module of the pressure sensor to perform density correction on the original pressure value, effectively avoiding the depth measurement errors that occur in traditional systems under temperature and salinity stratification environments.

[0053] The real-time water temperature and salinity values ​​collected by the temperature, salinity and depth sensor (CTD) are converted into actual water density data (ρ) at the current location by an internal calculation module or an external processor; this density data is then transmitted to the pressure-depth conversion module using standard communication protocols (such as RS-485, MODBUS, etc.).

[0054] In traditional pressure-to-depth methods, water density (ρ) is used as the sole variable for correction. While this can solve common temperature and salinity stratification errors, residual errors may still exist in certain complex environments (such as deep sea, high-mineralization lakes, and brackish water confluence areas). In particular, under extreme temperature or high pressure conditions, factors such as water compressibility and sound velocity changes can indirectly affect the accuracy of depth estimation.

[0055] Therefore, this method further collects water body parameters that have a significant impact on pressure conversion, including water compressibility and changes in sound velocity in water.

[0056] Water compressibility represents the degree of volume change caused by a unit change in pressure. In deep-water, high-pressure environments, water is significantly pressurized, and its density does not change linearly and steadily. If compressibility is not considered, a non-linear deviation will occur between the pressure value and the actual depth. The compressibility is obtained by calculating the bulk modulus of pure water using a fourth-order polynomial based on collected water temperature data, which serves as the baseline bulk modulus. The expression is:

[0057] ;

[0058] T represents the water temperature. Based on the water temperature, two salinity-related correction terms, A and B, are further calculated: A is the linear salinity correction term, expressed as:

[0059] ;

[0060] B is the salinity squared correction term, expressed as: Combining A and B with the salinity value yields the basic bulk modulus of the saline body. The expression is: In the formula, S is salinity; the water compressibility is the basic bulk modulus. The reciprocal of.

[0061] The change in sound speed in water is the velocity of sound waves as they propagate through water, influenced by water temperature, salinity, and pressure. This change reflects the trend of water structure changes and can be used as an auxiliary parameter to correct the nonlinear shift of the pressure-depth function. The data is obtained by collecting the practical salinity (SP), original temperature (t), and water depth / pressure (p) from the field using a temperature, salinity, and depth sensor. These are then converted into absolute salinity (SA) and conservative temperature (CT) using the conversion algorithm in the GSW model. This includes substituting the input SP, p, latitude (lat), and longitude (lon) into the salinity conversion function in the GSW model to obtain the SA at the corresponding location. The expression is as follows: The original measured water temperature (i.e., in-situ temperature t) is converted into a conservative temperature CT using the GSW model. The conversion function takes SA, t, and p as inputs and outputs CT. The expression is as follows: The converted parameters SA, CT, and p are input into the sound velocity calculation function of the GSW model to obtain the isothermal compressibility. The expression is: The speed of sound in the GSW model is derived internally based on the thermodynamic derivative of the Gibbs free energy, and the expression is: ; For water density, Where c is the isothermal compressibility and c is the change in sound velocity in water. The calculated change in sound velocity in water is expressed in meters per second (m / s) and can be used to correct the propagation time of sonar or ultrasonic ranging modules.

[0062] Based on the obtained changes in sound velocity in water and the water compressibility, the water depth correction factor K is calculated, and its expression is: ; For reference sound speed (e.g., the sound speed of standard seawater at T=10°C, S=35, p=0 dbar, approximately 1490 m / s); For water compressibility, This is a reference value for water body compressibility.

[0063] The raw pressure value P output in real time by the pressure sensor and the actual water density ρ are input into the conversion module to calculate the corrected water depth value, expressed as: In the formula, is the corrected water depth value (unit: m), g is the gravitational acceleration (unit: m / s²), and K is the water depth correction factor, which is dimensionless.

[0064] The corrected water depth value is output to the system's main control module and fused with depth information acquired by other sensors (such as sonar or INS).

[0065] The relative depth data obtained by the sonar ranging module is compared and fused with the corrected pressure depth data to generate the target water depth value.

[0066] Specifically, the sonar ranging module measures the relative distance between the end of the measuring rod and the water surface or bottom by measuring the time difference of sound wave propagation, featuring fast real-time response and independence from water density; while the pressure sensor calculates water depth by converting pressure, exhibiting long-term stability and anti-interference capabilities. Due to their different working principles, each may have a certain degree of measurement error or deviation under certain dynamic or abnormal hydrological conditions.

[0067] To fully utilize the complementary advantages of these two types of data, the system introduces a data fusion mechanism. The fusion process includes: normalizing the real-time acquired sonar data and the corrected pressure data so that they are both within the range [0,1]; calculating a weighted average of the normalized sonar data and the corrected pressure data to generate a normalized target water depth value; and then denormalizing the normalized target water depth value to restore the actual target water depth value in a physical sense. .

[0068] Through the aforementioned comparison and fusion strategy, the system can achieve higher-precision depth measurement in various complex underwater environments and improve its fault tolerance to sudden errors. The fused target depth value is not only used for data recording but can also be used as a feedback signal input to the control module to realize real-time attitude adjustment and depth closed-loop control of the measuring rod.

[0069] By combining the changing trends of motion state information provided by the inertial navigation unit and the target water depth value, the attitude and depth position of the test probe are adjusted in real time through the control system.

[0070] The inertial navigation unit can acquire information such as acceleration, angular velocity, and attitude angle of the probe in real time during its movement in the water, and then deduce its motion trend and rate of change, such as ascent / descent rate, forward / backward tilt angle change, and lateral offset trend. At the same time, the system obtains the current target water depth value through the data fusion module, which reflects the ideal depth position that the probe should reach in the current environment.

[0071] To achieve adaptive and flexible control, the system uses a fuzzy logic reasoning model to dynamically generate control commands for the test probe. This fuzzy controller takes the changing trend of motion state information and the target water depth as inputs, and the probe attitude adjustment and depth position correction as outputs, thus realizing the uncertainty mapping between input and output and optimizing the control strategy.

[0072] The motion state information (such as angular velocity, acceleration, and attitude angle changes) provided by the inertial navigation unit, as well as the deviation between the fused target water depth value and the current water depth, are converted into fuzzy linguistic variables.

Claims

1. A method for automatically positioning a test bar underwater depth, characterized in that: The utility model relates to a kind of underwater test rod control system, including: Integrate pressure sensor, sonar ranging module and inertial navigation unit on test rod, for real-time acquisition of current underwater pressure data of test rod, relative depth distance and motion state information; The pressure sensor is used to sense the hydrostatic pressure corresponding to the water depth position where the test rod is located in real time, and by measuring the pressure on a unit area, combining liquid density and gravitational constant, the depth value is preliminarily converted; The sonar ranging module is arranged at the position of the side or bottom of the test rod facing the target surface, and by emitting an acoustic pulse signal outward, the time required for the acoustic wave to be reflected from emission to reception is measured, and the distance to the reflecting surface is calculated by combining the sound velocity; The inertial navigation unit is composed of a three-axis accelerometer, a three-axis gyroscope and a magnetometer, for real-time acquisition of acceleration, angular velocity and attitude angle information of the test rod in three-dimensional space;The short-time position change trend is calculated by integral algorithm; Further integrate temperature-salinity-depth sensor on the test rod, for real-time monitoring of temperature, salinity and density change of the current position of the water body, and obtaining the actual water density data of the current position; Input the actual water density data obtained into the pressure sensor depth conversion module, and dynamically correct the pressure depth data corresponding to the original pressure value output by the pressure sensor based on the actual water density data; The pressure sensor depth conversion module further calculates the depth correction coefficient according to the obtained water compressibility and water sound velocity change value, and nonlinearly corrects the initial water depth corresponding to the original pressure value, and outputs the corrected water depth data; The water compression rate is obtained in the following manner: according to the collected water temperature data, the bulk modulus of pure water is calculated by a fourth-order polynomial as a reference bulk modulus , the expression is: ; T is the water temperature, and two correction terms A and B related to salinity are further calculated according to the water temperature: A is a linear salinity correction term, and the expression is: ; B is a salinity square correction term, expressed as: ; A and B are combined with the salinity value to obtain the basic bulk modulus of the saltwater body , expressed as: ; in the formula, S is salinity; the water compression rate is the reciprocal of the basic bulk modulus . The method for obtaining the change value of the sound speed in water is as follows: collecting the practical salinity SP, the original temperature t and the water depth pressure p on site by the temperature-salinity-depth sensor, inputting the SP, the p, the latitude lat and the longitude Ion into the salinity conversion function in the GSW model to obtain the SA at the corresponding position, and the expression is as follows: ; The original measured water temperature is converted to conservative temperature CT by the GSW model, the conversion function takes SA, t and p as inputs and outputs CT, the expression is: ; the converted parameters SA, CT and p are input into the sound speed calculation function of the GSW model to obtain the isothermal compressibility , the expression is: , the sound speed is derived based on the thermodynamic derivative of Gibbs free energy inside the GSW model, the expression is: ; is the density of the water body, is the isothermal compressibility, and c is the change value of the sound speed in water; Compare and fuse the relative depth data obtained by the sonar ranging module with the corrected pressure depth data to generate the target water depth value; According to the obtained water speed change value and water compression rate, a water depth correction coefficient K is calculated, and the expression is as follows: ; is a reference speed; is a water compression rate, is a reference water compression rate value; The raw pressure value P output by the pressure sensor in real time and the actual water density are input to the conversion module, and the corrected water depth value is calculated, and the expression is: ; in the formula, is the corrected water depth value, g is the acceleration of gravity, and K is the water depth correction coefficient. Normalize the real-time acquired sonar data and corrected pressure data so that they are both within [0, 1], and generate the normalized target water depth value by weighted average calculation of the normalized sonar data and corrected pressure data, and then denormalize the normalized target water depth value to recover the actual target water depth value in physical sense; Combine the change trend of the motion state information provided by the inertial navigation unit and the target water depth value, and adjust the attitude and depth position of the test rod in real time by the control system; The fuzzy controller takes the change trend of the motion state information and the target water depth value as input items, and takes the test rod attitude adjustment amount and depth position correction amount as output items.

2. The method of claim 1, wherein: The temperature-salinity-depth sensor includes a temperature acquisition unit, a salinity acquisition unit and a pressure acquisition unit, calculates the water density based on temperature and salinity parameters, and transmits the density data to the pressure depth conversion module through a standard communication protocol.

3. The method of claim 1, wherein: Fuzzy logic reasoning is used to dynamically generate control instructions for the test rod, and the fuzzy controller takes the change trend of the motion state information and the target water depth value as input items, and takes the test rod attitude adjustment amount and depth position correction amount as output items; Convert the deviation value between the motion state information provided by the inertial navigation unit and the target water depth value fused and generated and the current water depth into fuzzy language variables; According to the fuzzification result of the current input variable, match the rules that meet the conditions in the fuzzy rule base, and perform fuzzy reasoning operation; The inference process adopts the Mamdani fuzzy inference method, and the fuzzy synthesis of the results of multiple rules meeting the conditions is performed to form a fuzzy set of output variables. In the case of multiple rules being activated at the same time, the output set will be a combination of multiple fuzzy outputs. The fuzzy output set is converted into a control variable through a defuzzification process to drive the control system to perform specific adjustment actions. The defuzzification method includes the barycenter method, and the result is the weighted average of all output membership functions multiplied by their values. The final control variable is sent to the attitude adjustment mechanism and depth adjustment mechanism on the test rod as an instruction signal to achieve dynamic control of its real-time attitude and position.

4. A test boom underwater depth automatic positioning device based on the test boom underwater depth automatic positioning method according to any one of claims 1-3, characterized in that: It includes a multi-source sensor acquisition module, an environmental parameter measurement module, a pressure depth dynamic correction module, a data fusion module, and an intelligent control decision module. The multi-source sensor acquisition module integrates pressure sensors, sonar ranging modules, and inertial navigation units on the test rod to obtain real-time underwater pressure data, relative depth distance, and motion state information. The environmental parameter measurement module further integrates temperature, salinity, and depth sensors on the test rod to monitor the temperature, salinity, and density changes at the current location and obtain the actual water density data. The pressure depth dynamic correction module inputs the actual water density data into the pressure sensor depth conversion module and dynamically corrects the pressure depth data corresponding to the original pressure value output by the pressure sensor based on the actual water density data. The data fusion module compares and fuses the relative depth data obtained by the sonar ranging module with the corrected pressure depth data to generate the target water depth value. The intelligent control decision module combines the change trend of the motion state information provided by the inertial navigation unit and the target water depth value to adjust the attitude and depth position of the test rod in real time through the control system.

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