A real-time pressure self-compensation and accurate measurement control method for deep-sea rotating speed sensing

Abstract

The present application relates to the technical field of rotational speed measurement, and discloses a real-time pressure self-compensation and precise measurement control method for deep-sea rotational speed sensing, which comprises the following steps: collecting the dynamic pressure difference inside and outside a sensing device, inputting the physical property parameters of an updated viscoelastic dynamic response model into a microprocessor, calculating the response time constant representing the phase delay characteristic of an elastic pressure transmission medium according to the parameter value drift characteristic, obtaining an original rotational speed pulse signal with a viscous damping hysteresis characteristic, and constructing a phase compensation filter by using the response time constant, so that the original signal is subjected to a first-order leading phase compensation operation to obtain a calibrated rotational speed measurement value. The present application realizes dynamic mapping of a physical rheological process to signal compensation logic, compensates for the phase bias generated by the high-pressure rheological medium in situ, eliminates the waveform distortion of the pulse signal under the deep-sea extreme pressure working condition, and ensures the measurement stability of the rotational speed sensing system under the variable acceleration rotation working condition of a deep-sea vehicle.

Description

Technical Field

[0001] This invention belongs to the field of rotational speed measurement technology, and particularly relates to a real-time pressure self-compensation and precise measurement control method for deep-sea rotational speed sensing. Background Technology

[0002] Current deep-sea resource exploration and deep-sea submersible operations place high demands on the speed sensing accuracy of rotating machinery. A pressure-compensated structure is employed, filling the sensing device with oil or an elastic pressure-transmitting medium to balance internal and external pressures, protecting the sensing components from structural damage under hydrostatic conditions. However, during rapid descents or encounters with alternating pressure fields, the pressure-transmitting medium exhibits nonlinear viscoelastic rheological effects. This effect, driven by transient pressure gradients, causes a step change in the mechanical damping of the sensing shaft. While the industry typically considers the impact of pressure on speed measurement to be merely a linear damping fluctuation, employing a gain compensation strategy based on steady-state pressure, the underlying physical mechanism reveals that the rheological properties of the pressure-transmitting medium dynamically respond to pressure fluctuations. This results in phase hysteresis and pulse waveform broadening at the sensing interface. Static calibration logic cannot detect the dynamic delay caused by the medium's rheological changes, making the measurement system prone to pulse edge loss and signal tracking failure under transient speed variations.

[0003] Existing control methods have shortcomings. For example, Chinese invention patent application CN121679593A discloses a method and device for oil pressure compensation in a deep-sea acoustic signal transceiver. It uses a PID controller to dynamically feed silicone oil based on the internal and external pressure difference to maintain the macroscopic pressure balance inside and outside the tank. The volumetric feedback control method implicitly relies on the underlying assumption that the pressure transmission medium is an ideal incompressible fluid with instantaneous response characteristics. In the actual transient alternating pressure field of the deep sea, the medium exhibits strong nonlinear viscoelastic rheological hysteresis under high pressure. The PID volumetric adjustment can only ensure the balance at the macroscopic static stress level, which is detached from the objective physical fact that the medium's internal microscopic phase delay and dynamic mechanical damping change caused by high pressure rheology. The preset premise is fundamentally mismatched with the actual extreme pressure variation boundary conditions of the deep sea. As a result, when the control logic faces high-frequency speed pulse signals, it cannot cancel the dynamic phase distortion induced by the rheological effect of the medium in the time domain, and cannot suppress the transient broadening of the pulse waveform.

[0004] Therefore, the technical problem to be solved by this invention is to reconstruct the dynamic rheological characteristics of the pressure transmission medium on the basis of achieving real-time balance of internal and external pressure, eliminate the phase hysteresis and pulse broadening distortion of the rotation speed signal caused by rheological effects, and ensure the accurate measurement and control of rotation speed under deep-sea transformer operating conditions. Summary of the Invention

[0005] This invention provides a real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing, comprising the following steps: Step S101: Collect external environmental pressure data and internal cavity pressure data of the deep-sea sensing device, and calculate the dynamic pressure difference between the inside and outside of the device. Step S102: Input the dynamic pressure difference into the pre-stored viscoelastic dynamic response model in the internal storage space of the microprocessor. The viscoelastic dynamic response model converts the dynamic pressure difference into an equivalent pressure load acting on the elastic pressure transmission medium in the sensing cavity through the built-in physical property feature matrix, and updates the medium density, dynamic viscosity and bulk modulus parameters stored in the physical property feature matrix in real time according to the equivalent pressure load. Step S103: Based on the numerical drift characteristics of each physical property parameter in the physical property feature matrix as it evolves with the time axis, calculate the shear stress response delay of the elastic pressure transmission medium under the current depth pressure field, and extract the corresponding response time constant accordingly to quantify and define the transient phase offset of the elastic pressure transmission medium to the rotational speed pulse signal. Step S104: Obtain the original rotational speed pulse signal output by the sensing component. The original rotational speed pulse signal has phase lag characteristics induced by viscous damping caused by high pressure compression of the elastic pressure transmission medium and waveform distortion characteristics at the edge of the pulse signal. Step S105: Construct a phase compensation filter using the response time constant, and perform a first-order lead phase compensation operation on the original speed pulse signal through the phase compensation filter to compensate for the signal hysteresis caused by the elastic pressure transmission medium, and output the calibrated speed measurement value.

[0006] Preferably, step S102 involves updating the parameters stored in the physical property feature matrix in real time based on the equivalent pressure load, including: retrieving the preset array of initial physical property parameters of the elastic pressure transmission medium in the physical property feature matrix; inputting the equivalent pressure load as an independent variable into the dynamic evolution equation corresponding to the physical property feature matrix, and calculating the real-time drift of the initial physical property parameters under the current dynamic pressure difference; and using the real-time drift to numerically cover the initial physical property parameters to obtain an input reference used to characterize the phase distortion of the original rotational speed pulse signal.

[0007] Preferably, step S103 extracts the response time constant characterizing the phase delay characteristics of the elastic pressure-transmitting medium at the current depth, including: monitoring the transient rate of change of the medium property parameters in the material property matrix with the equivalent pressure load; calculating the time-domain response deviation between the transient rate of change and the equivalent pressure load, wherein the time-domain response deviation is used to characterize the delay effect of physical damping on signal propagation; and confirming the time-domain response deviation as the response time constant, which is used as the weighting weight for dynamic phase correction of the original rotational speed pulse signal.

[0008] Preferably, after outputting the calibrated rotational speed measurement value in step S105, the method further includes: detecting the pulse edge steepness of the calibrated rotational speed measurement value; when the pulse edge time width is detected to exceed the preset 10μs threshold, automatically increasing the compensation gain coefficient of the phase compensation filter to suppress the signal waveform broadening generated by the elastic pressure transmission medium and ensure the integrity of the rotational speed pulse signal tracking under the variable acceleration rotational condition of the deep-sea submersible.

[0009] Preferably, before step S101, the method further includes: filling the sensing cavity with an elastic pressure-transmitting medium, using the volume deformation of the elastic pressure-transmitting medium under pressure to perform static balance adjustment of the internal and external pressures of the device, and using the elastic pressure-transmitting medium to transmit the external seawater pressure to the internal pressure sensing unit through physical deformation, thus providing a physical source of internal cavity pressure data for step S101.

[0010] Preferably, in step S102, the viscoelastic dynamic response model is preset by defining a logic operation interval in the internal non-volatile memory of the microprocessor. The logic operation interval has an independent data bus channel for retrieving the real-time drift amount in the physical property feature matrix and transmitting it to the phase compensation filter in real time.

[0011] Preferably, in step S104, the original rotation speed pulse signal is acquired non-contactly through a Hall sensor or a photoelectric pulse generator. Before entering the microprocessor, the original rotation speed pulse signal is first processed by a limiting circuit to filter out common-mode interference noise introduced by the deep-sea submersible's power supply, ensuring the signal purity of the input phase compensation filter.

[0012] Preferably, the method establishes a closed-loop self-compensation logic through pressure data acquisition, physical property parameter update, and signal feature reconstruction, so that each set of calibrated rotational speed measurement values ​​is associated with the response time constant of the corresponding sampling time, thereby achieving time alignment between rotational speed measurement results and environmental pressure under the turbulent conditions of deep ocean currents.

[0013] Preferably, after outputting the calibrated rotational speed measurement value in step S105, the calibrated rotational speed measurement value is sent to the attitude control module of the deep-sea submersible as dynamic input data for evaluating the operating status of the deep-sea submersible, and the navigation system assists in real-time correction of the deep-sea submersible's navigation trajectory and motion attitude reconstruction.

[0014] Compared with existing technologies, the real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing of this invention has the following advantages: 1. In real-time pressure self-compensation of deep-sea rotational speed sensing, a dynamic calibration mechanism based on in-loop simulation operators is constructed. The external environmental pressure sequence is collected by the pressure sensor and the transient pressure gradient is extracted. The rheological topology mesh inside the microprocessor is driven to undergo data deformation in real time. The viscoelastic rheological characteristics of the physical pressure transmission medium under high pressure are directly translated into rheological relaxation parameters in the digital domain. This achieves deep coupling between the measurement compensation logic and the deep-sea alternating pressure field, eliminating the drawbacks of the traditional static lookup table method that cannot adapt to dynamic pressure difference fluctuations. It ensures that the compensation parameters are always updated synchronously with the evolution of external working conditions, and improves the environmental adaptability accuracy of the sensing device under complex working conditions such as rapid descent of deep-sea submersibles or drastic changes in ocean currents.

[0015] 2. The original rotational speed signal is processed by a time-domain dynamic anti-filter based on rheological relaxation parameters. The mechanical damping hysteresis caused by the high-pressure rheology of the pressure transmission medium is offset in situ in the time domain using a first-order lead differential algorithm. This suppresses the phase hysteresis and edge broadening of the pulse signal under high-pressure conditions, restores the true angular velocity pulse sequence, solves the problem of pulse edge loss caused by signal waveform distortion under deep-sea extreme pressure conditions, and ensures the integrity and stability of the device's speed pulse tracking under variable acceleration rotation conditions.

[0016] 3. Through cross-dimensional collaboration of real-time pressure equalization adjustment and dynamic decoupling of signal phase frequency, the nonlinear pressure deformation interference of the physical sealing medium is reduced to a signal phase frequency calibration problem inside the processor. This self-evolving measurement method driven by a real-time model enables the dynamic response capability of the speed sensing system to break free from its dependence on the response speed of physical compensation hardware. Without changing the existing mechanical seal structure or using expensive special pressure-resistant materials, it achieves measurement stability that conventional physical frameworks cannot reach, avoiding the risk of system control instability caused by transient high-pressure impacts. Attached Figure Description

[0017] Figure 1 This is a flowchart of the real-time pressure self-compensation and accurate measurement method for deep-sea rotation speed sensing according to the present invention; Figure 2 This is a diagram of the collaborative control architecture of the physical layer and the digital self-compensation logic layer of the sensing device of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0019] It should be noted that all directional and positional terms used in this invention, such as: up, down, left, right, front, back, vertical, horizontal, inner, outer, top, bottom, transverse, longitudinal, center, etc., are only used to explain the relative positional relationship and connection between components in a specific state (as shown in the accompanying drawings). They are only for the convenience of describing this invention and do not require that this invention be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention. In addition, the descriptions of "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated.

[0020] In the description of this invention, unless otherwise explicitly specified and limited, the terms installation, connection, and linking should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections; they can refer to direct connections or indirect connections through an intermediate medium; they can refer to the internal connection of two components. For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances.

[0021] In the description of this specification, references to the terms "an embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example, and the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0022] A real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing includes the following steps: Step S101: Collect external environmental pressure data and internal cavity pressure data of the deep-sea sensing device, and calculate the dynamic pressure difference between the inside and outside of the device. Step S102: Input the dynamic pressure difference into the pre-stored viscoelastic dynamic response model in the internal storage space of the microprocessor. The viscoelastic dynamic response model converts the dynamic pressure difference into an equivalent pressure load acting on the elastic pressure transmission medium in the sensing cavity through the built-in physical property feature matrix, and updates the medium density, dynamic viscosity and bulk modulus parameters stored in the physical property feature matrix in real time according to the equivalent pressure load. Step S103: Based on the numerical drift characteristics of each physical property parameter in the physical property feature matrix as it evolves with the time axis, calculate the shear stress response delay of the elastic pressure transmission medium under the current depth pressure field, and extract the corresponding response time constant accordingly to quantify and define the transient phase offset of the elastic pressure transmission medium to the rotational speed pulse signal. Step S104: Obtain the original rotational speed pulse signal output by the sensing component. The original rotational speed pulse signal has phase lag characteristics induced by viscous damping caused by high pressure compression of the elastic pressure transmission medium and waveform distortion characteristics at the edge of the pulse signal. Step S105: Construct a phase compensation filter using the response time constant, and perform a first-order lead phase compensation operation on the original speed pulse signal through the phase compensation filter to compensate for the signal hysteresis caused by the elastic pressure transmission medium, and output the calibrated speed measurement value.

[0023] Preferably, step S102 involves updating the parameters stored in the physical property feature matrix in real time based on the equivalent pressure load, including: retrieving the preset array of initial physical property parameters of the elastic pressure transmission medium in the physical property feature matrix; inputting the equivalent pressure load as an independent variable into the dynamic evolution equation corresponding to the physical property feature matrix, and calculating the real-time drift of the initial physical property parameters under the current dynamic pressure difference; and using the real-time drift to numerically cover the initial physical property parameters to obtain an input reference used to characterize the phase distortion of the original rotational speed pulse signal.

[0024] Preferably, in step S105, the original rotational speed pulse signal is subjected to a first-order lead phase compensation operation through a phase compensation filter, and the operation rule is expressed by the following formula: ,in, This is the output signal after phase compensation. The original rotational speed pulse signal is τ, and the response time constant is extracted in step S103.

[0025] Preferably, step S103 extracts the response time constant characterizing the phase delay characteristics of the elastic pressure-transmitting medium at the current depth, including: monitoring the transient rate of change of the medium property parameters in the material property matrix with the equivalent pressure load; calculating the time-domain response deviation between the transient rate of change and the equivalent pressure load, wherein the time-domain response deviation is used to characterize the delay effect of physical damping on signal propagation; and confirming the time-domain response deviation as the response time constant, which is used as the weighting weight for dynamic phase correction of the original rotational speed pulse signal.

[0026] Preferably, after outputting the calibrated rotational speed measurement value in step S105, the method further includes: detecting the pulse edge steepness of the calibrated rotational speed measurement value; when the pulse edge time width is detected to exceed the preset 10μs threshold, automatically increasing the compensation gain coefficient of the phase compensation filter to suppress the signal waveform broadening generated by the elastic pressure transmission medium and ensure the integrity of the rotational speed pulse signal tracking under the variable acceleration rotational condition of the deep-sea submersible.

[0027] Preferably, before step S101, the method further includes: filling the sensing cavity with an elastic pressure-transmitting medium, using the volume deformation of the elastic pressure-transmitting medium under pressure to perform static balance adjustment of the internal and external pressures of the device, and using the elastic pressure-transmitting medium to transmit the external seawater pressure to the internal pressure sensing unit through physical deformation, thus providing a physical source of internal cavity pressure data for step S101.

[0028] Preferably, in step S102, the viscoelastic dynamic response model is preset by defining a logic operation interval in the internal non-volatile memory of the microprocessor. The logic operation interval has an independent data bus channel for retrieving the real-time drift amount in the physical property feature matrix and transmitting it to the phase compensation filter in real time.

[0029] Preferably, in step S104, the original rotation speed pulse signal is acquired non-contactly through a Hall sensor or a photoelectric pulse generator. Before entering the microprocessor, the original rotation speed pulse signal is first processed by a limiting circuit to filter out common-mode interference noise introduced by the deep-sea submersible's power supply, ensuring the signal purity of the input phase compensation filter.

[0030] Preferably, the method establishes a closed-loop self-compensation logic through pressure data acquisition, physical property parameter update, and signal feature reconstruction, so that each set of calibrated rotational speed measurement values ​​is associated with the response time constant of the corresponding sampling time, thereby achieving time alignment between rotational speed measurement results and environmental pressure under the turbulent conditions of deep ocean currents.

[0031] Preferably, after outputting the calibrated rotational speed measurement value in step S105, the calibrated rotational speed measurement value is sent to the attitude control module of the deep-sea submersible as dynamic input data for evaluating the operating status of the deep-sea submersible, and the navigation system assists in real-time correction of the deep-sea submersible's navigation trajectory and motion attitude reconstruction.

[0032] Example 1: When a deep-sea submersible traverses water layers of different depths, the static pressure of the external seawater environment fluctuates. Under the superposition of static pressure and dynamic pressure difference, the elastic pressure-transmitting medium filled inside undergoes nonlinear viscoelastic rheology, resulting in a prolonged intrinsic relaxation time of the pressure-transmitting medium. This rheological effect induces a deterioration in the transient hydrodynamic damping of the sensing shaft, causing high-frequency phase hysteresis and pulse edge broadening in the original rotational speed pulse signal output by the sensing component. The static gain calibration mechanism using steady-state pressure values ​​cannot eliminate the phase error caused by the dynamic rheology of the medium. There is a risk of pulse signal tracking loss when the deep-sea submersible is rotating with variable acceleration.

[0033] The pressure sensor collects real-time external environmental pressure data and internal cavity pressure data of the deep-sea sensing device, calculates the dynamic pressure difference between the inside and outside of the device, and the microprocessor retrieves the viscoelastic dynamic response model pre-stored in the internal storage space. The dynamic pressure difference is input into the corresponding dynamic evolution equation of the viscoelastic dynamic response model to calculate the real-time drift of the medium density, dynamic viscosity, and bulk modulus under the current dynamic pressure difference. The microprocessor uses the real-time drift to numerically overlay the initial physical property parameters, continuously monitors the transient rate of change of the medium physical property parameters in the physical property characteristic matrix with the equivalent pressure load, calculates the time-domain response deviation between the transient rate of change and the equivalent pressure load, and extracts the response time constant τ, which characterizes the shear stress response delay of the elastic pressure-transmitting medium. The Hall sensor component collects the raw rotational speed pulse signal with phase hysteresis and waveform distortion characteristics. The microprocessor uses the response time constant τ to construct a phase compensation filter for the original rotational speed pulse signal. The first-order lead phase compensation operation is performed, and the operation rules are as follows: ,in, This is the output signal after phase compensation. The original rotational speed pulse signal is given, τ is the response time constant, and t is the time variable.

[0034] The microprocessor uses the differential component driven by τ to cancel the signal hysteresis generated by the elastic pressure transmission medium in situ, outputs the calibrated speed measurement value, and performs pulse edge steepness detection on the calibrated speed measurement value; when the pulse edge time width exceeds the 10μs threshold, the microprocessor automatically increases the compensation gain coefficient of the phase compensation filter to suppress the signal waveform broadening generated by the elastic pressure transmission medium. The calibrated speed measurement value is sent to the attitude control module of the deep-sea submersible as dynamic input data for evaluating the operating status of the deep-sea submersible; through the coordination of the pressure equalization adjustment process and the speed signal phase frequency compensation process, the rheological drag at the physical level is converted into signal filtering parameters in the digital domain, and the speed measurement system continuously outputs a stable speed pulse sequence under alternating pressure field conditions.

[0035] Example 2: This example simulates a deep-sea high-pressure testing platform, including a high-pressure hydraulic vessel with a maximum pressure capacity of 60MPa and a temperature control error limit of ±0.5℃. An integrated variable-frequency micro-motor serves as the test object. External pipelines connect a servo hydraulic pump and a high-speed solenoid valve to generate alternating pressure loads. A signal generator superimposes 20dB Gaussian white noise and 50Hz power frequency harmonic interference onto the sensor signal source input to the microprocessor. A high-precision photoelectric encoder, independent of the pressurized fluid, reads the reference rotational speed data through the optical window of the end cap. The microprocessor then uses the original rotational speed pulse signal... The sampling period of the phase compensation filter is set based on the spectral bandwidth and the transient characteristics of the high-frequency rheological response of the elastic pressure-transmitting medium. When the cutoff frequency corresponding to the extracted response time constant τ approaches the Nyquist frequency limit of the microprocessor, the microprocessor sets the sampling period to 5μs according to the Nyquist sampling theorem to ensure that the quantization resolution of the pulse edge time width is greater than 1% of the full scale. This constructs a signal discretization benchmark suitable for deep-sea pressure fluctuation environments. When the microprocessor performs continuous-domain lead phase compensation discretization, it acquires the original rotational speed pulse signal from the input port with a set sampling period Δt to generate a time-discrete sequence. .

[0036] Within the data storage area, a continuous N-period sliding sampling window is defined, containing the current sampling point k and historical sampling points. The amplitude difference between the first and last sampling points within the sliding sampling window is extracted and divided by the time span (N-1)Δt to generate a differential approximation value for the replacement continuous derivative term. This value is then multiplied by the floating-point number at the memory address where the response time constant τ is located at the corresponding sampling time to generate a feedforward compensation component. The feedforward compensation component is then combined with the basic signal sequence. The current amplitude is algebraically added, and the measured rotational speed after discrete state calibration is output. The sliding sampling window length N is selected as a positive integer of 3 or 4. The reference static pressure in the high-pressure hydraulic reactor is set to 50 MPa. The servo hydraulic pump applies dynamic pressure disturbances at low pressure change rates of 0.5 MPa / s, medium pressure change rates of 2.0 MPa / s, and high pressure change rates of 5.0 MPa / s, respectively. The Hall sensor component acquires the uncompensated raw rotational speed pulse signal under the above gradient pressure field. Data from the uncompensated control group showed that the original rotational speed pulse signal exhibited waveform broadening under the condition of 50 MPa static pressure superimposed with a high pressure change rate of 5.0 MPa / s. The measured pulse edge time width reached 284 μs, and there was a phase lag of 14.6 degrees relative to the reference rotational speed data, causing the loss of effective pulse counts received by the attitude control module. Under the same gradient condition, the microprocessor retrieved the pre-stored viscoelastic dynamic response model. Under the condition of a high pressure change rate of 5.0 MPa / s, the microprocessor calculated the equivalent pressure load based on the external environmental pressure data and the internal cavity pressure data, and updated the physical property characteristic matrix in real time. The response time constant τ, which characterizes the shear stress response delay under the current depth pressure field, was extracted to be 12.3 ms. The microprocessor discretized the original rotational speed pulse signal containing noise. Input phase compensation filter, according to the operation rules Solve for, where, This is the output signal after phase compensation. The original rotational speed pulse signal is given by τ, which is the response time constant and t is the time variable. The phase compensation filter uses the differential component driven by the response time constant τ to generate reverse compensation amplitude at the rising and falling edges of the pulse. Simultaneously, it uses the differential operation characteristics to suppress the low-frequency baseline drift generated by 50Hz power frequency harmonics and Gaussian white noise. The output intermediate state differential amplitude reaches a peak value of 3.2V in the edge transition region, which cancels the physical bias caused by rheological hysteresis in the time domain.

[0037] The microprocessor detects the steepness of the pulse edge of the calibrated speed measurement value. When the measured pulse edge time width reaches 11.5μs and exceeds the 10μs threshold, the microprocessor increases the compensation gain coefficient of the phase compensation filter by a predetermined ratio. Test group data of the method used in this invention show that within the pressure change rate gradient from 0.5MPa / s to 5.0MPa / s, the pulse edge time width of the calibrated speed measurement value converges to the range of 4.1μs to 4.8μs, and the phase error is maintained within 0.5 degrees. After the pressure change rate exceeds the critical point of 8.0MPa / s, the physical response saturation of the elastic pressure transmission medium induces transient micro-cavitation, causing the bulk modulus to drop, and the compensated phase error increases nonlinearly to 2.3 degrees. The dynamic pressure difference range corresponding to 0.5MPa / s to 5.0MPa / s constitutes the working window of the phase compensation algorithm. Within this working window, the speed sensing system overcomes the signal distortion caused by high-pressure rheology and external noise interference, and continuously outputs a stable speed pulse sequence to the attitude control module.

[0038] Example 3: When the submersible is in a deep-sea alternating pressure field, the elastic pressure-transmitting medium inside the sensing device responds to external water pressure fluctuations. The shear stress transmission within the medium exhibits nonlinear damping characteristics, causing phase drift in the rotational speed measurement signal. The microprocessor receives external environmental pressure data and internal cavity pressure data transmitted by the pressure sensor, calculates the difference between the external environmental pressure data and the internal cavity pressure data, and generates a dynamic pressure difference. The physical property characteristic matrix stored inside the microprocessor includes basic values ​​of medium density, dynamic viscosity, and bulk modulus. The dynamic pressure difference is substituted as an independent variable into a preset pressure-related quadratic polynomial to calculate the real-time drift. The microprocessor adds this real-time drift to the corresponding basic value and outputs the medium density, dynamic viscosity, and bulk modulus for the current sampling period. The integral modulus parameter is updated, and the physical property matrix is ​​called. The physical property matrix calls the preset pressure-correlated quadratic polynomial. The polynomial coefficient array is generated by the offline multi-point calibration program of the external high-pressure rheology tester. The test host drives the servo pressurization pump to establish a static pressure holding state in the sealed test cylinder filled with the same batch of elastic pressure-transmitting medium in a pressure gradient of 2MPa from 0MPa to 60MPa full scale. In each pressure stabilization cycle, the ultrasonic transducer array arranged on the end face is used to record the physical response characteristics of sound wave propagation time and broadband attenuation rate, and the measured data of medium density and dynamic viscosity at the corresponding pressure are converted and output. The test host collects the measured data in the background and uses the deviation from the normal pressure reference value as the dependent variable and the corresponding dynamic pressure difference as the independent variable. The data is input into the built-in least squares parameter identification module to extract the fitting determination coefficient. When the coefficients of the quadratic term and the constants of the linear term are greater than 0.98, they are written into the read-only data segment of the microprocessor through the programming interface to perform dynamic evolution calculations and solidify the benchmark.

[0039] The microprocessor continuously records the equivalent pressure load of the current sampling period and the previous sampling period. It obtains the transient rate of change of the equivalent pressure load through differential operations, extracts the dynamic viscosity and bulk modulus parameters of the current sampling period, calculates the ratio of the dynamic viscosity to the bulk modulus, and generates the basic relaxation time characterizing the intrinsic hysteresis properties of the medium. The microprocessor divides the transient rate of change by a preset reference pressure rate of change to generate a dimensionless load change coefficient. It then multiplies the basic relaxation time by the load change coefficient to generate a time-domain response deviation. The microprocessor identifies this time-domain response deviation as the response time constant τ, acquires the original rotational speed pulse signal, and sets... The differential compensation component of the fixed-phase compensation filter compensates for signal hysteresis caused by physical rheology. The microprocessor continuously monitors the steepness of the pulse edge of the calibrated rotation speed measurement value. When the time width of the measured pulse edge exceeds the 10μs threshold, the difference between the measured time width and the 10μs threshold is calculated and multiplied by the fixed gain adjustment step size to generate the gain compensation component. The microprocessor adds the original compensation gain coefficient to the gain compensation component and updates the phase compensation filter. The above continuous discrete algebraic operations convert the rheological disturbance at the physical level into deterministic signal filtering parameters. Under alternating pressure impact, the deep-sea rotation speed sensing system continuously outputs a stable rotation speed pulse sequence to the attitude control module.

[0040] Example 4: When the deep-sea submersible's sensing device is in the assembly stage before launching, the constant pressure calibration bench applies a standard atmospheric pressure load to the internal elastic pressure-transmitting medium. After the microprocessor confirms that the cavity temperature is at a reference of 20°C, it drives the acoustic wave node to emit an ultrasonic pulse sequence, records the round-trip propagation time and attenuation amplitude of the pulse, and converts the round-trip propagation time and attenuation amplitude into the initial sound velocity and initial attenuation coefficient, respectively. Combined with the static mass of the medium, the basic value of the medium density is calculated, and multiplied by the square of the initial sound velocity to obtain the basic value of the bulk modulus. The basic value of the dynamic viscosity is calculated based on the initial attenuation coefficient. The basic values ​​of the medium density, bulk modulus, and dynamic viscosity are written into the memory to overwrite the default array, thus establishing the initial physical property characteristic matrix.

[0041] After establishing the initial physical property characteristic matrix, the microprocessor controls the constant pressure calibration bench to gradually increase the pressure increment rate in steps of 1.0 MPa / s. The speed generator synchronously applies a constant speed to the sensing shaft. The microprocessor continuously compares the phase dispersion difference of the speed measurement values ​​under two adjacent pressure increment rates. When the phase dispersion difference exceeds the 0.1 degree threshold, the corresponding critical pressure increment rate is locked, and the reference pressure change rate is calculated by multiplying the critical pressure increment rate by a constant of 0.8. This reference pressure change rate is solidified into the dynamic evolution equation as a benchmark parameter for quantifying the load change coefficient. The uncertainty of variables caused by batch differences in the physical properties of the elastic pressure transmission medium is eliminated through an offline calibration process. The speed sensing system is then transferred to the deep-sea environment with the initial physical property baseline solidified.

[0042] Example 5: When the deep-sea submersible's sensing device faces long-term anchoring monitoring in the deep-sea environment, the elastic pressure-transmitting medium may experience long-term high-pressure penetration or microstructural fatigue induced by temperature cycling, resulting in reference property drift. The microprocessor initiates an adaptive reference reshaping mode. When it detects that the submersible is in quasi-static suspension and the standard deviation of external environmental pressure fluctuations is below the 0.01MPa threshold for 100 consecutive sampling periods, it determines that the system has entered a pressure equilibrium steady state. The microprocessor then reads the dynamic differential pressure residual value output by the current pressure sensor and removes this dynamic differential pressure residual value as a static deviation from the input of the physical property feature matrix, achieving real-time alignment of the physical zero point.

[0043] After the microprocessor completes zero-point alignment, it controls the built-in self-test signal source to input an analog pulse sequence with a nominal frequency of 100Hz and a fixed edge steepness to the phase compensation filter. The microprocessor calculates the gain correction factor by comparing the algebraic residual between the measured pulse edge steepness at the output of the phase compensation filter and the preset nominal steepness. The gain correction factor is multiplied by the original compensation gain coefficient of the phase compensation filter to obtain the updated compensation parameter, and this parameter overwrites the old value in the memory. The above closed-loop feedback mechanism translates the aging loss of the sensing hardware into the adaptive adjustment increment of the digital compensation model, ensuring that the speed sensing system maintains the extraction accuracy of the response time constant τ and the consistency of signal calibration under long-term service conditions.

[0044] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit of this application and the scope of protection of this invention, and all of these forms are within the protection scope of this application.

Claims

1. A real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing, characterized in that, Includes the following steps: Step S101: Collect external environmental pressure data and internal cavity pressure data of the deep-sea sensing device, and calculate the dynamic pressure difference between the inside and outside of the device. Step S102: Input the dynamic pressure difference into the pre-stored viscoelastic dynamic response model in the internal storage space of the microprocessor. The viscoelastic dynamic response model converts the dynamic pressure difference into an equivalent pressure load acting on the elastic pressure transmission medium in the sensing cavity through the built-in physical property feature matrix, and updates the medium density, dynamic viscosity and bulk modulus parameters stored in the physical property feature matrix in real time according to the equivalent pressure load. Step S103: Based on the numerical drift characteristics of each physical property parameter in the physical property feature matrix as it evolves with the time axis, calculate the shear stress response delay of the elastic pressure transmission medium under the current depth pressure field, and extract the corresponding response time constant accordingly to quantify and define the transient phase offset of the elastic pressure transmission medium to the rotational speed pulse signal. Step S104: Obtain the original rotational speed pulse signal output by the sensing component. The original rotational speed pulse signal has phase lag characteristics induced by viscous damping caused by high pressure compression of the elastic pressure transmission medium and waveform distortion characteristics at the edge of the pulse signal. Step S105: Construct a phase compensation filter using the response time constant, and perform a first-order lead phase compensation operation on the original speed pulse signal through the phase compensation filter to compensate for the signal hysteresis caused by the elastic pressure transmission medium, and output the calibrated speed measurement value.

2. The real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing according to claim 1, characterized in that, Step S102 involves updating the parameters stored in the physical property feature matrix in real time based on the equivalent pressure load, including: retrieving the preset array of initial physical property parameters of the elastic pressure transmission medium in the physical property feature matrix; inputting the equivalent pressure load as an independent variable into the dynamic evolution equation corresponding to the physical property feature matrix, and calculating the real-time drift of the initial physical property parameters under the current dynamic pressure difference; and using the real-time drift to numerically cover the initial physical property parameters to obtain an input reference used to characterize the phase distortion of the original rotational speed pulse signal.

3. The real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing according to claim 1, characterized in that, Step S103 extracts the response time constant characterizing the phase delay characteristics of the elastic pressure transmission medium at the current depth, including: monitoring the transient change rate of the medium property parameters in the material property matrix with the equivalent pressure load; calculating the time domain response deviation between the transient change rate and the equivalent pressure load, the time domain response deviation being used to characterize the delay effect of physical damping on signal propagation; and confirming the time domain response deviation as the response time constant, which is used as the weighting weight for dynamic phase correction of the original rotational speed pulse signal.

4. The real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing according to claim 1, characterized in that, After outputting the calibrated speed measurement value in step S105, the method further includes: detecting the pulse edge steepness of the calibrated speed measurement value; when the pulse edge time width is detected to exceed the preset 10μs threshold, automatically increasing the compensation gain coefficient of the phase compensation filter to suppress the signal waveform broadening caused by the elastic pressure transmission medium and ensure the integrity of speed pulse signal tracking under the variable acceleration rotation condition of the deep submersible.

5. The real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing according to claim 1, characterized in that, Before step S101, the process also includes: filling the sensing cavity with an elastic pressure-transmitting medium, using the volume deformation of the elastic pressure-transmitting medium under pressure to perform static balance adjustment of the internal and external pressures of the device, and using the elastic pressure-transmitting medium to transmit the external seawater pressure to the internal pressure sensing unit through physical deformation, thus providing a physical source of internal cavity pressure data for step S101.

6. The real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing according to claim 1, characterized in that, In step S102, the viscoelastic dynamic response model is preset by defining a logic operation range in the internal non-volatile memory of the microprocessor. The logic operation range has an independent data bus channel, which is used to retrieve the real-time drift amount in the material property characteristic matrix and transmit it to the phase compensation filter in real time.

7. The real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing according to claim 1, characterized in that, In step S104, the original rotation speed pulse signal is acquired non-contactly through a Hall sensor or a photoelectric pulse generator. Before entering the microprocessor, the original rotation speed pulse signal is first processed by a limiting circuit to filter out common-mode interference noise introduced by the deep-sea submersible's power supply, ensuring the signal purity of the input phase compensation filter.

8. The real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing according to claim 1, characterized in that, The method establishes a closed-loop self-compensation logic through pressure data acquisition, physical property parameter update, and signal feature reconstruction, so that each set of calibrated speed measurement values ​​output is associated with the response time constant of the corresponding sampling time.

9. The real-time pressure self-compensation and precise measurement control method for deep-sea rotation speed sensing according to claim 1, characterized in that, After outputting the calibrated rotational speed measurement value in step S105, the calibrated rotational speed measurement value is sent to the attitude control module of the deep-sea submersible as dynamic input data to evaluate the operating status of the deep-sea submersible. The auxiliary navigation system performs real-time correction of the deep-sea submersible's navigation trajectory and reconstructs its motion attitude.

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