Seawater detection system based on wireless disposable temperature-salinity-depth sensor

Abstract

The invention relates to the field of seawater detection, and particularly discloses a seawater detection system based on a wireless disposable temperature-salinity-depth sensor, which comprises an underwater sensor unit, a water surface relay unit and a data analysis terminal, and realizes accurate adjustment of the movement speed of the sensor through closed-loop feedback control. Wherein the underwater sensor unit comprises a pressure self-adaptive buoyancy system, a multi-parameter sensing array and an anti-interference communication module; the closed-loop feedback control takes real-time speed deviation as input; according to the invention, by adopting a dynamic buoyancy adjustment and self-adaptive communication strategy, stable motion control precision and data transmission reliability can be maintained under complex hydrological conditions. The pressure self-adaptive buoyancy system realizes quick response through linkage of a micro air pump and a compressed air cylinder, and can automatically adapt to different ocean scenes by combining three intelligent working modes, so that high-precision data acquisition can still be completed under a five-level sea condition, and the operation robustness in a severe environment is greatly improved.

Description

Technical Field

[0001] The invention belongs to the field of seawater detection, in particular to a seawater detection system based on a wireless disposable temperature, salinity and depth sensor. Background Art

[0002] In marine environmental monitoring, accurate acquisition of temperature, salinity, and depth (CTD) data is crucial for marine scientific research, resource exploration, and climate forecasting. Traditional CTD sensors, often cable-tethered or self-contained, have limitations such as complex deployment, high recovery costs, and poor real-time performance. In recent years, wireless disposable sensors have gained increasing attention due to their ease of operation and low cost. These sensors utilize self-adjusting buoyancy to achieve controlled sinking and surfacing, while simultaneously transmitting collected data to a surface platform in real time via wireless communication.

[0003] Existing technologies typically employ open-loop or simple closed-loop mechanisms for buoyancy control, such as airbag inflation and deflation based on a preset time or depth. However, these methods struggle to cope with complex dynamic factors in the ocean environment, such as sudden changes in seawater density gradients and turbulent disturbances. This can lead to unstable sensor motion (with deviations often exceeding ±0.5 m / s), compromising the vertical resolution and temporal consistency of data acquisition. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a seawater detection system based on a wireless disposable temperature, salinity and depth sensor to solve the problems in the existing technology such as insufficient buoyancy control accuracy leading to unstable movement speed, poor communication reliability and inability to adapt to dynamic changes in complex marine environments.

[0005] A seawater detection system based on a wireless disposable temperature, salinity and depth sensor includes an underwater sensor unit, a surface relay unit and a data analysis terminal. The system achieves precise adjustment of the sensor movement speed through closed-loop feedback control, wherein:

[0006] The underwater sensor unit includes a pressure adaptive buoyancy system, a multi-parameter sensor array and an anti-interference communication module;

[0007] The closed-loop feedback control takes the real-time speed deviation as input and realizes speed control through the three-level linkage of buoyancy adjustment calculation, actuator response and environmental compensation;

[0008] The buoyancy regulation is dynamically coupled with the data transmission power to form a collaborative optimization control loop.

[0009] Preferably, the core algorithm of the closed-loop feedback control includes the velocity-buoyancy coupling equation:

[0010]

[0011] Where: v(t) is the real-time speed, obtained by differential calculation of the depth sensor; v0 is the basic speed setting value; F b (τ) is the buoyancy, which is converted by measuring the pressure difference between the inside and outside of the bladder; F target is the target buoyancy; m is the mass of the sensor; K is the gain coefficient adjusted according to the seawater density gradient; τ is the time integral variable.

[0012] Preferably, the target buoyancy F target The calculation of takes into account the influence of fluid resistance and pressure gradient, and the calculation formula is:

[0013]

[0014] Where: mg is the sensor gravity compensation item; C d is the dimensionless fluid resistance coefficient; ρ w is the density of seawater; A is the flow cross-sectional area of ​​the sensor; v d is the preset diving speed; is the steady-state fluid resistance term; β is the pressure gradient compensation coefficient; ΔP is the ambient pressure gradient; βΔP is the pressure gradient compensation term.

[0015] Preferably, the pressure gradient ΔP is calculated using the discretized form of the fluid continuity equation:

[0016]

[0017] in, is the depth change rate; ρ w is the density of seawater.

[0018] Preferably, the dynamic response performance of the buoyancy regulation system is constrained by a time constant:

[0019]

[0020] Among them: A pump is the effective area of ​​the air pump; ΔF max is the maximum buoyancy adjustment; ΔF error For the allowable error.

[0021] Preferably, the communication module adopts a power adaptive strategy, and its transmission power P tx The adjustment strategy is:

[0022]

[0023] Contains: P0 is the reference transmission power; α is the underwater acoustic signal attenuation coefficient; d is the current water depth; e αd is the water depth compensation term; v(t) is the current movement speed; v d is the target movement speed.

[0024] Preferably, the quantitative relationship between the communication bit error rate BER and the transmission power is determined by an error function:

[0025]

[0026] Where erfc(·) is the complementary error function; G r is the receiving antenna gain; N0 is the noise power spectral density; B is the communication channel bandwidth.

[0027] Preferably, the real-time adjustment algorithm of the gain coefficient K is:

[0028]

[0029] Where: K0 is the basic gain coefficient; γ is the density sensitivity coefficient; is the seawater density gradient.

[0030] Preferably, the mechanical design of the buoyancy system satisfies the volume adjustment range formula:

[0031]

[0032] Where V0 is the nominal volume of the buoyancy system; ΔF max The maximum buoyancy adjustment.

[0033] Preferably, there are three working modes, and the mode switching conditions are:

[0034] Constant velocity profile mode: enabled when the density gradient detected is less than the set threshold;

[0035] Jump-layer focusing mode: enabled when the density gradient detected is greater than the set threshold;

[0036] Emergency ascent mode: triggered when the depth exceeds the safety threshold or the power supply voltage is abnormal.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] By adopting dynamic buoyancy regulation and adaptive communication strategies, it is able to maintain stable motion control accuracy and data transmission reliability under complex hydrological conditions. The pressure-adaptive buoyancy system achieves rapid response through the linkage of a micro air pump and compressed gas cylinder. Combined with three intelligent working modes, it can automatically adapt to different marine scenarios, ensuring high-precision data acquisition even in sea conditions of level 5, significantly improving operational robustness in harsh environments.

[0039] The dynamic coupling of buoyancy regulation and communication power ensures real-time data and optimizes energy efficiency. The mechanical design balances regulation capability with structural safety through a volumetric adjustment formula. Furthermore, a density gradient-driven gain coefficient adjustment algorithm and pressure gradient compensation mechanism effectively suppress control deviations caused by sudden environmental changes, enabling the sensor to maintain its preset trajectory in complex areas such as thermocline zones. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 Schematic diagram of the system of the present invention. DETAILED DESCRIPTION

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0042] like Figure 1 As shown:

[0043] Example 1: The present invention provides a seawater detection system based on a wireless disposable temperature, salinity and depth sensor, comprising an underwater sensor unit, a surface relay unit and a data analysis terminal. The system achieves precise adjustment of the sensor movement speed through closed-loop feedback control, wherein:

[0044] The underwater sensor unit includes a pressure-adaptive buoyancy system, a multi-parameter sensor array, and an anti-interference communication module;

[0045] Closed-loop feedback control uses real-time speed deviation as input and achieves speed control through a three-level linkage of buoyancy adjustment calculation, actuator response, and environmental compensation.

[0046] Buoyancy regulation and data transmission power are dynamically coupled to form a collaborative optimization control loop;

[0047] The pressure-adaptive buoyancy system dynamically controls buoyancy by adjusting the pressure differential between the inside and outside of the bladder. A multi-parameter sensor array collects real-time seawater temperature (measurement range -2°C to 35°C, accuracy ±0.01°C), salinity (conductivity range 0-65mS / cm, accuracy ±0.01mS / cm), and depth data (0-500dbar, accuracy ±0.5%FS). The anti-interference communication module uses the AES128 encryption algorithm to ensure data transmission security (communication rate ≥1.2kbps, distance ≥15km).

[0048] Closed-loop feedback control uses real-time velocity deviation as input and achieves precise regulation through a three-stage linkage: first, the buoyancy adjustment is calculated based on the velocity-buoyancy coupling equation, where the target buoyancy comprehensively compensates for gravity, fluid resistance, and pressure gradient; second, a micro air pump is used to rapidly adjust the buoyancy; and finally, dynamic environmental compensation is performed by combining the seawater density gradient. Buoyancy adjustment is dynamically coupled with data transmission power. When the sensor's sinking speed exceeds a preset value, the communication module automatically increases the transmission power.

[0049] The system can still operate stably in sea conditions up to level 5, completing a 500-meter profile measurement within 6 minutes with a data sampling rate of 4Hz. The data analysis terminal receives data in real time via satellite communications and uses an adaptive Kalman filter algorithm to eliminate noise. The temperature resolution reaches 0.001°C and the salinity resolution reaches 0.001mS / cm, providing high-precision hydrological data for marine scientific research.

[0050] The bladder pressure is regulated by an intelligent inflation and deflation mechanism, which achieves precise control through the coordinated work of a micro air pump and a compressed gas cylinder;

[0051] When buoyancy needs to be increased, a micro-pump injects gas from a compressed gas cylinder into the bladder, causing it to expand. To reduce buoyancy, a solenoid valve opens, releasing gas to deflate the bladder. The compressed gas cylinder provides a stable, high-pressure gas source, while the micro-pump precisely regulates the amount of air entering. Together, they deliver rapid response. This entire adjustment process is automatically controlled by the pressure sensor, providing real-time feedback and controlling the pace of inflation and deflation, ensuring the sensor maintains optimal operating conditions at varying water depths.

[0052] Specifically, the core algorithm of closed-loop feedback control includes the velocity-buoyancy coupling equation:

[0053]

[0054] Where: v(t) is the real-time speed, obtained by differential calculation of the depth sensor; v0 is the basic speed setting value; F b (τ) is the buoyancy, which is converted by measuring the pressure difference between the inside and outside of the bladder; F target is the target buoyancy; m is the sensor mass; K is the gain coefficient adjusted according to the seawater density gradient; τ is the time integral variable;

[0055] Among them, the real-time speed v(t) is determined by the basic speed v0 and the buoyancy deviation integral term. The system continuously calculates the current buoyancy F b (τ) and target buoyancy F target The difference is combined with the sensor mass m and the dynamic gain coefficient K to dynamically adjust the sinking or floating speed;

[0056] F b (τ) is measured in real time through the pressure difference between the inside and outside of the bladder, directly reflecting the current buoyancy state, F targetThe comprehensive fluid resistance, gravity and environmental pressure gradient are pre-set to provide a benchmark for speed control. The coefficient K is dynamically adjusted according to the seawater density gradient to enhance the algorithm's adaptability to environmental changes.

[0057] Specifically, the target buoyancy F target The calculation of takes into account the influence of fluid resistance and pressure gradient, and the calculation formula is:

[0058]

[0059] Where: mg is the sensor gravity compensation item; C d is the dimensionless fluid resistance coefficient; ρ w is the density of seawater; A is the flow cross-sectional area of ​​the sensor; v d is the preset diving speed; is the steady-state fluid resistance term; β is the pressure gradient compensation coefficient; ΔP is the ambient pressure gradient; βΔP is the pressure gradient compensation term;

[0060] Among them, gravity compensation, fluid resistance compensation and pressure gradient compensation enable the target buoyancy to dynamically adapt to the complex changes in the underwater environment, providing a stable motion control foundation for the sensor, allowing it to dive or float accurately at a preset speed;

[0061] mg represents the sensor's own gravity, which serves as the basic reference value for buoyancy adjustment. is the steady-state fluid resistance term, which is expressed by the fluid resistance coefficient C d , seawater density ρ w , the sensor's flow cross-sectional area A and the preset diving speed v d Calculated to offset the effects of fluid resistance on the sensor during movement, βΔP is the ambient pressure gradient compensation term, where β is the compensation coefficient and ΔP is the ambient pressure gradient. This term corrects for pressure fluctuations caused by changes in seawater density or depth, ensuring accurate buoyancy adjustment.

[0062] Specifically, the calculation of the pressure gradient ΔP adopts the discretized form of the fluid continuity equation:

[0063]

[0064] in, is the depth change rate; ρ w is the density of seawater.

[0065] Among them, this formula provides real-time pressure gradient data for the closed-loop control system to correct the target buoyancy F target The compensation term (βΔP) in is used to adapt to pressure fluctuations at different water depths and motion states, ensuring the accuracy of buoyancy regulation.

[0066] By seawater density ρ w , gravitational acceleration g, depth change rate (i.e., the depth change per unit time) and the inverse of the real-time velocity v(t) to dynamically calculate the ambient pressure gradient;

[0067] Reflects the speed of the vertical movement of the sensor, and combined with the real-time velocity v(t), characterizes the dynamic characteristics of pressure changes with depth; ρ w It reflects the static pressure gradient of seawater and is the benchmark factor for pressure changes.

[0068] Example 2: This example is basically the same as the previous example, except that the dynamic response performance of the buoyancy adjustment system is constrained by a time constant:

[0069]

[0070] Among them: A pump is the effective area of ​​the air pump; ΔF max is the maximum buoyancy adjustment; ΔF error is the allowable error;

[0071] Among them, this formula quantifies the time required for the system to trigger the adjustment and reach the target buoyancy, which is affected by the sensor mass m, seawater density ρ w , gain coefficient K and other parameters.

[0072] Specifically, the communication module adopts a power adaptive strategy, and its transmission power P tx The adjustment strategy is:

[0073]

[0074] Contains: P0 is the reference transmission power; α is the underwater acoustic signal attenuation coefficient; d is the current water depth; e αd is the water depth compensation term; v(t) is the current movement speed; v d is the target movement speed;

[0075] Among them, the power adaptive strategy of the communication module adjusts the transmission power P intelligently tx To ensure data transmission reliability; When the actual speed v(t) of the sensor deviates from the target value v d When the signal is disturbed by turbulence or unstable motion, the power is increased proportionally to offset the signal interference caused by turbulence or unstable motion.

[0076] Specifically, the quantitative relationship between the communication bit error rate BER and the transmission power is determined by the error function:

[0077]

[0078] Where erfc(·) is the complementary error function; G r is the receiving antenna gain; N0 is the noise power spectral density; B is the communication channel bandwidth;

[0079] Among them, this formula is the quantitative relationship between communication bit error rate (BER) and transmission power, which is accurately characterized by a mathematical model. When P tx This formula quantifies the improvement in communication quality when dynamically adjusted according to water depth and speed.

[0080] Specifically, the real-time adjustment algorithm of the gain coefficient K is:

[0081]

[0082] Where: K0 is the basic gain coefficient; γ is the density sensitivity coefficient; is the seawater density gradient;

[0083] Among them, the real-time adjustment algorithm of the gain coefficient K optimizes the control performance by dynamically responding to changes in seawater density; when the sensor passes through the density jump layer (such as ), K automatically increases to enhance the closed-loop control response speed and suppress speed fluctuations;

[0084] In uniform water In the process, K returns to the base value K0 to avoid over-adjustment.

[0085] Example 3: This example is basically the same as the previous example, except that the mechanical design of the buoyancy system satisfies the volume adjustment range formula:

[0086]

[0087] Where V0 is the nominal volume of the buoyancy system; ΔF max is the maximum buoyancy adjustment;

[0088] Among them, this system clarifies the mechanical design boundary of the buoyancy system through the volume adjustment range formula and quantifies the limit range of the bladder expansion / contraction (for example, when the nominal volume V0 = 500mL, if ΔF max =10N, the upper limit of volume adjustment is about 1.1V0), ensuring structural safety.

[0089] Specifically, there are three working modes, and the mode switching conditions are:

[0090] Constant velocity profile mode: enabled when the density gradient detected is less than the set threshold;

[0091] Jump-layer focusing mode: enabled when the density gradient detected is greater than the set threshold;

[0092] Emergency ascent mode: triggered when the depth exceeds the safety threshold or the power supply voltage is abnormal.

[0093] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0094] In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other.

[0095] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A seawater detection system based on a wireless disposable temperature, salinity and depth sensor, characterized in that: The system comprises an underwater sensor unit, a surface relay unit and a data analysis terminal. The system achieves precise adjustment of the sensor movement speed through closed-loop feedback control, wherein: The underwater sensor unit includes a pressure adaptive buoyancy system, a multi-parameter sensor array and an anti-interference communication module; The closed-loop feedback control takes the real-time speed deviation as input and realizes speed control through the three-level linkage of buoyancy adjustment calculation, actuator response and environmental compensation; The buoyancy regulation is dynamically coupled with the data transmission power to form a collaborative optimization control loop.

2. A seawater detection system based on a wireless disposable temperature, salinity and depth sensor as claimed in claim 1, characterized in that: The core algorithm of the closed-loop feedback control includes the velocity-buoyancy coupling equation: Where: v(t) is the real-time speed, obtained by differential calculation of the depth sensor; v0 is the basic speed setting value; F b (τ) is the buoyancy, which is converted by measuring the pressure difference between the inside and outside of the bladder; F target is the target buoyancy; m is the mass of the sensor; K is the gain coefficient adjusted according to the seawater density gradient; τ is the time integral variable.

3. A seawater detection system based on a wireless disposable temperature, salinity and depth sensor as claimed in claim 2, characterized in that: The target buoyancy F target The calculation of takes into account the influence of fluid resistance and pressure gradient, and the calculation formula is: Where: mg is the sensor gravity compensation item; C d is the dimensionless fluid resistance coefficient; ρ w is the density of seawater; A is the flow cross-sectional area of ​​the sensor; v d is the preset diving speed; is the steady-state fluid resistance term; β is the pressure gradient compensation coefficient; ΔP is the ambient pressure gradient; βΔP is the pressure gradient compensation term.

4. A seawater detection system based on a wireless disposable temperature, salinity and depth sensor as claimed in claim 3, characterized in that: The calculation of the pressure gradient ΔP adopts the discretized form of the fluid continuity equation: in, is the depth change rate; ρ w is the density of seawater.

5. A seawater detection system based on a wireless disposable temperature, salinity and depth sensor as claimed in claim 4, characterized in that: The dynamic response performance of the buoyancy control system is constrained by the time constant: Among them: A pump is the effective area of ​​the air pump; ΔF max is the maximum buoyancy adjustment; ΔF error For the allowable error.

6. A seawater detection system based on a wireless disposable temperature, salinity and depth sensor as claimed in claim 5, characterized in that: The communication module adopts a power adaptive strategy, and its transmission power P tx The adjustment strategy is: Contains: P0 is the reference transmission power; α is the underwater acoustic signal attenuation coefficient; d is the current water depth; e αd is the water depth compensation term; v(t) is the current movement speed; v d is the target movement speed.

7. A seawater detection system based on a wireless disposable temperature, salinity and depth sensor as claimed in claim 6, characterized in that: The quantitative relationship between the communication bit error rate BER and the transmission power is determined by the error function: Where erfc(·) is the complementary error function; G r is the receiving antenna gain; N0 is the noise power spectral density; B is the communication channel bandwidth.

8. The seawater detection system based on a wireless disposable temperature, salinity and depth sensor as claimed in claim 2, characterized in that: The real-time adjustment algorithm of the gain coefficient K is: Where: K0 is the basic gain coefficient; γ is the density sensitivity coefficient; is the seawater density gradient.

9. The seawater detection system based on a wireless disposable temperature, salinity and depth sensor as claimed in claim 1, characterized in that: The mechanical design of the buoyancy system satisfies the volume adjustment range formula: Where V0 is the nominal volume of the buoyancy system; ΔF max is the maximum buoyancy adjustment; ρ w is the density of seawater.

10. The seawater detection system based on wireless disposable temperature, salinity and depth sensor according to claim 1, characterized in that: Contains three working modes, and the mode switching conditions are: Constant velocity profile mode: enabled when the density gradient detected is less than the set threshold; Jump-layer focusing mode: enabled when the density gradient detected is greater than the set threshold; Emergency ascent mode: triggered when the depth exceeds the safety threshold or the power supply voltage is abnormal.

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