A Passive Buoyancy Compensation Device and Method Based on a Multi-Stage Accumulator

Abstract

The present invention discloses a passive buoyancy compensation device and method based on a multi-stage accumulator. The passive buoyancy compensation device includes a pressure-resistant housing provided with a plurality of accumulator cavities, and each accumulator cavity is provided with an accumulator made of an elastic bladder; openings are provided at the top and bottom of the accumulator cavity. Among them, the opening of the accumulator is connected to the top opening of the accumulator cavity and is sealed by an accumulator plug; the accumulator plug is used to adjust the volume adjustment liquid in the accumulator; the bottom openings of the accumulator cavities are uniformly connected to a hydraulic pipeline and then communicated with the outside of the pressure-resistant housing. The device of the present invention is safe, small in volume and does not require energy consumption, and can solve the problem of excessive change in net buoyancy during the diving and surfacing processes of submersible equipment.

Description

Technical Field

[0001] The present invention relates to the field of buoyancy compensation for submersibles, and particularly to a passive buoyancy compensation device and method based on a multi-stage accumulator. Background Art

[0002] When a submersible device dives, it needs negative buoyancy within a certain range to ensure the diving speed. Similarly, when surfacing, it needs positive buoyancy within a certain range. When diving very deep, the seawater density changes greatly, and the compressibility of seawater needs to be considered, that is, as the sea depth increases, the ocean density will increase. Generally, the compressibility of a submersible device is less than that of seawater, so that the negative buoyancy value of the submersible device will decrease with the increase of the diving depth during the diving process, resulting in difficulty in diving at large diving depths. Therefore, during the diving process of a submersible device, in order to maintain the diving speed, it is necessary to compensate the negative buoyancy of the equipment to a certain extent. Currently, the buoyancy compensation technologies used are as follows:

[0003] 1. Oil bladder oil injection buoyancy compensation: It belongs to an active buoyancy compensation technology. According to the diving state of the submersible device (mainly the diving speed) and the ocean depth where it is located, etc., actively control the amount of oil in the oil bladder, and then change the overall buoyancy condition of the equipment to achieve active compensation of buoyancy. That is, during the diving process, as the depth increases and the negative buoyancy value decreases, the diving speed decreases. At this time, part of the oil liquid is pumped from the external oil bladder into the cavity, thereby reducing the overall displacement of the equipment and achieving compensation for negative buoyancy. From this process, it can be seen that this method requires some sensors for judgment, consumes energy, and has low safety, and it is difficult to pump oil in the case of large ocean depths.

[0004] 2. Buoyancy compensation liquid type buoyancy compensation: It belongs to a passive buoyancy compensation technology. The buoyancy compensation liquid has a certain compressibility (greater than that of seawater), and uses the water pressure change during the diving process to change the volume of the buoyancy compensation liquid, thereby affecting the overall displacement of the equipment and achieving passive buoyancy compensation. In "Haiyan-X", silicone oil with high compressibility is used as the buoyancy compensation liquid. For "Haiyan-X" with a body weight of 398.55 Kg, in order to dive to 10,000 m, 48.6 L of silicone oil is used for buoyancy compensation. During the compensation process, no active control is required and no energy is consumed, but the disadvantage is that the buoyancy compensation liquid occupies a large volume and has a large mass. Therefore, a passive buoyancy compensation technology that is safe, small in volume and does not require energy consumption is needed. Summary of the Invention

[0005] The present invention provides a passive buoyancy compensation device based on a multi-stage accumulator, which is safe, small in volume and does not require energy consumption, and can solve the problem of excessive change in net buoyancy during the diving and surfacing processes of submersible equipment.

[0006] A passive buoyancy compensation device based on a multi-stage accumulator, comprising a pressure-resistant housing provided with a plurality of accumulator cavities, and an accumulator made of an elastic bladder is arranged in each accumulator cavity;

[0007] Openings are provided at the top and bottom of the accumulator cavity. Among them, the opening of the accumulator is connected to the top opening of the accumulator cavity and is sealed by cooperation with an accumulator plug; the accumulator plug is used to adjust the volume adjustment liquid in the accumulator; the bottom openings of the accumulator cavities are uniformly connected to a hydraulic pipeline and then communicated with the outside of the pressure-resistant housing.

[0008] The present invention also provides a passive buoyancy compensation method based on a multi-stage accumulator, using the above passive buoyancy compensation device to perform buoyancy compensation for the diving and surfacing of a subsea device. Among them, in the passive buoyancy compensation device, the selection and configuration process of the multi-stage accumulator includes the following steps:

[0009] (1) Use a CTD (Conductivity-Temperature-Depth) instrument to measure the ocean density and pressure corresponding to the depth h of the subsea area, and respectively fit to obtain the relationship ρ between seawater density and depth h and the relationship P between pressure and depth h ;

[0010] (2) According to the relationship P between the subsea area pressure and depth h , combined with the material and shape of the subsea device, use finite element software simulation to obtain the change of the drainage volume of the device with depth V during the entire diving process 排h , then the net buoyancy of the device changes with depth h as: F 净浮h = F 浮h - G = ρ h gV 排h - mg;

[0011] Among them, F 浮h is the buoyancy force on the device at a depth of h, G is the gravity of the device, m is the mass of the device, and g is the acceleration due to gravity;

[0012] (3) Determine the parameter range of a single accumulator and the number d of accumulators required; among them, the parameters of the accumulator include the pre-charge pressure P j and the accumulator volume V j , j represents the number of the accumulator;

[0013] (4) Determine the fitness function, specifically as follows:

[0014] (4-1) The buoyancy force that can be provided when a single accumulator contracts is f j ;

[0015] (4-2) The accumulators are arranged in ascending order according to the pre-charge pressure, and are successively (P1, V1), (P2, V2), …, (P d , Vd ) After they are combined, the net buoyancy reduction of the submersible equipment is F X ;

[0016] (4-3) Taking 1m as the interval, the depth h = [0, 1, 2, …, H] is taken, and the buoyancy compensation requirements F at different depths are calculated 净浮h and the accumulator compensation value F X The difference ΔF = F 净浮h - F X ;

[0017] (4-4) Take Value1 = max(ΔF) + |min(ΔF)|, which is the sum of the absolute values of the positive and negative changes in buoyancy during the upward or downward movement of the equipment after compensation; take as the average deviation of buoyancy during the upward or downward movement of the equipment after compensation;

[0018] (4-5) Introduce weights W1 and W2 such that W1, W2 ∈ [0, 1] and W1 + W2 = 1. The fitness function is:

[0019] Value = W1 × Value1 + W2 × Value2

[0020] In the formula, the smaller the Value, the smaller the buoyancy change and the better the buoyancy compensation effect. Adjust the weight values W1 and W2 according to the buoyancy compensation requirements;

[0021] (5) Determine the parameters of the accumulator through the particle swarm optimization algorithm;

[0022] (6) Configure the multi-stage accumulator according to the parameters of the accumulator.

[0023] In step (3), the pre-charge pressure P j of a single accumulator ranges from

[0024] P j ∈ [0, P B

[0025] where P B is the maximum water pressure in the area where the submersible is located;

[0026] The volume V j of a single accumulator ranges from:

[0027] V j ∈ [V jmin , V jmax = [0.05, ΔF 净浮max / g]

[0028] where ΔF 净浮max = max|F 净浮h ​|, which is the maximum value of the net buoyancy change, and the volume unit is L.

[0029] The number d of accumulators is generally taken as 2 to 5, which is determined by the required buoyancy compensation effect. The better the required buoyancy compensation effect, the more the number of accumulators.

[0030] In step (4-1), the buoyancy that can be provided when a single accumulator contracts is:

[0031]

[0032] In the formula, P0 is the atmospheric pressure. When the diving depth satisfies , the accumulator will start to contract to provide buoyancy.

[0033] In step (4-2), F X is a piecewise function, and the formula is:

[0034]

[0035] In step (5), when the number of accumulators is d, the parameters to be determined are x = (P1, P2,..., P d , V1, V2,..., V d ), and the specific determination process is as follows:

[0036] (5-1) Initialization

[0037] A group of D-dimensional vectors x is called a particle. For the position interval of a single particle:

[0038] x max = (x max-1 , x max-2 ,..., x max-D ) = (P B , P B ,..., P B , V max , V max ,..., V max )

[0039] x min = (x min-1 , x min-2 ,..., x min-D ) = [0, 0,..., 0, V min , V min ,..., V min )

[0040] Set the speed interval as:

[0041] v max = (v max-1 , v max-2 ,..., vmax-D ) = [0.5, 0.5, …, 0.5, 0.05, 0.05, …, 0.05]

[0042] v min = -v max

[0043] For the position value of the i-th dimension of the particle, it should satisfy x i ∈ [x min-i , x max-i , and the velocity value should satisfy v i ∈ [v min-i , v max-i ; Each particle of the algorithm represents a potential solution to the problem. Let the population size N = 100, and randomly initialize the velocity and position of each solution in the search space. Subsequently, iterative calculations are performed on these N groups of potential solutions;

[0044] x n-i = rand(x min-i , x max-i )

[0045] v n-i = rand(v min-i , v max-i )

[0046] x n-i is the position value of the i-th dimension data of the n-th particle in the population. When randomly initializing, take the value in its corresponding position interval [x min-i , x max-i ; v n-i is the velocity value of the i-th dimension data of the n-th particle in the population. When randomly initializing, take the value in its corresponding velocity interval [v min-i , v max-i ;

[0047] (5 - 2): Particle fitness value calculation

[0048] Substitute the position vector of each particle into the fitness function Value = W1 × Value1 + W2 × Value2 to calculate the fitness value Value of each particle n ;

[0049] (5 - 3): Record the individual extreme value and the global extreme value

[0050] Record the position data with the smallest individual fitness value as the individual extreme value: Q n = (Q n1 , Q n1 , …, Q nD) The currently initialized position data is the individual extreme value data of the corresponding particle; compare the fitness values of each particle, and the particle with the smallest fitness value is recorded as the global extreme value: Q g =(Q g1 ,Q g1 ,…,Q gD );

[0051] (5-4): Update the velocity and position. If it exceeds, then in each iteration, the particle updates its own velocity and position through the individual extreme value and the global extreme value, that is

[0052]

[0053]

[0054] where ω k is the inertia weight, ω k =ω start (ω start -ω end )(T max -k) / T max , ω start =0.9, ω end =0.4; T max is the maximum number of iterations, k is the current number of iterations, and k = 1 at the first update; u = 1, 2, 3, …, D; i = 1, 2, 3, …, n; V iu is the velocity of the particle; c1 and c2 are non-negative constants, called acceleration factors; r1 and r2 are random numbers distributed in the interval [0, 1];

[0055] If the calculated particle position and velocity exceed their position interval and velocity interval, then adjust the position or velocity. If it is greater than the maximum value, take the maximum value; if it is less than the minimum value, take the minimum value;

[0056] (5-5): Calculate the particle fitness value

[0057] Substitute the updated position of each particle into the fitness function to calculate the fitness value of each particle

[0058] (5-6): Update the individual extreme value and the global extreme value

[0059] Record the position data with the smallest particle fitness value as the individual extreme value: Q n =(Q n1 ,Q n1 ,…,Q nD ); Compare the fitness values of each particle, and the particle with the smallest fitness value is recorded as the global extreme value: Q g =(Q g1 ,Qg1 , …, Q gD ), and the corresponding fitness value is denoted as Value g ;

[0060] (5 - 7): Determine whether the termination condition is satisfied

[0061] Determine the fitness value requirement Value according to the buoyancy compensation requirement need , and set the maximum number of iterations T max , when Value g < Value need or T > T max , terminate the calculation, and at this time Q g =(Q g1 , Q g1 , …, Q gD ) is the optimal solution obtained by the particle swarm optimization algorithm, and the corresponding fitness value is Value g ; otherwise, continue to execute step (5 - 4);

[0062] Among them, Q g corresponds to a set of optimal accumulator parameter configurations x = (P1, P2, …, P d , V1, V2, …, V d )=(Q g1 , Q g1 , …, Q gD ), d = D / 2, P1 and V1 represent the pre - charge pressure and effective volume of the first accumulator.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] 1. The present invention innovatively selects multiple accumulators with different volumes and pre - charge pressures for buoyancy compensation, which is convenient to use; the accumulators are selected before use, and no active control is required during use, no energy consumption is needed, and it occupies a small volume of the equipment and has high safety.

[0065] 2. The accumulator selection of the present invention is flexible; for different sub - sea depths, different sub - sea equipment can select different accumulator combinations to achieve better buoyancy compensation effects.

[0066] 3. The present invention uses the particle swarm optimization algorithm to select accumulators, and introduces a weight value into the fitness function, and adjusts the weight according to the speed stability requirement and active buoyancy compensation amount of the diving equipment to meet different usage conditions.

[0067] 4. For a submersible device equipped with a selected and installed appropriate multi-stage accumulator, during the diving and surfacing processes, the change in net buoyancy caused by factors such as changes in ocean density is compensated, and the change in net buoyancy is reduced. Without actively changing the net buoyancy of the device by other means, the purpose of controlling the speed of the device during the entire surfacing and diving processes can be achieved, reducing energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 FIG. is a schematic structural diagram of a passive buoyancy compensation device based on a multi-stage accumulator according to the present invention;

[0069] Figure 2 FIG. is a schematic diagram of the usage of the multi-stage accumulator in the present invention;

[0070] Figure 3 FIG. is a flowchart of the selection and configuration process of the multi-stage accumulator of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0071] The present invention will be further described in detail below with reference to the drawings and embodiments. It should be noted that the following embodiments are intended to facilitate the understanding of the present invention and do not limit it in any way.

[0072] As Figure 1 shown, a passive buoyancy compensation device based on a multi-stage accumulator includes a pressure-resistant housing 1 provided with a plurality of accumulator cavities, and each accumulator cavity is provided with an accumulator 2 made of an elastic leather bag. Openings are provided at the top and bottom of the accumulator cavity. Among them, the opening of the accumulator 2 is connected to the top opening of the accumulator cavity and is sealed by an accumulator plug 3. The accumulator plug 3 is used to adjust the volume adjustment liquid 4 in the accumulator and achieve sealing; the bottom openings of the accumulator cavities are uniformly connected to a hydraulic pipeline 5 and then communicated with the outside of the pressure-resistant housing 1.

[0073] In this embodiment, 4 accumulator cavities are provided, and the accumulator 2 is a rubber leather bag; after pre-charging the pressure, the pressure-resistant housing 1 can withstand the pressure of the accumulator leather bag; the accumulator plug 3 is used to isolate the high-pressure gas in the accumulator from the external environment and achieve sealing; when in use, different amounts of volume adjustment liquid 4 are injected first to change the effective volume of the high-pressure gas in each accumulator 2.

[0074] Before use, open the corresponding accumulator plug 3, inject the volume adjustment liquid 4, and then screw on the plug after pre-charging a certain pressure to complete the configuration of a single accumulator 2. Operate sequentially to configure the pressure and volume of each accumulator to meet the usage requirements.

[0075] As Figure 2As shown in the figure, when the submersible equipment dives to a certain depth, if the external water pressure is P and satisfies P1 < P < P2 < P3 < P4, the volume of the accumulator on the far left changes under pressure, and the accumulator with a pre-charge pressure greater than the external pressure is not compressed and its volume remains unchanged. Different external water pressures have different effects on the volume change of the multi-stage accumulator, thereby realizing the buoyancy compensation of the accumulator.

[0076] A passive buoyancy compensation method based on a multi-stage accumulator uses a passive buoyancy compensation device to compensate for the buoyancy during the diving and surfacing of submersible equipment. Among them, as Figure 3 shown, the selection and configuration process of the multi-stage accumulator includes the following steps:

[0077] S10: Use a CTD (Conductivity, Temperature, Depth) instrument to measure the relationship between the seawater density, pressure and depth h in the submersible sea area.

[0078] The maximum diving depth of the equipment is H. The CTD instrument measures the seawater density and pressure information at depths h ∈ [0, H] in the ocean, and fits to obtain the relationship ρ between the seawater density and depth in the submersible sea area h and the relationship P between the pressure and depth h .

[0079] S20: Calculate the buoyancy compensation requirement of the system from the change in seawater density and the change in the volume of the equipment under pressure.

[0080] From the relationship P between the pressure and depth in the submersible sea area h , combined with the equipment material and shape, the change in the drainage volume of the equipment with depth V 排h is obtained through finite element software simulation. Then, the net buoyancy of the equipment changes with depth h as follows:

[0081] F 净浮h = F 浮h - G = ρ h gV 排h - mg

[0082] where F 浮h is the net buoyancy of the equipment at depth h, G is the gravity of the equipment, m is the mass of the equipment, and g is the acceleration due to gravity.

[0083] S30: Determine the parameter range of the accumulator and the number of accumulators required.

[0084] The pre-charge pressure range of the accumulator is between the atmospheric pressure and the maximum water pressure P B in the submersible sea area, expressed as the relative pressure, that is: P j ∈ [0, P B ; if the volume of the accumulator is too small, the compensation effect is not obvious, and at the same time, it cannot occupy too large a volume. Adjust according to the buoyancy compensation requirement. The volume range of a single accumulator can be taken as: V j ∈ [Vjmin , V jmax = 0.05, ΔF 净浮max / g], where ΔF 净浮max = max|F 净浮h |, which is the maximum value of the net buoyancy change. The volume unit is L. The number of accumulators required is generally taken as d = 2 - 5, which is determined by the required buoyancy compensation effect. The better the buoyancy compensation effect is needed, the more the number of accumulators.

[0085] S40: Fitness function determination

[0086] For a single accumulator, the parameters to be selected are the pre-charge pressure P j , the accumulator volume V j . When the diving depth satisfies , the accumulator will start to contract to provide buoyancy. The buoyancy that a single accumulator can provide when contracting is:

[0087]

[0088] Where: P0 is the atmospheric pressure.

[0089] The accumulators are arranged in ascending order of pre-charge pressure, which are (P1, V1), (P2, V2), …, (P d , V d ). After their combination, the reduction in the net buoyancy of the device is F X , and F X is a piecewise function.

[0090]

[0091] Taking 1m as the interval, taking the depth h = [0, 1, 2, …, H], calculate the difference ΔF between the buoyancy compensation requirement F 净浮h at different depths and the accumulator compensation value F X as ΔF = F 净浮h - F X . Take Value1 = max(ΔF) + |min(ΔF)|, which is the sum of the absolute values of the positive and negative buoyancy changes during the upward or downward movement of the compensated device; take as the average deviation of the buoyancy during the upward or downward movement of the compensated device. When the device needs to meet the condition of a small active buoyancy compensation amount, a smaller Value1 value is required. When the device has a requirement for the speed stability during upward and downward movement, a smaller Value2 value is required.

[0092] Introduce weights W1, W2 such that W1, W2 ∈ [0, 1], W1 + W2 = 1, and take the fitness function as

[0093] Value = W1 × Value1 + W2 × Value2

[0094] Among them, the smaller the Value, the smaller the buoyancy change, and the better the buoyancy compensation effect. The weight values W1 and W2 are adjusted according to the buoyancy compensation requirements.

[0095] S50: The particle swarm optimization algorithm determines the parameters of the accumulator.

[0096] When the number of accumulators is d, the number of parameters D to be determined = 2d, which are x = (P1, P2,..., P d , V1, V2,..., V d ). The specific steps are as follows:

[0097] S51: Initialization

[0098] A group of D-dimensional vectors x is called a particle. For the position interval of a single particle:

[0099] x max =(x max-1 , x max-2 ,..., x max-D )=(P B , P B ,..., P B , V max , V max ,..., V max )

[0100] x min =(x min-1 , x min-2 ,..., x min-D )=[0, 0,..., 0, V min , V min ,..., V min )

[0101] Set the speed interval as:

[0102] v max =(v max-1 , v max-2 ,..., v max-D )=[0.5, 0.5,..., 0.5, 0.05, 0.05,..., 0.05]

[0103] v min =-v max

[0104] For the i-th dimensional position value of the particle, it should satisfy x i ∈[x min-i , x max-i , and the speed value should satisfy v i ∈[v min-i , v max-i. Each particle of the algorithm represents a potential solution to the problem. Let the population size N = 100. The velocity and position of each solution are randomly initialized in the search space, and then iterative calculations are performed by these N groups of potential solutions.

[0105] x n-i = rand(x min-i ,x max-i )

[0106] v n-i = rand(v min-i ,v max-i )

[0107] x n-i is the position value of the i-th dimensional data of the n-th particle in the population. When randomly initializing, take the value in its corresponding position interval [x min-i ,x max-i . v n-i is the velocity value of the i-th dimensional data of the n-th particle in the population. When randomly initializing, take the value in its corresponding velocity interval [v min-i ,v max-i .

[0108] S52: Particle fitness value calculation

[0109] Substitute the position vector of each particle into the fitness function to calculate the fitness value Value of each particle n .

[0110] S53: Record individual extreme value and population extreme value

[0111] Record the position data with the smallest individual fitness value as the individual extreme value: Q n =(Q n1 ,Q n1 ,…,Q nD ), and the currently initialized position data is the individual extreme value data of the corresponding particle; compare the fitness values of each particle, and record the particle with the smallest fitness value as the population extreme value: Q g =(Q g1 ,Q g1 ,…,Q gD ).

[0112] S54: Update velocity and position. If it exceeds, then

[0113] In each iteration process, the particle updates its own velocity and position through the individual extreme value and the population extreme value, that is

[0114]

[0115]

[0116] where ω k is the inertia weight, ω k = ω start (ω start - ω end )(T max - k) / T max , ω start = 0.9, ω end = 0.4; T max is the maximum number of iterations, k is the current number of iterations, and k = 1 for the first update; u = 1, 2, 3, …, D; i = 1, 2, 3, …, n; V iu is the velocity of the particle; c1 and c2 are non - negative constants, called acceleration factors; r1 and r2 are random numbers distributed in the interval [0, 1].

[0117] If the calculated particle position and velocity exceed their position interval and velocity interval, then adjust the position or velocity. If it is greater than the maximum value, take the maximum value; if it is less than the minimum value, take the minimum value.

[0118] S55: Particle fitness value calculation

[0119] Substitute the updated positions of each particle into the fitness function to calculate the fitness value of each particle

[0120] S56: Update individual extreme value and population extreme value

[0121] Record the position data with the minimum particle fitness value as the individual extreme value: Q n =(Q n1 , Q n1 , …, Q nD ); Compare the fitness values of each particle, and record the particle with the minimum fitness value as the population extreme value: Q g =(Q g1 , Q g1 , …, Q gD ), and the corresponding fitness value is denoted as Value g .

[0122] S57: Determine whether the termination condition is satisfied

[0123] Determine the fitness value requirement Value according to the buoyancy compensation requirement need , and set the maximum number of iterations T max . When Value g <Value need or T > T max , terminate the calculation. At this time, Q g =(Q g1 , Q g1 , …, QgD ) is the optimal solution obtained by the particle swarm optimization algorithm, and the corresponding fitness value is Value g ; otherwise, continue to execute S54;

[0124] Among them, Q g corresponds to a set of optimal accumulator parameter configurations x = (P1, P2,..., P d , V1, V2,..., V d ) = (Q g1 , Q g1 ,..., Q gD ), d = D / 2, P1 and V1 represent the pre-charge pressure and effective volume of the first accumulator.

[0125] S60: Configure a multi-stage accumulator.

[0126] Install the configured multi-stage accumulator on the submersible device. During the diving and surfacing process of the submersible device, the change in net buoyancy caused by factors such as changes in ocean density is compensated, and the change in net buoyancy is reduced.

[0127] The above-described embodiments have detailed the technical solutions and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the present invention. Any modifications, supplements, and equivalent replacements made within the scope of the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A passive buoyancy compensation method based on a multi-stage accumulator, characterized in that, A passive buoyancy compensation device is used to compensate for the buoyancy during the diving and surfacing of a subsea device; the passive buoyancy compensation device includes a pressure-resistant housing provided with a number of accumulator cavities, and each accumulator cavity is provided with an accumulator made of an elastic bladder. Openings are provided at the top and bottom of the accumulator cavity. Among them, the opening of the accumulator is connected to the top opening of the accumulator cavity and is sealed by an accumulator plug; the accumulator plug is used to adjust the volume adjustment liquid in the accumulator; the bottom openings of the accumulator cavities are uniformly connected to a hydraulic pipeline and then communicated with the outside of the pressure-resistant housing. In the passive buoyancy compensation device, the selection and configuration process of the multi-stage accumulator includes the following steps: (1) The ocean density and pressure corresponding to the depth h in the submersible sea area are measured by a CTD, and the relationships between seawater density and depth ρ h and between pressure and depth P h ; (2) According to the relationship between the pressure and depth in the diving sea area \(P\) h , combined with the material and shape of the diving equipment, the change of the drainage volume of the equipment with depth \(V\) 排h during the whole diving process is obtained by finite element software simulation. Then the net buoyancy of the equipment changes with depth \(h\) as: \(F\) 净浮h = \(F\) 浮h - \(G=\rho\) h \(gV\) 排h - \(mg\); Among them, F 浮h is the buoyancy force on the device at a depth of h, G is the gravity force on the device, m is the mass of the device, and g is the acceleration due to gravity; (3) Determine the parameter range of a single accumulator and the required number d of accumulators; among them, the parameters of the accumulator include the pre-charge pressure P j and the accumulator volume V j , where j represents the number of the accumulator; (4) Determine the fitness function, specifically as follows: When a single energy accumulator contracts, the buoyancy it can provide is f j ; (4-2) The accumulators are arranged in ascending order according to the pre-charge pressure, which are (P1, V1), (P2, V2), …, (P d , V d ). After they are combined, the reduction in the net buoyancy of the submersible device is F X ; (4-3) At intervals of 1 m, take the depth h = [0, 1, 2, …, H], and calculate the buoyancy compensation requirements F at different depths 净浮h and the accumulator compensation value F X The difference ΔF = F 净浮h - F X ; (4-4) Take Value1 = max(ΔF) + |min(ΔF)|, which is the sum of the absolute values of the positive and negative changes in buoyancy during the upward or downward movement of the compensated device; take as the average deviation of buoyancy during the upward or downward movement of the compensated device; (4-5) Introduce weights W1 and W2 such that W1, W2 ∈ [0, 1] and W1 + W2 = 1. The fitness function is: Value = W1 × Value1 + W2 × Value2 In the formula, the smaller the Value value, the smaller the buoyancy change and the better the buoyancy compensation effect. The weight values W1 and W2 are adjusted according to the buoyancy compensation requirements. (5) Determine the parameters of the accumulator through the particle swarm optimization algorithm. (6) Configure the multi-stage accumulator according to the parameters of the accumulator.

2. The passive buoyancy compensation method based on a multi-stage accumulator according to claim 1, wherein, In step (3), the pre-charge pressure P of a single accumulator j ranges from P j ∈ [0, P B ​ Among them, P B is the maximum water pressure in the area where the submersible dives.

3. The passive buoyancy compensation method based on a multi-stage accumulator according to claim 1, characterized in that In step (3), the volume V of a single accumulator j ranges as follows: V j ∈ [V jmin , V jmax = [0.05, ΔF 净浮max / g] where, ΔF 净浮max = max|F 净浮h |, which is the maximum value of the net buoyancy change, and the volume unit is L.

4. The passive buoyancy compensation method based on a multi-stage accumulator according to claim 1, characterized in that, In step (3), the number d of accumulators is 2 to 5.

5. The passive buoyancy compensation method based on a multi-stage accumulator according to claim 1, characterized in that In step (4-1), the buoyancy that can be provided when a single accumulator shrinks is: Wherein, P0 is the atmospheric pressure. When the diving depth satisfies , the accumulator will start to contract to provide buoyancy.

6. The passive buoyancy compensation method based on a multi-stage accumulator according to claim 5, characterized in that, In step (4-2), F X is a piecewise function, and the formula is:

7. The passive buoyancy compensation method based on a multi-stage accumulator according to claim 1, characterized in that In step (5), when the number of accumulators is d, the parameters to be determined are x = (P1, P2, …, P d , V1, V2, …, V d ), and the specific determination process is as follows: (5-1) Initialization A group of D-dimensional vectors x is called a particle. For a single particle, the position interval is: x max =(x max-1 , x max-2 , …, x max-D ) = (P B , P B , …, P B , V max , V max , …, V max ) x min =(x min-1 , x min-2 , …, x min-D ) = [0, 0, …, 0, V min , V min , …, V min ​ Set the velocity interval to: v max = (v max-1 , v max-2 , …, v max-D ) = [0.5, 0.5, …, 0.5, 0.05, 0.05, …, 0.05] v min = -v max For the position value of the i-th dimension of the particle, it should satisfy x i ∈[x min-i , x max-i , and for the velocity value, it should satisfy v i ∈[v min-i , v max-i ; Each particle of the algorithm represents a potential solution to the problem. Let the population size N = 100, and randomly initialize the velocity and position of each solution in the search space. Subsequently, iterative calculations are performed with these N groups of potential solutions; x n-i = rand(x min-i , x max-i ) v n-i = rand(v min-i , v max-i ) x n-i is the position value of the i-th dimensional data of the n-th particle in the population. When randomly initialized, it takes a value in the corresponding position interval [x min-i , x max-i ; v n-i is the velocity value of the i-th dimensional data of the n-th particle in the population. When randomly initialized, it takes a value in the corresponding velocity interval [v min-i , v max-i ; (5-2): Calculate the particle fitness value Substitute the position vectors of each particle into the fitness function Value = W1×Value1 + W2×Value2 to calculate the fitness value Value of each particle n ; (5-3): Record the individual extreme value and the group extreme value Record the position data with the smallest individual fitness value as the individual extreme value: Q n =(Q n1 , Q n1 , …, Q nD ), and the currently initialized position data is the individual extreme value data of the corresponding particle; compare the fitness values of each particle, and record the particle with the smallest fitness value as the global extreme value: Q g =(Q g1 , Q g1 , …, Q gD ); (5-4): Update the velocity and position. If it exceeds, then in each iteration process, the particle updates its own velocity and position through the individual extreme value and the group extreme value, that is Among them, ω k is the inertia weight, ω k = ω start (ω start - ω end )(T max - k) / T max , ω start = 0.9, ω end = 0.4; T max is the maximum number of iterations, k is the current number of iterations, and k = 1 at the first update; u = 1, 2, 3, …, D; i = 1, 2, 3, …, n; V iu is the velocity of the particle; c1 and c2 are non - negative constants, called acceleration factors; r1 and r2 are random numbers distributed in the interval [0, 1]; If it is calculated that the particle position and velocity exceed their position interval and velocity interval, then adjust the position or velocity. If it is greater than the maximum value, take the maximum value; if it is less than the minimum value, take the minimum value. (5-5): Calculate the particle fitness value Substitute the updated positions of each particle into the fitness function to calculate the fitness value of each particle (5-6): Update the individual extreme value and the group extreme value Record the position data with the minimum particle fitness value as the individual extreme value: Q n =(Q n1 , Q n1 , …, Q nD ); Compare the fitness values of each particle, and record the particle with the minimum fitness value as the global extreme value: Q g =(Q g1 , Q g1 , …, Q gD ), and the corresponding fitness value is denoted as Value g ; (5-7): Determine whether the termination condition is met Determine the fitness value requirement Value according to the buoyancy compensation requirement need , and set the maximum number of iterations T max , when Value g < Value need or T > T max , terminate the calculation. At this time, Q g = (Q g1 , Q g1 , …, Q gD ) is the optimal solution obtained by the particle swarm optimization algorithm, and the corresponding fitness value is Value g ; otherwise, continue to execute step (5-4); Among them, Q g corresponds to a set of optimal accumulator parameter configurations x = (P1, P2, …, P d , V1, V2, …, V d ) = (Q g1 , Q g1 , …, Q gD ), where d = D / 2, and P1 and V1 represent the pre-charge pressure and effective volume of the first accumulator.

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