Slurry dehydration and solidification treatment method for movable geotextile tube bag

Abstract

The invention discloses a movable geotextile pipe bag mud dewatering and curing treatment method, and relates to the technical field of sludge treatment.According to the movable geotextile pipe bag mud dewatering and curing treatment method, the adding amount of a flocculating agent is dynamically adjusted according to mud data monitored in real time, and the situation of agent waste or insufficient drug effect caused by a traditional fixed-proportion agent adding mode is avoided; a fuzzy control algorithm is adopted to dynamically adapt to the component change of the slurry, the cost of excessive use of chemicals is reduced, a chemical adding strategy is automatically adjusted, the slurry treatment effect is more stable, meanwhile, a multi-stage chemical adding mode is adopted, a flocculating agent is evenly distributed in the slurry, the flocculating agent can cover large particles and fine particles, and the treatment efficiency is improved. The problem of non-uniform flocculation caused by a single dosing point is improved, the overall efficiency of slurry dehydration is effectively improved by treating slurry with different particle sizes at different stages, and the stirring strength is dynamically adjusted based on slurry flow and particle size parameters, so that a flocculating agent and particles in the slurry are fully mixed, and the flocculation effect is improved.

Description

Technical Field

[0001] The invention relates to the technical field of sludge treatment, in particular to a mobile geotube bag sludge dehydration and solidification treatment method. Background Art

[0002] Geotube dehydration and solidification treatment is widely used in dredging, silt removal and tailings treatment projects, and the slurry is dehydrated and solidified through geotubes.

[0003] For example, the publication number: CN102583950A discloses a mobile contaminated sludge tube bag dehydration and volume reduction treatment method, which is characterized by using an environmental dredging ship or a mud pump to transport the contaminated sludge in the river or reservoir to a closed pipeline mixer, adding a stabilizing solidifying agent to the first pipeline mixer, and adding a sludge flocculating conditioning agent to the second pipeline mixer, finally achieving the dehydration and volume reduction of the sludge in the geotextile tube bag, and the solidification and stabilization of the sludge pollutants. After the sludge in the geotextile tube bag is dehydrated and consolidated for 7 to 50 days, the sludge moisture content reaches below 55%, and finally the sludge in the tube bag is transported off-site by a mobile vehicle body to reach the relevant national standards for treatment and disposal or resource utilization. The technical innovation highlights of this method are "environmental dredging + chemicals + geotextile tube bag dehydration + natural drying of sludge + mobile vehicle body", which not only has a large amount of sludge treatment during the project implementation, but also does not require site area, has a simple process, and has low operating costs; it can achieve good economic benefits;

[0004] As in the above scheme, although a mobile vehicle is used to increase the convenience of geotube mud dehydration and solidification treatment, the dosing method of geotube dehydration and solidification treatment is not limited. Most of the current schemes use manual or fixed-ratio dosing methods, and flocculants are added according to the preset ratio. They do not have the function of real-time monitoring and feedback adjustment. The mud composition, concentration and flow rate will continue to change in actual operation. The fixed-ratio dosing method cannot respond to such changes in time, resulting in excessive or insufficient dosage. In order to ensure the effect, excessive use of chemicals is usually performed. If it is not carried out, the operating cost will be increased, and it is easy to cause the mud solidification effect to be unstable, affecting the dehydration efficiency and making it difficult to ensure the solidification effect.

[0005] At present, some traditional methods manually monitor the mud properties and manually adjust the dosage, or increase mechanical stirring to enhance the dispersion effect of the agent. However, manual intervention is still difficult to achieve precise control, and the operation is complicated and there are large errors. Therefore, a mobile geotube mud dehydration and solidification treatment method is urgently needed to solve such problems. Summary of the invention

[0006] In view of the above existing problems, the present invention is proposed.

[0007] Therefore, the present invention provides a mobile geotube mud dehydration and solidification treatment method to solve the problem of lack of intelligent control and reliance on manual adjustment.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0009] The present invention provides a method for dehydrating and solidifying slurry in a movable geotube bag, which comprises:

[0010] Step S1, real-time monitoring and data collection of mud,

[0011] Before the mud enters the geotube for processing, a sensor network is deployed to monitor the real-time characteristic data of the mud and continuously monitor it.

[0012] Step S2, intelligent dosing control,

[0013] Based on the mud characteristic data collected in step S1, the fuzzy control algorithm is used to calculate the best type and dosage of flocculant, and the type and dosage of flocculant are dynamically adjusted.

[0014] And according to the water content, particle characteristics and pH value of the mud, the dosing pump's injection rate and flocculant concentration are automatically adjusted.

[0015] Step S2 adapts to changes in mud types in real time, including high-concentration, high-viscosity or high-organic mud, thereby increasing the utilization rate of flocculants and reducing operating costs;

[0016] Step S3, multi-stage dosing and flocculation,

[0017] The dosing process is divided into two levels, corresponding to the different characteristics of mud particles:

[0018] The first stage of pre-flocculation is to separate large particles and high-concentration mud before the mud enters the geotube bag. At this time, the flocculant is fully mixed with the coarse particles in the mud to form large-particle flocs.

[0019] The second stage of fine flocculation is to treat the untreated fine particles and colloids in the first stage. The mud is treated with secondary flocculation in the tube bag.

[0020] Multi-stage dosing can ensure that the flocculant is evenly distributed in the mud, achieving a more stable solidification effect;

[0021] Step S4, filtering and dehydrating,

[0022] The slurry after multi-stage dosing and dynamic stirring is transported to the geotube bag for filtration and dehydration. The filtration and dehydration is carried out in stages.

[0023] Step S5, solidification treatment,

[0024] After the mud is dehydrated and solidified, it is sorted according to the density and particle size of the solidified material.

[0025] Furthermore, in step S1, the sensor network includes a moisture content sensor, a turbidity sensor, a pH sensor, a flow sensor, and a particle size sensor.

[0026] In step S1, the real-time characteristic data includes: water content, particle distribution, pH, real-time flow rate and particle size distribution of the mud.

[0027] Furthermore, in step S2, based on the mud characteristic data collected in step S1, the type and amount of flocculant are dynamically adjusted:

[0028] The mud characteristic data obtained from step S1 include:

[0029] Water content W, that is, the proportion of water in the mud,

[0030] Particle size P, i.e. the diameter of solid particles in the mud,

[0031] Mud concentration C, that is, the mass percentage of solid particles in the mud,

[0032] and pH, the acidity or alkalinity of the mud,

[0033] The input variables are converted into fuzzy sets using fuzzy membership functions, which are defined as high, medium, and low. The membership function of each input is:

[0034] Moisture content W membership function:

[0035] If x <W min orx>W max , then μW(x)=0,

[0036] If W min ≤x≤W opt ,but

[0037] If W opt <x≤W max ,but

[0038] Among them, W min Indicates the minimum moisture content, W opt represents the ideal moisture content, W max Indicates the maximum moisture content;

[0039] Particle size P membership function:

[0040] If y <P min ory>P max , then μP(y)=0,

[0041] If P min ≤y≤P opt ,but

[0042] If P opt <y≤P max ,but

[0043] Among them, P min Indicates the minimum particle size, P opt represents the ideal particle size, P max Indicates the maximum particle size;

[0044] Mud concentration C membership function:

[0045] If z <C min orz>C max , then μC(z)=0,

[0046] If C min ≤z≤C opt ,but

[0047] If C opt <z≤C max ,but

[0048] Among them, C min Indicates the minimum mud concentration, C opt represents the ideal mud concentration, C max Indicates the maximum mud concentration.

[0049] Furthermore, in step S2, fuzzy inference rules are defined:

[0050] Rule 1 means that if W is high, P is large, and C is high, the dosage is large and a high molecular weight flocculant is used.

[0051] Rule 2 means that if W is low, P is small, and C is low, the dosage is small and inorganic flocculants are used.

[0052] Rule 3 means that if W is in the range, P is in the range, and C is in the range, then the dosage is appropriate and an organic flocculant is used.

[0053] Convert fuzzy output into flocculant dosage and type:

[0054] Among them, ∫ Dr (·) represents the integration of all possible values ​​of flocculant dosage, A represents the final flocculant dosage, μ A (x) represents the membership function of the dosage, and x represents the range of the dosage;

[0055] Defuzzification formula for flocculant type:

[0056] Among them, T represents the final determined flocculant type, Ti represents different flocculant types including polymer, inorganic and organic, μ T (Ti) represents the membership function of flocculant type Ti;

[0057] Dynamically adjust according to real-time collected mud data to automatically adapt to changes in mud composition;

[0058] Through the fuzzy control algorithm, the type and dosage of flocculants are dynamically adjusted according to the real-time mud characteristics, so that the agents can be used efficiently and the mud can be solidified efficiently.

[0059] Furthermore, in step S2, the dosing rate of the dosing pump and the flocculant concentration are automatically adjusted according to the water content, particle characteristics and pH value of the mud. The specific adjustment method is:

[0060] Real-time monitoring of slurry properties as input to control dosing pumps, including:

[0061] Water content W, ranging from 0≤W≤100, represents the percentage of water in the mud.

[0062] Particle size P, represents the average diameter of solid particles in the mud,

[0063] pH, ranging from 0 ≤ pH ≤ 14, indicates the acidity and alkalinity of the mud.

[0064] Calculate the acceleration rate R:

[0065] Among them, R represents the flocculant injection rate, W represents the water content of the mud, P represents the size of the mud particles, pH represents the acidity and alkalinity of the mud, α, β1, γ, β2, δ represent the adjustment coefficients, which are set based on empirical data, and P opt Indicates the optimal particle size, that is, the ideal mud particle diameter, pH opt Indicates the best acid-base conditions for flocculants. represents the exponential effect of water content, that is, the nonlinear effect of water content on the injection acceleration rate. This indicates an inverse effect of particle size, with smaller particles requiring more flocculant. The Sigmoid function form representing the pH value shows the smoothing effect of pH on the flocculant addition rate. When the pH is close to the optimal value, the addition rate increases.

[0066] Calculate flocculant concentration:

[0067] Among them, C flocrepresents the flocculant concentration, W represents the water content of the mud, P represents the mud particle size, η, θ1, θ2 represent the empirical coefficients, P opt represents the optimal particle size, It represents the exponential effect of water content. The higher the water content, the higher the concentration of flocculant. It means that particle size is inversely proportional to concentration, the smaller the particle, the higher the concentration;

[0068] To make dynamic adjustments:

[0069]

[0070] Among them, R new Represents the new acceleration rate, R old represents the acceleration rate of the previous moment, C floc,new Indicates the new flocculant concentration, C floc,old It indicates the flocculant concentration at the previous moment, and τ indicates the time constant, which controls the response speed of the dosing pump adjustment;

[0071] The time constant is introduced to avoid over-adjustment or mutation, making the change of dosing rate and flocculant concentration smoother.

[0072] Furthermore, in step S3, large particle matter refers to particle matter with a particle size of more than 75 μm, and high-concentration mud refers to mud with a solid content of more than 10%.

[0073] Furthermore, in step S3, dynamic stirring and mixing is performed, and a high-frequency vibration stirring device is arranged after each dosing point, and the stirring intensity is dynamically adjusted according to the mud flow and particle size monitored in real time.

[0074] Furthermore, in step S3, the stirring intensity is dynamically adjusted in real time based on the flow rate Qm and particle size P of the mud:

[0075] Define the parameters:

[0076] The mud flow rate Qm represents the volume flow rate of the mud flowing through the system. The larger the flow rate, the greater the stirring intensity to make the flocculant fully mixed.

[0077] The particle size P represents the average diameter of the particles in the mud. The smaller the diameter, the stronger the stirring intensity required.

[0078] Viscosity μ indicates the viscosity of the mud. The higher the viscosity, the higher the stirring intensity required.

[0079] Define the relationship between stirring intensity Is and mud flow, particle size and viscosity:

[0080] Among them, Is represents the stirring intensity, Qm represents the mud flow rate, P represents the particle size, μ represents the viscosity of the mud, and P opt represents the optimal particle size, i.e. the target particle diameter, μ opt represents the optimal viscosity, i.e. the target slurry viscosity; α, γ, δ are the adjustment coefficients of stirring intensity and flow rate, particle size and viscosity respectively; β1, β2, β3 are the exponential parameters of flow rate, particle size and viscosity respectively. represents the nonlinear effect of mud flow rate on stirring intensity, represents the inverse effect of particle size on stirring intensity, It indicates the proportional effect of viscosity on stirring intensity;

[0081] Introducing the time constant τ s Smoothly adjust the stirring intensity. The dynamic adjustment formula of stirring intensity is:

[0082] Among them, Is ,new Indicates the new stirring intensity, Is ,old represents the stirring intensity at the previous moment, Is represents the stirring intensity calculated based on the current mud flow, particle size and viscosity, τ s Indicates the time constant for agitation intensity adjustment. It is dynamically updated based on real-time data to quickly and smoothly adjust agitation intensity when flow, particle size or viscosity changes.

[0083] Furthermore, in the mud dehydration process of step S4, the dehydration stages are divided into:

[0084] Rapid drainage stage: free water is quickly discharged and the mud moisture content is reduced to 60-70%.

[0085] Slowing drainage stage: capillary water and part of adsorbed water are discharged, and the moisture content drops to 30-50%.

[0086] Slow drainage and solidification stage: The combined water and adsorbed water are gradually discharged, the moisture content drops to 15-30%, and the mud solidifies into shape.

[0087] Furthermore, in step S4, the geotube bag in the slow drainage and curing stage adopts a super-hydrophobic membrane material, which has an anti-clogging function and can effectively accelerate the drainage of water.

[0088] The beneficial effects of the present invention are:

[0089] The present invention dynamically adjusts the dosage of flocculant according to the real-time monitored mud data, avoids the waste of agents or insufficient efficacy caused by the traditional fixed-ratio dosing method, adopts fuzzy control algorithm to dynamically adapt to the changes in mud composition, reduces the cost of excessive use of agents, and automatically adjusts the dosing strategy to make the mud treatment effect more stable.

[0090] The present invention adopts a multi-stage dosing method to make the flocculant evenly distributed in the mud. The flocculant can cover large particles and fine particles, improve the problem of uneven flocculation caused by a single dosing point, and treat muds of different particle sizes at different stages, effectively improving the overall efficiency of mud dehydration.

[0091] The present invention dynamically adjusts the stirring intensity based on the mud flow rate and particle size parameters, so that the flocculant is fully mixed with the particles in the mud, thereby improving the flocculation effect and accelerating dehydration. The super-hydrophobic membrane effectively prevents fine particles in the mud from clogging the holes of the filter bag, allowing water to be discharged faster, thereby improving the dehydration efficiency of the entire system.

[0092] The present invention can flexibly cope with different types of mud, significantly improves the treatment effect of high-concentration and high-viscosity mud, and ensures the stability of the dehydration and solidification process. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0094] Figure 1 It is a schematic diagram of the process of the mobile geotube mud dehydration and solidification treatment method of the present invention. DETAILED DESCRIPTION

[0095] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0096] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0097] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0098] Example 1, reference Figure 1 This embodiment provides a method for dehydrating and solidifying slurry in a mobile geotube bag, comprising the following steps:

[0099] Step S1, real-time monitoring and data collection of mud,

[0100] Before the mud enters the geotube for processing, a sensor network is deployed to monitor the real-time characteristic data of the mud and continuously monitor it.

[0101] In step S1, the sensor network includes a moisture content sensor, a turbidity sensor, a pH sensor, a flow sensor, and a particle size sensor.

[0102] In step S1, the real-time characteristic data includes: the water content, particle distribution, pH, real-time flow rate and particle size distribution of the mud;

[0103] Step S2, intelligent dosing control,

[0104] Based on the mud characteristic data collected in step S1, the fuzzy control algorithm is used to calculate the best type and dosage of flocculant, and the type and dosage of flocculant are dynamically adjusted.

[0105] And according to the water content, particle characteristics and pH value of the mud, the dosing pump's injection rate and flocculant concentration are automatically adjusted.

[0106] Step S2 adapts to changes in mud types in real time, including high-concentration, high-viscosity or high-organic mud, thereby increasing the utilization rate of flocculants and reducing operating costs;

[0107] In step S2, based on the mud characteristic data collected in step S1, the type and amount of flocculant are dynamically adjusted:

[0108] The mud characteristic data obtained from step S1 include:

[0109] Water content W, that is, the proportion of water in the mud,

[0110] Particle size P, i.e. the diameter of solid particles in the mud,

[0111] Mud concentration C, that is, the mass percentage of solid particles in the mud,

[0112] and pH, the acidity or alkalinity of the mud,

[0113] The input variables are converted into fuzzy sets using fuzzy membership functions, which are defined as high, medium, and low. The membership function of each input is:

[0114] Moisture content W membership function:

[0115] If x <W min orx>W max , then μW(x)=0,

[0116] If W min ≤x≤Wopt ,but

[0117] If W opt <x≤W max ,but

[0118] Among them, W min Indicates the minimum moisture content, W opt represents the ideal moisture content, W max Indicates the maximum moisture content;

[0119] Particle size P membership function:

[0120] If y <P min ory>P max , then μP(y)=0,

[0121] If P min ≤y≤P opt ,but

[0122] If P opt <y≤P max ,but

[0123] Among them, P min Indicates the minimum particle size, P opt represents the ideal particle size, P max Indicates the maximum particle size;

[0124] Mud concentration C membership function:

[0125] If z <C min orz>C max , then μC(z)=0,

[0126] If C min ≤z≤C opt ,but

[0127] If C opt <z≤C max ,but

[0128] Among them, C min Indicates the minimum mud concentration, C opt represents the ideal mud concentration, C max Indicates the maximum mud concentration;

[0129] In step S2, the fuzzy inference rules are defined:

[0130] Rule 1 means that if W is high, P is large, and C is high, the dosage is large and a high molecular weight flocculant is used.

[0131] Rule 2 means that if W is low, P is small, and C is low, the dosage is small and inorganic flocculants are used.

[0132] Rule 3 means that if W is in the range, P is in the range, and C is in the range, then the dosage is appropriate and an organic flocculant is used.

[0133] Convert fuzzy output into flocculant dosage and type:

[0134] Among them, ∫ Dr (·) represents the integration of all possible values ​​of flocculant dosage, A represents the final flocculant dosage, μ A (x) represents the membership function of the dosage, and x represents the range of the dosage;

[0135] Defuzzification formula for flocculant type:

[0136] Among them, T represents the final determined flocculant type, Ti represents different flocculant types including polymer, inorganic and organic, μ T (Ti) represents the membership function of flocculant type Ti;

[0137] Dynamically adjust according to real-time collected mud data to automatically adapt to changes in mud composition;

[0138] Through fuzzy control algorithm, the type and dosage of flocculants are dynamically adjusted according to the real-time mud characteristics, so that the agent can be used efficiently and the mud can be solidified efficiently;

[0139] In step S2, the dosing rate of the dosing pump and the flocculant concentration are automatically adjusted according to the water content, particle characteristics and pH value of the mud. The specific adjustment method is:

[0140] Real-time monitoring of slurry properties as input to control dosing pumps, including:

[0141] Water content W, ranging from 0≤W≤100, represents the percentage of water in the mud.

[0142] Particle size P, represents the average diameter of solid particles in the mud,

[0143] pH, ranging from 0 ≤ pH ≤ 14, indicates the acidity and alkalinity of the mud.

[0144] Calculate the acceleration rate R:

[0145] Among them, R represents the flocculant injection rate, W represents the water content of the mud, P represents the size of the mud particles, pH represents the acidity and alkalinity of the mud, α, β1, γ, β2, δ represent the adjustment coefficients, which are set based on empirical data, and Popt Indicates the optimal particle size, that is, the ideal mud particle diameter, pH opt Indicates the best acid-base conditions for flocculants. represents the exponential effect of water content, that is, the nonlinear effect of water content on the injection acceleration rate. This indicates an inverse effect of particle size, with smaller particles requiring more flocculant. The Sigmoid function form representing the pH value shows the smoothing effect of pH on the flocculant addition rate. When the pH is close to the optimal value, the addition rate increases.

[0146] Calculate flocculant concentration:

[0147] Among them, C floc represents the flocculant concentration, W represents the water content of the mud, P represents the mud particle size, η, θ1, θ2 represent the empirical coefficients, P opt represents the optimal particle size, It represents the exponential effect of water content. The higher the water content, the higher the concentration of flocculant. It means that particle size is inversely proportional to concentration, the smaller the particle, the higher the concentration;

[0148] To make dynamic adjustments:

[0149]

[0150] Among them, R new Represents the new acceleration rate, R old represents the acceleration rate of the previous moment, C floc,new Indicates the new flocculant concentration, C floc,old It indicates the flocculant concentration at the previous moment, and τ indicates the time constant, which controls the response speed of the dosing pump adjustment;

[0151] Introducing a time constant avoids over-adjustment or mutation, making the change of the dosing rate and flocculant concentration smoother;

[0152] Specifically, based on the monitored mud characteristics, a fuzzy control algorithm is used to dynamically calculate the optimal flocculant type and dosage, which greatly improves the utilization efficiency of the flocculant and avoids the problem of excessive or insufficient flocculants caused by fluctuations in mud composition in traditional methods. The fuzzy control algorithm performs nonlinear adjustments based on the water content, particle size and pH value of the mud, and through defuzzification technology, converts the fuzzy reasoning results into specific dosage and type, thereby achieving precise deployment of the agent, which not only improves the flocculation effect, but also significantly reduces operating costs.

[0153] In addition, the traditional solution usually sets a single dosing point for one-time dosing before the mud enters the geotube bag. A single dosing point cannot ensure that the agent is evenly distributed throughout the mud flow process, which limits the flocculation effect. When treating high-concentration or high-viscosity mud, it is difficult to achieve the best dehydration and solidification effect. Complex mud components, such as mud with high clay or organic matter content, require different flocculation conditions to achieve optimal dehydration. A single dosing method cannot meet the diverse treatment requirements, the treatment efficiency is low, and the geotube bag is prone to mud clogging. When the water content of the mud changes greatly, the single dosing mode is difficult to adjust to the adaptive state in a short time, resulting in significant differences in the dehydration effect of the system in different time periods. The following optimizations were made against this background:

[0154] Step S3, multi-stage dosing and flocculation,

[0155] The dosing process is divided into two levels, corresponding to the different characteristics of mud particles:

[0156] The first stage of pre-flocculation is to separate large particles and high-concentration mud before the mud enters the geotube bag. At this time, the flocculant is fully mixed with the coarse particles in the mud to form large-particle flocs.

[0157] The second stage of fine flocculation is to treat the untreated fine particles and colloids in the first stage. The mud is treated with secondary flocculation in the tube bag.

[0158] Multi-stage dosing can ensure that the flocculant is evenly distributed in the mud, achieving a more stable solidification effect;

[0159] Specifically, the slurry is subjected to preliminary and fine flocculation treatment through a multi-stage dosing strategy. The primary flocculation process mainly targets large particles and high-concentration slurry. Large particles can quickly combine with flocculants to form floccules. The subsequent fine flocculation treatment targets the remaining fine particles and colloidal substances through more refined chemical formulation and high-frequency dynamic stirring, so that the flocculant is more evenly distributed in the slurry, thereby improving the overall effect of dehydration and solidification.

[0160] In step S3, large particle matter refers to particle matter with a particle size of more than 75 μm, and high-concentration mud refers to mud with a solid content of more than 10%;

[0161] In step S3, dynamic stirring and mixing is performed, and a high-frequency vibration stirring device is configured after each dosing point to dynamically adjust the stirring intensity according to the mud flow and particle size monitored in real time;

[0162] In step S3, the stirring intensity is based on the flow rate Q of the mud m And particle size P is adjusted dynamically in real time:

[0163] Define the parameters:

[0164] Mud flow Qm It indicates the volume flow rate of the slurry flowing through the system. The larger the flow rate, the greater the stirring intensity to make the flocculant fully mixed.

[0165] The particle size P represents the average diameter of the particles in the mud. The smaller the diameter, the stronger the stirring intensity required.

[0166] Viscosity μ indicates the viscosity of the mud. The higher the viscosity, the higher the stirring intensity required.

[0167] Define the relationship between stirring intensity Is and mud flow, particle size and viscosity:

[0168] Among them, I s Indicates the stirring intensity, Q m represents the mud flow rate, P represents the particle size, μ represents the viscosity of the mud, and P opt represents the optimal particle size, i.e. the target particle diameter, μ opt represents the optimal viscosity, i.e. the target slurry viscosity; α, γ, δ are the adjustment coefficients of stirring intensity and flow rate, particle size and viscosity respectively; β1, β2, β3 are the exponential parameters of flow rate, particle size and viscosity respectively. represents the nonlinear effect of mud flow rate on stirring intensity, represents the inverse effect of particle size on stirring intensity, It indicates the proportional effect of viscosity on stirring intensity;

[0169] Introducing the time constant τ s Smoothly adjust the stirring intensity. The dynamic adjustment formula of stirring intensity is:

[0170] Among them, I s,new Indicates the new stirring intensity, I s,old Indicates the stirring intensity at the previous moment, I s represents the stirring intensity calculated based on the current mud flow, particle size and viscosity, τ s Indicates the time constant for agitation intensity adjustment, dynamically updated based on real-time data, allowing agitation intensity to be adjusted quickly and smoothly when flow, particle size or viscosity changes;

[0171] Specifically, in the mixing stage, a high-frequency dynamic mixing device based on real-time data adjustment is deployed. The mixing intensity is adjusted in real time according to the mud flow, particle size and viscosity, so that mud particles of different particle sizes can fully contact and evenly mix with the flocculant. By dynamically adjusting the mixing intensity, the flocculation efficiency of the mud is greatly improved, and the solid-liquid separation process is faster.

[0172] Step S4, filtering and dehydrating,

[0173] The slurry after multi-stage dosing and dynamic stirring is transported to the geotube bag for filtration and dehydration. The filtration and dehydration is carried out in stages.

[0174] In the mud dehydration process of step S4, the dehydration stages are divided into:

[0175] Rapid drainage stage: free water is quickly discharged and the mud moisture content is reduced to 60-70%.

[0176] Slowing drainage stage: capillary water and part of adsorbed water are discharged, and the moisture content drops to 30-50%.

[0177] Slow drainage and solidification stage: combined water and adsorbed water are gradually discharged, the moisture content drops to 15-30%, and the mud solidifies and takes shape;

[0178] In step S4, the geotube bag in the slow drainage and solidification stage adopts super-hydrophobic membrane material, which has anti-clogging function and can effectively accelerate the discharge of water; specifically, in the dehydration stage, stage-by-stage control is carried out, a large amount of free water is discharged in the initial stage, discharged through capillary water in the middle stage, and bound water and adsorbed water are removed in the final stage, and finally a relatively stable solid substance is formed. The super-hydrophobic membrane effectively prevents fine particles in the mud from clogging the holes of the filter bag, greatly improving the dehydration efficiency and shortening the dehydration time.

[0179] Step S5, solidification treatment,

[0180] After the mud is dehydrated and solidified, it is sorted according to the density and particle size of the solidified material;

[0181] The present invention also uses a mobile vehicle body to transport the bottom mud in the tube bag to outside the site.

[0182] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A mobile geotube mud dehydration and solidification treatment method, characterized by: include, Step S1, real-time monitoring and data collection of mud. Before the mud enters the geotube for processing, a sensor network is deployed to monitor the real-time characteristic data of the mud and continuously monitor it. Step S2, intelligent dosing control, based on the mud characteristic data collected in step S1, uses fuzzy control algorithm to calculate the best type and dosage of flocculant, and dynamically adjusts the type and dosage of flocculant. And according to the water content, particle characteristics and pH value of the mud, the dosing pump's injection rate and flocculant concentration are automatically adjusted; Step S3, multi-stage dosing and flocculation. The dosing process is divided into two levels, corresponding to mud particles with different characteristics: The first stage of pre-flocculation is to separate large particles and high-concentration mud before the mud enters the geotube bag. At this time, the flocculant is fully mixed with the coarse particles in the mud to form large particle flocs. The second stage of fine flocculation is to treat the fine particles and colloidal substances that were not treated in the first stage. The mud is treated with secondary flocculation in the tube bag; Step S4, filtration and dehydration, the slurry after multi-stage dosing and dynamic stirring is transported to the geotube bag for filtration and dehydration, and the filtration and dehydration is carried out in stages. Step S5, solidified material processing, after the mud is dehydrated and solidified, it is sorted according to the solidified material density and particle size.

2. A mobile geotube mud dehydration and solidification treatment method according to claim 1, characterized in that: In step S1, the sensor network includes a moisture content sensor, a turbidity sensor, a pH sensor, a flow sensor, and a particle size sensor. In step S1, the real-time characteristic data includes: water content, particle distribution, pH, real-time flow rate and particle size distribution of the mud.

3. A method for dehydrating and solidifying slurry in a mobile geotube bag according to claim 2, characterized in that: In step S2, based on the mud characteristic data collected in step S1, the type and amount of flocculant are dynamically adjusted: The mud characteristic data obtained from step S1 include: Water content W, that is, the proportion of water in the mud, Particle size P, i.e. the diameter of solid particles in the mud, Mud concentration C, that is, the mass percentage of solid particles in the mud, and pH, the acidity or alkalinity of the mud, The input variables are converted into fuzzy sets using fuzzy membership functions, which are defined as high, medium, and low. The membership function of each input is: Moisture content W membership function: If x <W min orx>W max , then μ W (x) = 0, If W min ≤x≤W opt ,but If W opt <x≤W max ,but Among them, W min Indicates the minimum moisture content, W opt represents the ideal moisture content, W max Indicates the maximum moisture content; Particle size P membership function: If y <P min ory>P max , then μ P (y) = 0, If P min ≤y≤P opt ,but If P opt <y≤P max ,but Among them, P min Indicates the minimum particle size, P opt represents the ideal particle size, P max Indicates the maximum particle size; Mud concentration C membership function: If z <C min orz>C max , then μ C (z) = 0, If C min ≤z≤C opt ,but If C opt <z≤C max ,but Among them, C min Indicates the minimum mud concentration, C opt represents the ideal mud concentration, C max Indicates the maximum mud concentration.

4. A mobile geotube mud dehydration and solidification treatment method according to claim 3, characterized in that: In step S2, the fuzzy inference rules are defined: If W is high, P is large, and C is high, the dosage is large and a high molecular weight flocculant is used. If W is low, P is small, and C is low, the dosage is small and inorganic flocculants are used. If W, P and C are in the range, the dosage is moderate, and organic flocculants are used. Convert fuzzy output into flocculant dosage and type: Among them, ∫ Dr (·) represents the integration of all possible values ​​of flocculant dosage, A represents the final flocculant dosage, μ A (x) represents the membership function of the dosage, and x represents the range of the dosage; Defuzzification formula for flocculant type: Where, T represents the final determined flocculant type, T i Indicates different types of flocculants including polymer, inorganic and organic, μ T (T i ) indicates flocculant type T i The membership function of Make dynamic adjustments based on the real-time collected mud data and automatically adapt to changes in mud composition.

5. A method for dehydrating and solidifying slurry in a mobile geotube bag according to claim 4, characterized in that: In step S2, the dosing rate of the dosing pump and the flocculant concentration are automatically adjusted according to the water content, particle characteristics and pH value of the mud. The specific adjustment method is: Real-time monitoring of slurry properties as input to control dosing pumps, including: Water content W, ranging from 0≤W≤100, represents the percentage of water in the mud. Particle size P, represents the average diameter of solid particles in the mud, pH, ranging from 0 ≤ pH ≤ 14, indicates the acidity and alkalinity of the mud. Calculate the acceleration rate R: Where R represents the flocculant addition rate, W represents the water content of the mud, P represents the size of the mud particles, pH represents the acidity and alkalinity of the mud, α, β1, γ, β2, δ represent the adjustment coefficients, which are set based on empirical data, and P opt Indicates the optimal particle size, that is, the ideal mud particle diameter, pH opt Indicates the best acid-base conditions for flocculants. represents the exponential effect of water content, that is, the nonlinear effect of water content on the injection acceleration rate. represents the inverse effect of particle size, The Sigmoid function form of pH value represents the smoothing effect of pH on flocculant addition rate; Calculate flocculant concentration: Among them, C floc represents the flocculant concentration, W represents the water content of the mud, P represents the mud particle size, η, θ1, θ2 represent the empirical coefficients, P opt represents the optimal particle size, It represents the exponential effect of water content. The higher the water content, the higher the concentration of flocculant. It means that particle size is inversely proportional to concentration, the smaller the particle, the higher the concentration; To make dynamic adjustments: Among them, R new Represents the new acceleration rate, R old represents the acceleration rate of the previous moment, C floc,new Indicates the new flocculant concentration, C floc,old It indicates the flocculant concentration at the previous moment, and τ indicates the time constant, which controls the response speed of the dosing pump adjustment.

6. A method for dehydrating and solidifying slurry in a mobile geotube bag according to claim 5, characterized in that: In step S3, large particle matter refers to particle matter with a particle size of more than 75 μm, and high-concentration mud refers to mud with a solid content of more than 10%.

7. A method for dehydrating and solidifying slurry in a mobile geotube bag according to claim 6, characterized in that: In step S3, dynamic stirring and mixing is performed, and a high-frequency vibration stirring device is arranged after each dosing point, and the stirring intensity is dynamically adjusted according to the mud flow and particle size monitored in real time.

8. A method for dehydrating and solidifying slurry in a mobile geotube bag according to claim 7, characterized in that: In step S3, the stirring intensity is based on the flow rate Q of the mud m And particle size P is adjusted dynamically in real time: Define the parameters: Mud flow Q m represents the volume flow rate of mud flowing through the system, The particle size P represents the average diameter of the particles in the mud. Viscosity μ represents the viscosity of the mud. Definition of stirring intensity I s Relationship with mud flow, particle size and viscosity: Among them, I s Indicates the stirring intensity, Q m represents the mud flow rate, P represents the particle size, μ represents the viscosity of the mud, and P opt represents the optimal particle size, i.e. the target particle diameter, μ opt represents the optimal viscosity, i.e. the target slurry viscosity; α, γ, δ are the adjustment coefficients of stirring intensity and flow rate, particle size and viscosity respectively; β1, β2, β3 are the exponential parameters of flow rate, particle size and viscosity respectively. represents the nonlinear effect of mud flow rate on stirring intensity, represents the inverse effect of particle size on stirring intensity, It indicates the proportional effect of viscosity on stirring intensity; Introducing the time constant τ s Smoothly adjust the stirring intensity. The dynamic adjustment formula of stirring intensity is: Among them, I s,new Indicates the new stirring intensity, I s,old Indicates the stirring intensity at the previous moment, I s represents the stirring intensity calculated based on the current mud flow, particle size and viscosity, τ s Indicates the time constant for adjusting the stirring intensity.

9. A mobile geotube mud dehydration and solidification treatment method according to claim 8, characterized in that: In the mud dehydration process of step S4, the dehydration stages are divided into: Rapid drainage stage: free water is quickly discharged and the mud moisture content is reduced to 60-70%. Slowing down the drainage stage: capillary water and part of the adsorbed water are discharged, and the moisture content drops to 30-50%, Slow drainage and solidification stage: The combined water and adsorbed water are gradually discharged, the moisture content drops to 15-30%, and the mud solidifies into shape.

10. A method for dehydrating and solidifying slurry in a mobile geotube bag according to claim 9, characterized in that: In step S4, the geotube bag in the slow drainage and curing stage adopts a super hydrophobic membrane material.

Images