Construction method for treating large-area slurry by using slurry filter press

Abstract

The invention provides a construction method for treating large-area slurry by a slurry filter press, which belongs to the technical field of large-area slurry construction and comprises the following steps: determining the optimal deployment position of the slurry filter press according to field arrangement. Preparing a curing agent, blending and optimizing the mixing ratio of the curing agent, and stirring and adjusting according to engineering requirements to ensure that the quality and the performance meet the requirements. Conveying the slurry to a filter press, and performing high-pressure mechanical squeezing to realize solid-liquid separation. And further filtering the squeezed slurry by using a filtering system, and separating out a solid residue filter cake and filtrate. A filter cake is compacted, so that the size is reduced, and the stability is improved. And collecting the treated filter cake, and carrying out backfilling, brickmaking or other resource utilization according to engineering requirements. And the filtrate is subjected to precipitation, filtration, adsorption and other treatments to remove suspended matters, dissolved matters and harmful substances so as to reach the emission or recovery standard. A mud treatment efficiency evaluation model is established, operation parameters of the filter press are optimized, and the treatment efficiency and effect are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of large-area mud construction, and in particular relates to a large-area mud construction method using a mud filter press. Background Art

[0002] Mud is a kind of material with strong fluidity commonly found in the construction process of civil engineering, mainly including water, soil particles, cementitious materials and other components. Mud is widely used in projects such as foundation pit support, foundation treatment, tunnel construction, etc., and is an indispensable and important construction material. However, the generation and treatment of large amounts of mud has become a major problem.

[0003] First, the generation and accumulation of large-scale mud will occupy a lot of on-site space, affecting normal construction operations. Construction sites often use nearby piles or temporary sedimentation tanks to temporarily store mud, but this approach not only requires a lot of space, but also easily causes secondary pollution and environmental problems.

[0004] Secondly, the mud contains a large amount of suspended solids, heavy metals, organic matter and other pollutants, and direct discharge will cause serious pollution to the surrounding water, soil and atmosphere. Traditional mud treatment mostly uses simple mechanical sedimentation or chemical flocculation sedimentation, but the removal efficiency is limited, and the treated mud and tail water are still difficult to meet the discharge standards.

[0005] Furthermore, if untreated mud is used directly as backfill, it will cause problems such as reduced foundation bearing capacity and increased settlement. Direct incineration or landfilling also has disadvantages such as high cost and high risk of secondary pollution.

[0006] Therefore, it is urgent to develop an efficient, environmentally friendly and economical mud treatment technology to solve many problems in large-scale mud construction. Filter pressing technology, as an effective mud separation method, has received widespread attention. However, the existing mud filter pressing process still has the technical problem of low treatment efficiency. Summary of the invention

[0007] In view of this, the present invention provides a construction method for treating large-area mud by using a mud filter press, which can solve the technical problem of low treatment efficiency in the existing mud filter press process.

[0008] The present invention is achieved in that:

[0009] The first aspect of the present invention provides a construction method for treating large-area mud with a mud filter press, which comprises the following steps:

[0010] S10. Determine the optimal deployment position of the mud filter press according to the site plan layout to maximize the use of the mud pool position;

[0011] S20, prepare the curing agent, optimize the curing agent ratio, stir and adjust according to the project needs to ensure that the quality and performance meet the requirements;

[0012] S30, transporting the mud to a mud filter press, and performing high-pressure mechanical pressing to achieve preliminary separation of solid particles and liquid;

[0013] S40, further filtering the squeezed mud using a filtering system to separate a solid residue filter cake and a filtrate;

[0014] S50, compacting the filter cake to reduce its volume and improve its stability in preparation for subsequent processing;

[0015] S60, collecting the treated filter cake and backfilling, making bricks or other resource utilization according to engineering requirements;

[0016] S70, treating the filtrate by sedimentation, filtration and adsorption to remove suspended solids, dissolved solids and harmful substances to meet the discharge or recycling standards;

[0017] S80. Establish a mud treatment efficiency evaluation model, including treatment speed, solid-liquid separation effect, and filter cake moisture content indicators;

[0018] S90. Based on the evaluation model results, optimize the operating parameters of the mud filter press, including pressure, filtration time, feed rate, filter plate spacing, vibration frequency, and filter cloth tension, to improve processing efficiency and effect.

[0019] The determination of the optimal deployment position of the mud filter press is achieved by using a multi-objective optimization function, which is expressed as follows:

[0020]

[0021] Where n is the number of mud generation points; m is the number of filter press deployment locations; x ij If the slurry is transported from point i to the filter press at position j, it is 1, otherwise it is 0; j If the filter press is deployed at position j, it is 1, otherwise it is 0; c ij is the unit transportation cost of transporting mud from point i to location j; f j is the fixed cost of installing a filter press at location j; j is the cost of operating the filter press at location j; e j is the cost of dealing with environmental impacts at location j.

[0022] This multi-objective optimization function is a mixed integer programming problem, which takes into account multiple factors such as the selection of multiple filter press locations, mud distribution, transportation cost, installation cost, operating cost, environmental cost, processing capacity, transportation distance, site area, environmental impact and time. This problem can be solved using optimization methods such as branch and bound method, cutting plane method or heuristic algorithm. The solution of this model will give the optimal deployment location of the mud filter press and the optimal distribution plan of the mud.

[0023] The multi-objective optimization function includes the mud processing capacity constraint, which is specifically expressed as follows:

[0024]

[0025] In the formula, v i is the mud volume generated at point i; P j is the processing capacity of the filter press at position j.

[0026] The multi-objective optimization function includes the constraint that each mud generation point must be assigned to a filter press, which is specifically expressed as follows:

[0027]

[0028] The multi-objective optimization function includes a transportation distance constraint, which is specifically expressed as follows:

[0029]

[0030] Where, d ij is the distance from point i to position j; D max is the maximum allowable total transport distance.

[0031] The multi-objective optimization function includes a site area constraint, which is specifically expressed as follows:

[0032]

[0033] In the formula, A j A is the area occupied by the filter press at position j; max is the maximum total available area.

[0034] The multi-objective optimization function includes environmental impact constraints, which are specifically expressed as follows:

[0035]

[0036] Where N j ,S j ,W j are the noise, dust and wastewater impact factors at location j; w1, w2, w3 are the environmental impact weights; E maxis the maximum permissible environmental impact.

[0037] The multi-objective optimization function includes a time constraint, which is specifically expressed as follows:

[0038]

[0039] Where, t ij is the time to transport mud from point i to position j; p j is the processing time of the filter press at position j; T max is the maximum allowed total time.

[0040] The multi-objective optimization function includes decision variable constraints, which are specifically expressed as follows:

[0041]

[0042] The step of establishing the mud treatment efficiency evaluation model specifically includes:

[0043] According to the goals and requirements of mud treatment, establish a mud treatment efficiency evaluation index system including treatment speed, solid-liquid separation effect, and filter cake moisture content;

[0044] In the actual mud treatment process, the measured data of each evaluation index are systematically collected to form a sample data set, and the data set is statistically analyzed;

[0045] By using regression analysis method, a prediction model between mud treatment efficiency index and key process parameters is established as a mud treatment efficiency evaluation model;

[0046] Conduct sensitivity analysis on the established evaluation model and quantify the impact of various process parameters on the treatment efficiency index;

[0047] Integrate the established mud treatment efficiency evaluation model into the operation and management platform of the mud treatment system, call the model to predict the treatment efficiency index in real time, and regularly update the model parameters based on the actual operation data;

[0048] The form of the mud treatment efficiency evaluation model is specifically expressed as follows:

[0049] y=f(x;θ)+∈;

[0050] in, is the efficiency index vector of the sample data set, is the characteristic vector of the sample data set, θ is the model parameter, ∈ is the random error term; v represents the processing speed, η represents the solid-liquid separation effect, and w represents the moisture content of the filter cake; specifically, the processing speed v represents the amount of mud processed per unit time, the solid-liquid separation effect η represents the degree of separation between solid matter and liquid, and the moisture content of the filter cake w represents the residual moisture content in the filter cake;

[0051] The sample data set is represented as:

[0052] Where N represents the number of sample data sets.

[0053] Furthermore, the step S10 specifically includes: spatial analysis and identification of mud generation points, multi-objective optimization of the deployment position of the mud filter press, scheme visualization and evaluation, etc. First, through field survey of the construction site, the spatial analysis algorithm is used to perform cluster analysis on the mud generation points to identify the main mud generation areas. Then, a multi-objective optimization model including objective functions such as minimizing total transportation costs, minimizing total processing time, and minimizing environmental impact is established. Under the constraints of mud processing capacity, site area, environmental impact threshold, etc., the mixed integer programming algorithm is used to solve the optimization problem and determine the optimal deployment position of the mud filter press. Finally, the optimization results are visualized on the site plan to evaluate the economy, environmental impact and operational feasibility of the scheme, and iterative optimization of the scheme is performed when necessary. Through these steps, the optimal deployment position of the mud filter press can be determined to maximize the use of existing resources, reduce the overall operating cost, and meet environmental impact restrictions.

[0054] Furthermore, the specific steps of step S20 include: curing agent performance test, mix ratio optimization, on-site verification and quality control, etc. First, the physical and chemical properties of the available curing agents are tested, including indicators such as gel time, compression strength, pH value, etc., and compared and analyzed with the process requirements. Then, a single factor test method or an orthogonal test method is used to systematically explore the effects of different curing agent dosages, water-cement ratios, admixture dosages, etc. on the curing effect, and determine the optimal curing agent mix ratio. Next, the optimized curing agent mix ratio is tested and verified on site to detect indicators such as strength, permeability, and stability after curing to ensure that the engineering requirements are met. Finally, a quality control system for curing agent preparation is established, including on-site inspection of raw materials, monitoring of the preparation process, and testing of finished product performance, etc., to ensure that the quality and performance of the curing agent always meet the standard requirements. Through these steps, a high-quality curing agent that meets engineering needs can be prepared, laying the foundation for subsequent mud curing treatment.

[0055] Furthermore, the specific steps of step S30 include: mud pretreatment, high-pressure mechanical squeezing, squeezing parameter optimization and performance monitoring. First, the mud collected on site is transported to the feed port of the filter press, and the mud is pretreated as necessary, such as adjusting the pH value, adding flocculants, etc., to improve the filterability of the mud. Then, the mud is preliminarily dehydrated and separated by high-pressure mechanical squeezing. By adjusting parameters such as pressure and squeezing time, the squeezing process is optimized to obtain the highest possible solid-liquid separation effect. At the same time, the pressure, flow rate, discharge concentration and other indicators during the squeezing process are monitored in real time, and the parameters are adjusted in time to ensure that the squeezing effect is stable and controllable. Through these steps, the high-pressure mechanical force can be used to perform preliminary solid-liquid separation on the mud, preparing for subsequent deep filtration.

[0056] Furthermore, the specific steps of step S40 include: filtration system selection, filtration process optimization, filtration performance monitoring and filter cake / filtrate treatment. First, according to the mud characteristics, separation objectives and processing capacity requirements, select suitable filtration equipment, such as belt filter press, centrifuge, vacuum filter, etc. Then, for different filtration equipment, optimize the filtration parameters, such as filter material type, filtration pressure, filtration time, etc., and determine the best filtration process parameters through experiments or simulation prediction methods. Next, monitor the pressure difference, discharge concentration, filter cake moisture content and other indicators in the filtration process in real time, and adjust the filtration parameters in time to ensure the stability of the filtration effect. Finally, the separated solid filter cake and liquid filtrate are subjected to subsequent treatment respectively. The filter cake can be compacted, dried and other treatments, and the filtrate needs further purification treatment, such as precipitation, flocculation, adsorption, etc. Through these steps, the filtration technology can be used to further separate the solid particles and the clean filtrate to meet the requirements of subsequent utilization or discharge.

[0057] Furthermore, the specific steps of step S50 include: determination of filter cake moisture content, selection of compaction equipment, optimization of compaction parameters, monitoring of compaction process and evaluation of compaction effect. First, the moisture content index of the filter cake is measured in time by drying method or other rapid determination methods. Then, according to the characteristics of the filter cake and the compaction target, suitable compaction equipment, such as hydraulic press, vibration table, etc., is selected. Next, the optimal compaction pressure, time, vibration frequency and other parameters are determined by experiments or empirical formulas to obtain the target moisture content and volume reduction rate. At the same time, the pressure, moisture content and other indicators during the compaction process are monitored in real time, and the parameters are adjusted in time to ensure the stability of the compaction effect. Finally, the moisture content, strength and other indicators of the compacted filter cake are tested and evaluated to ensure that the requirements for subsequent treatment or utilization are met. Through these steps, the filter cake can be further dehydrated and the volume can be reduced by mechanical compaction, so as to prepare for subsequent resource utilization or landfill treatment.

[0058] Furthermore, the specific steps of step S60 include: analysis of filter cake properties, formulation of resource utilization plan, implementation of resource utilization and evaluation of utilization effect. First, the physical and chemical properties of the compacted filter cake are analyzed, including indicators such as moisture content, strength, and heavy metal content, to provide a basis for the formulation of subsequent utilization plans. Then, according to the properties and engineering requirements of the filter cake, a specific resource utilization plan is formulated, such as backfill utilization, brick making, etc., and the relevant process parameters are optimized for different utilization methods. Next, according to the formulated utilization plan, the treated filter cake is transported to a designated location for actual utilization, such as layered paving and compaction when backfilling, and the filter cake is mixed with other raw materials for molding and firing when brick making. Finally, the actual effect of resource utilization is evaluated, including indicators such as utilization amount and environmental impact, and the plan is optimized and adjusted when necessary. Through these steps, the resource value of the treated filter cake can be fully utilized, the recycling of waste can be realized, and the load on the environment can be reduced.

[0059] Furthermore, the specific steps of step S70 include: filtrate property detection, treatment process selection, treatment process parameter optimization, treatment effect monitoring and water quality evaluation after treatment. First, the physical and chemical properties of the separated filtrate are detected, including pH value, suspended matter content, heavy metal concentration and other indicators, to provide a basis for the formulation of subsequent treatment plans. Then, according to the filtrate properties and discharge / reuse requirements, a suitable deep treatment process is selected, such as flocculation precipitation, adsorption, membrane separation, etc. Next, for the selected treatment process, key parameters such as flocculant dosage, adsorbent type, membrane flux, etc. are optimized through experimental or simulation methods to obtain the best treatment effect. At the same time, key indicators in the treatment process, such as effluent pH value, turbidity, heavy metal concentration, etc., are monitored in real time, and process parameters are adjusted in time to ensure that the treatment effect is stable and meets the standards. Finally, the treated water sample is fully tested to confirm that various indicators meet the discharge or reuse standard requirements, and the treatment process is further optimized if necessary. Through these steps, appropriate deep treatment technology can be used to remove suspended matter, dissolved matter and harmful substances in the filtrate to meet the standards for water discharge or reuse.

[0060] Furthermore, the specific steps of step S80 include: index system construction, data collection and analysis, model establishment and verification, sensitivity analysis, and model application and update. First, according to the goals and requirements of mud treatment, a mud treatment efficiency evaluation index system including treatment speed, solid-liquid separation effect, filter cake moisture content, etc. is established. Then, in the actual mud treatment process, the measured data of each evaluation index is systematically collected, and the data is statistically analyzed to understand the relationship between the indicators. Next, a modeling method such as regression analysis and gray correlation is used to establish an evaluation model for mud treatment efficiency, and the model is verified and calibrated through measured data to ensure the accuracy and reliability of the model prediction. After that, a sensitivity analysis is performed on the evaluation model to identify the key factors that have the greatest impact on the treatment efficiency, providing a basis for subsequent process optimization. Finally, the established evaluation model is applied to the actual mud treatment process, and the model parameters are regularly updated to ensure that the model continues to reflect the actual situation. Through these steps, a systematic mud treatment efficiency evaluation system can be established to provide a scientific basis for optimizing mud treatment.

[0061] Furthermore, the specific steps of step S90 include: key parameter identification, single factor test, orthogonal test optimization, field verification and adjustment, and automatic control system development. First, combined with the aforementioned efficiency evaluation model, the key parameters affecting the processing efficiency of the mud filter press are identified, such as pressure, filtration time, feed rate, filter plate spacing, vibration frequency, filter cloth tension, etc. Then, for each key parameter, a single factor test method is used to conduct experimental research to explore the influence of the parameter on the processing efficiency and determine the optimal value range of each parameter. Next, the orthogonal test design method is used to systematically study the combination optimization of multiple key parameters to find the optimal process parameter combination that comprehensively considers each parameter. Subsequently, the optimized process parameter combination is applied to the actual mud treatment process, and the parameters are further optimized and adjusted through on-site monitoring and effect evaluation to ensure that the treatment effect meets the requirements. Finally, based on the optimized parameters, an automatic control system for the mud filter press is developed to realize real-time monitoring and automatic adjustment of key parameters and improve the stability and reliability of the treatment process. Through these steps, the processing efficiency and quality of the mud filter press can be further improved.

[0062] Optionally, the single factor test step in step S90 includes: conducting tests using different combinations of parameters such as pressure, filtration time, feed rate, filter plate spacing, vibration frequency, filter cloth tension, etc., testing the impact of each parameter on the processing efficiency, and determining the optimal value range of each parameter.

[0063] Optionally, the orthogonal experiment optimization step in step S90 includes: using the orthogonal experiment design method to systematically explore the combined optimization of multiple key parameters such as pressure, filtration time, feed rate, filter plate spacing, vibration frequency, filter cloth tension, etc., to find the optimal process parameter combination that comprehensively considers each parameter.

[0064] Optionally, the on-site verification and adjustment step in step S90 includes: applying the optimized process parameter combination to the actual mud treatment process, evaluating the treatment effect through on-site monitoring of indicators such as discharge concentration, filter press inlet and outlet pressure difference, and filter cake moisture content, and appropriately adjusting parameters according to the monitoring results to ensure that the treatment effect meets the requirements.

[0065] Optionally, the automatic control system development step in step S90 includes: developing an automatic control system for the mud filter press based on the optimized process parameters, capable of real-time monitoring of key indicators such as pressure, flow, and moisture content, and automatically adjusting parameters such as pressure, feed rate, and vibration frequency according to a preset control algorithm to ensure the stability and reliability of the mud treatment process.

[0066] Compared with the prior art, the beneficial effects of the mud filter press construction method for treating large-area mud are as follows:

[0067] First, this method determines the optimal layout plan of the mud filter press through spatial analysis of the mud generation points and multi-objective optimization of the mud filter press deployment location, maximizes the utilization of the existing mud pool location, shortens the mud transportation distance, and thus significantly reduces the overall operating cost.

[0068] Secondly, this method adopts the preparation of high-quality curing agent and performance control measures to ensure the stability and reliability of mud curing treatment, laying a solid foundation for subsequent resource utilization. At the same time, parameter optimization and performance monitoring during the filter press process improve the effect of initial separation and create good conditions for subsequent deep filtration treatment.

[0069] Furthermore, this method treats and utilizes the filter cake and filtrate in a targeted manner, which not only achieves effective separation of solid particles and clean water, but also greatly reduces the environmental burden through resource utilization. Compared with traditional simple sedimentation or landfill treatment, this method greatly reduces the risk of secondary pollution.

[0070] Finally, this method established a comprehensive evaluation system for mud treatment efficiency, and used an optimization algorithm to determine the optimal combination of key process parameters, realizing intelligent control of the mud treatment process and continuously improving treatment efficiency and quality. This method based on mathematical modeling and algorithm optimization has greatly improved the reliability and stability of mud treatment.

[0071] In conclusion, the method of the present invention fully integrates engineering practice and scientific theory, systematically optimizes the entire process of mud filter pressing, and solves the technical problem of low processing efficiency in the existing mud filter pressing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 A flow chart of the method provided by the present invention;

[0073] Figure 2 It is the construction process flow chart in Example 2;

[0074] Figure 3 It is the plan layout diagram of the filter press in Example 2. DETAILED DESCRIPTION

[0075] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0076] like Figure 1 As shown, it is a flow chart of a construction method for treating large-area mud with a mud filter press provided by the present invention, and the method comprises the following steps:

[0077] S10. Determine the optimal deployment position of the mud filter press according to the site plan layout to maximize the use of the mud pool position;

[0078] S20, prepare the curing agent, optimize the curing agent ratio, stir and adjust according to the project needs to ensure that the quality and performance meet the requirements;

[0079] S30, transporting the mud to a mud filter press, and performing high-pressure mechanical pressing to achieve preliminary separation of solid particles and liquid;

[0080] S40, further filtering the squeezed mud using a filtering system to separate a solid residue filter cake and a filtrate;

[0081] S50, compacting the filter cake to reduce its volume and improve its stability in preparation for subsequent processing;

[0082] S60, collecting the treated filter cake and backfilling, making bricks or other resource utilization according to engineering requirements;

[0083] S70, treating the filtrate by sedimentation, filtration and adsorption to remove suspended solids, dissolved solids and harmful substances to meet the discharge or recycling standards;

[0084] S80. Establish a mud treatment efficiency evaluation model, including treatment speed, solid-liquid separation effect, and filter cake moisture content indicators;

[0085] S90. Based on the evaluation model results, optimize the operating parameters of the mud filter press, including pressure, filtration time, feed rate, filter plate spacing, vibration frequency, and filter cloth tension, to improve processing efficiency and effect.

[0086] The specific implementation methods of the above steps are described in detail below:

[0087] Step S10: Determine the optimal deployment position of the mud filter press according to the site layout

[0088] 1. Analysis of mud generation point location: First, conduct a field survey of the construction site to determine the exact location and amount of mud generation points. Based on the distribution and amount of mud generation points, use a spatial analysis algorithm to cluster the mud generation points and identify the main mud generation areas.

[0089] 2. Optimization of the location of the mud filter press: A multi-objective optimization model is established, and the objective functions include minimizing the total transportation cost, minimizing the total processing time, minimizing the environmental impact, etc. The constraints include the mud processing capacity, site area, environmental impact threshold, etc. The mixed integer programming algorithm is used to solve the optimization problem and obtain the optimal deployment location of the mud filter press.

[0090] 3. Visualization and evaluation of the scheme: The optimization results are visualized on the site plan to intuitively reflect the deployment location of the mud filter press and the transportation path of the mud. At the same time, the economic efficiency, environmental impact and operational feasibility of the scheme are evaluated, and the scheme is iteratively optimized when necessary.

[0091] The purpose of this step is to determine the optimal deployment location of the mud filter press to maximize the use of the existing mud pool location, shorten the mud transportation distance, reduce the overall cost, and meet the environmental impact restrictions. Through spatial analysis, multi-objective optimization and program evaluation, an optimal deployment plan that comprehensively considers all factors is obtained.

[0092] Step S20: Prepare and optimize the curing agent ratio

[0093] 1. Curing agent performance test: Conduct physical and chemical performance tests on available curing agents, including gel time, compression strength, pH value and other indicators, and compare and analyze them with process requirements.

[0094] 2. Mix ratio optimization: Use single factor test method or orthogonal test method to systematically explore the effects of different curing agent dosage, water-cement ratio, admixture dosage, etc. on the curing effect, and determine the best curing agent mix ratio. The optimized curing agent mix ratio is obtained through data fitting and analysis.

[0095] 3. On-site verification: The optimized curing agent mix ratio is tested and verified on-site to test the strength, permeability, stability and other indicators after curing to ensure that the project requirements are met. If necessary, the mix ratio can be further optimized.

[0096] 4. Quality control: Establish a quality control system for curing agent preparation, including on-site inspection of raw materials, monitoring of the preparation process, testing of finished product performance, etc. Ensure that the quality and performance of the curing agent always meet the standard requirements.

[0097] The purpose of this step is to prepare a high-quality curing agent that meets the engineering requirements and lays the foundation for the subsequent mud curing treatment. Through systematic performance testing, mix ratio optimization and on-site verification, the performance of the curing agent is ensured to be stable and reliable. At the same time, quality control measures are established to ensure the quality of the curing agent during preparation and use.

[0098] Step S30: transport the slurry to the filter press for preliminary separation

[0099] 1. Mud pretreatment: The mud collected on site is transported to the feed port of the filter press. The mud is pretreated as necessary, such as adjusting the pH value, adding flocculants, etc., to improve the filterability of the mud.

[0100] 2. High-pressure mechanical pressing: Use high-pressure mechanical pressing to perform preliminary dehydration and separation of the mud. During the pressing process, the mud is strongly squeezed, and the solid particles and liquid are initially separated.

[0101] 3. Optimization of pressing parameters: By adjusting the pressure, pressing time and other parameters, the pressing process can be optimized to obtain the highest possible solid-liquid separation effect. The best pressing parameters can be determined by experimental methods or model prediction methods.

[0102] 4. Performance monitoring: Real-time monitoring of pressure, flow, discharge concentration and other indicators during the pressing process, timely adjustment of parameters to ensure stable and controllable pressing effect.

[0103] The purpose of this step is to use high-pressure mechanical force to perform preliminary solid-liquid separation on the mud, preparing for subsequent deep filtration. The effect of preliminary separation can be maximized by optimizing the squeezing parameters and real-time performance monitoring.

[0104] Step S40: Further separation of solid and liquid using a filtration system

[0105] 1. Filtration system selection: According to the mud characteristics, separation objectives and processing capacity requirements, select appropriate filtration equipment, such as belt filter press, centrifuge, vacuum filter, etc.

[0106] 2. Filtration process optimization: Optimize filtration parameters for different filtration equipment, such as filter material type, filtration pressure, filtration time, etc. Determine the best filtration process parameters through experiments or simulation prediction methods.

[0107] 3. Filtration performance monitoring: Real-time monitoring of pressure difference, discharge concentration, filter cake moisture content and other indicators during the filtration process, timely adjustment of filtration parameters to ensure stable filtration effect.

[0108] 4. Filter cake and filtrate treatment: The solid filter cake and liquid filtrate obtained by separation are subjected to subsequent treatment respectively. The filter cake can be compacted, dried, etc., while the filtrate requires further purification treatment, such as precipitation, flocculation, adsorption, etc.

[0109] The purpose of this step is to use filtration technology to further separate solid particles and clean filtrate. By rationally selecting filtration equipment and optimizing filtration parameters, the solid-liquid separation effect can be maximized. At the same time, the separated two-phase materials are subjected to targeted subsequent treatment to meet the requirements of subsequent utilization or discharge.

[0110] Step S50: compacting the filter cake

[0111] 1. Determination of filter cake moisture content: Use drying method or other rapid determination methods to measure the moisture content of the filter cake in a timely manner.

[0112] 2. Compacting equipment selection: According to the filter cake characteristics and compaction goals, select appropriate compacting equipment, such as hydraulic press, vibration table, etc.

[0113] 3. Optimization of compaction parameters: Determine the optimal compaction pressure, time, vibration frequency and other parameters through experiments or empirical formulas to obtain the target moisture content and volume reduction rate.

[0114] 4. Compaction process monitoring: Real-time monitoring of pressure, moisture content and other indicators during the compaction process, timely adjustment of parameters to ensure stable compaction effect.

[0115] 5. Compaction effect evaluation: Test and evaluate the moisture content, strength and other indicators of the compacted filter cake to ensure that it meets the requirements for subsequent processing or utilization.

[0116] The purpose of this step is to further dehydrate and reduce the volume of the filter cake through mechanical compaction, so as to prepare for subsequent resource utilization or landfill treatment. By optimizing the compaction process parameters and process monitoring, the compaction effect is ensured to be stable and reliable.

[0117] Step S60: Recycling the compacted filter cake

[0118] 1. Filter cake property analysis: The physical and chemical properties of the compacted filter cake are analyzed, including indicators such as moisture content, strength, and heavy metal content, to provide a basis for the formulation of subsequent utilization plans.

[0119] 2. Resource utilization plan formulation: According to the properties and characteristics of the filter cake and engineering requirements, formulate a specific resource utilization plan, such as backfill utilization, brick making, etc. Optimize relevant process parameters for different utilization methods.

[0120] 3. Implementation of resource utilization: According to the formulated utilization plan, the treated filter cake is transported to the designated location for actual utilization. For example, when backfilling, layered paving and compaction are adopted; when making bricks, the filter cake is mixed with other raw materials and then formed and fired.

[0121] 4. Utilization effect evaluation: Evaluate the actual effect of resource utilization, including utilization volume, environmental impact and other indicators, and optimize and adjust the plan when necessary.

[0122] The purpose of this step is to give full play to the resource value of the treated filter cake, to achieve the recycling of waste as much as possible, and to reduce the burden on the environment. Through systematic property analysis and targeted utilization plan formulation, the environmental friendliness and economy of filter cake resource utilization are ensured.

[0123] Step S70: deep treatment of the filtrate

[0124] 1. Filtrate property testing: The physical and chemical properties of the separated filtrate are tested, including pH value, suspended matter content, heavy metal concentration and other indicators, to provide a basis for the formulation of subsequent treatment plans.

[0125] 2. Treatment process selection: According to the properties of the filtrate and the discharge / reuse requirements, select the appropriate deep treatment process, such as flocculation sedimentation, adsorption, membrane separation, etc.

[0126] 3. Optimization of treatment process parameters: For the selected treatment process, optimize key parameters such as flocculant dosage, adsorbent type, membrane flux, etc. through experiments or simulation methods to obtain the best treatment effect.

[0127] 4. Treatment effect monitoring: Real-time monitoring of key indicators in the treatment process, such as effluent pH, turbidity, heavy metal concentration, etc., timely adjustment of process parameters to ensure that the treatment effect is stable and meets the standards.

[0128] 5. Post-treatment water quality evaluation: Conduct comprehensive testing on treated water samples to confirm that all indicators meet the discharge or reuse standards. Further optimize the treatment process if necessary.

[0129] The purpose of this step is to use appropriate deep treatment technology to remove suspended matter, dissolved matter and harmful substances in the filtrate, so that the treated water can meet the water quality standards for discharge or reuse. Through the optimization of process parameters and real-time monitoring of treatment effects, the treatment process is ensured to be stable and efficient, and the impact on the environment is minimized.

[0130] Step S80: Establishing a mud treatment efficiency evaluation model

[0131] 1. Index system construction: According to the goals and requirements of mud treatment, a mud treatment efficiency evaluation index system including treatment speed, solid-liquid separation effect, filter cake moisture content, etc. is established.

[0132] 2. Data collection and analysis: In the actual mud treatment process, the measured data of each evaluation index are systematically collected and statistically analyzed to understand the relationship between the indicators.

[0133] 3. Model establishment and verification: Use regression analysis, grey correlation and other modeling methods to establish a mud treatment efficiency evaluation model. Verify and calibrate the model through measured data to ensure the accuracy and reliability of model prediction.

[0134] 4. Sensitivity analysis: Conduct sensitivity analysis on the evaluation model to identify the key factors that have the greatest impact on the processing efficiency and provide a basis for subsequent process optimization.

[0135] 5. Model application and updating: Apply the established evaluation model to the actual mud treatment process and regularly update the model parameters to ensure that the model continues to reflect the actual situation.

[0136] The purpose of this step is to establish a systematic mud treatment efficiency evaluation system to quantify the key performance indicators of the treatment process. Through data analysis and modeling, the key factors affecting the treatment efficiency are identified to provide a scientific basis for subsequent process optimization. At the same time, the evaluation model can be continuously applied in actual operation to provide decision support for optimizing mud treatment.

[0137] Step S90: Optimizing the operating parameters of the mud filter press

[0138] 1. Identification of key parameters: Combined with the aforementioned efficiency evaluation model, identify the key parameters that affect the processing efficiency of the mud filter press, such as pressure, filtration time, feed rate, filter plate spacing, vibration frequency, filter cloth tension, etc.

[0139] 2. Single factor test: For each key parameter, a single factor test method is used to conduct experimental research to explore the influence of the parameter on the processing efficiency. By analyzing the test data, the optimal value range of each parameter is determined.

[0140] 3. Orthogonal experiment optimization: Using the orthogonal experiment design method, systematically study the combination optimization of multiple key parameters to find the optimal process parameter combination that comprehensively considers various parameters.

[0141] 4. On-site verification and adjustment: Apply the optimized process parameter combination to the actual mud treatment process, and further optimize and adjust the parameters through on-site monitoring and effect evaluation to ensure that the treatment effect meets the requirements.

[0142] 5. Development of automatic control system: Based on the optimized parameters, develop the automatic control system of the mud filter press to realize real-time monitoring and automatic adjustment of key parameters and improve the stability and reliability of the processing process.

[0143] 6. Establishment of optimization parameter model: Based on the results of the above single factor test and orthogonal test, establish the optimization model between the key parameters of the mud filter press and the processing efficiency. The model can be a regression model, a neural network model or other data-driven model. The model can describe the influence degree and interaction of each parameter on the processing index.

[0144] 7. Model simulation and optimization: Using the established optimization parameter model, numerical optimization algorithms such as genetic algorithm and particle swarm optimization are used to find the process parameter combination that can achieve the optimal processing efficiency. Through model simulation, the influence of different parameter combinations on the processing effect is analyzed.

[0145] 8. Field verification and feedback: Apply the optimized process parameter combination to the actual mud treatment process, and conduct field testing and evaluation of the treatment effect. According to the actual effect, appropriately adjust the parameters of the optimization model to ensure that the model prediction results are consistent with the actual situation.

[0146] 9. Automatic optimization control: Integrate the optimized process parameters into the automatic control system of the mud filter press to achieve real-time monitoring and automatic optimization and adjustment of key parameters. The control system can automatically adjust the parameters according to the real-time monitored processing indicators to continuously optimize the mud processing efficiency.

[0147] The purpose of this step is to establish an optimization parameter model, use numerical optimization algorithms to find the optimal process parameter combination, and integrate it into the automatic control system to achieve intelligent optimization of the operating parameters of the mud filter press and continuously improve the efficiency and quality of mud treatment. This requires combining actual operating data, continuously improving the optimization model, and improving the adaptive ability of the control system.

[0148] In summary, this method of using a mud filter press to treat large-scale mud construction fully considers various factors in the mud treatment process, and through systematic optimization design and intelligent parameter control, it maximizes the mud treatment efficiency while also minimizing environmental impact. This method embodies the characteristics of combining engineering practice with scientific theory, and provides a reliable technical support for large-scale mud treatment.

[0149] For steps S80 and S90, specifically, step S80 is to establish a mud treatment efficiency evaluation model:

[0150] The purpose of this step is to establish a systematic mud treatment efficiency evaluation system to quantify the key performance indicators of the treatment process. The specific steps are as follows:

[0151] 1. Construction of indicator system

[0152] According to the goals and requirements of mud treatment, a mud treatment efficiency evaluation index system including treatment speed v, solid-liquid separation effect η, filter cake moisture content w, etc. is established. Among them, treatment speed v represents the amount of mud treated per unit time, solid-liquid separation effect η represents the degree of separation between solid matter and liquid, and filter cake moisture content w represents the residual moisture content in the filter cake. These indicators can fully reflect the key performance of the mud treatment process.

[0153] 2. Data Collection and Analysis

[0154] In the actual mud treatment process, the measured data of each evaluation index are systematically collected to form a sample data set. in is the feature vector of the i-th sample, is the corresponding efficiency index value. Perform statistical analysis on the data set to understand the correlation and internal rules between the indicators.

[0155] 3. Model establishment and verification

[0156] The regression analysis method is used to establish a prediction model between the mud treatment efficiency index and the key process parameters. The model is assumed to be in the form of:

[0157] y=f(x;θ)+∈;

[0158] in is the efficiency index vector, is the feature vector, θ is the model parameter, and ∈ is the random error term. Linear regression, neural network and other methods can be used to fit the model parameter θ, and the model prediction performance can be evaluated through cross-validation and other methods to ensure that the model prediction results are consistent with the actual situation.

[0159] 4. Sensitivity analysis

[0160] The sensitivity analysis of the established evaluation model is carried out to quantify the influence of each process parameter on the processing efficiency index. The grey correlation analysis method can be used to calculate the correlation γ between each parameter and the efficiency index:

[0161]

[0162] Among them, Δ(x j ,y k )=|x j -y k | is the absolute difference between the jth parameter and the kth index, and ρ is the resolution coefficient. The larger the correlation value, the more significant the impact of the parameter on the index.

[0163] 5. Model application and update

[0164] The established mud treatment efficiency evaluation model is integrated into the operation and management platform of the mud treatment system, and the model is called in real time to predict the treatment efficiency index. At the same time, the model parameter θ is regularly updated according to the actual operation data to ensure that the model continues to accurately reflect the actual working conditions.

[0165] The following is step S90, i.e. optimizing the operating parameters of the mud filter press:

[0166] The purpose of this step is to establish an optimization parameter model, use numerical optimization algorithms to find the optimal process parameter combination, and integrate it into the automatic control system to achieve intelligent optimization of the mud filter press operating parameters and continuously improve the efficiency and quality of mud treatment. The specific steps are as follows:

[0167] 1. Identification of key parameters

[0168] Combined with the above-mentioned efficiency evaluation model, the key parameters affecting the processing efficiency of the mud filter press are identified, including pressure P, filtration time t, feed rate Q, filter plate spacing d, vibration frequency f, filter cloth tension σ, etc.

[0169] 2. Single Factor Experiment

[0170] For each key parameter, a single factor test method is used to conduct experimental research to explore the influence of this parameter on the processing efficiency. For example, a single factor test of pressure P can be performed by setting different pressure values ​​P = {P1, P2, ..., P m}, and tested its influence on the processing speed v, solid-liquid separation effect η and filter cake moisture content w, and obtained the functional relationship v=g1(P),η=g2(P),w=g3(P). By analyzing the test data, the optimal value range of each parameter was determined.

[0171] 3. Orthogonal test optimization

[0172] The orthogonal experimental design method is used to systematically study the combination optimization of multiple key parameters. N (k m ) type orthogonal test matrix, where N is the number of tests, k is the number of parameter levels, and m is the number of parameters. According to the results of the single factor test, the value range of each parameter is determined, and then an orthogonal test is conducted to test the response value of each indicator. The test results are analyzed using the variance analysis method to find the optimal process parameter combination that comprehensively considers each parameter.

[0173] 4. Optimization parameter model establishment

[0174] Based on the above single factor test and orthogonal test results, an optimization model between the key parameters of the mud filter press and the processing efficiency is established. This model can describe the influence and interaction of each parameter on the processing index. The model form is assumed to be:

[0175] y=f(x;θ)+∈

[0176] in, is the efficiency index vector, is the parameter vector, θ is the model parameter, and ∈ is the random error term. The model parameter θ can be fitted by multiple linear regression, neural network and other methods.

[0177] 5. Model simulation and optimization

[0178] Using the established optimization parameter model, numerical optimization algorithms such as genetic algorithm and particle swarm optimization are used to find the process parameter combination x that can achieve the optimal processing efficiency. * Through model simulation, the influence of different parameter combinations on the processing effect is analyzed to find the global optimal solution.

[0179] 6. Optional, on-site verification and feedback

[0180] The optimized process parameter combination x * It is applied to the actual mud treatment process to conduct field tests and evaluations on the treatment effect. According to the actual effect, the parameter θ of the optimization model is appropriately adjusted to ensure that the model prediction results are consistent with the actual situation.

[0181] 7.Optional, automatic optimization control

[0182] The optimized process parameters are integrated into the automatic control system of the mud filter press to achieve real-time monitoring and automatic optimization and adjustment of key parameters. The control system can automatically adjust the parameter x according to the real-time monitored processing index y, so that the processing effect is continuously optimized and the efficiency and quality of mud processing are improved.

[0183] In summary, by establishing an optimization parameter model, using a numerical optimization algorithm to find the optimal process parameters, and integrating them into the automatic control system, the intelligent optimization of the operating parameters of the mud filter press is achieved, and the efficiency and quality of mud treatment are continuously improved. This method makes full use of technical means such as mathematical modeling, algorithm optimization and automatic control, and provides reliable technical support for large-scale mud treatment.

[0184] Specifically, the principle of the present invention is to adopt systematic optimization design and intelligent parameter control means to achieve refined control of the entire mud treatment process.

[0185] First, the optimal layout of the mud filter press was determined through spatial analysis of the mud generation point and multi-objective optimization of the filter press deployment location. This optimization design based on actual engineering needs and operating conditions maximizes the use of the existing mud pool location, shortens the mud transportation distance, and thus significantly reduces the overall operating cost. At the same time, factors such as environmental impact are taken into consideration, making the mud treatment solution more environmentally friendly and sustainable.

[0186] Secondly, in the mud pretreatment and curing stage, the present invention adopts the preparation and performance control measures of high-quality curing agent. Through the optimization of the system's mix ratio and on-site verification, the performance of the curing agent is ensured to be stable and reliable, laying the foundation for subsequent resource utilization. This approach of focusing on process quality control greatly improves the reliability of mud curing treatment.

[0187] Furthermore, in the filter press separation process, the present invention maximizes the effect of initial separation through parameter optimization and real-time performance monitoring. This method based on process model and feedback control makes the filter press treatment more stable and efficient, creating good conditions for subsequent deep filtration.

[0188] Finally, the present invention adopts targeted treatment and utilization measures for the filter cake and filtrate respectively. Through compaction, drying and other treatment methods, the volume and moisture content of the filter cake are effectively controlled; and the filtrate is deeply purified by precipitation, flocculation, adsorption and other methods to meet the standard requirements for discharge or reuse. This method of solid-liquid separation and separate treatment greatly improves the efficiency of resource utilization and minimizes the impact on the environment.

[0189] In general, the core of the method of the present invention is to systematically optimize the entire process of mud treatment, make full use of technical means such as mathematical modeling, algorithm optimization and automatic control, and realize refined control of mud treatment.

[0190] In order to better understand and implement the present invention, the following provides an embodiment 1 of a specific application scenario of the present invention: A rail transit project in a certain city is a large-scale underground railway project, involving a large amount of foundation pit excavation and foundation treatment operations. A large amount of mud waste is generated during these projects, which has become a major problem in construction management. In order to properly handle the mud, the project adopts the method of using a mud filter press to handle large-area mud construction proposed by the present invention.

[0191] 1. Identification and distribution analysis of mud generation points

[0192] According to the construction plan and on-site investigation, there are 8 main mud generation points in the project, located in the foundation pit excavation area and the foundation treatment site. The mud generation volume of each generation point is about 100-300m 3 / d, the total mud production is about 1500m 3 In order to optimize the deployment of mud filter presses, spatial analysis and cluster identification of these mud generation points were first performed.

[0193] Through GIS spatial analysis software, the location information of 8 mud production points was entered into the system, and the K-means clustering algorithm was used to divide these points into 3 main clustering areas, located in the west, middle and east of the project. The mud production points in each clustering area are relatively concentrated, which provides a basis for the subsequent deployment optimization of the filter press.

[0194] 2. Optimization of mud filter press deployment

[0195] Based on the spatial distribution characteristics of the above-mentioned mud generation points and the actual conditions of the project site, the deployment location of the mud filter press was optimized using the mixed integer programming method. The optimization objectives include: minimizing the total transportation cost, minimizing the total processing time, minimizing the environmental impact, etc. The constraints include: mud processing capacity, site area, environmental impact threshold, etc.

[0196] By solving the optimization problem, the best solution was determined to deploy one mud filter press each on the west, middle and east sides of the project. This not only maximized the use of the existing mud pool location and significantly shortened the mud transportation distance, but also controlled the environmental impact within an acceptable range.

[0197] 3. Preparation and quality control of curing agent

[0198] According to the actual characteristics of the engineering mud, an environmentally friendly cement-based curing agent was selected. First, the physical and chemical properties of the curing agent were systematically tested, and the results showed that its gel time was 2-4 hours, and the 28d compressive strength reached 8MPa, which met the engineering requirements.

[0199] Then, the curing agent ratio was optimized through single factor test and orthogonal test. After several rounds of tests, the optimal curing agent dosage was 10%, water-cement ratio was 0.5, and admixture dosage was 2%. This solution not only meets the strength index, but is also harmless to the environment.

[0200] In order to ensure the stable quality of the curing agent, a strict quality control system has been established, including raw material inspection, preparation process monitoring, finished product performance testing, etc. At the same time, the preparation of the curing agent is carried out in a special mixing equipment to ensure the accuracy of the mix ratio.

[0201] 4. Initial separation of mud

[0202] The mud collected on site was transported to the first filter press deployed on the west side of the project for preliminary separation. First, the mud was pre-treated by pH adjustment and flocculant addition to improve its filterability. Then, in the filter press, the mud was mechanically squeezed at a high pressure of 75 bar to initially separate the solid and liquid.

[0203] By adjusting the optimization of pressure and time parameters, the optimal parameters of the filter pressing process were finally determined to be: pressure 75bar, pressing time 45min. Under this condition, the discharge concentration after pressing reached 30%, which met the requirements of subsequent filtration treatment. During the entire filter pressing process, pressure, flow, concentration and other indicators were monitored in real time to ensure the stability of the separation effect.

[0204] 5. Deep filtration and processing

[0205] The mud slurry obtained by preliminary separation was transported to the second belt filter press in the middle for deep filtration. By optimizing the parameters such as filter material type, filtration pressure, and filtration time, the optimal filtration process conditions were finally determined as: polyester long fiber filter material, filtration pressure 2 bar, and filtration time 90 minutes.

[0206] Under this process condition, the moisture content of the filter cake after filtration is reduced to 25%, which meets the requirements of subsequent treatment. At the same time, the clear liquid produced by filtration undergoes further deep treatment such as flocculation sedimentation and activated carbon adsorption, and all indicators meet the Class A standard of the "Pollutant Discharge Standard for Urban Wastewater Treatment Plants" and can be discharged directly.

[0207] 6. Resource utilization of filter cake

[0208] The filter cake with a moisture content of 25% obtained after filtration was first compacted by a hydraulic press. After compaction at 35 bar, the moisture content of the filter cake was further reduced to 18%, and the volume was reduced to 1 / 3 of the original.

[0209] According to the physical and chemical properties of the filter cake, its main components are soil particles and a small amount of cement, which can be used as backfill materials. Therefore, the compacted filter cake was transported to the foundation treatment site on the east side of the project, laid in layers and rolled for foundation reinforcement. This not only solved the problem of filter cake disposal, but also saved a large amount of natural backfill materials.

[0210] After monitoring, the backfill treatment has no adverse effects on the surrounding soil and groundwater, fully meeting the requirements of environmental protection. In addition, compared with direct landfill, this resource utilization method reduces the burden on the environment and realizes the recycling of waste.

[0211] 7. Deep treatment of filtrate

[0212] After preliminary separation by filter press and deep filtration by belt filter press, a large amount of clear filtrate was obtained. The filtrate was systematically tested for its physical and chemical properties, and the results showed that it still contained a small amount of suspended matter, dissolved matter, heavy metals and other pollutants.

[0213] To ensure that the filtrate meets the discharge standards, the third treatment equipment - membrane concentration device - was deployed on the east side. By optimizing parameters such as membrane materials, operating pressure, and residence time, the final removal rates were: suspended solids 99.5%, COD 95%, and heavy metals over 90%. All indicators of the treated filtrate have reached the Class A standard of the "Pollutant Discharge Standard for Urban Wastewater Treatment Plants" and can be discharged safely.

[0214] In addition, the concentrate produced by the membrane concentration device is not suitable for direct discharge due to its high concentration of pollutants. Therefore, a deep treatment process of chemical oxidation + activated carbon adsorption is adopted to further remove organic matter and heavy metals, and finally meet the requirements of the "Hazardous Waste Identification Standards" and can be sent to qualified units for safe disposal.

[0215] 8. Intelligent optimization of mud processing efficiency

[0216] In order to continuously improve the efficiency and quality of mud treatment, this project established a mud treatment efficiency evaluation system covering treatment speed, solid-liquid separation effect, filter cake moisture content, etc. Through systematic monitoring and data analysis of various indicators in the actual treatment process, a corresponding prediction model was established.

[0217] The grey correlation analysis method was used to quantitatively analyze the influence of key parameters such as pressure, filtration time, and feed rate on the processing efficiency. Based on this, the genetic algorithm was used to optimize the combination of these process parameters and determine the parameter settings that can achieve the optimal processing efficiency, including: pressure 70 bar, filtration time 50 min, feed rate 150 m / s, and the like. 3 / h, etc.

[0218] Finally, the optimized process parameters were integrated into the automatic control system of the filter press. The control system can monitor various performance indicators in real time and automatically adjust parameters such as pressure, feed rate, vibration frequency, etc. according to the preset optimization algorithm to continuously optimize the treatment effect. This intelligent control method greatly improves the stability and reliability of mud treatment.

[0219] In this embodiment 1, the project achieved remarkable results in the mud treatment process:

[0220] 1) The total operating cost is reduced by more than 30% compared with the traditional solution, which reflects good economic efficiency;

[0221] 2) The environmental impact indicators of the treated filtrate and filter cake meet or exceed the relevant standards, and environmental protection is effectively guaranteed;

[0222] 3) The overall processing efficiency has been increased by more than 40% compared with before, meeting the needs of large-scale mud construction.

[0223] In addition, the following is a specific embodiment 2 of a simplified process of the present invention: Figure 2 The on-site mud treatment construction process is described as follows: mud preparation → filtration and squeezing → solid-liquid separation → filter cake treatment → filtrate treatment → mud cake compression → recycling.

[0224] (I) Construction preparation

[0225] 1. Location preparation:

[0226] Using BIM simulation and 3D animation technology, the pile foundation area is gridded to determine the optimal deployment, ensure that the mud concentration point can be maximized, and confirm the location of the optimal mud pool and filter press.

[0227] 2. Preparation of admixtures:

[0228] Due to the liquid state and polluting nature of the mud, it is impossible to discharge it or bury it on site. Therefore, after the mud is roller-pressed for drainage, a sedimentation solidifier is added to the treated mud, which is solidified and compressed into a mud cake for discharge.

[0229] Through joint laboratory research on the curing agent ratio, the maximum effect of the curing agent on mud treatment is achieved to ensure the sedimentation of mud on site

[0230] 3. Site preparation:

[0231] A mobile mud filter press is a mud filter press placed on a flatbed truck, with a conveyor, folding platform, guardrail, mud mixing box, high-pressure pump, etc. at the bottom. The mobile filter press moves with the pile foundation construction area.

[0232] The mud filter press is equipped with muck trucks and forklifts around it, and the filter press operating area is 3m*17m.

[0233] 4. Mechanical preparation: The filter press is divided into plate and frame filter press and chamber filter press. It is an intermittent pressure filtration equipment used for solid-liquid separation of various suspensions. It relies on the pressing device to press the filter plate, and then press the suspension into the filter chamber with a material pump, and separate the solid particles and liquid materials through the filter cloth.

[0234] (II) Key Processes

[0235] 1. Construction deployment

[0236] Root Figure 3 As shown, according to the site plan layout, the optimal site deployment is determined to maximize the use of the mud pool location;

[0237] 2. Preparation of curing agent

[0238] Before mud treatment, prepare the curing agent. Optimize the curing agent ratio, stir and adjust according to the project needs to ensure that the quality and performance meet the requirements;

[0239] 3. Filtration and pressing

[0240] The core of mud treatment is filtering and squeezing through a mud filter. The mud passes through the filtration system of the mud filter and is mechanically squeezed at high pressure. Solid particles are separated, while water and dissolved substances are discharged through the filter screen, thus achieving mud purification and treatment.

[0241] 4. Solid-liquid separation

[0242] During the filtration and squeezing process, the solid particles in the mud are separated to form solid residue, and the filtered liquid is called filtrate. Through proper treatment and collection, the solid residue and filtrate can be effectively separated into solid and liquid, and treated or disposed of separately.

[0243] 5. Filter cake treatment

[0244] After filtering and squeezing, the solid particles in the mud form a layer of compacted solid residue, called filter cake. The treatment of filter cake usually includes steps such as squeezing, drying, and collection to reduce the volume and improve the stability of the solid residue for subsequent treatment and disposal.

[0245] 6. Filtrate treatment

[0246] The filtered liquid filtrate needs to be further treated to remove suspended matter, dissolved matter and harmful substances to meet the requirements of discharge or recycling. Common treatment methods include sedimentation, filtration, adsorption, ion exchange, etc. to improve the quality and cleanliness of the filtrate.

[0247] 7. Recycling

[0248] After the mud treatment is completed, the treated mud and filtrate can be recycled. Through proper treatment and adjustment, the mud and filtrate can be reused in engineering construction to achieve effective utilization of resources and sustainable development of the environment.

[0249] The mud press mud treatment technology achieves efficient treatment and purification of mud through mechanical pressure. It has the advantages of fast processing speed, good effect and easy operation. It is widely used in civil engineering, tunnel engineering and underground engineering, providing reliable mud treatment solutions for engineering construction.

[0250] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for treating large-area mud by using a mud filter press, characterized in that: The following steps are involved: S10. Determine the optimal deployment position of the mud filter press according to the site plan layout to maximize the use of the mud pool position; S20, prepare the curing agent, optimize the curing agent ratio, stir and adjust according to the project needs to ensure that the quality and performance meet the requirements; S30, transporting the mud to a mud filter press, and performing high-pressure mechanical pressing to achieve preliminary separation of solid particles and liquid; S40, further filtering the squeezed mud using a filtering system to separate a solid residue filter cake and a filtrate; S50, compacting the filter cake to reduce its volume and improve its stability in preparation for subsequent processing; S60, collecting the treated filter cake and backfilling, making bricks or other resource utilization according to engineering requirements; S70, treating the filtrate by sedimentation, filtration and adsorption to remove suspended solids, dissolved solids and harmful substances to meet the discharge or recycling standards; S80. Establish a mud treatment efficiency evaluation model, including treatment speed, solid-liquid separation effect, and filter cake moisture content indicators; S90. Based on the evaluation model results, optimize the operating parameters of the mud filter press, including pressure, filtration time, feed rate, filter plate spacing, vibration frequency, and filter cloth tension, to improve processing efficiency and effect.

2. The method for treating large-area mud by using a mud filter press according to claim 1, characterized in that: The determination of the optimal deployment position of the mud filter press is achieved by using a multi-objective optimization function, which is expressed as follows: Where n is the number of mud generation points; m is the number of filter press deployment locations; x ij If the slurry is transported from point i to the filter press at position j, it is 1, otherwise it is 0; j If the filter press is deployed at position j, it is 1, otherwise it is 0; c ij is the unit transportation cost of transporting mud from point i to location j; f j is the fixed cost of installing a filter press at location j; q j is the cost of operating the filter press at location j; e j is the cost of dealing with environmental impacts at location j.

3. The method for treating large-area mud by using a mud filter press according to claim 2, characterized in that: The multi-objective optimization function includes the mud processing capacity constraint, which is specifically expressed as follows: In the formula, v i is the mud volume generated at point i; P j is the processing capacity of the filter press at position j.

4. The method for treating large-area mud by using a mud filter press according to claim 3, characterized in that: The multi-objective optimization function contains the constraint that each mud generation point must be assigned to a filter press, which is specifically expressed as follows:

5. The method for treating large-area mud by using a mud filter press according to claim 4, characterized in that: The multi-objective optimization function includes a transportation distance constraint, which is specifically expressed as follows: Where, d ij is the distance from point i to position j; d max is the maximum allowable total transport distance.

6. The method for treating large-area mud by using a mud filter press according to claim 5, characterized in that: The multi-objective optimization function includes a site area constraint, which is specifically expressed as follows: In the formula, A j A is the area occupied by the filter press at position j; max is the maximum total available area.

7. A method for treating large-area mud by using a mud filter press according to claim 6, characterized in that: The multi-objective optimization function includes environmental impact constraints, which are specifically expressed as follows: Where N j ,S j ,W j are the noise, dust and wastewater impact factors at location j; w1, w2, w3 are the environmental impact weights; E max is the maximum permissible environmental impact.

8. The method for treating large-area mud by using a mud filter press according to claim 7, characterized in that: The multi-objective optimization function includes a time constraint, which is specifically expressed as follows: Where, t ij is the time to transport mud from point i to position j; p j is the processing time of the filter press at position j; T max is the maximum allowed total time.

9. A method for treating large-area mud by using a mud filter press according to claim 8, characterized in that: The multi-objective optimization function contains decision variable constraints, which are specifically expressed as follows:

10. A method for treating large-area mud by using a mud filter press according to claim 9, characterized in that: The steps of establishing the mud treatment efficiency evaluation model specifically include: According to the goals and requirements of mud treatment, establish a mud treatment efficiency evaluation index system including treatment speed, solid-liquid separation effect, and filter cake moisture content; In the actual mud treatment process, the measured data of each evaluation index are systematically collected to form a sample data set, and the data set is statistically analyzed; By using regression analysis method, a prediction model between mud treatment efficiency index and key process parameters is established as a mud treatment efficiency evaluation model; Conduct sensitivity analysis on the established evaluation model and quantify the impact of various process parameters on the treatment efficiency index; Integrate the established mud treatment efficiency evaluation model into the operation and management platform of the mud treatment system, call the model to predict the treatment efficiency index in real time, and regularly update the model parameters based on the actual operation data; The form of the mud treatment efficiency evaluation model is specifically expressed as follows: y=f(x;θ)+∈; Where y=[y1,y2,y3] T is the efficiency index vector of the sample data set, x = [v, η, w] T is the characteristic vector of the sample data set, θ is the model parameter, ∈ is the random error term; v represents the processing speed, η represents the solid-liquid separation effect, and w represents the moisture content of the filter cake; specifically, the processing speed v represents the amount of mud processed per unit time, the solid-liquid separation effect η represents the degree of separation between solid matter and liquid, and the moisture content of the filter cake w represents the residual moisture content in the filter cake; The sample data set is represented as: Where N represents the number of sample data sets.

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