Intelligent control method for dewatering of metal surface treatment wastewater sludge

Abstract

The present application belongs to the technical field of artificial intelligence processing of metal surface treatment wastewater pollution, and discloses an intelligent control method for metal surface treatment wastewater sludge dewatering, which comprises the following steps: collecting characteristic data of wastewater sludge in real time; matching parameters in a preset dewatering parameter database to obtain a dewatering control parameter group; performing multi-stage dewatering on a dewatering device during metal surface treatment wastewater to obtain primary dewatering sludge; monitoring the water content in the primary dewatering sludge and the filtrate turbidity during metal surface treatment wastewater to obtain a dewatering effect quantitative value; performing gradient correction on the dewatering control parameter group based on the deviation of the dewatering effect quantitative value and a purification threshold to obtain an optimized dewatering parameter group; and performing deep dewatering on the primary dewatering sludge to obtain recycled water after metal surface treatment wastewater; the present application can improve the efficiency of intelligent control of metal surface treatment wastewater sludge dewatering.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of artificial intelligence processing of metal surface treatment wastewater pollution, and particularly relates to an intelligent control method for dewatering of metal surface treatment wastewater sludge. BACKGROUND

[0002] In the dewatering control of metal surface treatment wastewater sludge, the existing technology is not comprehensive and accurate in the collection and processing of wastewater sludge characteristic data, often only focuses on a single index and ignores the collaborative analysis of solid density and ion conductivity, so that the characteristic data cannot completely reflect the physical and chemical properties of the sludge. Based on this, the matched dewatering control parameter group lacks pertinence and is difficult to adapt to the dewatering needs of different sludge characteristics, affecting the efficiency and effect of primary dewatering.

[0003] At the same time, the existing technology has obvious deficiencies in dewatering effect evaluation and parameter optimization. On the one hand, there is a lack of scientific weighting fusion mechanism for monitoring the moisture content of primary dewatering sludge and the turbidity of filtrate, which cannot quantitatively and comprehensively evaluate the dewatering effect; on the other hand, the parameter correction is mostly empirical adjustment, without gradient and precise correction based on the deviation of dewatering effect and purification threshold, resulting in unreasonable parameter setting in the deep dewatering stage, difficulty in controlling the moisture content of sludge and the turbidity of filtrate in the ideal range, unstable quality of recycled water, and inability to meet the requirements of efficient and high-quality dewatering treatment. SUMMARY

[0004] The application provides an intelligent control method for dewatering of metal surface treatment wastewater sludge to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the application provides an intelligent control method for dewatering of metal surface treatment wastewater sludge, which comprises:

[0006] S1, real-time collection of characteristic data of wastewater sludge in the metal surface;

[0007] S2, parameter matching of a preset dewatering parameter database based on the characteristic data, to obtain a dewatering control parameter group of the wastewater sludge;

[0008] S3, multi-stage dewatering of a dewatering equipment during metal surface treatment wastewater based on the dewatering control parameter group, to obtain primary dewatering sludge of the metal surface;

[0009] S4, monitoring of the moisture content in the primary dewatering sludge and the turbidity of filtrate during metal surface treatment wastewater, to obtain a dewatering effect quantitative value of the primary dewatering sludge;

[0010] S5, gradient correction of the dewatering control parameter group based on the deviation of the dewatering effect quantitative value and a purification threshold, to obtain an optimized dewatering parameter group of the primary dewatering sludge.

[0011] S6、based on the optimization of the dehydration parameter group, the primary dewatering sludge is dewatered, and the reuse water after the metal surface treatment wastewater is obtained.

[0012] In a preferred embodiment, the characteristic data of the wastewater sludge in the metal surface is collected in real time, including:

[0013] The sludge mixture in the metal surface treatment wastewater sedimentation tank is subjected to solid-liquid separation, and the settled sludge and supernatant of the metal surface are obtained;

[0014] The solid phase density of the settled sludge is determined, and the solid phase density of the settled sludge is obtained;

[0015] The ion conductivity of the supernatant is determined, and the ion conductivity of the supernatant is obtained;

[0016] The solid phase density and ion conductivity are combined to obtain the characteristic data of the metal surface.

[0017] In a preferred embodiment, the preset dehydration parameter database is matched based on the characteristic data to obtain the dehydration control parameter group of the wastewater sludge, including:

[0018] The eigenvalue of the characteristic data is separated to obtain the solid phase density value and the ion conductivity value of the characteristic data;

[0019] Based on the dehydration parameter mapping table of the preset dehydration parameter database, the solid phase density value and the ion conductivity value are indexed in horizontal and vertical coordinates to obtain the dehydration control parameter group of the dehydration parameter mapping table.

[0020] In a preferred embodiment, the dehydration control parameter group of the dehydration parameter mapping table is obtained by indexing the solid phase density value and the ion conductivity value based on the dehydration parameter mapping table of the preset dehydration parameter database, including:

[0021] The solid phase density value is subjected to normalization conversion processing to obtain a solid phase density normalized value of the solid phase density value, wherein the calculation formula of the solid phase density normalized value is as follows:

[0022]

[0023] In the formula, The solid phase density normalized value is the solid phase density normalized value, The preset minimum density boundary value is the preset minimum density boundary value, The preset maximum density boundary value is the preset maximum density boundary value, The measured solid phase density value is the measured solid phase density value;

[0024] The ion conductivity value is normalized and converted to obtain a conductivity normalized value of the ion conductivity value, wherein the calculation formula of the conductivity normalized value is as follows:

[0025]

[0026] In the formula, is the conductivity normalized value, is a preset minimum conductivity boundary value, is a preset maximum conductivity boundary value, is a measured ion conductivity value;

[0027] Based on the solid phase density normalized value and the conductivity normalized value, a two-dimensional coordinate matching operation is performed in the dewatering parameter mapping table to obtain a unique corresponding parameter record in the dewatering parameter mapping table.

[0028] The parameter record is directly subjected to parameter matching processing to obtain a dewatering control parameter group of the dewatering parameter mapping table.

[0029] In a preferred embodiment, based on the dewatering control parameter group, a multi-stage dewatering of the metal surface treatment wastewater is performed on the dewatering equipment to obtain primary dewatering sludge of the metal surface, comprising:

[0030] The dewatering control parameter group is subjected to control instruction analysis to obtain a multi-stage control instruction of the dewatering control parameter group;

[0031] Based on the multi-stage control instruction, a multi-stage filtration is performed on the metal surface wastewater sludge until the pressure filtration is completed to obtain a pressure filtration stage completion signal of the dewatering control parameter group;

[0032] The pressure filtration stage completion signal is subjected to effectiveness verification to obtain the primary dewatering sludge of the metal surface.

[0033] In a preferred embodiment, the moisture content in the primary dewatering sludge and the filtrate turbidity during the metal surface treatment wastewater are monitored to obtain a dewatering effect quantitative value of the primary dewatering sludge, comprising:

[0034] The real-time moisture content of the primary dewatering sludge and the real-time turbidity of the filtrate generated during the metal surface treatment wastewater sludge are collected;

[0035] Based on a preset moisture content weight factor and a filtrate turbidity weight factor, the real-time moisture content and the real-time turbidity are subjected to weighted fusion to obtain a dewatering effect comprehensive evaluation value of the primary dewatering sludge;

[0036] The dewatering effect comprehensive evaluation value is subjected to numerical quantification to obtain a dewatering effect quantitative value of the primary dewatering sludge.

[0037] In a preferred embodiment, the step of weighting and fusing the real-time moisture content and the real-time turbidity based on preset moisture content weighting factors and filtrate turbidity weighting factors to obtain a comprehensive evaluation value of the dewatering effect of the primary dewatered sludge includes:

[0038] Call the historical database of the dewatering process for the wastewater sludge from the metal surface treatment;

[0039] Based on the first preset interval to which the real-time moisture content belongs and the second preset interval to which the real-time turbidity belongs, the weighting factors of the historical database are extracted to obtain the moisture content weighting factor of the real-time moisture content and the filtrate turbidity weighting factor of the real-time turbidity.

[0040] The moisture content weighting factor and the filtrate turbidity weighting factor are linearly superimposed to obtain the comprehensive evaluation value of the dehydration effect. The calculation formula for the comprehensive evaluation value of the dehydration effect is as follows:

[0041]

[0042] In the formula, This is a comprehensive evaluation value for the dehydration effect. For the matching moisture content weighting factor, The real-time moisture content, For the matching filtrate turbidity weighting factor, The real-time turbidity is [value].

[0043] In a preferred embodiment, the step of performing gradient correction on the dewatering control parameter set based on the deviation between the quantified dewatering effect value and the purification threshold to obtain the optimized dewatering parameter set for the primary dewatered sludge includes:

[0044] Calculate the deviation between the quantitative value of the dehydration effect and the preset purification threshold;

[0045] Based on the preset deviation range of the deviation value, the parameter gradient correction is performed on the dewatering parameter correction increment library of the primary dewatered sludge to obtain the parameter correction increment value of the dewatering control parameter group.

[0046] The parameter correction increment value is superimposed on the parameters in the dewatering control parameter group to generate the optimized dewatering parameter group for the primary dewatered sludge.

[0047] In a preferred embodiment, calculating the deviation between the quantified value of the dehydration effect and a preset purification threshold includes:

[0048] Obtain the quantitative value of the dehydration effect and the purification threshold;

[0049] The deviation rate between the quantified value of the dehydration effect and the purification threshold is calculated to obtain the deviation value of the quantified value of the dehydration effect. The formula for calculating the deviation value is as follows:

[0050]

[0051] In the formula, The deviation value is... This is a quantitative value for the dehydration effect. The preset purification threshold is used.

[0052] In a preferred embodiment, the step of performing deep dewatering on the primary dewatered sludge based on the optimized dewatering parameter set to obtain reclaimed water after the metal surface treatment wastewater includes:

[0053] Analyze the parameters of the deep dehydration stage in the optimized dehydration parameter set;

[0054] Based on the deep dewatering stage parameters, the preset metal surface treatment sludge dewatering process instruction library is matched with the instructions to obtain the deep dewatering operation instruction sequence of the metal surface.

[0055] The primary dewatered sludge is subjected to staged deep dewatering according to the deep dewatering operation instruction sequence to obtain the recycled water after the metal surface treatment wastewater.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] 1. This invention collects and combines the solid density and ionic conductivity of wastewater sludge in real time to form comprehensive characteristic data. Based on a preset dewatering parameter database, it performs precise two-dimensional coordinate matching to obtain a targeted set of dewatering control parameters. Combined with multi-stage dewatering operations, it can fully adapt to the physicochemical properties of sludge, significantly improve the efficiency and stability of primary dewatering, and lay a reliable foundation for subsequent treatment.

[0058] 2. This invention monitors the moisture content and turbidity of the primary dewatered sludge and obtains a quantitative value of the dewatering effect through weighted fusion. Based on the deviation of this value from the purification threshold, a gradient correction is performed to generate an optimized dewatering parameter set for deep dewatering. This allows for precise control of the dewatering process, ensuring that the quality of reclaimed water meets standards. It not only improves the accuracy of dewatering treatment but also enhances the adaptability and reliability of the entire process, providing strong support for the efficient treatment of wastewater sludge from metal surface treatment. Attached Figure Description

[0059] Figure 1 This is a schematic flowchart of an intelligent control method for dewatering sludge from metal surface treatment wastewater, provided in an embodiment of the present invention.

[0060] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0061] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0062] This application provides an intelligent control method for dewatering sludge from metal surface treatment wastewater. The executing entity of this intelligent control method for dewatering sludge from metal surface treatment wastewater includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the intelligent control method for dewatering sludge from metal surface treatment wastewater can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0063] Reference Figure 1 The diagram shown is a flowchart illustrating an intelligent control method for dewatering sludge from metal surface treatment wastewater, according to an embodiment of the present invention. In this embodiment, the intelligent control method for dewatering sludge from metal surface treatment wastewater includes:

[0064] S1. Real-time acquisition of characteristic data of wastewater and sludge on metal surfaces;

[0065] In this embodiment of the invention, the real-time acquisition of characteristic data of wastewater sludge on the metal surface includes:

[0066] Solid-liquid separation is performed on the sludge mixture in the sedimentation tank of metal surface treatment wastewater to obtain settled sludge and supernatant from the metal surface.

[0067] The solid density of the settled sludge was determined by measuring its solid density.

[0068] The ionic conductivity of the supernatant was measured to obtain the ionic conductivity of the supernatant.

[0069] The solid density and ionic conductivity data are combined to obtain the characteristic data of the metal surface.

[0070] Specifically, a certain amount of sludge mixture is taken from the sedimentation tank of metal surface treatment wastewater and transferred to a centrifuge tube. The mixture is then centrifuged using a centrifuge. The centrifugal force causes the solid particles in the mixture to settle to the bottom of the centrifuge tube, while the liquid remains in the upper layer. After centrifugation, the settled sludge in the lower layer and the supernatant in the upper layer are separated.

[0071] Further, take an appropriate amount of settled sludge and place it in a funnel lined with quantitative filter paper. Slowly rinse the settled sludge with distilled water to remove impurities attached to the surface. Then, put the filter paper with settled sludge into an oven and dry it at a fixed temperature until constant weight. After taking it out, weigh the mass of the dried settled sludge using a balance. At the same time, use a specific gravity bottle of known volume to first weigh the mass of the empty specific gravity bottle.

[0072] Further, the dried settled sludge is placed into a specific gravity bottle, distilled water is added to the mark, the total mass is weighed, the volume of the settled sludge is calculated, and finally the solid density of the settled sludge is obtained by dividing the mass of the dried settled sludge by its volume.

[0073] Next, take an appropriate amount of supernatant and pour it into a clean, dry measuring cup, ensuring that there are no impurities remaining in the measuring cup. Clean and dry the electrodes of the conductivity meter, and slowly insert them into the supernatant, ensuring that the electrodes are completely immersed in the liquid and do not touch the inner wall of the measuring cup. Turn on the conductivity meter, and after the value on the instrument display screen stabilizes, read and record the value. This value is the ionic conductivity of the supernatant.

[0074] Furthermore, the measured solid density of the settled sludge and the ionic conductivity of the supernatant are entered into the same data record table, so that the two values ​​correspond one-to-one to form a set of related data. This set of related data, which includes solid density and ionic conductivity, is the characteristic data of the metal surface.

[0075] In summary, solid-liquid separation of sludge mixture in the sedimentation tank of metal surface treatment wastewater can accurately separate solid and liquid components, providing independent samples for subsequent separate measurements, ensuring that the index measurements are not disturbed and guaranteeing the accuracy of characteristic data.

[0076] In summary, the solid density obtained by measuring the solid density of settled sludge can reflect the state of sludge solid particles, correlate with the difficulty of dewatering and the treatment method, and provide a physical characteristic basis for matching appropriate dewatering parameters.

[0077] In summary, the ionic conductivity of the supernatant can reflect the content of soluble ions in the liquid, the chemical characteristics of the reaction, and its influence on dehydration and filtration performance and the difficulty of filtrate treatment. It is an important reference for determining process parameters.

[0078] In summary, combining solid density and ionic conductivity data to obtain characteristic data can comprehensively reflect the sludge condition by integrating physical and chemical properties, avoiding misjudgment based on a single indicator, making the matched dewatering control parameter set more targeted, and improving the efficiency and effect of primary dewatering.

[0079] S2. Based on the characteristic data, perform parameter matching on the preset dewatering parameter database to obtain the dewatering control parameter set for the wastewater sludge;

[0080] In this embodiment of the invention, the step of matching parameters to a preset dewatering parameter database based on the characteristic data to obtain the dewatering control parameter set for the wastewater sludge includes:

[0081] The characteristic data is subjected to eigenvalue separation to obtain the solid density value and ionic conductivity value of the characteristic data;

[0082] Based on the dehydration parameter mapping table of the preset dehydration parameter database, the solid density value and the ionic conductivity value are indexed by horizontal and vertical axes to obtain the dehydration control parameter group of the dehydration parameter mapping table.

[0083] The dehydration parameter mapping table based on the preset dehydration parameter database indexes the solid density value and the ionic conductivity value using horizontal and vertical axes to obtain the dehydration control parameter group of the dehydration parameter mapping table, including:

[0084] The solid density value is normalized to obtain the normalized solid density value, wherein the formula for calculating the normalized solid density value is as follows:

[0085]

[0086] In the formula, This is the normalized value of the solid density. To preset the minimum density boundary value, To preset the maximum density boundary value, This is the measured solid density value;

[0087] The ionic conductivity value is normalized to obtain a normalized conductivity value, wherein the formula for calculating the normalized conductivity value is as follows:

[0088]

[0089] In the formula, This is the normalized value of conductivity. To preset the minimum conductivity boundary value, To preset the maximum conductivity boundary value, This is the measured ionic conductivity value;

[0090] Based on the normalized values ​​of solid density and conductivity, a two-dimensional coordinate matching operation is performed in the dehydration parameter mapping table to obtain the unique corresponding parameter record in the dehydration parameter mapping table.

[0091] The parameter records are directly matched to obtain the dehydration control parameter group of the dehydration parameter mapping table.

[0092] Specifically, from the acquired characteristic data of the metal surface, the solid density value of the settled sludge and the ionic conductivity value of the supernatant are extracted.

[0093] Furthermore, these two values ​​are stored separately in different data fields of the data processing system. One field is dedicated to storing the solid density value, and the other field is dedicated to storing the ionic conductivity value. This completes the eigenvalue separation of the characteristic data, and yields the solid density value and ionic conductivity value of the characteristic data.

[0094] Furthermore, open the preset dehydration parameter database and retrieve the dehydration parameter mapping table. The horizontal axis of the mapping table is marked with different solid density values, and the vertical axis is marked with different ionic conductivity values. Each intersection of the horizontal and vertical axes corresponds to a set of dehydration control parameters.

[0095] Furthermore, find the coordinate point on the horizontal axis that perfectly matches the obtained solid density value, and find the coordinate point on the vertical axis that perfectly matches the obtained ionic conductivity value. Determine the intersection of these two coordinate points in the mapping table. The set of parameters recorded at this intersection is the dewatering control parameter set for wastewater sludge obtained from the dewatering parameter mapping table.

[0096] Specifically, the standard range of solid density values ​​is retrieved from the preset dehydration parameter database. This range includes the minimum and maximum possible values ​​of solid density. The minimum value of this range is subtracted from the actual measured solid density value to obtain the difference between the two. This difference is then divided by the difference between the maximum and minimum values ​​of this range. Through this calculation, a value between the minimum and maximum normalized values ​​is obtained. This value is the solid density normalized value.

[0097] Furthermore, the standard range of ionic conductivity values ​​is retrieved from the preset dehydration parameter database. This range includes the minimum and maximum possible values ​​of ionic conductivity. The minimum value of this range is subtracted from the actual measured ionic conductivity value to obtain the difference between the two.

[0098] Furthermore, divide this difference by the difference between the maximum and minimum values ​​within that range. Through this calculation, a value between the minimum and maximum normalized values ​​is obtained. This value is the conductivity normalized value of the ionic conductivity.

[0099] Furthermore, open the dehydration parameter mapping table in the preset dehydration parameter database. The horizontal axis of the mapping table represents the normalized value of solid density, with the scale distributed sequentially from the minimum normalized value to the maximum normalized value. The vertical axis represents the normalized value of conductivity, with the scale also distributed sequentially from the minimum normalized value to the maximum normalized value. Each intersection of the horizontal and vertical axes corresponds to a unique parameter record.

[0100] Furthermore, find the scale point on the horizontal axis that corresponds exactly to the normalized value of the solid density, and find the scale point on the vertical axis that corresponds exactly to the normalized value of the conductivity. The parameter record corresponding to the intersection of these two scale points is the parameter record that is uniquely matched in the dehydration parameter mapping table.

[0101] Further, examine the unique corresponding parameter record found. This record contains all the specific parameters required to complete wastewater sludge dewatering. Extract these parameters directly and combine them in a preset order to form a complete set of parameters. This set of parameters is the dewatering control parameter group of the dewatering parameter mapping table.

[0102] Specifically, That is, the normalized solid density value is a result obtained through calculation, and its value comes from the calculation of the measured solid density value, the preset minimum density boundary value, and the preset maximum density boundary value. That is, the measured solid density value is derived from the value obtained by measuring the solid density of the settled sludge in the sedimentation tank of metal surface treatment wastewater. That is, the preset minimum density boundary value is derived from the minimum possible solid density stored in the preset dehydration parameter database; The preset maximum density boundary value is derived from the maximum possible solid density stored in the preset dehydration parameter database.

[0103] Furthermore, the significance of this formula is to convert the measured solid density value into a value within a normalized range corresponding to the preset minimum density boundary value and the preset maximum density boundary value. Through this conversion, the influence of measured solid density values ​​of different magnitudes on subsequent parameter matching can be eliminated, so that measured solid density values ​​of different sizes can correspond to the horizontal coordinate axis in the dehydration parameter mapping table under a unified normalized scale, providing a unified standard numerical basis for accurate coordinate matching in the dehydration parameter mapping table.

[0104] Furthermore, when the measured solid density value is equal to the preset minimum density boundary value, the calculated normalized solid density value is the minimum value within the normalization range; when the measured solid density value is equal to the preset maximum density boundary value, the calculated normalized solid density value is the maximum value within the normalization range; when the measured solid density value gradually increases between the preset minimum density boundary value and the preset maximum density boundary value, the normalized solid density value will also gradually increase from the minimum value to the maximum value within the normalization range, that is, the larger the measured solid density value, the larger the normalized solid density value, and the two show a synchronous trend.

[0105] Specifically, That is, the conductivity normalization value is the result obtained by calculation. Its value comes from the calculation of the measured ionic conductivity value, the preset minimum conductivity boundary value, and the preset maximum conductivity boundary value. That is, the measured ionic conductivity value is obtained by measuring the ionic conductivity of the supernatant in the sedimentation tank of metal surface treatment wastewater; That is, the preset minimum conductivity boundary value is derived from the minimum possible ionic conductivity value stored in the preset dehydration parameter database; The preset maximum conductivity boundary value is derived from the maximum possible ionic conductivity value stored in the preset dehydration parameter database.

[0106] Furthermore, the significance of this formula is to convert the measured ionic conductivity value into a value within a normalized range corresponding to the preset minimum conductivity boundary value and the preset maximum conductivity boundary value. Through this conversion, the influence of measured ionic conductivity values ​​of different magnitudes on subsequent parameter matching can be eliminated, so that measured ionic conductivity values ​​of different sizes can correspond to the vertical coordinate axis in the dehydration parameter mapping table under a unified normalized scale, providing a unified standard numerical basis for accurate coordinate matching in the dehydration parameter mapping table.

[0107] Furthermore, when the measured ionic conductivity value equals the preset minimum conductivity boundary value, the calculated conductivity normalized value is the minimum value within the normalization range; when the measured ionic conductivity value equals the preset maximum conductivity boundary value, the calculated conductivity normalized value is the maximum value within the normalization range; as the measured ionic conductivity value gradually increases between the preset minimum conductivity boundary value and the preset maximum conductivity boundary value, the conductivity normalized value will also gradually increase from the minimum to the maximum value within the normalization range, that is, the larger the measured ionic conductivity value, the larger the conductivity normalized value, and the two show a synchronous trend.

[0108] In summary, by separating eigenvalues ​​from characteristic data to obtain solid density and ionic conductivity values, key indicators reflecting the physical and chemical properties of sludge can be accurately extracted, enabling subsequent parameter matching to focus on core indicators and avoid irrelevant interference.

[0109] In summary, based on the dewatering parameter mapping table of the preset dewatering parameter database, the solid density value and ionic conductivity value are indexed by horizontal and vertical axes to obtain the dewatering control parameter set. The mapping table can accurately associate the two core indicators with the dewatering parameters, making the parameter set suitable for sludge characteristics, improving the matching targeting and accuracy, providing a scientific basis for multi-stage dewatering, and ensuring the efficiency and stability of primary dewatering.

[0110] In summary, normalizing the solid density value to obtain the normalized solid density value can unify the scale of the measured value, eliminate the influence of magnitude, and provide a consistent benchmark for coordinate matching.

[0111] In summary, normalizing the ionic conductivity values ​​to obtain normalized conductivity values ​​can unify the scale of their measured values, avoid matching biases, and ensure consistent reference with the normalized solid density values.

[0112] In summary, a unique parameter record is obtained by matching two-dimensional coordinates based on two normalized values. This allows for precise positioning by combining the physical and chemical properties of sludge, ensuring that the parameter record closely matches reality.

[0113] In summary, directly matching the recorded parameters to obtain the dewatering control parameter set can transform precision into targeted control parameters, adapt to differences in sludge characteristics, improve primary dewatering efficiency and stability, and solve the problem of parameters lacking specificity.

[0114] S3. Based on the dewatering control parameter group, the dewatering equipment for metal surface treatment wastewater is subjected to multi-stage dewatering to obtain primary dewatered sludge from the metal surface.

[0115] In this embodiment of the invention, the multi-stage dewatering of the dewatering equipment for metal surface treatment wastewater based on the dewatering control parameter set to obtain primary dewatered sludge from the metal surface includes:

[0116] The dehydration control parameter group is parsed to obtain multi-level control commands for the dehydration control parameter group;

[0117] Based on the multi-level control commands, the wastewater sludge on the metal surface is filtered in multiple stages until the pressure filtration is completed, and the pressure filtration stage completion signal of the dewatering control parameter group is obtained.

[0118] The effectiveness of the filter press completion signal is verified to obtain the primary dewatered sludge on the metal surface.

[0119] Specifically, the dehydration control parameter set is input into the control system of the dehydration equipment. The control system converts the dehydration operation requirements at each level contained in the parameter set into operation instructions that the equipment can recognize, according to the preset instruction conversion rules. These instructions correspond to each level of operation in the multi-stage dehydration process, and finally form a multi-stage control instruction arranged in sequence.

[0120] Furthermore, the wastewater sludge from the metal surface is transported to the initial filtration device of the dewatering equipment. According to the first-level instruction in the multi-level control command, the device is started and adjusted to the operating state required by the instruction to perform the first-level filtration of the wastewater sludge. After the first-level filtration is completed, the treated sludge is transported to the next-level filtration device and operated according to the second-level instruction.

[0121] Furthermore, this process continues until the final stage of filtration is completed; when the final stage of filtration is finished, the monitoring device of the dewatering equipment will automatically send a signal indicating that the filtration stage is complete.

[0122] Furthermore, the completion signal of the filter press stage is checked to confirm that the dewatering equipment has stopped all filter press operations. At the same time, it is checked that the filter press time recorded by the equipment has reached the total time set in the multi-level control command, and the sludge state at the outlet of the last stage filter device meets the basic requirements of primary dewatering. At this time, the signal is determined to be valid.

[0123] Furthermore, after the signal verification is valid, the sludge that has undergone multi-stage pressure filtration is taken out from the last stage filtration device. This sludge is the primary dewatered sludge on the metal surface.

[0124] In summary, by parsing the control commands of the dehydration control parameter set to obtain multi-level control commands, the parameter set can be converted into operation commands that the equipment can recognize, so that each action has a basis, ensuring that multi-level dehydration is carried out in an orderly manner and avoiding chaos.

[0125] In summary, multi-stage filtration based on multi-level control commands, from filtration to pressure filtration completion and obtaining a completion signal, can improve the dewatering gradient effect and reduce the moisture content through step-by-step filtration. The signal clearly indicates the endpoint, ensuring the integrity of the process.

[0126] In summary, validating the filter press completion signal yields primary dewatered sludge, confirming that the dewatering effect meets standards, preventing substandard sludge from entering subsequent stages, ensuring stable quality, and laying the foundation for deep dewatering.

[0127] S4. Monitor the moisture content in the primary dewatered sludge and the turbidity of the filtrate from the metal surface treatment wastewater to obtain a quantitative value of the dewatering effect of the primary dewatered sludge.

[0128] In this embodiment of the invention, the step of monitoring the moisture content in the primary dewatered sludge and the turbidity of the filtrate from the metal surface treatment wastewater to obtain a quantitative value of the dewatering effect of the primary dewatered sludge includes:

[0129] The real-time moisture content of the primary dewatered sludge and the real-time turbidity of the filtrate generated during the metal surface treatment wastewater sludge collection were collected.

[0130] Based on the preset moisture content weighting factor and filtrate turbidity weighting factor, the real-time moisture content and the real-time turbidity are weighted and fused to obtain the comprehensive evaluation value of the dewatering effect of the primary dewatered sludge.

[0131] The comprehensive evaluation value of the dewatering effect is numerically quantified to obtain the quantitative value of the dewatering effect of the primary dewatered sludge.

[0132] The real-time moisture content and real-time turbidity are weighted and fused based on preset moisture content weighting factors and filtrate turbidity weighting factors to obtain a comprehensive evaluation value of the dewatering effect of the primary dewatered sludge, including:

[0133] Call the historical database of the dewatering process for the wastewater sludge from the metal surface treatment;

[0134] Based on the first preset interval to which the real-time moisture content belongs and the second preset interval to which the real-time turbidity data belongs, the weighting factors of the historical database are extracted to obtain the moisture content weighting factor of the real-time moisture content and the filtrate turbidity weighting factor of the real-time turbidity.

[0135] The moisture content weighting factor and the filtrate turbidity weighting factor are linearly superimposed to obtain the comprehensive evaluation value of the dehydration effect. The calculation formula for the comprehensive evaluation value of the dehydration effect is as follows:

[0136]

[0137] In the formula, This is a comprehensive evaluation value for the dehydration effect. For the matching moisture content weighting factor, The real-time moisture content, For the matching filtrate turbidity weighting factor, The real-time turbidity is [value].

[0138] Specifically, take an appropriate amount of sample from the primary dewatered sludge, place it in the sample tray of the moisture analyzer, close the instrument door, start the instrument for testing. The instrument removes the moisture from the sludge by heating and drying. After the test is completed, directly read the moisture content of the primary dewatered sludge displayed by the instrument, which is the real-time moisture content.

[0139] Furthermore, at the same time, collect the filtrate generated during the wastewater sludge treatment of metal surfaces, pour the filtrate into the cuvette of the turbidimeter, ensure that the liquid is free of air bubbles and fills the cuvette, place the cuvette into the detection chamber of the turbidimeter, close the lid, start the turbidimeter to perform the test, and after the value stabilizes, read and record the turbidity of the filtrate displayed by the instrument, which is the real-time turbidity.

[0140] Furthermore, the moisture content weighting factor and filtrate turbidity weighting factor are retrieved from the preset parameter storage module. The moisture content weighting factor is used to reflect the importance of real-time moisture content in the evaluation of dehydration effect, and the filtrate turbidity weighting factor is used to reflect the importance of real-time turbidity in the evaluation of dehydration effect.

[0141] Furthermore, the real-time moisture content is multiplied by the moisture content weighting factor to obtain the moisture content weighted value, and the real-time turbidity is multiplied by the filtrate turbidity weighting factor to obtain the turbidity weighted value. The moisture content weighted value and the turbidity weighted value are then added together to obtain the comprehensive evaluation value of the dewatering effect of the primary dewatered sludge.

[0142] Furthermore, the comprehensive evaluation value of the dewatering effect is input into the quantitative processing system. The system maps the comprehensive evaluation value to a specific numerical level according to the preset grading standard. Each level corresponds to a fixed quantitative value. For example, when the comprehensive evaluation value is in a certain range, the system automatically converts it into the quantitative value corresponding to that range. Through this conversion, the specific value obtained is the quantitative value of the dewatering effect of the primary dewatered sludge.

[0143] Specifically, by entering "metal surface treatment wastewater sludge dewatering process" as a search keyword through the query interface of the data management system, the system performs precise matching in various stored databases based on the keyword. After finding the corresponding historical database, it retrieves all the contents of that database to the current data processing interface, thus completing the call to the historical database.

[0144] Furthermore, in the historical database, multiple first preset intervals of moisture content and the corresponding moisture content weight factor for each interval are pre-stored, as well as multiple second preset intervals of turbidity and the corresponding filtrate turbidity weight factor for each interval.

[0145] Furthermore, the real-time moisture content is compared one by one with the range of the first preset interval to determine the first preset interval into which it completely falls, and the weight factor corresponding to the interval is extracted as the moisture content weight factor of the real-time moisture content.

[0146] Furthermore, in the same manner, the real-time turbidity is compared one by one with the range of the second preset interval to determine the second preset interval into which it completely falls, and the weight factor corresponding to the interval is extracted as the filtrate turbidity weight factor of the real-time turbidity.

[0147] Furthermore, the obtained values ​​of moisture content weighting factor and filtrate turbidity weighting factor are added together, that is, the values ​​of moisture content weighting factor and filtrate turbidity weighting factor are combined into a sum, which is the comprehensive evaluation value of the dewatering effect of primary dewatered sludge.

[0148] Specifically, The comprehensive evaluation value of dehydration effect is a result obtained through calculation. Its value comes from the calculation of the matched moisture content weighting factor, real-time moisture content, matched filtrate turbidity weighting factor, and real-time turbidity. The matching moisture content weighting factor is derived from the historical database of metal surface treatment wastewater sludge dewatering process, and is extracted based on the first preset interval to which the real-time moisture content belongs. The real-time moisture content is derived from data obtained by testing the primary dewatered sludge using a moisture analyzer. The matching filtrate turbidity weighting factor is derived from the historical database of metal surface treatment wastewater sludge dewatering process, based on the weighting factor extracted from the second preset interval to which the real-time turbidity belongs. Real-time turbidity is data obtained by detecting the filtrate produced during the treatment of sludge in wastewater from metal surface treatment using a turbidity meter.

[0149] Furthermore, the significance of this formula is that it combines real-time moisture content and real-time turbidity with their respective matching weighting factors, and then merges the two combined results to form a value that can comprehensively reflect the dewatering effect of primary dewatering sludge. Through this calculation, both the moisture content in the sludge and the turbidity of the filtrate are taken into account, thereby comprehensively evaluating the dewatering effect and providing a basis for subsequent judgment on whether the dewatering meets the standards.

[0150] Furthermore, when the real-time moisture content increases, while the matched moisture content weighting factor, the matched filtrate turbidity weighting factor, and the real-time turbidity remain unchanged, the comprehensive evaluation value of the dewatering effect will increase accordingly. Similarly, when the real-time turbidity increases, while the matched moisture content weighting factor, the matched filtrate turbidity weighting factor, and the real-time moisture content remain unchanged, the comprehensive evaluation value of the dewatering effect will also increase accordingly. Conversely, when the real-time moisture content or real-time turbidity decreases, the comprehensive evaluation value of the dewatering effect will decrease accordingly, assuming other factors remain unchanged. In other words, the real-time moisture content and real-time turbidity show a synchronous trend with the comprehensive evaluation value of the dewatering effect.

[0151] In summary, collecting real-time moisture content of primary dewatered sludge and real-time turbidity of filtrate can capture the dewatering effect from two dimensions, comprehensively reflecting the actual situation and avoiding the limitations of a single indicator.

[0152] In summary, the comprehensive evaluation value of dehydration effect obtained by weighting and integrating the two indicators based on preset weighting factors can reflect the different importance of the two indicators, make the evaluation fit the process requirements, and overcome the bias of simple superposition.

[0153] In summary, quantifying the comprehensive evaluation value to obtain a quantitative value of the dehydration effect can transform the abstract evaluation into a specific numerical value, providing an intuitive basis for comparing with the purification threshold and judging the compliance status, facilitating the analysis of the degree of deviation, and laying the foundation for parameter correction.

[0154] In summary, accessing the historical database of sludge dewatering processes for metal surface treatment wastewater can provide practical process data support for the selection of weighting factors, avoiding unreasonable subjective settings and improving applicability.

[0155] In summary, extracting weighting factors based on the preset intervals of real-time moisture content and turbidity enables the weights to accurately correspond to the data range, match the actual degree of influence, and enhance the pertinence and scientific nature of the allocation.

[0156] In summary, the comprehensive evaluation value of dehydration effect obtained by linearly superimposing the two weighting factors can be used to integrate the two indicators according to their weights, taking into account the influence of both and reflecting the difference in importance, so as to comprehensively and accurately reflect the primary dehydration effect and provide a reliable basis for subsequent quantification.

[0157] S5. Based on the deviation between the quantified value of the dewatering effect and the purification threshold, the dewatering control parameter set is gradient-corrected to obtain the optimized dewatering parameter set for the primary dewatered sludge.

[0158] In this embodiment of the invention, the step of performing gradient correction on the dewatering control parameter set based on the deviation between the quantified value of the dewatering effect and the purification threshold to obtain the optimized dewatering parameter set for the primary dewatered sludge includes:

[0159] Calculate the deviation between the quantitative value of the dehydration effect and the preset purification threshold;

[0160] Based on the preset deviation range of the deviation value, the parameter gradient correction is performed on the dewatering parameter correction increment library of the primary dewatered sludge to obtain the parameter correction increment value of the dewatering control parameter group.

[0161] The parameter correction increment value is superimposed on the parameters in the dewatering control parameter group to generate the optimized dewatering parameter group for the primary dewatered sludge.

[0162] The calculation of the deviation between the quantitative value of the dehydration effect and the preset purification threshold includes:

[0163] Obtain the quantitative value of the dehydration effect and the purification threshold;

[0164] The deviation rate between the quantified value of the dehydration effect and the purification threshold is calculated to obtain the deviation value of the quantified value of the dehydration effect. The formula for calculating the deviation value is as follows:

[0165]

[0166] In the formula, The deviation value is... This is a quantitative value for the dehydration effect. The preset purification threshold is used.

[0167] Specifically, the quantitative value of the dewatering effect of the primary dewatered sludge is retrieved, and the purification threshold is retrieved from the preset standard database. The quantitative value of the dewatering effect is subtracted from the purification threshold, and the result is the deviation value between the quantitative value of the dewatering effect and the preset purification threshold.

[0168] Furthermore, the preset deviation interval is a set of consecutive deviation ranges that are pre-divided. Each range corresponds to a set of parameter correction increment values ​​in the dewatering parameter correction increment library of primary dewatered sludge. The calculated deviation value is compared with the range of each preset deviation interval one by one to determine which preset deviation interval is completely included in the deviation value.

[0169] Furthermore, the parameter correction increment value corresponding to this interval is then extracted from the dehydration parameter correction increment library. This value is the parameter correction increment value of the dehydration control parameter group.

[0170] Furthermore, the parameter correction increment value is merged with each parameter in the dewatering control parameter group in a one-to-one correspondence relationship, that is, each parameter is added with its corresponding parameter correction increment value. The new parameter group formed after such merging operation is the optimized dewatering parameter group for primary dewatered sludge.

[0171] Specifically, the dewatering effect quantification value of the primary dewatered sludge obtained earlier is retrieved from the data storage module, and the preset purification threshold is retrieved from the preset standard parameter library. These two values ​​are stored in the same data processing interface to complete the acquisition of the dewatering effect quantification value and the purification threshold.

[0172] Furthermore, the purification threshold is subtracted from the quantified value of the dehydration effect to obtain the difference between the two. This difference is then divided by the purification threshold. Through this calculation, a value reflecting the degree of deviation of the quantified value of the dehydration effect from the purification threshold is obtained. This value is the deviation value of the quantified value of the dehydration effect.

[0173] Specifically, The deviation value is a result obtained through calculation, and its value comes from the calculation of the quantified value of dehydration effect and the preset purification threshold. The quantitative value of dewatering effect is derived from the numerical quantification of the comprehensive evaluation value of the dewatering effect of primary dewatered sludge. The preset purification threshold is derived from the benchmark values ​​stored in the preset standard parameter library used to determine whether the dehydration effect meets the standard.

[0174] Furthermore, the significance of this formula lies in calculating the difference between the quantitative value of the dehydration effect and the preset purification threshold, and then comparing this difference with the preset purification threshold to obtain a value presented as a percentage. This intuitively reflects the degree of deviation of the quantitative value of the dehydration effect from the preset purification threshold, providing a clear basis for subsequent gradient correction of the dehydration control parameter group based on the degree of deviation.

[0175] Furthermore, when the quantified value of the dehydration effect is greater than the preset purification threshold, the deviation value is positive, and the larger the quantified value of the dehydration effect, the larger the positive value of the deviation value; when the quantified value of the dehydration effect is less than the preset purification threshold, the deviation value is negative, and the smaller the quantified value of the dehydration effect, the smaller the negative value of the deviation value; when the quantified value of the dehydration effect is equal to the preset purification threshold, the deviation value is zero, that is, the degree of deviation between the quantified value of the dehydration effect and the preset purification threshold changes synchronously with the difference between the two.

[0176] In summary, calculating the deviation between the quantitative value of the dehydration effect and the preset purification threshold can accurately quantify the degree of deviation between the dehydration effect and the standard, providing a clear basis for subsequent parameter correction and avoiding the blindness of adjusting based on experience.

[0177] In summary, by extracting parameter correction increment values ​​from the dehydration parameter correction increment library based on the preset deviation range to which the deviation value belongs, the correction amount can be matched with the degree of deviation, achieving gradient precision correction, ensuring that the corrected parameters are more in line with actual dehydration needs, and overcoming the instability that may be caused by a one-time large adjustment.

[0178] In summary, by superimposing the parameter correction increments onto the dehydration control parameter set to generate an optimized dehydration parameter set, targeted adjustments can be made based on the original parameters. This allows the parameter set to adapt to the deviations in the current dehydration effect, improving the adaptability and accuracy of the parameters. It provides optimized operational guidelines for deep dehydration and ensures that the quality of recycled water consistently meets standards.

[0179] In summary, obtaining quantitative values ​​of dehydration effect and purification thresholds are two key values ​​that can be clearly compared, providing a basis for subsequent deviation calculations and ensuring the accuracy of the calculation objects.

[0180] In summary, the deviation value is obtained by calculating the deviation rate between the quantitative value of dehydration effect and the purification threshold. This deviation value can be intuitively reflected as a percentage, making the deviation easier to understand and judge, and avoiding the problem that the relative deviation cannot be reflected by the difference alone.

[0181] In summary, this calculation method can accurately quantify the gap between the dehydration effect and the standard, providing a clear and quantifiable basis for gradient correction based on the degree of deviation, ensuring the pertinence and accuracy of subsequent parameter correction, and helping to bring the dehydration effect closer to the purification threshold through correction, thereby improving the quality control capability of deep dehydration.

[0182] S6. Based on the optimized dewatering parameter set, the primary dewatered sludge is subjected to deep dewatering to obtain the recycled water after the metal surface treatment wastewater.

[0183] In this embodiment of the invention, the step of performing deep dewatering on the primary dewatered sludge based on the optimized dewatering parameter set to obtain reclaimed water after the metal surface treatment wastewater includes:

[0184] Analyze the parameters of the deep dehydration stage in the optimized dehydration parameter set;

[0185] Based on the deep dewatering stage parameters, the preset metal surface treatment sludge dewatering process instruction library is matched with the instructions to obtain the deep dewatering operation instruction sequence of the metal surface.

[0186] The primary dewatered sludge is subjected to staged deep dewatering according to the deep dewatering operation instruction sequence to obtain the recycled water after the metal surface treatment wastewater.

[0187] Specifically, the optimized dehydration parameter set is input into the parameter parsing system. The system extracts various parameters specifically for the deep dehydration stage from the optimized dehydration parameter set according to the preset parameter classification rules. These parameters cover the specific requirements such as pressure, time, and temperature required in the deep dehydration process. Through this extraction operation, the deep dehydration stage parameters in the optimized dehydration parameter set are obtained.

[0188] Furthermore, the preset metal surface treatment sludge dewatering process instruction library is opened. This instruction library stores multiple sets of operation instructions corresponding to parameters of different depth dewatering stages. Each set of instructions specifies in detail the equipment start-up sequence, operating status and switching method during the deep dewatering process.

[0189] Furthermore, the obtained deep dehydration stage parameters are compared one by one with the parameters in the instruction library to find the set of operation instructions that match the parameters perfectly. The sequence formed by arranging these instructions in chronological order is the deep dehydration operation instruction sequence for the metal surface.

[0190] Further, the primary dewatered sludge is transported to the feed inlet of the deep dewatering equipment. Following the first instruction in the deep dewatering operation instruction sequence, the pretreatment device of the equipment is started to pre-condition the primary dewatered sludge.

[0191] Furthermore, after pretreatment, the main dewatering device is started according to the second instruction, and dewatering is performed according to the pressure and time required by the instruction. After the main dewatering is completed, the filtration and purification device is started according to subsequent instructions to purify the generated liquid. When all instructions are executed, the liquid collected from the outlet of the purification device is the recycled water after metal surface treatment wastewater.

[0192] In summary, by analyzing and optimizing the parameters of the deep dehydration stage in the dehydration parameter set, key parameters specifically for deep dehydration can be accurately extracted, process requirements can be clarified, precise basis can be provided for instruction matching, and operations can be clearly directed.

[0193] In summary, by matching the parameters of the deep dehydration stage with the preset process instruction library to obtain the deep dehydration operation instruction sequence, the parameters and operation instructions can be accurately matched, ensuring the relevance and applicability of the instructions and avoiding operational deviations.

[0194] In summary, by performing deep dewatering in stages according to the instruction sequence to obtain reclaimed water, the dewatering effect can be gradually improved. Strict process control can ensure that the quality of reclaimed water meets the standards, thereby achieving efficient treatment of wastewater and sludge and effective recycling of water resources.

[0195] In the several embodiments provided by this invention, it should be understood that the disclosed method can be implemented in other ways.

[0196] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0197] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, and technology that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0198] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent control method for dewatering sludge from metal surface treatment wastewater, characterized in that, The method includes: S1. Real-time acquisition of characteristic data of wastewater sludge from metal surface treatment, including: Solid-liquid separation is performed on the sludge mixture in the sedimentation tank of metal surface treatment wastewater to obtain settled sludge and supernatant of the metal surface treatment wastewater sludge; The solid density of the settled sludge was determined by measuring its solid density. The ionic conductivity of the supernatant was measured to obtain the ionic conductivity of the supernatant. By combining the data of the solid density and ionic conductivity, the characteristic data of the metal surface treatment wastewater sludge are obtained. S2. Place the characteristic data in a preset dewatering parameter database for parameter matching to obtain the dewatering control parameter set for the wastewater sludge; S3. Based on the dewatering control parameter set, the metal surface treatment wastewater sludge is dewatered in multiple stages to obtain the primary dewatered sludge of the metal surface treatment wastewater sludge. S4. Monitor the moisture content in the primary dewatered sludge and the turbidity of the filtrate during the dewatering of the metal surface treatment wastewater sludge to obtain a quantitative value of the dewatering effect of the primary dewatered sludge. S5. Based on the deviation between the quantified value of the dewatering effect and the purification threshold, the dewatering control parameter set is gradient-corrected to obtain the optimized dewatering parameter set for the primary dewatered sludge. S6. Based on the optimized dewatering parameter set, the primary dewatered sludge is subjected to deep dewatering to obtain the reclaimed water after dewatering the metal surface treatment wastewater sludge.

2. The intelligent control method for dewatering sludge from metal surface treatment wastewater as described in claim 1, characterized in that, The step of placing the characteristic data into a preset dewatering parameter database for parameter matching to obtain the dewatering control parameter set for the wastewater sludge includes: The characteristic data is subjected to eigenvalue separation to obtain the solid density value and ionic conductivity value of the characteristic data; Based on the dehydration parameter mapping table of the preset dehydration parameter database, the solid density value and the ionic conductivity value are indexed by horizontal and vertical axes to obtain the dehydration control parameter group of the dehydration parameter mapping table.

3. The intelligent control method for dewatering sludge from metal surface treatment wastewater as described in claim 2, characterized in that, The dehydration parameter mapping table based on the preset dehydration parameter database indexes the solid density value and the ionic conductivity value using horizontal and vertical axes to obtain the dehydration control parameter group of the dehydration parameter mapping table, including: The solid density value is normalized to obtain the normalized solid density value, wherein the formula for calculating the normalized solid density value is as follows: In the formula, This is the normalized value of the solid density. To preset the minimum density boundary value, To preset the maximum density boundary value, This is the measured solid density value; The ionic conductivity value is normalized to obtain a normalized conductivity value, wherein the formula for calculating the normalized conductivity value is as follows: In the formula, This is the normalized value of conductivity. To preset the minimum conductivity boundary value, To preset the maximum conductivity boundary value, This is the measured ionic conductivity value; Based on the normalized values ​​of solid density and conductivity, a two-dimensional coordinate matching operation is performed in the dehydration parameter mapping table to obtain the unique corresponding parameter record in the dehydration parameter mapping table. The parameter records are directly matched to obtain the dehydration control parameter group of the dehydration parameter mapping table.

4. The intelligent control method for dewatering sludge from metal surface treatment wastewater as described in claim 1, characterized in that, The process of performing multi-stage dewatering on the metal surface treatment wastewater sludge based on the aforementioned dewatering control parameter set to obtain primary dewatered sludge includes: The dehydration control parameter group is parsed to obtain multi-level control commands for the dehydration control parameter group; Based on the multi-level control commands, the metal surface treatment wastewater sludge is filtered in multiple stages until the pressure filtration is completed, and the pressure filtration stage completion signal of the dewatering control parameter group is obtained. The validity of the completion signal of the filter press stage is verified to obtain the primary dewatered sludge of the metal surface treatment wastewater sludge.

5. The intelligent control method for dewatering sludge from metal surface treatment wastewater as described in claim 1, characterized in that, The monitoring of the moisture content in the primary dewatered sludge and the turbidity of the filtrate during the dewatering of the metal surface treatment wastewater sludge, to obtain a quantitative value of the dewatering effect of the primary dewatered sludge, includes: The real-time moisture content of the primary dewatered sludge and the real-time turbidity of the filtrate generated during the dewatering of the metal surface treatment wastewater sludge were collected. Based on the preset moisture content weighting factor and filtrate turbidity weighting factor, the real-time moisture content and the real-time turbidity are weighted and fused to obtain the comprehensive evaluation value of the dewatering effect of the primary dewatered sludge. The comprehensive evaluation value of the dewatering effect is numerically quantified to obtain the quantitative value of the dewatering effect of the primary dewatered sludge.

6. The intelligent control method for dewatering sludge from metal surface treatment wastewater as described in claim 5, characterized in that, The real-time moisture content and real-time turbidity are weighted and fused based on preset moisture content weighting factors and filtrate turbidity weighting factors to obtain a comprehensive evaluation value of the dewatering effect of the primary dewatered sludge, including: Call the historical database of the dewatering process for the wastewater sludge from the metal surface treatment; Based on the first preset interval to which the real-time moisture content belongs and the second preset interval to which the real-time turbidity belongs, the weighting factors of the historical database are extracted to obtain the moisture content weighting factor of the real-time moisture content and the filtrate turbidity weighting factor of the real-time turbidity. The moisture content weighting factor and the filtrate turbidity weighting factor are linearly superimposed to obtain the comprehensive evaluation value of the dehydration effect. The calculation formula for the comprehensive evaluation value of the dehydration effect is as follows: In the formula, This is a comprehensive evaluation value for the dehydration effect. For the matching moisture content weighting factor, The real-time moisture content, For the matching filtrate turbidity weighting factor, The real-time turbidity is [value].

7. The intelligent control method for dewatering sludge from metal surface treatment wastewater as described in claim 1, characterized in that, The deviation between the quantified dewatering effect value and the purification threshold is used to perform gradient correction on the dewatering control parameter set to obtain the optimized dewatering parameter set for the primary dewatered sludge, including: Calculate the deviation between the quantitative value of the dehydration effect and the preset purification threshold; Based on the preset deviation range of the deviation value, the parameter gradient correction is performed on the dewatering parameter correction increment library of the primary dewatered sludge to obtain the parameter correction increment value of the dewatering control parameter group. The parameter correction increment value is superimposed on the parameters in the dewatering control parameter group to generate the optimized dewatering parameter group for the primary dewatered sludge.

8. The intelligent control method for dewatering sludge from metal surface treatment wastewater as described in claim 7, characterized in that, The calculation of the deviation between the quantitative value of the dehydration effect and the preset purification threshold includes: Obtain the quantitative value of the dehydration effect and the purification threshold; The deviation rate between the quantified value of the dehydration effect and the purification threshold is calculated to obtain the deviation value of the quantified value of the dehydration effect. The formula for calculating the deviation value is as follows: In the formula, The deviation value is... This is a quantitative value for the dehydration effect. The preset purification threshold is used.

9. The intelligent control method for dewatering sludge from metal surface treatment wastewater as described in claim 1, characterized in that, The process of further dewatering the primary dewatered sludge based on the optimized dewatering parameter set to obtain reclaimed water after dewatering the metal surface treatment wastewater sludge includes: Analyze the parameters of the deep dehydration stage in the optimized dehydration parameter set; Based on the deep dewatering stage parameters, the preset metal surface treatment wastewater sludge dewatering process instruction library is matched to obtain the deep dewatering operation instruction sequence of the metal surface wastewater sludge. The primary dewatered sludge is subjected to staged deep dewatering according to the deep dewatering operation instruction sequence to obtain the reclaimed water after dewatering the metal surface treatment wastewater sludge.

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