10735 results about "Treatment system" patented technology

The invention relates to an intelligent diagnosis and treatment method and system based on a knowledge graph and a large language model. The method comprises the steps of constructing a basic framework of a medical field knowledge graph based on collected medical field data, constructing multi-level knowledge graph expression, obtaining symptom description of a patient through multiple rounds of dialogues, diagnosing the patient and generating a diagnosis report, rechecking and adjusting the diagnosis report by a professional physician, and finally outputting the diagnosis report. The intelligent diagnosis and treatment system comprises a knowledge graph construction module, an intelligent question and answer system, an entity matching module, an intelligent diagnosis module, a doctor review and diagnosis report adjustment module, a diagnosis report output module and the like. And main diseases are screened, so that the coverage is wider. And three levels of knowledge maps are constructed, so that text matching with finer granularity can be carried out. The non-standardized expression of the patient is firstly converted into standardized medical terms through a large model, and drug allergy and the like are taken into consideration, so that the diagnosis accuracy is improved, and the diagnosis and treatment risk is reduced.

The invention discloses a digital twinning-based wastewater and dirty salt treatment process optimization method and system, and relates to the technical field of intelligent wastewater and dirty salt treatment. The method comprises the steps that a digital twinborn model synchronously mapped with a processing system is established, and the digital twinborn model integrates the technological parameter incidence relation of an evaporation section, a crystallization section and a filtering section; collecting component data and flow data of the polluted salt wastewater corresponding to each process section in real time; correcting model characteristic parameters of each process section in the digital twin model based on the component data and the flow data collected in real time; according to the corrected digital twin model and the optimization target, generating a process optimization strategy corresponding to each process section; and monitoring the component data of the treated discharge water, reuse water, industrial salt and solid waste in real time, and if the data does not reach the standard, triggering model parameter correction, optimization strategy iteration or cross-section collaborative logic recalculation. According to the invention, intelligent cooperation of wastewater and dirty salt treatment is realized.

The invention relates to the field of wastewater treatment, and provides an industrial wastewater membrane process intelligent optimization method and system based on multi-dimensional data modeling. The method comprises the following steps: acquiring wastewater quality parameters of a target scene and a production line equipment state in real time through a multi-dimensional sensor network, and constructing a digital twinborn model of a wastewater treatment system in the target scene; the membrane surface pollution type of each node in the wastewater treatment system is identified through a digital twin model, and the inner membrane pollution evolution condition in the future preset duration is predicted; a multi-strategy evolutionary reinforcement learning algorithm is adopted, the wastewater quality parameters, the production line equipment state and the membrane pollution prediction result are combined, multi-target dynamic optimization is conducted on a wastewater treatment system through a multi-agent collaborative decision-making algorithm, an optimization strategy is generated based on the multi-target dynamic optimization result, and membrane process operation parameters and production control parameters are dynamically adjusted. According to the method, real-time intelligent adjustment of membrane process operation can be realized, the stability of membrane process operation is guaranteed, and the treatment efficiency of membrane process operation is improved.

The invention relates to the technical field of environment intelligent management, and discloses a multi-community-oriented AI intelligent household garbage control processing system which comprises a multi-mode sensing module, a data processing and edge calculation module, a garbage quantity prediction and scheduling optimization module, an intelligent decision and multi-source data fusion module and a self-adaptive adjustment and feedback mechanism module. The multi-community-oriented AI intelligent household garbage control processing method comprises the following steps that S1, a multi-modal sensing module collects garbage data; s2, an edge calculation module performs preprocessing, classification and encrypted transmission; s3, optimizing transportation and scheduling; s4, generating an optimal processing decision; and S5, adaptively adjusting the strategy. Through the technical scheme of combining multi-modal perception and edge calculation, accurate garbage data acquisition and efficient processing in a multi-community environment are realized, the technical effects of reducing data transmission burden and improving garbage classification data quality are achieved, and garbage classification is more accurate and reliable.

The invention discloses a smelting waste gas recycling optimization system based on fuzzy control, and relates to the technical field of automatic control. The problems of low control precision and response lag caused by the fact that an existing static membership function cannot adapt to multi-scale working condition changes in real time are solved. Comprising a sensing acquisition module, a membership reconstruction module, a feature decoupling module, a coupling compensation module, a rule optimization module and an execution control module. Standardized data are acquired through sensing acquisition and filtering, an adaptive membership function is constructed by adopting incremental fuzzy clustering, and closed-loop self-correction of a multi-modal control instruction is realized by combining wavelet packet decoupling, feed-forward compensation and double-depth Q network reinforcement learning online optimization; the waste gas desulfurization efficiency, energy consumption optimization and treatment system stability of waste gas treatment can be effectively improved.

The invention discloses a treatment system and a treatment method for chemical production waste gas, and relates to the technical field of industrial waste gas treatment. The system comprises a waste gas collection unit, a pretreatment unit, a multi-stage purification unit and an intelligent control unit. The intelligent control unit monitors data through a sensor network, the data processing and analysis module evaluates the processing effect and predicts the trend, the intelligent decision and adjustment module optimizes the parameters of each unit in sequence, and the remote monitoring and alarm module monitors and alarms in real time. The system can efficiently treat waste gas, realizes automatic intelligent control, ensures the stable treatment effect, reduces the risk of environmental pollution, and is widely applied to the field of chemical production waste gas treatment.

A plurality of resolved incident tickets of a technology landscape may be received from an incident handling system. A plurality of events may be received from a metric monitoring system monitoring the technology landscape. An incident cluster having related incidents may be generated from the plurality of resolved incident tickets, and a correlated event of the plurality of events may be identified for the incident cluster. The correlated event may be stored with an incident resolution obtained from the incident cluster, to obtain labeled training data. A machine learning (ML) model may be trained with the labeled training data to obtain an incident prediction model. A new event may be processed with the incident prediction model to provide a predicted incident and a predicted resolution.

The invention provides a sewage treatment system and method based on a large language model and multi-agent collaboration, and the system comprises a sensor network which is used for collecting the water quality parameters of sewage in real time; the monitoring agent is used for performing data verification on the water quality parameters; the at least one edge computing node is used for performing data preprocessing on the water quality parameters; the cloud decision intelligent agent is used for generating a sewage treatment strategy according to the preprocessed water quality parameters based on a large language model; the execution agent is used for executing the sewage treatment strategy and treating the sewage; the evaluation agent is used for analyzing and evaluating the sewage treatment effect and feeding back the sewage treatment effect to the cloud decision agent so as to optimize the sewage treatment strategy; by constructing an intelligent and dynamic treatment system, real-time monitoring, intelligent analysis and self-adaptive treatment of the mariculture sewage are realized, so that the sewage treatment stability and environmental protection benefits are improved, and the sustainable development of the mariculture industry is promoted.

To perform efficient surface treatment on a surface to be treated which is positioned on a lower surface side of a structure.SOLUTION: A surface treatment system jets jetted material to a surface to be treated which is set on a lower surface of a structure. The system includes: a surface treatment device which has a nozzle head provided with a jetting nozzle which is inserted in a base end opening part and jets the jetted material, and having a tip end opening part arranged opposite to the surface to be treated; and a nozzle head support device for supporting the nozzle head. The nozzle head support device includes: a pillar arranged in a periphery of the surface to be treated; an arm mechanism which has an arm main body of which a base end is connected to the pillar and rotates around the pillar, and includes a rotation shaft parallel to the pillar and arranged on a joint of a link; and a nozzle head mounting member which is connected to a tip end of the arm mechanism and on which the nozzle head is mounted.SELECTED DRAWING: Figure 1

The invention belongs to the technical field of medical artificial intelligence, and discloses an artificial intelligence-based auxiliary diagnosis and treatment system, which comprises a multi-modal data acquisition module, a dynamic learning module, a diagnosis reasoning module, a privacy protection module, an interactive decision module and an early warning monitoring module, the output end of the multi-modal data acquisition module is connected with the input end of the privacy protection module, the output end of the privacy protection module is connected with the input end of the dynamic learning module, the output end of the dynamic learning module is connected with the input end of the diagnostic reasoning module, and the output end of the diagnostic reasoning module is connected with the input end of the interactive decision module. And the early warning monitoring module monitors abnormal data in real time and performs bidirectional interaction with the diagnosis reasoning module. According to the method, multi-source medical data are integrated, and high-precision real-time auxiliary diagnosis is realized by adopting a dynamic incremental learning and privacy encryption technology; the medical worker cooperation efficiency is improved through an interactive interface, the safety is guaranteed in combination with real-time monitoring and early warning, and the system can remarkably improve the diagnosis and treatment efficiency and accuracy.

The invention relates to the technical field of neuromuscular electrical stimulation, and provides a multi-modal feedback self-adaptive adjustment neuromuscular regulation and control treatment system, which comprises wearable working equipment for outputting pulse electric signals to adjust nerves and muscles to form movement or adjustment feeling, electromyographic signals, motion data and user feeling input are collected to conduct feedback adjustment on output parameters of the output pulse electric signals; the handheld control equipment is used for being connected with the wearable working equipment and controlling the output working mode and the working state of the wearable working equipment; and the server-side equipment is used for managing user information and preference of the handheld control equipment, setting function authority of the handheld control equipment, acquiring data acquired by the wearable working equipment, and realizing self-adaptive output of output parameters of the pulse electric signals of the wearable working equipment based on a self-adaptive reinforcement learning algorithm. Adaptive optimization of millisecond-level dynamic electrical stimulation parameters is realized through a multi-modal feedback data fusion technology in combination with a layered reinforcement learning architecture.

The invention relates to a multi-agent medical diagnosis and treatment system which comprises a plurality of agents. The plurality of agents comprise: a task planning agent analyzes input content and generates a corresponding task process, and the task planning agent sequentially issues task instructions to a data management agent, a tool use agent and a medical decision agent according to the task process; the task instructions comprise a data task instruction, a tool task instruction and a decision task instruction; the data management agent extracts patient data from the database and sends the patient data to the task planning agent according to a data task instruction issued by the task planning agent; the tool using agent performs feature extraction processing on the patient data according to the patient data and the tool task instruction issued by the task planning agent so as to obtain key features and send the key features to the task planning agent; and the medical decision-making agent carries out diagnosis and treatment reasoning according to the key features and the decision-making task instruction issued by the task planning agent, and a diagnosis report is obtained and displayed.

The invention discloses a multi-angle particle therapy system without a rotating rack and a using method thereof, and relates to the technical field of particle therapy equipment, and the treatment system comprises an accelerator, an irradiation system, a control system, a patient supporting system and an imaging system. The patient supporting system comprises a containing and fixing device, a two-dimensional translation system, a rotating system and a multi-degree-of-freedom mechanical positioning system, the containing and fixing device is connected with the two-dimensional translation system, the two-dimensional translation system is connected with the rotating system, and the two-dimensional translation system controls the relative position of a patient and a rotating center; the rotating system rotates a patient to an appointed angle of a treatment plan or cooperates with the imaging system to obtain a three-dimensional image of the patient, and the irradiation system irradiates a tumor target area; the use method comprises the following steps: generating a treatment plan by reconstructing a three-dimensional CT image, and completing irradiation at different angles according to the treatment plan. According to the treatment system, multi-angle irradiation on a patient can be realized under the condition that a rotating rack is not used, and the manufacturing period and cost of the particle treatment system can be reduced.

The invention relates to the technical field of ecological environment monitoring, in particular to a multi-dimensional data analysis-based water body pollution monitoring and processing system, which comprises a dynamic data cube construction module, a pollution event slice extraction module, a multi-dimensional feature fingerprint coupling module, a pollution source reverse traceability module and a self-adaptive early warning trigger module. The method comprises the following steps: receiving water quality parameters of an internet of things sensor, meteorological data of a meteorological hydrological station and satellite remote sensing spectral data, and constructing a dynamic data cube of unified space-time coordinates and feature axes; identifying pollution event slices by using entropy change analysis and a self-adaptive threshold method; carrying out characteristic coupling analysis on the pollution event, and fusing a spectrum fluctuation mode, a physicochemical gradient and toxicity response to generate a pollution characteristic fingerprint; pollution source positioning and contribution weight estimation are realized by adopting a dynamic time warping algorithm, and corresponding disposal equipment is driven to start based on an early warning level, so that intelligent closed-loop control of pollution identification, source tracing and treatment is realized.

The invention discloses an integrated water quality monitoring and processing system for aquaculture, and the system comprises a data collection module which is used for obtaining dissolved oxygen, ammonia nitrogen, pH value, temperature and flow data from a plurality of spatial distributed sensing nodes; the data preprocessing module is used for completing noise removal, correction and time sequence synchronization; the water quality state estimation module is used for outputting real-time multi-point water quality states based on a distributed unscented Kalman filtering algorithm; the space-time fluid modeling module is used for constructing a Lagrange model to extract a flow velocity field and a diffusion coefficient; the scheduling optimization module is used for generating an aeration and dosing scheme by adopting an improved multi-target Pareto optimization algorithm based on a space-time sensitive boundary; the execution module is used for controlling an air blower, an aeration pipe and a dosing pump to complete oxygenation and dosing operations; and the self-adaptive updating module is used for collecting feedback data to adjust filtering gain and optimizing parameters so as to realize closed-loop control of the system.

The invention relates to the field of intelligent temperature control of industrial kilns, and discloses a graphitization furnace temperature uniformity optimization processing system which comprises a temperature monitoring module, a dynamic matrix control module, a material-control coupling module, a lattice feedback module and a multi-objective optimization module. The method comprises the following steps: constructing an equivalent temperature field through multi-source temperature data fusion; predicting a graphitization trend and generating a dynamic matrix control instruction in combination with a multi-physical field model; dynamically adjusting a thermal conductivity matching temperature gradient of the guard plate; online correcting a material constant based on lattice feedback; closed-loop control is formed, and the process stability and energy efficiency of the graphitization furnace are improved. Through multi-source fusion monitoring, multi-physical field coupling modeling, dynamic thermal conductivity regulation and control, lattice feedback online correction and reinforcement learning multi-objective optimization, temperature uniformity control and energy efficiency improvement of the graphitization furnace are realized, and material performance and process economy are guaranteed.

The invention provides a multiphase collaborative purification intelligent treatment system for heavy metal wastewater, which relates to the technical field of wastewater treatment and comprises a pretreatment module, a main treatment module, an advanced treatment module, a post-treatment and recycling module, a sludge treatment module and an intelligent control module. The intelligent control module comprises a data acquisition layer, a control layer and a management layer, and intelligent control on each treatment module is realized by monitoring parameters such as pH value, ORP (oxidation-reduction potential), conductivity and heavy metal ion concentration of the wastewater on line. The data acquisition layer acquires processing parameters in real time through various sensors; the control layer executes control logic based on the PLC / DCS and monitors the operation state through SCADA (Supervisory Control And Data Acquisition); the management layer adopts AI algorithms such as a water quality-energy consumption correlation regression model and a time sequence water quality fluctuation learning model to optimize processing parameters. According to the system, the treatment process can be intelligently adjusted according to the characteristics of the wastewater, the maximization of the heavy metal wastewater treatment efficiency, the minimization of chemical consumption and the minimization of energy consumption are realized, and the treatment effect and the system stability are improved.

The invention relates to the technical field of circulating water treatment, and discloses a circulating water treatment closed-loop optimization method and system based on water quality prediction.The circulating water treatment closed-loop optimization method based on water quality prediction.The circulating water treatment closed-loop optimization method based on water quality predictioncomprises the steps that a time sequence knowledge graph supporting the time dimension is constructed and used for representing water quality parameters and time sequence evolution characteristics of the relation of the water quality parameters; constructing a multi-time scale prediction engine to predict a future water quality state; developing a predictive constraint generator, and converting future water quality prediction into current decision constraints; a space-time sensitive multi-objective optimization algorithm is introduced, and a medicament proportioning strategy is optimized; a multi-time-scale collaborative optimization system is realized, so that short-term response and long-term stability are further balanced; an environment adaptation active evolution system is constructed, and automatic adjustment of the system along with environment changes is achieved; according to the invention, the fundamental transformation of a circulating water treatment control mode is realized, and a brand new closed-loop optimization normal form is provided for a circulating water treatment system.

The invention provides a massage robot multi-mode fusion treatment system and method based on 3D vision, and relates to the technical field of massage robots. The region recognition module is used for establishing a human body recognition model and recognizing human body features in the processed image; the massage terminal is used for carrying out massage operation according to parts needing to be massaged and human body characteristics and monitoring skin pressure of the massaged parts in real time; the pain sense recognition module is used for human body pain sense recognition; the force adjusting module is used for adjusting skin pressure. According to the method, pertinence and safety of massage operation are remarkably improved through multi-modal image preprocessing and an initialized human body recognition model of a fusion segmentation model and a key point detection model; a global path strategy is generated and optimized through a hybrid ant colony algorithm, efficient and accurate motion control of the mechanical arm is achieved, through multi-modal data fusion analysis, the pain feeling of a user is sensed in real time, the massage strength is dynamically adjusted, and the comfort and the safety coefficient are improved.

The invention provides low-carbon fuel blending coupling combustion test equipment and method, and the equipment comprises a blending fuel feeding system which is used for blending solid-phase, liquid-phase and gas-phase low-carbon fuels with fossil solid fuels or other solid fuels in proportion; the one-dimensional combustion furnace is used for coupling combustion of the blended fuel; the flue gas treatment system is used for carrying out cooling, dust removal, desulfurization, denitration and carbon dioxide adsorption and trapping treatment on flue gas generated by coupling combustion; the control cabinet is used for controlling the stable and safe operation of the whole experiment platform; the low-carbon coupling combustion test system and method and the coupling combustion low-carbon technology have the beneficial effects that the coupling combustion condition that the actual boiler is internally mixed with low-carbon fuel is simulated by adopting a feeding and conveying mode of accurately controlling the blending combustion proportion, and the low-carbon coupling combustion test system and method and the coupling combustion low-carbon technology are formed; the device has multiple innovative functions of controlling the blending combustion ratio, efficiently coupling combustion, comprehensively purifying flue gas, adsorbing and trapping carbon dioxide, saving energy, reducing carbon and the like.

The present application relates to the field of wastewater treatment, and provides a treatment system and method for electroless nickel-plating waste liquid. The treatment system comprises a decomplexing pretreatment system; an oxidation-decomplexing system comprising a redox reactor and a decomplexing reactor which are connected in sequence, wherein an oxidizing agent in the redox reactor is oxygen, and an oxidizing agent in the decomplexing reactor is hydrogen peroxide; a chemical precipitation system comprising a neutralization reaction tank and a sedimentation tank which are connected in sequence, wherein the sedimentation tank is equipped with a filter system; and an evaporation crystallization system comprising an evaporation device, a crystallization device, and a separation device which are arranged in sequence. In the treatment system and method for electroless nickel-plating waste liquid, a two-stage oxidation method is employed to achieve oxidation and decomplexing of the waste liquid; in addition, combining chemical precipitation treatment and evaporation crystallization treatment not only reduces the waste liquid treatment cost but also avoids the introduction of other impurities, and allows for the separation of nickel salts and phosphate salts, so that the operation is easy and convenient, the treatment cost is low, the nickel removal rate is high, and resource utilization of nickel is facilitated.

The invention relates to the technical field of spray towers, and discloses a spray tower for a tail gas treatment system, the spray tower comprises a tower body, a circulating water tank is fixedly arranged at the bottom of the tower body, a gas inlet end is fixedly arranged on the lower side wall of the tower body, a plurality of layers of pore plates are fixedly arranged in the tower body, and a filler layer is fixedly arranged above the pore plates. An air outlet end is fixedly arranged at the top end of the tower body, a filtering assembly is fixedly arranged in the circulating water tank and comprises an air inlet pipe, the top end of the air inlet pipe is fixedly connected with the top end of the tower body, and the bottom end of the air inlet pipe penetrates through the circulating water tank and is fixedly connected with a first cylinder; and a barrel II is slidably connected to the interior of the barrel I. Impurities in washing liquid are filtered through the filter screen, the cyclic utilization effect is achieved, the filter screen is backwashed through pushing force generated when filtered gas in the tower body flows, the impurities are carried and discharged through the blow-off pipe, and the automatic cleaning effect is achieved.

The invention relates to the technical field of sewage treatment, in particular to an aerobic aeration treatment system for plateau domestic sewage treatment, which comprises a pretreatment unit, a biological treatment unit, an advanced treatment unit and a recycling unit which are connected in sequence, the system further comprises a data acquisition module, an aerobic aeration intelligent regulation and control module, a biochemical environment constant-temperature maintenance module, a carbon-nitrogen proportion and backflow dynamic regulation and control module, a digital twinning and sludge characteristic simulation module and an energy collaborative scheduling module. Compared with the prior art which adopts a standard aeration strategy and cannot adapt to the special environment of low air pressure and low oxygen partial pressure of the plateau, the system can accurately adapt to the plateau environment by integrating real-time atmospheric pressure and water temperature monitoring, dynamically calculating the oxygen saturation solubility and correcting the aeration control target according to the oxygen saturation solubility, so that the aeration control target is optimized. Stable supply of dissolved oxygen required by biochemical reaction is ensured, and the technical bottleneck of low efficiency of traditional sewage treatment in plateau regions is fundamentally overcome.

The embodiment of the invention provides a water conservancy project intelligent processing system based on BIM and GIS. The water conservancy project intelligent processing system comprises the steps that material strength and construction timestamps of engineering components are extracted through a BIM parser to generate a topological relation graph; combining the remote sensing image and the geological data through a coordinate converter to determine a three-dimensional terrain field; establishing a spatial Hash grid correlation topological relation graph and a three-dimensional terrain field; constructing a digital twinborn body containing structural stress distribution and a hydrodynamic model on the basis of a correlation result; executing Monte Carlo simulation in the digital twin according to the real-time sensor data to generate a prediction scene set; when abnormal data is monitored, performing reverse tracing along the topological relation graph to generate a multi-factor association graph; and optimizing a disposal plan weight coefficient through a reinforcement learning algorithm and updating the knowledge base. Pixel-level matching of the rock-soil layer permeability coefficient and the concrete member strength is achieved, the system can recognize the coupling relation between a geological weak area and a structural high-risk point, meanwhile, a knowledge graph containing a construction time sequence is constructed, and a cause chain of quality defects can be traced.

The invention discloses a cyclic utilization and purification treatment system for slurry in pile foundation engineering construction. According to the invention, the purification treatment system is utilized to realize the double breakthrough of environmental friendliness and high resource efficiency in the construction process through the deep enabling of the intelligent regulation and control module. The system constructs a closed-loop management chain of the slurry life cycle by relying on full-process data perception and dynamic optimization capability. The intelligent regulation and control module captures fine changes of physical and chemical characteristics of the slurry in real time and automatically regulates the operation mode of the treatment equipment, so that the purified slurry always keeps the optimal engineering performance index, and the risk of pile body defects caused by quality fluctuation of the slurry is greatly reduced. By means of the intelligent design of the waste slurry recycling path, pollution sources in traditional construction are converted into reusable engineering materials, damage to the ecological environment caused by outward transportation and landfill of waste is remarkably reduced, and an engineering site is promoted to move towards the near-zero emission target.

The invention provides a chemical sewage advanced treatment system and method based on multistage membrane separation, and relates to the technical field of chemical sewage treatment.The method comprises the steps that pollution load data under preset membrane flux is collected, and the cascade reflux amount in the current membrane separation process is determined through the pollution load data and a real-time pressure index during membrane separation filtration; according to the separation interference deviation, the steady-state filtering period of the membrane separation filtering grade in the constant flux change is predicted, the steady-state filtering period is synchronously screened, and the full-flow separation limit of the multistage membrane separation unit in different pollution loads is obtained; and generating a separation regulation and control index when the equivalent flux generates peak offset according to the cascade reflux quantity and the full-flow separation limit, and performing starting point triggering on the treatment flow of the multistage membrane separation sewage and dirt. Under the dynamic working condition of operation of the multistage membrane separation system, balance adjustment can be carried out on the advanced treatment process trigger of the chemical sewage, so that the standard-reaching rate of membrane separation chemical sewage advanced treatment is increased.

The invention discloses a process and system for recovering phosphorus and fluorine from ardealite leachate, which comprises the following steps: feeding the ardealite leachate into an induced crystallization reactor for induced crystallization, discharging generated large-particle fluorapatite crystals from a crystal discharge port at the bottom of the induced crystallization reactor, and collecting and recycling; aluminum hydroxide flocs and fine-particle fluorapatite crystals enter a cyclone separator along with the effluent, the fine-particle fluorapatite crystals are separated and then flow back to the induced crystallization reactor, the aluminum hydroxide flocs form precipitates in the flocculation sedimentation tank through flocculation to be removed, and the effluent of the flocculation sedimentation tank enters a multi-stage treatment system. According to the method disclosed by the invention, fluorine and phosphorus in the phosphogypsum leachate are recovered together, the recovered fluorapatite finished product is high in purity and can be recycled, and the amount of chemical sludge is also greatly reduced, so that the treatment cost of the sludge is reduced.

The invention discloses a shallow lake water quality pollution treatment system and method, and relates to the technical field of water pollution, and the method comprises the steps: S1, building a disturbance intensity index DIX and ammonia nitrogen concentration change curve, achieving the quantitative recognition of bottom mud disturbance and pollution release behaviors, training a rebound risk prediction model according to the quantitative recognition, and outputting a rebound risk prediction coefficient Ft; and the capability of pre-judging the rebound trend of the ammonia nitrogen pollution is effectively improved. In the step S2, the adjusted aeration response frequency BAF is dynamically generated based on the rebound risk prediction coefficient Ft value, so that the aeration behavior is converted into a risk-driven system from a traditional timing system, the energy consumption and disturbance intensity are further reduced, and the treatment efficiency is improved. And S3, further introducing a governance residual coefficient GRC, constructing a complete feedback closed loop, and realizing accurate evaluation and secondary strategy optimization of the governance effect of each round, thereby avoiding the problem of effect back-off or excessive disturbance after governance.

The invention discloses a sewage discharge control method based on artificial intelligence, and belongs to the technical field of sewage treatment, and the method specifically comprises the steps: collecting the sewage flow of each subarea and the operation data of a corresponding treatment plant, constructing a time series prediction model, and outputting the sewage load deduction value of each subarea in the future; historical data of a treatment plant are called, a cost-load curve is constructed, and a cost gradient abrupt change inflection point is identified as a load critical value; the treatment plant with the load deduction value exceeding the critical value is determined as a positive treatment plant, and the treatment plant with the load deduction value lower than the critical value and the unit cost lower than the regional reference value is determined as a negative treatment plant; constructing an optimization model aiming at minimizing the scheduling loss, and generating a cross-region conveying path and a scheduling instruction set; scheduling the treatment plants corresponding to all the urban partitions according to the scheduling control instruction set; according to the method, the scheduling instruction is generated by constructing the scheduling loss minimization optimization model, dynamic cross-regional optimization scheduling of the urban sewage is realized, and the economical efficiency and the operation efficiency of a sewage treatment system are improved.

The invention discloses a zeolite adsorption and desorption integrated treatment system, and particularly relates to the field of zeolite separation treatment, and the zeolite adsorption and desorption integrated treatment system comprises a process sensing module, a dynamic partition control module, a global optimization control module and a cooling regeneration module. According to the zeolite adsorption and desorption integrated treatment system, the problem of blind operation in the traditional technology is solved through the process sensing module, a data basis is provided for dynamic partition, the intelligent monitoring level is improved, and the performance of an adsorbent is fully exerted; the problem of non-uniform heat and mass transfer of a bed layer is effectively solved through the dynamic partition control module, the desorption heat utilization efficiency is improved, and meanwhile, the service life of an adsorbent is prolonged; a dynamic optimization function is constructed through the global optimization control module, energy consumption, solvent recovery income and stability are comprehensively considered, self-adaptive adjustment of operation parameters is achieved, the energy consumption is reduced while the processing efficiency is guaranteed, and the environmental benefits are remarkably improved.