8372 results about "Treatment system" patented technology

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 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 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 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 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 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 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 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.

The invention provides a tumor electric field treatment system, an electrode slice temperature detection method and an electrode slice anomaly detection method, the system comprises an electrode slice and an adapter provided with a first controller, the electrode slice comprises a plurality of electrode units and a plurality of temperature detection units, the plurality of temperature detection units are divided into a plurality of row groups and a plurality of column groups, and the first controller is connected with the adapter. The grounding ends of the temperature detection units in each row group are jointly connected to the same grounding wire, and the signal ends of the temperature detection units in each column group are connected to the same dual-purpose signal wire after being in short circuit with the corresponding electrode units; when the dual-purpose signal line is connected to the temperature sampling point, the grounding wires are sequentially conducted, so that temperature detection signals detected by the temperature detection units are sampled based on the temperature sampling point; when the dual-purpose signal line is connected to the alternating power line, alternating electric signals are transmitted to the electrode units. Therefore, the temperature of the electrode plate can be detected by using fewer conductive traces, and whether the electrode plate is abnormal or not can be judged through temperature detection.

The utility model discloses a tumor electric field treatment device and a treatment system, the tumor electric field treatment device is provided with a frame body and a pole piece module, the frame body forms a skeleton structure of the treatment device, the pole piece module is attached to the frame body, the pole piece module is provided with a plurality of electrode contacts, and each electrode contact can form an active contact or a passive contact. The active contact and the radio frequency generation module can form a loop; after the treatment device is implanted into a tumor excision part, all the electrode contacts form active contacts, and all the electrode contacts and the radio frequency generation module form a loop to distinguish normal tissues from pathological tissues; after the normal tissue and the lesion tissue are distinguished, the electrode contacts in the normal tissue area form passive contacts, and the electrode contacts in the lesion tissue area form active contacts, so that targeted treatment of the lesion tissue is realized, and side effects generated by electric field treatment are reduced.

The invention discloses a large-scale pig breeding wastewater purification treatment system, and relates to the technical field of wastewater treatment.The large-scale pig breeding wastewater purification treatment system is characterized in that the ion concentration of anaerobic liquid is monitored through a multi-ion sensing array, and a multi-channel feeding system is controlled to synthesize customized struvite compound fertilizer; the AI prediction control unit predicts the optimal medicament dosage and realizes millisecond-level closed-loop regulation; the multi-dimensional synergistic biochemical treatment module comprises an A / O biochemical treatment unit and an electric field enhanced anaerobic ammonia oxidation reactor, the electric field enhanced anaerobic ammonia oxidation reactor applies a direct-current electric field through an electrode pair, and engineering conductive biochar is used as a carrier to accelerate microbial metabolism; the sludge low-temperature pyrolysis self-consistent circulation module is used for pyrolyzing and converting residual sludge into biochar, biofuel and wood vinegar, and the biochar activation treatment unit is used for preparing engineering conductive biochar and forming a substance closed loop through a self-consistent circulation conveying system; and the digital twinning intelligent management and control platform realizes intelligent management and control of the system.

The invention relates to the technical field of intelligent diagnosis and treatment, and discloses a remote intelligent disease diagnosis and treatment system and method based on a block chain. The method comprises the steps that multi-modal physiological data such as real-time vital signs, historical medical record texts and medical images of a patient are collected, an encrypted data packet is generated, distributed storage is conducted through a block chain node network, and a data hash value and a timestamp are generated; and calling an intelligent contract to extract cross-modal features, generating a standardized feature vector set containing a multi-feature association identifier, and constructing a diagnosis and treatment decision tree capable of dynamically adjusting branch paths according to the standardized feature vector set. Verifying decision validity through a consensus mechanism, and generating a treatment instruction sequence containing drug configuration, instrument operation and a follow-up visit period; and monitoring feedback data in real time and updating the feedback data to the block chain, triggering an intelligent contract to generate a correction scheme when the deviation exceeds a threshold value, and writing the difference data as a new transaction record into the block chain, thereby realizing multi-modal data security management and control and dynamic precise diagnosis and treatment.

The invention provides a tumor electric field treatment system, an electrode slice temperature detection method and an electrode slice anomaly detection method, the system comprises an alternating current signal generator, an electrode slice and a controller, the electrode slice comprises a plurality of electrode units and a plurality of temperature detection units, the plurality of temperature detection units are divided into a plurality of row groups and a plurality of column groups, and the plurality of electrode units are connected with the controller. The grounding ends of the temperature detection units in each row group are jointly connected to the same grounding wire, and the signal ends of the temperature detection units in each column group are connected to the same dual-purpose signal wire after being in short circuit with the corresponding electrode units; when the dual-purpose signal line is connected to the temperature sampling point, the grounding wires are sequentially conducted, so that temperature detection signals detected by the temperature detection units are sampled based on the temperature sampling point; when the dual-purpose signal line is connected to the alternating power line, alternating electric signals are transmitted to the electrode units. Therefore, the temperature of the electrode plate can be detected by using fewer conductive traces, and whether the electrode plate is abnormal or not can be judged through temperature detection.

The invention relates to the technical field of data processing, and discloses a flue gas treatment intelligent regulation and control method and system based on artificial intelligence and a medium. The method comprises the following steps: collecting parameter data of a flue gas system through a sensor network and processing to obtain preprocessed data; using unsupervised clustering to identify working condition features and categories; constructing an emission concentration error active switching control model according to the working condition information; different working condition control parameters are optimized by adopting a differential evolution algorithm; optimized parameters are input into a controller, and modes are dynamically switched according to pollutant errors. The control strategy can be automatically switched according to the working condition characteristics of the flue gas treatment system, the complex and changeable industrial production environment can be effectively dealt with, and the system operation cost is optimized while stable and up-to-standard emission of pollutants is guaranteed.

The invention relates to the technical field of environmental engineering water treatment automatic control, and discloses a landfill leachate treatment control method based on cooperative control. The method comprises the following steps: acquiring real-time monitored water quality parameter data streams including a pretreatment stage pH value, a main treatment stage COD concentration, a deep treatment stage membrane pressure difference and the like in a landfill leachate treatment system, inputting the data streams into a cooperative control framework, and dynamically correcting PID controller parameters through a nonlinear gain function to generate a primary adjustment instruction; evaluating and generating a strategy optimization instruction based on the reinforcement learning strategy network; inputting the two into a grey prediction model and outputting a cooperative control signal containing a feedforward compensation amount; and finally, dynamically adjusting the coagulant dosage, the aeration intensity and the working pressure of the membrane component according to the signal to form a closed-loop control loop. The method can master the water quality change in real time, accurately regulate and control the treatment process, improve the stability and reliability of the treatment system, and effectively improve the landfill leachate treatment effect.

The invention provides a tumor electric field treatment system, an electrode slice temperature detection method and an electrode slice anomaly detection method, the system comprises an electrode slice and an adapter provided with a first controller, the electrode slice comprises a plurality of electrode units and a plurality of temperature detection units, the plurality of temperature detection units are divided into a plurality of row groups and a plurality of column groups, and the first controller is connected with the adapter. The grounding ends of the temperature detection units in each row group are jointly connected to the same grounding wire, and the signal ends of the temperature detection units in each column group are connected to the same dual-purpose signal wire after being in short circuit with the corresponding electrode units; when the dual-purpose signal line is connected to the temperature sampling point, the grounding wires are sequentially conducted, so that temperature detection signals detected by the temperature detection units are sampled based on the temperature sampling point; when the dual-purpose signal line is connected to the alternating power line, alternating electric signals are transmitted to the electrode units. Therefore, the temperature of the electrode plate can be detected by using fewer conductive traces, and whether the electrode plate is abnormal or not can be judged through temperature detection.

The invention provides an APF and SVG cooperative control-based electric energy quality comprehensive treatment system, and belongs to the technical field of intelligent power grid industry and electric energy quality comprehensive treatment, and the system comprises the steps of obtaining a power grid current signal and a voltage signal, and detecting a harmonic component and a voltage deviation through a harmonic detection module; a collaborative decision controller is adopted to determine a compensation strategy according to the harmonic component and the voltage deviation, and compensation tasks of an active power filter channel and a static var generator channel are distributed; harmonic compensation current is generated through an active power filter channel, and high-frequency harmonics are suppressed; reactive compensation current is generated through a static var generator channel, and voltage fluctuation is stabilized; and the compensation current is filtered through the filtering module and is output to a power grid. The electric energy quality comprehensive treatment system can effectively inhibit power grid harmonic waves, stabilize voltage fluctuation and improve electric energy quality, and is suitable for a complex power grid environment.

The invention belongs to the field of industrial thermal engineering and intelligent modeling, and discloses a heat exchanger heat exchange coefficient prediction method and system based on a physical information neural network. The method comprises the following steps: acquiring multi-dimensional operation data through a signal acquisition system, cleaning abnormal and blank values, standardizing, and segmenting into time sequence samples by adopting a sliding window method; a double-layer physical information long-short-term memory network is constructed, and a time sequence feature and a physical equation residual error are combined to generate a space-time fusion feature matrix. And a composite loss function including data loss, physical equation loss and physical consistency loss is designed, physical and data driving influences are balanced through hyper-parameter tuning, and accurate prediction of the heat exchange coefficient is achieved based on a gradient descent optimization model. The method combines field physical laws and data features, improves the reliability and physical interpretability of prediction, and is suitable for operation optimization of the heat exchanger of the desulfurization wastewater treatment system of the thermal power plant.

The invention relates to the technical field of sewage treatment, in particular to a dynamic control method applied to a culture tail water circulation treatment system. The method comprises the following steps: continuously detecting aquaculture tail water on a water inlet pipeline, calculating the ratio of chemical oxygen demand to five-day biochemical oxygen demand as a first degradation index, and calculating the ratio of ultraviolet absorbance to total organic carbon concentration as a second degradation index; according to the first degradation index and the second degradation index, identifying aging complementary and range complementary organic load degradation characteristics, and determining a process treatment path based on the organic load degradation characteristics; performing primary pretreatment on the aquaculture tail water in different process treatment paths to obtain intermediate water quality data; detecting the ammonia nitrogen concentration of the intermediate water quality data, and extracting the time change rate of the ammonia nitrogen concentration as an ammonia nitrogen conversion parameter. According to the invention, the oxygen utilization efficiency and the removal rate of organic matters and nitrogen are improved through regional dissolved oxygen and function configuration optimization.

The invention discloses a VTE real-time monitoring and intelligent prevention and treatment system, and belongs to the technical field of intelligent prevention and treatment, and the system comprises a baseline construction module which is used for collecting multi-dimensional VTE parameters, calculating the normal fluctuation interval of each parameter to form an initial individualized baseline, and constructing a self-adaptive individualized baseline through threshold calibration; the trend identification module is used for dynamically setting a sliding window duration, calculating a VTE trend slope and a VTE product deviation, constructing a trend constraint and a product deviation constraint, and when the two constraints are not met at the same time and the continuous deviation duration is exceeded, judging that the deviation is continuous abnormal deviation; the time sequence risk prediction module is used for calculating deviation values of various parameters of the target patient, constructing a space-time fusion feature matrix, inputting a time sequence risk prediction model and outputting a VTE risk probability; and the early warning and intervention module is used for performing double judgment and intervention, setting three-level early warning and intervention measures, calculating an improvement rate to verify a prevention and control effect in real time, and realizing VTE early recognition and intelligent prevention and control.

The invention relates to the technical field of safety monitoring, and discloses a multistage safety early warning and linkage processing system for an electricity-hydrogen complementary energy station, and the system comprises a monitoring collection module which is used for deploying a multi-source sensor network in the electricity-hydrogen complementary energy station, collecting key parameter data in real time, and generating a real-time data set comprising a timestamp, a sensor ID and a parameter value; the anomaly detection module is used for performing multi-dimensional analysis by adopting an anomaly detection algorithm according to the real-time data set, identifying an anomaly mode and outputting a graded early warning signal; the evaluation grading module is used for carrying out dynamic risk evaluation in combination with the early warning signal and the system state, and outputting a quantitative risk grade and a disposal suggestion; the linkage triggering module is used for automatically matching and triggering a corresponding plan according to the risk level and outputting a specific linkage control instruction; an execution feedback module; according to the invention, the emergency response speed is improved, the false alarm rate caused by normal working condition fluctuation is reduced, and fundamental conversion from passive response to active early warning is realized.

The invention discloses an urban road rainwater runoff stage treatment system and method, and relates to the technical field of urban rainwater pollution treatment. In order to solve the problems that an existing system is difficult to monitor multi-index water quality in real time, the pollution degree is accurately recognized, and distribution control lacks dynamics, the system is provided with a multi-source spectrum water quality monitor at the tail end of a pipe network, turbidity, COD, TOC and heavy metal concentration are monitored in real time, rainfall intensity data are accessed into a control center, the pollutant load instantaneous rate L is calculated through a weighted summation formula, and the real-time monitoring of the pollution degree is achieved. A controllable flow distribution module in the flow distribution well distributes the rainwater to an enhanced treatment unit, a biological aerated filter system or a horizontal flow sedimentation tank, wherein the enhanced treatment unit comprises a rotational flow sand setting unit, an electrochemical heavy metal degradation unit and a chemical flocculation unit. The system is mainly used for realizing quality-divided efficient treatment and resource recycling of rainwater and guaranteeing the safety of a receiving water body.

The invention provides a tumor electric field treatment system and an electrode slice temperature detection method, the system comprises an electrode slice and a controller, the electrode slice comprises a plurality of electrode units and a plurality of temperature detection units, the plurality of temperature detection units are divided into a plurality of row groups and a plurality of column groups, the grounding ends of the temperature detection units in each row group are jointly connected to the same grounding wire, and the signal ends of the temperature detection units in each column group are connected to the same dual-purpose signal wire after being in short circuit with the corresponding electrode units; when the dual-purpose signal line is connected to the temperature sampling point, the grounding wires are sequentially conducted, so that temperature detection signals detected by the temperature detection units are sampled based on the temperature sampling point; when the dual-purpose signal line is connected to the alternating power line, alternating electric signals are transmitted to the electrode units. In this way, a plurality of electrode units can be zoned and controlled using fewer conductive traces.

The present invention relates to the field of biomedicine and discloses a platelet-rich plasma for anti-aging and promoting tissue repair and regeneration, a preparation method, and an application thereof, comprising the following steps: obtaining concentrated platelet plasma, and treating the concentrated platelet plasma with low-intensity pulsed ultrasound; the treatment conditions are one of the following treatment methods: 1) the treatment power is 2 to 5 W / cm 2 , the pulse period is 50%, and the ultrasonic treatment time is 2~10 min; 2) First, the first ultrasonic treatment is performed: using 0.2~1.0 W / cm 2 , the pulse period is 50%, ultrasonic treatment is 1~5 min; then the second ultrasonic treatment is carried out: 1.5~5.0 W / cm 2 , the pulse period is 50%, and the ultrasonic treatment is 1 to 5 minutes; the present invention adopts a special ultrasonic treatment system to obtain a PRR product with special activation and lysis characteristics. The product has active substances that are beneficial to tissue repair and regeneration and anti-aging, and shows excellent effects in promoting cell proliferation, cell migration and wound healing.

The invention discloses an online order full-process automatic processing system and method. The system comprises an order state analysis module, a cross-platform collaborative adaptation module, a resource scheduling planning module, an environment load evaluation module and a task scheduling optimization module. According to the invention, by analyzing the trend of the key time sequence change of the order life cycle, the circulation bottleneck can be identified and the time section exceeding the threshold value can be generated, so that the task sequence is matched with the system load, the scheduling coordination and the response precision are enhanced, the execution capability is dynamically compared to form the optimal distribution instruction, and the cooperation efficiency and the transmission continuity are improved. Based on a utilization rate change identification trend, resource distribution is balanced, scheduling flexibility and controllability are enhanced, resource and energy consumption cooperative adjustment is realized through environment load evaluation, operation stability and environment adaptability are improved, high efficiency and continuous optimization of an order flow are realized, and processing capability and operation toughness of a system under high concurrency are enhanced.