112 results about "Process safety" patented technology

The invention discloses an industrial area atmospheric environment monitoring management system and method, and relates to the technical field of industrial Internet of Things environment monitoring, and the method comprises the steps: triggering polarization imaging to scan a target region based on the time-space information of an abnormal event signal, obtaining the polarization characteristic data of a pollution plume, and generating a spatial distribution characteristic parameter; inputting the sound pressure abnormal indexes and the spatial distribution characteristic parameters into an industrial equipment leakage causal model, calculating a pollution source confidence coefficient, and when the pollution source confidence coefficient reaches a process safety dynamic threshold value, obtaining an industrial equipment traceability result and a leakage level; according to the traceability result of the industrial equipment and the leakage level, a hierarchical control instruction is obtained, meanwhile, the actually measured attenuation rate of the industrial pollutants is calculated, and the dynamic response effect is verified; according to the method, cross-modal fusion modeling is carried out on acoustic abnormal information and pollutant spatial distribution characteristics, so that the technical limitation that pollution source positioning is carried out by depending on a static empirical formula traditionally is broken through.

The invention discloses a multi-mode-based hidden danger identification monitoring early warning method and system, and belongs to the technical field of risk early warning, and the method specifically comprises the steps: collecting related data of a chemical production region, including chemical production related data and personnel related data, judging whether a physical cause causing personal injury exists or not based on a preset process safety critical value, if so, generating a three-dimensional dynamic danger potential field based on chemical production related data, generating a personnel movement track based on personnel related data, mapping the personnel movement track to the three-dimensional dynamic danger potential field, generating a multi-modal knowledge graph, and performing multi-modal mapping on the multi-modal knowledge graph; the method comprises the following steps: acquiring a multi-modal knowledge graph, performing causal reasoning on a path in the multi-modal knowledge graph, generating an early warning signal when a reasoning result shows that a personnel gathering behavior and a physical cause have convergence, and outputting the early warning signal; based on multi-dimensional information evolution prediction, a traceable causal chain can be generated when the hidden danger is still in the initial stage, and the accuracy and advancement of early warning are remarkably improved.

The invention discloses a process monitoring method for an abnormal operation state in a safe water treatment process. The method comprises the following steps: firstly, segmenting original data from the dimension of time by adopting a sequential division method, and standardizing the interiors of blocks; then, a multi-scale feature extraction network is adopted to extract restrictive multi-scale spatio-temporal features from spatial dimensions by adding network function independence and information diversity constraints; and a deep stationary subspace network is established, and decoupling of stationary and non-stationary features is realized by applying difference constraints to network output features. And finally, constructing a process state change statistic by using the non-stationary features, performing data reconstruction by using the stationary features reflecting the process equilibrium state, constructing a statistic of a residual space, and completing process monitoring of the non-stationary process. According to the method, non-stationary faults influencing process safety and stationary faults caused by process mechanism abnormity can be effectively identified, and the method has high practical application value and effectiveness.

The invention relates to the technical field of industrial process control, and discloses a digital twinning-based fermentation process temperature adaptive control system, which comprises a data acquisition and state representation module, a probability generation type digital twinning module, an adaptive risk management module, an opportunity constraint model prediction control module and a model iteration trigger module, according to the method, probability distribution of future states is predicted by constructing probability generation type digital twinning, and the uncertainty of the model is quantified in real time; the system can dynamically adjust the risk tolerance, drives the chance constraint model prediction controller, seeks an optimal control solution on the premise of ensuring the process safety probability, triggers the model adaptive update by means of an online evaluation mechanism, and realizes the optimal control solution on the basis of effectively managing the process uncertainty. The fermentation temperature is subjected to high-performance self-adaptive control considering safety and economy, and the problem that a traditional deterministic model is insufficient in control robustness is solved.

The invention discloses a false data injection and concealment inspection method, system and equipment for safety testing of a process industrial system, and belongs to the technical field of industrial control system automatic monitoring and process safety. The problem that safety testing and safety protection drilling are not comprehensive in safety detection of a process industrial system is solved. According to the method, historical data and online measurement data collected in an industrial process are analyzed, an attack vector is designed, a data sequence is generated by utilizing an online self-adaptive updating strategy, and then the data sequence is injected into an industrial control system running in real time. The state of the controlled system deviates from an expected value on the premise of not causing the detection system to generate additional alarm. According to the method, whether data injection has concealment or not is detected online, and whether the data injection is still valid or completely invalid or not can be judged from the perspective of defense of system security testing. The method is used for safety testing and safety protection drilling in safety detection of a process industry system.

The invention is applicable to the field of exhaust control, and discloses an exhaust control method, system and device and a medium, the method comprises the following steps: acquiring exhaust operation state data to obtain a historical data set; a predicted pressure value is obtained by combining the historical data set with the weighting factor and adopting a weighted moving average prediction model; obtaining a predicted pressure change rate through the predicted pressure value, and comparing the predicted pressure change rate with a preset threshold value to obtain an exhaust triggering condition; on the basis that the exhaust triggering condition is met, exhaust parameters are generated through a digital twin simulation model, and exhaust is executed according to the exhaust parameters; based on the pressure value and the sealing state in the exhaust process, the exhaust state is judged in combination with the recovery threshold value, and an execution instruction is obtained; and exhaust abnormity detection is carried out based on the execution instruction to complete exhaust control, the process safety is guaranteed, whole-process data are recorded and uploaded, an exhaust closed loop is realized, and the accuracy, stability and safety of exhaust control are improved.

The application discloses a hidden danger identification monitoring and early warning method and system based on multi-modal, and belongs to the technical field of risk early warning. The method specifically comprises the following steps: collecting relevant data of a chemical production area, including chemical production related data and personnel related data; judging whether there is a physical inducement causing personnel injury based on a preset process safety critical value; if there is, generating a three-dimensional dynamic danger potential field based on the chemical production related data; generating a personnel motion trajectory based on the personnel related data; mapping the personnel motion trajectory to the three-dimensional dynamic danger potential field; generating a multi-modal knowledge graph; and performing causal reasoning on the path in the multi-modal knowledge graph. When the reasoning result shows that the personnel gathering behavior and the physical inducement exist convergence, an early warning signal is generated, and the early warning signal is output. The application can generate a traceable causal chain when the hidden danger is still in the initial stage based on multi-dimensional information evolution prediction, and significantly improves the accuracy and advance nature of early warning.

The invention relates to the field of safety monitoring, and particularly discloses a calcium formate production process safety monitoring method and system, which utilize a distributed control system to collect original production data, and ensure time consistency of all monitoring variables through data synchronization processing, thereby laying a foundation for subsequent analysis. Thirdly, performing feature engineering processing on the synchronized data, extracting features such as short-term and medium-term change rates, moving average values and standard deviations of temperature, pressure and stirrer current, constructing state features of the reaction kettle, and capturing dynamic operation information of the system; in order to predict potential risks, a trend prediction model based on deep learning is adopted, a historical temperature sequence is converted into a future temperature trajectory, and prospective pre-judgment on the temperature trend is provided; meanwhile, the current system health condition is evaluated in combination with a state recognition model, the risk level is determined through a decision tree model according to the abnormal score and the predicted temperature maximum value, and graded early warning is achieved.

The invention discloses a self-reaction substance drying process safety assessment and classification method based on thermal analysis kinetics. The method comprises the following steps: performing a multi-heating-rate programmed heating test on a self-reaction substance under a closed condition by adopting DSC to obtain an exothermic initial temperature, a peak temperature and a specific exothermic quantity, constructing a thermal decomposition kinetic model based on the obtained data, and solving kinetic parameters such as apparent activation energy and pre-exponential factors; combining an energy conservation equation and a thermal explosion theory, predicting a self-accelerated decomposition temperature SADT under an adiabatic condition TD24 and a given filling and heat dissipation condition, determining a temperature safety threshold value of a drying process according to the SADT, and dividing a working condition safety interval; further introducing three dimensionless safety factors including a temperature safety margin, a time safety margin and a thermal explosion margin, constructing a comprehensive risk index, and carrying out risk grade division on the drying working condition. The method provided by the invention has the advantages of low sample consumption, simple test conditions and standardized calculation process, can quantitatively evaluate the safety drying temperature upper limit of different self-reaction substances and under different process conditions, and provides a reliable basis for drying process design and safety control of the self-reaction substances.

The invention discloses a hydrogen concentration measurement method based on a multi-mode sensor, and relates to the technical field of gas detection and industrial process safety monitoring. Hydrogen sensors based on different physical principles are introduced in the same measurement link, and environmental variables such as temperature, humidity, pressure and the like and sensor output are collected together; a multi-dimensional feature is formed after normalization and time alignment, and then fusion is performed by using a weight adaptive to the change of an environment, so that instantaneous errors generated by a single sensor due to temperature drift, wet drift or pressure fluctuation are shared or suppressed, and the stability and repeatability of a fusion result are improved; furthermore, a cross sensitivity compensation module arranged before fusion identifies response differences between hydrogen and interference components such as carbon monoxide and methane by using a machine learning model obtained by training under a multi-gas mixing working condition, and the probability of false signals and false alarms caused by coexisting gas is reduced on the premise that a special detection channel is not added.

The invention relates to a communication engineering full-process safety production risk dynamic assessment method, in particular to the technical field of communication engineering, and effectively overcomes the hysteresis quality and one-sidedness of a traditional static assessment method. According to the method, real-time data stream processing and an online learning mechanism are fused, continuous perception and quantitative evaluation of safety production risks are realized, short-term sudden risk response and long-term law research and judgment can be intelligently balanced, the timeliness of risk early warning and the accuracy of decision support are remarkably improved, the engineering field safety management and control capability is enhanced, and the engineering field safety management and control efficiency is improved. The occurrence probability of safety accidents is reduced.

The invention discloses a plastic woven bag production process safety monitoring system, and relates to the technical field of plastic woven bag production safety, and the system comprises a dust concentration sensor module, a temperature and humidity sensor module, a harmful chemical gas concentration sensor module, a smoke sensor module and an electrostatic monitoring sensor module through an integrated detection module. The monitoring camera and the integrated controller module are used for realizing all-directional and real-time monitoring of a production workshop; potential safety hazards such as fire disasters and dust concentration exceeding standards can be automatically identified and warned; meanwhile, the system has remote control and data transmission functions, monitoring data can be transmitted to a control center in real time, information support is provided for managers, and the safety monitoring system effectively improves the safety in the production process of the plastic woven bags, reduces the occurrence risk of safety accidents and has wide application prospects and popularization value.

The invention relates to ultrasonic-assisted equipment for preparing sodium ferrate from red mud, which comprises a reaction kettle, a heating plate, a vibrating plate, a red mud alkaline leaching residue slurry storage tank, a sodium hypochlorite storage tank, a temperature measuring element and a stirrer device, and is characterized in that the heating plate and the vibrating plate are sequentially arranged at the bottom of the reaction kettle, and the heating plate is attached to the bottom of the reaction kettle; an ultrasonic vibration head is arranged at the bottom of the vibration plate; the temperature measuring element is arranged on the reaction kettle through a connecting piece, and a temperature measuring probe of the temperature measuring element extends into the reaction kettle; the stirrer device is arranged above the reaction kettle through a fixed bracket, and a stirring rod of the stirrer device extends into the reaction kettle; the red mud alkaline leaching residue slurry storage tank is communicated with the red mud alkaline leaching residue slurry inlet; and the sodium hypochlorite storage tank is communicated with the sodium hypochlorite feeding hole. The sodium ferrate prepared by the method is high in concentration, high in generation rate and high in process safety, and ultrasonic equipment is simple in structure and low in cost.

A method includes receiving multiple security framework requirements, mapping the security framework requirements to a predicate, mapping the predicate to a system-specific implementation, evaluating, using a runtime system, the target system by analyzing a multitude of build files using the system-specific implementation, and presenting a report indicating whether the security framework requirements are satisfied.

The utility model discloses a portable filter pressure relief observer which comprises a sight glass, and a one-way valve is arranged at an outlet of the sight glass to prevent oil from flowing backwards. A portable emptying valve is arranged at the bottom of the sight glass, so that timely emptying after pressure relief of the filter is facilitated, and next observation is not affected. The problems that an existing sight glass is not tight in sealing, glass is fragile, oil flows backwards and maintenance is difficult are solved, and the process safety and the convenience of equipment maintenance are improved.

The present invention introduces a zoning disposal method for tailings pond closure, which divides the beach surface into coarse sand area, soft beach area, and clear area-water area at the tail of the reservoir in sequence from the front of the dam body to the tail of the reservoir. The disposal method of the present invention can quickly and safely complete the reinforcement disposal of the soft beach of the tailings pond, complete the closure of the reservoir surface within a specified time, and provide a high-bearing capacity, low-compressibility, and low-water content working platform for subsequent greening after the closure of the reservoir; and for the tailings pond that still uses the original drainage well at the tail of the reservoir to discharge floodwater after closure, it not only effectively guarantees the progress, quality and process safety of the closure of the soft beach, but also ensures that the overall slope of the beach surface after closure is consistent with the design, which is beneficial to flood control and flood discharge safety after closure, and greatly reduces the consumption of closure covering soil.

The invention provides a virtual power plant peak regulation-oriented sewage plant safety capacity scheduling method and device. The method comprises the following steps of: carrying out load-process dynamic coupling modeling; after the peak regulation task is received, calculating the maximum power regulation quantity which can be safely executed in the response time window Twin under the current working condition for each load object; in the day-ahead plan scheduling, the power adjustment starting time of the load object is advanced to be before the response time window Twin, and the declarable capacity is planned according to the maximum technical adjustment power; in intra-day scheduling, all Pdisgt are aggregated; and forming a safe schedulable resource pool by the load objects of 0, carrying out load object combination optimization and generating a scheduling instruction. The method has the advantages that under the given peak regulation task of the power grid, the safety capacity delta Pmax of each load object in the sewage plant under the current working condition is calculated and determined in real time, safety dispatching is achieved based on the safety capacity delta Pmax, and the problems of uncredibility of dispatching instructions and process safety risks are solved.

The invention relates to a gas phase chemical reaction heat measurement system and method based on a heat flow method calorimeter (RC1e type). An inert medium and a small gas phase reactor are additionally arranged in a reaction kettle of an original heat flow method calorimeter, a gas raw material is introduced into the gas phase reactor for reaction, and heat released by the reaction is transferred to a calorimetric system through the inert medium for real-time monitoring. The method solves the problem that a traditional heat flow method calorimeter cannot directly measure gas-gas reaction heat, the application range of the calorimeter is expanded, and the method is suitable for gas-phase reaction thermodynamic research and process safety evaluation under high-temperature and high-pressure conditions.

The invention discloses a pilot operated safety valve state monitoring method and device with helium online leakage detection, and relates to the technical field of industrial process safety and equipment state monitoring, and the method comprises the steps: installing a microcavity leakage collection module on a to-be-detected pilot operated safety valve, connecting a helium online analysis subsystem and a tracing gas source through a pipeline, and carrying out the detection of the helium online leakage detection of the to-be-detected pilot operated safety valve; starting a vacuum pump set to vacuumize to a working vacuum degree; pure nitrogen is introduced to eliminate background helium, sampling analysis is performed after an interface is closed, and a helium background signal is recorded as a base line; low-concentration helium mixed gas is injected at a controlled speed, a tracing environment is constructed, and helium concentration, pressure and temperature multi-dimensional time sequence data are synchronously collected and preprocessed; inputting the data into a composite artificial intelligence model to judge a leakage state and divide alarm grades; the leakage rate is analyzed, the remaining life is calculated, monitoring information is uploaded to an upper-layer system, multi-channel notification is triggered, and monitoring is completed. Through the helium mass spectrum and the edge AI technology, accurate real-time monitoring is achieved, and the problem of off-line lag misinformation is solved.

The invention discloses a method for continuously preparing a pore-forming agent H by using a dynamic tubular reactor, and relates to the technical field of preparation of pore-forming agents H. The method comprises the following steps: material preparation, equipment preparation, nitration reaction, parameter control and obtaining of a crude product; compared with a stirring reactor, the dynamic tubular reactor has remarkable advantages, the heat effect treatment capacity is improved, the mixing capacity is enhanced, and the operation window is larger, so that a safer, more efficient, more stable and more sustainable synthesis production process can be developed; the benefits brought in production are not limited to improvement of the process safety, but also implementation of a more efficient and lower-cost process, so that the downstream processing cost and the labor cost are reduced; when the pipe length of the dynamic tubular reactor is far greater than the pipe diameter and the material system is in a turbulent flow state, the equipment is close to ideal plug flow, the material flows forwards like a piston, different paddle forms are matched, interfacial tension is overcome by means of high turbulence, and small-scale macromixing is realized.

The present application relates to the field of anti-falling monitoring, and more particularly to a real-time monitoring response method and platform for an anti-falling device. The method comprises the following steps: continuously collecting information about workers based on the anti-falling device to generate a baseline sequence of working states; calculating a real-time falling rate peak value of the baseline sequence of working states; comparing the real-time falling rate peak value with a preset safety falling threshold value; when the real-time falling rate peak value is greater than a first-level safety falling threshold value, activating a slow locking mechanism of the anti-falling device; and when the real-time falling rate peak value is greater than a second-level safety falling threshold value, activating an emergency locking mechanism of the anti-falling device. The present application actively intervenes in high-altitude workers and provides full-process safety protection, thereby improving the continuity and safety of high-altitude work.

The present application relates to the technical field of biomass mixed coal combustion, and discloses a safety system for bamboo reed biomass mixed coal pulverization. The system is composed of a bamboo reed biomass raw material attribute detection module, a mixed coal proportion self-adaptive regulation and control module, a combustion environment multi-source sensing module, a safety risk quantitative evaluation module and a control strategy dynamic generation module, and the modules are connected through a data flow pipeline. The raw material attribute detection module collects water content fluctuation data and particle morphology characteristic sequences in real time; the mixed coal proportion regulation and control module calculates mixed coal ratio adjustment amount accordingly; the combustion environment sensing module synchronously obtains combustion chamber temperature field change trajectory and flue gas composition concentration time series data; the safety risk evaluation module integrates the above temperature, flue gas and ratio data to generate risk probability distribution; and the control strategy generation module analyzes the risk distribution and outputs an instruction sequence for driving an execution mechanism. The present application realizes whole-process safety monitoring and dynamic regulation and control from raw material characteristics to combustion state.

The application discloses an industrial area atmospheric environment monitoring management system and method, relates to the technical field of industrial internet of things environment monitoring, and comprises the following steps: triggering polarization imaging to scan a target area based on the space-time information of an abnormal event signal, acquiring polarization characteristic data of a pollution plume, and generating a spatial distribution characteristic parameter; inputting a sound pressure abnormality index and the spatial distribution characteristic parameter into an industrial equipment leakage causal model, calculating a pollution source confidence, and acquiring an industrial equipment traceability result and a leakage level when the pollution source confidence reaches a process safety dynamic threshold; acquiring hierarchical control instructions according to the industrial equipment traceability result and the leakage level, calculating a measured attenuation rate of an industrial pollutant, and verifying a dynamic response effect; and the application breaks through the technical limitation of traditional pollution source positioning depending on static empirical formulas by cross-modal fusion modeling of acoustic abnormal information and pollutant spatial distribution characteristics.

The utility model relates to the field of chemical engineering automatic control equipment, in particular to a vinylamine reactor outlet pneumatic control valve assembly which comprises a pneumatic high-pressure adjusting angle valve A and a pneumatic high-pressure adjusting angle valve B which are arranged in parallel, and two process valves are respectively connected in series in front of and behind the pneumatic high-pressure adjusting angle valve A and the pneumatic high-pressure adjusting angle valve B; and the controller is electrically connected with the pneumatic high-pressure adjusting angle valve A and the pneumatic high-pressure adjusting angle valve B and is used for switching the pneumatic high-pressure adjusting angle valve A and the pneumatic high-pressure adjusting angle valve B. The utility model has the following beneficial effects: the technical scheme is simple in process, saves a flash tank, a pipeline and auxiliary instruments and facilities, optimizes the field operation layout, and improves the production efficiency. Maintenance is safe, control means are increased, the service life of control is prolonged, maintenance cost is saved, operation can be carried out in an emergency state, and process safety is guaranteed.

The application discloses a kind of dangerous chemical enterprise area dynamic process safety risk grading early warning method, and the application relates to safety management technical field, wherein including: obtaining the regional process safety data and safety risk element index system of dangerous chemical enterprise;According to regional process safety data, safety risk element index system and preset risk possibility rule table, determine the regional dynamic risk possibility grade of dangerous chemical enterprise;The inherent risk grade of the region of the dangerous chemical enterprise is evaluated, and according to the inherent risk grade of the region, determine the regional basis consequence grade of dangerous chemical enterprise;Based on the regional dynamic risk possibility grade, the regional basis consequence grade and preset regional risk grade evaluation matrix, risk grading dynamic early warning is carried out, and the regional risk grade of the dangerous chemical enterprise is obtained.The application can reflect the process safety risk grade in actual production process, ensure the real-time of process safety risk early warning.

The invention discloses a safety control system and method for a methanol production process, relates to the technical field of production control, and solves the technical problems that threshold judgment is singly carried out on data, potential threats in the production process are not deeply analyzed, and production safety cannot be guaranteed. Through cooperation of the equipment parameter acquisition unit and the production safety analysis unit, equipment working data can be accurately acquired and compared with preset parameters, whether the production process is normal or abnormal is clearly judged, a basis is provided for subsequent analysis, and the normal production analysis unit performs periodic continuous monitoring and risk index calculation on normal results, so that the production safety is improved. Through combination of historical data, potential risks can be found in advance, the safety of the production process in a state similar to a normal state is guaranteed, accidents caused by accumulation of the potential risks are avoided, and when a production abnormality analysis unit faces an abnormal result, the influence of abnormality on production is reduced by deeply analyzing the relation between abnormal data and associated parameters and generating regulation and control information.

The embodiments of the present application relate to the technical field of automatic control of multiple regulating valves in fluorine chemical industry, and provide a method and system for automatic control of multiple regulating valves in fluorine chemical industry to solve the problems of low efficiency and poor safety in the automatic control of multiple regulating valves in fluorine chemical industry in the prior art. Among them, based on the Markov decision process, the optimal operating conditions under the current fluorine chemical production conditions are evaluated and the optimal operating conditions are predicted; based on the process safety limit and the product quality target, an ideal opening adjustment scheme is generated, and the pulse width modulation control instruction is sent to the actuator of the corresponding multiple regulating valves in fluorine chemical industry through the industrial communication bus to obtain the actual valve control strategy of the multiple regulating valves in fluorine chemical industry; the difference between the actual effect and the expected effect is compared to obtain an improved control strategy; the control strategy is continuously optimized according to the experience accumulated by the improved control strategy. The technical solution provided by the embodiments of the present application can improve the efficiency and safety of the automatic control of multiple regulating valves in fluorine chemical industry.

The invention belongs to the technical field of organic synthesis and fine chemical engineering, and particularly relates to a method for continuously synthesizing 2, 5-dimethoxy-4-nitrochlorobenzene. A continuous flow reaction system is adopted, 2, 5-dimethoxychlorobenzene and 75%-78% nitric acid are pumped into the system respectively, mixed and then enter a silicon carbide microchannel reactor, an initial reaction is carried out at the temperature of 40-60 DEG C, then the mixture enters a coil delay microreactor at the temperature of 50-70 DEG C to complete nitration, and the total retention time is 20-80 seconds. According to the method disclosed by the invention, accurate temperature control on the strong exothermic nitration reaction is realized through enhanced mixing and heat transfer of the microreactor, concentrated sulfuric acid does not need to be added, the reaction can be completed within tens of seconds, the raw material conversion rate is high (the residue is less than or equal to 0.13%), the product selectivity is good (the content is more than or equal to 98.33%), and the production efficiency and the process safety are remarkably improved; the method is suitable for green, efficient and continuous production of the intermediate, realizes accurate monitoring, and is suitable for large-scale safe production.

The invention relates to the technical field of process safety and explosion prevention, in particular to a graded explosion suppression-explosion venting control method and system based on dynamic pressure characteristics. The method comprises the steps of information collection and preprocessing, dynamic feature extraction, feature parameter normalization, dynamic weight distribution, comprehensive risk index calculation, execution of a corresponding grading response strategy and degradation and revocation control. Through multi-feature fusion, a dynamic weight, a nonlinear saturation function and a hierarchical trigger mechanism with hysteresis, the explosive risk assessment is fundamentally converted from static and single states to dynamic and comprehensive states, and the prevention and control response spans from isolation and extensive states to collaborative and fine states. Finally, an intelligent explosion-proof system which is high in sensitivity, low in false alarm rate, self-adaptive and reversible is constructed, and the safety protection level of the combustible gas container under various complex working conditions is remarkably improved.

The present application relates to a kind of PID controller parameter online optimization method based on reinforcement learning and RBF neural network, storage medium and control system, the method includes: in the actual control system of the chemical process deployment trained reinforcement learning intelligent agent, the reinforcement learning intelligent agent is based on Actor-Critic framework and RBF neural network construction;Real-time acquisition chemical process original data, and transform into state vector for inputing the reinforcement learning intelligent agent, output obtains the optimal adjustment amount of PID controller parameter;Wherein, the state space of the reinforcement learning intelligent agent includes the process variable of the chemical process, action space is defined as the adjustment amount of PID controller parameter, reward function is the composite function of fusion tracking error, overshoot, control action change rate and process safety constraint.Compared with prior art, the present application has the advantages of significantly improving the adaptive ability and control precision of control system.