CN-121979160-A - Efficient intelligent chemical engineering regulation and control system

CN121979160ACN 121979160 ACN121979160 ACN 121979160ACN-121979160-A

Abstract

The invention relates to the technical field of industrial automation and intelligent manufacturing, in particular to a high-efficiency intelligent chemical regulation and control system, which aims to solve the problem of pain in the whole process production of chemical industry and realize stable control of production parameters and process optimization and upgrading. The system comprises a raw material research end, a process simulation module, an automatic acquisition end, a quality control feedback module and a technical training end, wherein the five core modules are subjected to cross-technology fusion and full-link collaborative design, and a closed-loop intelligent system of 'set value driving-full-flow precise regulation' is constructed. The system is adapted to a chemical full-scene production unit, effectively solves the problems of short plates produced in the prior art, has the advantages of real-time monitoring, dynamic optimization, good expansibility and the like, is suitable for full-flow intelligent upgrading of production in industries such as chemical industry, energy source, environmental protection and the like, and has wide application prospect.

Inventors

YANG JIARUI
FENG YANWEN
GUO XIANGLI
TANG MENG
HUANG ZHIHUI
WANG RUINAN
LI JIALE
PENG JIAJUN
DING MANMAN

Assignees

天津市职业大学

Dates

Publication Date: 20260505
Application Date: 20260323

Claims (10)

1. An efficient intelligent chemical regulation system, comprising: The raw material analysis end (Source) is used for analyzing physical and chemical characteristics of raw materials and intelligently processing data, and adopts a frequency division interferometry technology and a deep learning neural network algorithm to realize stable continuous transmission and accurate analysis of raw material data, provide data support for whole-flow production optimization and solve the problem of insufficient accuracy of traditional manual experience matching; The process simulation module (Model) is based on a wireless network and a wired control heterogeneous fusion architecture, adopts an industrial digital twin technology to carry out multi-physical field coupling simulation and dynamic optimization on a production process, supports smooth transition from a manual control mode to semi-automatic control, can accurately output a set value optimization solution set comprising a process parameter threshold value, an equipment operation strategy and an energy consumption optimization scheme for at least 20 typical industrial scenes, and adapts to the production requirements of chemical multi-working conditions; The automatic acquisition end (Auto) has the function of automatically acquiring multi-source heterogeneous data, adopts a distributed sensor network architecture, configures five adjustable acquisition rates, and realizes high-precision time sequence data acquisition and fusion processing; The quality control feedback module (Reback) comprises a multi-variable cooperative control subsystem of flow, pressure, temperature and the like, adopts CCON (continuous control optimization algorithm) and SLPCON (cascade predictive control algorithm), combines a real-time trend analysis and visualization technology, realizes intelligent diagnosis and dynamic compensation of abnormal working conditions, effectively avoids false alarm of missing report, has self-adaptive adjustment capability of production environment, and ensures stable tracking of parameters; And the technical training end (Train) is used for constructing a real operation system combining the normalized field training and the VR virtual simulation, adopting a distributed data storage architecture, and realizing technical capability systematic precipitation and iteration through a knowledge graph and a skill matrix. And (3) carrying out dedicated field training of chemical industry for at least 12 times each year, wherein the VR scene restoration degree is more than or equal to 95%, the core skill period of new staff is shortened to 3 months, and the manpower training cost of enterprises is reduced.
2. The efficient intelligent chemical regulation and control system according to claim 1, wherein the sampling frequency of the frequency division interferometry technology of the raw material research end (Source) is 10-50Hz, the deep learning algorithm integrates two modes of supervised learning and unsupervised learning, the data transmission delay is less than or equal to 50ms, and the raw material characteristic identification accuracy is more than or equal to 98%.
3. The system of claim 1, wherein the wireless network of the process simulation module (Model) adopts 5G or Wi-Fi 6 technology, the wired control adopts industrial ethernet protocol, the multi-physical field coupling simulation error rate is less than or equal to 3%, and the process parameter threshold, the equipment operation strategy and the energy consumption optimization scheme of not less than 20 typical industrial scenes can be output.
4. The high-efficiency intelligent chemical engineering regulation system according to claim 1, wherein the annual acquisition precision of the automatic acquisition end (Auto) is better than 10 mm/year, the switching time of the five-gear acquisition rate (riveting speed, medium speed, fast speed, high speed and extremely fast) is less than or equal to 200ms, the acquisition frequency in the extremely fast mode is more than or equal to 100Hz, and the full-link data consistency error is less than or equal to 0.5 percent through a Kalman filtering algorithm and a data consistency verification mechanism.
5. The efficient intelligent chemical regulation and control system according to claim 1, wherein the flow control precision of the quality control feedback module (Reback) is +/-2%, the pressure control precision is +/-0.5 kPa, the temperature control precision is +/-1 ℃, the abnormal working condition identification response time is less than or equal to 10ms, and the dynamic response time of key parameters such as the quenching oil temperature is less than or equal to 10 seconds.
6. The system of claim 1, wherein the technical training terminal (Train) performs at least 12 on-site training operations each year, and the VR virtual simulation system supports process fault diagnosis and emergency treatment scenerisation training, and the training data storage period is not less than 5 years, and the knowledge graph and skill matrix support technical ability quantitative assessment and iteration.
7. The system of any one of claims 1-6, further comprising a multi-channel alarm module, wherein the alarm response time is less than or equal to 10 seconds, abnormal alarm information can be pushed through a small program, a workgroup, a mailbox and other multi-channel channels, the monitoring precision meets the requirements of + -5% of helium consumption, + -3% of water consumption and + -2% of electricity consumption, and dynamic threshold setting based on historical data is supported.
8. The high-efficiency intelligent chemical engineering regulation system according to claim 7, further comprising a data storage and analysis module, wherein the storage capacity can be expanded to PB level by adopting a distributed database technology, the system has a data visualization function and custom instrument panel configuration, and real-time analysis and mining of production data, analog data and alarm data are supported.
9. The efficient intelligent chemical engineering regulation system according to claim 8, wherein the system adopts a modularized design, each module realizes data interaction through a standardized interface, supports hot plug upgrade, and can stably operate in an environment with the overall reliability MTBF of more than or equal to 10000 hours at-20 ℃ to 60 ℃ and the relative humidity of less than or equal to 95% (without condensation).
10. A high-efficiency intelligent chemical engineering regulation system, characterized by comprising the high-efficiency intelligent chemical engineering regulation system according to any one of claims 1 to 9.

Description

Efficient intelligent chemical engineering regulation and control system Technical Field The invention belongs to the technical field of industrial automation and intelligent manufacturing, and particularly relates to a high-efficiency intelligent chemical regulation and control system. The system focuses on the production scene of the whole process in the chemical industry, adapts various core production units such as a reaction device (a reaction kettle, a reactor and the like), separation equipment (a tower device, a centrifugal machine and the like), a fluid conveying system, heat exchange equipment, a storage device and the like, and realizes the accurate control of parameters, the dynamic optimization of the process, the early warning of safety risks and the sedimentation of operation skills of the whole process of the chemical production through the cooperative operation of five core modules. Background In the deep digital transformation process of the chemical industry, enterprises face industry common challenges such as insufficient security risk prevention and control accuracy, extensive overall process energy consumption and cost management and control, insufficient release of fusion value of multi-source heterogeneous data, delayed dynamic optimization response of process parameters and the like. The traditional chemical management and control system has the following core bottlenecks in the technical architecture and the practical application performance level. 1. The raw material-process suitability is insufficient, the traditional production relies on manual experience to match the raw material characteristics and process parameters, and the accurate analysis means for the key characteristics of raw material components, viscosity, reactivity and the like are lacking. When the characteristics of the raw materials fluctuate, the problems of insufficient reaction, substandard product purity, sudden increase of energy consumption and the like are easily caused by the cooperative unbalance of multiple devices, and the cross-scene parameter adjustment period is long and the adaptability is poor. 2. The full-flow simulation precision and dynamic response are deficient, the existing simulation technology is mostly single physical field simulation, the error rate is more than 10%, and complex working conditions of multi-equipment linkage cannot be accurately re-carved. When the load fluctuation (> 20%) is faced, the response time of the conventional regulation and control system reaches more than 90 seconds, the overshoot is more than 15%, the real-time optimization of the process parameters is difficult to realize, a digital twin real-time iteration mechanism is lacked, and the potential safety risk cannot be prejudged. 3. The data acquisition precision and timeliness are both lost, that is, a traditional sensing device adopts a single-point measurement architecture, the annual precision is less than 50 mm/year, and a 4-20mA transmission protocol limits the data refreshing frequency to 1Hz, so that instantaneous anomalies such as sudden pressure rise and sudden fluid flow velocity change of the tower equipment cannot be captured. The data fusion delay of the multi-source equipment is more than 30 seconds, the data distortion causes misjudgment of regulation and control decisions, and hidden danger is caused in production safety burial. 4. The quality control feedback system is fragmented, the traditional controller-upper rack is formed into a data island, and a multi-parameter cooperative control mechanism such as flow, pressure, temperature and the like is lacked. And the single PID regulation is relied on, the abnormal working condition identification is delayed, the false alarm rate of the missing report reaches 15%, the fault positioning time is over 72 minutes on average, and burst problems such as collapse, liquid leakage and flooding are difficult to rapidly treat. 5. The technical training and the actual operation are disjoint, namely that in the traditional 'engineer with bare' mode, the new staff takes an on duty period as long as 8 months, and the high-risk abnormal scene cannot be simulated. The conventional VR training has the defects of large physical engine error, insufficient coverage of a fault library and the like, and the technical capability precipitation lacks a systematic mechanism, so that the method is difficult to adapt to the operation and emergency requirements of a full scene. Along with the deep fusion of industry 4.0 and intelligent manufacturing, the chemical industry puts forward higher requirements on the precision, the synergy and the intellectualization of the whole-process production control, and a high-efficiency intelligent chemical regulation system integrating the accurate research and analysis of raw materials, the dynamic simulation of the process, the accurate perception of multi-source data, the cooperative regulation of all parameters and the training of a