CN-115270473-B - Digital twinning-based RTO intelligent monitoring and diagnosis method

CN115270473BCN 115270473 BCN115270473 BCN 115270473BCN-115270473-B

Abstract

The invention relates to an RTO intelligent monitoring and diagnosing method based on digital twinning, which comprises the steps of firstly collecting data including running data, size information and maintenance records of RTO, establishing a multi-dimensional database, carrying out structural analysis and functional analysis on the RTO based on the database, carrying out RTO mechanism model construction and RTO data driving model construction to obtain a digital twinning module aiming at the RTO, secondly simulating the internal running state of the RTO according to the digital twinning module of the RTO obtained in the first step, realizing real-time monitoring and diagnosing of the running state of the RTO, thirdly connecting the simulated internal running process to AR glasses, realizing visual analysis, and adopting corresponding security decisions based on visual analysis results. The invention can prevent the RTO parts from being damaged, even the furnace shutdown and explosion accidents caused by the fact that part of parameters exceed a reasonable range, and ensure the stable and safe operation of RTO equipment.

Inventors

GAO XIANG
ZHOU CAN
WU WEIHONG
ZHANG YOU
ZHANG YONGXIN
Fang Tiegen
HAN SHANGBO
ZHENG CHENGHANG
YAO LONGCHAO
HUA YI
YU YUEKAI
HU TENG
YANG JIAN

Assignees

浙江大学
浙江大学
浙江大学嘉兴研究院
浙江大学嘉兴研究院

Dates

Publication Date: 20260421
Application Date: 20220801
Priority Date: 20220801

Claims (7)

1. The intelligent monitoring and diagnosing method for the regenerative incinerator based on digital twinning is characterized by comprising the following steps of: step one, collecting data including operation data, size information and maintenance records of a heat accumulating type incinerator, establishing a multi-dimensional database, carrying out structural analysis and functional analysis on the heat accumulating type incinerator based on the database, and constructing a mechanism model of the heat accumulating type incinerator and a data driving model of the heat accumulating type incinerator to obtain a digital twin module aiming at the heat accumulating type incinerator; Step two, simulating the internal operation state of the heat accumulating type incinerator according to the digital twin module of the heat accumulating type incinerator obtained in the step one, so as to realize real-time monitoring and diagnosis of the operation state of the heat accumulating type incinerator; step three, connecting the simulated internal operation process to the AR glasses, realizing visual analysis, and adopting corresponding security decisions based on visual analysis results; the method for constructing the mechanism model of the regenerative incinerator comprises the following steps: (a) Acquiring size information and bearing functions of each component of the heat accumulating type incinerator based on a heat accumulating type incinerator database; (b) Establishing a mathematical equation set between key parameters and measurable variables from physical and chemical rules in the production process of the heat accumulating type incinerator through structural analysis and functional analysis of the heat accumulating type incinerator, wherein the physical and chemical rules comprise an energy conservation law, a momentum conservation law, a mass conservation law engineering thermodynamic principle, a heat transfer theory, a Newton theorem, a combustion heat equation and a Gaussian law; (c) Based on the mathematical equation set established in the step (b), finishing to obtain a mechanism model describing the production operation process of the heat accumulating type incinerator; The data driving model construction of the heat accumulating type incinerator comprises the following steps: (a) Acquiring size information and bearing functions of each component of the heat accumulating type incinerator and initial quantity of key parameters in operation of the heat accumulating type incinerator based on a heat accumulating type incinerator database; (b) Acquiring parameters which need to be subjected to numerical value output according to the established mechanism model of the heat accumulating type incinerator; (c) Establishing a mathematical expression between the parameters and the key parameters by using a mathematical modeling method, and establishing a functional relationship of the parameters; The mathematical modeling method comprises, but is not limited to, regression analysis modeling, neural network modeling and support vector machine modeling, wherein the key parameters comprise temperature in the operation process of the heat accumulating type incinerator, heat change in the heat accumulating type incinerator, organic waste gas treatment capacity and treatment efficiency, organic waste gas flow, LEL concentration and opening degree of each air inlet valve and air outlet valve in the heat accumulating type incinerator; The method comprises the steps of taking the temperature in the operation process of the heat accumulating type incinerator as a key parameter, establishing a heat balance model in the multi-component complex heat exchange process based on a heat accumulating type incinerator database and a heat accumulating type incinerator heat data model, and calculating the temperature of each section of the heat accumulating type incinerator, wherein the operation of establishing the heat balance model in the multi-component complex heat exchange process comprises the steps of establishing an unknown parameter relation equation through data driving, increasing heat accumulating calculation accuracy through a local heat accumulator microcosmic heat transfer model, and establishing a VOCs complex component mixed combustion equation through regression analysis; the equations for modeling include: The exhaust gas inputs heat: ; the pre-heat bypass provides heat: ; inlet temperature calculation after mixing: ; and (3) calculating the temperature of the gas heated by the heat accumulator: ; Heat of gas heated by the heat accumulator: ; heat generated by combustion of combustible materials in the exhaust gas: ; heat generated by combustion of fuel: ; heat dissipated by the front heat bypass: ; Heat dissipated by the post heat bypass: ; Combustion chamber gas temperature calculation: ; calculating the gas temperature after heat storage by a heat accumulator: ; ; And (3) calculating the gas temperature after post heat bypass: ; wherein, Q in is the heat input by the waste gas; Q pb provides heat for the front-end thermal bypass, Q cb is combustion chamber gas heat, Q ha is gas heat heated by a heat accumulator, Q cmb is heat generated by combustion of combustible substances in exhaust gas, Q fc is heat generated by combustion of fuel, Q fuel is heat input by fuel, Q air is heat input by dilution wind, Q pbo is heat dissipated by the front-end thermal bypass, Q rb is heat dissipated by the rear-end thermal bypass, Q out is heat of output exhaust gas, Q pin is calculated by the inlet temperature after mixing, mu is heat loss rate, rho is exhaust gas density under the standard condition, v in is inlet exhaust gas volume flow under the standard condition, T amb is ambient temperature, T cb is combustion chamber gas temperature, T out is outlet exhaust gas temperature, T in is inlet exhaust gas temperature, v fuel is fuel volume flow under the standard condition, cp ain is average constant pressure capacity after preheating inlet exhaust gas, deltacH fc is low-level heat productivity of fuel, LEL is inlet exhaust gas concentration is actually measured, LEL is LEL concentration is exhaust gas density under the standard condition, v in is inlet exhaust gas temperature is equal to the standard temperature of in , and the inlet exhaust gas temperature is equal to the standard temperature of the lower than the standard temperature of the inlet temperature of the explosion; The average constant pressure specific heat capacity of the inlet exhaust gas; m pb is the front-end thermal bypass exhaust mass flow; Δh cb is the enthalpy change of the exhaust gas heated to the combustion chamber temperature with reference to the temperature; v pb is the pre-heat bypass flow, cp acb is the average constant pressure specific heat capacity of the exhaust gas at the temperature of the combustion chamber, cp apin is the average constant pressure specific heat capacity of the exhaust gas at the temperature of the inlet exhaust gas after being preheated, deltah pin is the enthalpy change of the exhaust gas at the temperature after being preheated by the reference temperature, m pin is the total mass of the exhaust gas after being preheated, eta ha is the heat storage energy recovery efficiency, T min is the temperature after being preheated by the exhaust gas, T ha is the gas temperature after being heated by the heat storage, T cb is the temperature of the combustion chamber, m ha is the total mass of the exhaust gas after being heated by the heat storage, deltah ha is the average constant pressure specific heat capacity of the exhaust gas at the temperature of the gas after being heated by the reference temperature of the exhaust gas after being heated by the heat storage, deltah pin is the enthalpy change of the temperature after being heated by the reference temperature of the exhaust gas after being preheated, deltacH cmb is the low-position heating power of the combustible substance in the exhaust gas after being preheated, v air is the volume flow of the dilution wind, cp acbf is the average constant pressure after being heated by the combustion chamber, T ha is the average constant pressure after being heated by the heat storage temperature of the bypass heat storage, deltaheat storage temperature after being heated by the bypass heat bypass temperature after being heated by the temperature after being equal to 3735 is the average heat storage temperature after being heated by the bypass temperature after being equal to the temperature after being heat by the bypass temperature is equal to the temperature after being heat by the temperature after being heat is equal to the temperature after being heat by the temperature is heat temperature after being the temperature is the temperature heat has the heat is the heat.
2. The intelligent monitoring and diagnosing method for the regenerative furnace based on the digital twin system of claim 1, wherein the operation data comprise, but are not limited to, the content of organic waste gas input into a regenerative chamber before the regenerative furnace operates, the opening degree of each air inlet valve and air outlet valve in the regenerative furnace, the temperature of a combustion chamber, the temperature of a pipeline, the LEL concentration at each valve, the average heat value of the organic waste gas input into the regenerative chamber, and the treatment capacity and the treatment efficiency of the corresponding organic waste gas before the regenerative furnace operates; The size information comprises, but is not limited to, the geometric size of the regenerative incinerator, the geometric size and shape of each component in the regenerative incinerator and the geometric relationship among the components, wherein each component comprises a combustion chamber, a regenerative chamber, a heat accumulator, a front bypass valve, a rear bypass valve, a main waste valve, a fresh air valve, a poppet valve, a combustion air valve, a combustion valve, a main fan, a bypass fan and a combustion fan; the maintenance record comprises a parameter alarm record, a manual inspection record and an equipment account of the heat accumulating type incinerator.
3. The intelligent monitoring and diagnosing method for the heat accumulating type incinerator based on the digital twin system of claim 1, wherein the structural analysis comprises the steps of analyzing size information of the heat accumulating type incinerator to determine components of the heat accumulating type incinerator, the functional analysis comprises the steps of analyzing bearing functions of all components of the heat accumulating type incinerator and coupling relations of all components, 3D MAX, solidworks or AutoCAD is adopted to construct a model during structural analysis, and Matlab or Simulink is adopted to simulate functions of an operation process during functional analysis.
4. The intelligent monitoring and diagnosing method for the heat accumulating type incinerator based on the digital twin system according to claim 1, wherein the second step comprises the steps of monitoring key parameters in the operation process of the heat accumulating type incinerator and diagnosing whether the operation state of the heat accumulating type incinerator is normal.
5. The intelligent monitoring and diagnosing method for the regenerative incinerator based on digital twinning as set forth in claim 1, wherein the third step is as follows: (a) Based on a heat accumulating type incinerator database, constructing a three-dimensional data field of the heat accumulating type incinerator by combining the geometric configuration of the heat accumulating type incinerator and real-time monitoring data of the heat accumulating type incinerator; (b) The three-dimensional data field of the heat accumulating type incinerator is led into the AR glasses; (c) The three-dimensional data field of the heat accumulating type incinerator can be visualized by using AR glasses.
6. The intelligent monitoring and diagnosing method for the regenerative incinerator based on the digital twin system according to claim 1 is characterized in that corresponding safety decisions are adopted, including but not limited to adjusting organic waste gas feeding, maintaining possible fault points, regulating and controlling the temperature range in the operation process of the regenerative incinerator, and timely cutting off the power supply of equipment to stop working.
7. The intelligent monitoring and diagnosing method for digital twin heat accumulating type incinerator according to claim 1, wherein each section temperature comprises heat accumulator inlet temperature, heat accumulator outlet temperature, combustion chamber temperature and gas outlet temperature.

Description

Digital twinning-based RTO intelligent monitoring and diagnosis method Technical Field The invention belongs to the technical field of intelligent manufacturing and automation, and particularly relates to an RTO intelligent monitoring and diagnosing method based on digital twinning. Background Heat accumulating type incinerator (REGENERATIVE THERMAL Oxidizer, RTO), especially three-chamber RTO is currently commonly used as waste gas treatment equipment at the end of the production process in the pharmaceutical and chemical industries. However, due to process limitations, existing RTO control systems are not capable of monitoring the furnace temperature in real time and making reasonable regulation strategies. Besides, due to lack of equipment early warning and fault tracing measures, the RTO furnace can be stopped for a long time when the RTO furnace is stopped due to equipment faults, and the personnel safety of staff can be threatened greatly. In addition, when the temperature in the heat storage chamber is too high, the service life of the heat storage body may be reduced. Digital twinning is a universally adapted theoretical technology system, can be applied in a plurality of fields, and has more application in the fields of product design, product manufacturing, medical analysis, engineering construction and the like. By fully utilizing data such as a physical model, sensor update, operation history and the like, the simulation process of multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities is integrated, and mapping is completed in a virtual space, so that the full life cycle process of corresponding entity equipment is reflected. In the current treatment process mainly based on RTO, the operation experience of operators on equipment is still used as the most important basis, the optimization space of the waste gas treatment industry is very limited, and the economic benefit and the safety of the industry can be reduced by simply relying on manual experience, so that the optimization of RTO operation can not be achieved. Therefore, a digital twin technology is integrated into an RTO processing system, an RTO multidimensional database is established, and simulation monitoring of RTO operation is realized by importing a three-dimensional data field into AR glasses. Disclosure of Invention In order to overcome the defects and shortcomings of the prior art, the invention provides an RTO intelligent monitoring and diagnosing method based on digital twinning. The technical scheme adopted by the invention is as follows: an RTO intelligent monitoring and diagnosing method based on digital twinning comprises the following steps: Step one, collecting data including running data, size information and maintenance records of RTO, establishing a multidimensional database, carrying out structural analysis and functional analysis on the RTO based on the database, and constructing an RTO mechanism model and an RTO data driving model to obtain a digital twin module for the RTO; Step two, simulating the internal running state of the RTO according to the digital twin module of the RTO obtained in the step one, so as to realize real-time monitoring and diagnosis of the running state of the RTO; and thirdly, connecting the simulated internal operation process to the AR glasses, realizing visual analysis, and adopting corresponding security decisions based on visual analysis results. Preferably, the operation data comprises, but is not limited to, the content of organic waste gas input into a regenerator before RTO operation, the opening degree of each inlet valve and each outlet valve in RTO, the temperature of a combustion chamber, the temperature of a pipeline, the LEL concentration at each valve, the average heat value of the organic waste gas input into the regenerator, and the treatment capacity and the treatment efficiency of the corresponding organic waste gas before feeding; The dimension information comprises, but is not limited to, the geometric dimension of RTO, the geometric shape of RTO, the geometric dimension and shape of each component in the interior and the geometric relationship among each component, wherein each component comprises a combustion chamber, a regenerator, a heat accumulator, a front bypass valve, a rear bypass valve, a main waste valve, a fresh air valve, a lift valve, a combustion air valve, a combustion valve, a main fan, a bypass fan and a combustion fan; the maintenance record comprises an RTO parameter alarm record, a manual inspection record and an equipment account. Preferably, the structural analysis comprises the steps of analyzing the size information of the RTO to determine the RTO component parts, the functional analysis comprises the steps of analyzing the bearing functions of all components of the RTO and the coupling relations of all components, constructing a model by adopting 3D MAX, solidWorks or AutoCAD during the structural analy