CN113627020A - Printing workshop VOCs diffusion model and intelligent monitoring system - Google Patents
Printing workshop VOCs diffusion model and intelligent monitoring system Download PDFInfo
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Abstract
The invention discloses a VOCs diffusion model and an intelligent monitoring system for a printing workshop, which mainly comprise the following steps: establishing a diffusion model of VOCs in a printing workshop; establishing a VOCs gas distribution model of a printing workshop; and (5) building an intelligent VOCs monitoring system. According to the invention, a FLUENT simulation method is adopted to simulate the diffusion model values of VOCs in a printing workshop, the VOCs gas distribution of the printing workshop in the printing process is obtained according to a FLUENT simulation result, and the construction of a VOCs monitoring system is guided through the simulation result; the method comprises the steps of carrying out theoretical analysis on VOCs particle diffusion paths, establishing a concentration diffusion model of VOCs, researching flow field distribution of VOCs in a printing workshop, designing an intelligent monitoring system of VOCs, and providing technical support for achieving VOCs end treatment.
Description
Technical Field
The invention belongs to the field of printing machinery detection, and particularly relates to a VOCs diffusion model and an intelligent monitoring system for a printing workshop.
Background
In the printing and packaging industry, main products of packaging factories and printing factories are printing products of various plastic films, a large amount of color ink and organic solvent are used in the production of the plastic films, the ink solvent is a main source of VOCs waste gas in the printing process, the components of the ink solvent contain toluene, ethyl acetate and a small amount of butanone, the ink solvent volatilizes in the form of waste gas in the printing production process, the ink solvent is free of tissue diffusion and is easy to gather around a printing machine, so that the workshop environment is severe, the physical health of workers is seriously affected, and the toluene can damage the hematopoietic system of the human body and induce leukemia; ethyl acetate has an irritating odor; butanone stimulates the central nervous system of the human body. The printing workshop belongs to a tall building space, the internal airflow factor is complex, and the gas is easily influenced by environmental comprehensive factors such as temperature, humidity, pressure and the like. The treatment of VOCs becomes a serious environmental problem to be solved urgently in China, and concerns about the health of people.
Enterprises and colleges at home and abroad make a great deal of research on the aspect of printing VOCs and apply research results to the aspect of printing VOCs control. The whole research direction is mainly divided into two parts, source control and tail end treatment. And the research on the discharge characteristics, the discharge rules, the discharge lists and the like of the VOCs in the printing process is very little, the VOCs in a workshop in the printing process are concentrated in the area near the VOCs source and are in descending uneven distribution, and the concentration is influenced by a plurality of factors such as time, air flow and the like, so that the harmful gas diffusion rules in the neighborhood range of the printing machine can be analyzed through a corresponding monitoring scheme, and a certain basis is provided for finding out a corresponding control method.
Disclosure of Invention
The invention aims to: the VOCs diffusion model and the intelligent monitoring system for the printing workshop are provided for solving the technical problems. The method comprises the steps of researching the emission source and the emission characteristics of the VOCs, carrying out theoretical analysis on the particle diffusion path of the VOCs, establishing a concentration diffusion model of the VOCs, researching the flow field distribution of the VOCs in a printing workshop, designing an intelligent monitoring system of the VOCs, and providing technical support for the treatment of the tail end of the VOCs.
In order to achieve the purpose, the invention adopts the following technical scheme:
the utility model provides a print shop VOCs diffusion model and intelligent monitoring system, mainly includes following 3 parts:
a. establishing a diffusion model of VOCs in a printing workshop;
b. establishing a VOCs gas distribution model of a printing workshop;
c. and (5) building an intelligent VOCs monitoring system.
The printing workshop has the disadvantages of large internal space, complex temperature field and airflow field and complex environment. According to the invention, a numerical calculation model for representing VOCs diffusion of a printing workshop is established by solving a VOCs diffusion differential equation; the method comprises the steps of predicting the range concentration distribution of VOCs formed after the VOCs are diffused in a printing workshop by calculating the concentration value of VOCs released by a plurality of VOCs release sources in the printing operation process at any point in the printing workshop.
According to the method, a GDPLD model is adopted to relate to a continuity equation shown in a formula (1), a momentum equation shown in formulas (2), (3) and (4) and an energy equation shown in a formula (5) in a diffusion model of VOCs in a printing workshop, and the VOCs waste gas diffusion behavior in the printing workshop is analyzed; meanwhile, a diffusion equation comprising non-reaction components is shown as a formula (6) and a gas state equation is shown as a formula (7), so that diffusion of the multi-component mixed gas is simulated;
ρV＝nZRT (7)
where ρ is the mixed density of multi-component VOCs gases such as toluene, ethyl acetate, and methyl ethyl ketone, u is the gas velocity, t is the diffusion time, u, v, and w respectively represent the normal velocities in the x, y, and z directions, and Fx、Fy、FzA momentum source term; p is static pressure, i is internal energy, T is thermodynamic temperature, and phi is a dissipation function; ciFor the volume fraction of each gas in the mixed gas, taking n kinds of mixed gases as an example, since the sum of n kinds of gases is equal to a unit gas, only n-1 kinds of gases need to be specified; sh、SiInternal heat and mass sources, μ, k, D, respectivelycV, n, Z and R are gas volumes, masses, compressibilities and gas constants in the equation of state, for physical parameters related to internal friction, heat transfer and diffusion capability, respectively.
According to the VOCs gas distribution model in the printing workshop, the numerical value of the VOCs diffusion model in the printing workshop is simulated by using a FLUENT simulation method, and the VOCs gas distribution in the printing workshop in the printing process is obtained according to a FLUENT simulation result.
Further, a printing workshop is inspected on the spot to be a VOCs diffusion simulation object, then a three-dimensional model is established according to the building structure and the size of the workshop, the position of a ventilation opening in the workshop and the air flow speed are measured, and whether the workshop is provided with ventilation openings at the head side and the tail side of the printing machine or not is observed;
the three-dimensional model of the printing workshop is led into FLUENT for gridding division, the size of the established printing workshop model is large, but the size of the air outlet is small, so that the result of gas simulation in the printing workshop is accurate, the air outlet and the grids of the printing workshop are divided into regions independently, then a printer, a goods shelf and the like in the printing workshop are divided into regions with a relatively rule, grids with different grid sizes and sizes are selected for division, and the effectiveness of the grids is guaranteed.
The grid form and density have important influence on the numerical calculation result, the method adopts pure hexahedron grid division, and has the advantages of accurate control on spatial grid distribution, highest memory utilization efficiency in all grid types, higher calculation accuracy and higher convergence rate when the grid direction can be arranged along the flow direction, and the number of generated grids is 350-450 ten thousand.
In the invention, parameters such as air inlet speed, air inlet angle, air inlet height, average temperature, average humidity, average air pressure and the like in a measuring workshop are used as boundary conditions of the simulation process. And determining the air inlet form of the simulation process according to the measured air inlet speed, air inlet angle, air inlet height and other parameters so as to research the influence of workshop airflow distribution on the temperature and VOCs distribution in the printing workshop.
The simulation of VOCs air flow turbulence in a printing workshop adopts a modified kappa-epsilon two-equation model and adopts Boussinesq hypothesis, and the diffusion of VOCs gas adopts a finite volume method. The Boussinesq is assumed to be: the density of the gas in the printing workshop is related to the pressure and the temperature in the workshop, when VOCs flows at low speed, the gas pressure does not change greatly, the main change is that the density changes caused by the temperature change, therefore, the density changes of the gas caused by the pressure change in the workshop are ignored, and only the density changes of the VOCs caused by the temperature change in the workshop are considered.
Improved kappa-epsilon two-equation model:
where k is the kinetic energy of the turbulence, ω is the dissipation ratio of the turbulence, P and μtTurbulence generation rate and turbulence viscosity, the moldThe model combines the advantages of k-epsilon and k-omega models by calculating a mixing function F1The function is 0 near the wall and 1 at the boundary layer.
Determination of convergence criteria: when the residual error of the VOCs energy equation (5) is less than 10-6The residual error of the continuity equation (1), the gas velocity component, kappa and omega is less than 10-3. Meanwhile, all the calculated residual error curves tend to be horizontal so as to ensure the stability of all the parameter values.
Setting of boundary conditions and parameters: selecting VOCs diffusion simulation boundary conditions of the printing workshop, wherein the selected VOCs diffusion simulation boundary conditions comprise a gas inlet boundary of the printing workshop, a gas outlet boundary of the printing workshop, a VOCs diffusion source model in the printing workshop, a printer model boundary and the like. On the premise of ensuring the calculation precision and the calculation speed, the parameters are reasonably set.
Setting of initial conditions: unsteady state problem initial conditions. Detecting the field working environment, measuring the outdoor temperature of the workshop, and measuring parameters such as air humidity, wind direction and wind speed outside the workshop; during detection, parameters such as average temperature, average humidity and average air pressure in a workshop are measured. As an initial condition of the simulation process.
According to the invention, an intelligent monitoring system of VOCs is built, the building of the VOCs monitoring system is guided through a simulation result, a VOCs sensor module is responsible for collecting VOCs gas information and converting the collected gas concentration and other information into electric signals through an AD converter, and the electric signals are sent to a data processing module through a wireless network; secondly, through a link structure for transmitting VOCs concentration information measured by a plurality of VOCs sensor modules through a data processing module, the data information can be distributed and collected, the collected digital voltage signals are processed to obtain real VOCs concentration information, the processed information is sent to a computer and is displayed in computer software in a centralized mode, and therefore data transmission is completed.
And finally, receiving the data information sent by the data processing module through computer monitoring software, and reading the VOCs concentration information and distribution state of the printing workshop measured by the VOCs sensor module in real time through the software.
VOCs sensor module mainly used VOCs concentration information's collection and transmission mainly includes ARM singlechip, gas sensor, power, WIFI module etc..
Compared with the prior art, the invention has the beneficial effects that:
the VOCs pollutant emission list is established by researching the emission source and the emission characteristics of the VOCs, the VOCs particle diffusion path is theoretically analyzed, the concentration diffusion model of the VOCs is established, the VOCs flow field distribution in a printing workshop is researched, the VOCs intelligent monitoring system is designed, and the technical support is provided for realizing the VOCs end treatment.
Drawings
The following detailed description of embodiments of the invention is provided in conjunction with the appended drawings, in which:
FIG. 1 is a diagram of a print shop VOCs diffusion model and intelligent monitoring system;
FIG. 2 is a diagram of a printing shop model and test points distribution;
FIG. 3 is a print shop VOCs monitoring hardware system;
FIG. 4 is a graph of the distribution of the test points around the printer.
Detailed Description
The present invention will be further described with reference to the following examples, but is not limited thereto.
Examples
1. Numerical simulation of VOCs diffusion characteristics of printing workshop
(1) Establishment of mathematical physical model
Constructing a model: as shown in fig. 2, a two-dimensional sketch of a print shop was constructed. Under the condition of ensuring the simulation accuracy, a series of reasonable simplifications are carried out on the structural three-dimensional model of the printing workshop so as to improve the calculation speed of the simulation. Due to the complex environment of the printing workshop and the need of simplifying the complex VOCs diffusion model of the printing workshop, the printing machine 5, the article rack 1, the article rack 2, the article rack 3 and the article rack 4 are VOCs diffusion sources. During field detection, the printing machine in the workshop is in a running state.
The air inlet form is as follows: and determining the air inlet form of the simulation process according to the measured air inlet speed, air inlet angle, air inlet height and other parameters so as to research the influence of workshop airflow distribution on the temperature and VOCs distribution in the printing workshop.
Grid generation: the form and density of the grid have an important influence on the numerical calculation result. The method adopts pure hexahedral mesh division, and has the advantages of precise control of spatial mesh distribution and highest memory utilization efficiency among all mesh types. When the grid direction can be arranged along the flow direction, the calculation accuracy is higher, the convergence speed is also higher, and the number of generated grids is determined to be 400 ten thousand.
(2) Fluent computing parameter settings
VOCs airflow model of printing workshop: the simulation of VOCs air flow turbulence in a printing workshop adopts a modified kappa-epsilon two-equation model and adopts Boussinesq hypothesis, and the diffusion of VOCs gas adopts a finite volume method. The Boussinesq is assumed to be: the density of the gas in the printing workshop is related to the pressure and the temperature in the workshop, when VOCs flows at low speed, the gas pressure does not change greatly, the main change is that the density changes caused by the temperature change, therefore, the density changes of the gas caused by the pressure change in the workshop are ignored, and only the density changes of the VOCs caused by the temperature change in the workshop are considered.
Improved kappa-epsilon two-equation model:
where k is the kinetic energy of the turbulence, ω is the dissipation ratio of the turbulence, P and μtTurbulence generation rate and turbulence viscosity, which combines the advantages of k-epsilon and k-omega models by calculating a mixing function F1The function is 0 near the wall and 1 at the boundary layer.
Determination of convergence criteria: when the residual error of the VOCs energy equation (5) is less than 10-6The residual error of the continuity equation (1), the gas velocity component, kappa and omega is less than 10-3. Meanwhile, all the calculated residual curves tend to be horizontalTo ensure the stability of each parameter value.
Setting of boundary conditions and parameters: selecting VOCs diffusion simulation boundary conditions of the printing workshop, wherein the selected VOCs diffusion simulation boundary conditions comprise a gas inlet boundary of the printing workshop, a gas outlet boundary of the printing workshop, a VOCs diffusion source model in the printing workshop, a printer model boundary and the like. On the premise of ensuring the calculation precision and the calculation speed, the parameters are reasonably set.
Setting of initial conditions: unsteady state problem initial conditions. Detecting the field working environment, measuring the outdoor temperature of the workshop, and measuring parameters such as air humidity, wind direction and wind speed outside the workshop; during detection, parameters such as average temperature, average humidity and average air pressure in a workshop are measured. As an initial condition of the simulation process.
(3) VOCs diffusion dynamics simulation content and result visualization
Simulation content: and (4) performing numerical simulation on the VOCs dangerous gas diffusion rule under the condition that a plurality of VOCs diffusion sources in the printing workshop simultaneously emit VOCs. The method is used for simulating the values of the concentration fields of the VOCs under different boundary conditions and initial conditions, and researching the influence on the diffusion condition of the VOCs under different air inlet states and the influence of an air inlet form on workshop airflow.
And (4) visualizing the result: the gas distribution concentration data items for each desired position in the press room VOCs simulation results are represented as images. A large number of data sets constitute a data image, while respective attribute values of the data are represented in the form of multidimensional data.
2. VOCs measuring scheme for printing workshop
And (4) measuring the distribution of VOCs in the printing workshop. VOCs in a workshop are concentrated in the area near the source of the VOCs in the printing process and are distributed in a descending and uneven mode, and the concentration is influenced by a plurality of factors such as time, air flow and the like. In order to accurately monitor the distribution characteristics of VOCs in a workshop in the printing process, a non-uniform VOCs sensor array layout scheme is adopted to monitor harmful gas in the range of VOCs diffusion sources. VOCs sensor module: this module is used for VOCs concentration information's collection and transmission, mainly includes ARM singlechip, gas sensor, power, WIFI module etc.. As shown in fig. 3, the gas sensor is an electrochemical sensor for gaseous benzene, an electrochemical sensor for gaseous toluene, or an electrochemical sensor for gaseous isopropyl alcohol. The power supplies are supplied power to the sensor modules, when the concentration of VOCs in the printing workshop changes, the conductivity of the gas sensor also changes, the single chip microcomputer collects voltage changes caused by the change of the concentration of the VOCs, and the voltage changes of the gas sensor are sent to the data processing module through the WIFI module.
A data processing module: the data processing module is used for transmitting VOCs concentration information measured by the VOCs sensor modules, so that the data information can be distributed and collected, and the digital voltage signals from the mobile phone are processed to obtain real VOCs concentration information. The module mainly comprises an ARM chip STM32, a data receiving and transmitting indicator light, a serial port module and the like. The ARM chip is responsible for receiving the multichannel signal that VOCs sensor module sent, through signal processing algorithm, handles the save to the sensor signal to signal after will handling is through calculating conversion concentration signal, sends to the computer through the serial ports.
Computer monitoring software: writing a designed VOCs monitoring interface through MATLAB, connecting with an STM32 single chip microcomputer through serial equipment, acquiring VOCs concentration information of a data processing module, setting an alarm threshold value in monitoring software, and triggering alarm when the concentration exceeds the standard.
Measuring point distribution scheme: as shown in fig. 2 and 4, the sources of VOCs leakage during printing mainly come from the ink tanks, printer color unit groups, printer delivery table 51, printer feed table 52, shelf 1, shelf 2, shelf 3, shelf 4, and the like. According to the distribution characteristics of gas around the printing machine, non-uniform array measuring points are adopted for distribution, 10 VOCs sensor modules (measuring points are distributed on two sides of the printing machine, the measuring points are (the first), (the fifth), (the ninth) and the tenth), the measuring points are (the fifth) operating side monitoring points, the measuring points (the ninth and the ninth) are monitoring points above the color group, and the measuring points are used for measuring the leakage of VOCs at the printing machine; VOCs sensor modules (measuring points) are respectively arranged at the air inlet, the air outlet and the goods shelf
)。
Claims (8)
1. The utility model provides a print shop VOCs diffusion model and intelligent monitoring system which characterized in that includes the following step:
a. establishing a diffusion model of VOCs in a printing workshop;
b. establishing a VOCs gas distribution model of a printing workshop;
c. and (5) building an intelligent VOCs monitoring system.
2. The printing shop VOCs diffusion model and intelligent monitoring system according to claim 1, wherein the step a is used for establishing a diffusion model of VOCs in the printing shop, and the GDPLD model is used for analyzing the waste gas diffusion behavior of VOCs in the printing shop by using a continuity equation as shown in formula (1), momentum equations as shown in formulas (2), (3) and (4) and an energy equation as shown in formula (5); meanwhile, the diffusion equation comprising the non-reactive components is shown as the formula (6) and the gas state equation is shown as the formula (7), so that the diffusion of the multi-component mixed gas is simulated:
ρV＝nZRT (7)
where ρ is the mixed density of multi-component VOCs gases such as toluene, ethyl acetate, and methyl ethyl ketone, u is the gas velocity, t is the diffusion time, u, v, and w respectively represent the normal velocities in the x, y, and z directions, and Fx、Fy、FzA momentum source term; p is static pressure, i is internal energy, T is thermodynamic temperature, and phi is a dissipation function; ciFor the volume fraction of each gas in the mixed gas, taking n kinds of mixed gases as an example, since the sum of n kinds of gases is equal to a unit gas, only n-1 kinds of gases need to be specified; sh、SiInternal heat and mass sources, μ, k, D, respectivelycV, n, Z and R are gas volumes, masses, compressibilities and gas constants in the equation of state, for physical parameters related to internal friction, heat transfer and diffusion capability, respectively.
3. The print shop VOCs diffusion model and intelligent monitoring system of claim 1, wherein: and b, establishing a VOCs gas distribution model of the printing workshop, simulating the value of the VOCs diffusion model in the printing workshop by using a FLUENT simulation method, and obtaining the VOCs gas distribution of the printing workshop in the printing process according to the FLUENT simulation result.
4. The press shop VOCs diffusion model and intelligent monitoring system of claim 3, wherein the specific steps of using FLUENT simulation method are:
firstly, establishing a simulation model to examine a printing workshop on the spot as a VOCs diffusion simulation object, then establishing a three-dimensional model according to the building structure and the size of the workshop, and measuring the position of an air vent inside the workshop and the air flow speed;
secondly, measuring an air inlet form of the workshop, and determining the air inlet form of the simulation process according to the measured air inlet speed, air inlet angle, air inlet height and other parameters;
thirdly, grid division of the simulation model, namely guiding the three-dimensional model of the printing workshop into FLUENT for grid division, and independently dividing the air outlet and the grid of the printing workshop in different areas;
and fourthly, setting FLUENT calculation parameters, and simulating the airflow turbulence of the VOCs in the printing workshop by adopting a modified kappa-epsilon two-equation model and adopting Boussinesq hypothesis, wherein the diffusion of the VOCs gas adopts a finite volume method.
5. The printing shop VOCs diffusion model and intelligent monitoring system according to claim 4, wherein the mesh division of the simulation model in the third step is pure hexahedron mesh division, the mesh direction can be arranged along the flow direction, and the number of generated meshes is 350-450 ten thousand.
6. The print shop VOCs diffusion model and intelligent monitoring system of claim 4, wherein the modified k-e two equation model in the fourth step is:
where k is the kinetic energy of the turbulence, ω is the dissipation ratio of the turbulence, P and μtTurbulence generation rate and turbulence viscosity, which combines the advantages of k-epsilon and k-omega models by calculating a mixing function F1The function is 0 near the wall and 1 at the boundary layer.
7. The printing shop VOCs diffusion model and intelligent monitoring system according to claim 1, wherein the intelligent monitoring system for VOCs constructed in step c mainly comprises:
1) the VOCs sensor module collects VOCs gas information, converts the collected gas concentration information into an electric signal through an AD converter and sends the electric signal to the data processing module through a wireless network;
2) the data processing module transmits VOCs concentration information measured by the VOCs sensor modules to a link structure, so that data information can be distributed and collected, the collected digital voltage signals are processed to obtain real VOCs concentration information, the processed information is sent to a computer and is displayed in a centralized manner in computer software, and data transmission is completed;
3) and the computer monitoring software receives the data information sent by the data processing module and reads the VOCs concentration information and distribution state of the printing workshop measured by the VOCs sensor module in real time through the software.
8. The press shop VOCs diffusion model and intelligent monitoring system of claim 7, wherein: the VOCs sensor module is mainly used for collecting and sending VOCs concentration information and mainly comprises an ARM single chip microcomputer, a gas sensor, a power supply, a WIFI module and the like.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114113486A (en) * | 2021-11-30 | 2022-03-01 | 北京地拓科技发展有限公司 | Method and device for monitoring VOCs emission of external facade in urban residential community |
| CN114264778A (en) * | 2021-12-24 | 2022-04-01 | 江苏云聚汇科技有限公司 | VOCS monitoring system for on-line monitoring |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114113486A (en) * | 2021-11-30 | 2022-03-01 | 北京地拓科技发展有限公司 | Method and device for monitoring VOCs emission of external facade in urban residential community |
| CN114264778A (en) * | 2021-12-24 | 2022-04-01 | 江苏云聚汇科技有限公司 | VOCS monitoring system for on-line monitoring |
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