CN110851979A - Chemical plant air flow distribution simulation system based on NARS technology - Google Patents
Chemical plant air flow distribution simulation system based on NARS technology Download PDFInfo
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Abstract
The invention discloses a chemical plant airflow distribution simulation system based on NARS technology, which comprises an information acquisition module, a data analysis module, a monitoring module, a display screen, a simulation unit, an evaluation unit and intelligent equipment, wherein the information acquisition module is used for acquiring information of a chemical plant; the air flow information acquisition unit is used for acquiring air flow information, the air flow information comprises factory information and air information, the factory information comprises air flow type data, air flow position data, air flow range data, air flow concentration data and air flow speed data, and the air information comprises air temperature data.
Description
Technical Field
The invention relates to the technical field of airflow distribution simulation, in particular to a chemical plant airflow distribution simulation system based on NARS technology.
Background
The air flow distribution refers to the air flow velocity distribution on the inlet section of the electric dust collector. The uniformity of the airflow distribution has a great influence on the dust removal efficiency. When the airflow distribution is not uniform, the dust removal efficiency improved at the position with low flow velocity is far insufficient to make up the reduction of the efficiency at the position with high flow velocity, so that the total dust removal efficiency is reduced. There are several indicators for evaluating the uniformity of the airflow distribution.
The plant geographical distribution simulation system with the bulletin number of CN108920680A is simple in structure, easy and convenient to operate and low in hardware requirement, but cannot rapidly simulate airflow distribution, simultaneously has a large difference between a simulation image and actual airflow distribution, and cannot accurately analyze defects of the simulation system, so that a chemical plant airflow distribution simulation system based on NARS technology is provided.
Disclosure of Invention
The invention aims to provide a chemical plant air flow distribution simulation system based on NARS technology, which can simulate the air flow distribution of a chemical plant by collecting various air flow data, analyzing and operating the air flow distribution simulation model, and performing simulated air flow distribution conversion in the simulation unit to solve the problem of difficult rapid simulation of air flow distribution, the real-time data and the collected data are analyzed by the monitoring module, so as to obtain the difference value between the two data, the difference between the actual airflow distribution and the simulated airflow distribution image is replaced, the problem of large difference between the simulated image and the actual airflow distribution is solved, the defects of the simulation system are judged by analyzing the difference values of the actual airflow range data, the real-time airflow concentration data, the real-time airflow position data and the airflow range data, and the airflow concentration data and the airflow position data through the evaluation unit, and the problem that the defects of the simulation system are difficult to accurately analyze is solved.
The technical problem to be solved by the invention is as follows:
(1) how to preliminarily analyze various collected airflow data by setting analysis operation and preliminary simulation airflow distribution operation, convert the analyzed data into a space rectangular coordinate, and convert the space rectangular coordinate into an airflow distribution image in a simulation unit, so as to solve the problem that the airflow distribution is difficult to be quickly simulated in the prior art;
(2) how to perform detailed difference analysis on the airflow distribution data when the simulation unit converts the airflow distribution image and the airflow distribution data when information is acquired by changing the setting of analysis operation, and perform data replacement in the simulation unit, so as to solve the problem of large difference between the simulation image and the actual airflow distribution in the prior art;
(3) how to perform difference value analysis on the air flow range data, the real-time air flow concentration data, the real-time air flow position data, the air flow range data, the air flow concentration data and the air flow position data through the setting of the evaluation unit and calculate the difference value range between the actual air flow distribution and the air flow distribution image, so that the problem that accurate analysis on the defects of a simulation system is difficult in the prior art is solved.
The purpose of the invention can be realized by the following technical scheme: a chemical plant airflow distribution simulation system based on NARS technology comprises an information acquisition module, a data analysis module, a monitoring module, a display screen, a simulation unit, an evaluation unit and intelligent equipment;
the information acquisition unit is used for acquiring airflow information, the airflow information comprises factory information and air information, the factory information comprises airflow type data, airflow position data, airflow range data, airflow concentration data and airflow flowing speed data, the air information comprises air temperature data and wind speed data, and the wind speed data is represented as flowing speed data of air and is transmitted to the data analysis module;
the data analysis module is used for analyzing and operating air flow type data, air flow position data, air flow range data, air flow concentration data, air flow speed data, air temperature data and air speed data to obtain corner coordinates ZBl and a space rectangular coordinate system and transmitting the corner coordinates ZBl and the space rectangular coordinate system to the simulation unit;
the simulation unit is used for preliminarily simulating the airflow distribution operation on the corner coordinate ZBl and the space rectangular coordinate system to obtain an airflow distribution image and transmitting the airflow distribution image to the display screen;
the monitoring module is used for transmitting real-time airflow range data, real-time airflow concentration data, real-time airflow position data, real-time air temperature data, real-time wind speed data, monitoring information acquisition time data and simulated distribution time data to the data analysis unit;
the data analysis unit is also used for carrying out change analysis operation on the real-time airflow range data, the real-time airflow concentration data, the real-time airflow position data, the monitoring information acquisition time data and the simulated distribution time data to obtain the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration, and transmitting the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration to the simulation unit for data image updating;
the evaluation unit evaluates the data image of the simulation unit according to the real-time airflow range data, the real-time airflow concentration data, the real-time airflow position data, the airflow range data, the airflow concentration data and the airflow position data to obtain a range correct signal, a range deviation signal, a concentration correct signal, a concentration chaotic signal, a position error signal and a position accurate signal, and transmits the range correct signal, the range deviation signal, the concentration correct signal, the concentration chaotic signal, the position error signal and the position accurate signal to the intelligent device;
the intelligent equipment is used for receiving a correct range signal, a range deviation signal, a correct concentration signal, a chaotic concentration signal, an incorrect position signal and an accurate position signal and reminding a user, and the display screen is used for displaying airflow distribution images.
As a further improvement of the invention: the specific operation process of the analysis operation is as follows:
the method comprises the following steps: acquiring air flow type data, classifying air flows according to the air flow type data, and specifically detecting and classifying the air flows through an air flow detection device;
step two: acquiring air flow type data, air flow position data, air flow range data, air flow concentration data, air flow velocity data, air temperature data and air speed data, and sequentially marking the data as QZi, QWI, QFi, QNi, QLi, Kwi and FSi, wherein i is 1,2,3.... times.n, and the QZi, QWI, QFi, QNi, QLi, Kwi and FSi are in one-to-one correspondence;
step three: setting an origin of a coordinate system, establishing a rectangular spatial coordinate system, wherein the origin can be any point on the ground, acquiring airflow type data and airflow range data and airflow position data corresponding to the airflow type data, respectively representing different types of airflows on the rectangular spatial coordinate system, and marking corner coordinates ZBl of the airflows, wherein l is 1,2,3.
As a further improvement of the invention: the specific operation process of the simulated airflow distribution operation comprises the following steps:
e1: establishing a simulation image;
e2: acquiring corner coordinates ZBl and a space rectangular coordinate system, converting the corner coordinates and the space rectangular coordinate system into analog signals, and marking the analog signals on analog images;
e3: a different color virtual fill shadow is set to fill the simulated image in E2, and the different color image area is labeled as Mj, j being 1,2,3.
As a further improvement of the invention: the specific operation process of the change analysis operation is as follows:
s1: acquiring real-time airflow range data, real-time airflow concentration data, real-time airflow position data, information acquisition time data and simulation distribution time data, and sequentially marking the data as qfo, qno, qwo, CJo and FMo, wherein o is 1,2 and 3.
S2: calculating a time difference value T1 (FMo-CJo) according to the information acquisition time data and the simulated distribution time data, acquiring real-time air flow position data and air flow position data, and bringing the real-time air flow position data and the air flow position data into a calculation formula L1 (qwo-QWi), wherein L1 represents position change distance data;
s3: acquiring position change distance data L1 and a time difference T1 in S2, and substituting the position change distance data L1 and the time difference T1 together with the airflow flow speed data QLi into a calculation formula QLi (L1/T1) u, wherein u is an image factor of the airflow flow speed, so that the position change distance L of different airflows is (FMo-CJo) QLi/u;
s4: acquiring real-time airflow range data, real-time airflow concentration data, real-time air temperature data and real-time wind speed data, and comparing the real-time airflow range data, the real-time airflow concentration data, the real-time air temperature data and the real-time wind speed data with the airflow range data, the airflow concentration data, the air temperature data and the wind speed data respectively to obtain a range data difference P1, a concentration data difference P2, a temperature change difference P3 and a wind speed change difference P4;
s5: when one of the values P3 and P4 is set to be 0, the imaging factors u2 and u3 of the air temperature and the air speed to the air flow range and the air flow concentration are calculated, and specifically: when P3 is equal to zero and both P1 and P2 are not equal to zero, qfo-QFi-P4-u 3, qno-QNi-P4-u 3, thereby deriving an air temperature influence factor u3, when P4 is equal to zero and both P1 and P2 are not equal to zero, qfo-QFi-P3-u 2, qno-QNi-P3-u 2, thereby deriving a wind speed influence factor u2, when P3 and P4 are equal to zero, the air temperature and wind speed have no influence on the airflow range and airflow concentration, and when P1 and P2 are equal to zero, the air temperature and wind speed are determined to have no influence on the airflow range and airflow concentration;
s6: and acquiring the wind speed influence factor u2 and the air temperature influence factor u3 in the step S5, and substituting the wind speed influence factor u2 and the air temperature influence factor u3 into real-time airflow position data, real-time airflow range data and real-time airflow concentration data calculation formulas of different types of airflows, so as to calculate the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration.
As a further improvement of the invention: the specific operation process of the evaluation operation is as follows:
r1: respectively carrying out difference calculation on the real-time air flow range data and the real-time air flow concentration data, the air flow range data and the air flow concentration data to obtain a range data difference value P1 and a concentration data difference value P2, setting two difference preset values A1 and A2, and respectively comparing the difference values with a range data difference value P1 and a concentration data difference value P2, wherein the method specifically comprises the following steps:
k1: when the P1 is not less than A1, the airflow range is judged to be within the error range, the airflow range of the data image is judged to be accurate, and a range correct signal is generated;
k2: when P1 is larger than A1, the airflow range is judged to be out of the error range, the airflow range of the data image is judged to be inaccurate, and a range deviation signal is generated;
k3: when the P2 is not less than A2, the airflow concentration is judged to be within the error range, the airflow concentration of the data image is judged to be accurate, and a concentration correct signal is generated;
k4: when P2 is larger than A2, the airflow concentration is judged to be out of the error range, the airflow concentration of the data image is judged to be inaccurate, and a concentration chaotic signal is generated;
r2: acquiring real-time airflow position data and airflow position data, marking the real-time airflow position data and the airflow position data as ZBl and zbl for comparison, wherein the ZBl coordinates are (Xa1, Yc1) and the zbl coordinates are (Xa2, Yc2), wherein a and c are both natural numbers, and the position change difference value of the real-time airflow position data and the airflow position data is ZBl and zbl difference value
Wherein Gh is a difference number, and h is 1,2,3.
R3: substituting the above-mentioned Gh in R2 into the calculation formula
Wherein P isGhExpressed as the mean value of the differences Gh between ZBl and zbl, a mean preset value GF is set and is compared with PGhComparing, specifically comprising:
ER 1: when GF is less than or equal to PGhIf so, judging that the position change is small, and the simulation degree of the data image is accurate to generate a position accurate signal;
ER 2: when GF < PGhIf so, the position is judged to be changed greatly, the simulation degree of the data image is inaccurate, and a position error signal is generated.
The invention has the beneficial effects that:
(1) the information acquisition unit is used for acquiring air flow type data, air flow position data, air flow range data, air flow concentration data, air flow speed data, air temperature data and air speed data and transmitting the data to the data analysis module, the data analysis module is used for analyzing the air flow type data, the air flow position data, the air flow range data, the air flow concentration data, the air flow speed data, the air temperature data and the air speed data to obtain a corner coordinate ZBl and a space rectangular coordinate system and transmitting the corner coordinate ZBl and the space rectangular coordinate system to the simulation unit, the simulation unit is used for preliminarily simulating air flow distribution operation on the corner coordinate ZBl and the space rectangular coordinate system to obtain an air flow distribution image, preliminarily analyzing various acquired air flow data by setting the analysis operation and the preliminary simulated air flow distribution operation, and converting the analyzed data into space rectangular coordinates, the space rectangular coordinate is converted into the airflow distribution image in the simulation unit, so that the airflow distribution image can truly reflect the airflow distribution condition in the chemical plant, the professional can conveniently and clearly know the airflow distribution, and the safety of the chemical plant is improved.
(2) The monitoring module is used for transmitting real-time airflow range data, real-time airflow concentration data, real-time airflow position data, real-time air temperature data, real-time wind speed data, monitoring information acquisition time data and simulated distribution time data to the data analysis unit; the data analysis unit is also used for carrying out change analysis operation on the real-time airflow range data, the real-time airflow concentration data, the real-time airflow position data, the monitoring information acquisition time data and the simulation distribution time data to obtain the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration, transmitting the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration to the simulation unit for data image updating, carrying out detailed difference analysis on the airflow distribution data when the simulation unit converts the airflow distribution image and the airflow distribution data when the information is acquired through the setting of the change analysis operation, carrying out data replacement in the simulation unit, avoiding overlarge difference between the airflow distribution image and actual airflow distribution, enabling the airflow distribution image to be more accurate, and facilitating operation of professionals on the airflow distribution.
(3) The evaluation unit evaluates the data image of the simulation unit according to the real-time air flow range data, the real-time air flow concentration data, the real-time air flow position data, the air flow range data, the air flow concentration data and the air flow position data to obtain a range correct signal, a range deviation signal, a concentration correct signal, a concentration chaotic signal, a position error signal and a position accurate signal, and transmits the range correct signal, the range deviation signal, the concentration correct signal, the concentration chaotic signal, the position error signal and the position accurate signal to the intelligent device, the intelligent device is used for receiving the range correct signal, the range deviation signal, the concentration correct signal, the concentration chaotic signal, the position error signal and the position accurate signal and reminding a user, the display screen is used for displaying an air flow distribution image, and the difference value analysis is carried out on the air flow range data, the real-time air flow concentration data, and calculating the difference range between the actual airflow distribution and the airflow distribution image, avoiding the deviation of the airflow distribution image from the actual condition, analyzing the defects of the simulation system and facilitating the correction of professionals.
Drawings
The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a system block diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention relates to a chemical plant air flow distribution simulation system based on NARS technology, which comprises an information acquisition module, a data analysis module, a monitoring module, a display screen, a simulation unit, an evaluation unit and an intelligent device;
the information acquisition unit is used for acquiring airflow information, the airflow information comprises factory information and air information, the factory information comprises airflow type data, airflow position data, airflow range data, airflow concentration data and airflow flowing speed data, the air information comprises air temperature data and wind speed data, and the wind speed data is represented as flowing speed data of air and is transmitted to the data analysis module;
the data analysis module is used for analyzing and operating the air flow type data, the air flow position data, the air flow range data, the air flow concentration data, the air flow speed data, the air temperature data and the air speed data, and the specific operation process of the analysis and operation is as follows:
the method comprises the following steps: acquiring air flow type data, classifying air flows according to the air flow type data, and specifically detecting and classifying the air flows through an air flow detection device;
step two: acquiring air flow type data, air flow position data, air flow range data, air flow concentration data, air flow velocity data, air temperature data and air speed data, and sequentially marking the data as QZi, QWI, QFi, QNi, QLi, Kwi and FSi, wherein i is 1,2,3.... times.n, and the QZi, QWI, QFi, QNi, QLi, Kwi and FSi are in one-to-one correspondence;
step three: setting an origin of a coordinate system, establishing a spatial rectangular coordinate system, wherein the origin can be any point on the ground, simultaneously acquiring airflow type data, airflow range data and airflow position data corresponding to the airflow type data, respectively representing different types of airflows on the spatial rectangular coordinate system, and marking corner coordinates ZBl of the airflows, wherein B represents different types of airflows, and l represents the positions of different corner points;
step four: transmitting the corner coordinates ZBl marked in the step three and the space rectangular coordinate system to the simulation unit;
the simulation unit is used for preliminarily simulating the airflow distribution operation for the corner coordinate ZBl and the space rectangular coordinate system, and the specific operation process of the simulated airflow distribution operation is as follows:
e1: establishing a simulation image;
e2: acquiring corner coordinates ZBl and a space rectangular coordinate system, converting the corner coordinates and the space rectangular coordinate system into analog signals, and marking the analog signals on analog images;
e3: setting different colors of virtual filling shadows to fill the simulated image in E2, and marking the image areas of the different colors as Mj, j being 1,2,3.... p, wherein the overlapping part shadows are marked as Md, d being 1,2,3.... y;
e4: transmitting the air flow distribution image to a display screen;
the monitoring module is used for transmitting real-time airflow range data, real-time airflow concentration data, real-time airflow position data, real-time air temperature data, real-time wind speed data, monitoring information acquisition time data and simulated distribution time data to the data analysis unit;
the data analysis unit is further used for performing change analysis operation on the real-time airflow range data, the real-time airflow concentration data, the real-time airflow position data, the monitoring information acquisition time data and the simulated distribution time data, and the specific operation process of the change analysis operation is as follows:
s1: acquiring real-time airflow range data, real-time airflow concentration data, real-time airflow position data, information acquisition time data and simulation distribution time data, and sequentially marking the data as qfo, qno, qwo, CJo and FMo, wherein o is 1,2 and 3.
S2: calculating a time difference value T1 (FMo-CJo) according to the information acquisition time data and the simulated distribution time data, acquiring real-time air flow position data and air flow position data, and bringing the real-time air flow position data and the air flow position data into a calculation formula L1 (qwo-QWi), wherein L1 represents position change distance data;
s3: acquiring position change distance data L1 and a time difference T1 in S2, and substituting the position change distance data L1 and the time difference T1 together with the airflow flow speed data QLi into a calculation formula QLi (L1/T1) u, wherein u is an image factor of the airflow flow speed, so that the position change distance L of different airflows is (FMo-CJo) QLi/u;
s4: acquiring real-time airflow range data, real-time airflow concentration data, real-time air temperature data and real-time wind speed data, and comparing the real-time airflow range data, the real-time airflow concentration data, the real-time air temperature data and the real-time wind speed data with the airflow range data, the airflow concentration data, the air temperature data and the wind speed data respectively to obtain a range data difference P1, a concentration data difference P2, a temperature change difference P3 and a wind speed change difference P4;
s5: when one of the values P3 and P4 is set to be 0, the imaging factors u2 and u3 of the air temperature and the air speed to the air flow range and the air flow concentration are calculated, and specifically: when P3 is equal to zero and both P1 and P2 are not equal to zero, qfo-QFi-P4-u 3, qno-QNi-P4-u 3, thereby deriving an air temperature influence factor u3, when P4 is equal to zero and both P1 and P2 are not equal to zero, qfo-QFi-P3-u 2, qno-QNi-P3-u 2, thereby deriving a wind speed influence factor u2, when P3 and P4 are equal to zero, the air temperature and wind speed have no influence on the airflow range and airflow concentration, and when P1 and P2 are equal to zero, the air temperature and wind speed are determined to have no influence on the airflow range and airflow concentration;
s6: acquiring the wind speed influence factor u2 and the air temperature influence factor u3 in the step S5, and bringing the wind speed influence factor u2 and the air temperature influence factor u3 into real-time airflow position data, real-time airflow range data and real-time airflow concentration data calculation formulas of different types of airflows, so as to calculate the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration data, and transmitting the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration data to;
the evaluation unit evaluates the data image of the simulation unit according to the real-time airflow range data, the real-time airflow concentration data, the real-time airflow position data, the airflow range data, the airflow concentration data and the airflow position data, and the specific operation process of the evaluation operation is as follows:
r1: respectively carrying out difference calculation on the real-time air flow range data and the real-time air flow concentration data, the air flow range data and the air flow concentration data to obtain a range data difference value P1 and a concentration data difference value P2, setting two difference preset values A1 and A2, and respectively comparing the difference values with a range data difference value P1 and a concentration data difference value P2, wherein the method specifically comprises the following steps:
k1: when the P1 is not less than A1, the airflow range is judged to be within the error range, the airflow range of the data image is judged to be accurate, and a range correct signal is generated;
k2: when P1 is larger than A1, the airflow range is judged to be out of the error range, the airflow range of the data image is judged to be inaccurate, and a range deviation signal is generated;
k3: when the P2 is not less than A2, the airflow concentration is judged to be within the error range, the airflow concentration of the data image is judged to be accurate, and a concentration correct signal is generated;
k4: when P2 is larger than A2, the airflow concentration is judged to be out of the error range, the airflow concentration of the data image is judged to be inaccurate, and a concentration chaotic signal is generated;
r2: acquiring real-time airflow position data and airflow position data, marking the data as ZBl and zbl for comparison, wherein the coordinates of ZBl are (Xa1, Yc1), and the coordinates of zbl are (Xa 1)2, Yc2), wherein a and c are natural numbers, and the position change difference between the real-time airflow position data and the airflow position data is ZBl and zblWherein Gh is a difference number, and h is 1,2,3.
R3: substituting the above-mentioned Gh in R2 into the calculation formula
Wherein P isGhExpressed as the mean value of the differences Gh between ZBl and zbl, a mean preset value GF is set and is compared with PGhComparing, specifically comprising:
ER 1: when GF is less than or equal to PGhIf so, judging that the position change is small, and the simulation degree of the data image is accurate to generate a position accurate signal;
ER 2: when GF < PGhIf so, judging that the position change is large, and the simulation degree of the data image is inaccurate, and generating a position error signal;
r3: transmitting a correct range signal, a range deviation signal, a correct concentration signal, a chaotic concentration signal, a wrong position signal and a precise position signal to intelligent equipment;
the intelligent equipment is used for receiving a correct range signal, a range deviation signal, a correct concentration signal, a chaotic concentration signal, an incorrect position signal and an accurate position signal and reminding a user, and the display screen is used for displaying airflow distribution images.
When the air flow distribution simulation system works, the information acquisition unit is used for acquiring air flow type data, air flow position data, air flow range data, air flow concentration data, air flow flowing speed data, air temperature data and air speed data and transmitting the data to the data analysis module, the data analysis module is used for analyzing the air flow type data, the air flow position data, the air flow range data, the air flow concentration data, the air flow flowing speed data, the air temperature data and the air speed data to obtain a corner coordinate ZBl and a space rectangular coordinate system and transmitting the corner coordinate ZBl and the space rectangular coordinate system to the simulation unit, the simulation unit is used for preliminarily simulating air flow distribution operation on the corner coordinate ZBl and the space rectangular coordinate system, and the specific operation process of the simulated air flow distribution operation is as follows: e1: establishing a simulation image; e2: acquiring corner coordinates ZBl and a space rectangular coordinate system, converting the corner coordinates and the space rectangular coordinate system into analog signals, and marking the analog signals on analog images; e3: setting virtual filling shadows of different colors to fill a simulated image in E2, marking the area of the image of different colors as Mj, j being 1,2,3.. eta.p, wherein the shadow of the overlapped part is marked as Md, d being 1,2,3.. eta.y, and transmitting the airflow distribution image to a display screen, and a monitoring module is used for transmitting real-time airflow range data, real-time airflow concentration data, real-time airflow position data, real-time air temperature data, real-time wind speed data, monitoring information acquisition time data and simulated distribution time data to a data analysis unit; the data analysis unit is also used for carrying out change analysis operation on the real-time airflow range data, the real-time airflow concentration data, the real-time airflow position data, the monitoring information acquisition time data and the simulated distribution time data to obtain the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration, and transmitting the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration to the simulation unit for data image updating; the evaluation unit evaluates the data image of the simulation unit according to the real-time airflow range data, the real-time airflow concentration data, the real-time airflow position data, the airflow range data, the airflow concentration data and the airflow position data to obtain a range correct signal, a range deviation signal, a concentration correct signal, a concentration chaotic signal, a position error signal and a position accurate signal, and transmits the range correct signal, the range deviation signal, the concentration correct signal, the concentration chaotic signal, the position error signal and the position accurate signal to the intelligent device; the intelligent equipment is used for receiving a correct range signal, a range deviation signal, a correct concentration signal, a chaotic concentration signal, an incorrect position signal and an accurate position signal and reminding a user, and the display screen is used for displaying airflow distribution images.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (4)
1. A chemical plant airflow distribution simulation system based on NARS technology is characterized by comprising an information acquisition module, a data analysis module, a monitoring module, a display screen, a simulation unit, an evaluation unit and intelligent equipment;
the information acquisition unit is used for acquiring airflow information, the airflow information comprises factory information and air information, the factory information comprises airflow type data, airflow position data, airflow range data, airflow concentration data and airflow flowing speed data, the air information comprises air temperature data and wind speed data, and the wind speed data is represented as flowing speed data of air and is transmitted to the data analysis module;
the data analysis module is used for analyzing and operating air flow type data, air flow position data, air flow range data, air flow concentration data, air flow speed data, air temperature data and air speed data to obtain corner coordinates ZBl and a space rectangular coordinate system and transmitting the corner coordinates ZBl and the space rectangular coordinate system to the simulation unit;
the simulation unit is used for preliminarily simulating the airflow distribution operation for the corner coordinate ZBl and the space rectangular coordinate system, and the specific operation process of the simulated airflow distribution operation is as follows:
e1: establishing a simulation image;
e2: acquiring corner coordinates ZBl and a space rectangular coordinate system, converting the corner coordinates and the space rectangular coordinate system into analog signals, and marking the analog signals on analog images;
e3: setting different colors of virtual fill shadows to fill the simulated image in E2, and marking the different colors of image areas as Mj, j being 1,2,3.. cndot, with overlapping portion shadows being marked as Md, d being 1,2,3.. cndot, and transmitting the air flow map image to the display screen;
the monitoring module is used for transmitting real-time airflow range data, real-time airflow concentration data, real-time airflow position data, real-time air temperature data, real-time wind speed data, monitoring information acquisition time data and simulated distribution time data to the data analysis unit;
the data analysis unit is also used for carrying out change analysis operation on the real-time airflow range data, the real-time airflow concentration data, the real-time airflow position data, the monitoring information acquisition time data and the simulated distribution time data to obtain the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration, and transmitting the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration to the simulation unit for data image updating;
the evaluation unit evaluates the data image of the simulation unit according to the real-time airflow range data, the real-time airflow concentration data, the real-time airflow position data, the airflow range data, the airflow concentration data and the airflow position data to obtain a range correct signal, a range deviation signal, a concentration correct signal, a concentration chaotic signal, a position error signal and a position accurate signal, and transmits the range correct signal, the range deviation signal, the concentration correct signal, the concentration chaotic signal, the position error signal and the position accurate signal to the intelligent device;
the intelligent equipment is used for receiving a correct range signal, a range deviation signal, a correct concentration signal, a chaotic concentration signal, an incorrect position signal and an accurate position signal and reminding a user, and the display screen is used for displaying airflow distribution images.
2. The NARS technology-based chemical plant gas flow distribution simulation system of claim 1, wherein the specific operation process of the analysis operation is as follows:
the method comprises the following steps: acquiring air flow type data, classifying air flows according to the air flow type data, and specifically detecting and classifying the air flows through an air flow detection device;
step two: acquiring air flow type data, air flow position data, air flow range data, air flow concentration data, air flow velocity data, air temperature data and air speed data, and sequentially marking the data as QZi, QWI, QFi, QNi, QLi, Kwi and FSi, wherein i is 1,2,3.... times.n, and the QZi, QWI, QFi, QNi, QLi, Kwi and FSi are in one-to-one correspondence;
step three: setting an origin of a coordinate system, establishing a rectangular spatial coordinate system, wherein the origin can be any point on the ground, acquiring airflow type data and airflow range data and airflow position data corresponding to the airflow type data, respectively representing different types of airflows on the rectangular spatial coordinate system, and marking corner coordinates ZBl of the airflows, wherein l is 1,2,3.
3. The NARS technology-based chemical plant gas flow distribution simulation system of claim 1, wherein the variation analysis operation comprises the following specific operation procedures:
s1: acquiring real-time airflow range data, real-time airflow concentration data, real-time airflow position data, information acquisition time data and simulation distribution time data, and sequentially marking the data as qfo, qno, qwo, CJo and FMo, wherein o is 1,2 and 3.
S2: calculating a time difference value T1 (FMo-CJo) according to the information acquisition time data and the simulated distribution time data, acquiring real-time air flow position data and air flow position data, and bringing the real-time air flow position data and the air flow position data into a calculation formula L1 (qwo-QWi), wherein L1 represents position change distance data;
s3: acquiring position change distance data L1 and a time difference T1 in S2, and substituting the position change distance data L1 and the time difference T1 together with the airflow flow speed data QLi into a calculation formula QLi (L1/T1) u, wherein u is an image factor of the airflow flow speed, so that the position change distance L of different airflows is (FMo-CJo) QLi/u;
s4: acquiring real-time airflow range data, real-time airflow concentration data, real-time air temperature data and real-time wind speed data, and comparing the real-time airflow range data, the real-time airflow concentration data, the real-time air temperature data and the real-time wind speed data with the airflow range data, the airflow concentration data, the air temperature data and the wind speed data respectively to obtain a range data difference P1, a concentration data difference P2, a temperature change difference P3 and a wind speed change difference P4;
s5: when one of the values P3 and P4 is set to be 0, the imaging factors u2 and u3 of the air temperature and the air speed to the air flow range and the air flow concentration are calculated, and specifically: when P3 is equal to zero and both P1 and P2 are not equal to zero, qfo-QFi-P4-u 3, qno-QNi-P4-u 3, thereby deriving an air temperature influence factor u3, when P4 is equal to zero and both P1 and P2 are not equal to zero, qfo-QFi-P3-u 2, qno-QNi-P3-u 2, thereby deriving a wind speed influence factor u2, when P3 and P4 are equal to zero, the air temperature and wind speed have no influence on the airflow range and airflow concentration, and when P1 and P2 are equal to zero, the air temperature and wind speed are determined to have no influence on the airflow range and airflow concentration;
s6: and acquiring the wind speed influence factor u2 and the air temperature influence factor u3 in the step S5, and substituting the wind speed influence factor u2 and the air temperature influence factor u3 into real-time airflow position data, real-time airflow range data and real-time airflow concentration data calculation formulas of different types of airflows, so as to calculate the real-time airflow position data, the real-time airflow range data and the real-time airflow concentration.
4. The NARS technology-based chemical plant gas flow distribution simulation system of claim 1, wherein the specific operation process of the evaluation operation is as follows:
r1: respectively carrying out difference calculation on the real-time air flow range data and the real-time air flow concentration data, the air flow range data and the air flow concentration data to obtain a range data difference value P1 and a concentration data difference value P2, setting two difference preset values A1 and A2, and respectively comparing the difference values with a range data difference value P1 and a concentration data difference value P2, wherein the method specifically comprises the following steps:
k1: when the P1 is not less than A1, the airflow range is judged to be within the error range, the airflow range of the data image is judged to be accurate, and a range correct signal is generated;
k2: when P1 is larger than A1, the airflow range is judged to be out of the error range, the airflow range of the data image is judged to be inaccurate, and a range deviation signal is generated;
k3: when the P2 is not less than A2, the airflow concentration is judged to be within the error range, the airflow concentration of the data image is judged to be accurate, and a concentration correct signal is generated;
k4: when P2 is larger than A2, the airflow concentration is judged to be out of the error range, the airflow concentration of the data image is judged to be inaccurate, and a concentration chaotic signal is generated;
r2: acquiring real-time airflow position data and airflow position data, marking the real-time airflow position data and the airflow position data as ZBl and zbl for comparison, wherein the ZBl coordinates are (Xa1, Yc1) and the zbl coordinates are (Xa2, Yc2), wherein a and c are both natural numbers, and the position change difference value of the real-time airflow position data and the airflow position data is ZBl and zbl difference value
Wherein Gh is a difference number, and h is 1,2,3.
R3: substituting the above-mentioned Gh in R2 into the calculation formula
Wherein P isGhExpressed as the mean value of the differences Gh between ZBl and zbl, a mean preset value GF is set and is compared with PGhComparing, specifically comprising:
ER 1: when GF is less than or equal to PGhIf so, judging that the position change is small, and the simulation degree of the data image is accurate to generate a position accurate signal;
ER 2: when GF < PGhIf so, the position is judged to be changed greatly, the simulation degree of the data image is inaccurate, and a position error signal is generated.
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