CN108009337A - A kind of on-line proving system based on process simulation software - Google Patents
A kind of on-line proving system based on process simulation software Download PDFInfo
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Abstract
A kind of on-line proving system based on process simulation software, Web application modules receive the instruction of user terminal Web browser, log-on data acquisition module gathered data, reconciled through data after module is reconciled the data collected and pass to simulation calculation module, simulation calculation module starts calibration simulation model, result is output to template engine module after the completion of simulation calculation module simulation calculating, template engine module updates result to calibration report template, new calibration report is generated, new calibration report is returned to user terminal Web browser by Web application modules.The present invention realizes onlineization and the automation of production process calibration, substitutes and manually carries out data record, statistics and analysis, and writes the work of report.The calibration report generation cycle greatly shortens, and a few minutes are shorten to from conventional several weeks, can provide the basic data of characterization production process operation conditions for technologist in time, and provide foundation for technological transformation technical measures.
Description
Technical Field
The invention relates to an online calibration method in a production process. In particular to an on-line calibration system based on process simulation software.
Background
The process simulation is a theory and a method for comprehensively applying subjects such as process control, system engineering, mathematical computation and the like, and is a technology for describing unit processes, equipment and the whole process system in the industries such as chemical engineering and the like by using a computer. The technology comprises a static simulation mode and a dynamic simulation mode, can calculate material balance, heat balance, phase balance and the like of a chemical process, and can predict the influence of the change of an operating variable on a process technology. The technology is a product of fusion of engineering technology and computer technology, and with the development of computer technology, the technology provides a fast and efficient method for comprehensive analysis and optimization of a chemical device system.
Device calibration refers to the collection of process data that can reflect the production state of a device during production. The device, the operation unit and the equipment are subjected to material, heat and process calculation, so that the material balance, the product distribution, the product yield, the energy consumption and material consumption, the heating furnace load, the cold exchange equipment capacity, the rectifying tower load and the unit running state of the device are mastered, the problems in actual production are analyzed and found, and a reliable basis is provided for further optimizing operation and technical improvement and improving economic and technical indexes.
At present, the calibration of the petrochemical enterprise device is generally divided into 3 steps of data acquisition, data analysis and report writing, and all the work is finished manually. The data acquisition lasts for 72 hours generally, a specially-assigned person manually records online measurement data (generally, the online measurement data is recorded once per hour) in the production process, material composition analysis data which cannot be measured online is derived from an LIMS database, technicians can perform simulation calculation and sorting analysis by using the acquired data, and engineers and technicians lack the simulation calculation knowledge possibly need to spend several weeks to complete a complete calibration report.
Disclosure of Invention
The invention aims to solve the technical problem of providing an online calibration system based on process simulation software, which overcomes the defects of long calibration time period, high labor intensity and lack of unmeasured key parameters in reports of the conventional device.
The technical scheme adopted by the invention is as follows: an online calibration system based on process simulation software is characterized in that a Web application module receives an instruction of a Web browser at a user end, a data acquisition module is started to acquire data, the acquired data are transferred to a simulation calculation module after being reconciled by a data reconciliation module, the simulation calculation module starts a calibration simulation model, a result is output to a template engine module after the simulation calculation of the simulation calculation module is completed, the template engine module updates the result to a calibration report template to generate a new calibration report, and the Web application module returns the new calibration report to the Web browser at the user end, specifically:
the data acquisition module is used for acquiring operation data and assay data of the production process on line from the real-time database and the LIMS database;
the data input end of the data reconciliation module is connected with the data output end of the data acquisition module and is used for correcting the data acquired by the data acquisition module, eliminating the system error and meeting the requirements of material balance and energy balance;
the calibration simulation model is connected with the data input end and the data output end of the simulation calculation module and used for calculating material balance, energy balance and equipment energy efficiency in the production process;
the analog computation module is respectively connected with the data output end of the data reconciliation module and the data input end of the template engine module and is used for performing analog computation on the reconciled data and outputting an analog computation result;
the calibration report template is used for binding a simulation calculation result at a specified position in a report file customized in the actual production process to generate a calibration report;
the template engine module is used for updating the simulation calculation result output by the simulation calculation module to the calibration report template to generate a calibration report and outputting the calibration report to the Web application module;
and the data input end of the Web application module is respectively connected with the template engine module and the data output end of the Web browser at the user end, and the data output end of the Web application module is respectively connected with the data acquisition module and the data input end of the Web browser at the user end and used for calling the data of the data acquisition module, the analog computation module and the template engine module according to the parameters and the instructions of the Web browser at the user end, generating a calibration report on line and returning the calibration report to the Web browser at the user end in HTML, WORD and PDF file formats.
The data acquisition module is communicated with the real-time database and the LIMS database through an ODBC interface, the operation data comprise temperature, pressure, flow and liquid level of logistics and equipment, the assay data comprise quality analysis data of raw materials, intermediate materials and products, and the online acquired data comprise a real-time value, a historical value, a maximum value, a minimum value, an average value and a standard deviation value.
The data reconciliation module corrects the data acquired by the data acquisition module, eliminates system errors and meets the requirements of material balance and energy balance, and the data correction method adopts 1 of the following 6:
(a) Amplitude limiting filtering method
According to empirical judgment, determining the maximum deviation value allowed by two times of sampling, setting the maximum deviation value as A, and judging each time a new value is detected: if the difference between the current new value and the last value is < = A, the current new value is valid, if the difference between the current new value and the last value is greater than A, the current new value is invalid, the current new value is abandoned, and the last value is used for replacing the current value;
(b) Median method
Continuously sampling for N times, wherein N is an odd number, the sampling values of the N times are arranged according to the size, and the intermediate value is taken as the effective value;
(c) Arithmetic mean method
Continuously taking N sampling values to perform arithmetic mean operation;
(d) Recursive averaging method
Taking N sampling values continuously as a queue, fixing the length of the queue as N, putting a new data sampled each time into the tail of the queue according to a first-in first-out principle, throwing away a data at the head of the original queue, and carrying out arithmetic mean operation on the N data in the queue to obtain a new filtering result;
(e) Amplitude limiting averaging method
The method is a combination of an amplitude limiting filtering method and a recursive average filtering method, and new data sampled each time are subjected to amplitude limiting processing and then are sent to a queue for recursive average filtering processing;
(f) First order lag method
And taking the parameter a = 0-1, and obtaining the filtering result at this time = (1-a) × the sampling value + a at this time × the filtering result at the last time.
The calculation of the material balance, the energy balance and the equipment energy efficiency in the production process by the calibration simulation model is specifically as follows:
(a) Balance of materials
In the formula: s-loss of material
F i -flow of the ith feed stream
P i Flow of the ith product stream
(b) Energy balance ∑ H in ＝∑H out +Q
In the formula: h in Energy of the inlet device
H out Energy of the discharge device
Q-heat loss
(c) Equipment energy efficiency:
compressor polytropic efficiency eta p Formula for calculation
Basic relational expression of compressor
In the formula: n-coefficient of variation
k-heat capacity ratio, k = Cp/Cv
Cp-isobaric heat capacity
Cv-constant volume heat capacity
η p -efficiency of polytropic
Delta h-enthalpy change
P in Compressor inlet pressure
P out -compressor outlet pressure
V in -molar volume.
The simulation calculation module is used for carrying out simulation calculation on the blended data by utilizing the process simulation software to load the calibration simulation model and outputting a simulation calculation result, and specifically comprises the following steps: the process simulation software comprises Aspen Plus, aspen Hysys and Aspen EDR, the simulation calculation module calls the process simulation software to load the calibration simulation model, the blended data are input into the calibration simulation model, then the calibration simulation model is calculated, and the calculation result is returned to the simulation calculation module.
The on-line calibration system based on the process simulation software realizes the on-line and automation of the calibration in the production process, and replaces the manual work for data recording, statistics and analysis and report writing. The calibration result based on the process simulation software is more reliable and comprehensive, and the defects of insufficient field measurement data and the like can be overcome. The generation period of the calibration report is greatly shortened from several weeks to several minutes, the basic data for representing the operation condition of the production process can be provided for process personnel in time, and a basis is provided for technical improvement.
Drawings
FIG. 1 is a flow chart of an on-line calibration system based on process simulation software according to the present invention.
In the drawings
1: client-side Web browser 2: web application module
3: the data acquisition module 4: real-time database and LIMS database
5: the data reconciliation module 6: analog computation module
7: and (3) calibrating a simulation model 8: template engine module
9: calibration report template
Detailed Description
The present invention relates to a process simulation software-based online calibration system, and more particularly, to a process simulation software-based online calibration system.
As shown in fig. 1, in the online calibration system based on process simulation software of the present invention, a Web application module 2 receives an instruction of a user-side Web browser 1, starts a data acquisition module 3 to acquire data, and transfers the acquired data to a simulation computation module 6 after being reconciled by a data reconciliation module 5, the simulation computation module 6 starts a calibration simulation model 7, the simulation computation module 6 outputs a result to a template engine module 8 after completing the simulation computation, the template engine module updates the result to a calibration report template 9 to generate a new calibration report, and the Web application module 2 returns the new calibration report to the user-side Web browser 1, specifically:
the data acquisition module 3 is used for acquiring operation data and assay data of the production process on line from the real-time database and the LIMS database 4; the data acquisition module 3 is communicated with a real-time database and an LIMS database through an ODBC interface, the operation data comprises temperature, pressure, flow and liquid level of logistics and equipment, the assay data comprises quality analysis data of raw materials, intermediate materials and products, and the online acquired data comprises a real-time value, a historical value, a maximum value, a minimum value, an average value and a standard deviation value.
The data input end of the data harmonizing module 5 is connected with the data output end of the data acquisition module 3 and is used for correcting the data acquired by the data acquisition module 3, eliminating system errors and meeting the requirements of material balance and energy balance;
the data reconciliation module 5 corrects the data collected by the data collection module 3, eliminates the system error, and meets the material balance and the energy balance, and the data correction method adopts 1 of the following 6:
(a) Amplitude limiting filtering method
According to empirical judgment, determining the maximum deviation value allowed by two times of sampling, setting the maximum deviation value as A, and judging each time a new value is detected: if the difference between the current new value and the last value is less than = A, the current new value is valid, if the difference between the current new value and the last value is greater than A, the current new value is invalid, the current new value is abandoned, and the last value is used for replacing the current value;
(b) Median method
Continuously sampling for N times, wherein N is an odd number, the sampling values of the N times are arranged according to the size, and the intermediate value is taken as the effective value;
(c) Arithmetic mean method
Continuously taking N sampling values to perform arithmetic mean operation;
(d) Recursive averaging method
Taking N continuous sampling values as a queue, fixing the length of the queue to be N, putting a new data sampled each time into the tail of the queue according to a first-in first-out principle, throwing away a data at the head of the original queue, and carrying out arithmetic mean operation on the N data in the queue to obtain a new filtering result;
(e) Amplitude limiting averaging method
The method is a combination of an amplitude limiting filtering method and a recursive average filtering method, and new data sampled each time are subjected to amplitude limiting processing and then are sent to a queue for recursive average filtering processing;
(f) First order lag method
Taking the parameter a = 0-1, and the filtering result = (1-a) = (sampling value + a) of this time and the filtering result of the last time.
The calibration simulation model 7 is connected with the data input end and the data output end of the simulation calculation module 6 and is used for calculating material balance, energy balance and equipment energy efficiency in the production process; the specific calculation of material balance, energy balance and equipment energy efficiency in the production process is as follows:
(a) Material balance
In the formula: s-loss of material
F i The flow rate of the ith feed stream
P i Flow of the ith product stream
(b) Energy balance ∑ H in ＝∑H out +Q
In the formula: h in Energy of the inlet means
H out Energy of the discharge device
Q-heat loss
(c) Equipment energy efficiency:
compressor polytropic efficiency eta p Formula for calculation
Basic relational expression of compressor
In the formula: n-coefficient of variation
k-heat capacity ratio, k = Cp/Cv
Cp-isobaric heat capacity
Cv-constant volume heat capacity
η p -polytropic efficiency
Delta h-enthalpy change
P in Compressor inlet pressure
P out -compressor outlet pressure
V in -molar volume.
The simulation calculation module 6 is respectively connected with the data output end of the data reconciliation module 5 and the data input end of the template engine module 8 and is used for performing simulation calculation on the reconciled data and outputting a simulation calculation result;
the simulation calculation module 6 is used for performing simulation calculation on the blended data by loading a calibration simulation model through process simulation software and outputting a simulation calculation result, and specifically comprises the following steps: the process simulation software comprises Aspen Plus, aspen Hysys and Aspen EDR, the simulation calculation module calls the process simulation software to load the calibration simulation model, the blended data are input into the calibration simulation model, then the calibration simulation model is calculated, and the calculation result is returned to the simulation calculation module.
A calibration report template 9, which is used for binding a simulation calculation result at a specified position in a report file customized in the actual production process to generate a calibration report;
the template engine module 8, the data input end and the data output end are connected to the calibration report template 9 respectively, the data input end is also connected to the simulation computation module 6, and the template engine module is used for updating the simulation computation result output by the simulation computation module 6 to the calibration report template to generate a calibration report and outputting the calibration report to the Web application module 2;
and the data input end of the Web application module 2 is respectively connected with the template engine module 8 and the data output end of the user side Web browser 1, and the data output end of the Web application module is respectively connected with the data acquisition module 3 and the data input end of the user side Web browser 1, and the Web application module is used for calling the data of the data acquisition module 3, the analog computation module 6 and the template engine module 8 according to the parameters and instructions of the user side Web browser 1, generating a calibration report on line, and returning the calibration report to the user side Web browser 1 in HTML, WORD and PDF file formats.
Examples of the invention
A delayed coker is illustrated below:
a certain delayed coking device is built in 10 months in 2007, and one-time start in 12 months in 2009 is successful, so that a qualified product is produced. The method takes the vacuum residue produced by a newly built 1000 ten thousand ton/year atmospheric and vacuum distillation unit as a raw material to carry out secondary processing, and the annual vacuum residue treatment capacity is 230 ten thousand ton. Device floor area 210 × 117=2470m 2 About 36.855 mu, is positioned at the west side of a tank field of an aromatic hydrocarbon department, and is newly built at the north side of a 20 ten thousand ton/year sulfur recovery device and at the south side of a newly built sewage treatment plant. The device is designed by Luoyang Petrochemical Engineering (LPEC) company, and adopts the domestic advanced process flow of 'flexibly adjusting the circulation ratio'.
The delayed coking device consists of two parts, namely process production and petroleum coke treatment, and is divided into eight production units according to respective production characteristics. The process production part comprises five units of a heating furnace, a reaction unit, a fractionation unit, an absorption stabilization unit and a steam blowing and emptying unit; the petroleum coke treatment part comprises three units of hydraulic decoking, coke cooling water sealing treatment and petroleum coke loading.
Calibrating the content:
(1) Device processing capability
(2) The device has balanced material, energy and material consumption
(3) Main process parameter index of equipment
(4) Product quality level
And (3) calibrating results:
1. properties of the raw materials
The properties of the raw materials in this calibration are shown in Table 1, and the density of the raw materials is 1060.9kg/m 3 Residual raw materialThe highest carbon content is 26.8%, compared with the design, the raw material property during the calibration period is heavy, the carbon residue is high, and the coke yield is high; the sulfur content calibration period was 4.291% lower than the design 5.29%.
TABLE 1 vacuum residuum
2. Production load
As shown in Table 2, the residual oil treatment capacity in the calibration period is 18446.26 tons, the daily average load is 6148.75 tons/day, the annual treatment capacity is 215.21 ten thousand tons calculated by the annual operation time of 8400 hours, and the design requirement of 230 ten thousand tons/year is not met.
During the calibration of the device, the external low crude gas amount of the absorption stabilization system treatment device is lower than a design value, the high crude gas amount is lower than the design value, the external light hydrocarbon amount is higher than the design value, and the whole treatment capacity (residual oil + external materials) of the device is less than 6733 tons/day of the design.
TABLE 2 production load
| Item | Unit | Design value | Actual value |
| Residual oil treatment | t | 18446.26 | |
| Average daily load | t/d | 6571.44 | 6148.75 |
| Annual throughput | Wan Dun | 230 | 215.21 |
| Average daily load of light hydrocarbons | t/d | 0 | 1.36 |
| Daily average load of plateau qi | t/d | 6.65 | 0.60 |
| Low daily average load of crude gas | t/d | 154.2 | 117.48 |
| Is totaled | t/d | 6732.29 | 6268.20 |
3. Device circulation ratio
The circulation ratio of the device during calibration is controlled to be 0.23, which is lower than the designed circulation ratio of 0.4, the circulation ratio of the device is low, and the device has great benefits for improving the treatment capacity and increasing the liquid yield of the device, and is specifically shown in Table 3.
TABLE 3 device circulation ratio
4. Material balance
As can be seen from the data in Table 4, the yield of dry gas is higher than the design value, the yield of liquefied gas is higher than the design value, the yield of gasoline is higher than the design value, the yield of diesel is lower than the design value, and the yield of wax oil is higher than the design value; the light yield is 35.36 percent and is lower than the design value, the liquid yield is 58.42 percent and is higher than the design value, which has direct relation with the properties of raw materials and the control of the circulation ratio, the control of the circulation ratio is low, and the carbon residue of the raw materials is lower than the design value as the main reason.
From the aspect of processing loss, the average processing loss during the calibration period is 0.19t/h, the average loss rate is about 0.07%, and the loss rate is normal, the main reason is that the coke amount is calculated after the detection of the air height of a coke tower, an error exists, meanwhile, the density of the coke in the tower is an estimated value, a large error exists, the metering of the coke is inaccurate, and meanwhile, the backwashing sump oil is not effectively metered.
TABLE 4 summary of material balance data
5. Accounting for energy consumption
As can be seen from the data in Table 5, the average energy consumption during the calibration of the plant was 25.1129 kg standard oil/ton raw material (energy consumption for removing hot output, hot feed, and low temperature heat output), and the design total plant energy consumption was 31.75 kg standard oil/ton raw material (energy consumption values for low temperature heat output, hot feed, nitrogen, clean air, and wastewater were subtracted from the design energy consumption) and the calibration energy consumption was lower than the design energy consumption value.
TABLE 5 energy consumption accounting summary sheet
6. Product quality analysis
1) Dry gas and liquefied gas
As shown in Table 6, the content of components above C3 in the dry gas during calibration was 4.0%, which was higher than the design value by 3%, which was lower than the index requirement. The content of the components below C2 of the liquefied gas is respectively 0.01 percent and 0.05 percent, which are lower than the index requirement, and the content of the components above C5 is respectively 0.19 percent and 0.16 percent, which are lower than the index requirement.
TABLE 6 Properties of Dry gas and liquefied gas
2) Diesel oil
As shown in Table 7, the 95% point of the diesel during calibration was 313 ℃ and 315 ℃ respectively, which was lower than 349 ℃ for the design, which was lower than <365 ℃ for the control index requirement, and the product was acceptable.
TABLE 7 Properties of diesel fuels
| Analysis item | Unit of | Design value (index) | 2016 (5 months and 5 days) | 2016 (5 months and 6 days) |
| IP | ℃ | 203 | 170 | 176 |
| 10％ | ℃ | 231 | 227 | 233 |
| 50％ | ℃ | 283 | 267 | 270 |
| 90％ | ℃ | 338 | 304 | 303 |
| 95％ | ℃ | 349(≯365) | 313 | 315 |
| EP | ℃ | 364 | 323 | 330 |
| Density (20 ℃ C.) | kg/m 3 | 864 | 855 | 855 |
| Sulfur content | ％wt | 2.5 | 2.392 | 2.392 |
3) Wax oil
As shown in Table 8, the carbon residue analysis of the wax oil during calibration was 0.06%, which was not higher than 1.5% below the index requirement, and the product quality was acceptable, which was also lower than 1.0% of the design, which is related to the lighter wax oil component and the higher diesel oil component content in the wax oil. The initial boiling point of the wax oil is 205 ℃, which is lower than the designed 345 ℃, and is also lower than the dry point 323 ℃ of the diesel oil, and the difference between the initial boiling point of the wax oil and the dry point of the diesel oil is 118, which shows that the overlapping degree of the wax oil and the diesel oil is very high, and a great part of diesel oil components are not separated out in the wax oil, which is related to the low steam temperature and the poor stripping effect of a wax oil stripping tower and the property of raw materials.
TABLE 8 Properties of wax oils
4) Petroleum coke
As shown in Table 9, the analysis of the volatile matter content of the coke during the calibration period is respectively 8.35% and 8.35%, which is lower than 10.5% of the design value and lower than not higher than 14% required by the control index, and the product is qualified. The sulfur content was 7.01% and 7.01%, respectively, which was lower than the designed 7.9%, depending on the amount of sulfur in the residue.
TABLE 9 Properties of the Petroleum Coke
| Analysis item | Unit of | Design value (index) | 2016 (5 months and 5 days) | 2016 (5 months and 6 days) |
| Ash content | ％ | 0.15(≯1) | 0.29 | 0.29 |
| Volatile component | ％ | 10.5(≯14) | 8.35 | 8.35 |
| Total sulfur content | ％ | 7.9(≯9) | 7.01 | 7.01 |
7. Analysis of each of the main operating parameters
1) Heating furnace system
As shown in tables 10 and 11, the furnace temperatures of the points A and B of the heating furnace accord with the design range, the furnace outlet temperature does not accord with the design range, the oxygen content of the flue gas of the heating furnace is between 1.49 and 2.80 percent, the flue gas temperature of the furnace A is between 122.0 and 134.3 ℃, the flue gas temperature of the furnace B is between 133.8 and 145.4 ℃, and the flue gas temperature of the furnace B accords with the design index of 110 to 150 ℃.
During calibration, the thermal efficiency of the furnace A is between 92.15 and 92.93 percent, the thermal efficiency of the furnace B is between 91.72 and 92.27 percent, the design furnace efficiency is 91.1 percent, and the design index is met.
TABLE 10 furnace F-101A Process Material operating conditions
TABLE 11 furnace F-101B Process Material operating conditions
2) Crude oil preheating system
As shown in Table 12, the final temperature of the heat exchange of the residual oil was designed to be 301 ℃ and the temperature of the oil after mixing with the circulating oil was 318 ℃ in D-102, and the calibration data showed that the temperature was 299.7 ℃ which is lower than the design temperature, the feed temperature of the heating furnace was low and the fuel gas consumption was high.
The temperature of residual oil entering the device is 162.3 ℃ and is higher than the designed 155 ℃, and the temperature has great influence on the heat exchange final temperature.
TABLE 12 raw material preheat operating data
3) Fractionation system
As shown in Table 13, the temperature at the top of the fractionating tower is controlled to be above 130.3 ℃, higher than the designed 111 ℃, and the top pressure is controlled to be between 0.098 and 0.135MPa, higher than the designed 0.1MPa, within the process index range; the pressure of D-103 is about 0.089MPa, which is higher than the designed 0.04MPa.
TABLE 13 fractionating column operating data
4) Absorption stabilizing system
As shown in Table 14, the absorption stabilizing system has qualified control indexes during the calibration of the device, the pressure of the top of the reabsorption tower is controlled to be about 1.209MPa and higher than the designed 1.0MPa, the pressure is high, and the absorption effect is good.
The temperature of the bottom of the desorption tower is controlled to be 132.3-142.9 ℃ which is lower than the designed 160 ℃, and is in the process index range; the temperature of the stable tower bottom is controlled to be between 182.1 and 188.1 ℃ and is lower than the designed 205 ℃, and the temperature is in the process index range.
TABLE 14 absorption of Stable operating data
5) Operating conditions of air pressure unit
As shown in Table 15, during calibration, the air compressor train was operating normally with an average compressor inlet air enrichment of 32083, which is lower than the designed 33083Nm 3 The amount of/h, the load is slightly lower than the design. The normal range of the variable efficiency of the compressor is 0.7-0.84, the first-stage variable efficiency is normal, and the second-stage variable efficiency is normal. The rotating speed of the steam turbine is about 7207 r/min and is lower than the designed 7805 r/min; the steam consumption of 3.5MPa is higher than the designed consumption of 40.5t/h, the consumption is related to the total amount of rich gas, the first-stage inlet pressure is 0.081MPa and is higher than the designed 0.04MPa, and the consumption is also lower than the designed consumption.
Meter 15 air pressure unit operation condition
In conclusion, after the method is implemented, a complete calibration report can be quickly provided, a large amount of time is saved for process personnel, and effective basis is provided for the process personnel to master the running state of the production device and optimize and adjust corresponding process operation parameters in time, so that reliable technical guidance is provided for stable production, cost reduction and efficiency improvement of the device.
Claims (5)
1. The on-line calibration system based on the process simulation software is characterized in that a Web application module (2) receives an instruction of a user side Web browser (1), a data acquisition module (3) is started to acquire data, the acquired data are transferred to a simulation calculation module (6) after being reconciled by a data reconciliation module (5), the simulation calculation module (6) starts a calibration simulation model (7), the simulation calculation module (6) outputs a result to a template engine module (8) after completing the simulation calculation, the template engine module updates the result to a calibration report template (9) to generate a new calibration report, and the Web application module (2) returns the new calibration report to the user side Web browser (1), specifically:
the data acquisition module (3) is used for acquiring operation data and assay data of the production process on line from the real-time database and the LIMS database (4);
the data input end of the data reconciliation module (5) is connected with the data output end of the data acquisition module (3) and is used for correcting the data acquired by the data acquisition module (3), eliminating system errors and meeting the requirements of material balance and energy balance;
the calibration simulation model (7) is connected with the data input end and the data output end of the simulation calculation module (6) and is used for calculating material balance, energy balance and equipment energy efficiency in the production process;
the simulation calculation module (6) is respectively connected with the data output end of the data reconciliation module (5) and the data input end of the template engine module (8) and is used for carrying out simulation calculation on the reconciled data and outputting a simulation calculation result;
a calibration report template (9) used for binding a simulation calculation result at a specified position in a report file customized in the actual production process to generate a calibration report;
the template engine module (8), the data input end and data output end connect said calibration report template (9) separately, the data input end still connects the said analog computation module (6), is used for updating the analog computation result that the analog computation module (6) outputs to the calibration report template and producing the calibration report, and output the calibration report to the Web application module (2);
and the data input end of the Web application module (2) is respectively connected with the data output ends of the template engine module (8) and the user side Web browser (1), and the data output end of the Web application module is respectively connected with the data acquisition module (3) and the data input end of the user side Web browser (1) and is used for calling the data of the data acquisition module (3), the analog computation module (6) and the template engine module (8) according to the parameters and instructions of the user side Web browser (1), generating a calibration report on line and returning the calibration report to the user side Web browser (1) in HTML, WORD and PDF file formats.
2. The on-line calibration system based on process simulation software as claimed in claim 1, wherein the data collection module (3) is in communication with the real-time database and the LIMS database via an ODBC interface, the operation data includes temperature, pressure, flow rate and liquid level of logistics and equipment, the assay data includes quality analysis data of raw materials, intermediate materials and products, and the on-line collected data includes real-time values, historical values, maximum values, minimum values, average values and standard deviation values.
3. The on-line calibration system based on the process simulation software as claimed in claim 1, wherein the data reconciliation module (5) corrects the data acquired by the data acquisition module (3) to eliminate system errors and satisfy material balance and energy balance, and the data correction method adopts 1 of the following 6:
(a) Amplitude limiting filtering method
According to empirical judgment, determining the maximum deviation value allowed by two times of sampling, setting the maximum deviation value as A, and judging each time a new value is detected: if the difference between the current new value and the last value is less than = A, the current new value is valid, if the difference between the current new value and the last value is greater than A, the current new value is invalid, the current new value is abandoned, and the last value is used for replacing the current value;
(b) Median method
Continuously sampling for N times, wherein N is an odd number, the sampling values of the N times are arranged according to the size, and the intermediate value is taken as the effective value;
(c) Arithmetic mean method
Continuously taking N sampling values to perform arithmetic mean operation;
(d) Recursive averaging method
Taking N continuous sampling values as a queue, fixing the length of the queue to be N, putting a new data sampled each time into the tail of the queue according to a first-in first-out principle, throwing away a data at the head of the original queue, and carrying out arithmetic mean operation on the N data in the queue to obtain a new filtering result;
(e) Amplitude limiting averaging method
The method is a combination of an amplitude limiting filtering method and a recursive average filtering method, wherein new data sampled each time are subjected to amplitude limiting processing and then are sent to a queue for recursive average filtering processing;
(f) First order lag method
And taking the parameter a = 0-1, and obtaining the filtering result at this time = (1-a) × the sampling value + a at this time × the filtering result at the last time.
4. The on-line calibration system based on the process simulation software as claimed in claim 1, wherein the calculation of the material balance, the energy balance and the equipment energy efficiency in the production process by the calibration simulation model (7) is specifically as follows:
(a) Material balance
In the formula: s-loss of material
F i The flow rate of the ith feed stream
P i Flow of the ith product stream
(b) Energy balance ∑ H in ＝∑H out +Q
In the formula: h in Energy of the inlet device
H out Energy of the discharging device
Q-heat loss
(c) Equipment energy efficiency:
compressor polytropic efficiency eta p Formula for calculation
Basic relational expression of compressor
In the formula: n-coefficient of variation
k-heat capacity ratio, k = Cp/Cv
Cp-isobaric heat capacity
Cv-constant volume heat capacity
η p -polytropic efficiency
Delta h-enthalpy change
P in Compressor inlet pressure
P out -compressor outlet pressure
V in -molar volume.
5. The on-line calibration system based on process simulation software according to claim 1, wherein the simulation computation module (6) utilizes the process simulation software to load a calibration simulation model to perform simulation computation on the blended data, and outputs a simulation computation result, specifically: the process simulation software comprises Aspen Plus, aspen Hysys and Aspen EDR, the simulation calculation module calls the process simulation software to load the calibration simulation model, the blended data are input into the calibration simulation model, then the calibration simulation model is calibrated to calculate, and the calculation result is returned to the simulation calculation module.
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