CN117707101B - Production line supervision and control system for large-scale processing of carbon nanotubes - Google Patents
Production line supervision and control system for large-scale processing of carbon nanotubes Download PDFInfo
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- 239000002041 carbon nanotube Substances 0.000 title claims abstract description 244
- 229910021393 carbon nanotube Inorganic materials 0.000 title claims abstract description 244
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- 238000011156 evaluation Methods 0.000 claims abstract description 172
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Abstract
The invention belongs to the technical field of carbon nanotube production control, in particular to a production line supervision control system for large-scale carbon nanotube processing, which comprises a supervision control platform, an intelligent monitoring module, a reactor regulation and control module, a reactor recapture module, a production performance evaluation module and a remote control end; according to the invention, the intelligent monitoring module is used for monitoring the operation of the reactor in the carbon nanotube production line, the corresponding reactor is operated and regulated when the unqualified signal of the operation condition is generated, the abnormal capture and judgment are carried out on the reactor through the reactor abnormal capture module, the production performance condition of the corresponding reactor is analyzed through the production performance evaluation module when the analysis signal of the reactor is generated, and the remote control end is used for giving an early warning when the maintenance signal or the unqualified signal of the production table of the reactor is generated, so that the intelligent degree is high, the production efficiency, the production stability and the production quality of the carbon nanotube production line are guaranteed, and the difficulty of large-scale processing of the carbon nanotubes is remarkably reduced.
Description
Technical Field
The invention relates to the technical field of carbon nanotube production control, in particular to a production line supervision and control system for large-scale carbon nanotube processing.
Background
The carbon nano tube mainly comprises a plurality of layers to tens of layers of coaxial circular tubes formed by carbon atoms arranged in a hexagonal way, and the layers keep a fixed distance, so that the carbon nano tube has the characteristics of good conductivity, high-temperature stability, large length-diameter ratio, high specific surface area and the like, and has wide application prospects in the fields of electronics, materials, biomedicine and the like, for example, the carbon nano tube can be used as an electrode material of a lithium ion battery to improve the charge-discharge capacity and the current density of the lithium ion battery, and can also be used as a catalyst carrier, a sensor material, a reinforcing material and the like;
The production line of the carbon nano tube mainly comprises corresponding reactors, the corresponding production line is required to be monitored and controlled in the production process of the carbon nano tube, the reactors in a plurality of groups of carbon nano tube production lines are difficult to effectively monitor and automatically adaptively regulate and control at present, abnormal capturing and accurate evaluation of production performance of the reactors cannot be realized, the production efficiency, the production stability and the production quality of the carbon nano tube production line are not guaranteed, and the difficulty of large-scale processing of the carbon nano tube is increased;
In view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide a production line supervision control system for large-scale processing of carbon nanotubes, which solves the problems that the reactors in a plurality of groups of carbon nanotube production lines are difficult to effectively monitor and automatically adaptively regulate and control, abnormal capture and accurate evaluation of production performance of the reactors cannot be realized, and the large-scale processing difficulty of the carbon nanotubes is high in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the production line supervision control system for large-scale carbon nanotube processing comprises a supervision control platform, an intelligent monitoring module, a reactor regulation and control module, a reactor different-catching module, a production performance evaluation module and a remote control end; the monitoring control platform acquires all carbon nanotube production lines needing to be monitored, the intelligent monitoring module monitors the operation of the reactors in the carbon nanotube production lines, generates operation condition qualified signals or operation condition unqualified signals of the corresponding reactors through analysis, and sends the operation condition unqualified signals to the reactor regulation and control module through the monitoring control platform;
When the reactor regulation and control module receives the unqualified signal of the operation condition, carrying out operation regulation and control on the corresponding reactor, recording the regulation and control duration, generating regulation and control early warning information if the operation regulation and control is not completed within a specified time, and sending the regulation and control early warning information to a supervision and control platform;
The reactor abnormal capture module is used for carrying out abnormal capture judgment on the reactor, generating a reactor maintenance signal and a reactor production analysis signal through analysis, sending the reactor maintenance signal of the corresponding reactor to a remote control end through a supervision and control platform, and sending the reactor production analysis signal of the corresponding reactor to a production performance evaluation module through the supervision and control platform; after receiving the reactor production analysis signals, the production performance evaluation module analyzes the production performance conditions of the carbon nano tube production of the corresponding reactor, generates production table disqualification signals or production table qualification signals through analysis, and sends the production table disqualification signals of the corresponding reactor to a remote management and control end through a supervision and control platform.
Further, the specific operation process of the intelligent monitoring module comprises the following steps:
Collecting real-time temperatures at a plurality of positions inside a reactor in a corresponding carbon nano tube production line, carrying out average calculation on all the real-time temperatures to obtain a production temperature detection value, collecting air pressure data inside the reactor in the corresponding carbon nano tube production line and marking the air pressure data as a production pressure detection value, and collecting flow data of carbon source gas input into the reactor in the corresponding carbon nano tube production line and marking the flow data as a production carbon source flow value; calculating the difference value between the production temperature detection value and the set standard temperature value, taking an absolute value to obtain a production temperature condition value, and obtaining a production pressure condition value and a production carbon source value in a similar way;
Performing numerical calculation on the production temperature condition value, the production pressure condition value and the production carbon source value to obtain a carbon nanotube yield test value, performing numerical comparison on the carbon nanotube yield test value and a preset carbon nanotube yield test threshold, and generating an operation condition disqualification signal if the carbon nanotube yield test value exceeds the preset carbon nanotube yield test threshold; and if the carbon nanotube yield value does not exceed the preset carbon nanotube yield threshold, generating an operation condition qualification signal.
Further, the specific analysis process for performing the abnormality capturing analysis on the reactor is as follows:
Collecting the times of generating regulation and control early warning information by a reactor in a corresponding carbon nano tube production line in unit time, marking the times as a reactor regulation and control value, collecting the total times of regulating and controlling the reactor in the corresponding carbon nano tube production line by a reactor regulation and control module in unit time, marking the total times as a reactor total regulation value, and calculating the ratio of the reactor regulation and control value to the reactor total regulation value to obtain a reactor deterioration regulation and control occupation value;
The method comprises the steps of carrying out numerical calculation on a reactor adjustment detection value and a reactor adjustment degradation detection occupation value to obtain a reactor adjustment evaluation value, carrying out numerical comparison on the reactor adjustment evaluation value and a preset reactor adjustment evaluation threshold value, and generating a reactor maintenance detection signal if the reactor adjustment evaluation value exceeds the preset reactor adjustment evaluation threshold value.
If the reactor condition evaluation value does not exceed the preset reactor condition evaluation threshold, setting a plurality of detection time points in unit time, performing variance calculation on real-time temperatures at a plurality of positions inside the reactor in the carbon nano tube production line corresponding to the corresponding detection time points to obtain a temperature cloth detection value, performing numerical comparison on the temperature cloth detection value and the preset temperature cloth detection threshold, and if the temperature cloth detection value exceeds the preset temperature cloth detection threshold, judging that the inside of the reactor corresponding to the corresponding detection time points is in a state with uneven temperature distribution;
Collecting the difference between the maximum value and the minimum value of the detected values of the production temperature in the reactor in the corresponding carbon nano tube production line in unit time, marking the difference as the production temperature amplitude deviation value, acquiring the production air pressure amplitude deviation value and the production carbon source amplitude deviation value in a similar way, and marking the number occupation ratio of the detected points in the state of uneven temperature distribution in the reactor in the corresponding carbon nano tube production line in unit time as the temperature non-uniform time occupation value;
Performing numerical calculation on the reactor condition evaluation value, the temperature non-uniformity time occupying value, the production temperature amplitude deviation value, the production air pressure amplitude deviation value and the production carbon source amplitude deviation value to obtain a reactor abnormal capture value, performing numerical comparison on the reactor abnormal capture value and a preset reactor abnormal capture threshold value, and generating a reactor maintenance detection signal if the reactor abnormal capture value exceeds the preset reactor abnormal capture threshold value; if the reactor differential capture value does not exceed the preset reactor differential capture threshold, generating a reactor analysis signal.
Further, the specific operation process of the production performance evaluation module comprises the following steps:
Setting an evaluation period, collecting the total operation duration of the reactor in the corresponding carbon nano tube production line in the evaluation period, collecting the carbon source gas amount consumed by the reactor in the corresponding carbon nano tube production line in the evaluation period, marking the carbon source gas amount as the carbon source consumption amount, and calculating the ratio of the carbon source consumption amount to the total operation duration to obtain a carbon source consumption meter value; obtaining a preset carbon source consumption table value range, carrying out difference value calculation on the carbon source consumption table value and the median value of the preset carbon source consumption table value range, and taking an absolute value to obtain a carbon source consumption analysis value;
Collecting the yield of the carbon nanotubes produced by the corresponding carbon nanotube production line in the evaluation period, and calculating the ratio of the consumption of the carbon source to the yield of the produced carbon nanotubes to obtain the carbon nanotube production table value; acquiring purity detection information of carbon nanotubes produced by a corresponding carbon nanotube production line in an evaluation period, and acquiring the non-qualification rate of the carbon nanotubes in the production process of a reactor in the corresponding carbon nanotube production line in the evaluation period based on the purity detection information of the carbon nanotubes;
Performing numerical calculation on the carbon source consumption analysis value, the carbon nanotube production table value and the carbon nanotube non-qualification rate to obtain a carbon nanotube production evaluation value, performing numerical comparison on the carbon nanotube production evaluation value and a preset carbon nanotube production evaluation threshold value, and generating a production table non-qualification signal of a corresponding reactor if the carbon nanotube production evaluation value exceeds the preset carbon nanotube production evaluation threshold value; and if the carbon nanotube yield evaluation value does not exceed the preset carbon nanotube yield evaluation threshold value, generating a yield list qualification signal of the corresponding reactor.
Further, the supervision control platform is in communication connection with the production line pipe conveying evaluation module, the production line pipe conveying evaluation module is used for setting an evaluation period with the number of days being L1, carrying out production traceability analysis on all the carbon nanotube production lines in the evaluation period so as to mark the corresponding carbon nanotube production lines as high-grade production lines or low-grade production lines, generating a pipe conveying evaluation disqualification signal or a pipe conveying evaluation qualification signal through analysis, and sending the pipe conveying evaluation disqualification signal to a remote management and control end through the supervision control platform.
Further, the specific analysis process of the production traceability analysis is as follows:
Collecting the times of generating a reactor dimension detection signal and the times of generating a production table disqualification signal by the corresponding carbon nano tube production line in an evaluation period, respectively marking the times as dimension detection signal frequency value and production table disfrequency value, collecting single outage duration of the corresponding carbon nano tube production line stopped running due to faults in the production process in the evaluation period, carrying out summation calculation on all the single outage total duration of the corresponding carbon nano tube production line in the evaluation period to obtain a fault outage analysis value, and marking the number of the single outage duration exceeding a preset single outage duration threshold as an overdriving frequency analysis value;
Performing numerical calculation on the dimension detection signal frequency value, the production table abnormal frequency value, the failure outage time analysis value and the over outage frequency analysis value of the corresponding carbon nanotube production line to obtain a carbon nanotube production line evaluation value, performing numerical comparison on the carbon nanotube production line evaluation value and a preset carbon nanotube production line evaluation threshold value, and marking the corresponding carbon nanotube production line as a high-speed abnormal production line if the carbon nanotube production line evaluation value exceeds the preset carbon nanotube production line evaluation threshold value; and if the evaluation value of the carbon nano tube production line does not exceed the evaluation threshold of the carbon nano tube production line, marking the corresponding carbon nano tube production line as a low-grade production line.
Further, after marking the corresponding carbon nanotube production line as a high-grade production line or a low-grade production line, if the low-grade production line does not exist in the carbon nanotube production line to be monitored, generating a tube transportation evaluation disqualification signal; if the low-grade production line exists in the carbon nano tube production line to be monitored, collecting the number of the high-grade production line and the number of the low-grade production line in the carbon nano tube production line to be monitored, and calculating the ratio of the number of the high-grade production line to the number of the low-grade production line to obtain a high-grade detection value of the production line;
Performing average calculation on the evaluation values of the carbon nanotube production lines of all the carbon nanotube production lines to be monitored to obtain a production line transportation value, performing numerical calculation on the production line transportation value and a production line high-difference detection value to obtain a production line evaluation value, performing numerical comparison on the production line evaluation value and a preset production line evaluation threshold, and generating a transportation line evaluation disqualification signal if the production line evaluation value exceeds the preset production line evaluation threshold; and if the production line evaluation value does not exceed the preset production line evaluation threshold, generating a pipe transportation evaluation qualified signal.
Compared with the prior art, the invention has the beneficial effects that:
1. According to the invention, the intelligent monitoring module is used for monitoring the operation of the reactor in the carbon nanotube production line, the corresponding reactor is operated and regulated when the unqualified signal of the operation condition is generated, the abnormal capturing and judging are carried out on the reactor through the reactor abnormal capturing module, the production performance status of the corresponding reactor is analyzed when the analysis signal of the reactor is generated, and the remote control end is used for giving out early warning when the maintenance signal or the unqualified signal of the production table of the reactor is generated, so that the intelligent degree is high, the production efficiency, the production stability and the production quality of the carbon nanotube production line are guaranteed, and the difficulty of large-scale processing of the carbon nanotubes is remarkably reduced;
2. According to the invention, the production traceability analysis is carried out on all the carbon nano tube production lines in the evaluation period through the production line transportation evaluation module so as to mark the corresponding carbon nano tube production lines as high-grade production lines or low-grade production lines, the operation conditions of all the carbon nano tube production lines in the evaluation period can be effectively evaluated and accurately fed back, the follow-up supervision measures matched with different carbon nano tube production lines are conveniently adopted, the targeted management is realized, and the planning difficulty of a follow-up management scheme is reduced.
Drawings
For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
FIG. 1 is a system block diagram of a first embodiment of the present invention;
Fig. 2 is a system block diagram of a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: as shown in fig. 1, the production line supervision and control system for large-scale processing of carbon nanotubes provided by the invention comprises a supervision and control platform, an intelligent monitoring module, a reactor regulation and control module, a reactor different-capture module, a production performance evaluation module and a remote management and control end; the supervision and control platform obtains all carbon nanotube production lines to be supervised, and the production equipment in the carbon nanotube production lines is mainly a reactor, the supervision and control of the carbon nanotube production lines is mainly aimed at the reactor, the reactor is used for synthesizing carbon nanotubes, and different reactor types such as a tubular reactor, a kettle type reactor and the like can be selected according to specific process requirements;
Further, the carbon source is a starting material for synthesizing the carbon nanotubes, and provides carbon elements required for synthesis, and common carbon sources include methane, ethylene, and the like; during the reaction in the reactor, molecules of the carbon source are activated and decomposed to release single carbon atoms, and the single carbon atoms are polymerized into carbon nanotubes through the action of the catalyst; in addition, the catalyst plays a key role in the synthesis of the carbon nano tube, can accelerate the reaction process and control the morphology of the carbon nano tube, and the common catalyst is iron, nickel, cobalt and other metals and oxides thereof.
The intelligent monitoring module monitors the operation of the reactor in the carbon nanotube production line, generates an operation condition qualified signal or an operation condition unqualified signal of the corresponding reactor through analysis, and sends the operation condition unqualified signal to the reactor regulation and control module through the supervision control platform, so that the real-time monitoring and accurate feedback of the operation condition of the reactor are realized, the corresponding regulation and control of the reactor are conveniently carried out in time, and the production stability and the production effect of the reactor are ensured; specifically, the operation process of the intelligent monitoring module is as follows:
Collecting real-time temperatures at a plurality of positions inside a reactor in a corresponding carbon nano tube production line, carrying out average calculation on the real-time temperatures at all positions to obtain a production temperature detection value, collecting air pressure data inside the reactor in the corresponding carbon nano tube production line and marking the air pressure data as a production pressure detection value, and collecting flow data (namely the amount of carbon source gas input in a certain time) of inputting carbon source gas into the reactor of the corresponding carbon nano tube production line and marking the flow data as a production carbon source flow value;
Carrying out difference calculation on the production temperature detection value and the set standard temperature value and taking an absolute value to obtain a production temperature Kuang Zhi, carrying out difference calculation on the production pressure detection value and the set standard air pressure value and taking an absolute value to obtain a production pressure condition value, carrying out difference calculation on the production carbon source flow value and the set standard flow value and taking an absolute value to obtain a production carbon source value;
by the formula Carrying out numerical calculation on the production temperature Kuang Zhi YL, the production pressure condition value YK and the production carbon source value YS to obtain a carbon nano tube yield test value YP, wherein a1, a2 and a3 are preset proportionality coefficients, and the values of a1, a2 and a3 are positive numbers; and, the larger the value of the carbon nanotube yield inspection value YP is, the worse the current running condition of the corresponding reactor is indicated;
Comparing the carbon nanotube yield value YP with a preset carbon nanotube yield threshold value, and if the carbon nanotube yield value YP exceeds the preset carbon nanotube yield threshold value, indicating that the current running condition of the corresponding reactor is poor, generating a running condition disqualification signal; if the carbon nanotube yield detection value YP does not exceed the preset carbon nanotube yield detection threshold, the current operation condition of the corresponding reactor is good, and an operation condition qualification signal is generated.
When the reactor regulation and control module receives the disqualified signal of the operation condition, the corresponding reactor is operated and regulated, and the regulation and control duration is recorded, wherein the larger the value of the regulation and control duration is, the lower the regulation and control efficiency of the corresponding regulation and control is, the more unfavorable the generation of the carbon nano tube is, the worse the control performance of the corresponding reactor is, and the manual regulation and control are required to be carried out in time; if the operation regulation is not completed within the set time, generating regulation and control early warning information and sending the regulation and control early warning information to the supervision and control platform; preferably, the supervision and control platform sends the regulation and control early warning information of the corresponding reactor to the remote control end, and the remote control end displays the regulation and control early warning information and reminds a manager to manually control the corresponding reactor through manual intervention according to the need;
The reactor abnormal capture module is used for carrying out abnormal capture judgment on the reactor, generating a reactor maintenance signal and a reactor production analysis signal through analysis, sending the reactor maintenance signal of the corresponding reactor to the remote control end through the supervision and control platform, and sending out corresponding early warning after the remote control end receives the reactor maintenance signal so as to remind a manager to timely inspect and maintain the reactor in the corresponding carbon nano tube production line, so that timely treatment on the reactor is realized to ensure the subsequent operation performance; the specific analysis process for the anomaly capture analysis of the reactor is as follows:
Collecting the times of generating regulation and control early warning information by a reactor in a corresponding carbon nano tube production line in unit time, marking the times as a reactor regulation and control value, collecting the total times of regulating and controlling the reactor in the corresponding carbon nano tube production line by a reactor regulation and control module in unit time, marking the total times as a reactor total regulation value, and calculating the ratio of the reactor regulation and control value to the reactor total regulation value to obtain a reactor deterioration regulation and control occupation value; it should be noted that, the larger the values of the reactor adjustment detection value TY and the reactor adjustment detection occupation value TL, the worse the adjustment performance of the corresponding reactor in unit time;
by the formula Carrying out numerical calculation on the reactor adjustment detection value TY and the reactor adjustment degradation detection occupation value TL to obtain a reactor adjustment condition evaluation value TX, wherein, ew1 and ew2 are preset proportionality coefficients, and ew2 is more than ew1 and more than 0; and, the larger the value of the reactor condition evaluation value TX, the larger the probability that the abnormal regulation performance of the reactor exists; and comparing the reactor condition evaluation value TX with a preset reactor condition evaluation threshold value, and generating a reactor maintenance signal if the reactor condition evaluation value TX exceeds the preset reactor condition evaluation threshold value, which indicates that the probability of abnormality of the regulation performance of the reactor is high.
Further, if the reactor condition evaluation value TX does not exceed the preset reactor condition evaluation threshold, a plurality of detection time points are set in a unit time, variance calculation is performed on real-time temperatures at a plurality of positions inside the reactor in the carbon nanotube production line corresponding to the corresponding detection time points to obtain a temperature distribution detection value, the temperature distribution detection value is compared with a preset temperature distribution detection threshold in value, if the temperature distribution detection value exceeds the preset temperature distribution detection threshold, it is indicated that the temperature difference of each position in the reactor corresponding to the corresponding detection time point is large, and the inside of the reactor corresponding to the corresponding detection time point is judged to be in a state with uneven temperature distribution;
And collecting the difference between the maximum value and the minimum value of the production temperature detection values in the reactors in the corresponding carbon nanotube production line in unit time, marking the difference as a production temperature amplitude deviation value, and similarly obtaining a production air pressure amplitude deviation value and a production carbon source amplitude deviation value, wherein the larger the values of the production temperature amplitude deviation value, the production air pressure amplitude deviation value and the production carbon source amplitude deviation value are, the larger the fluctuation of the temperature, the air pressure and the carbon source gas input quantity in the corresponding reactors is, and the more unfavorable the production effect is ensured; marking the number ratio of detection time points in the state of uneven temperature distribution in the reactor in the corresponding carbon nano tube production line in unit time as the temperature uneven time ratio;
by the formula Carrying out numerical calculation on the reactor condition evaluation value TX, the temperature non-uniformity time occupying value WZ, the production temperature amplitude deviation value WK, the production air pressure amplitude deviation value WY and the production carbon source amplitude deviation value WT to obtain a reactor different capturing value WP, wherein kp1, kp2, kp3, kp4 and kp5 are preset proportion coefficients, and the values of kp1, kp2, kp3, kp4 and kp5 are all larger than zero; and, the larger the value of the reactor abnormal catching value WP is, the more abnormal the operation of the corresponding reactor in unit time is, the greater the probability of abnormality is;
Comparing the different capture value WP of the reactor with a preset different capture threshold value of the reactor, and if the different capture value WP of the reactor exceeds the different capture threshold value of the preset reactor, indicating that the operation of the corresponding reactor in unit time is abnormal, and detecting and maintaining the corresponding reactor in time, generating a reactor maintenance detection signal; if the reactor differential capture value WP does not exceed the preset reactor differential capture threshold, the operation of the corresponding reactor in unit time is normal, and a reactor analysis signal is generated.
The reactor abnormal capture module sends a reactor production analysis signal of a corresponding reactor to the production performance evaluation module through the supervision control platform, the production performance evaluation module analyzes the production performance condition of carbon nano tube production of the corresponding reactor after receiving the reactor production analysis signal, generates a production table disqualification signal or a production table qualification signal through analysis, and sends a production table disqualification signal of the corresponding reactor to the remote control end through the supervision control platform, and the remote control end sends corresponding early warning when receiving the production table disqualification signal so as to remind a manager to timely carry out reason investigation and analysis and overhaul the corresponding reactor, thereby further ensuring the subsequent production efficiency and production quality; the specific operation process of the production performance evaluation module is as follows:
Setting an evaluation period, preferably two hours; collecting the total operation time of the reactor in the corresponding carbon nano tube production line in the evaluation period, collecting the carbon source gas amount consumed by the reactor in the corresponding carbon nano tube production line in the evaluation period, marking the carbon source gas amount as carbon source consumption amount, and calculating the ratio of the carbon source consumption amount to the total operation time to obtain a carbon source consumption meter value; obtaining a preset carbon source consumption table value range, carrying out difference value calculation on the carbon source consumption table value and the median value of the preset carbon source consumption table value range, and taking an absolute value to obtain a carbon source consumption analysis value; wherein, the smaller the value of the carbon source analysis value is, the more normal the carbon source consumption condition of the corresponding reactor is in the evaluation period;
Collecting the yield of the carbon nanotubes produced by the corresponding carbon nanotube production line in the evaluation period, and calculating the ratio of the consumption of the carbon source to the yield of the produced carbon nanotubes to obtain the carbon nanotube production table value; and the larger the numerical value of the carbon nano tube production table value is, the worse the production conversion condition of the corresponding carbon nano tube production line is indicated; acquiring purity detection information of carbon nanotubes produced by a corresponding carbon nanotube production line in an evaluation period, and acquiring the non-qualification rate of the carbon nanotubes in the production process of a reactor in the corresponding carbon nanotube production line in the evaluation period based on the purity detection information of the carbon nanotubes; the larger the numerical value of the non-qualification rate of the carbon nano tube is, the worse the production quality condition of the corresponding carbon nano tube production line is in the evaluation period;
It should be noted that, the purity detection information is obtained by detecting through a corresponding analysis means and is sent to the production performance evaluation module through the supervision and control platform, the adopted corresponding analysis means such as spectrum analysis, electron microscope observation, etc., the spectrum analysis is a common purity detection means, and the chemical structure and composition of the carbon nanotube are determined by analyzing the light absorption, emission or scattering spectrum of the carbon nanotube, and the common spectrum analysis methods include infrared spectrum, raman spectrum, ultraviolet-visible spectrum, etc., and these methods can detect whether impurities such as metal ions, non-carbon elements, etc. exist in the carbon nanotube; electron microscope observation is mainly realized by an electron microscope, wherein the electron microscope is an instrument for observing the shape and structure of the carbon nanotube, and can determine the diameter, the length and the shape of the carbon nanotube, whether defects or impurities exist or not and the like;
by the formula Carrying out numerical calculation on a carbon source analysis value QW, a carbon nanotube production table value QY and a carbon nanotube non-qualification rate QK to obtain a carbon nanotube production evaluation value QX, wherein eq1, eq2 and eq3 are preset weight coefficients, and eq3 is larger than eq2 is larger than eq1 and larger than 0; and, the larger the value of the carbon nanotube production evaluation value QX is, the more abnormal the production performance of the corresponding carbon nanotube production line is in the evaluation period; comparing the carbon nanotube yield evaluation value QX with a preset carbon nanotube yield evaluation threshold value, and if the carbon nanotube yield evaluation value QX exceeds the preset carbon nanotube yield evaluation threshold value, indicating that the production performance of the corresponding carbon nanotube production line is abnormal in the evaluation period, generating a yield failure signal of the corresponding reactor; if the carbon nanotube yield evaluation value QX does not exceed the preset carbon nanotube yield evaluation threshold, indicating that the production performance of the corresponding carbon nanotube production line is normal in the evaluation period, generating a yield qualification signal of the corresponding reactor.
Embodiment two: as shown in fig. 2, the difference between the present embodiment and embodiment 1 is that the supervisory control platform is in communication connection with the production line pipe evaluation module, and the production line pipe evaluation module is configured to set an evaluation period of L1 days, preferably, L1 is twenty-five days; the production traceability analysis is carried out on all the carbon nanotube production lines in the evaluation period so as to mark the corresponding carbon nanotube production lines as high-grade production lines or low-grade production lines, the running conditions of all the carbon nanotube production lines in the evaluation period can be effectively evaluated and accurately fed back, the follow-up supervision measures matched with different carbon nanotube production lines are conveniently adopted, the targeted management is realized, and the planning difficulty of a follow-up management scheme is reduced;
The management personnel are reminded to increase the production supervision on all carbon nanotube production lines in the follow-up process, the corresponding personnel training and personnel investment are enhanced, and the follow-up stable and efficient production is further ensured; the specific analysis process of the production traceability analysis is as follows:
Collecting the times of generating a reactor dimension detection signal and the times of generating a production table disqualification signal by the corresponding carbon nano tube production line in an evaluation period, respectively marking the times as dimension detection signal frequency value and production table disfrequency value, collecting single outage duration of the corresponding carbon nano tube production line stopped running due to faults in the production process in the evaluation period, carrying out summation calculation on all single outage total durations of the corresponding carbon nano tube production line in the evaluation period to obtain a fault outage analysis value, carrying out numerical comparison on the single outage duration and a preset single outage duration threshold value, and marking the number of the single outage durations exceeding the preset single outage duration threshold value as an overdriving frequency analysis value;
by the formula Performing numerical calculation on a dimension detection signal frequency value FK, a production table abnormal frequency value FW, a failure outage time analysis value FS and an ultra outage frequency analysis value FQ of a corresponding carbon nanotube production line to obtain a carbon nanotube production line evaluation value FY, wherein c1, c2, c3 and c4 are preset proportion coefficients, and the values of c1, c2, c3 and c4 are positive numbers; and, the larger the value of the evaluation value FY of the carbon nano tube production line is, the worse the running condition of the corresponding carbon nano tube production line in the evaluation period is;
Comparing the evaluation value FY of the carbon nano tube production line with a preset evaluation threshold value of the carbon nano tube production line, and marking the corresponding carbon nano tube production line as a high-grade production line if the evaluation value FY of the carbon nano tube production line exceeds the evaluation threshold value of the preset carbon nano tube production line, which indicates that the running condition of the corresponding carbon nano tube production line in the evaluation period is poor; if the evaluation value FY of the carbon nano tube production line does not exceed the evaluation threshold value of the carbon nano tube production line, indicating that the running condition of the corresponding carbon nano tube production line in the evaluation period is good, marking the corresponding carbon nano tube production line as a low-grade production line.
Further, after marking the corresponding carbon nanotube production line as a high-grade production line or a low-grade production line, if the low-grade production line does not exist in the carbon nanotube production line to be monitored, that is, the running conditions of all the carbon nanotube production lines in the evaluation period are poor, a tube conveying evaluation disqualification signal is generated; if the low-grade production line exists in the carbon nano tube production line to be monitored, collecting the number of the high-grade production line and the number of the low-grade production line in the carbon nano tube production line to be monitored, and calculating the ratio of the number of the high-grade production line to the number of the low-grade production line to obtain a high-grade detection value of the production line;
and average value calculation is carried out on the evaluation values of the carbon nanotube production line of all the carbon nanotube production lines to be supervised to obtain a production line pipe conveying value, and the production line pipe conveying value is calculated according to a formula Carrying out numerical calculation on a production line pipe transporting value FM and a production line high-difference detection value FN to obtain a production line analysis value FX, wherein ey1 and ey2 are preset proportionality coefficients, and ey2 is greater than ey2 and greater than 0; and, the larger the numerical value of the production line evaluation value FX, the worse the running condition of all the carbon nano tube production lines in the evaluation period is comprehensively;
comparing the production line evaluation value FX with a preset production line evaluation threshold value, and if the production line evaluation value FX exceeds the preset production line evaluation threshold value, indicating that the running conditions of all the carbon nanotube production lines in the evaluation period are poor in combination, generating a pipe transportation evaluation disqualification signal; if the production line evaluation value FX does not exceed the preset production line evaluation threshold, indicating that the running conditions of all the carbon nanotube production lines in the evaluation period are better in combination, generating a tube transportation evaluation qualified signal.
The working principle of the invention is as follows: when the intelligent monitoring system is used, the intelligent monitoring module is used for monitoring the operation of the reactors in the carbon nanotube production line, the operation condition qualified signals or the operation condition unqualified signals of the corresponding reactors are generated through analysis, the operation of the corresponding reactors is regulated and controlled through the reactor regulation and control module when the operation condition unqualified signals are generated, and regulation and control early warning information is generated if the operation regulation and control are not completed within a specified time, so that the reactors in a plurality of groups of carbon nanotube production lines can be effectively monitored and automatically adaptively regulated and controlled, the difficulty in production management is reduced, and the large-scale processing of carbon nanotubes is facilitated; the abnormal capture judgment is carried out on the reactor through the reactor abnormal capture module, the reactor maintenance detection signal and the reactor analysis signal are generated through analysis, the production performance state of the corresponding reactor is analyzed through the production performance evaluation module when the reactor analysis signal is generated, the remote control end is enabled to send out early warning when the reactor maintenance detection signal or the production table disqualification signal is generated, management staff is timely reminded to conduct reason investigation and analysis and overhaul the corresponding reactor, the intelligent degree is high, the production efficiency, the production stability and the production quality of the carbon nano tube production line are guaranteed, and the difficulty of large-scale processing of the carbon nano tubes is remarkably reduced.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (5)
1. The production line supervision and control system for large-scale carbon nanotube processing is characterized by comprising a supervision and control platform, an intelligent monitoring module, a reactor regulation and control module, a reactor different-catching module, a production performance evaluation module and a remote control end; the monitoring control platform acquires all carbon nanotube production lines needing to be monitored, the intelligent monitoring module monitors the operation of the reactors in the carbon nanotube production lines, generates operation condition qualified signals or operation condition unqualified signals of the corresponding reactors through analysis, and sends the operation condition unqualified signals to the reactor regulation and control module through the monitoring control platform;
When the reactor regulation and control module receives the unqualified signal of the operation condition, carrying out operation regulation and control on the corresponding reactor, recording the regulation and control duration, generating regulation and control early warning information if the operation regulation and control is not completed within a specified time, and sending the regulation and control early warning information to a supervision and control platform;
The reactor abnormal capture module is used for carrying out abnormal capture judgment on the reactor, generating a reactor maintenance signal or a reactor production analysis signal through analysis, sending the reactor maintenance signal of the corresponding reactor to a remote control end through a supervision and control platform, and sending the reactor production analysis signal of the corresponding reactor to a production performance evaluation module through the supervision and control platform; after receiving the reactor production analysis signals, the production performance evaluation module analyzes the production performance conditions of the carbon nano tube production of the corresponding reactor, generates production table disqualification signals or production table qualification signals through analysis, and sends the production table disqualification signals of the corresponding reactor to a remote management and control end through a supervision and control platform;
the specific analysis process for the anomaly capture analysis of the reactor is as follows:
Collecting the times of generating regulation and control early warning information by a reactor in a corresponding carbon nano tube production line in unit time, marking the times as a reactor regulation and control value, collecting the total times of regulating and controlling the reactor in the corresponding carbon nano tube production line by a reactor regulation and control module in unit time, marking the total times as a reactor total regulation value, and calculating the ratio of the reactor regulation and control value to the reactor total regulation value to obtain a reactor deterioration regulation and control occupation value;
by the formula Carrying out numerical calculation on the reactor adjustment detection value TY and the reactor adjustment degradation detection occupation value TL to obtain a reactor adjustment condition evaluation value TX, wherein, ew1 and ew2 are preset proportionality coefficients, and ew2 is more than ew1 and more than 0; if the reactor condition evaluation value exceeds a preset reactor condition evaluation threshold value, generating a reactor dimension detection signal;
If the reactor condition evaluation value does not exceed the preset reactor condition evaluation threshold, setting a plurality of detection time points in unit time, performing variance calculation on real-time temperatures at a plurality of positions inside the reactor in the carbon nano tube production line corresponding to the corresponding detection time points to obtain a temperature distribution detection value, and if the temperature distribution detection value exceeds the preset temperature distribution detection threshold, judging that the inside of the reactor corresponding to the corresponding detection time points is in a state with uneven temperature distribution;
Collecting the difference between the maximum value and the minimum value of the detected values of the production temperature in the reactor in the corresponding carbon nano tube production line in unit time, marking the difference as the production temperature amplitude deviation value, acquiring the production air pressure amplitude deviation value and the production carbon source amplitude deviation value in a similar way, and marking the number occupation ratio of the detected points in the state of uneven temperature distribution in the reactor in the corresponding carbon nano tube production line in unit time as the temperature non-uniform time occupation value;
by the formula Carrying out numerical calculation on the reactor condition evaluation value TX, the temperature non-uniformity time occupying value WZ, the production temperature amplitude deviation value WK, the production air pressure amplitude deviation value WY and the production carbon source amplitude deviation value WT to obtain a reactor different capturing value WP, wherein kp1, kp2, kp3, kp4 and kp5 are preset proportion coefficients, and the values of kp1, kp2, kp3, kp4 and kp5 are all larger than zero; if the reactor differential capture value exceeds a preset reactor differential capture threshold value, generating a reactor maintenance signal; if the reactor differential capture value does not exceed the preset reactor differential capture threshold value, generating a reactor analysis signal;
The specific operation process of the production performance evaluation module comprises the following steps:
Setting an evaluation period, collecting the total operation duration of the reactor in the corresponding carbon nano tube production line in the evaluation period, collecting the carbon source gas amount consumed by the reactor in the corresponding carbon nano tube production line in the evaluation period, marking the carbon source gas amount as the carbon source consumption amount, and calculating the ratio of the carbon source consumption amount to the total operation duration to obtain a carbon source consumption meter value; obtaining a preset carbon source consumption table value range, carrying out difference value calculation on the carbon source consumption table value and the median value of the preset carbon source consumption table value range, and taking an absolute value to obtain a carbon source consumption analysis value;
Collecting the yield of the carbon nanotubes produced by the corresponding carbon nanotube production line in the evaluation period, and calculating the ratio of the consumption of the carbon source to the yield of the produced carbon nanotubes to obtain the carbon nanotube production table value; acquiring purity detection information of carbon nanotubes produced by a corresponding carbon nanotube production line in an evaluation period, and acquiring the non-qualification rate of the carbon nanotubes in the production process of a reactor in the corresponding carbon nanotube production line in the evaluation period based on the purity detection information of the carbon nanotubes;
by the formula Carrying out numerical calculation on a carbon source analysis value QW, a carbon nanotube production table value QY and a carbon nanotube non-qualification rate QK to obtain a carbon nanotube production evaluation value QX, wherein eq1, eq2 and eq3 are preset weight coefficients, and eq3 is larger than eq2 is larger than eq1 and larger than 0; if the carbon nano tube yield evaluation value exceeds a preset carbon nano tube yield evaluation threshold value, generating a yield failure signal of the corresponding reactor; and if the carbon nanotube yield evaluation value does not exceed the preset carbon nanotube yield evaluation threshold value, generating a yield list qualification signal of the corresponding reactor.
2. The production line supervisory control system for large-scale processing of carbon nanotubes according to claim 1, wherein the specific operation process of the intelligent monitoring module comprises:
Collecting real-time temperatures at a plurality of positions inside a reactor in a corresponding carbon nano tube production line, carrying out average calculation on all the real-time temperatures to obtain a production temperature detection value, collecting air pressure data inside the reactor in the corresponding carbon nano tube production line and marking the air pressure data as a production pressure detection value, and collecting flow data of carbon source gas input into the reactor in the corresponding carbon nano tube production line and marking the flow data as a production carbon source flow value; calculating the difference value between the production temperature detection value and the set standard temperature value, taking an absolute value to obtain a production temperature condition value, and obtaining a production pressure condition value and a production carbon source value in a similar way;
by the formula Carrying out numerical calculation on the production temperature Kuang Zhi YL, the production pressure condition value YK and the production carbon source value YS to obtain a carbon nano tube yield test value YP, wherein a1, a2 and a3 are preset proportionality coefficients, and the values of a1, a2 and a3 are positive numbers; if the carbon nanotube yield value exceeds a preset carbon nanotube yield threshold, generating an operation condition disqualification signal; and if the carbon nanotube yield value does not exceed the preset carbon nanotube yield threshold, generating an operation condition qualification signal.
3. The production line supervision control system for large-scale processing of carbon nanotubes according to claim 1, wherein the supervision control platform is in communication connection with a production line tube evaluation module, the production line tube evaluation module is used for setting an evaluation period with a number of days of L1, performing production retrospective analysis on all carbon nanotube production lines in the evaluation period to mark the corresponding carbon nanotube production line as a high-grade production line or a low-grade production line, generating a tube evaluation disqualification signal or a tube evaluation qualification signal through analysis, and transmitting the tube evaluation disqualification signal to a remote control end through the supervision control platform.
4. The production line supervisory control system for large-scale processing of carbon nanotubes according to claim 3, wherein the specific analysis process of the production retrospective analysis is as follows:
Collecting the times of generating a reactor dimension detection signal and the times of generating a production table disqualification signal by the corresponding carbon nano tube production line in an evaluation period, respectively marking the times as dimension detection signal frequency value and production table disfrequency value, collecting single outage duration of the corresponding carbon nano tube production line stopped running due to faults in the production process in the evaluation period, carrying out summation calculation on all the single outage total duration of the corresponding carbon nano tube production line in the evaluation period to obtain a fault outage analysis value, and marking the number of the single outage duration exceeding a preset single outage duration threshold as an overdriving frequency analysis value;
by the formula Performing numerical calculation on a dimension detection signal frequency value FK, a production table abnormal frequency value FW, a failure outage time analysis value FS and an ultra outage frequency analysis value FQ of a corresponding carbon nanotube production line to obtain a carbon nanotube production line evaluation value FY, wherein c1, c2, c3 and c4 are preset proportion coefficients, and the values of c1, c2, c3 and c4 are positive numbers; if the evaluation value of the carbon nano tube production line exceeds a preset evaluation threshold of the carbon nano tube production line, marking the corresponding carbon nano tube production line as a high-grade production line; and if the evaluation value of the carbon nano tube production line does not exceed the evaluation threshold of the carbon nano tube production line, marking the corresponding carbon nano tube production line as a low-grade production line.
5. The production line supervision control system for large-scale processing of carbon nanotubes according to claim 4, wherein after marking the corresponding carbon nanotube production line as a high-grade production line or a low-grade production line, if the low-grade production line does not exist in the carbon nanotube production line to be supervised, a tube transportation evaluation disqualification signal is generated; if the low-grade production line exists in the carbon nano tube production line to be monitored, collecting the number of the high-grade production line and the number of the low-grade production line in the carbon nano tube production line to be monitored, and calculating the ratio of the number of the high-grade production line to the number of the low-grade production line to obtain a high-grade detection value of the production line;
and average value calculation is carried out on the evaluation values of the carbon nanotube production line of all the carbon nanotube production lines to be supervised to obtain a production line pipe conveying value, and the production line pipe conveying value is calculated according to a formula Carrying out numerical calculation on a production line pipe transporting value FM and a production line high-difference detection value FN to obtain a production line analysis value FX, wherein ey1 and ey2 are preset proportionality coefficients, and ey2 is greater than ey2 and greater than 0; if the production line evaluation value exceeds a preset production line evaluation threshold, generating a pipe transportation evaluation disqualification signal; and if the production line evaluation value does not exceed the preset production line evaluation threshold, generating a pipe transportation evaluation qualified signal.
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