CN117889985A - Online temperature monitoring method and system for processing flow - Google Patents
Online temperature monitoring method and system for processing flow Download PDFInfo
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- CN117889985A CN117889985A CN202410086305.2A CN202410086305A CN117889985A CN 117889985 A CN117889985 A CN 117889985A CN 202410086305 A CN202410086305 A CN 202410086305A CN 117889985 A CN117889985 A CN 117889985A
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- G—PHYSICS
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- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K13/00—Thermometers specially adapted for specific purposes
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- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/48—Thermography; Techniques using wholly visual means
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- G01K1/026—Means for indicating or recording specially adapted for thermometers arrangements for monitoring a plurality of temperatures, e.g. by multiplexing
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D23/00—Control of temperature
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- G05D23/1919—Control of temperature characterised by the use of electric means characterised by the type of controller
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- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D23/00—Control of temperature
- G05D23/19—Control of temperature characterised by the use of electric means
- G05D23/1927—Control of temperature characterised by the use of electric means using a plurality of sensors
- G05D23/193—Control of temperature characterised by the use of electric means using a plurality of sensors sensing the temperaure in different places in thermal relationship with one or more spaces
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Abstract
The invention relates to the technical field of processing procedure monitoring, and particularly discloses a processing procedure online temperature monitoring method and system, wherein the method comprises the following steps: the temperature sensors are used for monitoring temperature data of corresponding position points of each temperature sensor in real time; the infrared image acquisition module is used for acquiring real-time infrared image information of the PAN precursor in each processing cavity; the temperature control data docking port is used for acquiring real-time temperature control data of each processing cavity; the circulating fan control data docking port is used for acquiring real-time circulating fan control data of each processing cavity; and the monitoring and early warning module is used for judging the temperature state of each reaction cavity according to the temperature data monitored by the temperature sensor and the real-time infrared image information, and carrying out abnormal analysis on the processing state according to comparison of the judging result with the real-time temperature control data and the circulating fan control data.
Description
Technical Field
The invention relates to the technical field of processing procedure monitoring, in particular to a processing procedure online temperature monitoring method and system.
Background
Temperature monitoring is a common control index in the processing and production process, deviation and anomaly of temperature control can cause great influence on the quality of products, and for the processing process of carbon fibers, the pre-oxidized, low-temperature carbonized, high-temperature carbonized and graphitized processes of the pretreated Polyacrylonitrile (PAN) filaments are needed, and in the process, the environment temperature state and the product temperature state in each processing cavity are needed to be accurately detected, so that measures are timely taken when the abnormality occurs, and the quality of the products is ensured.
The mode that temperature monitoring adopted mainly sets up temperature sensor and monitors the temperature in every processing chamber in real time, compares through temperature value and the temperature of settlement, and then judges the degree of accuracy of temperature control, carries out the early warning when the actual temperature in the processing chamber is great with the control temperature difference, and then handles the problem that equipment exists.
The existing temperature monitoring method can judge the temperature of each processing cavity in the carbon fiber processing process, but because of the sensitivity of PAN wires to the temperature, the uniformity of the temperature distribution of each processing cavity has a larger influence on the consistency of products, meanwhile, the existing temperature judging mode has poorer abnormal judging sensitivity to temperature control, and when the condition that the difference between the actual temperature and the control temperature is larger occurs, the condition that the product is influenced more is indicated, and a certain loss is caused.
Disclosure of Invention
The invention aims to provide a processing flow online temperature monitoring method and system, which solve the following technical problems:
How to improve the comprehensiveness and sensitivity of the temperature monitoring of each reaction cavity.
The aim of the invention can be achieved by the following technical scheme:
a process flow online temperature monitoring system, the system comprising:
The temperature sensors are arranged in each processing cavity, and are used for monitoring temperature data of corresponding position points of each temperature sensor in real time;
The infrared image acquisition module is used for acquiring real-time infrared image information of the PAN precursor in each processing cavity;
the temperature control data docking port is used for acquiring real-time temperature control data of each processing cavity;
The circulating fan control data docking port is used for acquiring real-time circulating fan control data of each processing cavity;
The monitoring and early warning module is used for judging the temperature state of each reaction cavity according to the temperature data monitored by the temperature sensor and the real-time infrared image information, and carrying out abnormal analysis on the processing state according to comparison of the judging result with the real-time temperature control data and the circulating fan control data;
And the feedback adjustment module is used for carrying out feedback adjustment on the temperature control data and the circulating fan control data according to the result of the anomaly analysis.
Further, the process of judging the temperature state of each reaction chamber comprises the following steps:
Acquiring an average value of environmental temperature and an uniformity coefficient of the environmental temperature in the reaction cavity according to temperature data monitored by a temperature sensor;
Identifying the position of the PAN precursor in the infrared image information, and acquiring a lattice temperature mean value and a lattice temperature uniformity coefficient in an identification area according to a preset point position;
Determining the average value of the temperature field of the reaction cavity according to the average value of the ambient temperature and the average value of the lattice temperature, and determining the uniformity coefficient of the temperature field of the reaction cavity according to the uniformity coefficient of the ambient temperature and the uniformity coefficient of the lattice temperature; and judging the temperature state of each reaction cavity according to the average value of the temperature field and the uniformity coefficient of the temperature field.
Further, the process of obtaining the uniformity coefficient of the environmental temperature includes:
by the formula:
calculating an environmental temperature uniformity coefficient s ET (t) of the current time point;
The process for obtaining the lattice temperature uniformity coefficient comprises the following steps:
by the formula:
Calculating to obtain a lattice temperature uniformity coefficient s PT (t) of the current time point;
the temperature field average value obtaining process comprises the following steps:
by the formula:
Calculating to obtain a temperature field average value T field (T) of the current time point;
by the formula:
calculating a temperature field uniformity coefficient s field (t) of the current time point;
Wherein n is the number of temperature sensors in the current reaction cavity, i epsilon [1, n ], ET i (t) is the real-time temperature obtained by the ith sensor, is the real-time temperature average value obtained by all sensors, m is the lattice number in the identification area, j epsilon [1, m ], PT i (t) is the real-time temperature at the j-th lattice,/> is the temperature average value of all lattices, mu is the temperature conductivity coefficient, gamma is the adjustment coefficient, and gamma > 1 is satisfied.
Further, the process of analyzing the processing abnormality includes:
by the formula:
Calculating to obtain a temperature control difference T Δ (T) at the current time point;
comparing the temperature control difference T Δ (T) with a first preset difference interval [ T1 Δlow,T1Δ up ]:
If , carrying out temperature early warning on the current reaction cavity;
if T Δ(t)∈[T1Δlow,T1Δ up ], then compare T Δ (T) with the first predetermined delta interval [ T2 Δlow,T2Δ up ]:
if T Δ(t)∈[T2Δlow,T2Δ up ], judging that the current temperature control state of the reaction cavity is normal;
If , carrying out feedback adjustment on the temperature control data of the current reaction cavity;
Wherein p (t) is real-time power of the reaction chamber temperature control device, f T is a reaction chamber temperature diffusion function, and t1 is a preset fixed period.
Further, the process of feedback adjustment of the current reaction chamber temperature control data includes:
Taking t1 as a period, adjusting temperature control data of a next period according to temperature control difference of a previous period, wherein the adjusting process comprises the following steps:
by the formula:
calculating to obtain the adjustment quantity delta p1 of the reaction cavity temperature control equipment in the current period;
Wherein T Δ is the temperature control delta of the previous cycle, is the inverse function of f T, W is a condition coefficient, when , w=1, otherwise, w= -1; mu is the increment coefficient and satisfies 1.1 > mu > 1.
Further, the process of analyzing the processing abnormality further includes:
by the formula:
calculating to obtain the temperature uniformity difference s Δ (t) at the current time point;
Comparing the temperature uniformity difference s Δ (t) with a preset uniformity difference interval [ s1 Δ,s2Δ ]:
If s Δ(t)＜s1Δ, judging that the current temperature uniformity state of the reaction chamber is normal;
If s Δ(t)＞s2Δ, carrying out temperature uniformity early warning on the current reaction cavity;
If s Δ(t)∈[s1Δ,s2Δ ], taking t1 as a period, judging whether the average power mean value of the control of the circulating fan of the period reaches a preset critical value or not:
If the temperature uniformity of the current reaction cavity is met, carrying out temperature uniformity early warning on the current reaction cavity;
if not, carrying out feedback adjustment on the temperature uniformity of the current reaction cavity;
wherein t1 is a preset fixed period.
Further, the process of feedback adjusting the temperature uniformity of the current reaction chamber comprises:
by the formula:
Calculating to obtain the control power increment delta p2 of the circulating fan in the current period;
wherein pm is a preset critical value, is the average power average value of the control of the circulating fan in the previous period, s Δ is the temperature uniformity difference in the previous period, and τ is a preset fixed coefficient.
The method adopts a processing flow on-line temperature monitoring system to monitor and control the temperature.
The invention has the beneficial effects that:
(1) According to the invention, through the monitoring process of the temperature of the surfaces of the plurality of temperature sensors and the products in each processing cavity, the overall temperature state in the processing cavity can be accurately judged, the comprehensiveness of the temperature monitoring process is further improved, the monitored data and the real-time temperature control data and the circulating fan control data are combined and analyzed, the existing temperature control abnormality can be more timely judged, namely the sensitivity of abnormality early warning is improved, in addition, the feedback adjustment module carries out feedback adjustment on the temperature control data and the circulating fan control data according to the result of the abnormality analysis, and the current temperature state is adaptively self-adjusted in the error controllable range, so that the accuracy of temperature control is further ensured.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a logic block diagram of an on-line temperature monitoring system for a process flow 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.
Referring to fig. 1, in one embodiment, an online temperature monitoring system for a processing flow is provided, where the system includes a temperature sensor, an infrared image acquisition module, a temperature control data docking port, a circulating fan control data docking port, a monitoring and early warning module, and a feedback adjustment module, and each processing chamber is provided with a plurality of sets of temperature sensors for monitoring temperature data of corresponding position points of each temperature sensor in real time; the infrared image acquisition module is used for acquiring real-time infrared image information of the PAN precursor in each processing cavity, so that the overall temperature state in the processing cavity can be accurately judged through the monitoring process of a plurality of temperature sensors and the surface temperature of the product in each processing cavity, the comprehensiveness of the temperature monitoring process is further improved, and the temperature control data docking port is used for acquiring real-time temperature control data of each processing cavity; the circulating fan control data docking port is used for acquiring real-time circulating fan control data of each processing cavity, therefore, the temperature state of each reaction cavity is judged according to temperature data monitored by the temperature sensor and real-time infrared image information through the monitoring and early warning module, the processing state is further subjected to abnormal analysis according to comparison of a judging result and the real-time temperature control data and the circulating fan control data, in the process, the monitored data, the real-time temperature control data and the circulating fan control data are combined and analyzed, the existing temperature control abnormality can be judged more timely, namely, the sensitivity of abnormality early warning is improved, in addition, the feedback adjustment module carries out feedback adjustment on the temperature control data and the circulating fan control data according to the result of the abnormality analysis, and then the current temperature state is adaptively self-regulated in an error controllable range, and the accuracy of temperature control is further guaranteed.
The process of judging the temperature state of each reaction cavity comprises the following steps: acquiring an average value of environmental temperature and an uniformity coefficient of the environmental temperature in the reaction cavity according to temperature data monitored by a temperature sensor; the process for obtaining the uniformity coefficient of the environmental temperature comprises the following steps: by the formula:
calculating an environmental temperature uniformity coefficient s ET (t) of the current time point;
wherein n is the number of temperature sensors in the current reaction cavity, i epsilon [1, n ], ET i (t) is the real-time temperature obtained by the ith sensor, is the real-time temperature average value obtained by all sensors, so that the environmental temperature uniformity coefficient can reflect the dispersion of temperature values of temperature points at different positions, and further the distribution state of the current temperature can be judged through s ET (t), and when the temperature state distribution is uniform, the value of s ET (t) is approaching 0; the identification process is to identify the position of the PAN precursor in the infrared image information, wherein the identification process is based on a machine learning training model, the specific machine learning training model is obtained by training working state images of different processing chambers, and the method is not further described herein, and then the lattice temperature average value and the lattice temperature uniformity coefficient in an identification area are obtained according to preset point positions; the process for acquiring the lattice temperature uniformity coefficient comprises the following steps: by the formula:
calculating to obtain a lattice temperature uniformity coefficient s PT (t) of the current time point; wherein m is the number of lattices in the identification area, j epsilon [1, m ], PT i (t) is the real-time temperature at the j-th lattice, is the temperature average value of all lattices, so that the lattice temperature uniformity coefficient obtained by the calculation can judge the temperature uniformity of the current temperature acting on the product, and further determine the temperature field average value of the reaction cavity according to the ambient temperature average value and the lattice temperature average value, and the temperature field average value is determined by the formula:
Calculating to obtain a temperature field average value T field (T) of the current time point; μ is a temperature conductivity coefficient, so that the temperature state in the current reaction cavity can be judged more accurately by the mean value of the temperature field; determining the temperature field uniformity coefficient of the reaction cavity according to the ambient temperature uniformity coefficient and the lattice temperature uniformity coefficient; by the formula:
Calculating a temperature field uniformity coefficient s field (t) of the current time point; wherein, gamma is an adjustment coefficient and satisfies gamma > 1, so that the embodiment synthesizes product temperature and space temperature in the reaction chamber to accurately judge the temperature overall condition and overall distribution condition of the temperature field mean value and the temperature field uniformity coefficient, and the process of analyzing the processing abnormality comprises:
by the formula:
Calculating to obtain a temperature control difference T Δ (T) at the current time point; wherein, p (T) is real-time power of the reaction chamber temperature control device, f T is a reaction chamber temperature diffusion function, which is obtained by fitting according to reaction chamber test data, and T1 is a preset fixed period, which is selectively set according to empirical data, so that the temperature control difference T Δ (T) is compared with a first preset difference interval [ T1 Δlow,T1Δ up ]: the [ T1 Δlow,T1Δ up ] is set according to the error permission condition in the test data, so that if is used for explaining the difference process, the problem of abnormal temperature control exists, and then the temperature early warning is carried out on the current reaction cavity; if T Δ(t)∈[T1Δlow,T1Δ up ], then compare T Δ (T) with the first predetermined delta interval [ T2 Δlow,T2Δ up ]: the [ T2 Δlow,T2Δ up ] is set according to the fitting of the allowable error data in the ideal state, and the [ T2 Δlow,T2Δup]∈[T1Δlow,T1Δ up ] is satisfied, so that if the T Δ(t)∈[T2Δlow,T2Δ up ] is satisfied, the current temperature control state of the reaction chamber is judged to be normal; if/> , performing feedback adjustment on the current reaction chamber temperature control data, wherein the process of performing feedback adjustment on the current reaction chamber temperature control data comprises the following steps: taking t1 as a period, adjusting temperature control data of a next period according to temperature control difference of a previous period, wherein the adjusting process comprises the following steps:
by the formula:
Calculating to obtain the adjustment quantity delta p1 of the reaction cavity temperature control equipment in the current period; wherein T Δ is the temperature control delta of the previous cycle, is the inverse function of f T, W is a condition coefficient, when/> , w=1, otherwise, w= -1; mu is an increment coefficient and satisfies 1.1 & gtmu & gt1, and the increment coefficient is set according to test data fitting and is used for correcting the obtained adjustment quantity, so that through the process, on the basis of judging that temperature control abnormality occurs, different treatment strategies can be adopted when the accumulated difference average value is too large, on one hand, potential risks can be timely judged, and on the other hand, when the temperature is judged to be in a controllable range, the normal operation of the current processing process can be ensured through a feedback adjustment mode, and further the quality of a prepared product is ensured.
In addition, the process of analyzing the processing abnormality further includes: by the formula:
Calculating to obtain the temperature uniformity difference s Δ (t) at the current time point; comparing the temperature uniformity difference s Δ (t) with a preset uniformity difference interval [ s1 Δ,s2Δ ], wherein the preset uniformity difference interval is set according to empirical data in a fitting way, so that if s Δ(t)＜s1Δ, the current temperature distribution state is uniform, and the current temperature uniformity state of the reaction chamber is judged to be normal; if s Δ(t)＞s2Δ, the current temperature state is in an uncontrollable state, and then the temperature uniformity early warning is carried out on the current reaction cavity; if s Δ(t)∈[s1Δ,s2Δ ], taking t1 as a period, judging whether the average power mean value of the control of the circulating fan of the period reaches a preset critical value or not: if the temperature uniformity of the current reaction cavity is achieved, carrying out feedback adjustment on the temperature uniformity of the current reaction cavity if the temperature uniformity of the current reaction cavity is not achieved, wherein the process for carrying out feedback adjustment on the temperature uniformity of the current reaction cavity comprises the following steps:
by the formula:
calculating to obtain the control power increment delta p2 of the circulating fan in the current period; wherein pm is a preset critical value, is a mean power value of control of the circulating fan in the previous period, s Δ is a temperature uniformity difference in the previous period, τ is a preset fixed coefficient, and is set by fitting according to empirical data, and the obtained increment is corrected.
In one embodiment, a process flow online temperature monitoring method is provided that employs a process flow online temperature monitoring system to perform temperature monitoring and control processes.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (8)
1. An on-line process flow temperature monitoring system, the system comprising:
The temperature sensors are arranged in each processing cavity, and are used for monitoring temperature data of corresponding position points of each temperature sensor in real time;
The infrared image acquisition module is used for acquiring real-time infrared image information of the PAN precursor in each processing cavity;
the temperature control data docking port is used for acquiring real-time temperature control data of each processing cavity;
The circulating fan control data docking port is used for acquiring real-time circulating fan control data of each processing cavity;
The monitoring and early warning module is used for judging the temperature state of each reaction cavity according to the temperature data monitored by the temperature sensor and the real-time infrared image information, and carrying out abnormal analysis on the processing state according to comparison of the judging result with the real-time temperature control data and the circulating fan control data;
And the feedback adjustment module is used for carrying out feedback adjustment on the temperature control data and the circulating fan control data according to the result of the anomaly analysis.
2. The on-line process flow temperature monitoring system of claim 1, wherein the process of determining the temperature status of each reaction chamber comprises:
Acquiring an average value of environmental temperature and an uniformity coefficient of the environmental temperature in the reaction cavity according to temperature data monitored by a temperature sensor;
Identifying the position of the PAN precursor in the infrared image information, and acquiring a lattice temperature mean value and a lattice temperature uniformity coefficient in an identification area according to a preset point position;
Determining the average value of the temperature field of the reaction cavity according to the average value of the ambient temperature and the average value of the lattice temperature, and determining the uniformity coefficient of the temperature field of the reaction cavity according to the uniformity coefficient of the ambient temperature and the uniformity coefficient of the lattice temperature; and judging the temperature state of each reaction cavity according to the average value of the temperature field and the uniformity coefficient of the temperature field.
3. The on-line temperature monitoring system of claim 2, wherein the process of obtaining the ambient temperature uniformity coefficient comprises:
by the formula:
calculating an environmental temperature uniformity coefficient s ET (t) of the current time point;
The process for obtaining the lattice temperature uniformity coefficient comprises the following steps:
by the formula:
Calculating to obtain a lattice temperature uniformity coefficient s PT (t) of the current time point;
the temperature field average value obtaining process comprises the following steps:
by the formula:
Calculating to obtain a temperature field average value T field (T) of the current time point;
by the formula:
calculating a temperature field uniformity coefficient s field (t) of the current time point;
Wherein n is the number of temperature sensors in the current reaction cavity, i epsilon [1, n ], ET i (t) is the real-time temperature obtained by the ith sensor, is the real-time temperature average value obtained by all sensors, m is the lattice number in the identification area, j epsilon [1, m ], PT i (t) is the real-time temperature at the j-th lattice,/> is the temperature average value of all lattices, mu is the temperature conductivity coefficient, gamma is the adjustment coefficient, and gamma > 1 is satisfied.
4. A process flow on-line temperature monitoring system according to claim 3, wherein the process of analyzing the process anomalies comprises:
by the formula:
Calculating to obtain a temperature control difference T Δ (T) at the current time point;
comparing the temperature control difference T Δ (T) with a first preset difference interval [ T1 Δlow,T1Δ up ]:
if , carrying out temperature early warning on the current reaction cavity;
if T Δ(t)∈[T1Δlow,T1Δ up ], then compare T Δ (T) with the first predetermined delta interval [ T2 Δlow,T2Δ up ]:
if T Δ(t)∈[T2Δlow,T2Δ up ], judging that the current temperature control state of the reaction cavity is normal;
If , carrying out feedback adjustment on the temperature control data of the current reaction cavity;
Wherein p (t) is real-time power of the reaction chamber temperature control device, f T is a reaction chamber temperature diffusion function, and t1 is a preset fixed period.
5. The on-line process flow temperature monitoring system of claim 4, wherein the feedback adjustment of the current reactor temperature control data comprises:
Taking t1 as a period, adjusting temperature control data of a next period according to temperature control difference of a previous period, wherein the adjusting process comprises the following steps:
by the formula:
calculating to obtain the adjustment quantity delta p1 of the reaction cavity temperature control equipment in the current period;
Wherein T Δ is the temperature control delta of the previous cycle, is the inverse function of f T, W is a condition coefficient, when , w=1, otherwise, w= -1; mu is the increment coefficient and satisfies 1.1 > mu > 1.
6. A process flow on-line temperature monitoring system as recited in claim 3, wherein the process of analyzing the process anomalies further comprises:
by the formula:
calculating to obtain the temperature uniformity difference s Δ (t) at the current time point;
Comparing the temperature uniformity difference s Δ (t) with a preset uniformity difference interval [ s1 Δ,s2Δ ]:
If s Δ(t)＜s1Δ, judging that the current temperature uniformity state of the reaction chamber is normal;
If s Δ(t)＞s2Δ, carrying out temperature uniformity early warning on the current reaction cavity;
If s Δ(t)∈[s1Δ,s2Δ ], taking t1 as a period, judging whether the average power mean value of the control of the circulating fan of the period reaches a preset critical value or not:
If the temperature uniformity of the current reaction cavity is met, carrying out temperature uniformity early warning on the current reaction cavity;
if not, carrying out feedback adjustment on the temperature uniformity of the current reaction cavity;
wherein t1 is a preset fixed period.
7. The on-line process flow temperature monitoring system of claim 6, wherein the process of feedback adjusting the temperature uniformity of the current reaction chamber comprises:
by the formula:
Calculating to obtain the control power increment delta p2 of the circulating fan in the current period;
Wherein pm is a preset critical value, is the average power average value of the control of the circulating fan in the previous period, s Δ is the temperature uniformity difference in the previous period, and τ is a preset fixed coefficient.
8. A process flow on-line temperature monitoring method, characterized in that the method adopts a process flow on-line temperature monitoring system according to any one of claims 1-7 for temperature monitoring and controlling processes.
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| CN202410086305.2A CN117889985A (en) | 2024-01-22 | 2024-01-22 | Online temperature monitoring method and system for processing flow |
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| CN202410086305.2A CN117889985A (en) | 2024-01-22 | 2024-01-22 | Online temperature monitoring method and system for processing flow |
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