CN117889985A - Online temperature monitoring method and system for processing flow - Google Patents

Online temperature monitoring method and system for processing flow Download PDF

Info

Publication number
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
Authority
CN
China
Prior art keywords
temperature
current
control data
uniformity
real
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202410086305.2A
Other languages
Chinese (zh)
Inventor
罗袆
尹致丹
高媛
尹昱
杨冲
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Inon Technology Co ltd
Chinese Academy of Inspection and Quarantine CAIQ
Original Assignee
Shenzhen Inon Technology Co ltd
Chinese Academy of Inspection and Quarantine CAIQ
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenzhen Inon Technology Co ltd, Chinese Academy of Inspection and Quarantine CAIQ filed Critical Shenzhen Inon Technology Co ltd
Priority to CN202410086305.2A priority Critical patent/CN117889985A/en
Publication of CN117889985A publication Critical patent/CN117889985A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01KMEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
    • G01K13/00Thermometers specially adapted for specific purposes
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01JMEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/48Thermography; Techniques using wholly visual means
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01KMEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
    • G01K1/00Details of thermometers not specially adapted for particular types of thermometer
    • G01K1/02Means for indicating or recording specially adapted for thermometers
    • G01K1/026Means for indicating or recording specially adapted for thermometers arrangements for monitoring a plurality of temperatures, e.g. by multiplexing
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D23/00Control of temperature
    • G05D23/19Control of temperature characterised by the use of electric means
    • G05D23/1919Control of temperature characterised by the use of electric means characterised by the type of controller
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D23/00Control of temperature
    • G05D23/19Control of temperature characterised by the use of electric means
    • G05D23/1927Control of temperature characterised by the use of electric means using a plurality of sensors
    • G05D23/193Control 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
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P70/00Climate change mitigation technologies in the production process for final industrial or consumer products
    • Y02P70/50Manufacturing or production processes characterised by the final manufactured product
    • Y02P70/62Manufacturing or production processes characterised by the final manufactured product related technologies for production or treatment of textile or flexible materials or products thereof, including footwear

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Remote Sensing (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Control Of Temperature (AREA)

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

Online temperature monitoring method and system for processing flow
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.
CN202410086305.2A 2024-01-22 2024-01-22 Online temperature monitoring method and system for processing flow Pending CN117889985A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202410086305.2A CN117889985A (en) 2024-01-22 2024-01-22 Online temperature monitoring method and system for processing flow

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202410086305.2A CN117889985A (en) 2024-01-22 2024-01-22 Online temperature monitoring method and system for processing flow

Publications (1)

Publication Number Publication Date
CN117889985A true CN117889985A (en) 2024-04-16

Family

ID=90640807

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202410086305.2A Pending CN117889985A (en) 2024-01-22 2024-01-22 Online temperature monitoring method and system for processing flow

Country Status (1)

Country Link
CN (1) CN117889985A (en)

Similar Documents

Publication Publication Date Title
CN112526251B (en) Transformer substation power equipment fault diagnosis method based on data driving
CN212895016U (en) Aluminum electrolysis cell condition diagnosis system based on LoRa wireless measurement and control technology
CN115781697A (en) Industrial robot control system
CN117764422B (en) Intelligent energy-saving operation and maintenance management cloud platform
CN118349051B (en) Dynamic monitoring control method and system for annealing kiln glass temperature
CN118132963B (en) Industrial gas production quality online analysis method and system
CN117368644A (en) Sensor cable detection method
CN113177646A (en) Power distribution equipment online monitoring method and system based on self-adaptive edge proxy
CN108416386A (en) A kind of method and system judged extremely for Hydropower Unit bearing temperature
CN118378834A (en) Energy-saving type energy comprehensive management system and method for optimizing energy scheduling
CN118051083A (en) Intelligent temperature control method and device for heating wire
CN116755411A (en) Industrial equipment data acquisition method and device
CN117889985A (en) Online temperature monitoring method and system for processing flow
CN118170091A (en) Edge intelligent computing industrial control method and system
CN118034417A (en) Plant introduction and conservation environment monitoring management system
CN115015483B (en) Feeding, supplying, analyzing and processing system based on meat pigeon growth data
CN115238769B (en) Abnormal data monitoring method and device based on artificial intelligence
CN118464209B (en) Temperature data monitoring and optimizing method for remote temperature sensing monitoring and alarming
CN118278823B (en) Quality control system for composite board production
CN107065840A (en) A kind of bipolar plates prepare the remote control and diagnostic system and its method of hot press
CN116257019B (en) PLC (programmable logic controller) management method and system based on cloud
CN118068819B (en) Large model data management system for high quality diagnostics and decision making
CN118534832A (en) Medical equipment remote control method and system
CN112235156A (en) Internet of things equipment state online monitoring method and system based on mobile communication
CN118568580A (en) Method and device for aging screening of seeker electronic cabin

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination