CN116136674B - Vacuum induction furnace control system based on remote control of Internet of things - Google Patents
Vacuum induction furnace control system based on remote control of Internet of things Download PDFInfo
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Abstract
The invention discloses a vacuum induction furnace control system based on remote control of the Internet of things, which relates to the field of program control systems and comprises a remote control port, an Internet of things transmission port and a vacuum furnace port, wherein the remote control port is used for providing a remote control signal, controlling the operation of a vacuum furnace, calculating threat coefficients of the vacuum furnace according to a feedback signal of the vacuum furnace and substituting the threat coefficients into a data calculation strategy, the Internet of things transmission port is used for constructing an information flow transmission channel between the remote control port and the vacuum furnace port, the vacuum furnace port is used for collecting and transmitting vacuum furnace working data, checking the transmission data of the remote control port, transmitting an original control signal back to the remote control port to request the remote control port to confirm if a contrast value is larger than a contrast threshold, operating the control signal if the contrast value is smaller than or equal to the contrast threshold, transmitting the contrast value data to a data calculation module, and primarily judging control instructions.
Description
Technical Field
The invention relates to the field of program control systems, in particular to a vacuum induction furnace control system based on remote control of the Internet of things.
Background
The control system is a management system which consists of a control main body, a control object and a control medium and has the self target and function, the control system means that any interested or variable quantity in a machine, a mechanism or other equipment can be kept and changed according to a desired mode, the control system is implemented for enabling the controlled object to reach a preset ideal state, the control system enables the controlled object to approach to a certain required stable state, namely, a vacuum furnace utilizes a vacuum system to discharge partial substances in the furnace chamber in a specific space of the furnace chamber, so that the pressure in the furnace chamber is smaller than a standard atmospheric pressure, the space in the furnace chamber is in order to realize the vacuum state, the existing vacuum furnace mostly realizes the remote control of the Internet of things, but the existing vacuum furnace control system is not fully stable enough, has insufficient functionality and safety, can not quickly find hidden production hazards possibly existing in the vacuum furnace in the process of checking remote control instructions, can not realize the use problems of real-time control and dynamic compensation in the preparation process and the like;
for example, in the chinese patent with publication number CN115718459a, a control system and method for a heat sink vacuum furnace are disclosed, which can monitor the state in the furnace in real time according to real-time display of parameters such as temperature and air pressure in the furnace, and can timely monitor and accurately feedback alarm level when the state parameter in the furnace exceeds standard and the working safety of the vacuum furnace is affected in the working process of the heat sink vacuum furnace control system, so that the whole heat sink vacuum furnace control system is facilitated to realize real-time control and dynamic compensation, effectively improve the automation level of production execution and the quality control capability of products, sort data on the basis of monitoring the exceeding standard state parameter in the furnace and the working safety of the vacuum furnace, calculate the data into an abnormal data evolution model, obtain the evolution process of abnormal data, extract the spreading dangerous variables which affect the working safety of the vacuum furnace in a short time in the future, and facilitate rapid prediction of risks;
as another example, in chinese patent with publication number CN110411228A, a method for uniformly controlling the furnace temperature of a vacuum furnace in the sintering process is disclosed, which comprises the following steps: (1) Manufacturing a standard sample by using a material feed sensitive to temperature; (2) After degreasing, uniformly distributing the degreased sample pieces to 36 different positions in a vacuum furnace, namely, upper, middle, lower, front, middle and rear positions in the vacuum furnace, sintering under the same standard sintering process conditions, and measuring the size of the sintered standard sample pieces; (3) Summarizing size data of the sintered sample pieces, using histogram normal distribution to represent the dispersion condition of the sizes of all the sample pieces in each area in the furnace, coloring the size data of the sample pieces, and judging the distribution condition of the temperatures of each area in the furnace through data colors; (4) And adjusting thermocouple temperature compensation and resistance value of a heating carbon rod in each area in the furnace according to standard deviation and average value of sample size in each area in the furnace, thereby improving uniformity of furnace temperature. According to the technical scheme, the problem of quality fluctuation caused by furnace temperature uniformity during sintering of the product can be effectively avoided, and the sintering yield of the product is improved;
all of the above patents exist: the invention provides a vacuum induction furnace control system based on remote control of the Internet of things, which aims to solve the problems that the existing vacuum furnace control system is not comprehensive and stable enough, has insufficient functionality and safety, can not quickly find out possible hidden production hazards of a vacuum furnace when checking remote control instructions, can not realize real-time control and dynamic compensation in the preparation process and the like.
Disclosure of Invention
The invention mainly aims to provide a vacuum induction furnace control system based on remote control of the Internet of things, which can effectively solve the problems in the background art: the existing vacuum furnace control system is not comprehensive and stable enough, has insufficient functionality and safety, can not quickly find out possible hidden production hazards of the vacuum furnace by checking remote control instructions, and can not realize real-time control, dynamic compensation and other use problems in the preparation process.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
the vacuum induction furnace control system based on the Internet of things remote control comprises a remote control port, an Internet of things transmission port and a vacuum furnace port, wherein the remote control port is used for providing a remote control signal, controlling the operation of a vacuum furnace and calculating threat coefficients of the vacuum furnace according to the feedback signal of the vacuum furnace in a data calculation strategy, the Internet of things transmission port is used for constructing an information flow transmission channel between the remote control port and the vacuum furnace port, and the vacuum furnace port is used for collecting and transmitting vacuum furnace working data and checking the transmission data of the remote control port;
the vacuum furnace port comprises a data acquisition module, a data receiving module, a data checking module, a data inquiring module, a furnace body control module and a furnace body monitoring module, wherein the data acquisition module is used for acquiring real-time data of internal materials of the vacuum furnace in the operation process, the data receiving module is used for receiving control data information transmitted by the remote control port, the data checking module is used for checking control instructions sent by the remote control port through a data checking strategy, the data inquiring module is used for extracting and inquiring past operation and instruction data of the vacuum furnace, the furnace body control module is used for controlling the furnace body according to the transmission instructions of the remote control port, and the furnace body monitoring module is used for acquiring operation data of the vacuum furnace in the operation process.
The remote control port comprises an alarm module, a control operation module, a data calculation module and a data storage module, wherein the control operation module is used for transmitting control instructions to the vacuum furnace port and controlling the operation of the vacuum furnace port, the data calculation module is used for substituting threat data acquired by the vacuum furnace port into a threat data calculation strategy to calculate data threat values, the alarm module is used for dividing the data threat values and providing corresponding alarm grades, and the data storage module is used for correspondingly storing the transmission instructions and feedback data of the furnace body.
The invention is further improved in that the data acquisition module comprises a temperature acquisition unit, a material acquisition unit, a vacuum degree acquisition unit and an abnormal value extraction unit, wherein the temperature acquisition unit is used for acquiring an average temperature value in the vacuum furnace, the material acquisition unit is used for acquiring melting proportion data of materials in the working process of the vacuum furnace, the vacuum degree acquisition unit is used for acquiring average vacuum degree data in the vacuum furnace, and the abnormal value extraction unit is used for comparing acquired data of the temperature acquisition unit, the material acquisition unit and the vacuum degree acquisition unit with corresponding data safety ranges and extracting abnormal values in the acquired data.
The invention is further improved in that the data checking module comprises a data extracting unit and a data predicting unit, wherein the output end of the data inquiring module is connected with the data extracting unit, the data extracting unit is used for extracting inquiring data of the data inquiring module, and the data predicting unit is used for substituting the extracted data into a data predicting strategy to conduct data prediction.
The invention is further improved in that the output end of the furnace body monitoring module is connected with a furnace body abnormal value unit, the furnace body abnormal value unit is used for extracting the furnace body abnormal value in the monitoring data of the furnace body monitoring module, and the output ends of the abnormal value extracting unit and the furnace body abnormal value unit are connected with the data calculating module.
The invention further improves that the data prediction strategy comprises the following specific steps:
s11, collecting control instructions of the remote control port, and inquiring variables of temperature, material fusion proportion and vacuum degree in the vacuum furnace when the control instructions are executed in the data storage module by the data inquiry moduleRate of change of (2)
、/>
And->
Simultaneously extracting production tasks in the vacuum furnace to obtain a material fusion ratio +.>
And vacuum degree variable>
The starting value of the temperature variable is calculated as: />
Wherein n is the number of the temperature sensors uniformly distributed in the furnace body,
for the monitoring area of the ith sensor, < +.>
The detected temperature of the ith sensor;
s12, when the data is imported into a data prediction formula to calculate and execute the control instruction, calculating the final state value of each variable,
，/>
，/>
wherein->
For the final value of temperature, +.>
For the final value of the material fusion ratio, +.>
Is the final value of the vacuum, +.>
Is run time;
s13, extracting a required target final state value from the data storage module,
、/>
and->
Substituting the final value and the target final state value into a data comparison formula, calculating a comparison value of the final value and the target final state value,
and comparing the comparison value with a set comparison threshold, if the comparison value is larger than the comparison threshold, transmitting the original control signal back to the remote control port, requesting the remote control port to confirm, and if the comparison value is smaller than or equal to the comparison threshold, operating the control signal and transmitting the comparison value data to the data calculation module.
The invention is further improved in that the furnace body monitoring module comprises a furnace body monitoring strategy, and the furnace body monitoring strategy comprises the following specific steps:
s14, collecting the electric signal input/output data of the furnace body, wherein the electric signal input/output data comprises input current
Output current
Input voltage->
And output voltage +.>
；
S15, importing monitoring data of the furnace body into a furnace body threat coefficient calculation formula to calculate a threat value of the furnace body, wherein the furnace body threat coefficient calculation formula is as follows:
wherein->
For a safe range value of the output current, +.>
For a safe range value of the input current, +.>
For the safety range value of the output voltage, +.>
For the safe range value of the input voltage, +.>
Closest to the safe range value of the output current +.>
Value of->
Closest to the safe range value of the input current +.>
Value of->
Closest to the safe range value of the output voltage +.>
Value of->
Is the most of the safe range values of the input voltageApproach->
Is a value of (2);
s16, transmitting the threat coefficient obtained through calculation to a data calculation module.
The invention is further improved in that the threat data calculation strategy comprises the following specific steps:
s17, extracting the threat coefficient and the contrast value obtained by calculation and substituting the threat coefficient and the contrast value into a data threat value calculation formula to calculate a data threat value, wherein the data threat value calculation formula is as follows:
；
s18, comparing the data threat value with a set alarm range value, and finding out a corresponding alarm level to alarm.
Compared with the prior art, the invention has the following beneficial effects:
the invention collects the control command of the remote control port, the data inquiry module inquires the temperature in the vacuum furnace, the material fusion proportion, the change rate of vacuum degree variable, the running time and the final running state when executing the control command in the data storage module, the data is imported into the data prediction formula to calculate the final value of each variable when executing the control command, the target final state value required by the smelting work is extracted in the data storage module, the contrast value of the final value and the target final state value is calculated, the contrast value is compared with the set contrast threshold value, if the contrast value is larger than the contrast threshold value, the original control signal is transmitted back to the remote control port to request the remote control port to confirm, if the contrast value is smaller than or equal to the contrast threshold value, the control signal is run, and the contrast value data is transmitted to the data calculation module to preliminarily judge the control command, so as to avoid the loss of equipment and internal raw materials caused by wrong commands.
According to the invention, the electric signal input and output data of the furnace body are collected, the monitoring data of the furnace body are imported into a furnace body threat coefficient calculation formula to calculate the threat value of the furnace body, the calculated threat coefficient and the comparison value are extracted and substituted into the data threat value calculation formula to calculate the data threat value, the threat value is compared with the set alarm range value, the corresponding alarm grade is found out to alarm, the data analysis is comprehensive, the risk is estimated, and the automation level of production execution and the product quality control capability are improved more effectively.
Drawings
Fig. 1 is a schematic diagram of an overall framework of a vacuum induction furnace control system based on remote control of the internet of things.
Fig. 2 is a schematic diagram of a data acquisition module of a vacuum induction furnace control system based on remote control of the internet of things.
Fig. 3 is a schematic connection diagram of a data query module, a data receiving module, a data checking module and a furnace body control module of the vacuum induction furnace control system based on remote control of the internet of things.
Fig. 4 is a schematic connection diagram of a data acquisition module, a furnace body monitoring module, a data calculation module and an alarm module of the vacuum induction furnace control system based on remote control of the internet of things.
Detailed Description
In order that the technical means, the creation characteristics, the achievement of the objects and the effects of the present invention may be easily understood, it should be noted that in the description of the present invention, the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or elements to be referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "a", "an", "the" and "the" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The invention is further described below in conjunction with the detailed description.
Example 1
The embodiment provides that a control instruction of a remote control port is acquired, a data query module queries and executes the control instruction in a data storage module, the change rate, the operation time and the final operation state of a vacuum furnace temperature, a material fusion proportion and a vacuum degree variable, data are imported into a data prediction formula, the final state value of each variable is calculated and executed when the control instruction is calculated and executed, the target final state value required by smelting work is extracted in the data storage module, a contrast value is compared with a set contrast threshold value, an original control signal is transmitted back to the remote control port if the contrast value is larger than the contrast threshold value, the remote control port is requested to confirm, if the contrast value is smaller than or equal to the contrast threshold value, the control signal is operated, and contrast value data are transmitted to a data calculation module, the control instruction is primarily judged, equipment and internal raw material loss caused by the error instruction are avoided, as shown in fig. 1-4, a vacuum induction furnace control system based on the remote control of an internet of things comprises the remote control port, an internet of things transmission port and a vacuum furnace port, the remote control port is used for providing a remote control signal, the operation of the vacuum furnace is controlled, the remote control port is used for checking the data transmission of the vacuum furnace in a data transmission strategy of the vacuum furnace, and the vacuum furnace is used for checking the data transmission port in the vacuum furnace, and the vacuum furnace is used for carrying out the vacuum data transmission control port;
the vacuum furnace port comprises a data acquisition module, a data receiving module, a data checking module, a data inquiring module, a furnace body control module and a furnace body monitoring module, wherein the data acquisition module is used for acquiring real-time data of internal materials of the vacuum furnace in the operation process, the data receiving module is used for receiving control data information transmitted by the remote control port, the data checking module is used for checking control instructions sent by the remote control port through a data checking strategy, the data inquiring module is used for extracting and inquiring past operation and instruction data of the vacuum furnace, the furnace body control module is used for controlling the furnace body according to the transmission instructions of the remote control port, and the furnace body monitoring module is used for acquiring operation data of the vacuum furnace in the operation process.
In this embodiment, the remote control port includes an alarm module, a control operation module, a data calculation module and a data storage module, where the control operation module is used to transmit a control instruction to the vacuum furnace port and control the operation of the vacuum furnace port, the data calculation module is used to substitute threat data collected by the vacuum furnace port into a threat data calculation strategy to calculate a data threat value, the alarm module is used to divide the data threat value and provide a corresponding alarm level, and the data storage module is used to store the transmission instruction and feedback data of the furnace body.
In this embodiment, the data acquisition module includes temperature acquisition unit, material acquisition unit, vacuum degree acquisition unit and outlier extraction element, and temperature acquisition unit is used for gathering the inside average temperature value of vacuum furnace, and material acquisition unit is used for gathering vacuum furnace work in-process, and the melting proportion data of material, vacuum degree acquisition unit are used for gathering the average vacuum degree data in the vacuum furnace, and outlier extraction element is used for comparing temperature acquisition unit, material acquisition unit and vacuum degree acquisition unit's collection data with corresponding data safety range, draws the outlier in the collection data.
In this embodiment, the data checking module includes a data extracting unit and a data predicting unit, the output end of the data querying module is connected with the data extracting unit, the data extracting unit is used for extracting the query data of the data querying module, and the data predicting unit is used for substituting the extracted data into the data predicting policy to perform data prediction.
In this embodiment, the output end of the furnace body monitoring module is connected with a furnace body abnormal value unit, the furnace body abnormal value unit is used for extracting a furnace body abnormal value in the monitoring data of the furnace body monitoring module, and the output ends of the abnormal value extracting unit and the furnace body abnormal value unit are both connected with the data calculating module.
In this embodiment, the data prediction strategy includes the following specific steps:
s11, collecting control instructions of a remote control port, and inquiring the change rate of temperature, material fusion proportion and vacuum degree variables in the vacuum furnace when the control instructions are executed in the data storage module by the data inquiring module
、/>
And->
Wherein i represents the ith variable, and simultaneously extracting production tasks in the vacuum furnace to obtain a material fusion ratio +.>
And vacuum degree variable>
The starting value of the temperature variable is calculated as: />
Wherein n is the number of temperature sensors uniformly distributed in the furnace body, and +.>
For the monitoring area of the ith sensor, < +.>
The detected temperature of the ith sensor;
s12, when the data is imported into a data prediction formula to calculate and execute the control instruction, calculating the final state value of each variable,
，/>
，/>
wherein->
For the final value of temperature, +.>
For the final value of the material fusion ratio, +.>
Is the final value of the vacuum, +.>
Is run time;
s13, extracting a target final state value required by the smelting work in a data storage module,
、/>
and->
Substituting the final value and the target final state value into a data comparison formula, and calculating the comparison value of the final value and the target final state value, < >>
And comparing the comparison value with a set comparison threshold, if the comparison value is larger than the comparison threshold, transmitting the original control signal back to the remote control port, requesting the remote control port to confirm, and if the comparison value is smaller than or equal to the comparison threshold, operating the control signal and transmitting the comparison value data to the data calculation module.
Example 2
The embodiment collects electric signal input and output data of a furnace body on the basis of embodiment 1, monitors data of the furnace body are imported into a furnace body threat coefficient calculation formula to calculate threat values of the furnace body, the threat coefficients and the comparison values obtained through calculation are extracted and substituted into the data threat value calculation formula to calculate data threat values, the threat values are compared with set alarm range values, corresponding alarm levels are found out to alarm, data analysis is comprehensive, risk prediction is facilitated, automation level and product quality control capacity of production execution are improved more effectively, as shown in fig. 1-4, a vacuum induction furnace control system based on remote control of the Internet of things comprises a remote control port, an Internet of things transmission port and a vacuum furnace port, the remote control port is used for providing remote control signals to control operation of the vacuum furnace, and according to feedback signals of the vacuum furnace, threat coefficients of the vacuum furnace are calculated in a data calculation strategy, the Internet of things transmission port is used for constructing an information flow transmission channel between the remote control port and the vacuum furnace port, and the vacuum furnace port is used for collecting and transmitting data of the remote control port, and checking the transmission data of the remote control port is used for checking the remote control port.
The vacuum furnace port comprises a data acquisition module, a data receiving module, a data checking module, a data inquiring module, a furnace body control module and a furnace body monitoring module, wherein the data acquisition module is used for acquiring real-time data of internal materials of the vacuum furnace in the operation process, the data receiving module is used for receiving control data information transmitted by the remote control port, the data checking module is used for checking control instructions sent by the remote control port through a data checking strategy, the data inquiring module is used for extracting and inquiring past operation and instruction data of the vacuum furnace, the furnace body control module is used for controlling the furnace body according to the transmission instructions of the remote control port, and the furnace body monitoring module is used for acquiring operation data of the vacuum furnace in the operation process.
In this embodiment, the remote control port includes an alarm module, a control operation module, a data calculation module and a data storage module, where the control operation module is used to transmit a control instruction to the vacuum furnace port and control the operation of the vacuum furnace port, the data calculation module is used to substitute threat data collected by the vacuum furnace port into a threat data calculation strategy to calculate a data threat value, the alarm module is used to divide the data threat value and provide a corresponding alarm level, and the data storage module is used to store the transmission instruction and feedback data of the furnace body.
In this embodiment, the data acquisition module includes temperature acquisition unit, material acquisition unit, vacuum degree acquisition unit and outlier extraction element, and temperature acquisition unit is used for gathering the inside average temperature value of vacuum furnace, and material acquisition unit is used for gathering vacuum furnace work in-process, and the melting proportion data of material, vacuum degree acquisition unit are used for gathering the average vacuum degree data in the vacuum furnace, and outlier extraction element is used for comparing temperature acquisition unit, material acquisition unit and vacuum degree acquisition unit's collection data with corresponding data safety range, draws the outlier in the collection data.
In this embodiment, the data checking module includes a data extracting unit and a data predicting unit, the output end of the data querying module is connected with the data extracting unit, the data extracting unit is used for extracting the query data of the data querying module, and the data predicting unit is used for substituting the extracted data into the data predicting policy to perform data prediction.
In this embodiment, the output end of the furnace body monitoring module is connected with a furnace body abnormal value unit, the furnace body abnormal value unit is used for extracting a furnace body abnormal value in the monitoring data of the furnace body monitoring module, and the output ends of the abnormal value extracting unit and the furnace body abnormal value unit are both connected with the data calculating module.
In this embodiment, the data prediction strategy includes the following specific steps:
s11, collecting control instructions of a remote control port, and inquiring the change rate of temperature, material fusion proportion and vacuum degree variables in the vacuum furnace when the control instructions are executed in the data storage module by the data inquiring module
、/>
And->
Simultaneously extracting production tasks in the vacuum furnace to obtain a material fusion ratio +.>
And vacuum degree variable>
The starting value of the temperature variable is calculated as: />
Wherein n is the number of temperature sensors uniformly distributed in the furnace body, and +.>
For the monitoring area of the ith sensor, < +.>
The detected temperature of the ith sensor;
s12, when the data is imported into a data prediction formula to calculate and execute the control instruction, calculating the final state value of each variable,
，/>
，/>
wherein->
For the final value of temperature, +.>
For the final value of the material fusion ratio, +.>
Is the final value of the vacuum, +.>
Is run time;
s13, extracting a required target final state value from the data storage module,
、/>
and->
Final value and targetSubstituting the state value into a data comparison formula, calculating a comparison value of the final value and the target final state value,
and comparing the comparison value with a set comparison threshold, if the comparison value is larger than the comparison threshold, transmitting the original control signal back to the remote control port, requesting the remote control port to confirm, and if the comparison value is smaller than or equal to the comparison threshold, operating the control signal and transmitting the comparison value data to the data calculation module.
In this embodiment, the furnace body monitoring module includes a furnace body monitoring policy, where the furnace body monitoring policy includes the following specific steps:
s14, collecting the electric signal input/output data of the furnace body, wherein the electric signal input/output data comprises input current
Output current
Input voltage->
And output voltage +.>
；
S15, importing monitoring data of the furnace body into a furnace body threat coefficient calculation formula to calculate a threat value of the furnace body, wherein the furnace body threat coefficient calculation formula is as follows:
wherein, the method comprises the steps of, wherein,
for a safe range value of the output current, +.>
For a safe range value of the input current,
for the safety range value of the output voltage, +.>
For a safe range value of the input voltage,
closest to the safe range value of the output current +.>
Value of->
Closest to the safe range value of the input current
Value of->
Closest to the safe range value of the output voltage +.>
Value of->
Closest to the safe range value of the input voltage +.>
Is a value of (2);
s16, transmitting the threat coefficient obtained by calculation to a data calculation module;
the threat data calculation strategy comprises the following specific steps:
s17, extracting the threat coefficient and the contrast value obtained by calculation and substituting the threat coefficient and the contrast value into a data threat value calculation formula to calculate a data threat value, wherein the data threat value calculation formula is as follows:
；
s18, comparing the data threat value with a set alarm range value, and finding out a corresponding alarm level to alarm.
It is important to note that the construction and arrangement of the invention as shown in the various exemplary embodiments is illustrative only. Although only a few embodiments have been described in detail in this disclosure, those skilled in the art who review this disclosure will readily appreciate that many modifications are possible (e.g., variations in sizes, dimensions, structures, shapes and proportions of the various elements, values of parameters (e.g., temperature, pressure, etc.), mounting arrangements, use of materials, colors, orientations, etc.) without materially departing from the novel teachings and advantages of the subject matter described in this disclosure. For example, elements shown as integrally formed may be constructed of multiple parts or elements, the position of elements may be reversed or otherwise varied, and the nature or number of discrete elements or positions may be altered or varied. Accordingly, all such modifications are intended to be included within the scope of present invention. The order or sequence of any process or method steps may be varied or re-sequenced according to alternative embodiments. In the claims, any means-plus-function clause is intended to cover the structures described herein as performing the recited function and not only structural equivalents but also equivalent structures. Other substitutions, modifications, changes and omissions may be made in the design, operating conditions and arrangement of the exemplary embodiments without departing from the scope of the present inventions. Therefore, the invention is not limited to the specific embodiments, but extends to various modifications that nevertheless fall within the scope of the appended claims.
Furthermore, in an effort to provide a concise description of the exemplary embodiments, all features of an actual implementation may not be described (i.e., those not associated with the best mode presently contemplated for carrying out the invention, or those not associated with practicing the invention).
It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.
Claims (1)
1. A vacuum induction furnace control system based on remote control of the Internet of things is characterized in that: the system comprises a remote control port, an internet of things transmission port and a vacuum furnace port, wherein the remote control port is used for providing a remote control signal, controlling the operation of the vacuum furnace, calculating threat coefficients of the vacuum furnace according to a data calculation strategy of feedback signals of the vacuum furnace, the internet of things transmission port is used for constructing an information flow transmission channel between the remote control port and the vacuum furnace port, and the vacuum furnace port is used for collecting and transmitting vacuum furnace working data and checking the transmission data of the remote control port;
the vacuum furnace port comprises a data acquisition module, a data receiving module, a data checking module, a data inquiring module, a furnace body control module and a furnace body monitoring module, wherein the data acquisition module is used for acquiring real-time data of internal materials of the vacuum furnace in the operation process, the data receiving module is used for receiving control data information transmitted by the remote control port, the data checking module is used for checking control instructions sent by the remote control port through a data checking strategy, the data inquiring module is used for extracting and inquiring past operation and instruction data of the vacuum furnace, the furnace body control module is used for controlling the furnace body according to the transmission instructions of the remote control port, and the furnace body monitoring module is used for acquiring operation data of the vacuum furnace in the operation process; the remote control port comprises an alarm module, a control operation module, a data calculation module and a data storage module, wherein the control operation module is used for transmitting control instructions to the vacuum furnace port and controlling the operation of the vacuum furnace port, the data calculation module is used for substituting threat data acquired by the vacuum furnace port into a threat data calculation strategy to calculate data threat values, the alarm module is used for dividing the data threat values and providing corresponding alarm grades, and the data storage module is used for correspondingly storing the transmission instructions and feedback data of the furnace body; the data acquisition module comprises a temperature acquisition unit, a material acquisition unit, a vacuum degree acquisition unit and an abnormal value extraction unit, wherein the temperature acquisition unit is used for acquiring an average temperature value in the vacuum furnace, the material acquisition unit is used for acquiring melting proportion data of materials in the working process of the vacuum furnace, the vacuum degree acquisition unit is used for acquiring the average vacuum degree data in the vacuum furnace, and the abnormal value extraction unit is used for comparing the acquired data of the temperature acquisition unit, the material acquisition unit and the vacuum degree acquisition unit with corresponding data safety ranges and extracting abnormal values in the acquired data; the data checking module comprises a data extraction unit and a data prediction unit, the output end of the data inquiry module is connected with the data extraction unit, the data extraction unit is used for extracting inquiry data of the data inquiry module, and the data prediction unit is used for substituting the extracted data into a data prediction strategy to perform data prediction; the output end of the furnace body monitoring module is connected with a furnace body abnormal value unit, the furnace body abnormal value unit is used for extracting a furnace body abnormal value in the monitoring data of the furnace body monitoring module, and the output ends of the abnormal value extraction unit and the furnace body abnormal value unit are connected with the data calculation module; the data prediction strategy comprises the following specific steps:
s11, collecting control instructions of a remote control port, and inquiring the change rate of temperature, material fusion proportion and vacuum degree variables in the vacuum furnace when the control instructions are executed in the data storage module by the data inquiring module
、/>
And->
Simultaneously extracting production tasks in the vacuum furnace to obtain a material fusion ratio +.>
And vacuum degree variable>
The starting value of the temperature variable is calculated as: />
Wherein n is the number of temperature sensors uniformly distributed in the furnace body, and +.>
For the monitoring area of the ith sensor, < +.>
The detected temperature of the ith sensor;
s12, when the data is imported into a data prediction formula to calculate and execute the control instruction, calculating the final state value of each variable,
，/>
，/>
wherein->
For the final value of temperature, +.>
For the final value of the material fusion ratio, +.>
Is vacuumFinal value of degree +.>
Is run time;
s13, extracting a required target final state value from the data storage module,
、/>
and->
Substituting the final value and the target final state value into a data comparison formula, calculating a comparison value of the final value and the target final state value,
comparing the comparison value with a set comparison threshold, if the comparison value is larger than the comparison threshold, transmitting the original control signal back to the remote control port, requesting the remote control port to confirm, and if the comparison value is smaller than or equal to the comparison threshold, operating the control signal and transmitting the comparison value data to the data calculation module; the furnace body monitoring module comprises a furnace body monitoring strategy, and the furnace body monitoring strategy comprises the following specific steps:
s14, collecting the electric signal input/output data of the furnace body, wherein the electric signal input/output data comprises input current
Output current->
Input voltage->
And output voltage +.>
；
S15, importing monitoring data of the furnace body into a furnace body threat coefficient calculation formula to calculate a threat value of the furnace body, wherein the furnace body threat coefficient calculation formula is as follows:
wherein, the method comprises the steps of, wherein,
for a safe range value of the output current, +.>
For a safe range value of the input current,
for the safety range value of the output voltage, +.>
For a safe range value of the input voltage,
closest to the safe range value of the output current +.>
Value of->
Closest to the safe range value of the input current
Value of->
Closest to the safe range value of the output voltage +.>
Value of->
Closest to the safe range value of the input voltage +.>
Is a value of (2);
s16, transmitting the threat coefficient obtained by calculation to a data calculation module; the threat data calculation strategy comprises the following specific steps:
s17, extracting the threat coefficient and the contrast value obtained by calculation and substituting the threat coefficient and the contrast value into a data threat value calculation formula to calculate a data threat value, wherein the data threat value calculation formula is as follows:
；
s18, comparing the data threat value with a set alarm range value, and finding out a corresponding alarm level to alarm.
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