CN115542860B - Intelligent bearing production line process supervision control system based on Internet of things - Google Patents
Intelligent bearing production line process supervision control system based on Internet of things Download PDFInfo
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Abstract
The invention relates to the field of bearing production supervision, in particular to an intelligent bearing production line process supervision control system based on the Internet of things, which comprises a cloud supervision platform, a processing analysis unit, an operation coefficient acquisition unit, a self-checking operation unit, an information feedback platform and an authorization terminal; according to the invention, the overtime order is carefully analyzed through the self-checking operation unit, so that the processing operation time of each processing station of the overtime order and the change condition of the operating oil temperature and the operating voltage of each process equipment are known, namely, the production condition of the bearing production line is more comprehensively known, and the existing production line processing problem is timely solved; the information feedback platform is used for constructing an intercommunication platform, so that a registration manager and registration workers can directly exchange information to improve the communication efficiency, the processing condition of each station and the operation condition of each process device can be timely known, and meanwhile, the production problem can be timely solved according to the feedback condition of each station, namely the condition of the lamplight color of each station.
Description
Technical Field
The invention relates to the field of bearing production supervision, in particular to an intelligent bearing production line process supervision control system based on the Internet of things.
Background
The bearing is an important part in modern mechanical equipment, and has the main functions of supporting a mechanical rotating body, reducing the friction coefficient in the motion process of the mechanical rotating body and ensuring the rotation precision of the mechanical rotating body, the bearing industry in China rapidly develops, the bearing variety is from less to more, the product quality and the technical level are from low to high, the industry scale is from small to large, and a professional production system with basically complete product categories and reasonable production layout is formed;
the existing bearing production line process supervision control system is mainly used for singly supervising production line equipment or machining conditions, can not comprehensively make deep analysis and judgment on machining stations, machining equipment and machining quality of the bearing, and can not feed back information, so that an administrator and workers can not directly communicate, the processing rate of production problems is reduced, and the conditions of the machining stations and the machining equipment are not objectively reflected;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide an intelligent bearing production line process supervision control system based on the Internet of things, which solves the technical defects, namely, a self-checking operation unit is used for carrying out detailed analysis on overtime orders, so as to know the processing operation time of each processing station of the overtime orders and the change condition of the operating oil temperature and voltage of each process equipment, namely, the production condition of the bearing production line is more comprehensively known, and the existing production line processing problem is timely solved; the information feedback platform is used for constructing an intercommunication platform, so that a registration manager and registration workers can directly exchange information to improve the communication efficiency, the processing condition of each station and the operation condition of each process device can be timely known, and meanwhile, the production problem can be timely solved according to the feedback condition of each station, namely the condition of the lamplight color of each station.
The aim of the invention can be achieved by the following technical scheme:
the intelligent bearing production line process supervision and control system based on the Internet of things comprises a cloud supervision platform, a processing analysis unit, an operation coefficient acquisition unit, a self-checking operation unit, an information feedback platform and an authorization terminal, wherein the cloud supervision platform is in bidirectional communication connection with the processing analysis unit, the operation coefficient acquisition unit is in bidirectional communication connection with the processing analysis unit, the self-checking operation unit is in bidirectional communication connection with the processing analysis unit, the cloud supervision platform is in unidirectional communication connection with the information feedback platform, and the information feedback platform is in unidirectional communication connection with the authorization terminal;
the self-checking operation unit is used for collecting the order duration of the machined bearing, carrying out efficiency analysis on the order duration of the machined bearing, obtaining a timeout signal and an advance signal, and sending the timeout signal and the advance signal to the machining analysis unit;
the operation coefficient acquisition unit is used for acquiring operation state information of the equipment, analyzing the operation state information of the equipment, acquiring a qualified operation coefficient, and sending the qualified operation coefficient to the processing analysis unit, wherein the operation state information comprises transformer oil temperature and operation voltage;
after receiving the qualified operation coefficient and the overtime signal, the processing analysis unit monitors and analyzes processing and production process equipment in the overtime order bearing corresponding to the overtime signal in real time, divides the result into unqualified process equipment and qualified process equipment, and sends corresponding numbers of the unqualified process equipment and the qualified process equipment to the cloud supervision platform;
after receiving the overtime signal, the processing analysis unit analyzes the processing stations of the overtime order corresponding to the overtime signal, obtains the numbers corresponding to the normal operation stations and the abnormal operation stations and sends the numbers to the cloud supervision platform;
after receiving corresponding numbers of unqualified process equipment and qualified process equipment, the cloud supervision platform generates a normal information feedback signal and an abnormal information feedback signal, and sends the signals and the numbers of corresponding stations to the information feedback platform;
after receiving numbers corresponding to the abnormal operation stations and the normal operation stations, the cloud supervision platform generates corresponding abnormal information feedback signals and normal information feedback signals, and sends the signals and the corresponding stations to the information feedback platform;
the information feedback platform receives the number corresponding to the normal operation station and the normal information feedback signal and then sends the number and the normal information feedback signal to the display unit; and the information feedback platform receives the number corresponding to the abnormal operation station and the abnormal information feedback signal and then sends the number and the abnormal information feedback signal to the authorization terminal.
Preferably, the specific efficiency analysis process of the self-checking operation unit is as follows:
step one: acquiring a machined bearing order in real time, marking the machined bearing order as i, i=1, 2, …, n and n as positive integers, acquiring a difference value between the current moment and the machined bearing order placing moment, marking the difference value as order completion time, and setting a mark as WDi;
step two: acquiring a specified finishing date of a machined bearing order, acquiring a difference value between the specified finishing date of the bearing order and the ordering date of the bearing order, marking the difference value as specified machining time length, and setting a label GDi;
step three: calculating the ratio of the time for completing the order to the specified processing time, and if the corresponding ratio is more than 1, marking the corresponding processed bearing order as a overtime order, and generating an overtime signal; if the corresponding ratio is less than 1, marking the corresponding processed bearing order as an advance order; an advance signal is generated, the timeout signal being represented as a set of all timeout bearing orders, the advance signal being represented as a set of all advance bearing orders.
Preferably, the process of analyzing the qualified operation coefficient of the operation coefficient acquisition unit is as follows:
the first step: acquiring historical processed bearing orders of a bearing production line, and marking the corresponding historical processed bearing orders which are qualified in quality inspection and good in customer evaluation as data acquisition orders;
and a second step of: acquiring data acquisition order production time, marking the data acquisition order production time as an acquisition time threshold, dividing the acquisition time threshold into a plurality of sub-time periods at intervals of each minute, marking the sub-time periods as o, o=1, 2, …, q and q as positive integers, acquiring transformer oil temperature values and equipment operation voltage values of production equipment in each sub-time period, and marking corresponding oil temperature values and voltage values as YWo and DVo respectively;
and a third step of: constructing transformer oil Wen Jige { YW1, YW2, …, YWq } and a device operation voltage set { DV1, DV2, …, DVq } in an acquisition time threshold, acquiring a device operation oil temperature set and a maximum subset and a minimum subset in the device operation voltage set, and marking the maximum subset and the minimum subset as YWmax and YWmin and DVmax and DVmin, wherein YWmax is an upper limit value of a qualified oil temperature corresponding to an oil temperature value of a production line, YWmin is a lower limit value of the qualified oil temperature corresponding to the oil temperature value of the production line, DVmax is an upper limit value of a qualified voltage corresponding to the voltage value of the production line, and DVmin is a lower limit value of the qualified voltage corresponding to the voltage value of the production line;
fourth step: and obtaining a qualified operation coefficient Xo through a formula.
Preferably, the processing analysis unit specifically monitors and analyzes the following processes:
step S1: selecting a record process of a bearing processing line with overtime order to obtain corresponding production process equipment of a matched bearing processing line, and marking the corresponding production process equipment as g, wherein g=1, 2, …, p and p are positive integers;
step S2: in the running process of the bearing processing line, the oil temperature value and the voltage value of each processing procedure device are obtained in real time, the oil temperature value and the voltage value of each production procedure device are respectively marked as JYp and JVp, the running coefficient YXp of each processing procedure device is obtained through a running coefficient calculation formula, and the running coefficient YXp is compared with the qualified running coefficient Xo: if the operation coefficient YXp is more than or equal to the qualified operation coefficient Xo, judging that the corresponding processing procedure equipment is qualified in operation, and marking the corresponding processing procedure equipment as operation qualified procedure equipment; and if the operation coefficient YXp is smaller than the qualified operation coefficient Xo, judging that the corresponding processing procedure equipment is unqualified in operation, and marking the corresponding production processing procedure equipment as unqualified operation procedure equipment.
Preferably, the processing analysis unit analyzes the processing station and the product quality of the overtime order corresponding to the overtime signal, and the specific steps are as follows:
acquiring a machining station for machining the bearing in the overtime order in real time, marking the machining station for machining the bearing in the overtime order as k, wherein k=1, 2, …, m and m are positive integers, acquiring a difference value between the machining end time and the machining start time of the corresponding station of the current bearing, marking the difference value as machining time, and setting the mark as JGk;
obtaining the difference value between the processing end time and the processing start time of the corresponding station of the current bearing, marking the difference value with normal operation time, setting the mark as YXk, calculating the ratio of the processing time to the normal operation time, and marking the corresponding station as an abnormal operation station if the corresponding ratio is more than 1; if the corresponding ratio is less than 1, marking the corresponding station as a normal operation station;
the product quality analysis is as follows:
acquiring a bearing processed by a overtime order, marking the bearing processed by the overtime order as x, x=1, 2, …, z and z as positive integers, acquiring the processed bearing surface smoothness value, marking the processed bearing surface smoothness value as GHx, constructing a collection { GH1, GH2, …, GHz } of all bearing surface smoothness values after the processing of the overtime order is completed, acquiring a maximum subset and a minimum subset in the collection of the equipment processing bearing surface smoothness, marking the collection and the minimum subset as GHmax and GHmin, wherein GHmax is represented as the maximum upper limit value of the equipment processing bearing surface smoothness value, GHmin is represented as the maximum lower limit value of the equipment processing bearing surface smoothness value, acquiring the smoothness coefficient Y of the overtime processing bearing surface through a formula, acquiring the smoothness coefficient GBX of the order-specified processing bearing surface, calculating the ratio of the smoothness coefficient GBX and the smoothness coefficient GBX, and generating a good signal corresponding to the bearing order if the corresponding ratio is more than 1; if the corresponding ratio is less than 1, generating an inferior signal corresponding to the bearing order; transmitting the superior signal and the inferior signal to a cloud supervision platform; the superior signal and the inferior signal are respectively expressed as a corresponding set of superior orders and inferior orders;
acquiring a smoothness coefficient L of the surface of the bearing to be processed in advance through a formula, calculating the ratio of the smoothness coefficient of the surface of the bearing to the smoothness coefficient GBX of the surface of the bearing to be processed currently regulated, namely calculating the ratio of L to GBX, and if the corresponding ratio is more than 1, generating a super-quality signal corresponding to the bearing order; if the corresponding ratio is less than 1, generating an ultra-poor signal corresponding to the bearing order; the supergood signal and the superpoor signal are represented as corresponding sets of supergood orders and superpoor orders, respectively.
Preferably, the authorization terminal comprises a registration manager and a registration worker, and the registration manager and the registration worker are in bidirectional communication connection; the information feedback platform comprises the following specific feedback processes:
step T1: after receiving the signal and the abnormal operation station and the normal operation station, the information feedback platform generates an information transmission instruction, marks the private network covered by the information feedback platform as an information transmission alternating current network, and simultaneously carries out communication connection on the authorization terminal through the information transmission alternating current network;
step T2: the registration manager and the registration workers in the information transmission alternating current network can preview according to the operation condition of the stations, meanwhile, the registration manager and the registration workers communicate through the information transmission alternating current network to rectify the operation of the stations, and if the processing analysis unit analyzes the rectified stations, the information feedback platform automatically replaces the corresponding station information after judging that the corresponding stations are qualified.
The beneficial effects of the invention are as follows:
according to the invention, the operation of the equipment is analyzed through the operation coefficient acquisition unit, the qualified operation coefficient is acquired and is used as an analysis basis of the processing analysis unit, the processing of the bearing is influenced by the operation state of the equipment, namely, the qualified operation coefficient can improve the accuracy of production analysis, the state of the equipment during processing the bearing can be known more accurately, and the subsequent timely adjustment of the equipment is facilitated;
in the invention, after receiving the qualified operation coefficient and overtime orders, the processing analysis unit monitors the overtime order bearing processing production process equipment in real time, analyzes all the process equipment in the production line, prevents the occurrence of processing overtime caused by abnormal process equipment, improves the working efficiency of bearing processing, and has the effect of real-time supervision and timely feedback and adjustment of all the process equipment;
according to the invention, the information feedback platform is used for constructing the intercommunication platform, information feedback is carried out on registration administrators and registration workers, information transmission time can be reduced by establishing an information feedback channel, meanwhile, the registration administrators and the registration workers directly carry out information communication to improve communication efficiency, meanwhile, the processing condition of each station and the operation condition of each process equipment can be timely known, and meanwhile, according to the feedback condition of each station, namely the condition of the lamplight color of each station, the reaction can be timely carried out, so that the timely solution of production problems is facilitated.
Drawings
The invention is further described below with reference to the accompanying drawings;
FIG. 1 is a functional block diagram 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.
Example 1
Referring to fig. 1, the intelligent bearing production line process supervision control system based on the internet of things comprises a cloud supervision platform, a processing analysis unit, an operation coefficient acquisition unit, a self-checking operation unit, an information feedback platform and an authorization terminal, wherein the cloud supervision platform is in bidirectional communication connection with the processing analysis unit, the operation coefficient acquisition unit is in bidirectional communication connection with the processing analysis unit, the self-checking operation unit is in bidirectional communication connection with the processing analysis unit, the cloud supervision platform is in unidirectional communication connection with the information feedback platform, and the information feedback platform is in unidirectional communication connection with the authorization terminal;
the authorization terminal comprises a registration manager and a registration worker, and the registration manager and the registration worker are in bidirectional communication connection;
the self-checking operation unit is used for collecting machined bearing orders, analyzing the working efficiency of the machined bearing orders, classifying the machined bearing orders, and the specific working efficiency analysis and classification process is as follows:
step one: acquiring a machined bearing order in real time, marking the machined bearing order as i, i=1, 2, …, n and n as positive integers, acquiring a difference value between the current moment and the machined bearing order placing moment, marking the difference value as order completion time, and setting a mark as WDi;
step two: acquiring a specified finishing date of a machined bearing order, acquiring a difference value between the specified finishing date of the bearing order and the ordering date of the bearing order, marking the difference value as specified machining time length, and setting a label GDi;
step three: calculating the ratio of the time length of completing the order to the specified processing time length, if the corresponding ratio is more than 1, marking the corresponding processed bearing order as a overtime order, generating an overtime signal, and sending the overtime signal to a processing analysis unit; analyzing the overtime order, knowing the processing operation time of each processing station of the overtime order and the change condition of the operating oil temperature and the operating voltage of each process equipment, and solving the existing production line processing problem in time; if the corresponding ratio is less than 1, marking the corresponding processed bearing order as an advance order; generating an advance signal, and transmitting the advance signal to a cloud supervision platform; the timeout signal is represented as a set of all timeout bearing orders and the advance signal is represented as a set of all advance bearing orders;
after receiving the overtime signal, the processing analysis unit analyzes the processing station of the overtime order corresponding to the overtime signal; the specific analysis steps are as follows:
acquiring a machining station for machining the bearing in the overtime order in real time, marking the machining station for machining the bearing in the overtime order as k, wherein k=1, 2, …, m and m are positive integers, acquiring a difference value between the machining end time and the machining start time of the corresponding station of the current bearing, marking the difference value as machining time, and setting the mark as JGk;
obtaining the difference value between the processing end time and the processing start time of the corresponding station of the current bearing, marking the difference value with normal operation time, setting the mark as YXk, calculating the ratio of the processing time to the normal operation time, and marking the corresponding station as an abnormal operation station if the corresponding ratio is more than 1;
if the corresponding ratio is less than 1, marking the corresponding station as a normal operation station, and sending the number corresponding to the abnormal operation station to a cloud supervision platform;
the product quality analysis is as follows:
acquiring a bearing processed by a overtime order, marking the bearing processed by the overtime order as x, x=1, 2, …, z and z as positive integers, acquiring a processed bearing surface smoothness value, marking the processed bearing surface smoothness value as GHx, constructing a collection { GH1, GH2, …, GHz } of all bearing surface smoothness values after the processing of the overtime order is completed, acquiring a maximum subset and a minimum subset in the collection of the equipment processing bearing surface smoothness, marking the maximum subset and the minimum subset as GHMax and GHMin, wherein GHMax is expressed as the maximum upper limit value of the equipment processing bearing surface smoothness value, GHMin is expressed as the maximum lower limit value of the equipment processing bearing surface smoothness value,
the method comprises the steps of acquiring a smoothness coefficient L of a bearing surface to be processed in advance through the formula, carrying out ratio calculation on the smoothness coefficient L of the bearing surface to be processed currently and the smoothness coefficient GBX of the bearing surface to be processed currently, namely carrying out ratio calculation on the L and GBX, if the corresponding ratio is more than 1, generating a super-high-quality signal corresponding to a bearing order, analyzing the super-high-quality order corresponding to the super-high-quality signal, processing the super-high-quality signal quickly and well, greatly improving the production efficiency of equipment, if the corresponding ratio is less than 1, generating a super-high-quality signal corresponding to the bearing order, analyzing the super-high-quality order corresponding to the super-high-quality signal, wherein the time is long, the product quality is poor, the normal production of the equipment is not facilitated, and the super-high-quality signal and the super-low-quality signal are respectively expressed as a set of the corresponding super-high-quality order and super-low-quality order; the super-quality signal and the super-quality signal are sent to a cloud supervision platform;
the operation coefficient acquisition unit is used for analyzing the operation of the equipment to acquire qualified operation coefficients, the qualified operation coefficients are acquired to serve as analysis basis of the processing analysis unit, the processing of the bearing is affected by the operation state of the equipment, namely, the qualified operation coefficients can improve the accuracy of production analysis, the state of the equipment in the processing of the bearing can be known more accurately, the follow-up timely adjustment of the equipment is facilitated, and the acquisition process of the qualified operation coefficients is as follows:
the first step: acquiring historical processed bearing orders of a bearing production line, and marking the corresponding historical processed bearing orders which are qualified in quality inspection and good in customer evaluation as data acquisition orders;
and a second step of: acquiring data acquisition order production time, marking the data acquisition order production time as an acquisition time threshold, dividing the acquisition time threshold into a plurality of sub-time periods at intervals of each minute, marking the sub-time periods as o, o=1, 2, …, q and q as positive integers, acquiring transformer oil temperature values and equipment operation voltage values of production equipment in each sub-time period, and marking corresponding oil temperature values and voltage values as YWo and DVo respectively;
and a third step of: constructing transformer oil Wen Jige { YW1, YW2, …, YWq } and a device operation voltage set { DV1, DV2, …, DVq } in an acquisition time threshold, acquiring a device operation oil temperature set and a maximum subset and a minimum subset in the device operation voltage set, and marking the maximum subset and the minimum subset as YWmax and YWmin and DVmax and DVmin, wherein YWmax is an upper limit value of a qualified oil temperature corresponding to an oil temperature value of a production line, YWmin is a lower limit value of the qualified oil temperature corresponding to the oil temperature value of the production line, DVmax is an upper limit value of a qualified voltage corresponding to the voltage value of the production line, and DVmin is a lower limit value of the qualified voltage corresponding to the voltage value of the production line;
fourth step: and calculating a formula by a qualified operation coefficient:
the correction coefficient in the formula is obtained by sampling analysis by a person skilled in the art, such as a temperature correction coefficient, the person skilled in the art randomly extracts five time periods, monitors the five time periods, obtains real-time oil temperature values around the production line in the five time periods, namely 35 ℃,32 ℃,24 ℃,26 ℃ and 30 ℃, obtains a proper oil temperature interval 22-36 ℃ corresponding to production of the production line, marks the median value in a qualified temperature interval as optimal oil temperature, namely 29 ℃, and can adjust the real-time oil temperature value to the optimal temperature through the temperature correction coefficient in the analysis and calculation process, namely 0.84,0.88,1.09,1.14 and 0.95 corresponding to the temperature correction coefficient in the five time periods, and takes the average value as 0.98;
fifth step: sending the qualified operation coefficient to a processing analysis unit;
after receiving the qualified operation coefficient and the overtime signal, the processing analysis unit monitors the overtime order bearing processing production procedure in real time, analyzes each procedure in the production line, prevents the processing overtime caused by abnormal procedures, improves the working efficiency of bearing processing, and specifically monitors and analyzes the following procedures:
step S1: selecting a record process of a bearing processing line with overtime order to obtain corresponding production process equipment of a matched bearing processing line, and marking the corresponding production process equipment as g, wherein g=1, 2, …, p and p are positive integers;
step S2: in the running process of the bearing processing line, the oil temperature value and the voltage value of each processing procedure device are obtained in real time, the oil temperature value and the voltage value of each production procedure device are respectively marked as JYp and JVp, the running coefficient YXp of each processing procedure device is obtained through a running coefficient calculation formula, and the running coefficient YXp is compared with the qualified running coefficient Xo: if the operation coefficient YXp is more than or equal to the qualified operation coefficient Xo, judging that the corresponding processing procedure equipment is qualified in operation, and marking the corresponding processing procedure equipment as operation qualified procedure equipment; if the operation coefficient YXp is smaller than the qualified operation coefficient Xo, judging that the corresponding processing procedure equipment is unqualified for operation, and marking the corresponding production processing procedure equipment as unqualified operation procedure equipment;
step S3: the serial numbers corresponding to the unqualified process equipment are sent to a cloud supervision platform, the cloud supervision platform carries out real-time operation analysis on each processing process equipment, and timely adjusts the unqualified process equipment, so that unqualified bearing processing caused by abnormal oil temperature and voltage in the processing process is prevented;
after receiving the numbers corresponding to the abnormal operation stations and the normal operation stations, the cloud supervision platform generates corresponding abnormal information feedback signals and normal information feedback signals, and sends the signals and the numbers of the corresponding stations to the information feedback platform;
the information feedback platform is used for constructing an intercommunication platform, carrying out information feedback on registration administrators and registration workers, establishing information feedback channels can reduce information transmission time, simultaneously, the registration administrators and the registration workers directly carry out information communication to improve communication efficiency, meanwhile, the processing condition of each station is timely known, the production problem is solved, in addition, the registration administrators and the registration workers can only operate equipment, and the safety of equipment information is improved, and the specific feedback process is as follows:
step T1: after receiving the signal and the abnormal operation station and the normal operation station, the information feedback platform generates an information transmission instruction, marks the private network covered by the information feedback platform as an information transmission alternating current network, and simultaneously carries out communication connection on the authorization terminal through the information transmission alternating current network;
step T2: registering an administrator and a registration worker in the information transmission alternating current network can preview according to the operation condition of the stations, meanwhile, the administrator and the worker communicate through the information transmission alternating current network to rectify the operation of the stations, and if the processing analysis unit analyzes the rectified stations, the information feedback platform automatically replaces the corresponding station information after judging that the corresponding stations are qualified;
step T3: for the normal information feedback signal, the information feedback platform receives the normal information feedback signal and then sends the normal information feedback signal to the display unit, and the display unit immediately controls the display mechanism to mark the normal operation station and display the normal operation station as a green light after receiving the signal;
for the abnormal information feedback signal, the information feedback platform receives the abnormal information feedback signal and sends the abnormal information feedback signal to the display unit, and the display unit immediately controls the display mechanism to mark the abnormal operation station and display the abnormal operation station as a red light after receiving the signal; the operation condition of the station can be more intuitively known by a power-assisted manager and workers.
The working process and principle of the invention are as follows:
the intelligent bearing production line process supervision control system based on the Internet of things is used for analyzing the processed bearing orders and classifying the processed bearing production orders when in operation; analyzing the equipment operation through an operation coefficient acquisition unit to obtain a qualified operation coefficient, and sending the qualified operation coefficient to a production analysis unit; after receiving the qualified environmental coefficient and the overtime order through the production analysis unit, real-time monitoring the overtime order bearing processing production process equipment; after receiving the information feedback signals and the corresponding process equipment through the information feedback platform, carrying out information feedback on a registration manager and a registration worker; after receiving the signals and the abnormal operation stations and the normal operation stations, the information feedback platform feeds back information to the registration manager and the registration workers, and after receiving the feedback, the registration manager and the registration workers communicate through an information transmission alternating current network to rectify and change the process equipment.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (4)
1. The intelligent bearing production line process supervision control system based on the Internet of things is characterized by comprising a cloud supervision platform, a processing analysis unit, an operation coefficient acquisition unit, a self-checking operation unit, an information feedback platform and an authorization terminal;
the self-checking operation unit is used for collecting the order duration of the machined bearing, carrying out efficiency analysis on the order duration of the machined bearing, obtaining a timeout signal and an advance signal, and sending the timeout signal and the advance signal to the machining analysis unit;
the operation coefficient acquisition unit is used for acquiring operation state information of the equipment, analyzing the operation state information of the equipment, acquiring a qualified operation coefficient, and sending the qualified operation coefficient to the processing analysis unit, wherein the operation state information comprises transformer oil temperature and operation voltage;
after receiving the qualified operation coefficient and the overtime signal, the processing analysis unit monitors and analyzes processing and production process equipment in the overtime order bearing corresponding to the overtime signal in real time, divides the result into unqualified process equipment and qualified process equipment, and sends corresponding numbers of the unqualified process equipment and the qualified process equipment to the cloud supervision platform;
after receiving the overtime signal, the processing analysis unit analyzes the processing stations of the overtime order corresponding to the overtime signal, obtains the numbers corresponding to the normal operation stations and the abnormal operation stations and sends the numbers to the cloud supervision platform;
after receiving corresponding numbers of unqualified process equipment and qualified process equipment, the cloud supervision platform generates a normal information feedback signal and an abnormal information feedback signal, and sends the feedback signals and the numbers of corresponding stations to the information feedback platform;
after receiving numbers corresponding to the abnormal operation stations and the normal operation stations, the cloud supervision platform generates corresponding abnormal information feedback signals and normal information feedback signals, and sends the feedback signals and the corresponding stations to the information feedback platform;
the information feedback platform receives the number corresponding to the normal operation station and the normal information feedback signal and then sends the number and the normal information feedback signal to the display unit; the information feedback platform receives the number corresponding to the abnormal operation station and the abnormal information feedback signal and then sends the number and the abnormal information feedback signal to the authorization terminal;
the processing analysis unit specifically monitors and analyzes the following processes:
step S1: selecting a record process of a bearing processing line with overtime order to obtain corresponding production process equipment of a matched bearing processing line, and marking the corresponding production process equipment as g, wherein g=1, 2, …, p and p are positive integers;
step S2: in the running process of the bearing processing line, the oil temperature value and the voltage value of each processing procedure device are obtained in real time, the oil temperature value and the voltage value of each production procedure device are respectively marked as JYp and JVp, the running coefficient YXp of each processing procedure device is obtained through a running coefficient calculation formula, and the running coefficient YXp is compared with the qualified running coefficient Xo: if the operation coefficient YXp is more than or equal to the qualified operation coefficient Xo, judging that the corresponding processing procedure equipment is qualified in operation, and marking the corresponding processing procedure equipment as operation qualified procedure equipment; if the operation coefficient YXp is smaller than the qualified operation coefficient Xo, judging that the corresponding processing procedure equipment is unqualified for operation, and marking the corresponding production processing procedure equipment as unqualified operation procedure equipment;
the processing analysis unit analyzes the processing station and the product quality of the overtime order corresponding to the overtime signal, and specifically comprises the following steps:
acquiring a machining station for machining the bearing in the overtime order in real time, marking the machining station for machining the bearing in the overtime order as k, wherein k=1, 2, …, m and m are positive integers, acquiring a difference value between the machining end time and the machining start time of the corresponding station of the current bearing, marking the difference value as machining time, and setting the mark as JGk;
obtaining the difference value between the processing end time and the processing start time of the corresponding station of the current bearing, marking the difference value with normal operation time, setting the mark as YXk, calculating the ratio of the processing time to the normal operation time, and marking the corresponding station as an abnormal operation station if the corresponding ratio is more than 1; if the corresponding ratio is less than 1, marking the corresponding station as a normal operation station;
the product quality analysis is as follows:
acquiring a bearing processed by a overtime order, marking the bearing processed by the overtime order as x, x=1, 2, …, z and z as positive integers, acquiring the processed bearing surface smoothness value, marking the processed bearing surface smoothness value as GHx, constructing a collection { GH1, GH2, …, GHz } of all bearing surface smoothness values after the processing of the overtime order is completed, acquiring a maximum subset and a minimum subset in the collection of the equipment processing bearing surface smoothness, marking the collection and the minimum subset as GHmax and GHmin, wherein GHmax is represented as the maximum upper limit value of the equipment processing bearing surface smoothness value, GHmin is represented as the maximum lower limit value of the equipment processing bearing surface smoothness value, acquiring the smoothness coefficient Y of the overtime processing bearing surface through a formula, acquiring the smoothness coefficient GBX of the order-specified processing bearing surface, calculating the ratio of the smoothness coefficient GBX and the smoothness coefficient GBX, and generating a good signal corresponding to the bearing order if the corresponding ratio is more than 1; if the corresponding ratio is less than 1, generating an inferior signal corresponding to the bearing order; transmitting the superior signal and the inferior signal to a cloud supervision platform; the superior signal and the inferior signal are respectively expressed as a corresponding set of superior orders and inferior orders;
acquiring a smoothness coefficient L of the surface of the bearing to be processed in advance through a formula, calculating the ratio of the smoothness coefficient of the surface of the bearing to the smoothness coefficient GBX of the surface of the bearing to be processed currently regulated, namely calculating the ratio of L to GBX, and if the corresponding ratio is more than 1, generating a super-quality signal corresponding to the bearing order; if the corresponding ratio is less than 1, generating an ultra-poor signal corresponding to the bearing order; the supergood signal and the superpoor signal are represented as corresponding sets of supergood orders and superpoor orders, respectively.
2. The intelligent bearing production line process supervision control system based on the internet of things according to claim 1, wherein the specific efficiency analysis process of the self-checking operation unit is as follows:
step one: acquiring a machined bearing order in real time, marking the machined bearing order as i, i=1, 2, …, n and n as positive integers, acquiring a difference value between the current moment and the machined bearing order placing moment, marking the difference value as order completion time, and setting a mark as WDi;
step two: acquiring a specified finishing date of a machined bearing order, acquiring a difference value between the specified finishing date of the bearing order and the ordering date of the bearing order, marking the difference value as specified machining time length, and setting a label GDi;
step three: calculating the ratio of the time for completing the order to the specified processing time, and if the corresponding ratio is more than 1, marking the corresponding processed bearing order as a overtime order, and generating an overtime signal; if the corresponding ratio is less than 1, marking the corresponding processed bearing order as an advance order; an advance signal is generated, the timeout signal being represented as a set of all timeout bearing orders, the advance signal being represented as a set of all advance bearing orders.
3. The intelligent bearing production line process supervision control system based on the internet of things according to claim 1, wherein the qualified operation coefficient analysis process of the operation coefficient acquisition unit is as follows:
the first step: acquiring historical processed bearing orders of a bearing production line, and marking the corresponding historical processed bearing orders which are qualified in quality inspection and good in customer evaluation as data acquisition orders;
and a second step of: acquiring data acquisition order production time, marking the data acquisition order production time as an acquisition time threshold, dividing the acquisition time threshold into a plurality of sub-time periods at intervals of each minute, marking the sub-time periods as o, o=1, 2, …, q and q as positive integers, acquiring transformer oil temperature values and equipment operation voltage values of production equipment in each sub-time period, and marking corresponding oil temperature values and voltage values as YWo and DVo respectively;
and a third step of: constructing transformer oil Wen Jige { YW1, YW2, …, YWq } and a device operation voltage set { DV1, DV2, …, DVq } in an acquisition time threshold, acquiring a device operation oil temperature set and a maximum subset and a minimum subset in the device operation voltage set, and marking the maximum subset and the minimum subset as YWmax and YWmin and DVmax and DVmin, wherein YWmax is an upper limit value of a qualified oil temperature corresponding to an oil temperature value of a production line, YWmin is a lower limit value of the qualified oil temperature corresponding to the oil temperature value of the production line, DVmax is an upper limit value of a qualified voltage corresponding to the voltage value of the production line, and DVmin is a lower limit value of the qualified voltage corresponding to the voltage value of the production line;
fourth step: and obtaining a qualified operation coefficient Xo through a formula.
4. The intelligent bearing production line process supervision control system based on the internet of things according to claim 1, wherein the authorization terminal comprises a registration manager and a registration worker, and the registration manager and the registration worker are in bidirectional communication connection; the information feedback platform comprises the following specific feedback processes:
step T1: after receiving the signal and the abnormal operation station and the normal operation station, the information feedback platform generates an information transmission instruction, marks the private network covered by the information feedback platform as an information transmission alternating current network, and simultaneously carries out communication connection on the authorization terminal through the information transmission alternating current network;
step T2: the registration manager and the registration workers in the information transmission alternating current network can preview according to the operation condition of the stations, meanwhile, the registration manager and the registration workers communicate through the information transmission alternating current network to rectify the operation of the stations, and if the processing analysis unit analyzes the rectified stations, the information feedback platform automatically replaces the corresponding station information after judging that the corresponding stations are qualified.
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Denomination of invention: Intelligent bearing production line process supervision and control system based on the Internet of Things Granted publication date: 20230526 Pledgee: Anhui Sixian Rural Commercial Bank Co.,Ltd. Pledgor: Anhui Jiarui Bearing Co.,Ltd. Registration number: Y2024980002400 |
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