CN114640905B - Ceramic production cloud data processing control system and method - Google Patents
Ceramic production cloud data processing control system and method Download PDFInfo
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Abstract
The invention discloses a ceramic production cloud data processing control system, which comprises a basic equipment module, a data acquisition module, a data transmission module, a cloud server and a control module, wherein the basic equipment module comprises: the cloud server is used for processing and analyzing the data uploaded by the data transmission module, and comprises: obtaining basic recommended production process parameters of each main device according to production data and environmental data; respectively comparing the production data and the environmental data acquired at the current moment with the production data and the environmental data acquired at the previous moment to obtain difference data, and predicting the production running state of each main device according to the variation trend of the difference data obtained at different historical moments so as to obtain the predicted adjustment production process parameters of each main device; and combining the basic recommended production process parameters and the predicted adjusted production process parameters to obtain the final recommended production process parameters of each main device.
Description
Technical Field
The invention relates to the technical field of ceramic production, in particular to a cloud data processing control system and method for ceramic production.
Background
The datamation reconstruction of the architectural ceramic production line is an important foundation and premise for realizing intelligent manufacturing in the architectural ceramic industry, and the implementation basis of the datamation reconstruction is to make the data of the whole production flow open and online. With the continuous development of the ceramic industry, ceramic enterprises have more appeal in the aspects of digital fine management, energy consumption fine management, resource optimization configuration, production flexibility, intellectualization and the like of equipment while the production automation degree is continuously improved, and want to comprehensively realize interconnection and intercommunication of data such as whole-line equipment data, process data, product data, quality inspection data, energy consumption data and the like, improve the production efficiency through digital integration, and further realize transformation and upgrade of a production control mode to achieve a digital and intelligent factory.
However, the automation degree of the domestic existing production line of the architectural ceramic enterprises is gradually higher, but the equipment is old and the datamation degree is poorer. Under the present circumstances, a series of problems are caused in the production process of the architectural ceramics: the forklift is inaccurate in feeding in a raw material workshop, the slurry formula fluctuates greatly due to wrong feeding, the quality fluctuation of the powder formula is caused, the molding and firing are further influenced, and finally, the production process is unstable and the product defects are generated. The problems of inaccurate measurement, large process loss and incapability of tracing in measurement of slurry in a slurry pool and powder in a powder bin are often caused; the analysis of data such as product process, product quality and the like is lagged, and online real-time analysis cannot be realized; whether the process quality inspection data are matched with the process parameters cannot be distinguished and processed in time; the manager has difficulty in accessing data and cannot make management and technical decision in time. Production abnormity can not be early-warned and alarmed in time, most defects can be found only by finished products, and then the defects can be returned to a production line to find reasons according to defect types, and the reasons for defect generation can not be found in time, so that effective treatment suggestions and debugging methods cannot be provided.
Disclosure of Invention
The invention aims to provide a ceramic production cloud data processing control system and a ceramic production cloud data processing control method, which can effectively solve the technical problems in the prior art.
In order to achieve the above object, an embodiment of the present invention provides a ceramic production cloud data processing control system, which includes a basic device module, a data acquisition module, a data transmission module, a cloud server, and a control module:
the basic equipment module comprises main equipment arranged in a raw material workshop and a forming workshop of the ceramic production line, and each main equipment has a data function;
the data acquisition module comprises an equipment data acquisition unit and an environment data acquisition unit, the equipment data acquisition unit comprises a data acquisition module used for acquiring the production data of each main equipment, and the environment data acquisition unit is used for acquiring the environment data of the raw material workshop and the forming workshop;
the data transmission module is used for transmitting the production data acquired by the equipment data acquisition unit and the environmental data acquired by the environmental data acquisition unit to a cloud server;
the cloud server is used for processing and analyzing the data uploaded by the data transmission module, and comprises:
obtaining basic recommended production process parameters of each main device according to the production data and the environmental data;
respectively comparing the production data and the environmental data acquired at the current moment with the production data and the environmental data acquired at the previous moment to obtain difference data, and predicting the production running state of each main device according to the variation trend of the difference data obtained at different historical moments so as to obtain the predicted adjustment production process parameters of each main device;
combining the basic recommended production process parameters and the predicted adjustment production process parameters to obtain final recommended production process parameters of each main device;
the control module comprises a device controller for controlling the production operation parameters of each main device, the final recommended production process parameters are fed back to each corresponding device controller through the data transmission module, and each device controller controls the production operation parameters of the corresponding main device according to the corresponding final recommended production process parameters.
Preferably, a self-adaptive acquisition cycle is adopted for each of the equipment data acquisition unit and the environmental data acquisition unit, and the acquisition cycle is a time interval between the current time and the previous time for acquiring data; the acquisition period is determined by:
the cocyclt (i +1) represents an i +1 th collection period, tbase represents a preset basic time length, signt (i) represents a symbol judgment function, and macocylt represents a maximum value of the collection period, wherein:
c represents a preset constant parameter, recdtq (i) represents the number of semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, dterr (i) represents the error rate of the semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, and ythr represents a preset acquisition cycle judgment threshold; dterr (i) = k × err (i)/recdtq (i), where k is a preset coefficient, and err (i) represents the number of substandard semi-finished products/finished products obtained after passing through the corresponding main equipment in the time period in which the ith collection cycle is effective.
Preferably, the ceramic production cloud data processing control system further comprises an image acquisition module, wherein the image acquisition module comprises a camera device arranged at an outlet position of each semi-finished product/finished product of the main equipment, and each camera device is used for acquiring a real-time image of each semi-finished product/finished product and sending the real-time image to the cloud server through the data transmission module;
the cloud server is further configured to:
in the current acquisition period, comparing the semi-finished product/finished product real-time image acquired by each camera device with the corresponding semi-finished product/finished product sample image to find out the semi-finished product/finished product which does not reach the standard, so as to determine the number and error rate of the semi-finished product/finished product which does not reach the standard in the current acquisition period;
and calculating the next acquisition cycle of each equipment data acquisition unit and each environmental data acquisition unit according to the error rate and the formula, and feeding back the next acquisition cycle to each equipment data acquisition unit and each environmental data acquisition unit to acquire data according to the next acquisition cycle.
Preferably, the main equipment of the raw material plant comprises a continuous ball and a spray tower;
the equipment data collector corresponding to the continuous ball is used for collecting production data of a rolling crushing system, production data of a batching system, production data of a stirring system and production data of a continuous ball milling system;
and the equipment data acquisition unit arranged corresponding to the spraying tower is used for spraying tower production data and powder bin production data.
Preferably, the main equipment of the forming workshop comprises a press, a drying kiln, a glaze line, a kiln, a polishing line and a packing line;
the equipment data acquisition unit arranged corresponding to the press is used for acquiring the press production batch progress information and the press production data;
the equipment data collector corresponding to the drying kiln is used for collecting the production data of the drying kiln;
the equipment data acquisition unit arranged corresponding to the glaze line is used for acquiring the production data of the glaze line;
the equipment data acquisition unit corresponding to the kiln is used for acquiring fired product batch information and kiln production data;
the equipment data acquisition unit which is arranged corresponding to the polishing line is used for acquiring polishing product batch information and polishing line production data;
and the equipment data acquisition unit corresponding to the packing line is used for acquiring the production data of the packing line.
The invention correspondingly provides a ceramic production cloud data processing control method, which is suitable for a ceramic production cloud data processing system comprising a basic equipment module, a data acquisition module, a data transmission module, a cloud server and a control module, wherein the basic equipment module comprises main equipment arranged in a raw material workshop and a forming workshop of a ceramic production line, and each main equipment has a data function; the control module comprises a device controller for controlling the production operation parameters of each main device; the method comprises the following steps:
s1, collecting production data of each main device through a device data collector of the data collection module and collecting environmental data of the raw material workshop and the forming workshop through an environmental data collector;
s2, transmitting the production data collected by the equipment data collector and the environmental data collected by the environmental data collector to a cloud server;
s3, the cloud server is used for processing and analyzing the data uploaded by the data transmission module, and the method comprises the following steps:
s31, obtaining basic recommended production process parameters of each main device according to the production data and the environmental data;
s32, respectively comparing the production data and the environmental data acquired at the current moment with the production data and the environmental data acquired at the previous moment to obtain difference data, and predicting the production running state of each main device according to the variation trend of the difference data acquired at different historical moments so as to obtain the predicted adjustment production process parameters of each main device;
s33, combining the basic recommended production process parameters and the predicted adjustment production process parameters to obtain the final recommended production process parameters of each main device;
and S4, feeding back the final recommended production process parameters to each corresponding equipment controller through the data transmission module, so that each equipment controller controls the production operation parameters of the corresponding main equipment according to the corresponding final recommended production process parameters.
Preferably, each of the device data collector and the environmental data collector adopts a self-adaptive collection period, and the collection period is a time interval between the current time and the previous time for collecting data; the acquisition period is determined by:
the cocyclt (i +1) represents an i +1 th collection period, tbase represents a preset basic time length, signt (i) represents a symbol judgment function, and macocylt represents a maximum value of the collection period, wherein:
c represents a preset constant parameter, recdtq (i) represents the number of semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, dterr (i) represents the error rate of the semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, and ythr represents a preset acquisition cycle judgment threshold; dterr (i) = k × err (i)/recdtq (i), where k is a preset coefficient, and err (i) represents the number of substandard semi-finished products/finished products obtained after passing through the corresponding main equipment in the time period in which the ith collection cycle is effective.
Preferably, the ceramic production cloud data processing control further comprises an image acquisition module, wherein the image acquisition module comprises a camera device arranged at the semi-finished product/finished product outlet position of each piece of main equipment; the method further comprises the following steps:
acquiring a real-time image of each semi-finished product/finished product through each camera device and sending the real-time image to a cloud server through the data transmission module;
the cloud server compares the semi-finished product/finished product real-time image acquired by each camera device with the corresponding semi-finished product/finished product sample image in the current acquisition period to find out the semi-finished product/finished product which does not reach the standard, so that the number and the error rate of the semi-finished product/finished product which does not reach the standard in the current acquisition period are determined;
and the cloud server calculates the next acquisition cycle of each equipment data acquisition device and each environmental data acquisition device according to the error rate and the formula, and feeds back the next acquisition cycle to each equipment data acquisition device and each environmental data acquisition device so as to acquire data according to the next acquisition cycle.
Preferably, the main equipment of the raw material plant comprises a continuous ball and a spray tower;
the equipment data collector corresponding to the continuous ball is used for collecting production data of a rolling crushing system, production data of a batching system, production data of a stirring system and production data of a continuous ball milling system;
and the equipment data acquisition unit arranged corresponding to the spraying tower is used for spraying tower production data and powder bin production data.
Preferably, the main equipment of the forming workshop comprises a press, a drying kiln, a glaze line, a kiln, a polishing line and a packing line;
the equipment data acquisition unit arranged corresponding to the press is used for acquiring the press production batch progress information and the press production data;
the equipment data collector corresponding to the drying kiln is used for collecting the production data of the drying kiln;
the equipment data acquisition unit arranged corresponding to the glaze line is used for acquiring the production data of the glaze line;
the equipment data acquisition unit corresponding to the kiln is used for acquiring batch information of fired products and kiln production data;
the equipment data acquisition unit which is arranged corresponding to the polishing line is used for acquiring polishing product batch information and polishing line production data;
and the equipment data acquisition unit corresponding to the packing line is used for acquiring the production data of the packing line.
Compared with the prior art, the cloud data processing control system and method for ceramic production provided by the embodiment of the invention have the following technical effects: the production method can calculate to obtain basic recommended production process parameters of each main device based on production data and environmental data of each main device of a raw material workshop and a forming workshop of a ceramic production line, predict the production running state of each main device according to the variation trend of the data obtained at different historical moments so as to obtain the predicted adjusted production process parameters of each main device and further obtain the final recommended production process parameters, control the corresponding production running parameters of each main device according to the final recommended production process parameters, control the production running state of each main device in advance, avoid the problem of the state of each main device and perform corresponding early warning treatment, process the upcoming production running state of each main device in advance, avoid the influence on the quality of output semi-finished products/finished products due to the occurrence of the state of each main device, thereby improving the production quality of semi-finished products/finished products.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a cloud data processing control system for ceramic production according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of another ceramic production cloud data processing control system according to an embodiment of the present invention.
Fig. 3 is a schematic flow chart of a cloud data processing control method for ceramic production according to an embodiment of the present invention.
Fig. 4 is a schematic flow chart of another ceramic production cloud data processing control method according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically connected, electrically connected or can communicate with each other; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1, an embodiment of the present invention provides a ceramic production cloud data processing control system 1, where the ceramic production cloud data processing control system 1 includes a basic device module 11, a data acquisition module 12, a data transmission module 13, a cloud server 14, and a control module 15:
the basic equipment module 11 comprises main equipment arranged in a raw material workshop and a forming workshop of the ceramic production line, and each main equipment has a data function;
the data acquisition module 12 comprises an equipment data acquisition unit and an environment data acquisition unit, the equipment data acquisition unit comprises a data acquisition unit used for acquiring production data of each main equipment, and the environment data acquisition unit is used for acquiring environment data of the raw material workshop and the forming workshop;
the data transmission module 13 is configured to transmit the production data acquired by the equipment data acquirer and the environmental data acquired by the environmental data acquirer to a cloud server 14;
the cloud server 14 is configured to process and analyze the data uploaded by the data transmission module, and includes:
obtaining basic recommended production process parameters of each main device according to the production data and the environmental data;
respectively comparing the production data and the environmental data acquired at the current moment with the production data and the environmental data acquired at the previous moment to obtain difference data, and predicting the production running state of each main device according to the variation trend of the difference data obtained at different historical moments so as to obtain the predicted adjustment production process parameters of each main device;
combining the basic recommended production process parameters and the predicted adjustment production process parameters to obtain final recommended production process parameters of each main device;
the control module 15 includes a device controller for controlling the production operation parameters of each of the main devices, the final recommended production process parameters are fed back to each of the corresponding device controllers through the data transmission module 13, and each of the device controllers controls the production operation parameters of the corresponding main device according to the corresponding final recommended production process parameters.
Wherein the main equipment of the raw material workshop comprises a continuous ball and a spray tower;
the equipment data collector corresponding to the continuous ball is used for collecting production data of a rolling crushing system, production data of a batching system, production data of a stirring system and production data of a continuous ball milling system;
and the equipment data acquisition unit arranged corresponding to the spraying tower is used for spraying tower production data and powder bin production data.
Specifically, in a raw material workshop, the feeding weighing information such as the Dinghui energy pulping, the frequent crushing, the continuous ball and the like is butted, the material quantity is automatically recorded, and the electric energy, the slurry flow and the water flow information of various devices (the pulping, the quick-viewing crushing and the continuous ball) are collected.
For example, the device data collector provided corresponding to the continuous ball: collecting weighing data of a pug slurrying system, namely a material feeder, water consumption weighing data and additive weighing data; continuous ball-material feeding machine weighing data, water consumption weighing data and additive weighing data are collected and are acquired, and stick crushing-slurry melting-continuous ball power consumption data, quality inspection data and bearing glimpse reporting data are acquired. In addition, the key production operation parameters, power consumption, yield and material consumption of the crusher, the key production operation parameters, power consumption, yield and material consumption of the slurry balls and the key production operation parameters, power consumption, yield and material consumption of the continuous balls are collected. In addition, the actual input amount of the formula is calibrated: the actual formula input amount counted in each hour or each shift can be compared with the theoretical amount, the belt speed is automatically adjusted according to the difference of the deviation rate, and the formula accuracy is improved.
Another example is: by establishing a spray tower central control system, important parameters (powder, moisture, tower top temperature, slurry pressure and the like) of the spray tower are collected and monitored in real time, the parameter change condition of the spray tower can be fed back quickly, and quick feedback adjustment, abnormal tracing and automatic control are realized. The method comprises the following steps:
moisture on-line monitoring: install the moisture tester on spray tower powder conveyor belt to two transmission band drop positions in front of the moisture tester install small-size agitating unit, stir the homogenization to the powder, guarantee powder moisture real-time detection's accuracy.
Collecting key parameters of a spray tower: the method realizes the establishment of the existing parameters of the central control system by monitoring various important parameters of the spray tower: the temperature of the hot blast furnace, the temperature of the top of the spray tower, the temperature in the spray tower, the pressure in the spray tower and the exhaust temperature.
Quality control class parameters: slurry pressure acquisition (powder particle size), roots fan wind pressure, frequency (pulverized coal diffusion), delivery pump frequency, current (pulverized coal addition), and compressed air pressure (pulverized coal diffusion).
Energy efficiency optimization type parameters: a pulverized coal weighing system, slurry flow, combustion supporting and exhaust flow.
The main equipment of the forming workshop comprises a press, a drying kiln, a glaze line, a kiln, a polishing line and a packing line;
the equipment data acquisition unit arranged corresponding to the press is used for acquiring the press production batch progress information and the press production data; for example, parameters of press equipment are acquired through a butt press system data, and powder detection data of a press machine are input through a powder center control machine in a raw material workshop to read powder data.
And the equipment data acquisition unit arranged corresponding to the drying kiln is used for acquiring the production data of the drying kiln.
The equipment data acquisition unit arranged corresponding to the glaze line is used for acquiring the production data of the glaze line;
the equipment data acquisition unit corresponding to the kiln is used for acquiring fired product batch information and kiln production data; for example, the kiln parameters are collected in real time by butting a kiln control system with an external monitoring instrument of a fan.
The equipment data acquisition unit which is arranged corresponding to the polishing line is used for acquiring polishing product batch information and polishing line production data;
and the equipment data acquisition unit corresponding to the packing line is used for acquiring the production data of the packing line.
It can be seen that, in the cloud data processing control system for ceramic production provided by the embodiment of the present invention, based on the production data and the environmental data of each main device in the raw material shop and the forming shop of the ceramic production line, the basic recommended production process parameter of each main device is obtained by calculation, and the production operation state of each main device is predicted according to the variation trend of the data obtained at different historical times, so as to obtain the predicted adjustment production process parameter of each main device, further obtain the final recommended production process parameter, and control the production operation parameter of each corresponding main device according to the final recommended production process parameter, so that the production operation state of each main device can be controlled in advance, the problem of the state of each main device is avoided, then the corresponding early warning processing is performed, and the upcoming production operation state of each main device can be processed in advance, the quality of the output semi-finished products/finished products is prevented from being influenced by the occurrence of conditions of each main device, so that the production quality of the semi-finished products/finished products is improved.
Referring to fig. 2, an embodiment of the present invention provides another ceramic production cloud data processing control system 2, where the ceramic production cloud data processing control system 2 includes a basic device module 11, a data acquisition module 12, a data transmission module 13, a cloud server 14, and a control module 15, and unlike the previous embodiment, the ceramic production cloud data processing control system 2 of the present embodiment further includes an image acquisition module 16.
In addition, in this embodiment, a self-adaptive acquisition cycle is adopted for each of the device data acquisition unit and the environmental data acquisition unit, where the acquisition cycle is a time interval between the current time and the previous time for acquiring data; the acquisition period is determined by:
cocytlt (i +1) represents an i +1 th acquisition cycle, tbase represents a preset basic time length, sign (i) represents a symbol judgment function, macocylt represents the maximum value of the acquisition cycle, wherein:
c represents a preset constant parameter, recdtq (i) represents the number of semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, dterr (i) represents the error rate of the semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, and ythr represents a preset acquisition cycle judgment threshold; dterr (i) = k × err (i)/recdtq (i), where k is a preset coefficient, and err (i) represents the number of substandard semi-finished products/finished products obtained after passing through the corresponding main equipment in the time period in which the ith collection cycle is effective.
It can be seen that the acquisition cycle of each of the device data acquisition devices and the environmental data acquisition device in the embodiment of the present invention is not a fixed acquisition cycle, and the fixed acquisition cycle is not favorable for saving resources and for discovering the abnormality of each of the main devices in time. The invention adopts a self-adaptive acquisition cycle, the possibility of abnormality occurrence of each main device is judged through the value of sign (i), the larger the value of sign (i), the smaller the possibility of abnormality occurrence of the main device is, therefore, when cocytlt (i +1) < macocylt, the larger cocytlt (i +1) is, wherein the calculation of the symbol judgment function is calculated according to the number of semi-finished products/finished products and the error rate of the semi-finished products/finished products obtained after the main device passes through the corresponding acquisition cycle, the larger the number change of the semi-finished products/finished products in two adjacent time periods is, the faster the error rate of the semi-finished products/finished products is increased, the larger the possibility of abnormality occurrence of the main device is shown, therefore, when:
the value of sign (i) can make the next acquisition period self-adaptively shorten, conversely, make the acquisition period self-adaptively enlarge, until not satisfying the time that the clock (i +1) < clock, set the acquisition period as clock. The setting mode of the embodiment of the invention can acquire the production data of the main equipment with a larger acquisition period as much as possible when the number of semi-finished products/finished products and the error rate of the semi-finished products/finished products are normal, and then, as the number of the semi-finished products/finished products and the error rate of the semi-finished products/finished products become larger, the acquisition period is shortened, so that the production abnormity of the main equipment is ensured to be found in time.
The time period during which the collection cycle takes effect refers to the duration of the collection cycle, for example, the times when the 1 st production data and the last production data acquired by the member node in the ith collection cycle are respectively t1 and t2, and the time period during which the ith collection cycle takes effect is [ t1, t2 ].
Further, the image acquisition module 16 includes a camera device disposed at an outlet of each semi-finished product/finished product of the main device, and each camera device is configured to obtain a real-time image of each semi-finished product/finished product and send the real-time image to the cloud server 14 through the data transmission module.
The cloud server 14 is further configured to:
in the current acquisition period, comparing the semi-finished product/finished product real-time image acquired by each camera device with the corresponding semi-finished product/finished product sample image to find out the semi-finished product/finished product which does not reach the standard, so as to determine the number and error rate of the semi-finished product/finished product which does not reach the standard in the current acquisition period;
and calculating the next acquisition cycle of each equipment data acquisition unit and each environmental data acquisition unit according to the error rate and the formula, and feeding back the next acquisition cycle to each equipment data acquisition unit and each environmental data acquisition unit to acquire data according to the next acquisition cycle.
It can be understood that the structures and functions of other modules of the ceramic production cloud data processing control system 2 provided in this embodiment are substantially the same as those of the corresponding modules of the ceramic production cloud data processing control system 1 provided in the above embodiment, and are not described herein again.
Referring to fig. 3, an embodiment of the present invention provides a ceramic production cloud data processing control method, which is applicable to the ceramic production cloud data processing system shown in fig. 1, where the basic device module includes main devices disposed in a raw material shop and a forming shop of a ceramic production line, and each of the main devices has a data function; the control module comprises a device controller for controlling the production operation parameters of each main device; the method comprises the following steps:
s1, collecting production data of each main device through a device data collector of the data collection module and collecting environmental data of the raw material workshop and the forming workshop through an environmental data collector;
s2, transmitting the production data collected by the equipment data collector and the environmental data collected by the environmental data collector to a cloud server;
s3, the cloud server is used for processing and analyzing the data uploaded by the data transmission module, and the method comprises the following steps:
s31, obtaining basic recommended production process parameters of each main device according to the production data and the environmental data;
s32, respectively comparing the production data and the environmental data acquired at the current moment with the production data and the environmental data acquired at the previous moment to obtain difference data, and predicting the production running state of each main device according to the variation trend of the difference data acquired at different historical moments so as to obtain the predicted adjustment production process parameters of each main device;
s33, combining the basic recommended production process parameters and the predicted adjustment production process parameters to obtain the final recommended production process parameters of each main device;
and S4, feeding back the final recommended production process parameters to each corresponding equipment controller through the data transmission module, so that each equipment controller controls the production operation parameters of the corresponding main equipment according to the corresponding final recommended production process parameters.
Wherein the main equipment of the raw material workshop comprises a continuous ball and a spray tower;
the equipment data collector corresponding to the continuous ball is used for collecting production data of a rolling crushing system, production data of a batching system, production data of a stirring system and production data of a continuous ball milling system;
and the equipment data acquisition unit arranged corresponding to the spraying tower is used for spraying tower production data and powder bin production data.
Specifically, in a raw material workshop, the feeding weighing information such as slurry melting by utilizing the Dinghui energy, crushing by using the large number of times, continuous balls and the like is butted, the material quantity is automatically recorded, and the electric energy, the slurry flow and the water flow information of each device (slurry melting, crushing by using the large number of times and continuous balls) are collected.
For example, the device data collector provided corresponding to the continuous ball: collecting weighing data of a pug slurrying system, namely a material feeder, water consumption weighing data and additive weighing data; continuous ball-material feeding machine weighing data, water consumption weighing data and additive weighing data are collected and are acquired, and stick crushing-slurry melting-continuous ball power consumption data, quality inspection data and bearing glimpse reporting data are acquired. In addition, the key production operation parameters, power consumption, yield and material consumption of the crusher, the key production operation parameters, power consumption, yield and material consumption of the slurry balls and the key production operation parameters, power consumption, yield and material consumption of the continuous balls are collected. In addition, the actual input amount of the formula is calibrated: the actual formula input amount counted in each hour or each shift can be compared with the theoretical amount, the belt speed is automatically adjusted according to the difference of the deviation rate, and the formula accuracy is improved.
Another example is: by establishing a spray tower central control system, important parameters (powder, moisture, tower top temperature, slurry pressure and the like) of the spray tower are collected and monitored in real time, the parameter change condition of the spray tower can be fed back quickly, and quick feedback adjustment, abnormal tracing and automatic control are realized. The method comprises the following steps:
moisture on-line monitoring: install the moisture tester on spray tower powder conveyor belt to two transmission band drop positions in front of the moisture tester install small-size agitating unit, stir the homogenization to the powder, guarantee powder moisture real-time detection's accuracy.
Collecting key parameters of a spray tower: the existing parameters of the central control system are established by monitoring various important parameters of the spray tower: the temperature of the hot blast furnace, the temperature of the top of the spray tower, the temperature in the spray tower, the pressure in the spray tower and the exhaust temperature.
Quality control class parameters: slurry pressure acquisition (powder particle size), Roots blower wind pressure, frequency (pulverized coal diffusion), delivery pump frequency, current (pulverized coal addition), and compressed air pressure (pulverized coal diffusion).
Energy efficiency optimization type parameters: a pulverized coal weighing system, slurry flow, combustion supporting and exhaust flow.
The main equipment of the forming workshop comprises a press, a drying kiln, a glaze line, a kiln, a polishing line and a packing line;
the equipment data acquisition unit arranged corresponding to the press is used for acquiring the press production batch progress information and the press production data; for example, parameters of press equipment are acquired through a butt press system data, and powder detection data of a press machine are input through a powder center control machine in a raw material workshop to read powder data.
And the equipment data acquisition unit arranged corresponding to the drying kiln is used for acquiring the production data of the drying kiln.
The equipment data acquisition unit arranged corresponding to the glaze line is used for acquiring the production data of the glaze line;
the equipment data acquisition unit corresponding to the kiln is used for acquiring fired product batch information and kiln production data; for example, the kiln parameters are collected in real time by butting a kiln control system with an external monitoring instrument of a fan.
The equipment data acquisition unit which is arranged corresponding to the polishing line is used for acquiring polishing product batch information and polishing line production data;
and the equipment data acquisition unit corresponding to the packing line is used for acquiring the production data of the packing line.
It can be seen that, according to the cloud data processing control method for ceramic production provided by the embodiment of the present invention, a basic recommended production process parameter of each main device can be obtained by calculating based on production data and environmental data of each main device in a raw material workshop and a forming workshop of a ceramic production line, and a production operation state of each main device can be predicted by combining variation trends of data obtained according to different historical times, so as to obtain a predicted adjustment production process parameter of each main device, further obtain a final recommended production process parameter, and control a production operation parameter of each corresponding main device according to the final recommended production process parameter, so that the production operation state of each main device can be controlled in advance, problems occurring in the state of each main device can be avoided, then corresponding early warning processing can be performed, and an upcoming production operation state of each main device can be processed in advance, the quality of the output semi-finished products/finished products is prevented from being influenced by the occurrence of conditions of each main device, so that the production quality of the semi-finished products/finished products is improved.
Referring to fig. 4, an embodiment of the present invention provides a ceramic production cloud data processing control method, which is applicable to the ceramic production cloud data processing system shown in fig. 1, where the basic device module includes main devices disposed in a raw material shop and a forming shop of a ceramic production line, and each of the main devices has a data function; the control module comprises a device controller for controlling the production operation parameters of each main device; the ceramic production cloud data processing control system further comprises an image acquisition module, wherein the image acquisition module comprises a camera device arranged at the semi-finished product/finished product outlet position of each piece of main equipment; the ceramic production cloud data processing control method provided in this embodiment is based on the ceramic production cloud data processing control method shown in fig. 3, and further includes the steps of:
s5, acquiring a real-time image of each semi-finished product/finished product through each camera device and sending the real-time image to a cloud server through the data transmission module;
s6, the cloud server compares the semi-finished product/finished product real-time image acquired by each camera device with the corresponding semi-finished product/finished product sample image in the current acquisition period to find out the semi-finished product/finished product which does not reach the standard, so as to determine the number and error rate of the semi-finished product/finished product which does not reach the standard in the current acquisition period;
s7, the cloud server calculates the next acquisition cycle of each equipment data acquisition unit and each environmental data acquisition unit according to the error rate and the following formula, and feeds back the next acquisition cycle to each equipment data acquisition unit and each environmental data acquisition unit to acquire data according to the next acquisition cycle:
the cocyclt (i +1) represents an i +1 th collection period, tbase represents a preset basic time length, signt (i) represents a symbol judgment function, and macocylt represents a maximum value of the collection period, wherein:
c represents a preset constant parameter, recdtq (i) represents the number of semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, dterr (i) represents the error rate of the semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, and ythr represents a preset acquisition cycle judgment threshold; dterr (i) = k × err (i)/recdtq (i), where k is a preset coefficient, and err (i) represents the number of substandard semi-finished products/finished products obtained after passing through the corresponding main equipment in the time period in which the ith collection cycle is effective.
It can be seen that each of the device data collector and the environmental data collector provided in this embodiment adopts a self-adaptive collection period, where the collection period is a time interval between the current time and the previous time when data is collected. The invention adopts a self-adaptive acquisition cycle, the possibility of abnormality occurrence of each main device is judged by the value of the sign (i), the larger the value of the sign (i), the smaller the possibility of abnormality occurrence of the main device is, therefore, when the value of the sign (i +1) < macocylt, the larger the cocyclt (i +1) is, wherein the calculation of the symbol judgment function is calculated according to the number of semi-finished products/finished products and the error rate of the semi-finished products/finished products obtained after the corresponding main device passes through the acquisition cycle, the larger the number change of the semi-finished products/finished products in two adjacent time periods is, the faster the error rate of the semi-finished products/finished products is increased, the higher the possibility of abnormality occurrence of the main device is shown, and therefore, when:
the value of sign (i) can make the next acquisition period self-adaptively shorten, conversely, make the acquisition period self-adaptively enlarge, until not satisfying the time that the clock (i +1) < clock, set the acquisition period as clock. The setting mode of the embodiment of the invention can acquire the production data of the main equipment with a larger acquisition period as much as possible when the number of semi-finished products/finished products and the error rate of the semi-finished products/finished products are normal, and then, as the number of the semi-finished products/finished products and the error rate of the semi-finished products/finished products become larger, the acquisition period is shortened, so that the production abnormity of the main equipment is ensured to be found in time.
The time period during which the collection cycle takes effect refers to the duration of the collection cycle, for example, the times when the 1 st production data and the last production data acquired by the member node in the ith collection cycle are respectively t1 and t2, and the time period during which the ith collection cycle takes effect is [ t1, t2 ].
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. The utility model provides a ceramic manufacture cloud data processing control system which characterized in that, includes basic equipment module, data acquisition module, data transmission module, cloud ware and control module:
the basic equipment module comprises main equipment arranged in a raw material workshop and a forming workshop of the ceramic production line, and each main equipment has a data function;
the data acquisition module comprises an equipment data acquisition unit and an environment data acquisition unit, the equipment data acquisition unit is used for acquiring the production data of each main equipment, and the environment data acquisition unit is used for acquiring the environment data of the raw material workshop and the forming workshop;
the data transmission module is used for transmitting the production data acquired by the equipment data acquisition unit and the environmental data acquired by the environmental data acquisition unit to a cloud server;
the cloud server is used for processing and analyzing the data uploaded by the data transmission module, and comprises:
obtaining basic recommended production process parameters of each main device according to the production data and the environmental data;
respectively comparing the production data and the environmental data acquired at the current moment with the production data and the environmental data acquired at the previous moment to obtain difference data, and predicting the production running state of each main device according to the variation trend of the difference data obtained at different historical moments so as to obtain the predicted adjustment production process parameters of each main device;
combining the basic recommended production process parameters and the predicted adjustment production process parameters to obtain final recommended production process parameters of each main device;
the control module comprises a device controller for controlling the production operation parameters of each main device, the final recommended production process parameters are fed back to each corresponding device controller through the data transmission module, and each device controller controls the production operation parameters of the corresponding main device according to the corresponding final recommended production process parameters.
2. The cloud data processing control system for ceramic production according to claim 1, wherein an adaptive acquisition cycle is adopted for each of the device data acquisition unit and the environmental data acquisition unit, and the acquisition cycle is a time interval between the current time and the previous time for acquiring data; the acquisition period is determined by:
the cocyclt (i +1) represents an i +1 th collection period, tbase represents a preset basic time length, signt (i) represents a symbol judgment function, and macocylt represents a maximum value of the collection period, wherein:
c represents a preset constant parameter, recdtq (i) represents the number of semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, dterr (i) represents the error rate of the semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, and ythr represents a preset acquisition cycle judgment threshold; dterr (i) = k × err (i)/recdtq (i), where k is a preset coefficient, and err (i) represents the number of substandard semi-finished products/finished products obtained after passing through the corresponding main equipment in the time period in which the ith collection cycle is effective.
3. The cloud data processing control system for ceramic production according to claim 2, further comprising an image acquisition module, wherein the image acquisition module includes a camera device disposed at an outlet of each semi-finished product/finished product of the main equipment, and each camera device is configured to acquire a real-time image of each semi-finished product/finished product and send the real-time image to a cloud server through the data transmission module;
the cloud server is further configured to:
in the current acquisition period, comparing the semi-finished product/finished product real-time image acquired by each camera device with the corresponding semi-finished product/finished product sample image to find out the semi-finished product/finished product which does not reach the standard, so as to determine the number and error rate of the semi-finished product/finished product which does not reach the standard in the current acquisition period;
and calculating the next acquisition cycle of each equipment data acquisition unit and each environmental data acquisition unit according to the error rate and the formula, and feeding back the next acquisition cycle to each equipment data acquisition unit and each environmental data acquisition unit to acquire data according to the next acquisition cycle.
4. The ceramic production cloud data processing control system of claim 2, wherein the primary equipment of the raw material plant comprises a continuous ball and a spray tower;
the equipment data collector corresponding to the continuous ball is used for collecting production data of a rolling crushing system, production data of a batching system, production data of a stirring system and production data of a continuous ball milling system;
and the equipment data acquisition unit arranged corresponding to the spraying tower is used for spraying tower production data and powder bin production data.
5. The cloud data processing control system for ceramic production according to claim 2, wherein the main equipment of the forming workshop comprises a press, a drying kiln, a glaze line, a kiln, a polishing line and a packing line;
the equipment data acquisition unit arranged corresponding to the press is used for acquiring the press production batch progress information and the press production data;
the equipment data collector corresponding to the drying kiln is used for collecting the production data of the drying kiln;
the equipment data acquisition unit arranged corresponding to the glaze line is used for acquiring the production data of the glaze line;
the equipment data acquisition unit corresponding to the kiln is used for acquiring fired product batch information and kiln production data;
the equipment data acquisition unit which is arranged corresponding to the polishing line is used for acquiring polishing product batch information and polishing line production data;
and the equipment data acquisition unit corresponding to the packing line is used for acquiring the production data of the packing line.
6. The ceramic production cloud data processing control method is characterized by being applicable to a ceramic production cloud data processing system comprising a basic equipment module, a data acquisition module, a data transmission module, a cloud server and a control module, wherein the basic equipment module comprises main equipment arranged in a raw material workshop and a forming workshop of a ceramic production line, and each main equipment has a data function; the control module comprises a device controller for controlling the production operation parameters of each main device; the method comprises the following steps:
s1, collecting production data of each main device through a device data collector of the data collection module and collecting environmental data of the raw material workshop and the forming workshop through an environmental data collector;
s2, transmitting the production data collected by the equipment data collector and the environmental data collected by the environmental data collector to a cloud server;
s3, the cloud server is used for processing and analyzing the data uploaded by the data transmission module, and the method comprises the following steps:
s31, obtaining basic recommended production process parameters of each main device according to the production data and the environmental data;
s32, respectively comparing the production data and the environmental data acquired at the current moment with the production data and the environmental data acquired at the previous moment to obtain difference data, and predicting the production running state of each main device according to the variation trend of the difference data acquired at different historical moments so as to obtain the predicted adjustment production process parameters of each main device;
s33, combining the basic recommended production process parameters and the predicted adjustment production process parameters to obtain the final recommended production process parameters of each main device;
and S4, feeding back the final recommended production process parameters to each corresponding equipment controller through the data transmission module, so that each equipment controller controls the production operation parameters of the corresponding main equipment according to the corresponding final recommended production process parameters.
7. The cloud data processing control method for ceramic production according to claim 6, wherein each of the device data collector and the environmental data collector adopts an adaptive collection period, and the collection period is a time interval between the current time and the previous time for collecting data; the acquisition period is determined by:
the cocyclt (i +1) represents an i +1 th collection period, tbase represents a preset basic time length, signt (i) represents a symbol judgment function, and macocylt represents a maximum value of the collection period, wherein:
c represents a preset constant parameter, recdtq (i) represents the number of semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, dterr (i) represents the error rate of the semi-finished products/finished products obtained after passing through corresponding main equipment in the time period in which the ith acquisition cycle takes effect, and ythr represents a preset acquisition cycle judgment threshold; dterr (i) = k × err (i)/recdtq (i), where k is a preset coefficient, and err (i) represents the number of substandard semi-finished products/finished products obtained after passing through the corresponding main equipment in the time period in which the ith collection cycle is effective.
8. The ceramic production cloud data processing control method of claim 7, wherein the ceramic production cloud data processing control further comprises an image acquisition module, the image acquisition module comprising a camera device provided at a semi-finished product/finished product outlet position of each of the main devices; the method further comprises the following steps:
acquiring a real-time image of each semi-finished product/finished product through each camera device and sending the real-time image to a cloud server through the data transmission module;
the cloud server compares the semi-finished product/finished product real-time image acquired by each camera device with the corresponding semi-finished product/finished product sample image in the current acquisition period to find out the semi-finished product/finished product which does not reach the standard, so that the number and the error rate of the semi-finished product/finished product which does not reach the standard in the current acquisition period are determined;
and the cloud server calculates the next acquisition period of each equipment data acquisition device and each environmental data acquisition device according to the error rate and the formula, and feeds back the next acquisition period to each equipment data acquisition device and each environmental data acquisition device so as to acquire data according to the next acquisition period.
9. The ceramic production cloud data processing control method of claim 7, wherein the main equipment of the raw material plant comprises a continuous ball and a spray tower;
the equipment data collector corresponding to the continuous ball is used for collecting production data of a rolling crushing system, production data of a batching system, production data of a stirring system and production data of a continuous ball milling system;
and the equipment data acquisition unit arranged corresponding to the spraying tower is used for spraying tower production data and powder bin production data.
10. The cloud data processing control method for ceramic production according to claim 7, wherein the main equipment of the forming workshop comprises a press, a drying kiln, a glaze line, a kiln, a polishing line and a packing line;
the equipment data acquisition unit corresponding to the press is used for acquiring the press production batch progress information and the press production data;
the equipment data collector corresponding to the drying kiln is used for collecting the production data of the drying kiln;
the equipment data acquisition unit arranged corresponding to the glaze line is used for acquiring the production data of the glaze line;
the equipment data acquisition unit corresponding to the kiln is used for acquiring fired product batch information and kiln production data;
the equipment data acquisition unit which is arranged corresponding to the polishing line is used for acquiring polishing product batch information and polishing line production data;
and the equipment data acquisition unit corresponding to the packing line is used for acquiring the production data of the packing line.
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