CN118519409B - A data collaborative processing method and system - Google Patents
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Abstract
本发明公开了一种数据协同处理方法及系统，涉及数据协同处理技术领域，解决了现有技术中，无法在工业加工区域进行信息融合控制，以至于无法执行数据协同处理的技术问题，具体为数据协同层生成信息融合控制信号并发送至信息融合控制单元，信息融合控制单元对工业加工区域进行信息融合控制，将工业加工区域内各个数据产端所在位置进行数据采集并将各个数据产端根据运行流程进行数据链连接，构建区域数据网络，将生产数据设置o个子数据类型，在工业加工工件进行加工处理时，以多个传感器对区域数据网络内任一数据产端进行数据采集分析，并以单个传感器数据产端所在区域数据网络进行数据采集分析。
The present invention discloses a data collaborative processing method and system, relates to the technical field of data collaborative processing, and solves the technical problem in the prior art that information fusion control cannot be performed in an industrial processing area, so that data collaborative processing cannot be performed. Specifically, a data collaborative layer generates an information fusion control signal and sends it to an information fusion control unit, the information fusion control unit performs information fusion control on the industrial processing area, collects data at the location of each data production end in the industrial processing area, and connects each data production end through a data link according to an operation process to build a regional data network, sets o sub-data types for production data, and when an industrial processing workpiece is processed, uses multiple sensors to collect and analyze data on any data production end in the regional data network, and uses a single sensor data production end to collect and analyze data in the regional data network.
Description
Technical Field
The invention relates to the technical field of data cooperative processing, in particular to a data cooperative processing method and a data cooperative processing system.
Background
The industrial big data takes the product data as the core, greatly expands the traditional industrial data range, and simultaneously comprises the related technology and application of the industrial big data.
However, in the prior art, information fusion control cannot be performed in an industrial processing area, so that data collaborative processing cannot be performed, processing risk monitoring accuracy cannot be reduced while processing detection efficiency cannot be guaranteed, in addition, data storage and sharing analysis control cannot be performed on industrial production, monitoring strength of industrial processing is reduced, and data tracing or data checking cannot be performed when processing is abnormal.
In view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The present invention is directed to a data collaborative processing method and system for solving the above-mentioned problems.
The aim of the invention can be achieved by the following technical scheme:
A data cooperative processing system comprises a data management layer and a data cooperative layer,
The data collaborative layer generates an information fusion control signal and sends the information fusion control signal to the information fusion control unit, the information fusion control unit performs information fusion control on an industrial processing area, performs data acquisition on the position of each data generating end in the industrial processing area, performs data chain connection on each data generating end according to an operation flow, builds an area data network, sets production data into o sub-data types, performs data acquisition and analysis on any data generating end in the area data network through a plurality of sensors when an industrial processing workpiece is processed, and performs data acquisition and analysis on the area data network where a single sensor data generating end is located.
As a preferred embodiment of the present invention, the process of performing data collection and analysis on any data source in the regional data network by using a plurality of sensors is as follows:
The method comprises the steps of obtaining time registration information and time delay information, wherein the time registration information and the time delay information are respectively the maximum floating deviation value of the numerical value of the sub-data type corresponding to the same overlapping acquisition time of a plurality of sensors of data production end production data and the numerical value of Ren Yitong time period, and the continuous extension span value of the updating deviation time length of each sub-data type numerical value after the sub-data type numerical value acquisition is carried out by taking the same overlapping acquisition time of the plurality of sensors as a starting point.
As a preferred embodiment of the present invention, if the time registration information exceeds a value maximum floating deviation value threshold, or the time delay information exceeds an update deviation duration continuously extending span value threshold, generating a simultaneously stored high risk signal and transmitting the simultaneously stored high risk signal to the data cooperative layer;
If the time registration information does not exceed the numerical maximum floating deviation value threshold and the time delay information does not exceed the updating deviation duration continuously prolonged span value threshold, generating a simultaneous storage low risk signal and sending the simultaneous storage low risk signal to the data cooperative layer.
As a preferred embodiment of the invention, after the data coordination layer receives the high risk signal stored at the same time, the data production end performs data acquisition pretreatment, the data production end performs acquisition cycle setting according to the floating cycle of the acquired production data corresponding to each sensor type, the production data corresponding to each sub-data type is counted and the acquisition time is recorded, meanwhile, the detection time is set in all the acquisition time, namely, the detection time is represented as the time when each sub-data type is transmitted to the data management layer is consistent, no sub-data type has numerical value floating in the detection period of the data management coordination layer, and the detection time is set to ensure that the data production end can acquire all data at a certain time and the acquired data transmission time is consistent when a plurality of sensors detect.
As a preferred implementation mode of the invention, the data acquisition and analysis process is carried out by using the regional data network where the data generating end of a single sensor is positioned, and the data acquisition and analysis process is as follows:
According to the probability that the current processing of the data generating end needs to be reworked due to the fact that the corresponding numerical value of the acquired sub-data type is floating beyond a set threshold in the sub-data type of the production data of the data generating end, if the corresponding probability exceeds the reworking probability threshold, the acquired sensor of the corresponding sub-data type is set as a representative sensor, otherwise, the acquired sensor of the corresponding sub-data type is set as a non-representative sensor; the overlapping time periods of the single representative sensor monitoring process, in which the floating trend of the corresponding monitoring sub-data types of any two data generating ends is consistent, are obtained, if the overlapping time periods of the single representative sensor monitoring process, in which the floating trend of the corresponding monitoring sub-data types of any two data generating ends is consistent, are lower than an overlapping time period threshold value, the corresponding sub-data types of any two data generating ends are not affected, otherwise, if the overlapping time periods of the single representative sensor monitoring process, in which the floating trend of the corresponding monitoring sub-data types of any two data generating ends is consistent, are higher than the overlapping time period threshold value, the corresponding sub-data types of any two data generating ends are affected.
As a preferred embodiment of the invention, the formation control data and the formation release data are obtained, and the formation control data and the formation release data are respectively the buffer period reduction speed of the same trend floating of the data value of the other data production terminal type after the data value of the subtype data of any one of any two data production terminals with influence floats, and the duration reduction span of the same trend floating of any two data production terminals after the control of the data of any two data production terminal type when any two data production terminals with influence float with the same trend.
As a preferred embodiment of the invention, if the formation control data exceeds the buffer period reduction speed threshold and the formation release data exceeds the duration reduction span threshold, generating a data cooperative regulation qualified signal; if the formation control data does not exceed the buffer period reduction speed threshold or the formation release data does not exceed the duration reduction span threshold, generating a data cooperative regulation disqualification signal.
As a preferred embodiment of the present invention, the data management layer generates a data storage analysis signal and sends the data storage analysis signal to the data storage analysis unit, the data storage analysis unit performs data storage analysis on industrial production, running equipment in an industrial processing area is uniformly marked as a data producing end, the produced data of each data producing end is uniformly stored, and the storage area is marked as a data storage end; and acquiring single operation data and matched operation data, generating a data storage low-efficiency signal or a data storage high-efficiency signal according to data analysis, and transmitting the data storage low-efficiency signal to a data management layer.
As a preferred embodiment of the present invention, a data management layer generates a data sharing analysis signal and sends the signal to a data sharing analysis unit, the data sharing analysis unit performs data sharing analysis on a data storage terminal, collects data prediction information, substitutes the data prediction information into a formula to obtain a prediction analysis coefficient of production data corresponding to a data production terminal in the data storage terminal, and generates a low sharing signal and sends the low sharing signal to the data management layer if the prediction analysis coefficient exceeds a prediction analysis coefficient threshold; if the predictive analysis coefficient does not exceed the predictive analysis coefficient threshold, a high-sharing signal is generated and sent to the data management layer.
As a preferred embodiment of the invention, a data cooperative processing method comprises the following specific processing steps:
S1, information fusion control is carried out on an industrial processing area;
step S11: a plurality of sensors are used for carrying out data acquisition and analysis on any data generating end in the regional data network;
Step S12: carrying out data acquisition and analysis by using a regional data network where a single sensor data generating end is positioned;
Step S2: data storage analysis, which is to perform data storage analysis on industrial production;
step S3: and carrying out data sharing analysis on the data storage end.
Compared with the prior art, the invention has the beneficial effects that:
1. According to the invention, data storage analysis is carried out on industrial production, and whether real-time data storage is qualified is judged by carrying out analysis according to the storage of real-time production data of the industrial production, so that the data cooperative processing in the industrial processing process can be reasonably executed, meanwhile, the data storage in the industrial processing process can be ensured to be effective, the data detection accuracy of the industrial processing is improved, and the comprehensiveness of data tracing can be ensured; the data sharing analysis is carried out on the data storage end, the type analysis is carried out according to the storage data of the data production end, the sharing data division is carried out through the type analysis, the data sharing efficiency of the data production end is improved, and meanwhile, different storage periods can be set according to the sharing data division, so that the storage efficiency of the data storage end is guaranteed, and the storage pressure is relieved.
2. According to the invention, the information fusion control is carried out on the industrial processing area, the information fusion control analysis is carried out on the industrial processing area through the data collaborative acquisition analysis, the operation efficiency of the industrial processing area is evaluated while the production feasibility of the industrial processing area is detected, and the data regulation and control can be accurately and intuitively carried out according to the visual monitoring of the data of each position.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
FIG. 1 is a schematic block diagram of the present invention;
FIG. 2 is a schematic block diagram of a first embodiment of the present invention;
FIG. 3 is a schematic block diagram of a second embodiment of the present invention;
Fig. 4 is a flow chart of the method of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, 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.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
Referring to fig. 1, a data cooperative processing system includes a data management layer and a data cooperative layer, in the operation process of industrial construction, the data management layer and the data cooperative layer are used for carrying out data acquisition and analysis on an industrial processing area, and judging the operation efficiency of the industrial processing area according to real-time data acquisition and analysis, and judging the potential risk of the industrial processing area according to data analysis, so that the overall operation efficiency of the industrial processing area is improved, and the timeliness of operation control on the industrial processing area is ensured;
Example 1
Referring to fig. 2, the data management layer is used as a management medium for data storage, performs real-time data acquisition and storage on the operation of the industrial processing area, and performs data management and control on the industrial processing through storage data management, so that data tracing is facilitated to improve the management efficiency of industrial production;
The data management layer generates a data storage analysis signal and sends the data storage analysis signal to the data storage analysis unit, the data storage analysis unit performs data storage analysis on industrial production after receiving the data storage analysis signal, and analyzes and judges whether real-time data storage is qualified according to the storage of real-time generated data of the industrial production, so that the data cooperative processing in the industrial processing process can be reasonably executed, the data storage in the industrial processing process can be effectively ensured, the data detection accuracy of the industrial processing is improved, and the comprehensiveness of data tracing can be ensured;
The operation equipment in the industrial processing area is uniformly marked as a data generating end, the reference numbers i and i are natural numbers larger than 1, and data generated by the corresponding operation equipment are collected and stored in the operation process of the industrial processing area, wherein the data generated by the operation equipment are expressed as operation data of the operation equipment, such as parameters of carrying capacity of a carrier, conveying speed floating quantity of a conveying belt and the like; uniformly storing the generated data of each data generating end and marking the storage area as a data storage end;
Acquiring the overlapping time length of a data storage effective period and a data updating average period in a single operation of the same data generating end in the data storage end, simultaneously acquiring the corresponding shortening speed of the overlapping time length of the data storage updating period in the cooperative operation of the adjacent data generating ends in the data storage end, and respectively marking the corresponding shortening speed of the overlapping time length of the data storage effective period and the data updating average period in the single operation of the same data generating end in the data storage end and the overlapping time length of the data storage updating period in the cooperative operation of the adjacent data generating ends in the data storage end as single operation data and cooperative operation data, and comparing a period overlapping time length threshold value and an overlapping time length shortening speed threshold value respectively: the data updating average period is represented as an average period of real-time updating of production data of the data generating end, and the data storage updating period is represented as an updated data storage period of the corresponding data generating end in the data storage end;
If the overlapping time length of the data storage effective period and the data updating average period in the same data generating end in the data storage end does not exceed the period overlapping time length threshold value, or the corresponding shortening speed of the overlapping time length of the data storage updating period in the data storage end when the adjacent data generating end operates cooperatively exceeds the overlapping time length shortening speed threshold value, judging that the data storage analysis of the data generating end in the data storage end is low-efficiency, generating a data storage low-efficiency signal and sending the data storage low-efficiency signal to a data management layer, and after the data management layer receives the data storage low-efficiency signal, monitoring the data production period of the data generating end in real time and regulating and controlling the stored data updating in real time;
If the overlapping time length of the data storage effective period and the data updating average period in the same data generating end in the data storage end during single operation exceeds a period overlapping time length threshold value, and the corresponding shortening speed of the overlapping time length of the data storage updating period in the data storage end during the cooperative operation of the adjacent data generating ends does not exceed the overlapping time length shortening speed threshold value, judging that the data storage analysis of the data generating end in the data storage end is efficient, generating a data storage efficient signal and transmitting the data storage efficient signal to a data management layer;
After receiving the data storage high-efficiency signal, the data management layer generates a data sharing analysis signal and sends the data sharing analysis signal to the data sharing analysis unit, and after receiving the data sharing analysis signal, the data sharing analysis unit performs data sharing analysis on the data storage end, performs type analysis according to the stored data of the data production end, performs sharing data division through the type analysis, improves the data sharing efficiency of the data production end, and can set different storage periods according to the sharing data division so as to ensure the storage efficiency of the data storage end and relieve the storage pressure;
acquiring a reciprocating floating span value corresponding to a numerical floating period of production data in a historical period of a data production end in a data storage end and a numerical floating period of a current period, acquiring a ratio of the number of floating same trend moments to the number of total moments when the numerical floating trends of the same processing progress ratio corresponding to the production data production values of the same type of data production ends in the storage end are consistent, and marking the ratio of the number of floating same trend moments to the number of total moments as WFK and SKB when the numerical floating trends of the production data in the historical period of the data production ends in the data storage end and the numerical floating period corresponding to the current period are consistent, wherein the ratio of the number of floating same trend moments to the number of total moments when the numerical floating trends of the same processing progress ratio corresponding to the production data production values of the same type of data production ends in the storage end are consistent;
obtaining a maximum value floating frequency difference corresponding to a deviation value of a current production data set quantity and an actual completion quantity, corresponding to a production data historical value of a data production end in a data storage end, and marking the maximum value floating frequency difference corresponding to the deviation value of the current production data set quantity and the actual completion quantity, corresponding to the production data historical value of the data production end in the data storage end, as a PLC;
Uniformly marking the data as data prediction information, and substituting the data prediction information into a formula to obtain a prediction analysis coefficient YC of the data production end corresponding to the production data in the data storage end, wherein the formula is as follows:
Fy1, fy2 and fy3 are respectively preset proportionality coefficients of the reciprocating floating span value corresponding to the numerical value floating period, the ratio of the same trend time quantity to the total time quantity and the maximum numerical value floating frequency difference corresponding to the deviation value, and beta is taken as an error correction factor, and the value is 1.23;
Comparing a prediction analysis coefficient YC of the corresponding production data of the data production end in the data storage end with a prediction analysis coefficient threshold value:
If the predictive analysis coefficient of the production data corresponding to the data producer in the data storage terminal exceeds the predictive analysis coefficient threshold, judging that the production data of the data producer is low in predictability, generating a low-sharing signal and sending the low-sharing signal to a data management layer, setting effective storage duration according to the floating period of the production data of the data producer corresponding to the low-sharing signal after the data management layer receives the low-sharing signal, setting a period threshold to be cleaned after the effective storage duration is finished, and cleaning the data if no data is queried in the period threshold to be cleaned;
If the predictive analysis coefficient of the production data corresponding to the data producer in the data storage terminal does not exceed the predictive analysis coefficient threshold, judging that the production data of the data producer is high in predictability, generating a high-sharing signal and sending the high-sharing signal to the data management layer, setting effective storage time length according to the predictive influence period of the production data of the data producer corresponding to the high-sharing signal after the data management layer receives the high-sharing signal, wherein the predictive influence period is represented as a period which has the same trend probability as the floating trend of the production data corresponding to the data producer and can be deduced according to the floating trend of the current production data and can be used for trend deduction according to the numerical value, setting a compressed storage period after the effective storage time length is finished, storing the production data stored in the compressed storage period after compression for data retroactive access, setting a period threshold to be cleaned after the compressed storage period is finished, and cleaning the data without data inquiry in the period threshold to be cleaned;
Example two
Referring to fig. 3, the data collaboration layer is configured to perform data analysis, data transmission, etc. on data stored in the data management layer, so as to determine feasibility of industrial processing by data collaboration processing, and perform processing tracing and inspection according to timeliness of the data;
The data collaborative layer generates an information fusion control signal and sends the information fusion control signal to the information fusion control unit, the information fusion control unit performs information fusion control on the industrial processing area after receiving the information fusion control signal, performs information fusion control analysis on the industrial processing area through data collaborative acquisition analysis, performs production feasibility detection on the industrial processing area, performs operation efficiency evaluation on the industrial processing area, and performs data regulation and control accurately and intuitively according to the data visual monitoring of each position;
When the industrial processing area is operated, the maximum floating deviation value of the numerical value of each sub data type corresponding to the same overlapping acquisition time of a plurality of sensors of the data production end and the numerical value of the time of Ren Yitong period is acquired, the continuous extension span value of the update deviation time is stored after the numerical value of each sub data type is acquired, the continuous extension span value of the update deviation time is compared with the continuous extension span value of the maximum floating deviation value of the update deviation time after the numerical value of each sub data type is acquired, the maximum floating deviation value of the numerical value of the sub data type corresponding to the same overlapping acquisition time of the plurality of sensors of the data production end and the numerical value of Ren Yitong period is acquired, the same overlapping acquisition time of the plurality of sensors is the starting point, and the continuous extension span value of the update deviation is compared with the continuous extension span value of the update deviation time of the threshold value after the numerical value of each sub data type is acquired:
If the numerical value of the sub data type corresponding to the same overlapping acquisition time of a plurality of sensors of the data production end and the numerical value of the time period of Ren Yitong exceed the numerical value maximum floating deviation value threshold, or the continuous extension span value of the update deviation time length of the numerical value storage of each sub data type after the numerical value acquisition of the sub data type is carried out by taking the same overlapping acquisition time of the plurality of sensors as the starting point, the continuous extension span value of the update deviation time length is continuously extended, the plurality of sensors are judged to have risks for acquiring data at the same time of the same data production end, a high risk signal is generated and stored at the same time and is sent to a data collaborative layer, after the data collaborative layer receives the high risk signal stored at the same time, the data production end carries out data acquisition preprocessing, the data production end carries out statistics and records acquisition time according to the floating period of the acquired production data corresponding to each sensor type, and the detection time is set in all the acquisition time, namely the detection time is indicated as the time of each sub data type to be consistent with the time of the data management layer, and no detection time of any sub data type is detected in the detection time period of the data management layer, the detection time is consistent, the data can be transmitted to the data management layer, the time consumption performance of the data can be guaranteed to be synchronously when the data can be synchronously acquired, and the data can be synchronously transmitted, and the performance of the data can be guaranteed is guaranteed;
If the numerical value of the corresponding sub-data type at the same overlapping acquisition time of a plurality of sensors of the data production end and the numerical value of the time period of Ren Yitong are not greater than the numerical value maximum floating deviation value threshold, and the continuous extension span value of the update deviation duration of the numerical value storage of each sub-data type after the numerical value acquisition of the sub-data type is carried out by taking the same overlapping acquisition time of the plurality of sensors as the starting point, the continuous extension span value of the update deviation duration is not greater than the continuous extension span value threshold of the update deviation duration, the plurality of sensors are judged to have no risk on the acquired data at the same time of the same data production end, a low risk signal is generated, the low risk signal is stored at the same time, the low risk signal is transmitted to a data cooperation layer, the data cooperation layer carries out data acquisition analysis by using the area data network of the single sensor data production end after receiving the low risk signal at the same time, and the current processing of the data production end is required to be reworked by the acquired sub-data type corresponding to the numerical value of the acquired sub-data type exceeding the set threshold value, if the corresponding probability exceeds the reworked probability threshold, the acquired sensor of the corresponding sub-data type is set as the representative sensor, otherwise, and the sensor corresponding sub-data type is set to be the non-representative sensor;
When each data generating end of the regional data network operates cooperatively, data analysis is carried out on the monitoring sub-data types of the representative sensors of each data generating end, an overlapping period with consistent floating trend of the monitoring sub-data types corresponding to any two data generating ends in the single representative sensor monitoring process is obtained, if the overlapping period with consistent floating trend of the monitoring sub-data types corresponding to any two data generating ends in the single representative sensor monitoring process is lower than an overlapping period threshold value, the corresponding sub data types of the corresponding arbitrary two data generating ends are not affected, otherwise, if the overlapping time period of the floating trend coincidence of the corresponding monitoring sub data types of the arbitrary two data generating ends in the single representative sensor monitoring process is higher than the overlapping time period threshold value, the corresponding sub data types of the corresponding arbitrary two data generating ends are affected;
The method comprises the steps of obtaining the buffer period reduction speed of the same trend floating of the data value of the other data production terminal type after the sub-type data value of any one of the affected any two data production terminals floats, and the duration reduction span of the same trend floating of any one of the two data production terminal type data after the affected any two data production terminals float, and respectively marking the buffer period reduction speed of the same trend floating of the data value of the other data production terminal type after the sub-type data value of any one of the affected any two data production terminals floats, the duration reduction span of the same trend floating of any one of the two data production terminal type data after the affected any two data production terminals float as forming control data and forming release data, and comparing the control data and the release data with a buffer period reduction speed threshold and a duration reduction span threshold respectively: in the technical scheme of the part, the scene of the same trend floating is expressed as that the data floating of the data generating end exceeds a set threshold value, the abnormal floating in the prior art is realized, and the data floating in the set threshold value is not counted even if the same trend floating;
If the data value of the subtype of any one of the two affected data generating ends floats and then the data value of the other data generating terminal forms a buffering period with the same trend to float, the speed of the buffering period is reduced to exceed a threshold value of the speed of the buffering period, and the duration reduction span of the same trend of the two data generating terminals after the data management of the data of any two affected data generating terminals with the same trend floats exceeds a threshold value of the duration reduction span, judging that the data collaborative analysis of the regional data network is qualified, generating a data collaborative regulation qualified signal and sending the data collaborative regulation qualified signal to a data collaborative layer;
If the data value of the subtype of any one of the two affected data producing ends floats and then the data value of the other data producing terminal forms a buffering period of the same trend floating, the speed of which is reduced does not exceed a buffering period of which is reduced, or if the duration of which is reduced and the duration of which is not longer than the duration of which is reduced after the data of any one of the two affected data producing terminals floats and is controlled by the data of the same trend, the data collaborative analysis of the regional data network is judged to be unqualified, a data collaborative regulation disqualified signal is generated and sent to a data collaborative layer, the data collaborative layer carries out operation regulation and control on the data producing end after receiving the data collaborative regulation disqualified signal, carries out data floating control on the affected data producing end, carries out floating regulation and control after the data floating of the data producing end, reduces the duration of the same trend, avoids the operation efficiency of each data producing end in the regional data network from being reduced, and the operation time of the data producing end can be regulated if necessary;
referring to fig. 4, a data cooperative processing method specifically includes the following steps:
S1, information fusion control is carried out on an industrial processing area;
step S11: a plurality of sensors are used for carrying out data acquisition and analysis on any data generating end in the regional data network;
Step S12: carrying out data acquisition and analysis by using a regional data network where a single sensor data generating end is positioned;
Step S2: data storage analysis, which is to perform data storage analysis on industrial production;
step S3: and carrying out data sharing analysis on the data storage end.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions;
When the method is used, the data cooperative layer generates an information fusion control signal and sends the information fusion control signal to the information fusion control unit, the information fusion control unit performs information fusion control on an industrial processing area, performs data acquisition on the position of each data generating end in the industrial processing area, performs data chain connection on each data generating end according to an operation flow, builds an area data network, performs data acquisition analysis on any data generating end in the area data network through a plurality of sensors when an industrial processing workpiece is processed, and performs data acquisition analysis on the area data network where a single sensor data generating end is located.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
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