CN117148794A - Monitoring method for judging timeliness and authenticity of data acquisition in cement industry - Google Patents
Monitoring method for judging timeliness and authenticity of data acquisition in cement industry Download PDFInfo
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Abstract
The invention discloses a monitoring method for judging timeliness and authenticity of data acquisition in the cement industry, which comprises the following steps: s1, selecting a plurality of measuring point data for judging whether the data state is abnormal or not; s2, constructing an industrial Internet of things platform based on the equipment object model to realize model level flow calculation; s3, establishing an object model of the virtual equipment for judging the data state, wherein the object model of the virtual equipment corresponds to the data acquisition link one by one; s4, establishing a flow calculation task in the system, wherein the parameter entering of the task is related to the parameter entering equipment and the corresponding measuring point attribute, and judging whether each data acquisition link is abnormal or not through the flow calculation task; s5, carrying out abnormal interruption alarm prompt of the corresponding data acquisition link when the abnormality occurs. The invention does not need to change the existing data acquisition mode, does not need to additionally increase equipment acquisition equipment, reduces the related measuring point data, and is simpler and more convenient.
Description
Technical Field
The invention belongs to the technical field of data monitoring, and relates to a monitoring method for judging timeliness and authenticity of data acquisition in the cement industry.
Background
At present, the production process data in the cement industry basically originate from an open data interface provided by industrial control systems such as site DCS, PLC and the like, and the acquisition protocol is mostly OPC_DA or OPC_UA. At present, most group cement enterprises acquire data in a manner that a data acquisition device is deployed in a factory to be connected with a data server for acquiring data, and the data are transmitted to an industrial Internet of things platform in real time by utilizing the Internet. And important data support is provided for headquarter application scenes such as production monitoring, equipment analysis, index statistics and the like.
However, the existing technology cannot analyze and judge timeliness and authenticity of data acquisition in real time, because data of a plurality of production lines in a plurality of areas and factories are required to be managed in a data platform of group management, related equipment, measuring points and corresponding data volumes are large, real-time monitoring is carried out on data of each measuring point, because workload is too large, real-time performance is difficult to ensure, when an abnormal interrupt occurs in the whole data acquisition link, such as abnormal data service end, abnormal network, abnormal acquisition device and the like, a headquarter application side cannot sense data abnormality in real time, so that the following influence is generated on a service:
1. after the data is abnormally interrupted, the original equipment data can keep the value unchanged at the moment before the data is interrupted. If the rotary kiln host operation signal is true before the data is interrupted, and the value perceived by the headquarter application side is still true after the data is interrupted, if the rotary kiln is abnormally stopped in a factory, the headquarter cannot perceive in real time.
2. After the data abnormality is interrupted, the original indexes are still continuously calculated, and indexes such as energy, quality, yield, library position and the like are still calculated according to the numerical value before the data abnormality, so that the indexes continuously generate errors.
3. After the data is abnormally interrupted, the headquarter cannot timely obtain feedback, and mechanisms such as real-time sensing, prompting and alarming are lacking, so that the headquarter cannot monitor the timeliness and the authenticity of the data of each factory in real time.
Accordingly, there is a need in the art for improvements in this regard to timely identifying anomalies and sources of anomalies after they occur, and to timely notify field data managers of the process to avoid or reduce factory-group data errors.
Disclosure of Invention
The invention aims to provide a monitoring method for judging timeliness and authenticity of data acquisition in the cement industry, which is used for solving the technical problems that in the prior art, large-scale real-time monitoring is difficult to be carried out on data of a plurality of production lines in a plurality of areas and factories, and therefore, abnormal real-time monitoring and alarming are difficult to be effectively carried out on a corresponding whole data acquisition link.
The monitoring method for judging the timeliness and the authenticity of the data acquisition in the cement industry comprises the following steps:
s1, selecting a plurality of measuring point data for judging whether the data state is abnormal or not;
s2, constructing an industrial Internet of things platform based on the equipment object model to realize model level flow calculation;
s3, establishing an object model of the virtual equipment for judging the data state, wherein the object model of the virtual equipment corresponds to the data acquisition link one by one;
s4, establishing a flow calculation task in the system, wherein the parameter entering of the task is related to the parameter entering equipment and the corresponding measuring point attribute, and judging whether each data acquisition link is abnormal or not through the flow calculation task;
s5, carrying out abnormal interruption alarm prompt of the corresponding data acquisition link when the abnormality occurs.
Preferably, in the step S1, the measurement points are measurement points that are all provided in the production line corresponding to each data acquisition link, and the data of the corresponding measurement points will not be set to 0 in normal production of the production line and will continuously fluctuate.
Preferably, the data collected by the method are related data of a cement kiln production line, and the data of the measuring points selected in the step S1 are specifically as follows: a. kiln bucket lifting-current, kiln main motor-current, c. high temperature fan-current, d. kiln head Roots fan-outlet pressure.
Preferably, in the step S2, the equipment object model is set based on a unified specification, and the equipment ID is specified according to the region-factory-production line, so as to determine the position of the data of the stream calculation input parameters and the stream calculation output parameters; the equipment object model of the same production line forms a complete data acquisition link, the equipment object model comprises a parameter entering device and a measuring point corresponding to the measuring point data, if the related measuring point data meet the abnormal judgment standard, the attribute of the related measuring point is abnormal, otherwise, the attribute of the related measuring point is normal.
Preferably, in the step S3, in each complete data acquisition link, the measurement point state of the measurement point data determined in the step S1 is used as an input parameter to be associated with the object model of the corresponding virtual device, and the corresponding state attribute indicates whether the data acquisition link is abnormal; when the measuring point states of the measuring point data are abnormal, the state attribute of the virtual equipment is abnormal, and the corresponding whole data acquisition link is abnormal; when the measuring point states of the four measuring point data are not abnormal, the state attribute of the virtual equipment is normal, which means that the corresponding whole data acquisition link is normal.
Preferably, in the step S4, the stream calculation task includes: the monitoring result of each measuring point data is related to the object model of the virtual equipment corresponding to the data acquisition link of the virtual equipment, when the object model of the same virtual equipment is not changed for a plurality of continuous times, the abnormal interruption of the data acquisition link of the production line is judged, and the output parameter is returned to the object model of the virtual equipment; when the data is normal, the parameter is always returned to the object model.
Preferably, the stream calculation automatically identifies the line location based on the device ID base field of the incoming request
Preferably, the alarm module used in the step S5 includes an online statistics large screen, and after an abnormality interrupt occurs in a certain production line, a popup window can occur in the online statistics large screen of data corresponding to the abnormality, including information of factory-production line description and offline time; the factory-production line is determined according to the equipment ID basic field, the alarm prompt information is stored in a system, and the system can call the information of the abnormal production line in real time according to the requirement after alarming.
Preferably, the alert module used in step S5 includes an alert pushing module, configured to configure a responsive pushing person, where the pushing person corresponds to an abnormality of a corresponding data acquisition link, and the alert pushing module can push alert information by using any one or two or more of a sms, an enterprise group, an APP, and a phone group call.
The invention has the following advantages:
1. the scheme utilizes the existing data acquisition link, does not need to change the existing data acquisition mode and does not need to additionally increase equipment acquisition equipment. The data state of each corresponding measuring point data is judged by adopting a mode of establishing a virtual equipment object model during modeling, and a parameter-output association mode between the virtual equipment object model and a flow calculation task is set in the flow calculation task, so that the judgment of the timeliness and the authenticity of corresponding data can be realized by only establishing the object model of the production line, a task is not required to be established in a targeted mode, and the process of increasing, decreasing and modifying related tasks caused by increasing, decreasing and changing the production line is reduced, and the method is simpler and more convenient.
2. According to the scheme, the time efficiency and the authenticity of judging each data are reduced, the related measuring point data which are continuously input are calculated and judged by adopting a stream calculation task mode, the input parameters and the output parameters in the model level calculation are adopted, and the positions of the data of the input parameters and the output parameters in the stream calculation can be judged through the ID basic field.
3. According to the scheme, the interruption, retransmission and recovery of the data stream can be automatically processed by adopting the stream calculation task, so that timeliness and authenticity of headquarter data can be monitored in real time, reliability of index operation values is improved, and the monitoring timeliness and reliability are good.
4. After the data link is abnormal, the scheme informs headquarter management personnel and the data management personnel of the factory in the modes of large screen popup window, mobile phone short message and the like at the first time so as to ensure that the abnormality is handled as soon as possible.
5. The scheme can also provide a data on-line state statistics mode for headquarters, and can carry out abnormal log statistics, icon analysis and real-time monitoring on data of each area, each factory and each production line.
Drawings
FIG. 1 is a schematic diagram of a data flow calculation task structure in the present invention.
Fig. 2 is a schematic diagram of an internet of things platform system to which the present invention is applied.
Detailed Description
The following detailed description of the embodiments of the invention, given by way of example only, is presented in the accompanying drawings to aid in a more complete, accurate, and thorough understanding of the inventive concepts and aspects of the invention by those skilled in the art.
As shown in fig. 1-2, the invention discloses a monitoring method for judging timeliness and authenticity of data acquisition in cement industry, which comprises the following steps:
s1, selecting a plurality of measuring point data for judging whether the data state is abnormal or not.
In this embodiment, four measurement point data are selected as the basis for determining whether there is an abnormality in the data from the data acquisition link, and as the basis for determining the data state, the measurement point data are specifically as follows: a. kiln bucket lifting-current, kiln main motor-current, c. high temperature fan-current, d. kiln head Roots fan-outlet pressure.
The above-mentioned measurement point data are selected because the above-mentioned four measurement point data satisfy the following requirements:
1. unification: all cement kiln production lines are provided with the measuring points.
2. Importance: the measurement point data are all important parameters in the cement kiln process, and the data are not set to 0 when the cement kiln system is normally produced.
3. High frequency properties: in the producing environment, the measuring point data can be continuously and dynamically changed.
Therefore, the system can judge whether the data are abnormal according to whether the data of the measuring points are 0 or not and whether the change is stopped, and further judge whether the whole data acquisition link is abnormal or not. Therefore, based on the monitoring of the measuring point data, whether abnormal interruption exists in various cement kiln production systems and corresponding whole data acquisition links or not can be monitored.
S2, constructing an industrial Internet of things platform based on the equipment object model, and realizing model level flow calculation.
In this embodiment, the equipment model is set based on the unified cement industry or the system specification of the group, so as to facilitate data intercommunication. The complete data acquisition link is formed by the equipment model of the same cement kiln production line or cement kiln factory.
For example: as shown in fig. 2, the whole data acquisition link is divided into 5 areas, and area 1 is the OPC server side of each factory; the area 2 is industrial safety isolation equipment; the 3 area is a data acquisition device, and the equipment is mainly responsible for data acquisition and forwarding; the area 4 is an industrial Internet of things platform; and the 5 area is an online statistics large screen and short message warning function module. With zones 1-3 in the factory and zones 4-5 in the cloud (headquarters).
The function can analyze the abnormality of the data acquisition link between the areas 1-4, complete analysis and judgment in the Internet of things platform (area 4), and provide the analysis and judgment for the area 5 for application. The timeliness and the authenticity of the data acquisition in the cement industry are judged.
Based on the measurement point data determined in the previous step, the equipment object model corresponding to the data acquisition link at least comprises the following four input devices and measurement points, and the modeling is shown in table 1.
Table 1: modeling data table of parameter entering equipment and measuring point
In the scheme, the parameter entering equipment comprises a rotary kiln, a kiln hopper lifting device, a high-temperature fan and a kiln head Roots fan, the parameter entering of the corresponding object model comprises a corresponding production line number and equipment ID, if the related measuring point data meet the abnormal judgment standard, the attribute of the related measuring point is abnormal, and otherwise, the attribute of the related measuring point is normal.
The factory and production line equipment ID basic field setting specification is as follows: according to the area-factory-production line, the device ID is normalized to determine the position of the stream calculation input and output data. Specifically, table 2 is shown.
Table 2: basic field setting example table of factory and production line
And S3, establishing an object model of the virtual equipment for judging the data state, wherein the object model of the virtual equipment corresponds to the data acquisition link one by one.
The virtual device model and the attributes established in this step are shown in table 3.
Table 3: modeling data table of virtual device for judging data state
| Sequence number | Device name | Device ID | Object model | State attributes |
| 1 | Data state | Online | dtml：HLSN-Online-01-00 | State |
In each complete data acquisition link, the measuring point states of the four measuring point data determined in the step S1 are used as input parameters to be associated with object models of corresponding virtual equipment, and the corresponding state attributes indicate whether the data acquisition link is abnormal or not. When the measuring point states of the four measuring point data are abnormal, the state attribute of the virtual equipment is abnormal, and the corresponding whole data acquisition link is indicated to be abnormal; when the measuring point states of the four measuring point data are not abnormal, the state attribute of the virtual equipment is normal, and the corresponding whole data acquisition link is normal, and the abnormal corresponding measuring point or related line occurs.
S4, establishing a flow calculation task in the system, associating the parameter entering equipment of the task with the corresponding measuring point attribute, and judging whether each data acquisition link is abnormal or not through the flow calculation task.
The stream computation task includes: the monitoring results of the four measuring point data are related to the object model of the virtual equipment corresponding to the data acquisition link, when the a, b, c, d four measuring point data related to the object model of the same virtual equipment are not changed for 30 seconds continuously, the abnormal interruption of the data acquisition link of the production line is judged, and the parameter is returned to the object model of the virtual equipment (dtml: HLSN-Online-01-00/State); when the data is normal, the parameter is always returned to the object model (dtml: HLSN-Online-01-00/State).
The specific data flow calculation task structure is shown in fig. 1, the flow calculation is carried out on the corresponding models of the input parameter and the output parameter, the related object instance data under the models can automatically participate in the operation, and the flow calculation automatically identifies the position of the production line according to the equipment ID basic field of the input parameter. The method comprises the following steps:
01_02_01_512 (kiln main motor-current data of rotary kiln in Anhui 2# factory 1# production line);
01_02_01_428 (kiln inlet bucket lifting-current data of kiln inlet bucket lifting in Anhui 2# factory 1# production line);
01_02_01_506 (high temperature fan-current data of high temperature fan in Anhui 2# factory 1# production line);
01_02_01_825 (kiln head Roots blower-outlet pressure data for kiln head Roots blower in Anhui 2# factory 1# production line);
when the flow calculation task is executed, the data state of the Anhui-2 # factory-1 # production line can be identified according to the equipment ID basic field, and therefore the parameters are returned to the object model 01_02_01_Online of the virtual equipment. When the four input parameters (namely, the measurement point states of the corresponding four measurement point data) of the object model 01_02_01_online of the virtual device are abnormal, the state attribute of the virtual device is abnormal, and the state attribute represents that the corresponding whole data acquisition link is abnormal.
S5, carrying out abnormal interruption alarm prompt of the corresponding data acquisition link when the abnormality occurs.
An online statistics large screen is arranged in headquarter application, so that functions of chart statistics and analysis of online data conditions, data exception logs and the like of each region-factory-production line are realized. When the state attribute returned by the virtual equipment is abnormal, a certain production line corresponding to the surface is abnormally interrupted, and then a popup window can appear on the large online statistics screen of data corresponding to the abnormality, wherein the popup window comprises information such as factory-production line description (specifically representing that a 2# line of a Ningnational cement plant is offline), offline time and the like. The factory-production line is determined according to the equipment ID basic field, the alarm prompt information is stored in a system, and the system can call the information of the abnormal production line in real time according to the requirement after alarming. The large screen system can also integrate a log function, and base information such as offline time, online time, offline times and the like of each production line can be counted.
Besides the large-screen alarm function, the system can also be provided with a short message alarm module as an important tool for alarm pushing. After the data state of the related industrial Internet of things platform and the stream calculation task are set, the method can configure the responsive pushing personnel, and the pushing personnel correspond to the abnormal state of the corresponding data acquisition link. When the data is abnormal, the data is pushed to mobile phones of all related persons through short messages at the first time. When the alert module obtains the field data from the IoT platform to become "true," the alert is pushed. Besides the short message pushing mode, other pushing modes also comprise modes of enterprise group, APP, telephone group call and the like, and pushing is completed by setting a corresponding group alarm module, APP alarm module or telephone group call module.
After related personnel acquire offline information through a large screen, an alarm short message and the like, the related personnel analyze and judge the cause of the abnormality on site at the first time and process the cause in time.
While the invention has been described above with reference to the accompanying drawings, it will be apparent that the invention is not limited to the above embodiments, but is capable of being modified or applied to other applications without modification, as long as various insubstantial modifications of the inventive concept and technical solutions are adopted, all within the scope of the invention.
Claims (9)
1. A monitoring method for judging timeliness and authenticity of data acquisition in cement industry is characterized by comprising the following steps: comprises the following steps:
s1, selecting a plurality of measuring point data for judging whether the data state is abnormal or not;
s2, constructing an industrial Internet of things platform based on the equipment object model to realize model level flow calculation;
s3, establishing an object model of the virtual equipment for judging the data state, wherein the object model of the virtual equipment corresponds to the data acquisition link one by one;
s4, establishing a flow calculation task in the system, wherein the parameter entering of the task is related to the parameter entering equipment and the corresponding measuring point attribute, and judging whether each data acquisition link is abnormal or not through the flow calculation task;
s5, carrying out abnormal interruption alarm prompt of the corresponding data acquisition link when the abnormality occurs.
2. The monitoring method for judging the timeliness and the authenticity of data acquisition in the cement industry according to claim 1, wherein the monitoring method is characterized by comprising the following steps: in step S1, the measurement points are measurement points of each production line corresponding to each data acquisition link, and the corresponding measurement point data will not be set to 0 in normal production of the production line and will continuously fluctuate.
3. The monitoring method for judging the timeliness and the authenticity of data acquisition in the cement industry according to claim 2, wherein the monitoring method is characterized by comprising the following steps: the data collected by the method are related data of a cement kiln production line, and the data of the measuring points selected in the step S1 are specifically as follows: a. kiln bucket lifting-current, kiln main motor-current, c. high temperature fan-current, d. kiln head Roots fan-outlet pressure.
4. The monitoring method for judging the timeliness and the authenticity of data acquisition in the cement industry according to claim 1, wherein the monitoring method is characterized by comprising the following steps: in the step S2, the equipment object model is set based on a unified specification, and the equipment ID is specified according to the region-factory-production line, so as to determine the position of the data of the stream calculation input parameters and the stream calculation output parameters; the equipment object model of the same production line forms a complete data acquisition link, the equipment object model comprises a parameter entering device and a measuring point corresponding to the measuring point data, if the related measuring point data meet the abnormal judgment standard, the attribute of the related measuring point is abnormal, otherwise, the attribute of the related measuring point is normal.
5. The monitoring method for judging the timeliness and the authenticity of data acquisition in the cement industry according to claim 1, wherein the monitoring method is characterized by comprising the following steps: in the step S3, in each complete data acquisition link, the measurement point state of the measurement point data determined in the step S1 is used as an input parameter to be associated with the object model of the corresponding virtual device, and the corresponding state attribute indicates whether the data acquisition link is abnormal; when the measuring point states of the measuring point data are abnormal, the state attribute of the virtual equipment is abnormal, and the corresponding whole data acquisition link is abnormal; when the measuring point states of the four measuring point data are not abnormal, the state attribute of the virtual equipment is normal, which means that the corresponding whole data acquisition link is normal.
6. The monitoring method for judging the timeliness and the authenticity of data acquisition in the cement industry according to claim 1, wherein the monitoring method is characterized by comprising the following steps: in the step S4, the stream calculation task includes: the monitoring result of each measuring point data is related to the object model of the virtual equipment corresponding to the data acquisition link of the virtual equipment, when the object model of the same virtual equipment is not changed for a plurality of continuous times, the abnormal interruption of the data acquisition link of the production line is judged, and the output parameter is returned to the object model of the virtual equipment; when the data is normal, the parameter is always returned to the object model.
7. The monitoring method for judging the timeliness and the authenticity of data acquisition in the cement industry according to claim 6, wherein the monitoring method is characterized by comprising the following steps: the stream calculation automatically identifies the line location based on the device ID base field of the incoming parameters.
8. The monitoring method for judging the timeliness and the authenticity of data acquisition in the cement industry according to claim 1, wherein the monitoring method is characterized by comprising the following steps: the alarm module used in the step S5 comprises an online statistics large screen, and after an abnormal interrupt occurs in a certain production line, the online statistics large screen of data corresponding to the abnormal event has a popup window, and the popup window comprises information of factory-production line description and offline time; the factory-production line is determined according to the equipment ID basic field, the alarm prompt information is stored in a system, and the system can call the information of the abnormal production line in real time according to the requirement after alarming.
9. The monitoring method for judging the timeliness and the authenticity of data acquisition in the cement industry according to claim 1, wherein the monitoring method is characterized by comprising the following steps: the alarm module used in the step S5 includes an alarm push module, configured to configure a responsive push person, where the push person corresponds to an abnormality of a corresponding data acquisition link, and the alarm push module can push alarm information by using any one or two or more of a short message, an enterprise group, an APP, and a telephone group call.
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