CN111637914A - Metering data acquisition and analysis control system based on big data analysis method - Google Patents
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Abstract
The invention provides a metering data acquisition and analysis control system based on a big data analysis method. The control system comprises N metering data acquisition nodes distributed on the metering data flow line; at least one metering data gathering node is respectively connected with a metering data acquisition terminal and a metering data filter node; the system comprises a plurality of measurement data acquisition nodes, a plurality of measurement data processing nodes and a plurality of measurement data processing nodes, wherein each measurement data acquisition node is provided with Kn measurement instruments and corresponding measurement data gates; the metering data analysis system carries out big data analysis on the data stored by the data transmission bus, a metering data acquisition terminal and a metering data filter node, so that a metering data gating regulation signal is given, and the metering data measurement accuracy of N metering data acquisition nodes is ensured to the maximum extent; when all the measuring instruments have faults, the measuring data acquisition nodes corresponding to the faulty measuring instruments can be accurately positioned.
Description
Technical Field
The invention belongs to the technical field of measurement and control, and particularly relates to a measurement data acquisition and analysis control system based on a big data analysis method.
Background
The production line of high precision products requires strict parameter control, and the production line flow usually requires continuous and uninterrupted parameter monitoring and control. Although the production of the products can be realized through the flow type large-scale industrialization, for each product, in order to ensure the quality of the product, the parameters added by a plurality of nodes involved in each production process are still ensured to be in a standard range. For example, the chemical production process of the parameter composition controlled chemical product is extremely complex, and is accompanied by a plurality of unidentified physical and chemical reactions. For the continuous process industry, a stable working condition is maintained, so that accidents and secondary disasters can be reduced, the product quality is stabilized, and optimal cost operation is performed under the optimized working condition to obtain the maximum economic benefit; for the production process of products in the semiconductor industry with added component control, different alloy components are added at different nodes, and the obtained products are quite different, for example, conductors, semiconductors and superconductors can be respectively obtained through different added control; for example, in the food industry, different products such as wine, vinegar or soy sauce can be obtained by controlling the temperature and humidity and other parameters of the food processing flow.
In order to ensure the quality of the final product, in different nodes involved in the production line of the product, each node needs to be configured with a plurality of sensors, measuring instruments or parameter control devices for measuring relevant parameters at the node, so that problems of single node or node metering data are avoided. However, as previously mentioned, for the continuous flow industry, a production line typically involves thousands of control nodes, and even if ten sensors are deployed for different nodes, hundreds of thousands of metering data are obtained. If a product fails, developers need to analyze hundreds of thousands of data to find out a failed node or a failed sensor, so that the workload is huge and the efficiency is low. The failure referred to herein includes not only an abnormal situation affecting the safety of the device (collectively referred to as a safety failure), but also a deviation in product quality and optimum operating conditions (collectively referred to as a performance failure).
The Chinese invention patent with the application number of CN201610263402.X provides a chemical production online fault detection and diagnosis technology based on a physical-big data mixed model, after a target operation unit is selected, all historical data of the unit are scanned, and after parameters are verified, an accident knowledge base and a parameter model are established; in the subsequent on-line detection process, the on-line data is directly imported into the parameter model, fault data in the on-line data is obtained after scanning, an alarm is sent out, and the fault data is compared with data in the accident knowledge base to obtain the fault reason. However, this solution does not solve the problem of sensor data failure.
Big data (big data) refers to a data set which cannot be captured, managed and processed by a conventional software tool within a certain time range, and is a massive, high-growth rate and diversified information asset which needs a new processing mode to have stronger decision-making power, insight discovery power and flow optimization capability. Big data analysis refers to the analysis of data on a huge scale. Big data can summarize large Volume (Volume), fast speed (Velocity), multiple types (Variety), Value (Value), and authenticity (Veracity).
In summary, the invention provides a measurement data acquisition and analysis control system based on a big data analysis method.
Disclosure of Invention
The present invention is directed to a corresponding and effective solution for solving the above technical problems.
In order to solve the problem of sensor faults of a production line system of high-precision products, the invention provides a metering data acquisition and analysis control system based on a big data analysis method.
The control system comprises N metering data acquisition nodes distributed on the metering data flow line, a metering data acquisition terminal and a metering data filter node; at least one metering data gathering node is respectively connected with the metering data acquisition terminal and the metering data filter node; the system comprises a plurality of measurement data acquisition nodes, a plurality of measurement data processing nodes and a plurality of measurement data processing nodes, wherein each measurement data acquisition node is provided with Kn measurement instruments and corresponding measurement data gates; and the metering data gating device selects the metering data collected by one of the metering instruments according to the metering data gating adjusting signal and outputs the metering data to the data transmission bus.
The metering data analysis system carries out big data analysis on the data stored by the data transmission bus, a metering data acquisition terminal and a metering data filter node, so that a metering data gating regulation signal is given, and the metering data measurement accuracy of N metering data acquisition nodes is ensured to the maximum extent; when all the measuring instruments have faults, the measuring data acquisition nodes corresponding to the faulty measuring instruments can be accurately positioned.
Specifically, in a first aspect of the present invention, a metering data acquisition control system based on a big data analysis method is provided, where the control system includes N metering data acquisition nodes distributed on the metering data flow line, a metering data acquisition endpoint, and a metering data filter node; and at least one metering data gathering node is respectively connected with the metering data acquisition terminal and the metering data filter node.
As a first advantage of the present invention, Kn meters are provided for the kth metering data acquisition node, and the Kn meters acquire at least Kn metering data at the kth metering data acquisition node;
a metering data gate K is arranged for the Kth metering data acquisition node and is connected with the Kn metering instruments;
the metering data gate K is connected to a data transmission bus, and the data transmission bus comprises N data registers;
the metering data gating device K selects the metering data collected by one of the Kn metering devices to be output to the data transmission bus according to the metering data gating adjusting signal and stores the metering data into one of the N data registers;
as a second advantage of the present invention, at the metering data acquisition end point, the metering data stored in the N data registers of the data transmission bus is acquired and sent to the first metering data summarization node connected thereto;
the metering data filter node receives metering data output by a metering data gate connected with the metering data acquisition end point and sends the metering data to a second metering data summary node connected with the metering data filter node;
it is worth pointing out that, as an embodiment of the big data technology of the present invention, the control system further includes a data set analysis engine, where the data set analysis engine receives outputs of the first and second metering data summarization nodes, and outputs the metering data gating adjustment signal based on the metering data stored in the N data registers of the data transmission bus.
Unlike the prior art, each node employs the same number of redundant sensor configurations, in the present invention, K is 1. Kn is inversely related to the size of K, and Kn is more than 2.
This configuration is to fully consider the situation that data transmitted from a node far away in the production flow line is likely to fail in a long time, and therefore, a larger number of measuring instruments or sensors need to be configured.
The measurement data gating adjusting signals are N paths of independent signals, and the N paths of independent signals are respectively used as feedback adjusting signals of a measurement data gating device connected with the N measurement data acquisition nodes.
Preferably, in an initial state, the metering data gate K randomly selects the metering data collected by one of the Kn meters to be output to the data transmission bus.
In order to facilitate the subsequent analysis system to perform big data analysis, the metering data gating device K selects the metering data collected by one of the Kn metering devices to be output to the data transmission bus according to the metering data gating adjustment signal, and stores the metering data into one of the N data registers, including: and standardizing the metering data and storing the metering data in the data register.
In a second aspect of the present invention, a metering data analysis system based on a big data analysis method is provided, and the analysis system is implemented based on the aforementioned control system acquisition process.
Specifically, a standard attribute value sequence of the metering data corresponding to the N metering data acquisition nodes on the metering data flow line is stored at the metering data acquisition end point;
the data set analysis engine calculates the difference index values of the standard attribute value sequence and the metering data stored in N data registers of the data transmission bus acquired by the metering data acquisition end point;
if the difference index value is smaller than a first preset threshold value, the data set analysis engine calculates a similarity measurement sequence of the standard attribute value and the metering data received by the metering data filter node and output by a metering data gating device connected with the metering data acquisition terminal;
and if the similarity of the similarity metric sequence is not greater than a second preset threshold value, the data set analysis engine sends a metering data gating adjusting signal to a gate of a corresponding path.
The standard attribute value sequence of the metering data corresponding to the N metering data acquisition nodes is S ═ S1, S2,....... SN }; the metering data stored in the N data registers of the data transmission bus acquired by the metering data acquisition end point is J { J1, J2...... JN };
the difference index value CjsThe definition is as follows:
it is worth pointing out that, unlike the method of calculating the difference value in the prior art that generally employs the KL divergence value, the difference index value described in the present invention is further improved, and is combined with the JSD (Jensen-Shannon) divergence expression value, so as to obtain the difference index value applicable to the scenario of the present invention, which is one of the contributions of the present invention.
And if the randomly selected metering data acquisition node is the mth metering data acquisition node, the data set analysis engine sends a metering data gating regulation signal to the metering data gating device connected with the mth metering data acquisition node.
Specifically, the data set analysis engine sends a metering data gating adjustment signal to a metering data gating device connected to the mth metering data acquisition node, and the metering data gating device connected to the mth metering data acquisition node switches the gating signal so that the currently selected metering device is disabled.
And if all the meters connected with the m-th metering data acquisition node are forbidden, sending out an alarm signal.
As a more important improvement of the invention, an alarm signal is issued if there is only one meter left which is not disabled for the meter to which the m-th meter data collection node is connected.
Correspondingly, the data set analysis engine sends out a random gating adjusting signal or a constant signal aiming at the metering data gating devices connected with other metering data acquisition nodes.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed 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 to obtain other drawings without creative efforts.
FIG. 1 is a bus schematic diagram of a metering data acquisition control system of the present application;
FIG. 2 is a schematic view of a metrology data analysis system of the present application;
FIG. 3 is a schematic diagram of metering data strobe adjustment signal acquisition according to the present application;
FIG. 4 is a schematic diagram of a data set analysis engine control method according to the present application.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
In order that the above objects, features and advantages of the present invention can be more clearly understood, the present invention will be further described with reference to the accompanying drawings and examples. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
Referring to fig. 1, a bus diagram of a metering data collection control system according to an embodiment of the present invention is shown. In fig. 1, for convenience of illustration, redundant parts are omitted in a form of a dotted line, for example, a part of the flow line of the metering data is omitted by a dotted line, and except for the 1 st and 2 nd gates, connections of the 3 rd to n th gates to corresponding data acquisition nodes are also indicated by ellipses.
Referring to fig. 1, the metering data acquisition control system includes a complete metering data flow line. The metering data flow line comprises 1-n metering data acquisition nodes.
The metering data collection node may perform different functions for different product manufacturing processes. For example, for a precision electronic product, the metrology data collection node is used to detect certain property parameters of the electronic product arriving at the node, such as conductivity, reflectivity, and resistance; for chemical products, the metering data acquisition node is used for monitoring the attribute values of the components added into the products by the node, such as component proportion, temperature value, humidity value and the like;
at least one meter is configured for each of the meter data collection nodes. The at least one meter is used for measuring related metering parameters of the same data acquisition node, such as the specific attribute parameters of the electronic product or the attribute values of the components of the chemical product.
For each of the metering data acquisition nodes, a metering data gate is configured, and the metering data gate is connected with the metering instrument;
in the present embodiment, although not shown in fig. 1, the metering data flow line is a directed flow line from a start point (first metering data collection node), an intermediate node (2-nth metering data collection nodes) to an end point (calculation data collection end point);
the number of the meters configured at the starting point is the largest, and the number of the meters configured at the nth node is the smallest; the number of meters arranged at the end point is N.
Thus, referring to fig. 1, the control system includes N metering data collection nodes distributed on the metering data flow line, as well as a metering data collection endpoint and a metering data filter node; and at least one metering data gathering node is respectively connected with the metering data acquisition terminal and the metering data filter node.
For the Kth metering data acquisition node, at least Kn metering data are acquired by the Kn metering instruments at the Kth metering data acquisition node; a metering data gate K is arranged for the Kth metering data acquisition node and is connected with the Kn metering instruments;
the metering data gate K is connected to a data transmission bus, and the data transmission bus comprises N data registers;
the metering data gating device K selects the metering data collected by one of the Kn metering instruments to output to the data transmission bus according to the metering data gating adjusting signal and stores the metering data to one of the N data registers;
at the metering data acquisition end point, acquiring metering data stored in N data registers of the data transmission bus, and sending the metering data to a first metering data summary node connected with the metering data summary node;
the metering data filter node receives metering data output by a metering data gate connected with the metering data acquisition end point and sends the metering data to a second metering data summary node connected with the metering data filter node;
the control system further comprises a data set analysis engine, wherein the data set analysis engine receives the outputs of the first metering data summarization node and the second metering data summarization node, and outputs the metering data gating regulation signal based on the metering data stored in the N data registers of the data transmission bus;
wherein, K1.... N; kn is inversely related to the size of K, and Kn is more than 2.
The measurement data gating adjusting signals are N paths of independent signals, and the N paths of independent signals are respectively used as feedback adjusting signals of a measurement data gating device connected with the N measurement data acquisition nodes.
The measurement data gating device K selects the measurement data collected by one of the Kn measurement instruments to be output to the data transmission bus according to the measurement data gating adjusting signal and stores the measurement data to one of the N data registers, and the measurement data gating device K comprises: and standardizing the metering data and storing the metering data in the data register.
In an initial state, the metering data gate K randomly selects the metering data collected by one of the Kn metering instruments to output to the data transmission bus.
Referring to fig. 2, a schematic diagram of a system for analyzing metrology data according to the present application is shown.
The analysis system comprises the control system, and a standard attribute value sequence of the metering data corresponding to N metering data acquisition nodes on the metering data flow line is stored at the metering data acquisition end point;
the data set analysis engine calculates the difference index values of the standard attribute value sequence and the metering data stored in N data registers of the data transmission bus acquired by the metering data acquisition end point;
if the difference index value is smaller than a first preset threshold value, the data set analysis engine calculates a similarity measurement sequence of the standard attribute value and the metering data received by the metering data filter node and output by a metering data gating device connected with the metering data acquisition terminal;
and if the similarity of the similarity metric sequence is not greater than a second preset threshold value, the data set analysis engine sends a metering data gating adjusting signal to a gate of a corresponding path.
In particular, on the basis of fig. 2, see fig. 3-4. FIG. 3 is a schematic diagram of metering data strobe adjustment signal acquisition, and FIG. 4 is a schematic diagram of a data set analysis engine control method.
The standard attribute value sequence of the metering data corresponding to the N metering data acquisition nodes is S ═ S1, S2...... multidata, SN }; the metering data stored in the N data registers of the data transmission bus acquired by the metering data acquisition end point is J { J1, J2...... JN };
the difference index value CjsThe definition is as follows:
and if the randomly selected metering data acquisition node is the mth metering data acquisition node, the data set analysis engine sends a metering data gating regulation signal to the metering data gating device connected with the mth metering data acquisition node.
The data set analysis engine sends a metering data gating adjusting signal to a metering data gating device connected with an m-th metering data acquisition node, and the metering data gating device connected with the m-th metering data acquisition node switches a gating signal, so that the selected metering device is forbidden, and data of other metering devices are selected next time; and aiming at the metering data strobing devices connected with other metering data acquisition nodes, the data set analysis engine sends out random strobe adjustment signals or invariable signals.
And if all the meters connected with the m-th metering data acquisition node are forbidden, sending out an alarm signal.
It is worth noting that if a meter connected to a metering data collection node is disabled, it means that the meter is no longer being used to monitor data, and of course, is not being selected by the metering data gate connected to that node.
In the present embodiment, although not shown, more preferable aspects further include; an alarm signal is issued if there is only one meter left with the meter connected to the m-th meter data collection node not disabled.
According to the technical scheme, when the data acquired by the metering instrument at a certain node is abnormal, the current metering instrument can be forbidden rapidly, so that production is not influenced; if all meters are disabled or not in sufficient quantity, an alarm signal is issued and the point of failure can be located directly.
The present invention can be easily implemented by those skilled in the art from the above detailed description. It should be understood, however, that the intention is not to limit the invention to the particular embodiments described. On the basis of the disclosed embodiments, a person skilled in the art can combine different technical features at will, thereby implementing different technical solutions.
Claims (10)
1. A metering data acquisition control system based on a big data analysis method comprises N metering data acquisition nodes distributed on a metering data flow line, a metering data acquisition terminal and a metering data filter node;
at least one measurement data summarization node is connected with the measurement data acquisition terminal and the measurement data filter node respectively, and the measurement data summarization node is characterized in that:
for the Kth metering data acquisition node, at least Kn metering data are acquired by the Kn metering instruments at the Kth metering data acquisition node;
a metering data gate K is arranged for the Kth metering data acquisition node and is connected with the Kn metering instruments;
the metering data gate K is connected to a data transmission bus, and the data transmission bus comprises N data registers;
the metering data gating device K selects the metering data collected by one of the Kn metering instruments to output to the data transmission bus according to the metering data gating adjusting signal and stores the metering data to one of the N data registers;
at the metering data acquisition end point, acquiring metering data stored in N data registers of the data transmission bus, and sending the metering data to a first metering data summary node connected with the metering data summary node;
the metering data filter node receives metering data output by a metering data gate connected with the metering data acquisition end point and sends the metering data to a second metering data summary node connected with the metering data filter node;
the control system further comprises a data set analysis engine, wherein the data set analysis engine receives the outputs of the first metering data summarization node and the second metering data summarization node, and outputs the metering data gating regulation signal based on the metering data stored in the N data registers of the data transmission bus;
wherein, K1.... N; kn is inversely related to the size of K, and Kn is more than 2.
2. The control system of claim 1, wherein the metrology data strobe adjustment signal is an N-way independent signal that serves as a feedback adjustment signal for a metrology data strobe coupled to the N metrology data acquisition nodes, respectively.
3. The control system of claim 1, wherein in an initial state, the metering data gate K randomly selects the metering data collected by one of the Kn meters to be output to the data transmission bus.
4. The control system of claim 1, wherein the metering data gate K selects the metering data collected by one of the Kn meters to be output to the data transmission bus and stored in one of the N data registers according to a metering data gate adjustment signal, and comprises: and standardizing the metering data and storing the metering data in the data register.
5. A system for analyzing measurement data based on a big data analysis method, the analysis system including the control system according to any one of claims 1 to 4, wherein:
the metering data acquisition end point stores a standard attribute value sequence of the metering data corresponding to N metering data acquisition nodes on the metering data flow line;
the data set analysis engine calculates the difference index values of the standard attribute value sequence and the metering data stored in N data registers of the data transmission bus acquired by the metering data acquisition end point;
if the difference index value is smaller than a first preset threshold value, the data set analysis engine calculates a similarity measurement sequence of the standard attribute value and the metering data received by the metering data filter node and output by a metering data gating device connected with the metering data acquisition terminal;
and if the similarity of the similarity metric sequence is not greater than a second preset threshold value, the data set analysis engine sends a metering data gating adjusting signal to a gate of a corresponding path.
6. The analysis system of claim 5, wherein the standard attribute value sequence of the metrology data corresponding to the N metrology data acquisition nodes is S ═ S1, S2...... multidata., SN }; the metering data stored in the N data registers of the data transmission bus acquired by the metering data acquisition end point is J { J1, J2...... JN };
the difference index value CjsThe definition is as follows:
7. the analysis system as claimed in claim 5, wherein the metrology data gate connected to the metrology data collection endpoint randomly selects metrology data corresponding to one of the N metrology data collection nodes on the metrology data flow line stored at the metrology data collection endpoint, and if the randomly selected metrology data collection node is the mth metrology data collection node, the data set analysis engine sends out a metrology data gate adjustment signal to the metrology data gate connected to the mth metrology data collection node.
8. The analysis system of claim 7, wherein the data set analysis engine issues a metering data strobe throttling signal to a metering data strobe connected to an mth metering data acquisition node, the metering data strobe connected to the mth metering data acquisition node switching the strobe signal such that the currently selected meter is disabled.
9. The analytical system of claim 7, wherein the alarm signal is issued if all meters connected to the mth metering data collection node are disabled.
10. The analytics system of claim 7, wherein the data set analysis engine issues a random gate adjustment signal or a constant signal for other meter data collection node-connected meter data strobes.
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| CN115597653B (en) * | 2022-12-14 | 2023-11-03 | 中顺世纪(深圳)电子有限责任公司 | Intelligent identification method and system for semiconductor quality detection equipment |
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