CN111898916A - Coal industry chain risk monitoring system and monitoring method thereof - Google Patents
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Abstract
The invention discloses a coal industry chain risk monitoring system and a monitoring method thereof, wherein the system comprises an operation data acquisition terminal which is arranged on each industry chain node and is used for acquiring operation data of each industry chain node; the operation data association module is in communication connection with the operation data acquisition terminal and is used for establishing an association relation between operation data; the operation data merging module is in communication connection with the operation data acquisition terminal and is used for merging and simplifying the operation data; the single-node risk assessment module is respectively in communication connection with the operation data association module and the operation data merging module and is used for assessing the risk of a single industrial chain node; and the whole industrial chain risk assessment module is in communication connection with the single-node risk assessment module and is used for assessing the risk of the whole industrial chain according to the risk of the single industrial chain node. The invention can improve the defects of the prior art and improve the timeliness of risk monitoring.
Description
Technical Field
The invention belongs to the technical field of coal industry wind control management, and particularly relates to a coal industry chain risk monitoring system and a monitoring method thereof.
Background
Coal is a main energy source in China and is an important economic support in China. With the improvement of the national market economy system, the safe operation of the coal industry in the market economy is ensured, and the method becomes one of important guarantees for ensuring the economic development of China. The existing mode for monitoring risks of the coal industry chain is mostly established on large-scale calculation and analysis of operation data, and the mode cannot process the operation data in time, so that the risk monitoring is delayed.
Disclosure of Invention
Based on the defects of the prior art, the technical problem to be solved by the invention is to provide a coal industry chain risk monitoring system and a monitoring method thereof, which can reduce the loss rate of effective data in the process of merging and simplifying operation data and improve the timeliness of risk monitoring.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention provides a coal industry chain risk monitoring system, which comprises an operation data acquisition terminal, a monitoring server and a monitoring server, wherein the operation data acquisition terminal is installed on each industry chain node and is used for acquiring operation data of each industry chain node; the operation data association module is in communication connection with the operation data acquisition terminal and is used for establishing an association relation between operation data; the operation data merging module is in communication connection with the operation data acquisition terminal and is used for merging and simplifying the operation data; the single-node risk assessment module is respectively in communication connection with the operation data association module and the operation data merging module and is used for assessing the risk of a single industrial chain node; and the whole industrial chain risk assessment module is in communication connection with the single-node risk assessment module and is used for assessing the risk of the whole industrial chain according to the risk of the single industrial chain node.
The monitoring method of the coal industry chain risk monitoring system comprises the following steps:
A. an operation data acquisition terminal acquires operation data of each industrial chain node;
B. the operation data association module establishes an association relation between operation data;
C. the operation data merging module merges and simplifies the operation data;
D. c, the single-node risk assessment module assesses the risk of a single industrial chain node according to the simplified operation data obtained in the step C;
E. and the whole industry chain risk assessment module assesses the risk of the whole industry chain according to the risk of the single industry chain node.
Optionally, in step B, the data set of each operation data is compared with the data sets of other operation data one by one, a correlation function is obtained by fitting, and a weight coefficient of the correlation function is determined according to a deviation value of the correlation function and the actual data set.
Further, in the fitting process, the data set is partitioned and subjected to block fitting, all sub-functions obtained by fitting are classified according to linear correlation, and at least one characteristic factor is extracted from each sub-function; and then carrying out choleryzation on all the sub-functions to obtain a correlation function, wherein all characteristic factors are kept unchanged in the process of the choleryzation.
Optionally, in step C, an industrial chain node to be evaluated is selected, the operation data of the industrial chain node is used as high-priority data, other operation data is used as low-priority data, the low-priority data is converted into associated data of the high-priority data by using an association function with a weight coefficient, and then the high-priority data and the associated data are normalized.
Furthermore, traversing the low-priority data, marking the linearly related data, and deleting the data with the weight coefficient lower than a preset threshold value in the marked low-priority data before converting the related data.
Therefore, the coal industry chain risk monitoring system and the monitoring method thereof have the beneficial effects that:
the invention combines and simplifies the operation data by calculating the correlation function with the weight coefficient and utilizing the correlation function, thereby greatly reducing the data volume of the operation data. The block fitting mode is used in the process of fitting the correlation function, the fitting speed is improved, the problem that fitting dimensions of different sub-functions are different easily occurs after block fitting, and distortion of the correlation function in the fitting process can be effectively reduced by using the characteristic factors. By dividing the operation data into different priorities and carrying out accurate deletion and directional combination, the loss rate of effective data in the process of combining and simplifying the operation data can be reduced, so that the evaluation accuracy is not greatly influenced while the operation data amount is reduced.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following detailed description is given in conjunction with the preferred embodiments, together with the accompanying drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments will be briefly described below.
Fig. 1 is a schematic structural diagram of a coal industry chain risk monitoring system according to the present invention.
In the figure: 1. operating a data acquisition terminal; 2. an operational data association module; 3. an operation data merging module; 4. a single node risk assessment module; 5. and a whole industry chain risk assessment module.
Detailed Description
Other aspects, features and advantages of the present invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which form a part of this specification, and which illustrate, by way of example, the principles of the invention. In the referenced drawings, the same or similar components in different drawings are denoted by the same reference numerals.
As shown in fig. 1, the coal industry chain risk monitoring system provided by the present invention includes an operation data acquisition terminal 1 installed on each industry chain node, and configured to acquire operation data of each industry chain node; the operation data association module 2 is in communication connection with the operation data acquisition terminal 1 and is used for establishing an association relation between operation data; the operation data merging module 3 is in communication connection with the operation data acquisition terminal 1 and is used for merging and simplifying operation data; the single-node risk assessment module 4 is respectively in communication connection with the operation data association module 2 and the operation data merging module 3 and is used for assessing the risk of a single industrial chain node; and the whole industrial chain risk evaluation module 5 is in communication connection with the single-node risk evaluation module 4 and is used for evaluating the risk of the whole industrial chain according to the risk of the single industrial chain node.
The monitoring method of the coal industry chain risk monitoring system comprises the following steps:
A. the operation data acquisition terminal 1 acquires operation data of each industrial chain node;
B. the operation data association module 2 establishes an association relation between operation data;
C. the operation data merging module 3 merges and simplifies the operation data;
D. c, the single-node risk assessment module 4 assesses the risk of a single industrial chain node according to the simplified operation data obtained in the step C;
E. the whole industry chain risk assessment module 5 assesses the risk of the whole industry chain according to the risk of the single industry chain node.
And step B, comparing the data set of each operation data with the data sets of other operation data one by one, fitting to obtain a correlation function, and determining a weight coefficient of the correlation function according to a deviation value of the correlation function and the actual data set.
In the fitting process, the data set is partitioned and subjected to block fitting, all sub-functions obtained by fitting are classified according to linear correlation, and at least one characteristic factor is extracted from each class of sub-functions; and then carrying out choleryzation on all the sub-functions to obtain a correlation function, wherein all characteristic factors are kept unchanged in the process of the choleryzation.
And C, selecting an industrial chain node to be evaluated, taking the operation data of the industrial chain node as high-priority data and other operation data as low-priority data, converting the low-priority data into the associated data of the high-priority data by using an associated function with a weight coefficient, and then normalizing the high-priority data and the associated data.
Traversing the low-priority data, marking the linearly related data, and deleting the data with the weight coefficient lower than a preset threshold value in the marked low-priority data before converting the related data.
Before and after the priority data are converted, the feature vectors of the data before and after the conversion are respectively extracted, and the feature factors related to the correlation functions used in the conversion process are simultaneously positioned on the feature vectors of the data before and after the conversion by adjusting the data after the conversion. Through fine adjustment of the converted data, the converted feature consistency among different data can be improved, and therefore later evaluation of the data is facilitated.
While the foregoing is directed to the preferred embodiment of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Claims (6)
1. A coal industry chain risk monitoring system, comprising:
the operation data acquisition terminal (1) is installed on each industrial chain node and is used for acquiring the operation data of each industrial chain node;
the operation data association module (2) is in communication connection with the operation data acquisition terminal (1) and is used for establishing an association relation between operation data;
the operation data merging module (3) is in communication connection with the operation data acquisition terminal (1) and is used for merging and simplifying the operation data;
the single-node risk assessment module (4) is respectively in communication connection with the operation data association module (2) and the operation data merging module (3) and is used for assessing the risk of a single industrial chain node;
and the whole industry chain risk evaluation module (5) is in communication connection with the single-node risk evaluation module (4) and is used for evaluating the risk of the whole industry chain according to the risk of the single industry chain node.
2. The monitoring method of the coal industry chain risk monitoring system according to claim 1, wherein: the method comprises the following steps:
A. the operation data acquisition terminal (1) acquires operation data of each industrial chain node;
B. the operation data association module (2) establishes an association relation between operation data;
C. the operation data merging module (3) merges and simplifies the operation data;
D. c, a single-node risk evaluation module (4) evaluates the risk of a single industrial chain node according to the simplified operation data obtained in the step C;
E. and the industrial chain-wide risk assessment module (5) assesses the industrial chain-wide risk according to the risk of the single industrial chain node.
3. The monitoring method of the coal industry chain risk monitoring system as claimed in claim 2, wherein in step B, the data sets of each operation data are compared with the data sets of other operation data one by one, fitting is performed to obtain the correlation function, and the weight coefficient of the correlation function is determined according to the deviation value of the correlation function and the actual data set.
4. The monitoring method of the coal industry chain risk monitoring system of claim 3, wherein in the fitting process, the data set is partitioned and subjected to block fitting, then all sub-functions obtained by fitting are classified according to linear correlation, and at least one characteristic factor is extracted from each sub-function; and then carrying out choleryzation on all the sub-functions to obtain a correlation function, wherein all characteristic factors are kept unchanged in the process of the choleryzation.
5. A monitoring method of a coal industry chain risk monitoring system as claimed in claim 4, wherein in step C, the industry chain node to be evaluated is selected, the operation data of the industry chain node is used as high priority data, other operation data are used as low priority data, the low priority data are converted into the associated data of the high priority data by using the associated function with the weight coefficient, and then the high priority data and the associated data are normalized.
6. The monitoring method of the coal industry chain risk monitoring system as claimed in claim 5, wherein the low priority data is traversed, the linearly correlated data is marked, and the data with the weight coefficient lower than the preset threshold value in the marked low priority data is deleted before the correlated data conversion is carried out.
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Cited By (1)
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| CN116452396A (en) * | 2023-06-17 | 2023-07-18 | 北京清众神州大数据有限公司 | Monitoring method, device, equipment and medium for energy industry chain |
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