CN113093678A - Data processing method for power plant DCS (distributed control System) - Google Patents
Data processing method for power plant DCS (distributed control System) Download PDFInfo
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- CN113093678A CN113093678A CN202110370943.3A CN202110370943A CN113093678A CN 113093678 A CN113093678 A CN 113093678A CN 202110370943 A CN202110370943 A CN 202110370943A CN 113093678 A CN113093678 A CN 113093678A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/4185—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by the network communication
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/33—Director till display
- G05B2219/33139—Design of industrial communication system with expert system
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention discloses a data processing method for a power plant DCS, which comprises the following steps: A. the master station and the slave station establish encrypted communication connection; B. the slave station sends the collected data to the master station; C. the master station classifies and stores the received collected data; D. the master station transmits control information to the slave station. The invention can improve the defects of the prior art and improve the compatibility of the data processing method to different DCS systems.
Description
Technical Field
The invention relates to the technical field of power plant automation, in particular to a data processing method for a power plant DCS.
Background
In recent years, a Distributed Control System (DCS for short) is applied to a power plant operation System, various parameters and real-time data of the operation of a plurality of power plant units are monitored, and how to effectively process the data contains rich and valuable information in mass data acquired by the DCS System is one of the keys for improving the operation efficiency of the DCS System. However, because the DCS system adopts a centralized management and decentralized control architecture, and its configuration structure is specifically configured according to a specific application scenario, the existing data processing method cannot be compatible with DCS systems of different configuration structures, so that under each actual application condition, a data processing flow of the DCS system needs to be specially rewritten and debugged, which increases the use cost and operational risk of the system.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a data processing method for a power plant DCS, which can solve the defects of the prior art and improve the compatibility of the data processing method for different DCS systems.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows.
A data processing method for a power plant DCS comprises the following steps:
A. the master station and the slave station establish encrypted communication connection;
B. the slave station sends the collected data to the master station;
C. the master station classifies and stores the received collected data;
D. the master station transmits control information to the slave station.
Preferably, in step a, establishing an encrypted communication connection comprises the steps of,
a1, the master station sends the communication interface information to the slave station, and the slave station encrypts the received communication interface information and sends the encrypted communication interface information back to the master station;
a2, the master station obtains a communication key according to the communication interface information before and after encryption;
a3, the communication data between the master station and the slave station are encrypted by the communication key and then transmitted, and the communication key is updated in real time.
Preferably, in step a2, the encrypted communication interface information is secondarily encrypted to ensure that the secondarily encrypted communication interface information is linearly related to the primarily encrypted communication interface information, and then encryption operators used in the two encryptions are linearly combined to obtain the communication key.
Preferably, in step a3, the encrypted communication data is line-shifted and then subjected to a hybrid column operation, and the first byte of the communication key is byte-replaced with the first byte of the operation result.
Preferably, in step B, the slave station preprocesses the acquired data before transmitting the acquired data, and comprises the steps of,
b1, the slave station extracts the characteristics of the collected historical data and clusters the characteristics;
b2, extracting at least one feature from each feature set to establish a feature sample;
and B3, performing feature extraction on the collected data sent in real time, calculating a stable boundary of the features, and directly sending the collected data if the stable boundary completely falls into the feature sample, or preprocessing the collected data.
Preferably, in step B3, the preprocessing of the collected data includes the steps of,
b31, performing secondary acquisition on the acquired data;
b32, comparing the acquired data acquired twice to obtain a characteristic deviation matrix;
and B33, correcting the acquired data acquired newly by using the characteristic deviation matrix, then calculating a stable boundary again, if the stable boundary falls into the characteristic sample, sending the corrected acquired data, otherwise, repeating the step B33 until the stable boundary falls into the characteristic sample.
Preferably, in step C, the classifying and storing the collected data includes the steps of,
c1, storing the collected data in a data buffer area;
c2, pre-classifying the collected data according to the sending source address of the collected data;
c3, sequentially carrying out secondary classification on each pre-classified collected data according to the data type and the data content;
and C4, storing the acquired data subjected to secondary classification into a data storage area.
Preferably, the data buffer area adopts a stack storage form.
Preferably, in step C3, a weight list of data types and data contents is created, and the collected data is classified using the weighted weights of the data types and the data contents.
Preferably, in step C3, after the secondary classification, an association link between the collected data belonging to the same pre-classification in step C2 is established among the collected data of the same class.
Adopt the beneficial effect that above-mentioned technical scheme brought to lie in: the invention improves the data processing efficiency of the DCS system by optimizing the data processing flow under the premise of ensuring the safety.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
Example 1
A data processing method for a power plant DCS comprises the following steps:
A. the master station and the slave station establish encrypted communication connection;
B. the slave station sends the collected data to the master station;
C. the master station classifies and stores the received collected data;
D. the master station transmits control information to the slave station.
In step a, establishing an encrypted communication connection comprises the following steps,
a1, the master station sends the communication interface information to the slave station, and the slave station encrypts the received communication interface information and sends the encrypted communication interface information back to the master station;
a2, the master station obtains a communication key according to the communication interface information before and after encryption;
a3, the communication data between the master station and the slave station are encrypted by the communication key and then transmitted, and the communication key is updated in real time.
In step a2, the encrypted communication interface information is encrypted for the second time, to ensure that the communication interface information encrypted for the second time is linearly related to the communication interface information encrypted for the first time, and then encryption operators used in the encryption for the second time are linearly combined to obtain a communication key.
In step C, classifying and storing the collected data comprises the following steps,
c1, storing the collected data in a data buffer area;
c2, pre-classifying the collected data according to the sending source address of the collected data;
c3, sequentially carrying out secondary classification on each pre-classified collected data according to the data type and the data content;
and C4, storing the acquired data subjected to secondary classification into a data storage area.
Example 2
A data processing method for a power plant DCS comprises the following steps:
A. the master station and the slave station establish encrypted communication connection;
B. the slave station sends the collected data to the master station;
C. the master station classifies and stores the received collected data;
D. the master station transmits control information to the slave station.
In step a, establishing an encrypted communication connection comprises the following steps,
a1, the master station sends the communication interface information to the slave station, and the slave station encrypts the received communication interface information and sends the encrypted communication interface information back to the master station;
a2, the master station obtains a communication key according to the communication interface information before and after encryption;
a3, the communication data between the master station and the slave station are encrypted by the communication key and then transmitted, and the communication key is updated in real time.
In step a2, the encrypted communication interface information is encrypted for the second time, to ensure that the communication interface information encrypted for the second time is linearly related to the communication interface information encrypted for the first time, and then encryption operators used in the encryption for the second time are linearly combined to obtain a communication key.
In step C, classifying and storing the collected data comprises the following steps,
c1, storing the collected data in a data buffer area;
c2, pre-classifying the collected data according to the sending source address of the collected data;
c3, sequentially carrying out secondary classification on each pre-classified collected data according to the data type and the data content;
and C4, storing the acquired data subjected to secondary classification into a data storage area.
In step B, the slave station preprocesses the acquired data before sending the acquired data, comprising the following steps,
b1, the slave station extracts the characteristics of the collected historical data and clusters the characteristics;
b2, extracting at least one feature from each feature set to establish a feature sample;
and B3, performing feature extraction on the collected data sent in real time, calculating a stable boundary of the features, and directly sending the collected data if the stable boundary completely falls into the feature sample, or preprocessing the collected data.
In step B3, the preprocessing of the collected data includes the steps of,
b31, performing secondary acquisition on the acquired data;
b32, comparing the acquired data acquired twice to obtain a characteristic deviation matrix;
and B33, correcting the acquired data acquired newly by using the characteristic deviation matrix, then calculating a stable boundary again, if the stable boundary falls into the characteristic sample, sending the corrected acquired data, otherwise, repeating the step B33 until the stable boundary falls into the characteristic sample.
Compared with the embodiment 1, the embodiment 2 has the advantages that the probability of invalid data is reduced and the data processing efficiency is improved by preprocessing the acquired data.
Example 3
A data processing method for a power plant DCS comprises the following steps:
A. the master station and the slave station establish encrypted communication connection;
B. the slave station sends the collected data to the master station;
C. the master station classifies and stores the received collected data;
D. the master station transmits control information to the slave station.
In step a, establishing an encrypted communication connection comprises the following steps,
a1, the master station sends the communication interface information to the slave station, and the slave station encrypts the received communication interface information and sends the encrypted communication interface information back to the master station;
a2, the master station obtains a communication key according to the communication interface information before and after encryption;
a3, the communication data between the master station and the slave station are encrypted by the communication key and then transmitted, and the communication key is updated in real time.
In step a2, the encrypted communication interface information is encrypted for the second time, to ensure that the communication interface information encrypted for the second time is linearly related to the communication interface information encrypted for the first time, and then encryption operators used in the encryption for the second time are linearly combined to obtain a communication key.
In step C, classifying and storing the collected data comprises the following steps,
c1, storing the collected data in a data buffer area;
c2, pre-classifying the collected data according to the sending source address of the collected data;
c3, sequentially carrying out secondary classification on each pre-classified collected data according to the data type and the data content;
and C4, storing the acquired data subjected to secondary classification into a data storage area.
The data cache area adopts a stack storage form.
In step C3, a weight list of data types and data contents is created, and the collected data is classified using the weighted weights of the data types and the data contents.
In step C3, after the secondary classification, an association link between the collected data belonging to the same pre-classification in step C2 is established in the collected data of the same category.
In step B, the slave station preprocesses the acquired data before sending the acquired data, comprising the following steps,
b1, the slave station extracts the characteristics of the collected historical data and clusters the characteristics;
b2, extracting at least one feature from each feature set to establish a feature sample;
and B3, performing feature extraction on the collected data sent in real time, calculating a stable boundary of the features, and directly sending the collected data if the stable boundary completely falls into the feature sample, or preprocessing the collected data.
In step B3, the preprocessing of the collected data includes the steps of,
b31, performing secondary acquisition on the acquired data;
b32, comparing the acquired data acquired twice to obtain a characteristic deviation matrix;
and B33, correcting the acquired data acquired newly by using the characteristic deviation matrix, then calculating a stable boundary again, if the stable boundary falls into the characteristic sample, sending the corrected acquired data, otherwise, repeating the step B33 until the stable boundary falls into the characteristic sample.
Compared with the embodiment 2, the embodiment 3 improves the data reading and writing speed by optimizing the data classification mode, thereby further improving the data processing efficiency.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. A data processing method for a power plant DCS is characterized by comprising the following steps:
A. the master station and the slave station establish encrypted communication connection;
B. the slave station sends the collected data to the master station;
C. the master station classifies and stores the received collected data;
D. the master station transmits control information to the slave station.
2. The power plant DCS system data processing method of claim 1, wherein: in step a, establishing an encrypted communication connection comprises the following steps,
a1, the master station sends the communication interface information to the slave station, and the slave station encrypts the received communication interface information and sends the encrypted communication interface information back to the master station;
a2, the master station obtains a communication key according to the communication interface information before and after encryption;
a3, the communication data between the master station and the slave station are encrypted by the communication key and then transmitted, and the communication key is updated in real time.
3. The power plant DCS system data processing method of claim 2, wherein: in step a2, the encrypted communication interface information is encrypted for the second time, to ensure that the communication interface information encrypted for the second time is linearly related to the communication interface information encrypted for the first time, and then encryption operators used in the encryption for the second time are linearly combined to obtain a communication key.
4. A power plant DCS system data processing method as claimed in claim 3, wherein: in step a3, the encrypted communication data is line-shifted and then subjected to a hybrid column operation, and the first byte of the communication key is subjected to byte substitution using the first byte of the operation result.
5. The power plant DCS system data processing method of claim 1, wherein: in step B, the slave station preprocesses the acquired data before sending the acquired data, comprising the following steps,
b1, the slave station extracts the characteristics of the collected historical data and clusters the characteristics;
b2, extracting at least one feature from each feature set to establish a feature sample;
and B3, performing feature extraction on the collected data sent in real time, calculating a stable boundary of the features, and directly sending the collected data if the stable boundary completely falls into the feature sample, or preprocessing the collected data.
6. The power plant DCS system data processing method of claim 5, wherein: in step B3, the preprocessing of the collected data includes the steps of,
b31, performing secondary acquisition on the acquired data;
b32, comparing the acquired data acquired twice to obtain a characteristic deviation matrix;
and B33, correcting the acquired data acquired newly by using the characteristic deviation matrix, then calculating a stable boundary again, if the stable boundary falls into the characteristic sample, sending the corrected acquired data, otherwise, repeating the step B33 until the stable boundary falls into the characteristic sample.
7. The power plant DCS system data processing method of claim 6, wherein: in step C, classifying and storing the collected data comprises the following steps,
c1, storing the collected data in a data buffer area;
c2, pre-classifying the collected data according to the sending source address of the collected data;
c3, sequentially carrying out secondary classification on each pre-classified collected data according to the data type and the data content;
and C4, storing the acquired data subjected to secondary classification into a data storage area.
8. The power plant DCS system data processing method of claim 7, wherein: the data cache area adopts a stack storage form.
9. The power plant DCS system data processing method of claim 8, wherein: in step C3, a weight list of data types and data contents is created, and the collected data is classified using the weighted weights of the data types and the data contents.
10. The power plant DCS system data processing method of claim 9, wherein: in step C3, after the secondary classification, an association link between the collected data belonging to the same pre-classification in step C2 is established in the collected data of the same category.
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