CN115776378B - Real-time access method for time sequence data of nuclear power industrial Internet platform - Google Patents
Real-time access method for time sequence data of nuclear power industrial Internet platform Download PDFInfo
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Abstract
The invention discloses a real-time access method for time sequence data of a nuclear power industrial Internet platform, which comprises the following steps: collecting sensor data or PI system data, and transmitting the sensor data or PI system data to an entering edge server; the edge server performs caching and data cleaning, data conversion, data frequency reduction, frequency reduction and data compression processing on the time sequence data; accessing the processed data into an MQTT server or a Kafka of a nuclear power industrial Internet platform by using an MQTT protocol or a Kafka protocol, and transmitting the data in a binary or JSON data packet mode; and the nuclear power industry internet platform side receives the time sequence data and writes the time sequence data information obtained after analysis into the time sequence database center. The beneficial effects are that: (1) Before sensor data enter the edge server, the sensor data need to pass through a safety gatekeeper, so that the safety of data transmission is ensured.
Description
Technical Field
The invention belongs to a time sequence data real-time access method, and particularly relates to a time sequence data real-time access method for a nuclear power industrial Internet platform.
Background
In the nuclear power field, time series data (hereinafter referred to as time series data) are mainly data collected and generated by various types of real-time monitoring, checking and analyzing equipment in a nuclear power plant, and generally, the time series data mainly originate from a PI database, an on-site sensor and the like.
The nuclear power industry internet platform is characterized in that a sensing system of all elements is built in a unified nuclear power data standard system frame, an information island is opened, a service platform of nuclear power industry big data is built, on the basis, data of a nuclear power service system can be integrated and processed by accessing structured data, unstructured data and time sequence data, a unified data standard is built, multiple services such as equipment monitoring, fault diagnosis and fault prediction are supported, and real-time access of the time sequence data is an important content in the aspect of data access of the nuclear power industry internet platform.
When the edge data is accessed in real time, the current nuclear power industry internet platform supports the access by adopting the MQTT and the Kafka, the time sequence data is divided into common time sequence data and high-frequency time sequence data, and how to use the MQTT and the Kafka to access the two time sequence data efficiently has important influence on the construction of the nuclear power industry internet platform.
In order to effectively support real-time access of time sequence data, a reasonable time sequence data real-time access mechanism and method are required to be provided, and high efficiency, safety and reliability of data access are guaranteed.
Disclosure of Invention
The invention aims to provide a real-time access method for time sequence data of a nuclear power industrial Internet platform, which can effectively improve the efficiency of time sequence data access and ensure the safety and reliability of data access.
The technical scheme of the invention is as follows: a real-time access method for time sequence data of a nuclear power industrial Internet platform comprises the following steps:
step 1: collecting sensor data or PI system data, and transmitting the sensor data or PI system data to an entering edge server;
step 2: the edge server performs caching and data cleaning, data conversion, data frequency reduction, frequency reduction and data compression processing on the time sequence data;
step 3: accessing the processed data into an MQTT server or a Kafka of a nuclear power industrial Internet platform by using an MQTT protocol or a Kafka protocol, and transmitting the data in a binary or JSON data packet mode;
step 4: and the nuclear power industry internet platform side receives the time sequence data and writes the time sequence data information obtained after analysis into the time sequence database center.
The step 1 comprises the following steps:
step 11: the sensor collects equipment time sequence data from the field equipment, firstly, the data are transmitted to an edge gateway, and the edge gateway converts an industrial field protocol into an MQTT protocol;
step 12: the edge gateway transmits the data after protocol conversion to the safety gatekeeper;
step 13: the safety gatekeeper transmits the data to the edge server;
step 14: and if the time sequence data is acquired from the PI system, directly transmitting the acquired data to an edge server.
The industrial field protocol comprises ModBus, RS-232 and HART.
The step 2 comprises the following steps:
step 21: after receiving the time sequence data sent by the edge gateway, the edge server stores the original data in a local time sequence database;
step 22: performing data cleaning on the time sequence data, and designing cleaning rules according to the storage requirement of the central side time sequence data;
step 23: converting the name of the measuring point, and converting the name of the measuring point at the side of the power plant into the name of the measuring point on the nuclear power industrial Internet platform according to the name code of the measuring point at the side of the power plant and the name code mapping rule of the measuring point on the nuclear power industrial Internet platform;
step 24: performing frequency and dimension reduction processing on the time sequence data;
step 25: and compressing the time sequence data.
The step 22 includes the steps of:
step 221: determining the type of the measuring point according to the name of the measuring point in the time sequence data;
step 222: checking whether the measuring point data meets the requirement according to the reasonable value range of each type of measuring point; if the requirement is not met, step 224 is entered, otherwise, the subsequent inspection is continued;
step 223: checking whether the measurement point value is an invalid value or a null value, if the measurement point value is an invalid value or a null value, proceeding to step 224;
step 224: the abnormal condition of the measured point value is processed, if the data which exceeds the normal range and is unreasonable logically is found, the data is corrected or discarded; if the measured point value is found to be an invalid value or a null value, discarding the piece of data, and if the null value occurs, filling by using a default value.
The step 24 includes the steps of:
step 241: for high-frequency time sequence data, firstly, performing factory side calculation analysis processing in an edge server of a power plant side, and after the analysis processing is finished, transmitting a characteristic value or a result after the analysis processing to a nuclear power industry internet platform through an MQTT;
step 242: and (5) carrying out downsampling on the common time sequence data and then transmitting the downsampled common time sequence data.
Step 25 includes the following steps:
judging whether data transmitted to the nuclear power industrial Internet platform is required to be subjected to data compression processing according to the data scale and the actual condition of the commercial network bandwidth between the power plant side and the nuclear power industrial Internet platform data center side, if the transmitted data occupies more than 10% of the commercial network bandwidth, the data compression processing is required, and adopting a specific compression algorithm to compress, for example: gzip, snappy, zlib.
The step 3 comprises the following steps:
step 31: the edge server performs cleaning, conversion, dimension reduction and compression treatment on the time sequence data, and evaluates the condition of occupying bandwidth by data transmission according to the data scale after the treatment is completed;
step 32: if the occupied bandwidth is less than 10% of the commercial network bandwidth when the JSON data packet is adopted for transmission, adopting the JSON data packet mode for real-time data transmission;
step 33: if the JSON data packet is adopted for transmission, the occupied bandwidth is more than or equal to 10% of the bandwidth of the commercial network, and the binary data packet is adopted for real-time data transmission.
The step 4 comprises the following steps:
step 41: the time sequence data is accessed into an MQTT server at the platform side from the edge side;
step 42: if the data directly enter the MQTT server, the MQTT server is used as a message producer, and the data is written into the Kafka cluster;
step 43: the Flink program is used as a message consumer, receives the message in Kafka, and unpacks, decompresses, decodes and performs data standardization processing on the message after receiving the message;
step 44: if the processed data is high-frequency time sequence data, the processed data is written into the HBase database by using a Flink program, otherwise, the processed data is written into the platform side time sequence database.
The invention has the beneficial effects that:
(1) Before sensor data enter the edge server, the sensor data need to pass through a safety gatekeeper, so that the safety of data transmission is ensured;
(2) The edge server is adopted to carry out caching, cleaning, conversion, frequency reduction and compression treatment on the time sequence data, so that the quality of access data is ensured, and the access pressure of the time sequence data on the platform side is reduced;
(3) When the MQTT and the Kafka message are accessed in real time, the JSON format message structure can be adopted, the binary message structure can be adopted, and a user can select according to development efficiency and the condition of bandwidth from the edge side to the platform side.
Drawings
FIG. 1 is a flow of time series data collection and transmission to an edge server;
FIG. 2 is a process flow of processing time sequence data by an edge server;
FIG. 3 is a diagram of a data cleansing process performed on power plant side timing data;
FIG. 4 is a data down conversion process of power plant side time series data;
FIG. 5 is a flow chart of power plant side time series data transmitted to a platform in a binary or JSON data packet mode;
FIG. 6 is a flow chart of receiving time series data and writing the time series data into a database at the platform side.
Detailed Description
The invention will be described in further detail with reference to the accompanying drawings and specific examples.
The equipment in the nuclear power plant can generate a large amount of time sequence data in the operation process, special sensors are installed on some equipment, the sensors can acquire the time sequence data of the equipment in real time, and finally the time sequence data generated by the sensors can enter a nuclear power industry internet platform.
For high-frequency time sequence data, cleaning, conversion, dimension reduction and compression processing are required before the high-frequency time sequence data is uploaded to a nuclear power industry internet platform, and for common time sequence data such as PI system data, MQTT or Kafka can be directly adopted to access the platform.
The invention provides a real-time access method for time sequence data of a nuclear power industrial Internet platform, which comprises the following steps:
step 1: collecting sensor data or PI system data, and transmitting the sensor data or PI system data to an entering edge server;
as shown in fig. 1, the method mainly comprises the following steps:
step 11: the sensor collects device time sequence data from the field device, firstly, the data is transmitted to the edge gateway, and the edge gateway converts an industrial field protocol into an MQTT protocol, wherein the industrial field protocol comprises, but is not limited to, modBus, RS-232, HART and the like;
step 12: the edge gateway transmits the data after protocol conversion to the safety gatekeeper;
step 13: the safety gatekeeper transmits the data to the edge server;
step 14: and if the time sequence data is acquired from the PI system, directly transmitting the acquired data to an edge server.
Step 2: the edge server performs caching and data cleaning, data conversion, data frequency reduction, frequency reduction and data compression processing on the time sequence data;
as shown in fig. 2, the method mainly comprises the following steps:
step 21: after receiving the time sequence data sent by the edge gateway, the edge server stores the original data in a local time sequence database;
step 22: data cleaning is carried out on the time sequence data, and a cleaning rule with reasonable design is required according to the storage requirement of the time sequence data at the central side, for example: null processing, noise data processing, etc., the data cleaning process is as shown in fig. 3, and the cleaning process is as follows:
step 221: and determining the type of the measuring point according to the name of the measuring point in the time sequence data. Such as: the name of the measuring point comprises a common temperature measuring point with a letter of TMP, a common pressure measuring point with a letter of PT, and the like;
step 222: and checking whether the measuring point data meets the requirements according to the reasonable value range of each type of measuring point. Such as: for temperature type measuring points, the measuring point value cannot exceed the normal temperature range, for pressure and flow type measuring points, the measuring point value cannot be negative, if the requirements are not met, d) is entered, otherwise, the subsequent inspection is continued;
step 223: it is checked whether the measurement point value is an invalid value or a null value. During the process of uploading the measurement point data, there are some invalid values or null values, such as: the temperature type measuring point value is Chinese character or null, the measuring point quality value is null, and the like, if the measuring point value is an invalid value or null value, d) is entered, otherwise, the subsequent processing flow is carried out;
step 224: and (5) processing abnormal conditions of the measurement point values. If the data which is beyond the normal range and is unreasonable logically is found, correcting or discarding the data; if the measurement point value is found to be an invalid value or a null value, discarding the piece of data, and if the null value occurs, filling with a default value, such as: if the measurement point quality value is empty, the quality value is set to 0 (meeting the quality requirement) if the measurement point value is valid.
Step 23: converting the name of the measuring point, and converting the name of the measuring point at the power plant side into the name of the measuring point on the nuclear power industrial Internet platform according to the name coding mapping rule of the measuring point at the power plant side and the name coding mapping rule of the measuring point of the nuclear power industrial Internet platform, wherein the converting rule of the name of the measuring point is as follows:
the time sequence data measuring point codes of the nuclear power industrial Internet platform consist of power plant codes, separators and power plant side time sequence data measuring point codes;
sequential data station codes can only use letters, numbers and underlining, and can only start with letters;
the separator is underlined "_";
if the mapped time sequence data measuring point codesIn the presence of a middle score "-", the middle score needs to be replaced with an under score.
Character length limits of each part in the encoding of the time sequence data measuring points of the nuclear power industrial internet platform are shown in table 1:
table 1 Nuclear power industry Internet platform time sequence data measuring point code character string length limitation of each part
| Time sequence data measuring point coding component | Maximum length of character string |
| Power plant code | 2 |
| Power plant side measuring point code | 32 |
The corresponding information of the power plant name and the power plant code is shown in table 2.
TABLE 2 Power plant name and Power plant code correspondence table
The conversion examples of the power plant side measuring point and the nuclear power industry internet platform measuring point are as follows:
power plant: fuqing nuclear power
And (3) a unit: no. 5 machine set
And (3) power plant side measuring point coding: 5RCV002MI_WH01
The corresponding measurement point codes in the nuclear power industry internet platform should be: fq_5rcv002mi_wh01.
Step 24: and performing frequency and dimension reduction processing on the time sequence data. In terms of data dimension reduction, specific data dimension reduction algorithms are used, such as: the principal component analysis algorithm, the local linear embedding algorithm and the like map data points in the original high-dimensional space into the low-dimensional space, redundant information and noise information are reduced, and the scale of the data is reduced. In terms of data frequency reduction, the high-frequency time sequence data and the common time sequence data are respectively processed, the data frequency reduction processing mode is shown in fig. 4, and the processing mode is as follows:
step 241: for the high-frequency time sequence data, firstly, factory side calculation analysis processing is carried out in an edge server of a power plant side, and after the analysis processing is finished, the characteristic value or a result after the analysis processing is transmitted to a nuclear power industry Internet platform through an MQTT. For example, for equipment vibration data, only the calculated characteristic value and the spectrum analysis result are transmitted;
step 242: and (5) carrying out downsampling on the common time sequence data and then transmitting the downsampled common time sequence data. For example, for data in PI systems, the data may be downsampled to the minute level for transmission, as required by the service.
Step 25: and compressing the time sequence data. Judging whether data transmitted to the nuclear power industrial Internet platform is required to be subjected to data compression processing according to the data scale and the actual condition of the commercial network bandwidth between the power plant side and the nuclear power industrial Internet platform data center side, and if the transmission data occupy more than 10% of the commercial network bandwidth, the data compression processing is required. Compression may be performed using a specific compression algorithm, such as: gzip, snappy, zlib, etc.
Step 3: accessing the processed data into an MQTT server or a Kafka of a nuclear power industrial Internet platform by using an MQTT protocol or a Kafka protocol, and transmitting the data in a binary or JSON data packet mode;
as shown in fig. 5, the method mainly comprises the following steps:
step 31: the edge server performs cleaning, conversion, dimension reduction and compression treatment on the time sequence data, and evaluates the condition of occupying bandwidth by data transmission according to the data scale after the treatment is completed;
step 32: if the occupied bandwidth is less than 10% of the commercial network bandwidth when the JSON data packet is adopted for transmission, the JSON data packet mode can be adopted for real-time data transmission;
step 33: if the JSON data packet is adopted for transmission, the occupied bandwidth is more than or equal to 10% of the bandwidth of the commercial network, and the binary data packet is adopted for real-time data transmission.
Step 4: and the nuclear power industry internet platform side receives the time sequence data and writes the time sequence data information obtained after analysis into the time sequence database center.
As shown in fig. 6, mainly comprises the following steps:
step 41: the time sequence data is accessed into an MQTT server at the platform side from the edge side;
step 42: if the data directly enter the MQTT server, the MQTT server is used as a message producer, and the data is written into the Kafka cluster;
step 43: the Flink program is used as a message consumer, receives the message in Kafka, and unpacks, decompresses, decodes and performs data standardization processing on the message after receiving the message;
step 44: if the processed data is high-frequency time sequence data, the processed data is written into the HBase database by using a Flink program, otherwise, the processed data is written into the platform side time sequence database.
The main advantages of the invention are as follows:
the invention considers two scenes of high-frequency time sequence data access and common time sequence data access in time sequence data, and establishes corresponding access modes aiming at different time sequence data types;
before entering the edge server, the edge gateway data needs to pass through a unidirectional gateway, so that the safety of data transmission can be effectively ensured;
aiming at the characteristic of larger scale of the high-frequency time sequence data, the calculation, the processing and the analysis of the high-frequency time sequence data are carried out in a power plant side edge server, and only the characteristic value and the analysis result are uploaded to a nuclear power industrial Internet platform, so that the occupation of bandwidth is further reduced;
when the time sequence data is accessed, JSON and binary data packets can be adopted, so that a user can select a proper data packet format by himself;
on one hand, the user can select a proper compression algorithm according to actual service demands; on the other hand, the occupancy rate of the network bandwidth during time sequence data transmission can be further reduced;
after the time sequence data is accessed to the nuclear power industrial internet platform, the operations of decompressing, unpacking and writing the data package into the database are automatically completed by the platform, and related development work is not needed.
Claims (5)
1. The real-time access method for the time sequence data of the nuclear power industrial Internet platform is characterized by comprising the following steps of:
step 1: collecting sensor data or PI system data, and transmitting the sensor data or PI system data to an entering edge server;
comprising the following steps:
step 11: the sensor collects equipment time sequence data from the field equipment, firstly, the data are transmitted to an edge gateway, and the edge gateway converts an industrial field protocol into an MQTT protocol;
step 12: the edge gateway transmits the data after protocol conversion to the safety gatekeeper;
step 13: the safety gatekeeper transmits the data to the edge server;
step 14: if the time sequence data is acquired from the PI system, the acquired data is directly transmitted to an edge server;
step 2: the edge server performs caching and data cleaning, data conversion, data frequency reduction, frequency reduction and data compression processing on the time sequence data;
comprising the following steps:
step 21: after receiving the time sequence data sent by the edge gateway, the edge server stores the original data in a local time sequence database;
step 22: performing data cleaning on the time sequence data, and designing cleaning rules according to the storage requirement of the central side time sequence data;
step 23: converting the name of the measuring point, and converting the name of the measuring point at the side of the power plant into the code of the measuring point on the nuclear power industrial Internet platform according to the code of the name of the measuring point at the side of the power plant and the code mapping rule of the name of the measuring point on the nuclear power industrial Internet platform;
step 24: performing frequency and dimension reduction processing on the time sequence data;
comprising the following steps:
step 241: for high-frequency time sequence data, firstly, performing factory side calculation analysis processing in an edge server of a power plant side, and after the analysis processing is finished, transmitting a characteristic value or a result after the analysis processing to a nuclear power industry internet platform through an MQTT;
step 242: for the common time sequence data, the down sampling is carried out and then the common time sequence data is transmitted;
step 25: compressing time sequence data;
step 3: accessing the processed data into an MQTT server or a Kafka of a nuclear power industrial Internet platform by using an MQTT protocol or a Kafka protocol, and transmitting the data in a binary or JSON data packet mode;
comprising the following steps:
step 31: the edge server performs cleaning, conversion, dimension reduction and compression treatment on the time sequence data, and evaluates the condition of occupying bandwidth by data transmission according to the data scale after the treatment is completed;
step 32: if the occupied bandwidth is less than 10% of the commercial network bandwidth when the JSON data packet is adopted for transmission, adopting the JSON data packet mode for real-time data transmission;
step 33: if the occupied bandwidth is more than or equal to 10% of the bandwidth of the commercial network when the JSON data packet is adopted for transmission, the binary data packet is adopted for real-time data transmission;
step 4: and the nuclear power industry internet platform side receives the time sequence data and writes the time sequence data information obtained after analysis into the time sequence database center.
2. The method for accessing the time sequence data of the nuclear power industry internet platform in real time according to claim 1, which is characterized in that: the industrial field protocol comprises ModBus, RS-232 and HART.
3. The method for accessing time series data of a nuclear power industrial internet platform according to claim 1, wherein the step 22 comprises the steps of:
step 221: determining the type of the measuring point according to the name of the measuring point in the time sequence data;
step 222: checking whether the measuring point data meets the requirement according to the reasonable value range of each type of measuring point; if the requirement is not met, step 224 is entered, otherwise, the subsequent inspection is continued;
step 223: checking whether the measurement point value is an invalid value or a null value, if the measurement point value is an invalid value or a null value, proceeding to step 224;
step 224: the abnormal condition of the measured point value is processed, if the data which exceeds the normal range and is unreasonable logically is found, the data is corrected or discarded; if the measured point value is found to be an invalid value or a null value, discarding the data, and if the null value occurs, filling by using a default value.
4. The method for accessing time series data of a nuclear power industrial internet platform according to claim 1, wherein the step 25 comprises the following steps:
judging whether data transmitted to the nuclear power industrial Internet platform is required to be subjected to data compression processing according to the data scale and the actual condition of the commercial network bandwidth between the power plant side and the nuclear power industrial Internet platform data center side, if the transmission data occupies more than 10% of the commercial network bandwidth, the data compression processing is required, and adopting a Gzip, snappy or zlib compression algorithm to compress.
5. The method for accessing the time sequence data of the internet platform of the nuclear power industry in real time according to claim 1, wherein the step 4 comprises the following steps:
step 41: the time sequence data is accessed into an MQTT server at the platform side from the edge side;
step 42: if the data directly enter the MQTT server, the MQTT server is used as a message producer, and the data is written into the Kafka cluster;
step 43: the Flink program is used as a message consumer, receives the message in Kafka, and unpacks, decompresses, decodes and performs data standardization processing on the message after receiving the message;
step 44: if the processed data is high-frequency time sequence data, the processed data is written into the HBase database by using a Flink program, otherwise, the processed data is written into the platform side time sequence database.
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