A data collection method and device, electronic equipment and medium

Abstract

The application discloses a data collection method and device, electronic equipment and medium, comprising: collecting system determines N first preset points according to N kinds of to-be-collected data types in data collection requirements, and collects real-time data; a data platform obtains the real-time data from the collecting system, stores the real-time data into a database according to a collection sequence, obtains N first data point clusters, determines N first actual performance data according to the N first data point clusters and a first preset configuration table, determines M actual performance data tables according to the N first actual performance data and a second preset configuration table, and sends the M actual performance data tables to a server for viewing by a client. The application collects real-time data through N first preset points, and can collect one or several types of data; the data platform is further provided with a preset configuration table, the obtained data is processed according to corresponding requirements in the preset configuration table, the data processing process is simplified, and time is saved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data collection, and in particular to a data collection method and device, electronic equipment and a medium. BACKGROUND

[0002] Flow production manufacturing enterprises produce various types of data in the process of production and manufacturing, which can usually be collected from programmable logic controllers in the form of electric text.

[0003] Flow production manufacturing enterprises produce a large amount of data in the process of production and manufacturing, and there are many types of data, and different types of data require different codes to implement data collection. When different types of data need to be collected, the electric text structure and the program code of the programmable logic controller need to be modified, which makes the data collection efficiency low. Therefore, how to improve the efficiency of data collection is a problem to be solved. SUMMARY

[0004] The embodiments of the present application provide a data collection method, device, electronic equipment and medium, which solve the technical problem of low efficiency of data collection in the prior art and achieve the technical effect of improving the efficiency of data collection.

[0005] In a first aspect, the present application provides a data collection method, which comprises:

[0006] The collection system for acquiring real-time data of the to-be-collected device determines N first preset points of the to-be-collected device according to N types of to-be-collected data in the data collection requirement, and collects real-time data corresponding to the N first preset points in a preset time period, the N types of to-be-collected data correspond one-to-one to the N first preset points, and N is a positive integer;

[0007] The data platform obtains the real-time data corresponding to the N first preset points from the collection system, and stores the real-time data of the N first preset points in the database according to the collection sequence to obtain N first data point clusters, the real-time data corresponding to the N first preset points and the N first data point clusters correspond one-to-one;

[0008] The data platform determines N first performance data according to the N first data point clusters and a first preset configuration table, the first preset configuration table includes processing requirements of the real-time data, and the N first data point clusters and the N first performance data correspond one-to-one;

[0009] The data platform determines M performance data tables according to the N first performance data and a second preset configuration table, and sends the M performance data tables to the server, the second preset configuration table includes processing requirements of the N first performance data, and M is a positive integer;

[0010] The server receives and stores the M pieces of performance data tables for the client to view.

[0011] Further, the method further comprises:

[0012] When the data acquisition requirement changes, the acquisition system determines Q second preset points of the to-be-acquired device according to Q types of to-be-acquired data in the changed data acquisition requirement, and acquires real-time data corresponding to the Q second preset points in a preset time period, the Q types of to-be-acquired data correspond to the Q second preset points in a one-to-one manner, and Q is a positive integer.

[0013] The data platform obtains the real-time data corresponding to the Q second preset points from the acquisition system, and stores the real-time data of the Q second preset points in the database according to the acquisition sequence to obtain Q second data point clusters, the real-time data corresponding to the Q second preset points correspond to the Q second data point clusters in a one-to-one manner.

[0014] The first preset configuration table is updated according to the Q types of to-be-acquired data, and an updated first preset configuration table is obtained.

[0015] The data platform determines Q second performance data according to the Q second data point clusters and the updated first preset configuration table, the Q second data point clusters correspond to the Q second performance data in a one-to-one manner.

[0016] The second preset configuration table is updated according to the changed data acquisition requirement, and an updated second preset configuration table is obtained.

[0017] The data platform determines P pieces of performance data tables according to the Q second performance data and the updated second preset configuration table, and sends the P pieces of performance data tables to the server, and P is a positive integer.

[0018] The server receives and stores the P pieces of performance data tables for the client to view.

[0019] Further, the method comprises:

[0020] The client sends a query request.

[0021] The server receives the query request, determines W pieces of performance data tables according to the query request, and packs the W pieces of performance data tables as a query result, and W is a positive integer less than or equal to M.

[0022] The server returns the query result to the client, so that the client displays the query result.

[0023] Further, the method comprises:

[0024] The client sends a login request to the server.

[0025] The server receives and verifies the login request, and generates a verification result, and the server returns the verification result to the client;

[0026] The client determines whether to interact with the server according to the received verification result.

[0027] Further, the method comprises:

[0028] The real-time data is respectively added with a time stamp;

[0029] After the data platform obtains the real-time data, it is judged that the time interval between the time stamp in the real-time data and the current time;

[0030] According to the preset response time and the time interval, the network transmission state between the data platform and the system of the to-be-collected device is determined.

[0031] Further, before the collection system for obtaining real-time data of the to-be-collected device determines N first preset points of the to-be-collected device according to N types of to-be-collected data types in the data collection requirement, the method further comprises:

[0032] The collection system and the data platform are connected to the preset network according to the preset network configuration;

[0033] The system of the to-be-collected device in the preset network matches with the data platform according to the preset protocol.

[0034] Further, the data platform obtains the real-time data corresponding to the N first preset points from the collection system, comprising:

[0035] It is judged whether the real-time data meets the firewall policy;

[0036] If the real-time data meets the firewall policy, the real-time data is transmitted to the data platform;

[0037] If the real-time data does not meet the firewall policy, the real-time data is discarded.

[0038] In a second aspect, the application provides a data collection device, comprising:

[0039] A real-time data acquisition module, through a collection system for obtaining real-time data of a to-be-collected device, determines N first preset points of the to-be-collected device according to N types of to-be-collected data types in the data collection requirement, and collects real-time data corresponding to the N first preset points in a preset time period, the N types of to-be-collected data types correspond one-to-one to the N first preset points, and N is a positive integer;

[0040] The first data point cluster determination module is configured to obtain, by the data platform, real-time data corresponding to N first preset point positions from the collection system, store the real-time data of the N first preset point positions in the database according to the collection sequence, and obtain N first data point clusters, wherein the real-time data corresponding to the N first preset point positions and the N first data point clusters are in one-to-one correspondence.

[0041] The first performance data determination module is configured to determine, by the data platform, N first performance data according to the N first data point clusters and a first preset configuration table, wherein the first preset configuration table includes processing requirements of the real-time data, and the N first data point clusters and the N first performance data are in one-to-one correspondence.

[0042] The performance data table determination module is configured to determine, by the data platform, M performance data tables according to the N first performance data and a second preset configuration table, and send the M performance data tables to the server, wherein the second preset configuration table includes processing requirements of the N first performance data, and M is a positive integer.

[0043] The viewing module is configured to receive and store, by the server, the M performance data tables for the client to view.

[0044] In a third aspect, the present application provides an electronic device, comprising:

[0045] a processor;

[0046] a memory for storing processor-executable instructions;

[0047] The processor is configured to execute to implement the data collection method provided in the first aspect.

[0048] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by the processor of the electronic device, the electronic device can execute the data collection method provided in the first aspect.

[0049] The one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0050] The application determines N first preset points in the to-be-collected device according to N types of to-be-collected data, and the collection system collects real-time data of the to-be-collected device through the N first preset points and transmits the real-time data to a data platform, so that N first data point clusters can be obtained. The data platform can obtain N first actual performance data according to the N first data point clusters and a first preset configuration table. The data platform can finally obtain M actual performance data tables according to the N first actual performance data and a second preset configuration table, for relevant personnel to view. The application collects real-time data through the N first preset points, can collect one or several types of data, and is simpler to operate, so that the collection efficiency is improved. Compared with the current method of processing real-time data through a large amount of code to obtain a final actual performance data table, the application also simplifies the data processing process and saves time by presetting a configuration table in the data platform and processing the obtained data according to the corresponding requirements in the preset configuration table, which is equivalent to improving the collection efficiency.

[0051] The application also determines Q second preset points according to Q types of to-be-collected data in the changed data collection requirement, and the collection system transmits real-time data of the Q second preset points to the data platform, so that Q second data point clusters can be obtained. The data platform updates the preset configuration table according to the changed data collection requirement to obtain an updated preset configuration table. The data platform can obtain Q second actual performance data according to the Q second data point clusters and the updated preset configuration table. The data platform can finally obtain P actual performance data tables according to the Q second actual performance data and the updated preset configuration table to meet the changed data collection requirement. Compared with the method of modifying the text structure and the program code of the programmable logic controller, the application can meet the changed data collection requirement by changing the preset points and updating the preset configuration table according to the changed requirement. Changing the preset points and updating the preset configuration table according to the changed requirement to realize data collection is not only simple in operation, but also simplifies the data collection process after the collection requirement changes, saves time, and improves the collection efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0053] Figure 1 A flowchart of a data collection method provided by the application;

[0054] Figure 2 AFigure 3 A top view of preset points of the device to be collected 5;

[0055] Figure 3 A structural schematic diagram of a process control system provided by the present application;

[0056] Figure 4 A schematic diagram of a first data point cluster provided by the present application;

[0057] Figure 5 A structural schematic diagram of a data collection device provided by the present application;

[0058] Figure 6 A structural schematic diagram of an electronic device provided by the present application.

[0059] Reference signs:

[0060] 1 - collection system, 2 - real-time data platform, 3 - process control system server, 4 - client, 5 - device to be collected, 6 - temperature preset point, 7 - pressure preset point, 8 - humidity preset point, 9 - flow rate preset point, 10 - temperature first data point cluster, 11 - pressure first data point cluster. DETAILED DESCRIPTION

[0061] The embodiment of the present application provides a data collection method, and solves the technical problem of low efficiency of data collection in the prior art.

[0062] To solve the above technical problem, the technical scheme of the embodiment of the present application is as follows:

[0063] A data collection method, the method comprising: a collection system for acquiring real-time data of a device to be collected determining N first preset points of the device to be collected according to N types of data to be collected in a data collection requirement, and collecting real-time data corresponding to the N first preset points in a preset time period, the N types of data to be collected corresponding to the N first preset points in a one-to-one manner, and N being a positive integer; a data platform obtaining the real-time data corresponding to the N first preset points from the collection system, and storing the real-time data of the N first preset points in a database according to a collection sequence to obtain N first data point clusters, the real-time data corresponding to the N first preset points corresponding to the N first data point clusters in a one-to-one manner; the data platform determining N first performance data according to the N first data point clusters and a first preset configuration table, the first preset configuration table including processing requirements of the real-time data, the N first data point clusters corresponding to the N first performance data in a one-to-one manner; the data platform determining M performance data tables according to the N first performance data and a second preset configuration table, and sending the M performance data tables to a server, the second preset configuration table including processing requirements of the N first performance data, and M being a positive integer; and the server receiving and storing the M performance data tables for a client to view.

[0064] The application determines N first preset points in the to-be-collected device according to N types of to-be-collected data, and the collection system collects real-time data of the to-be-collected device through the N first preset points and transmits the real-time data to the data platform, so that N first data point clusters can be obtained. The data platform can obtain N first actual performance data according to the N first data point clusters and a first preset configuration table. The data platform can finally obtain M actual performance data tables according to the N first actual performance data and a second preset configuration table, so as to be viewed by relevant personnel. The application collects real-time data through the N first preset points, can collect one or several types of data, and is more simple to operate, and therefore improves the collection efficiency. Compared with the current method of processing real-time data through a large amount of code to obtain a final actual performance data table, the application further presets a configuration table in the data platform, processes the obtained data according to the corresponding requirements in the preset configuration table, simplifies the data processing process, saves time, and improves the collection efficiency.

[0065] The application further determines Q second preset points according to Q types of to-be-collected data in the changed data collection requirement, and the collection system transmits real-time data of the Q second preset points to the data platform, so that Q second data point clusters can be obtained. The data platform updates the preset configuration table according to the changed data collection requirement, and obtains an updated preset configuration table. The data platform can obtain Q second actual performance data according to the Q second data point clusters and the updated preset configuration table. The data platform can finally obtain P actual performance data tables according to the Q second actual performance data and the updated preset configuration table, so as to meet the changed data collection requirement. Compared with the method of modifying the electric text structure and the program code of the programmable logic controller, the application can meet the changed data collection requirement by changing the preset points and updating the preset configuration table according to the changed requirement. Changing the preset points and updating the preset configuration table according to the changed requirement to realize data collection is not only simple in operation mode, but also simplifies the data collection process after the collection requirement changes, saves time, and improves the collection efficiency.

[0066] In order to better understand the above technical solutions, the above technical solutions will be described in detail in combination with the drawings in the specification and specific embodiments.

[0067] Firstly, the term "and / or" appearing in the present text is only to describe the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of existence of A alone, existence of A and B, and existence of B alone. In addition, the character " / " in the present text generally represents an "or" relationship between the front and rear associated objects.

[0068] The application provides a data acquisition method as shown in Figure 1 The application provides a process control system as shown in Figure 3 The application provides a process control system as shown in Figure 3 The application provides a process control system as shown in

[0069] The application provides a process control system as shown in Figure 3 The application provides a process control system as shown in Figure 3 The application provides a process control system as shown in Figure 3 The application provides a process control system as shown in Figure 3 The application provides a process control system as shown in

[0070] The application provides a process control system as shown in

[0071] The application provides a process control system as shown in

[0072] The application provides a data acquisition method as shown in Figure 1 The application provides a data acquisition method as shown in

[0073] The application provides a data acquisition method as shown in

[0074] In step S12, the data platform obtains real-time data corresponding to N first preset points from the acquisition system, and stores the real-time data of the N first preset points into the database according to the acquisition order to obtain N first data point clusters. The real-time data corresponding to the N first preset points corresponds one-to-one with the N first data point clusters.

[0075] Step S13: The data platform determines N first performance data based on the N first data point clusters and the first preset configuration table. The first preset configuration table includes the processing requirements for real-time data, and the N first data point clusters correspond one-to-one with the N first performance data.

[0076] Step S14: The data platform determines M performance data tables based on N first performance data and the second preset configuration table, and sends the M performance data tables to the server. The second preset configuration table includes the processing requirements of N first performance data, where M is a positive integer.

[0077] Step S15: The server receives and stores M performance data tables for the client to view.

[0078] Before executing step S11, the acquisition system and data platform used to acquire real-time data from the device to be acquired can be connected to a preset network according to a preset network configuration, and the acquisition system and data platform can be matched in the preset network according to a preset protocol.

[0079] For example, before performing step S11, the following can be done: Figure 3 The data acquisition system 1 and real-time data platform 2 shown are connected to the process control system network according to a preset network configuration. Within the process control system network, data acquisition system 1 and real-time data platform 2 are matched according to a preset protocol. This preset protocol can be a communication protocol or other protocols; no restrictions are placed here. After the data acquisition system 1 and real-time data platform 2 are matched, real-time data platform 2 can acquire real-time data from data acquisition system 1.

[0080] Regarding step S11, the acquisition system for acquiring real-time data of the device to be acquired determines N first preset points of the device to be acquired based on the N types of data to be acquired in the data acquisition requirements, and acquires the real-time data corresponding to the N first preset points within a preset time period. The N types of data to be acquired correspond one-to-one with the N first preset points, and N is a positive integer.

[0081] The data acquisition system is used to obtain the process parameters of the equipment to be acquired and convert them into real-time data. The N types of data to be acquired in the data acquisition requirements can be temperature, pressure, humidity, flow rate, etc. The data acquisition requirements can include only one type of data or multiple types, depending on the actual needs.

[0082] After determining the type of data to be collected, the first preset point corresponding to the type of data to be collected in the device to be collected is determined according to the type of data to be collected. The preset time can be 1h, 2h, 12h or 24h, etc., which can be selected according to actual needs.

[0083] For example, Figure 2 For Figure 3 The preset point of the device to be collected 5 is shown in the top view, the temperature preset point 6 is used to collect temperature, the pressure preset point 7 is used to collect pressure, the humidity preset point 8 is used to collect humidity, and the flow rate preset point 9 is used to collect flow rate. If the type of data to be collected is temperature and pressure, and the preset time is 24h, then the temperature preset point 6 and the pressure preset point 7 are determined as the first preset point, and the temperature preset point 6 and the pressure preset point 7 collect temperature real-time data and pressure real-time data respectively within 24h.

[0084] Regarding step S12, the data platform obtains the real-time data corresponding to the N first preset points from the collection system, and stores the real-time data of the N first preset points in the database according to the collection order, to obtain N first data point clusters. The real-time data corresponding to the N first preset points correspond one-to-one to the N first data point clusters.

[0085] The data platform can be a big data resource platform, a data lake, and a data mart, etc. The database is located in the data platform. It should be noted that the real-time data collected by each first preset point within the preset time corresponds to a first data point cluster in the data platform (database).

[0086] For example, the type of data to be collected is temperature and pressure, and the preset time is 24h. As shown in Figure 3 , the real-time data platform 2 obtains the temperature real-time data and the pressure real-time data within 24h from the temperature preset point 6 and the pressure preset point 7 respectively. The real-time data platform 2 stores the temperature real-time data and the pressure real-time data in the database according to the order of collection (as shown in Figure 2 , A-B-C-D-E-…-L are obtained in turn), to obtain the temperature first data point cluster 10 as shown on the left side of Figure 4 ; and the real-time data platform 2 stores the pressure real-time data in the database according to the order of collection, to obtain the pressure first data point cluster 11 as shown on the right side of Figure 4 . Figure 4 The "left side" and "right side" in Figure 4 are relative to the top, bottom, left and right of Figure 4 .

[0087] Furthermore, when the acquisition system transmits real-time data to the data platform (database), timestamps can be added to the real-time data. After the data platform obtains the real-time data, it determines the time interval between the timestamp in the real-time data and the current time. Based on the preset response time and time interval, it determines the network transmission status between the data platform and the system of the device to be acquired.

[0088] For example, such as Figure 3 The acquisition system 1 shown on the left ( Figure 3 The "left side" in the text refers to... Figure 3 In terms of up, down, left, and right (referring to the surrounding environment), the acquisition system 1 uses methods such as... Figure 2 The first preset point 6 shown is used to collect real-time temperature data of the device to be collected within 24 hours.

[0089] Real-time temperature data and timestamps can be combined in the following ways:

[0090] Real-time temperature data #timestamp

[0091] For example: 1234#1645607642, the 1234 before the # symbol is the real-time temperature data collected within 24 hours at the first preset point 6, and the 1645607642 after the # symbol is the timestamp.

[0092] The time interval is determined based on the added timestamp 1645607642 and the time when the real-time data platform 2 receives the timestamp 1645607642. Based on the time interval and the preset response time, the transmission status of the network corresponding to the real-time data platform 2 and the acquisition system 1 is determined. If the time interval is less than the preset response time, it indicates that the transmission status of the network corresponding to the real-time data platform 2 and the acquisition system 1 is normal. If the time interval is greater than the preset response time, it indicates that the transmission status of the network corresponding to the real-time data platform 2 and the acquisition system 1 is abnormal. The relevant responsible persons can check the network transmission status of the network corresponding to the real-time data platform 2 and the acquisition system 1.

[0093] Furthermore, firewall policies can be configured between the data platform and the acquisition system to ensure that the real-time data acquired by the data platform is secure (i.e., the real-time data does not contain Trojans, viruses, etc.). The specific methods are as follows:

[0094] During the process of the acquisition system transmitting real-time data corresponding to N first preset points to the data platform, it is determined whether the real-time data meets the firewall policy.

[0095] If the real-time data meets the firewall policy, the real-time data will be transmitted to the data platform.

[0096] If real-time data does not meet the firewall policy, the real-time data will be discarded.

[0097] For example, as Figure 3 The left shown collection system 1 in the transmission of real-time data to real-time data platform 2, determine whether the collection system 1 transmission of real-time data to meet the firewall policy.

[0098] If the firewall policy is met, the data platform 2 receives the collection system 1 transmission of real-time data;

[0099] If the firewall policy is not met, the data platform 2 does not receive the collection system 1 transmission of real-time data, and sends an alarm to the relevant personnel.

[0100] Regarding step S13, the data platform determines N first performance data according to N first data point clusters and a first preset configuration table, the first preset configuration table includes the processing requirement of real-time data, and the N first data point clusters correspond to the N first performance data one by one.

[0101] The first preset configuration table includes the processing requirement of real-time data, and the processing requirement can be average value, extreme value or difference value, etc.

[0102] For example, when the first data point cluster is composed of temperature real-time data with a preset time of 24h, the processing requirement of temperature real-time data in the corresponding first preset configuration table can include one or more of the following requirements:

[0103] Determine the average temperature in the preset time;

[0104] Determine the maximum temperature difference in the preset time;

[0105] Determine the highest temperature per hour in the preset time;

[0106] Determine the lowest temperature per hour in the preset time.

[0107] The processing requirement of real-time data contained in the first preset configuration table can also be determined according to actual conditions, which is not limited here.

[0108] The first performance data obtained by processing the real-time data in the first data point cluster according to the corresponding processing requirement of real-time data in the first preset configuration table (i.e. average value, extreme value or difference value, etc.).

[0109] It should be noted that no matter whether the processing requirement of a certain type of real-time data in the first preset configuration table is one or more, the first performance data corresponding to the type of real-time data is ultimately obtained.

[0110] For example, the first data point cluster is composed of temperature real-time data with a preset time of 24 hours, and the processing requirements of the temperature real-time data in the first preset configuration table are “determining the average temperature in the preset time” and “determining the maximum difference of the temperature in the preset time”. After the data platform determines the average temperature in 24 hours and the maximum difference of the temperature in 24 hours according to the temperature real-time data in 24 hours, the “average temperature” and “maximum difference of the temperature” are packaged as the first performance data of the temperature.

[0111] Regarding step S14, the data platform determines M performance data tables according to the N first performance data and a second preset configuration table, and sends the M performance data tables to the server. The second preset configuration table includes the processing requirements of the N first performance data, and M is a positive integer.

[0112] After obtaining the N first performance data, the data platform processes the N first performance data according to the second preset configuration table. The second preset configuration table includes the processing requirements of the N first performance data, which can include the storage location of the data in the server and the data packaging rules, etc.

[0113] For example, the data platform has obtained the first performance data of the temperature, the first performance data of the pressure, and the first performance data of the humidity. The processing requirements of the above-mentioned three kinds of first performance data in the second preset configuration table can include:

[0114] (1) packaging the first performance data of the temperature into a performance data table R, and determining the storage location of the performance data table R in the server;

[0115] (2) combining the first performance data of the temperature and the first performance data of the pressure to obtain a performance data table S, and determining the storage location of the performance data table S in the server;

[0116] (3) combining the first performance data of the temperature, the first performance data of the pressure, and the first performance data of the humidity to obtain a performance data table T, and determining the storage location of the performance data table T in the server.

[0117] The processing requirements of the first performance data contained in the second preset configuration table can also be determined according to actual conditions, which is not limited here.

[0118] The N first performance data can be processed according to the processing requirements in the second preset configuration table to obtain M performance data tables, and the data platform can send the M performance data tables to the corresponding server.

[0119] Regarding step S15, the server receives and stores the M performance data tables for the client to view.

[0120] After receiving the corresponding performance data table, the server can display it on the client for relevant personnel to view. The specific method is as follows:

[0121] The client sends a query request;

[0122] The server receives a query request, determines W performance data tables based on the query request, and packages the W performance data tables into a query result, where W is a positive integer less than or equal to M.

[0123] The server returns the query results to the client so that the client can display the results.

[0124] For example, taking the aforementioned performance data tables R, S, and T as examples, such as... Figure 3 The client 4 sends a query request to the process control system server 3. The query request includes a request to view the performance data table 1 and the performance data table 2. The process control system server 3 responds to the query request, packages the performance data table 1 and the performance data table 2 into a query result, and returns the query result to the client 4 so that the client 4 can display the query result.

[0125] Furthermore, to prevent performance data from being leaked to unauthorized personnel, security can be improved through the following methods.

[0126] The client sends a login request to the server;

[0127] The server receives and verifies the login request, generates a verification result, and returns the verification result to the client.

[0128] The client determines whether it can interact with the server based on the received verification result.

[0129] For example, such as Figure 3 The client 4 shown sends a login request to the process control system server 3, wherein the login request can be obtained by the client 4 entering user identity credentials (such as username and password) in a package.

[0130] The process control system server 3 verifies the legitimacy of the login request based on pre-stored user credentials. If the login request is legitimate, the verification result is "verification passed"; if the login request is illegitimate, the verification result is "verification failed". The process control system server 3 returns the verification result, i.e., "verification passed" or "verification failed", to the client 4.

[0131] When the verification result is "verification passed", it means that the username and password stored in the process control system server 3 can match, and the client 4 can send a query request to the process control system server 3; when the verification result is "verification failed", it means that the username and password stored in the process control system server 3 do not match, and the client 4 cannot send a query request to the process control system server 3.

[0132] In summary, according to the N types of data to be collected, the application determines N first preset points in the device to be collected. The collection system collects real-time data of the device to be collected through the N first preset points and transmits the real-time data to the data platform. Then, the N first data point clusters can be obtained. According to the N first data point clusters and the first preset configuration table, the data platform can obtain N first performance data. According to the N first performance data and the second preset configuration table, the data platform can finally obtain M performance data tables for relevant personnel to view. The application collects real-time data through N first preset points, which can collect one or several types of data, and the operation is simpler, thereby improving the collection efficiency. Compared with the current method of processing real-time data through a large number of codes to obtain the final performance data table, the application also simplifies the data processing process by presetting the configuration table in the data platform and processing the obtained data according to the corresponding requirements in the preset configuration table, thereby saving time and improving the collection efficiency.

[0133] After steps S11-S15 are performed, the current data collection requirement can be met. When the data collection requirement changes, steps S16-S22 can be performed to meet the changed data collection requirement.

[0134] It should be noted that steps S11-S15 are similar to steps S16-S22. The similar parts can be referred to steps S11-S15, and only the different parts of steps S11-S15 and steps S16-S22 will be described below.

[0135] Step S16, when the data collection requirement changes, the collection system determines Q second preset points of the device to be collected according to Q types of data to be collected in the changed data collection requirement, and collects real-time data corresponding to the Q second preset points in a preset time period. The Q types of data to be collected correspond to the Q second preset points one by one, and Q is a positive integer.

[0136] Step S17, the data platform obtains the real-time data corresponding to the Q second preset points from the collection system, and stores the real-time data of the Q second preset points in the database according to the collection order to obtain Q second data point clusters. The real-time data corresponding to the Q second preset points and the Q second data point clusters correspond to each other one by one.

[0137] Step S18, updating the first preset configuration table according to the Q types of data to be collected, to obtain an updated first preset configuration table.

[0138] Step S19, the data platform determines Q second performance data according to the Q second data point clusters and the updated first preset configuration table, and the Q second data point clusters and the Q second performance data correspond one by one.

[0139] Step S20, updating the second preset configuration table according to the changed data collection requirements, to obtain an updated second preset configuration table.

[0140] Step S21, the data platform determines P performance data tables according to the Q second performance data and the updated second preset configuration table, and sends the P performance data tables to the server, P being a positive integer.

[0141] Step S22, the server receives and stores the P performance data tables for the client to view.

[0142] Before step S16 is performed, it is necessary to determine whether the Q types of data to be collected in the changed data collection requirements are the same as the N types of data to be collected before the change, if the Q types of data to be collected are the same as the N types of data to be collected, then step S17 is directly executed; if the Q types of data to be collected are completely different or partially different from the N types of data to be collected, then step S16 is executed.

[0143] Regarding step S16, when the data collection requirements change, the collection system determines Q second preset points of the collection device according to the Q types of data to be collected in the changed data collection requirements, and collects real-time data corresponding to the Q second preset points in a preset time period, the Q types of data to be collected correspond one by one to the Q second preset points, and Q is a positive integer.

[0144] The Q types of data to be collected in the changed data collection requirements can be one type of data to be collected, or multiple types of data to be collected. The Q types of data to be collected can be partially the same as the above-mentioned N types of data to be collected. The collection system can determine the Q second preset points in the collection device according to the Q types of data to be collected.

[0145] For example, as Figure 2As shown, temperature preset point 6 is used to collect temperature, pressure preset point 7 is used to collect pressure, humidity preset point 8 is used to collect humidity, and flow preset point 9 is used to collect flow rate. The initial data collection requirements specify temperature and pressure as the data types to be collected, corresponding to temperature preset point 6 and pressure preset point 7. If the data collection requirements change, and the data types to be collected in the changed requirements are humidity and flow rate, then the corresponding second preset points are humidity preset point 8 and flow rate preset point 9, respectively.

[0146] Regarding step S17, the data platform obtains real-time data corresponding to Q second preset points from the acquisition system, and stores the real-time data of the Q second preset points into the database according to the acquisition order to obtain a cluster of Q second data points. The real-time data corresponding to the Q second preset points corresponds one-to-one with the cluster of Q second data points.

[0147] The revised data collection requirements described above will be explained using humidity and flow rate as the data types to be collected:

[0148] like Figure 2 As shown, the data platform collects real-time data from preset humidity point 8 and preset flow rate point 9 within a preset time period, and stores them in the database according to the collection order to obtain the second data point cluster of humidity and the second data point cluster of flow rate.

[0149] Regarding step S18, the first preset configuration table is updated according to the Q types of data to be collected, resulting in the updated first preset configuration table.

[0150] Similarly, let's take the data types to be collected in the revised data collection requirements as humidity and flow rate as an example:

[0151] The data platform updates the first preset configuration table according to the processing requirements of the two types of data to be collected, namely humidity and flow rate, to obtain the updated first preset configuration table.

[0152] Regarding step S19, the data platform determines Q second performance data based on the Q second data point clusters and the updated first preset configuration table, with each of the Q second data point clusters corresponding to one of the Q second performance data.

[0153] Similarly, let's take the data types to be collected in the revised data collection requirements as humidity and flow rate as an example:

[0154] The data platform obtains the second humidity data based on the humidity second data point cluster and the corresponding processing requirements in the first preset configuration table;

[0155] The data platform obtains the second actual data of the flow rate based on the second data point cluster of the flow rate and the corresponding processing requirements in the first preset configuration table.

[0156] As for step S20, the second preset configuration table is updated according to the changed data collection requirement, to obtain an updated second preset configuration table.

[0157] When the data collection requirement changes, it means that the final performance data table needs to be changed. Specifically, the second preset configuration table can be updated according to the changed data collection requirement.

[0158] For example, the initial data collection requirement is to combine the temperature first performance data and the pressure first performance data to obtain the performance data table 2, and to determine the storage location of the performance data table 2 in the server.

[0159] The current data collection requirement is to combine the humidity first performance data and the flow rate first performance data to obtain the performance data table U, and to determine the storage location of the performance data table U in the server.

[0160] The second preset configuration table can be updated according to the above current data collection requirement to obtain an updated second preset configuration table.

[0161] As for step S21, the data platform determines P performance data tables according to the Q second performance data and the updated second preset configuration table, and sends the P performance data tables to the server, where P is a positive integer.

[0162] Step S21 is similar to step S14, and specific reference can be made to the description of step S14.

[0163] As for step S22, the server receives and stores the P performance data tables for the client to view.

[0164] Step S22 is similar to step S15, and specific reference can be made to the description of step S15.

[0165] In summary, the application also determines Q second preset points according to Q types of data to be collected in the changed data collection requirement, and the real-time data of the Q second preset points is transmitted to the data platform by the collection system, so that Q second data point clusters can be obtained. The data platform updates the preset configuration table according to the changed data collection requirement to obtain an updated preset configuration table. The data platform can obtain Q second performance data according to the Q second data point clusters and the updated preset configuration table, and can finally obtain P performance data tables according to the Q second performance data and the updated preset configuration table to meet the changed data collection requirement. When the data collection requirement changes, compared with the method of modifying the electric text structure and the program code of the programmable logic controller, the application can meet the changed data collection requirement by changing the preset points and updating the preset configuration table according to the changed requirement. Changing the preset points and updating the preset configuration table according to the changed requirement to realize data collection not only has a simple operation mode, but also simplifies the process of data collection after the collection requirement changes, saves time, and improves collection efficiency.

[0166] Based on the same inventive concept, the application also provides a data collection device as shown in Figure 5 The device comprises:

[0167] The real-time data acquisition module 51 determines N first preset points of the device to be collected by the collection system for acquiring real-time data of the device to be collected according to N types of data to be collected in the data collection requirement, and acquires real-time data corresponding to the N first preset points in a preset time period, the N types of data to be collected correspond to the N first preset points one by one, and N is a positive integer;

[0168] The first data point cluster determination module 52 is configured to obtain the real-time data corresponding to the N first preset points from the collection system by the data platform, and store the real-time data of the N first preset points in the database according to the collection sequence to obtain N first data point clusters, the real-time data corresponding to the N first preset points and the N first data point clusters correspond to each other one by one;

[0169] The first performance data determination module 53 is configured to determine N first performance data according to the N first data point clusters and the first preset configuration table by the data platform, the first preset configuration table includes processing requirements of the real-time data, and the N first data point clusters and the N first performance data correspond to each other one by one;

[0170] The performance data table determination module 54 is configured to determine M performance data tables according to the N first performance data and the second preset configuration table by the data platform, and send the M performance data tables to the server, the second preset configuration table includes processing requirements of the N first performance data, and M is a positive integer;

[0171] A viewing module 55 is configured to receive and store the M performance data tables by the server for the client to view.

[0172] Further, the device further comprises:

[0173] A second preset point determination sub-module is configured to determine Q second preset points of the to-be-collected device according to Q to-be-collected data types in the changed data collection requirement when the data collection requirement changes, and collect real-time data corresponding to the Q second preset points in a preset time period, the Q to-be-collected data types and the Q second preset points are in one-to-one correspondence, and Q is a positive integer.

[0174] A Q-second-data-point cluster determination sub-module is configured to obtain the real-time data corresponding to the Q second preset points from the collection system, and store the real-time data of the Q second preset points in the database according to the collection sequence to obtain Q second data point clusters, the real-time data corresponding to the Q second preset points and the Q second data point clusters are in one-to-one correspondence.

[0175] A first preset configuration table updating sub-module is configured to update the first preset configuration table according to the Q to-be-collected data types to obtain an updated first preset configuration table.

[0176] A second performance data determination sub-module is configured to determine Q second performance data according to the Q second data point clusters and the updated first preset configuration table, the Q second data point clusters and the Q second performance data are in one-to-one correspondence.

[0177] A second preset configuration table updating sub-module is configured to update the second preset configuration table according to the changed data collection requirement to obtain an updated second preset configuration table.

[0178] A performance data table determination sub-module is configured to determine P performance data tables according to the Q second performance data and the updated second preset configuration table, and send the P performance data tables to the server, and P is a positive integer.

[0179] A viewing sub-module is configured to receive and store the P performance data tables by the server for the client to view.

[0180] Further, the viewing module 55 is configured to:

[0181] The client sends a query request.

[0182] The server receives the query request, determines W performance data tables according to the query request, and packs the W performance data tables as a query result, and W is a positive integer less than or equal to M.

[0183] The server returns the query result to the client for display by the client.

[0184] Further, the viewing module 55 is further used for:

[0185] The client sends a login request to the server;

[0186] The server receives and verifies the login request and generates a verification result, and the server returns the verification result to the client;

[0187] The client determines whether to interact with the server according to the received verification result.

[0188] Further, the real-time data acquisition module 51 is used for:

[0189] Adding a timestamp to the real-time data respectively;

[0190] After the data platform acquires the real-time data, determining a time interval between the timestamp in the real-time data and the current time;

[0191] According to the preset response time and the time interval, determining a network transmission state between the data platform and the system of the to-be-collected device.

[0192] Further, before the collection system for acquiring real-time data of the to-be-collected device determines N first preset points of the to-be-collected device according to N types of to-be-collected data in the data collection requirement, the device further comprises:

[0193] A network submodule, the collection system and the data platform are connected to a preset network according to a preset network configuration;

[0194] A matching submodule, the system of the to-be-collected device and the data platform are matched according to a preset protocol in the preset network.

[0195] Further, the first data point cluster determination module 52 is further used for:

[0196] Determining whether the real-time data meet a firewall policy;

[0197] If the real-time data meet the firewall policy, transmitting the real-time data to the data platform;

[0198] If the real-time data do not meet the firewall policy, discarding the real-time data.

[0199] Based on the same inventive concept, the present application provides an electronic device as shown in Figure 6 The electronic device comprises:

[0200] A processor 61;

[0201] A memory 62 for storing executable instructions of the processor 61;

[0202] The processor 61 is configured to perform to implement the data collection method provided in the foregoing.

[0203] Based on the same inventive concept, the present application further provides a non-transitory computer-readable storage medium, when instructions in the storage medium are executed by the processor 61 of the electronic device, the electronic device can execute the data collection method provided in the foregoing.

[0204] Since the electronic device introduced in the embodiment is the electronic device used to implement the information processing method in the embodiment of the present application, based on the information processing method introduced in the embodiment of the present application, those skilled in the art can understand the specific implementation of the electronic device in the embodiment and its various forms, so the electronic device how to implement the method in the embodiment of the present application will not be introduced in detail. As long as the electronic device used to implement the information processing method in the embodiment of the present application is implemented by those skilled in the art, it belongs to the scope of the present application.

[0205] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer usable storage media containing computer usable program code (including but not limited to disk memory, CD-ROM, optical memory, etc.).

[0206] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The function specified in one flow or multiple flows and / or blocks. Figure 1 The device that implements the function specified in one block or multiple blocks.

[0207] These computer program instructions can also be stored in a computer readable memory capable of guiding the computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer readable memory produce a product including instruction devices, which implement the functions specified in the flowcharts and / or block diagrams. Figure 1 The function specified in one flow or multiple flows and / or blocks. Figure 1the function specified in the one or more blocks.

[0208] These computer program instructions can also be loaded into computer or other programmable data processing devices, so that a series of operation steps are performed on the computer or other programmable data processing devices to generate computer-implemented processes, thus the instructions executed on the computer or other programmable data processing devices provide processes for implementing the flows Figure 1 the flows or processes and / or blocks Figure 1 the steps of the function specified in the one or more blocks.

[0209] Although preferred embodiments of the application have been described, those skilled in the art will recognize that additional modifications and variations can be made thereto without departing from the spirit and scope of the application. It is therefore intended that the appended claims cover all such modifications and variations as fall within the scope of the application.

[0210] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore intended that the invention be covered within the scope of the appended claims, and their equivalents.

Claims

1. A data acquisition method, characterized by, The method comprises: The acquisition system for acquiring real-time data of a device to be collected determines N first preset points of the device to be collected according to N types of data to be collected in a data collection requirement, and collects real-time data corresponding to the N first preset points within a preset time period, the N types of data to be collected correspond to the N first preset points one by one, and N is a positive integer; The data platform obtains the real-time data corresponding to the N first preset points from the acquisition system, and stores the real-time data of the N first preset points into a database according to an acquisition sequence to obtain N first data point clusters, the real-time data corresponding to the N first preset points correspond to the N first data point clusters one by one; The data platform determines N first performance data according to the N first data point clusters and a first preset configuration table, the first preset configuration table comprises processing requirements of the real-time data, and the N first data point clusters correspond to the N first performance data one by one; The data platform determines M performance data tables according to the N first performance data and a second preset configuration table, and sends the M performance data tables to a server, the second preset configuration table comprises processing requirements of the N first performance data, and M is a positive integer; The server receives and stores the M performance data tables for a client to view.

2. The method of claim 1, wherein, The method comprises: When the data collection requirement changes, the acquisition system determines Q second preset points of the device to be collected according to Q types of data to be collected in the changed data collection requirement, and collects real-time data corresponding to the Q second preset points within a preset time period, the Q types of data to be collected correspond to the Q second preset points one by one, and Q is a positive integer; The data platform obtains the real-time data corresponding to the Q second preset points from the acquisition system, and stores the real-time data of the Q second preset points into a database according to an acquisition sequence to obtain Q second data point clusters, the real-time data corresponding to the Q second preset points correspond to the Q second data point clusters one by one; The first preset configuration table is updated according to the Q types of data to be collected to obtain an updated first preset configuration table; The data platform determines Q second performance data according to the Q second data point clusters and the updated first preset configuration table, and the Q second data point clusters correspond to the Q second performance data one by one; The second preset configuration table is updated according to the changed data collection requirement to obtain an updated second preset configuration table; The data platform determines P performance data tables according to the Q second performance data and the updated second preset configuration table, and sends the P performance data tables to a server, and P is a positive integer; The server receives and stores the P performance data tables for the client to view.

3. The method of claim 1, wherein, The method comprises: The client sends a query request; The server receives the query request, and determines W pieces of performance data tables according to the query request, and packs the W pieces of performance data tables as a query result, W being a positive integer less than or equal to M; The server returns the query result to the client, so that the client displays the query result.

4. The method of claim 3, wherein, The method comprises: The client sends a login request to the server; The server receives and verifies the login request, and generates a verification result, and returns the verification result to the client; The client determines whether to interact with the server according to the received verification result.

5. The method of claim 1, wherein, The method comprises: Adding a timestamp to the real-time data respectively; After the data platform obtains the real-time data, determining the time interval between the timestamp in the real-time data and the current time; According to the preset response time and the time interval, determining the network transmission state between the data platform and the system of the to-be-collected device.

6. The method of claim 1, wherein, Before the collection system for collecting real-time data of a to-be-collected device determines N first preset points of the to-be-collected device according to N types of to-be-collected data in data collection requirements, the method further comprises: The collection system and the data platform are connected to a preset network according to a preset network configuration; The system of the to-be-collected device and the data platform are matched according to a preset protocol in the preset network.

7. The method of claim 1, wherein, The data platform obtains real-time data corresponding to the N first preset points from the collection system, comprising: Determining whether the real-time data meet a firewall policy; If the real-time data meet the firewall policy, transmitting the real-time data to the data platform; If the real-time data do not meet the firewall policy, discarding the real-time data.

8. A data acquisition device, characterized by The device comprises: A real-time data acquisition module, which determines N first preset points of a to-be-collected device according to N types of to-be-collected data in data collection requirements through a collection system for collecting real-time data of the to-be-collected device, and collects real-time data corresponding to the N first preset points in a preset time period, the N types of to-be-collected data corresponding to the N first preset points one by one, N being a positive integer; A first data point cluster determination module, which is configured to obtain real-time data corresponding to the N first preset points from the collection system by a data platform, and store the real-time data of the N first preset points in a database according to a collection sequence to obtain N first data point clusters, the real-time data corresponding to the N first preset points corresponding to the N first data point clusters one by one; A first performance data determination module, configured to determine N first performance data according to the N first data point clusters and a first preset configuration table by the data platform, the first preset configuration table comprising processing requirements of the real-time data, the N first data point clusters corresponding to the N first performance data one by one; An achievement data table determination module is configured to determine M pieces of achievement data tables according to the N pieces of first achievement data and a second preset configuration table, and send the M pieces of achievement data tables to a server, wherein the second preset configuration table comprises processing requirements of the N pieces of first achievement data, and M is a positive integer; A viewing module is configured to receive and store the M pieces of achievement data tables by the server, so as to be viewed by a client.

9. An electronic device, comprising: Comprise: A processor; A memory for storing executable instructions of the processor; The processor is configured to execute to realize a data collection method as claimed in any one of claims 1 to 7.

10. A non-transitory computer readable storage medium, when instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute a data collection method as claimed in any one of claims 1 to 7.

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