Data processing method and data processing device suitable for an automated production line

Abstract

The embodiment of the application discloses a data processing method and device suitable for an automatic production line, wherein the method comprises the following steps: acquiring sampling data corresponding to each signal in N signals and time mark information of the sampling data; buffering the sampling data corresponding to each signal and the time mark information of the sampling data into a buffer area corresponding to each signal; one signal corresponds to one buffer area, and the buffer areas among different signals are different; when a trigger event for data integration exists, performing data integration processing on the sampling data corresponding to each signal and the time mark information of the sampling data in the buffer area corresponding to each signal according to the time mark information, to obtain M sampling data sets; performing compression processing on the M sampling data sets to obtain compressed data, and storing the compressed data and target time mark information in a database, wherein the target time mark information is determined based on the time mark information of the sampling data included in the M sampling data sets. By using the method, the space occupied by data storage is saved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent manufacturing, and in particular to a data processing method and a data processing device suitable for an automated production line. BACKGROUND

[0002] An automated production line belongs to the technical field of intelligent manufacturing, and refers to a production organization form in which a product process is realized by an automatic machine system. It is formed on the basis of further development of a continuous assembly line. Its characteristics are as follows: a processing object is automatically transferred from one machine tool to another machine tool, and is automatically processed, loaded and unloaded, and inspected by the machine tool; the task of a worker is only to adjust, supervise and manage the automatic line, and the worker does not participate in direct operation; all machine devices operate according to a uniform beat, and the production process is highly continuous. Common automated production lines are, for example, automobile or test systems.

[0003] In the working process of an automated production line, a large amount of data is usually collected, and the collected data is stored in a database. Because the data volume is relatively large, and there may be a large amount of invalid data, the use of a common data storage method to save the collected data in the database may have a relatively large requirement for the storage space of the database. Therefore, in the field of automated production, how to effectively perform data storage has become one of the technical problems to be solved at present. SUMMARY

[0004] The embodiments of the present application provide a data processing method, device and equipment suitable for an automated production line, and a storage medium, which can save the storage space of a database.

[0005] In one aspect, the embodiments of the present application provide a data processing method suitable for an automated production line, comprising:

[0006] obtaining sampling data corresponding to each signal in N signals and time tag information of the sampling data;

[0007] caching the sampling data corresponding to each signal and the time tag information into a buffer area corresponding to the each signal; one signal corresponds to one buffer area, and the buffer areas between different signals are different;

[0008] when a triggering event of data integration exists, performing data integration processing on the sampling data corresponding to each signal in each signal buffer area and the time tag information of the sampling data according to the time tag information to obtain M sampling data sets;

[0009] performing compression processing on the M sampling data sets to obtain compressed data, and associating and storing the compressed data and target time tag information in the database, the target time tag information being determined based on the time tag information of the sampling data included in the M sampling data sets.

[0010] In one aspect, the embodiments of the present application also provide a data processing device suitable for an automated production line, comprising:

[0011] an acquisition unit, configured to acquire sampling data corresponding to each of N signals and time stamp information of the sampling data;

[0012] a storage unit, configured to cache the sampling data corresponding to each of the signals and the time stamp information into a buffer area corresponding to each of the signals; one signal corresponds to one buffer area, and the buffer areas of different signals are different;

[0013] a processing unit, configured to, when there is a triggering event for data integration, perform data integration processing on the sampling data corresponding to each of the signals and the time stamp information of the sampling data in each of the signal buffer areas according to the time stamp information to obtain M sampling data sets;

[0014] the processing unit is further configured to perform compression processing on the M sampling data sets to obtain compressed data, and store the compressed data and target time stamp information in the database, the target time stamp information being determined based on the time stamp information of the sampling data included in the M sampling data sets.

[0015] In one aspect, the embodiments of the present application provide a data processing device suitable for an automated production line, comprising: a processor suitable for implementing one or more computer programs; a computer storage medium, the computer storage medium storing one or more computer programs, the one or more computer programs being suitable for being loaded and executed by the processor:

[0016] acquiring sampling data corresponding to each of N signals and time stamp information of the sampling data;

[0017] caching the sampling data corresponding to each of the signals and the time stamp information into a buffer area corresponding to each of the signals; one signal corresponds to one buffer area, and the buffer areas of different signals are different;

[0018] when there is a triggering event for data integration, performing data integration processing on the sampling data corresponding to each of the signals and the time stamp information of the sampling data in each of the signal buffer areas according to the time stamp information to obtain M sampling data sets;

[0019] performing compression processing on the M sampling data sets to obtain compressed data, and storing the compressed data and target time stamp information in the database, the target time stamp information being determined based on the time stamp information of the sampling data included in the M sampling data sets.

[0020] In one aspect, the embodiment of the present application provides a computer storage medium, which stores a computer program. The computer program is executed by a processor of a data processing device, and is used for performing the following steps:

[0021] obtaining sampling data corresponding to each of N signals and time tag information of the sampling data;

[0022] caching the sampling data corresponding to each of the signals and the time tag information into a buffer area corresponding to each of the signals; one signal corresponds to one buffer area, and the buffer areas of different signals are different;

[0023] when a triggering event of data integration exists, performing data integration processing on the sampling data corresponding to each of the signals and the time tag information of the sampling data in each of the signal buffer areas according to the time tag information, to obtain M sampling data sets;

[0024] performing compression processing on the M sampling data sets to obtain compressed data, and storing the compressed data and target time tag information in the database, the target time tag information being determined based on the time tag information of the sampling data included in the M sampling data sets.

[0025] In one aspect, the embodiment of the present application provides a computer program product or a computer program. The computer program product includes a computer program, which can be referred to as a computer program. The computer program is stored in a computer storage medium. A processor of a data processing device reads the computer program from the computer storage medium. The processor executes the computer program, so that the data processing device performs the following steps:

[0026] obtaining sampling data corresponding to each of N signals and time tag information of the sampling data;

[0027] caching the sampling data corresponding to each of the signals and the time tag information into a buffer area corresponding to each of the signals; one signal corresponds to one buffer area, and the buffer areas of different signals are different;

[0028] when a triggering event of data integration exists, performing data integration processing on the sampling data corresponding to each of the signals and the time tag information of the sampling data in each of the signal buffer areas according to the time tag information, to obtain M sampling data sets;

[0029] performing compression processing on the M sampling data sets to obtain compressed data, and storing the compressed data and target time tag information in the database, the target time tag information being determined based on the time tag information of the sampling data included in the M sampling data sets.

[0030] In the embodiments of the present application, after the sampling data corresponding to each signal and the time scale information of the sampling data are collected, the sampling data corresponding to each signal and the time scale information are buffered into the buffer area corresponding to each signal, one signal corresponding to one buffer area, so as to facilitate the management of the sampling data of each signal; further, when there is a triggering event of data integration, the sampling data corresponding to each signal and the time scale information of the sampling data in the buffer area corresponding to each signal are subjected to data integration processing according to the time scale information, to obtain M sampling data sets; finally, the M sampling data sets are subjected to compression processing to obtain compressed data, and the compressed data and the target time scale information are stored in the database. In this way, the data in the database is subjected to compression processing, which can save storage space to a certain extent, and the sampling data is stored in the dimension of the time scale information, realizing the time unified management of the various sampling data, facilitating subsequent data query, and being beneficial to improving the data query efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0032] Figure 1 is a data storage schematic diagram on an automatic production line provided by the embodiments of the present application;

[0033] Figure 2 is a flowchart of a data processing method provided by the embodiments of the present application;

[0034] Figure 3 is a schematic diagram of N buffer areas provided by the embodiments of the present application;

[0035] Figure 4 is a schematic diagram of a data integration table provided by the embodiments of the present application;

[0036] Figure 5 is a schematic diagram of a data query reference table provided by the embodiments of the present application;

[0037] Figure 6 is a structural schematic diagram of a data processing device provided by the embodiments of the present application;

[0038] Figure 7 is a data processing device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application.

[0040] The embodiment of the present application provides a data storage scheme, specifically, sampling data corresponding to each signal in N signals and time mark information of the sampling data are acquired; further, the sampling data corresponding to each signal and the time mark information of the sampling data are cached into a buffer area corresponding to each signal; when a trigger event of data integration exists, the sampling data corresponding to each signal and the time mark information of the sampling data in the buffer area corresponding to each signal are subjected to data integration processing according to the time mark information to obtain M sampling data sets; finally, the M sampling data sets are subjected to compression processing to obtain compressed data, and the compressed data and target time mark information are stored in a database in association. The above data storage scheme of the present application mainly stores the sampling data in the buffer area of each signal in the database after integration and compression according to the time mark information as a dimension, so that the storage space of the database can be saved, and subsequent data query in the database can be based on the time mark information, and time unified management of data in the database is realized.

[0041] The data processing scheme can be executed by a data processing device, which can be a terminal device, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a vehicle-mounted terminal, etc.; or the data processing device 101 can also be a server, which can be an independent physical server, can be a server cluster or a distributed system composed of multiple physical servers, or can be a cloud server providing cloud computing services.

[0042] The above data storage scheme can be applied to an automatic production line and used for storing data generated on the automatic production line. Figure 1 An automatic production line data storage schematic diagram is provided for the embodiment of the present application, from which it can be seen that the data storage scheme of the present application can be applied to an automatic production line and used for storing data generated on the automatic production line. Figure 1It can be seen that the data storage of the automatic production line can include five stages of data acquisition, data buffering, data arrangement, data storage and data playback. The embodiments of the present application can run through the five stages of the automatic production line. For example, in the embodiments of the present application, the sampling data corresponding to each of the N signals can be obtained in the data acquisition stage. The sampling data corresponding to each signal and the time stamp information of the sampling data are cached in the buffer area corresponding to each signal, which is equivalent to the operation performed in the data buffering stage. According to the time stamp information, the sampling data corresponding to each signal and the time stamp information of the sampling data in the buffer area corresponding to each signal are integrated to obtain M sampling data sets, which is equivalent to the operation performed in the data arrangement stage. The M sampling data sets are compressed to obtain compressed data, and the compressed data and the target time stamp information are stored in the database, which is equivalent to the operation performed in the data storage stage. Subsequently, if it is necessary to query the data in the database, the time stamp information to be queried can be carried in the query request, and the data processing device can query based on the time stamp information and the data stored in the database. This process is equivalent to the data playback stage on the automatic production line.

[0043] Based on the above data processing scheme, the embodiments of the present application provide a data processing method suitable for an automatic production line, as shown in Figure 2 , a flowchart of a data processing method provided by the embodiments of the present application. Figure 2 The data processing method shown can be executed by a data processing device, and specifically can be executed by a processor in the data processing device. Figure 2 The data processing method shown can include the following steps:

[0044] Step S201, obtaining sampling data corresponding to each of N signals and time stamp information of the sampling data.

[0045] The N signals can be signals generated in the automatic production line scenario, which are tools for carrying data and carriers of data. The signals here can be digital signals or analog signals. The sampling data corresponding to each signal can be obtained by sampling each signal. It should be understood that sampling a signal is the discretization of a continuous signal in time, that is, taking the instantaneous value of the analog signal at each point according to a certain time interval.

[0046] For example, the sampling data can be the motor current value, machine tool pressure value, or machine tool processor load value of a certain machine tool in an automated production line, which can then monitor the real-time working status of that machine tool, such as working energy consumption, pressure load, or processor load. The sampling data can also be a set of the above values ​​of several machine tools in an automated production line. By collecting the data of the above value set, a mapping relationship can be established between the above values ​​of several machine tools, thereby monitoring the collaborative working status of several machine tools.

[0047] For example, when the current value of a machine tool in an automated production line fluctuates, one or more downstream machine tools will also experience fluctuations in machine pressure or machine processor load at fixed intervals. Users can analyze and study the sampled data to adjust the operating parameters of the machine tool experiencing the current fluctuation, thereby eliminating the fluctuation. Furthermore, by collecting subsequent sampled data, it's possible to observe whether the pressure or machine processor load fluctuations of the downstream machine tools have been eliminated synchronously, achieving the goal of debugging and optimizing the automated production line.

[0048] The types and quantities of sampling data in automated production lines can be arbitrarily set based on the user's actual needs, and can also be added or deleted arbitrarily during the production process based on actual needs. This application does not impose any special limitations on the specific content of the sampling data. It should be understood that the data processing method of this application is applicable to the extraction and recording of any sampling data in automated production lines.

[0049] In one embodiment, sampling each signal to obtain the corresponding sampled data can mean: within the signal sampling period, sampling N signals separately to obtain the corresponding sampled data for each signal; N is an integer greater than or equal to 1. The signal sampling period can be preset; if the signal sampling period is 1 second, it means that sampling is performed once every 1 second.

[0050] The time stamp information of the sampled data corresponding to each signal can be determined based on the sampling time of the sampled data. In specific implementation, the sampling time for each signal is sampled and the reference time is subtracted; the time stamp information of the sampled data corresponding to each signal is determined based on the result of the subtraction operation. The reference time can be set according to the actual application scenario. In the embodiment of this application, the reference time can be 00:00:00 on January 1, 1970.

[0051] For example, for the i-th signal in the N signals, assuming that the sampling time of the sampling data corresponding to the i-th signal is January 1, 2017, 0:00:00, the time stamp information of the sampling data corresponding to the i-th signal is 3153600000 milliseconds.

[0052] In step S202, the sampling data corresponding to each signal and the time stamp information of the sampling data are cached into the buffer area corresponding to each signal.

[0053] In the embodiment of the present application, in order to avoid the problem of storage confusion of sampling data between different signals, the sampling data corresponding to each signal is independently stored. The specific method is: a separate buffer area is opened for each signal. If there are N signals, there are N buffer areas. The sampling data corresponding to each signal is cached into the corresponding buffer area. For example, the sampling data corresponding to signal 1 is cached into the buffer area corresponding to signal 1, and the sampling data corresponding to signal 2 is cached into the buffer area corresponding to signal 2. The sampling data cached in the buffer area corresponding to each signal can be obtained by sampling and processing the corresponding signal in a plurality of signal sampling periods.

[0054] The buffer area corresponding to each signal not only caches the sampling data corresponding to the corresponding signal, but also caches the time stamp information of the sampling data.

[0055] In a specific implementation, the sampling data and the time stamp information of the sampling data in the buffer area corresponding to each signal are stored in the form of key-value pairs. Based on this, caching the sampling data and the time stamp information of the sampling data corresponding to each signal into the buffer area corresponding to each signal can include: taking the sampling data corresponding to each signal as value information, and taking the time stamp information of the sampling data corresponding to each signal as key information corresponding to the aforementioned value information; based on the mutually corresponding key information and value information, the sampling data corresponding to each signal is cached in the form of key-value pairs in the buffer area corresponding to each signal. In short, based on the mutually corresponding key information and value information, the sampling data corresponding to each signal is cached in the form of key-value pairs in the buffer area corresponding to each signal, which is to store the mutually corresponding key information and value information in the buffer area corresponding to each signal. It should be noted that the key information can be represented as key, and the value information can be represented as value. The sampling data and the time stamp information of the sampling data stored in the form of key-value pairs in any buffer area can be represented as <key, value>.

[0056] For example, referring to Figure 3 , a structure diagram of N buffer areas is provided for the embodiment of the present application. Each signal corresponds to a separate buffer area. For example, in Figure 3 , signal 1 corresponds to buffer area 1, and buffer area 1 is represented as 301 in Figure 3 , signal 2 corresponds to buffer area 2, and buffer area 2 is represented as 302 inFigure 3 N is represented as 302, and signal N corresponds to buffer N, buffer N is represented as 303 in Figure 3 <key, value> stored in 301, which is obtained by sampling signal 1 in the past one or more signal sampling periods.

[0057] Step S203, when there is a trigger event for data integration, according to the time stamp information, the sampling data corresponding to each signal in each buffer and the time stamp information of the sampling data are integrated to obtain M sampling data sets.

[0058] In one embodiment, the trigger event for data integration can be that the i-th data integration period arrives. The data processing device can pre-set the data integration period, such as every 1 minute is a data integration period, when a data integration period arrives, it is necessary to start integrating the sampling data in each buffer corresponding to each signal. Wherein, i is a positive integer greater than or equal to 1.

[0059] Based on this, according to the time stamp information, the sampling data corresponding to each signal in each buffer and the time stamp information of the sampling data are integrated to obtain M sampling data sets, which can mean that the sampling data in each buffer is integrated into a plurality of sampling data sets according to the time stamp information, the sampling data in each sampling data set comes from N different buffers, and the time stamp information corresponding to each sampling data set is matched with the time stamp information corresponding to each sampling data in the sampling data set.

[0060] In a specific implementation, according to the time stamp information, the sampling data corresponding to each signal in each buffer and the time stamp information of the sampling data are integrated to obtain M sampling data sets, including: determining the M time stamp information of the i-th data integration period based on the M time stamp information corresponding to the i-1-th data integration period; wherein a data integration period includes M sampling data sets obtained from the buffer of each signal, each data set corresponds to a time stamp information, and the difference between the time stamp information of any two data sets is the same; any data set stores the sampling data in N buffers matched with the time stamp information corresponding to the any data set; according to the M time stamp information of the i-th data integration period and the key-value pairs in the buffer corresponding to each signal, the sampling data in each buffer matched with each time stamp information in the M time stamp information is obtained, and M sampling data sets included in the i-th data integration period are obtained. A data integration period can be 1 second, and M can be 1000. According to the time stamp information, the sampling data of each signal in the buffer of each signal can be integrated to obtain 1000 sampling data from the buffer in 1 second.

[0061] It should be noted that if i is 1, the i-1th data integration period can refer to the configuration time of the first data integration period, and the configuration time of the first data integration period can configure any one or more of the following information: how many sampling data sets need to be included in the first data integration period, such as 5, 10, and more; how different is the time mark information between any two adjacent sampling data sets, such as 1 second or 5 seconds or other time mark difference information between any two adjacent sampling data sets; how long is a data integration period apart, such as every 1 minute is a data integration period, or every 5 minutes is a data integration period, etc.; and how to determine the time mark information corresponding to each data sampling set in the subsequent data integration period based on the time mark information corresponding to the plurality of sampling data sets in the previous data integration period, etc.

[0062] In the method, the M time mark information of the i th data integration period and the key-value pairs in the buffer corresponding to each signal are used to obtain the sampling data in each buffer that matches each time mark information in the M time mark information, to obtain M sampling data sets included in the i th data integration period. The method can include: performing a preset operation on the M th time mark information corresponding to the i-1 th integration period, and using the operation result as the first time mark information of the i th integration period; and sequentially determining M-1 time mark information according to a time mark interval threshold and the first time mark information. The preset operation can include an addition operation by x, where x represents any positive integer, or the preset operation can also include a multiplication operation, a subtraction operation, or other more complex operations, which are not limited herein. The time mark interval threshold can be 1 millisecond, or 2 milliseconds or any millisecond value.

[0063] For example, assuming that each data integration period corresponds to M sampling data sets, the preset operation represents an addition operation by 1, the time mark interval threshold is 1 millisecond, and the M th sampling data set in the M sampling data sets of the i-1 th data integration period corresponds to the time mark information 3453535324 milliseconds. The first sampling data set in the i th data integration period can correspond to the time mark information 3453535324+1=3453535325 milliseconds. Then, 3453535325 milliseconds is added by 1 to obtain the time mark information corresponding to the second sampling data set, and so on, until the time mark information corresponding to the M th sampling data set in the i th data integration period is obtained.

[0064] The M sampling sets can be recorded by a data integration table, as shown in Figure 4 A schematic diagram of a data integration table provided by an embodiment of the present application is shown in Figure 4The middle 401 represents a sample data set, 402 represents the time scale information corresponding to the sample data set corresponding to 401, and similarly, 403 represents a sample data set, and 404 represents the time scale information corresponding to the sample data set corresponding to 403. For Figure 4 Other sample data sets in the middle are the same as the foregoing, and will not be introduced here.

[0065] From Figure 4 As can be seen from the middle, each data sample set includes sample data from N buffers, and the time scale information of each sample data in the N buffers is matched with the time scale information of each sample data set. That is, the time scale information of the sample data from different buffers in each sample data set is the same as the time scale information corresponding to the sample data set. Optionally, the M data sets are arranged in ascending order according to their corresponding time scale information, that is, the time scale information of the first data set is smaller than the time scale information of the second data set; and in each data set, the sample data is arranged in ascending order according to the buffer from which it comes, for example, the first sample data in a sample data set is from buffer 1 corresponding to signal 1; or, in each data set, the sample data can also be arranged in descending order according to the buffer from which it comes, for example, the first sample data in a sample data set is from the buffer corresponding to signal N. It should be noted that the present application only lists two arrangement modes of the data sample set and the arrangement mode of the sample data in the data sample set, and other arrangement modes can exist in actual application, which is not limited by the present application.

[0066] In another embodiment, the trigger event of data integration can also include that the data processing device receives an operation instruction for integrating the sample data in the buffer. The operation instruction can be generated according to the user input integration operation. In this way, the user can freely control the time of integrating the data, which is convenient for the user to manage.

[0067] If the trigger event of data integration includes that the data processing device receives an operation instruction of integrating the sampling data in the buffer, the data integration processing of the sampling data corresponding to each signal in the buffer and the time stamp information of the sampling data according to the time stamp information obtains an integrated data, which can include: determining the time stamp information corresponding to each sampling data set in the W2 sampling data sets obtained by the data integration processing based on the W1 time stamp information corresponding to the W1 sampling data sets obtained by the previous data integration processing, and then obtaining the sampling data from the buffer based on the time stamp information of each sampling data set to obtain the W2 sampling data sets. Wherein, W1 and W2 can be positive integers, and can be the same or different. It should be noted that the specific implementation manner here is the same as the manner of determining the M sampling data sets when the i th data integration period arrives, and the specific implementation manner can be referred to the foregoing, which will not be described here.

[0068] Step S204, compressing the M sampling data sets to obtain compressed data, and storing the compressed data and the target time stamp information in the database.

[0069] Wherein, the target time stamp information is determined based on the time stamp information of the sampling data included in the M sampling data sets. As a feasible embodiment, the time stamp information corresponding to the first sampling data set in the M sampling data sets can be taken as the target time stamp information. For example, in the Figure 4 , the time stamp information 3453535325 corresponding to the first sampling data set can be taken as the target time stamp information.

[0070] As another feasible implementation manner, the target time stamp information can be a time stamp information range, and the time stamp information corresponding to the first sampling data set and the time stamp information corresponding to the last sampling data set in the M sampling data sets can be taken as the target time stamp information. For example, in the Figure 4 , the time stamp information corresponding to the first sampling data set is 3453535325, and the time stamp information corresponding to the last sampling data set is 3453536324, so the target time stamp information can be represented as (3453535325, 345353536324).

[0071] In other embodiments, the target time stamp information can also be obtained by presetting operation on the time stamp information corresponding to each sampling data set in the M sampling data sets, or the target time stamp information can also be the time stamp information corresponding to the sampling data set located in the middle of the M sampling data sets. The preset operation can be any reasonable operation manner, which will not be described here.

[0072] The compression of the M sets of sampling data can be implemented by a sampling compression algorithm, such as a ZIP compression algorithm, a peer-to-peer algorithm, Snappy, lz4, Huffman coding, and the like. The compressed data can be stored in a data query reference table in the database. In a specific implementation, the compressed data and the target timestamp information are stored in association in the database, including: storing the target timestamp information in a timestamp column of the data query reference table, and storing the compressed data in a compressed value column corresponding to the timestamp information column.

[0073] For example, referring to Figure 5 A schematic diagram of a data query reference table provided by an embodiment of the present application is shown in FIG. 5. The data query reference table stores a plurality of sets of compressed data and target timestamp information corresponding to each other. In Figure 5 In the data query reference table shown in FIG. 5, 501 represents a timestamp column, and 502 represents a compressed value column. Each timestamp column in 501 corresponds to one compressed value column in 502. For example, 503 represents a timestamp column and a compressed value column corresponding to each other. Each set of timestamp column and compressed value column corresponding to each other is used to store a set of compressed data and target timestamp information in association. The data query reference table can further include an identification column, as shown in 504 in FIG. 5. The identification column is used to uniquely identify a set of compressed data and target timestamp information in association. Figure 5 In the data query reference table shown in FIG. 5, 501 represents a timestamp column, and 502 represents a compressed value column. Each timestamp column in 501 corresponds to one compressed value column in 502. For example, 503 represents a timestamp column and a compressed value column corresponding to each other. Each set of timestamp column and compressed value column corresponding to each other is used to store a set of compressed data and target timestamp information in association. The data query reference table can further include an identification column, as shown in 504 in FIG. 5. The identification column is used to uniquely identify a set of compressed data and target timestamp information in association.

[0074] Optionally, the compressed data and the target timestamp information can be first stored in the data query reference table, and then added to the database by calling a data adding method of the database.

[0075] In one embodiment, after the data is stored in the database according to the above steps S201-S204, if subsequent data in the database is to be queried, only the timestamp information needs to be transmitted as a query condition. Specifically, a data query request is received, the data query request carrying timestamp information; the compressed data corresponding to the timestamp information in the query request is determined from the data query reference table; and the determined compressed data is decompressed to obtain the data queried by the query request.

[0076] In the embodiments of the present application, after the sampling data corresponding to each signal and the time scale information of the sampling data are collected, the sampling data corresponding to each signal and the time scale information are buffered into the buffer area corresponding to each signal, one signal corresponds to one buffer area, so as to facilitate the management of the sampling data of each signal; further, when there is a triggering event of data integration, the sampling data corresponding to each signal and the time scale information of the sampling data in the buffer area corresponding to each signal are subjected to data integration processing according to the time scale information, to obtain M sampling data sets; finally, the M sampling data sets are subjected to compression processing to obtain compressed data, and the compressed data and the target time scale information are stored in the database in association. In this way, the data in the database is subjected to compression processing, which can save storage space to a certain extent, and the sampling data is stored in the dimension of the time scale information, realizing the time unified management of the various sampling data, facilitating subsequent data query, and being beneficial to improving the data query efficiency.

[0077] In the prior art automatic production line, the data processing and storage modes of each machine tool may be different, and the time axis references of their respective data may also be different. When joint judgment or cooperative debugging needs to be performed between different machine tools, the lack of mapping relationship between data and the phenomenon of being unable to be synchronously debugged may be caused due to the non-uniformity of the time axis references. The data processing method of the present application stores each item of data in the automatic production line by using a unified time scale information, overcomes the defect of the lack of mapping relationship between data caused by the differences in the data processing and storage modes of each machine tool, and thus can achieve the effect of the uniformity of the time axis and the explicitness of the mapping relationship of the data obtained between each machine tool, which is beneficial to the operation of optimizing and debugging the automatic production line.

[0078] Based on the above-mentioned various data processing method embodiments, the present application provides a data processing device suitable for an automatic production line, which is described below with reference to Figure 6 The structure of the data processing device provided in the embodiments of the present application is shown in the figure. Figure 6 The data processing device can run the following units:

[0079] The acquisition unit 601 is configured to acquire the sampling data corresponding to each signal in the N signals and the time scale information of the sampling data.

[0080] The storage unit 602 is configured to buffer the sampling data corresponding to each signal and the time scale information of the sampling data into the buffer area corresponding to each signal; one signal corresponds to one buffer area, and the buffer areas between different signals are different.

[0081] The processing unit 603 is configured to, when a trigger event of data integration exists, perform data integration processing on the sampling data corresponding to each of the N signals and the time stamp information of the sampling data corresponding to each of the N signals according to the time stamp information, to obtain M sets of sampling data.

[0082] The processing unit 603 is further configured to perform compression processing on the M sets of sampling data to obtain compressed data, and store the compressed data and target time stamp information in the database, the target time stamp information being determined based on the time stamp information of the sampling data included in the M sets of sampling data.

[0083] In an embodiment, the obtaining unit 601, when obtaining the sampling data corresponding to each of the N signals and the time stamp information of the sampling data, performs the following steps:

[0084] In a signal sampling period, sampling processing is performed on the N signals respectively to obtain the sampling data corresponding to each of the N signals; N is an integer greater than or equal to 1;

[0085] For the sampling data corresponding to each of the N signals, the time stamp information of the sampling data corresponding to each of the N signals is determined based on the sampling time of the sampling processing.

[0086] In an embodiment, the obtaining unit 601, when determining the time stamp information of the sampling data corresponding to each of the N signals based on the sampling time of the sampling processing, performs the following steps:

[0087] The sampling time of the sampling processing on each of the N signals is subtracted from a reference time;

[0088] The time stamp information of the sampling data corresponding to each of the N signals is determined based on the result of the subtraction operation.

[0089] In an embodiment, the storage unit 602, when buffering the sampling data corresponding to each of the N signals and the time stamp information into the buffer corresponding to each of the N signals, performs the following steps:

[0090] The sampling data corresponding to each of the N signals is taken as value information, and the time stamp information of the sampling data corresponding to each of the N signals is taken as key information corresponding to the value information;

[0091] The key information and the value information corresponding to each other are buffered in the buffer corresponding to each of the N signals in the form of key-value pairs.

[0092] In an embodiment, the trigger event of data integration includes the arrival of an i-th data integration period, i being an integer greater than or equal to 1; the processing unit 603, when performing data integration processing on the sampling data corresponding to each of the N signals and the time stamp information of the sampling data corresponding to each of the N signals according to the time stamp information, performs the following steps:

[0093] determining the M timestamp information of the i th data integration period based on the M timestamp information corresponding to the i-1 th data integration period; wherein one data integration period comprises M sample data sets obtained from the buffer of each signal, each sample data set corresponds to a timestamp information, and the difference between any two timestamp information is the same; any data set stores the sample data in the N buffer matching the timestamp information corresponding to the any data set;

[0094] obtaining the sample data in each buffer matching each timestamp information in the M timestamp information of the i th data integration period according to the M timestamp information of the i th data integration period and each key-value pair in the buffer corresponding to each signal, and obtaining M sample data sets included in the i th data integration period.

[0095] In one embodiment, the processing unit 603 performs the following steps when determining the M timestamp information of the i th integration period based on the M timestamp information corresponding to the i-1 th data integration period:

[0096] performing a preset operation on the M timestamp information corresponding to the i-1 th data integration period, and the operation result is used as the first timestamp information of the i th data integration period;

[0097] sequentially determining M-1 timestamp information according to the timestamp interval threshold and the first timestamp information.

[0098] In one embodiment, the data processing apparatus further comprises a determination unit 604, which is configured to determine target timestamp information based on the timestamp information of the sample data included in the M sample data sets; and the determination unit 604 performs the following steps when determining the target timestamp information based on the timestamp information of the sample data included in the M sample data sets:

[0099] using the timestamp information corresponding to the first sample data set as the target timestamp information;

[0100] Alternatively, the target timestamp information is composed based on the timestamp information of the sample data corresponding to the first sample data set and the timestamp information corresponding to the last sample data set.

[0101] In one embodiment, the database comprises a data query reference table, and the data query reference table comprises timestamp columns and data columns corresponding to each other; and the storage unit 602 performs the following steps when storing the compressed data and the target timestamp information in the database:

[0102] The target time stamp information is stored in the time stamp column of the data query lookup table, and the compressed data is stored in the compressed value column corresponding to the time stamp column.

[0103] In one embodiment, the data processing device further includes a receiving unit 605, which is used to receive a data query request, the data query request carrying time stamp information; the determining unit 604 is further used to determine compressed data corresponding to the time stamp information in the query request from a data query reference table; the processing unit 603 is further used to decompress the determined compressed data to obtain the data queried by the query request.

[0104] According to one embodiment of this application, Figure 2 The data processing method shown can involve various steps that can be derived from... Figure 6 This is performed by each unit in the data processing apparatus shown. For example, Figure 2 The aforementioned step S601 can be performed by Figure 6 The acquisition unit 601 in the data processing device is used to execute steps S202 and S204, which can be performed by... Figure 6 The data processing device is executed by the storage unit 602, and steps S203 and S204 can be performed by... Figure 6 The processing unit 603 in the data processing device performs the operation.

[0105] According to another embodiment of this application, Figure 6 The data processing apparatus shown can be composed of individual or combined units into one or more other units, or some of the units can be further divided into multiple functionally smaller units. This achieves the same operation without affecting the technical effects of the embodiments of this application. The above-mentioned units are based on logical function division. In practical applications, the function of one unit can be implemented by multiple units, or the function of multiple units can be implemented by one unit. In other embodiments of this application, the data processing apparatus may also include other units. In practical applications, these functions can also be implemented with the assistance of other units, and can be implemented collaboratively by multiple units.

[0106] According to another embodiment of this application, the following can be achieved by running on a general-purpose computing device, such as a computer, which includes processing elements and storage elements such as a central processing unit (CPU), random access memory (RAM), and read-only memory (ROM), a device capable of performing operations such as... Figure 2 The computer program (including program code) for each step involved in the corresponding method shown, to construct such... Figure 6The data processing device shown in the method and the data processing device shown in the method are used to implement the data processing method of the embodiments of the application. The computer program can be recorded on a computer readable storage medium, loaded into the data processing device through the computer readable storage medium, and run in the data processing device.

[0107] In the embodiments of the application, after the sampling data corresponding to each signal and the time stamp information of the sampling data are collected, the sampling data corresponding to each signal and the time stamp information are buffered into a buffer area corresponding to each signal. One signal corresponds to one buffer area, so as to facilitate the management of the sampling data of each signal. Further, when there is a triggering event of data integration, the sampling data corresponding to each signal and the time stamp information of the sampling data in the buffer area corresponding to each signal are subjected to data integration processing according to the time stamp information, to obtain M sampling data sets. Finally, the M sampling data sets are subjected to compression processing to obtain compressed data, and the compressed data and target time stamp information are stored in association in a database. In this way, the data in the database is subjected to compression processing, so that the storage space can be saved to a certain extent, and the sampling data is stored in the dimension of the time stamp information, so that the sampling data is subjected to time unified management, which facilitates subsequent data query and is conducive to improving the data query efficiency.

[0108] Based on the above-mentioned data processing method embodiments and data processing device embodiments, the embodiments of the application provide a data processing device suitable for an automatic production line, as shown in Figure 7 , which is a structural schematic diagram of a data processing device provided in the embodiments of the application. Figure 7 The data processing device can include a processor 901, an input interface 902, an output interface 903, and a computer storage medium 904. The processor 901, the input interface 902, the output interface 903, and the computer storage medium 904 can be connected through a bus or other means.

[0109] The computer storage medium 904 can be stored in the memory of the data processing device, and the computer storage medium 904 is used to store a computer program, and the processor 901 is used to execute the computer program stored in the computer storage medium 904. The processor 901, also known as a CPU (Central Processing Unit, Central Processing Unit), is the computing core and control core of the data processing device, which is suitable for implementing one or more computer programs, and is particularly suitable for loading and executing:

[0110] obtaining sampling data corresponding to each signal in N signals and time stamp information of the sampling data;

[0111] buffer the sampling data corresponding to each signal and the time stamp information of the sampling data into the buffer area corresponding to each signal, one signal corresponding to one buffer area, the buffer areas being different between different signals;

[0112] when there is a triggering event for data integration, perform data integration processing on the sampling data corresponding to each signal and the time stamp information of the sampling data in the buffer area corresponding to each signal according to the time stamp information, to obtain M sampling data sets;

[0113] perform compression processing on the M sampling data sets to obtain compressed data, and store the compressed data and target time stamp information in the database, the target time stamp information being determined based on the time stamp information of the sampling data included in the M sampling data sets.

[0114] In the embodiments of the present application, after the sampling data corresponding to each signal and the time stamp information of the sampling data are collected, the sampling data corresponding to each signal and the time stamp information are buffered into the buffer area corresponding to each signal, one signal corresponding to one buffer area, so as to facilitate management of the sampling data of each signal. Further, when there is a triggering event for data integration, data integration processing is performed on the sampling data corresponding to each signal and the time stamp information of the sampling data in the buffer area corresponding to each signal according to the time stamp information, to obtain M sampling data sets. Finally, compression processing is performed on the M sampling data sets to obtain compressed data, and the compressed data and target time stamp information are stored in the database. In this way, the data in the database is compressed, which can save storage space to a certain extent, and the sampling data is stored in the dimension of time stamp information, realizing time-unified management of the sampling data, facilitating subsequent data query, and being conducive to improving data query efficiency.

[0115] The embodiments of the present application also provide a computer storage medium (Memory), which is a memory device of a data processing device, and is used for storing programs and data. It can be understood that the computer storage medium herein can include a built-in storage medium of the data processing device, and of course can also include an extended storage medium supported by the data processing device. The computer storage medium provides a storage space, which stores an operating system of the data processing device. Moreover, one or more computer programs suitable for being loaded and executed by the processor 701 are also stored in the storage space. It should be noted that the computer storage medium herein can be a high-speed RAM memory, or a non-volatile memory such as at least one disk memory; optionally, the computer storage medium can also be at least one computer storage medium located away from the aforementioned processor.

[0116] In one embodiment, the one or more computer programs stored in the computer storage medium can be loaded and executed by the processor 701:

[0117] Obtaining sampling data corresponding to each of the N signals and time stamp information of the sampling data;

[0118] Caching the sampling data corresponding to each of the signals and the time stamp information of the sampling data into a buffer corresponding to each of the signals; one signal corresponds to one buffer, and the buffers between different signals are different;

[0119] When there is a triggering event of data integration, performing data integration processing on the sampling data corresponding to each of the signals and the time stamp information of the sampling data in the buffer corresponding to each of the signals according to the time stamp information to obtain M sampling data sets;

[0120] Performing compression processing on the M sampling data sets to obtain compressed data, and storing the compressed data and target time stamp information in the database, the target time stamp information being determined based on the time stamp information of the sampling data included in the M sampling data sets.

[0121] In one embodiment, when the processor 701 obtains the sampling data corresponding to each of the N signals and the time stamp information of the sampling data, the processor 701 performs the following steps:

[0122] In a signal sampling period, respectively sampling N signals to obtain sampling data corresponding to each of the signals; N is an integer greater than or equal to 1;

[0123] For the sampling data corresponding to each of the signals, determining the time stamp information of the sampling data corresponding to each of the signals based on the sampling time of the sampling processing.

[0124] In one embodiment, when the processor 701 determines the time stamp information of the sampling data corresponding to each of the signals based on the sampling time of the sampling processing, the processor 701 performs the following steps:

[0125] Performing difference operation on the sampling time of the sampling processing on each signal and a reference time;

[0126] Determining the time stamp information of the sampling data corresponding to each of the signals based on the result of the difference operation.

[0127] In one embodiment, when the processor 701 caches the sampling data corresponding to each of the signals and the time stamp information into the buffer corresponding to each of the signals, the processor 701 performs the following steps:

[0128] Taking the sampling data corresponding to each of the signals as value information, and taking the time stamp information of the sampling data corresponding to each of the signals as key information corresponding to the value information;

[0129] cache into the buffer corresponding to each signal in the form of key-value pairs based on the corresponding key information and value information.

[0130] In one embodiment, the trigger event of data integration includes the arrival of the i-th data integration period, i being an integer greater than or equal to 1; the processor 701 performs the following steps when performing data integration processing on the sampling data corresponding to each signal in the buffer and the time stamp information of the sampling data according to the time stamp information to obtain M sampling data sets:

[0131] determining the M time stamp information of the i-th data integration period based on the M-th time stamp information corresponding to the i-1-th data integration period; wherein one data integration period includes M sampling data sets obtained from the buffer of each signal, each sampling data set corresponds to a time stamp information, and the difference between any two time stamp information is the same; any data set stores N sampling data in the buffer corresponding to the time stamp information of the any data set;

[0132] According to the M time stamp information of the i-th data integration period and the key-value pairs in the buffer corresponding to each signal, the sampling data in each buffer that matches each time stamp information in the M time stamp information is obtained, and M sampling data sets included in the i-th data integration period are obtained.

[0133] In one embodiment, the processor 701 performs the following steps when determining the M time stamp information of the i-th integration period based on the M-th time stamp information corresponding to the i-1-th data integration period:

[0134] performing a preset operation on the M-th time stamp information corresponding to the i-1-th data integration period, and the operation result is used as the first time stamp information of the i-th data integration period;

[0135] sequentially determining M-1 time stamp information according to the time stamp interval threshold and the first time stamp information.

[0136] In one embodiment, the processor 701 is further configured to perform:

[0137] determining target time stamp information based on the time stamp information of the sampling data included in the M sampling data sets;

[0138] The determination of the target time stamp information based on the time stamp information of the sampling data included in the M sampling data sets includes: taking the time stamp information corresponding to the first sampling data set as the target time stamp information;

[0139] Alternatively, the target time stamp information is composed based on the time stamp information of the sampling data corresponding to the first sampling data set and the time stamp information corresponding to the last sampling data set.

[0140] In an embodiment, the database comprises a data query reference table, the data query reference table comprises a time stamp column and a data column corresponding to each other, and the processor 701, when storing the compressed data and the target time stamp information in the database, performs the following steps:

[0141] stores the target time stamp information in the time stamp column of the data query reference table, and stores the compressed data in a compressed value column corresponding to the time stamp column.

[0142] In an embodiment, the processor 701 is further configured to perform the following steps:

[0143] receive a data query request, the data query request carrying time stamp information;

[0144] determine the compressed data corresponding to the time stamp information in the query request from the data query reference table;

[0145] decompress the determined compressed data to obtain the data queried by the query request.

[0146] In an embodiment, after the sampling data corresponding to each signal and the time stamp information of the sampling data are collected, the sampling data corresponding to each signal and the time stamp information are buffered in a buffer area corresponding to each signal, one signal corresponding to one buffer area, so as to facilitate the management of the sampling data of each signal. Further, when there is a triggering event of data integration, the sampling data corresponding to each signal and the time stamp information of the sampling data in each buffer area corresponding to each signal are integrated according to the time stamp information to obtain M sampling data sets. Finally, the M sampling data sets are compressed to obtain compressed data, and the compressed data and the target time stamp information are stored in the database. In this way, the data in the database is compressed, which can save storage space to a certain extent, and the sampling data is stored according to the time stamp information, which realizes the time unified management of the sampling data, facilitates subsequent data query, and is beneficial to improving the data query efficiency.

[0147] An embodiment of the present application further provides a computer program product or a computer program, the computer program product comprising a computer program, the computer program being stored in a computer storage medium, and the computer program being loaded and executed by the processor 701:

[0148] obtain the sampling data corresponding to each signal in the N signals and the time stamp information of the sampling data;

[0149] The sampling data corresponding to each signal and the time stamp information are buffered into a buffer corresponding to each signal, one signal corresponding to one buffer, and the buffers being different between different signals;

[0150] When a triggering event for data integration exists, the sampling data corresponding to each signal and the time stamp information of the sampling data in each signal buffer are subjected to data integration processing according to the time stamp information to obtain M sampling data sets;

[0151] The M sampling data sets are subjected to compression processing to obtain compressed data, and the compressed data and target time stamp information are stored in the database in association, the target time stamp information being determined based on the time stamp information of the sampling data included in the M sampling data sets.

[0152] In the embodiments of the present application, after the sampling data corresponding to each signal and the time stamp information of the sampling data are collected, the sampling data corresponding to each signal and the time stamp information are buffered into a buffer corresponding to each signal, one signal corresponding to one buffer, so as to facilitate the management of the sampling data of each signal. Further, when a triggering event for data integration exists, the sampling data corresponding to each signal and the time stamp information of the sampling data in each signal buffer are subjected to data integration processing according to the time stamp information to obtain M sampling data sets. Finally, the M sampling data sets are subjected to compression processing to obtain compressed data, and the compressed data and target time stamp information are stored in the database in association. In this way, the data in the database is subjected to compression processing, which can save storage space to a certain extent, and the sampling data is stored in the dimension of time stamp information, which realizes the time unified management of the sampling data, facilitates subsequent data query, and is conducive to improving the data query efficiency.

Claims

1. A data processing method suitable for automated production lines, characterized in that, include: Acquire the sampling data and time stamp information of each of the N signals; the sampling data corresponding to each signal includes a set of values ​​of multiple machine tools on an automated production line, and there is a mapping relationship between the values ​​of at least two different machine tools in the set of sampling data; The sampling data and time stamp information of each signal are cached in the buffer corresponding to each signal. Each signal corresponds to a buffer, and different signals have different buffers. When a data integration trigger event occurs, the sampled data corresponding to each signal in the buffer corresponding to each signal and the time stamp information of the sampled data are processed according to the time stamp information to obtain M sampled datasets; wherein, a sampled dataset includes N sampled data from N buffers, and the N sampled data in a sampled dataset have the same time stamp information; the trigger event for data integration includes the arrival of the i-th data integration cycle, where i is an integer greater than or equal to 1; The M sampled datasets are compressed to obtain compressed data, and the compressed data and target time stamp information are associated and stored in a database. The target time stamp information is determined based on the time stamp information of the sampled data included in the M sampled datasets. The step of integrating the sampled data corresponding to each signal in the buffer according to the time stamp information and the time stamp information of the sampled data to obtain M sampled datasets includes: Based on the Mth time stamp information corresponding to the (i-1)th data integration period, the M time stamp information of the i-th data integration period is determined; wherein, a data integration period includes M sampled datasets obtained from the buffer of each signal, each sampled dataset corresponds to a time stamp information, and the time stamp information corresponding to any two datasets is identical; each dataset stores sampled data in N buffers that match the time stamp information corresponding to the dataset. Based on the M time stamp information of the i-th data integration period and each key-value pair in the buffer corresponding to each signal, the sampled data in each buffer that matches each time stamp information in the M time stamp information is obtained, and the M sampled datasets included in the i-th data integration period are obtained. The acquisition of the sampling data and time stamp information of each of the N signals includes: Within the signal sampling period, N signals are sampled and processed to obtain the sampled data corresponding to each signal; N is an integer greater than or equal to 1. For each signal's corresponding sampled data, the time stamp information of the sampled data corresponding to each signal is determined based on the sampling time of the sampling process; The determination of the time stamp information for the sampled data corresponding to each signal based on the sampling time of the sampling process includes: The sampling time for each signal is compared with the reference time. The time stamp information of the sampling data corresponding to each signal is determined based on the result of the difference operation; The step of caching the sampling data and time stamp information corresponding to each signal into the buffer corresponding to each signal includes: The sampled data corresponding to each signal is used as value information, and the time stamp information of the sampled data corresponding to each signal is used as key information corresponding to the value information; Based on the corresponding key and value information, they are cached in the buffer corresponding to each signal in the form of key-value pairs; The step of determining the M timestamps for the i-th integration period based on the M timestamps corresponding to the (i-1)-th data integration period includes: A preset calculation is performed on the Mth time stamp information corresponding to the (i-1)th data integration period, and the calculation result is used as the first time stamp information of the i-th data integration period; M-1 time stamp information are determined sequentially according to the time stamp interval threshold and the first time stamp information.

2. The method as described in claim 1, characterized in that, The method further includes: The target time stamp information is determined based on the time stamp information of the sampled data included in the M sampled datasets; The determination of target time stamp information based on the time stamp information of the sampled data included in the M sampled datasets includes: Use the time-stamped information corresponding to the first sampled dataset as the target time-stamped information; or, The target time stamp information is composed of the time stamp information of the sampled data corresponding to the first sampled dataset and the time stamp information corresponding to the last sampled dataset.

3. The method as described in claim 1, characterized in that, The database includes a data lookup table, which includes corresponding time-stamp columns and data columns. The step of associating and storing the compressed data and target time-stamp information in the database includes: The target time stamp information is stored in the time stamp column of the data query lookup table, and the compressed data is stored in the compressed value column corresponding to the time stamp column.

4. The method as described in claim 3, characterized in that, The method further includes: Receive a data query request, wherein the data query request carries time stamp information; Determine the compressed data corresponding to the time stamp information in the query request from the data query reference table; The determined compressed data is decompressed to obtain the data requested in the query request.

5. A data processing device suitable for automated production lines, characterized in that, A data processing method suitable for automated production lines as described in any one of claims 1-4, comprising: The acquisition unit is used to acquire the sampling data and time stamp information of each of the N signals; The storage unit is used to cache the sampling data and time stamp information corresponding to each signal into the buffer corresponding to each signal; one signal corresponds to one buffer, and the buffers for different signals are different. The processing unit is used to perform data integration processing on the sampled data corresponding to each signal and the time stamp information of the sampled data in the buffer corresponding to each signal according to the time stamp information when there is a trigger event for data integration, to obtain M sampled datasets. The processing unit is also used to compress the M sampled datasets to obtain compressed data; The storage unit is also used to associate and store the compressed data and target time stamp information in the database, wherein the target time stamp information is determined based on the time stamp information of the sampled data included in the M sampled datasets.

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