Information processing system, information processing method, and information processing program

Abstract

To provide an information processing system for displaying a graph with limited resources while reducing the probability that intended information cannot be displayed, an information processing method, and an information processing program.SOLUTION: An information processing system includes: a first data selection unit 22 which selects first pieces of data 27-1 to 27-3 smaller in number, in accordance with a predetermined first algorithm, from multiple pieces of data (raw data 21) to be displayed on a graph; a second data selection unit 23 which selects second pieces of data 28-1, 28-2 in accordance with predetermined settings from the multiple pieces of data; and a graph generation unit 24 which generates a graph 26 on the basis of the first data and the second data. The settings include a second algorithm for determining data to be displayed on a graph, and parameters.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing system, an information processing method, and an information processing program. [Background technology]

[0002] When analyzing data, it is common to use a graph to visually represent it. When the target data is large, for example, depending on resources, a method is adopted in which only a portion of the data is represented as a graph.

[0003] For example, Japanese Patent Application Laid-Open Publication No. 2013-246500 (Patent Document 1) discloses a technology for processing time series data in order to display multiple time series data on a display screen in multiple stages with a time granularity that is the display time per dot on the display. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-246500 Summary of the Invention [Problem to be solved by the invention]

[0005] The methods disclosed in the prior art select the data to be displayed according to a predetermined algorithm without considering the meaning of the data, which means that there is a high possibility that the data that is actually desired to be displayed will not be displayed in a graph.

[0006] Therefore, an object of the present invention is to provide a technique for displaying graphs using limited resources while reducing the possibility that information that should be displayed will not be displayed. [Means for solving the problem]

[0007] An information processing system according to one embodiment of the present invention includes a first data selection unit that selects a smaller number of first data from a plurality of data to be displayed in a graph in accordance with a predetermined first algorithm, a second data selection unit that selects a smaller number of second data from the plurality of data in accordance with predetermined settings, and a graph generation unit that generates a graph based on the first data and the second data, where the settings include a second algorithm and parameters for determining that the data should be displayed in a graph.

[0008] According to this configuration, a smaller number of first data from the multiple data to be displayed in the graph is used to display the graph according to a predetermined first algorithm, thereby reducing the resources required for processing compared to when all of the multiple data are used, and since second data selected according to predetermined settings is also displayed in the graph, the possibility of data that should be displayed in the graph not being displayed can be reduced.

[0009] The settings may further include criteria for selecting a smaller number of data from the plurality of data that are determined to be displayed in the graph. With this configuration, even when there is a plurality of data to be displayed in the graph, an increase in required resources can be suppressed.

[0010] The first data selection unit may select one first data for each predetermined number of data, and the second data selection unit may select one second data for each predetermined number of data. With this configuration, one first data and at most one second data are selected for each predetermined number of data, thereby preventing an increase in the number of selected data.

[0011] The first data selection unit and the second data selection unit may be configured to decrease the predetermined number of first data and second data to be selected over time. This configuration reduces the resources required for the initial display and allows the user to view more detailed graphs over time.

[0012] The graph generating unit may represent the first data in a graph in a first display format, and represent the second data in a graph in a second display format. With this configuration, the first data and the second data are represented in different display formats, making it easier for the user to distinguish between the data.

[0013] The parameter of the setting may be changed according to at least one of a function and a third algorithm. With this configuration, the setting to be selected as the second data can be adjusted depending on the situation.

[0014] The information processing system may further include a storage unit that stores at least one of a first predefined preset that can be used as the first algorithm and a second predefined preset that can be used as the setting. With this configuration, even a user with little knowledge can perform necessary settings in a short time.

[0015] The information processing system may further include an information processing device that executes a browser application. The graph may be displayed via a browser provided by the execution of the browser application. With this configuration, the graph can be displayed using a general-purpose browser application.

[0016] An information processing method according to another example of the present invention includes the steps of selecting a smaller number of first data from a plurality of data to be displayed in a graph in accordance with a predetermined first algorithm, selecting second data from the plurality of data in accordance with predetermined settings, and generating a graph based on the first data and the second data, wherein the settings include a second algorithm and parameters for determining that the data should be displayed in a graph.

[0017] According to yet another example of the present invention, an information processing program causes a computer to execute the steps of selecting a smaller number of first data from a plurality of data to be displayed in a graph in accordance with a predetermined first algorithm, selecting second data from the plurality of data in accordance with predetermined settings, and generating a graph based on the first data and the second data, wherein the settings include a second algorithm and parameters for determining that the data should be displayed in a graph. [Effects of the Invention]

[0018] According to the present invention, it is possible to display graphs using limited resources while reducing the possibility that information that should be displayed will not be displayed. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a diagram illustrating an overview of an information processing method executed by an information processing system according to an embodiment of the present invention. [Figure 2] 1 is a schematic diagram showing an example of the overall configuration of an information processing system according to the present embodiment; [Figure 3] FIG. 2 is a block diagram showing an example of a hardware configuration of a control device of the information processing system according to the present embodiment. [Figure 4] FIG. 2 is a block diagram showing an example of a hardware configuration of an information processing device in the information processing system according to the present embodiment. [Figure 5] FIG. 1 is a diagram illustrating an example of a graph display according to the related art. [Figure 6] FIG. 10 is a diagram showing an example of a graph display according to the present embodiment. [Figure 7] FIG. 10 is a schematic diagram showing an example of a user interface screen including a graph display provided by the information processing system according to the present embodiment. [Figure 8] FIG. 10 is a schematic diagram showing an example of a user interface screen including a graph display provided by the information processing system according to the present embodiment. [Figure 9]FIG. 10 is a schematic diagram showing another example of a user interface screen including a graph display provided by the information processing system according to the present embodiment. [Figure 10] FIG. 1 is a schematic diagram showing an example of a functional configuration of an information processing system according to an embodiment of the present invention. [Figure 11] FIG. 10 is a schematic diagram showing a modified example of the functional configuration of the information processing system according to the present embodiment. [Figure 12] FIG. 10 is a schematic diagram showing another modified example of the functional configuration example of the information processing system according to the present embodiment. [Figure 13] FIG. 10 is a diagram illustrating an example in which a plurality of threshold values ​​are set in the important data setting (important data determination setting) according to the present embodiment. [Figure 14] FIG. 10 is a diagram for illustrating another example in which a plurality of threshold values ​​are set in the important data setting (important data determination setting) according to the present embodiment. [Figure 15] 10A and 10B are diagrams illustrating an example of setting a variable threshold value included in an important data setting (important data determination setting) according to the present embodiment. [Figure 16] FIG. 10 is a diagram illustrating another example of setting a variable threshold value included in the important data setting (important data determination setting) according to the present embodiment. [Figure 17] FIG. 10 is a diagram illustrating yet another setting example of important data setting (important data determination setting) according to the present embodiment. [Figure 18] FIG. 10 is a schematic diagram showing an example of a user interface screen relating to presets provided by the information processing system according to the present embodiment. [Figure 19] FIG. 10 is a diagram for explaining the processing load depending on the size of a bucket in the information processing system according to the present embodiment. [Figure 20] FIG. 10 is a diagram for illustrating another example of graph display according to the present embodiment. [Figure 21] FIG. 10 is a diagram illustrating an example of important data selection setting according to the present embodiment. [Figure 22] 10A to 10C are diagrams for explaining an example of how a graph display changes over time according to the present embodiment. [Figure 23] 10A to 10C are diagrams for illustrating an example of a display mode of a graph display according to the present embodiment. [Figure 24] FIG. 10 is a diagram for illustrating another example of a display mode of a graph display according to the present embodiment. [Figure 25] 10A and 10B are diagrams for explaining an example of changing the display granularity of important data according to the present embodiment. [Figure 26] 10A and 10B are diagrams for explaining an example of a process for generating representative data according to the present embodiment. [Figure 27] FIG. 27 is a diagram for explaining the process of displaying a graph using representative data generated by the process shown in FIG. 26. [Figure 28] 10A and 10B are diagrams for explaining another example of processing for generating representative data according to the present embodiment. [Figure 29] FIG. 29 is a diagram for explaining the process of graph display using the representative data generated by the process shown in FIG. 28. [Figure 30] 10 is a flowchart showing a processing procedure for displaying a graph in information processing system 1 according to the present embodiment. [Figure 31] 10 is a flowchart showing a processing procedure relating to setting in information processing system 1 according to the present embodiment. [Figure 32] 32 is a flowchart showing the processing steps of the setting preset creation processing shown in FIG. 31. [Figure 33] 32 is a flowchart showing the processing steps for creating new settings shown in FIG. 31. [Figure 34] 32 is a flowchart showing the processing steps of a process for creating settings based on the setting preset shown in FIG. 31. DETAILED DESCRIPTION OF THE INVENTION

[0020] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail with reference to the accompanying drawings, in which the same or corresponding parts are designated by the same reference numerals and will not be described repeatedly.

[0021] <A. Application Example> First, an example of a scenario to which the present invention is applied will be described.

[0022] FIG. 1 is a diagram for explaining an outline of an information processing method executed by an information processing system 1 according to the present embodiment.

[0023] Referring to FIG. 1, first, it is assumed that a plurality of data (raw data 21) are targets of graph display. The information processing system 1 includes a first data selection unit 22 (such as a sampling module 80 described later), a second data selection unit 23 (such as an important data selection module 90 described later), and a graph generation unit 24 (such as a graph generation module 74 described later).

[0024] The first data selection unit 22 selects a smaller number of first data 27-1 to 27-3 (sampling data described later) from the raw data 21 according to a first algorithm. Also, the second data selection unit 23 selects second data 28-1 and 28-2 (important data or selected important data described later) from the raw data 21 according to a predetermined setting.

[0025] The graph generation unit 24 generates a graph 26 based on the first data 27-1 to 27-3 and the second data 28-1 and 28-2.

[0026] The setting used by the second data selection unit 23 includes a second algorithm and parameters (such as a threshold value 25, etc.) for determining data to be displayed on the graph. That is, the setting includes an algorithm and parameters for selecting data that is important (meaningful) to the user.

[0027] <B. Overall Configuration Example> Next, an overall configuration example of the information processing system 1 according to the present embodiment will be described.

[0028] Fig. 2 is a schematic diagram showing an example of the overall configuration of information processing system 1 according to the present embodiment. Referring to Fig. 2, information processing system 1 according to the present embodiment includes, as main components, a control device 100, an information processing device 200, and an HMI (Human Machine Interface) 300.

[0029] The control device 100 may be embodied as a type of computer, such as a programmable logic controller (PLC). The control device 100 is connected to the field device group 10 via a field bus 2. The field bus 2 preferably employs an industrial communication protocol. Known examples of such communication protocols include EtherCAT (registered trademark), EtherNet / IP (registered trademark), DeviceNet (registered trademark), and CompoNet (registered trademark).

[0030] The field device group 10 includes devices that collect input data from a field such as a production site, and devices that perform some kind of action on the field based on a command (output data) generated by the control device 100.

[0031] In the configuration example shown in FIG. 2, the field device group 10 includes a remote I / O (Input / Output) device 12, a relay group 14, a servo driver 18, and a servo motor 20.

[0032] The control device 100 has a time series database that sequentially stores input data from the field device group 10, output data to the field device group 10, and internal data managed within the control device 100, and displays or outputs the raw data stored in the time series database in a manner described below.

[0033] The information processing device 200 accesses the control device 100 and displays a graph of the data stored in the control device 100. In the configuration example shown in Fig. 2, the information processing device 200 is connected to the control device 100 via a higher-level network 4, but may be connected to the control device 100 in any manner.

[0034] The HMI 300 is connected to the control device 100 via the upper network 4, displays information from the control device 100, and transmits a command according to a user operation to the control device 100.

[0035] <C. Hardware Configuration Example> Next, a hardware configuration example of the main devices of the information processing system 1 according to the present embodiment will be described.

[0036] (c1: Control Device 100) FIG. 3 is a block diagram showing a hardware configuration example of the control device 100 of the information processing system 1 according to the present embodiment. Referring to FIG. 3, the control device 100 includes a processor 102 such as a CPU (Central Processing Unit) or an MPU (Micro-Processing Unit), a chip set 104, a main storage device 106, a secondary storage device 108, an upper network controller 110, a USB (Universal Serial Bus) controller 112, a memory card interface 114, an internal bus controller 122, a field bus controller 120, and I / O units 124-1, 124-2,....

[0037] The processor 102 reads out various programs stored in the secondary storage device 108, expands them in the main storage device 106, and executes them to realize the processes required for the control device 100. The chip set 104 controls data transmission between the processor 102 and each component.

[0038] In the secondary storage device 108, a system program 131, a user program 132 that describes the content of control operations, an application execution environment program 133 that provides an environment for executing an arbitrary application as described later, and an application program 134 that describes an arbitrary one or more applications are stored.

[0039] The upper network controller 110 controls data exchange with other devices via the upper network 4. The USB controller 112 controls data exchange with the information processing device 200 via a USB connection.

[0040] The memory card interface 114 is configured to allow a memory card 116 to be attached and detached, and is capable of writing data to the memory card 116 and reading various data (user programs, trace data, etc.) from the memory card 116.

[0041] The internal bus controller 122 is an interface for exchanging data with the I / O units 124-1, 124-2, . . . mounted on the control device 100.

[0042] The fieldbus controller 120 controls the exchange of data with other devices via the fieldbus 2 .

[0043] FIG. 3 shows an example of a configuration in which the processor 102 executes a program to provide the required functions, but some or all of these provided functions may be implemented using dedicated hardware circuits (e.g., an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array)). Alternatively, the main part of the control device 100 may be realized using hardware that conforms to a general-purpose architecture (e.g., an industrial PC based on a general-purpose PC). In this case, virtualization technology may be used to run multiple operating systems (OSs) for different purposes in parallel, and required applications may be executed on each OS.

[0044] (c2: information processing device 200) 4 is a block diagram showing an example of a hardware configuration of information processing device 200 in information processing system 1 according to the present embodiment. Information processing device 200 according to the present embodiment is configured, for example, by a general-purpose computer having hardware that complies with a general-purpose architecture.

[0045] 4, the information processing device 200 includes a processor 202 such as a CPU or a GPU (Graphics Processing Unit), an optical drive 204, a main storage device 206, a secondary storage device 208, a USB controller 212, a network controller 214, an input unit 216, and a display unit 218. These components are connected via a bus 220.

[0046] The processor 202 reads out various programs stored in the secondary storage device 208, expands them in the main storage device 206, and executes them to realize any processing.

[0047] The secondary storage device 208 typically stores an OS 222 and a browser application 224 for accessing the control device 100. The secondary storage device 208 may also store necessary programs other than the programs shown in FIG.

[0048] The information processing device 200 has an optical drive 204, and a program stored in a recording medium 205 (e.g., an optical recording medium such as a DVD (Digital Versatile Disc)) that non-transiently stores a computer-readable program is read and installed in a secondary storage device 208, etc.

[0049] Various programs executed by the information processing device 200 may be installed via a computer-readable recording medium 205, or may be installed by downloading them from a server device on a network, etc. In addition, the functions provided by the information processing device 200 according to this embodiment may be realized by using some of the modules provided by the OS 222.

[0050] The USB controller 212 controls the data exchange with the control device 100 via the USB connection. The network controller 214 controls the data exchange with other devices via an arbitrary network.

[0051] The input unit 216 is composed of a keyboard, a mouse, etc., and accepts user operations. The display unit 218 is composed of a display, various indicators, a printer, etc., and outputs the processing results from the processor 202, etc.

[0052] FIG. 4 shows a configuration example in which functions necessary for the processor 202 to execute a program are provided, but some or all of these provided functions may be implemented using a dedicated hardware circuit (for example, an ASIC or an FPGA, etc.).

[0053] (c3:HMI300) The HMI 300 according to the present embodiment is, for example, composed of a general-purpose computer having hardware according to a general-purpose architecture. Since the basic hardware configuration is the same as that of the information processing apparatus 200 shown in FIG. 4, detailed description will not be repeated.

[0054] <D. Outline of Processing> Next, the outline of processing in the information processing system 1 according to the present embodiment will be described.

[0055] The time-series data collected from the field can have an extremely large number of collections. For example, when collecting data at a cycle of 1 millisecond, the number of data for one day (24 hours) can reach 86.4 million. When graphically displaying all of these collected data, a large amount of resources are required for graph generation, etc., and a large amount of time is also required for processing.

[0056] Therefore, a common solution is to use only a portion of the collected data for graph display, using an algorithm to thin out the data used for graph display while maintaining the shape of the graph as much as possible.

[0057] However, the data to be used for graph display is simply selected according to a predetermined algorithm, without taking into consideration the meaning of the data (for example, whether the data is normal or abnormal, etc.). As a result, data that is important (meaningful) to the user (hereinafter also referred to as "important data") is not selected, and the user may miss the important data.

[0058] FIG. 5 is a diagram showing an example of a graph display according to the related art. FIG. 5 shows an example in which three points are selected from 15 points of raw data to display a simplified graph. That is, a simplified display is performed using the three points selected from the 15 points. Note that the target raw data includes normal data and abnormal data. Abnormal data is data having a value below a threshold value of 30.

[0059] In this case, the rate at which data is selected is 3 points / 15 points = 1 / 5, meaning that 1 out of 5 points will be selected for display. Therefore, we will assume a process in which 5 points are grouped together in chronological order into one bucket, and one piece of data is selected to represent each bucket.

[0060] In the example shown in Figure 5, the algorithm for selecting a representative point is to select the median value of the data contained in each bucket.

[0061] In the graph shown in Figure 5, black circles (●) represent selected data (data to be plotted), and white circles (○) represent unselected data (data not plotted). In the simplified display using only three points as shown in Figure 5, the two data marked A and B are both abnormal data, but are shown as white circles and are not displayed.

[0062] That is, a user who views the simplified display shown in FIG. 5 will overlook the fact that abnormal data is included.

[0063] FIG. 6 is a diagram showing an example of a graph display according to the present embodiment. FIG. 6 shows an example of displaying raw data similar to that in FIG. 5. In the example shown in FIG. 6, in addition to the data displayed in FIG. 5, two pieces of data marked with the symbols A and B, which are abnormal data, are further displayed.

[0064] The present embodiment employs a method that combines an algorithm for thinning out the data used for graph display while maintaining the shape of the graph as much as possible (for example, selection of the median value of each bin) and an algorithm for additionally selecting data based on importance.

[0065] As an algorithm for additionally selecting data based on importance, for example, in each bin, if important data exists, a process of definitely using the important data for graph display is assumed. In the example shown in FIG. 6, in each bin, the minimum value of the abnormal data is (additionally) selected (the two pieces of data marked with the symbols A and B).

[0066] Thus, in the present embodiment, while adopting a simplified display in which not all of the target raw data but only a part thereof is used for graph display, important data for the user, such as abnormal data, is excluded from the targets to be omitted.

[0067] <E. Terms> In this specification, "graph" includes anything that visually represents arbitrary data. In the following description, several types of graphs are exemplified, but the term "graph" is not limited to the exemplified representations and can include graphs in various expression modes.

[0068] In this specification, an algorithm (process) that thins out data used for graph display while maintaining the shape of the graph as much as possible is collectively referred to as "downsampling." As an example of downsampling, an algorithm that selects one sampled data for every predetermined number of data (for every bucket) may be used. However, the term "downsampling" is used for convenience and is not limited to a process that selects one sample for every predetermined number of samples, but may include any process that extracts a portion of the entire data. Data selected by downsampling is also referred to as "sampling data." The algorithm, parameters, etc. used for downsampling are collectively referred to as "sampling settings."

[0069] For example, the set of settings required to select one out of every five points of raw data to be displayed corresponds to "sampling settings," and each selected point corresponds to "sampling data."

[0070] In this specification, the algorithms and parameters for determining whether data is important are collectively referred to as “important data setting.” As an example of an algorithm used for important data setting, an algorithm that selects one sampling data for every predetermined number of data (for every bucket) may be used.

[0071] The important data settings include algorithms and parameters (e.g., thresholds and corresponding criteria) for determining whether data should be displayed in the graph (i.e., important data). The algorithms and parameters for determining whether data is important are collectively referred to as "important data determination settings."

[0072] In addition, the important data setting includes an algorithm and parameters for selecting at least a part from the data determined to be important data based on the important data setting for graph display. The algorithm and parameters for selecting at least a part of the important data and the like are collectively referred to as "important data selection setting". Based on the important data selection setting, the selected important data is referred to as "selected important data". That is, the important data selection setting further includes a selection criterion for selecting a smaller number of data from a plurality of data (a plurality of important data) determined to be displayed on the graph.

[0073] For example, a set of settings necessary for the process of determining data below a threshold as important data corresponds to "important data determination setting". A set of settings necessary for the process of selecting one piece of data that is the minimum value for each bucket from the data determined to be important data corresponds to "important data selection setting". In the following description, when simply described as "important data setting", it may include both important data determination setting and important data selection setting.

[0074] In addition, in this specification, "selection of data" includes not only the process of selecting (or extracting) one or more from a plurality of data, but also the process of determining (or generating) representative data (representative data) from a plurality of data, as described later.

[0075] <F. Usage Example> Next, a usage example of the graph display according to this embodiment will be described.

[0076] FIG. 7 and FIG. 8 are schematic diagrams showing an example of a user interface screen including a graph display provided by the information processing system 1 according to this embodiment. FIGS. 7 and 8 show an example of displaying a graph of time-series data.

[0077] Referring to FIG. 7, the user interface screen 240 includes a graph display area 250, a sampling setting area 260, and an important data setting area 270.

[0078] A graph including the sampled data and the selected important data is displayed in the graph display area 250. More specifically, the sampled data is represented in the form of a line graph 252, and the selected important data is represented by a cross (x) plot 254.

[0079] The graph also displays the threshold value 256 for the important data setting (important data determination setting).

[0080] The sampling setting area 260 includes a pull-down 262 for selecting an algorithm to be used for the sampling setting, and a slider 264 for inputting parameters to be used for the sampling setting. Fig. 7 shows an example in which 300 buckets are set and one point that is the median value is sampled for each bucket.

[0081] The important data setting area 270 includes a pull-down menu 272 for selecting an algorithm to be used for the important data setting (important data judgment setting), an input field 274 for inputting parameters to be used for the important data setting (important data judgment setting), a pull-down menu 276 for selecting the judgment criteria to be used for the important data setting (important data judgment setting), and a pull-down menu 278 for selecting the judgment criteria to be used for the important data setting (important data selection setting). Fig. 7 shows an example in which, for each bucket, data showing a value greater than a threshold value 256 is regarded as important data, and the maximum value of the important data appearing in each bucket is selected as selected important data.

[0082] Figure 8 shows an example of a graph display when the sampling settings are changed. More specifically, in Figure 8, the number of buckets has been reduced from 300 to 100. As a result, the number of sampled data points has also been reduced, and the line graph 252 has fewer vertices and a simpler shape.

[0083] As the number of sampled data decreases, the number of data considered to be important also decreases, resulting in a decrease in the amount of selected important data.

[0084] Fig. 9 is a schematic diagram showing another example of a user interface screen including a graph display provided by information processing system 1 according to the present embodiment. Fig. 9 shows an example of displaying a scatter diagram graph.

[0085] Referring to FIG. 9, the user interface screen 242 includes a graph display area 251, a sampling setting area 260, and an important data setting area 270.

[0086] A scatter plot including the sampled data and the selected important data is displayed in the graph display area 251. More specifically, the sampled data is represented by a black circle (●) plot 253, and the selected important data is represented by a cross (×) plot 254.

[0087] The graph also displays the threshold range 257 of the important data setting (important data judgment setting).

[0088] The sampling setting area 260 includes a pull-down 262 for selecting an algorithm to be used for the sampling setting, and a slider 264 for inputting parameters to be used for the sampling setting. Fig. 9 shows an example in which 300 buckets are set and one point is sampled for each bucket by random sampling.

[0089] The important data setting area 270 includes a pull-down menu 272 for selecting an algorithm used for important data setting (important data determination setting), an input field 275 for inputting a plurality of parameters used for important data setting (important data determination setting), a pull-down menu 276 for selecting a determination criterion used for important data setting (important data determination setting), and a pull-down menu 278 for selecting a determination criterion used for important data setting (important data selection setting). FIG. 9 shows an example in which data existing outside the threshold range 257 defined by four points input in the input field 275 is regarded as important data, and a setting is made to select so that the area of the polygon defined by the selected important data selected from each bucket is maximized.

[0090] Note that it is not limited to the example of the user interface screen shown in FIGS. 7 to 9, and any user interface screen may be provided.

[0091] <G. Functional configuration example> Next, a functional configuration example of the information processing system 1 according to the present embodiment will be described.

[0092] FIG. 10 is a schematic diagram showing a functional configuration example of the information processing system 1 according to the present embodiment. FIG. 10 shows, as a typical example, a configuration example in which the control device 100 is in charge of main processing and the user checks a graph on the information processing device 200.

[0093] Referring to FIG. 10, the control device 100 includes, as functional components, a data acquisition module 70, a sampling module 80, an important data selection module 90, and a graph generation module 74. These functional modules are typically realized by the processor 102 of the control device 100 executing the application program 134.

[0094] The control device 100 also has a setting preset group 50 and a setting group 60. The setting preset group 50 includes a sampling setting preset 52, an important data setting preset 54, and a graph setting preset 56. The setting group 60 includes a sampling setting 62, an important data setting 64, and a graph setting 66.

[0095] The data acquisition module 70 acquires raw data 72 from a time-series database or the like of the control device 100. The data acquisition module 70 can also add newly acquired data to the raw data 72.

[0096] The sampling module 80 selects a smaller number of data from the plurality of data to be displayed in a graph according to a predetermined algorithm. More specifically, the sampling module 80 selects sampled data 82 by downsampling from the raw data 72 based on the sampling settings 62.

[0097] The important data selection module 90 selects data from a plurality of data in accordance with predetermined settings. More specifically, the important data selection module 90 extracts important data included in the raw data 72 based on the important data settings 64, and selects at least a portion of the extracted important data as selected important data 92.

[0098] The graph generation module 74 generates a graph based on the data selected by the sampling module 80 and the data selected by the important data selection module 90. More specifically, the graph generation module 74 generates a graph using the sampled data 82 and the selected important data 92 based on the graph settings 66. The graph generation module 74 has a display update module 76 for updating the graph as time passes or as raw data 72 is added.

[0099] The sampling setting preset 52 includes one or more predefined settings (algorithms and parameters used for downsampling) available as sampling settings 62. The important data setting preset 54 includes one or more predefined settings (algorithms and parameters used for important data determination settings and selection criteria used for important data selection settings) available as important data settings 64. The graph setting preset 56 includes one or more predefined settings available as graph settings 66.

[0100] It is not necessary to store all types of presets included in the setting preset group 50, and it is acceptable to store at least some of them. Furthermore, it is also acceptable not to store the setting preset group 50.

[0101] Meanwhile, the information processing device 200 has a browser 230 as a functional configuration. The browser 230 is realized by the processor 202 of the information processing device 200 executing a browser application 224. Graphs are displayed via the browser 230 provided by the execution of the browser application 224. Via the browser 230 of the information processing device 200, the user can select, edit, update, etc. the setting preset group 50 and the setting group 60, and can also refer to graphs generated by the graph generation module 74 of the control device 100.

[0102] Fig. 11 is a schematic diagram showing a modified example of the functional configuration of information processing system 1 according to the present embodiment. Fig. 11 shows another typical example of a configuration in which control device 100 is in charge of main processing and the user checks graphs on HMI 300.

[0103] The functional configuration example shown in FIG. 11 is similar to the functional configuration example shown in FIG. 10, except that the graph generation module 74 of the control device 100 transmits the generated graph to the HMI 300.

[0104] FIG. 12 is a schematic diagram showing another modification of the functional configuration example of the information processing system 1 according to the present embodiment. In FIG. 12, as yet another typical example, a configuration example is shown in which an information processing apparatus 200 is responsible for main processing instead of the control apparatus 100.

[0105] In the configuration example shown in FIG. 12, the information processing apparatus 200 has the same functional modules as the control apparatus 100 in the configuration examples shown in FIGS. 10 and 11. However, since the raw data 72 is collected by the control apparatus 100, the information processing apparatus 200 further includes a data acquisition module 71 for acquiring the raw data 72 acquired by the control apparatus 100.

[0106] In the configuration example shown in FIG. 12, the user operates the information processing apparatus 200 to acquire the raw data 72 from the control apparatus 100 and checks a graph on the information processing apparatus 200 using the acquired raw data 72.

[0107] The configuration examples shown in FIGS. 10 to 12 are not limited thereto, and the data acquisition module 70, the sampling module 80, the important data selection module 90, and the graph generation module 74 can be implemented in any apparatus.

[0108] <H. Setting Example of Important Data Setting> Next, a setting example of important data setting for determining important data to be effectively graphically displayed will be described.

[0109] (h1: Multiple Threshold Values) In the examples shown in FIGS. 5 and 6, data below one threshold value 30 was regarded as abnormal data (important data), but a plurality of threshold values for determining important data may be set.

[0110] Fig. 13 is a diagram for explaining an example in which a plurality of thresholds are set in the important data setting (important data judgment setting) according to this embodiment. Fig. 13 shows an example in which two thresholds 31 and 32 are set. More specifically, data that exceeds threshold 31 and data that falls below threshold 32 are considered to be abnormal data (important data).

[0111] For example, in equipment where the air pressure of the monitored object must be maintained within an appropriate range, it is necessary to monitor both an abnormal increase (abnormality A) and an abnormal decrease (abnormality B) in air pressure. In such a case, a threshold value 31 corresponding to the abnormal increase and a threshold value 32 corresponding to the abnormal decrease may be set.

[0112] For example, for an abnormal increase (abnormality A), the maximum value in each bucket is selected as the important selection data, and for an abnormal decrease (abnormality B), the minimum value in each bucket is selected as the important selection data. Note that no important selection data is selected for buckets that do not contain important data. In this way, by additionally selecting important selection data, it is possible to avoid overlooking abnormal increases or decreases in tire pressure.

[0113] In the example shown in FIG. 13, in addition to the sampling data of each bucket, three pieces of data (important data) respectively labeled A, B, and C are selected as selected important data.

[0114] Fig. 14 is a diagram illustrating another example of setting a plurality of thresholds included in the important data setting (important data judgment setting) according to this embodiment. Fig. 14 shows an example in which two thresholds 33 and 34 are set. These thresholds are tiered, and for example, data exceeding threshold 33 (abnormality A) may be evaluated as requiring an inspection of the equipment and a detailed inspection of the product, while data below threshold 33 but exceeding threshold 34 (abnormality B) may be evaluated as requiring only a detailed inspection of the product.

[0115] 13 and 14 show examples of setting two thresholds, but more thresholds can be set. In addition, depending on the thresholds set, the algorithm for selecting important data (for example, the maximum / minimum / median value of important data in each bucket) can also be set arbitrarily.

[0116] That is, any important data determination setting (algorithm and parameters) and important data selection setting (algorithm and parameters) can be used depending on the target raw data. By using the important data setting according to the target raw data, important data that should not be overlooked in the target raw data can be more reliably selected.

[0117] (h2: changing threshold) The parameters (threshold values) included in the important data setting may be variable values ​​rather than fixed values. In other words, the parameters included in the important data setting may not be fixed values ​​but may be varied according to a function or an arbitrary algorithm.

[0118] Fig. 15 is a diagram for explaining an example of setting a changing threshold value included in the important data setting (important data judgment setting) according to this embodiment. Fig. 15 shows an example in which a periodic function is set as the threshold value.

[0119] For example, if the tire pressure of the vehicle being monitored is controlled to change periodically, the criteria for abnormal data must also be linked to the periodic change. Figure 15 shows an example in which the threshold value 35 is set using a periodic function.

[0120] In this way, the threshold value may be set using any function such as a periodic function.

[0121] In the example shown in FIG. 15, in addition to the sampling data of each bucket, data (important data) marked with a symbol A that exceeds the threshold value 35 is selected as selected important data.

[0122] Fig. 16 is a diagram for explaining another example of setting a variable threshold value included in the important data setting (important data determination setting) according to this embodiment. Fig. 16 shows an example in which data that deviates from the overall trend is determined as abnormal data (important data). More specifically, data that deviates significantly from the moving average of the time-series data is considered to be abnormal data (important data).

[0123] FIG. 16 shows an example in which data that is greater than a predetermined value (10 in this example) around a moving average 36 of the most recent five points is set as threshold value 37, and data that is smaller than the predetermined value (10 in this example) is set as threshold value 38. Data that exceeds threshold value 37 is considered to be abnormal A, and data that is smaller than threshold value 38 is considered to be abnormal B. Then, selected important data to be used for graph display is selected from the abnormal data (important data).

[0124] In this way, the judgment criterion may be set as a value that is a predetermined range away from the moving average of the time series data.

[0125] Fig. 17 is a diagram for explaining yet another setting example of the important data setting (important data judgment setting) according to this embodiment. Fig. 17 shows an example in which the important data judgment setting including the threshold value changes depending on the value of the variable mode indicating the state.

[0126] More specifically, the variable mode takes one of the values ​​"0", "1", and "2". When the variable mode is "0", the important data setting is disabled, when the variable mode is "1", the threshold is set to "100" and a value smaller than the threshold is set as important data, and when the variable mode is "2", the threshold is set to "0" and a value larger than the threshold is set as important data.

[0127] In the example shown in FIG. 17, in the range where the first variable mode is "2", data showing a value greater than the threshold value "100" is regarded as important data. Since the data marked with the sign A shows a value greater than 100, it is determined to be important data. On the other hand, since the data marked with the sign b is less than 100, it is determined not to be important data.

[0128] In the range where the next variable mode is "1", data showing a value less than the threshold value "0" is regarded as important data. Since the data marked with the sign c is greater than 0, it is determined not to be important data.

[0129] In the range where the variable mode is "0" again, the important data setting is invalidated, and it is determined that neither the data marked with the signs d nor e is important data.

[0130] <I. Preset of Settings> Regarding the sampling setting and the important data setting described above, presets including basic setting examples may be prepared. The user may be allowed to select a preset and edit it as appropriate. Also, the user may be allowed to generate and save arbitrary presets.

[0131] FIG. 18 is a schematic diagram showing an example of a user interface screen related to the preset provided by the information processing system 1 according to the present embodiment. FIG. 18 shows, as an example, an example of a preset for the important data setting.

[0132] Referring to FIG. 18, the user interface screen 280 includes one or more pull-downs 281 for selecting a preset and a display area 282 showing the content of the preset.

[0133] Each of the display areas 282 includes a pull-down 283 for selecting an algorithm used for important data determination settings, input fields 284, 285 for setting parameters associated with the selected algorithm, and a pull-down 286 for selecting a criterion for determination.

[0134] Also, each of the display areas 282 includes a pull-down 287 for selecting a selection criterion used for important data selection settings.

[0135] The user can perform important data settings, for example, including threshold value 37 and threshold value 38 as shown in FIG. 16, by making desired settings on the user interface screen 280 shown in FIG. 18.

[0136] Thus, by preparing one or more presets, similar settings can be used when visualizing similar data, thereby reducing the labor involved in setting.

[0137] <J. Temporal change in display accuracy> Generally, the load of display processing depends on the downsampling period (the size of the bucket). Therefore, for example, immediately after starting to display a graph, the size of the bucket may be increased to generate and display the graph, and as time passes while the graph is being displayed, the size of the bucket may be made smaller.

[0138] For example, immediately after starting to display a graph, one point may be selected as sampling data for every 1000 points of data, and after selecting important data included in the 1000 points of data, the data may be merged to generate a graph. Then, as time passes, it may be changed to select one point as sampling data for every 100 points of data, and after selecting important data included in the 100 points of data, the data may be merged to generate a graph.

[0139] FIG. 19 is a diagram for explaining the processing load according to the size of the bucket in the information processing system 1 according to the present embodiment.

[0140] In FIG. 19(A), an example with a bucket size of 5 is shown. When the bucket size is large, the number of buckets decreases, so the number of data points included in the graph also decreases, and the time required for graph display is shortened. On the other hand, in FIG. 19(B), an example with a bucket size of 3 is shown. When the bucket size is small, the number of buckets increases, so the number of data points included in the graph also increases, and the time required for graph display becomes longer.

[0141] Thus, the control device 100 (or the information processing device 200) may decrease a predetermined number (bucket size) for selecting sampling data and selected important data over time.

[0142] By setting the bucket size relatively large immediately after the start of graph display and then adjusting it to be small, the number of data points used for graph display is relatively small immediately after the start of graph display. As a result, the graph can be generated and displayed in a short time, so the user can grasp the outline of the graph in a short time. If the user does not switch to the display of another graph or the like and time passes in that state, a more detailed graph is displayed, so the user can grasp more detailed information included in the graph.

[0143] <K. Target Data> Next, the raw data that is the target of graph display according to the present embodiment will be described.

[0144] (k1: Type of target data) In the above description, a typical example of downsampling is a process of resampling target raw data (time-series data) to reduce the sampling rate. However, the term "downsampling" in this specification is not limited to downsampling in the narrow sense, but also encompasses processes that target non-time-series data. In other words, the target raw data for graph display is not limited to time-series data, but includes any non-time-series data.

[0145] For example, downsampling may involve employing an algorithm that resamples data that constitutes a scatter plot plotted in two-dimensional space.

[0146] Fig. 20 is a diagram for explaining another example of a graph display according to the present embodiment. Fig. 20 shows a scatter plot consisting of 50 points of data as an example of a graph. Such a scatter plot may, for example, show the inspection results of the positions of holes drilled in a plate-like workpiece. The samples indicate the (X, Y) coordinates in a coordinate system set for the workpiece.

[0147] In the graph shown in FIG. 20, black circles (●) represent data selected based on arbitrary sampling settings, and white circles (◯) represent data not selected (data not plotted).

[0148] In the graph shown in Fig. 20, a reference frame 40 is set as a criterion included in the important data setting, and data existing outside the reference frame 40 is regarded as important data. Based on the important data setting, some of this important data is selected as selected important data. More specifically, in the example shown in Fig. 20, three pieces of data (important data) respectively labeled A, B, and C are selected as selected important data.

[0149] In the example shown in FIG. 20, of the 50 points of raw data of interest, the data used for the scatter plot is thinned to 18 points.

[0150] As described above, the raw data to be displayed in a graph according to this embodiment is not limited to time-series data, but may also include non-time-series data.

[0151] Fig. 21 is a diagram for explaining an example of important data selection settings according to this embodiment, which shows an example of important data selection settings applied to a scatter diagram plotted in a two-dimensional space.

[0152] 21, for example, for each bucket, data that exists outside the threshold range of a rectangle defined by four specified points can be regarded as important data. Furthermore, if there are multiple important data for each bucket, the selected important data can be selected based on any algorithm.

[0153] As an example, an algorithm for selecting the important data may be adopted that maximizes the area of ​​a polygon defined by the important data selected from each bucket.

[0154] 21, there are important data A1 to A3, important data B1 to B3, important data C1 to C3, and important data D1 to D3 in each bucket. That is, important data A1 to A3 belong to one bucket, important data B1 to B3 belong to another bucket, important data C1 to B3 belong to yet another bucket, and important data D1 to B3 belong to yet another bucket.

[0155] Assume that one of three important data items is selected for each bucket. In this example, a total of four important data items are selected as selected important data items. The combination is determined so that the area enclosed by the four selected important data items is maximized. As a result, important data items A1, B2, C3, and D4 are selected.

[0156] It should be noted that the selection algorithm is not limited to the algorithm that maximizes the area, and any selection algorithm can be employed.

[0157] (k2: Add target data) In this embodiment, not only is it possible to process raw data acquired in advance, but also data that is generated afterwards.

[0158] When processing prepared data, the control device 100 (or the information processing device 200) selects sampled data from the target raw data by downsampling, extracts important data contained in the target raw data, and selects at least a portion of the extracted important data as selected important data. Finally, the sampled data and the selected important data are displayed in graph form.

[0159] At production sites, new data (such as measurement values ​​from sensors) is generated sequentially as operations proceed. There is a need to be able to display this sequentially generated data in graph form.

[0160] To meet such needs, if there is new data to be added as target raw data, it may be possible to add it as a target for graph display. More specifically, in response to a user operation or the occurrence of new data to be added, the control device 100 (or the information processing device 200) selects sampled data by downsampling from the new data to be added, extracts important data included in the new data to be added, and selects at least a portion of the extracted important data as selected important data. Finally, the sampled data and selected important data for the new data to be added are displayed in graph form.

[0161] Fig. 22 is a diagram for explaining an example of how a graph display according to the present embodiment changes over time. With reference to Fig. 22, for example, when a graph is displayed using already acquired data (raw data), after a predetermined time has elapsed, newly acquired data is added and the newly added data is added and displayed on the graph. In the example shown in Fig. 22, two pieces of data have been added.

[0162] In this way, if the graph display is maintained during the operation of the production site, newly generated data is sequentially added to the graph. The user can obtain the necessary information while checking the graph to which the sequential data is added.

[0163] <L. Display mode> Next, the display mode of the graph display according to this embodiment will be described.

[0164] (l1: Change in display mode) As described above, the sampling data and the selected important data are graphically displayed, but the display mode such as the graph format may be varied depending on the type of data.

[0165] FIG. 23 is a diagram for explaining an example of the display mode of the graph display according to this embodiment. FIG. 23(A) shows an example in which time-series data in which the value increases with the passage of time includes abnormal data. For example, one sampling data is selected for each bucket (for example, the median value of each bucket is selected), and the abnormal data is regarded as the selected important data.

[0166] FIG. 23(B) shows an example of the graph display of the merged data obtained by merging the sampling data and the selected important data selected in FIG. 23(A).

[0167] In the graph display shown in FIG. 23(B), it is difficult to understand that the target time-series data (raw data) has the characteristic that the value increases with the passage of time. Thus, if the sampling data and the selected important data are graphically displayed in the same format, the recognition of information may be degraded.

[0168] Therefore, they may be displayed so that the sampling data and the selected important data can be distinguished from each other.

[0169] FIG. 24 is a diagram for explaining another example of the display mode of the graph display according to this embodiment.

[0170] 24(A) shows an example in which the display modes (colors, shapes, etc.) of the figures representing the sampling data and the selected important data are different from each other. More specifically, the sampling data is represented by a black circle (●), and the selected important data is represented by a white triangle (△).

[0171] 24(B) shows an example in which the graph formats for the sampling data and the selected important data are different from each other. More specifically, the sampling data is shown as a line graph, and the selected important data is shown as a scatter plot (plot only).

[0172] 24(C) shows an example in which objects (text, graphics, etc.) are attached according to the meaning of the data. More specifically, objects (alphabet) are attached only to the selected important data, and no objects are attached to the sampling data.

[0173] Note that an object may be attached only to the sampling data, or an object having a different meaning may be attached to each data.

[0174] In this way, the control device 100 (or the information processing device 200) may represent the sampling data in a graph in a first display format, and represent the selected important data in a graph in a second display format. By displaying the graph in a display format according to the type of data, the meaning of the data displayed in the graph can be more clearly recognized.

[0175] (l2: Display granularity of important data) In the above explanation, when multiple important data appear in one bucket, one important data (selected important data) is selected based on the important data setting. However, the important data setting may be changed depending on the situation. For example, all important data may be regarded as selected important data and a graph may be displayed.

[0176] FIG. 25 is a diagram for explaining an example of changing the display granularity of important data according to the present embodiment. In FIG. 25(A), for example, an example of the temporal change in the load generated in the motor is shown. In the graph shown in FIG. 25(A), the black circles (●) represent data selected based on an arbitrary sampling setting, and the white circles (○) represent abnormal data in which the load is greater than a predetermined threshold value.

[0177] In the graph shown in FIG. 25(A), it can be read that abnormal data occurred frequently in a certain specific time period, and then the occurrence frequency of the abnormal data decreased.

[0178] On the other hand, FIG. 25(B) shows an example of displaying important data (selected important data) selected based on the important data setting among the important data. In this graph, the temporal change in the occurrence frequency of abnormal data cannot be read.

[0179] As described above, depending on the situation, by changing the important data setting, more important data may be graphically displayed. By graphically displaying more important data, the number of data points to be displayed increases, and it may take more time to generate and display the graph. However, by graphically displaying more important data, it becomes easier to grasp the trend of the important data.

[0180] <M. Generation of representative data>

[0181] (m1: Average value of the vertical coordinate and average value of the horizontal coordinate) ​Fig. 26 is a diagram for explaining an example of a process for generating representative data according to this embodiment, in which each bucket contains six pieces of data (raw data).

[0182] Representative data (corresponding to sampling data) representing the six data points contained in each bucket is generated. The value (ordinate) of the representative data is set to the average value of the six data points contained in each bucket. The position of the representative data on the time axis (abscissa) is also set to the average value of the time of the six data points contained in each bucket. In this way, representative data (sampling data) may be generated using the average values ​​of the ordinates and abscissas for the multiple data points contained in each bucket.

[0183] The abnormal data (important data) marked with A is unique in Bucket 1, so its value is used as is. In contrast, in Bucket 2, there are two abnormal data (important data), so the representative data (selected important data) is generated using the average values ​​of the ordinate and abscissa for the two abnormal data.

[0184] In this way, representative data (selected important data) may be generated using the average values ​​of the ordinates and abscissas for the plurality of important data included in each bucket.

[0185] Figure 27 is a diagram for explaining the process of graph display using the representative data generated by the process shown in Figure 26. The representative data (sampling data) generated by the process shown in Figure 26 has coordinate values ​​as shown in Figure 27(A). The representative data (selected important data) generated by the process shown in Figure 26 has coordinate values ​​as shown in Figure 27(B).

[0186] The control device 100 (or the information processing device 200) generates a graph as shown in FIG. 27(C) using the coordinate value groups shown in FIG. 27(A) and FIG. 27(B).

[0187] (m2: mean value of ordinate and center of abscissa) Fig. 28 is a diagram for explaining another example of processing for generating representative data according to this embodiment. Fig. 28 shows an example in which each bucket contains four pieces of data (raw data).

[0188] Representative data (corresponding to sampling data) representing the four data points contained in each bucket is generated. The value (ordinate) of the representative data is set to the average value of the four data points contained in each bucket. Furthermore, the position of the representative data on the time axis (abscissa) is set to the center of each bucket. In this way, representative data (sampling data) may be generated using the average value of the ordinates of the multiple data points contained in each bucket and the center of each bucket.

[0189] The abnormal data (important data) marked with A is unique in bucket 1, so its value is used as is. However, representative data (selected important data) may be generated using the average value of the ordinates of multiple important data included in each bucket and the center of each bucket.

[0190] Figure 29 is a diagram for explaining the process of graph display using representative data generated by the process shown in Figure 28. The representative data (sampling data) generated by the process shown in Figure 28 has coordinate values ​​as shown in Figure 29(A). The representative data (selected important data) generated by the process shown in Figure 29 has coordinate values ​​as shown in Figure 29(B).

[0191] The control device 100 (or the information processing device 200) generates a graph as shown in FIG. 29(C) using the coordinate value groups shown in FIG. 29(A) and FIG. 29(B).

[0192] In this way, by setting the horizontal coordinates of the representative data (sampling data) as the centers of the respective buckets, if the widths of all the buckets are the same, as shown in Fig. 29(C), a graph composed of sampling data arranged at equal intervals in the horizontal direction can be generated. That is, as shown in Fig. 29(A), for the sampling data, the information of the horizontal coordinates becomes unnecessary, and resource consumption such as memory can be suppressed. In particular, in embedded devices where resources are easily restricted, such a specification is beneficial.

[0193] On the other hand, considering that the important data is a singular value, it is difficult to think that the important data appears in all the buckets. That is, since whether the important data is included or not changes depending on the bucket, even if the center of each bucket is set as the horizontal coordinate of the selected important data, the interval between adjacent selected important data does not become constant. Therefore, for the selected important data, as shown in Fig. 29(B), it is preferable to have the information of both the vertical and horizontal coordinates.

[0194] However, by sharing the horizontal coordinates between the sampling data and the selected important data, there may be a case where the visibility when the user views the graph can be improved. Therefore, the horizontal coordinate of the selected important data may be set as the center of the corresponding bucket.

[0195] <N. Processing Procedure> Next, the processing procedure in the information processing system 1 according to the present embodiment will be described. In the following description, the description will be based on the configuration example shown in Fig. 10, but in another configuration example, the execution subject of the processing can be appropriately changed.

[0196] (n1: Graph Display) First, the processing related to graph display will be described.

[0197] C Fig. 30 is a flowchart showing a processing procedure for displaying a graph in information processing system 1 according to the present embodiment. The processing shown in Fig. 30 is realized by processor 102 of control device 100 executing application program 134, and by processor 202 of information processing device 200 executing browser application 224.

[0198] The control device 100 determines whether or not it has been accessed from the browser 230 of the information processing device 200 (step S100). If it has not been accessed (NO in step S100), the processing from step S100 onwards is repeated.

[0199] When the user starts the browser 230 on the information processing device 200 and opens a graph display screen, the control device 100 accesses the information processing device 200 .

[0200] If the access has been received (YES in step S100), the information processing device 200 transmits graph settings to the information processing device 200 (step S102). The graph settings include the size of the graph display area, the period and number of points of data to be displayed on one screen, etc. The browser 230 of the information processing device 200 generates a user interface screen based on the graph settings.

[0201] Next, the control device 100 determines whether or not a request for graph display has been received from the browser 230 of the information processing device 200 (step S104). If a request for graph display has not been received (NO in step S104), the process of step S104 is repeated.

[0202] If a request for graph display is received (YES in step S104), the control device 100 determines the bucket size based on the graph settings (step S106).

[0203] Then, the control device 100 selects sampling data from the target raw data based on the sampling setting (step S108). That is, the control device 100 selects a smaller number of data (sampling data) from the multiple data to be displayed in graph form according to a predetermined algorithm.

[0204] Furthermore, the control device 100 extracts important data from the target raw data based on the important data setting, and selects selected important data from the extracted important data (step S110). That is, the control device 100 selects data (selected important data) from a plurality of data in accordance with a predetermined setting.

[0205] The selection of sampling data and the selection of important data may be performed in any order.

[0206] Next, the control device 100 generates a graph including the sampling data and the selected importance data (step S112) and transmits it to the information processing device 200 (step S114). That is, the control device 100 generates a graph based on the sampling data and the selected importance data. The browser 230 of the information processing device 200 draws the graph from the control device 100 on a user interface screen. Through this process, the graph is displayed on the information processing device 200.

[0207] Next, the control device 100 determines whether there is data to be added to the raw data (step S116). If there is data to be added to the raw data (YES in step S116), the control device 100 sets the raw data including the data to be added as a new target (step S118), and repeats the processing from step S108 onwards.

[0208] If there is no data to be added to the raw data (NO in step S116), the control device 100 determines whether a predetermined time has passed since the previous graph generation (step S120). If the predetermined time has passed since the previous graph generation (YES in step S120), the control device 100 reduces the size of the bucket (step S122) and repeats the processing from step S108 onwards.

[0209] If a predetermined time has not passed since the previous graph generation (NO in step S120), the control device 100 determines whether the graph display on the browser 230 of the information processing device 200 is still ongoing (step S124). If the graph display on the browser 230 is still ongoing (YES in step S124), the processing from step S116 onwards is repeated.

[0210] If the graph display on the browser 230 is not continuing (NO in step S124), the control device 100 ends the process related to the graph display.

[0211] (n2: Settings) Next, the setting process will be described.

[0212] Fig. 31 is a flowchart showing a processing procedure related to setting in information processing system 1 according to the present embodiment. The processing shown in Fig. 31 is realized by processor 102 of control device 100 executing application program 134, and by processor 202 of information processing device 200 executing browser application 224.

[0213] 31, the control device 100 determines whether or not a request to create or add a setting preset has been received from the browser 230 of the information processing device 200 (step S200). If a request to create or add a setting preset has been received (YES in step S200), the control device 100 executes a process to create a setting preset (step S202).

[0214] If a request to create or add a setting preset has not been received (NO in step S200), the control device 100 determines whether a request to create or add a setting has been received from the browser 230 of the information processing device 200 (step S204). If a request to create or add a setting has been received (YES in step S204), the control device 100 determines whether the received request is a request to create or add a setting based on a preset (step S206).

[0215] If the received request is not a request to create or add a setting based on a preset (NO in step S206), the control device 100 executes a process to create a new setting (step S208). If the received request is a request to create or add a setting based on a preset (YES in step S206), the control device 100 executes a process to create a setting based on the setting preset (step S210).

[0216] If a request for creating or adding settings has not been received (NO in step S204), the processing relating to settings ends.

[0217] Fig. 32 is a flowchart showing the processing steps of the setting preset creation processing shown in Fig. 31. Referring to Fig. 32, the control device 100 receives a designation of a name to be given to the setting preset to be created from the user (step S220). Subsequently, the control device 100 receives a designation of a type of the setting preset to be created from the user (step S222).

[0218] When a sampling setting preset is specified ("Sampling Setting Preset" in step S222), the control device 100 accepts the specification of an algorithm to be used for the sampling setting (step S224). Examples of the algorithm include median, average, moving average, and Largest-Triangle-Three-Buckets. The control device 100 also accepts the specification of parameters to be used for the sampling setting (step S226). Examples of parameters include setting the abscissa to the median value of the bucket. Finally, the control device 100 generates and stores a sampling setting preset including the specified algorithm and parameters (step S228). Then, the process returns.

[0219] When an important data setting preset is specified ("Important data setting preset" in step S222), the control device 100 accepts the specification of an algorithm to be used for the important data setting (step S230). Examples of the algorithm include a threshold value, a moving average, and a function. The control device 100 also accepts the specification of parameters to be used for the important data setting (step S232). Examples of parameters include a moving average. The control device 100 also accepts the specification of selection criteria to be used for the important data selection setting (step S234). Examples of parameters include selection of the maximum value of the important data. Finally, the control device 100 generates and stores a sampling setting preset including the specified algorithm, parameters, and selection criteria (step S236). Then, the process returns.

[0220] When a graph setting preset is specified ("Graph setting preset" in step S222), the control device 100 accepts the specification of the graph type (step S238). Examples of graph types include line graphs and scatter plots. The control device 100 also accepts the specification of columns to be used for each axis of the graph (step S240). Examples of column specification include specifying the first column as the horizontal axis of a scatter plot and the second column as the vertical axis of the scatter plot. The control device 100 also accepts the specification of the display method and units for each axis (step S242). Finally, the control device 100 generates and stores a graph setting preset including the specified graph type, column specification, and display method and unit specification (step S244). Then, the process returns.

[0221] Fig. 33 is a flowchart showing the processing procedure for the new setting creation processing shown in Fig. 31. Referring to Fig. 33, the control device 100 receives a designation of the type of setting to be newly created from the user (step S250).

[0222] When the sampling setting is specified ("Sampling setting" in step S250), the control device 100 accepts the specification of the algorithm to be used in the sampling setting (step S252). The control device 100 also accepts the specification of the parameters to be used in the sampling setting (step S254). Finally, the control device 100 generates and stores the sampling setting including the specified algorithm and parameters (step S256). Then, the process returns.

[0223] When important data settings are specified (in step S250, "important data settings"), the control device 100 accepts the specification of the algorithm used for the important data settings (step S258). Further, the control device 100 accepts the specification of the parameters used for the important data settings (step S260). Further, the control device 100 accepts the specification of the selection criteria used for the important data selection settings (step S262). Finally, the control device 100 generates and stores a sampling setting including the specified algorithm, parameters, and selection criteria (step S264). Then, the process returns.

[0224] When graph settings are specified (in step S250, "graph settings"), the control device 100 accepts the specification of the graph type (step S266). Further, the control device 100 accepts the specification of the columns to be used for each axis of the graph (step S268). Further, the control device 100 accepts the specification of the display method and unit for each axis (step S270). Finally, the control device 100 generates and stores a graph setting including the specified graph type, column specification, and display method and unit specification (step S272). Then, the process returns.

[0225] Figure 34 is a flowchart showing the processing procedure of creating settings based on the setting preset shown in Figure 31. Referring to Figure 34, the control device 100 reads the specified setting preset from the group of setting presets prepared in advance (step S280). The control device 100 changes the read values (such as algorithms and parameters) according to the user operation (step S282). Finally, the control device 100 stores the setting including the changed values according to the user operation (step S284). Then, the process returns.

[0226] <O. Addendum> The present embodiment as described above includes the following technical ideas.

[0227] [Configuration 1] An information processing system (1) comprising a first data selection unit (22; 80) that selects a smaller number of first data (27; 82) from a plurality of data (21; 72) to be displayed in a graph in accordance with a predetermined first algorithm; a second data selection unit (23; 90) that selects second data (28; 92) from the plurality of data in accordance with a predetermined setting (64); a graph generating unit (24; 74) that generates a graph based on the first data and the second data; The information processing system, wherein the settings include a second algorithm and parameters for determining data to be displayed on the graph.

[0228] [Configuration 2] 2. The information processing system of claim 1, wherein the settings further include criteria for selecting a smaller number of data from the plurality of data determined to be displayed in the graph.

[0229] [Configuration 3] the first data selection unit selects one of the first data for every predetermined number of data; 3. The information processing system according to configuration 1 or 2, wherein the second data selection unit selects one of the second data for each of the predetermined number of data.

[0230] [Configuration 4] 4. The information processing system according to claim 3, wherein the first data selection unit and the second data selection unit decrease the predetermined number for selecting the first data and the second data over time.

[0231] [Configuration 5] The information processing system according to any one of configurations 1 to 4, wherein the graph generation unit represents the first data in the graph in a first display format and represents the second data in the graph in a second display format.

[0232] [Configuration 6] 6. The information processing system according to any one of configurations 1 to 5, wherein the setting parameters vary according to at least one of a function and a third algorithm.

[0233] [Configuration 7] The information processing system according to any one of configurations 1 to 6, further comprising a storage unit that stores at least one of a predefined first preset (52) that can be used as the first algorithm and a predefined second preset (54) that can be used as the setting.

[0234] [Configuration 8] Further comprising an information processing device (200) that executes a browser application (224), 8. The information processing system according to any one of configurations 1 to 7, wherein the graph is displayed via a browser (230) provided by executing the browser application.

[0235] [Configuration 9] An information processing method, comprising: a step (S108) of selecting a smaller number of first data (27; 82) from the plurality of data (21; 72) to be displayed in a graph according to a predetermined first algorithm; selecting (S110) second data (28; 92) from the plurality of data in accordance with a predetermined setting (64); generating a graph based on the first data and the second data (S112, S114); An information processing method, wherein the settings include a second algorithm and parameters for determining data to be displayed on the graph.

[0236] [Configuration 10] An information processing program (134) for a computer (100; 200): a step (S108) of selecting a smaller number of first data (27; 82) from the plurality of data (21; 72) to be displayed in a graph according to a predetermined first algorithm; A step (S110) of selecting second data (28; 92) according to a predetermined setting (64) from the plurality of data; Execute steps (S112, S114) of generating a graph based on the first data and the second data; The setting includes a second algorithm and parameters for determining data to be displayed in the graph, and is an information processing program.

[0237] <P. Advantage> According to the information processing system 1 according to the present embodiment, while data used for graph display is selected while maintaining the shape of the graph as much as possible, important (meaningful) data (important data) for the user is also selected. As a result, the resources required for graph display can be reduced, and the important data selected according to the preset setting is also represented in the graph, reducing the possibility that the user misses the important data.

[0238] The embodiments disclosed this time should be considered as illustrative in all respects and not restrictive. The scope of the present invention is shown not by the above description but by the claims, and it is intended that all modifications within the meaning and scope equivalent to the claims are included.

Explanation of Reference Signs

[0239] [[ID=??]] Since the specific content corresponding to , ,

[0239] , and <00..861> is not provided in the original text, I have left them as they are with the question marks in the translated text. If you have the actual content for these tags, please let me know and I can provide a more accurate translation.1 Information processing system, 2 Field bus, 4 Upper network, 10 Field device group, 12 Remote I / O device, 14 Relay group, 18 Servo driver, 20 Servo motor, 21, 72 Raw data, 22 First data selection unit, 23 Second data selection unit, 24 Graph generation unit, 25, 30, 31, 32, 33, 34, 35, 37, 38, 256 Threshold value, 26 Graph, 27 First data, 28 Second data, 36 Moving average, 40 Reference frame, 50 Setting preset group, 52 Sampling setting preset, 54 Important data setting preset, 56 Graph setting preset, 60 Setting group, 62 Sampling setting, 64 Important data setting, 66 Graph setting, 70, 71 Data acquisition module, 74 Graph generation module, 76 Display update module, 80 Sampling module, 82 Sampling data, 90 Important data selection module, 92 Selective important data, 100, control device, 102, 202, processor, 104, chipset, 106, 206, main memory, 108, 208, secondary memory, 110, upper network controller, 112, 212, USB controller, 114, memory card interface, 116, memory card, 120, field bus controller, 122, internal bus controller, 124, I / O unit, 131, system program, 132, user program, 133, application execution environment program, 134, application program, 200, information processing device, 204, optical drive, 205, recording medium, 214, network controller, 216, input unit, 218, display unit, 220, bus, 222, OS, 224, browser application, 230, browser, 240, 242, 280, user interface screen, 250, 251, graph display area, 252, line graph, 253, 254, plot, 257 Threshold range, 260 Sampling setting area, 262,272,276,278,281,283,286,287 Pull-down, 264 Slider, 270 Important data setting area, 274,275,284,285 Input field, 282 Display area, 300 HMI.

Claims

1. An information processing system, a first data selection unit that selects a smaller number of first data from a plurality of data to be graph-displayed in accordance with a predetermined first algorithm; a second data selection unit that selects second data from the plurality of data in accordance with a predetermined setting; a graph generation unit that generates a graph based on the first data and the second data, The setting is: a second algorithm and parameters for determining which data should be displayed on the graph; a criterion for selecting a smaller number of data from the plurality of data determined to be displayed on the graph; the first data selection unit selects one of the first data for each predetermined number of data; the second data selection unit selects one of the second data for each of the predetermined number of data; an information processing system, wherein the first data selection unit and the second data selection unit decrease the predetermined number for selecting the first data and the second data over time;

2. The information processing system according to claim 1 , wherein the graph generating unit represents the first data in the graph in a first display format and represents the second data in the graph in a second display format.

3. The information processing system according to claim 1 , wherein the parameters of the settings are varied according to at least one of a function and a third algorithm.

4. The information processing system according to any one of claims 1 to 3, further comprising a storage unit that stores at least one of a predefined first preset that can be used as the first algorithm and a predefined second preset that can be used as the setting.

5. further comprising an information processing device that executes a browser application; 5. The information processing system according to claim 1, wherein the graph is displayed via a browser provided by executing the browser application.

6. An information processing method, comprising: selecting a smaller number of first data from the plurality of data to be graphed in accordance with a predetermined first algorithm; selecting second data from the plurality of data in accordance with a predetermined setting; generating a graph based on the first data and the second data; The setting is: a second algorithm and parameters for determining which data should be displayed on the graph; a criterion for selecting a smaller number of data from the plurality of data determined to be displayed on the graph; the step of selecting the first data includes the step of selecting one of the first data for every predetermined number of data; the step of selecting the second data includes the step of selecting one of the second data for each of the predetermined number of data; An information processing method, wherein in the step of selecting the first data and the step of selecting the second data, the predetermined number for selecting the first data and the second data decreases over time.

7. An information processing program, which is installed on a computer, selecting a smaller number of first data from the plurality of data to be graphed in accordance with a predetermined first algorithm; selecting second data from the plurality of data in accordance with a predetermined setting; generating a graph based on the first data and the second data; The setting is: a second algorithm and parameters for determining which data should be displayed on the graph; a criterion for selecting a smaller number of data from the plurality of data determined to be displayed on the graph; the step of selecting the first data includes the step of selecting one of the first data for every predetermined number of data; the step of selecting the second data includes the step of selecting one of the second data for each of the predetermined number of data; an information processing program, wherein in the step of selecting the first data and the step of selecting the second data, the predetermined number for selecting the first data and the second data decreases over time.

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